From f74a96540229f4573f58f28318d8595f1e766c71 Mon Sep 17 00:00:00 2001 From: Lisa Hopcroft <54442530+LisaHopcroft@users.noreply.github.com> Date: Tue, 15 Feb 2022 14:36:54 +0000 Subject: [PATCH] feat: new notebooks and diffable for this release --- notebooks/booster-third-doses.ipynb | 1343 +- .../diffable_python/booster-third-doses.py | 13 +- .../opensafely_vaccine_report_overall.py | 2 +- .../population_characteristics.py | 205 +- notebooks/diffable_python/second_doses.py | 2 +- .../opensafely_vaccine_report_overall.ipynb | 2 +- notebooks/population_characteristics.ipynb | 62583 +++++++++------- notebooks/second_doses.ipynb | 2 +- 8 files changed, 38663 insertions(+), 25489 deletions(-) diff --git a/notebooks/booster-third-doses.ipynb b/notebooks/booster-third-doses.ipynb index b193266..d83bf62 100644 --- a/notebooks/booster-third-doses.ipynb +++ b/notebooks/booster-third-doses.ipynb @@ -13,7 +13,7 @@ "source": [ "OpenSAFELY is a new secure analytics platform for electronic patient records built on behalf of NHS England to deliver urgent academic and operational research during the pandemic. \n", "\n", - "This is an extension of our [regular weekly report](https://reports.opensafely.org/reports/vaccine-coverage/) on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our paper available [here](https://doi.org/10.3399/BJGP.2021.0376).** \n", + "This is an extension of our [regular weekly report](https://reports.opensafely.org/reports/vaccine-coverage/) on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our [peer-reviewed publication in the British Journal of General Practice](https://doi.org/10.3399/BJGP.2021.0376).** \n", "\n", "The full analytical methods behind the latest results in this report are available [here](https://github.com/opensafely/nhs-covid-vaccination-uptake).\n", "\n", @@ -37,7 +37,7 @@ { "data": { "text/markdown": [ - "### Report last updated **17 Jan 2022**" + "### Report last updated **31 Jan 2022**" ], "text/plain": [ "" @@ -204,12 +204,9 @@ "- [**55-59** population](#Cumulative-third-dose-vaccination-figures-among-55-59-population)\n", "- [**50-54** population](#Cumulative-third-dose-vaccination-figures-among-50-54-population)\n", "- [**40-49** population](#Cumulative-third-dose-vaccination-figures-among-40-49-population)\n", - "\n", - "\n", - "- [**All groups (Summary)**](#Summary))\n", - "\n", - "\n", - "\n" + "- [**30-39** population](#Cumulative-third-dose-vaccination-figures-among-30-39-population)\n", + "- [**18-29** population](#Cumulative-third-dose-vaccination-figures-among-18-29-population)\n", + "- [**All groups (Summary)**](#Summary)\n" ] }, { @@ -8696,11 +8693,36 @@ }, "output_type": "display_data" }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/second_third_doses.py:71: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " df = df.drop([\"Previous week's vaccination coverage (%)\", \"Total eligible\", \"Vaccinated over last 7d (%)\"],1)\n", + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/second_third_doses.py:74: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " df2 = df2.drop([\"Previous week's vaccination coverage (%)\", \"Vaccinated over last 7d (%)\"],1)\n", + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/second_third_doses.py:96: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " df = df.drop(f\"{dose_type} Doses due (% of total)\", 1)\n" + ] + }, + { + "data": { + "text/markdown": [ + "[Back to top](#Contents)" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "data": { "text/markdown": [ "## \n", - " # Summary" + " ## Cumulative third dose vaccination figures among 30-39 population \n", + " Please refer to footnotes below table for information." ], "text/plain": [ "" @@ -8730,93 +8752,1274 @@ " \n", " \n", " \n", + " \n", " Third Doses due at 17 Jan 2022 (n)\n", " Third doses overdue (n)\n", " Third doses given (n)\n", " Third doses given (% of due)\n", " Total population\n", " \n", + " \n", + " Category\n", + " Group\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " 80+\n", - " 2,415\n", - " 2,163\n", - " 252\n", - " 10.4\n", - " 4,109\n", + " overall\n", + " overall\n", + " 7,812\n", + " 7,021\n", + " 791\n", + " 10.1\n", + " 12,950\n", " \n", " \n", - " 70-79\n", - " 4,242\n", - " 3,773\n", - " 469\n", - " 11.1\n", - " 7,049\n", + " Sex\n", + " F\n", + " 4,004\n", + " 3,605\n", + " 399\n", + " 10.0\n", + " 6,664\n", " \n", " \n", - " care home\n", - " 1,645\n", - " 1,491\n", - " 154\n", + " M\n", + " 3,815\n", + " 3,423\n", + " 392\n", + " 10.3\n", + " 6,286\n", + " \n", + " \n", + " Ethnicity (broad categories)\n", + " Black\n", + " 1,337\n", + " 1,190\n", + " 147\n", + " 11.0\n", + " 2,219\n", + " \n", + " \n", + " Mixed\n", + " 1,295\n", + " 1,169\n", + " 126\n", + " 9.7\n", + " 2,093\n", + " \n", + " \n", + " Other\n", + " 1,288\n", + " 1,162\n", + " 126\n", + " 9.8\n", + " 2,156\n", + " \n", + " \n", + " South Asian\n", + " 1,393\n", + " 1,260\n", + " 133\n", + " 9.5\n", + " 2,275\n", + " \n", + " \n", + " Unknown\n", + " 1,162\n", + " 1,036\n", + " 126\n", + " 10.8\n", + " 1,967\n", + " \n", + " \n", + " White\n", + " 1,344\n", + " 1,218\n", + " 126\n", " 9.4\n", - " 2,779\n", + " 2,247\n", " \n", " \n", - " shielding (aged 16-69)\n", - " 490\n", - " 441\n", + " ethnicity 16 groups\n", + " African\n", + " 378\n", + " 343\n", + " 35\n", + " 9.3\n", + " 637\n", + " \n", + " \n", + " Bangladeshi or British Bangladeshi\n", + " 448\n", + " 399\n", " 49\n", - " 10.0\n", - " 868\n", + " 10.9\n", + " 714\n", " \n", " \n", - " 65-69\n", - " 2,555\n", - " 2,310\n", - " 245\n", - " 9.6\n", - " 4,270\n", + " Caribbean\n", + " 413\n", + " 378\n", + " 35\n", + " 8.5\n", + " 693\n", " \n", " \n", - " LD (aged 16-64)\n", - " 945\n", - " 840\n", - " 105\n", - " 11.1\n", - " 1,631\n", + " Chinese\n", + " 413\n", + " 371\n", + " 42\n", + " 10.2\n", + " 665\n", " \n", " \n", - " 60-64\n", - " 3,115\n", - " 2,793\n", - " 322\n", - " 10.3\n", - " 5,271\n", + " Other\n", + " 427\n", + " 385\n", + " 42\n", + " 9.8\n", + " 700\n", " \n", " \n", - " 55-59\n", - " 3,745\n", - " 3,388\n", - " 357\n", - " 9.5\n", - " 6,251\n", + " Other Asian\n", + " 427\n", + " 392\n", + " 35\n", + " 8.2\n", + " 707\n", " \n", " \n", - " 50-54\n", - " 4,046\n", - " 3,633\n", + " British or Mixed British\n", " 413\n", + " 371\n", + " 42\n", " 10.2\n", - " 6,755\n", + " 728\n", " \n", " \n", - " 40-49\n", - " 7,525\n", - " 6,748\n", - " 777\n", - " 10.3\n", - " 12,453\n", + " Indian or British Indian\n", + " 399\n", + " 364\n", + " 35\n", + " 8.8\n", + " 658\n", + " \n", + " \n", + " Irish\n", + " 420\n", + " 392\n", + " 28\n", + " 6.7\n", + " 679\n", + " \n", + " \n", + " Other Black\n", + " 427\n", + " 371\n", + " 56\n", + " 13.1\n", + " 700\n", + " \n", + " \n", + " Other White\n", + " 420\n", + " 378\n", + " 42\n", + " 10.0\n", + " 679\n", + " \n", + " \n", + " Other mixed\n", + " 406\n", + " 357\n", + " 49\n", + " 12.1\n", + " 686\n", + " \n", + " \n", + " Pakistani or British Pakistani\n", + " 399\n", + " 350\n", + " 49\n", + " 12.3\n", + " 693\n", + " \n", + " \n", + " Unknown\n", + " 1,169\n", + " 1,057\n", + " 112\n", + " 9.6\n", + " 1,946\n", + " \n", + " \n", + " White + Asian\n", + " 441\n", + " 385\n", + " 56\n", + " 12.7\n", + " 700\n", + " \n", + " \n", + " White + Black African\n", + " 399\n", + " 357\n", + " 42\n", + " 10.5\n", + " 693\n", + " \n", + " \n", + " White + Black Caribbean\n", + " 413\n", + " 371\n", + " 42\n", + " 10.2\n", + " 679\n", + " \n", + " \n", + " Index of Multiple Deprivation (quintiles)\n", + " 1 Most deprived\n", + " 1,526\n", + " 1,365\n", + " 161\n", + " 10.6\n", + " 2,464\n", + " \n", + " \n", + " 2\n", + " 1,519\n", + " 1,365\n", + " 154\n", + " 10.1\n", + " 2,478\n", + " \n", + " \n", + " 3\n", + " 1,435\n", + " 1,302\n", + " 133\n", + " 9.3\n", + " 2,408\n", + " \n", + " \n", + " 4\n", + " 1,491\n", + " 1,344\n", + " 147\n", + " 9.9\n", + " 2,457\n", + " \n", + " \n", + " 5 Least deprived\n", + " 1,484\n", + " 1,323\n", + " 161\n", + " 10.8\n", + " 2,506\n", + " \n", + " \n", + " Unknown\n", + " 357\n", + " 322\n", + " 35\n", + " 9.8\n", + " 637\n", + " \n", + " \n", + "\n", + "" + ], + "text/plain": [ + " Third Doses due at 17 Jan 2022 (n) \\\n", + "Category Group \n", + "overall overall 7,812 \n", + "Sex F 4,004 \n", + " M 3,815 \n", + "Ethnicity (broad categories) Black 1,337 \n", + " Mixed 1,295 \n", + " Other 1,288 \n", + " South Asian 1,393 \n", + " Unknown 1,162 \n", + " White 1,344 \n", + "ethnicity 16 groups African 378 \n", + " Bangladeshi or British Bangladeshi 448 \n", + " Caribbean 413 \n", + " Chinese 413 \n", + " Other 427 \n", + " Other Asian 427 \n", + " British or Mixed British 413 \n", + " Indian or British Indian 399 \n", + " Irish 420 \n", + " Other Black 427 \n", + " Other White 420 \n", + " Other mixed 406 \n", + " Pakistani or British Pakistani 399 \n", + " Unknown 1,169 \n", + " White + Asian 441 \n", + " White + Black African 399 \n", + " White + Black Caribbean 413 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 1,526 \n", + " 2 1,519 \n", + " 3 1,435 \n", + " 4 1,491 \n", + " 5 Least deprived 1,484 \n", + " Unknown 357 \n", + "\n", + " Third doses overdue (n) \\\n", + "Category Group \n", + "overall overall 7,021 \n", + "Sex F 3,605 \n", + " M 3,423 \n", + "Ethnicity (broad categories) Black 1,190 \n", + " Mixed 1,169 \n", + " Other 1,162 \n", + " South Asian 1,260 \n", + " Unknown 1,036 \n", + " White 1,218 \n", + "ethnicity 16 groups African 343 \n", + " Bangladeshi or British Bangladeshi 399 \n", + " Caribbean 378 \n", + " Chinese 371 \n", + " Other 385 \n", + " Other Asian 392 \n", + " British or Mixed British 371 \n", + " Indian or British Indian 364 \n", + " Irish 392 \n", + " Other Black 371 \n", + " Other White 378 \n", + " Other mixed 357 \n", + " Pakistani or British Pakistani 350 \n", + " Unknown 1,057 \n", + " White + Asian 385 \n", + " White + Black African 357 \n", + " White + Black Caribbean 371 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 1,365 \n", + " 2 1,365 \n", + " 3 1,302 \n", + " 4 1,344 \n", + " 5 Least deprived 1,323 \n", + " Unknown 322 \n", + "\n", + " Third doses given (n) \\\n", + "Category Group \n", + "overall overall 791 \n", + "Sex F 399 \n", + " M 392 \n", + "Ethnicity (broad categories) Black 147 \n", + " Mixed 126 \n", + " Other 126 \n", + " South Asian 133 \n", + " Unknown 126 \n", + " White 126 \n", + "ethnicity 16 groups African 35 \n", + " Bangladeshi or British Bangladeshi 49 \n", + " Caribbean 35 \n", + " Chinese 42 \n", + " Other 42 \n", + " Other Asian 35 \n", + " British or Mixed British 42 \n", + " Indian or British Indian 35 \n", + " Irish 28 \n", + " Other Black 56 \n", + " Other White 42 \n", + " Other mixed 49 \n", + " Pakistani or British Pakistani 49 \n", + " Unknown 112 \n", + " White + Asian 56 \n", + " White + Black African 42 \n", + " White + Black Caribbean 42 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 161 \n", + " 2 154 \n", + " 3 133 \n", + " 4 147 \n", + " 5 Least deprived 161 \n", + " Unknown 35 \n", + "\n", + " Third doses given (% of due) \\\n", + "Category Group \n", + "overall overall 10.1 \n", + "Sex F 10.0 \n", + " M 10.3 \n", + "Ethnicity (broad categories) Black 11.0 \n", + " Mixed 9.7 \n", + " Other 9.8 \n", + " South Asian 9.5 \n", + " Unknown 10.8 \n", + " White 9.4 \n", + "ethnicity 16 groups African 9.3 \n", + " Bangladeshi or British Bangladeshi 10.9 \n", + " Caribbean 8.5 \n", + " Chinese 10.2 \n", + " Other 9.8 \n", + " Other Asian 8.2 \n", + " British or Mixed British 10.2 \n", + " Indian or British Indian 8.8 \n", + " Irish 6.7 \n", + " Other Black 13.1 \n", + " Other White 10.0 \n", + " Other mixed 12.1 \n", + " Pakistani or British Pakistani 12.3 \n", + " Unknown 9.6 \n", + " White + Asian 12.7 \n", + " White + Black African 10.5 \n", + " White + Black Caribbean 10.2 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 10.6 \n", + " 2 10.1 \n", + " 3 9.3 \n", + " 4 9.9 \n", + " 5 Least deprived 10.8 \n", + " Unknown 9.8 \n", + "\n", + " Total population \n", + "Category Group \n", + "overall overall 12,950 \n", + "Sex F 6,664 \n", + " M 6,286 \n", + "Ethnicity (broad categories) Black 2,219 \n", + " Mixed 2,093 \n", + " Other 2,156 \n", + " South Asian 2,275 \n", + " Unknown 1,967 \n", + " White 2,247 \n", + "ethnicity 16 groups African 637 \n", + " Bangladeshi or British Bangladeshi 714 \n", + " Caribbean 693 \n", + " Chinese 665 \n", + " Other 700 \n", + " Other Asian 707 \n", + " British or Mixed British 728 \n", + " Indian or British Indian 658 \n", + " Irish 679 \n", + " Other Black 700 \n", + " Other White 679 \n", + " Other mixed 686 \n", + " Pakistani or British Pakistani 693 \n", + " Unknown 1,946 \n", + " White + Asian 700 \n", + " White + Black African 693 \n", + " White + Black Caribbean 679 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 2,464 \n", + " 2 2,478 \n", + " 3 2,408 \n", + " 4 2,457 \n", + " 5 Least deprived 2,506 \n", + " Unknown 637 " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "**Footnotes:**\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- Patient counts rounded to the nearest 7." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## \n", + " ## Third Doses Overdue Among 30-39 Population" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "Third doses which have not been given at least 14 weeks since the second dose" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "Error bars indicate possible error caused by rounding" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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Third Doses due at 17 Jan 2022 (n)Third doses overdue (n)Third doses given (n)Third doses given (% of due)Total population
CategoryGroup
overalloverall8,8697,95991010.315,064
SexF4,5434,1164279.47,721
M4,3263,84348311.27,350
Ethnicity (broad categories)Black1,4491,29515410.62,513
Mixed1,5471,37217511.32,555
Other1,5121,35815410.22,541
South Asian1,5191,35816110.62,604
Unknown1,3371,2041339.92,310
White1,5051,3721338.82,534
ethnicity 16 groupsAfrican4834275611.6812
Bangladeshi or British Bangladeshi4624065612.1770
Caribbean455413429.2791
Chinese4834275611.6833
Other490455357.1805
Other Asian441406357.9770
British or Mixed British4413924911.1749
Indian or British Indian504455499.7847
Irish4904345611.4819
Other Black4904414910.0840
Other White4764274910.3777
Other mixed462420429.1777
Pakistani or British Pakistani476434428.8819
Unknown1,2601,12713310.62,184
White + Asian4623996313.6812
White + Black African5184625610.8882
White + Black Caribbean462420429.1791
Index of Multiple Deprivation (quintiles)1 Most deprived1,6591,49116810.12,870
21,6801,51216810.02,814
31,6731,5121619.62,800
41,7501,56818210.42,947
5 Least deprived1,6871,50518210.82,884
Unknown4273715613.1749
\n", + "
" + ], + "text/plain": [ + " Third Doses due at 17 Jan 2022 (n) \\\n", + "Category Group \n", + "overall overall 8,869 \n", + "Sex F 4,543 \n", + " M 4,326 \n", + "Ethnicity (broad categories) Black 1,449 \n", + " Mixed 1,547 \n", + " Other 1,512 \n", + " South Asian 1,519 \n", + " Unknown 1,337 \n", + " White 1,505 \n", + "ethnicity 16 groups African 483 \n", + " Bangladeshi or British Bangladeshi 462 \n", + " Caribbean 455 \n", + " Chinese 483 \n", + " Other 490 \n", + " Other Asian 441 \n", + " British or Mixed British 441 \n", + " Indian or British Indian 504 \n", + " Irish 490 \n", + " Other Black 490 \n", + " Other White 476 \n", + " Other mixed 462 \n", + " Pakistani or British Pakistani 476 \n", + " Unknown 1,260 \n", + " White + Asian 462 \n", + " White + Black African 518 \n", + " White + Black Caribbean 462 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 1,659 \n", + " 2 1,680 \n", + " 3 1,673 \n", + " 4 1,750 \n", + " 5 Least deprived 1,687 \n", + " Unknown 427 \n", + "\n", + " Third doses overdue (n) \\\n", + "Category Group \n", + "overall overall 7,959 \n", + "Sex F 4,116 \n", + " M 3,843 \n", + "Ethnicity (broad categories) Black 1,295 \n", + " Mixed 1,372 \n", + " Other 1,358 \n", + " South Asian 1,358 \n", + " Unknown 1,204 \n", + " White 1,372 \n", + "ethnicity 16 groups African 427 \n", + " Bangladeshi or British Bangladeshi 406 \n", + " Caribbean 413 \n", + " Chinese 427 \n", + " Other 455 \n", + " Other Asian 406 \n", + " British or Mixed British 392 \n", + " Indian or British Indian 455 \n", + " Irish 434 \n", + " Other Black 441 \n", + " Other White 427 \n", + " Other mixed 420 \n", + " Pakistani or British Pakistani 434 \n", + " Unknown 1,127 \n", + " White + Asian 399 \n", + " White + Black African 462 \n", + " White + Black Caribbean 420 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 1,491 \n", + " 2 1,512 \n", + " 3 1,512 \n", + " 4 1,568 \n", + " 5 Least deprived 1,505 \n", + " Unknown 371 \n", + "\n", + " Third doses given (n) \\\n", + "Category Group \n", + "overall overall 910 \n", + "Sex F 427 \n", + " M 483 \n", + "Ethnicity (broad categories) Black 154 \n", + " Mixed 175 \n", + " Other 154 \n", + " South Asian 161 \n", + " Unknown 133 \n", + " White 133 \n", + "ethnicity 16 groups African 56 \n", + " Bangladeshi or British Bangladeshi 56 \n", + " Caribbean 42 \n", + " Chinese 56 \n", + " Other 35 \n", + " Other Asian 35 \n", + " British or Mixed British 49 \n", + " Indian or British Indian 49 \n", + " Irish 56 \n", + " Other Black 49 \n", + " Other White 49 \n", + " Other mixed 42 \n", + " Pakistani or British Pakistani 42 \n", + " Unknown 133 \n", + " White + Asian 63 \n", + " White + Black African 56 \n", + " White + Black Caribbean 42 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 168 \n", + " 2 168 \n", + " 3 161 \n", + " 4 182 \n", + " 5 Least deprived 182 \n", + " Unknown 56 \n", + "\n", + " Third doses given (% of due) \\\n", + "Category Group \n", + "overall overall 10.3 \n", + "Sex F 9.4 \n", + " M 11.2 \n", + "Ethnicity (broad categories) Black 10.6 \n", + " Mixed 11.3 \n", + " Other 10.2 \n", + " South Asian 10.6 \n", + " Unknown 9.9 \n", + " White 8.8 \n", + "ethnicity 16 groups African 11.6 \n", + " Bangladeshi or British Bangladeshi 12.1 \n", + " Caribbean 9.2 \n", + " Chinese 11.6 \n", + " Other 7.1 \n", + " Other Asian 7.9 \n", + " British or Mixed British 11.1 \n", + " Indian or British Indian 9.7 \n", + " Irish 11.4 \n", + " Other Black 10.0 \n", + " Other White 10.3 \n", + " Other mixed 9.1 \n", + " Pakistani or British Pakistani 8.8 \n", + " Unknown 10.6 \n", + " White + Asian 13.6 \n", + " White + Black African 10.8 \n", + " White + Black Caribbean 9.1 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 10.1 \n", + " 2 10.0 \n", + " 3 9.6 \n", + " 4 10.4 \n", + " 5 Least deprived 10.8 \n", + " Unknown 13.1 \n", + "\n", + " Total population \n", + "Category Group \n", + "overall overall 15,064 \n", + "Sex F 7,721 \n", + " M 7,350 \n", + "Ethnicity (broad categories) Black 2,513 \n", + " Mixed 2,555 \n", + " Other 2,541 \n", + " South Asian 2,604 \n", + " Unknown 2,310 \n", + " White 2,534 \n", + "ethnicity 16 groups African 812 \n", + " Bangladeshi or British Bangladeshi 770 \n", + " Caribbean 791 \n", + " Chinese 833 \n", + " Other 805 \n", + " Other Asian 770 \n", + " British or Mixed British 749 \n", + " Indian or British Indian 847 \n", + " Irish 819 \n", + " Other Black 840 \n", + " Other White 777 \n", + " Other mixed 777 \n", + " Pakistani or British Pakistani 819 \n", + " Unknown 2,184 \n", + " White + Asian 812 \n", + " White + Black African 882 \n", + " White + Black Caribbean 791 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 2,870 \n", + " 2 2,814 \n", + " 3 2,800 \n", + " 4 2,947 \n", + " 5 Least deprived 2,884 \n", + " Unknown 749 " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "**Footnotes:**\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- Patient counts rounded to the nearest 7." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## \n", + " ## Third Doses Overdue Among 18-29 Population" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "Third doses which have not been given at least 14 weeks since the second dose" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "Error bars indicate possible error caused by rounding" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## \n", + " # Summary" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", "
Third Doses due at 17 Jan 2022 (n)Third doses overdue (n)Third doses given (n)Third doses given (% of due)Total population
80+2,4152,16325210.44,109
70-794,2423,77346911.17,049
care home1,6451,4911549.42,779
shielding (aged 16-69)4904414910.0868
65-692,5552,3102459.64,270
LD (aged 16-64)94584010511.11,631
60-643,1152,79332210.35,271
55-593,7453,3883579.56,251
50-544,0463,63341310.26,755
40-497,5256,74877710.312,453
30-397,8127,02179110.112,950
18-298,8697,95991010.315,064
\n", @@ -8834,6 +10037,8 @@ "55-59 3,745 \n", "50-54 4,046 \n", "40-49 7,525 \n", + "30-39 7,812 \n", + "18-29 8,869 \n", "\n", " Third doses overdue (n) Third doses given (n) \\\n", "80+ 2,163 252 \n", @@ -8846,6 +10051,8 @@ "55-59 3,388 357 \n", "50-54 3,633 413 \n", "40-49 6,748 777 \n", + "30-39 7,021 791 \n", + "18-29 7,959 910 \n", "\n", " Third doses given (% of due) Total population \n", "80+ 10.4 4,109 \n", @@ -8857,7 +10064,9 @@ "60-64 10.3 5,271 \n", "55-59 9.5 6,251 \n", "50-54 10.2 6,755 \n", - "40-49 10.3 12,453 " + "40-49 10.3 12,453 \n", + "30-39 10.1 12,950 \n", + "18-29 10.3 15,064 " ] }, "metadata": {}, @@ -8880,7 +10089,7 @@ " )\n", "\n", "\n", - "second_third_doses(tablelist, tablelist_2nd, cohorts=[\"80+\", \"70-79\", \"care home\", \"shielding (aged 16-69)\", \"65-69\", \"60-64\", \"55-59\", \"50-54\", \"LD (aged 16-64)\", \"40-49\"], dose_type=\"Third\", time_period=latest_date_3rdDUE_delay,\n", + "second_third_doses(tablelist, tablelist_2nd, cohorts=[\"80+\", \"70-79\", \"care home\", \"shielding (aged 16-69)\", \"65-69\", \"60-64\", \"55-59\", \"50-54\", \"LD (aged 16-64)\", \"40-49\", \"30-39\",\"18-29\"], dose_type=\"Third\", time_period=latest_date_3rdDUE_delay,\n", " max_ylim=100,\n", " latest_date_fmt=latest_date_fmt,\n", " latest_date_fmt_2=latest_date_3rdDUE_fmt, \n", diff --git a/notebooks/diffable_python/booster-third-doses.py b/notebooks/diffable_python/booster-third-doses.py index 207ec61..01caddc 100644 --- a/notebooks/diffable_python/booster-third-doses.py +++ b/notebooks/diffable_python/booster-third-doses.py @@ -5,7 +5,7 @@ # OpenSAFELY is a new secure analytics platform for electronic patient records built on behalf of NHS England to deliver urgent academic and operational research during the pandemic. # -# This is an extension of our [regular weekly report](https://reports.opensafely.org/reports/vaccine-coverage/) on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our paper available [here](https://doi.org/10.3399/BJGP.2021.0376).** +# This is an extension of our [regular weekly report](https://reports.opensafely.org/reports/vaccine-coverage/) on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our [peer-reviewed publication in the British Journal of General Practice](https://doi.org/10.3399/BJGP.2021.0376).** # # The full analytical methods behind the latest results in this report are available [here](https://github.com/opensafely/nhs-covid-vaccination-uptake). # @@ -78,12 +78,9 @@ # - [**55-59** population](#Cumulative-third-dose-vaccination-figures-among-55-59-population) # - [**50-54** population](#Cumulative-third-dose-vaccination-figures-among-50-54-population) # - [**40-49** population](#Cumulative-third-dose-vaccination-figures-among-40-49-population) -# -# -# - [**All groups (Summary)**](#Summary)) -# -# -# +# - [**30-39** population](#Cumulative-third-dose-vaccination-figures-among-30-39-population) +# - [**18-29** population](#Cumulative-third-dose-vaccination-figures-among-18-29-population) +# - [**All groups (Summary)**](#Summary) # # In[3]: @@ -112,7 +109,7 @@ ) -second_third_doses(tablelist, tablelist_2nd, cohorts=["80+", "70-79", "care home", "shielding (aged 16-69)", "65-69", "60-64", "55-59", "50-54", "LD (aged 16-64)", "40-49"], dose_type="Third", time_period=latest_date_3rdDUE_delay, +second_third_doses(tablelist, tablelist_2nd, cohorts=["80+", "70-79", "care home", "shielding (aged 16-69)", "65-69", "60-64", "55-59", "50-54", "LD (aged 16-64)", "40-49", "30-39","18-29"], dose_type="Third", time_period=latest_date_3rdDUE_delay, max_ylim=100, latest_date_fmt=latest_date_fmt, latest_date_fmt_2=latest_date_3rdDUE_fmt, diff --git a/notebooks/diffable_python/opensafely_vaccine_report_overall.py b/notebooks/diffable_python/opensafely_vaccine_report_overall.py index 9911489..b6aad24 100644 --- a/notebooks/diffable_python/opensafely_vaccine_report_overall.py +++ b/notebooks/diffable_python/opensafely_vaccine_report_overall.py @@ -5,7 +5,7 @@ # # OpenSAFELY is a new secure analytics platform for electronic patient records built on behalf of NHS England to deliver urgent academic and operational research during the pandemic. # -# This is our regular weekly report on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our paper available [here](https://doi.org/10.3399/BJGP.2021.0376).** +# This is our regular weekly report on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our [peer-reviewed publication in the British Journal of General Practice](https://doi.org/10.3399/BJGP.2021.0376).** # # The full analytical methods behind the latest results in this report are available [here](https://github.com/opensafely/nhs-covid-vaccination-uptake). # diff --git a/notebooks/diffable_python/population_characteristics.py b/notebooks/diffable_python/population_characteristics.py index 3f1df96..372b6c7 100644 --- a/notebooks/diffable_python/population_characteristics.py +++ b/notebooks/diffable_python/population_characteristics.py @@ -1,20 +1,37 @@ #!/usr/bin/env python # coding: utf-8 +# In[1]: + + + # # Vaccines and patient characteristics + +# In[2]: + + + + + + + # ### Import libraries and data # # The datasets used for this report are created using the study definition [`/analysis/study_definition.py`](../analysis/study_definition.py), using codelists referenced in [`/codelists/codelists.txt`](../codelists/codelists.txt). -# In[1]: + +# In[3]: + + get_ipython().run_line_magic('load_ext', 'autoreload') get_ipython().run_line_magic('autoreload', '2') - + import pandas as pd import numpy as np +import json from datetime import datetime, timedelta import subprocess from IPython.display import display, Markdown, HTML @@ -29,7 +46,10 @@ # ### Import our custom functions -# In[2]: + +# In[4]: + + # import custom functions from 'lib' folder @@ -37,20 +57,26 @@ sys.path.append('../lib/') -# In[3]: +# In[5]: + + from data_processing import load_data from second_third_doses import abbreviate_time_period -# In[4]: +# In[6]: -from report_results import find_and_save_latest_date, create_output_dirs -# In[5]: +from report_results import find_and_save_latest_date, create_output_dirs, report_results, round7 + + +# In[7]: + + # create output directories to save files into @@ -59,19 +85,26 @@ # ### Load and Process the raw data -# In[6]: +# In[8]: -df = load_data() -# In[7]: + +df = load_data( save_path = savepath ) + + +# In[9]: + + latest_date, formatted_latest_date = find_and_save_latest_date(df, savepath=savepath) -# In[8]: +# In[10]: + + print(f"Latest Date: {formatted_latest_date}") @@ -81,13 +114,18 @@ # #### Calculate cumulative sums at each date and select latest date + previous figures for comparison -# In[9]: + +# In[11]: + + from report_results import cumulative_sums -# In[10]: +# In[12]: + + # population subgroups - in a dict to indicate which field to filter on @@ -147,13 +185,17 @@ } -# In[11]: +# In[13]: + + df_dict_cum = cumulative_sums(df, groups_of_interest=population_subgroups, features_dict=features_dict, latest_date=latest_date) -# In[12]: +# In[14]: + + # for details on second/third doses, no need for breakdowns of any groups (only "overall" figures will be included) @@ -170,19 +212,26 @@ # ### Cumulative vaccination figures - overall -# In[13]: + +# In[15]: + + from report_results import make_vaccine_graphs -# In[14]: +# In[16]: + + make_vaccine_graphs(df, latest_date=latest_date, grouping="priority_status", savepath_figure_csvs=savepath_figure_csvs, savepath=savepath, suffix=suffix) -# In[15]: +# In[17]: + + make_vaccine_graphs(df, latest_date=latest_date, include_total=False, savepath=savepath, savepath_figure_csvs=savepath_figure_csvs, suffix=suffix) @@ -190,19 +239,26 @@ # ### Reports -# In[16]: + +# In[18]: + + from report_results import summarise_data_by_group -# In[17]: +# In[19]: + + summarised_data_dict = summarise_data_by_group(df_dict_cum, latest_date=latest_date, groups=groups) -# In[18]: +# In[20]: + + summarised_data_dict_2nd_dose = summarise_data_by_group(df_dict_cum_second_dose, latest_date=latest_date, groups=groups) @@ -212,20 +268,27 @@ # ### Proportion of each eligible population vaccinated to date -# In[20]: + +# In[21]: + + from report_results import create_summary_stats, create_detailed_summary_uptake -# In[21]: +# In[22]: + + summ_stat_results, additional_stats = create_summary_stats(df, summarised_data_dict, formatted_latest_date, groups=groups, savepath=savepath, suffix=suffix) -# In[22]: +# In[23]: + + summ_stat_results_2nd_dose, _ = create_summary_stats(df, summarised_data_dict_2nd_dose, formatted_latest_date, @@ -237,7 +300,9 @@ vaccine_type="third_dose", suffix=suffix) -# In[23]: +# In[24]: + + # display the results of the summary stats on first and second doses @@ -245,7 +310,9 @@ display(Markdown(f"*\n figures rounded to nearest 7")) -# In[24]: +# In[25]: + + # other information on vaccines @@ -258,7 +325,10 @@ # # Detailed summary of coverage among population groups as at latest date -# In[25]: + +# In[26]: + + create_detailed_summary_uptake(summarised_data_dict, formatted_latest_date, @@ -268,13 +338,18 @@ # # Demographics time trend charts -# In[26]: + +# In[27]: + + from report_results import plot_dem_charts -# In[27]: +# In[28]: + + plot_dem_charts(summ_stat_results, df_dict_cum, formatted_latest_date, pop_subgroups=["80+", "70-79", "65-69","shielding (aged 16-69)", "60-64", "55-59", "50-54", "40-49", "30-39", "18-29"], groups_dict=features_dict, @@ -284,7 +359,10 @@ # ## Completeness of ethnicity recording -# In[28]: + +# In[29]: + + from data_quality import * @@ -294,7 +372,10 @@ # # Second doses -# In[29]: + +# In[30]: + + # only count second doses where the first dose was given at least 14 weeks ago @@ -332,7 +413,9 @@ def subtract_from_date(s, unit, number, description): description="latest_date_of_first_dose_for_due_second_doses") -# In[30]: +# In[31]: + + # filter data @@ -346,7 +429,9 @@ def subtract_from_date(s, unit, number, description): df_s.loc[(pd.to_datetime(df_s["covid_vacc_date"]) <= "2020-12-07"), "covid_vacc_second_dose_date"] = 0 -# In[31]: +# In[32]: + + # add "brand of first dose" to list of features to break down by @@ -359,7 +444,9 @@ def subtract_from_date(s, unit, number, description): features_dict_2[k] = ls -# In[32]: +# In[33]: + + # data processing / summarising @@ -376,7 +463,9 @@ def subtract_from_date(s, unit, number, description): # -# In[33]: +# In[34]: + + # latest date of 14 weeks ago is entered as the latest_date when calculating cumulative sums below. @@ -405,7 +494,10 @@ def subtract_from_date(s, unit, number, description): # # Booster/third doses -# In[34]: + +# In[35]: + + # Only want to count third doses where the second dose was given some period of time ago. @@ -419,7 +511,9 @@ def subtract_from_date(s, unit, number, description): description="latest_date_of_second_dose_for_due_third_doses") -# In[35]: +# In[36]: + + # filtering for third doses that are "due" @@ -434,13 +528,15 @@ def subtract_from_date(s, unit, number, description): df_t.loc[(pd.to_datetime(df_t["covid_vacc_second_dose_date"]) <= "2020-12-21"), "covid_vacc_third_dose_date"] = 0 -# In[36]: +# In[37]: + + # summarise third doses to date (after filtering above) -# Include 40+ age groups plus priority groups (50+/CEV/Care home etc) only -population_subgroups_third = {key: value for key, value in population_subgroups.items() if 0 < value < 11} +# Include 18+ age groups plus priority groups (50+/CEV/Care home etc) only +population_subgroups_third = {key: value for key, value in population_subgroups.items() if 0 < value < 13} df_dict_cum_third_dose = cumulative_sums(df_t, groups_of_interest=population_subgroups_third, features_dict=features_dict, latest_date=latest_date, reference_column_name="covid_vacc_third_dose_date") @@ -453,13 +549,17 @@ def subtract_from_date(s, unit, number, description): savepath=savepath, vaccine_type="third_dose") -# In[ ]: +# In[38]: + + display(Markdown(f"## For comparison look at second dose coverate UP TO {booster_delay_number} {booster_delay_unit.upper()} AGO")) -# In[37]: +# In[39]: + + # latest date of 200 days ago is entered as the latest_date when calculating cumulative sums below. @@ -469,6 +569,27 @@ def subtract_from_date(s, unit, number, description): df_3rdDUE = df.copy() df_3rdDUE.loc[(pd.to_datetime(df_3rdDUE["covid_vacc_second_dose_date"]) <= "2020-12-21"), "covid_vacc_second_dose_date"] = 0 +df_dict_cum_3rdDUE = cumulative_sums( + df_3rdDUE, groups_of_interest=population_subgroups_third, features_dict=features_dict, + latest_date=date_3rdDUE, + reference_column_name="covid_vacc_second_dose_date" + ) + +summarised_data_dict_3rdDUE = summarise_data_by_group( + df_dict_cum_3rdDUE, latest_date=date_3rdDUE, + groups=population_subgroups_third.keys() + ) + +create_detailed_summary_uptake(summarised_data_dict_3rdDUE, formatted_latest_date=date_3rdDUE, + groups=population_subgroups_third.keys(), + savepath=savepath, vaccine_type=f"second_dose_{booster_delay_number}{booster_delay_unit_short}_ago") + + +# In[40]: + + + + df_dict_cum_3rdDUE = cumulative_sums( df_3rdDUE, groups_of_interest=population_subgroups_third, features_dict=features_dict, latest_date=date_3rdDUE, diff --git a/notebooks/diffable_python/second_doses.py b/notebooks/diffable_python/second_doses.py index e8c98be..e23a1b1 100644 --- a/notebooks/diffable_python/second_doses.py +++ b/notebooks/diffable_python/second_doses.py @@ -5,7 +5,7 @@ # OpenSAFELY is a new secure analytics platform for electronic patient records built on behalf of NHS England to deliver urgent academic and operational research during the pandemic. # -# This is an extension of our [regular weekly report](https://reports.opensafely.org/reports/vaccine-coverage/) on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our paper available [here](https://doi.org/10.3399/BJGP.2021.0376).** +# This is an extension of our [regular weekly report](https://reports.opensafely.org/reports/vaccine-coverage/) on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our [peer-reviewed publication in the British Journal of General Practice](https://doi.org/10.3399/BJGP.2021.0376).** # # The full analytical methods behind the latest results in this report are available [here](https://github.com/opensafely/nhs-covid-vaccination-uptake). # diff --git a/notebooks/opensafely_vaccine_report_overall.ipynb b/notebooks/opensafely_vaccine_report_overall.ipynb index a944fdc..3835ce8 100644 --- a/notebooks/opensafely_vaccine_report_overall.ipynb +++ b/notebooks/opensafely_vaccine_report_overall.ipynb @@ -8,7 +8,7 @@ "\n", "OpenSAFELY is a new secure analytics platform for electronic patient records built on behalf of NHS England to deliver urgent academic and operational research during the pandemic. \n", "\n", - "This is our regular weekly report on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our paper available [here](https://doi.org/10.3399/BJGP.2021.0376).** \n", + "This is our regular weekly report on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our [peer-reviewed publication in the British Journal of General Practice](https://doi.org/10.3399/BJGP.2021.0376).** \n", "\n", "The full analytical methods behind the latest results in this report are available [here](https://github.com/opensafely/nhs-covid-vaccination-uptake).\n", "\n", diff --git a/notebooks/population_characteristics.ipynb b/notebooks/population_characteristics.ipynb index 2ebac93..2af0a9d 100644 --- a/notebooks/population_characteristics.ipynb +++ b/notebooks/population_characteristics.ipynb @@ -1,34 +1,45 @@ { "cells": [ { - "cell_type": "markdown", - "metadata": { - "lines_to_next_cell": 2 - }, + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], "source": [ - "# Vaccines and patient characteristics" + "\n", + "# # Vaccines and patient characteristics" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 2, "metadata": {}, + "outputs": [], "source": [ - "### Import libraries and data\n", "\n", - "The datasets used for this report are created using the study definition [`/analysis/study_definition.py`](../analysis/study_definition.py), using codelists referenced in [`/codelists/codelists.txt`](../codelists/codelists.txt). " + "\n", + "\n", + "\n", + "\n", + "# ### Import libraries and data\n", + "# \n", + "# The datasets used for this report are created using the study definition [`/analysis/study_definition.py`](../analysis/study_definition.py), using codelists referenced in [`/codelists/codelists.txt`](../codelists/codelists.txt). " ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ - "%load_ext autoreload\n", - "%autoreload 2\n", - " \n", + "\n", + "\n", + "get_ipython().run_line_magic('load_ext', 'autoreload')\n", + "get_ipython().run_line_magic('autoreload', '2')\n", + "\n", "import pandas as pd\n", "import numpy as np\n", + "import json\n", "from datetime import datetime, timedelta\n", "import subprocess\n", "from IPython.display import display, Markdown, HTML\n", @@ -38,140 +49,153 @@ "suffix = \"_tpp\"\n", "\n", "# get current branch\n", - "current_branch = subprocess.run([\"git\", \"rev-parse\", \"--abbrev-ref\", \"HEAD\"], capture_output=True).stdout.decode(\"utf8\").strip()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Import our custom functions" + "current_branch = subprocess.run([\"git\", \"rev-parse\", \"--abbrev-ref\", \"HEAD\"], capture_output=True).stdout.decode(\"utf8\").strip()\n", + "\n", + "\n", + "# ### Import our custom functions" ] }, { "cell_type": "code", - "execution_count": 2, - "metadata": {}, + "execution_count": 4, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "# import custom functions from 'lib' folder\n", "import sys\n", - "sys.path.append('../lib/')\n" + "sys.path.append('../lib/')" ] }, { "cell_type": "code", - "execution_count": 3, - "metadata": {}, + "execution_count": 5, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "from data_processing import load_data\n", - "from second_third_doses import abbreviate_time_period" + "from second_third_doses import abbreviate_time_period\n" ] }, { "cell_type": "code", - "execution_count": 4, - "metadata": {}, + "execution_count": 6, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ - "from report_results import find_and_save_latest_date, create_output_dirs" + "\n", + "\n", + "from report_results import find_and_save_latest_date, create_output_dirs, report_results, round7" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ + "\n", + "\n", "# create output directories to save files into \n", - "savepath, savepath_figure_csvs, savepath_table_csvs = create_output_dirs()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Load and Process the raw data " + "savepath, savepath_figure_csvs, savepath_table_csvs = create_output_dirs()\n", + "\n", + "\n", + "# ### Load and Process the raw data " ] }, { "cell_type": "code", - "execution_count": 6, - "metadata": {}, + "execution_count": 8, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/data_processing.py:152: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/data_processing.py:153: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", " df = df.drop([\"imd\",\"ethnicity_16\", \"ethnicity\", 'ethnicity_6_sus',\n", - "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/data_processing.py:195: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/data_processing.py:206: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", " df = df.drop(['care_home', 'age'], 1)\n" ] } ], "source": [ - "df = load_data()" + "\n", + "\n", + "df = load_data( save_path = savepath )" ] }, { "cell_type": "code", - "execution_count": 7, - "metadata": {}, + "execution_count": 9, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "latest_date, formatted_latest_date = find_and_save_latest_date(df, savepath=savepath)" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Latest Date: 15 Dec 2021\n" + "Latest Date: 02 Feb 2022\n" ] } ], "source": [ - "print(f\"Latest Date: {formatted_latest_date}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Summarise by group and demographics at latest date" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Calculate cumulative sums at each date and select latest date + previous figures for comparison" + "\n", + "\n", + "print(f\"Latest Date: {formatted_latest_date}\")\n", + "\n", + "\n", + "# ### Summarise by group and demographics at latest date\n", + "\n", + "# #### Calculate cumulative sums at each date and select latest date + previous figures for comparison" ] }, { "cell_type": "code", - "execution_count": 9, - "metadata": {}, + "execution_count": 11, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "from report_results import cumulative_sums" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "metadata": { "lines_to_next_cell": 2 }, "outputs": [], "source": [ + "\n", + "\n", "# population subgroups - in a dict to indicate which field to filter on\n", "\n", "\n", @@ -226,13 +250,15 @@ " \"16-17\": [\"sex\", \"ethnicity_6_groups\", \"imd_categories\"],\n", " \"LD (aged 16-64)\": [\"sex\", \"ageband_5yr\", \"ethnicity_6_groups\"],\n", " \"DEFAULT\": DEFAULT # other age groups\n", - " }\n" + " }" ] }, { "cell_type": "code", - "execution_count": 11, - "metadata": {}, + "execution_count": 13, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [ { "name": "stderr", @@ -244,15 +270,19 @@ } ], "source": [ + "\n", + "\n", "df_dict_cum = cumulative_sums(df, groups_of_interest=population_subgroups, features_dict=features_dict, latest_date=latest_date)" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ + "\n", + "\n", "# for details on second/third doses, no need for breakdowns of any groups (only \"overall\" figures will be included)\n", "second_dose_features = {}\n", "for g in groups:\n", @@ -262,33 +292,35 @@ " latest_date=latest_date, reference_column_name=\"covid_vacc_second_dose_date\")\n", "\n", "df_dict_cum_third_dose = cumulative_sums(df, groups_of_interest=population_subgroups, features_dict=second_dose_features, \n", - " latest_date=latest_date, reference_column_name=\"covid_vacc_third_dose_date\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Cumulative vaccination figures - overall" + " latest_date=latest_date, reference_column_name=\"covid_vacc_third_dose_date\")\n", + "\n", + "\n", + "# ### Cumulative vaccination figures - overall" ] }, { "cell_type": "code", - "execution_count": 13, - "metadata": {}, + "execution_count": 15, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "from report_results import make_vaccine_graphs" ] }, { "cell_type": "code", - "execution_count": 14, - "metadata": {}, + "execution_count": 16, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [ { "data": { - "image/png": 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", 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Cprv7oNQAM1uPAg+4WaR/Rpk2IXwZ1qXZZK80Z25bqb5CmceByo41mfvEd4TP8g4yKp2rJghVWzz0wzw0+iXfh7AfP2VmPd0932e8RtxRlaM14RT61HImmdloQl+hHwmduk+mcO0IzfmZy8zs01NIJaqgfbaK88znLkIFsT0h4Xra3TN/eKy50FBVuyearjXh2HAT4cdIvzzLOwoY5u5Xpgak/VguREHfcwUc16piIWFdV7af5jsGYmYtCcnphoSO8tn6fE0m+7G9B6G5MNPdhPdymLu/lmPZFxD6SP/J3R/OMsoBhP6pKZ+nxTOgkni+8Ix+VQlaTlaFNCleS/iAbsj2opltaWapDsMzo8ft0l7fgMI7mBZqJtAu/ZeCmW1N/nJwquy8Im269Qj9KjItJ/T/ycvdPyU0DR4b/f1A6IeQ8jGhXX5bdx+X5a/SXwU1zd1/cvfXCZ1U1yf0AYBQSSno/RLeawczS1WAUr90jsgY743o8aiM4an1/WaW+Oa4+32ExDS1Hf0f4cuxYyXr7/PM+WTM0wlNZocB+xI6lGd+yTYjbbuIHJ8xn6WETsTHRE1S2YwhdJIfnCumamhGqACkO5ZQrUmX+nGU7zP9mFARWeMzMrNdCZXtN7JNVIv+S6j0rGoiippAdssYb61jTWTfQhbi7j8Qqg49CX2B1tquskxTHjWjX0Q4dnYvYFGZ+8Th0bRvZwy/k3DW2KXAtGgfLVTmMo4i7C/vVGEeKVXeZwuU63j6OKHi/Bih0nd3VWbs7gvd/UlC02r69lDZMS3vvp5n+ip/z1VyXKvMWsuNttfxwOGWdqFxM9siWm7O/TTan14kHO8HRK0e2YwAfmbhRKvUtJ0I+9+IjHneREiQj3f353Ms+0+EFqUL3P1v2cZx94kZ+18qgRwBtE9vjYkSxwOyxJOY5VQmZ4UrCvBNC1cg/6uF3vgPEqoFrQnt7icRmjY+JPTJWgTca2aXEDLJvxC+gGrS04SzWx41s78SOpmex+rqQmWmEnaWq8xsJWGnO6OScacA+5nZy4RfF1/7mmcRZRpG+LW8PaE5YNV7dnc3sz8Aw6NfuE9FsbYj7CxfuPtf88S+zszsFELfjJcIHb5T6+trVldhpgBtzOx/CVWNH919YpbZQSghnws8Z2bnE5qATiE0763i7pPN7HHg0qg6MIbQd+UiwinfH0bxDSeclfMeYV33Ipz+fE80n0/N7DrgdjPrSji4/EhoJvwlcF9UwctlWPSe747WQeYB6mXgnOj9vENobj4sy3z+HE37dnTAmUU4y2lHd/+juy82s/OAv5nZs4REbzHhDLkfq7qDZvEycLCZ3UzolNsb+BOhYpMu9Wv0LDP7F7CykiRipZldTKgUPEJoZmlPaGb/hML7EdWUKwnr/RUzu5FwDLmIkBSuOkvR3WdH1crzzGw+YRs8hlDFLtSZhATiFTO7n1Bd24jQV6bU3c81s/0JyfPzhF/D6xPW92LWTpqy2dbMHiD0q+pCWK9vZKkGPEs4o3E3wtmxVbGvmd1AOKOxL6HaPszdp+WebG2F7rProNLjqbsvs3C3gTOAie6et7+emQ1l9Wcwl7Buj2XNszqnAHtEn+EcYL67zyDsQ8eZ2URCN4XfkD1ZmgKcamZHEqp9i939Ywr8nst3XMuhsrgvIiRNL5jZnYR+m5dFsdyUZ57PEratIcD66T+WgU/dPXUG572EJvXhZpY6UeIKwjFzVdxmdg5h//k78EnG/OZFRQjM7CjCdv0y8HrGeN/7mmeOZzOC8Bk/YmZnE9bjeYQm0VVnthbNcrzwsxp2JSQ6swmJygLCxn0Ma57dtzuhs+BSQs//Y6j8LMWTMpZxKdnPrJpBxlkbhKvgTiL0MZtAKAeOIv91uHYkVCmWEr4sLyfLWYCEjXM84Yt91Vk7me8lbfzWhF8mTvgFkW0d7kL4klwYzXcG4UC8S551X9WzFDPX3y6E/kpfRjHOjj7LrmnjrE/4pZkqXa/1HjPmuRUhgSv0Olwzo+1mJmtf0+csQmUj/bpWl6aPE413bDTeD4SD21RCp8WCrthO2C4duDrLa00JTRvzCAfyFwi/BtdYx9G4vQjXvvouivcj4JyMcQ4jdOpfRujYPxbYfx0+uzW2N0J15EpCsryUkPz1Yu2z/UoJPwDmEhIVz9j3BmUsJ3Udrp+iz6HS63BlWXdrraMs4xR0lmI07JeEEz1+Ilwj6WTCiSDvZ4y3edrnMIfQZybbvpw17ui17oR9cG60vFmEg+++0etdCc1UnxP22XmE7b5fnvfbP4rjN9Fn+B2rqzgbVTLNPdEyNsw177TxB0XL2JOwfy8hHJcruw7XSTnmUdV9tqrzzHo8zThGOfCHAt/7cYTjfepz+5xwKZWWaeN0I1Qxl5J2PStCUv0E4Vi3kPCjaGcy9gtCU91L0efmrPndUsj3XEHHtSzvLWvc0WuZ1+EaTgHX4YrmU9lf5rGgIyFB+z5678+z9nfPqBzzS4/3wRzjjcoXdzSPNoTEbkG0Tl4DemaMUxTLsWgmIiKJFPWvmQ686O4nxh1PbYiqSdOB0e5+bL7xo2kGESqQnb3yJqKiYGZXEaovm7l7Va93JVIU8jYpiojUJTP7G6Ep62vCRSqHECrIt8YZV22I+olsR+iW0YH8TUP1ipn1IlQRhwBDlWxJfaaES0SSpgnh7K52hM7W7xDuSVhnJ5fUoZ2AkYSmsSEe3ZmiAfkH4XN+hdD3TKTeUpOiiIiISC2L+0rzIiIiIvWeEi4RERGRWqY+XFKpjTbayDt16hR3GCIiRWX8+PHz3b1t3HFIsijhkkp16tSJcePq+s4uIiLFzcxm5h9LGho1KYqIiIjUMiVcIiIiIrVMCZeIiIhILVMfLhERkQQaP378xmVlZfcR7kagAkmyVQCTysvLT+rdu/fcbCMo4RIREUmgsrKy+zbZZJPubdu2XVhSUqKrlCdYRUWFzZs3r8ecOXPuAw7MNo4yZhERkWTarm3btt8r2Uq+kpISb9u27SJCNTL7OHUYj4iIiBSuRMlW8Yg+q0rzKiVcIiIikcfGfsGR97zNZf+cHHcosZs/f37ptddem/MCrh9//HGju+++u02+eX388ceNOnfuvG3NRVd8lHCJiEiDl0q0zv/HRMZ+viDucBLh22+/Lb3//vs3zjXOJ5980vjJJ5/Mm3CJOs2LiEgD99jYLzj/HxMB6LdlGw7asT0D+3WMOar4nXXWWZt/+eWXjbt169Zjr732+h7g9ddfb2VmfvbZZ8/+/e9/v/CCCy5o/9lnnzXp1q1bj6OPPnr+UUcd9d3AgQO3XLZsWQnArbfe+sUvf/nLH+J9J8mghEtERBqkx8Z+wfAPvlpV0br6kO2VaKW56aabZu2///5NP/rooykPPvjgBkOHDm07derUybNnzy7r27dv9wEDBiy56qqrvrrpppvajRw5cjrA4sWLS0aPHj2tWbNmPnHixMZHH330VpMmTZoa93tJAiVcIiLS4BRbVevsZyZ0mDZncbOanGeXTVosveGwnl8WMu7o0aNbHHHEEQvKysro0KFDeb9+/Za89dZbzVq1alWRPt7y5cvtxBNP3GLKlClNS0pKmDlzZuOajLmYKeESEZEGJT3ZUlWrMO6FnSx51VVXtdt4441XPPvss59XVFTQtGnT3rUcWtFQwiUiIg1CMTchFlqJqkmtWrVa+cMPP5QA7LXXXovvvffetqeddtq3c+fOLXvnnXea33bbbV/OnDmz0ZIlS0pT0yxatKh08803X15aWsrtt9++4cqVK+s67MRSwiUiIvVaZqJVDE2ISbDJJpus7N2795LOnTtvu/feey/adtttl3Xv3n1bM/PLLrtsVseOHcvbtWu3sqyszLt27dpj4MCB808//fS5hx566NbPP/986913331x06ZNK/IvqWGwQsuE0vD06dPHx40bF3cYIiLrLI6+WmY23t37VHc+EyZMmNGzZ8/5NRGT1I0JEyZs1LNnz07ZXlOFS0RE6p1ibj6U+kkJl4iI1CvFdgaiNAxKuEREpF5QVUuSTAlXAplZf+BIYA+gE+DAF8AbwBPu/mZcsYmIJJGqWpJ0SrgSxszeA3oCS4APgImAAZsBvwVOMbP3aqJDpohIsVNVS4qFEq7k+QQ4Gxjl7mtcwMTMSoGfA7+PIzARkaTQpR6k2CjhShh3PzLHayuBV6M/EZEGSc2HdevTTz9db/DgwR2nT5/etKKigl/84heL7rrrrlnvvfdeky+//LLRkUceuQjgzDPP3Kx58+YrL7/88m/ijjmJSuIOQLIzszPM7I9mtoGZvWlm081s/7jjEhGJy2Njv+DIe95e47Y8T568i5KtWlRRUcHBBx+8zYEHHvjdzJkzJ33++eeTfvjhh5IhQ4a0HzduXLMXX3yxVU0tq7y8vKZmlUiqcCXX6cAdwDFAL2ARcD3wQowxiYjEQlWtePzzn/9s0bhx44ohQ4Z8C1BWVsbdd9/9ZadOnXYoKytzd6dbt27NzzrrrNkAU6dObdq3b9+uX3/9daNTTjnlmwsvvHAuwJ133tnmrrvuardixQrbaaedfhg2bNjMsrIymjVr1mvw4MHfvP766y1vuOGGWcOHD2/1yiuvbFBaWur9+/f/fujQobPifP81SQlXcrUDvgH2Ah4A3gPuijUiEZE6pk7x8Zo4cWLTnj17Lk0f1qZNm4r27dsv/+1vfzt/2rRpTYYNG/YFwJlnntl0+vTpTcaMGfPxd999V9q9e/ftzj777HmTJ09u/Mwzz7QZN27cR40bN/Zjjjmm4913373haaed9u2yZctKtttuu2W33HLL1998803pySef3Omzzz6bVFJSwvz580uzR1WclHAl11zgDGBz4CxgfWBxIROa2RnASYTLSUwEjgeaAU8SLjMxAzjC3RfWdNAiIjVFVa00z/+hA3OnNKvReW7cYykH35HzptjujpmtdQ/AaPha4w8YMOC7pk2betOmTcvbtGmzYtasWWUvv/xyi0mTJjXr2bNnd4Aff/yxZOONNy4HKC0tZdCgQQsB2rRps7Jx48YVRx111Bb77bffolTfsPpCCVdyXQVcB0wDngNuAUbnm8jM2gN/Anq4+zIzewo4CugBvObu15rZucC5wDm1FLuIyDpTVSs5tt9++2XDhw9vnT5swYIFJXPmzGlUWlq6ViLWuHHjVcNKS0spLy83d7fDDz/82zvuuOOrzPEbNWpUUVYWUpH11luPDz74YOqIESNaPvHEE63vuuuujf/73/9Oq4W3FQslXAnl7vcA96QNOrEKk5cBTc1sBaGy9TVwHtA/ev0hYBRKuEQkQXSphxzyVKJqy4EHHrj4wgsvLLn99ts3PO20074tLy/n1FNP7XD44YfP32STTVa888476+ebx69+9avvf/Ob32xz/vnnf9O+ffvyb775pnTRokWlXbp0WZ4+3qJFi0qWLFlScuSRRy7q37//ki5dumxfe++s7inhShgz+3uOl93dcyZe7v6Vmd1IuDL9MuDf7v5vM2vn7rOjcWab2cY1F7WISPWo+TCZSkpKeP7556cPHjx4ixtuuGHTiooK9t5770W33XbbV99//33JjTfeuGm3bt16pDrNZ9O7d+8fL7zwwq/22WefLhUVFay33np+2223fZGZcH333Xel+++//zY//fSTAVx55ZWxJJm1xdzXqghKjMysIsfL7u45OxGaWWvgWcKtgb4DngaeAW539w3Sxlvo7q2zTD8YGAzQsWPH3jNnzqzqWxARKVh9bD40s/E1cTeQCRMmzOjZs+f8mohJ6saECRM26tmzZ6dsr6nClTw7R49HRf9fTrhe2oXA2AKm/wXwubvPAzCz54BdgW/MbNOourUpoVP+Wtx9KDAUoE+fPsrGRaTWqKolDYkSroRx9/EAZvYMcL27vx4970Loh5Wv39UXwM/MrBmhSXEfYBzwA3AccG30OLxW3oCISB71saolko8SrmS7xsz6EW5efRDwbb4J3H1slKy9B5QD7xMqVs2Bp8zsREJSdnitRS0iUglVtaShUsKVXCcBjwC/i57PocCbVrv7JcAlGYN/IlS7RERikZ5sqaolDY0SroRy99fMbAugWzToI3dfnmsaEZEkUhOiiBKuxDKzJsChhCvDl0bD3N2viDMuEZFC6bpaIqsp4Uqu4YQzDtPvneCAEi4RSTQlWvVHaWlp786dOy9buXKlbbPNNsueeuqpGS1atFjr8kW9evXq9v77739UlXmnpvn4448bjRw5svkpp5yyoOYiT56SuAOQSvUDXgGOJnRwPxw4ItaIRETySPXTGvv5Avpt2YarD9meJ0/eRclWkWrcuHHFRx99NOWTTz6ZvN566/lNN93UNv318vJyAKqSbGVO88knnzR+8skn29Rc1GsvKwmUcCXXc8CH7v6kuz+b+os7KBGRymR2ileiVb/svvvuS6ZPn974hRdeaNGvX78uBxxwwJZdu3bdFqBZs2a9ACoqKjj55JM379y587ZdunTpce+997YGyDXNBRdc0H7cuHHNu3Xr1uOyyy7buHfv3l3HjBnTNLXcnXbaqdvYsWObpseyePHikn333XerLl269Nhvv/222mGHHbq9+eabzVLzPf300zfbYYcdur322mvNL7300nadO3fetnPnzttefvnlGwN8/PHHjTp37rxtan4XX3xxuzPPPHMzgL59+3Y94YQTOvTq1atb586dtx05cmQzgBdffLF5t27denTr1q1H9+7deyxcuLBKOZSaFJNrd2BrMzsGSJVZ3d17xhiTiMha1Cm+/luxYgWvvPJKywEDBnwP8OGHH67//vvvT+7WrdsaJ3MNGzZsg4kTJzadOnXq5NmzZ5f17du3+4ABA5bkmuaqq6766qabbmo3cuTI6QBt2rRZed9992206667fvnhhx82Xr58ufXr129Z+jQ33HBD2w022GDltGnTprz77rtNdtlll1XJ07Jly0q22267ZbfccsvXo0ePbvbYY49tOH78+KnuTu/evbvvs88+izfaaKOVud7v0qVLS95///2P/vWvfzUfPHjwlp988snkm266aZPbbrtt5oABA35YtGhRSbNmzXLdGWYtSriSa5vocbPoT0QkcXRdrbpx0X8u6jB94fRmNTnPbVpvs/SK3a7Ieb/Cn376qaRbt249APr167d4yJAh81999dXmO+ywww+ZiRPA6NGjWxxxxBELysrK6NChQ3m/fv2WvPXWW81atWpVUdk0mQYNGrTwhhtu2PSnn36adffdd280cODAtW5vNGbMmOZDhgyZC7Dzzjv/2KVLl6Wp10pLSxk0aNBCgFGjRjXfd999v2vZsmUFwH777bdw5MiRLQ4//PDvcsUwcODABQC//vWvlyxZsqRk/vz5pT/72c+W/PnPf+5wxBFHLDj66KMXbr311kq46gN3V3OviCSWqloNQ6oPV+bwyqo7ue7PXGhFqEWLFhV77LHH94899tgGI0aMaDN+/Pi1lp9rOY0aNaooKyvLOV5ZWZlXVKwO58cff1zjO9fMyHx+9dVXzzn44IMXDR8+vNWuu+7a/eWXX57Wq1evHwt5T6CEK9HMrAPQHWgSDXJ3/2eMIYmIqKoVg3yVqKTYa6+9Ft97771tTzvttG/nzp1b9s477zS/7bbbvvzwww+bVjZNq1atVi5ZsqQ0fdgpp5wy/9BDD91m5513XtKuXbu1mv923XXXJU888UTrAw44YPH48eObTJs2Lev899577yUnnHBCpyuuuGKOu/PSSy+1fvDBBz/bfPPNyxcsWFA2Z86c0latWlW88sorrfbZZ5/vU9M9/vjjrQ844IDFr7zySvMWLVqs3HDDDVdOnjy5cd++fZf17dt32dixY9efNGlSEyVc9YCZDQZuJ7oGV5rM5yIidUJVLcnn2GOP/W7MmDHNu3fvvq2Z+WWXXTarY8eO5R9++GGl0/Tt23dZWVmZd+3atcfAgQPnX3LJJXP32GOPpeuvv/7K448/fq3mRICzzz573hFHHNGpS5cuPbbbbrulXbt2Xda6deu1ErPdd9996cCBA7/daaedukfxzdttt92WAZx11lmz+/bt233zzTf/aZtttlkjcWrduvXKXr16dVuyZEnp0KFDPwe4/vrrNx4zZkzLkpIS79Kly7LDDjtsUVXWjeUqy0l8zOxT4BvC5SEeIFyT6yV3P7WuYujTp4+PGzeurhYnIgml62pVjZmNd/c+1Z3PhAkTZvTs2TNrwlHfzZgxY73+/ft3/fTTTyeVlq5dZygvL2f58uXWrFkznzx5cuMBAwZ0+fTTTyc1adKk2klN3759u954441f7rnnnkvzj72mCRMmbNSzZ89O2V5ThSu52gM3ExKuEcA7wImxRiQiDY6aD6Wu3X777RteeeWV7a+++uovsyVbEC4Lsccee3RdsWKFuTs333zzzJpItmqTEq7k+h74EVhGuBF1U3S2oojUETUfSlxOO+20b0877bRvc43TunXrikmTJk2tjeW/8847H9fGfJVwJdejhAvT3g78JRp2c3zhiEhDoaqWSM1TwpVQ7n5G6n8ze4DQ365K96kSEakKVbUSp6KiosJKSkoS3VQmQUVFhQGVXvpCCVdCmdkZQDnwMHAvsKmZneHuL8QbmYjUR6pqJdKkefPm9Wjbtu0iJV3JVlFRYfPmzWsFTKpsHCVcyXU6cAdwDNALWARcDyjhEpEao6pWcpWXl580Z86c++bMmbMduvdx0lUAk8rLy0+qbAQlXMnVjnBZiL0Il4V4D7gr1ohEpF5RVSvZevfuPRc4MO44pGYo4UquucAZwObAWcD6wOJYIxKRekFVLZG6p4Qrua4CrgOmAc8BtwCj4wxIRIqbLmAqEh8lXAnl7vcA96QN0kVPRWSdqflQJF5KuBLKzP6eZbC7uxIvESmYmg9FkkEJV3INyjLMUaVLRAqkqpZIcijhSq6d0/5vTbjavC58KiIFSU+2VNUSiZ8SroRy9/Hpz81sG+BC4E/xRCQixUBNiCLJpIQroczs+7SnpUATYFZM4YhIEVATokhyKeFKrgWEPlsAK4EZwKVxBSMiyaWqlkjyKeFKKHfvFHcMIpJ8qmqJFAclXAllZq2AW4FfR4NeBM5w90XxRSUiSaGqlkhxUcKVXLcBxwJfRc8HAQYcH1dAIhI/XS1epDgp4UquXwPXu/u5AGZ2HUq2RBo0NR+KFC8lXMXD848iIvWRmg9Fip8SruR6CTjbzAZGz9sDw2KMR0RioKqWSP2ghCu5TgdKWN1p/mHgjNiiEZE6paqWSP2ihCuh3P074HdxxyEidU9VLZH6RwlXQpnZboQLnXYiXGkewN196wKm3QC4D9iO0PfrBOBj4MlofjOAI9x9Yc1GLSLVoaqWSP2lhCu5Hgc2B34Cyqs47a3Ay+5+mJk1ApoB5wOvufu1ZnYucC5wTk0GLCLrRpd6EKn/lHAllwMXuvvVVZnIzFoCexKu24W7LweWm9lBQP9otIeAUSjhEomdmg9FGgYlXAljZjtF/z4M7GtmY4FVTX/u/l6eWWwFzAMeMLOewHhgCNDO3WdH85htZhvXePAiUjA1H4o0LEq4kmccq6+5ZcC/M14vJbcyYCfgj+4+1sxuJTQfFsTMBgODATp21MFfpDaoqiXS8CjhSp5hVO8ip7OAWe4+Nnr+DCHh+sbMNo2qW5sCc7NN7O5DgaEAffr00cVWRWqQqloiDZcSroRx90EAZrYnMMXd50fPmwBtCph+jpl9aWZd3f1jYB9gSvR3HHBt9Di8dt6BiGSjqpZIw6aEK7lGAkcBT0fPDwIeI3+TIsAfgUejMxQ/I9yDsQR4ysxOBL4ADq/xiEUkq/RkS1UtkYZJCVfCRJWt/oT+W4ebWffopT2BFYXMw90/APpkeWmfGghRRAqkJkQRSVHClTw/By4h9OM6LPpLeTWWiESkytSEKCLplHAlz1PA5OjxFuA/hORrIfBWfGGJSCFU1RKRbJRwJYy7TwWmmtmWwDx3Xxp3TCJSGFW1RKQySrgSxszeJlyW4YXMZMvM2gIHAL93913iiE9E1qaqlojko4QreeYQbjyNmX0BfE3oQL8Z0CEa5x/xhCYi6XQPRBEplBKuhHH3Q8xsa2AgsBuQOnJ/REjEHnf3T+OKT0QCNR+KSFUo4UqgKKG6Iu44RGRtaj6sp8Y9ABOfWf18k+3h19fGF4/UO0q4REQKpKpWPZOeZM2MTgLfYvf44pF6TQmXiEgeqmrVM6lEKz3J2mJ32P4w6HN8vLFJvaWES0QkB1W16onKqllKsqSOKOEqAmbWGWgH/MfdPe54RBoCVbXqCVWzJCGUcCWUmY0i3GT6VmAs4dIQtwNDYgxLpEFQVaseyJZoKcmSGCnhSq4dgMeAA4FJwHTgaJRwidSq9GRLVa0io2ZDSTAlXMnVBGgK9AGeBz4F9oszIJH6TE2IRaqyJEuJliSMEq7kmgjcTLhx9Y3ArsBXsUYkUg/pavFFSn2zpMgo4UquY4FTgU/cfaSZdQGujDkmkXpFfbWKjJoMpYgp4Uquc4G73P3d6PmbwCExxiNSb6j5sMiomiX1gBKu5BoE/AtIJVw7E273c3VcAYnUB6pqFQlVs6SeUcKVMGY2hHAmogO3m9l10Uttge/iikuk2KmqVSRUzZJ6SglX8jQjJFcALaPnDiwAro8rKJFipqpWwqmaJQ2AEq6EcfdrgGvMbCRwmbuPijkkkaKlqlbCqZolDYgSroRy95+b2W5m9lugNG34sBjDEikKutRDgqmaJQ2UEq6EMrNHCFeWXzWI0LSohEskBzUfJpSqWdLAKeFKrgOA8cCzQHnMsYgknpoPE0jVLJFVlHAl10jgbXe/Lu+YIg2cqloJo2qWyFqUcCXXhsCVZrY/sDAa5u5+UIwxiSSKqloJomqWSE5KuJJrt4xHCH24RARVtRJD1SyRgijhSq4t4w5AJIlU1UoAVbNEqkwJV0K5+0wz2wHYGxgBtAdmxBqUSMxU1YqZqlki60wJV0KZ2VHAw0AJ8CFwHrAE3cBaGiBVtWKkapZIjVDClVyXAa8Dv4iev0hIukQaFFW1YqJqlkiNUsKVXJsBf2d1wrUCaBpfOCJ1S1WtGKiaJVJrlHAl10Tgd9H/xwK/AibEF45I3dBteepYZUmWEi2RGqWEK7nOAl4g3NLnOGAB8OdYIxKpZWo+rENqMhSpU0q4Esrd3zazbYBdCEnXGHdfmGcykaKVnmyp+bCWqMlQJDZKuBLGzM4E/km4l2K6rmbm7n5zgfMpBcYBX7n7/mbWBngS6ES4vMQRSuAkCdRXqw6omiUSOyVcyXMjMCt6zORAQQkXMASYCrSMnp8LvObu15rZudHzc6oZq8g6U1+tOpAt0VKSJRILJVzJczzwTvS4Tsxsc2A/4CrgzGjwQUD/6P+HgFEo4ZIYKNGqZWo2FEkkJVwJ4+4PAZjZ74Bn3H1K9LwjsHuBs7kF+AvQIm1YO3efHS1jtpltXGNBixRIneJrkZoNRRJNCVdyXUJoEpwSPd+dcOX5x3JNZGb7A3PdfbyZ9a/qQs1sMDAYoGNHfRFKzVGn+FqgapZI0VDClTBmdhzhMhAGXGJm/xu9tA3wQwGz2A040Mz2BZoALc3sEeAbM9s0qm5tCszNNrG7DwWGAvTp08er925E1Cm+VqiaJVJ0lHAlTydCXysHekR/ABXA9fkmdvfziG4BFFW4/uzux5jZDYRE7trocXjNhi2yNjUh1jB1ghcpWkq4kud64A7gXeB84N+E5Ot7dy+vxnyvBZ4ysxOBL4DDqxuoSDapihagqlZNULOhSL1g7mo1Sioza0SoeDVJDXP3D+tq+X369PFx48bV1eKkHsisaAGqaq2rbNUsUKJVBMxsvLv3iTsOSRZVuBLKzA4ChgHNM14qjSEckbzUKb4GqJolUm8p4UquqwkXQO0OvEjoDP9yrBGJZKFO8TVAneBF6j0lXMm1FaHz+03AXYRk65BYIxLJoE7x1aBqlkiDooQruZYBi4EVwOlAM2D7OAMSSVFVax1VlmQp0RKp95RwJderQBvgCeB30bDH4wtHJFBVax2oybBoPD3taV767CW6tenGOX119zOpOUq4EsrdjwAwsxJComWES0SIxEJVrSpSk2FRSCVYKeO+CWdmd2vTLa6QpJ5SwpVQZrYecDKrbzj9OuEMxYq4YpKGSTebriJVsxKtsgSrT7s+qx733WpfDu+iSxVKzVLClVz3A8ekPT8E6Ee4SrxInVDzYYFUzUosJViSFEq4kusA4DngL0AJ4Qr0B8YakTQYaj4skKpZiZSeZCnBkqRQwpVcI4G33f0zADMbQ7jFj0itUlWrALqnYWJkVrBgzSRLCZYkhRKu5GoDXGNmqarWLsBbZjYCcHc/KL7QpD5SVSsPNRsmRq4KVup/JVmSNEq4kmvP6HGPtGH9o0dVuqRGqaqVg5oNY6UKltQXSriSa8u4A5D6T1WtHNRsGBtVsKQ+UsKVUO4+M+4YpP7SpR4qoWbDOqcKljQUSrhEGhg1H2ahZsM6pQqWNERKuEQaCDUfZlA1q87kuhaWkitpKJRwJYyZXQ48CfQG3lDTotQEVbXSqJpV63SxUZG1KeFKnguAacADwFGAEi5ZZ6pqRVTNqlVKsETyM3ddYSBJzGwu0BhoAcwDfkh72d1967qKpU+fPj5u3Li6WpzUMFW1yF7NAiVa1ZQvwQIadIJlZuPdvU/+MaUhUYUrea4GzickXC2BZvGGI8UoPdlqcFUtVbNqnCpYItWnCldCmdlI4DJ3HxVXDKpwFZ8G24RYWZIFSrTWgSpY1aMKl2SjCldCufvPzay/mV1HuLL8S+7+ZtxxSXI1yCZEdYCvEapgidQ+JVwJZWYnAfcAFg0628wGu/v9MYYlCdTgqlpqMqw2JVgidU9NigllZp8Ac4FLCEnXJcDG7t6lrmJQk2KyNairxavJsFrURFi31KQo2ajClVybADe4+6sAZrYlcFO8IUlSNJjmQzUZrhNVsESSRwlXck0BLjWzzaPnJwKTYoxHEqBBNB+qybDKlGCJJJ8SruQ6CxgBXBg9XxgNkwaq3le1VM0qmBIskeKjhCuh3P0tM9sG2CUa9La7L4gzJolHva5qqZpVECVYIsVPCVeCRQnWi3HHIfGot53iK0uylGitogRLpP5RwiWSQPWy+VBNhpVSgiVS/ynhEkmQetd8qCbDrJRgiTQ8SrgSyMxKgSeBYe4+Iu54pG7Um6qWmgzXogRLRJRwJZC7rzSzbkARfttKVdWbqpaaDFdRgiUimZRwJdck4HIz2wKYnRro7n+NLySpaUVf1VKTIaAES0Ty0619EsrMKrIMdncvrasYdGuf2lP0Va1s1SxoMImWbpUjuejWPpKNKlzJtU7fWmbWARhGuDVQBTDU3W81szaEfmGdgBnAEe6+sGZClaoo2qpWA65mqYIlItWlCleCmVkjoAfwubsvKnCaTYFN3f09M2sBjAcOBgYBC9z9WjM7F2jt7ufkmpcqXDWrKKtaDfim0elJlipYUhWqcEk2qnAllJn1AoYDmwG/MrO/AW+5++9zTefus4n6fLn7YjObCrQHDgL6R6M9BIwCciZcUjOK8gKmDawDfGYFC9ZMslTBEpHqUsKVXLcDSwEjNA0+ApxUlRmYWSegFzAWaBclY7j7bDPbuEajlayKqvmwgTUZ5qtgKckSkZqkhCu5egJXAldFz78GCk6SzKw58Cxwurt/b2aFTjcYGAzQsWNCE4MiUFTNhw2gmqUKlojETQlXcs0C9or+3wE4mtDZPS8zW4+QbD3q7s9Fg78xs02j6tamwNxs07r7UGAohD5c6x5+w1U0Va1siVY9TbJUwRKRuCnhSq7rgfui/1PX3hqUbyILpaz7gakZ1+waARwHXBs9Dq+xSAUokqpWPW02VAVLRJJOZykmmJntBexH6Mf1gru/UcA0uwOjgYmEvl8A5xP6cT1FuHr9F8Dh7r4g17x0lmJhiqJTfD28bla+ChboTEKJh85SlGxU4Uq2BYTkKPV/Xu7+FiFBy2afmghKVkt082E9q2bluhaWKlgiknRKuBLKzM4iNCtCdKaimZ3t7jfHGJZEEt18WE86wetioyJSn6hJMaHMbB4wB7gZKAFOBzZ29zq7nIOaFLNLZFWrHlSzdLscqS/UpCjZqMKVXDOBe9z977CqM/zJ8YYk6clWIqpaRVzNUgVLRBoSJVwJY2ZnRv9OAi42s/aEJsUTgJcqnVBqVaKaEIu0mqUES0QaMjUpJoyZVQBO9o7v7u6ldRWLmhSDxDQhFuGZhrofoTREalKUbFThSp5kfnM2MKmKFhBvVauIqlm6FpaISOWUcCWMuz8UdwwNXWZFK5aqVpH0zdLV3EVECqOEK6HMbADhqvBbAqlmRHf3VvFFVf/F2im+CKpZuhaWiMi6UcKVXA8Sblb9NbAy3lDqv1g7xSe4mqWO7iIiNUMJV3KVA6e7++1xB1LfxdIpPqHVLCVYIiK1QwlXcp0I3GNmGwHfR8NcV5qvOXVe1aosyYox0VKCJSJSN5RwJdcpQCfg4rRhTrjyvFRTnVa1EtRkqARLRCQeSriSax/gZeA5YEXMsdQbdVbVSkiToRIsEZFkUMKVXPcBjYEH3b087mCKXWaiVWtVrZirWUqwRESSSQlXcp0MNANOMbNl0TBdFmId1HrzYYzVLCVYIiLFQQlXcn0LzI87iGJWq82HMXWAV4IlIlKclHAllLt3ijuGYlZrVa06bjJUgiUiUj8o4UooM/tdlsHu7g/XeTBFpFaqWnXYZKgES0SkflLClVwPEi4DkUkJVyVqtKpVR02GSrBERBoGJVzJ9RdWJ1ytgd8Bb8UXTnLVaFWrFpsMM5MrUIIlItJQKOFKKHe/Mf25mU0ALoopnMSqkapWLTYZpidZmclV6n8lWCIi9Z8SroQysxFpT8uA3sB6MYWTODVS1aqFalauJkIlVyIiDZcSruTaP+P5j8C5cQSSJNW+gGkNV7PUB0tERAqhhCu5tkz7fyXwjbs36Fv8rHPzYQ12gFeCJSIi60IJV0K5+0wz241wA+tSADPD3YfFGlgM1rn5sIaaDHP1w1KCJSIihVDClVBm9ghwdPogwlmLDSbhWufmw2yJVoFJVr4zCZVgiYjIulDClVwHAOOBZ4EGd/PqKjcfVqNvls4kFBGR2qaEK7lGAm+7+3VxB1KXqtR8uI59s3QmoYiI1DUlXMm1IXClme0PLIyGubsfFGNMtargqlYV+2apo7uIiMRNCVdy7ZbxCNlv9VMvpCdbWataVWgyVIIlIiJJo4QrubbMP0rxy9mEWGCToRIsERFJOiVcCeXuM+OOobZV2oSYp8lwVYL18puAEiwREUk+c6+3rVRSTX369PFx48bV+HyzVrVKX6u0yfDpls1zVrAAJVgikhhmNt7d++QfUxoSVbikTmVWtc5sM4Z+U+5cI8l6eosdeal5M2ixMcx/k3GTVcESEZHipoRL6kR6Vevo0tc4vd0E2jVqApNDopWeZI375gtYuoA+LTYBlGCJiEjxU8LVgJjZr4BbCbcKus/dr63tZWYmWhe3fIdtl0/k6RXr85JtBp06w/ptGbd01qokSwmWiIjUN0q4GggzKwXuAH4JzALeNbMR7j6ltpb52NgvmDjiFs4oHcPYTSr4oMlCbgRo0plx9hPw0+pmwhabKMkSEZF6SwlXw9EXmO7unwGY2RPAQUCNJ1yX/XMy3355LV+VfEjLDku5BxjXtAnQhD7NNocWm9AHdXQXEZGGQwlXw9Ee+DLt+SygX20saOE3pzNy/TkA7FDegkYt26mCJSIiDZoSrobDsgxb65ogZjYYGAzQsWOOm0XnsGnLJvRZ2ph9N9uDwwfcvE7zEBERqU+UcDUcs4AOac83B77OHMndhwJDIVyHa10WdM4R/1yXyUREROqtkrgDkDrzLtDZzLY0s0bAUcCImGMSERFpEFThaiDcvdzMTgNeIVwW4u/uPjnmsERERBoEJVwNiLu/BLyUd0QRERGpUWpSFBEREallSrhEREREapkSLhEREZFapoRLREREpJYp4RIRERGpZea+Tte2lAbAzOYBM9dx8o2A+TUYTn2kdZSb1k9+Wke5xbV+tnD3tjEsVxJMCZfUCjMb5+594o4jybSOctP6yU/rKDetH0kSNSmKiIiI1DIlXCIiIiK1TAmX1JahcQdQBLSOctP6yU/rKDetH0kM9eESERERqWWqcImIiIjUMiVcInXAzErN7JG44xARkXiUxR2A1A9m9gfgUXf/LnreGjja3e+MNbCEcPeVZtbWzBq5+/K440kiM2sL/B7oRNqxyd1PiCumpDGzh9392HzDGjIz25W1t6FhsQUkElHCJTXl9+5+R+qJuy80s98DSrhWmwH8x8xGAD+kBrr7X2OLKFmGA6OBV4GVMceSVNumPzGzUqB3TLEkjpk9DGwNfMDqbcgBJVwSOyVcUlNKzMw8Ogsj+iJoFHNMSfN19FcCtIg5liRq5u7nxB1EEpnZecD5QFMz+z41GFiOzsRL1wfo4TobTBJIZylKjTCzGwhl/LsJvyhPAb5097PijEuKh5ldCYxx95fijiWpzOwadz8v7jiSysyeBv7k7rPjjkUkkxIuqRFmVgKcDOxD+OX9b+A+d1fTUCTqo/QXQrNQk9Rwd987tqASxMwWA+sDPwErCNuRu3vLWANLEDM7BHjd3RdFzzcA+rv783HGlRRmNhLYEXiHsB0B4O4HxhWTSIoSLqkxZtYU6OjuH8cdSxKZ2b+BJ4E/EyqAxwHz1IwmhTKzD9x9x4xh77t7r5hCShQz2yvbcHd/o65jEcmkPlxSI8zsQOAGQr+tLc1sR+By/bJcw4bufr+ZDYm+AN4wM30RRMxsz2zD3f3Nuo4lwbJdykfH8YgSK0ky7ahSUy4B+gKjANz9AzPrFGdACbQiepxtZvsROtBvHmM8SXN22v9NCNvTeEBNrquNM7O/AncQ+kr+kbCOBDCznwF/A7oTfvyVAj+oWVqSQAmX1JRyd19kZnHHkWRXmlkr4CzCl0JL4Ix4Q0oOdz8g/bmZdQCujymcpPojcBGhaTrVV/IPsUaULLcDRwFPE85Y/B3QOdaIRCLqwyU1wszuB14DzgUOBf4ErOfup8QamBQtC9n7h+6+fdyxJImZNSecTPBD3pEbGDMb5+59zOxDd98hGjbG3XeNOzYRVbikpvwRuIBwZtDjwCvAFbFGlBBmdluu1939T3UVS5KZ2d8IzWQQ+irtCEyILaCEMbNTCT9o1o+eLwGu090c1rDUzBoBH5jZ9cBsovUlEjdVuERqmZktByYBTxH6ba3R7uruD8URV9KY2XFpT8uBGe7+n7jiSRIzuxDYFTjN3T+Lhm0F3AqMdfcr44wvKcxsC2AusB6hub4VcKe7T481MBGUcEkNiL4ohwBdo0FTgdt0/7LAzDYEDgeOJCQSTwLPuvvCWAOTomFmHwM93f3HjOFNgQnu3iWeyESkUGpSlGoxs98BpwNnAu8Rqjc7ATeYmW4aC7j7t4Qr8N9tZu2Bo4HJZnaOuz8cb3TxM7OJrG5KzPQT8Clwjbs36ObFzGQrGrbMzCriiCdJtA1JMVDCJdV1KnCIu89IG/a6mR0KPIFuGruKme1ESLZ+CfwLnc6fsn+O18qA7YAHgYZ8cc9ZZraPu7+WPtDM9ib0U2rotA1J4inhkupqmZFsAeDuM8xM174BzOwywhfCVEISep67l8cbVXK4+8w8o3waJasN2Z+A4Wb2FiFRd2BnYDfgoDgDSwJtQ1IM1IdLqsXMxrt776q+1pBETT6fAcuiQamdLnWvwB1iCUyKipk1AQYS7sVpwGTg0WxNjSKSPEq4pFrMbCmQ7QwgA7Zy9wZ/SnZ05lSlCvh1LiIiRU4Jl1SLkgkREZH8lHCJSKzM7D3gOeBxd/807nik+JjZJoT7uVYAFxMuxHwood/kEHfXiQUSu2x3nhcRqUutgQ2AkWb2jpmdYWabxRyTFJcHgSnAl8BIQn/J/YDRhEuyiMROFS4RiZWZvefuO0X/70G4dMZvCNWJx919aJzxJYGZ/crdX47+bwX8lXCW4iTgDHf/Js744mZm77t7r+j/L9y9Y9prH7j7jrEFJxJRhUuklplZczO73Mwmm9kiM5tnZv81s0Fxx5Y07j7a3U8F2gPXAbvEHFJSXJ32/02Ea28dALwL3BNLRMmS/l2Wee0/fc9JImhDlGpRMlGQRwmXhfgf4DLgNuBY4OdmdnWuCRuIaZkD3H2lu7/s7sfHEVDC9XH3C919prvfDHSKO6AEGG5mzQHc/cLUQDPbhizbl0gc1KQo1WJmw4F/AK8CRwDrEy7ueSHwlbufH2N4iWBmE9y9Z9rzd919ZzMrAaa4e7cYw5MiYGazCM2IBvwB2Nqjg7eZfahruYkknypcUl2d3P1Bd5/l7n8FDnT3T4DjCf1wBH4ws90BzOwAYAGAu1cQvkAbPDPrZmb7pKoUacN/FVdMCXMv0AJoDjwEbASrzs77IL6wks/MVCWVRFCFS6rFzMYAf3H3t6Jk4jR3/5/otY/dvWu8EcbPzHYA7gO6EDo5n+Du08ysLXC0u98Wa4AxM7M/Eao2U4EdCafxD49eW9WhXmRdZHaiF4mLEi6plrRkoiswETjR3T9WMiGFMrOJwC7uvsTMOgHPAA+7+63pZ581dGbWjXDfxPaE20N9DYxw96mxBpYAZvZhZS8BXdy9cV3GI5KNEi6RGJnZ8e7+QNxxxMnMprh7j7TnzQlJ1xRgb53SD2Z2DuFyGU8As6LBmwNHAU+4+7VxxZYEZvYN4aSUhZkvAWPcXdd1k9gp4ZJq0y/vdafmDjCz14Ez3f2DtGFlwN+B37p7aVyxJYWZTQO2dfcVGcMbAZPdvXM8kSWDmd0PPODub2V57TF3HxhDWCJrUMIl1aJf3vmpuSM3M9scKHf3OVle283d/xNDWIliZh8B/5N5b9LoXqb/Vl9JkeRTwiXVol/e+am5Q6orOlvzduATwu1rADoC2xBOVHk5rthEpDBlcQcgRa8C2AyYmTF80+g1gReA5ulNZilmNqrOo5Gi4+4vm1kXoC+h6d4IFeV33X1lrMGJSEFU4ZJq0S9vERGR/JRwSbVFV0zXL28REZFKKOESERERqWW6tY+IiIhILVPCJSIiIlLLlHCJSOKY2Z/NzM1sUI5xmpnZpbnGERFJCiVcIlKsmgGXAINijkNEJC8lXCKSCFFVa76ZjQe2Txv+tJktNLMfzWyKmR0SvTQuetwrqoZdamaNzOxGM/vKzL6Lpm1b529GRCSDEi4RiZ2Z9QRuAOYA9wC/SHv5XeAvwHnR82Fm1gQ4P3o+lXB7qWeicc4C/gncAvwauKuWwxcRyUtXmheRJOgfPd7s7vebWQfgQqAU6EFIqBqljd8J+Hf0/1x3fwLAzB6Ihp2cNu6AWopZRKRgSrhEJIkselwPOA54jVCxOgXYD2gCZLuIoAHlwP5A6sK7quSLSOyUcIlIEoyKHs8ws1Lg+Oh5KvFqRqhq7ZY2zfeE+3VuY2a/Bd4iNCX2JiRprxKqY1uyuhomIhIL/fITkdi5+wTgbGAT4DTg/6KXlgNPEDrR/wZ4JW2aFYR+XxsAjwB7ANdEw/Yg3OPz18AbdfEeRERy0a19RERERGqZKlwiIiIitUwJl4iIiEgtU8IlIiIiUsuUcImIiIjUMiVcIiIiIrVMCZeIiIhILVPCJSIiIlLLlHCJiIiI1LL/B+/j8lJncnJvAAAAAElFTkSuQmCC", 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" ] @@ -300,12 +332,14 @@ } ], "source": [ + "\n", + "\n", "make_vaccine_graphs(df, latest_date=latest_date, grouping=\"priority_status\", savepath_figure_csvs=savepath_figure_csvs, savepath=savepath, suffix=suffix)" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -318,7 +352,7 @@ }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -330,29 +364,33 @@ } ], "source": [ - "make_vaccine_graphs(df, latest_date=latest_date, include_total=False, savepath=savepath, savepath_figure_csvs=savepath_figure_csvs, suffix=suffix)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Reports " + "\n", + "\n", + "make_vaccine_graphs(df, latest_date=latest_date, include_total=False, savepath=savepath, savepath_figure_csvs=savepath_figure_csvs, suffix=suffix)\n", + "\n", + "\n", + "# ### Reports " ] }, { "cell_type": "code", - "execution_count": 16, - "metadata": {}, + "execution_count": 18, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "from report_results import summarise_data_by_group" ] }, { "cell_type": "code", - "execution_count": 17, - "metadata": {}, + "execution_count": 19, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [ { "name": "stderr", @@ -368,52 +406,64 @@ } ], "source": [ + "\n", + "\n", "summarised_data_dict = summarise_data_by_group(df_dict_cum, latest_date=latest_date, groups=groups)" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ + "\n", + "\n", "summarised_data_dict_2nd_dose = summarise_data_by_group(df_dict_cum_second_dose, latest_date=latest_date, groups=groups)\n", "\n", - "summarised_data_dict_3rd_dose = summarise_data_by_group(df_dict_cum_third_dose, latest_date=latest_date, groups=groups)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Proportion of each eligible population vaccinated to date" + "summarised_data_dict_3rd_dose = summarise_data_by_group(df_dict_cum_third_dose, latest_date=latest_date, groups=groups)\n", + "\n", + "\n", + "# ### Proportion of each eligible population vaccinated to date" ] }, { "cell_type": "code", - "execution_count": 20, - "metadata": {}, + "execution_count": 21, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "from report_results import create_summary_stats, create_detailed_summary_uptake" ] }, { "cell_type": "code", - "execution_count": 21, - "metadata": {}, + "execution_count": 22, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "summ_stat_results, additional_stats = create_summary_stats(df, summarised_data_dict, formatted_latest_date, groups=groups, \n", " savepath=savepath, suffix=suffix)" ] }, { "cell_type": "code", - "execution_count": 22, - "metadata": {}, + "execution_count": 23, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "summ_stat_results_2nd_dose, _ = create_summary_stats(df, summarised_data_dict_2nd_dose, formatted_latest_date, \n", " groups=groups, savepath=savepath, \n", " vaccine_type=\"second_dose\", suffix=suffix)\n", @@ -425,8 +475,10 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": {}, + "execution_count": 24, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [ { "data": { @@ -449,148 +501,148 @@ " \n", " \n", " \n", - " first dose as at 15 Dec 2021\n", - " second dose as at 15 Dec 2021\n", - " third dose as at 15 Dec 2021\n", + " first dose as at 02 Feb 2022\n", + " second dose as at 02 Feb 2022\n", + " third dose as at 02 Feb 2022\n", " \n", " \n", " \n", " \n", " Total vaccinated in TPP\n", - " 45,003\n", - " 39,998\n", - " 4,998\n", + " 89,999\n", + " 80,003\n", + " 10,003\n", " \n", " \n", " 80+\n", - " 90.5% (1,939 of 2,142)\n", - " 80.7% (1,729 of 2,142)\n", - " 10.5% (224 of 2,142)\n", + " 89.9% (3,794 of 4,221)\n", + " 79.9% (3,374 of 4,221)\n", + " 10.1% (427 of 4,221)\n", " \n", " \n", " 70-79\n", - " 90.1% (3,136 of 3,479)\n", - " 80.3% (2,793 of 3,479)\n", - " 10.1% (350 of 3,479)\n", + " 90.2% (6,188 of 6,860)\n", + " 79.2% (5,432 of 6,860)\n", + " 10.1% (693 of 6,860)\n", " \n", " \n", " care home\n", - " 89.9% (1,253 of 1,393)\n", - " 79.9% (1,113 of 1,393)\n", - " 8.5% (119 of 1,393)\n", + " 89.8% (2,534 of 2,821)\n", + " 79.2% (2,233 of 2,821)\n", + " 9.4% (266 of 2,821)\n", " \n", " \n", " shielding (aged 16-69)\n", - " 88.3% (371 of 420)\n", - " 81.7% (343 of 420)\n", - " 11.7% (49 of 420)\n", + " 89.5% (777 of 868)\n", + " 83.1% (721 of 868)\n", + " 10.5% (91 of 868)\n", " \n", " \n", " 65-69\n", - " 89.7% (1,946 of 2,170)\n", - " 80.3% (1,743 of 2,170)\n", - " 10.6% (231 of 2,170)\n", + " 90.0% (3,976 of 4,417)\n", + " 80.3% (3,549 of 4,417)\n", + " 10.3% (455 of 4,417)\n", " \n", " \n", " LD (aged 16-64)\n", - " 90.4% (728 of 805)\n", - " 79.1% (637 of 805)\n", - " 10.4% (84 of 805)\n", + " 91.3% (1,463 of 1,603)\n", + " 80.8% (1,295 of 1,603)\n", + " 9.2% (147 of 1,603)\n", " \n", " \n", " 60-64\n", - " 89.8% (2,401 of 2,674)\n", - " 79.6% (2,128 of 2,674)\n", - " 10.5% (280 of 2,674)\n", + " 90.4% (4,928 of 5,453)\n", + " 79.6% (4,340 of 5,453)\n", + " 10.1% (553 of 5,453)\n", " \n", " \n", " 55-59\n", - " 89.9% (2,863 of 3,185)\n", - " 80.2% (2,555 of 3,185)\n", - " 10.1% (322 of 3,185)\n", + " 90.3% (5,621 of 6,223)\n", + " 80.2% (4,991 of 6,223)\n", + " 9.6% (595 of 6,223)\n", " \n", " \n", " 50-54\n", - " 89.1% (3,080 of 3,458)\n", - " 78.9% (2,730 of 3,458)\n", - " 9.7% (336 of 3,458)\n", + " 89.4% (6,013 of 6,727)\n", + " 79.3% (5,334 of 6,727)\n", + " 10.0% (672 of 6,727)\n", " \n", " \n", " 40-49\n", - " 90.1% (5,530 of 6,139)\n", - " 80.7% (4,956 of 6,139)\n", - " 9.9% (609 of 6,139)\n", + " 89.9% (11,018 of 12,257)\n", + " 80.5% (9,863 of 12,257)\n", + " 9.9% (1,211 of 12,257)\n", " \n", " \n", " 30-39\n", - " 89.7% (5,719 of 6,377)\n", - " 79.7% (5,082 of 6,377)\n", - " 9.3% (595 of 6,377)\n", + " 90.3% (11,704 of 12,957)\n", + " 80.4% (10,416 of 12,957)\n", + " 9.6% (1,239 of 12,957)\n", " \n", " \n", " 18-29\n", - " 90.3% (6,699 of 7,420)\n", - " 79.4% (5,894 of 7,420)\n", - " 9.8% (728 of 7,420)\n", + " 89.8% (13,440 of 14,966)\n", + " 80.3% (12,019 of 14,966)\n", + " 10.2% (1,526 of 14,966)\n", " \n", " \n", " 16-17\n", - " 90.3% (9,345 of 10,346)\n", - " 80.2% (8,302 of 10,346)\n", - " 10.4% (1,078 of 10,346)\n", + " 89.9% (18,550 of 20,636)\n", + " 79.6% (16,436 of 20,636)\n", + " 10.3% (2,135 of 20,636)\n", " \n", " \n", "\n", "
" ], "text/plain": [ - " first dose as at 15 Dec 2021 \\\n", - "Total vaccinated in TPP 45,003 \n", - "80+ 90.5% (1,939 of 2,142) \n", - "70-79 90.1% (3,136 of 3,479) \n", - "care home 89.9% (1,253 of 1,393) \n", - "shielding (aged 16-69) 88.3% (371 of 420) \n", - "65-69 89.7% (1,946 of 2,170) \n", - "LD (aged 16-64) 90.4% (728 of 805) \n", - "60-64 89.8% (2,401 of 2,674) \n", - "55-59 89.9% (2,863 of 3,185) \n", - "50-54 89.1% (3,080 of 3,458) \n", - "40-49 90.1% (5,530 of 6,139) \n", - "30-39 89.7% (5,719 of 6,377) \n", - "18-29 90.3% (6,699 of 7,420) \n", - "16-17 90.3% (9,345 of 10,346) \n", - "\n", - " second dose as at 15 Dec 2021 \\\n", - "Total vaccinated in TPP 39,998 \n", - "80+ 80.7% (1,729 of 2,142) \n", - "70-79 80.3% (2,793 of 3,479) \n", - "care home 79.9% (1,113 of 1,393) \n", - "shielding (aged 16-69) 81.7% (343 of 420) \n", - "65-69 80.3% (1,743 of 2,170) \n", - "LD (aged 16-64) 79.1% (637 of 805) \n", - "60-64 79.6% (2,128 of 2,674) \n", - "55-59 80.2% (2,555 of 3,185) \n", - "50-54 78.9% (2,730 of 3,458) \n", - "40-49 80.7% (4,956 of 6,139) \n", - "30-39 79.7% (5,082 of 6,377) \n", - "18-29 79.4% (5,894 of 7,420) \n", - "16-17 80.2% (8,302 of 10,346) \n", - "\n", - " third dose as at 15 Dec 2021 \n", - "Total vaccinated in TPP 4,998 \n", - "80+ 10.5% (224 of 2,142) \n", - "70-79 10.1% (350 of 3,479) \n", - "care home 8.5% (119 of 1,393) \n", - "shielding (aged 16-69) 11.7% (49 of 420) \n", - "65-69 10.6% (231 of 2,170) \n", - "LD (aged 16-64) 10.4% (84 of 805) \n", - "60-64 10.5% (280 of 2,674) \n", - "55-59 10.1% (322 of 3,185) \n", - "50-54 9.7% (336 of 3,458) \n", - "40-49 9.9% (609 of 6,139) \n", - "30-39 9.3% (595 of 6,377) \n", - "18-29 9.8% (728 of 7,420) \n", - "16-17 10.4% (1,078 of 10,346) " + " first dose as at 02 Feb 2022 \\\n", + "Total vaccinated in TPP 89,999 \n", + "80+ 89.9% (3,794 of 4,221) \n", + "70-79 90.2% (6,188 of 6,860) \n", + "care home 89.8% (2,534 of 2,821) \n", + "shielding (aged 16-69) 89.5% (777 of 868) \n", + "65-69 90.0% (3,976 of 4,417) \n", + "LD (aged 16-64) 91.3% (1,463 of 1,603) \n", + "60-64 90.4% (4,928 of 5,453) \n", + "55-59 90.3% (5,621 of 6,223) \n", + "50-54 89.4% (6,013 of 6,727) \n", + "40-49 89.9% (11,018 of 12,257) \n", + "30-39 90.3% (11,704 of 12,957) \n", + "18-29 89.8% (13,440 of 14,966) \n", + "16-17 89.9% (18,550 of 20,636) \n", + "\n", + " second dose as at 02 Feb 2022 \\\n", + "Total vaccinated in TPP 80,003 \n", + "80+ 79.9% (3,374 of 4,221) \n", + "70-79 79.2% (5,432 of 6,860) \n", + "care home 79.2% (2,233 of 2,821) \n", + "shielding (aged 16-69) 83.1% (721 of 868) \n", + "65-69 80.3% (3,549 of 4,417) \n", + "LD (aged 16-64) 80.8% (1,295 of 1,603) \n", + "60-64 79.6% (4,340 of 5,453) \n", + "55-59 80.2% (4,991 of 6,223) \n", + "50-54 79.3% (5,334 of 6,727) \n", + "40-49 80.5% (9,863 of 12,257) \n", + "30-39 80.4% (10,416 of 12,957) \n", + "18-29 80.3% (12,019 of 14,966) \n", + "16-17 79.6% (16,436 of 20,636) \n", + "\n", + " third dose as at 02 Feb 2022 \n", + "Total vaccinated in TPP 10,003 \n", + "80+ 10.1% (427 of 4,221) \n", + "70-79 10.1% (693 of 6,860) \n", + "care home 9.4% (266 of 2,821) \n", + "shielding (aged 16-69) 10.5% (91 of 868) \n", + "65-69 10.3% (455 of 4,417) \n", + "LD (aged 16-64) 9.2% (147 of 1,603) \n", + "60-64 10.1% (553 of 5,453) \n", + "55-59 9.6% (595 of 6,223) \n", + "50-54 10.0% (672 of 6,727) \n", + "40-49 9.9% (1,211 of 12,257) \n", + "30-39 9.6% (1,239 of 12,957) \n", + "18-29 10.2% (1,526 of 14,966) \n", + "16-17 10.3% (2,135 of 20,636) " ] }, "metadata": {}, @@ -611,6 +663,8 @@ } ], "source": [ + "\n", + "\n", "# display the results of the summary stats on first and second doses\n", "display(pd.DataFrame(summ_stat_results).join(pd.DataFrame(summ_stat_results_2nd_dose)).join(pd.DataFrame(summ_stat_results_3rd_dose))) \n", "display(Markdown(f\"*\\n figures rounded to nearest 7\"))" @@ -618,13 +672,13 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "Oxford-AZ vaccines (% of all first doses): **0.1%** (42)" + "Oxford-AZ vaccines (% of all first doses): **0.1%** (77)" ], "text/plain": [ "" @@ -636,7 +690,7 @@ { "data": { "text/markdown": [ - "Pfizer vaccines (% of all first doses): **0.2%** (84)" + "Pfizer vaccines (% of all first doses): **0.2%** (140)" ], "text/plain": [ "" @@ -648,7 +702,7 @@ { "data": { "text/markdown": [ - "Moderna vaccines (% of all first doses): **0.1%** (28)" + "Moderna vaccines (% of all first doses): **0.1%** (49)" ], "text/plain": [ "" @@ -660,7 +714,7 @@ { "data": { "text/markdown": [ - "Second doses (% of all vaccinated): **88.9%** (39,998)" + "Second doses (% of all vaccinated): **88.9%** (80,003)" ], "text/plain": [ "" @@ -672,7 +726,7 @@ { "data": { "text/markdown": [ - "Second doses (% of Ox-AZ first doses): **6200.0%** (2,604)" + "Second doses (% of Ox-AZ first doses): **6190.9%** (4,767)" ], "text/plain": [ "" @@ -684,7 +738,7 @@ { "data": { "text/markdown": [ - "Second doses (% of Pfizer first doses): **1500.0%** (1,260)" + "Second doses (% of Pfizer first doses): **1765.0%** (2,471)" ], "text/plain": [ "" @@ -696,7 +750,7 @@ { "data": { "text/markdown": [ - "Second doses (% of Moderna first doses): **10875.0%** (3,045)" + "Second doses (% of Moderna first doses): **12257.1%** (6,006)" ], "text/plain": [ "" @@ -756,24 +810,22 @@ } ], "source": [ + "\n", + "\n", "# other information on vaccines\n", "\n", "for x in additional_stats.keys():\n", " display(Markdown(f\"{x}: {additional_stats[x]}\"))\n", " \n", - "display(Markdown(f\"*\\n figures rounded to nearest 7\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Detailed summary of coverage among population groups as at latest date" + "display(Markdown(f\"*\\n figures rounded to nearest 7\"))\n", + "\n", + "\n", + "# # Detailed summary of coverage among population groups as at latest date" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -791,7 +843,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **80+** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **80+** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -857,579 +909,579 @@ " \n", " overall\n", " overall\n", - " 1939\n", - " 90.5\n", - " 2142\n", - " 88.9\n", - " 1.6\n", - " reached\n", + " 3794\n", + " 89.9\n", + " 4221\n", + " 88.7\n", + " 1.2\n", + " 02-Feb\n", " \n", " \n", " sex\n", " F\n", - " 1029\n", - " 91.3\n", - " 1127\n", - " 90.1\n", - " 1.2\n", + " 1960\n", + " 90.0\n", + " 2177\n", + " 89.1\n", + " 0.9\n", " reached\n", " \n", " \n", " M\n", - " 910\n", + " 1834\n", " 89.7\n", - " 1015\n", - " 87.6\n", - " 2.1\n", - " 16-Dec\n", + " 2044\n", + " 88.4\n", + " 1.3\n", + " 03-Feb\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", + " 56\n", + " 80.0\n", + " 70\n", + " 80.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 0-15\n", - " 105\n", - " 93.8\n", - " 112\n", - " 87.5\n", - " 6.3\n", - " reached\n", + " 231\n", + " 89.2\n", + " 259\n", + " 86.5\n", + " 2.7\n", + " 04-Feb\n", " \n", " \n", " 16-17\n", - " 126\n", - " 90.0\n", - " 140\n", - " 85.0\n", - " 5.0\n", - " reached\n", + " 217\n", + " 88.6\n", + " 245\n", + " 88.6\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 18-29\n", - " 119\n", + " 245\n", + " 92.1\n", + " 266\n", " 89.5\n", - " 133\n", - " 84.2\n", - " 5.3\n", - " 15-Dec\n", + " 2.6\n", + " reached\n", " \n", " \n", " 30-34\n", - " 126\n", - " 90.0\n", - " 140\n", - " 90.0\n", - " 0.0\n", - " unknown\n", + " 245\n", + " 89.7\n", + " 273\n", + " 87.2\n", + " 2.5\n", + " 02-Feb\n", " \n", " \n", " 35-39\n", - " 133\n", - " 90.5\n", - " 147\n", - " 85.7\n", - " 4.8\n", - " reached\n", + " 238\n", + " 89.5\n", + " 266\n", + " 89.5\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 40-44\n", - " 133\n", - " 90.5\n", - " 147\n", - " 90.5\n", + " 252\n", + " 92.3\n", + " 273\n", + " 92.3\n", " 0.0\n", " reached\n", " \n", " \n", " 45-49\n", - " 126\n", - " 94.7\n", - " 133\n", - " 94.7\n", - " 0.0\n", + " 259\n", + " 92.5\n", + " 280\n", + " 90.0\n", + " 2.5\n", " reached\n", " \n", " \n", " 50-54\n", - " 133\n", - " 86.4\n", - " 154\n", - " 86.4\n", + " 238\n", + " 91.9\n", + " 259\n", + " 91.9\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " 55-59\n", - " 140\n", - " 90.9\n", - " 154\n", - " 90.9\n", - " 0.0\n", + " 280\n", + " 93.0\n", + " 301\n", + " 90.7\n", + " 2.3\n", " reached\n", " \n", " \n", " 60-64\n", - " 119\n", - " 94.4\n", - " 126\n", - " 94.4\n", - " 0.0\n", - " reached\n", + " 238\n", + " 89.5\n", + " 266\n", + " 86.8\n", + " 2.7\n", + " 03-Feb\n", " \n", " \n", " 65-69\n", - " 126\n", - " 90.0\n", - " 140\n", - " 90.0\n", + " 245\n", + " 87.5\n", + " 280\n", + " 87.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-74\n", - " 126\n", - " 90.0\n", - " 140\n", - " 90.0\n", + " 266\n", + " 90.5\n", + " 294\n", + " 90.5\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " 75-79\n", - " 105\n", - " 78.9\n", - " 133\n", - " 78.9\n", - " 0.0\n", - " unknown\n", + " 252\n", + " 90.0\n", + " 280\n", + " 87.5\n", + " 2.5\n", + " reached\n", " \n", " \n", " 80-84\n", - " 140\n", - " 100.0\n", - " 140\n", - " 95.0\n", - " 5.0\n", + " 252\n", + " 92.3\n", + " 273\n", + " 89.7\n", + " 2.6\n", " reached\n", " \n", " \n", " 85-89\n", - " 140\n", - " 90.9\n", - " 154\n", - " 90.9\n", + " 252\n", + " 85.7\n", + " 294\n", + " 85.7\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " 90+\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 28\n", + " 80.0\n", + " 35\n", + " 80.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 322\n", - " 90.2\n", - " 357\n", - " 88.2\n", - " 2.0\n", - " reached\n", + " 644\n", + " 87.6\n", + " 735\n", + " 85.7\n", + " 1.9\n", + " 10-Feb\n", " \n", " \n", " Mixed\n", - " 315\n", + " 630\n", " 90.0\n", - " 350\n", - " 88.0\n", - " 2.0\n", + " 700\n", + " 89.0\n", + " 1.0\n", " reached\n", " \n", " \n", " Other\n", - " 308\n", - " 91.7\n", - " 336\n", - " 89.6\n", - " 2.1\n", + " 658\n", + " 90.4\n", + " 728\n", + " 89.4\n", + " 1.0\n", " reached\n", " \n", " \n", " South Asian\n", - " 329\n", - " 90.4\n", - " 364\n", - " 88.5\n", - " 1.9\n", - " reached\n", + " 672\n", + " 89.7\n", + " 749\n", + " 87.9\n", + " 1.8\n", + " 03-Feb\n", " \n", " \n", " Unknown\n", - " 308\n", - " 89.8\n", - " 343\n", - " 89.8\n", - " 0.0\n", - " unknown\n", + " 553\n", + " 90.8\n", + " 609\n", + " 89.7\n", + " 1.1\n", + " reached\n", " \n", " \n", " White\n", - " 350\n", - " 89.3\n", - " 392\n", - " 87.5\n", - " 1.8\n", - " 17-Dec\n", + " 644\n", + " 90.2\n", + " 714\n", + " 88.2\n", + " 2.0\n", + " reached\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 98\n", - " 93.3\n", - " 105\n", - " 86.7\n", - " 6.6\n", + " 203\n", + " 93.5\n", + " 217\n", + " 90.3\n", + " 3.2\n", " reached\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 105\n", - " 88.2\n", - " 119\n", - " 88.2\n", + " 175\n", + " 83.3\n", + " 210\n", + " 83.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 91\n", - " 92.9\n", - " 98\n", - " 92.9\n", - " 0.0\n", + " 196\n", + " 90.3\n", + " 217\n", + " 87.1\n", + " 3.2\n", " reached\n", " \n", " \n", " Chinese\n", - " 91\n", - " 86.7\n", - " 105\n", - " 86.7\n", + " 189\n", + " 87.1\n", + " 217\n", + " 87.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 105\n", - " 93.8\n", - " 112\n", - " 93.8\n", + " 210\n", + " 88.2\n", + " 238\n", + " 88.2\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " Other Asian\n", - " 105\n", - " 93.8\n", - " 112\n", - " 87.5\n", - " 6.3\n", + " 196\n", + " 93.3\n", + " 210\n", + " 90.0\n", + " 3.3\n", " reached\n", " \n", " \n", " British or Mixed British\n", - " 119\n", - " 89.5\n", - " 133\n", - " 84.2\n", - " 5.3\n", - " 15-Dec\n", + " 196\n", + " 90.3\n", + " 217\n", + " 90.3\n", + " 0.0\n", + " reached\n", " \n", " \n", " Indian or British Indian\n", - " 98\n", - " 93.3\n", - " 105\n", - " 93.3\n", - " 0.0\n", - " reached\n", + " 196\n", + " 87.5\n", + " 224\n", + " 84.4\n", + " 3.1\n", + " 07-Feb\n", " \n", " \n", " Irish\n", - " 105\n", - " 88.2\n", - " 119\n", - " 88.2\n", + " 210\n", + " 90.9\n", + " 231\n", + " 90.9\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " Other Black\n", - " 77\n", - " 91.7\n", - " 84\n", - " 83.3\n", - " 8.4\n", + " 196\n", + " 90.3\n", + " 217\n", + " 87.1\n", + " 3.2\n", " reached\n", " \n", " \n", " Other White\n", - " 112\n", - " 94.1\n", - " 119\n", + " 210\n", " 88.2\n", - " 5.9\n", - " reached\n", + " 238\n", + " 88.2\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other mixed\n", - " 91\n", - " 86.7\n", - " 105\n", - " 86.7\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 93.1\n", + " 203\n", + " 89.7\n", + " 3.4\n", + " reached\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 98\n", - " 87.5\n", - " 112\n", - " 87.5\n", + " 203\n", + " 90.6\n", + " 224\n", + " 90.6\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " Unknown\n", - " 315\n", - " 91.8\n", - " 343\n", - " 91.8\n", - " 0.0\n", - " reached\n", + " 602\n", + " 89.6\n", + " 672\n", + " 88.5\n", + " 1.1\n", + " 04-Feb\n", " \n", " \n", " White + Asian\n", - " 105\n", - " 88.2\n", - " 119\n", - " 88.2\n", + " 196\n", + " 87.5\n", + " 224\n", + " 87.5\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black African\n", - " 98\n", + " 196\n", " 93.3\n", - " 105\n", + " 210\n", " 93.3\n", " 0.0\n", " reached\n", " \n", " \n", " White + Black Caribbean\n", - " 126\n", - " 90.0\n", - " 140\n", - " 85.0\n", - " 5.0\n", - " reached\n", + " 224\n", + " 88.9\n", + " 252\n", + " 88.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 378\n", - " 90.0\n", - " 420\n", - " 88.3\n", - " 1.7\n", - " reached\n", + " 721\n", + " 89.6\n", + " 805\n", + " 87.8\n", + " 1.8\n", + " 03-Feb\n", " \n", " \n", " 2\n", - " 371\n", - " 91.4\n", - " 406\n", - " 89.7\n", - " 1.7\n", + " 735\n", + " 91.3\n", + " 805\n", + " 90.4\n", + " 0.9\n", " reached\n", " \n", " \n", " 3\n", - " 350\n", - " 89.3\n", - " 392\n", - " 87.5\n", - " 1.8\n", - " 17-Dec\n", + " 693\n", + " 89.2\n", + " 777\n", + " 88.3\n", + " 0.9\n", + " 08-Feb\n", " \n", " \n", " 4\n", - " 385\n", - " 90.2\n", - " 427\n", - " 88.5\n", + " 735\n", + " 89.7\n", + " 819\n", + " 88.0\n", " 1.7\n", - " reached\n", + " 03-Feb\n", " \n", " \n", " 5 Least deprived\n", - " 350\n", - " 89.3\n", - " 392\n", - " 89.3\n", - " 0.0\n", - " unknown\n", + " 728\n", + " 89.7\n", + " 812\n", + " 87.9\n", + " 1.8\n", + " 03-Feb\n", " \n", " \n", " Unknown\n", - " 98\n", - " 93.3\n", - " 105\n", - " 93.3\n", + " 189\n", + " 90.0\n", + " 210\n", + " 90.0\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 546\n", - " 91.8\n", - " 595\n", - " 89.4\n", - " 2.4\n", + " 1169\n", + " 90.3\n", + " 1295\n", + " 88.6\n", + " 1.7\n", " reached\n", " \n", " \n", " under 30\n", - " 1393\n", + " 2632\n", " 90.0\n", - " 1547\n", - " 88.7\n", - " 1.3\n", + " 2926\n", + " 88.5\n", + " 1.5\n", " reached\n", " \n", " \n", " housebound\n", " no\n", - " 1911\n", - " 90.4\n", - " 2114\n", - " 88.7\n", - " 1.7\n", - " reached\n", + " 3759\n", + " 89.9\n", + " 4179\n", + " 88.8\n", + " 1.1\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 28\n", - " 100.0\n", - " 28\n", - " 100.0\n", + " 35\n", + " 83.3\n", + " 42\n", + " 83.3\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1925\n", - " 90.8\n", - " 2121\n", - " 88.8\n", - " 2.0\n", - " reached\n", + " 3759\n", + " 89.8\n", + " 4186\n", + " 88.6\n", + " 1.2\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 100.0\n", + " 35\n", + " 100.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " current_copd\n", " no\n", - " 1918\n", - " 90.7\n", - " 2114\n", - " 89.1\n", - " 1.6\n", - " reached\n", + " 3759\n", + " 89.9\n", + " 4179\n", + " 88.6\n", + " 1.3\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 100.0\n", - " 21\n", - " 100.0\n", + " 42\n", + " 85.7\n", + " 49\n", + " 85.7\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1918\n", - " 90.7\n", - " 2114\n", - " 88.7\n", - " 2.0\n", - " reached\n", + " 3752\n", + " 89.9\n", + " 4172\n", + " 88.8\n", + " 1.1\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", + " 42\n", + " 85.7\n", + " 49\n", + " 85.7\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 1918\n", - " 90.4\n", - " 2121\n", + " 3759\n", + " 89.9\n", + " 4179\n", " 88.8\n", - " 1.6\n", - " reached\n", + " 1.1\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 100.0\n", - " 21\n", - " 100.0\n", + " 35\n", + " 83.3\n", + " 42\n", + " 83.3\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1918\n", - " 90.4\n", - " 2121\n", - " 88.8\n", - " 1.6\n", - " reached\n", + " 3752\n", + " 89.8\n", + " 4179\n", + " 88.6\n", + " 1.2\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 21\n", + " 42\n", " 100.0\n", - " 21\n", + " 42\n", " 100.0\n", " 0.0\n", " reached\n", @@ -1437,135 +1489,135 @@ " \n", " LD\n", " no\n", - " 1904\n", - " 90.7\n", - " 2100\n", - " 89.0\n", - " 1.7\n", - " reached\n", + " 3703\n", + " 89.7\n", + " 4130\n", + " 88.5\n", + " 1.2\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 35\n", - " 83.3\n", - " 42\n", - " 83.3\n", + " 91\n", + " 92.9\n", + " 98\n", + " 92.9\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " ssri\n", " no\n", - " 1925\n", - " 90.5\n", - " 2128\n", - " 88.8\n", - " 1.7\n", - " reached\n", + " 3752\n", + " 89.8\n", + " 4179\n", + " 88.6\n", + " 1.2\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 100.0\n", - " 14\n", - " 100.0\n", + " 42\n", + " 85.7\n", + " 49\n", + " 85.7\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 1925\n", - " 90.8\n", - " 2121\n", - " 89.1\n", - " 1.7\n", - " reached\n", + " 3759\n", + " 89.8\n", + " 4186\n", + " 88.6\n", + " 1.2\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 83.3\n", + " 42\n", + " 83.3\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1918\n", - " 90.4\n", - " 2121\n", - " 88.8\n", - " 1.6\n", - " reached\n", + " 3766\n", + " 89.8\n", + " 4193\n", + " 88.5\n", + " 1.3\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 100.0\n", - " 21\n", + " 35\n", " 100.0\n", - " 0.0\n", + " 35\n", + " 80.0\n", + " 20.0\n", " reached\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1925\n", - " 90.8\n", - " 2121\n", - " 88.8\n", - " 2.0\n", - " reached\n", + " 3766\n", + " 89.8\n", + " 4193\n", + " 88.6\n", + " 1.2\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 28\n", + " 80.0\n", + " 35\n", + " 80.0\n", " 0.0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1918\n", - " 90.4\n", - " 2121\n", + " 3759\n", + " 89.9\n", + " 4179\n", " 88.8\n", - " 1.6\n", - " reached\n", + " 1.1\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 100.0\n", - " 21\n", - " 100.0\n", + " 35\n", + " 83.3\n", + " 42\n", + " 83.3\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1554\n", - " 90.2\n", - " 1722\n", - " 88.2\n", - " 2.0\n", - " reached\n", + " 3052\n", + " 89.9\n", + " 3395\n", + " 88.9\n", + " 1.0\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 385\n", - " 91.7\n", - " 420\n", - " 90.0\n", + " 742\n", + " 89.8\n", + " 826\n", + " 88.1\n", " 1.7\n", - " reached\n", + " 02-Feb\n", " \n", " \n", "\n", @@ -1574,403 +1626,403 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1939 \n", - "sex F 1029 \n", - " M 910 \n", - "ageband_5yr 0 21 \n", - " 0-15 105 \n", - " 16-17 126 \n", - " 18-29 119 \n", - " 30-34 126 \n", - " 35-39 133 \n", - " 40-44 133 \n", - " 45-49 126 \n", - " 50-54 133 \n", - " 55-59 140 \n", - " 60-64 119 \n", - " 65-69 126 \n", - " 70-74 126 \n", - " 75-79 105 \n", - " 80-84 140 \n", - " 85-89 140 \n", - " 90+ 14 \n", - "ethnicity_6_groups Black 322 \n", - " Mixed 315 \n", - " Other 308 \n", - " South Asian 329 \n", - " Unknown 308 \n", - " White 350 \n", - "ethnicity_16_groups African 98 \n", - " Bangladeshi or British Bangladeshi 105 \n", - " Caribbean 91 \n", - " Chinese 91 \n", - " Other 105 \n", - " Other Asian 105 \n", - " British or Mixed British 119 \n", - " Indian or British Indian 98 \n", - " Irish 105 \n", - " Other Black 77 \n", - " Other White 112 \n", - " Other mixed 91 \n", - " Pakistani or British Pakistani 98 \n", - " Unknown 315 \n", - " White + Asian 105 \n", - " White + Black African 98 \n", - " White + Black Caribbean 126 \n", - "imd_categories 1 Most deprived 378 \n", - " 2 371 \n", - " 3 350 \n", - " 4 385 \n", - " 5 Least deprived 350 \n", - " Unknown 98 \n", - "bmi 30+ 546 \n", - " under 30 1393 \n", - "housebound no 1911 \n", + "overall overall 3794 \n", + "sex F 1960 \n", + " M 1834 \n", + "ageband_5yr 0 56 \n", + " 0-15 231 \n", + " 16-17 217 \n", + " 18-29 245 \n", + " 30-34 245 \n", + " 35-39 238 \n", + " 40-44 252 \n", + " 45-49 259 \n", + " 50-54 238 \n", + " 55-59 280 \n", + " 60-64 238 \n", + " 65-69 245 \n", + " 70-74 266 \n", + " 75-79 252 \n", + " 80-84 252 \n", + " 85-89 252 \n", + " 90+ 28 \n", + "ethnicity_6_groups Black 644 \n", + " Mixed 630 \n", + " Other 658 \n", + " South Asian 672 \n", + " Unknown 553 \n", + " White 644 \n", + "ethnicity_16_groups African 203 \n", + " Bangladeshi or British Bangladeshi 175 \n", + " Caribbean 196 \n", + " Chinese 189 \n", + " Other 210 \n", + " Other Asian 196 \n", + " British or Mixed British 196 \n", + " Indian or British Indian 196 \n", + " Irish 210 \n", + " Other Black 196 \n", + " Other White 210 \n", + " Other mixed 189 \n", + " Pakistani or British Pakistani 203 \n", + " Unknown 602 \n", + " White + Asian 196 \n", + " White + Black African 196 \n", + " White + Black Caribbean 224 \n", + "imd_categories 1 Most deprived 721 \n", + " 2 735 \n", + " 3 693 \n", + " 4 735 \n", + " 5 Least deprived 728 \n", + " Unknown 189 \n", + "bmi 30+ 1169 \n", + " under 30 2632 \n", + "housebound no 3759 \n", + " yes 35 \n", + "chronic_cardiac_disease no 3759 \n", + " yes 35 \n", + "current_copd no 3759 \n", + " yes 42 \n", + "dmards no 3752 \n", + " yes 42 \n", + "dementia no 3759 \n", + " yes 35 \n", + "psychosis_schiz_bipolar no 3752 \n", + " yes 42 \n", + "LD no 3703 \n", + " yes 91 \n", + "ssri no 3752 \n", + " yes 42 \n", + "chemo_or_radio no 3759 \n", + " yes 35 \n", + "lung_cancer no 3766 \n", + " yes 35 \n", + "cancer_excl_lung_and_haem no 3766 \n", " yes 28 \n", - "chronic_cardiac_disease no 1925 \n", - " yes 14 \n", - "current_copd no 1918 \n", - " yes 21 \n", - "dmards no 1918 \n", - " yes 21 \n", - "dementia no 1918 \n", - " yes 21 \n", - "psychosis_schiz_bipolar no 1918 \n", - " yes 21 \n", - "LD no 1904 \n", + "haematological_cancer no 3759 \n", " yes 35 \n", - "ssri no 1925 \n", - " yes 14 \n", - "chemo_or_radio no 1925 \n", - " yes 14 \n", - "lung_cancer no 1918 \n", - " yes 21 \n", - "cancer_excl_lung_and_haem no 1925 \n", - " yes 14 \n", - "haematological_cancer no 1918 \n", - " yes 21 \n", - "ckd no 1554 \n", - " yes 385 \n", + "ckd no 3052 \n", + " yes 742 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 90.5 2142 \n", - "sex F 91.3 1127 \n", - " M 89.7 1015 \n", - "ageband_5yr 0 75.0 28 \n", - " 0-15 93.8 112 \n", - " 16-17 90.0 140 \n", - " 18-29 89.5 133 \n", - " 30-34 90.0 140 \n", - " 35-39 90.5 147 \n", - " 40-44 90.5 147 \n", - " 45-49 94.7 133 \n", - " 50-54 86.4 154 \n", - " 55-59 90.9 154 \n", - " 60-64 94.4 126 \n", - " 65-69 90.0 140 \n", - " 70-74 90.0 140 \n", - " 75-79 78.9 133 \n", - " 80-84 100.0 140 \n", - " 85-89 90.9 154 \n", - " 90+ 66.7 21 \n", - "ethnicity_6_groups Black 90.2 357 \n", - " Mixed 90.0 350 \n", - " Other 91.7 336 \n", - " South Asian 90.4 364 \n", - " Unknown 89.8 343 \n", - " White 89.3 392 \n", - "ethnicity_16_groups African 93.3 105 \n", - " Bangladeshi or British Bangladeshi 88.2 119 \n", - " Caribbean 92.9 98 \n", - " Chinese 86.7 105 \n", - " Other 93.8 112 \n", - " Other Asian 93.8 112 \n", - " British or Mixed British 89.5 133 \n", - " Indian or British Indian 93.3 105 \n", - " Irish 88.2 119 \n", - " Other Black 91.7 84 \n", - " Other White 94.1 119 \n", - " Other mixed 86.7 105 \n", - " Pakistani or British Pakistani 87.5 112 \n", - " Unknown 91.8 343 \n", - " White + Asian 88.2 119 \n", - " White + Black African 93.3 105 \n", - " White + Black Caribbean 90.0 140 \n", - "imd_categories 1 Most deprived 90.0 420 \n", - " 2 91.4 406 \n", - " 3 89.3 392 \n", - " 4 90.2 427 \n", - " 5 Least deprived 89.3 392 \n", - " Unknown 93.3 105 \n", - "bmi 30+ 91.8 595 \n", - " under 30 90.0 1547 \n", - "housebound no 90.4 2114 \n", - " yes 100.0 28 \n", - "chronic_cardiac_disease no 90.8 2121 \n", - " yes 66.7 21 \n", - "current_copd no 90.7 2114 \n", - " yes 100.0 21 \n", - "dmards no 90.7 2114 \n", - " yes 75.0 28 \n", - "dementia no 90.4 2121 \n", - " yes 100.0 21 \n", - "psychosis_schiz_bipolar no 90.4 2121 \n", - " yes 100.0 21 \n", - "LD no 90.7 2100 \n", + "overall overall 89.9 4221 \n", + "sex F 90.0 2177 \n", + " M 89.7 2044 \n", + "ageband_5yr 0 80.0 70 \n", + " 0-15 89.2 259 \n", + " 16-17 88.6 245 \n", + " 18-29 92.1 266 \n", + " 30-34 89.7 273 \n", + " 35-39 89.5 266 \n", + " 40-44 92.3 273 \n", + " 45-49 92.5 280 \n", + " 50-54 91.9 259 \n", + " 55-59 93.0 301 \n", + " 60-64 89.5 266 \n", + " 65-69 87.5 280 \n", + " 70-74 90.5 294 \n", + " 75-79 90.0 280 \n", + " 80-84 92.3 273 \n", + " 85-89 85.7 294 \n", + " 90+ 80.0 35 \n", + "ethnicity_6_groups Black 87.6 735 \n", + " Mixed 90.0 700 \n", + " Other 90.4 728 \n", + " South Asian 89.7 749 \n", + " Unknown 90.8 609 \n", + " White 90.2 714 \n", + "ethnicity_16_groups African 93.5 217 \n", + " Bangladeshi or British Bangladeshi 83.3 210 \n", + " Caribbean 90.3 217 \n", + " Chinese 87.1 217 \n", + " Other 88.2 238 \n", + " Other Asian 93.3 210 \n", + " British or Mixed British 90.3 217 \n", + " Indian or British Indian 87.5 224 \n", + " Irish 90.9 231 \n", + " Other Black 90.3 217 \n", + " Other White 88.2 238 \n", + " Other mixed 93.1 203 \n", + " Pakistani or British Pakistani 90.6 224 \n", + " Unknown 89.6 672 \n", + " White + Asian 87.5 224 \n", + " White + Black African 93.3 210 \n", + " White + Black Caribbean 88.9 252 \n", + "imd_categories 1 Most deprived 89.6 805 \n", + " 2 91.3 805 \n", + " 3 89.2 777 \n", + " 4 89.7 819 \n", + " 5 Least deprived 89.7 812 \n", + " Unknown 90.0 210 \n", + "bmi 30+ 90.3 1295 \n", + " under 30 90.0 2926 \n", + "housebound no 89.9 4179 \n", + " yes 83.3 42 \n", + "chronic_cardiac_disease no 89.8 4186 \n", + " yes 100.0 35 \n", + "current_copd no 89.9 4179 \n", + " yes 85.7 49 \n", + "dmards no 89.9 4172 \n", + " yes 85.7 49 \n", + "dementia no 89.9 4179 \n", + " yes 83.3 42 \n", + "psychosis_schiz_bipolar no 89.8 4179 \n", + " yes 100.0 42 \n", + "LD no 89.7 4130 \n", + " yes 92.9 98 \n", + "ssri no 89.8 4179 \n", + " yes 85.7 49 \n", + "chemo_or_radio no 89.8 4186 \n", + " yes 83.3 42 \n", + "lung_cancer no 89.8 4193 \n", + " yes 100.0 35 \n", + "cancer_excl_lung_and_haem no 89.8 4193 \n", + " yes 80.0 35 \n", + "haematological_cancer no 89.9 4179 \n", " yes 83.3 42 \n", - "ssri no 90.5 2128 \n", - " yes 100.0 14 \n", - "chemo_or_radio no 90.8 2121 \n", - " yes 66.7 21 \n", - "lung_cancer no 90.4 2121 \n", - " yes 100.0 21 \n", - "cancer_excl_lung_and_haem no 90.8 2121 \n", - " yes 66.7 21 \n", - "haematological_cancer no 90.4 2121 \n", - " yes 100.0 21 \n", - "ckd no 90.2 1722 \n", - " yes 91.7 420 \n", + "ckd no 89.9 3395 \n", + " yes 89.8 826 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.9 \n", - "sex F 90.1 \n", - " M 87.6 \n", - "ageband_5yr 0 75.0 \n", - " 0-15 87.5 \n", - " 16-17 85.0 \n", - " 18-29 84.2 \n", - " 30-34 90.0 \n", - " 35-39 85.7 \n", - " 40-44 90.5 \n", - " 45-49 94.7 \n", - " 50-54 86.4 \n", - " 55-59 90.9 \n", - " 60-64 94.4 \n", - " 65-69 90.0 \n", - " 70-74 90.0 \n", - " 75-79 78.9 \n", - " 80-84 95.0 \n", - " 85-89 90.9 \n", - " 90+ 66.7 \n", - "ethnicity_6_groups Black 88.2 \n", - " Mixed 88.0 \n", - " Other 89.6 \n", - " South Asian 88.5 \n", - " Unknown 89.8 \n", - " White 87.5 \n", - "ethnicity_16_groups African 86.7 \n", - " Bangladeshi or British Bangladeshi 88.2 \n", - " Caribbean 92.9 \n", - " Chinese 86.7 \n", - " Other 93.8 \n", - " Other Asian 87.5 \n", - " British or Mixed British 84.2 \n", - " Indian or British Indian 93.3 \n", - " Irish 88.2 \n", - " Other Black 83.3 \n", + "overall overall 88.7 \n", + "sex F 89.1 \n", + " M 88.4 \n", + "ageband_5yr 0 80.0 \n", + " 0-15 86.5 \n", + " 16-17 88.6 \n", + " 18-29 89.5 \n", + " 30-34 87.2 \n", + " 35-39 89.5 \n", + " 40-44 92.3 \n", + " 45-49 90.0 \n", + " 50-54 91.9 \n", + " 55-59 90.7 \n", + " 60-64 86.8 \n", + " 65-69 87.5 \n", + " 70-74 90.5 \n", + " 75-79 87.5 \n", + " 80-84 89.7 \n", + " 85-89 85.7 \n", + " 90+ 80.0 \n", + "ethnicity_6_groups Black 85.7 \n", + " Mixed 89.0 \n", + " Other 89.4 \n", + " South Asian 87.9 \n", + " Unknown 89.7 \n", + " White 88.2 \n", + "ethnicity_16_groups African 90.3 \n", + " Bangladeshi or British Bangladeshi 83.3 \n", + " Caribbean 87.1 \n", + " Chinese 87.1 \n", + " Other 88.2 \n", + " Other Asian 90.0 \n", + " British or Mixed British 90.3 \n", + " Indian or British Indian 84.4 \n", + " Irish 90.9 \n", + " Other Black 87.1 \n", " Other White 88.2 \n", - " Other mixed 86.7 \n", - " Pakistani or British Pakistani 87.5 \n", - " Unknown 91.8 \n", - " White + Asian 88.2 \n", + " Other mixed 89.7 \n", + " Pakistani or British Pakistani 90.6 \n", + " Unknown 88.5 \n", + " White + Asian 87.5 \n", " White + Black African 93.3 \n", - " White + Black Caribbean 85.0 \n", - "imd_categories 1 Most deprived 88.3 \n", - " 2 89.7 \n", - " 3 87.5 \n", - " 4 88.5 \n", - " 5 Least deprived 89.3 \n", - " Unknown 93.3 \n", - "bmi 30+ 89.4 \n", - " under 30 88.7 \n", - "housebound no 88.7 \n", - " yes 100.0 \n", - "chronic_cardiac_disease no 88.8 \n", - " yes 66.7 \n", - "current_copd no 89.1 \n", + " White + Black Caribbean 88.9 \n", + "imd_categories 1 Most deprived 87.8 \n", + " 2 90.4 \n", + " 3 88.3 \n", + " 4 88.0 \n", + " 5 Least deprived 87.9 \n", + " Unknown 90.0 \n", + "bmi 30+ 88.6 \n", + " under 30 88.5 \n", + "housebound no 88.8 \n", + " yes 83.3 \n", + "chronic_cardiac_disease no 88.6 \n", " yes 100.0 \n", - "dmards no 88.7 \n", - " yes 75.0 \n", + "current_copd no 88.6 \n", + " yes 85.7 \n", + "dmards no 88.8 \n", + " yes 85.7 \n", "dementia no 88.8 \n", - " yes 100.0 \n", - "psychosis_schiz_bipolar no 88.8 \n", - " yes 100.0 \n", - "LD no 89.0 \n", " yes 83.3 \n", - "ssri no 88.8 \n", + "psychosis_schiz_bipolar no 88.6 \n", " yes 100.0 \n", - "chemo_or_radio no 89.1 \n", - " yes 66.7 \n", - "lung_cancer no 88.8 \n", - " yes 100.0 \n", - "cancer_excl_lung_and_haem no 88.8 \n", - " yes 66.7 \n", + "LD no 88.5 \n", + " yes 92.9 \n", + "ssri no 88.6 \n", + " yes 85.7 \n", + "chemo_or_radio no 88.6 \n", + " yes 83.3 \n", + "lung_cancer no 88.5 \n", + " yes 80.0 \n", + "cancer_excl_lung_and_haem no 88.6 \n", + " yes 80.0 \n", "haematological_cancer no 88.8 \n", - " yes 100.0 \n", - "ckd no 88.2 \n", - " yes 90.0 \n", + " yes 83.3 \n", + "ckd no 88.9 \n", + " yes 88.1 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.6 \n", - "sex F 1.2 \n", - " M 2.1 \n", + "overall overall 1.2 \n", + "sex F 0.9 \n", + " M 1.3 \n", "ageband_5yr 0 0.0 \n", - " 0-15 6.3 \n", - " 16-17 5.0 \n", - " 18-29 5.3 \n", - " 30-34 0.0 \n", - " 35-39 4.8 \n", + " 0-15 2.7 \n", + " 16-17 0.0 \n", + " 18-29 2.6 \n", + " 30-34 2.5 \n", + " 35-39 0.0 \n", " 40-44 0.0 \n", - " 45-49 0.0 \n", + " 45-49 2.5 \n", " 50-54 0.0 \n", - " 55-59 0.0 \n", - " 60-64 0.0 \n", + " 55-59 2.3 \n", + " 60-64 2.7 \n", " 65-69 0.0 \n", " 70-74 0.0 \n", - " 75-79 0.0 \n", - " 80-84 5.0 \n", + " 75-79 2.5 \n", + " 80-84 2.6 \n", " 85-89 0.0 \n", " 90+ 0.0 \n", - "ethnicity_6_groups Black 2.0 \n", - " Mixed 2.0 \n", - " Other 2.1 \n", - " South Asian 1.9 \n", - " Unknown 0.0 \n", - " White 1.8 \n", - "ethnicity_16_groups African 6.6 \n", + "ethnicity_6_groups Black 1.9 \n", + " Mixed 1.0 \n", + " Other 1.0 \n", + " South Asian 1.8 \n", + " Unknown 1.1 \n", + " White 2.0 \n", + "ethnicity_16_groups African 3.2 \n", " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", + " Caribbean 3.2 \n", " Chinese 0.0 \n", " Other 0.0 \n", - " Other Asian 6.3 \n", - " British or Mixed British 5.3 \n", - " Indian or British Indian 0.0 \n", + " Other Asian 3.3 \n", + " British or Mixed British 0.0 \n", + " Indian or British Indian 3.1 \n", " Irish 0.0 \n", - " Other Black 8.4 \n", - " Other White 5.9 \n", - " Other mixed 0.0 \n", + " Other Black 3.2 \n", + " Other White 0.0 \n", + " Other mixed 3.4 \n", " Pakistani or British Pakistani 0.0 \n", - " Unknown 0.0 \n", + " Unknown 1.1 \n", " White + Asian 0.0 \n", " White + Black African 0.0 \n", - " White + Black Caribbean 5.0 \n", - "imd_categories 1 Most deprived 1.7 \n", - " 2 1.7 \n", - " 3 1.8 \n", + " White + Black Caribbean 0.0 \n", + "imd_categories 1 Most deprived 1.8 \n", + " 2 0.9 \n", + " 3 0.9 \n", " 4 1.7 \n", - " 5 Least deprived 0.0 \n", + " 5 Least deprived 1.8 \n", " Unknown 0.0 \n", - "bmi 30+ 2.4 \n", - " under 30 1.3 \n", - "housebound no 1.7 \n", - " yes 0.0 \n", - "chronic_cardiac_disease no 2.0 \n", + "bmi 30+ 1.7 \n", + " under 30 1.5 \n", + "housebound no 1.1 \n", " yes 0.0 \n", - "current_copd no 1.6 \n", + "chronic_cardiac_disease no 1.2 \n", " yes 0.0 \n", - "dmards no 2.0 \n", + "current_copd no 1.3 \n", " yes 0.0 \n", - "dementia no 1.6 \n", + "dmards no 1.1 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.6 \n", + "dementia no 1.1 \n", " yes 0.0 \n", - "LD no 1.7 \n", + "psychosis_schiz_bipolar no 1.2 \n", " yes 0.0 \n", - "ssri no 1.7 \n", + "LD no 1.2 \n", " yes 0.0 \n", - "chemo_or_radio no 1.7 \n", + "ssri no 1.2 \n", " yes 0.0 \n", - "lung_cancer no 1.6 \n", + "chemo_or_radio no 1.2 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 2.0 \n", + "lung_cancer no 1.3 \n", + " yes 20.0 \n", + "cancer_excl_lung_and_haem no 1.2 \n", " yes 0.0 \n", - "haematological_cancer no 1.6 \n", + "haematological_cancer no 1.1 \n", " yes 0.0 \n", - "ckd no 2.0 \n", + "ckd no 1.0 \n", " yes 1.7 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall reached \n", + "overall overall 02-Feb \n", "sex F reached \n", - " M 16-Dec \n", + " M 03-Feb \n", "ageband_5yr 0 unknown \n", - " 0-15 reached \n", - " 16-17 reached \n", - " 18-29 15-Dec \n", - " 30-34 unknown \n", - " 35-39 reached \n", + " 0-15 04-Feb \n", + " 16-17 unknown \n", + " 18-29 reached \n", + " 30-34 02-Feb \n", + " 35-39 unknown \n", " 40-44 reached \n", " 45-49 reached \n", - " 50-54 unknown \n", + " 50-54 reached \n", " 55-59 reached \n", - " 60-64 reached \n", + " 60-64 03-Feb \n", " 65-69 unknown \n", - " 70-74 unknown \n", - " 75-79 unknown \n", + " 70-74 reached \n", + " 75-79 reached \n", " 80-84 reached \n", - " 85-89 reached \n", + " 85-89 unknown \n", " 90+ unknown \n", - "ethnicity_6_groups Black reached \n", + "ethnicity_6_groups Black 10-Feb \n", " Mixed reached \n", " Other reached \n", - " South Asian reached \n", - " Unknown unknown \n", - " White 17-Dec \n", + " South Asian 03-Feb \n", + " Unknown reached \n", + " White reached \n", "ethnicity_16_groups African reached \n", " Bangladeshi or British Bangladeshi unknown \n", " Caribbean reached \n", " Chinese unknown \n", - " Other reached \n", + " Other unknown \n", " Other Asian reached \n", - " British or Mixed British 15-Dec \n", - " Indian or British Indian reached \n", - " Irish unknown \n", + " British or Mixed British reached \n", + " Indian or British Indian 07-Feb \n", + " Irish reached \n", " Other Black reached \n", - " Other White reached \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani unknown \n", - " Unknown reached \n", + " Other White unknown \n", + " Other mixed reached \n", + " Pakistani or British Pakistani reached \n", + " Unknown 04-Feb \n", " White + Asian unknown \n", " White + Black African reached \n", - " White + Black Caribbean reached \n", - "imd_categories 1 Most deprived reached \n", + " White + Black Caribbean unknown \n", + "imd_categories 1 Most deprived 03-Feb \n", " 2 reached \n", - " 3 17-Dec \n", - " 4 reached \n", - " 5 Least deprived unknown \n", - " Unknown reached \n", + " 3 08-Feb \n", + " 4 03-Feb \n", + " 5 Least deprived 03-Feb \n", + " Unknown unknown \n", "bmi 30+ reached \n", " under 30 reached \n", - "housebound no reached \n", - " yes reached \n", - "chronic_cardiac_disease no reached \n", + "housebound no 02-Feb \n", " yes unknown \n", - "current_copd no reached \n", + "chronic_cardiac_disease no 03-Feb \n", " yes reached \n", - "dmards no reached \n", + "current_copd no 02-Feb \n", " yes unknown \n", - "dementia no reached \n", + "dmards no 02-Feb \n", + " yes unknown \n", + "dementia no 02-Feb \n", + " yes unknown \n", + "psychosis_schiz_bipolar no 03-Feb \n", " yes reached \n", - "psychosis_schiz_bipolar no reached \n", + "LD no 03-Feb \n", " yes reached \n", - "LD no reached \n", + "ssri no 03-Feb \n", " yes unknown \n", - "ssri no reached \n", - " yes reached \n", - "chemo_or_radio no reached \n", + "chemo_or_radio no 03-Feb \n", " yes unknown \n", - "lung_cancer no reached \n", + "lung_cancer no 03-Feb \n", " yes reached \n", - "cancer_excl_lung_and_haem no reached \n", + "cancer_excl_lung_and_haem no 03-Feb \n", " yes unknown \n", - "haematological_cancer no reached \n", - " yes reached \n", - "ckd no reached \n", - " yes reached " + "haematological_cancer no 02-Feb \n", + " yes unknown \n", + "ckd no 02-Feb \n", + " yes 02-Feb " ] }, "metadata": {}, @@ -1999,7 +2051,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **70-79** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **70-79** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -2065,484 +2117,484 @@ " \n", " overall\n", " overall\n", - " 3136\n", - " 90.1\n", - " 3479\n", - " 88.1\n", - " 2.0\n", + " 6188\n", + " 90.2\n", + " 6860\n", + " 88.7\n", + " 1.5\n", " reached\n", " \n", " \n", " sex\n", " F\n", - " 1589\n", - " 90.4\n", - " 1757\n", - " 88.8\n", + " 3220\n", + " 90.9\n", + " 3542\n", + " 89.3\n", " 1.6\n", " reached\n", " \n", " \n", " M\n", - " 1547\n", - " 89.8\n", - " 1722\n", - " 87.4\n", - " 2.4\n", - " 15-Dec\n", + " 2968\n", + " 89.5\n", + " 3318\n", + " 88.0\n", + " 1.5\n", + " 04-Feb\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 35\n", - " 83.3\n", - " 42\n", + " 77\n", + " 91.7\n", + " 84\n", " 83.3\n", - " 0.0\n", - " unknown\n", + " 8.4\n", + " reached\n", " \n", " \n", " 0-15\n", - " 189\n", - " 90.0\n", - " 210\n", - " 90.0\n", - " 0.0\n", - " unknown\n", + " 392\n", + " 91.8\n", + " 427\n", + " 88.5\n", + " 3.3\n", + " reached\n", " \n", " \n", " 16-17\n", - " 238\n", - " 89.5\n", - " 266\n", - " 84.2\n", - " 5.3\n", - " 15-Dec\n", + " 406\n", + " 89.2\n", + " 455\n", + " 87.7\n", + " 1.5\n", + " 05-Feb\n", " \n", " \n", " 18-29\n", - " 210\n", - " 90.9\n", - " 231\n", - " 87.9\n", - " 3.0\n", + " 392\n", + " 90.3\n", + " 434\n", + " 88.7\n", + " 1.6\n", " reached\n", " \n", " \n", " 30-34\n", - " 245\n", - " 94.6\n", - " 259\n", - " 91.9\n", - " 2.7\n", - " reached\n", + " 420\n", + " 89.6\n", + " 469\n", + " 86.6\n", + " 3.0\n", + " 02-Feb\n", " \n", " \n", " 35-39\n", - " 189\n", - " 87.1\n", - " 217\n", - " 87.1\n", - " 0.0\n", - " unknown\n", + " 413\n", + " 89.4\n", + " 462\n", + " 87.9\n", + " 1.5\n", + " 04-Feb\n", " \n", " \n", " 40-44\n", - " 189\n", - " 90.0\n", - " 210\n", - " 86.7\n", - " 3.3\n", - " reached\n", + " 385\n", + " 88.7\n", + " 434\n", + " 87.1\n", + " 1.6\n", + " 07-Feb\n", " \n", " \n", " 45-49\n", - " 217\n", - " 93.9\n", - " 231\n", - " 93.9\n", + " 406\n", + " 90.6\n", + " 448\n", + " 90.6\n", " 0.0\n", " reached\n", " \n", " \n", " 50-54\n", - " 189\n", - " 87.1\n", - " 217\n", - " 87.1\n", - " 0.0\n", - " unknown\n", + " 406\n", + " 93.5\n", + " 434\n", + " 91.9\n", + " 1.6\n", + " reached\n", " \n", " \n", " 55-59\n", - " 175\n", - " 83.3\n", - " 210\n", - " 83.3\n", - " 0.0\n", - " unknown\n", + " 406\n", + " 89.2\n", + " 455\n", + " 87.7\n", + " 1.5\n", + " 05-Feb\n", " \n", " \n", " 60-64\n", - " 210\n", - " 88.2\n", - " 238\n", - " 88.2\n", - " 0.0\n", - " unknown\n", + " 406\n", + " 90.6\n", + " 448\n", + " 89.1\n", + " 1.5\n", + " reached\n", " \n", " \n", " 65-69\n", - " 203\n", - " 90.6\n", - " 224\n", - " 90.6\n", - " 0.0\n", - " reached\n", + " 399\n", + " 89.1\n", + " 448\n", + " 87.5\n", + " 1.6\n", + " 05-Feb\n", " \n", " \n", " 70-74\n", - " 182\n", - " 92.9\n", - " 196\n", - " 89.3\n", - " 3.6\n", + " 392\n", + " 90.3\n", + " 434\n", + " 88.7\n", + " 1.6\n", " reached\n", " \n", " \n", " 75-79\n", - " 210\n", - " 88.2\n", - " 238\n", - " 85.3\n", - " 2.9\n", - " 19-Dec\n", + " 406\n", + " 89.2\n", + " 455\n", + " 89.2\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 80-84\n", - " 217\n", - " 91.2\n", - " 238\n", - " 88.2\n", - " 3.0\n", - " reached\n", + " 392\n", + " 88.9\n", + " 441\n", + " 87.3\n", + " 1.6\n", + " 06-Feb\n", " \n", " \n", " 85-89\n", - " 196\n", - " 90.3\n", - " 217\n", - " 90.3\n", - " 0.0\n", + " 413\n", + " 92.2\n", + " 448\n", + " 90.6\n", + " 1.6\n", " reached\n", " \n", " \n", " 90+\n", - " 28\n", - " 100.0\n", - " 28\n", - " 100.0\n", + " 70\n", + " 83.3\n", + " 84\n", + " 83.3\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 553\n", - " 90.8\n", - " 609\n", - " 88.5\n", - " 2.3\n", + " 1050\n", + " 90.9\n", + " 1155\n", + " 89.7\n", + " 1.2\n", " reached\n", " \n", " \n", " Mixed\n", - " 553\n", - " 89.8\n", - " 616\n", - " 88.6\n", - " 1.2\n", - " 16-Dec\n", + " 1071\n", + " 90.0\n", + " 1190\n", + " 88.2\n", + " 1.8\n", + " reached\n", " \n", " \n", " Other\n", - " 511\n", - " 89.0\n", - " 574\n", - " 87.8\n", + " 1057\n", + " 89.9\n", + " 1176\n", + " 88.7\n", " 1.2\n", - " 20-Dec\n", + " 02-Feb\n", " \n", " \n", " South Asian\n", - " 518\n", - " 91.4\n", - " 567\n", - " 88.9\n", - " 2.5\n", - " reached\n", + " 1078\n", + " 89.5\n", + " 1204\n", + " 88.4\n", + " 1.1\n", + " 05-Feb\n", " \n", " \n", " Unknown\n", - " 441\n", - " 87.5\n", - " 504\n", - " 86.1\n", + " 924\n", + " 89.8\n", + " 1029\n", + " 88.4\n", " 1.4\n", - " 27-Dec\n", + " 03-Feb\n", " \n", " \n", " White\n", - " 546\n", - " 89.7\n", - " 609\n", - " 87.4\n", - " 2.3\n", - " 15-Dec\n", + " 1001\n", + " 91.1\n", + " 1099\n", + " 89.2\n", + " 1.9\n", + " reached\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 189\n", - " 93.1\n", - " 203\n", - " 89.7\n", - " 3.4\n", + " 329\n", + " 92.2\n", + " 357\n", + " 90.2\n", + " 2.0\n", " reached\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 168\n", - " 85.7\n", - " 196\n", - " 85.7\n", - " 0.0\n", - " unknown\n", + " 315\n", + " 90.0\n", + " 350\n", + " 88.0\n", + " 2.0\n", + " reached\n", " \n", " \n", " Caribbean\n", - " 154\n", - " 88.0\n", - " 175\n", - " 88.0\n", - " 0.0\n", - " unknown\n", + " 343\n", + " 92.5\n", + " 371\n", + " 90.6\n", + " 1.9\n", + " reached\n", " \n", " \n", " Chinese\n", - " 140\n", - " 90.9\n", - " 154\n", - " 90.9\n", + " 322\n", + " 88.5\n", + " 364\n", + " 88.5\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " Other\n", - " 161\n", - " 95.8\n", - " 168\n", - " 91.7\n", - " 4.1\n", - " reached\n", + " 329\n", + " 88.7\n", + " 371\n", + " 86.8\n", + " 1.9\n", + " 06-Feb\n", " \n", " \n", " Other Asian\n", - " 161\n", - " 88.5\n", - " 182\n", + " 336\n", + " 92.3\n", + " 364\n", " 88.5\n", - " 0.0\n", - " unknown\n", + " 3.8\n", + " reached\n", " \n", " \n", " British or Mixed British\n", - " 168\n", - " 88.9\n", - " 189\n", - " 85.2\n", - " 3.7\n", - " 17-Dec\n", + " 308\n", + " 89.8\n", + " 343\n", + " 85.7\n", + " 4.1\n", + " 02-Feb\n", " \n", " \n", " Indian or British Indian\n", - " 168\n", - " 88.9\n", - " 189\n", - " 85.2\n", - " 3.7\n", - " 17-Dec\n", + " 336\n", + " 90.6\n", + " 371\n", + " 88.7\n", + " 1.9\n", + " reached\n", " \n", " \n", " Irish\n", - " 147\n", - " 87.5\n", - " 168\n", - " 87.5\n", - " 0.0\n", - " unknown\n", + " 329\n", + " 90.4\n", + " 364\n", + " 86.5\n", + " 3.9\n", + " reached\n", " \n", " \n", " Other Black\n", - " 168\n", - " 92.3\n", - " 182\n", + " 329\n", + " 90.4\n", + " 364\n", " 88.5\n", - " 3.8\n", + " 1.9\n", " reached\n", " \n", " \n", " Other White\n", - " 168\n", - " 85.7\n", - " 196\n", - " 85.7\n", + " 329\n", + " 90.4\n", + " 364\n", + " 90.4\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " Other mixed\n", - " 168\n", - " 88.9\n", - " 189\n", - " 88.9\n", - " 0.0\n", - " unknown\n", + " 315\n", + " 90.0\n", + " 350\n", + " 88.0\n", + " 2.0\n", + " reached\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 168\n", - " 92.3\n", - " 182\n", - " 92.3\n", + " 294\n", + " 89.4\n", + " 329\n", + " 89.4\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 504\n", - " 90.0\n", - " 560\n", - " 87.5\n", - " 2.5\n", + " 917\n", + " 90.3\n", + " 1015\n", + " 89.0\n", + " 1.3\n", " reached\n", " \n", " \n", " White + Asian\n", - " 175\n", - " 86.2\n", - " 203\n", - " 86.2\n", - " 0.0\n", - " unknown\n", + " 350\n", + " 90.9\n", + " 385\n", + " 89.1\n", + " 1.8\n", + " reached\n", " \n", " \n", " White + Black African\n", - " 168\n", - " 92.3\n", - " 182\n", - " 88.5\n", - " 3.8\n", - " reached\n", + " 350\n", + " 89.3\n", + " 392\n", + " 87.5\n", + " 1.8\n", + " 04-Feb\n", " \n", " \n", " White + Black Caribbean\n", - " 154\n", - " 88.0\n", - " 175\n", - " 88.0\n", - " 0.0\n", - " unknown\n", + " 357\n", + " 89.5\n", + " 399\n", + " 87.7\n", + " 1.8\n", + " 03-Feb\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 581\n", - " 90.2\n", - " 644\n", - " 88.0\n", - " 2.2\n", - " reached\n", + " 1169\n", + " 89.8\n", + " 1302\n", + " 88.7\n", + " 1.1\n", + " 03-Feb\n", " \n", " \n", " 2\n", - " 616\n", - " 89.8\n", - " 686\n", - " 87.8\n", - " 2.0\n", - " 15-Dec\n", + " 1218\n", + " 90.6\n", + " 1344\n", + " 88.0\n", + " 2.6\n", + " reached\n", " \n", " \n", " 3\n", - " 630\n", - " 91.8\n", - " 686\n", - " 90.8\n", - " 1.0\n", + " 1162\n", + " 90.7\n", + " 1281\n", + " 89.6\n", + " 1.1\n", " reached\n", " \n", " \n", " 4\n", - " 595\n", + " 1190\n", " 90.4\n", - " 658\n", - " 88.3\n", - " 2.1\n", + " 1316\n", + " 89.4\n", + " 1.0\n", " reached\n", " \n", " \n", " 5 Least deprived\n", - " 546\n", - " 88.6\n", - " 616\n", - " 86.4\n", - " 2.2\n", - " 19-Dec\n", + " 1148\n", + " 89.6\n", + " 1281\n", + " 88.0\n", + " 1.6\n", + " 03-Feb\n", " \n", " \n", " Unknown\n", - " 168\n", - " 88.9\n", - " 189\n", - " 85.2\n", - " 3.7\n", - " 17-Dec\n", + " 301\n", + " 91.5\n", + " 329\n", + " 89.4\n", + " 2.1\n", + " reached\n", " \n", " \n", " bmi\n", " 30+\n", - " 994\n", - " 91.0\n", - " 1092\n", - " 89.1\n", - " 1.9\n", - " reached\n", + " 1855\n", + " 89.8\n", + " 2065\n", + " 88.1\n", + " 1.7\n", + " 02-Feb\n", " \n", " \n", " under 30\n", - " 2142\n", - " 89.7\n", - " 2387\n", - " 87.7\n", - " 2.0\n", - " 16-Dec\n", + " 4333\n", + " 90.5\n", + " 4788\n", + " 89.0\n", + " 1.5\n", + " reached\n", " \n", " \n", " housebound\n", " no\n", - " 3108\n", - " 90.1\n", - " 3451\n", - " 88.0\n", - " 2.1\n", + " 6118\n", + " 90.2\n", + " 6783\n", + " 88.6\n", + " 1.6\n", " reached\n", " \n", " \n", " yes\n", - " 28\n", + " 70\n", " 100.0\n", - " 28\n", + " 70\n", " 100.0\n", " 0.0\n", " reached\n", @@ -2550,230 +2602,230 @@ " \n", " chronic_cardiac_disease\n", " no\n", - " 3108\n", - " 90.1\n", - " 3451\n", - " 88.0\n", - " 2.1\n", + " 6132\n", + " 90.2\n", + " 6797\n", + " 88.7\n", + " 1.5\n", " reached\n", " \n", " \n", " yes\n", - " 28\n", - " 100.0\n", - " 28\n", - " 100.0\n", + " 56\n", + " 88.9\n", + " 63\n", + " 88.9\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 3101\n", - " 90.0\n", - " 3444\n", - " 88.0\n", - " 2.0\n", + " 6111\n", + " 90.2\n", + " 6776\n", + " 88.6\n", + " 1.6\n", " reached\n", " \n", " \n", " yes\n", - " 35\n", - " 83.3\n", - " 42\n", - " 83.3\n", + " 77\n", + " 91.7\n", + " 84\n", + " 91.7\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " dmards\n", " no\n", - " 3101\n", - " 90.0\n", - " 3444\n", - " 88.2\n", - " 1.8\n", + " 6118\n", + " 90.1\n", + " 6790\n", + " 88.6\n", + " 1.5\n", " reached\n", " \n", " \n", " yes\n", - " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 70\n", + " 100.0\n", + " 70\n", + " 100.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " dementia\n", " no\n", - " 3101\n", - " 90.0\n", - " 3444\n", - " 88.0\n", - " 2.0\n", + " 6118\n", + " 90.3\n", + " 6776\n", + " 88.6\n", + " 1.7\n", " reached\n", " \n", " \n", " yes\n", - " 35\n", - " 83.3\n", - " 42\n", - " 83.3\n", + " 70\n", + " 90.9\n", + " 77\n", + " 90.9\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 3094\n", - " 89.8\n", - " 3444\n", - " 88.0\n", - " 1.8\n", - " 15-Dec\n", + " 6125\n", + " 90.2\n", + " 6790\n", + " 88.7\n", + " 1.5\n", + " reached\n", " \n", " \n", " yes\n", - " 35\n", - " 83.3\n", - " 42\n", - " 83.3\n", + " 63\n", + " 90.0\n", + " 70\n", + " 90.0\n", " 0.0\n", " unknown\n", " \n", " \n", " LD\n", " no\n", - " 3059\n", - " 89.9\n", - " 3402\n", - " 87.9\n", - " 2.0\n", - " 15-Dec\n", + " 6062\n", + " 90.1\n", + " 6727\n", + " 88.7\n", + " 1.4\n", + " reached\n", " \n", " \n", " yes\n", - " 70\n", - " 90.9\n", - " 77\n", - " 90.9\n", - " 0.0\n", + " 126\n", + " 94.7\n", + " 133\n", + " 89.5\n", + " 5.2\n", " reached\n", " \n", " \n", " ssri\n", " no\n", - " 3108\n", - " 90.1\n", - " 3451\n", - " 88.2\n", - " 1.9\n", + " 6125\n", + " 90.2\n", + " 6790\n", + " 88.7\n", + " 1.5\n", " reached\n", " \n", " \n", " yes\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", + " 63\n", + " 90.0\n", + " 70\n", + " 90.0\n", " 0.0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 3101\n", - " 89.9\n", - " 3451\n", - " 88.0\n", - " 1.9\n", - " 15-Dec\n", + " 6125\n", + " 90.2\n", + " 6790\n", + " 88.7\n", + " 1.5\n", + " reached\n", " \n", " \n", " yes\n", - " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 63\n", + " 90.0\n", + " 70\n", + " 90.0\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 3101\n", - " 90.0\n", - " 3444\n", - " 88.0\n", - " 2.0\n", + " 6125\n", + " 90.2\n", + " 6790\n", + " 88.7\n", + " 1.5\n", " reached\n", " \n", " \n", " yes\n", - " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 56\n", + " 88.9\n", + " 63\n", + " 88.9\n", " 0.0\n", " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 3101\n", - " 90.0\n", - " 3444\n", - " 88.0\n", - " 2.0\n", + " 6125\n", + " 90.2\n", + " 6790\n", + " 88.7\n", + " 1.5\n", " reached\n", " \n", " \n", " yes\n", - " 35\n", - " 100.0\n", - " 35\n", - " 100.0\n", + " 63\n", + " 90.0\n", + " 70\n", + " 90.0\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 3094\n", - " 90.0\n", - " 3437\n", - " 88.0\n", - " 2.0\n", + " 6118\n", + " 90.2\n", + " 6783\n", + " 88.6\n", + " 1.6\n", " reached\n", " \n", " \n", " yes\n", - " 42\n", - " 100.0\n", - " 42\n", + " 70\n", " 100.0\n", - " 0.0\n", + " 70\n", + " 90.0\n", + " 10.0\n", " reached\n", " \n", " \n", " ckd\n", " no\n", - " 2485\n", - " 90.6\n", - " 2744\n", + " 4935\n", + " 90.0\n", + " 5481\n", " 88.5\n", - " 2.1\n", + " 1.5\n", " reached\n", " \n", " \n", " yes\n", - " 651\n", - " 88.6\n", - " 735\n", - " 85.7\n", - " 2.9\n", - " 18-Dec\n", + " 1253\n", + " 90.9\n", + " 1379\n", + " 89.3\n", + " 1.6\n", + " reached\n", " \n", " \n", "\n", @@ -2782,403 +2834,403 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 3136 \n", - "sex F 1589 \n", - " M 1547 \n", - "ageband_5yr 0 35 \n", - " 0-15 189 \n", - " 16-17 238 \n", - " 18-29 210 \n", - " 30-34 245 \n", - " 35-39 189 \n", - " 40-44 189 \n", - " 45-49 217 \n", - " 50-54 189 \n", - " 55-59 175 \n", - " 60-64 210 \n", - " 65-69 203 \n", - " 70-74 182 \n", - " 75-79 210 \n", - " 80-84 217 \n", - " 85-89 196 \n", - " 90+ 28 \n", - "ethnicity_6_groups Black 553 \n", - " Mixed 553 \n", - " Other 511 \n", - " South Asian 518 \n", - " Unknown 441 \n", - " White 546 \n", - "ethnicity_16_groups African 189 \n", - " Bangladeshi or British Bangladeshi 168 \n", - " Caribbean 154 \n", - " Chinese 140 \n", - " Other 161 \n", - " Other Asian 161 \n", - " British or Mixed British 168 \n", - " Indian or British Indian 168 \n", - " Irish 147 \n", - " Other Black 168 \n", - " Other White 168 \n", - " Other mixed 168 \n", - " Pakistani or British Pakistani 168 \n", - " Unknown 504 \n", - " White + Asian 175 \n", - " White + Black African 168 \n", - " White + Black Caribbean 154 \n", - "imd_categories 1 Most deprived 581 \n", - " 2 616 \n", - " 3 630 \n", - " 4 595 \n", - " 5 Least deprived 546 \n", - " Unknown 168 \n", - "bmi 30+ 994 \n", - " under 30 2142 \n", - "housebound no 3108 \n", - " yes 28 \n", - "chronic_cardiac_disease no 3108 \n", - " yes 28 \n", - "current_copd no 3101 \n", - " yes 35 \n", - "dmards no 3101 \n", - " yes 28 \n", - "dementia no 3101 \n", - " yes 35 \n", - "psychosis_schiz_bipolar no 3094 \n", - " yes 35 \n", - "LD no 3059 \n", + "overall overall 6188 \n", + "sex F 3220 \n", + " M 2968 \n", + "ageband_5yr 0 77 \n", + " 0-15 392 \n", + " 16-17 406 \n", + " 18-29 392 \n", + " 30-34 420 \n", + " 35-39 413 \n", + " 40-44 385 \n", + " 45-49 406 \n", + " 50-54 406 \n", + " 55-59 406 \n", + " 60-64 406 \n", + " 65-69 399 \n", + " 70-74 392 \n", + " 75-79 406 \n", + " 80-84 392 \n", + " 85-89 413 \n", + " 90+ 70 \n", + "ethnicity_6_groups Black 1050 \n", + " Mixed 1071 \n", + " Other 1057 \n", + " South Asian 1078 \n", + " Unknown 924 \n", + " White 1001 \n", + "ethnicity_16_groups African 329 \n", + " Bangladeshi or British Bangladeshi 315 \n", + " Caribbean 343 \n", + " Chinese 322 \n", + " Other 329 \n", + " Other Asian 336 \n", + " British or Mixed British 308 \n", + " Indian or British Indian 336 \n", + " Irish 329 \n", + " Other Black 329 \n", + " Other White 329 \n", + " Other mixed 315 \n", + " Pakistani or British Pakistani 294 \n", + " Unknown 917 \n", + " White + Asian 350 \n", + " White + Black African 350 \n", + " White + Black Caribbean 357 \n", + "imd_categories 1 Most deprived 1169 \n", + " 2 1218 \n", + " 3 1162 \n", + " 4 1190 \n", + " 5 Least deprived 1148 \n", + " Unknown 301 \n", + "bmi 30+ 1855 \n", + " under 30 4333 \n", + "housebound no 6118 \n", " yes 70 \n", - "ssri no 3108 \n", - " yes 21 \n", - "chemo_or_radio no 3101 \n", - " yes 28 \n", - "lung_cancer no 3101 \n", - " yes 28 \n", - "cancer_excl_lung_and_haem no 3101 \n", - " yes 35 \n", - "haematological_cancer no 3094 \n", - " yes 42 \n", - "ckd no 2485 \n", - " yes 651 \n", + "chronic_cardiac_disease no 6132 \n", + " yes 56 \n", + "current_copd no 6111 \n", + " yes 77 \n", + "dmards no 6118 \n", + " yes 70 \n", + "dementia no 6118 \n", + " yes 70 \n", + "psychosis_schiz_bipolar no 6125 \n", + " yes 63 \n", + "LD no 6062 \n", + " yes 126 \n", + "ssri no 6125 \n", + " yes 63 \n", + "chemo_or_radio no 6125 \n", + " yes 63 \n", + "lung_cancer no 6125 \n", + " yes 56 \n", + "cancer_excl_lung_and_haem no 6125 \n", + " yes 63 \n", + "haematological_cancer no 6118 \n", + " yes 70 \n", + "ckd no 4935 \n", + " yes 1253 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 90.1 3479 \n", - "sex F 90.4 1757 \n", - " M 89.8 1722 \n", - "ageband_5yr 0 83.3 42 \n", - " 0-15 90.0 210 \n", - " 16-17 89.5 266 \n", - " 18-29 90.9 231 \n", - " 30-34 94.6 259 \n", - " 35-39 87.1 217 \n", - " 40-44 90.0 210 \n", - " 45-49 93.9 231 \n", - " 50-54 87.1 217 \n", - " 55-59 83.3 210 \n", - " 60-64 88.2 238 \n", - " 65-69 90.6 224 \n", - " 70-74 92.9 196 \n", - " 75-79 88.2 238 \n", - " 80-84 91.2 238 \n", - " 85-89 90.3 217 \n", - " 90+ 100.0 28 \n", - "ethnicity_6_groups Black 90.8 609 \n", - " Mixed 89.8 616 \n", - " Other 89.0 574 \n", - " South Asian 91.4 567 \n", - " Unknown 87.5 504 \n", - " White 89.7 609 \n", - "ethnicity_16_groups African 93.1 203 \n", - " Bangladeshi or British Bangladeshi 85.7 196 \n", - " Caribbean 88.0 175 \n", - " Chinese 90.9 154 \n", - " Other 95.8 168 \n", - " Other Asian 88.5 182 \n", - " British or Mixed British 88.9 189 \n", - " Indian or British Indian 88.9 189 \n", - " Irish 87.5 168 \n", - " Other Black 92.3 182 \n", - " Other White 85.7 196 \n", - " Other mixed 88.9 189 \n", - " Pakistani or British Pakistani 92.3 182 \n", - " Unknown 90.0 560 \n", - " White + Asian 86.2 203 \n", - " White + Black African 92.3 182 \n", - " White + Black Caribbean 88.0 175 \n", - "imd_categories 1 Most deprived 90.2 644 \n", - " 2 89.8 686 \n", - " 3 91.8 686 \n", - " 4 90.4 658 \n", - " 5 Least deprived 88.6 616 \n", - " Unknown 88.9 189 \n", - "bmi 30+ 91.0 1092 \n", - " under 30 89.7 2387 \n", - "housebound no 90.1 3451 \n", - " yes 100.0 28 \n", - "chronic_cardiac_disease no 90.1 3451 \n", - " yes 100.0 28 \n", - "current_copd no 90.0 3444 \n", - " yes 83.3 42 \n", - "dmards no 90.0 3444 \n", - " yes 80.0 35 \n", - "dementia no 90.0 3444 \n", - " yes 83.3 42 \n", - "psychosis_schiz_bipolar no 89.8 3444 \n", - " yes 83.3 42 \n", - "LD no 89.9 3402 \n", + "overall overall 90.2 6860 \n", + "sex F 90.9 3542 \n", + " M 89.5 3318 \n", + "ageband_5yr 0 91.7 84 \n", + " 0-15 91.8 427 \n", + " 16-17 89.2 455 \n", + " 18-29 90.3 434 \n", + " 30-34 89.6 469 \n", + " 35-39 89.4 462 \n", + " 40-44 88.7 434 \n", + " 45-49 90.6 448 \n", + " 50-54 93.5 434 \n", + " 55-59 89.2 455 \n", + " 60-64 90.6 448 \n", + " 65-69 89.1 448 \n", + " 70-74 90.3 434 \n", + " 75-79 89.2 455 \n", + " 80-84 88.9 441 \n", + " 85-89 92.2 448 \n", + " 90+ 83.3 84 \n", + "ethnicity_6_groups Black 90.9 1155 \n", + " Mixed 90.0 1190 \n", + " Other 89.9 1176 \n", + " South Asian 89.5 1204 \n", + " Unknown 89.8 1029 \n", + " White 91.1 1099 \n", + "ethnicity_16_groups African 92.2 357 \n", + " Bangladeshi or British Bangladeshi 90.0 350 \n", + " Caribbean 92.5 371 \n", + " Chinese 88.5 364 \n", + " Other 88.7 371 \n", + " Other Asian 92.3 364 \n", + " British or Mixed British 89.8 343 \n", + " Indian or British Indian 90.6 371 \n", + " Irish 90.4 364 \n", + " Other Black 90.4 364 \n", + " Other White 90.4 364 \n", + " Other mixed 90.0 350 \n", + " Pakistani or British Pakistani 89.4 329 \n", + " Unknown 90.3 1015 \n", + " White + Asian 90.9 385 \n", + " White + Black African 89.3 392 \n", + " White + Black Caribbean 89.5 399 \n", + "imd_categories 1 Most deprived 89.8 1302 \n", + " 2 90.6 1344 \n", + " 3 90.7 1281 \n", + " 4 90.4 1316 \n", + " 5 Least deprived 89.6 1281 \n", + " Unknown 91.5 329 \n", + "bmi 30+ 89.8 2065 \n", + " under 30 90.5 4788 \n", + "housebound no 90.2 6783 \n", + " yes 100.0 70 \n", + "chronic_cardiac_disease no 90.2 6797 \n", + " yes 88.9 63 \n", + "current_copd no 90.2 6776 \n", + " yes 91.7 84 \n", + "dmards no 90.1 6790 \n", + " yes 100.0 70 \n", + "dementia no 90.3 6776 \n", " yes 90.9 77 \n", - "ssri no 90.1 3451 \n", - " yes 75.0 28 \n", - "chemo_or_radio no 89.9 3451 \n", - " yes 80.0 35 \n", - "lung_cancer no 90.0 3444 \n", - " yes 80.0 35 \n", - "cancer_excl_lung_and_haem no 90.0 3444 \n", - " yes 100.0 35 \n", - "haematological_cancer no 90.0 3437 \n", - " yes 100.0 42 \n", - "ckd no 90.6 2744 \n", - " yes 88.6 735 \n", + "psychosis_schiz_bipolar no 90.2 6790 \n", + " yes 90.0 70 \n", + "LD no 90.1 6727 \n", + " yes 94.7 133 \n", + "ssri no 90.2 6790 \n", + " yes 90.0 70 \n", + "chemo_or_radio no 90.2 6790 \n", + " yes 90.0 70 \n", + "lung_cancer no 90.2 6790 \n", + " yes 88.9 63 \n", + "cancer_excl_lung_and_haem no 90.2 6790 \n", + " yes 90.0 70 \n", + "haematological_cancer no 90.2 6783 \n", + " yes 100.0 70 \n", + "ckd no 90.0 5481 \n", + " yes 90.9 1379 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.1 \n", - "sex F 88.8 \n", - " M 87.4 \n", + "overall overall 88.7 \n", + "sex F 89.3 \n", + " M 88.0 \n", "ageband_5yr 0 83.3 \n", - " 0-15 90.0 \n", - " 16-17 84.2 \n", - " 18-29 87.9 \n", - " 30-34 91.9 \n", - " 35-39 87.1 \n", - " 40-44 86.7 \n", - " 45-49 93.9 \n", - " 50-54 87.1 \n", - " 55-59 83.3 \n", - " 60-64 88.2 \n", - " 65-69 90.6 \n", - " 70-74 89.3 \n", - " 75-79 85.3 \n", - " 80-84 88.2 \n", - " 85-89 90.3 \n", - " 90+ 100.0 \n", - "ethnicity_6_groups Black 88.5 \n", - " Mixed 88.6 \n", - " Other 87.8 \n", - " South Asian 88.9 \n", - " Unknown 86.1 \n", - " White 87.4 \n", - "ethnicity_16_groups African 89.7 \n", - " Bangladeshi or British Bangladeshi 85.7 \n", - " Caribbean 88.0 \n", - " Chinese 90.9 \n", - " Other 91.7 \n", + " 0-15 88.5 \n", + " 16-17 87.7 \n", + " 18-29 88.7 \n", + " 30-34 86.6 \n", + " 35-39 87.9 \n", + " 40-44 87.1 \n", + " 45-49 90.6 \n", + " 50-54 91.9 \n", + " 55-59 87.7 \n", + " 60-64 89.1 \n", + " 65-69 87.5 \n", + " 70-74 88.7 \n", + " 75-79 89.2 \n", + " 80-84 87.3 \n", + " 85-89 90.6 \n", + " 90+ 83.3 \n", + "ethnicity_6_groups Black 89.7 \n", + " Mixed 88.2 \n", + " Other 88.7 \n", + " South Asian 88.4 \n", + " Unknown 88.4 \n", + " White 89.2 \n", + "ethnicity_16_groups African 90.2 \n", + " Bangladeshi or British Bangladeshi 88.0 \n", + " Caribbean 90.6 \n", + " Chinese 88.5 \n", + " Other 86.8 \n", " Other Asian 88.5 \n", - " British or Mixed British 85.2 \n", - " Indian or British Indian 85.2 \n", - " Irish 87.5 \n", + " British or Mixed British 85.7 \n", + " Indian or British Indian 88.7 \n", + " Irish 86.5 \n", " Other Black 88.5 \n", - " Other White 85.7 \n", - " Other mixed 88.9 \n", - " Pakistani or British Pakistani 92.3 \n", - " Unknown 87.5 \n", - " White + Asian 86.2 \n", - " White + Black African 88.5 \n", - " White + Black Caribbean 88.0 \n", - "imd_categories 1 Most deprived 88.0 \n", - " 2 87.8 \n", - " 3 90.8 \n", - " 4 88.3 \n", - " 5 Least deprived 86.4 \n", - " Unknown 85.2 \n", - "bmi 30+ 89.1 \n", - " under 30 87.7 \n", - "housebound no 88.0 \n", + " Other White 90.4 \n", + " Other mixed 88.0 \n", + " Pakistani or British Pakistani 89.4 \n", + " Unknown 89.0 \n", + " White + Asian 89.1 \n", + " White + Black African 87.5 \n", + " White + Black Caribbean 87.7 \n", + "imd_categories 1 Most deprived 88.7 \n", + " 2 88.0 \n", + " 3 89.6 \n", + " 4 89.4 \n", + " 5 Least deprived 88.0 \n", + " Unknown 89.4 \n", + "bmi 30+ 88.1 \n", + " under 30 89.0 \n", + "housebound no 88.6 \n", " yes 100.0 \n", - "chronic_cardiac_disease no 88.0 \n", + "chronic_cardiac_disease no 88.7 \n", + " yes 88.9 \n", + "current_copd no 88.6 \n", + " yes 91.7 \n", + "dmards no 88.6 \n", " yes 100.0 \n", - "current_copd no 88.0 \n", - " yes 83.3 \n", - "dmards no 88.2 \n", - " yes 80.0 \n", - "dementia no 88.0 \n", - " yes 83.3 \n", - "psychosis_schiz_bipolar no 88.0 \n", - " yes 83.3 \n", - "LD no 87.9 \n", + "dementia no 88.6 \n", " yes 90.9 \n", - "ssri no 88.2 \n", - " yes 75.0 \n", - "chemo_or_radio no 88.0 \n", - " yes 80.0 \n", - "lung_cancer no 88.0 \n", - " yes 80.0 \n", - "cancer_excl_lung_and_haem no 88.0 \n", - " yes 100.0 \n", - "haematological_cancer no 88.0 \n", - " yes 100.0 \n", + "psychosis_schiz_bipolar no 88.7 \n", + " yes 90.0 \n", + "LD no 88.7 \n", + " yes 89.5 \n", + "ssri no 88.7 \n", + " yes 90.0 \n", + "chemo_or_radio no 88.7 \n", + " yes 90.0 \n", + "lung_cancer no 88.7 \n", + " yes 88.9 \n", + "cancer_excl_lung_and_haem no 88.7 \n", + " yes 90.0 \n", + "haematological_cancer no 88.6 \n", + " yes 90.0 \n", "ckd no 88.5 \n", - " yes 85.7 \n", + " yes 89.3 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 2.0 \n", + "overall overall 1.5 \n", "sex F 1.6 \n", - " M 2.4 \n", - "ageband_5yr 0 0.0 \n", - " 0-15 0.0 \n", - " 16-17 5.3 \n", - " 18-29 3.0 \n", - " 30-34 2.7 \n", - " 35-39 0.0 \n", - " 40-44 3.3 \n", + " M 1.5 \n", + "ageband_5yr 0 8.4 \n", + " 0-15 3.3 \n", + " 16-17 1.5 \n", + " 18-29 1.6 \n", + " 30-34 3.0 \n", + " 35-39 1.5 \n", + " 40-44 1.6 \n", " 45-49 0.0 \n", - " 50-54 0.0 \n", - " 55-59 0.0 \n", - " 60-64 0.0 \n", - " 65-69 0.0 \n", - " 70-74 3.6 \n", - " 75-79 2.9 \n", - " 80-84 3.0 \n", - " 85-89 0.0 \n", + " 50-54 1.6 \n", + " 55-59 1.5 \n", + " 60-64 1.5 \n", + " 65-69 1.6 \n", + " 70-74 1.6 \n", + " 75-79 0.0 \n", + " 80-84 1.6 \n", + " 85-89 1.6 \n", " 90+ 0.0 \n", - "ethnicity_6_groups Black 2.3 \n", - " Mixed 1.2 \n", + "ethnicity_6_groups Black 1.2 \n", + " Mixed 1.8 \n", " Other 1.2 \n", - " South Asian 2.5 \n", + " South Asian 1.1 \n", " Unknown 1.4 \n", - " White 2.3 \n", - "ethnicity_16_groups African 3.4 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", + " White 1.9 \n", + "ethnicity_16_groups African 2.0 \n", + " Bangladeshi or British Bangladeshi 2.0 \n", + " Caribbean 1.9 \n", " Chinese 0.0 \n", - " Other 4.1 \n", - " Other Asian 0.0 \n", - " British or Mixed British 3.7 \n", - " Indian or British Indian 3.7 \n", - " Irish 0.0 \n", - " Other Black 3.8 \n", + " Other 1.9 \n", + " Other Asian 3.8 \n", + " British or Mixed British 4.1 \n", + " Indian or British Indian 1.9 \n", + " Irish 3.9 \n", + " Other Black 1.9 \n", " Other White 0.0 \n", - " Other mixed 0.0 \n", + " Other mixed 2.0 \n", " Pakistani or British Pakistani 0.0 \n", - " Unknown 2.5 \n", - " White + Asian 0.0 \n", - " White + Black African 3.8 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 2.2 \n", - " 2 2.0 \n", - " 3 1.0 \n", - " 4 2.1 \n", - " 5 Least deprived 2.2 \n", - " Unknown 3.7 \n", - "bmi 30+ 1.9 \n", - " under 30 2.0 \n", - "housebound no 2.1 \n", - " yes 0.0 \n", - "chronic_cardiac_disease no 2.1 \n", - " yes 0.0 \n", - "current_copd no 2.0 \n", + " Unknown 1.3 \n", + " White + Asian 1.8 \n", + " White + Black African 1.8 \n", + " White + Black Caribbean 1.8 \n", + "imd_categories 1 Most deprived 1.1 \n", + " 2 2.6 \n", + " 3 1.1 \n", + " 4 1.0 \n", + " 5 Least deprived 1.6 \n", + " Unknown 2.1 \n", + "bmi 30+ 1.7 \n", + " under 30 1.5 \n", + "housebound no 1.6 \n", " yes 0.0 \n", - "dmards no 1.8 \n", + "chronic_cardiac_disease no 1.5 \n", " yes 0.0 \n", - "dementia no 2.0 \n", + "current_copd no 1.6 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.8 \n", + "dmards no 1.5 \n", " yes 0.0 \n", - "LD no 2.0 \n", + "dementia no 1.7 \n", " yes 0.0 \n", - "ssri no 1.9 \n", + "psychosis_schiz_bipolar no 1.5 \n", " yes 0.0 \n", - "chemo_or_radio no 1.9 \n", + "LD no 1.4 \n", + " yes 5.2 \n", + "ssri no 1.5 \n", " yes 0.0 \n", - "lung_cancer no 2.0 \n", + "chemo_or_radio no 1.5 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 2.0 \n", + "lung_cancer no 1.5 \n", " yes 0.0 \n", - "haematological_cancer no 2.0 \n", + "cancer_excl_lung_and_haem no 1.5 \n", " yes 0.0 \n", - "ckd no 2.1 \n", - " yes 2.9 \n", + "haematological_cancer no 1.6 \n", + " yes 10.0 \n", + "ckd no 1.5 \n", + " yes 1.6 \n", "\n", " Date projected to reach 90% \n", "category group \n", "overall overall reached \n", "sex F reached \n", - " M 15-Dec \n", - "ageband_5yr 0 unknown \n", - " 0-15 unknown \n", - " 16-17 15-Dec \n", + " M 04-Feb \n", + "ageband_5yr 0 reached \n", + " 0-15 reached \n", + " 16-17 05-Feb \n", " 18-29 reached \n", - " 30-34 reached \n", - " 35-39 unknown \n", - " 40-44 reached \n", + " 30-34 02-Feb \n", + " 35-39 04-Feb \n", + " 40-44 07-Feb \n", " 45-49 reached \n", - " 50-54 unknown \n", - " 55-59 unknown \n", - " 60-64 unknown \n", - " 65-69 reached \n", + " 50-54 reached \n", + " 55-59 05-Feb \n", + " 60-64 reached \n", + " 65-69 05-Feb \n", " 70-74 reached \n", - " 75-79 19-Dec \n", - " 80-84 reached \n", + " 75-79 unknown \n", + " 80-84 06-Feb \n", " 85-89 reached \n", - " 90+ reached \n", + " 90+ unknown \n", "ethnicity_6_groups Black reached \n", - " Mixed 16-Dec \n", - " Other 20-Dec \n", - " South Asian reached \n", - " Unknown 27-Dec \n", - " White 15-Dec \n", + " Mixed reached \n", + " Other 02-Feb \n", + " South Asian 05-Feb \n", + " Unknown 03-Feb \n", + " White reached \n", "ethnicity_16_groups African reached \n", - " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean unknown \n", - " Chinese reached \n", - " Other reached \n", - " Other Asian unknown \n", - " British or Mixed British 17-Dec \n", - " Indian or British Indian 17-Dec \n", - " Irish unknown \n", + " Bangladeshi or British Bangladeshi reached \n", + " Caribbean reached \n", + " Chinese unknown \n", + " Other 06-Feb \n", + " Other Asian reached \n", + " British or Mixed British 02-Feb \n", + " Indian or British Indian reached \n", + " Irish reached \n", " Other Black reached \n", - " Other White unknown \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani reached \n", + " Other White reached \n", + " Other mixed reached \n", + " Pakistani or British Pakistani unknown \n", " Unknown reached \n", - " White + Asian unknown \n", - " White + Black African reached \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived reached \n", - " 2 15-Dec \n", + " White + Asian reached \n", + " White + Black African 04-Feb \n", + " White + Black Caribbean 03-Feb \n", + "imd_categories 1 Most deprived 03-Feb \n", + " 2 reached \n", " 3 reached \n", " 4 reached \n", - " 5 Least deprived 19-Dec \n", - " Unknown 17-Dec \n", - "bmi 30+ reached \n", - " under 30 16-Dec \n", + " 5 Least deprived 03-Feb \n", + " Unknown reached \n", + "bmi 30+ 02-Feb \n", + " under 30 reached \n", "housebound no reached \n", " yes reached \n", "chronic_cardiac_disease no reached \n", - " yes reached \n", - "current_copd no reached \n", " yes unknown \n", + "current_copd no reached \n", + " yes reached \n", "dmards no reached \n", - " yes unknown \n", + " yes reached \n", "dementia no reached \n", + " yes reached \n", + "psychosis_schiz_bipolar no reached \n", " yes unknown \n", - "psychosis_schiz_bipolar no 15-Dec \n", - " yes unknown \n", - "LD no 15-Dec \n", + "LD no reached \n", " yes reached \n", "ssri no reached \n", " yes unknown \n", - "chemo_or_radio no 15-Dec \n", + "chemo_or_radio no reached \n", " yes unknown \n", "lung_cancer no reached \n", " yes unknown \n", "cancer_excl_lung_and_haem no reached \n", - " yes reached \n", + " yes unknown \n", "haematological_cancer no reached \n", " yes reached \n", "ckd no reached \n", - " yes 18-Dec " + " yes reached " ] }, "metadata": {}, @@ -3207,7 +3259,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **care home** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **care home** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -3273,182 +3325,182 @@ " \n", " overall\n", " overall\n", - " 1253\n", - " 89.9\n", - " 1393\n", - " 88.9\n", - " 1.0\n", - " 15-Dec\n", + " 2534\n", + " 89.8\n", + " 2821\n", + " 88.3\n", + " 1.5\n", + " 02-Feb\n", " \n", " \n", " sex\n", " F\n", - " 651\n", - " 90.3\n", - " 721\n", - " 89.3\n", - " 1.0\n", - " reached\n", + " 1274\n", + " 89.2\n", + " 1428\n", + " 87.7\n", + " 1.5\n", + " 05-Feb\n", " \n", " \n", " M\n", - " 602\n", - " 89.6\n", - " 672\n", - " 88.5\n", - " 1.1\n", - " 17-Dec\n", + " 1260\n", + " 90.9\n", + " 1386\n", + " 89.4\n", + " 1.5\n", + " reached\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 14\n", - " 100.0\n", - " 14\n", + " 28\n", " 100.0\n", - " 0.0\n", + " 28\n", + " 75.0\n", + " 25.0\n", " reached\n", " \n", " \n", " 0-15\n", - " 84\n", - " 92.3\n", - " 91\n", - " 84.6\n", - " 7.7\n", + " 161\n", + " 92.0\n", + " 175\n", + " 92.0\n", + " 0.0\n", " reached\n", " \n", " \n", " 16-17\n", - " 84\n", - " 85.7\n", - " 98\n", + " 175\n", + " 89.3\n", + " 196\n", " 85.7\n", - " 0.0\n", - " unknown\n", + " 3.6\n", + " 03-Feb\n", " \n", " \n", " 18-29\n", - " 70\n", - " 83.3\n", - " 84\n", - " 83.3\n", + " 154\n", + " 91.7\n", + " 168\n", + " 91.7\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " 30-34\n", - " 70\n", - " 83.3\n", - " 84\n", - " 83.3\n", - " 0.0\n", - " unknown\n", + " 175\n", + " 92.6\n", + " 189\n", + " 88.9\n", + " 3.7\n", + " reached\n", " \n", " \n", " 35-39\n", - " 84\n", - " 85.7\n", - " 98\n", - " 85.7\n", + " 161\n", + " 85.2\n", + " 189\n", + " 85.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 40-44\n", - " 91\n", - " 92.9\n", - " 98\n", - " 85.7\n", - " 7.2\n", - " reached\n", + " 140\n", + " 83.3\n", + " 168\n", + " 83.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 45-49\n", - " 84\n", - " 92.3\n", - " 91\n", - " 84.6\n", - " 7.7\n", - " reached\n", + " 161\n", + " 88.5\n", + " 182\n", + " 88.5\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 50-54\n", - " 77\n", - " 91.7\n", - " 84\n", - " 91.7\n", - " 0.0\n", + " 168\n", + " 92.3\n", + " 182\n", + " 88.5\n", + " 3.8\n", " reached\n", " \n", " \n", " 55-59\n", - " 84\n", - " 92.3\n", - " 91\n", - " 92.3\n", + " 175\n", + " 89.3\n", + " 196\n", + " 89.3\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " 60-64\n", - " 77\n", - " 84.6\n", - " 91\n", - " 84.6\n", - " 0.0\n", - " unknown\n", + " 182\n", + " 92.9\n", + " 196\n", + " 89.3\n", + " 3.6\n", + " reached\n", " \n", " \n", " 65-69\n", - " 84\n", - " 100.0\n", - " 84\n", - " 100.0\n", + " 161\n", + " 88.5\n", + " 182\n", + " 88.5\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " 70-74\n", - " 98\n", - " 93.3\n", - " 105\n", - " 86.7\n", - " 6.6\n", - " reached\n", + " 168\n", + " 88.9\n", + " 189\n", + " 88.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 75-79\n", - " 84\n", - " 92.3\n", - " 91\n", - " 92.3\n", - " 0.0\n", - " reached\n", + " 154\n", + " 88.0\n", + " 175\n", + " 84.0\n", + " 4.0\n", + " 05-Feb\n", " \n", " \n", " 80-84\n", - " 70\n", - " 90.9\n", - " 77\n", - " 90.9\n", + " 161\n", + " 88.5\n", + " 182\n", + " 88.5\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " 85-89\n", - " 84\n", - " 85.7\n", - " 98\n", - " 85.7\n", + " 161\n", + " 92.0\n", + " 175\n", + " 92.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " 90+\n", - " 14\n", + " 49\n", " 100.0\n", - " 14\n", + " 49\n", " 100.0\n", " 0.0\n", " reached\n", @@ -3456,73 +3508,73 @@ " \n", " ethnicity_6_groups\n", " Black\n", - " 210\n", - " 93.8\n", - " 224\n", - " 90.6\n", + " 399\n", + " 89.1\n", + " 448\n", + " 85.9\n", " 3.2\n", - " reached\n", + " 03-Feb\n", " \n", " \n", " Mixed\n", - " 224\n", - " 88.9\n", - " 252\n", - " 88.9\n", - " 0.0\n", - " unknown\n", + " 427\n", + " 92.4\n", + " 462\n", + " 90.9\n", + " 1.5\n", + " reached\n", " \n", " \n", " Other\n", - " 189\n", - " 90.0\n", - " 210\n", - " 90.0\n", - " 0.0\n", - " unknown\n", + " 455\n", + " 90.3\n", + " 504\n", + " 88.9\n", + " 1.4\n", + " reached\n", " \n", " \n", " South Asian\n", - " 238\n", - " 89.5\n", - " 266\n", - " 89.5\n", - " 0.0\n", - " unknown\n", + " 434\n", + " 92.5\n", + " 469\n", + " 89.6\n", + " 2.9\n", + " reached\n", " \n", " \n", " Unknown\n", - " 189\n", - " 90.0\n", - " 210\n", - " 90.0\n", - " 0.0\n", - " unknown\n", + " 392\n", + " 90.3\n", + " 434\n", + " 88.7\n", + " 1.6\n", + " reached\n", " \n", " \n", " White\n", - " 203\n", - " 87.9\n", - " 231\n", - " 87.9\n", - " 0.0\n", - " unknown\n", + " 434\n", + " 88.6\n", + " 490\n", + " 87.1\n", + " 1.5\n", + " 08-Feb\n", " \n", " \n", " dementia\n", " no\n", - " 1246\n", - " 90.4\n", - " 1379\n", - " 89.3\n", - " 1.1\n", + " 2513\n", + " 90.0\n", + " 2793\n", + " 88.2\n", + " 1.8\n", " reached\n", " \n", " \n", " yes\n", - " 14\n", + " 28\n", " 100.0\n", - " 14\n", + " 28\n", " 100.0\n", " 0.0\n", " reached\n", @@ -3534,125 +3586,125 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 1253 89.9 1393 \n", - "sex F 651 90.3 721 \n", - " M 602 89.6 672 \n", - "ageband_5yr 0 14 100.0 14 \n", - " 0-15 84 92.3 91 \n", - " 16-17 84 85.7 98 \n", - " 18-29 70 83.3 84 \n", - " 30-34 70 83.3 84 \n", - " 35-39 84 85.7 98 \n", - " 40-44 91 92.9 98 \n", - " 45-49 84 92.3 91 \n", - " 50-54 77 91.7 84 \n", - " 55-59 84 92.3 91 \n", - " 60-64 77 84.6 91 \n", - " 65-69 84 100.0 84 \n", - " 70-74 98 93.3 105 \n", - " 75-79 84 92.3 91 \n", - " 80-84 70 90.9 77 \n", - " 85-89 84 85.7 98 \n", - " 90+ 14 100.0 14 \n", - "ethnicity_6_groups Black 210 93.8 224 \n", - " Mixed 224 88.9 252 \n", - " Other 189 90.0 210 \n", - " South Asian 238 89.5 266 \n", - " Unknown 189 90.0 210 \n", - " White 203 87.9 231 \n", - "dementia no 1246 90.4 1379 \n", - " yes 14 100.0 14 \n", + "overall overall 2534 89.8 2821 \n", + "sex F 1274 89.2 1428 \n", + " M 1260 90.9 1386 \n", + "ageband_5yr 0 28 100.0 28 \n", + " 0-15 161 92.0 175 \n", + " 16-17 175 89.3 196 \n", + " 18-29 154 91.7 168 \n", + " 30-34 175 92.6 189 \n", + " 35-39 161 85.2 189 \n", + " 40-44 140 83.3 168 \n", + " 45-49 161 88.5 182 \n", + " 50-54 168 92.3 182 \n", + " 55-59 175 89.3 196 \n", + " 60-64 182 92.9 196 \n", + " 65-69 161 88.5 182 \n", + " 70-74 168 88.9 189 \n", + " 75-79 154 88.0 175 \n", + " 80-84 161 88.5 182 \n", + " 85-89 161 92.0 175 \n", + " 90+ 49 100.0 49 \n", + "ethnicity_6_groups Black 399 89.1 448 \n", + " Mixed 427 92.4 462 \n", + " Other 455 90.3 504 \n", + " South Asian 434 92.5 469 \n", + " Unknown 392 90.3 434 \n", + " White 434 88.6 490 \n", + "dementia no 2513 90.0 2793 \n", + " yes 28 100.0 28 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.9 \n", - "sex F 89.3 \n", - " M 88.5 \n", - "ageband_5yr 0 100.0 \n", - " 0-15 84.6 \n", + "overall overall 88.3 \n", + "sex F 87.7 \n", + " M 89.4 \n", + "ageband_5yr 0 75.0 \n", + " 0-15 92.0 \n", " 16-17 85.7 \n", - " 18-29 83.3 \n", - " 30-34 83.3 \n", - " 35-39 85.7 \n", - " 40-44 85.7 \n", - " 45-49 84.6 \n", - " 50-54 91.7 \n", - " 55-59 92.3 \n", - " 60-64 84.6 \n", - " 65-69 100.0 \n", - " 70-74 86.7 \n", - " 75-79 92.3 \n", - " 80-84 90.9 \n", - " 85-89 85.7 \n", + " 18-29 91.7 \n", + " 30-34 88.9 \n", + " 35-39 85.2 \n", + " 40-44 83.3 \n", + " 45-49 88.5 \n", + " 50-54 88.5 \n", + " 55-59 89.3 \n", + " 60-64 89.3 \n", + " 65-69 88.5 \n", + " 70-74 88.9 \n", + " 75-79 84.0 \n", + " 80-84 88.5 \n", + " 85-89 92.0 \n", " 90+ 100.0 \n", - "ethnicity_6_groups Black 90.6 \n", - " Mixed 88.9 \n", - " Other 90.0 \n", - " South Asian 89.5 \n", - " Unknown 90.0 \n", - " White 87.9 \n", - "dementia no 89.3 \n", + "ethnicity_6_groups Black 85.9 \n", + " Mixed 90.9 \n", + " Other 88.9 \n", + " South Asian 89.6 \n", + " Unknown 88.7 \n", + " White 87.1 \n", + "dementia no 88.2 \n", " yes 100.0 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.0 \n", - "sex F 1.0 \n", - " M 1.1 \n", - "ageband_5yr 0 0.0 \n", - " 0-15 7.7 \n", - " 16-17 0.0 \n", + "overall overall 1.5 \n", + "sex F 1.5 \n", + " M 1.5 \n", + "ageband_5yr 0 25.0 \n", + " 0-15 0.0 \n", + " 16-17 3.6 \n", " 18-29 0.0 \n", - " 30-34 0.0 \n", + " 30-34 3.7 \n", " 35-39 0.0 \n", - " 40-44 7.2 \n", - " 45-49 7.7 \n", - " 50-54 0.0 \n", + " 40-44 0.0 \n", + " 45-49 0.0 \n", + " 50-54 3.8 \n", " 55-59 0.0 \n", - " 60-64 0.0 \n", + " 60-64 3.6 \n", " 65-69 0.0 \n", - " 70-74 6.6 \n", - " 75-79 0.0 \n", + " 70-74 0.0 \n", + " 75-79 4.0 \n", " 80-84 0.0 \n", " 85-89 0.0 \n", " 90+ 0.0 \n", "ethnicity_6_groups Black 3.2 \n", - " Mixed 0.0 \n", - " Other 0.0 \n", - " South Asian 0.0 \n", - " Unknown 0.0 \n", - " White 0.0 \n", - "dementia no 1.1 \n", + " Mixed 1.5 \n", + " Other 1.4 \n", + " South Asian 2.9 \n", + " Unknown 1.6 \n", + " White 1.5 \n", + "dementia no 1.8 \n", " yes 0.0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 15-Dec \n", - "sex F reached \n", - " M 17-Dec \n", + "overall overall 02-Feb \n", + "sex F 05-Feb \n", + " M reached \n", "ageband_5yr 0 reached \n", " 0-15 reached \n", - " 16-17 unknown \n", - " 18-29 unknown \n", - " 30-34 unknown \n", + " 16-17 03-Feb \n", + " 18-29 reached \n", + " 30-34 reached \n", " 35-39 unknown \n", - " 40-44 reached \n", - " 45-49 reached \n", + " 40-44 unknown \n", + " 45-49 unknown \n", " 50-54 reached \n", - " 55-59 reached \n", - " 60-64 unknown \n", - " 65-69 reached \n", - " 70-74 reached \n", - " 75-79 reached \n", - " 80-84 reached \n", - " 85-89 unknown \n", + " 55-59 unknown \n", + " 60-64 reached \n", + " 65-69 unknown \n", + " 70-74 unknown \n", + " 75-79 05-Feb \n", + " 80-84 unknown \n", + " 85-89 reached \n", " 90+ reached \n", - "ethnicity_6_groups Black reached \n", - " Mixed unknown \n", - " Other unknown \n", - " South Asian unknown \n", - " Unknown unknown \n", - " White unknown \n", + "ethnicity_6_groups Black 03-Feb \n", + " Mixed reached \n", + " Other reached \n", + " South Asian reached \n", + " Unknown reached \n", + " White 08-Feb \n", "dementia no reached \n", " yes reached " ] @@ -3683,7 +3735,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **shielding (aged 16-69)** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **shielding (aged 16-69)** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -3749,262 +3801,262 @@ " \n", " overall\n", " overall\n", - " 371\n", - " 88.3\n", - " 420\n", - " 86.7\n", - " 1.6\n", - " 22-Dec\n", + " 777\n", + " 89.5\n", + " 868\n", + " 88.7\n", + " 0.8\n", + " 06-Feb\n", " \n", " \n", " newly_shielded_since_feb_15\n", " no\n", - " 364\n", - " 88.1\n", - " 413\n", - " 86.4\n", - " 1.7\n", - " 22-Dec\n", + " 770\n", + " 89.4\n", + " 861\n", + " 87.8\n", + " 1.6\n", + " 04-Feb\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 100.0\n", + " 7\n", + " 100.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " sex\n", " F\n", - " 196\n", - " 90.3\n", - " 217\n", - " 87.1\n", - " 3.2\n", + " 406\n", + " 90.6\n", + " 448\n", + " 89.1\n", + " 1.5\n", " reached\n", " \n", " \n", " M\n", - " 175\n", - " 86.2\n", - " 203\n", - " 82.8\n", - " 3.4\n", - " 22-Dec\n", + " 371\n", + " 88.3\n", + " 420\n", + " 88.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " ageband\n", " 16-29\n", - " 49\n", - " 87.5\n", - " 56\n", - " 87.5\n", - " 0.0\n", - " unknown\n", + " 98\n", + " 93.3\n", + " 105\n", + " 86.7\n", + " 6.6\n", + " reached\n", " \n", " \n", " 30-39\n", - " 49\n", - " 87.5\n", - " 56\n", - " 75.0\n", - " 12.5\n", - " 16-Dec\n", + " 91\n", + " 86.7\n", + " 105\n", + " 86.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 40-49\n", - " 35\n", - " 71.4\n", - " 49\n", - " 71.4\n", + " 98\n", + " 87.5\n", + " 112\n", + " 87.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 50-59\n", - " 63\n", - " 90.0\n", - " 70\n", - " 90.0\n", + " 105\n", + " 83.3\n", + " 126\n", + " 83.3\n", " 0.0\n", " unknown\n", " \n", " \n", " 60-69\n", - " 49\n", - " 100.0\n", - " 49\n", - " 100.0\n", - " 0.0\n", - " reached\n", + " 98\n", + " 87.5\n", + " 112\n", + " 81.2\n", + " 6.3\n", + " 04-Feb\n", " \n", " \n", " 70-79\n", - " 84\n", - " 92.3\n", - " 91\n", - " 84.6\n", - " 7.7\n", - " reached\n", + " 182\n", + " 89.7\n", + " 203\n", + " 89.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 80+\n", - " 42\n", - " 85.7\n", - " 49\n", - " 85.7\n", + " 105\n", + " 93.8\n", + " 112\n", + " 93.8\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 63\n", + " 126\n", " 90.0\n", - " 70\n", + " 140\n", " 90.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Mixed\n", - " 56\n", - " 80.0\n", - " 70\n", - " 80.0\n", - " 0.0\n", - " unknown\n", + " 147\n", + " 91.3\n", + " 161\n", + " 87.0\n", + " 4.3\n", + " reached\n", " \n", " \n", " Other\n", - " 63\n", + " 126\n", " 90.0\n", - " 70\n", + " 140\n", " 90.0\n", " 0.0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 56\n", - " 88.9\n", - " 63\n", - " 88.9\n", + " 126\n", + " 85.7\n", + " 147\n", + " 85.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 49\n", - " 87.5\n", - " 56\n", - " 87.5\n", + " 105\n", + " 88.2\n", + " 119\n", + " 88.2\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", - " 77\n", - " 84.6\n", - " 91\n", - " 84.6\n", + " 147\n", + " 91.3\n", + " 161\n", + " 91.3\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 70\n", - " 83.3\n", - " 84\n", - " 83.3\n", - " 0.0\n", - " unknown\n", + " 161\n", + " 88.5\n", + " 182\n", + " 84.6\n", + " 3.9\n", + " 04-Feb\n", " \n", " \n", " 2\n", - " 56\n", - " 80.0\n", - " 70\n", - " 80.0\n", + " 126\n", + " 85.7\n", + " 147\n", + " 85.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 3\n", - " 77\n", - " 91.7\n", - " 84\n", - " 83.3\n", - " 8.4\n", - " reached\n", + " 147\n", + " 87.5\n", + " 168\n", + " 87.5\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 4\n", - " 77\n", - " 91.7\n", - " 84\n", - " 91.7\n", + " 147\n", + " 91.3\n", + " 161\n", + " 91.3\n", " 0.0\n", " reached\n", " \n", " \n", " 5 Least deprived\n", - " 70\n", - " 90.9\n", - " 77\n", - " 90.9\n", + " 154\n", + " 91.7\n", + " 168\n", + " 91.7\n", " 0.0\n", " reached\n", " \n", " \n", " Unknown\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 83.3\n", + " 42\n", + " 83.3\n", " 0.0\n", " unknown\n", " \n", " \n", " LD\n", " no\n", - " 364\n", - " 88.1\n", - " 413\n", - " 86.4\n", - " 1.7\n", - " 22-Dec\n", + " 763\n", + " 89.3\n", + " 854\n", + " 88.5\n", + " 0.8\n", + " 08-Feb\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", + " 14\n", + " 100.0\n", + " 14\n", + " 100.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " ckd\n", " no\n", - " 280\n", - " 87.0\n", - " 322\n", - " 87.0\n", - " 0.0\n", - " unknown\n", + " 644\n", + " 89.3\n", + " 721\n", + " 88.3\n", + " 1.0\n", + " 06-Feb\n", " \n", " \n", " yes\n", - " 84\n", - " 85.7\n", - " 98\n", + " 133\n", + " 90.5\n", + " 147\n", " 85.7\n", - " 0.0\n", - " unknown\n", + " 4.8\n", + " reached\n", " \n", " \n", "\n", @@ -4013,127 +4065,127 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 371 88.3 420 \n", - "newly_shielded_since_feb_15 no 364 88.1 413 \n", - " yes 0 0.0 0 \n", - "sex F 196 90.3 217 \n", - " M 175 86.2 203 \n", - "ageband 16-29 49 87.5 56 \n", - " 30-39 49 87.5 56 \n", - " 40-49 35 71.4 49 \n", - " 50-59 63 90.0 70 \n", - " 60-69 49 100.0 49 \n", - " 70-79 84 92.3 91 \n", - " 80+ 42 85.7 49 \n", - "ethnicity_6_groups Black 63 90.0 70 \n", - " Mixed 56 80.0 70 \n", - " Other 63 90.0 70 \n", - " South Asian 56 88.9 63 \n", - " Unknown 49 87.5 56 \n", - " White 77 84.6 91 \n", - "imd_categories 1 Most deprived 70 83.3 84 \n", - " 2 56 80.0 70 \n", - " 3 77 91.7 84 \n", - " 4 77 91.7 84 \n", - " 5 Least deprived 70 90.9 77 \n", - " Unknown 14 66.7 21 \n", - "LD no 364 88.1 413 \n", - " yes 0 0.0 0 \n", - "ckd no 280 87.0 322 \n", - " yes 84 85.7 98 \n", + "overall overall 777 89.5 868 \n", + "newly_shielded_since_feb_15 no 770 89.4 861 \n", + " yes 7 100.0 7 \n", + "sex F 406 90.6 448 \n", + " M 371 88.3 420 \n", + "ageband 16-29 98 93.3 105 \n", + " 30-39 91 86.7 105 \n", + " 40-49 98 87.5 112 \n", + " 50-59 105 83.3 126 \n", + " 60-69 98 87.5 112 \n", + " 70-79 182 89.7 203 \n", + " 80+ 105 93.8 112 \n", + "ethnicity_6_groups Black 126 90.0 140 \n", + " Mixed 147 91.3 161 \n", + " Other 126 90.0 140 \n", + " South Asian 126 85.7 147 \n", + " Unknown 105 88.2 119 \n", + " White 147 91.3 161 \n", + "imd_categories 1 Most deprived 161 88.5 182 \n", + " 2 126 85.7 147 \n", + " 3 147 87.5 168 \n", + " 4 147 91.3 161 \n", + " 5 Least deprived 154 91.7 168 \n", + " Unknown 35 83.3 42 \n", + "LD no 763 89.3 854 \n", + " yes 14 100.0 14 \n", + "ckd no 644 89.3 721 \n", + " yes 133 90.5 147 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 86.7 \n", - "newly_shielded_since_feb_15 no 86.4 \n", - " yes NaN \n", - "sex F 87.1 \n", - " M 82.8 \n", - "ageband 16-29 87.5 \n", - " 30-39 75.0 \n", - " 40-49 71.4 \n", - " 50-59 90.0 \n", - " 60-69 100.0 \n", - " 70-79 84.6 \n", - " 80+ 85.7 \n", + "overall overall 88.7 \n", + "newly_shielded_since_feb_15 no 87.8 \n", + " yes 100.0 \n", + "sex F 89.1 \n", + " M 88.3 \n", + "ageband 16-29 86.7 \n", + " 30-39 86.7 \n", + " 40-49 87.5 \n", + " 50-59 83.3 \n", + " 60-69 81.2 \n", + " 70-79 89.7 \n", + " 80+ 93.8 \n", "ethnicity_6_groups Black 90.0 \n", - " Mixed 80.0 \n", + " Mixed 87.0 \n", " Other 90.0 \n", - " South Asian 88.9 \n", - " Unknown 87.5 \n", - " White 84.6 \n", - "imd_categories 1 Most deprived 83.3 \n", - " 2 80.0 \n", - " 3 83.3 \n", - " 4 91.7 \n", - " 5 Least deprived 90.9 \n", - " Unknown 66.7 \n", - "LD no 86.4 \n", - " yes NaN \n", - "ckd no 87.0 \n", + " South Asian 85.7 \n", + " Unknown 88.2 \n", + " White 91.3 \n", + "imd_categories 1 Most deprived 84.6 \n", + " 2 85.7 \n", + " 3 87.5 \n", + " 4 91.3 \n", + " 5 Least deprived 91.7 \n", + " Unknown 83.3 \n", + "LD no 88.5 \n", + " yes 100.0 \n", + "ckd no 88.3 \n", " yes 85.7 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.6 \n", - "newly_shielded_since_feb_15 no 1.7 \n", + "overall overall 0.8 \n", + "newly_shielded_since_feb_15 no 1.6 \n", " yes 0.0 \n", - "sex F 3.2 \n", - " M 3.4 \n", - "ageband 16-29 0.0 \n", - " 30-39 12.5 \n", + "sex F 1.5 \n", + " M 0.0 \n", + "ageband 16-29 6.6 \n", + " 30-39 0.0 \n", " 40-49 0.0 \n", " 50-59 0.0 \n", - " 60-69 0.0 \n", - " 70-79 7.7 \n", + " 60-69 6.3 \n", + " 70-79 0.0 \n", " 80+ 0.0 \n", "ethnicity_6_groups Black 0.0 \n", - " Mixed 0.0 \n", + " Mixed 4.3 \n", " Other 0.0 \n", " South Asian 0.0 \n", " Unknown 0.0 \n", " White 0.0 \n", - "imd_categories 1 Most deprived 0.0 \n", + "imd_categories 1 Most deprived 3.9 \n", " 2 0.0 \n", - " 3 8.4 \n", + " 3 0.0 \n", " 4 0.0 \n", " 5 Least deprived 0.0 \n", " Unknown 0.0 \n", - "LD no 1.7 \n", - " yes 0.0 \n", - "ckd no 0.0 \n", + "LD no 0.8 \n", " yes 0.0 \n", + "ckd no 1.0 \n", + " yes 4.8 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 22-Dec \n", - "newly_shielded_since_feb_15 no 22-Dec \n", - " yes unknown \n", + "overall overall 06-Feb \n", + "newly_shielded_since_feb_15 no 04-Feb \n", + " yes reached \n", "sex F reached \n", - " M 22-Dec \n", - "ageband 16-29 unknown \n", - " 30-39 16-Dec \n", + " M unknown \n", + "ageband 16-29 reached \n", + " 30-39 unknown \n", " 40-49 unknown \n", " 50-59 unknown \n", - " 60-69 reached \n", - " 70-79 reached \n", - " 80+ unknown \n", + " 60-69 04-Feb \n", + " 70-79 unknown \n", + " 80+ reached \n", "ethnicity_6_groups Black unknown \n", - " Mixed unknown \n", + " Mixed reached \n", " Other unknown \n", " South Asian unknown \n", " Unknown unknown \n", - " White unknown \n", - "imd_categories 1 Most deprived unknown \n", + " White reached \n", + "imd_categories 1 Most deprived 04-Feb \n", " 2 unknown \n", - " 3 reached \n", + " 3 unknown \n", " 4 reached \n", " 5 Least deprived reached \n", " Unknown unknown \n", - "LD no 22-Dec \n", - " yes unknown \n", - "ckd no unknown \n", - " yes unknown " + "LD no 08-Feb \n", + " yes reached \n", + "ckd no 06-Feb \n", + " yes reached " ] }, "metadata": {}, @@ -4162,7 +4214,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **65-69** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **65-69** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -4228,561 +4280,561 @@ " \n", " overall\n", " overall\n", - " 1946\n", - " 89.7\n", - " 2170\n", - " 88.1\n", - " 1.6\n", - " 16-Dec\n", + " 3976\n", + " 90.0\n", + " 4417\n", + " 88.3\n", + " 1.7\n", + " reached\n", " \n", " \n", " sex\n", " F\n", - " 966\n", - " 90.2\n", - " 1071\n", - " 88.2\n", - " 2.0\n", - " reached\n", + " 1995\n", + " 89.6\n", + " 2226\n", + " 87.7\n", + " 1.9\n", + " 03-Feb\n", " \n", " \n", " M\n", - " 987\n", - " 89.8\n", - " 1099\n", - " 87.9\n", - " 1.9\n", - " 15-Dec\n", + " 1974\n", + " 90.1\n", + " 2191\n", + " 88.8\n", + " 1.3\n", + " reached\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 343\n", - " 92.5\n", - " 371\n", - " 90.6\n", + " 672\n", + " 88.9\n", + " 756\n", + " 87.0\n", " 1.9\n", - " reached\n", + " 06-Feb\n", " \n", " \n", " Mixed\n", - " 315\n", + " 693\n", " 90.0\n", - " 350\n", - " 88.0\n", - " 2.0\n", + " 770\n", + " 88.2\n", + " 1.8\n", " reached\n", " \n", " \n", " Other\n", - " 315\n", - " 90.0\n", - " 350\n", - " 90.0\n", - " 0.0\n", - " unknown\n", + " 665\n", + " 88.8\n", + " 749\n", + " 86.0\n", + " 2.8\n", + " 05-Feb\n", " \n", " \n", " South Asian\n", - " 350\n", - " 87.7\n", - " 399\n", - " 86.0\n", - " 1.7\n", - " 24-Dec\n", + " 637\n", + " 90.1\n", + " 707\n", + " 88.1\n", + " 2.0\n", + " reached\n", " \n", " \n", " Unknown\n", - " 301\n", - " 89.6\n", - " 336\n", - " 85.4\n", - " 4.2\n", - " 15-Dec\n", + " 637\n", + " 91.0\n", + " 700\n", + " 90.0\n", + " 1.0\n", + " reached\n", " \n", " \n", " White\n", - " 322\n", - " 88.5\n", - " 364\n", - " 88.5\n", - " 0.0\n", - " unknown\n", + " 672\n", + " 91.4\n", + " 735\n", + " 89.5\n", + " 1.9\n", + " reached\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 105\n", + " 210\n", " 93.8\n", - " 112\n", + " 224\n", " 93.8\n", " 0.0\n", " reached\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 105\n", - " 83.3\n", - " 126\n", - " 83.3\n", - " 0.0\n", - " unknown\n", + " 210\n", + " 90.9\n", + " 231\n", + " 87.9\n", + " 3.0\n", + " reached\n", " \n", " \n", " Caribbean\n", - " 98\n", - " 93.3\n", - " 105\n", - " 86.7\n", - " 6.6\n", + " 217\n", + " 91.2\n", + " 238\n", + " 91.2\n", + " 0.0\n", " reached\n", " \n", " \n", " Chinese\n", - " 105\n", - " 93.8\n", - " 112\n", - " 93.8\n", + " 210\n", + " 85.7\n", + " 245\n", + " 85.7\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " Other\n", - " 119\n", - " 89.5\n", - " 133\n", + " 245\n", + " 92.1\n", + " 266\n", " 89.5\n", - " 0.0\n", - " unknown\n", + " 2.6\n", + " reached\n", " \n", " \n", " Other Asian\n", - " 119\n", - " 94.4\n", - " 126\n", - " 88.9\n", - " 5.5\n", + " 196\n", + " 90.3\n", + " 217\n", + " 87.1\n", + " 3.2\n", " reached\n", " \n", " \n", " British or Mixed British\n", - " 98\n", - " 87.5\n", - " 112\n", - " 87.5\n", - " 0.0\n", - " unknown\n", + " 224\n", + " 94.1\n", + " 238\n", + " 91.2\n", + " 2.9\n", + " reached\n", " \n", " \n", " Indian or British Indian\n", - " 91\n", - " 86.7\n", - " 105\n", - " 86.7\n", - " 0.0\n", - " unknown\n", + " 224\n", + " 91.4\n", + " 245\n", + " 85.7\n", + " 5.7\n", + " reached\n", " \n", " \n", " Irish\n", - " 105\n", - " 93.8\n", - " 112\n", - " 87.5\n", - " 6.3\n", + " 210\n", + " 90.9\n", + " 231\n", + " 90.9\n", + " 0.0\n", " reached\n", " \n", " \n", " Other Black\n", - " 98\n", - " 87.5\n", - " 112\n", - " 87.5\n", - " 0.0\n", - " unknown\n", + " 217\n", + " 91.2\n", + " 238\n", + " 88.2\n", + " 3.0\n", + " reached\n", " \n", " \n", " Other White\n", - " 98\n", - " 87.5\n", - " 112\n", - " 87.5\n", - " 0.0\n", - " unknown\n", + " 210\n", + " 88.2\n", + " 238\n", + " 85.3\n", + " 2.9\n", + " 06-Feb\n", " \n", " \n", " Other mixed\n", - " 77\n", - " 84.6\n", - " 91\n", - " 84.6\n", - " 0.0\n", - " unknown\n", + " 217\n", + " 86.1\n", + " 252\n", + " 83.3\n", + " 2.8\n", + " 11-Feb\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 119\n", - " 89.5\n", - " 133\n", - " 89.5\n", - " 0.0\n", - " unknown\n", + " 217\n", + " 91.2\n", + " 238\n", + " 88.2\n", + " 3.0\n", + " reached\n", " \n", " \n", " Unknown\n", - " 287\n", - " 87.2\n", - " 329\n", - " 87.2\n", - " 0.0\n", - " unknown\n", + " 560\n", + " 89.9\n", + " 623\n", + " 88.8\n", + " 1.1\n", + " 02-Feb\n", " \n", " \n", " White + Asian\n", - " 91\n", - " 81.2\n", - " 112\n", - " 81.2\n", - " 0.0\n", - " unknown\n", + " 203\n", + " 90.6\n", + " 224\n", + " 87.5\n", + " 3.1\n", + " reached\n", " \n", " \n", " White + Black African\n", - " 105\n", - " 88.2\n", - " 119\n", - " 88.2\n", + " 182\n", + " 92.9\n", + " 196\n", + " 92.9\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " White + Black Caribbean\n", - " 112\n", - " 88.9\n", - " 126\n", - " 88.9\n", + " 231\n", + " 89.2\n", + " 259\n", + " 89.2\n", " 0.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 350\n", - " 89.3\n", - " 392\n", - " 89.3\n", - " 0.0\n", - " unknown\n", + " 735\n", + " 89.7\n", + " 819\n", + " 88.9\n", + " 0.8\n", + " 04-Feb\n", " \n", " \n", " 2\n", - " 406\n", - " 90.6\n", - " 448\n", - " 89.1\n", - " 1.5\n", - " reached\n", + " 749\n", + " 89.2\n", + " 840\n", + " 86.7\n", + " 2.5\n", + " 04-Feb\n", " \n", " \n", " 3\n", - " 371\n", - " 89.8\n", - " 413\n", - " 89.8\n", - " 0.0\n", - " unknown\n", + " 777\n", + " 91.0\n", + " 854\n", + " 89.3\n", + " 1.7\n", + " reached\n", " \n", " \n", " 4\n", - " 371\n", - " 91.4\n", - " 406\n", - " 89.7\n", + " 749\n", + " 89.2\n", + " 840\n", + " 87.5\n", " 1.7\n", - " reached\n", + " 05-Feb\n", " \n", " \n", " 5 Least deprived\n", - " 357\n", - " 87.9\n", - " 406\n", - " 84.5\n", - " 3.4\n", - " 19-Dec\n", + " 763\n", + " 90.8\n", + " 840\n", + " 89.2\n", + " 1.6\n", + " reached\n", " \n", " \n", " Unknown\n", - " 91\n", - " 86.7\n", - " 105\n", - " 86.7\n", - " 0.0\n", - " unknown\n", + " 210\n", + " 96.8\n", + " 217\n", + " 90.3\n", + " 6.5\n", + " reached\n", " \n", " \n", " bmi\n", " 30+\n", - " 539\n", - " 87.5\n", - " 616\n", - " 86.4\n", - " 1.1\n", - " 30-Dec\n", + " 1246\n", + " 91.3\n", + " 1365\n", + " 89.7\n", + " 1.6\n", + " reached\n", " \n", " \n", " under 30\n", - " 1407\n", - " 90.5\n", - " 1554\n", - " 88.7\n", - " 1.8\n", - " reached\n", + " 2723\n", + " 89.2\n", + " 3052\n", + " 87.6\n", + " 1.6\n", + " 05-Feb\n", " \n", " \n", " housebound\n", " no\n", - " 1939\n", - " 89.9\n", - " 2156\n", - " 88.3\n", + " 3927\n", + " 90.0\n", + " 4361\n", + " 88.4\n", " 1.6\n", - " 15-Dec\n", + " reached\n", " \n", " \n", " yes\n", - " 14\n", - " 100.0\n", - " 14\n", + " 49\n", " 100.0\n", - " 0.0\n", + " 49\n", + " 85.7\n", + " 14.3\n", " reached\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1918\n", - " 89.8\n", - " 2135\n", - " 87.9\n", - " 1.9\n", - " 15-Dec\n", + " 3934\n", + " 90.1\n", + " 4368\n", + " 88.3\n", + " 1.8\n", + " reached\n", " \n", " \n", " yes\n", - " 35\n", - " 100.0\n", - " 35\n", - " 100.0\n", + " 42\n", + " 85.7\n", + " 49\n", + " 85.7\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1932\n", - " 89.9\n", - " 2149\n", + " 3941\n", + " 90.1\n", + " 4375\n", " 88.3\n", - " 1.6\n", - " 15-Dec\n", + " 1.8\n", + " reached\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 83.3\n", + " 42\n", + " 83.3\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1932\n", - " 89.9\n", - " 2149\n", + " 3934\n", + " 90.1\n", + " 4368\n", " 88.3\n", - " 1.6\n", - " 15-Dec\n", + " 1.8\n", + " reached\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 42\n", + " 85.7\n", + " 49\n", + " 85.7\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 1932\n", - " 89.9\n", - " 2149\n", - " 88.3\n", + " 3934\n", + " 90.1\n", + " 4368\n", + " 88.5\n", " 1.6\n", - " 15-Dec\n", + " reached\n", " \n", " \n", " yes\n", - " 21\n", - " 100.0\n", - " 21\n", + " 42\n", " 100.0\n", - " 0.0\n", + " 42\n", + " 83.3\n", + " 16.7\n", " reached\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1925\n", - " 89.6\n", - " 2149\n", - " 87.9\n", - " 1.7\n", - " 16-Dec\n", + " 3934\n", + " 90.1\n", + " 4368\n", + " 88.5\n", + " 1.6\n", + " reached\n", " \n", " \n", " yes\n", - " 21\n", - " 100.0\n", - " 21\n", - " 100.0\n", + " 42\n", + " 85.7\n", + " 49\n", + " 85.7\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " LD\n", " no\n", - " 1911\n", - " 89.8\n", - " 2128\n", - " 88.2\n", + " 3885\n", + " 90.1\n", + " 4312\n", + " 88.5\n", " 1.6\n", - " 15-Dec\n", + " reached\n", " \n", " \n", " yes\n", - " 35\n", - " 83.3\n", - " 42\n", - " 83.3\n", - " 0.0\n", - " unknown\n", + " 91\n", + " 86.7\n", + " 105\n", + " 80.0\n", + " 6.7\n", + " 05-Feb\n", " \n", " \n", " ssri\n", " no\n", - " 1932\n", - " 89.9\n", - " 2149\n", - " 88.3\n", + " 3941\n", + " 90.1\n", + " 4375\n", + " 88.5\n", " 1.6\n", - " 15-Dec\n", + " reached\n", " \n", " \n", " yes\n", - " 21\n", - " 100.0\n", - " 21\n", - " 100.0\n", + " 28\n", + " 80.0\n", + " 35\n", + " 80.0\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 1932\n", - " 89.9\n", - " 2149\n", + " 3941\n", + " 90.1\n", + " 4375\n", " 88.3\n", - " 1.6\n", - " 15-Dec\n", + " 1.8\n", + " reached\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 83.3\n", + " 42\n", + " 83.3\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1925\n", - " 89.6\n", - " 2149\n", - " 87.9\n", - " 1.7\n", - " 16-Dec\n", + " 3941\n", + " 89.9\n", + " 4382\n", + " 88.3\n", + " 1.6\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 100.0\n", - " 21\n", - " 100.0\n", + " 28\n", + " 80.0\n", + " 35\n", + " 80.0\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1932\n", - " 89.9\n", - " 2149\n", + " 3941\n", + " 90.1\n", + " 4375\n", " 88.3\n", - " 1.6\n", - " 15-Dec\n", + " 1.8\n", + " reached\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 100.0\n", + " 35\n", + " 100.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1932\n", - " 89.9\n", - " 2149\n", - " 88.3\n", + " 3934\n", + " 90.1\n", + " 4368\n", + " 88.5\n", " 1.6\n", - " 15-Dec\n", + " reached\n", " \n", " \n", " yes\n", - " 21\n", + " 42\n", " 100.0\n", - " 21\n", - " 66.7\n", - " 33.3\n", + " 42\n", + " 83.3\n", + " 16.7\n", " reached\n", " \n", " \n", " ckd\n", " no\n", - " 1554\n", - " 89.5\n", - " 1736\n", - " 88.3\n", - " 1.2\n", - " 17-Dec\n", + " 3136\n", + " 90.3\n", + " 3472\n", + " 88.5\n", + " 1.8\n", + " reached\n", " \n", " \n", " yes\n", - " 392\n", - " 90.3\n", - " 434\n", - " 88.7\n", - " 1.6\n", - " reached\n", + " 840\n", + " 89.6\n", + " 938\n", + " 88.1\n", + " 1.5\n", + " 03-Feb\n", " \n", " \n", "\n", @@ -4791,318 +4843,318 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1946 \n", - "sex F 966 \n", - " M 987 \n", - "ethnicity_6_groups Black 343 \n", - " Mixed 315 \n", - " Other 315 \n", - " South Asian 350 \n", - " Unknown 301 \n", - " White 322 \n", - "ethnicity_16_groups African 105 \n", - " Bangladeshi or British Bangladeshi 105 \n", - " Caribbean 98 \n", - " Chinese 105 \n", - " Other 119 \n", - " Other Asian 119 \n", - " British or Mixed British 98 \n", - " Indian or British Indian 91 \n", - " Irish 105 \n", - " Other Black 98 \n", - " Other White 98 \n", - " Other mixed 77 \n", - " Pakistani or British Pakistani 119 \n", - " Unknown 287 \n", - " White + Asian 91 \n", - " White + Black African 105 \n", - " White + Black Caribbean 112 \n", - "imd_categories 1 Most deprived 350 \n", - " 2 406 \n", - " 3 371 \n", - " 4 371 \n", - " 5 Least deprived 357 \n", - " Unknown 91 \n", - "bmi 30+ 539 \n", - " under 30 1407 \n", - "housebound no 1939 \n", - " yes 14 \n", - "chronic_cardiac_disease no 1918 \n", + "overall overall 3976 \n", + "sex F 1995 \n", + " M 1974 \n", + "ethnicity_6_groups Black 672 \n", + " Mixed 693 \n", + " Other 665 \n", + " South Asian 637 \n", + " Unknown 637 \n", + " White 672 \n", + "ethnicity_16_groups African 210 \n", + " Bangladeshi or British Bangladeshi 210 \n", + " Caribbean 217 \n", + " Chinese 210 \n", + " Other 245 \n", + " Other Asian 196 \n", + " British or Mixed British 224 \n", + " Indian or British Indian 224 \n", + " Irish 210 \n", + " Other Black 217 \n", + " Other White 210 \n", + " Other mixed 217 \n", + " Pakistani or British Pakistani 217 \n", + " Unknown 560 \n", + " White + Asian 203 \n", + " White + Black African 182 \n", + " White + Black Caribbean 231 \n", + "imd_categories 1 Most deprived 735 \n", + " 2 749 \n", + " 3 777 \n", + " 4 749 \n", + " 5 Least deprived 763 \n", + " Unknown 210 \n", + "bmi 30+ 1246 \n", + " under 30 2723 \n", + "housebound no 3927 \n", + " yes 49 \n", + "chronic_cardiac_disease no 3934 \n", + " yes 42 \n", + "current_copd no 3941 \n", " yes 35 \n", - "current_copd no 1932 \n", - " yes 14 \n", - "dmards no 1932 \n", - " yes 14 \n", - "dementia no 1932 \n", - " yes 21 \n", - "psychosis_schiz_bipolar no 1925 \n", - " yes 21 \n", - "LD no 1911 \n", + "dmards no 3934 \n", + " yes 42 \n", + "dementia no 3934 \n", + " yes 42 \n", + "psychosis_schiz_bipolar no 3934 \n", + " yes 42 \n", + "LD no 3885 \n", + " yes 91 \n", + "ssri no 3941 \n", + " yes 28 \n", + "chemo_or_radio no 3941 \n", " yes 35 \n", - "ssri no 1932 \n", - " yes 21 \n", - "chemo_or_radio no 1932 \n", - " yes 14 \n", - "lung_cancer no 1925 \n", - " yes 21 \n", - "cancer_excl_lung_and_haem no 1932 \n", - " yes 14 \n", - "haematological_cancer no 1932 \n", - " yes 21 \n", - "ckd no 1554 \n", - " yes 392 \n", + "lung_cancer no 3941 \n", + " yes 28 \n", + "cancer_excl_lung_and_haem no 3941 \n", + " yes 35 \n", + "haematological_cancer no 3934 \n", + " yes 42 \n", + "ckd no 3136 \n", + " yes 840 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 89.7 2170 \n", - "sex F 90.2 1071 \n", - " M 89.8 1099 \n", - "ethnicity_6_groups Black 92.5 371 \n", - " Mixed 90.0 350 \n", - " Other 90.0 350 \n", - " South Asian 87.7 399 \n", - " Unknown 89.6 336 \n", - " White 88.5 364 \n", - "ethnicity_16_groups African 93.8 112 \n", - " Bangladeshi or British Bangladeshi 83.3 126 \n", - " Caribbean 93.3 105 \n", - " Chinese 93.8 112 \n", - " Other 89.5 133 \n", - " Other Asian 94.4 126 \n", - " British or Mixed British 87.5 112 \n", - " Indian or British Indian 86.7 105 \n", - " Irish 93.8 112 \n", - " Other Black 87.5 112 \n", - " Other White 87.5 112 \n", - " Other mixed 84.6 91 \n", - " Pakistani or British Pakistani 89.5 133 \n", - " Unknown 87.2 329 \n", - " White + Asian 81.2 112 \n", - " White + Black African 88.2 119 \n", - " White + Black Caribbean 88.9 126 \n", - "imd_categories 1 Most deprived 89.3 392 \n", - " 2 90.6 448 \n", - " 3 89.8 413 \n", - " 4 91.4 406 \n", - " 5 Least deprived 87.9 406 \n", - " Unknown 86.7 105 \n", - "bmi 30+ 87.5 616 \n", - " under 30 90.5 1554 \n", - "housebound no 89.9 2156 \n", - " yes 100.0 14 \n", - "chronic_cardiac_disease no 89.8 2135 \n", - " yes 100.0 35 \n", - "current_copd no 89.9 2149 \n", - " yes 66.7 21 \n", - "dmards no 89.9 2149 \n", - " yes 66.7 21 \n", - "dementia no 89.9 2149 \n", - " yes 100.0 21 \n", - "psychosis_schiz_bipolar no 89.6 2149 \n", - " yes 100.0 21 \n", - "LD no 89.8 2128 \n", + "overall overall 90.0 4417 \n", + "sex F 89.6 2226 \n", + " M 90.1 2191 \n", + "ethnicity_6_groups Black 88.9 756 \n", + " Mixed 90.0 770 \n", + " Other 88.8 749 \n", + " South Asian 90.1 707 \n", + " Unknown 91.0 700 \n", + " White 91.4 735 \n", + "ethnicity_16_groups African 93.8 224 \n", + " Bangladeshi or British Bangladeshi 90.9 231 \n", + " Caribbean 91.2 238 \n", + " Chinese 85.7 245 \n", + " Other 92.1 266 \n", + " Other Asian 90.3 217 \n", + " British or Mixed British 94.1 238 \n", + " Indian or British Indian 91.4 245 \n", + " Irish 90.9 231 \n", + " Other Black 91.2 238 \n", + " Other White 88.2 238 \n", + " Other mixed 86.1 252 \n", + " Pakistani or British Pakistani 91.2 238 \n", + " Unknown 89.9 623 \n", + " White + Asian 90.6 224 \n", + " White + Black African 92.9 196 \n", + " White + Black Caribbean 89.2 259 \n", + "imd_categories 1 Most deprived 89.7 819 \n", + " 2 89.2 840 \n", + " 3 91.0 854 \n", + " 4 89.2 840 \n", + " 5 Least deprived 90.8 840 \n", + " Unknown 96.8 217 \n", + "bmi 30+ 91.3 1365 \n", + " under 30 89.2 3052 \n", + "housebound no 90.0 4361 \n", + " yes 100.0 49 \n", + "chronic_cardiac_disease no 90.1 4368 \n", + " yes 85.7 49 \n", + "current_copd no 90.1 4375 \n", + " yes 83.3 42 \n", + "dmards no 90.1 4368 \n", + " yes 85.7 49 \n", + "dementia no 90.1 4368 \n", + " yes 100.0 42 \n", + "psychosis_schiz_bipolar no 90.1 4368 \n", + " yes 85.7 49 \n", + "LD no 90.1 4312 \n", + " yes 86.7 105 \n", + "ssri no 90.1 4375 \n", + " yes 80.0 35 \n", + "chemo_or_radio no 90.1 4375 \n", " yes 83.3 42 \n", - "ssri no 89.9 2149 \n", - " yes 100.0 21 \n", - "chemo_or_radio no 89.9 2149 \n", - " yes 66.7 21 \n", - "lung_cancer no 89.6 2149 \n", - " yes 100.0 21 \n", - "cancer_excl_lung_and_haem no 89.9 2149 \n", - " yes 66.7 21 \n", - "haematological_cancer no 89.9 2149 \n", - " yes 100.0 21 \n", - "ckd no 89.5 1736 \n", - " yes 90.3 434 \n", + "lung_cancer no 89.9 4382 \n", + " yes 80.0 35 \n", + "cancer_excl_lung_and_haem no 90.1 4375 \n", + " yes 100.0 35 \n", + "haematological_cancer no 90.1 4368 \n", + " yes 100.0 42 \n", + "ckd no 90.3 3472 \n", + " yes 89.6 938 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.1 \n", - "sex F 88.2 \n", - " M 87.9 \n", - "ethnicity_6_groups Black 90.6 \n", - " Mixed 88.0 \n", - " Other 90.0 \n", - " South Asian 86.0 \n", - " Unknown 85.4 \n", - " White 88.5 \n", + "overall overall 88.3 \n", + "sex F 87.7 \n", + " M 88.8 \n", + "ethnicity_6_groups Black 87.0 \n", + " Mixed 88.2 \n", + " Other 86.0 \n", + " South Asian 88.1 \n", + " Unknown 90.0 \n", + " White 89.5 \n", "ethnicity_16_groups African 93.8 \n", - " Bangladeshi or British Bangladeshi 83.3 \n", - " Caribbean 86.7 \n", - " Chinese 93.8 \n", + " Bangladeshi or British Bangladeshi 87.9 \n", + " Caribbean 91.2 \n", + " Chinese 85.7 \n", " Other 89.5 \n", - " Other Asian 88.9 \n", - " British or Mixed British 87.5 \n", - " Indian or British Indian 86.7 \n", - " Irish 87.5 \n", - " Other Black 87.5 \n", - " Other White 87.5 \n", - " Other mixed 84.6 \n", - " Pakistani or British Pakistani 89.5 \n", - " Unknown 87.2 \n", - " White + Asian 81.2 \n", - " White + Black African 88.2 \n", - " White + Black Caribbean 88.9 \n", - "imd_categories 1 Most deprived 89.3 \n", - " 2 89.1 \n", - " 3 89.8 \n", - " 4 89.7 \n", - " 5 Least deprived 84.5 \n", - " Unknown 86.7 \n", - "bmi 30+ 86.4 \n", - " under 30 88.7 \n", - "housebound no 88.3 \n", - " yes 100.0 \n", - "chronic_cardiac_disease no 87.9 \n", - " yes 100.0 \n", + " Other Asian 87.1 \n", + " British or Mixed British 91.2 \n", + " Indian or British Indian 85.7 \n", + " Irish 90.9 \n", + " Other Black 88.2 \n", + " Other White 85.3 \n", + " Other mixed 83.3 \n", + " Pakistani or British Pakistani 88.2 \n", + " Unknown 88.8 \n", + " White + Asian 87.5 \n", + " White + Black African 92.9 \n", + " White + Black Caribbean 89.2 \n", + "imd_categories 1 Most deprived 88.9 \n", + " 2 86.7 \n", + " 3 89.3 \n", + " 4 87.5 \n", + " 5 Least deprived 89.2 \n", + " Unknown 90.3 \n", + "bmi 30+ 89.7 \n", + " under 30 87.6 \n", + "housebound no 88.4 \n", + " yes 85.7 \n", + "chronic_cardiac_disease no 88.3 \n", + " yes 85.7 \n", "current_copd no 88.3 \n", - " yes 66.7 \n", + " yes 83.3 \n", "dmards no 88.3 \n", - " yes 66.7 \n", - "dementia no 88.3 \n", - " yes 100.0 \n", - "psychosis_schiz_bipolar no 87.9 \n", - " yes 100.0 \n", - "LD no 88.2 \n", + " yes 85.7 \n", + "dementia no 88.5 \n", " yes 83.3 \n", - "ssri no 88.3 \n", - " yes 100.0 \n", + "psychosis_schiz_bipolar no 88.5 \n", + " yes 85.7 \n", + "LD no 88.5 \n", + " yes 80.0 \n", + "ssri no 88.5 \n", + " yes 80.0 \n", "chemo_or_radio no 88.3 \n", - " yes 66.7 \n", - "lung_cancer no 87.9 \n", - " yes 100.0 \n", + " yes 83.3 \n", + "lung_cancer no 88.3 \n", + " yes 80.0 \n", "cancer_excl_lung_and_haem no 88.3 \n", - " yes 66.7 \n", - "haematological_cancer no 88.3 \n", - " yes 66.7 \n", - "ckd no 88.3 \n", - " yes 88.7 \n", + " yes 100.0 \n", + "haematological_cancer no 88.5 \n", + " yes 83.3 \n", + "ckd no 88.5 \n", + " yes 88.1 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.6 \n", - "sex F 2.0 \n", - " M 1.9 \n", + "overall overall 1.7 \n", + "sex F 1.9 \n", + " M 1.3 \n", "ethnicity_6_groups Black 1.9 \n", - " Mixed 2.0 \n", - " Other 0.0 \n", - " South Asian 1.7 \n", - " Unknown 4.2 \n", - " White 0.0 \n", + " Mixed 1.8 \n", + " Other 2.8 \n", + " South Asian 2.0 \n", + " Unknown 1.0 \n", + " White 1.9 \n", "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 6.6 \n", + " Bangladeshi or British Bangladeshi 3.0 \n", + " Caribbean 0.0 \n", " Chinese 0.0 \n", - " Other 0.0 \n", - " Other Asian 5.5 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 0.0 \n", - " Irish 6.3 \n", - " Other Black 0.0 \n", - " Other White 0.0 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 0.0 \n", - " White + Asian 0.0 \n", + " Other 2.6 \n", + " Other Asian 3.2 \n", + " British or Mixed British 2.9 \n", + " Indian or British Indian 5.7 \n", + " Irish 0.0 \n", + " Other Black 3.0 \n", + " Other White 2.9 \n", + " Other mixed 2.8 \n", + " Pakistani or British Pakistani 3.0 \n", + " Unknown 1.1 \n", + " White + Asian 3.1 \n", " White + Black African 0.0 \n", " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 0.0 \n", - " 2 1.5 \n", - " 3 0.0 \n", + "imd_categories 1 Most deprived 0.8 \n", + " 2 2.5 \n", + " 3 1.7 \n", " 4 1.7 \n", - " 5 Least deprived 3.4 \n", - " Unknown 0.0 \n", - "bmi 30+ 1.1 \n", - " under 30 1.8 \n", + " 5 Least deprived 1.6 \n", + " Unknown 6.5 \n", + "bmi 30+ 1.6 \n", + " under 30 1.6 \n", "housebound no 1.6 \n", + " yes 14.3 \n", + "chronic_cardiac_disease no 1.8 \n", " yes 0.0 \n", - "chronic_cardiac_disease no 1.9 \n", - " yes 0.0 \n", - "current_copd no 1.6 \n", + "current_copd no 1.8 \n", " yes 0.0 \n", - "dmards no 1.6 \n", + "dmards no 1.8 \n", " yes 0.0 \n", "dementia no 1.6 \n", - " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.7 \n", + " yes 16.7 \n", + "psychosis_schiz_bipolar no 1.6 \n", " yes 0.0 \n", "LD no 1.6 \n", - " yes 0.0 \n", + " yes 6.7 \n", "ssri no 1.6 \n", " yes 0.0 \n", - "chemo_or_radio no 1.6 \n", + "chemo_or_radio no 1.8 \n", " yes 0.0 \n", - "lung_cancer no 1.7 \n", + "lung_cancer no 1.6 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.6 \n", + "cancer_excl_lung_and_haem no 1.8 \n", " yes 0.0 \n", "haematological_cancer no 1.6 \n", - " yes 33.3 \n", - "ckd no 1.2 \n", - " yes 1.6 \n", + " yes 16.7 \n", + "ckd no 1.8 \n", + " yes 1.5 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 16-Dec \n", - "sex F reached \n", - " M 15-Dec \n", - "ethnicity_6_groups Black reached \n", + "overall overall reached \n", + "sex F 03-Feb \n", + " M reached \n", + "ethnicity_6_groups Black 06-Feb \n", " Mixed reached \n", - " Other unknown \n", - " South Asian 24-Dec \n", - " Unknown 15-Dec \n", - " White unknown \n", + " Other 05-Feb \n", + " South Asian reached \n", + " Unknown reached \n", + " White reached \n", "ethnicity_16_groups African reached \n", - " Bangladeshi or British Bangladeshi unknown \n", + " Bangladeshi or British Bangladeshi reached \n", " Caribbean reached \n", - " Chinese reached \n", - " Other unknown \n", + " Chinese unknown \n", + " Other reached \n", " Other Asian reached \n", - " British or Mixed British unknown \n", - " Indian or British Indian unknown \n", + " British or Mixed British reached \n", + " Indian or British Indian reached \n", " Irish reached \n", - " Other Black unknown \n", - " Other White unknown \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani unknown \n", - " Unknown unknown \n", - " White + Asian unknown \n", - " White + Black African unknown \n", + " Other Black reached \n", + " Other White 06-Feb \n", + " Other mixed 11-Feb \n", + " Pakistani or British Pakistani reached \n", + " Unknown 02-Feb \n", + " White + Asian reached \n", + " White + Black African reached \n", " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived unknown \n", - " 2 reached \n", - " 3 unknown \n", - " 4 reached \n", - " 5 Least deprived 19-Dec \n", - " Unknown unknown \n", - "bmi 30+ 30-Dec \n", - " under 30 reached \n", - "housebound no 15-Dec \n", - " yes reached \n", - "chronic_cardiac_disease no 15-Dec \n", + "imd_categories 1 Most deprived 04-Feb \n", + " 2 04-Feb \n", + " 3 reached \n", + " 4 05-Feb \n", + " 5 Least deprived reached \n", + " Unknown reached \n", + "bmi 30+ reached \n", + " under 30 05-Feb \n", + "housebound no reached \n", " yes reached \n", - "current_copd no 15-Dec \n", + "chronic_cardiac_disease no reached \n", " yes unknown \n", - "dmards no 15-Dec \n", + "current_copd no reached \n", " yes unknown \n", - "dementia no 15-Dec \n", - " yes reached \n", - "psychosis_schiz_bipolar no 16-Dec \n", - " yes reached \n", - "LD no 15-Dec \n", + "dmards no reached \n", " yes unknown \n", - "ssri no 15-Dec \n", + "dementia no reached \n", " yes reached \n", - "chemo_or_radio no 15-Dec \n", + "psychosis_schiz_bipolar no reached \n", " yes unknown \n", - "lung_cancer no 16-Dec \n", - " yes reached \n", - "cancer_excl_lung_and_haem no 15-Dec \n", + "LD no reached \n", + " yes 05-Feb \n", + "ssri no reached \n", + " yes unknown \n", + "chemo_or_radio no reached \n", + " yes unknown \n", + "lung_cancer no 02-Feb \n", " yes unknown \n", - "haematological_cancer no 15-Dec \n", + "cancer_excl_lung_and_haem no reached \n", " yes reached \n", - "ckd no 17-Dec \n", - " yes reached " + "haematological_cancer no reached \n", + " yes reached \n", + "ckd no reached \n", + " yes 03-Feb " ] }, "metadata": {}, @@ -5131,7 +5183,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **LD (aged 16-64)** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **LD (aged 16-64)** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -5197,182 +5249,182 @@ " \n", " overall\n", " overall\n", - " 728\n", - " 90.4\n", - " 805\n", - " 88.7\n", - " 1.7\n", + " 1463\n", + " 91.3\n", + " 1603\n", + " 89.5\n", + " 1.8\n", " reached\n", " \n", " \n", " sex\n", " F\n", - " 378\n", - " 91.5\n", - " 413\n", - " 89.8\n", - " 1.7\n", + " 721\n", + " 91.2\n", + " 791\n", + " 89.4\n", + " 1.8\n", " reached\n", " \n", " \n", " M\n", - " 350\n", - " 89.3\n", - " 392\n", - " 89.3\n", - " 0.0\n", - " unknown\n", + " 742\n", + " 91.4\n", + " 812\n", + " 89.7\n", + " 1.7\n", + " reached\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 7\n", - " 100.0\n", - " 7\n", + " 21\n", " 100.0\n", - " 0.0\n", + " 21\n", + " 66.7\n", + " 33.3\n", " reached\n", " \n", " \n", " 0-15\n", - " 42\n", - " 85.7\n", - " 49\n", - " 85.7\n", + " 98\n", + " 93.3\n", + " 105\n", + " 93.3\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " 16-17\n", - " 49\n", - " 100.0\n", - " 49\n", - " 100.0\n", + " 105\n", + " 93.8\n", + " 112\n", + " 93.8\n", " 0.0\n", " reached\n", " \n", " \n", " 18-29\n", - " 49\n", - " 100.0\n", - " 49\n", - " 100.0\n", - " 0.0\n", + " 98\n", + " 93.3\n", + " 105\n", + " 86.7\n", + " 6.6\n", " reached\n", " \n", " \n", " 30-34\n", - " 42\n", - " 100.0\n", - " 42\n", - " 83.3\n", - " 16.7\n", - " reached\n", + " 84\n", + " 85.7\n", + " 98\n", + " 85.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 35-39\n", - " 49\n", - " 100.0\n", - " 49\n", - " 100.0\n", + " 98\n", + " 93.3\n", + " 105\n", + " 93.3\n", " 0.0\n", " reached\n", " \n", " \n", " 40-44\n", - " 49\n", - " 100.0\n", - " 49\n", - " 100.0\n", + " 77\n", + " 91.7\n", + " 84\n", + " 91.7\n", " 0.0\n", " reached\n", " \n", " \n", " 45-49\n", - " 56\n", - " 100.0\n", - " 56\n", - " 87.5\n", - " 12.5\n", - " reached\n", + " 105\n", + " 88.2\n", + " 119\n", + " 88.2\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 50-54\n", - " 49\n", - " 87.5\n", - " 56\n", - " 87.5\n", + " 119\n", + " 89.5\n", + " 133\n", + " 89.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 55-59\n", - " 42\n", - " 85.7\n", - " 49\n", - " 85.7\n", + " 98\n", + " 93.3\n", + " 105\n", + " 93.3\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " 60-64\n", - " 49\n", - " 87.5\n", - " 56\n", - " 87.5\n", - " 0.0\n", - " unknown\n", + " 91\n", + " 92.9\n", + " 98\n", + " 85.7\n", + " 7.2\n", + " reached\n", " \n", " \n", " 65-69\n", - " 56\n", - " 88.9\n", - " 63\n", - " 88.9\n", - " 0.0\n", - " unknown\n", + " 91\n", + " 92.9\n", + " 98\n", + " 85.7\n", + " 7.2\n", + " reached\n", " \n", " \n", " 70-74\n", - " 42\n", - " 85.7\n", - " 49\n", - " 85.7\n", - " 0.0\n", - " unknown\n", + " 84\n", + " 92.3\n", + " 91\n", + " 84.6\n", + " 7.7\n", + " reached\n", " \n", " \n", " 75-79\n", - " 56\n", - " 88.9\n", - " 63\n", - " 88.9\n", + " 98\n", + " 93.3\n", + " 105\n", + " 93.3\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " 80-84\n", - " 42\n", + " 84\n", " 85.7\n", - " 49\n", + " 98\n", " 85.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 85-89\n", - " 42\n", - " 85.7\n", - " 49\n", - " 85.7\n", + " 98\n", + " 93.3\n", + " 105\n", + " 93.3\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " 90+\n", - " 7\n", + " 14\n", " 100.0\n", - " 7\n", + " 14\n", " 100.0\n", " 0.0\n", " reached\n", @@ -5380,56 +5432,56 @@ " \n", " ethnicity_6_groups\n", " Black\n", - " 112\n", - " 88.9\n", - " 126\n", - " 88.9\n", - " 0.0\n", - " unknown\n", + " 252\n", + " 92.3\n", + " 273\n", + " 89.7\n", + " 2.6\n", + " reached\n", " \n", " \n", " Mixed\n", - " 147\n", - " 91.3\n", - " 161\n", - " 87.0\n", - " 4.3\n", + " 259\n", + " 92.5\n", + " 280\n", + " 90.0\n", + " 2.5\n", " reached\n", " \n", " \n", " Other\n", - " 119\n", - " 89.5\n", - " 133\n", - " 89.5\n", - " 0.0\n", - " unknown\n", + " 266\n", + " 90.5\n", + " 294\n", + " 88.1\n", + " 2.4\n", + " reached\n", " \n", " \n", " South Asian\n", - " 119\n", - " 89.5\n", - " 133\n", - " 89.5\n", - " 0.0\n", - " unknown\n", + " 245\n", + " 89.7\n", + " 273\n", + " 87.2\n", + " 2.5\n", + " 02-Feb\n", " \n", " \n", " Unknown\n", - " 119\n", - " 94.4\n", - " 126\n", - " 94.4\n", + " 203\n", + " 90.6\n", + " 224\n", + " 90.6\n", " 0.0\n", " reached\n", " \n", " \n", " White\n", - " 119\n", - " 94.4\n", - " 126\n", - " 94.4\n", - " 0.0\n", + " 238\n", + " 91.9\n", + " 259\n", + " 89.2\n", + " 2.7\n", " reached\n", " \n", " \n", @@ -5439,117 +5491,117 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 728 90.4 805 \n", - "sex F 378 91.5 413 \n", - " M 350 89.3 392 \n", - "ageband_5yr 0 7 100.0 7 \n", - " 0-15 42 85.7 49 \n", - " 16-17 49 100.0 49 \n", - " 18-29 49 100.0 49 \n", - " 30-34 42 100.0 42 \n", - " 35-39 49 100.0 49 \n", - " 40-44 49 100.0 49 \n", - " 45-49 56 100.0 56 \n", - " 50-54 49 87.5 56 \n", - " 55-59 42 85.7 49 \n", - " 60-64 49 87.5 56 \n", - " 65-69 56 88.9 63 \n", - " 70-74 42 85.7 49 \n", - " 75-79 56 88.9 63 \n", - " 80-84 42 85.7 49 \n", - " 85-89 42 85.7 49 \n", - " 90+ 7 100.0 7 \n", - "ethnicity_6_groups Black 112 88.9 126 \n", - " Mixed 147 91.3 161 \n", - " Other 119 89.5 133 \n", - " South Asian 119 89.5 133 \n", - " Unknown 119 94.4 126 \n", - " White 119 94.4 126 \n", + "overall overall 1463 91.3 1603 \n", + "sex F 721 91.2 791 \n", + " M 742 91.4 812 \n", + "ageband_5yr 0 21 100.0 21 \n", + " 0-15 98 93.3 105 \n", + " 16-17 105 93.8 112 \n", + " 18-29 98 93.3 105 \n", + " 30-34 84 85.7 98 \n", + " 35-39 98 93.3 105 \n", + " 40-44 77 91.7 84 \n", + " 45-49 105 88.2 119 \n", + " 50-54 119 89.5 133 \n", + " 55-59 98 93.3 105 \n", + " 60-64 91 92.9 98 \n", + " 65-69 91 92.9 98 \n", + " 70-74 84 92.3 91 \n", + " 75-79 98 93.3 105 \n", + " 80-84 84 85.7 98 \n", + " 85-89 98 93.3 105 \n", + " 90+ 14 100.0 14 \n", + "ethnicity_6_groups Black 252 92.3 273 \n", + " Mixed 259 92.5 280 \n", + " Other 266 90.5 294 \n", + " South Asian 245 89.7 273 \n", + " Unknown 203 90.6 224 \n", + " White 238 91.9 259 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.7 \n", - "sex F 89.8 \n", - " M 89.3 \n", - "ageband_5yr 0 100.0 \n", - " 0-15 85.7 \n", - " 16-17 100.0 \n", - " 18-29 100.0 \n", - " 30-34 83.3 \n", - " 35-39 100.0 \n", - " 40-44 100.0 \n", - " 45-49 87.5 \n", - " 50-54 87.5 \n", - " 55-59 85.7 \n", - " 60-64 87.5 \n", - " 65-69 88.9 \n", - " 70-74 85.7 \n", - " 75-79 88.9 \n", + "overall overall 89.5 \n", + "sex F 89.4 \n", + " M 89.7 \n", + "ageband_5yr 0 66.7 \n", + " 0-15 93.3 \n", + " 16-17 93.8 \n", + " 18-29 86.7 \n", + " 30-34 85.7 \n", + " 35-39 93.3 \n", + " 40-44 91.7 \n", + " 45-49 88.2 \n", + " 50-54 89.5 \n", + " 55-59 93.3 \n", + " 60-64 85.7 \n", + " 65-69 85.7 \n", + " 70-74 84.6 \n", + " 75-79 93.3 \n", " 80-84 85.7 \n", - " 85-89 85.7 \n", + " 85-89 93.3 \n", " 90+ 100.0 \n", - "ethnicity_6_groups Black 88.9 \n", - " Mixed 87.0 \n", - " Other 89.5 \n", - " South Asian 89.5 \n", - " Unknown 94.4 \n", - " White 94.4 \n", + "ethnicity_6_groups Black 89.7 \n", + " Mixed 90.0 \n", + " Other 88.1 \n", + " South Asian 87.2 \n", + " Unknown 90.6 \n", + " White 89.2 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.7 \n", - "sex F 1.7 \n", - " M 0.0 \n", - "ageband_5yr 0 0.0 \n", + "overall overall 1.8 \n", + "sex F 1.8 \n", + " M 1.7 \n", + "ageband_5yr 0 33.3 \n", " 0-15 0.0 \n", " 16-17 0.0 \n", - " 18-29 0.0 \n", - " 30-34 16.7 \n", + " 18-29 6.6 \n", + " 30-34 0.0 \n", " 35-39 0.0 \n", " 40-44 0.0 \n", - " 45-49 12.5 \n", + " 45-49 0.0 \n", " 50-54 0.0 \n", " 55-59 0.0 \n", - " 60-64 0.0 \n", - " 65-69 0.0 \n", - " 70-74 0.0 \n", + " 60-64 7.2 \n", + " 65-69 7.2 \n", + " 70-74 7.7 \n", " 75-79 0.0 \n", " 80-84 0.0 \n", " 85-89 0.0 \n", " 90+ 0.0 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 4.3 \n", - " Other 0.0 \n", - " South Asian 0.0 \n", + "ethnicity_6_groups Black 2.6 \n", + " Mixed 2.5 \n", + " Other 2.4 \n", + " South Asian 2.5 \n", " Unknown 0.0 \n", - " White 0.0 \n", + " White 2.7 \n", "\n", " Date projected to reach 90% \n", "category group \n", "overall overall reached \n", "sex F reached \n", - " M unknown \n", + " M reached \n", "ageband_5yr 0 reached \n", - " 0-15 unknown \n", + " 0-15 reached \n", " 16-17 reached \n", " 18-29 reached \n", - " 30-34 reached \n", + " 30-34 unknown \n", " 35-39 reached \n", " 40-44 reached \n", - " 45-49 reached \n", + " 45-49 unknown \n", " 50-54 unknown \n", - " 55-59 unknown \n", - " 60-64 unknown \n", - " 65-69 unknown \n", - " 70-74 unknown \n", - " 75-79 unknown \n", + " 55-59 reached \n", + " 60-64 reached \n", + " 65-69 reached \n", + " 70-74 reached \n", + " 75-79 reached \n", " 80-84 unknown \n", - " 85-89 unknown \n", + " 85-89 reached \n", " 90+ reached \n", - "ethnicity_6_groups Black unknown \n", + "ethnicity_6_groups Black reached \n", " Mixed reached \n", - " Other unknown \n", - " South Asian unknown \n", + " Other reached \n", + " South Asian 02-Feb \n", " Unknown reached \n", " White reached " ] @@ -5580,7 +5632,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **60-64** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **60-64** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -5646,349 +5698,349 @@ " \n", " overall\n", " overall\n", - " 2401\n", - " 89.8\n", - " 2674\n", - " 88.0\n", - " 1.8\n", - " 15-Dec\n", + " 4928\n", + " 90.4\n", + " 5453\n", + " 89.0\n", + " 1.4\n", + " reached\n", " \n", " \n", " sex\n", " F\n", - " 1190\n", - " 89.5\n", - " 1330\n", - " 87.9\n", - " 1.6\n", - " 17-Dec\n", + " 2534\n", + " 90.3\n", + " 2807\n", + " 89.0\n", + " 1.3\n", + " reached\n", " \n", " \n", " M\n", - " 1204\n", - " 89.6\n", - " 1344\n", - " 88.0\n", + " 2394\n", + " 90.5\n", + " 2646\n", + " 88.9\n", " 1.6\n", - " 16-Dec\n", + " reached\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 413\n", - " 88.1\n", - " 469\n", - " 88.1\n", - " 0.0\n", - " unknown\n", + " 861\n", + " 89.8\n", + " 959\n", + " 89.1\n", + " 0.7\n", + " 04-Feb\n", " \n", " \n", " Mixed\n", - " 427\n", - " 92.4\n", - " 462\n", - " 89.4\n", - " 3.0\n", + " 854\n", + " 90.4\n", + " 945\n", + " 88.9\n", + " 1.5\n", " reached\n", " \n", " \n", " Other\n", - " 413\n", - " 92.2\n", - " 448\n", - " 89.1\n", - " 3.1\n", + " 805\n", + " 91.3\n", + " 882\n", + " 88.9\n", + " 2.4\n", " reached\n", " \n", " \n", " South Asian\n", - " 406\n", - " 89.2\n", - " 455\n", - " 87.7\n", - " 1.5\n", - " 18-Dec\n", + " 812\n", + " 88.5\n", + " 917\n", + " 87.8\n", + " 0.7\n", + " 17-Feb\n", " \n", " \n", " Unknown\n", - " 315\n", - " 86.5\n", - " 364\n", - " 84.6\n", - " 1.9\n", - " 27-Dec\n", + " 742\n", + " 90.6\n", + " 819\n", + " 88.9\n", + " 1.7\n", + " reached\n", " \n", " \n", " White\n", - " 420\n", + " 854\n", + " 91.0\n", + " 938\n", " 89.6\n", - " 469\n", - " 88.1\n", - " 1.5\n", - " 16-Dec\n", + " 1.4\n", + " reached\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 105\n", - " 88.2\n", - " 119\n", - " 88.2\n", - " 0.0\n", - " unknown\n", + " 259\n", + " 92.5\n", + " 280\n", + " 90.0\n", + " 2.5\n", + " reached\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 140\n", - " 90.9\n", - " 154\n", - " 90.9\n", + " 266\n", + " 88.4\n", + " 301\n", + " 88.4\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " Caribbean\n", - " 133\n", - " 90.5\n", - " 147\n", - " 90.5\n", + " 280\n", + " 93.0\n", + " 301\n", + " 93.0\n", " 0.0\n", " reached\n", " \n", " \n", " Chinese\n", - " 140\n", - " 90.9\n", - " 154\n", - " 86.4\n", - " 4.5\n", - " reached\n", + " 266\n", + " 88.4\n", + " 301\n", + " 88.4\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other\n", - " 140\n", - " 90.9\n", - " 154\n", - " 90.9\n", - " 0.0\n", + " 273\n", + " 90.7\n", + " 301\n", + " 88.4\n", + " 2.3\n", " reached\n", " \n", " \n", " Other Asian\n", - " 119\n", - " 94.4\n", - " 126\n", - " 88.9\n", - " 5.5\n", - " reached\n", + " 266\n", + " 88.4\n", + " 301\n", + " 88.4\n", + " 0.0\n", + " unknown\n", " \n", " \n", " British or Mixed British\n", - " 133\n", - " 90.5\n", - " 147\n", - " 90.5\n", - " 0.0\n", - " reached\n", + " 231\n", + " 89.2\n", + " 259\n", + " 86.5\n", + " 2.7\n", + " 04-Feb\n", " \n", " \n", " Indian or British Indian\n", - " 119\n", - " 89.5\n", - " 133\n", - " 89.5\n", + " 245\n", + " 89.7\n", + " 273\n", + " 89.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 140\n", - " 90.9\n", - " 154\n", - " 90.9\n", - " 0.0\n", - " reached\n", + " 245\n", + " 87.5\n", + " 280\n", + " 82.5\n", + " 5.0\n", + " 05-Feb\n", " \n", " \n", " Other Black\n", - " 112\n", - " 88.9\n", - " 126\n", - " 88.9\n", - " 0.0\n", - " unknown\n", + " 259\n", + " 90.2\n", + " 287\n", + " 87.8\n", + " 2.4\n", + " reached\n", " \n", " \n", " Other White\n", - " 140\n", - " 87.0\n", - " 161\n", - " 82.6\n", - " 4.4\n", - " 19-Dec\n", + " 252\n", + " 92.3\n", + " 273\n", + " 89.7\n", + " 2.6\n", + " reached\n", " \n", " \n", " Other mixed\n", - " 133\n", - " 90.5\n", - " 147\n", - " 85.7\n", - " 4.8\n", - " reached\n", + " 238\n", + " 89.5\n", + " 266\n", + " 89.5\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 140\n", - " 95.2\n", - " 147\n", - " 95.2\n", - " 0.0\n", + " 287\n", + " 95.3\n", + " 301\n", + " 93.0\n", + " 2.3\n", " reached\n", " \n", " \n", " Unknown\n", - " 357\n", - " 87.9\n", - " 406\n", - " 87.9\n", - " 0.0\n", - " unknown\n", + " 735\n", + " 88.2\n", + " 833\n", + " 86.6\n", + " 1.6\n", + " 09-Feb\n", " \n", " \n", " White + Asian\n", - " 112\n", - " 84.2\n", - " 133\n", - " 78.9\n", - " 5.3\n", - " 22-Dec\n", + " 266\n", + " 92.7\n", + " 287\n", + " 92.7\n", + " 0.0\n", + " reached\n", " \n", " \n", " White + Black African\n", - " 119\n", - " 89.5\n", - " 133\n", - " 89.5\n", - " 0.0\n", - " unknown\n", + " 280\n", + " 93.0\n", + " 301\n", + " 90.7\n", + " 2.3\n", + " reached\n", " \n", " \n", " White + Black Caribbean\n", - " 112\n", - " 88.9\n", - " 126\n", - " 88.9\n", + " 287\n", + " 91.1\n", + " 315\n", + " 91.1\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 455\n", - " 90.3\n", - " 504\n", - " 88.9\n", + " 903\n", + " 89.0\n", + " 1015\n", + " 87.6\n", " 1.4\n", - " reached\n", + " 07-Feb\n", " \n", " \n", " 2\n", - " 483\n", - " 88.5\n", - " 546\n", - " 87.2\n", + " 938\n", + " 90.5\n", + " 1036\n", + " 89.2\n", " 1.3\n", - " 23-Dec\n", + " reached\n", " \n", " \n", " 3\n", - " 455\n", - " 90.3\n", - " 504\n", - " 87.5\n", - " 2.8\n", + " 973\n", + " 90.8\n", + " 1071\n", + " 89.5\n", + " 1.3\n", " reached\n", " \n", " \n", " 4\n", - " 427\n", - " 88.4\n", - " 483\n", - " 87.0\n", - " 1.4\n", - " 23-Dec\n", + " 910\n", + " 90.9\n", + " 1001\n", + " 90.2\n", + " 0.7\n", + " reached\n", " \n", " \n", " 5 Least deprived\n", - " 455\n", - " 90.3\n", - " 504\n", - " 88.9\n", - " 1.4\n", + " 952\n", + " 90.1\n", + " 1057\n", + " 88.1\n", + " 2.0\n", " reached\n", " \n", " \n", " Unknown\n", - " 119\n", - " 89.5\n", - " 133\n", - " 89.5\n", + " 252\n", + " 90.0\n", + " 280\n", + " 90.0\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 742\n", - " 89.8\n", - " 826\n", - " 88.1\n", - " 1.7\n", - " 15-Dec\n", + " 1477\n", + " 90.9\n", + " 1624\n", + " 89.7\n", + " 1.2\n", + " reached\n", " \n", " \n", " under 30\n", - " 1659\n", - " 89.8\n", - " 1848\n", - " 87.9\n", - " 1.9\n", - " 15-Dec\n", + " 3451\n", + " 90.1\n", + " 3829\n", + " 88.7\n", + " 1.4\n", + " reached\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 2366\n", - " 89.7\n", - " 2639\n", - " 88.1\n", - " 1.6\n", - " 16-Dec\n", + " 4886\n", + " 90.3\n", + " 5411\n", + " 88.9\n", + " 1.4\n", + " reached\n", " \n", " \n", " yes\n", - " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 42\n", + " 100.0\n", + " 42\n", + " 100.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " current_copd\n", " no\n", - " 2380\n", - " 89.7\n", - " 2653\n", - " 88.1\n", - " 1.6\n", - " 16-Dec\n", + " 4872\n", + " 90.3\n", + " 5397\n", + " 88.8\n", + " 1.5\n", + " reached\n", " \n", " \n", " yes\n", - " 21\n", + " 56\n", " 100.0\n", - " 21\n", + " 56\n", " 100.0\n", " 0.0\n", " reached\n", @@ -5996,18 +6048,18 @@ " \n", " dmards\n", " no\n", - " 2380\n", - " 89.7\n", - " 2653\n", - " 87.9\n", - " 1.8\n", - " 16-Dec\n", + " 4872\n", + " 90.3\n", + " 5397\n", + " 88.8\n", + " 1.5\n", + " reached\n", " \n", " \n", " yes\n", - " 21\n", + " 56\n", " 100.0\n", - " 21\n", + " 56\n", " 100.0\n", " 0.0\n", " reached\n", @@ -6015,37 +6067,37 @@ " \n", " dementia\n", " no\n", - " 2373\n", - " 89.7\n", - " 2646\n", - " 88.1\n", - " 1.6\n", - " 16-Dec\n", + " 4858\n", + " 90.4\n", + " 5376\n", + " 88.9\n", + " 1.5\n", + " reached\n", " \n", " \n", " yes\n", - " 28\n", - " 100.0\n", - " 28\n", - " 100.0\n", + " 70\n", + " 90.9\n", + " 77\n", + " 90.9\n", " 0.0\n", " reached\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 2373\n", - " 89.7\n", - " 2646\n", - " 88.1\n", - " 1.6\n", - " 16-Dec\n", + " 4879\n", + " 90.3\n", + " 5404\n", + " 88.9\n", + " 1.4\n", + " reached\n", " \n", " \n", " yes\n", - " 28\n", + " 49\n", " 100.0\n", - " 28\n", + " 49\n", " 100.0\n", " 0.0\n", " reached\n", @@ -6053,116 +6105,116 @@ " \n", " ssri\n", " no\n", - " 2373\n", - " 89.7\n", - " 2646\n", - " 88.1\n", - " 1.6\n", - " 16-Dec\n", + " 4879\n", + " 90.3\n", + " 5404\n", + " 89.0\n", + " 1.3\n", + " reached\n", " \n", " \n", " yes\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", + " 42\n", + " 85.7\n", + " 49\n", + " 85.7\n", " 0.0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 2373\n", - " 89.7\n", - " 2646\n", - " 87.8\n", - " 1.9\n", - " 16-Dec\n", + " 4872\n", + " 90.3\n", + " 5397\n", + " 88.8\n", + " 1.5\n", + " reached\n", " \n", " \n", " yes\n", - " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 56\n", + " 88.9\n", + " 63\n", + " 88.9\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 2380\n", - " 89.7\n", - " 2653\n", - " 87.9\n", - " 1.8\n", - " 16-Dec\n", + " 4886\n", + " 90.3\n", + " 5411\n", + " 88.9\n", + " 1.4\n", + " reached\n", " \n", " \n", " yes\n", - " 21\n", - " 100.0\n", - " 21\n", - " 100.0\n", + " 42\n", + " 85.7\n", + " 49\n", + " 85.7\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 2380\n", - " 89.7\n", - " 2653\n", - " 87.9\n", - " 1.8\n", - " 16-Dec\n", + " 4879\n", + " 90.4\n", + " 5397\n", + " 89.0\n", + " 1.4\n", + " reached\n", " \n", " \n", " yes\n", - " 21\n", - " 100.0\n", - " 21\n", - " 100.0\n", + " 49\n", + " 87.5\n", + " 56\n", + " 87.5\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 2373\n", - " 89.7\n", - " 2646\n", - " 87.8\n", - " 1.9\n", - " 16-Dec\n", + " 4886\n", + " 90.4\n", + " 5404\n", + " 89.0\n", + " 1.4\n", + " reached\n", " \n", " \n", " yes\n", - " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 42\n", + " 85.7\n", + " 49\n", + " 85.7\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1890\n", - " 89.4\n", - " 2114\n", - " 87.7\n", - " 1.7\n", - " 17-Dec\n", + " 3983\n", + " 90.5\n", + " 4403\n", + " 89.2\n", + " 1.3\n", + " reached\n", " \n", " \n", " yes\n", - " 504\n", - " 90.0\n", - " 560\n", - " 88.8\n", - " 1.2\n", - " reached\n", + " 945\n", + " 89.4\n", + " 1057\n", + " 87.4\n", + " 2.0\n", + " 04-Feb\n", " \n", " \n", "\n", @@ -6171,298 +6223,298 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 2401 \n", - "sex F 1190 \n", - " M 1204 \n", - "ethnicity_6_groups Black 413 \n", - " Mixed 427 \n", - " Other 413 \n", - " South Asian 406 \n", - " Unknown 315 \n", - " White 420 \n", - "ethnicity_16_groups African 105 \n", - " Bangladeshi or British Bangladeshi 140 \n", - " Caribbean 133 \n", - " Chinese 140 \n", - " Other 140 \n", - " Other Asian 119 \n", - " British or Mixed British 133 \n", - " Indian or British Indian 119 \n", - " Irish 140 \n", - " Other Black 112 \n", - " Other White 140 \n", - " Other mixed 133 \n", - " Pakistani or British Pakistani 140 \n", - " Unknown 357 \n", - " White + Asian 112 \n", - " White + Black African 119 \n", - " White + Black Caribbean 112 \n", - "imd_categories 1 Most deprived 455 \n", - " 2 483 \n", - " 3 455 \n", - " 4 427 \n", - " 5 Least deprived 455 \n", - " Unknown 119 \n", - "bmi 30+ 742 \n", - " under 30 1659 \n", - "chronic_cardiac_disease no 2366 \n", - " yes 28 \n", - "current_copd no 2380 \n", - " yes 21 \n", - "dmards no 2380 \n", - " yes 21 \n", - "dementia no 2373 \n", - " yes 28 \n", - "psychosis_schiz_bipolar no 2373 \n", - " yes 28 \n", - "ssri no 2373 \n", - " yes 21 \n", - "chemo_or_radio no 2373 \n", - " yes 28 \n", - "lung_cancer no 2380 \n", - " yes 21 \n", - "cancer_excl_lung_and_haem no 2380 \n", - " yes 21 \n", - "haematological_cancer no 2373 \n", - " yes 28 \n", - "ckd no 1890 \n", - " yes 504 \n", + "overall overall 4928 \n", + "sex F 2534 \n", + " M 2394 \n", + "ethnicity_6_groups Black 861 \n", + " Mixed 854 \n", + " Other 805 \n", + " South Asian 812 \n", + " Unknown 742 \n", + " White 854 \n", + "ethnicity_16_groups African 259 \n", + " Bangladeshi or British Bangladeshi 266 \n", + " Caribbean 280 \n", + " Chinese 266 \n", + " Other 273 \n", + " Other Asian 266 \n", + " British or Mixed British 231 \n", + " Indian or British Indian 245 \n", + " Irish 245 \n", + " Other Black 259 \n", + " Other White 252 \n", + " Other mixed 238 \n", + " Pakistani or British Pakistani 287 \n", + " Unknown 735 \n", + " White + Asian 266 \n", + " White + Black African 280 \n", + " White + Black Caribbean 287 \n", + "imd_categories 1 Most deprived 903 \n", + " 2 938 \n", + " 3 973 \n", + " 4 910 \n", + " 5 Least deprived 952 \n", + " Unknown 252 \n", + "bmi 30+ 1477 \n", + " under 30 3451 \n", + "chronic_cardiac_disease no 4886 \n", + " yes 42 \n", + "current_copd no 4872 \n", + " yes 56 \n", + "dmards no 4872 \n", + " yes 56 \n", + "dementia no 4858 \n", + " yes 70 \n", + "psychosis_schiz_bipolar no 4879 \n", + " yes 49 \n", + "ssri no 4879 \n", + " yes 42 \n", + "chemo_or_radio no 4872 \n", + " yes 56 \n", + "lung_cancer no 4886 \n", + " yes 42 \n", + "cancer_excl_lung_and_haem no 4879 \n", + " yes 49 \n", + "haematological_cancer no 4886 \n", + " yes 42 \n", + "ckd no 3983 \n", + " yes 945 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 89.8 2674 \n", - "sex F 89.5 1330 \n", - " M 89.6 1344 \n", - "ethnicity_6_groups Black 88.1 469 \n", - " Mixed 92.4 462 \n", - " Other 92.2 448 \n", - " South Asian 89.2 455 \n", - " Unknown 86.5 364 \n", - " White 89.6 469 \n", - "ethnicity_16_groups African 88.2 119 \n", - " Bangladeshi or British Bangladeshi 90.9 154 \n", - " Caribbean 90.5 147 \n", - " Chinese 90.9 154 \n", - " Other 90.9 154 \n", - " Other Asian 94.4 126 \n", - " British or Mixed British 90.5 147 \n", - " Indian or British Indian 89.5 133 \n", - " Irish 90.9 154 \n", - " Other Black 88.9 126 \n", - " Other White 87.0 161 \n", - " Other mixed 90.5 147 \n", - " Pakistani or British Pakistani 95.2 147 \n", - " Unknown 87.9 406 \n", - " White + Asian 84.2 133 \n", - " White + Black African 89.5 133 \n", - " White + Black Caribbean 88.9 126 \n", - "imd_categories 1 Most deprived 90.3 504 \n", - " 2 88.5 546 \n", - " 3 90.3 504 \n", - " 4 88.4 483 \n", - " 5 Least deprived 90.3 504 \n", - " Unknown 89.5 133 \n", - "bmi 30+ 89.8 826 \n", - " under 30 89.8 1848 \n", - "chronic_cardiac_disease no 89.7 2639 \n", - " yes 80.0 35 \n", - "current_copd no 89.7 2653 \n", - " yes 100.0 21 \n", - "dmards no 89.7 2653 \n", - " yes 100.0 21 \n", - "dementia no 89.7 2646 \n", - " yes 100.0 28 \n", - "psychosis_schiz_bipolar no 89.7 2646 \n", - " yes 100.0 28 \n", - "ssri no 89.7 2646 \n", - " yes 75.0 28 \n", - "chemo_or_radio no 89.7 2646 \n", - " yes 80.0 35 \n", - "lung_cancer no 89.7 2653 \n", - " yes 100.0 21 \n", - "cancer_excl_lung_and_haem no 89.7 2653 \n", - " yes 100.0 21 \n", - "haematological_cancer no 89.7 2646 \n", - " yes 80.0 35 \n", - "ckd no 89.4 2114 \n", - " yes 90.0 560 \n", + "overall overall 90.4 5453 \n", + "sex F 90.3 2807 \n", + " M 90.5 2646 \n", + "ethnicity_6_groups Black 89.8 959 \n", + " Mixed 90.4 945 \n", + " Other 91.3 882 \n", + " South Asian 88.5 917 \n", + " Unknown 90.6 819 \n", + " White 91.0 938 \n", + "ethnicity_16_groups African 92.5 280 \n", + " Bangladeshi or British Bangladeshi 88.4 301 \n", + " Caribbean 93.0 301 \n", + " Chinese 88.4 301 \n", + " Other 90.7 301 \n", + " Other Asian 88.4 301 \n", + " British or Mixed British 89.2 259 \n", + " Indian or British Indian 89.7 273 \n", + " Irish 87.5 280 \n", + " Other Black 90.2 287 \n", + " Other White 92.3 273 \n", + " Other mixed 89.5 266 \n", + " Pakistani or British Pakistani 95.3 301 \n", + " Unknown 88.2 833 \n", + " White + Asian 92.7 287 \n", + " White + Black African 93.0 301 \n", + " White + Black Caribbean 91.1 315 \n", + "imd_categories 1 Most deprived 89.0 1015 \n", + " 2 90.5 1036 \n", + " 3 90.8 1071 \n", + " 4 90.9 1001 \n", + " 5 Least deprived 90.1 1057 \n", + " Unknown 90.0 280 \n", + "bmi 30+ 90.9 1624 \n", + " under 30 90.1 3829 \n", + "chronic_cardiac_disease no 90.3 5411 \n", + " yes 100.0 42 \n", + "current_copd no 90.3 5397 \n", + " yes 100.0 56 \n", + "dmards no 90.3 5397 \n", + " yes 100.0 56 \n", + "dementia no 90.4 5376 \n", + " yes 90.9 77 \n", + "psychosis_schiz_bipolar no 90.3 5404 \n", + " yes 100.0 49 \n", + "ssri no 90.3 5404 \n", + " yes 85.7 49 \n", + "chemo_or_radio no 90.3 5397 \n", + " yes 88.9 63 \n", + "lung_cancer no 90.3 5411 \n", + " yes 85.7 49 \n", + "cancer_excl_lung_and_haem no 90.4 5397 \n", + " yes 87.5 56 \n", + "haematological_cancer no 90.4 5404 \n", + " yes 85.7 49 \n", + "ckd no 90.5 4403 \n", + " yes 89.4 1057 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.0 \n", - "sex F 87.9 \n", - " M 88.0 \n", - "ethnicity_6_groups Black 88.1 \n", - " Mixed 89.4 \n", - " Other 89.1 \n", - " South Asian 87.7 \n", - " Unknown 84.6 \n", - " White 88.1 \n", - "ethnicity_16_groups African 88.2 \n", - " Bangladeshi or British Bangladeshi 90.9 \n", - " Caribbean 90.5 \n", - " Chinese 86.4 \n", - " Other 90.9 \n", - " Other Asian 88.9 \n", - " British or Mixed British 90.5 \n", - " Indian or British Indian 89.5 \n", - " Irish 90.9 \n", - " Other Black 88.9 \n", - " Other White 82.6 \n", - " Other mixed 85.7 \n", - " Pakistani or British Pakistani 95.2 \n", - " Unknown 87.9 \n", - " White + Asian 78.9 \n", - " White + Black African 89.5 \n", - " White + Black Caribbean 88.9 \n", - "imd_categories 1 Most deprived 88.9 \n", - " 2 87.2 \n", - " 3 87.5 \n", - " 4 87.0 \n", - " 5 Least deprived 88.9 \n", - " Unknown 89.5 \n", - "bmi 30+ 88.1 \n", - " under 30 87.9 \n", - "chronic_cardiac_disease no 88.1 \n", - " yes 80.0 \n", - "current_copd no 88.1 \n", - " yes 100.0 \n", - "dmards no 87.9 \n", - " yes 100.0 \n", - "dementia no 88.1 \n", + "overall overall 89.0 \n", + "sex F 89.0 \n", + " M 88.9 \n", + "ethnicity_6_groups Black 89.1 \n", + " Mixed 88.9 \n", + " Other 88.9 \n", + " South Asian 87.8 \n", + " Unknown 88.9 \n", + " White 89.6 \n", + "ethnicity_16_groups African 90.0 \n", + " Bangladeshi or British Bangladeshi 88.4 \n", + " Caribbean 93.0 \n", + " Chinese 88.4 \n", + " Other 88.4 \n", + " Other Asian 88.4 \n", + " British or Mixed British 86.5 \n", + " Indian or British Indian 89.7 \n", + " Irish 82.5 \n", + " Other Black 87.8 \n", + " Other White 89.7 \n", + " Other mixed 89.5 \n", + " Pakistani or British Pakistani 93.0 \n", + " Unknown 86.6 \n", + " White + Asian 92.7 \n", + " White + Black African 90.7 \n", + " White + Black Caribbean 91.1 \n", + "imd_categories 1 Most deprived 87.6 \n", + " 2 89.2 \n", + " 3 89.5 \n", + " 4 90.2 \n", + " 5 Least deprived 88.1 \n", + " Unknown 90.0 \n", + "bmi 30+ 89.7 \n", + " under 30 88.7 \n", + "chronic_cardiac_disease no 88.9 \n", " yes 100.0 \n", - "psychosis_schiz_bipolar no 88.1 \n", + "current_copd no 88.8 \n", " yes 100.0 \n", - "ssri no 88.1 \n", - " yes 75.0 \n", - "chemo_or_radio no 87.8 \n", - " yes 80.0 \n", - "lung_cancer no 87.9 \n", + "dmards no 88.8 \n", " yes 100.0 \n", - "cancer_excl_lung_and_haem no 87.9 \n", + "dementia no 88.9 \n", + " yes 90.9 \n", + "psychosis_schiz_bipolar no 88.9 \n", " yes 100.0 \n", - "haematological_cancer no 87.8 \n", - " yes 80.0 \n", - "ckd no 87.7 \n", - " yes 88.8 \n", + "ssri no 89.0 \n", + " yes 85.7 \n", + "chemo_or_radio no 88.8 \n", + " yes 88.9 \n", + "lung_cancer no 88.9 \n", + " yes 85.7 \n", + "cancer_excl_lung_and_haem no 89.0 \n", + " yes 87.5 \n", + "haematological_cancer no 89.0 \n", + " yes 85.7 \n", + "ckd no 89.2 \n", + " yes 87.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.8 \n", - "sex F 1.6 \n", + "overall overall 1.4 \n", + "sex F 1.3 \n", " M 1.6 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 3.0 \n", - " Other 3.1 \n", - " South Asian 1.5 \n", - " Unknown 1.9 \n", - " White 1.5 \n", - "ethnicity_16_groups African 0.0 \n", + "ethnicity_6_groups Black 0.7 \n", + " Mixed 1.5 \n", + " Other 2.4 \n", + " South Asian 0.7 \n", + " Unknown 1.7 \n", + " White 1.4 \n", + "ethnicity_16_groups African 2.5 \n", " Bangladeshi or British Bangladeshi 0.0 \n", " Caribbean 0.0 \n", - " Chinese 4.5 \n", - " Other 0.0 \n", - " Other Asian 5.5 \n", - " British or Mixed British 0.0 \n", + " Chinese 0.0 \n", + " Other 2.3 \n", + " Other Asian 0.0 \n", + " British or Mixed British 2.7 \n", " Indian or British Indian 0.0 \n", - " Irish 0.0 \n", - " Other Black 0.0 \n", - " Other White 4.4 \n", - " Other mixed 4.8 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 0.0 \n", - " White + Asian 5.3 \n", - " White + Black African 0.0 \n", + " Irish 5.0 \n", + " Other Black 2.4 \n", + " Other White 2.6 \n", + " Other mixed 0.0 \n", + " Pakistani or British Pakistani 2.3 \n", + " Unknown 1.6 \n", + " White + Asian 0.0 \n", + " White + Black African 2.3 \n", " White + Black Caribbean 0.0 \n", "imd_categories 1 Most deprived 1.4 \n", " 2 1.3 \n", - " 3 2.8 \n", - " 4 1.4 \n", - " 5 Least deprived 1.4 \n", + " 3 1.3 \n", + " 4 0.7 \n", + " 5 Least deprived 2.0 \n", " Unknown 0.0 \n", - "bmi 30+ 1.7 \n", - " under 30 1.9 \n", - "chronic_cardiac_disease no 1.6 \n", + "bmi 30+ 1.2 \n", + " under 30 1.4 \n", + "chronic_cardiac_disease no 1.4 \n", " yes 0.0 \n", - "current_copd no 1.6 \n", + "current_copd no 1.5 \n", " yes 0.0 \n", - "dmards no 1.8 \n", + "dmards no 1.5 \n", " yes 0.0 \n", - "dementia no 1.6 \n", + "dementia no 1.5 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.6 \n", + "psychosis_schiz_bipolar no 1.4 \n", " yes 0.0 \n", - "ssri no 1.6 \n", + "ssri no 1.3 \n", " yes 0.0 \n", - "chemo_or_radio no 1.9 \n", + "chemo_or_radio no 1.5 \n", " yes 0.0 \n", - "lung_cancer no 1.8 \n", + "lung_cancer no 1.4 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.8 \n", + "cancer_excl_lung_and_haem no 1.4 \n", " yes 0.0 \n", - "haematological_cancer no 1.9 \n", + "haematological_cancer no 1.4 \n", " yes 0.0 \n", - "ckd no 1.7 \n", - " yes 1.2 \n", + "ckd no 1.3 \n", + " yes 2.0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 15-Dec \n", - "sex F 17-Dec \n", - " M 16-Dec \n", - "ethnicity_6_groups Black unknown \n", + "overall overall reached \n", + "sex F reached \n", + " M reached \n", + "ethnicity_6_groups Black 04-Feb \n", " Mixed reached \n", " Other reached \n", - " South Asian 18-Dec \n", - " Unknown 27-Dec \n", - " White 16-Dec \n", - "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi reached \n", + " South Asian 17-Feb \n", + " Unknown reached \n", + " White reached \n", + "ethnicity_16_groups African reached \n", + " Bangladeshi or British Bangladeshi unknown \n", " Caribbean reached \n", - " Chinese reached \n", + " Chinese unknown \n", " Other reached \n", - " Other Asian reached \n", - " British or Mixed British reached \n", + " Other Asian unknown \n", + " British or Mixed British 04-Feb \n", " Indian or British Indian unknown \n", - " Irish reached \n", - " Other Black unknown \n", - " Other White 19-Dec \n", - " Other mixed reached \n", + " Irish 05-Feb \n", + " Other Black reached \n", + " Other White reached \n", + " Other mixed unknown \n", " Pakistani or British Pakistani reached \n", - " Unknown unknown \n", - " White + Asian 22-Dec \n", - " White + Black African unknown \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived reached \n", - " 2 23-Dec \n", + " Unknown 09-Feb \n", + " White + Asian reached \n", + " White + Black African reached \n", + " White + Black Caribbean reached \n", + "imd_categories 1 Most deprived 07-Feb \n", + " 2 reached \n", " 3 reached \n", - " 4 23-Dec \n", + " 4 reached \n", " 5 Least deprived reached \n", " Unknown unknown \n", - "bmi 30+ 15-Dec \n", - " under 30 15-Dec \n", - "chronic_cardiac_disease no 16-Dec \n", - " yes unknown \n", - "current_copd no 16-Dec \n", + "bmi 30+ reached \n", + " under 30 reached \n", + "chronic_cardiac_disease no reached \n", " yes reached \n", - "dmards no 16-Dec \n", + "current_copd no reached \n", + " yes reached \n", + "dmards no reached \n", " yes reached \n", - "dementia no 16-Dec \n", + "dementia no reached \n", " yes reached \n", - "psychosis_schiz_bipolar no 16-Dec \n", + "psychosis_schiz_bipolar no reached \n", " yes reached \n", - "ssri no 16-Dec \n", + "ssri no reached \n", " yes unknown \n", - "chemo_or_radio no 16-Dec \n", + "chemo_or_radio no reached \n", " yes unknown \n", - "lung_cancer no 16-Dec \n", - " yes reached \n", - "cancer_excl_lung_and_haem no 16-Dec \n", - " yes reached \n", - "haematological_cancer no 16-Dec \n", + "lung_cancer no reached \n", " yes unknown \n", - "ckd no 17-Dec \n", - " yes reached " + "cancer_excl_lung_and_haem no reached \n", + " yes unknown \n", + "haematological_cancer no reached \n", + " yes unknown \n", + "ckd no reached \n", + " yes 04-Feb " ] }, "metadata": {}, @@ -6491,7 +6543,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **55-59** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **55-59** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -6557,428 +6609,428 @@ " \n", " overall\n", " overall\n", - " 2863\n", - " 89.9\n", - " 3185\n", - " 88.1\n", - " 1.8\n", - " 15-Dec\n", + " 5621\n", + " 90.3\n", + " 6223\n", + " 88.8\n", + " 1.5\n", + " reached\n", " \n", " \n", " sex\n", " F\n", - " 1463\n", - " 90.1\n", - " 1624\n", - " 88.4\n", - " 1.7\n", + " 2891\n", + " 90.2\n", + " 3206\n", + " 88.9\n", + " 1.3\n", " reached\n", " \n", " \n", " M\n", - " 1400\n", - " 89.7\n", - " 1561\n", - " 87.9\n", - " 1.8\n", - " 16-Dec\n", + " 2730\n", + " 90.5\n", + " 3017\n", + " 88.9\n", + " 1.6\n", + " reached\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 511\n", - " 89.0\n", - " 574\n", - " 86.6\n", - " 2.4\n", - " 17-Dec\n", + " 938\n", + " 90.5\n", + " 1036\n", + " 89.2\n", + " 1.3\n", + " reached\n", " \n", " \n", " Mixed\n", - " 511\n", - " 89.0\n", - " 574\n", - " 87.8\n", - " 1.2\n", - " 20-Dec\n", + " 959\n", + " 90.1\n", + " 1064\n", + " 87.5\n", + " 2.6\n", + " reached\n", " \n", " \n", " Other\n", - " 469\n", - " 90.5\n", - " 518\n", - " 89.2\n", - " 1.3\n", + " 994\n", + " 91.6\n", + " 1085\n", + " 91.0\n", + " 0.6\n", " reached\n", " \n", " \n", " South Asian\n", - " 490\n", - " 90.9\n", - " 539\n", - " 88.3\n", - " 2.6\n", - " reached\n", + " 910\n", + " 89.0\n", + " 1022\n", + " 87.0\n", + " 2.0\n", + " 05-Feb\n", " \n", " \n", " Unknown\n", - " 378\n", - " 90.0\n", - " 420\n", - " 88.3\n", - " 1.7\n", + " 861\n", + " 90.4\n", + " 952\n", + " 88.2\n", + " 2.2\n", " reached\n", " \n", " \n", " White\n", - " 504\n", - " 91.1\n", - " 553\n", - " 89.9\n", - " 1.2\n", + " 966\n", + " 90.2\n", + " 1071\n", + " 88.9\n", + " 1.3\n", " reached\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 161\n", - " 92.0\n", - " 175\n", - " 92.0\n", + " 280\n", + " 87.0\n", + " 322\n", + " 87.0\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 147\n", - " 87.5\n", - " 168\n", - " 83.3\n", - " 4.2\n", - " 19-Dec\n", + " 280\n", + " 93.0\n", + " 301\n", + " 90.7\n", + " 2.3\n", + " reached\n", " \n", " \n", " Caribbean\n", - " 140\n", - " 87.0\n", - " 161\n", - " 87.0\n", + " 294\n", + " 89.4\n", + " 329\n", + " 89.4\n", " 0.0\n", " unknown\n", " \n", " \n", " Chinese\n", - " 161\n", - " 88.5\n", - " 182\n", - " 84.6\n", - " 3.9\n", - " 17-Dec\n", + " 259\n", + " 88.1\n", + " 294\n", + " 85.7\n", + " 2.4\n", + " 07-Feb\n", " \n", " \n", " Other\n", - " 133\n", - " 90.5\n", - " 147\n", - " 85.7\n", - " 4.8\n", - " reached\n", + " 294\n", + " 89.4\n", + " 329\n", + " 87.2\n", + " 2.2\n", + " 03-Feb\n", " \n", " \n", " Other Asian\n", - " 154\n", - " 95.7\n", - " 161\n", - " 91.3\n", - " 4.4\n", - " reached\n", + " 273\n", + " 88.6\n", + " 308\n", + " 88.6\n", + " 0.0\n", + " unknown\n", " \n", " \n", " British or Mixed British\n", - " 154\n", - " 95.7\n", - " 161\n", - " 95.7\n", - " 0.0\n", + " 315\n", + " 93.8\n", + " 336\n", + " 91.7\n", + " 2.1\n", " reached\n", " \n", " \n", " Indian or British Indian\n", - " 154\n", - " 91.7\n", - " 168\n", - " 91.7\n", + " 287\n", + " 89.1\n", + " 322\n", + " 89.1\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " Irish\n", - " 154\n", - " 88.0\n", - " 175\n", - " 88.0\n", - " 0.0\n", - " unknown\n", + " 301\n", + " 89.6\n", + " 336\n", + " 87.5\n", + " 2.1\n", + " 03-Feb\n", " \n", " \n", " Other Black\n", - " 140\n", - " 90.9\n", - " 154\n", - " 90.9\n", - " 0.0\n", + " 315\n", + " 91.8\n", + " 343\n", + " 89.8\n", + " 2.0\n", " reached\n", " \n", " \n", " Other White\n", - " 140\n", - " 90.9\n", - " 154\n", - " 86.4\n", - " 4.5\n", + " 315\n", + " 90.0\n", + " 350\n", + " 88.0\n", + " 2.0\n", " reached\n", " \n", " \n", " Other mixed\n", - " 154\n", - " 84.6\n", - " 182\n", - " 80.8\n", - " 3.8\n", - " 24-Dec\n", + " 287\n", + " 93.2\n", + " 308\n", + " 90.9\n", + " 2.3\n", + " reached\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 175\n", - " 92.6\n", - " 189\n", - " 92.6\n", + " 322\n", + " 90.2\n", + " 357\n", + " 90.2\n", " 0.0\n", " reached\n", " \n", " \n", " Unknown\n", - " 434\n", - " 89.9\n", - " 483\n", - " 87.0\n", - " 2.9\n", - " 15-Dec\n", + " 854\n", + " 89.7\n", + " 952\n", + " 89.0\n", + " 0.7\n", + " 05-Feb\n", " \n", " \n", " White + Asian\n", - " 154\n", - " 91.7\n", - " 168\n", - " 91.7\n", - " 0.0\n", - " reached\n", + " 294\n", + " 87.5\n", + " 336\n", + " 85.4\n", + " 2.1\n", + " 10-Feb\n", " \n", " \n", " White + Black African\n", - " 154\n", - " 95.7\n", - " 161\n", - " 91.3\n", - " 4.4\n", - " reached\n", + " 336\n", + " 88.9\n", + " 378\n", + " 88.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 168\n", - " 92.3\n", - " 182\n", - " 88.5\n", - " 3.8\n", + " 301\n", + " 91.5\n", + " 329\n", + " 87.2\n", + " 4.3\n", " reached\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 532\n", - " 87.4\n", - " 609\n", - " 86.2\n", - " 1.2\n", - " 30-Dec\n", + " 1099\n", + " 89.7\n", + " 1225\n", + " 88.0\n", + " 1.7\n", + " 03-Feb\n", " \n", " \n", " 2\n", - " 581\n", + " 1029\n", " 90.2\n", - " 644\n", - " 88.0\n", - " 2.2\n", + " 1141\n", + " 89.0\n", + " 1.2\n", " reached\n", " \n", " \n", " 3\n", - " 532\n", - " 90.5\n", - " 588\n", - " 89.3\n", + " 1099\n", + " 90.8\n", + " 1211\n", + " 89.6\n", " 1.2\n", " reached\n", " \n", " \n", " 4\n", - " 539\n", - " 89.5\n", - " 602\n", - " 88.4\n", - " 1.1\n", - " 18-Dec\n", + " 1085\n", + " 91.7\n", + " 1183\n", + " 89.9\n", + " 1.8\n", + " reached\n", " \n", " \n", " 5 Least deprived\n", - " 525\n", - " 92.6\n", - " 567\n", - " 90.1\n", - " 2.5\n", + " 1029\n", + " 90.2\n", + " 1141\n", + " 88.3\n", + " 1.9\n", " reached\n", " \n", " \n", " Unknown\n", - " 154\n", - " 88.0\n", - " 175\n", - " 88.0\n", - " 0.0\n", - " unknown\n", + " 287\n", + " 89.1\n", + " 322\n", + " 87.0\n", + " 2.1\n", + " 05-Feb\n", " \n", " \n", " bmi\n", " 30+\n", - " 868\n", - " 90.5\n", - " 959\n", - " 89.1\n", - " 1.4\n", + " 1652\n", + " 91.5\n", + " 1806\n", + " 89.9\n", + " 1.6\n", " reached\n", " \n", " \n", " under 30\n", - " 1995\n", - " 89.6\n", - " 2226\n", - " 87.7\n", - " 1.9\n", - " 16-Dec\n", + " 3969\n", + " 89.9\n", + " 4417\n", + " 88.3\n", + " 1.6\n", + " 02-Feb\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 2828\n", - " 90.0\n", - " 3143\n", - " 88.2\n", - " 1.8\n", + " 5551\n", + " 90.2\n", + " 6153\n", + " 88.6\n", + " 1.6\n", " reached\n", " \n", " \n", " yes\n", - " 35\n", - " 83.3\n", - " 42\n", - " 83.3\n", + " 70\n", + " 90.9\n", + " 77\n", + " 90.9\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " current_copd\n", " no\n", - " 2835\n", - " 90.0\n", - " 3150\n", - " 88.2\n", - " 1.8\n", + " 5579\n", + " 90.4\n", + " 6174\n", + " 88.8\n", + " 1.6\n", " reached\n", " \n", " \n", " yes\n", - " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 42\n", + " 75.0\n", + " 56\n", + " 75.0\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 2835\n", - " 90.0\n", - " 3150\n", - " 88.2\n", - " 1.8\n", + " 5558\n", + " 90.2\n", + " 6160\n", + " 88.6\n", + " 1.6\n", " reached\n", " \n", " \n", " yes\n", - " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 63\n", + " 90.0\n", + " 70\n", + " 90.0\n", " 0.0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 2828\n", - " 89.8\n", - " 3150\n", - " 88.2\n", - " 1.6\n", - " 15-Dec\n", + " 5565\n", + " 90.2\n", + " 6167\n", + " 88.8\n", + " 1.4\n", + " reached\n", " \n", " \n", " yes\n", - " 35\n", - " 100.0\n", - " 35\n", - " 80.0\n", - " 20.0\n", - " reached\n", + " 56\n", + " 88.9\n", + " 63\n", + " 77.8\n", + " 11.1\n", + " 02-Feb\n", " \n", " \n", " ssri\n", " no\n", - " 2828\n", - " 90.0\n", - " 3143\n", - " 88.4\n", - " 1.6\n", + " 5558\n", + " 90.2\n", + " 6160\n", + " 88.8\n", + " 1.4\n", " reached\n", " \n", " \n", " yes\n", - " 35\n", - " 83.3\n", - " 42\n", - " 83.3\n", + " 63\n", + " 90.0\n", + " 70\n", + " 90.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 2338\n", - " 90.0\n", - " 2597\n", - " 88.1\n", - " 1.9\n", + " 4452\n", + " 90.1\n", + " 4942\n", + " 88.7\n", + " 1.4\n", " reached\n", " \n", " \n", " yes\n", - " 525\n", - " 89.3\n", - " 588\n", - " 88.1\n", - " 1.2\n", - " 19-Dec\n", + " 1169\n", + " 90.8\n", + " 1288\n", + " 88.6\n", + " 2.2\n", + " reached\n", " \n", " \n", "\n", @@ -6987,248 +7039,248 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 2863 \n", - "sex F 1463 \n", - " M 1400 \n", - "ethnicity_6_groups Black 511 \n", - " Mixed 511 \n", - " Other 469 \n", - " South Asian 490 \n", - " Unknown 378 \n", - " White 504 \n", - "ethnicity_16_groups African 161 \n", - " Bangladeshi or British Bangladeshi 147 \n", - " Caribbean 140 \n", - " Chinese 161 \n", - " Other 133 \n", - " Other Asian 154 \n", - " British or Mixed British 154 \n", - " Indian or British Indian 154 \n", - " Irish 154 \n", - " Other Black 140 \n", - " Other White 140 \n", - " Other mixed 154 \n", - " Pakistani or British Pakistani 175 \n", - " Unknown 434 \n", - " White + Asian 154 \n", - " White + Black African 154 \n", - " White + Black Caribbean 168 \n", - "imd_categories 1 Most deprived 532 \n", - " 2 581 \n", - " 3 532 \n", - " 4 539 \n", - " 5 Least deprived 525 \n", - " Unknown 154 \n", - "bmi 30+ 868 \n", - " under 30 1995 \n", - "chronic_cardiac_disease no 2828 \n", - " yes 35 \n", - "current_copd no 2835 \n", - " yes 28 \n", - "dmards no 2835 \n", - " yes 28 \n", - "psychosis_schiz_bipolar no 2828 \n", - " yes 35 \n", - "ssri no 2828 \n", - " yes 35 \n", - "ckd no 2338 \n", - " yes 525 \n", + "overall overall 5621 \n", + "sex F 2891 \n", + " M 2730 \n", + "ethnicity_6_groups Black 938 \n", + " Mixed 959 \n", + " Other 994 \n", + " South Asian 910 \n", + " Unknown 861 \n", + " White 966 \n", + "ethnicity_16_groups African 280 \n", + " Bangladeshi or British Bangladeshi 280 \n", + " Caribbean 294 \n", + " Chinese 259 \n", + " Other 294 \n", + " Other Asian 273 \n", + " British or Mixed British 315 \n", + " Indian or British Indian 287 \n", + " Irish 301 \n", + " Other Black 315 \n", + " Other White 315 \n", + " Other mixed 287 \n", + " Pakistani or British Pakistani 322 \n", + " Unknown 854 \n", + " White + Asian 294 \n", + " White + Black African 336 \n", + " White + Black Caribbean 301 \n", + "imd_categories 1 Most deprived 1099 \n", + " 2 1029 \n", + " 3 1099 \n", + " 4 1085 \n", + " 5 Least deprived 1029 \n", + " Unknown 287 \n", + "bmi 30+ 1652 \n", + " under 30 3969 \n", + "chronic_cardiac_disease no 5551 \n", + " yes 70 \n", + "current_copd no 5579 \n", + " yes 42 \n", + "dmards no 5558 \n", + " yes 63 \n", + "psychosis_schiz_bipolar no 5565 \n", + " yes 56 \n", + "ssri no 5558 \n", + " yes 63 \n", + "ckd no 4452 \n", + " yes 1169 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 89.9 3185 \n", - "sex F 90.1 1624 \n", - " M 89.7 1561 \n", - "ethnicity_6_groups Black 89.0 574 \n", - " Mixed 89.0 574 \n", - " Other 90.5 518 \n", - " South Asian 90.9 539 \n", - " Unknown 90.0 420 \n", - " White 91.1 553 \n", - "ethnicity_16_groups African 92.0 175 \n", - " Bangladeshi or British Bangladeshi 87.5 168 \n", - " Caribbean 87.0 161 \n", - " Chinese 88.5 182 \n", - " Other 90.5 147 \n", - " Other Asian 95.7 161 \n", - " British or Mixed British 95.7 161 \n", - " Indian or British Indian 91.7 168 \n", - " Irish 88.0 175 \n", - " Other Black 90.9 154 \n", - " Other White 90.9 154 \n", - " Other mixed 84.6 182 \n", - " Pakistani or British Pakistani 92.6 189 \n", - " Unknown 89.9 483 \n", - " White + Asian 91.7 168 \n", - " White + Black African 95.7 161 \n", - " White + Black Caribbean 92.3 182 \n", - "imd_categories 1 Most deprived 87.4 609 \n", - " 2 90.2 644 \n", - " 3 90.5 588 \n", - " 4 89.5 602 \n", - " 5 Least deprived 92.6 567 \n", - " Unknown 88.0 175 \n", - "bmi 30+ 90.5 959 \n", - " under 30 89.6 2226 \n", - "chronic_cardiac_disease no 90.0 3143 \n", - " yes 83.3 42 \n", - "current_copd no 90.0 3150 \n", - " yes 80.0 35 \n", - "dmards no 90.0 3150 \n", - " yes 80.0 35 \n", - "psychosis_schiz_bipolar no 89.8 3150 \n", - " yes 100.0 35 \n", - "ssri no 90.0 3143 \n", - " yes 83.3 42 \n", - "ckd no 90.0 2597 \n", - " yes 89.3 588 \n", + "overall overall 90.3 6223 \n", + "sex F 90.2 3206 \n", + " M 90.5 3017 \n", + "ethnicity_6_groups Black 90.5 1036 \n", + " Mixed 90.1 1064 \n", + " Other 91.6 1085 \n", + " South Asian 89.0 1022 \n", + " Unknown 90.4 952 \n", + " White 90.2 1071 \n", + "ethnicity_16_groups African 87.0 322 \n", + " Bangladeshi or British Bangladeshi 93.0 301 \n", + " Caribbean 89.4 329 \n", + " Chinese 88.1 294 \n", + " Other 89.4 329 \n", + " Other Asian 88.6 308 \n", + " British or Mixed British 93.8 336 \n", + " Indian or British Indian 89.1 322 \n", + " Irish 89.6 336 \n", + " Other Black 91.8 343 \n", + " Other White 90.0 350 \n", + " Other mixed 93.2 308 \n", + " Pakistani or British Pakistani 90.2 357 \n", + " Unknown 89.7 952 \n", + " White + Asian 87.5 336 \n", + " White + Black African 88.9 378 \n", + " White + Black Caribbean 91.5 329 \n", + "imd_categories 1 Most deprived 89.7 1225 \n", + " 2 90.2 1141 \n", + " 3 90.8 1211 \n", + " 4 91.7 1183 \n", + " 5 Least deprived 90.2 1141 \n", + " Unknown 89.1 322 \n", + "bmi 30+ 91.5 1806 \n", + " under 30 89.9 4417 \n", + "chronic_cardiac_disease no 90.2 6153 \n", + " yes 90.9 77 \n", + "current_copd no 90.4 6174 \n", + " yes 75.0 56 \n", + "dmards no 90.2 6160 \n", + " yes 90.0 70 \n", + "psychosis_schiz_bipolar no 90.2 6167 \n", + " yes 88.9 63 \n", + "ssri no 90.2 6160 \n", + " yes 90.0 70 \n", + "ckd no 90.1 4942 \n", + " yes 90.8 1288 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.1 \n", - "sex F 88.4 \n", - " M 87.9 \n", - "ethnicity_6_groups Black 86.6 \n", - " Mixed 87.8 \n", - " Other 89.2 \n", - " South Asian 88.3 \n", - " Unknown 88.3 \n", - " White 89.9 \n", - "ethnicity_16_groups African 92.0 \n", - " Bangladeshi or British Bangladeshi 83.3 \n", - " Caribbean 87.0 \n", - " Chinese 84.6 \n", - " Other 85.7 \n", - " Other Asian 91.3 \n", - " British or Mixed British 95.7 \n", - " Indian or British Indian 91.7 \n", - " Irish 88.0 \n", - " Other Black 90.9 \n", - " Other White 86.4 \n", - " Other mixed 80.8 \n", - " Pakistani or British Pakistani 92.6 \n", + "overall overall 88.8 \n", + "sex F 88.9 \n", + " M 88.9 \n", + "ethnicity_6_groups Black 89.2 \n", + " Mixed 87.5 \n", + " Other 91.0 \n", + " South Asian 87.0 \n", + " Unknown 88.2 \n", + " White 88.9 \n", + "ethnicity_16_groups African 87.0 \n", + " Bangladeshi or British Bangladeshi 90.7 \n", + " Caribbean 89.4 \n", + " Chinese 85.7 \n", + " Other 87.2 \n", + " Other Asian 88.6 \n", + " British or Mixed British 91.7 \n", + " Indian or British Indian 89.1 \n", + " Irish 87.5 \n", + " Other Black 89.8 \n", + " Other White 88.0 \n", + " Other mixed 90.9 \n", + " Pakistani or British Pakistani 90.2 \n", + " Unknown 89.0 \n", + " White + Asian 85.4 \n", + " White + Black African 88.9 \n", + " White + Black Caribbean 87.2 \n", + "imd_categories 1 Most deprived 88.0 \n", + " 2 89.0 \n", + " 3 89.6 \n", + " 4 89.9 \n", + " 5 Least deprived 88.3 \n", " Unknown 87.0 \n", - " White + Asian 91.7 \n", - " White + Black African 91.3 \n", - " White + Black Caribbean 88.5 \n", - "imd_categories 1 Most deprived 86.2 \n", - " 2 88.0 \n", - " 3 89.3 \n", - " 4 88.4 \n", - " 5 Least deprived 90.1 \n", - " Unknown 88.0 \n", - "bmi 30+ 89.1 \n", - " under 30 87.7 \n", - "chronic_cardiac_disease no 88.2 \n", - " yes 83.3 \n", - "current_copd no 88.2 \n", - " yes 80.0 \n", - "dmards no 88.2 \n", - " yes 80.0 \n", - "psychosis_schiz_bipolar no 88.2 \n", - " yes 80.0 \n", - "ssri no 88.4 \n", - " yes 83.3 \n", - "ckd no 88.1 \n", - " yes 88.1 \n", + "bmi 30+ 89.9 \n", + " under 30 88.3 \n", + "chronic_cardiac_disease no 88.6 \n", + " yes 90.9 \n", + "current_copd no 88.8 \n", + " yes 75.0 \n", + "dmards no 88.6 \n", + " yes 90.0 \n", + "psychosis_schiz_bipolar no 88.8 \n", + " yes 77.8 \n", + "ssri no 88.8 \n", + " yes 90.0 \n", + "ckd no 88.7 \n", + " yes 88.6 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.8 \n", - "sex F 1.7 \n", - " M 1.8 \n", - "ethnicity_6_groups Black 2.4 \n", - " Mixed 1.2 \n", - " Other 1.3 \n", - " South Asian 2.6 \n", - " Unknown 1.7 \n", - " White 1.2 \n", + "overall overall 1.5 \n", + "sex F 1.3 \n", + " M 1.6 \n", + "ethnicity_6_groups Black 1.3 \n", + " Mixed 2.6 \n", + " Other 0.6 \n", + " South Asian 2.0 \n", + " Unknown 2.2 \n", + " White 1.3 \n", "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 4.2 \n", + " Bangladeshi or British Bangladeshi 2.3 \n", " Caribbean 0.0 \n", - " Chinese 3.9 \n", - " Other 4.8 \n", - " Other Asian 4.4 \n", - " British or Mixed British 0.0 \n", + " Chinese 2.4 \n", + " Other 2.2 \n", + " Other Asian 0.0 \n", + " British or Mixed British 2.1 \n", " Indian or British Indian 0.0 \n", - " Irish 0.0 \n", - " Other Black 0.0 \n", - " Other White 4.5 \n", - " Other mixed 3.8 \n", + " Irish 2.1 \n", + " Other Black 2.0 \n", + " Other White 2.0 \n", + " Other mixed 2.3 \n", " Pakistani or British Pakistani 0.0 \n", - " Unknown 2.9 \n", - " White + Asian 0.0 \n", - " White + Black African 4.4 \n", - " White + Black Caribbean 3.8 \n", - "imd_categories 1 Most deprived 1.2 \n", - " 2 2.2 \n", + " Unknown 0.7 \n", + " White + Asian 2.1 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 4.3 \n", + "imd_categories 1 Most deprived 1.7 \n", + " 2 1.2 \n", " 3 1.2 \n", - " 4 1.1 \n", - " 5 Least deprived 2.5 \n", - " Unknown 0.0 \n", - "bmi 30+ 1.4 \n", - " under 30 1.9 \n", - "chronic_cardiac_disease no 1.8 \n", + " 4 1.8 \n", + " 5 Least deprived 1.9 \n", + " Unknown 2.1 \n", + "bmi 30+ 1.6 \n", + " under 30 1.6 \n", + "chronic_cardiac_disease no 1.6 \n", " yes 0.0 \n", - "current_copd no 1.8 \n", + "current_copd no 1.6 \n", " yes 0.0 \n", - "dmards no 1.8 \n", + "dmards no 1.6 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.6 \n", - " yes 20.0 \n", - "ssri no 1.6 \n", + "psychosis_schiz_bipolar no 1.4 \n", + " yes 11.1 \n", + "ssri no 1.4 \n", " yes 0.0 \n", - "ckd no 1.9 \n", - " yes 1.2 \n", + "ckd no 1.4 \n", + " yes 2.2 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 15-Dec \n", + "overall overall reached \n", "sex F reached \n", - " M 16-Dec \n", - "ethnicity_6_groups Black 17-Dec \n", - " Mixed 20-Dec \n", + " M reached \n", + "ethnicity_6_groups Black reached \n", + " Mixed reached \n", " Other reached \n", - " South Asian reached \n", + " South Asian 05-Feb \n", " Unknown reached \n", " White reached \n", - "ethnicity_16_groups African reached \n", - " Bangladeshi or British Bangladeshi 19-Dec \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi reached \n", " Caribbean unknown \n", - " Chinese 17-Dec \n", - " Other reached \n", - " Other Asian reached \n", + " Chinese 07-Feb \n", + " Other 03-Feb \n", + " Other Asian unknown \n", " British or Mixed British reached \n", - " Indian or British Indian reached \n", - " Irish unknown \n", + " Indian or British Indian unknown \n", + " Irish 03-Feb \n", " Other Black reached \n", " Other White reached \n", - " Other mixed 24-Dec \n", + " Other mixed reached \n", " Pakistani or British Pakistani reached \n", - " Unknown 15-Dec \n", - " White + Asian reached \n", - " White + Black African reached \n", + " Unknown 05-Feb \n", + " White + Asian 10-Feb \n", + " White + Black African unknown \n", " White + Black Caribbean reached \n", - "imd_categories 1 Most deprived 30-Dec \n", + "imd_categories 1 Most deprived 03-Feb \n", " 2 reached \n", " 3 reached \n", - " 4 18-Dec \n", + " 4 reached \n", " 5 Least deprived reached \n", - " Unknown unknown \n", + " Unknown 05-Feb \n", "bmi 30+ reached \n", - " under 30 16-Dec \n", + " under 30 02-Feb \n", "chronic_cardiac_disease no reached \n", - " yes unknown \n", + " yes reached \n", "current_copd no reached \n", " yes unknown \n", "dmards no reached \n", " yes unknown \n", - "psychosis_schiz_bipolar no 15-Dec \n", - " yes reached \n", + "psychosis_schiz_bipolar no reached \n", + " yes 02-Feb \n", "ssri no reached \n", " yes unknown \n", "ckd no reached \n", - " yes 19-Dec " + " yes reached " ] }, "metadata": {}, @@ -7257,7 +7309,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **50-54** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **50-54** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -7323,387 +7375,387 @@ " \n", " overall\n", " overall\n", - " 3080\n", - " 89.1\n", - " 3458\n", - " 87.7\n", - " 1.4\n", - " 19-Dec\n", + " 6013\n", + " 89.4\n", + " 6727\n", + " 87.8\n", + " 1.6\n", + " 04-Feb\n", " \n", " \n", " sex\n", " F\n", - " 1582\n", + " 3038\n", " 89.3\n", - " 1771\n", - " 88.1\n", - " 1.2\n", - " 19-Dec\n", + " 3402\n", + " 87.9\n", + " 1.4\n", + " 05-Feb\n", " \n", " \n", " M\n", - " 1498\n", - " 88.8\n", - " 1687\n", - " 87.6\n", - " 1.2\n", - " 22-Dec\n", + " 2975\n", + " 89.5\n", + " 3325\n", + " 87.8\n", + " 1.7\n", + " 04-Feb\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 532\n", - " 89.4\n", - " 595\n", - " 88.2\n", - " 1.2\n", - " 18-Dec\n", + " 1099\n", + " 91.8\n", + " 1197\n", + " 90.1\n", + " 1.7\n", + " reached\n", " \n", " \n", " Mixed\n", - " 518\n", + " 1043\n", + " 88.7\n", + " 1176\n", " 88.1\n", - " 588\n", - " 85.7\n", - " 2.4\n", - " 20-Dec\n", + " 0.6\n", + " 17-Feb\n", " \n", " \n", " Other\n", - " 553\n", - " 89.8\n", - " 616\n", - " 88.6\n", - " 1.2\n", - " 16-Dec\n", + " 1001\n", + " 89.4\n", + " 1120\n", + " 88.1\n", + " 1.3\n", + " 05-Feb\n", " \n", " \n", " South Asian\n", - " 490\n", - " 87.5\n", - " 560\n", - " 86.2\n", - " 1.3\n", - " 28-Dec\n", + " 959\n", + " 89.0\n", + " 1078\n", + " 87.0\n", + " 2.0\n", + " 05-Feb\n", " \n", " \n", " Unknown\n", - " 462\n", + " 875\n", " 88.0\n", - " 525\n", - " 86.7\n", - " 1.3\n", - " 25-Dec\n", + " 994\n", + " 85.9\n", + " 2.1\n", + " 08-Feb\n", " \n", " \n", " White\n", - " 532\n", - " 92.7\n", - " 574\n", - " 91.5\n", - " 1.2\n", - " reached\n", + " 1029\n", + " 88.6\n", + " 1162\n", + " 88.0\n", + " 0.6\n", + " 18-Feb\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 175\n", - " 86.2\n", - " 203\n", - " 86.2\n", - " 0.0\n", - " unknown\n", + " 329\n", + " 90.4\n", + " 364\n", + " 88.5\n", + " 1.9\n", + " reached\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 154\n", - " 91.7\n", - " 168\n", - " 87.5\n", - " 4.2\n", - " reached\n", + " 315\n", + " 90.0\n", + " 350\n", + " 90.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Caribbean\n", - " 175\n", - " 92.6\n", - " 189\n", - " 92.6\n", - " 0.0\n", + " 315\n", + " 90.0\n", + " 350\n", + " 88.0\n", + " 2.0\n", " reached\n", " \n", " \n", " Chinese\n", - " 168\n", - " 92.3\n", - " 182\n", - " 88.5\n", - " 3.8\n", + " 315\n", + " 91.8\n", + " 343\n", + " 89.8\n", + " 2.0\n", " reached\n", " \n", " \n", " Other\n", - " 168\n", - " 88.9\n", - " 189\n", - " 88.9\n", - " 0.0\n", - " unknown\n", + " 315\n", + " 90.0\n", + " 350\n", + " 88.0\n", + " 2.0\n", + " reached\n", " \n", " \n", " Other Asian\n", - " 154\n", - " 84.6\n", - " 182\n", - " 80.8\n", - " 3.8\n", - " 24-Dec\n", + " 336\n", + " 88.9\n", + " 378\n", + " 87.0\n", + " 1.9\n", + " 06-Feb\n", " \n", " \n", " British or Mixed British\n", - " 175\n", - " 89.3\n", - " 196\n", - " 85.7\n", - " 3.6\n", - " 16-Dec\n", + " 301\n", + " 86.0\n", + " 350\n", + " 86.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 161\n", - " 88.5\n", - " 182\n", - " 84.6\n", - " 3.9\n", - " 17-Dec\n", + " 357\n", + " 91.1\n", + " 392\n", + " 89.3\n", + " 1.8\n", + " reached\n", " \n", " \n", " Irish\n", - " 161\n", - " 88.5\n", - " 182\n", - " 88.5\n", - " 0.0\n", - " unknown\n", + " 308\n", + " 89.8\n", + " 343\n", + " 85.7\n", + " 4.1\n", + " 02-Feb\n", " \n", " \n", " Other Black\n", - " 154\n", - " 88.0\n", - " 175\n", - " 88.0\n", - " 0.0\n", - " unknown\n", - " \n", + " 336\n", + " 92.3\n", + " 364\n", + " 90.4\n", + " 1.9\n", + " reached\n", + " \n", " \n", " Other White\n", - " 154\n", - " 88.0\n", - " 175\n", - " 88.0\n", - " 0.0\n", - " unknown\n", + " 308\n", + " 89.8\n", + " 343\n", + " 87.8\n", + " 2.0\n", + " 02-Feb\n", " \n", " \n", " Other mixed\n", - " 147\n", - " 87.5\n", - " 168\n", - " 87.5\n", - " 0.0\n", - " unknown\n", + " 308\n", + " 88.0\n", + " 350\n", + " 86.0\n", + " 2.0\n", + " 09-Feb\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 168\n", - " 92.3\n", - " 182\n", - " 92.3\n", + " 329\n", + " 87.0\n", + " 378\n", + " 87.0\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 448\n", - " 90.1\n", - " 497\n", - " 88.7\n", - " 1.4\n", - " reached\n", + " 910\n", + " 89.7\n", + " 1015\n", + " 87.6\n", + " 2.1\n", + " 03-Feb\n", " \n", " \n", " White + Asian\n", - " 168\n", - " 88.9\n", - " 189\n", - " 88.9\n", - " 0.0\n", - " unknown\n", + " 315\n", + " 90.0\n", + " 350\n", + " 88.0\n", + " 2.0\n", + " reached\n", " \n", " \n", " White + Black African\n", - " 189\n", - " 87.1\n", - " 217\n", - " 87.1\n", - " 0.0\n", - " unknown\n", + " 308\n", + " 88.0\n", + " 350\n", + " 84.0\n", + " 4.0\n", + " 05-Feb\n", " \n", " \n", " White + Black Caribbean\n", - " 154\n", - " 91.7\n", - " 168\n", - " 91.7\n", + " 322\n", + " 88.5\n", + " 364\n", + " 88.5\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 609\n", - " 88.8\n", - " 686\n", - " 87.8\n", - " 1.0\n", - " 23-Dec\n", + " 1134\n", + " 89.0\n", + " 1274\n", + " 87.4\n", + " 1.6\n", + " 06-Feb\n", " \n", " \n", " 2\n", - " 595\n", - " 89.5\n", - " 665\n", - " 87.4\n", - " 2.1\n", - " 16-Dec\n", + " 1169\n", + " 89.8\n", + " 1302\n", + " 88.2\n", + " 1.6\n", + " 02-Feb\n", " \n", " \n", " 3\n", - " 560\n", - " 87.9\n", - " 637\n", - " 86.8\n", - " 1.1\n", - " 28-Dec\n", + " 1113\n", + " 88.8\n", + " 1253\n", + " 87.2\n", + " 1.6\n", + " 07-Feb\n", " \n", " \n", " 4\n", - " 574\n", - " 88.2\n", - " 651\n", - " 87.1\n", - " 1.1\n", - " 26-Dec\n", + " 1141\n", + " 90.6\n", + " 1260\n", + " 88.9\n", + " 1.7\n", + " reached\n", " \n", " \n", " 5 Least deprived\n", - " 581\n", - " 91.2\n", - " 637\n", - " 89.0\n", - " 2.2\n", - " reached\n", + " 1120\n", + " 88.4\n", + " 1267\n", + " 86.7\n", + " 1.7\n", + " 08-Feb\n", " \n", " \n", " Unknown\n", - " 161\n", - " 92.0\n", - " 175\n", - " 88.0\n", - " 4.0\n", + " 343\n", + " 90.7\n", + " 378\n", + " 88.9\n", + " 1.8\n", " reached\n", " \n", " \n", " bmi\n", " 30+\n", - " 896\n", - " 89.5\n", - " 1001\n", - " 86.7\n", - " 2.8\n", - " 16-Dec\n", + " 1743\n", + " 88.9\n", + " 1960\n", + " 87.1\n", + " 1.8\n", + " 06-Feb\n", " \n", " \n", " under 30\n", - " 2184\n", - " 88.9\n", - " 2457\n", - " 88.0\n", - " 0.9\n", - " 23-Dec\n", + " 4270\n", + " 89.6\n", + " 4767\n", + " 88.1\n", + " 1.5\n", + " 03-Feb\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 3052\n", - " 89.0\n", - " 3430\n", - " 87.6\n", - " 1.4\n", - " 20-Dec\n", + " 5950\n", + " 89.3\n", + " 6664\n", + " 87.8\n", + " 1.5\n", + " 05-Feb\n", " \n", " \n", " yes\n", - " 28\n", - " 100.0\n", - " 28\n", - " 100.0\n", + " 56\n", + " 88.9\n", + " 63\n", + " 88.9\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 3052\n", - " 89.2\n", - " 3423\n", - " 87.7\n", + " 5943\n", + " 89.4\n", + " 6650\n", + " 87.9\n", " 1.5\n", - " 18-Dec\n", + " 04-Feb\n", " \n", " \n", " yes\n", - " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 70\n", + " 90.9\n", + " 77\n", + " 90.9\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " dmards\n", " no\n", - " 3052\n", - " 89.0\n", - " 3430\n", - " 87.8\n", - " 1.2\n", - " 20-Dec\n", + " 5964\n", + " 89.5\n", + " 6664\n", + " 88.0\n", + " 1.5\n", + " 04-Feb\n", " \n", " \n", " yes\n", - " 28\n", - " 100.0\n", - " 28\n", - " 100.0\n", + " 49\n", + " 87.5\n", + " 56\n", + " 87.5\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 3052\n", - " 89.2\n", - " 3423\n", - " 87.7\n", + " 5957\n", + " 89.5\n", + " 6657\n", + " 88.0\n", " 1.5\n", - " 18-Dec\n", + " 04-Feb\n", " \n", " \n", " yes\n", - " 28\n", + " 56\n", " 80.0\n", - " 35\n", + " 70\n", " 80.0\n", " 0.0\n", " unknown\n", @@ -7711,40 +7763,40 @@ " \n", " ssri\n", " no\n", - " 3045\n", - " 89.1\n", - " 3416\n", + " 5950\n", + " 89.4\n", + " 6657\n", " 87.9\n", - " 1.2\n", - " 20-Dec\n", + " 1.5\n", + " 04-Feb\n", " \n", " \n", " yes\n", - " 35\n", - " 100.0\n", - " 35\n", - " 100.0\n", + " 56\n", + " 88.9\n", + " 63\n", + " 88.9\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 2478\n", - " 88.9\n", - " 2786\n", - " 87.4\n", - " 1.5\n", - " 20-Dec\n", + " 4788\n", + " 89.1\n", + " 5376\n", + " 87.5\n", + " 1.6\n", + " 05-Feb\n", " \n", " \n", " yes\n", - " 602\n", - " 89.6\n", - " 672\n", - " 88.5\n", - " 1.1\n", - " 17-Dec\n", + " 1225\n", + " 90.7\n", + " 1351\n", + " 89.1\n", + " 1.6\n", + " reached\n", " \n", " \n", "\n", @@ -7753,248 +7805,248 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 3080 \n", - "sex F 1582 \n", - " M 1498 \n", - "ethnicity_6_groups Black 532 \n", - " Mixed 518 \n", - " Other 553 \n", - " South Asian 490 \n", - " Unknown 462 \n", - " White 532 \n", - "ethnicity_16_groups African 175 \n", - " Bangladeshi or British Bangladeshi 154 \n", - " Caribbean 175 \n", - " Chinese 168 \n", - " Other 168 \n", - " Other Asian 154 \n", - " British or Mixed British 175 \n", - " Indian or British Indian 161 \n", - " Irish 161 \n", - " Other Black 154 \n", - " Other White 154 \n", - " Other mixed 147 \n", - " Pakistani or British Pakistani 168 \n", - " Unknown 448 \n", - " White + Asian 168 \n", - " White + Black African 189 \n", - " White + Black Caribbean 154 \n", - "imd_categories 1 Most deprived 609 \n", - " 2 595 \n", - " 3 560 \n", - " 4 574 \n", - " 5 Least deprived 581 \n", - " Unknown 161 \n", - "bmi 30+ 896 \n", - " under 30 2184 \n", - "chronic_cardiac_disease no 3052 \n", - " yes 28 \n", - "current_copd no 3052 \n", - " yes 28 \n", - "dmards no 3052 \n", - " yes 28 \n", - "psychosis_schiz_bipolar no 3052 \n", - " yes 28 \n", - "ssri no 3045 \n", - " yes 35 \n", - "ckd no 2478 \n", - " yes 602 \n", + "overall overall 6013 \n", + "sex F 3038 \n", + " M 2975 \n", + "ethnicity_6_groups Black 1099 \n", + " Mixed 1043 \n", + " Other 1001 \n", + " South Asian 959 \n", + " Unknown 875 \n", + " White 1029 \n", + "ethnicity_16_groups African 329 \n", + " Bangladeshi or British Bangladeshi 315 \n", + " Caribbean 315 \n", + " Chinese 315 \n", + " Other 315 \n", + " Other Asian 336 \n", + " British or Mixed British 301 \n", + " Indian or British Indian 357 \n", + " Irish 308 \n", + " Other Black 336 \n", + " Other White 308 \n", + " Other mixed 308 \n", + " Pakistani or British Pakistani 329 \n", + " Unknown 910 \n", + " White + Asian 315 \n", + " White + Black African 308 \n", + " White + Black Caribbean 322 \n", + "imd_categories 1 Most deprived 1134 \n", + " 2 1169 \n", + " 3 1113 \n", + " 4 1141 \n", + " 5 Least deprived 1120 \n", + " Unknown 343 \n", + "bmi 30+ 1743 \n", + " under 30 4270 \n", + "chronic_cardiac_disease no 5950 \n", + " yes 56 \n", + "current_copd no 5943 \n", + " yes 70 \n", + "dmards no 5964 \n", + " yes 49 \n", + "psychosis_schiz_bipolar no 5957 \n", + " yes 56 \n", + "ssri no 5950 \n", + " yes 56 \n", + "ckd no 4788 \n", + " yes 1225 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 89.1 3458 \n", - "sex F 89.3 1771 \n", - " M 88.8 1687 \n", - "ethnicity_6_groups Black 89.4 595 \n", - " Mixed 88.1 588 \n", - " Other 89.8 616 \n", - " South Asian 87.5 560 \n", - " Unknown 88.0 525 \n", - " White 92.7 574 \n", - "ethnicity_16_groups African 86.2 203 \n", - " Bangladeshi or British Bangladeshi 91.7 168 \n", - " Caribbean 92.6 189 \n", - " Chinese 92.3 182 \n", - " Other 88.9 189 \n", - " Other Asian 84.6 182 \n", - " British or Mixed British 89.3 196 \n", - " Indian or British Indian 88.5 182 \n", - " Irish 88.5 182 \n", - " Other Black 88.0 175 \n", - " Other White 88.0 175 \n", - " Other mixed 87.5 168 \n", - " Pakistani or British Pakistani 92.3 182 \n", - " Unknown 90.1 497 \n", - " White + Asian 88.9 189 \n", - " White + Black African 87.1 217 \n", - " White + Black Caribbean 91.7 168 \n", - "imd_categories 1 Most deprived 88.8 686 \n", - " 2 89.5 665 \n", - " 3 87.9 637 \n", - " 4 88.2 651 \n", - " 5 Least deprived 91.2 637 \n", - " Unknown 92.0 175 \n", - "bmi 30+ 89.5 1001 \n", - " under 30 88.9 2457 \n", - "chronic_cardiac_disease no 89.0 3430 \n", - " yes 100.0 28 \n", - "current_copd no 89.2 3423 \n", - " yes 80.0 35 \n", - "dmards no 89.0 3430 \n", - " yes 100.0 28 \n", - "psychosis_schiz_bipolar no 89.2 3423 \n", - " yes 80.0 35 \n", - "ssri no 89.1 3416 \n", - " yes 100.0 35 \n", - "ckd no 88.9 2786 \n", - " yes 89.6 672 \n", + "overall overall 89.4 6727 \n", + "sex F 89.3 3402 \n", + " M 89.5 3325 \n", + "ethnicity_6_groups Black 91.8 1197 \n", + " Mixed 88.7 1176 \n", + " Other 89.4 1120 \n", + " South Asian 89.0 1078 \n", + " Unknown 88.0 994 \n", + " White 88.6 1162 \n", + "ethnicity_16_groups African 90.4 364 \n", + " Bangladeshi or British Bangladeshi 90.0 350 \n", + " Caribbean 90.0 350 \n", + " Chinese 91.8 343 \n", + " Other 90.0 350 \n", + " Other Asian 88.9 378 \n", + " British or Mixed British 86.0 350 \n", + " Indian or British Indian 91.1 392 \n", + " Irish 89.8 343 \n", + " Other Black 92.3 364 \n", + " Other White 89.8 343 \n", + " Other mixed 88.0 350 \n", + " Pakistani or British Pakistani 87.0 378 \n", + " Unknown 89.7 1015 \n", + " White + Asian 90.0 350 \n", + " White + Black African 88.0 350 \n", + " White + Black Caribbean 88.5 364 \n", + "imd_categories 1 Most deprived 89.0 1274 \n", + " 2 89.8 1302 \n", + " 3 88.8 1253 \n", + " 4 90.6 1260 \n", + " 5 Least deprived 88.4 1267 \n", + " Unknown 90.7 378 \n", + "bmi 30+ 88.9 1960 \n", + " under 30 89.6 4767 \n", + "chronic_cardiac_disease no 89.3 6664 \n", + " yes 88.9 63 \n", + "current_copd no 89.4 6650 \n", + " yes 90.9 77 \n", + "dmards no 89.5 6664 \n", + " yes 87.5 56 \n", + "psychosis_schiz_bipolar no 89.5 6657 \n", + " yes 80.0 70 \n", + "ssri no 89.4 6657 \n", + " yes 88.9 63 \n", + "ckd no 89.1 5376 \n", + " yes 90.7 1351 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 87.7 \n", - "sex F 88.1 \n", - " M 87.6 \n", - "ethnicity_6_groups Black 88.2 \n", - " Mixed 85.7 \n", - " Other 88.6 \n", - " South Asian 86.2 \n", - " Unknown 86.7 \n", - " White 91.5 \n", - "ethnicity_16_groups African 86.2 \n", - " Bangladeshi or British Bangladeshi 87.5 \n", - " Caribbean 92.6 \n", - " Chinese 88.5 \n", - " Other 88.9 \n", - " Other Asian 80.8 \n", - " British or Mixed British 85.7 \n", - " Indian or British Indian 84.6 \n", - " Irish 88.5 \n", - " Other Black 88.0 \n", - " Other White 88.0 \n", - " Other mixed 87.5 \n", - " Pakistani or British Pakistani 92.3 \n", - " Unknown 88.7 \n", - " White + Asian 88.9 \n", - " White + Black African 87.1 \n", - " White + Black Caribbean 91.7 \n", - "imd_categories 1 Most deprived 87.8 \n", - " 2 87.4 \n", - " 3 86.8 \n", - " 4 87.1 \n", - " 5 Least deprived 89.0 \n", - " Unknown 88.0 \n", - "bmi 30+ 86.7 \n", - " under 30 88.0 \n", - "chronic_cardiac_disease no 87.6 \n", - " yes 100.0 \n", - "current_copd no 87.7 \n", - " yes 80.0 \n", - "dmards no 87.8 \n", - " yes 100.0 \n", - "psychosis_schiz_bipolar no 87.7 \n", + "overall overall 87.8 \n", + "sex F 87.9 \n", + " M 87.8 \n", + "ethnicity_6_groups Black 90.1 \n", + " Mixed 88.1 \n", + " Other 88.1 \n", + " South Asian 87.0 \n", + " Unknown 85.9 \n", + " White 88.0 \n", + "ethnicity_16_groups African 88.5 \n", + " Bangladeshi or British Bangladeshi 90.0 \n", + " Caribbean 88.0 \n", + " Chinese 89.8 \n", + " Other 88.0 \n", + " Other Asian 87.0 \n", + " British or Mixed British 86.0 \n", + " Indian or British Indian 89.3 \n", + " Irish 85.7 \n", + " Other Black 90.4 \n", + " Other White 87.8 \n", + " Other mixed 86.0 \n", + " Pakistani or British Pakistani 87.0 \n", + " Unknown 87.6 \n", + " White + Asian 88.0 \n", + " White + Black African 84.0 \n", + " White + Black Caribbean 88.5 \n", + "imd_categories 1 Most deprived 87.4 \n", + " 2 88.2 \n", + " 3 87.2 \n", + " 4 88.9 \n", + " 5 Least deprived 86.7 \n", + " Unknown 88.9 \n", + "bmi 30+ 87.1 \n", + " under 30 88.1 \n", + "chronic_cardiac_disease no 87.8 \n", + " yes 88.9 \n", + "current_copd no 87.9 \n", + " yes 90.9 \n", + "dmards no 88.0 \n", + " yes 87.5 \n", + "psychosis_schiz_bipolar no 88.0 \n", " yes 80.0 \n", "ssri no 87.9 \n", - " yes 100.0 \n", - "ckd no 87.4 \n", - " yes 88.5 \n", + " yes 88.9 \n", + "ckd no 87.5 \n", + " yes 89.1 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.4 \n", - "sex F 1.2 \n", - " M 1.2 \n", - "ethnicity_6_groups Black 1.2 \n", - " Mixed 2.4 \n", - " Other 1.2 \n", - " South Asian 1.3 \n", - " Unknown 1.3 \n", - " White 1.2 \n", - "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 4.2 \n", - " Caribbean 0.0 \n", - " Chinese 3.8 \n", - " Other 0.0 \n", - " Other Asian 3.8 \n", - " British or Mixed British 3.6 \n", - " Indian or British Indian 3.9 \n", - " Irish 0.0 \n", - " Other Black 0.0 \n", - " Other White 0.0 \n", - " Other mixed 0.0 \n", + "overall overall 1.6 \n", + "sex F 1.4 \n", + " M 1.7 \n", + "ethnicity_6_groups Black 1.7 \n", + " Mixed 0.6 \n", + " Other 1.3 \n", + " South Asian 2.0 \n", + " Unknown 2.1 \n", + " White 0.6 \n", + "ethnicity_16_groups African 1.9 \n", + " Bangladeshi or British Bangladeshi 0.0 \n", + " Caribbean 2.0 \n", + " Chinese 2.0 \n", + " Other 2.0 \n", + " Other Asian 1.9 \n", + " British or Mixed British 0.0 \n", + " Indian or British Indian 1.8 \n", + " Irish 4.1 \n", + " Other Black 1.9 \n", + " Other White 2.0 \n", + " Other mixed 2.0 \n", " Pakistani or British Pakistani 0.0 \n", - " Unknown 1.4 \n", - " White + Asian 0.0 \n", - " White + Black African 0.0 \n", + " Unknown 2.1 \n", + " White + Asian 2.0 \n", + " White + Black African 4.0 \n", " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 1.0 \n", - " 2 2.1 \n", - " 3 1.1 \n", - " 4 1.1 \n", - " 5 Least deprived 2.2 \n", - " Unknown 4.0 \n", - "bmi 30+ 2.8 \n", - " under 30 0.9 \n", - "chronic_cardiac_disease no 1.4 \n", + "imd_categories 1 Most deprived 1.6 \n", + " 2 1.6 \n", + " 3 1.6 \n", + " 4 1.7 \n", + " 5 Least deprived 1.7 \n", + " Unknown 1.8 \n", + "bmi 30+ 1.8 \n", + " under 30 1.5 \n", + "chronic_cardiac_disease no 1.5 \n", " yes 0.0 \n", "current_copd no 1.5 \n", " yes 0.0 \n", - "dmards no 1.2 \n", + "dmards no 1.5 \n", " yes 0.0 \n", "psychosis_schiz_bipolar no 1.5 \n", " yes 0.0 \n", - "ssri no 1.2 \n", + "ssri no 1.5 \n", " yes 0.0 \n", - "ckd no 1.5 \n", - " yes 1.1 \n", + "ckd no 1.6 \n", + " yes 1.6 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 19-Dec \n", - "sex F 19-Dec \n", - " M 22-Dec \n", - "ethnicity_6_groups Black 18-Dec \n", - " Mixed 20-Dec \n", - " Other 16-Dec \n", - " South Asian 28-Dec \n", - " Unknown 25-Dec \n", - " White reached \n", - "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi reached \n", + "overall overall 04-Feb \n", + "sex F 05-Feb \n", + " M 04-Feb \n", + "ethnicity_6_groups Black reached \n", + " Mixed 17-Feb \n", + " Other 05-Feb \n", + " South Asian 05-Feb \n", + " Unknown 08-Feb \n", + " White 18-Feb \n", + "ethnicity_16_groups African reached \n", + " Bangladeshi or British Bangladeshi unknown \n", " Caribbean reached \n", " Chinese reached \n", - " Other unknown \n", - " Other Asian 24-Dec \n", - " British or Mixed British 16-Dec \n", - " Indian or British Indian 17-Dec \n", - " Irish unknown \n", - " Other Black unknown \n", - " Other White unknown \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani reached \n", - " Unknown reached \n", - " White + Asian unknown \n", - " White + Black African unknown \n", - " White + Black Caribbean reached \n", - "imd_categories 1 Most deprived 23-Dec \n", - " 2 16-Dec \n", - " 3 28-Dec \n", - " 4 26-Dec \n", - " 5 Least deprived reached \n", + " Other reached \n", + " Other Asian 06-Feb \n", + " British or Mixed British unknown \n", + " Indian or British Indian reached \n", + " Irish 02-Feb \n", + " Other Black reached \n", + " Other White 02-Feb \n", + " Other mixed 09-Feb \n", + " Pakistani or British Pakistani unknown \n", + " Unknown 03-Feb \n", + " White + Asian reached \n", + " White + Black African 05-Feb \n", + " White + Black Caribbean unknown \n", + "imd_categories 1 Most deprived 06-Feb \n", + " 2 02-Feb \n", + " 3 07-Feb \n", + " 4 reached \n", + " 5 Least deprived 08-Feb \n", " Unknown reached \n", - "bmi 30+ 16-Dec \n", - " under 30 23-Dec \n", - "chronic_cardiac_disease no 20-Dec \n", - " yes reached \n", - "current_copd no 18-Dec \n", + "bmi 30+ 06-Feb \n", + " under 30 03-Feb \n", + "chronic_cardiac_disease no 05-Feb \n", " yes unknown \n", - "dmards no 20-Dec \n", + "current_copd no 04-Feb \n", " yes reached \n", - "psychosis_schiz_bipolar no 18-Dec \n", + "dmards no 04-Feb \n", " yes unknown \n", - "ssri no 20-Dec \n", - " yes reached \n", - "ckd no 20-Dec \n", - " yes 17-Dec " + "psychosis_schiz_bipolar no 04-Feb \n", + " yes unknown \n", + "ssri no 04-Feb \n", + " yes unknown \n", + "ckd no 05-Feb \n", + " yes reached " ] }, "metadata": {}, @@ -8023,7 +8075,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **40-49** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **40-49** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -8089,368 +8141,368 @@ " \n", " overall\n", " overall\n", - " 5530\n", - " 90.1\n", - " 6139\n", - " 88.6\n", + " 11018\n", + " 89.9\n", + " 12257\n", + " 88.4\n", " 1.5\n", - " reached\n", + " 02-Feb\n", " \n", " \n", " sex\n", " F\n", - " 2849\n", - " 90.0\n", - " 3164\n", - " 88.5\n", - " 1.5\n", - " reached\n", + " 5733\n", + " 89.7\n", + " 6391\n", + " 88.4\n", + " 1.3\n", + " 03-Feb\n", " \n", " \n", " M\n", - " 2681\n", + " 5285\n", " 90.1\n", - " 2975\n", - " 88.7\n", - " 1.4\n", + " 5866\n", + " 88.4\n", + " 1.7\n", " reached\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 896\n", - " 88.9\n", - " 1008\n", - " 87.5\n", - " 1.4\n", - " 20-Dec\n", + " 1869\n", + " 89.3\n", + " 2093\n", + " 88.0\n", + " 1.3\n", + " 05-Feb\n", " \n", " \n", " Mixed\n", - " 952\n", - " 90.1\n", - " 1057\n", - " 88.1\n", - " 2.0\n", + " 1883\n", + " 90.3\n", + " 2086\n", + " 88.9\n", + " 1.4\n", " reached\n", " \n", " \n", " Other\n", - " 917\n", - " 89.7\n", - " 1022\n", - " 88.4\n", - " 1.3\n", - " 16-Dec\n", + " 1827\n", + " 88.8\n", + " 2058\n", + " 87.4\n", + " 1.4\n", + " 08-Feb\n", " \n", " \n", " South Asian\n", - " 959\n", - " 90.7\n", - " 1057\n", - " 89.4\n", - " 1.3\n", + " 1862\n", + " 90.5\n", + " 2058\n", + " 88.8\n", + " 1.7\n", " reached\n", " \n", " \n", " Unknown\n", - " 826\n", - " 91.5\n", - " 903\n", - " 89.1\n", - " 2.4\n", + " 1722\n", + " 90.8\n", + " 1897\n", + " 89.3\n", + " 1.5\n", " reached\n", " \n", " \n", " White\n", - " 980\n", - " 89.7\n", - " 1092\n", - " 88.5\n", - " 1.2\n", - " 16-Dec\n", + " 1855\n", + " 89.8\n", + " 2065\n", + " 88.1\n", + " 1.7\n", + " 02-Feb\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 294\n", - " 91.3\n", - " 322\n", - " 89.1\n", - " 2.2\n", - " reached\n", + " 567\n", + " 89.0\n", + " 637\n", + " 89.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 273\n", - " 88.6\n", - " 308\n", - " 88.6\n", - " 0.0\n", - " unknown\n", + " 574\n", + " 89.1\n", + " 644\n", + " 88.0\n", + " 1.1\n", + " 07-Feb\n", " \n", " \n", " Caribbean\n", - " 280\n", - " 87.0\n", - " 322\n", - " 84.8\n", - " 2.2\n", - " 24-Dec\n", + " 637\n", + " 89.2\n", + " 714\n", + " 87.3\n", + " 1.9\n", + " 04-Feb\n", " \n", " \n", " Chinese\n", - " 315\n", - " 91.8\n", - " 343\n", - " 89.8\n", - " 2.0\n", + " 581\n", + " 91.2\n", + " 637\n", + " 90.1\n", + " 1.1\n", " reached\n", " \n", " \n", " Other\n", - " 315\n", - " 90.0\n", - " 350\n", - " 86.0\n", - " 4.0\n", + " 616\n", + " 90.7\n", + " 679\n", + " 88.7\n", + " 2.0\n", " reached\n", " \n", " \n", " Other Asian\n", - " 308\n", - " 93.6\n", - " 329\n", - " 91.5\n", - " 2.1\n", - " reached\n", + " 560\n", + " 89.9\n", + " 623\n", + " 87.6\n", + " 2.3\n", + " 02-Feb\n", " \n", " \n", " British or Mixed British\n", - " 294\n", - " 85.7\n", - " 343\n", - " 85.7\n", - " 0.0\n", - " unknown\n", + " 567\n", + " 88.0\n", + " 644\n", + " 87.0\n", + " 1.0\n", + " 16-Feb\n", " \n", " \n", " Indian or British Indian\n", - " 273\n", - " 92.9\n", - " 294\n", - " 90.5\n", - " 2.4\n", + " 581\n", + " 90.2\n", + " 644\n", + " 88.0\n", + " 2.2\n", " reached\n", " \n", " \n", " Irish\n", - " 315\n", - " 91.8\n", - " 343\n", - " 89.8\n", - " 2.0\n", - " reached\n", + " 616\n", + " 88.9\n", + " 693\n", + " 87.9\n", + " 1.0\n", + " 09-Feb\n", " \n", " \n", " Other Black\n", - " 294\n", - " 89.4\n", - " 329\n", - " 87.2\n", - " 2.2\n", - " 16-Dec\n", + " 609\n", + " 90.6\n", + " 672\n", + " 89.6\n", + " 1.0\n", + " reached\n", " \n", " \n", " Other White\n", - " 287\n", - " 91.1\n", - " 315\n", - " 88.9\n", - " 2.2\n", + " 623\n", + " 90.8\n", + " 686\n", + " 89.8\n", + " 1.0\n", " reached\n", " \n", " \n", " Other mixed\n", - " 280\n", - " 90.9\n", - " 308\n", - " 88.6\n", - " 2.3\n", + " 567\n", + " 90.0\n", + " 630\n", + " 88.9\n", + " 1.1\n", " reached\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 287\n", - " 89.1\n", - " 322\n", - " 87.0\n", - " 2.1\n", - " 18-Dec\n", + " 546\n", + " 88.6\n", + " 616\n", + " 86.4\n", + " 2.2\n", + " 06-Feb\n", " \n", " \n", " Unknown\n", - " 854\n", - " 91.0\n", - " 938\n", - " 89.6\n", - " 1.4\n", + " 1638\n", + " 90.0\n", + " 1820\n", + " 88.8\n", + " 1.2\n", " reached\n", " \n", " \n", " White + Asian\n", - " 287\n", - " 89.1\n", - " 322\n", - " 87.0\n", - " 2.1\n", - " 18-Dec\n", + " 546\n", + " 91.8\n", + " 595\n", + " 89.4\n", + " 2.4\n", + " reached\n", " \n", " \n", " White + Black African\n", - " 287\n", - " 89.1\n", - " 322\n", - " 89.1\n", - " 0.0\n", - " unknown\n", + " 581\n", + " 89.2\n", + " 651\n", + " 88.2\n", + " 1.0\n", + " 07-Feb\n", " \n", " \n", " White + Black Caribbean\n", - " 294\n", - " 89.4\n", - " 329\n", - " 87.2\n", - " 2.2\n", - " 16-Dec\n", + " 602\n", + " 90.5\n", + " 665\n", + " 89.5\n", + " 1.0\n", + " reached\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 1036\n", - " 88.6\n", - " 1169\n", - " 86.8\n", - " 1.8\n", - " 20-Dec\n", + " 2079\n", + " 89.5\n", + " 2324\n", + " 88.0\n", + " 1.5\n", + " 04-Feb\n", " \n", " \n", " 2\n", - " 1057\n", - " 92.1\n", - " 1148\n", - " 90.2\n", - " 1.9\n", - " reached\n", + " 2072\n", + " 89.7\n", + " 2310\n", + " 88.2\n", + " 1.5\n", + " 03-Feb\n", " \n", " \n", " 3\n", - " 1036\n", - " 89.2\n", - " 1162\n", - " 88.0\n", - " 1.2\n", - " 19-Dec\n", + " 2093\n", + " 89.8\n", + " 2331\n", + " 88.3\n", + " 1.5\n", + " 02-Feb\n", " \n", " \n", " 4\n", - " 1043\n", - " 90.3\n", - " 1155\n", - " 89.1\n", - " 1.2\n", + " 2093\n", + " 90.1\n", + " 2324\n", + " 89.2\n", + " 0.9\n", " reached\n", " \n", " \n", " 5 Least deprived\n", - " 1078\n", - " 90.1\n", - " 1197\n", - " 88.9\n", + " 2114\n", + " 89.9\n", + " 2352\n", + " 88.7\n", " 1.2\n", - " reached\n", + " 02-Feb\n", " \n", " \n", " Unknown\n", - " 280\n", - " 93.0\n", - " 301\n", - " 88.4\n", - " 4.6\n", + " 560\n", + " 90.9\n", + " 616\n", + " 88.6\n", + " 2.3\n", " reached\n", " \n", " \n", " bmi\n", " 30+\n", - " 1722\n", - " 90.8\n", - " 1897\n", - " 88.9\n", - " 1.9\n", + " 3318\n", + " 90.6\n", + " 3661\n", + " 89.5\n", + " 1.1\n", " reached\n", " \n", " \n", " under 30\n", - " 3801\n", + " 7700\n", " 89.6\n", - " 4242\n", - " 88.3\n", - " 1.3\n", - " 17-Dec\n", + " 8589\n", + " 88.0\n", + " 1.6\n", + " 03-Feb\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 5474\n", - " 90.1\n", - " 6076\n", - " 88.6\n", + " 10892\n", + " 89.9\n", + " 12117\n", + " 88.4\n", " 1.5\n", - " reached\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 56\n", - " 88.9\n", - " 63\n", - " 88.9\n", - " 0.0\n", - " unknown\n", + " 126\n", + " 90.0\n", + " 140\n", + " 85.0\n", + " 5.0\n", + " reached\n", " \n", " \n", " current_copd\n", " no\n", - " 5481\n", - " 90.2\n", - " 6076\n", - " 88.7\n", + " 10913\n", + " 89.9\n", + " 12145\n", + " 88.4\n", " 1.5\n", - " reached\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 49\n", - " 87.5\n", - " 56\n", - " 87.5\n", + " 105\n", + " 93.8\n", + " 112\n", + " 93.8\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " dmards\n", " no\n", - " 5460\n", - " 90.0\n", - " 6069\n", - " 88.6\n", - " 1.4\n", - " reached\n", + " 10892\n", + " 89.9\n", + " 12117\n", + " 88.4\n", + " 1.5\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 63\n", + " 126\n", " 90.0\n", - " 70\n", + " 140\n", " 90.0\n", " 0.0\n", " unknown\n", @@ -8458,37 +8510,37 @@ " \n", " psychosis_schiz_bipolar\n", " no\n", - " 5481\n", - " 90.2\n", - " 6076\n", - " 88.7\n", + " 10913\n", + " 89.9\n", + " 12138\n", + " 88.4\n", " 1.5\n", - " reached\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 49\n", - " 87.5\n", - " 56\n", - " 87.5\n", + " 105\n", + " 88.2\n", + " 119\n", + " 88.2\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 5481\n", - " 90.0\n", - " 6090\n", - " 88.5\n", + " 10934\n", + " 89.9\n", + " 12159\n", + " 88.4\n", " 1.5\n", - " reached\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 42\n", + " 84\n", " 85.7\n", - " 49\n", + " 98\n", " 85.7\n", " 0.0\n", " unknown\n", @@ -8496,21 +8548,21 @@ " \n", " ckd\n", " no\n", - " 4389\n", - " 90.0\n", - " 4879\n", - " 88.4\n", - " 1.6\n", - " reached\n", + " 8841\n", + " 89.9\n", + " 9835\n", + " 88.5\n", + " 1.4\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 1141\n", - " 90.6\n", - " 1260\n", - " 88.9\n", - " 1.7\n", - " reached\n", + " 2177\n", + " 89.9\n", + " 2422\n", + " 88.4\n", + " 1.5\n", + " 02-Feb\n", " \n", " \n", "\n", @@ -8519,248 +8571,248 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 5530 \n", - "sex F 2849 \n", - " M 2681 \n", - "ethnicity_6_groups Black 896 \n", - " Mixed 952 \n", - " Other 917 \n", - " South Asian 959 \n", - " Unknown 826 \n", - " White 980 \n", - "ethnicity_16_groups African 294 \n", - " Bangladeshi or British Bangladeshi 273 \n", - " Caribbean 280 \n", - " Chinese 315 \n", - " Other 315 \n", - " Other Asian 308 \n", - " British or Mixed British 294 \n", - " Indian or British Indian 273 \n", - " Irish 315 \n", - " Other Black 294 \n", - " Other White 287 \n", - " Other mixed 280 \n", - " Pakistani or British Pakistani 287 \n", - " Unknown 854 \n", - " White + Asian 287 \n", - " White + Black African 287 \n", - " White + Black Caribbean 294 \n", - "imd_categories 1 Most deprived 1036 \n", - " 2 1057 \n", - " 3 1036 \n", - " 4 1043 \n", - " 5 Least deprived 1078 \n", - " Unknown 280 \n", - "bmi 30+ 1722 \n", - " under 30 3801 \n", - "chronic_cardiac_disease no 5474 \n", - " yes 56 \n", - "current_copd no 5481 \n", - " yes 49 \n", - "dmards no 5460 \n", - " yes 63 \n", - "psychosis_schiz_bipolar no 5481 \n", - " yes 49 \n", - "ssri no 5481 \n", - " yes 42 \n", - "ckd no 4389 \n", - " yes 1141 \n", + "overall overall 11018 \n", + "sex F 5733 \n", + " M 5285 \n", + "ethnicity_6_groups Black 1869 \n", + " Mixed 1883 \n", + " Other 1827 \n", + " South Asian 1862 \n", + " Unknown 1722 \n", + " White 1855 \n", + "ethnicity_16_groups African 567 \n", + " Bangladeshi or British Bangladeshi 574 \n", + " Caribbean 637 \n", + " Chinese 581 \n", + " Other 616 \n", + " Other Asian 560 \n", + " British or Mixed British 567 \n", + " Indian or British Indian 581 \n", + " Irish 616 \n", + " Other Black 609 \n", + " Other White 623 \n", + " Other mixed 567 \n", + " Pakistani or British Pakistani 546 \n", + " Unknown 1638 \n", + " White + Asian 546 \n", + " White + Black African 581 \n", + " White + Black Caribbean 602 \n", + "imd_categories 1 Most deprived 2079 \n", + " 2 2072 \n", + " 3 2093 \n", + " 4 2093 \n", + " 5 Least deprived 2114 \n", + " Unknown 560 \n", + "bmi 30+ 3318 \n", + " under 30 7700 \n", + "chronic_cardiac_disease no 10892 \n", + " yes 126 \n", + "current_copd no 10913 \n", + " yes 105 \n", + "dmards no 10892 \n", + " yes 126 \n", + "psychosis_schiz_bipolar no 10913 \n", + " yes 105 \n", + "ssri no 10934 \n", + " yes 84 \n", + "ckd no 8841 \n", + " yes 2177 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 90.1 6139 \n", - "sex F 90.0 3164 \n", - " M 90.1 2975 \n", - "ethnicity_6_groups Black 88.9 1008 \n", - " Mixed 90.1 1057 \n", - " Other 89.7 1022 \n", - " South Asian 90.7 1057 \n", - " Unknown 91.5 903 \n", - " White 89.7 1092 \n", - "ethnicity_16_groups African 91.3 322 \n", - " Bangladeshi or British Bangladeshi 88.6 308 \n", - " Caribbean 87.0 322 \n", - " Chinese 91.8 343 \n", - " Other 90.0 350 \n", - " Other Asian 93.6 329 \n", - " British or Mixed British 85.7 343 \n", - " Indian or British Indian 92.9 294 \n", - " Irish 91.8 343 \n", - " Other Black 89.4 329 \n", - " Other White 91.1 315 \n", - " Other mixed 90.9 308 \n", - " Pakistani or British Pakistani 89.1 322 \n", - " Unknown 91.0 938 \n", - " White + Asian 89.1 322 \n", - " White + Black African 89.1 322 \n", - " White + Black Caribbean 89.4 329 \n", - "imd_categories 1 Most deprived 88.6 1169 \n", - " 2 92.1 1148 \n", - " 3 89.2 1162 \n", - " 4 90.3 1155 \n", - " 5 Least deprived 90.1 1197 \n", - " Unknown 93.0 301 \n", - "bmi 30+ 90.8 1897 \n", - " under 30 89.6 4242 \n", - "chronic_cardiac_disease no 90.1 6076 \n", - " yes 88.9 63 \n", - "current_copd no 90.2 6076 \n", - " yes 87.5 56 \n", - "dmards no 90.0 6069 \n", - " yes 90.0 70 \n", - "psychosis_schiz_bipolar no 90.2 6076 \n", - " yes 87.5 56 \n", - "ssri no 90.0 6090 \n", - " yes 85.7 49 \n", - "ckd no 90.0 4879 \n", - " yes 90.6 1260 \n", + "overall overall 89.9 12257 \n", + "sex F 89.7 6391 \n", + " M 90.1 5866 \n", + "ethnicity_6_groups Black 89.3 2093 \n", + " Mixed 90.3 2086 \n", + " Other 88.8 2058 \n", + " South Asian 90.5 2058 \n", + " Unknown 90.8 1897 \n", + " White 89.8 2065 \n", + "ethnicity_16_groups African 89.0 637 \n", + " Bangladeshi or British Bangladeshi 89.1 644 \n", + " Caribbean 89.2 714 \n", + " Chinese 91.2 637 \n", + " Other 90.7 679 \n", + " Other Asian 89.9 623 \n", + " British or Mixed British 88.0 644 \n", + " Indian or British Indian 90.2 644 \n", + " Irish 88.9 693 \n", + " Other Black 90.6 672 \n", + " Other White 90.8 686 \n", + " Other mixed 90.0 630 \n", + " Pakistani or British Pakistani 88.6 616 \n", + " Unknown 90.0 1820 \n", + " White + Asian 91.8 595 \n", + " White + Black African 89.2 651 \n", + " White + Black Caribbean 90.5 665 \n", + "imd_categories 1 Most deprived 89.5 2324 \n", + " 2 89.7 2310 \n", + " 3 89.8 2331 \n", + " 4 90.1 2324 \n", + " 5 Least deprived 89.9 2352 \n", + " Unknown 90.9 616 \n", + "bmi 30+ 90.6 3661 \n", + " under 30 89.6 8589 \n", + "chronic_cardiac_disease no 89.9 12117 \n", + " yes 90.0 140 \n", + "current_copd no 89.9 12145 \n", + " yes 93.8 112 \n", + "dmards no 89.9 12117 \n", + " yes 90.0 140 \n", + "psychosis_schiz_bipolar no 89.9 12138 \n", + " yes 88.2 119 \n", + "ssri no 89.9 12159 \n", + " yes 85.7 98 \n", + "ckd no 89.9 9835 \n", + " yes 89.9 2422 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.6 \n", - "sex F 88.5 \n", - " M 88.7 \n", - "ethnicity_6_groups Black 87.5 \n", - " Mixed 88.1 \n", - " Other 88.4 \n", - " South Asian 89.4 \n", - " Unknown 89.1 \n", - " White 88.5 \n", - "ethnicity_16_groups African 89.1 \n", - " Bangladeshi or British Bangladeshi 88.6 \n", - " Caribbean 84.8 \n", - " Chinese 89.8 \n", - " Other 86.0 \n", - " Other Asian 91.5 \n", - " British or Mixed British 85.7 \n", - " Indian or British Indian 90.5 \n", - " Irish 89.8 \n", - " Other Black 87.2 \n", - " Other White 88.9 \n", - " Other mixed 88.6 \n", - " Pakistani or British Pakistani 87.0 \n", - " Unknown 89.6 \n", - " White + Asian 87.0 \n", - " White + Black African 89.1 \n", - " White + Black Caribbean 87.2 \n", - "imd_categories 1 Most deprived 86.8 \n", - " 2 90.2 \n", - " 3 88.0 \n", - " 4 89.1 \n", - " 5 Least deprived 88.9 \n", - " Unknown 88.4 \n", - "bmi 30+ 88.9 \n", - " under 30 88.3 \n", - "chronic_cardiac_disease no 88.6 \n", - " yes 88.9 \n", - "current_copd no 88.7 \n", - " yes 87.5 \n", - "dmards no 88.6 \n", + "overall overall 88.4 \n", + "sex F 88.4 \n", + " M 88.4 \n", + "ethnicity_6_groups Black 88.0 \n", + " Mixed 88.9 \n", + " Other 87.4 \n", + " South Asian 88.8 \n", + " Unknown 89.3 \n", + " White 88.1 \n", + "ethnicity_16_groups African 89.0 \n", + " Bangladeshi or British Bangladeshi 88.0 \n", + " Caribbean 87.3 \n", + " Chinese 90.1 \n", + " Other 88.7 \n", + " Other Asian 87.6 \n", + " British or Mixed British 87.0 \n", + " Indian or British Indian 88.0 \n", + " Irish 87.9 \n", + " Other Black 89.6 \n", + " Other White 89.8 \n", + " Other mixed 88.9 \n", + " Pakistani or British Pakistani 86.4 \n", + " Unknown 88.8 \n", + " White + Asian 89.4 \n", + " White + Black African 88.2 \n", + " White + Black Caribbean 89.5 \n", + "imd_categories 1 Most deprived 88.0 \n", + " 2 88.2 \n", + " 3 88.3 \n", + " 4 89.2 \n", + " 5 Least deprived 88.7 \n", + " Unknown 88.6 \n", + "bmi 30+ 89.5 \n", + " under 30 88.0 \n", + "chronic_cardiac_disease no 88.4 \n", + " yes 85.0 \n", + "current_copd no 88.4 \n", + " yes 93.8 \n", + "dmards no 88.4 \n", " yes 90.0 \n", - "psychosis_schiz_bipolar no 88.7 \n", - " yes 87.5 \n", - "ssri no 88.5 \n", + "psychosis_schiz_bipolar no 88.4 \n", + " yes 88.2 \n", + "ssri no 88.4 \n", " yes 85.7 \n", - "ckd no 88.4 \n", - " yes 88.9 \n", + "ckd no 88.5 \n", + " yes 88.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", "overall overall 1.5 \n", - "sex F 1.5 \n", - " M 1.4 \n", - "ethnicity_6_groups Black 1.4 \n", - " Mixed 2.0 \n", - " Other 1.3 \n", - " South Asian 1.3 \n", - " Unknown 2.4 \n", - " White 1.2 \n", - "ethnicity_16_groups African 2.2 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 2.2 \n", - " Chinese 2.0 \n", - " Other 4.0 \n", - " Other Asian 2.1 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 2.4 \n", - " Irish 2.0 \n", - " Other Black 2.2 \n", - " Other White 2.2 \n", - " Other mixed 2.3 \n", - " Pakistani or British Pakistani 2.1 \n", - " Unknown 1.4 \n", - " White + Asian 2.1 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 2.2 \n", - "imd_categories 1 Most deprived 1.8 \n", - " 2 1.9 \n", - " 3 1.2 \n", - " 4 1.2 \n", + "sex F 1.3 \n", + " M 1.7 \n", + "ethnicity_6_groups Black 1.3 \n", + " Mixed 1.4 \n", + " Other 1.4 \n", + " South Asian 1.7 \n", + " Unknown 1.5 \n", + " White 1.7 \n", + "ethnicity_16_groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 1.1 \n", + " Caribbean 1.9 \n", + " Chinese 1.1 \n", + " Other 2.0 \n", + " Other Asian 2.3 \n", + " British or Mixed British 1.0 \n", + " Indian or British Indian 2.2 \n", + " Irish 1.0 \n", + " Other Black 1.0 \n", + " Other White 1.0 \n", + " Other mixed 1.1 \n", + " Pakistani or British Pakistani 2.2 \n", + " Unknown 1.2 \n", + " White + Asian 2.4 \n", + " White + Black African 1.0 \n", + " White + Black Caribbean 1.0 \n", + "imd_categories 1 Most deprived 1.5 \n", + " 2 1.5 \n", + " 3 1.5 \n", + " 4 0.9 \n", " 5 Least deprived 1.2 \n", - " Unknown 4.6 \n", - "bmi 30+ 1.9 \n", - " under 30 1.3 \n", + " Unknown 2.3 \n", + "bmi 30+ 1.1 \n", + " under 30 1.6 \n", "chronic_cardiac_disease no 1.5 \n", - " yes 0.0 \n", + " yes 5.0 \n", "current_copd no 1.5 \n", " yes 0.0 \n", - "dmards no 1.4 \n", + "dmards no 1.5 \n", " yes 0.0 \n", "psychosis_schiz_bipolar no 1.5 \n", " yes 0.0 \n", "ssri no 1.5 \n", " yes 0.0 \n", - "ckd no 1.6 \n", - " yes 1.7 \n", + "ckd no 1.4 \n", + " yes 1.5 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall reached \n", - "sex F reached \n", + "overall overall 02-Feb \n", + "sex F 03-Feb \n", " M reached \n", - "ethnicity_6_groups Black 20-Dec \n", + "ethnicity_6_groups Black 05-Feb \n", " Mixed reached \n", - " Other 16-Dec \n", + " Other 08-Feb \n", " South Asian reached \n", " Unknown reached \n", - " White 16-Dec \n", - "ethnicity_16_groups African reached \n", - " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean 24-Dec \n", + " White 02-Feb \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi 07-Feb \n", + " Caribbean 04-Feb \n", " Chinese reached \n", " Other reached \n", - " Other Asian reached \n", - " British or Mixed British unknown \n", + " Other Asian 02-Feb \n", + " British or Mixed British 16-Feb \n", " Indian or British Indian reached \n", - " Irish reached \n", - " Other Black 16-Dec \n", + " Irish 09-Feb \n", + " Other Black reached \n", " Other White reached \n", " Other mixed reached \n", - " Pakistani or British Pakistani 18-Dec \n", + " Pakistani or British Pakistani 06-Feb \n", " Unknown reached \n", - " White + Asian 18-Dec \n", - " White + Black African unknown \n", - " White + Black Caribbean 16-Dec \n", - "imd_categories 1 Most deprived 20-Dec \n", - " 2 reached \n", - " 3 19-Dec \n", + " White + Asian reached \n", + " White + Black African 07-Feb \n", + " White + Black Caribbean reached \n", + "imd_categories 1 Most deprived 04-Feb \n", + " 2 03-Feb \n", + " 3 02-Feb \n", " 4 reached \n", - " 5 Least deprived reached \n", + " 5 Least deprived 02-Feb \n", " Unknown reached \n", "bmi 30+ reached \n", - " under 30 17-Dec \n", - "chronic_cardiac_disease no reached \n", - " yes unknown \n", - "current_copd no reached \n", - " yes unknown \n", - "dmards no reached \n", + " under 30 03-Feb \n", + "chronic_cardiac_disease no 02-Feb \n", + " yes reached \n", + "current_copd no 02-Feb \n", + " yes reached \n", + "dmards no 02-Feb \n", " yes unknown \n", - "psychosis_schiz_bipolar no reached \n", + "psychosis_schiz_bipolar no 02-Feb \n", " yes unknown \n", - "ssri no reached \n", + "ssri no 02-Feb \n", " yes unknown \n", - "ckd no reached \n", - " yes reached " + "ckd no 02-Feb \n", + " yes 02-Feb " ] }, "metadata": {}, @@ -8789,7 +8841,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **30-39** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **30-39** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -8855,295 +8907,295 @@ " \n", " overall\n", " overall\n", - " 5719\n", - " 89.7\n", - " 6377\n", - " 88.1\n", - " 1.6\n", - " 16-Dec\n", + " 11704\n", + " 90.3\n", + " 12957\n", + " 88.9\n", + " 1.4\n", + " reached\n", " \n", " \n", " sex\n", " F\n", - " 2968\n", - " 90.0\n", - " 3297\n", - " 88.5\n", + " 6090\n", + " 90.5\n", + " 6727\n", + " 89.0\n", " 1.5\n", " reached\n", " \n", " \n", " M\n", - " 2751\n", - " 89.3\n", - " 3080\n", - " 88.0\n", - " 1.3\n", - " 18-Dec\n", + " 5607\n", + " 90.0\n", + " 6230\n", + " 88.8\n", + " 1.2\n", + " reached\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 945\n", - " 88.2\n", - " 1071\n", - " 87.6\n", - " 0.6\n", - " 05-Jan\n", + " 2002\n", + " 89.7\n", + " 2233\n", + " 88.4\n", + " 1.3\n", + " 03-Feb\n", " \n", " \n", " Mixed\n", - " 980\n", - " 91.5\n", - " 1071\n", + " 1988\n", + " 90.2\n", + " 2205\n", " 88.9\n", - " 2.6\n", + " 1.3\n", " reached\n", " \n", " \n", " Other\n", - " 1001\n", - " 89.4\n", - " 1120\n", - " 87.5\n", - " 1.9\n", - " 17-Dec\n", + " 1932\n", + " 90.8\n", + " 2128\n", + " 89.1\n", + " 1.7\n", + " reached\n", " \n", " \n", " South Asian\n", - " 1001\n", - " 89.4\n", - " 1120\n", - " 88.1\n", - " 1.3\n", - " 18-Dec\n", + " 2030\n", + " 90.1\n", + " 2254\n", + " 88.2\n", + " 1.9\n", + " reached\n", " \n", " \n", " Unknown\n", - " 861\n", - " 89.8\n", - " 959\n", - " 88.3\n", - " 1.5\n", - " 15-Dec\n", + " 1736\n", + " 90.5\n", + " 1918\n", + " 89.1\n", + " 1.4\n", + " reached\n", " \n", " \n", " White\n", - " 931\n", - " 89.9\n", - " 1036\n", - " 88.5\n", - " 1.4\n", - " 15-Dec\n", + " 2009\n", + " 90.3\n", + " 2226\n", + " 89.3\n", + " 1.0\n", + " reached\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 301\n", - " 89.6\n", - " 336\n", - " 87.5\n", - " 2.1\n", - " 16-Dec\n", + " 644\n", + " 92.0\n", + " 700\n", + " 90.0\n", + " 2.0\n", + " reached\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 301\n", - " 91.5\n", - " 329\n", - " 89.4\n", - " 2.1\n", - " reached\n", + " 616\n", + " 89.8\n", + " 686\n", + " 87.8\n", + " 2.0\n", + " 02-Feb\n", " \n", " \n", " Caribbean\n", - " 294\n", + " 588\n", " 89.4\n", - " 329\n", - " 87.2\n", - " 2.2\n", - " 16-Dec\n", + " 658\n", + " 88.3\n", + " 1.1\n", + " 05-Feb\n", " \n", " \n", " Chinese\n", - " 322\n", - " 90.2\n", - " 357\n", - " 90.2\n", - " 0.0\n", - " reached\n", - " \n", + " 623\n", + " 89.0\n", + " 700\n", + " 88.0\n", + " 1.0\n", + " 09-Feb\n", + " \n", " \n", " Other\n", - " 336\n", - " 90.6\n", - " 371\n", + " 609\n", + " 89.7\n", + " 679\n", " 88.7\n", - " 1.9\n", - " reached\n", + " 1.0\n", + " 04-Feb\n", " \n", " \n", " Other Asian\n", - " 301\n", - " 89.6\n", - " 336\n", - " 89.6\n", - " 0.0\n", - " unknown\n", + " 651\n", + " 91.2\n", + " 714\n", + " 89.2\n", + " 2.0\n", + " reached\n", " \n", " \n", " British or Mixed British\n", - " 301\n", - " 91.5\n", - " 329\n", - " 89.4\n", - " 2.1\n", - " reached\n", + " 637\n", + " 89.2\n", + " 714\n", + " 88.2\n", + " 1.0\n", + " 07-Feb\n", " \n", " \n", " Indian or British Indian\n", - " 329\n", - " 88.7\n", - " 371\n", - " 86.8\n", - " 1.9\n", - " 19-Dec\n", + " 623\n", + " 90.8\n", + " 686\n", + " 88.8\n", + " 2.0\n", + " reached\n", " \n", " \n", " Irish\n", - " 280\n", - " 88.9\n", - " 315\n", - " 88.9\n", - " 0.0\n", - " unknown\n", + " 581\n", + " 90.2\n", + " 644\n", + " 89.1\n", + " 1.1\n", + " reached\n", " \n", " \n", " Other Black\n", - " 280\n", - " 93.0\n", - " 301\n", - " 90.7\n", - " 2.3\n", - " reached\n", + " 623\n", + " 89.9\n", + " 693\n", + " 88.9\n", + " 1.0\n", + " 02-Feb\n", " \n", " \n", " Other White\n", - " 329\n", - " 92.2\n", - " 357\n", - " 90.2\n", - " 2.0\n", - " reached\n", + " 588\n", + " 89.4\n", + " 658\n", + " 88.3\n", + " 1.1\n", + " 05-Feb\n", " \n", " \n", " Other mixed\n", - " 329\n", - " 90.4\n", - " 364\n", - " 88.5\n", - " 1.9\n", + " 630\n", + " 90.9\n", + " 693\n", + " 88.9\n", + " 2.0\n", " reached\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 294\n", - " 87.5\n", - " 336\n", - " 85.4\n", - " 2.1\n", - " 23-Dec\n", + " 658\n", + " 89.5\n", + " 735\n", + " 87.6\n", + " 1.9\n", + " 03-Feb\n", " \n", " \n", " Unknown\n", - " 840\n", - " 90.2\n", - " 931\n", - " 88.0\n", - " 2.2\n", + " 1750\n", + " 91.6\n", + " 1911\n", + " 90.5\n", + " 1.1\n", " reached\n", " \n", " \n", " White + Asian\n", - " 280\n", - " 88.9\n", - " 315\n", - " 88.9\n", - " 0.0\n", - " unknown\n", + " 630\n", + " 90.9\n", + " 693\n", + " 87.9\n", + " 3.0\n", + " reached\n", " \n", " \n", " White + Black African\n", - " 301\n", - " 89.6\n", - " 336\n", - " 87.5\n", - " 2.1\n", - " 16-Dec\n", + " 651\n", + " 90.3\n", + " 721\n", + " 89.3\n", + " 1.0\n", + " reached\n", " \n", " \n", " White + Black Caribbean\n", - " 315\n", - " 90.0\n", - " 350\n", - " 86.0\n", - " 4.0\n", + " 602\n", + " 90.5\n", + " 665\n", + " 88.4\n", + " 2.1\n", " reached\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 1092\n", - " 91.2\n", - " 1197\n", - " 89.5\n", - " 1.7\n", + " 2240\n", + " 90.7\n", + " 2471\n", + " 89.8\n", + " 0.9\n", " reached\n", " \n", " \n", " 2\n", - " 1085\n", - " 88.6\n", - " 1225\n", - " 86.9\n", - " 1.7\n", - " 20-Dec\n", + " 2247\n", + " 90.7\n", + " 2478\n", + " 88.7\n", + " 2.0\n", + " reached\n", " \n", " \n", " 3\n", - " 1099\n", + " 2198\n", " 89.7\n", - " 1225\n", - " 88.6\n", - " 1.1\n", - " 16-Dec\n", + " 2450\n", + " 88.0\n", + " 1.7\n", + " 03-Feb\n", " \n", " \n", " 4\n", - " 1120\n", - " 89.4\n", - " 1253\n", - " 87.7\n", - " 1.7\n", - " 17-Dec\n", + " 2219\n", + " 90.6\n", + " 2450\n", + " 89.1\n", + " 1.5\n", + " reached\n", " \n", " \n", " 5 Least deprived\n", - " 1036\n", - " 90.8\n", - " 1141\n", - " 89.6\n", - " 1.2\n", + " 2205\n", + " 90.5\n", + " 2436\n", + " 89.4\n", + " 1.1\n", " reached\n", " \n", " \n", " Unknown\n", - " 287\n", - " 87.2\n", - " 329\n", - " 85.1\n", - " 2.1\n", - " 24-Dec\n", + " 588\n", + " 87.5\n", + " 672\n", + " 86.5\n", + " 1.0\n", + " 19-Feb\n", " \n", " \n", "\n", @@ -9152,178 +9204,178 @@ "text/plain": [ " vaccinated percent \\\n", "category group \n", - "overall overall 5719 89.7 \n", - "sex F 2968 90.0 \n", - " M 2751 89.3 \n", - "ethnicity_6_groups Black 945 88.2 \n", - " Mixed 980 91.5 \n", - " Other 1001 89.4 \n", - " South Asian 1001 89.4 \n", - " Unknown 861 89.8 \n", - " White 931 89.9 \n", - "ethnicity_16_groups African 301 89.6 \n", - " Bangladeshi or British Bangladeshi 301 91.5 \n", - " Caribbean 294 89.4 \n", - " Chinese 322 90.2 \n", - " Other 336 90.6 \n", - " Other Asian 301 89.6 \n", - " British or Mixed British 301 91.5 \n", - " Indian or British Indian 329 88.7 \n", - " Irish 280 88.9 \n", - " Other Black 280 93.0 \n", - " Other White 329 92.2 \n", - " Other mixed 329 90.4 \n", - " Pakistani or British Pakistani 294 87.5 \n", - " Unknown 840 90.2 \n", - " White + Asian 280 88.9 \n", - " White + Black African 301 89.6 \n", - " White + Black Caribbean 315 90.0 \n", - "imd_categories 1 Most deprived 1092 91.2 \n", - " 2 1085 88.6 \n", - " 3 1099 89.7 \n", - " 4 1120 89.4 \n", - " 5 Least deprived 1036 90.8 \n", - " Unknown 287 87.2 \n", + "overall overall 11704 90.3 \n", + "sex F 6090 90.5 \n", + " M 5607 90.0 \n", + "ethnicity_6_groups Black 2002 89.7 \n", + " Mixed 1988 90.2 \n", + " Other 1932 90.8 \n", + " South Asian 2030 90.1 \n", + " Unknown 1736 90.5 \n", + " White 2009 90.3 \n", + "ethnicity_16_groups African 644 92.0 \n", + " Bangladeshi or British Bangladeshi 616 89.8 \n", + " Caribbean 588 89.4 \n", + " Chinese 623 89.0 \n", + " Other 609 89.7 \n", + " Other Asian 651 91.2 \n", + " British or Mixed British 637 89.2 \n", + " Indian or British Indian 623 90.8 \n", + " Irish 581 90.2 \n", + " Other Black 623 89.9 \n", + " Other White 588 89.4 \n", + " Other mixed 630 90.9 \n", + " Pakistani or British Pakistani 658 89.5 \n", + " Unknown 1750 91.6 \n", + " White + Asian 630 90.9 \n", + " White + Black African 651 90.3 \n", + " White + Black Caribbean 602 90.5 \n", + "imd_categories 1 Most deprived 2240 90.7 \n", + " 2 2247 90.7 \n", + " 3 2198 89.7 \n", + " 4 2219 90.6 \n", + " 5 Least deprived 2205 90.5 \n", + " Unknown 588 87.5 \n", "\n", " total \\\n", "category group \n", - "overall overall 6377 \n", - "sex F 3297 \n", - " M 3080 \n", - "ethnicity_6_groups Black 1071 \n", - " Mixed 1071 \n", - " Other 1120 \n", - " South Asian 1120 \n", - " Unknown 959 \n", - " White 1036 \n", - "ethnicity_16_groups African 336 \n", - " Bangladeshi or British Bangladeshi 329 \n", - " Caribbean 329 \n", - " Chinese 357 \n", - " Other 371 \n", - " Other Asian 336 \n", - " British or Mixed British 329 \n", - " Indian or British Indian 371 \n", - " Irish 315 \n", - " Other Black 301 \n", - " Other White 357 \n", - " Other mixed 364 \n", - " Pakistani or British Pakistani 336 \n", - " Unknown 931 \n", - " White + Asian 315 \n", - " White + Black African 336 \n", - " White + Black Caribbean 350 \n", - "imd_categories 1 Most deprived 1197 \n", - " 2 1225 \n", - " 3 1225 \n", - " 4 1253 \n", - " 5 Least deprived 1141 \n", - " Unknown 329 \n", + "overall overall 12957 \n", + "sex F 6727 \n", + " M 6230 \n", + "ethnicity_6_groups Black 2233 \n", + " Mixed 2205 \n", + " Other 2128 \n", + " South Asian 2254 \n", + " Unknown 1918 \n", + " White 2226 \n", + "ethnicity_16_groups African 700 \n", + " Bangladeshi or British Bangladeshi 686 \n", + " Caribbean 658 \n", + " Chinese 700 \n", + " Other 679 \n", + " Other Asian 714 \n", + " British or Mixed British 714 \n", + " Indian or British Indian 686 \n", + " Irish 644 \n", + " Other Black 693 \n", + " Other White 658 \n", + " Other mixed 693 \n", + " Pakistani or British Pakistani 735 \n", + " Unknown 1911 \n", + " White + Asian 693 \n", + " White + Black African 721 \n", + " White + Black Caribbean 665 \n", + "imd_categories 1 Most deprived 2471 \n", + " 2 2478 \n", + " 3 2450 \n", + " 4 2450 \n", + " 5 Least deprived 2436 \n", + " Unknown 672 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.1 \n", - "sex F 88.5 \n", - " M 88.0 \n", - "ethnicity_6_groups Black 87.6 \n", + "overall overall 88.9 \n", + "sex F 89.0 \n", + " M 88.8 \n", + "ethnicity_6_groups Black 88.4 \n", " Mixed 88.9 \n", - " Other 87.5 \n", - " South Asian 88.1 \n", - " Unknown 88.3 \n", - " White 88.5 \n", - "ethnicity_16_groups African 87.5 \n", - " Bangladeshi or British Bangladeshi 89.4 \n", - " Caribbean 87.2 \n", - " Chinese 90.2 \n", + " Other 89.1 \n", + " South Asian 88.2 \n", + " Unknown 89.1 \n", + " White 89.3 \n", + "ethnicity_16_groups African 90.0 \n", + " Bangladeshi or British Bangladeshi 87.8 \n", + " Caribbean 88.3 \n", + " Chinese 88.0 \n", " Other 88.7 \n", - " Other Asian 89.6 \n", - " British or Mixed British 89.4 \n", - " Indian or British Indian 86.8 \n", - " Irish 88.9 \n", - " Other Black 90.7 \n", - " Other White 90.2 \n", - " Other mixed 88.5 \n", - " Pakistani or British Pakistani 85.4 \n", - " Unknown 88.0 \n", - " White + Asian 88.9 \n", - " White + Black African 87.5 \n", - " White + Black Caribbean 86.0 \n", - "imd_categories 1 Most deprived 89.5 \n", - " 2 86.9 \n", - " 3 88.6 \n", - " 4 87.7 \n", - " 5 Least deprived 89.6 \n", - " Unknown 85.1 \n", + " Other Asian 89.2 \n", + " British or Mixed British 88.2 \n", + " Indian or British Indian 88.8 \n", + " Irish 89.1 \n", + " Other Black 88.9 \n", + " Other White 88.3 \n", + " Other mixed 88.9 \n", + " Pakistani or British Pakistani 87.6 \n", + " Unknown 90.5 \n", + " White + Asian 87.9 \n", + " White + Black African 89.3 \n", + " White + Black Caribbean 88.4 \n", + "imd_categories 1 Most deprived 89.8 \n", + " 2 88.7 \n", + " 3 88.0 \n", + " 4 89.1 \n", + " 5 Least deprived 89.4 \n", + " Unknown 86.5 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.6 \n", + "overall overall 1.4 \n", "sex F 1.5 \n", - " M 1.3 \n", - "ethnicity_6_groups Black 0.6 \n", - " Mixed 2.6 \n", - " Other 1.9 \n", - " South Asian 1.3 \n", - " Unknown 1.5 \n", - " White 1.4 \n", - "ethnicity_16_groups African 2.1 \n", - " Bangladeshi or British Bangladeshi 2.1 \n", - " Caribbean 2.2 \n", - " Chinese 0.0 \n", - " Other 1.9 \n", - " Other Asian 0.0 \n", - " British or Mixed British 2.1 \n", - " Indian or British Indian 1.9 \n", - " Irish 0.0 \n", - " Other Black 2.3 \n", - " Other White 2.0 \n", - " Other mixed 1.9 \n", - " Pakistani or British Pakistani 2.1 \n", - " Unknown 2.2 \n", - " White + Asian 0.0 \n", - " White + Black African 2.1 \n", - " White + Black Caribbean 4.0 \n", - "imd_categories 1 Most deprived 1.7 \n", - " 2 1.7 \n", - " 3 1.1 \n", - " 4 1.7 \n", - " 5 Least deprived 1.2 \n", - " Unknown 2.1 \n", + " M 1.2 \n", + "ethnicity_6_groups Black 1.3 \n", + " Mixed 1.3 \n", + " Other 1.7 \n", + " South Asian 1.9 \n", + " Unknown 1.4 \n", + " White 1.0 \n", + "ethnicity_16_groups African 2.0 \n", + " Bangladeshi or British Bangladeshi 2.0 \n", + " Caribbean 1.1 \n", + " Chinese 1.0 \n", + " Other 1.0 \n", + " Other Asian 2.0 \n", + " British or Mixed British 1.0 \n", + " Indian or British Indian 2.0 \n", + " Irish 1.1 \n", + " Other Black 1.0 \n", + " Other White 1.1 \n", + " Other mixed 2.0 \n", + " Pakistani or British Pakistani 1.9 \n", + " Unknown 1.1 \n", + " White + Asian 3.0 \n", + " White + Black African 1.0 \n", + " White + Black Caribbean 2.1 \n", + "imd_categories 1 Most deprived 0.9 \n", + " 2 2.0 \n", + " 3 1.7 \n", + " 4 1.5 \n", + " 5 Least deprived 1.1 \n", + " Unknown 1.0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 16-Dec \n", + "overall overall reached \n", "sex F reached \n", - " M 18-Dec \n", - "ethnicity_6_groups Black 05-Jan \n", + " M reached \n", + "ethnicity_6_groups Black 03-Feb \n", " Mixed reached \n", - " Other 17-Dec \n", - " South Asian 18-Dec \n", - " Unknown 15-Dec \n", - " White 15-Dec \n", - "ethnicity_16_groups African 16-Dec \n", - " Bangladeshi or British Bangladeshi reached \n", - " Caribbean 16-Dec \n", - " Chinese reached \n", - " Other reached \n", - " Other Asian unknown \n", - " British or Mixed British reached \n", - " Indian or British Indian 19-Dec \n", - " Irish unknown \n", - " Other Black reached \n", - " Other White reached \n", + " Other reached \n", + " South Asian reached \n", + " Unknown reached \n", + " White reached \n", + "ethnicity_16_groups African reached \n", + " Bangladeshi or British Bangladeshi 02-Feb \n", + " Caribbean 05-Feb \n", + " Chinese 09-Feb \n", + " Other 04-Feb \n", + " Other Asian reached \n", + " British or Mixed British 07-Feb \n", + " Indian or British Indian reached \n", + " Irish reached \n", + " Other Black 02-Feb \n", + " Other White 05-Feb \n", " Other mixed reached \n", - " Pakistani or British Pakistani 23-Dec \n", + " Pakistani or British Pakistani 03-Feb \n", " Unknown reached \n", - " White + Asian unknown \n", - " White + Black African 16-Dec \n", + " White + Asian reached \n", + " White + Black African reached \n", " White + Black Caribbean reached \n", "imd_categories 1 Most deprived reached \n", - " 2 20-Dec \n", - " 3 16-Dec \n", - " 4 17-Dec \n", + " 2 reached \n", + " 3 03-Feb \n", + " 4 reached \n", " 5 Least deprived reached \n", - " Unknown 24-Dec " + " Unknown 19-Feb " ] }, "metadata": {}, @@ -9352,7 +9404,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **18-29** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **18-29** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -9418,295 +9470,295 @@ " \n", " overall\n", " overall\n", - " 6699\n", - " 90.3\n", - " 7420\n", - " 88.5\n", - " 1.8\n", - " reached\n", + " 13440\n", + " 89.8\n", + " 14966\n", + " 88.4\n", + " 1.4\n", + " 03-Feb\n", " \n", " \n", " sex\n", " F\n", - " 3430\n", - " 90.2\n", - " 3801\n", - " 88.4\n", - " 1.8\n", - " reached\n", + " 6909\n", + " 89.9\n", + " 7686\n", + " 88.6\n", + " 1.3\n", + " 02-Feb\n", " \n", " \n", " M\n", - " 3269\n", - " 90.5\n", - " 3612\n", - " 89.0\n", - " 1.5\n", - " reached\n", + " 6531\n", + " 89.6\n", + " 7287\n", + " 88.2\n", + " 1.4\n", + " 04-Feb\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 1169\n", - " 91.8\n", - " 1274\n", - " 89.6\n", - " 2.2\n", + " 2317\n", + " 90.7\n", + " 2555\n", + " 89.3\n", + " 1.4\n", " reached\n", " \n", " \n", " Mixed\n", - " 1064\n", - " 89.9\n", - " 1183\n", - " 88.2\n", - " 1.7\n", - " 15-Dec\n", + " 2310\n", + " 89.7\n", + " 2576\n", + " 88.3\n", + " 1.4\n", + " 03-Feb\n", " \n", " \n", " Other\n", - " 1148\n", + " 2296\n", " 89.6\n", - " 1281\n", - " 88.0\n", - " 1.6\n", - " 16-Dec\n", + " 2562\n", + " 87.7\n", + " 1.9\n", + " 03-Feb\n", " \n", " \n", " South Asian\n", - " 1127\n", - " 89.9\n", - " 1253\n", - " 88.3\n", - " 1.6\n", - " 15-Dec\n", + " 2247\n", + " 89.4\n", + " 2513\n", + " 88.0\n", + " 1.4\n", + " 05-Feb\n", " \n", " \n", " Unknown\n", - " 1057\n", - " 91.5\n", - " 1155\n", - " 90.3\n", - " 1.2\n", + " 2023\n", + " 90.6\n", + " 2233\n", + " 89.0\n", + " 1.6\n", " reached\n", " \n", " \n", " White\n", - " 1134\n", - " 89.5\n", - " 1267\n", - " 87.3\n", - " 2.2\n", - " 16-Dec\n", + " 2254\n", + " 89.4\n", + " 2520\n", + " 88.6\n", + " 0.8\n", + " 07-Feb\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 343\n", - " 90.7\n", - " 378\n", - " 90.7\n", - " 0.0\n", + " 721\n", + " 92.0\n", + " 784\n", + " 90.2\n", + " 1.8\n", " reached\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 357\n", - " 89.5\n", - " 399\n", - " 86.0\n", - " 3.5\n", - " 16-Dec\n", + " 721\n", + " 89.6\n", + " 805\n", + " 88.7\n", + " 0.9\n", + " 05-Feb\n", " \n", " \n", " Caribbean\n", - " 336\n", - " 92.3\n", - " 364\n", - " 90.4\n", - " 1.9\n", + " 714\n", + " 91.1\n", + " 784\n", + " 90.2\n", + " 0.9\n", " reached\n", " \n", " \n", " Chinese\n", - " 364\n", - " 92.9\n", - " 392\n", - " 91.1\n", - " 1.8\n", - " reached\n", + " 721\n", + " 88.8\n", + " 812\n", + " 87.1\n", + " 1.7\n", + " 06-Feb\n", " \n", " \n", " Other\n", - " 322\n", - " 86.8\n", - " 371\n", - " 84.9\n", - " 1.9\n", - " 26-Dec\n", + " 728\n", + " 91.2\n", + " 798\n", + " 90.4\n", + " 0.8\n", + " reached\n", " \n", " \n", " Other Asian\n", - " 378\n", - " 90.0\n", - " 420\n", - " 88.3\n", - " 1.7\n", - " reached\n", + " 700\n", + " 89.3\n", + " 784\n", + " 87.5\n", + " 1.8\n", + " 04-Feb\n", " \n", " \n", " British or Mixed British\n", - " 364\n", - " 89.7\n", - " 406\n", - " 89.7\n", - " 0.0\n", - " unknown\n", + " 693\n", + " 90.8\n", + " 763\n", + " 89.0\n", + " 1.8\n", + " reached\n", " \n", " \n", " Indian or British Indian\n", - " 357\n", - " 91.1\n", - " 392\n", - " 89.3\n", - " 1.8\n", - " reached\n", + " 742\n", + " 89.8\n", + " 826\n", + " 89.0\n", + " 0.8\n", + " 03-Feb\n", " \n", " \n", " Irish\n", - " 378\n", - " 91.5\n", - " 413\n", - " 89.8\n", - " 1.7\n", + " 700\n", + " 90.9\n", + " 770\n", + " 90.0\n", + " 0.9\n", " reached\n", " \n", " \n", " Other Black\n", - " 399\n", - " 91.9\n", - " 434\n", - " 90.3\n", - " 1.6\n", - " reached\n", + " 714\n", + " 89.5\n", + " 798\n", + " 88.6\n", + " 0.9\n", + " 05-Feb\n", " \n", " \n", " Other White\n", - " 364\n", - " 88.1\n", - " 413\n", - " 86.4\n", - " 1.7\n", - " 22-Dec\n", + " 707\n", + " 89.4\n", + " 791\n", + " 88.5\n", + " 0.9\n", + " 06-Feb\n", " \n", " \n", " Other mixed\n", - " 364\n", - " 91.2\n", - " 399\n", - " 89.5\n", - " 1.7\n", - " reached\n", + " 707\n", + " 89.4\n", + " 791\n", + " 88.5\n", + " 0.9\n", + " 06-Feb\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 364\n", - " 91.2\n", - " 399\n", - " 89.5\n", - " 1.7\n", - " reached\n", + " 686\n", + " 89.9\n", + " 763\n", + " 88.1\n", + " 1.8\n", + " 02-Feb\n", " \n", " \n", " Unknown\n", - " 980\n", - " 89.2\n", - " 1099\n", - " 87.9\n", - " 1.3\n", - " 19-Dec\n", + " 2037\n", + " 89.5\n", + " 2275\n", + " 88.0\n", + " 1.5\n", + " 04-Feb\n", " \n", " \n", " White + Asian\n", - " 336\n", - " 90.6\n", - " 371\n", - " 88.7\n", - " 1.9\n", - " reached\n", + " 735\n", + " 89.0\n", + " 826\n", + " 86.4\n", + " 2.6\n", + " 04-Feb\n", " \n", " \n", " White + Black African\n", - " 378\n", - " 88.5\n", - " 427\n", + " 707\n", + " 87.8\n", + " 805\n", " 85.2\n", - " 3.3\n", - " 18-Dec\n", + " 2.6\n", + " 07-Feb\n", " \n", " \n", " White + Black Caribbean\n", - " 315\n", - " 90.0\n", - " 350\n", - " 88.0\n", - " 2.0\n", + " 714\n", + " 90.3\n", + " 791\n", + " 89.4\n", + " 0.9\n", " reached\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 1309\n", - " 90.3\n", - " 1449\n", - " 88.4\n", - " 1.9\n", - " reached\n", + " 2618\n", + " 89.0\n", + " 2940\n", + " 87.4\n", + " 1.6\n", + " 06-Feb\n", " \n", " \n", " 2\n", - " 1260\n", - " 90.0\n", - " 1400\n", - " 88.0\n", - " 2.0\n", + " 2555\n", + " 90.1\n", + " 2835\n", + " 88.9\n", + " 1.2\n", " reached\n", " \n", " \n", " 3\n", - " 1302\n", - " 91.6\n", - " 1421\n", - " 90.1\n", + " 2527\n", + " 88.9\n", + " 2842\n", + " 87.4\n", " 1.5\n", - " reached\n", + " 07-Feb\n", " \n", " \n", " 4\n", - " 1190\n", - " 89.5\n", - " 1330\n", - " 87.9\n", - " 1.6\n", - " 17-Dec\n", + " 2583\n", + " 90.4\n", + " 2856\n", + " 89.0\n", + " 1.4\n", + " reached\n", " \n", " \n", " 5 Least deprived\n", - " 1302\n", - " 89.9\n", - " 1449\n", - " 88.4\n", - " 1.5\n", - " 15-Dec\n", + " 2513\n", + " 90.4\n", + " 2779\n", + " 89.2\n", + " 1.2\n", + " reached\n", " \n", " \n", " Unknown\n", - " 336\n", - " 90.6\n", - " 371\n", - " 88.7\n", + " 644\n", + " 89.3\n", + " 721\n", + " 87.4\n", " 1.9\n", - " reached\n", + " 04-Feb\n", " \n", " \n", "\n", @@ -9715,178 +9767,178 @@ "text/plain": [ " vaccinated percent \\\n", "category group \n", - "overall overall 6699 90.3 \n", - "sex F 3430 90.2 \n", - " M 3269 90.5 \n", - "ethnicity_6_groups Black 1169 91.8 \n", - " Mixed 1064 89.9 \n", - " Other 1148 89.6 \n", - " South Asian 1127 89.9 \n", - " Unknown 1057 91.5 \n", - " White 1134 89.5 \n", - "ethnicity_16_groups African 343 90.7 \n", - " Bangladeshi or British Bangladeshi 357 89.5 \n", - " Caribbean 336 92.3 \n", - " Chinese 364 92.9 \n", - " Other 322 86.8 \n", - " Other Asian 378 90.0 \n", - " British or Mixed British 364 89.7 \n", - " Indian or British Indian 357 91.1 \n", - " Irish 378 91.5 \n", - " Other Black 399 91.9 \n", - " Other White 364 88.1 \n", - " Other mixed 364 91.2 \n", - " Pakistani or British Pakistani 364 91.2 \n", - " Unknown 980 89.2 \n", - " White + Asian 336 90.6 \n", - " White + Black African 378 88.5 \n", - " White + Black Caribbean 315 90.0 \n", - "imd_categories 1 Most deprived 1309 90.3 \n", - " 2 1260 90.0 \n", - " 3 1302 91.6 \n", - " 4 1190 89.5 \n", - " 5 Least deprived 1302 89.9 \n", - " Unknown 336 90.6 \n", + "overall overall 13440 89.8 \n", + "sex F 6909 89.9 \n", + " M 6531 89.6 \n", + "ethnicity_6_groups Black 2317 90.7 \n", + " Mixed 2310 89.7 \n", + " Other 2296 89.6 \n", + " South Asian 2247 89.4 \n", + " Unknown 2023 90.6 \n", + " White 2254 89.4 \n", + "ethnicity_16_groups African 721 92.0 \n", + " Bangladeshi or British Bangladeshi 721 89.6 \n", + " Caribbean 714 91.1 \n", + " Chinese 721 88.8 \n", + " Other 728 91.2 \n", + " Other Asian 700 89.3 \n", + " British or Mixed British 693 90.8 \n", + " Indian or British Indian 742 89.8 \n", + " Irish 700 90.9 \n", + " Other Black 714 89.5 \n", + " Other White 707 89.4 \n", + " Other mixed 707 89.4 \n", + " Pakistani or British Pakistani 686 89.9 \n", + " Unknown 2037 89.5 \n", + " White + Asian 735 89.0 \n", + " White + Black African 707 87.8 \n", + " White + Black Caribbean 714 90.3 \n", + "imd_categories 1 Most deprived 2618 89.0 \n", + " 2 2555 90.1 \n", + " 3 2527 88.9 \n", + " 4 2583 90.4 \n", + " 5 Least deprived 2513 90.4 \n", + " Unknown 644 89.3 \n", "\n", " total \\\n", "category group \n", - "overall overall 7420 \n", - "sex F 3801 \n", - " M 3612 \n", - "ethnicity_6_groups Black 1274 \n", - " Mixed 1183 \n", - " Other 1281 \n", - " South Asian 1253 \n", - " Unknown 1155 \n", - " White 1267 \n", - "ethnicity_16_groups African 378 \n", - " Bangladeshi or British Bangladeshi 399 \n", - " Caribbean 364 \n", - " Chinese 392 \n", - " Other 371 \n", - " Other Asian 420 \n", - " British or Mixed British 406 \n", - " Indian or British Indian 392 \n", - " Irish 413 \n", - " Other Black 434 \n", - " Other White 413 \n", - " Other mixed 399 \n", - " Pakistani or British Pakistani 399 \n", - " Unknown 1099 \n", - " White + Asian 371 \n", - " White + Black African 427 \n", - " White + Black Caribbean 350 \n", - "imd_categories 1 Most deprived 1449 \n", - " 2 1400 \n", - " 3 1421 \n", - " 4 1330 \n", - " 5 Least deprived 1449 \n", - " Unknown 371 \n", + "overall overall 14966 \n", + "sex F 7686 \n", + " M 7287 \n", + "ethnicity_6_groups Black 2555 \n", + " Mixed 2576 \n", + " Other 2562 \n", + " South Asian 2513 \n", + " Unknown 2233 \n", + " White 2520 \n", + "ethnicity_16_groups African 784 \n", + " Bangladeshi or British Bangladeshi 805 \n", + " Caribbean 784 \n", + " Chinese 812 \n", + " Other 798 \n", + " Other Asian 784 \n", + " British or Mixed British 763 \n", + " Indian or British Indian 826 \n", + " Irish 770 \n", + " Other Black 798 \n", + " Other White 791 \n", + " Other mixed 791 \n", + " Pakistani or British Pakistani 763 \n", + " Unknown 2275 \n", + " White + Asian 826 \n", + " White + Black African 805 \n", + " White + Black Caribbean 791 \n", + "imd_categories 1 Most deprived 2940 \n", + " 2 2835 \n", + " 3 2842 \n", + " 4 2856 \n", + " 5 Least deprived 2779 \n", + " Unknown 721 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.5 \n", - "sex F 88.4 \n", - " M 89.0 \n", - "ethnicity_6_groups Black 89.6 \n", - " Mixed 88.2 \n", - " Other 88.0 \n", - " South Asian 88.3 \n", - " Unknown 90.3 \n", - " White 87.3 \n", - "ethnicity_16_groups African 90.7 \n", - " Bangladeshi or British Bangladeshi 86.0 \n", - " Caribbean 90.4 \n", - " Chinese 91.1 \n", - " Other 84.9 \n", - " Other Asian 88.3 \n", - " British or Mixed British 89.7 \n", - " Indian or British Indian 89.3 \n", - " Irish 89.8 \n", - " Other Black 90.3 \n", - " Other White 86.4 \n", - " Other mixed 89.5 \n", - " Pakistani or British Pakistani 89.5 \n", - " Unknown 87.9 \n", - " White + Asian 88.7 \n", + "overall overall 88.4 \n", + "sex F 88.6 \n", + " M 88.2 \n", + "ethnicity_6_groups Black 89.3 \n", + " Mixed 88.3 \n", + " Other 87.7 \n", + " South Asian 88.0 \n", + " Unknown 89.0 \n", + " White 88.6 \n", + "ethnicity_16_groups African 90.2 \n", + " Bangladeshi or British Bangladeshi 88.7 \n", + " Caribbean 90.2 \n", + " Chinese 87.1 \n", + " Other 90.4 \n", + " Other Asian 87.5 \n", + " British or Mixed British 89.0 \n", + " Indian or British Indian 89.0 \n", + " Irish 90.0 \n", + " Other Black 88.6 \n", + " Other White 88.5 \n", + " Other mixed 88.5 \n", + " Pakistani or British Pakistani 88.1 \n", + " Unknown 88.0 \n", + " White + Asian 86.4 \n", " White + Black African 85.2 \n", - " White + Black Caribbean 88.0 \n", - "imd_categories 1 Most deprived 88.4 \n", - " 2 88.0 \n", - " 3 90.1 \n", - " 4 87.9 \n", - " 5 Least deprived 88.4 \n", - " Unknown 88.7 \n", + " White + Black Caribbean 89.4 \n", + "imd_categories 1 Most deprived 87.4 \n", + " 2 88.9 \n", + " 3 87.4 \n", + " 4 89.0 \n", + " 5 Least deprived 89.2 \n", + " Unknown 87.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.8 \n", - "sex F 1.8 \n", - " M 1.5 \n", - "ethnicity_6_groups Black 2.2 \n", - " Mixed 1.7 \n", - " Other 1.6 \n", - " South Asian 1.6 \n", - " Unknown 1.2 \n", - " White 2.2 \n", - "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 3.5 \n", - " Caribbean 1.9 \n", - " Chinese 1.8 \n", - " Other 1.9 \n", - " Other Asian 1.7 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 1.8 \n", - " Irish 1.7 \n", - " Other Black 1.6 \n", - " Other White 1.7 \n", - " Other mixed 1.7 \n", - " Pakistani or British Pakistani 1.7 \n", - " Unknown 1.3 \n", - " White + Asian 1.9 \n", - " White + Black African 3.3 \n", - " White + Black Caribbean 2.0 \n", - "imd_categories 1 Most deprived 1.9 \n", - " 2 2.0 \n", + "overall overall 1.4 \n", + "sex F 1.3 \n", + " M 1.4 \n", + "ethnicity_6_groups Black 1.4 \n", + " Mixed 1.4 \n", + " Other 1.9 \n", + " South Asian 1.4 \n", + " Unknown 1.6 \n", + " White 0.8 \n", + "ethnicity_16_groups African 1.8 \n", + " Bangladeshi or British Bangladeshi 0.9 \n", + " Caribbean 0.9 \n", + " Chinese 1.7 \n", + " Other 0.8 \n", + " Other Asian 1.8 \n", + " British or Mixed British 1.8 \n", + " Indian or British Indian 0.8 \n", + " Irish 0.9 \n", + " Other Black 0.9 \n", + " Other White 0.9 \n", + " Other mixed 0.9 \n", + " Pakistani or British Pakistani 1.8 \n", + " Unknown 1.5 \n", + " White + Asian 2.6 \n", + " White + Black African 2.6 \n", + " White + Black Caribbean 0.9 \n", + "imd_categories 1 Most deprived 1.6 \n", + " 2 1.2 \n", " 3 1.5 \n", - " 4 1.6 \n", - " 5 Least deprived 1.5 \n", + " 4 1.4 \n", + " 5 Least deprived 1.2 \n", " Unknown 1.9 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall reached \n", - "sex F reached \n", - " M reached \n", + "overall overall 03-Feb \n", + "sex F 02-Feb \n", + " M 04-Feb \n", "ethnicity_6_groups Black reached \n", - " Mixed 15-Dec \n", - " Other 16-Dec \n", - " South Asian 15-Dec \n", + " Mixed 03-Feb \n", + " Other 03-Feb \n", + " South Asian 05-Feb \n", " Unknown reached \n", - " White 16-Dec \n", + " White 07-Feb \n", "ethnicity_16_groups African reached \n", - " Bangladeshi or British Bangladeshi 16-Dec \n", + " Bangladeshi or British Bangladeshi 05-Feb \n", " Caribbean reached \n", - " Chinese reached \n", - " Other 26-Dec \n", - " Other Asian reached \n", - " British or Mixed British unknown \n", - " Indian or British Indian reached \n", + " Chinese 06-Feb \n", + " Other reached \n", + " Other Asian 04-Feb \n", + " British or Mixed British reached \n", + " Indian or British Indian 03-Feb \n", " Irish reached \n", - " Other Black reached \n", - " Other White 22-Dec \n", - " Other mixed reached \n", - " Pakistani or British Pakistani reached \n", - " Unknown 19-Dec \n", - " White + Asian reached \n", - " White + Black African 18-Dec \n", + " Other Black 05-Feb \n", + " Other White 06-Feb \n", + " Other mixed 06-Feb \n", + " Pakistani or British Pakistani 02-Feb \n", + " Unknown 04-Feb \n", + " White + Asian 04-Feb \n", + " White + Black African 07-Feb \n", " White + Black Caribbean reached \n", - "imd_categories 1 Most deprived reached \n", + "imd_categories 1 Most deprived 06-Feb \n", " 2 reached \n", - " 3 reached \n", - " 4 17-Dec \n", - " 5 Least deprived 15-Dec \n", - " Unknown reached " + " 3 07-Feb \n", + " 4 reached \n", + " 5 Least deprived reached \n", + " Unknown 04-Feb " ] }, "metadata": {}, @@ -9915,7 +9967,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose) among **16-17** population up to 15 Dec 2021" + "## COVID vaccination rollout (first dose) among **16-17** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -9981,141 +10033,141 @@ " \n", " overall\n", " overall\n", - " 9345\n", - " 90.3\n", - " 10346\n", - " 88.5\n", - " 1.8\n", - " reached\n", + " 18550\n", + " 89.9\n", + " 20636\n", + " 88.4\n", + " 1.5\n", + " 02-Feb\n", " \n", " \n", " sex\n", " F\n", - " 4781\n", - " 90.3\n", - " 5292\n", + " 9457\n", + " 89.9\n", + " 10514\n", " 88.4\n", - " 1.9\n", - " reached\n", + " 1.5\n", + " 02-Feb\n", " \n", " \n", " M\n", - " 4571\n", - " 90.6\n", - " 5047\n", - " 88.8\n", - " 1.8\n", - " reached\n", + " 9093\n", + " 89.9\n", + " 10115\n", + " 88.5\n", + " 1.4\n", + " 02-Feb\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 1589\n", - " 90.4\n", - " 1757\n", - " 88.4\n", - " 2.0\n", + " 3150\n", + " 90.0\n", + " 3500\n", + " 88.6\n", + " 1.4\n", " reached\n", " \n", " \n", " Mixed\n", - " 1596\n", - " 89.8\n", - " 1778\n", - " 87.0\n", - " 2.8\n", - " 15-Dec\n", + " 3199\n", + " 90.1\n", + " 3549\n", + " 88.4\n", + " 1.7\n", + " reached\n", " \n", " \n", " Other\n", - " 1568\n", - " 90.0\n", - " 1743\n", - " 88.0\n", - " 2.0\n", - " reached\n", + " 3171\n", + " 89.9\n", + " 3528\n", + " 88.3\n", + " 1.6\n", + " 02-Feb\n", " \n", " \n", " South Asian\n", - " 1568\n", - " 90.3\n", - " 1736\n", - " 88.3\n", - " 2.0\n", - " reached\n", + " 3192\n", + " 89.9\n", + " 3549\n", + " 88.6\n", + " 1.3\n", + " 02-Feb\n", " \n", " \n", " Unknown\n", - " 1428\n", - " 90.7\n", - " 1575\n", - " 89.3\n", - " 1.4\n", + " 2737\n", + " 90.3\n", + " 3031\n", + " 89.1\n", + " 1.2\n", " reached\n", " \n", " \n", " White\n", - " 1596\n", - " 91.2\n", - " 1750\n", - " 90.0\n", - " 1.2\n", - " reached\n", + " 3108\n", + " 89.5\n", + " 3472\n", + " 87.9\n", + " 1.6\n", + " 04-Feb\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 1694\n", - " 91.0\n", - " 1862\n", - " 89.1\n", - " 1.9\n", - " reached\n", + " 3570\n", + " 89.8\n", + " 3976\n", + " 88.6\n", + " 1.2\n", + " 03-Feb\n", " \n", " \n", " 2\n", - " 1792\n", - " 90.5\n", - " 1981\n", - " 88.7\n", + " 3486\n", + " 89.7\n", + " 3885\n", + " 87.9\n", " 1.8\n", - " reached\n", + " 03-Feb\n", " \n", " \n", " 3\n", - " 1806\n", - " 90.2\n", - " 2002\n", - " 88.1\n", - " 2.1\n", + " 3542\n", + " 90.0\n", + " 3934\n", + " 88.6\n", + " 1.4\n", " reached\n", " \n", " \n", " 4\n", - " 1827\n", - " 90.3\n", - " 2023\n", - " 88.6\n", - " 1.7\n", - " reached\n", + " 3528\n", + " 89.8\n", + " 3927\n", + " 88.4\n", + " 1.4\n", + " 03-Feb\n", " \n", " \n", " 5 Least deprived\n", - " 1757\n", - " 89.6\n", - " 1960\n", - " 87.9\n", - " 1.7\n", - " 16-Dec\n", + " 3493\n", + " 90.2\n", + " 3871\n", + " 88.8\n", + " 1.4\n", + " reached\n", " \n", " \n", " Unknown\n", - " 476\n", - " 91.9\n", - " 518\n", - " 89.2\n", - " 2.7\n", - " reached\n", + " 938\n", + " 89.3\n", + " 1050\n", + " 88.0\n", + " 1.3\n", + " 05-Feb\n", " \n", " \n", "\n", @@ -10124,75 +10176,75 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 9345 90.3 10346 \n", - "sex F 4781 90.3 5292 \n", - " M 4571 90.6 5047 \n", - "ethnicity_6_groups Black 1589 90.4 1757 \n", - " Mixed 1596 89.8 1778 \n", - " Other 1568 90.0 1743 \n", - " South Asian 1568 90.3 1736 \n", - " Unknown 1428 90.7 1575 \n", - " White 1596 91.2 1750 \n", - "imd_categories 1 Most deprived 1694 91.0 1862 \n", - " 2 1792 90.5 1981 \n", - " 3 1806 90.2 2002 \n", - " 4 1827 90.3 2023 \n", - " 5 Least deprived 1757 89.6 1960 \n", - " Unknown 476 91.9 518 \n", + "overall overall 18550 89.9 20636 \n", + "sex F 9457 89.9 10514 \n", + " M 9093 89.9 10115 \n", + "ethnicity_6_groups Black 3150 90.0 3500 \n", + " Mixed 3199 90.1 3549 \n", + " Other 3171 89.9 3528 \n", + " South Asian 3192 89.9 3549 \n", + " Unknown 2737 90.3 3031 \n", + " White 3108 89.5 3472 \n", + "imd_categories 1 Most deprived 3570 89.8 3976 \n", + " 2 3486 89.7 3885 \n", + " 3 3542 90.0 3934 \n", + " 4 3528 89.8 3927 \n", + " 5 Least deprived 3493 90.2 3871 \n", + " Unknown 938 89.3 1050 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 88.5 \n", + "overall overall 88.4 \n", "sex F 88.4 \n", - " M 88.8 \n", - "ethnicity_6_groups Black 88.4 \n", - " Mixed 87.0 \n", - " Other 88.0 \n", - " South Asian 88.3 \n", - " Unknown 89.3 \n", - " White 90.0 \n", - "imd_categories 1 Most deprived 89.1 \n", - " 2 88.7 \n", - " 3 88.1 \n", - " 4 88.6 \n", - " 5 Least deprived 87.9 \n", - " Unknown 89.2 \n", + " M 88.5 \n", + "ethnicity_6_groups Black 88.6 \n", + " Mixed 88.4 \n", + " Other 88.3 \n", + " South Asian 88.6 \n", + " Unknown 89.1 \n", + " White 87.9 \n", + "imd_categories 1 Most deprived 88.6 \n", + " 2 87.9 \n", + " 3 88.6 \n", + " 4 88.4 \n", + " 5 Least deprived 88.8 \n", + " Unknown 88.0 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.8 \n", - "sex F 1.9 \n", - " M 1.8 \n", - "ethnicity_6_groups Black 2.0 \n", - " Mixed 2.8 \n", - " Other 2.0 \n", - " South Asian 2.0 \n", - " Unknown 1.4 \n", - " White 1.2 \n", - "imd_categories 1 Most deprived 1.9 \n", + "overall overall 1.5 \n", + "sex F 1.5 \n", + " M 1.4 \n", + "ethnicity_6_groups Black 1.4 \n", + " Mixed 1.7 \n", + " Other 1.6 \n", + " South Asian 1.3 \n", + " Unknown 1.2 \n", + " White 1.6 \n", + "imd_categories 1 Most deprived 1.2 \n", " 2 1.8 \n", - " 3 2.1 \n", - " 4 1.7 \n", - " 5 Least deprived 1.7 \n", - " Unknown 2.7 \n", + " 3 1.4 \n", + " 4 1.4 \n", + " 5 Least deprived 1.4 \n", + " Unknown 1.3 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall reached \n", - "sex F reached \n", - " M reached \n", + "overall overall 02-Feb \n", + "sex F 02-Feb \n", + " M 02-Feb \n", "ethnicity_6_groups Black reached \n", - " Mixed 15-Dec \n", - " Other reached \n", - " South Asian reached \n", + " Mixed reached \n", + " Other 02-Feb \n", + " South Asian 02-Feb \n", " Unknown reached \n", - " White reached \n", - "imd_categories 1 Most deprived reached \n", - " 2 reached \n", + " White 04-Feb \n", + "imd_categories 1 Most deprived 03-Feb \n", + " 2 03-Feb \n", " 3 reached \n", - " 4 reached \n", - " 5 Least deprived 16-Dec \n", - " Unknown reached " + " 4 03-Feb \n", + " 5 Least deprived reached \n", + " Unknown 05-Feb " ] }, "metadata": {}, @@ -10208,37 +10260,39 @@ } ], "source": [ + "\n", + "\n", "create_detailed_summary_uptake(summarised_data_dict, formatted_latest_date, \n", " groups=population_subgroups.keys(),\n", - " savepath=savepath)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Demographics time trend charts" + " savepath=savepath)\n", + "\n", + "\n", + "# # Demographics time trend charts" ] }, { "cell_type": "code", - "execution_count": 26, - "metadata": {}, + "execution_count": 27, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "from report_results import plot_dem_charts" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **80+** population up to 15 Dec 2021" + " ## COVID vaccination rollout among **80+** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -10269,7 +10323,7 @@ }, { "data": { - "image/png": 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", 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", 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", 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", 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", 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jxsSvXLmyV0ef1+mQCl0IIdpI/Shv+0oc9HNOwV8ZiXdNwmo7xPNvzke7QnEatmJ02aGJqhw8lfmO3AoS+wRxeUr0CT6pi3j/V/0o2NGm06cSkVjNFYtanPTlZz/7WckjjzzSZ+7cuWU7d+70v+mmm4q//fZb67Hbvf766wcnT56cMGTIEPuiRYuiNm7cuDM3N9f05z//uc/atWszg4KC3L///e+jHn/88cjHHnss7/bbb4/99NNPdw8fPtw+Y8aMQW16bu1MEroQQpym+p7r8esuwFIeQnVADf4mC/F1DqhzcKQqG7uzDBPBmHQdvoY6XP69Wefqx7svHz14T30yX3bLxBN8mgAYP358TXZ2tu+rr74aMm3atBPeXu/Xr5/zwQcfPDJjxoz4JUuW7I2MjHS99dZbwfv27fMbN25cAnjmQR8zZoxt69atfjExMfakpCQ7wLx584pfe+218I46p9MlCV0IIU7D9nU57FvjqcgtVSHUBJdwOGUll9iqmZV3gB8dSezPU4TYajgvJIgBb3pmEay/rZ54zPG6RWVerxWVdHuaPn162SOPPNLvk08+2V1QUHDCfJaenm4JDg525uTk+IBnCtUpU6ZUfPTRR0cNNfjtt99aTjS1ancgCV0IIU7RiswV7FvjwLcsGHpB/4ERxI1L4oG9SyHvAPkBQ/nix0DARt/SSpbFDmOztyKXSvz0/fKXvywKDg52jRs3rmbVqlWBTW3z5Zdf+n/++efBmzdv3nH22WfHX3bZZRXnnHNO1T333NM/IyPDd8SIEfbKykrDgQMHfFJSUmqzs7PN27dv9x0+fLj97bffDunoczodktCFEOIUrd6/mn7OKdALBp/9PbNylvLjl7AsqwrMSRyuDMZQV0GvWjtu/75sHnlOw77dqhLvogYPHuz4wx/+UHCi9TU1NerWW2+N/ec//5kVGxvr+POf/3z4xhtvjN2wYUPmyy+/nHXNNdcMqqurUwCPPPJIzsiRI+3/+Mc/Ds6YMWNISEiIc/z48badO3daOu6MTo8M/SqEEC2obyMPyxpK6OHYhuXVzhpCq6LpPzCCWSF/gLx03tw/nBKbAR0QiKnIhsVlZ1Bgb1Iun03vuVd3aNwy9GvPI0O/CiHEaWh4lvywp9NbTbDnCSl/kwVLlCJuXCQ/fgnpmYkU2Y34OGBwYS1RhUdwDBzKuP8s6+QzEGcCSehCCHEC9ZX57pLdTK6YQWBxFH2H9mLWPZ4pVElbDOkLYS+8nVVFkd2fwBo7/tpCYp8g6DOCoBkzOvckxBlDEroQQpxA41Hehu4fgwOIGxcJwI+frWHnypVQV4Wzzo8iuz/Wmjr61lopfWIhA8b379zgxRlHEroQQngtWfkhR36wNbzv55xCvOkC4kMSKCq20XeoleFTo9m44lm2//dTqmogwOKHvdpEQJ0di/Znwi+uo7ckc9EJJKELIYTXkR9s+JYFY+/lGafE32QhxBIKgNm8i9LsXSz743Kqdm2h0mkkyOkgIc+OX0kVeeH9KX1ioSRz0WnaNaErpX4D/BzQQDqwAPAHlgGxQBZwtda6tD3jEEKI5tS3ldc/gvbAE9cdt82rv/or1SWlUO7CUOMkyOkiNiiUvlY/iIHYGTMkmYtO1W4JXSkVDdwJJGqta5RSy4FrgETgc631k0qpB4AHgPvbKw4hhDiRY8deD62KxhJ19EhhP362hvT3VlBdUEKwo5ZxRwqhxIUrOpKk/yzvpMjFvn37fG6++eb+e/futbjdbqZNm1b+4osvZm/ZssXv8OHD5rlz55YD3H333X2tVqvrsccey+/smNtbe99yNwEWpZQDT2V+BPgdcI53/RvAV0hCF0J0sPpR3hqPvd5/YARl4T7M9Y7mdn71akzp31NZaSCoxk6Us4aA/qOgP9J7vRO53W6uuOKKIT//+c8L7rrrrn1Op5PrrrtuwF133RU9fPjwmrS0tID6hH66nE4nJlP3aJ1utyi11jlKqWeAQ0AN8InW+hOlVKTWOte7Ta5SKqKp/ZVSNwM3A/TvL7exhBCnp74ar7evxDNka02vEg5P/YZLBl3CrLjRPH3TXUwt3ofRAD66lkqTD0E1dsZXFlB5+3wGzLmnE89CAHz00UeBvr6+7rvuuqsYwGQy8dJLLx2OjY0daTKZtNaahIQE6z333JMLsHPnTsu4cePijxw5Yr711lvzH3rooQKAF154IeTFF1+MdDgcavTo0VVLliw5aDKZ8Pf3H3XzzTfnf/HFF0FPP/109kUXXWRrLp6uoj1vufcGLgcGAmXACqXU9a3dX2v9CvAKeEaKa48YhRBnjsxN+eQeKqHC6hkptNpZA73gsuln0988hdKPX2X7yr8TWuxHpcmHQLcTcBPsctI/KJQ+P7uFxDkdO9JbV/eH9X/ot7d0b5tOnzqk95Dqxyc/3uykL+np6Zbk5OTqxstCQkLc0dHRdfPmzSvKzMz0W7JkySGAu+++27J3716/b7/9dndZWZlx2LBhI+67777C7du3+65cuTIkLS1tl6+vr77++uv7v/TSS6G33357cU1NjWHEiBE1zz333JG2PLf21p73EaYBB7TWhQBKqXeBSUC+UqqPtzrvA5xwHF4hhGhLFdYCPhz+PPEh8QBcMugShsdF89jLG7i3/DNKM2so9e1FaF0tN8709eyUNBtSF3Ri1OJYWmuUUscVet7lx21/4YUXllksFm2xWJwhISGO7Oxs05o1awIzMjL8k5OThwHU1tYaIiIinABGo5H58+d3u87a7ZnQDwETlFL+eG65nw+kAVXAjcCT3r8/aMcYhBBnsMbPlde3lceHxLN4+mIAz/PkK6dwb52LRHWQlbXDwQfix58DCx7qxMi7h5Yq6faSlJRU88EHH/RuvKykpMSQl5dnNhqNxyV6X1/fhmVGoxGn06m01mrOnDnFixYtyjl2e7PZ7O4u7eaNGdrrwFrrjcBKYAueR9YMeG6hPwlcoJTaA1zgfS+EEG2u/rlygJrgEmoG5nPJoEsoXbacL6+7mh3/+S/fbzKTsS2AFVsTKTP4EKZMTHxAknlXNnPmzMra2lrD888/Hwqejmu33XZbvzlz5hRFRUU5bDZbi7lt+vTpFatWreqdk5NjAsjPzzdmZmaa2zv29tSuv4JorR8BHjlmsR1PtS6EEG3q2FnR6geJaXiuPG0xrH+dPW9mk+UfRoXFTJDTgcHXCkAvIC6lTScnE+3AYDDw/vvv77355psHPP30033cbjfnnXde+cKFC3MqKioMzzzzTJ+EhITE+k5xTRkzZkztQw89lHP++efHud1ufHx89MKFCw/FxcXVdeS5tKXud09BCCFO4LhZ0XqV0HeUJ1mXLltOxWsLoa6Kfe7elARY6B3gJPHiixkvPde7nSFDhji++OKLvccut1gsroyMjJ2NFh3VFr5nz57t9a9/8YtflP7iF784rq28urr6hzYNtoNIQhdCdFvHVuT1Y6+HVscQNtDaMCvaxhXPEvjC6xhKHLhDfNkbGg5A6nW/ZuS06Z15CkK0GUnoQohu69iKnOASQiyhhIVYiRsXSemy5Wz9YCVZNSUQGAEhivLQMOw1Dvyj+ksyFz2KJHQhRLdQX403Vj+1aXxIAoTw0zzlXunTXyTLZPC0lePA3HcAfSI81fmwyed0VOhCdAhJ6EKIbmH1/tW4tgeSWDKhYVk8FxBiCaWo2EZYjNXTTr5qFftdtRxy1+H2JvPAQC1t5aLHk4QuhOiSjq3Id5fsZmbJ7Z728Rjr0RvHQFm4D7te+gfBRcVkDelLhclMsEkTaHKRet3dcntd9HiS0IUQXdKxFXk8FxBkiyCsv5VZ94w+atvSZcv575J/syvAjCE4igo/XwItLsYOqcM29FJJ5uKM0G4DywghxMlakbmCBWsWsGDNAnaX7CaxZAKh1THEhyQQH5JAn/4hxI2LbNj+PxsPMfflDex66R/YVRWVFjMmq5mohCRSr/s1wx/8Rm6z90D3339/1JAhQ4bHxcUlJiQkJH7xxRcBp3KcVatWBX766acN+1511VWxixcv7t3cPvWWLFnSSyk15ocffvBraduzzz57SFFRkfFUYjwZUqELIbqMhl7rIfHEh8Q39Fg/tiKvl/PKs0wt3seuADOVFjO9e8G8W+bK2Os92GeffRbwv//9r1d6evoOi8Wic3NzTXa7/fgB3Fvhiy++CLRara4LLrig6mT3ffvtt0NGjx5te/PNN0NGjRrV7CQuX3/99XHPy7cHqdCFEJ2qcVXu2h7IzO23M3P7Hczcfgeq2PLThmmLYfGlsPhS8heez/Y/TyG0eDsukwuDjybUV5M89y5J5j1cTk6OT0hIiNNisWiAPn36OGNjYx0AH3zwQeCwYcMS4+LiEufMmRNbU1OjAKKjo5Nyc3NNAGvXrvUfN25c/O7du81LliwJf+mllyITEhIS16xZYwX4+uuvraNGjUqIiYlJOlG1Xl5ebkhLS7MuXrw467333mvY5uDBgz6pqanxCQkJiUOHDh1ef8zGnz9t2rTBw4cPHzZkyJDhzzzzTFj9vv7+/qPuuOOO6Pj4+MTk5OSEw4cPn3TBLRW6EKJTNa7KE0smEGSLgBDPurAY60+32NNXsuGLXDKrQnFrhdaeaU6DXQ5unGnxzoombeUd6ciDv+9n37OnTadP9R06tLrvn5844aQvV1xxRcX/+3//r29sbOyIKVOmVFx77bUll156qa26ulrdcsstAz/55JPdI0eOtM+aNSv26aefDn/44YebnNEzPj6+7oYbbii0Wq2uxx57LB/g1VdfDcvPz/dJS0vbtXXrVr9Zs2YNWbBgwXEjyS1durTXOeecUz5y5Eh7r169XN98843/lClTqv/1r3+FnH/++eVPPfVUntPppLKy8riieenSpVmRkZEum82mRo0alXj99deXRkVFuWpqagwTJ060/eMf/8i59dZbY/7xj3+E/+Uvfznh0LVNaXVC985v3hfPzGlZWmv3yXyQEELUa9yDfXfJbiZXzGBS7nSKqm3HdXorXbacgz9bRV1ONrssYVRYTBidRowG6GUyEZc6WWZGO4MEBwe7MzIydqxZsybw888/D7zxxhsHP/zww9ljx46tjomJsY8cOdIOMH/+/OJFixZFcJJTdM+cObPMaDQyZsyY2uLiYp+mtlm+fHnIXXfdVQBw1VVXlbz55pshU6ZMqZ4wYULVLbfcEutwOAyzZ88unTRpUs2x+z711FORH3/8cS+AvLw8n+3bt/tFRUVV+fj46GuuuaYcYMyYMVWfffZZ0MldmRYSulIqGPgVcC1gBgoBPyBSKfUd8ILW+suT/VAhxJnt2LbyofvHNDxL3rjT24///AM/fPwdbocbQ1AoFT6+OMy9+PaCO7g8JZrrxvfvxLMQzVXS7clkMjFjxozKGTNmVI4cObLmzTffDE1NTa0+0fZGo1G73Z4atKamptmmZj8/v4apVrU+biZW8vLyjN99911QZmam5fbbb8flcimllH7xxRezL774YtvatWt3v/POO8Hz588feOedd+bffvvtxfX7rlq1KvDrr78OTEtL2xUYGOgeN25cfH08JpNJGwyGhvNzOp0n3S+gpQp9JbAEmKq1Lmu8Qik1BviZUmqQ1vqfJ/vBQogzR1PPlMeHxHNvwJ/I3JTfkMzrK/PSZcvZ89Y7bFfFVBh9CDI5cPQyoY1BXHjNDdw7bWJnnYroZNu2bfM1GAwkJSXZAX744QdLTExMXUpKSm1OTo45IyPDd8SIEfYlS5aETp06tRIgJiambv369f5XX311xfLlyxvavAMDA10VFRUn1fv8zTff7H3llVcW/+c//zlYv2zs2LHxn3zyiXXQoEF1AwcOrLvnnnuKqqqqDFu2bPEHGhJ6WVmZMTg42BUYGOj+4Ycf/LZt23ZKvfNPpNmErrW+oJl1m4HNbRmMEKJnalyRA8SHxHPJoEvI/CifouzjK/Oty/5FltPRML1pYd/z2TzyHC5PiWakVOVntIqKCuOdd97Zv6Kiwmg0GnVsbKz9jTfeOOjv769feumlrDlz5gx2uVwkJydX33vvvYUADz/88JFbb7019qmnnnKMGTOmoUf7VVddVTZ79uzB//3vf3s999xzh1rz+StWrAj97W9/e1Tb9uWXX1765ptvhkyYMKFq4cKFUSaTSfv7+7uWLl16oPF2V111Vfkrr7wSHhcXlzh48ODa5OTkk+5d3xzV1C2F4zZSSgHzgEFa68eUUv2BKK31prYM5kRSU1N1WlpaR3yUEKKNrchcwWMbHiM1MpXF0xcfte69Z7fgLCxkXM5S8ivtFNvsAOT5VTYM2Zo6eSwjb3q8M0Lv9pRSm7XWbTrB+7Zt27KSk5OL2vKYovW2bdsWlpycHNvUutZ2insBcAPnAY8BlcA7wNi2CFAI0XPV32o/1zaL957dctS6omwbqmQjX5TlgkmjraAUVJrMBJpc+N3ymlTkQrRSaxP6eK31aKXUDwBa61KllLkd4xJCdGPH9mJPjUwlcHtMw+11Z2EhzuJirEC5bRtVfj6EW6uoVRb8zUb8gWFjUyWZC3ESWpvQHUopI6ABlFLheCp2IYQ4TuM288kVM47qxT7rntF8eeV0shwODD4G7EYfQozVJA91se38V5grSVyIU9LahL4QeA+IUEo9AcwG5MFPIUSz85Qvnr6Y957dQlGxjV6+NYRmrGXTFU+R5XRQaTFjDdQEaBfhIQaGX3gTw1MlmQtxqlqV0LXWS5VSm4HzAQVcobXe2a6RCSG6hWN7sMNPvdjrhcVYGb31NWq3/4gr0IXqHY7V5OJ/4/8IwOUp0SDJXIjT0qqErpT6O7BMa72oneMRQnQT9ZV542q83vZ1OXzzn4M8YfuKYFsdhsr1fFaRi2FAGL69HJTXWoiKDmfZLfI8uRBtpbWTs2wBHlJK7VVKPa2UatPHIIQQ3U/jZN64GgfI3JRPbWEt1XYngdWHMdSkY/PzweTrpFZZMPSNY9j0azopctHd7d692zx06NDhjZfdfffdfR9++OHIE+2zcOHC0BtuuKFH3wZq7S33N4A3lFIhwFXAU0qp/lrroe0anRCiS1qRuYK0/DSm11zLpNzpsB3ew/NIWsmhI9RVGzFWfUdM7Wbcjhrq/MxEhRqYOz7AO4mKzIgmRFs72elThwAJQCywq82jEUJ0C/Wd4IYWjaEo20ZBZS07civYkVuBoSSfINtBTI506oxuDCbP1KbDZt8BCz6WZC7a1bhx4+J/+ctfRiclJQ2LjY0dUT+FaWNvv/12cEpKSkJubq7pqquuip0/f36/Y6dMdbvd3HLLLTFDhw4dHhcXl/jqq6/2Brj++uv7L126NBjgggsuGDxnzpxYgL/97W9hd955Z9/du3ebBw0aNPyaa64ZMGTIkOGTJ08earPZTmm+9pPV2jb0p4ArgX3AcuDxY8d2F0L0XPXt5WFZQwk9HEs/5xTiTRegqi2ExVj5vHwDfbLXEVJng7oanCaNM8BCVKBi7niZ2rSn+nzJzn4lObY2nT41JNpaff4Nw05r0hen06nS09N3Llu2LPixxx7rO3369Mz6dUuWLOn197//PfLTTz/dEx4e7gJoasrUJUuW9EpPT7fs3Llze25urmncuHHDLrzwQttZZ51VuXbt2sB58+aV5+XlmQsKCjTA+vXrrddee20JwKFDh/z+/e9/7580adLBSy65ZNCSJUt633bbbSWnc06t0drH1g4AE7XWMtyfEGeghvbywxdgKQ+hzlqM3e5PgdGNq+I7Ug5/SJXLiJ/DjsFHYwowEz40iWGTz4FpkshF2/KMRn7i5XPmzCkFmDRpUtV9993XMAjat99+G7ht2zb/L7/8MjMkJKRhLJWmpkxdt25d4NVXX11iMpno16+fc/z48bZvvvnG/4ILLrAtWrQocvPmzX5xcXE1ZWVlxoMHD/ps3rw54NVXXz1UUFBgio6OttdPnTpq1KjqrKws3/a7Gj9pafrUBK31LmAT0N87hnsDrfWWpvcUQnRnJ5odLT4kAUJgz/4fGPTjegJ8TShTPtuDQwmpqeE8ewkDrusr7eRniNOtpE9VZGSks7y8/KhZ0kpKSowDBw60w09ToJpMJlwuV0P279+/v/3QoUO+GRkZfmeddVbDdKtNTZl6onlOBg4c6CgvLzd99NFHwVOnTq0sKSkxLVmypHdAQIC7d+/e7oKCAsxmc8PORqNRtzRla1tp6UPu9v79bBN/nmnHuIQQnai+IgcIyxrK9B9/Rexnl3Nofxk7cisY/+MqEsv2k6gOkm+xABAbFErQz38n7eSi3QUHB7sjIiIcH3zwQSBAfn6+8auvvgo+77zzbM3tFxMTU/fOO+/sXbBgwcC0tDS/5rY9++yzK1euXBnidDo5cuSIadOmTdapU6dWAYwZM8b28ssvR0ybNs12zjnn2BYtWhQ1fvz4Zj+7I7Q0ferN3pcXa61rG69TSjV7MYQQXV9To7zB8SO9Haoso66uDGtdNlG5u6nByfeDo/CLslBZCTF9wjj3mdc7/gTEGeuNN944cNttt/W///77+wHcf//9R4YPH25vab/k5GT7kiVL9s+dO3fwhx9+uPdE2/3sZz8r+/bbb63Dhg0brpTSf/zjH7P79+/vBJgyZYpt3bp1QSNGjLDb7fa68vJy41lnnVXZdmd3alo7feoWrfXolpa1F5k+VYj2sWDNguNGeQNPVT60aAzaGYizoJJA42FSf/w7xjI3fhFmvrL2psLXQsSwJACGTT6HkdJW3uXI9Kk9zylPn6qUigKiAYtSahSeYV8BgoA27dkohOg4zY3yBjSMv15bU0BIVT4x5RvJ1v7kDg7CL8JMZSVE9Aln7iNPdtIZCCGO1VIv94uA+UAM8NdGyyuBB1s6uFKqF/AaMALPTG3/B+wGluF5lj0LuFprXXpSUQshTsuJRnnbvi6HzE355B8owmo8zMTtf8NU5sQSZeGrvgOoMCn8+sQT3sdTlQshuo6W2tDrR4i7Smv9zikc/+/AGq31bO/86f54fhH4XGv9pFLqAeAB4P5TOLYQ4iS1VJlnbsqn8EAJgeUHiC7fiKHMzeF+IZQkxlFZXENE7ECpyoXoolo79Os7SqlLgeGAX6Plj51oH6VUEHAWngofrXUdUKeUuhw4x7vZG8BXSEIXokMcV5mnLYb0lQDkV9ZSdeg6AsqdjNn6N9whPgSkpFIQ5ENpsY3w2IFSlQvRhbV2pLiX8FTX5+K5hT4bz7PpzRkEFAKLlVLJwGbgLiBSa50LoLXOVUpFnOAzbwZuBujfv0ePpy9EuznR8+T1lXnpXVNJzxpKTq8JuN0am18kgc4csqJ7c3jwYIIi+lKadYBwqcyF6PJa+7D7JK31DUCp1vqPwESgXwv7mIDRwIta61FAFZ7b662itX5Fa52qtU4NDw9v7W5CiEYaP08OEO8TzCW5+2HxpbD4Usp+yOOw/3jKzP2owg+fuhL6+RVSPDgRe7UDQCpzIbqJ1g79WuP9u1op1RcoBga2sE82kK213uh9vxJPQs9XSvXxVud9gIKTDVoI0bym2sq3r8thxwdrcNocvGXw/C7vjtZUWGMoN2ZS47+bMKsvuUG+lGbZpCoXXdZNN93Ub8CAAfaHH364AGDKlClDo6Oj65YtW3YQ4Be/+EVMdHS04+uvvw788ssvj3vWfO7cuQN++9vf5o8ZM6b2gQceiHryySfzOvoc2kNrK/RV3h7rT+OZGz0LeLu5HbTWecBhpVT9A67nAzuAD4EbvctuBD44uZCFEC1pqhd75qZ8SpxRuJ0Kh9GfavyoMvnhMDqIsBwkvK6YiCDPkNNSlYuubPLkybbvvvvOCuByuSgtLTXt3r3bUr/++++/tzocjhPOcLZs2bKDY8aMqQVYuHBhn/aPuGO0tlPc496X7yilVgF+WuvyVux6B7DU28N9P7AAzy8Ry5VSNwGHgDknH7YQol5To701rsxLly3n4G8vpDZ4NtY6N1OKXubpiT/HcvhH/P2MhAX4Ul1yRCpy0W2cd955tt/97nf9ADZv3myJj4+vyc/P9yksLDRarVb3vn37/MaMGVP96aefBk+fPn3Q7t27LUlJSdXvv//+AYPBwLhx4+KfeeaZw2+//XZvu91uSEhISIyLi6v58MMPD7zwwgshL774YqTD4VCjR4+uWrJkyUGTqbU3sztXSwPLXNnMOrTW7za3v9Z6K9DUKEXntyo6IUSLGlfj9RpX5ulrMjlsuQqbuS+B+gjbYhOxHP6RsLoiYmOHenYIkopcnLz/vfhcv6LDB9t0kLGwfgOqL/rlr5ud9CU2NtZhMpn0nj17zF9//XXAhAkTqnJycny++OILa+/evZ3x8fE1ZrNZ79y507J169b9sbGxjjFjxiR8+umn1osuuqhhzPUXXngh5/XXX4/YtWvXDoAtW7b4rVy5MiQtLW2Xr6+vvv766/u/9NJLobfffntxW55je2np147LmlmngWYTuhCibbVUjdcrXbacisc/4iAfcdg1BZu1LxG9ivneZcdRaiWsrgj/qP5SkYtua8yYMbYvv/wyYMOGDdb77rsv/9ChQ+b169cHBAcHu8aNG2cDSEpKqho8eLADYPjw4dX79u0zN3fMNWvWBGZkZPgnJycPA6itrTVEREQ42/9s2kZLA8vIlElCdCEtVePgGe3tx8+cuN1nYfD3x0YwIRygsG8+jh8LPJV53FCpyMVpa6mSbk8TJ060ffvtt9Zdu3ZZxo4dWzNo0KC65557LtJqtboWLFhQBODr69t4GlOcTucJ29UBtNZqzpw5xYsWLcpp7/jbQ2ufQ3+4qeXNDSwjhGg7zY3w1rgapzKPH4NnU6zL0K7tGOwGcLsoNlaz78dQqcxFj3H22WfbFi1aFNW/f3+7yWQiMjLSVVFRYdyzZ49lyZIlBzdv3mxp+ShgMpm03W5Xvr6+evr06RVXXnnlkAcffDA/OjramZ+fbywvLzfGxcXVtff5tIXWtvRXNXrtB8wAdrZ9OEKIpjTVa71+3PXaXT9V4xhsVJj7oivXA0UE+bpxuDRFOgh/s5HYWKnMRc8wbty4mrKyMtOVV17Z0L6dkJBQU1VVZezTp0+rb5PPmzevcNiwYYkjRoyo/vDDDw889NBDOeeff36c2+3Gx8dHL1y48FB3Seitmj71uJ2U8gU+1Fpf1PYhHU+mTxVnquYq8xUP/I+SUo218hAGH/CL8KWibCc2ez5ObSNqyGDejbqcHbkVJPYJ4vKUaK4bL6Munklk+tSe55SnT22GP56hXYUQ7ahxMp+XGcHBpTc0rKtzTMIKTCl+maCYcnonDmPZRqjEjCEilnWufg3JfNktEzvvJIQQHaK1bejpeHq1AxiBcEDaz4VoY82NvX7wpQvZWzWAgr5jAbAFRhNiyqM8WvNd1TA4lESh/QDhgwceV5kLIXq+1lboMxq9dgL5Wutu05VfiO4i59+LmbnxMP6mn/rzhFryOLj0BmoP5FAw8kps1hjC/Avxo4i4sD1kHIgm1+ZD6ZEKMIeySypz0b7cbrdbGQyGk2+vFafF7XYrwH2i9a0dKe6gUqo3nglZTECkd2CZLW0TphBntvrKfObGw8Tma0KSEjhoiiNHxVDiqmOrM4uaYeByb8HHnkFdhBWAjFootFspDQjl3T6Xk9gnCIBEkMpctJeMwsLCxPDw8HJJ6h3H7XarwsLCYCDjRNu09pb743jmNd/HT7feNXDeacYohMDTVh756Y8kHHRSNSKWAW8uYcuzW7DtzyPMlEVJaS5OVyVmsx+WwJ/GxiiosFNkDiXDb7BU5KJDOJ3On+fl5b2Wl5c3gtbPByJOnxvIcDqdPz/RBq295X41MFhr3S267gvR1TXVVn7NLiMAg8fFeaY3zbsac91O6lzpaKOVvsPij3t+fO7LG6StXHSoMWPGFAAzOzsOcbzWJvQMoBcy1akQbaK+9/rVu3oxbLPnCSDlGsPWqVPxK3RATjxFznDq7F9RiZnwwT+Ntf6fjYf4YKtnICtpKxdC1GttQv9/wA9KqQzAXr9Qay2/pQnRSo2r8vre67MOuKgtKMIvuhffho2i0hhMXdk6bPZ8MO/wPk9+dGX+wdachkQulbkQol5rE/obwFNAOs30sBNCnFjjZ8rjQ+K5dONovnH4YEiZjl8vBzZbKOHWIuoq0z1Veb9IwEpl35HMfXlDw3GkKhdCNKW1Cb1Ia72wXSMRooc6arQ3n2AW53part7a74vN2hez8ztKcg+BwUipX2+q7VbCB/80N3njdnJAqnIhRJNam9A3K6X+H/AhR99yl8fWhGhB4/byKRuyWeufSk6vCVT49CXIcQSD5Qeq6iA8IhwCzQT0On5ucqnIhRAtaW1CH+X9e0KjZfLYmhDNaKjMC9OJd8GsDbnU5tWxZ/QEKvz6Y6zdRJXPYWrtVsLjBsoMaEKI09LagWXObe9AhOgJSpctp2LVKgCCSnYx01mDv9tNqMtJbbEJvygLfgNj8AuMoM5WTWFWBeGxTfdgr9f4drsQQpyIzIcuRBvat2Ixxr2HKYj2J08ZqA6IwF9r8pQRIgJwWMOp2PMhvhYT2lVIeOzAE/Zgrydt5kKI1pD50IVoI6XLlhOQkcWuASY+vGM4Az/IwVpuJCTIANZwCIzCdtgGOLE00Vb+n42H2HighPEDQ6S9XAhx0lp7y/3Zxu+VUs/g6SAnhMDTXh605BkICWR/RBDT3y8gr9wXk08Y5qF3NGxnDrTRd5iVWfeMPu4Y9bfapRoXQpwKmQ9diFPQuK0cPO3lYdk2Ng3ug3L5AGDyCQPzyKP2C4uxEjcu8oRt5eMHhnDd+P7tfwJCiB5H5kMX4hRUrFpF5Y500mMCKfPxw+0XxP6hvXCafIgOgrkvfcx7z3qe6myqGn/smGfLQdrKhRCnR+ZDF6KVGlfltbt2kRPlw7ZoCyGVZlx+Fix2f3zcbmrVQN57dgtF2TbCYjzTnB5bkctob0KIttbahN4H2K61rgRQSlmVUsO11hvbLzQhupb6qjwnyoeSvn5kBfkSUmlmwJDhmG3DKLKFEmYthoBw4Kfb63B873WpxoUQba21Cf1FoPF9w+omlgnRoxzbTl67axc54Zo/zqll+sZe+FWY8A90MEyls6+uP2FWmPX0jUCjinzHIdhxSCpyIUS7a21CV1rr+jZ0tNZupdSpdqgTolto/Ew54K3Kg5i+QRNi8yE8EOaO98xhvq8yoKEyB6nIhRAdr7VJeb9S6k48VTnAbcD+9glJiM7TuCo37j1MVqTiw/mhUFXIwI1++FUYCVSa8LgkgiOSefngAIpsdVhr3Ni0gbe9s6JJRS6E6GitTei3AguBh/D0dv8cuLm9ghKio9WPu37Nku1E5FRTEO1PdaTi4Ph+LLYpyCtgmY6EQJj789mQuoD3nt1CbWEZ1QY3WEwU9DY2HE8qciFER2vtwDIFwDXtHIsQnSbn34uZufEwEfmagmh/3r5jOFTmcdbOOpatc1JnHM6Raj+qrZHM3ZwAmzcwMtdOtcHN3hEBUokLITpdswldKfUQ8ILWuuQE688D/LXWq5paL0RXVl+VA8zceJjYfE1I0mhiZ8zgoulXw+JLWZblpNAegMMnFK0sWFQ8I/d4ZhC21ngqc6nEhRBdQUsVejrwkVKqFtgCFOIZy30okAJ8Bvy5PQMUor3UV+X+JgsR+RpXTBDlQ4v57ss34Ms30HVV5NcEUBI0AKf5SiLcBvoP6nXUMeLGRTJ8vCR0IUTnazaha60/AD5QSg0FJuN5Hr0C+Ddws9a6pv1DFOL0Na7G6/1UlSdACASFHOC9fT6U2xVmcy9cbo3TaMSi4rG4DfiF+zU56psQQnQFrW1D3wPsOZUPUEoZgTQgR2s9QykVAiwDYoEs4GqtdempHFuI1lq9fzW7S3YTHxJP8hd7GPZDKREFblwRPpQPLWbnEaDSSJldoY2RlEVcQ7Xdib+vqeHRs/pBYoQQoivqiGfJ78Iz1Wr9oNUPAJ9rrZ9USj3gfX9/B8QhzjCNq/L6ZL54+mIOPjuK2jwXflEWghKtfHIECishPDAA5QjF5hvP9qG+gC+Xp0QzSyZLEUJ0A+2a0JVSMcClwBPA3d7FlwPneF+/AXyFJHTRDhpX5Vfv6sWUHXkcfOlCavOq8Yvyp/z+/8d3678ib+8+3OZw9lqvxqJcGAOM0mtdCNHttHa2tcla6/UtLWvCc8BvgcBGyyK11rkAWutcpVTECT7zZrzPuvfvLxWSaNmx7eRHVeVLb6D24C7o5cCvl4OgC87iu/VfUZh1AJNvJHV6CNV2JwSY6DsytBPPQgghTk1rK/R/cPy47U0ta6CUmgEUaK03K6XOOdnAtNavAK8ApKam6hY2F+KoihwgPiSeSwZdAsBBZyQ5iVPw6+WkpDaXkoxCVF022hyO2f9KiuR5ciFEN9fSc+gTgUlAuFLq7kargvDMi96cycBMpdQleB51C1JK/RvIV0r18VbnfYCCUw9fCI8VmStIy08jNTKVxdMXH7c+xzyUCnNf/MzFVJTkgqMEbY7A5T8Mm8WArbePPE8uhOjWWqrQzYDVu13j2+YVwOzmdtRa/w74HYC3Qr9Xa329Uupp4EbgSe/fH5xK4EI0Vn+rvb4iB/j+bx+wM70S7bRTSRnuyvVsNQTg5yyhNjiKP778QmeFK4QQba6l59C/Br5WSr2utT7YRp/5JLBcKXUTcAiY00bHFWeQptrLUyNTmRP304/T3h1VVBt6Y9XZaEcGTl0OBFAbFEW/1CmdELUQQrSf1rah+yqlXsHz7HjDPlrr81qzs9b6Kzy92dFaFwPnn0yQQhzrRO3lpcuWk734RYw1Rdj6XEYdORgsWSi3lei4JO5+5MlOjlwIIdpHaxP6CuAl4DXA1X7hCNG0piryq3f1YtYBz4/jQVMcOSYHqysroNdcVLjG5tqCdpXjMvkTHhrOsMnndFL0QgjR/lqb0J1a6xdb3kyI9tFURT5lRx61B3fhl5BAloqlmmACfSqpNRygypUH2OjVdxA/+9tfOzd4IYToAK1N6B8ppW4D3gPs9QtPNAubEKeruWfKS5ctp2LVKvZWDWZPys/wS0igdH8ZvQ37uSLmjyw7OBK3y4++8QlSlQshzhitTeg3ev++r9EyDQxq23CE8GjumfKKVauo2L6D7BG/pMYQjOvQD/jZD+CoS2eVYxTV2kqfoQOZK+3lQogzSGsnZxnY3oGIM1tzFTngqcof/4iDfETtrl1kh8SggjVhKothkW+xca8Vm9OI1RpOeJ8oqcyFEGec1g796o9nLPb+WuubvdOpxmutV7VrdOKM0VRFfq5tFu89uwWAyu11KOdU6sy+kDiNErIxlWyi0ujAFTqFan2AyHipyoUQZ67W3nJfDGzGM2ocQDaenu+S0MVpqa/Mj63IAVY88D8KSgsIcpegamqoMZkpDPeM6++fvxZcRVj8zACExw6UqlwIcUZrbUIfrLWeq5S6FkBrXaOUUu0YlzhDNE7mYWoCdz2xjohSz6NoIeVurLZsdMVHlPu4qQ0IYkigJ6EX5uYSbiln7i9vgtQFnXkKQgjRJbQ2odcppSx4OsKhlBpMo97uQpyME81TPvflDaRm5WLFgrmuEHOdnV412ymMrMNVYyTSvxRyywEI961iWGywJHMhhPBqbUJ/BFgD9FNKLcUz8cr89gpK9Gyr968mvXAnCUcu4Pyi8zDpQJ747CuG2J1YsWCyrcekM3ADFdZaqmsUUcEwd7yh0VECIKnZ6QSEEOKM0tpe7p8qpbYAEwAF3KW1LmrXyESPcmxVbnRGk7x3VEM17pnvB3wddqrZR6XFl/BQCxTvJdwazLDZd8C06Z14BkII0bW1tpf7LOALrfXH3ve9lFJXaK3fb8/gRM9RX5UbndFAH6pLRhJSZ8PPWUJf/QmH3HWAZ1xhu0kRERvP3P7pcDAdZjwHqZLMhRCiOa2+5a61fq/+jda6TCn1CPB+u0QlepT6ucqT865gQPbZRDpsBNRU4PAJxd9cTkHMICqzDngqclshfsAwlQ556TBgirSTCyFEK7Q2oRuaWNbafcUZrv5We78jo4hwGwh3VWOry8ThOEKVv5HarArCYwd6KvK8dIhK8u6ZJO3kQgjRSq1NymlKqb8Ci/D0dL8Dz3PpQhxn+7ocMjflA1BYU0hizgQmVU/CYfbD6jrC6PSFfBcbht2sCDRBoKlRRR6VBAs+7uQzEEKI7qe1Cf0O4A/AMu/7T4CH2iUi0e1lbsqnKNuGO9hEdlUB/ao1vnUah3Mjte5MvhvclwocRPhWMXd8QKM9pSIXQohT1WJCV0oZgQ+01tM6IB7RAxTWFFLiX0xJ6WuM25HPwAKoCwlh7xAr5dUGggPBr66KYbEBUo0LIUQbaTGha61dSqlqpVSw1rq8I4IS3U/j2+zVeW4qLdWMyyjD1xHID/GhWMwuym0QHgxzx4M8Ry6EEG2rtbfca4F0pdSnQFX9Qq31ne0Sleh2Nr63AbvNgrkulwDtIionjcSCWjYNCaHWBwLNtYSbA+R5ciGEaCetTegfe/+IM1Dj6vtEam0WrJWHCSx6lWofEzbfAL4fGk2l2UxEIJ628qTZ8jy5EEK0k9aOFPeGdyz3/lrr3e0ck+hi6ju5hcVYAXAWFuIsLgbA4a7D4XJitTsx124m7lwL2/YYqbZbiIxP8jxTPvkcqcqFEKKdtXakuMuAZwAzMFAplQI8prWe2Y6xiU7UuCqvT+az7hkNwKYr5uJzYA954f2pVYdxY6fWJ4DSXgFkHAqmpA4i+4bL3ORCCNGBWnvL/VFgHPAVgNZ6q1JqYDvFJLqA+qq8l28NVlsxoRn7SZv9e4prignLrmJfmC+vXVNGqbGOAQ4TV2zww2G3QJ8kwvsgc5MLIUQHa21Cd2qty4+ZAl23QzyiCwmLsTJ662vU7tqFX0IC6bYi7K4aKsN8SR8UyqTNCtwRhCgfSuqMUpULIUQnam1Cz1BKXQcYlVJDgTuBb9svLNGZvv/bBxzZE0ig4xAl6VsoiPbn7XlGfsx1MtBu5I8l/tQcMFFeBuHBPtAnCaQqF0KITnUyI8X9HrAD/wH+B/ypvYISnWvvjiowBuJXmcaBCPhuiJUduRWMP2Ah4YgvGSZ/yqu9z5T/fLZMniKEEF1AswldKeUH3AoMAdKBiVprZ0cEJjpG485v9b3Xy3UwfrX7ee6KLQRVh/F4dg035tax7bAPRXZ/iG/UTi6PoQkhRJfQUoX+BuAA1gEXA8OAX7dzTKIDNX4kzVlcjLu6Gh+farIDN+Oy9+H8PQXsKTBj9LVK73UhhOjCWkroiVrrJACl1D+BTe0fkugI29flsOPjDEpKNUHuEkZvXUPljnRywjV/vMZNTJ2B5w9a2FNgpshuJTJWeq8LIURX1lJCd9S/0Fo7j+nlLrqxzE35lJRqrLZsos15AGSFm/i+n5GLNgQQ4DKS7jZQLb3XhRCiW2gpoScrpSq8rxVg8b5XgNZaB7VrdKJdlC5bTu0uJwFVNsLKX2PxHcMBI1vyFJdvsNKrwpeSoAH4BvsSEeQrVbkQQnQDzSZ0rbWxowIR7a++A1ztLicVOhiTuZoNMWb6fZCPcjvoRxC9Kn2ICoa7Xnqhs8MVQghxElr72JropkqXLadi1SoAfvSbToUhhIAqGyZzNV8n/ciQQ+H0Lqgj3K+OWmXBJwCGjR3dyVELIYQ4We2W0JVS/YAlQBTgBl7RWv9dKRUCLANigSzgaq11aXvFcaZqXI273Wdh8PenwhCCsXYTlXXfUGZ0MzBTEVDpQ7hfFclDXQx/cE1nhy2EEOIUtWeF7gTu0VpvUUoFApu986nPBz7XWj+plHoAeAC4vx3jOOOULlvOj585G6pxu9lAYQRACbpoFzhN1Po7iK+ro9bPSEhvI7ahMs+OEEJ0Z+2W0LXWuUCu93WlUmonEA1cDpzj3ewNPBO+SEJvI6XLlpP3yCO4U+4iKBBCyl/jywQX6cnxFFXZmVZcjcnqZEjcHpLtMVKVCyFED9EhbehKqVhgFLARiPQme7TWuUqpiBPsczNwM0D//v07Isxub8nKD3H8twK/lLso7d0fW0gZ/zjXxITCQaR+3ovqOhcRtdmE+9WRbI/BNnRWZ4cshBCijbR7QldKWYF3gF9rrSta+yy71voV4BWA1NRUmdmtFcq/LsVsiqLWLw9bSBlZYXsIqjYTnVGC0VbBAIubAEstw2KtDH/w484OVwghRBtq14SulPLBk8yXaq3f9S7OV0r18VbnfYCC9oyhp6rv9FZYU0hJTTEAQbWhWG3ZDEop4pDdRs2uClLrfKmpVQRY3Fya4iAyMACSZndy9EIIIdpae/ZyV8A/gZ1a6782WvUhcCPwpPfvD9orhp4sc1M+hQdKMNoOE6pdGJQRc10lvvZ0dmbuo7LGSD8/J/7UEhhsZdjsO4icJhOpCCFET9WeFfpk4GdAulJqq3fZg3gS+XKl1E3AIWBOO8bQ42xfl8P6rzOoyfMM25ryw18pirGSEJLA+vIyygNrqK4xEmhxMX5IFWFWXyInzZZZ0YQQoodrz17u3+AZIrYp57fX5/Zk9Y+juVQw/vZs+uZuJrdPAJ9cGk9M2X6q9wRQU2skItjIsNl3MFwqciGEOGMYOjsA0Xr7VizGWVWJyZ5N/6J/khhZy87oSYz8voBte4xU1ZroZVXM/flsRkoyF0KIM4oM/drFff+3D9i7owoAp/kKKgOiKeldSPUoiKneT+89AdTUKgKDrUTFJnkmUpHb60IIccaRhN5Frchcwer9q5mybTIOUxQ+zjxq1UHsNd8RVldJUKGFjcpCVa2REKubuT+fDakLOjtsIYQQnUQSehdUumw5+p21TLJMwOHjSebfXPoOAz53EljhQ5BPFbXKQsCAFAJAqnIhhBCS0LuS+qr8miXbKQ2cRrVjMybHRkz+RqZ/bqCg3IjFz0XyUBe2oRcwfs49nR2yEEKILkISeidrPL1pUMkuZjpriMh3sTMhB7e7ggD/GnCDy16Dxc+Prf1m8vMHf9XJUQshhOhqJKF3sn0rFmPce5hdA0IoDIjBbQwkuze4dCU+PsEk9c/D32wEYL1lHJMmXdbJEQshhOiKJKF3kvrK3Lj3IFnhsKevH/6lbgwGX0yqFh+C2B04kvV9bmHZLRMBGN7JMQshhOi6JKF3kn0rFpNZG0JBwljcRk1gaSUYwwkNGceYPq+z3nIuRf4TuTwlurNDFUII0Q1IQu9AjdvLjXsPUpAQgYtKjMYgtLkPZYYhZEXFc8OD3zAc79yxQgghRCtIQu9Aq9//lGK3wm0AEsbiohI/czC/uvMs5m5OYOOBEv48bUBnhymEEKIbkoTe3tIWU/rmv6jYYaM4JAkHNtw+gYDGhyAMcVOYuzmBHbkVjB8YwnXj+3d2xEIIIbohSejt7MfVK9l0yAflF4KDCpQpmPvOLfKsTJrdkMwT+wRJe7kQQohTJgm9nWxfl8OOjzPIywrDYS7H4BsMJl9qrIOYW3e2Z6PNNCTz+p7sQgghxKmQhN7W0hbz4+qVfLE3HO30QetyDCoYY/h5VPkOYJuh7qg5ZaUyF0II0RYkobeh7etyyPzQQE5OKC5XBT5Y8XFUkjbSxuGYPHKzo6QaF0II0S4koZ+utMWQvpIV2Ni/aQqmigJwVeBDECEOK+vNk/i8dgLjXSH07oNU40IIIdqFJPTTlb6S0rU7Ccq24BuajUuXE1xViQ9FLLniMnq7zuLPKdHSe10IIUS7koR+kupnRAvLGkpoVl9U6Uh8a8IwhGhcuhKj6k10LUz4xS3cOPfqzg5XCCHEGUIS+klavX81u0t2M3r7OZhqQ7FXfoFbV4AKxmUOoTgsmYjfXE5vqciFEEJ0IEnordBQle+KoF/OROJtfXGWf4N22VHuIswOA9XRCfx20e86O1QhhBBnKEnordBQle+eiMnZl7rK9bh0OWa3gdrgIHb1ncqkS2VaUyGEEJ1HEvoJrMhcwetb38NVcYSw4jguLZyPqi7DUbsel7sYiwvmzr2B3tJOLoQQoguQhH4Cq/evJv7bHUxLryM35hrqzH09yVyXUh7Sn6DUKZLMhRBCdBmS0L3q28kBqMxjZ1UOd2RayLeEUm3fAA4jUEJEeAS/WfRCp8YqhBBCHEsSuld9O/nVu3rRNyOGKYGXUxz4LU4qMJj88PHzIazfcIZNPqezQxVCCCGOIwkdT3Welp9GnCGShE2lZAaH4XJsxk0lvn6RRI+8hbhxkQyfKqO8CSGE6JokoQM5/17MI9858fEfRGZwLQ5sGIxmzH1iOeviixg5bXRnhyiEEEI064xN6PVt5gUVduZsKabcty/VfrU4tA1fv3DO/fnDUpELIYToNs7YhJ7z78XM3HgY3GZKfHtR6WfGYDJgMoZy1s9mSTIXQgjRrZwxCX1F5gpy/r2YyG02yoxmgu2aMlMEdksw1UY3ZlMvfMP/j7AYq9xiF0II0e0YOjuAjrJ6/2oGbDxMtdtMrdGHWl+oCjZQ5xeEwRRBYNhwwmKsxI2L7OxQhRBCiJPWKRW6Umo68HfACLymtX6yPT9vw5N/Yuz3OZSYI7D5mYm0VhHeJwVb6I0UZdsIi7Ey6x6pyoUQQnRfHV6hK6WMwCLgYiARuFYpldien5m5NY06ZaTOB0KM1YSEGDniPq8hmUtVLoQQorvrjAp9HLBXa70fQCn1NnA5sKOtP+j5eTfhdDlxazCYwimLmUSUslATlUSdVOZCCCF6kM5oQ48GDjd6n+1ddhSl1M1KqTSlVFphYeFpfaBBBYMlhmDtAwHhAFKZCyGE6FE6o0JXTSzTxy3Q+hXgFYDU1NTj1rfG7Uv/eSq7CSGEEN1OZ1To2UC/Ru9jgCOdEIcQQgjRY3RGQv8eGKqUGqiUMgPXAB92QhxCCCFEj9Hht9y11k6l1O3A//A8tvYvrfX2jo5DCCGE6Ek65Tl0rfVqYHVnfLYQQgjRE50xI8UJIYQQPZkkdCGEEKIHkIQuhBBC9ACS0IUQQogeQGl9SmO2dCilVCFw8BR3DwOK2jCcnkiuUfPk+rRMrlHzOuv6DNBah3fC54pO0C0S+ulQSqVprVM7O46uTK5R8+T6tEyuUfPk+oiOILfchRBCiB5AEroQQgjRA5wJCf2Vzg6gG5Br1Dy5Pi2Ta9Q8uT6i3fX4NnQhhBDiTHAmVOhCCCFEjycJXQghhOgBunxCV0pNV0rtVkrtVUo90Gh5slJqg1IqXSn1kVIqqIl9Y5VSNUqpH5RSO5VSm5RSN3bsGbQvpdS/lFIFSqmMY5a39vpopdTjjZaFKaUcSqnnOyL+jqCU6qeU+tL7M7BdKXVXo3XLlFJbvX+ylFJbm9g/9tjr29M08z17VCmV0+gaXXKC/Ycrpb5QSmUqpfYopf6glFItfOaDbX0e7amZ79rjSqkfvdfnE6VU3yb27fE/Q6IL0Fp32T94plfdBwwCzMA2ING77nvgbO/r/wMeb2L/WCCj0ftBwFZgQWefWxteo7OA0Y3P8ySvzz7gh0bLfum9Rs+fRAymzr4OLcTXBxjtfR0IZNb/HB2z3bPAwy39HPW0Py18zx4F7m1hf4t3/wu97/2B/wK/amE/W2ef+0lepxN914Iavb4TeOlM+xmSP13jT1ev0McBe7XW+7XWdcDbwOXedfHAWu/rT4GrWjqY1no/cDeeLx1KqQDvb93fe6v4y73LjUqpZ7zV7Y9KqTva+LzajNZ6LVDSxKrWXp8aYKdSqn7Qi7nA8vqVSqnLlFIbvdfnM6VUpHf5o0qpV5RSnwBL2uJc2ovWOldrvcX7uhLYCUQ33sZbTV4NvNXcsZRS8xvfvVBKrVJKneN9bVNKPaGU2qaU+q7+WnUDzX3PWuM6YL3W+hMArXU1cDvwAIBSyqqUWtzo+3SVUupJwOKtape27em0jxN917TWFY3eBgDN9jT2VuvrlFJbvH8meZefo5T6Sim1Uim1Sym1tKW7HEI01tUTejRwuNH7bH76jzgDmOl9PQfo18pjbgESvK9/D3yhtR4LnAs8rZQKAG4GBgKjtNYjgW7xH84xTub6vA1co5SKAVzAkUbrvgEmaK1Hebf7baN1Y4DLtdbXtVnU7UwpFQuMAjYes2oqkK+13nMahw8AvtNaJ+P5ZeoXp3GsjtTc9wzgdm8i/pdSqncT+w8HNjdeoLXeB1i9TT1/AMq11kne79MXWusHgBqtdYrWel6bnk0n8P4idxiYBzzcwuYFwAVa69F4foFe2GjdKODXQCKeOyaT2z5a0VN19YTe1G+n9b/9/h/wK6XUZjy3UetO4ZgXAg94202/AvyA/sA0PLfNnABa66Yq4K7uZK7PGuAC4Fpg2THrYoD/KaXSgfvw/Odd70OtdU3bhdy+lFJW4B3g18dUVeA592ar81aoA1Z5X2/Gc5u1O2jue/YiMBhIAXLxNEs0tf+JqlKN5/u0qGGB1qWnGmhXpbX+vda6H55f/m9vYXMf4FXvd2oFnuRdb5PWOltr7cbT9BXbDuGKHsrU2QG0IJujK8sYvNWj1noXnoSMUioOuLSVxxyF55YreP4jukprvbvxBt7bXN36Af2TuT5a6zpv4r8HT8K+rNHqfwB/1Vp/6L21/GijdVVtG3X7UUr54EnmS7XW7x6zzgRcieeOQ0ucHP2LsF+j1w6tdf3PjYuu//2q19z3LL9+oVLqVX76haWx7Xjal2m07SA8beSVPeH7dBL+A3wMPNLMNr8B8oFkPD9LtY3W2Ru97k4/Q6IL6OoV+vfAUKXUQKWUGbgG+BBAKRXh/dsAPAS81NLBvLdbn8GTpAD+B9xR306llBrlXf4JcKv3P3qUUiFtdUId5RSuz7PA/Vrr4mOWBwM53tfd8gkB77/vP4GdWuu/NrHJNGCX1jq7FYfLAlKUUgalVD887c/dXXPfsz6NtpuFpynnWEuBKUqpad59LHhuI//Fu/4TGlWtjW7bO7y/aHVrSqmhjd7OBHa1sEswkOutwn+Gp1OiEKetSyd07y3v2/Ek3p3Acq31du/qa5VSmXi+PEeAxSc4zGBvh66deDp7/UNrXb/t43huf/3ofaSk/vGt14BD3uXb8HT66ZKUUm8BG4B4pVS2Uuom76rWXh8AtNbbtdZvNLHqUWCFUmod3Xd6zMl4/uM8TzX9+NU1NH+73cRPldN64ACQjueXwy3tEG+HauF79pf6zmx4+pn8pon9a/B0ontIKbUbz7X5HqjvPPgnoLdSKsP7fTrXu/wVPN+xbtFHpZnv2pPec/sRz12xu5rYvfHP0AvAjUqp74A4utGdLtG1ydCvQrTA+/TDPK311Z0di+ie5GdIdARpnxGiGUqpx/BUn/M7ORTRTcnPkOgoUqELIYQQPUCXbkMXQgghROtIQhdCCCF6AEnoQgghRA8gCV2IYyilXN5H27Z7x2W/2/s8f3P7xCqluuzjjUKInk8SuhDHqx9jfDieIXEvofmRv8AzRKckdCFEp5Fe7kIcQyll01pbG70fhGeglDBgAPAmnolYAG7XWn/rHSRkGJ5BZ97AM1Lak8A5gC+wSGv9coedhBDijCMJXYhjHJvQvctK8czSVwm4tda13iE/39Jap3rHub9Xaz3Du/3NQITW+k9KKV88I8zN0Vof6MhzEUKcOWRgGSFap35GMh/geaVUCp7JM+JOsP2FwEil1Gzv+2BgKJ4KXggh2pwkdCFa4L3l7sIzj/UjnHimrKN2A+7QWv+vQ4IUQpzxpFOcEM1QSoXjmanuee/UqCeaKasSz7zz9f4H/LJ+NjGlVJxSKgAhhGgnUqELcTyLUmorntvrTjyd4OqnXX0BeEcpNQf4kp9myvoRcHpnE3sd+Duenu9bvNO3FgJXdEz4QogzkXSKE0IIIXoAueUuhBBC9ACS0IUQQogeQBK6EEII0QNIQhdCCCF6AEnoQgghRA8gCV0IIYToASShCyGEED3A/weYf9qQaeoeMgAAAABJRU5ErkJggg==", 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", 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", 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", 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", 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", + "image/png": 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", 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", + "image/png": 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", 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", + "image/png": 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", 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", 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VV165x7XZRYsWLX/66afbXXvttV1nz5695fbbb8+vybGUQEVEUqzidc7Deu5Lzx2t6dg2K8WRZZ6f/exnm2655ZaupaWlduqpp37evHlznzRpUpcJEyZ81a5du7KVK1c2b9GihX/77be2//77l1500UVftW3btmz69On71fRYSqAiIilUcXRteXftVCXPRGRlZfnw4cO37L333ruaNWvGKaecsmXZsmVZQ4YMORigVatWZTNmzFj58ccf73X11Vd3a9KkCc2aNfP77rvvi5oeSwlURCQe1ZUXq6HIIKFeJaXl3bUdW2TBcoIfVWJJyK5du1i0aFGbJ5988rPIsuuvv35DZGRuRL9+/Xaceuqpy/fcQ/w0lZ+ISDwi5cVqqaC4hGX5m1lZtI3iklLaZjULkmfF7tpOOZBzWq2P15gsXLgw68ADD8w5/PDDt+Tk5OxI9vHUAhURiVekvFiCKu2ulTpxyCGHlKxZs6b2f+XESQlURCTJGtFkCGVlZWXWpEmTzJ3iLkpZWZkBZZWtVwIVEUmiRtbqXFpYWNi3Q4cOmzM9iZaVlVlhYWE7YGll2yiBiogkQSNqdZYrLS397/Xr109Zv359fzJ/jE0ZsLS0tPS/K9tACVREpA7Fuqezgbc6yx1yyCEbgNGpjqO+KIGKiNSBxpw4GyslUBGRWmpk1zkllJIEamaXA/8NOLAEOA9oBcwEegCrgNPdvUalZURE6lNjvM4p36n3BGpmXYFLgb7u/o2ZPQGcCfQF5rj7rWY2EZgIXFXf8YmIVEfdtQKp68JtBrQ0s28JWp7rgKuBo8L104G5KIGKSBopKC7h0r++rcQpQAoSqLuvNbPbgdXAN8Cr7v6qmXV09/xwm3wz2z/W681sAjABoHt3fWhFJPkenb+a3PzNFJeUMn/nV0qcAqSmC3cf4GSgJ7AJeNLMzon39e4+GZgMkJeXl9E36opI+osMEHq8RTBv7e9H6TqnBFLRhTsSWOnuhQBm9gwwHCgws85h67MzsKGqnYiI1HWFlGgVq6UMbrGGFp1z6afkKaFUzBSxGhhqZq3MzIBjgI+A54Fzw23OBZ5LQWwikknqqEJKRQXFJXtUS2nRNVfVUWQ3qbgGOt/MngIWAaXA+wRdsm2AJ8zsFwRJdmx9xyYiGaiWFVIqir6nU7elSFVSMgrX3W8EbqyweAdBa1REpF5FbksBdE+nxE0zEYlIo1ZxFiGNsJV4KYGKSKOkWYSktpRARaRR0SxCUleUQEWk0dCk71KXlEBFpMFTd60kgxKoiDRoanVKsiiBikiDpXs6JZmUQEWkwVGXrdSHuBNoOAl8F4IKKqvcvSxpUYmIJEAjbKU+VZlAzawd8CvgLKAFUAhkAR3N7B3gPnd/LelRiohUQYlTUqG6FuhTwN+Aw919U/QKMzsE+JmZ9XL3B5MUn4hIpSIVU65ZoUFCUv+qTKDufmwV6xYCC+s8IhHJPEksKxZLJHEesOMziv1AJU5JibiugYZlx8YBvdz9JjPrDnRy93eTGp2IZIZIWbFOOUk/VKTUGMCXWd/Deo9h5thhST+uSEXxDiK6DygDfgTcBBQDTwNDkhSXiGSaOi4rVlH5dc51Glkr6SHeBHqYuw82s/cB3P1rM2uRxLhERAANEJL0FW8C/dbMmgIOYGYdCFqkIiJJocQp6S7eBHoPMAvY38xuAU4DrktaVCLSaClxSqaIK4G6+wwzWwgcAxjwU3f/KKmRiUijo3lrJZPEOwr3bmCmu9+b5HhEpJHSvLWSaeLtwl0EXGdmfQi6cme6+4LkhSUijUGkuxbQvLWScZrEs5G7T3f3nwCHAv8B/mBmnyQ1MhFp8J5bvJbl+VuAoMtWyVMySU2rsXwfOBjoASyv82hEpFGItDyX52+hb+dsZl6giRAk88R7DfQPwCnAZ8ATwM0V58YVEalOZSNsRTJRvC3QlcAwdy9KZjAi0jDp1hRpiKorZ3awu38MvAt0D+fALefui5IZnIhkPt2aIg1VdS3Q3wATgD/FWOcEc+OKSKaqqyoqMSaSr9jq1AAhaWiqK2c2IXz4Y3cviV5nZllJi0pE6kddVVHplAM5pwHqrpXGI95roG8Bg+NYJiKZpg6rqKi7VhqT6q6BdgK6Ai3NbBDBNH4A2UCrJMcmIhlEMwlJY1NdC/R4YDzQDbgjankxcE2SYhKRDKGZhKQxq+4a6HRgupmd6u5P11NMIpIBKnbXqstWGpt4q7E8bWajgH5AVtTym5IVmIikL3XXisQ/E9H9BNc8jwamENQDfTfRg5rZ3uF++hPcDvNzYAUwk2CawFXA6e7+daLHEJG6p1tTRL4T7yjc4e4+wMw+dPf/Z2Z/Ap6pxXHvBl5x99PMrAVBcr4GmOPut5rZRGAicFUtjiEidUS3pojsKd4E+k34e7uZdQE2Aj0TOaCZZQNHEAxOwt13AjvN7GTgqHCz6cBclEBFUkqJU6Ry8SbQF8Nu1z8S1AZ1gi7YRPQCCoGpZpYLLAR+DXR093wAd883s/1jvdjMJhDMjkT37voSiySDEqdI9eIdRHRz+PBpM3sRyHL3zbU45mDgEnefb2Z3E3TXxsXdJwOTAfLy8jzBGESkEpoMQSQ+1U2kcEoV63D3RK6DrgHWuPv88PlTBAm0wMw6h63PzsCGBPYtIgnSACGRmqmuBXpSFeucBAYSuft6M/vSzA5y9xXAMQTFuZcD5wK3hr+fq+m+RaTmCopLuPSvb6u7VqSGqptI4bwkHfcSYEY4Avdz4DygCfCEmf0CWA2MTdKxRSRUUFzCyqJtzN/5lRKnSA3Fex/oDbGWJzqRgrsvBvJirDomkf2JNFq1KEdWUFxCy43LgQPVXSuSgCZxbrct6mcX8GOCCQ9EJJUi5chqKNLyXO4HYjljlTxFEhDvKNzdCmqb2e3A80mJSERqpgblyMoHCq3TQCGR2or3PtCKWhHczykiaS5WxRRd7xSpvXivgS4hGHUL0BToAGgieZE0p4opIskTbwv0xKjHpUCBu5cmIR4RqQO6p1Mk+eK9BvqFme0DHBC+pmM4kcKipEYnIjWmmYRE6ke8Xbg3E0z+/hnfdeU68KPkhCUiNRHrOqdanSLJFW8X7unA98LKKSKSRgqKS3SdUyQF4k2gS4G90fy0Imnj0fmryc3fTHFJMBxBLU6R+hVvAv1f4H0zWwrsiCx099FJiUpEKhU9QOjxFqW0zWrG70cpeYrUt3gT6HTgD8ASoCx54YhIZWLV6Oy5ozUd22bRT8lTpN7Fm0CL3P2epEYiIpWqdGTt1KwURybSeMWbQBea2f8STN8X3YWr21hEkiw6eeo6p0j6iDeBDgp/D41apttYRJJIkyGIpLd4J1I4OtmBiDRYCZQcKyguoVfRNi4H2mY3o32bvei4PCsoOx9t/ZJgMnkRqXcpqQcq0qhESo7FkegKikso2rqj/NaUnu2DQUKV6pQDOafVVaQiUgPxduFui3qcRTA37kd1H45IAxVHybFYA4WGqstWJG2pHqhIiulap0hmUj1QkRRQjU6RzKd6oCL1KNZkCEqcIplJ9UBF6onKjIk0LPEm0M7AMncvBjCzNmbWz93nJy80kYYhMrL2mhWaDEGkIYk3gf4FGBz1fHuMZSJSwaPzV9OrKBjErlanSMMSbwI1d49cA8Xdy8ws0QFIIg3e7hVTgvs5Z14wLNVhiUgdijcJfm5mlxK0OgEuAj5PTkgimauqiiki0rDEm0AvBO4BriMYjTsHmJCsoEQyTazEqYopIg1bvBMpbADOTHIsIhmnysQpIg1alQnUzK4D7nP3rypZ/yOglbu/mIzgRNKVEqeIVNcCXQK8YGYlwCKgkGAu3N7AQGA28PtkBiiSdDWslhKzUkqLsFJKxWopoIopIg1UlQnU3Z8DnjOz3sAIgvtBtwCPABPc/ZvkhyiSZHFWS6lxpZQIVUwRaZDivQb6CfBJkmMRSZ0qqqWUd9eu2727VpVSRBo33cspUgld5xSRqqQsgZpZU2ABsNbdTzSzfYGZQA9gFXC6u3+dqvhEnlu8luX5W5Q4RSSmeKuxjHD3N6tbVkO/JijKnR0+nwjMcfdbzWxi+PyqWuxfpMaiy4wtz99C387ZmkFIRGJqEud2/xfnsriYWTdgFDAlavHJwPTw8XTgp4nuXyRRkVYnQN/O2Zw8sGuKIxKRdFXdfaDDgOFABzP7TdSqbIK6oIm6C/gt0DZqWUd3zwdw93wz27+SmCYQzoLUvbu61KT2IqNrb/rr22p1ikjcqmuBtgDaECTatlE/W4CExuWb2YnABndfmMjr3X2yu+e5e16HDh0S2YUIEHTXnvHXt1lZtK381hS1OkUkXtXdB/o68LqZTXP3L+romCOA0Wb2E4JJGbLN7BGgwMw6h63PzsCGOjqeSEyR7tq2WcFkCGp1ikhNxDsKdy8zm0wwQrb8Ne7+o5oe0N2vBq4GMLOjgCvc/Rwz+yNwLnBr+Pu5mu5bJB6RgUKR7tp+LdqlOiQRyUDxJtAngfsJBv3sSlIstwJPmNkvgNXA2CQdRxqxR+ev5ppZS4Dv7uuMOf2eiEg14k2gpe7+l+o3qxl3nwvMDR9vBI6p62OIwJ6TIvx+TM5393UqgYpIAuJNoC+Y2UXALGBHZGFlVVpE0oVmExKRZIk3gZ4b/r4yapkDveo2HJG6E6u7VolTROpKvJPJ90x2ICJ1YsFUCt56hKKtO+hVUsrjLcKqKSo3JiJ1LK6ZiMyslZldF47Excx6h/dziqSVgrceoeXG5RSXlNI2q1l8JcdUbkxEEhBvF+5UYCHBrEQAawhG5r6YjKBEaiJ6/trLi7YBB/L5qCfUXSsiSRVvAv2eu59hZmcBuPs3ZmZJjEukWrEGCEUmRVCtThFJtngT6E4za0kwcAgz+x5Ro3FF6lOVI2unalIEEakf8SbQG4FXgAPMbAbBdHzjkxWUSGU0slZE0kW8o3D/aWaLgKGAAb9296KkRiYSpcqJEEREUiDegtpjgH+5+0vh873N7Kfu/mwyg5PGLXpwkCZCEJF0E3cXrrvPijxx901mdiPwbFKikkarsqSpxCki6SbeBBrrftF4XysSt+gqKUqaIpLO4k2CC8zsDuBegpG4lxDcFypSJyqWGFNtThFJd3HNRESQMHcCM4EngG+AXyUrKGlcIiNr56/8ir6ds4MSYyIiaa7aFqiZNQWec/eR9RCPNCIaWSsimazaBOruu8xsu5m1c/fN9RGUNHy6n1NEMl2810BLgCVm9k9gW2Shu1+alKgkfSyYCkueqrPdFRSX1KxSSk2psoqI1JN4E+hL4Y80NkueqpOkFEmcxSWlAOVz1lZbKaWmVFlFROpJvDMRTQ/nwu3u7iuSHJOkm045cF7t/n669K9vs/yrLfTtmq3uWhFpEOKdiegk4HagBdDTzAYCN7n76CTGJhkuelIE3Z4iIg1NvLexTAIOBTYBuPtioGdSIpIGIfrWFEC3p4hIgxPvNdBSd99coQSoJyEeyXC6NUVEGot4E+hSMzsbaGpmvYFLgbeSF5ZkmiprdIqINEDxJtBLgGsJimg/CvwD+F2ygpLMoGopItKYVZlAzSwLuBD4PrAEGObupfURmKS3ihMhKHGKSGNTXQt0OvAt8G/gx8APgMuSHJOkuejkqWucItJYVZdA+7p7DoCZPQi8m/yQJF1pgJCIyHeqS6DfRh64e2mFUbjSiGjuWhGR3VWXQHPNbEv42ICW4XMD3N2zkxqdpIWC4hJ12YqIVFBlAnX3pvUViKSfR+evJjd/c/n8tUqeIiLfifc2FmlEoq91Pt6ilLZZzfj9KCVPEZFo9Z5AzewA4G9AJ6AMmOzud5vZvsBMoAewCjjd3b+u7/gyXh2UH8vN30zvnbtold2U3mVraNE5l35KniIiu4l3Lty6VAr8j7v/ABgK/MrM+gITgTnu3huYEz6XmoqUH6uhguISluVvZln+Zrbv3EWrFk3p17kdLbrmqjyYiEgM9d4Cdfd8ID98XGxmHwFdgZOBo8LNpgNzgavqO74GoQblx8q7a9d9N5MQwMkDu6rVKSJShZReAzWzHsAgYD7QMUyuuHu+me2fytgaA92aIiKSuJQlUDNrAzwNXObuW+K9x9TMJgATALp313/2idCECCIitZeSBGpmzQmS5wx3fyZcXGBmncPWZ2dgQ6zXuvtkYDJAXl6eSqrVgCqmiIjUnVSMwjXgQeAjd78jatXzwLnAreHv5+o7toZM3bUiInUrFS3QEcDPgCVmtjhcdg1B4nzCzH4BrAbGpiC2BkfdtSIiyZGKUbhvEEwFGMsx9RlLQ6buWhGR5NJMRA1Q9Ny1SpwiIsmhBNqAaO5aEZH6owTaAGjuWhGR+qcEmuEqjq7tuaM1HdtmaRYhEZEkUwLNQJEWJ7Dn6NqpWakMTUSk0VACrS91UCUFggFCvYq2cTnQNqsZZEP7NnvRcXkWLCeYSL5TTq2PIyIiVVMCrS+RKikJJreC4hKKtu4oHyDUs33QVbuHTjmqniIiUg+UQOtTDaqkRMSqlnLywK4M1TVOEZGUUgJNY5p+T0QkfSmBpiFNvycikv6UQNPQc4vXsjx/i1qdIiJpTAk0jURansvzt9C3czYzLxiW6pBERKQSSqBpoLKJ30VEJH0pgaaQKqaIiGQuJdAUUOIUEcl8SqD1TLemiIg0DEqg9Si6TqduTRERyWxKoEkW6a69YaPqdIqINCRKoEkU3V1LNqrTKSLSgCiBJkGsmYT6LW8HoDqdIiINhBJobVUoU7ZbubHsZt+VGlOZMRGRBkUJtLbCMmUFrXtXXW5MZcZERBoUJdBaKiguoci7M2rdbwCVGxMRaSyUQBMUuc55edE2QPd0iog0NkqgCYgeXRu5zqmJ30VEGhcl0BqoanStiIg0Lkqgcap0Cr7lKQ5MRERSQgk0DtHJU7MIiYgIKIFWKVaXrZKniIiAEmilVDVFRESqogRagVqdIiISDyXQKGp1iohIvNIugZrZCcDdQFNgirvfmszjRVqcgFqdIiISt7RKoGbWFLgXOBZYA7xnZs+7e1JuFqnY4lSrU0RE4pVWCRQ4FPjU3T8HMLPHgZNJwt2W79x3Pr3WL+HxFuHE7y3Cid+X1/BoqrIiItIoNUl1ABV0Bb6Mer4mXFbOzCaY2QIzW1BYWFirg7XNarZn1ZSaUpUVEZFGKd1aoBZjme/2xH0yMBkgLy/PY2wfl6EXPZDoS0VERNKuBboGOCDqeTdgXYpiERERqVS6JdD3gN5m1tPMWgBnAs+nOCYREZE9pFUXrruXmtnFwD8IbmN5yN2XpTgsERGRPaRVAgVw978Df091HCIiIlVJty5cERGRjKAEKiIikgAlUBERkQQogYqIiCTA3BOeiyDlzKwQ+KIWu2gPFNVROA2Rzk/VdH6qp3NUtVSdnwPdvUMKjtugZHQCrS0zW+DueamOI13p/FRN56d6OkdV0/nJbOrCFRERSYASqIiISAIaewKdnOoA0pzOT9V0fqqnc1Q1nZ8M1qivgYqIiCSqsbdARUREEqIEKiIikoCMTaBmdoKZrTCzT81sYtTyXDN728yWmNkLZpYd47U9zOwbM3vfzD4ys3fN7Nz6fQfJZ2YPmdkGM1taYXm858jN7OaoZe3N7Fsz+3N9xF8fzOwAM3st/BwsM7NfR62baWaLw59VZrY4xut7VDy/DUkV37NJZrY26vz8pJLX9zOzf5nZf8zsEzO73sysmmNeU9fvI9mq+K7dbGYfhufoVTPrEuO1Dfoz1KC5e8b9EJQ6+wzoBbQAPgD6huveA44MH/8cuDnG63sAS6Oe9wIWA+el+r3V8Xk6Ahgc/V5reI4+A96PWvbL8Dz9uQYxNEv1eagmvs7A4PBxW+A/kc9She3+BNxQ3WepIf1U8z2bBFxRzetbhq8/LnzeCngZ+FU1r9ua6veewLmq7LuWHfX4UuD+xvQZaug/mdoCPRT41N0/d/edwOPAyeG6g4B54eN/AqdWtzN3/xz4DcEHHDNrHf5F+V7YSj05XN7UzG4PW24fmtkldfy+6pS7zwO+irEq3nP0DfCRmUVu9D4DeCKy0sxOMrP54TmabWYdw+WTzGyymb0K/K0u3kuyuHu+uy8KHxcDHwFdo7cJW0ynA49VtS8zGx/dOjezF83sqPDxVjO7xcw+MLN3IucqzVX1PYvH2cCb7v4qgLtvBy4GJgKYWRszmxr1fTrVzG4FWoYtthl1+3aSp7LvmrtviXraGqhy1GbYGv23mS0Kf4aHy48ys7lm9pSZfWxmM6pryUvyZWoC7Qp8GfV8Dd/9p7cUGB0+HgscEOc+FwEHh4+vBf7l7kOAo4E/mllrYALQExjk7gOAjPmCV1CTc/Q4cKaZdQN2Aeui1r0BDHX3QeF2v41adwhwsrufXWdRJ5mZ9QAGAfMrrDocKHD3T2qx+9bAO+6eS/DHy/m12Fd9qep7BnBxmPgeMrN9Yry+H7AweoG7fwa0CS8bXA9sdvec8Pv0L3efCHzj7gPdfVydvpsUCf9w+hIYB9xQzeYbgGPdfTDBH6z3RK0bBFwG9CXoFRhR99FKTWRqAo31l1fkL7ufA78ys4UEXXI7E9jnccDE8JrXXCAL6A6MJOiCKQVw91itu0xQk3P0CnAscBYws8K6bsA/zGwJcCXBf5gRz7v7N3UXcnKZWRvgaeCyCq0GCN57la3POOwEXgwfLyTotkt3VX3P/gJ8DxgI5BN0ccd6fWUtLif4Pt1bvsD960QDTWfufq27H0DwB/fF1WzeHHgg/E49SZAsI9519zXuXkZwKaVHEsKVGmiW6gAStIbdW03dCFtG7v4xQQLEzPoAo+Lc5yCC7jsIvvinuvuK6A3CLpOMv3G2JufI3XeGifZ/CBLkSVGr/w+4w92fD7sqJ0Wt21a3USePmTUnSJ4z3P2ZCuuaAacQtKirU8ruf5RmRT3+1t0jn51dZMZ3r6rvWUFkoZk9wHd/HERbRnBtkKhtexFc4yxuKN+nGngUeAm4sYptLgcKgFyCz1JJ1LodUY8z5TPUoGVqC/Q9oLeZ9TSzFsCZwPMAZrZ/+LsJcB1wf3U7C7vubidICAD/AC6JXGMws0Hh8leBC8P/VDGzfevqDdWnBM7Rn4Cr3H1jheXtgLXh44wcxRz+Gz8IfOTud8TYZCTwsbuviWN3q4CBZtbEzA4guIaYyar6nnWO2m4MwWWBimYAPzSzkeFrWhJ0Sd4Wrn+VqBZZVDfwt+EfNRnPzHpHPR0NfFzNS9oB+WEr82cEA7kkTWVkAg27UC8mSHQfAU+4+7Jw9Vlm9h+CD+o6YGolu/leOPjlI4KBMf/n7pFtbyboSvkwHF4euZVjCrA6XP4BwSCJtGVmjwFvAweZ2Roz+0W4Kt5zBIC7L3P36TFWTQKeNLN/k7klq0YQ/Ef1I4t9S8aZVN1924zvWgZvAiuBJQR/kC1KQrz1pprv2W2RwT8E4wQuj/H6bwgGHV1nZisIzst7QGSg1e+Afcxsafh9OjpcPpngO5YxYwyq+K7dGr6/Dwl6fX4d4+XRn6H7gHPN7B2gDxnUk9MYaSo/kVoIR2iPc/fTUx2LZCZ9hjKX+tBFEmRmNxG0sManOBTJUPoMZTa1QEVERBKQkddARUREUk0JVEREJAFKoCIiIglQAhWpATPbFd7qsiyc1/Y34f20Vb2mh5ml9S1PIlJzSqAiNROZp7UfwRSHP6HqmWUgmHJNCVSkgdEoXJEaMLOt7t4m6nkvgskB2gMHAg8TTBwPcLG7vxXeFP8DgkkWphPMxnMrcBSwF3Cvu/+13t6EiNQJJVCRGqiYQMNlXxNU8ikGyty9JJzC7TF3zwvnCb7C3U8Mt58A7O/uvzOzvQhmMBrr7ivr872ISO1oIgWR2otULWkO/NnMBhJM9t2nku2PAwaY2Wnh83ZAb4IWqohkCCVQkVoIu3B3EdRxvJHKK2ns9jLgEnf/R70EKSJJoUFEIgkysw4ElWz+HJYqq6ySRjFB3dWIfwC/jFQcMbM+YcF2EckgaoGK1EzLsNB6c4L6nw8DkTJo9wFPm9lY4DW+q6TxIVAaVhyZBtxNMDJ3UVhOrRD4af2ELyJ1RYOIREREEqAuXBERkQQogYqIiCRACVRERCQBSqAiIiIJUAIVERFJgBKoiIhIApRARUREEvD/Acew1QttWG6mAAAAAElFTkSuQmCC", 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", 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LFmQNGzbs8NNOO+2LnJycnVGeS0lSRCQB5atVNRh58hx99NHFa9asKaiLcylJiojEoWrVvZSWlpZagwYNUn8y4gSVlpYaUFrRukiTpJldBvwScKAAGAs0A2YAnYFVwJnunvDoByIidUmtVvexpLCwsHvbtm23ZkKiLC0ttcLCwtbAkorWR5Ykzawj8Bugu7t/bWZPAmcD3YGX3H2SmU0AJgBXRRWHiEhNKUHuq6Sk5JcbNmyYvGHDhp5Ag2THUwtKgSUlJSW/rGhl1NWtjYCmZvYNQQlyHXA1cEK4fhowDyVJEUkRaphTtaOPPnoTMDTZcdSVyJKku681s9uB1cDXwBx3n2Nm7dx9fbjNejM7pKL9zWwcMA7gsMP04RSRaKlhjlQkyurWg4BhQBfgS+ApMzs30f3d/UHgQYD8/Py0r/cWkdSlhjlSmSirWwcCn7p7IYCZPQP0BzaaWfuwFNke2FTVQUREoqLRciSeKJPkaqCvmTUjqG49CZgPfAWcB0wKf86KMAYRkQptLCpW6VHiivKZ5DtmNhNYCJQA7xNUn7YAnjSzXxAk0lFRxSAiUpGNRcV8uvkrQKVHqVqkrVvd/UbgxnKLdxKUKkVE6kxsq9XLlCAlQRpxR0QyXvmGOS2zGtGmxQGaCFniUpIUkYxVacOcKa2THJmkCyVJEclI6tYhtUFJUkQyjoaTk9qiJCkiGUP9HqW2KUmKSEZQ9apEQUlSRNKaSo8SJSVJEUlLFQ1IrtKj1DYlSRFJO6palbqiJCkiaUNVq1LXlCRFJOWpalWSRUlSJF3MnwIFM5MdRZ3aWFTM5u076VpcwmVAy1bBcHLtmmTBMoJ/NbGhALJzajFSyVRKkiLpomBmvfnlXpYci4pLAPaMtdquZVbtnCA7B3JG1s6xJKMlnCTN7CCgA8HckKvcvTSyqESkYtk5MHZ2sqOIzJ5q1XWqVpXUUGWSNLPWwK+Bc4AmQCGQBbQzs7eB+9z95cijFJGMpmeOkqrilSRnAn8GfujuX8auMLOjgZ+ZWVd3fzii+EQkw6k7h6SyKpOku59cxboFwIJaj0hE6g0NRC6pLqFnkmZmwGigq7vfZGaHAdnu/m6k0YlIRlJ/R0kXiTbcuQ8oBX4E3AQUAU8DfSKKS0QylKpXJZ0kmiSPdffeZvY+gLt/YWZNIoxLRDKMSo+SjhJNkt+YWUPAAcysLUHJUkSkSmq5Kuks0SR5D/AscIiZ/Q4YCVwXWVQikjFmLVrLsvXblBwlLSWUJN19upktAE4CDPiJuy+PNDIRSWtlJchl67fRvX0rZlzQL9khiVRboq1b7wZmuPu9EccjImmusupVkXSUaHXrQuA6M+tGUO06w93nRxeWiKQbPXuUTJRodes0YJqZHQyMAH5vZoe5++GRRiciKU/JUTJZdWcB+T5wJNCZmk9SIyIZQn0eJdMl+kzy98AZwMfAk8DN5cdyFZH6Q30epb5ItCT5KdDP3TdHGYyIpAd165D6It5UWUe6+wrgXeCwcMzWPdx9YZTBiUjqKCs9AurWIfVGvJLk5cA44I4K1jnBWK4ikuHKP3vs3r6VunVIvRBvqqxx4cvT3L04dp2ZZUUWlYikDE1nJfVZos8k3wR6J7BMRDKEGueIxH8mmQ10BJqaWS+CIekAWgHN4h3czA4EJgM9Capnfw6sBGYQdCNZBZzp7l/UKHoRiYS6dogE4pUkTwXGAJ2AO2OWFwHXJHD8u4EX3X1kOLVWs3C/l9x9kplNACYAV1U3cBGJhqpXRb4V75lk2Ug7I9z96eoc2MxaAccRJFncfRewy8yGASeEm00D5qEkKZJUsS1XVb0q8q1Eh6V72swGAz2ArJjlN1WxW1egEJhiZrnAAuASoJ27rw/3X29mh1S0s5mNI2hZy2GH6YsqEoWKhpRT9arItxIdcecBgqrSEwmeMY4k6DsZ79i9gfHu/k44k8iERANz9weBBwHy8/M90f1EJD6NtyqSmERbt/Z396PM7AN3/39mdgfwTJx91gBr3P2d8P1MgiS50czah6XI9sCmmoUuIjWhRjkiiUs0SX4d/txhZh2ALUCXqnZw9w1m9rmZHeHuKwkmbF4W/jsPmBT+nFWjyEWk2tQoR6R6Ek2SL4TdOW4jmFvSCapd4xkPTA9btn4CjAUaAE+a2S+A1cCo6gYtItWnBClSfYk23Lk5fPm0mb0AZLn71gT2WwTkV7DqpIQjFEkV86dAwczknX9DAWTnVHs3DQogUnPxBhM4o4p1uHu855IimaNgZo0TVa3IzoGckdXaRc8fRfZPvJLk6VWsc+I33hHJLNk5MHZ2sqNIiKpXRfZfvMEExtZVICKy/zQogEjtSrSf5A0VLY8zmICI1BENCiASjURbt34V8zoLGAIsr/1wRKS69NxRJDqJtm7da9JlM7sd+GskEYlIQtRqVSR6iZYky2tGMDariCSBSo8idSPRZ5IFBK1ZARoCbQE9jxSpI7ENckCNckTqSqIlySExr0uAje5eEkE8IlJO+VJj2U+VHkWil+gzyc/M7CDg0HCfduFgAgsjjU6knlNfR5HkSrS69WaCyZM/5ttqVwd+FE1YIvWbGuWIpIZEq1vPBL7n7ruiDEZE1ChHJJUkmiSXAAeiuR9FIqXqVZHUkmiS/B/gfTNbAuwsW+juQyOJSqSeUfWqSGpKNElOA34PFACl0YUjUr9UNJycqldFUkeiSXKzu98TaSQi9YyePYqkvkST5AIz+x+Coehiq1vVBUSkmlS1KpI+Ek2SvcKffWOWqQuISDWp9CiSXhIdTODEqAMRyWQqPYqkJ80nKRIhNcwRSW+aT1IkIqpaFUl/mk9SpBbFztahqlWR9Kf5JEVqSfmSo0qPIulP80mK1AINJyeSmTSfpMh+UKtVkcyWaJJsDyx19yIAM2thZj3c/Z3oQhNJbWqYI5L5Ek2S9wO9Y97vqGCZSMbbWFTMb/73LUANc0Tqg0STpLl72TNJ3L3UzGra6Eck7fzlndXkrt9KUXEJ7+z6txrmiNQTiSa6T8zsNwSlR4CLgE+iCUkktZRVqz7RpISWWY3478EqOYrUF4kmyQuBe4DrCFq5vgSMiyooyQDzp0DBzGRHsd82FhXTdfNXPNEEejdZQ5P2ufRQghSpNxIdTGATcHbEsUgmKZgJGwogOyfZkdTIxqJiNm/fSVFx0Ii7S5vmNGmZCzkjkxyZiNSlKpOkmV0H3Ofu/65k/Y+AZu7+QhTBSZrLzoGxs5MdRbXs6dKxbu+xVvuq9ChSL8UrSRYAz5tZMbAQKCQYu/VwIA+YC/x3lAGK1AUNRC4iFakySbr7LGCWmR0ODCDoL7kNeAwY5+5fxzuBmTUE5gNr3X2ImR0MzAA6A6uAM939i/25CJGaUnIUkaok+kzyQ+DDGp7jEoIZQ1qF7ycAL7n7JDObEL6/qobHFqkxDQYgIvFE2tfRzDoBg4HfAZeHi4cBJ4SvpwHzUJKUOqSh5EQkUVEPCPAH4LdAy5hl7dx9PYC7rzezQyra0czGEXYzOeww/QKT2jNr0VqWrd+m0qOIxJXoLCAD3P2NeMvKrR8CbHL3BWZ2QnUDc/cHgQcB8vPzPc7mIlWKnedx2fptdG/fihkX9EtyVCKS6hokuN0fE1wWawAw1MxWAU8APzKzx4CNZtYeIPy5KcEYRGqk7NljWfVq9/atGJbXMclRiUg6iNdPsh/QH2hrZpfHrGpFMK9kpdz9auDq8DgnAFe4+7lmdhtwHjAp/DmrpsGLVEXPHkVkf8Wrbm0CtAi3i32uuA2o6dAjk4AnzewXwGpgVA2PI1IptVwVkdoQr5/kK8ArZjbV3T+r6UncfR5BK1bcfQtwUk2PJRJPbIJU6VFE9keirVsPMLMHCQYA2LOPu/8oiqBEakoJUkRqU6JJ8ingAWAysDu6cERqRs8fRSQKiSbJEne/P/5mInVLw8qJSJQSTZLPm9lFwLPAzrKFlc0OIlIX1DhHRKKWaJI8L/x5ZcwyB7rWbjgi8alqVUTqSqIDnHeJOhCReFS1KiJ1LdFh6ZoRDFB+mLuPC6fOOkKTLUtdUHIUkWRJtLp1CrCAYPQdgDUELV6VJCUySo4ikmyJJsnvuftZZnYOgLt/bWYWYVxSjyk5ikiqSDRJ7jKzpgSNdTCz7xHTylWkNig5ikiqSTRJ3gi8CBxqZtMJZvgYE1VQUr8oOYpIqkq0dev/mdlCoC9gwCXuvjnSyCTjKTmKSKpLtHXrcOCf7j47fH+gmf3E3Z+LMjjJXBoIQETSQcLVre7+bNkbd//SzG4EnoskKslYGghARNJJokmywX7sK6KqVRFJS4kmuvlmdidwL0EL1/EE/SZF4lLVqoikq0ST5HjgemBG+H4OcF0kEUlG0fyOIpLO4iZJM2sIzHL3gXUQjyTD/ClQMLNWD7lr7WI+bNCZa1YqQYpI+oqbJN19t5ntMLPW7r61LoKSOlYwEzYUQHZOrRxuY1Exn+7qxKzdx6h6VUTSWqLVrcVAgZn9H/BV2UJ3/00kUUndy86BsbP3+zDlq1f/R8lRRNJYoklydvhPpELq2iEimSjREXemhWO3HubuKyOOSdKIunaISCZLdMSd04HbgSZAFzPLA25y96ERxiYpqiwxAkqOIpLREq1unQgcA8wDcPdFZtYlopgkRVVUalRyFJFMlmiSLHH3reWmkPQI4pEUpQEBRKQ+SjRJLjGznwINzexw4DfAm9GFJalCDXJEpD6rzog71xJMtPwX4B/ALVEFJalBpUcRqe+qTJJmlgVcCHwfKAD6uXtJXQQmyaPSo4hIIF5JchrwDfAacBrwH8ClEcckSaTSo4jIt+Ilye7ungNgZg8D70YfkiSLBiMXEdlbvCT5TdkLdy8p17pVMsTGomI2b9+pwchFRMqJlyRzzWxb+NqApuF7A9zdW0UanUTuL++spuvmYDheVa+KiOytyiTp7g3rKhCpW7GNc55oAl3aNGfGBf2SHZaISEpJtAtItZnZocCfgWygFHjQ3e82s4MJJm/uDKwCznT3L6KKQ/ZVvnFOl53NadcyK8lRiYiknsiSJFAC/Je7LzSzlsCCcKqtMcBL7j7JzCYAE4CrIoxDQpV27ZiiBCkiUpHIkqS7rwfWh6+LzGw50BEYBpwQbjaNYDxYJckIaaYOEZGaibIkuYeZdQZ6Ae8A7cIEiruvN7NDKtlnHDAO4LDD9Mu8ptTvUUSk5iJPkmbWAngauNTdtyXajcTdHwQeBMjPz9dg6tVQ0VRW6tYhIlJ9kSZJM2tMkCCnu/sz4eKNZtY+LEW2BzZFGUN9U77kqNKjiEjNRdm61YCHgeXufmfMqr8C5wGTwp+zooqhvtGIOSIitSvKkuQA4GdAgZktCpddQ5AcnzSzXwCrgVERxlAvaEByEZFoRNm69XWCkXkqclJU561v1DBHRCQ6ddK6VWqfSo8iItFTkkwz6vMoIlJ3lCTTiKpWRUTqlpJkGlDVqohIcihJpjBVrYqIJJeSZAra7+Q4fwoUzEz8hBsKIDunBpGKiGQ2JckUUmslx4KZ1Ut82TmQM7Ka0YqIZD4lyRQya9Falq3fVjvVqtk5MHZ27QUnIlIPKUkmWexg5MvWb6N7+1bMuKBfkqMSERGABskOoL4rKz0CdG/fimF5HZMckYiIlFFJMknKSpAqPYqIpC4lyTpWWeMcERFJPUqSdUR9HkVE0o+SZB3QcHIiIulJSTJCGk5ORCS9KUlGRKVHEZH0pyRZy1R6FBHJHEqStUilRxGRzKIkWQtUehQRyUxKkvtJpUcRkcylJFlDKj2KiGQ+Jclq0qAAIiL1h5JkNahqVUSkflGSTICqVkVE6iclySqoalVEpH5TkqyEqlZFRERJsgKxCVJVqyIi9ZeSZAw9exQRkVhKkiFVr4qISHlKkqh6VUREKlavk6SqV0VEpCr1NkmqelVEROKpd0lSpUcREUlUUpKkmQ0C7gYaApPdfVLU59TAACIiUl11niTNrCFwL3AysAZ4z8z+6u7LojqnqlZFRKQmklGSPAb4yN0/ATCzJ4BhQK0nybfvO5+WXy6na3EJTzSBLm2a065JVnCmyFJyCthQANk5yY5CRCTtNUjCOTsCn8e8XxMu24uZjTOz+WY2v7CwcL9O2DKrUZAgW2bt13HSRnYO5IxMdhQiImkvGSVJq2CZ77PA/UHgQYD8/Px91iei70UP1WQ3ERERIDklyTXAoTHvOwHrkhCHiIhIlZKRJN8DDjezLmbWBDgb+GsS4hAREalSnVe3unuJmV0M/IOgC8gj7r60ruMQERGJJyn9JN39b8DfknFuERGRRCWjulVERCQtKEmKiIhUQklSRESkEkqSIiIilTD3GvXTr1NmVgh8VsPd2wCbazGcTKR7VDXdn/h0j6qWrPvzXXdvm4TzZoy0SJL7w8zmu3t+suNIZbpHVdP9iU/3qGq6P+lL1a0iIiKVUJIUERGpRH1Ikg8mO4A0oHtUNd2f+HSPqqb7k6Yy/pmkiIhITdWHkqSIiEiNKEmKiIhUIuWTpJkNMrOVZvaRmU2IWZ5rZm+ZWYGZPW9mrSrYt7OZfW1m75vZcjN718zOq9sriJaZPWJmm8xsSbnlid4fN7ObY5a1MbNvzOxPdRF/XTCzQ83s5fAzsNTMLolZN8PMFoX/VpnZogr271z+/maaKr5nE81sbcw9+nEl+/cws3+a2b/M7EMzu97MKppgPXafa2r7OqJUxXftZjP7ILw/c8ysQwX7ZvxnKGO5e8r+I5hK62OgK9AEWAx0D9e9Bxwfvv45cHMF+3cGlsS87wosAsYm+9pq8R4dB/SOvc5q3p+Pgfdjlv0qvEd/qkYMjZJ9H+LE1x7oHb5uCfyr7HNUbrs7gBvifY4y7V+c79lE4Io4+zcN9z8lfN8M+Dvw6zj7bU/2tVfzPlX2XWsV8/o3wAP17TOUyf9SvSR5DPCRu3/i7ruAJ4Bh4bojgFfD1/8HjIh3MHf/BLic4IOMmTUP/zp8LyxtDguXNzSz28NS2AdmNr6Wr6vWuPurwL8rWJXo/fkaWG5mZR2dzwKeLFtpZqeb2Tvh/ZlrZu3C5RPN7EEzmwP8uTauJSruvt7dF4avi4DlQMfYbcJSz5nA41Udy8zGxJayzewFMzshfL3dzH5nZovN7O2ye5UGqvqeJeKnwBvuPgfA3XcAFwMTAMyshZlNifk+jTCzSUDTsPQ1vXYvJxqVfdfcfVvM2+ZAla0hw1Lla2a2MPzXP1x+gpnNM7OZZrbCzKbHK41L9FI9SXYEPo95v4Zvf7ktAYaGr0cBhyZ4zIXAkeHra4F/unsf4ETgNjNrDowDugC93P0oIC2+xOVU5/48AZxtZp2A3cC6mHWvA33dvVe43W9j1h0NDHP3n9Za1BEzs85AL+Cdcqt+CGx09w/34/DNgbfdPZfgD5Tz9+NYdamq7xnAxWFye8TMDqpg/x7AgtgF7v4x0CKs5r8e2OruOeH36Z/uPgH42t3z3H10rV5NEoR/HH0OjAZuiLP5JuBkd+9N8EfpPTHregGXAt0JSvYDaj9aqY5UT5IV/RVV9lfaz4Ffm9kCgiq0XTU45inAhPA51DwgCzgMGEhQZVIC4O4VldRSXXXuz4vAycA5wIxy6zoB/zCzAuBKgl+IZf7q7l/XXsjRMrMWwNPApeX++ofg2qssRSZgF/BC+HoBQRVbOqjqe3Y/8D0gD1hPUCVd0f6VlZ6c4Pt0754F7l/UNNBU5e7XuvuhBH9QXxxn88bAQ+F36imChFjmXXdf4+6lBI89OkcQrlRDo2QHEMca9i4BdSIs5bj7CoIkh5l1AwYneMxeBNVtEHy5R7j7ytgNwiqOtO5AWp374+67wmT6XwRJ8PSY1X8E7nT3v4bVihNj1n1Vu1FHx8waEyTI6e7+TLl1jYAzCErG8ZSw9x+XWTGvv3H3ss/NblL/+1Wmqu/ZxrKFZvYQ3/4REGspwfM6YrbtSvDMsSgTvk/V8BdgNnBjFdtcBmwEcgk+S8Ux63bGvE6nz1DGSvWS5HvA4WbWxcyaAGcDfwUws0PCnw2A64AH4h0srGq7neAXP8A/gPFl9f5m1itcPge4MPzliZkdXFsXVFdqcH/uAK5y9y3llrcG1oav07JlcPj/+zCw3N3vrGCTgcAKd1+TwOFWAXlm1sDMDiV4npfuqvqetY/ZbjhBNX5504EfmNnAcJ+mBFWIt4br5xBTuoqpsv0m/OMlrZnZ4TFvhwIr4uzSGlgflhZ/RtBwSlJUSifJsLrzYoJkthx40t2XhqvPMbN/EXwg1wFTKjnM98JGJ8sJGqT80d3Ltr2ZoOrjg7B5dllXiMnA6nD5YoKGCSnJzB4H3gKOMLM1ZvaLcFWi9wcAd1/q7tMqWDUReMrMXiN9p0IaQPDL6EdWcVeGs6m6qrUR3/6F/wbwKVBA8AfXwgjirVNxvme3ljW4IXhuf1kF+39N0NDnOjNbSXBv3gPKGjjdAhxkZkvC79OJ4fIHCb5jafHMv4rv2qTw2j4gqL25pILdYz9D9wHnmdnbQDfSqEamPtKwdCJxhK2eR7v7mcmORdKTPkPpS/XdIlUws5sISkljkhyKpCl9htKbSpIiIiKVSOlnkiIiIsmkJCkiIlIJJUkREZFKKEmKlGNmu8NuIkvDcVgvD/ubVrVPZzNL2a5CIlIzSpIi+yobU7QHwXB9P6bqEVQgGD5MSVIkw6h1q0g5Zrbd3VvEvO9K0Dm+DfBd4FGCwcwBLnb3N8OO4f9BMNDANIIRZyYBJwAHAPe6+//W2UWISK1QkhQpp3ySDJd9QTB7TBFQ6u7F4XBkj7t7fjiu7RXuPiTcfhxwiLvfYmYHEIzUM8rdP63LaxGR/aPBBEQSUzZTRmPgT2aWRzAAdbdKtj8FOMrMRobvWwOHE5Q0RSRNKEmKxBFWt+4mmAfwRiqfwWGv3YDx7v6POglSRCKhhjsiVTCztgQzqPwpnAarshkcigjm7SzzD+BXZbNcmFm3cEJvEUkjKkmK7KtpOBF3Y4L5Ix8FyqbYug942sxGAS/z7QwOHwAl4SwXU4G7CVq8Lgyn6ioEflI34YtIbVHDHRERkUqoulVERKQSSpIiIiKVUJIUERGphJKkiIhIJZQkRUREKqEkKSIiUgklSRERkUr8fww5KVOXr8wNAAAAAElFTkSuQmCC", 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lG8aPH99u/fr1TS+77LKNU6dOzb/66qvXXH/99eV6B8+dO7f4ueeea/Pzn/+889SpUzfff//9aypyLSVQEZFsi2/37NibWa2+yQP/t3cyisTEmdMlz5g0JcVs+u53v/vF3Xff3bm0tNTOO++8j5o2beq33377waNGjfqsTZs2e5YvX960WbNm/tVXX9lBBx1U+qMf/eiz/Pz8PZMmTTqwotdSAhURqQlhu+feDkKfqYNQFuTl5flxxx23ef/999/dpEkTvv3tb29etGhRXv/+/Y8AaNGixZ4nnnhi+fvvv7/fjTfe2KVRo0Y0adLEx40b93FFr6UEKiJSXVINUQlLnxrLmX27d+9m7ty5rZ555pllsW233HLL+ljP3JhevXrtPO+884qrci2txiIiUl2SrJyybssOFnlXHvmir5Jnls2ZMyfv0EMP7X3CCSds7t27985sX08lUBGR6hQ3RGWf8ZwHtmVAAaqqzaKjjz56x6pVq2ps7TclUBGRKNLNIBQTV1Ub36tWJc76SQlURCSKdDMIhda1PIwpX/TlnrhZhBpYiXPPnj17rFGjRrm7SkmcPXv2GLAn1X4lUBGRqNLMIJQ4/V4DS5wxC0tKSnq2b99+U64n0T179lhJSUkbYGGqY5RARUSqSL1rA6Wlpf+9du3a8WvXrj2S3O+kugdYWFpa+t+pDqiVBGpm1wD/DTiwALgMaAFMBroBK4AL3L1CE/uKiFSrNDMIxa+WorbOwNFHH70eGFLbcdSUGl9Q28w6A28APd39SzN7Gvg70BP4zN3HmtkY4AB3vyHdubSgtohkVcIC17NafZMHPjsuuB03exDkVu/abC2o3dDUVhVuE6C5mX1FUPL8FLgRODncPwmYDqRNoCIiWZdiBqEG3M4poRpPoO6+2szuB1YCXwKvuPsrZtbB3deEx6wxs4NqOjYRaeASh6poBiFJo8Ybec3sAGAoUAAcDLQ0s0sq8PhRZjbbzGaXlJRkK0wRaYjiZhLSDEKSSW1U4Z4GLHf3EgAzex44DlhnZp3C0mcnYH2yB7v7I8AjELSB1lDMItJArGt5GFftuplZn4ZtnJpBSFKojQS6EjjWzFoQVOGeCswGtgGXAmPD31NqITYRaaD+PGslhWs2sWVHKbN2faY2TsmoNtpAZ5nZs8BcoBT4D0GJshXwtJn9gCDJDq/p2ESkHksyFd+6LTvYsDWYc7z7jlIOsY/5JO9r3HO2qmols1rphevutwG3JWzeSVAaFRGpfnFT8cUS55YdpQDk5zUhP68JX7bqSa/jLqFXPyVPyUwzEYlIg1GufVPVtFIFSqAiUj8lVNnuWj2f5bu6qH1Tqo0SqIjUTwlVtst3dWHK7uM0FEWqjRKoiNQ7sR610JU74qpslTylOuX6bPkiIvuIzRoU6yAEQVunkqdUN5VARaRemPXML2m15AW67yjlqWbQt9kqmnUqZPJlA2s7NKmnVAIVkZz351kr8QXPcMjOZeTnNaGgXUuadS6E3ufXdmhSj6kEKiI5K7Ym56zln/FUM/jywJ70umpabYclDYQSqIjklMSFrC9uPI1bW7/DYXtW0Sy/sJajk4ZECVREckb8smKxNTmv3jmfDttWgqpspYZFTqDhMmQHE0wAv8Ld92QtKhGRBCnX5JyQB/nBotciNSltAjWzNsCPgYuBZkAJkAd0MLO3gXHu/lrWoxSRBiu+nRM0llPqjkwl0GeBPwInuPsX8TvM7Gjgu2bW3d0fy1J8ItKAxUqdsXbOdq32o0NxHhTHHRTONiRS09ImUHc/Pc2+OcCcao9IRBq0xE5CAFd3CNs585Mkyo691fYptSJSG6iZGTAC6O7ud5hZV6Cju7+T1ehEpEFJ1kloaFHnoNSpdk6pY6J2IhoH7AG+CdwBbAGeA/pnKS4RaWBmPfNLui94hqeaQUG7lnRolhfsKEbVtFInRZ2JaIC7/xjYAeDunxN0KhIRqbLYTEI97eMgeebn7XuAqmmlDopaAv3KzBoDDmBm7QlKpCIilZZsJqEOmklIckTUBPob4AXgIDO7GzgfuDlrUYlIvRXfSaj7yme4pvFM8ls30UxCknMiJVB3f8LM5gCnAgZ8y90XZzUyEalXEsdzDihoyyUtwyn4OhUCmklIckvUXri/Bia7+0NZjkdE6qHE3rVDizoHkyFMaAMUqnet5KSoVbhzgZvNrAdBVe5kd5+dvbBEpD7QLEJSn0Wtwp0ETDKztsB5wC/MrKu7H5bV6EQkZyWWOq9tO5MBxeM0i5DUGxVdUPvrwBFAN+D9ao9GROqFxInfJ18xkAFbXw0SZjwNT5EcFrUN9BfAt4FlwNPAnYlz44qIZKyy7ajZhKT+iNoGuhwY6O4bshmMiOSm+MSZcuJ3VddKPZNpObMj3P194B2gazgHbhl3n5vN4ESkbks2NKVsgevEid9VXSv1TKYS6LXAKOCXSfY5wdy4ItJATZm3muI1mxOGpmjid2kYMi1nNiq8eZa774jfZ2Z5SR4iIg1ArORZvGYzPTu1ZvIVA2s7JJEaF7UNdCbQN8I2EamnEtfpvLjxNG5t+Q7tdu4XlDpj1NYpDUSmNtCOQGeguZn1IZjGD6A10CLLsYlIHZCsnVNtnSKZS6BnAiOBLsADcdu3ADdlKSYRqSNSTsEHauuUBi9TG2hsBqLz3P25GopJROqA+OQ5+ej3g4kQitGwFJFQ1Kn8njOzs4FeQF7c9jsqc1Ez2x8YDxxJ0Jv3+8AHwGSCWY5WABeEC3eLSA1LnEloQPG48glTVbXSwEWdiehhgjbPUwgS3/kEY0Mr69fAy+5+vpk1C899EzDN3cea2RhgDHBDFa4hIhWQ2EkI4mYSKkazCIkkiDoX7nHu/j3gc3f/f8BA4JDKXNDMWgMnAo8BuPuucFrAocCk8LBJwLcqc34RqbhYiTO+o5BWThFJL+owli/D39vN7GBgI1BQyWt2B0qACWZWCMwBfgp0cPc1AO6+xswOquT5RaQCEqtry5Lm7Akw4dngtto7RcqJmkD/GrZb3kewNqgTVOVW9pp9gdHuPitcrHtM1Aeb2SiC2ZHo2lXfjkUqK+PE7wue3Zs41d4pUk7UTkR3hjefM7O/AnnuvqmS11wFrHL3WeH9ZwkS6Doz6xSWPjsB61PE8gjwCEC/fv28kjGINFjJxnXuMzwlnto9RVLKNJHCt9Psw92fr+gF3X2tmX1iZoe7+wfAqeztHH8pMDb8PaWi5xaR5JJ1EEqaOGdPCEqeoGpbkQwylUDPTbPPgQon0NBo4ImwB+5HwGUEHZqeNrMfACuB4ZU8t4jESZwMIW2JU9W2IpFlmkjhsmxc1N3nAf2S7Do1G9cTaahSdhBKR9W2IpFEHQd6a7LtlZ1IQUSyKK4atnDNJp5qVkpBu5b7Lm6diqptRSKL2gt3W9ztPOAcYHH1hyMiVbbgWXatns+SRt3Yvms3+XlN6JAfcfVBVduKRBa1F+4+C2qb2f3AX7ISkYhUSqyj0K0bN7FlVxcu2nVjWXtnL02IIFLtopZAE7UgmBBBROqA+LZOWkN+XhPuOVszCYlkU9Q20AUEvW4BGgPtAbV/itSWuHbOdVt20H3DNp5qRtDWuW0ldOytUqdIlkUtgZ4Td7sUWOfupVmIR0SiiGvn3LIj+CgWtGsZtHXmqx1TpCZEbQP92MwOIJhAvgnQIZxIYW5WoxORpNZt2cHyhHbOY1XiFKlRUatw7wRGAsvYW5XrwDezE5aIlAmra9dt2cGGrTsBOGTnMuBQrZgiUouiVuFeAHzN3XdlMxgRSSKsrl2+qwsQdBD6ZL+vYYcNU/IUqUVRE+hCYH9STPAuItWv/LCUW1TiFKlDoibQ/wX+Y2YLgZ2xje4+JCtRiTRgiaulaFiKSN0UNYFOAn4BLAD2ZC8ckQYsbOssXLOJw3btpkXrxrRrtZ+GpYjUUVET6AZ3/01WIxFp4NbNfJxWny9mux9Ki2aN6dWpTbBDw1JE6qSoCXSOmf0vwfR98VW4GsYiUgXx63Res2Eb0JUHOz+g6fdEckDUBNon/H1s3DYNYxGpoq0zH+W6TVNp0awx3RqvZOsB32DyFQNrOywRiSDqRAqnZDsQkYYkVvK8btNUetrHtOzUB+hDS1XViuQMrQcqUsPiJ35v0boxW1t9g5ZawFok52g9UJEaFJ887xnWm17FbWo5IhGpLK0HKpJlf561kq0zH2XQl6/RfUfp3lVTivNg7YJgEWsRyTlaD1QkS+InRHiq2b/o1nglK/K6B2M78/OCgzpqiIpIrtJ6oCLVLHEmoQEFbSnY2ZKW+X3opbZOkXpD64GKVKP4Ns6bOrzN0MYz6dAsDz5bEkyIICL1RqOIx3UCPnP3j919NZBnZgOyGJdIzknsIDRq/7l02LYk2KmqWpF6J2oJ9PdA37j725NsE2mQEqtsy1ZMKSZInKq2FamXoiZQc/dYGyjuvsfMKtsBSaReSNbWObSos1ZMEWkgoibBj8zsKoJSJ8CPgI+yE5JI3ZYscV7bdiYDtr4alDqLwwM1REWkXovaBnolcBywGlgFDABGZSsokboq1s45a/lnDChoyz3DejP5ioFB8ly7YN+D1e4pUq9FnUhhPXBRlmMRqbNStnPGU3unSIOSNoGa2c3AOHf/LMX+bwIt3P2v2QhOpDbFLzVWrrq2eNzeqlpQda1IA5SpBLoAeMnMdgBzgRKCuXAPA4qAqcA92QxQpKYla+Pcp4PQhLvKJ0xV14o0OGkTqLtPAaaY2WHAIILxoJuBx4FR7v5l9kMUqTnxYznT9qpVda1Igxe1DXQJsCTLsYjUuliV7T3DevOdxtNgwV37VtWCqmtFBIjeC7famVljM/uPmf01vN/WzP5lZkvC3wfUVmzS8Px51kou/L+3KF6zmQEFbYNS54Jny/esBVXXighQ+dVYqsNPCdYUbR3eHwNMc/exZjYmvH9DbQUnDUOqyRDKqKpWRFKIuhrLIHd/M9O2qMysC3A2cDdwbbh5KHByeHsSMB0lUMmiyO2dIiJJRC2B/pby894m2xbVr4CfAflx2zq4+xoAd19jZgdV8twiaaUc0zl7Akx4du+BausUkTQyjQMdSDADUXszuzZuV2uCdUErzMzOAda7+xwzO7kSjx9FOAtS164qLUh0GeeujbV5xpKm2jpFJI1MJdBmQKvwuPjS4magsv9ZBgFDzOy/CMaUtjazx4F1ZtYpLH12AtYne7C7PwI8AtCvXz9PdoxIvApN+q42TxGJKNM40NeB181sort/XB0XdPcbgRsBwhLode5+iZndB1wKjA1/T6mO60nDlTZxJlbXgqpsRaRCoraB7mdmjwDd4h/j7t+sxljGAk+b2Q+AlcDwajy3NCCRSpyJ1bWgKlsRqZCoCfQZ4GFgPLC7ui7u7tMJetvi7huBU6vr3NLwVHh9TlXXikgVRE2gpe7++8yHidQODUkRkZoWNYG+ZGY/Al4AdsY2plqlRaQmxSfPtFPwxVN7p4hUUdQEemn4+/q4bQ50r95wRCqmXPIc0DXoHJQpQaq9U0SqKOpk8gXZDkQkqmTrdJZb4FrtmyKSZVGn8mtBMOVeV3cfFS5vdrgW0paaltjWWdbe2Xja3mEpqp4VkRoQtQp3AjCHYFYigFUEPXOVQKXGJK2ujYmvtlX1rIjUgKgJ9GvufqGZXQzg7l+amWUxLpF9pE2eMaq2FZEaFDWB7jKz5gQdhzCzrxHXG1ckGyK1dYqI1JKoCfQ24GXgEDN7gmA+25HZCkokZVtnLHnOnhDMJhSjdk8RqWFRe+H+y8zmAscCBvzU3TdkNTJpcCpU4tTKKSJSy6L2wh0GvOrufwvv729m33L3F7MZnDQcGUucyajNU0RqUeQqXHd/IXbH3b8ws9uAF7MSlTQ4sZLnPiXOZCumxKjKVkRqWaMqHBc1+YpEMqCgbfIVU5JRla2I1LKoSXC2mT0APETQE3c0wbhQkUqJb+8EKF6zmZ6dWpc/UNW0IlJHRU2go4FbgMnh/VeAm7MSkdR7ie2dAKPbvMHQnTNhQt7eA1VNKyJ1WMYEamaNgSnufloNxCP1XMoJESbcBWuXQL4WuBaR3JAxgbr7bjPbbmZt3H1TTQQl9VPG2YRUXSsiOSRqFe4OYIGZ/QvYFtvo7ldlJSqpdyJNxScikkOiJtC/hT8iFRafPCcf/T4DiseVX+xa7Z0ikmOizkQ0KZwLt6u7f5DlmKSeiPW0jZ9VaEDxuOTJUu2dIpJjos5EdC5wP9AMKDCzIuAOdx+SxdgkRyUmzn1mFSpGbZ0iUi9ErcK9HTgGmA7g7vPMrCBLMUkOSxyiUrbY9YK7guSpqloRqSeiJtBSd9+UsASoZyEeyWGph6hosWsRqX+iJtCFZvYdoLGZHQZcBczMXliSS5K1dWqIiojUdxWZiejnBIto/xn4J3BXtoKS3JC2rVNEpJ5Lm0DNLA+4Evg6sAAY6O6lNRGY1F0VSpyzJ8DHb8Chx9dwlCIi2ZWpBDoJ+Ar4N3AW8A3g6izHJHVUpUqcC8LlyNTuKSL1TKYE2tPdewOY2WPAO9kPSeqipL1ro1bVHno89Lssi9GJiNS8TAn0q9gNdy9N6IUrDUTkafhmT9hb4ozRsBURqacyJdBCM9sc3jageXjfAHf3JAs4Sq5LXKszbe/aeAueLZ8wNWxFROqptAnU3RvXVCBSNyRbq7NCVbYariIiDUTUYSzSAGjFFBGR6Go8gZrZIcAfgY7AHuARd/+1mbUFJgPdgBXABe7+eU3H1xBFmgghJlk7Z4zaO0WkAamNEmgp8D/uPtfM8oE54TqjI4Fp7j7WzMYAY4AbaiG+BqPSw1JSJUq1d4pIA1LjCdTd1wBrwttbzGwx0BkYCpwcHjaJYOJ6JdBqFt9BqNIzCKmdU0SkdttAzawb0AeYBXQIkyvuvsbMDqrN2OqrKfNWU7xmMz07tU6dOFVNKyKSUa0lUDNrBTwHXO3um6OOMTWzUcAogK5d1cklk8QhKbHkOfmKgakfpGpaEZGMaiWBmllTguT5hLs/H25eZ2adwtJnJ2B9sse6+yPAIwD9+vXTkmppJBuS0rNTa4YWdc78YFXTioikVRu9cA14DFjs7g/E7foLcCkwNvw9paZjq29iJU8NSRERqX61UQIdBHwXWGBm88JtNxEkzqfN7AfASmB4LcSW8+KrbIvXbGZAQdvMyTOxzVPtnCIiGdVGL9w3CKYCTObUmoylPkk2JCVydW1im6faOUVEMtJMRPVAlVZKiVGbp4hIhSiB5rgKT7+nFVNERKqFEmiOqtD0e/G0YoqISLVQAs0RqZYYq1SVraprRUSqTAk0R8TPIAQVSJzqYSsikhVKoDngz7NWMmv5ZwwoaJt+BqFk1MNWRCQrlEDrsMR2zkhDUpJRla2ISLVTAq2jqmVoioiIZI0SaB1ULUNTYtTmKSKSFUqgdUi1Dk2JUZuniEhWKIHWAcmm4dPQFBGRuk0JtA6IDVHJmDhTVdWqmlZEpMYpgdayCg1RSVVVq2paEZEapwRai+I7C0UeoqKqWhGROkEJtIYkTsUHVLyzkIiI1BlKoDUgcUxnzICCtlzbdiYDisdBcYQTqa1TRKTOUALNsoxjOifcFT0xqq1TRKTOUALNkgqN6VS7pohIzlECzZKkQ1O0mLWISL2hBFqN4jsKxZYe22doihazFhGpN5RAq0liR6GenVonH5qi6loRkXpBCbQaVHjydxERyXlKoFWUMnmqvVNEpF5rVNsB5LK0Jc9Ye2c8tXeKiNQbKoFWUHxHoYxDVNTeKSJSbymBVlBseMroNm9wa+vXaNdqPzoU55WfSUjVtSIi9ZoSaAXEr5wyqtlc2LES8lMkSVXXiojUa0qgESTOKjS0qHNQ4lQVrYhIg6UEmkrYi3bdlh1037CNa4D81k32VtmqilZEpEFTAk1h3czHafX5YpbvDjoHFbRrSYf8vL0HqIpWRKRBUwJNEKuuvWbDNqArD3Z+kKFFnTlWkyOIiEgcJdA48eM6Y9W1+8xlKyIiEqpzCdTMBgO/BhoD4919bE1c98+zVrLgL7/iqWYzg+rabWl62IqISINXp2YiMrPGwEPAWUBP4GIz65nt68ZKnkMbz6Rvs1VBW6faOEVEJI26VgI9Bljq7h8BmNlTwFDKT1NQLRKHpxS0a0mz/EINTRERkYzqWgLtDHwSd38VMCAbF3p73OV0X7tg3+Ep25ao2lZERCKpawnUkmzzfQ4wGwWMAujatWo9Y/PzwsQZG56Sr2pbERGJpq4l0FXAIXH3uwCfxh/g7o8AjwD069dvn+RaEcf+6NHKPlRERKRudSIC3gUOM7MCM2sGXAT8pZZjEhERKadOlUDdvdTMfgL8k2AYyx/cfVEthyUiIlJOnUqgAO7+d+DvtR2HiIhIOnWtCldERCQnKIGKiIhUghKoiIhIJSiBioiIVIISqIiISCWYe6XnIqh1ZlYCfFyFU7QDNlRTONmiGKtPLsSpGKtPLsRZWzEe6u7ta+G69UpOJ9CqMrPZ7t6vtuNIRzFWn1yIUzFWn1yIMxdilNRUhSsiIlIJSqAiIiKV0NAT6CO1HUAEirH65EKcirH65EKcuRCjpNCg20BFREQqq6GXQEVERColZxOomQ02sw/MbKmZjYnbXmhmb5nZAjN7ycxaJ3lsNzP70sz+Y2aLzewdM7s0S3EeYmavhddZZGY/rUSsC7MRW4T42prZv8xsSfj7gBTxuZndGbetnZl9ZWa/q6YYq/paZzW+hOulez6LzOxtM5tnZrPN7JgU8Wbt9Q6v8QczW594nSjxxR17jZntMLM2WYwz1es+OYxxnpmtMLN5KR7fy8xeNbMPw/fwLWZmGa55U8TY0r3OGeOLe1+Ojtv2OzMbGeX6Uke4e879ECx1tgzoDjQD5gM9w33vAieFt78P3Jnk8d2AhXH3uwPzgMuyEGsnoG94Ox/4sCqx1nB89wJjwttjgF+kiG8Z8J+4bT8Mn8/fVSCOJll8rascXzU9n68AZ4W3/wuYXtOvd3iNE4G+ideJEl/cse8A/wZGZinGlK97wnG/BG5Nsr15+PgzwvstgH8AP85w3a1VfZ0jxtcNWAcsBZqF236XredTP9n5ydUS6DHAUnf/yN13AU8BQ8N9hwMzwtv/As7LdDJ3/wi4FrgKwMxaht/S3w1LqUPD7Y3N7P6wxPNe/LfHNOde4+5zw9tbgMVA58rEGn5r/beZzQ1/jgu3n2xm083sWTN738yeyPRNO2J8Q4FJ4e1JwLdSnOZLYLGZxcazXQg8HRf3uWY2K3wup5pZh3D77Wb2iJm9Avwxxbmr47WucHxm1igstbQPj2kUloTapbgGkPH5dCBWSm4DfJruXGY2Mr6UbGZ/NbOTw9tbzexuM5sflho7pDtXQowzgM+S7YoSn5l9DWgF3AxcHDHeH4Qlwelm9miE0n+61z12fgMuAJ5M8vjvAG+6+yvh37wd+AnBF0HMrJWZTYj7LJ9nZmOB5mHJ8Yl0wWV4naPEB1ACTAPK1X7F1Qa8Z2YvmNkBZvYNM3sn7phuZvZeujglu3I1gXYGPom7v4q9b96FwJDw9nDgkIjnnAscEd7+OfCqu/cHTgHuM7OWwCigAOjj7kcBaT9kicysG9AHmFXJWNcDp7t7X4Ik8Ju4fX2Aq4GeBN/aB1UkthTxdXD3NRD8wwAOSvPwp4CLzKwLsJt9//m+ARzr7n3C434Wt+9oYKi7fyfFeavrta5QfO6+B3gcGBEecxow390jzxqT5Pm8muC99AlwP3Bj1HMl0RJ4290LCb5EXF6Fc8VcTbT4LiZICv8GDjezdO8LzOxg4BbgWOB09n7O0kn3usecAKxz9yVJHt8LmBO/wd2XAa0sqOq/Bdjk7r3Dz/Kr7j4G+NLdi9x9RPlTJpfkdY4SX8xY4H/MrHHC9j8CN4SxLQBuc/fFQDMz6x4es88XQal5uZpAk5WuYt2Jvw/82MzmEFSt7KrEOc8AxoRtF9OBPKArwT/Rh929FMDdk32LT35ys1bAc8DV7r65krE2BR41swXAMwTJMuYdd18V/uOfR1BFFFmK+CriZYJ/jhcDkxP2dQH+GcZ9PcE/t5i/uPuX6UJLsq0yr3Vl4vsD8L24a01Ic/59g07+fP4QuMbdDwGuAR6Ler4kdgF/DW/PoYKvdwpR47sIeCp8rz1P8OUlnWOA1939M3f/iuC9m0m61z0mlshTPT7VEAMn+Cw/VLbB/fMIMZW/SPrPTbr4YtddTlAdXvYF0oJ25f3d/fVw0ySCancIEuYF4e0LKf9elhqUqwl0FfuWNroQlijc/X13P8PdjyZ48y6LeM4+BNUwEHz4zgu/iRa5e9fw21+6D2VKZtaU4EP2hLs/H9teiVivIWg3KQT6EbQNxeyMu70baFLV+IB1ZtYpPKYTQQk4qbCabQ7wP+G54v2WoL2xN3AFwReSmG0ZwquW17oy8bn7JwTPwTeBAQRtaBmleT4vJUg4ECSRlJ10QqXs+xmNf96+cvfYe7FCr3caGeMzs6OAw4B/mdkKgmQaq8ZNFW+k5oQEKV/3MI4mwLdJnUAWEXxG4mPvTtDGuYVKfpYTzpfqdY4SX7x7gBuI9v94MnCBmfUAPEPpVrIsVxPou8BhZlZgZs0IPsR/AYhVJ5lZI4I2mocznSysgrmf4B8pwD+B0bF2RDPrE25/Bbgy/HBgZm0jnNsIvskvdvcHEvZVNNY2wJrwm/93CTpaVEm6+Aie01j7zKXAlAyn+yVBtdPGhO1tgNVx56mI6nytKxPfeIKq3KfdfXemYDM8n58CJ4W3vwlk+ue3AigK218PIXPCraoo8V0M3O7u3cKfg4HOZnZomnjfAU4K2/GaEKFfAmle99BpwPvuvirF458Ajjez0wDMrDlBk8e94f5XCNpECffHeph/FSbGtDK8zlHiK+Pu7wPFwDnh/U3A52Z2QnjId4HXw33LCL4w3YJKn7UuJxNoWIX6E4JEt5jgn9uicPfFZvYh8D7BP4RU1W5fs3AYC0G1yG/dPXbsnQTVpe9Z0NU/NgRiPLAy3D6fuGqXNAYRfAC+aXu7tv9XBWJtwt7S5TjgUjN7G+hB5tJbFOniGwucbmZLCKo/x6Y7kbsvcvdJSXbdDjxjZv+mgitPVNNrXZX4/kLQYSZq9W265/Ny4Jfhe+cegjb1RPGv95vAcoI2sPsJ2umrzMyeBN4iaL9cZWY/qEB8FwEvJGx7IdyeNF53Xx2ebxYwlSBZbEoXY4bXPRZHyurRsFlgKHCzmX0QxvQuQU9XgLuAA8xsYfj3nhJuf4Tg852pf0O61zljfEncTVDKjrmUoD36PaAIuCNu32TgEtT+Wes0E1EdZ0EP4BHufkHGg6XaWdBz90F3PyHjwdVzvXr5eptZK3ffGpZAXwD+4O6JiVgkp1RHu4lkiZndQfAtemQth9IgWTB4/4fs7Ymb7evV59f79rA6NY+g+vTF2g1HpOpUAhUREamEnGwDFRERqW1KoCIiIpWgBCoiIlIJSqAiFWBmu8MhC4ssmIf22nAcarrHdDOzKEOeRCSHKIGKVExsrtReBGNj/wu4LcNjuhFtzLCI5BD1whWpADPb6u6t4u53Jxig3w44FPgTwUTvAD9x95nhxBffIJhkYBLBjDhjgZOB/YCH3P3/auyPEJFqoQQqUgGJCTTc9jnBCiNbgD3uvsPMDgOedPd+FizpdZ27nxMePwo4yN3vMrP9CGbwGR5OLC4iOUITKYhUXWyy9KbA78ysiGC+0h4pjj8DOMrMzg/vtyGYoF0JVCSHKIGKVEFYhbubYKWa29i7Wk4jYEeqhwGj3f2fNRKkiGSFOhGJVJKZtSdYAeZ34dJiqVbL2UKwXmnMP4Efxlb9MLMeFizYLiI5RCVQkYppbsFC600J1r/8ExBbzmoc8JyZDQdeY+9qOe8BpeGqHxOBXxP0zJ0bLotVAnyrZsIXkeqiTkQiIiKVoCpcERGRSlACFRERqQQlUBERkUpQAhUREakEJVAREZFKUAIVERGpBCVQERGRSlACFRERqYT/D3TXPFZZNL1MAAAAAElFTkSuQmCC", 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", 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" ] @@ -10603,7 +10657,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **70-79** population up to 15 Dec 2021" + " ## COVID vaccination rollout among **70-79** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -10634,7 +10688,7 @@ }, { "data": { - "image/png": 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", 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", 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", + "image/png": 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", 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", 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", 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Nb35DZWUlTqeTMWPG8MorrzB79mzy8/NZu3YtTz31FGlpaXWep6HHVlvt57chhYWFNY/lzTffPO4cRUXHqoOXXHIJ//rXv2r6tGzcuJHk5GSfriHEmWzprqWs3LsSgISIBO4bcV8rR3Tm+fjjj/c1ts8zzzxT51Cxn376aafn9m233ZZ/2223Hdd34Nxzzy3fvn37Ce2kc+bMOTpnzpyjdZ1z9OjRZTt37txe+9pms5l//etfGUBG7WOCgoJcn3zyyd7a28vKyn6pL16Ar776ak/tY26++eaCm2+++YRk6Q9/+EPeH/7wh7za25tCmjbcZs6cSWpqKsOGDeOdd94hISEBgE6dOnH++eczYMAA7r33Xi655BKuu+46zj33XJKSkrj66qspLi5my5YtjBgxguTkZP72t7/x0EMPAXDLLbcwceLEEzpbBgYGsnDhQqZNm0ZSUhImk4nbbrsNMH7BpkyZwqefflozvNJut7No0SKuvfZaBg4cyMiRI+t9I3/iiSc455xzGD9+fM3j8NVbb73FggULGDhwIOeddx5ZWVlMnTqVgQMHMmjQIC6++GL++c9/EhUVVe85Gnpstc2ZM4fbbrutzs6WtT366KNMmzaN0aNHH5eYXXbZZSxfvryms+WCBQtITU1l4MCBJCYm8vLLL5/UcyDEmWrl3pXszN/Z+I5CnEaqsTL0mWzYsGE6NTW1tcMQQohm51198NiZv5P4iHgWTlh4SudWSq3XWtfdw/kUbNq0af+gQYPqbUYQbdemTZtsgwYNiq3rPqlICCHEGaiu6kN8RDyTek0i6+9/J+vvf2+lyIQ4XpvuI5GXl1fTF8Gjf//+DB8+vKZ/QG3JyckkJydTVlbGkiVLTrh/2LBhDBgwgMLCQpYvX37C/eeeey7x8fHk5uayYsWKE+4fM2YMvXr1Iisri1WrVp1w/9ixY+nWrRuHDh3iyy+/POH+CRMmEBUVxd69e48b6eAxZcoUbDYbO3fu5Pvvvz/h/qlTpxIeHs7WrVupq1ozffp0goOD2bhxY82QVm8zZ87E39+fn3/+uc5REXPmzAHgu+++Y9euXcfd5+fnx6xZswD4+uuv2bfv+KbKoKCgmj4fq1evJj09/bj7w8LCuPLKKwFYtWoVWVlZx93fqVOnmjk1Pv74Y/Lyjm/ei4qKYsKECQD85z//Oa7fBEDXrl0ZN24cACkpKSc0pfTs2bOmL8fbb7+NZwY4j7i4uJpJr2r/3oH87snvXvP97n2f/j1f7PmC2PBYLki6oOZ3790fD/LJI3ewa8MGtNlCV/dEbqf6uyfEqWjTiYQQQrRHm3I2ATDIPqhmW0HKEjq+9i59Dq7HVObEGWZprfCEOI70kRBCiDPM3FVzAVg4YSGvv/Yuh1K/ISrnIP5VlZj9NSal6JyQzMS/P9Wk80sfCXGyGuojIRUJIYQ4A3h3rvR0qgQ4lPoNgUVZ+GkHZn9NUEcHRTqGPGVr6HRnrT179vjPnDmzZ05Ojr/JZGL27Nk5Dz/88JHWjqs9k0RCCCHOAJ7OlR39YnFWdqH7J4pPn/4NdqsDswnG7D1EYIdqelzel+UHZkJo/UOwz2b+/v7Mnz8/fdSoUWUFBQWmwYMHJ06aNKnoTFhuu72SREIIIVpJXVWIsgO3cDCziJE7XqLrkb1khXZGaciOPYfs6PPZkD+Y3MISbKGtHPwZqkePHtU9evSoBujYsaOrd+/e5QcPHrRIItFyJJEQQohWsnLvSrbk7MDsiAG6kJGeQOK6VczJ2kSvwsMERpoJ7ugASwh5oRdwtDIGG2DraiVuRGRrh9+wD37fjSPbm3UZcTonlvGbF3xeDGznzp2W7du3B19wwQUlzRqHOI4kEkIIcZp5KhE783didsRQduAWEruEATAj4890zMsjMDKAsK6FYImGLklgTcIGTL1nSOsG30YUFhaarrzyyt7z5s075L2yp2h+kkgIIcRp5kki4iPi6f6JYuSOl2oSiYr8fAI7OigZdzkbcvuRm/stHCrBElqCrau1lSM/CSdROWhulZWVavLkyb2nTZuWP3v27KOtFcfZQhIJIYRoQXVNde1pzig7cAtJG/9GVNFhsNqgNIfADtWEJUeywW86uY4SMP8MtJHmjDOAy+Ximmuu6REXF1fx6KOPZrd2PGcDSSSEEKIFff/p+0TuLCDYP5iQwiqCS6oZ5gpF61LM6m8UdqhkfVRXTGGBlFujwGSGIn+qN76Gf4AZ7czBHttTmjR89MUXX1g/+OCDTn379i1PSEhIBHjssccyZsyYUdjasbVXkkgIIUQz865C2NMKCC/yp8LaheCig1iqNeXmAMwmCDYbTfd+AVUcrexAtQ7E32LMWOlvhqBQCyEdetLv/Atb66G0OZdeemmJ1np9a8dxNpFEQgghmtnKvSuJ/GIzF6WZ2RMQjtYOkrMPE5VzmCx7dxZNu48rkmMYtOZFdh3uDpYQysrsRNth6qOTWjt8IU6KJBJCCNFMlu5ayqKNy0kv28Ojm6HzEQe7exrVh8QuYWC1Edsjj4mWJ2E7LD88mVxHLLbuUdhA+kCINkkSCSGEaCYr964kvWwProoumHUhWfYO5ERGY7MG0GP+s7BwMmSlAUnGAZYQbB1lSKdo2ySREEKIk1DXKIwjRZXkllZy/qZfeXiLiRCl6FVYRmBCd4pCy6DkANv+cT+7Dk8Gy3SwGIlErqMEW2gbGtIpRB1MrR2AEEK0JZ45ILzlllZSVulg9DYzPXMddLIGEJiQQNiUKVCSA1Wl7MrtR64jFkLsNcfJkE7RHkhFQgghGuGpQgz6LpvLfzxEsF8QCRHOmvu3ZzoBRa9CM4E9O1Fybk825PaD1HJySzqBqTMWR09svazSjCHanVZJJJRSdwO/BTSwBZgLBAMpQCywH5iutS5ojfiEEAJg8+pV7Ph2DTvzdxJZXUbAEU2+JZK8oACyqouodrqodrpwWsFsgiO2aPz8Kji65TDVOh9/czVVjmIsQXapPpwmZWVl6pxzzkmoqqpSTqdTXXbZZQXPPvvs4daOqz077YmEUioG+B8gUWtdrpRaAlwDJAJfaq3nKaXuB+4H7jvd8QkhhMfaL5ZSeTCLTlWV2JWJwCowhVgJ7JcAwN7DRZRVOYkxFxLgdFLitILLacwHEWTB1i0CiKTf+RcycJxUIk6HwMBA/c033+wMDw93VVZWquHDh8d/+eWXhWPHji1t7djaq9Zq2vADgpRS1RiViMPAA8CF7vvfBNYgiYQQohXlV+TTqaqS837NoqBrFJUVVrZ0O4f1URcCsF0XkdgljKcsT7J8o3soZ3AOhNiJGzuI/qNjWvcBnIVMJhPh4eEugKqqKuVwOJRSqrXDatdOeyKhtc5QSj0NHATKgc+11p8rpSK11pnufTKVUp1Pd2xCCFGQsoSiFSvIKc8hwlVFYLUiImkI80bdzvbMoprFtQDuDP+GKyq/g/zdYJmOrXsUU++RCaUAHv724W57CvY06zLifTr2KXvi/CcaXQzM4XAwYMCAxIMHDwbMnj37yMUXXyzViBbUGk0bHYErgJ7AUWCpUmrWSRx/C3ALQPfu3VsiRCHEWaxoxQoq0tLI6wwEhFLp709KWL+aJCLl1nMB2LYug10f9eG7qi5gCSG3MgZb64Yu3Pz8/EhLS9uem5trnjx5cu+ff/45cPjw4RWtHVd71RpNG+OAfVrrHACl1H+A84BspVQXdzWiC3CkroO11q8CrwIMGzZMn6aYhRDtnKcSUZGWRmBCAv+eaabzB7m4KqM5OPBCEoErko81Vez6KZvcMju2YCAqSWamrMWXykFLs9lszlGjRhV//PHH4ZJItJzWSCQOAiOVUsEYTRtjgVSgFJgNzHN//7AVYhNCnKWKVqygYOsm9tn8+D4inQ1ZJVyiOxNsMR9XhVj+6EoozTGSCL/9TE38BObObuXohcfhw4f9LBaLttlszpKSErVmzZqwP/3pT1mtHVd71hp9JH5USi0DNgAO4BeMCoMVWKKUugkj2Zh2umMTQpwdvp/3JLs2ph63zVVWRlnPzuzvrDBVBjDhhxA6lpgIiQqo2WfXT9nk5oDNrxRbMMTZDkLS1ac7fNGAQ4cO+c+ZM6en0+lEa62uuOKK/GuvvVaWEG9BrTJqQ2v9CPBIrc2VGNUJIYRoUdvW/0SpdmBxmdA40TjAD44Gg4kAhnTpT+nRKsodVVj9+rF8/gYoznInEfuZmvwJzP2ktR+GqMM555xTvmPHju2tHcfZRGa2FEKcdaqdLswuE2smPsh+y9NUqEME6m4AjIm+hBmX3sry+RtwppcQ1tm9FkZpDja/UuKipQohhDdJJIQQZ43VC+7D+dlX+JtCcfmbCO7xKub8TIZE9GfhhIXH71ychc0vh6kRS4yfq7ZAVJJUIoSoRRIJIcRZw/nZV3RKL2Z373CKg41/f/ER8UzqNckYzvlTds2+nr4QNaKSpBIhRB0kkRBCtGueKgSALb2Eg52D+TW0J71sISyc8KyxU+pCln+02j2cM8fY19OMIRUIIRokiYQQol2rWPlfojJLONQ5mIOdg/i6RyLhZj86hwUcq0Jkmcgt6YTNmsPUxCXHDpYKhBCNkkRCCNFueJb7Bhj0XTb91ucSlVnCflsQS6/+V81+/Te/AJkH2OWpQviVYrNC3OXjYLTMCSHEyZBEQgjRbizauJygtHR6Hw7H/0g1h0yh7O4dTmmwlSuzjs1xl1VQRJWpExaz0ZQxNfETo/owTBbZag8cDgdJSUmJUVFRVV999dWe1o6nvZNEQgjRZtWuQNz4/UEyQ7tQbdYEVkOVfxA59u7YrAFQnAUlRv8HP1MnCEjC1iuKuBGDpArRzjz55JORffr0KS8pKTG3dixnA0kkhBBt1sq9K9mZv5P4iHj6/JRDVLYmO9SPCLMfF3aIIGzKFDrOmG7svHAyZBlDOJdvHwshdqbeM6R1H4Bodr/++qv/Z599Fv7AAw9kPvvss7L4yWkgiYQQos3wrkAARH6xmWvSzCREOMnPdLIrNBZnzzgCwwLo8cg8Y6fUhbBlGdt2R7Cr+gmwJJHrKMEWam2lR3F2OPyXB7tV7t7drMuIB/TtWxb99781uBjY73//+27//Oc/0wsLC6UacZqYfN1RKdVRKdVfKdVLKeXzcUII0Vw8FQiPi9LMxGRVA5Bl786B5FF0Dgs4/qAtyyBrC7uqx5FbafSBsHW1ykqd7dB7770XbrPZHKNHjy5r7VjOJg1WJJRS4cDvgWsBC5ADBAKRSqkfgBe11l+1eJRCiLNO7eoDUNOM4ZmF8qeXZ3CoYyWLRt3O9swiEruE0WP3K0ZfiIWTAWoqEbmOnth6WKU54zRprHLQEr755hvrF1980SEmJia8srLSVFpaarriiit6fvjhh/tOdyxnk8aaNpYBi4HRWuuj3ncopYYC1yulemmt32ih+IQQZynv/g9gdKa8Zr2DTkFZHHjnBgD89+2mNCwagMQuYVyRHAO/5EBVKRACUFOJsPWQKkR798ILL2S88MILGQArVqwInT9/fqQkES2vwURCaz2+gfvWA+ubPSIhxFnLuwpRtWE/E7IjiY8w3vyLd+SRbgpnr8sMpfkAOHtGUxESZgztLM6CX3LIKjTh59+T5fl3Ahj9IaQSIUSL8amzpVJKATOBXlrrx5VS3YEorfVPLRqdEOKs4l2FGLIrGHNZFRXZaQCoinLKzQHk2Lsfd4zN6u4TUWJUIvz8e4Jl4LH7pT/EWWnKlCnFU6ZMKW7tOM4Gvo7aeBFwARcDjwPFwPvA8BaKSwhxFqjdD8K7D8Sbi36Ds7yMzuX+AJRWBpA38Hwee+GBYydwj8gAwOIe2umuREgFQojTw9dE4hyt9RCl1C8AWusCpZSlBeMSQpwFaveDmJ7WgVHbjT4QrrIyKv0t/Hno7SR2CQMw+kB4qxnWOQ6YDpV2cgtLsHWVoZ1CnC6+JhLVSikzoAGUUnaMCoUQQpwS71EYB965gYoDaWTHhFHhZyHfYiWxSxgpt55b7/G7qscZIzLcyYMtFGnKEOI08jWRWAAsBzorpf4GXA081GJRCSHaLe/mDE81oiBlCUUrVlCRlkZgQgJ/HXU73X9YRLDFfFwVYtvbS9m1yWuKgKrJ5Drs2HpJZ0ohWotPE0tprd8B/gz8L5AJ/EZrvbQlAxNCtE/ek0rFR8Qzqdek45KIsClTAAi2mEmMDuO6c451rty1qYzckk7HTmYJwWaXCoQQrcnXURvPAyla6xdaOB4hRDvTUIfKgpQlFD3xMRVpaRTG9OSvo26Ho7A9s4hznfmUHsxl+b1v1hybW9IJmzWPqU/JIltCnCl8bdrYADyklIrDaOJI0VqntlxYQoj24vtP3ydyZwHB/sayCz2JJCLQRMqP91OxIw1XWRmm3tHkmM01zRkJgKmsmHJTJ5xlxlLfADZrHnGDmnX5BtHOxMTEJIWEhDhNJhN+fn5669atO2rv88c//jHaarU6H3/88ezmvv6CBQs6XX755UWxsbHVDe23c+dOy5QpU/ru3r17W3Ncd8aMGT3+/Oc/Zw8dOrTiVM6zYMGCTqmpqSGLFy8+6OsxPiUSWus3gTeVUhHAVcA/lFLdtdZ9mxirEKKd81QiIncWEFFsoUef+OPuP1JUiV+VA/wsZIVHU1blNJozQsuMOSECS6kIGEZYryim3jOplR6FaIu+/vrrXV26dHG0xrXffvttW3JycnljiURzcjgcpKSkHDhd16vtZBff6gMkALFAWrNHI4RoNzx9IYL9gwmO7syMR+Yx45F5XJIwhJF7DtNn0z6G784gtsiPtCHXU9VnFtFdZmFRF2EJmIyl01yq/Ee39sMQZ5GHH344csCAAf3i4uIS77777mjP9nHjxvXu379/vz59+vR/+umnbWC8eV911VWxffv27R8XF5f42GOPdV64cGHHrVu3Bt9www29EhISEktKSpT3+detWxccHx+fmJycnPDMM8909mx3OBzceuutXT3Xfuqpp2xgTPM9bNiw+PHjx/fu3bt3/+uuu6670+kEIDg4ePBdd90VPXDgwIQvv/zSOmLEiPi1a9cG/+Mf/7DfdtttXT3nXrBgQafZs2d3A3jxxRcjkpKS+iUkJCRed911PRwOI9d6/vnnO8XGxg4YPnx4/HfffXfSY6d97SPxD+BK4FdgCfBE7bU3hBBnt/r6QnimuAZ498eDdHztXaJyDlIaFk0Hm5WR/fOYaHmS5Uenk1tmB79SsIRAVBI2pCNlW/Xl4h3d8jNKmrUdKiLGWjb2hn6NLgY2duzYvkop5s6dm/OnP/0p15dz/+c//wnbs2dP4ObNm3dorRk3blyfTz/91Dpx4sSSd955Z39kZKSzpKREDR48OHHWrFkFu3fvDsjMzPT3NE3k5uaabTab86WXXur89NNPHxozZswJK5DedNNNsc8+++zByZMnl9x66601b/bPPfecLTw83Ll169Yd5eXlavjw4QmXXXZZEcCWLVtCfvnll61xcXFVY8aM6bt48eKOc+fOLSgvLzcNGDCg/LnnnjsM8PDDDwNw/fXXF4wcOTIBSAdYtmxZxIMPPpi5YcOGwGXLlkWkpqamBQQE6FmzZnV/+eWXO1122WVF8+bNi16/fv2OiIgI53nnnRc/YMCAk1o91dc+EvuAc7XWPr0gQoizT+3JpTwjMqo+XoUjL48D199Ax8wi7NkHyIrswdJp97Gg8iEOZ0WzZvs4ct19IaYmfgJJV8MwGc4pTt63336bFhsbW52RkeF38cUXx/Xv379i4sSJJY0dt2rVqrC1a9eGJSYmJgKUlZWZ0tLSAidOnFjyj3/8I/KTTz7pAJCVleW/bdu2wIEDB1YcOnQoYPbs2d0uu+yywqlTpxY1dP68vDxzcXGxefLkySUAN954Y95///vfcIDVq1eHpaWlBX/00UcdAYqLi83bt28PtFgsOikpqTQxMbEKYPr06fnr1q2zzp07t8BsNjNnzpyC2teJjo52dOvWrfLLL78M6d+/f8XevXsDx48fXzJv3jz71q1bgwcNGtQPoKKiwtS5c2fH2rVrQ0aOHFkcHR3tALjyyivzd+3aFXgST3mjy4gnaK3TgJ+A7u41NmporTeczMWEEO2PpxJRe4nvd388yLKvMrgwMxtLdSXby6G00gGRPRh583VM7J0GK1L5rnqBMaFULytxIwbBaBmR0R74UjloCZ6+CTExMY7Jkycf/f7770N8SSS01tx1112Z995773EfmFesWBH69ddfh6ampqaFhoa6RowYEV9eXm6y2+3OrVu3bl++fHnYiy++2DklJSVi6dKl+xs6v7FsVZ33qfnz5x+86qqrjktGVqxYEVr7GM/PFovF5edX91v41VdfXfDee+91TEhIqJg4cWKByWRCa62mTZuW51kd1eOtt97qUF9cvmqsj8Qf3d/n1/H19CldWQjRLngnETN3debA9TcY1YcH/4dpb/8NS3UlVf4BLJp2H0tnPUjB3xZwOPp8lqeYWJ73hLHEd1djQqn+o2Mav6AQ9SgqKjIVFBSYPLe/+uqrsIEDB5b7cuzEiROL3nrrLVthYaEJYN++ff4ZGRl+R48eNYeHhztDQ0Ndv/zyS+CmTZtCADIzM/2cTidz5sw5+uSTT2Zs2bIlGMBqtToLCwvNtc9vs9mcVqvV+dlnn1kBFi1aFOG5b/z48YUvvfSSvbKyUgFs3rw5oKioyARG00ZaWprF6XSybNmyiNGjRze6ENmsWbMKVq1a1XHp0qUR1113XT7AhAkTilasWNExIyPDDyA7O9u8a9cuy5gxY0p/+OGH0KysLHNlZaVavnx5R1+eL2+NLSN+i/vmRK31cUNKlFInVfoQQrQ/S3ctJTU7lWGRw1g4YaExxbV7YimAkAA/SkP8COzU6dg016kLWf6RyT0nBNiiIqQfhGgW6enpflOnTu0D4HQ61VVXXZV39dVX19nk8Oyzz3Z55ZVXan7xsrOzN2/bti1w+PDhCQDBwcGud955Z99VV11V+Oqrr9rj4uISe/fuXTFo0KBSgP379/vfdNNNsS6XSwE8/vjj6QA33HBD7p133tnj3nvvdaWmpu6wWq3ac4033nhj/29/+9vYoKAg18UXX1wT19133527f//+gKSkpH5aaxUREVG9cuXKXwGSk5NL7rnnnq5paWlB55xzTvH1119/tLHnwW63O/v27Vu+e/fuoIsuuqgMYOjQoRUPPfRQxtixY+NcLhf+/v56wYIFB8eOHVt63333HR45cmQ/u91ePXDgwDKn03lSJQqltW58J6U2aK2HNLbtdBs2bJhOTZXpLIRoLXNXzSU1O5UrU4cTvzeXclM5Vf4BZNm71wzntFflYY/tyYxH5hkHLZzM8o2TwRLC1BkuGDa3dR/EWUgptV5rPay5z7tp06b9gwYNkr50zWTFihWh8+fPj/zqq6/2tHYsmzZtsg0aNCi2rvsa6yMRBcQAQUqpwYAnSwkDZFYYIc4ydY3MCHbFkbTxCIUdKikKDMBpMVbq7KBMBFeBMtupyO90bIbKqsnkOmKxdY+SDpVCtAONjdq4FJgDdAWe8dpeDPylhWISQpyhFm1cTvx32xm97VgTsNORQ++iEjbHdCe6X0JN5WH5/A3kpruX9M7aAlXuYZ2WEGwdZVinEI2ZMmVK8ZQpUxrtE9HaGusj4ZnR8iqt9funKSYhxBmidgUivWwPc7eYiM3VZNndg7jMkJF4McWWTEoOlbB8/gYoziI3B2M4Z8QSqNoCUUkw95NWeiRCiJbi6xTZ7yulJgP9gUCv7Y835aJKqQ7A68AAQAM3AjuBFIxZM/cD07XWJ4yRFUKcPiv3rmRLzg7MDmM0hauyCxZVSMTA7gx+a3HNfsvnb8Cx8TX8PRtKc7D5lRJnc0/XH5VkzA0hhGh3fJ3Z8mWMPhEXYSQAV2PMLdFUzwOrtNZXK6Us7nP/BfhSaz1PKXU/cD9w3ylcQwhxCjwjMiZusDNiQyVO+yBKQuMp6lzJd4EhbJh/bBqZ3PQS/P2c2PwOMjXiYalACHEW8XWtjfO01jcABVrrx4BzgW5NuaBSKgwYA7wBoLWuck+3fQXgWS/4TeA3TTm/EKJ5LNq4HIARmx30LjqMq1N/HIGdMYeE4Nep03H72rpaCTIdNfpBgFQghDiL+DpFtmdCjzKlVDSQB/Rs4jV7ATnAQqXUIGA98AcgUmudCaC1zlRKda7rYKXULcAtAN27d69rFyHESardF2LQd9nc+P1BtMtC7/wSDvaOJV9/B04wdbPiAqpKgOIsY6VOoKzMRUh4iFQhRKuqa3nuxpYNb8rS2eIYXysSK9z9Gp4CNmD0Yfh3E6/pBwwBXtJaDwZKMZoxfKK1flVrPUxrPcxutzcxBCGEN8/slB791ucSxLkc7XoHaSP+xKFQOxUlmSceWJJTU4Wwh5voN1yGcwpxtvG1s+UT7pvvK6VWAIFa68ImXjMdSNda/+j+eRlGIpGtlOrirkZ0AY408fxCiEYUpCyhaMWKmp+vytlBtdNFoLt/c+ccBz8PHEW5tRudenVA7fiOQP8uXDj7geOnsV44GZAqhGgbRowYET906NCSb775Jqy4uNj88ssv758wYcJx63D8+9//Dp83b16XTz/9dM8dd9zRNTQ01Llp06aQnJwc/yeeeCJ97ty5BS6Xi9tvv73rf//733CllL733nszb7755oJZs2Z1nzhxYuHMmTMLx48f37tDhw7OpUuX7n/22Wdt+/bts/z+97/PnThxYt8RI0aUpKamWiMjI6s+++yzPd6zX7ZFjU1IdWUD96G1/s/JXlBrnaWUOqSUitda7wTGAtvdX7OBee7vH57suYUQvilasYLi7VvIiDLGWVQ6yym1jiY/zJjG+nAMVAVFEWgPZOo9Q0h5bAmAkUSkLoQty4wTZbk7VQpRy2cvPdct99CBZp240NatR9mlt991SouBORwOtWXLlh0pKSnhjz/+ePSECRN2ee5bvHhxh+effz7yiy++2G23250A2dnZ/qmpqWkbN24MnDp1ap+5c+cWLF68uMOWLVuCduzYsS0zM9NvxIgR/S655JKSMWPGFK9duzZ05syZhVlZWZYjR45ogG+//dZ67bXX5gMcPHgw8O2339573nnnHZg0aVKvxYsXd/zd736XfyqPqbU1VpG4rIH7NHDSiYTbncA77hEbe4G5GM0sS5RSNwEHgWlNPLcQwkvt6gNARVoaGVH+PDbTj45+sezNLeGavZcS7YwwJpByq3PSqC3LjiUQ0qlSnGHqW8nSs33atGkFAOedd17pvffea/Hc/91334Vu2rQp+KuvvtoVERHh8my//PLLj5rNZoYOHVqRl5fnD7Bu3brQ6dOn5/v5+dGtWzfHOeecU/LNN98Ejx8/vuSFF16IXL9+fWBcXFz50aNHzQcOHPBfv359yGuvvXbwyJEjfjExMZXnnXdeOcDgwYPL9u/fH9Byz8bp0diEVC0yCb7WeiNQ1zzvY1viekKczYpWrKhZSCunPIe88jwKe47gkG0Ql28LwVkZzYDyauxmf2w9jFU461ScZTRlZMnQTtG4U60cNFVkZKSj9uqb+fn55p49e1YCBAYGagA/Pz+8F6fq3r175cGDBwO2bt0aOGbMmDLPds/+YCwF7v29tp49e1YXFhb6ffzxx+GjR48uzs/P91u8eHHHkJAQV8eOHV1HjhzBYrHUHGw2m3V5ebmvfRXPWD49AKXUX+v6aunghBAnpyBlSc0y3p4vTxLR463FvPDbKB68xsSWHudgUl2prAymrNJBWJA/XXqENTxtdUnOsSRCqhDiDBUeHu7q3Llz9YcffhgKxnLZa9asCb/44otLGjqua9euVe+///6euXPn9kxNTW1wdesLLrigeNmyZREOh4PDhw/7/fTTT9bRo0eXAgwdOrTklVde6Txu3LiSCy+8sOSFF16IOueccxq8dlvn6/DPUq/bgcAUYEfzhyOEOBXe1QeP4h6d+LRnLptWzWVn/k7MjhhcFV0oC/Jje98OAFyRHMPUc2oNp/buC5GJMTpDKhGiDXjzzTf3/e53v+t+3333dQO47777Dvfv37+yseMGDRpUuXjx4r0zZszo/dFHH9W74ub1119/9LvvvrP269evv1JKP/bYY+ndu3d3AIwaNapk3bp1YQMGDKisrKysKiwsNI8ZM+aMXy/jVPi0jPgJBykVAHyktb60+UPynSwjLsQxBSlLyHrkEYKHD6eH1/TVk5dcR3rZHpKyL6Vnbhz+hYcIKT1IYJAftm7W+k+YeWyhrZxisIfCjN9eLct+twOyjLg4WU1eRrwBwRgTSwkhzhCeDpW7h3fh0VXH3uzTy/bgquhCv5yxWMtdVFV8C64cgkJ71H0izyRTntU6uyRh7wL9zr8Qhk04DY9ECNGW+LrWxhaMURoAZsAONGnBLiFEywkePpxnow6RnnWsAhHtugiLCqOz04StVxhVJR2ADjXLfZ/Au0NlklQghBAN87UiMcXrtgPI1lo7WiAeIYSPag/r9MwLkV7GcRWIkiATNqsFW2ggcSMi2frfek7o6RMhozJE07lcLpcymUxteoIlcTyXy6UAV333+zqz5QGlVEeMhbr8gEj3hFQbGjlUCNFCanes3N77fPeQzkD8dGhNBaL2cM56EwnvJEJGZYim2ZqTk5Not9sLJZloH1wul8rJyQkHtta3j69NG08Ac4BfOdbEoYGLTzFGIUQ96ppIyltFWhrFPTrxx8sc5JZWMm77GGxlMbgq/PEL8MPW1drwcE6oe5ZKqUSIJnI4HL/Nysp6PSsrawC+r+UkzmwuYKvD4fhtfTv42rQxHeitta5qlrCEEI2qayint8CEBD7tmWt0pqzsgokAioIq2dO3Q93DOesis1SKZjR06NAjwOWtHYc4vXxNJLYCHZCFtIRodvVVHrwnkoLjl/oO2BGL/XAvXOWVTNliIVh1N5oyulp55NY6ZqasPScEyCyVQohm4Wsi8b/AL0qprUDNpB5aa8k8hThF9VUeAhMSCJtyrJ/zyr0rqdqwn/jsDgQU7MfPmYHDXI3CjL/ZQpXZREG6pWaBrePUMScEIFUIIcQp8zWReBP4B7CFBnpuCiF8412FqF158KipQKz6lIAdsUQfPp+wbDBXFaHMAbjMENu7gT4QnvkgoO45IcbJnBBCiFPnayKRq7Ve0KKRCHEW8a5C1K48eKzcu5Kd+TuJj4jHfrgXHUttODCjLXYqO19D9MBOzLihgSW8vZsuCJE5IYQQLcLXRGK9Uup/gY84vmlDhn8K4aPGqhDefSAAKrdYGXvkdgJ1N4JKnZSHmOkTaQNgxiMXnngB734QIP0fhBCnha+JxGD395Fe22T4pxAnobEqhHcFAqD3kRF0LI2kPBjKQ8xED+wE+xq4gPcIDJD+D0KI08LXCakuaulAhDgb1NUXwlt8RDwLJywE4G+r11AeDA8+fWHN/SmPNXIBqUAIIU4zXyek+mtd27XWst6GEI3wNGl4j8yo3Yxh29+XbvtGEewXxCs/fEduSVVNc0aD6ppQSgghTiNfmzZKvW4HYqy9saP5wxGi/fFOIjzNGd7NGB13ltN5wx5Mzv2YLYoix1rMLo3TpLDiT8pjq2rOlbN/H/bYnsdOLhNKCSFama9NG/O9f1ZKPY3R8VII4aWuyaW8O1YuXvYRhx98l26OUcT7jSc+IoHDO/6PispMXBY7Rf4myrST4CAzidFhJ5zfHtvTGLoJRjXiwDfQY5Q0ZwghWo2vFYnagoFezRmIEO1BXZNLeVciDv9SQsDRcOgAEUGdavZxWez8HHUlqrcxU9QVyTHMaGyKa0+ThlQhhBCtyNc+Els4tliXGbAD0j9CnPVqVyA8SUTJLf/Lrp+yAcgpzyF/cx5sfpeAo+FUdiik++Wj+HBjBlBJgtlFmVmjeoeScuu59V+sruGdPUbJ3BBCiFbl6+psU4DL3F+XANFa63+1WFRCtBGeCoSHp/qw66dsctNLAMgvz6PMUQ5AZYdCogdb+XBjBtszi2qOC7aYuSI5puGLefpDeEifCCHEGcDXpo0uwDatdTGAUsqqlOqvtf6x5UIT4sxTXwWi9sRSO37ZQbWfi9cjPqCi0yECdTdiq/4EwC95sD2ziMQuYaTcei4pj30IcGJThkwwJYRoA3ytSLwElHj9XObeJsRZpb4KhMe2dRn8+mY11uIOuFxGa2Cg7ka4c8Rx50nsEiYVCCFEu+BrRUJprT19JNBau5RSTe2oKUSb0VgFwnthLYD4deMJOBpOfnA+JR168uPc9327UHGWsTaGN6lACCHaAF+Tgb1Kqf/hWBXid8DelglJiDNH7VEYdS3tvTN/Jx39Yum4rzeheVFkhWbwQdReEq19jjvX5tWr2PHtmhOukbN/H/aAkhMnlJIKhBCiDfA1kbgNWAA8hDF640vglpYKSogzSZ2La60yRkp4JpUqO3ALPdKNeduKOsSSaO1zQtPFjm/XHJtQymuJb3sA9AvJkOqDEKJN8nVCqiPANS0cixCtqqHJpMDo/7Drp2x+za8mpvp8lA6gKxfjp0Opqiyls8tEdN8O/P6eIfVewx7bkxmPzKu1xDdAjFQfhBBtUoOJhFLqIeBFrXV+PfdfDARrrVfUdb8QbUljk0l9+/VWyrM0ZSHlKB2Aq6ILwQHGn5BfAARaLcSNiGz8QjIjpRCiHWmsIrEF+FgpVQFsAHIw1troCyQDq4G/t2SAQrS02otq1bc6Z1ZJLpVB5axO+JSy/IEkWvs0PIFUfWRGSiFEO9JgIqG1/hD4UCnVFzgfYz6JIuBt4BatdXnLhyhEy6q9qJanCSOnPIf88rya/azFHagMdBrzQVg5cfhm7Xkfast0f7fIjJRCiPbD1z4Su4HdLRyLEKdFY0M618zfQOaBIjIDjuCiEhMBABQH5nHE5qi/CuG9EmdDZDSGEKIdabW5IJRSZiAVyNBaT1FKRQApQCywH5iutS5orfhE+1XXkM4jQ65iw/wN5JTnUJ6lyQ3KYbv1NfpkhhOouwHG7G0DCSDlsfuNE3mNvACgqhQsSVBVdyKRU+kesTF3Xks+PCGEOK1ac1KpPwA7AM9ayfcDX2qt5yml7nf/fF9rBSfaF+8qRF19ITbM30Buegn5wXmUhZSzL2I/ffaFE1nuR0yvE5fzBowkoqoULCHGz5YQsNrrjeG4JcCFEKKd8HX1z/O11t82ts1XSqmuwGTgb8Af3ZuvAC50334TWIMkEqKZeFchAhMS+LnPcN578F2qnJpqp4uIMhv5wbl81Pf/Eai7UXbgFnrrPGJ6hRnDNb15+kJYZOZJIYTwtSLx/4Dag+Pr2uar54A/A6Fe2yK11pkAWutMpVTnug5USt2CezKs7t2717WLEEDDVYj3HjSW9C4Nzsfl0uQH57LPtqtmXYzYLmHYigPqPrF3Xwjp6yCEOMs1No/EucB5gF0p9Uevu8IAc1MuqJSaAhzRWq9XSl14ssdrrV8FXgUYNmyYbmR3cRbzVCEKY3qSFx7NlrB+rH/lewDiqpyUBufzQUjnmlU4a/OsylknqUQIIQTQeEXCAljd+3lXD4qApn4UOx+4XCk1CWNOijCl1NtAtlKqi7sa0QU40sTzi7NYXVWIFxNuxpqbg8mvlLg9ewDoWBZBQXC+b6tw1rectxBCiEbnkfga+FoptUhrfaA5Lqi1fgB4AMBdkfiT1nqWUuopYDYwz/29gY+DQtRt93vv479vN1n27uCuQlizKrG5giiwFBDsFwRAlaWQvoPDeeJqHyaUqj2sU5o0hBCihq99JAKUUq9iDM2sOUZrfXEzxjIPWKKUugk4CExrxnOLs8Q+Ux8KB04iJ7IHAA6OYiuvJi8kg4yLvmXhhIWNn8RTgfCeQEqaMoQQok6+JhJLgZeB1wFnc11ca70GY3QGWus8YGxznVucPQpSlrD7vffJK6mk0j4JZ6DR7wFgZ/5hSspSCSncy9Cvgkj58f7GT5i5BapKyakMwR6KVCCEEKIBviYSDq31Sy0aiRBNsG1dBptXO3AEjaM81IIzsDM6sIiP+i8BjGW+J/wYSWi5BXtwPXM81DmxVAj2HknGvA/jJrT8AxFCiDbK10TiY6XU74DlQKVnY32rggpxOnw272XSdwRT7d8Jk181OZE9SOwSxnchv7AzfyfxEfHER8QTEWjCHmE/cT4IjxOW9A4xKhCyFoYQQjTK10Ritvv7vV7bNNCrecMRwneu1avwt08C8sgLO8zR8RV8pH+oSSI8/SHqbM7wHomRJX0ghBCiqXxdtKtnSwciRGN+fvZD9mwvrfnZYZ9MqbUrUQmR3HTPDcxdNbcmiZjUa1LDJ/MeiSF9IIQQosl8nSI7GGMq6+5a61vcy4rHa61XNHKoEM1mx5Ziykwd8a82lvZ2+lmoNldS3COduav+3wmViOMUZxlNGB5ShRBCiGbha9PGQmA9xiyXAOkYIzkkkRAtpnYFoszUEVNlLp+PiqvZdkVyDF8UPNJ4JaIkR+aCEEKIFuBrItFbaz1DKXUtgNa6XCmlWjAuIdizvZQiHU6Qq4BqpwuTK5cSazUpt57L0l1LWbl3JV8UcHwlInXh8ZUHMOaDqCqVCoQQQrQAXxOJKqVUEEYHS5RSvfEavSFEc/FMcX3AL478gPOIcGbxbddCgg5tJjjQjC04gJTH7mdn/k4iq8sI9g+mJ5FEBJqMTpXuOSBqlvYGcorBHhoiFQghhGgBviYSjwCrgG5KqXcw1suY01JBibOXZ6Gt/UmXAJDpV0bQoc3YqnIJ6dyB/IpMCvKhrKqUYCC+sso4sDILCrOOJRFdjq2FYe+CMR/EMJkPQgghmpuvoza+UEptAEYCCviD1jq3RSMTZ63AhAQORXSlrNLBngH9SdiwgeCI7qy/6Cg787OJj4iHrENMKixgWlhCraNlDgghhDidfB21MRX4r9b6E/fPHZRSv9Faf9CSwYn2z9OUkV1cyT5TH6oCRlNlCSCo1AkhfqTcei7/uu918isya5KIhbYx8MN/oMco6fMghBCtzOTjfo9orQs9P2itj2I0dwhxSjxNGXkllRSGxFFi7UppUBjlIWaiB3YCIL8in7LqsmOjMjwTSUmfByGEaHW+9pGoK+Hw9VghaioPtVWkpZE94HI2dBqFtdxF914dmHrPEACW7lrK3FXP1HSqXGgbA98uMoZx9hglzRdCCHEG8LUikaqUekYp1Vsp1Usp9SzGvBJC+MRTefCWXVzJ3vBoNgYMIKjUSUmQibgRkTX3r9y7kp35Own2DyYiMOL42SilGiGEEGcEX6sKdwIPAynunz8HHmqRiES7U5CyhLKffyZ4+HB6vLUYgIXv/I20dT/g0hpb2YcAlJvyeX+ZifeXAY4qIl2V9MRKRFEV9tAsmY1SCCHOQI0mEkopM/Ch1nrcaYhHtEOeJo2wKVMAePfHg6St+4GIIsDPjp/LH5fZgcXPq0DmqibYpYlQJuyh0C8aqUQIIcQZqNFEQmvtVEqVKaXCvTtcClGf2v0hKtLSCB4+nI4zpgPw4cYMumsNfnZCO8ymS48w4kZE0n90zLGTLJwM+Ev1QQghznC+Nm1UAFuUUl8ANYsfaK3/p0WiEm2apz9EYIIxx0NhTE8+DOvH+le+p8C8lg45RXQq74Sfy58uEWVMjXgK9mB8eXiviyGEEOKM5Wsi8Yn7S4jj1DUaw5NEePpD/PmV79meWUQiUGj+ieGFE/F35WC2KOKC1tadNEgzhhBCtAm+zmz5pnutje5a650tHJNoQ2pXH7KLK8kLj+aHDn6sWngVAD1yEvhNaQIhB/OId0yiU3kMfv4/YbOk09/1qXSgFEKINszXmS0vA54GLEBPpVQy8LjW+vIWjE20EXVVH4J7vEqFOkSg7kZ8YQKdym1UWAoI9gsiKErht+/osRU5pfIghBBtlq9NG48CI4A1AFrrjUqpni0Uk2gDPE0a3tUIjy5dN5Jp2sWwyGEsnLCQ5fM3ADD1nonGMt9bFpCy1724llQihBCiTfM1kXBorQuVUt7bdAvEI9qI3e+9j/++3WTZu7PV0pGSW38HQPcqJ/1MhQRWDyHQz8ILy+6gutKJf4CZlMeW1CzznVMZgj3C3sqPQgghxKnyNZHYqpS6DjArpfoC/wN813JhiTNN7U6V/vt282tYNK9ecy6DU7+hQ7HmaKjCFACBZRH4uwLwN/kb+/o5CdJ5kLmvZplve48kY2lvIYQQbdrJzGz5IFAJvAt8BjzZUkGJM493BQKgNCyavQPPZ5DDSURZJ0x+Jjp2MuYsC/KLIChKcctDlxoHL5zsNTJDlvkWQoj2pMFEQikVCNwG9AG2AOdqrR2nIzDR+ryrEJ4KxNJp91FgXkuh+SdsIVsYun4sfq79BAZaiI5w95WIgLjIX92TSiFTWwshRDvWWEXiTaAaWAdMBPoBd7VwTOIMUbRiBUXbtpMe0bWmApFy67nMXfUqUdtiSNwzkqDSCLRFYetmrVm1E4CFDx9LIGRkhhBCtFuNJRKJWuskAKXUG8BPLR+SaC11TW2dHtGVP4+6nS5dN+Iftokdq+ayM38nl+ffQaeyrth6WilIDzl2ktSFx6/SKVUIIYRo1xpbRrzac0OaNNq3d388yA+vvUv+5q1szyxie2YRe8Oj+SxqEIldwojpmkaBYz8A8RHxRAR1wtbVqEKEdLAcO5Es9S2EEGeVxioSg5RSRe7bCghy/6wArbUOa9HoRIvzVCE6ZhZhzz5AVmQPFnn1g+h7xEX/fXtx7B1FvN944t39IHLzSqCr14mKs47vVCmVCCGEOCs0mEhorc2nKxDROjyTShEeTU5kD0befB0TZxj9IOwb8hm0MwOTMxuX2YG/2Z/D2cdG/RakW0h5bAk5+/dhDyiRSoQQQpyFfB3+KdqZd388yIcbM5iTWQTh0fx54mAGORxs2uyAze/SzTGK0CyFqbKQQGsXbN0i6j5RcRb2gBL6hWRIJUIIIc5Cpz2RUEp1AxYDUYALeFVr/bxSKgJIAWKB/cB0rXXB6Y7vbJG++B2mbf6WqKLDZNm7ExyxmdgdEwkqi6A8PJ9gvyD8zf74W7tw4ewH6D86pu4TeTdnSCVCCCHOOq1RkXAA92itNyilQoH1SqkvgDnAl1rreUqp+4H7gftaIb52790fDxK79VOCA+PZ0Ps3lIX6c2mag05lMXTv2Zmp90wAIOWxzQBGEuEZjVGb9IkQQoiz2mlPJLTWmUCm+3axUmoHEANcAVzo3u1NjAXCJJFoRsd1rCzI45fBwyizdqU8LJ9g/AmKUsSNiKz7YO/RGN6kEiGEEGe1Vu0joZSKBQYDPwKR7iQDrXWmUqpzPcfcAtwC0L1799MUafvwy1uvEn4ok1JbAGWRioqwQLrHHqtAnKA4C0pyZDSGEEKIerVaIqGUsgLvA3dprYtqrSxaL631q8CrAMOGDZMVSOtRe3IpgPBDmWzrfR67e4/B32zCVl5P9cGjJMdYZIsQqTwIIYSoU6skEkopf4wk4h2t9X/cm7OVUl3c1YguwJHWiK298AzrDExIILu4krySSkptAeREnkd3Rw9sUVaKjqRSkL7SWN67DjnFYA8NkSqEEEKIerXGqA0FvAHs0Fo/43XXR8BsYJ77+4enO7b2wFOJKN6+hYwof1afn0Dgr91wuTSYqrCXR9XMSJny2BJyjmQQ0qHnsRN4mjMAe0Ap/aJD6rmSEEII0ToVifOB64EtSqmN7m1/wUggliilbgIOAtNaIbY2z1OJyIjy56sEJ50OxRJQ1pH84FxCLMEEh5uO61Bpj+3JjEfmHTtBXUt+CyGEEPVojVEb32BMsV2XsaczlvagIGUJu997n32mPpSExmNxjKYy8UL2RVbjr4MJOhrFEZOLPX36kHLruSeewDO1tYd0qhRCCHESGlu0S5zhilaswH/fbgpD4qiy2KmyBFAYbORpfjqUkiATJVEBXJFcz4RSJTlG8uAhnSqFEEKcBJkiuw2payRG0bbt7LJ2ITMynICAAnaO/oqd+TuJj4hn4YSFxk6pC2HLPNhe64SZGKMypAIhhBCiiaQi0YbULLDlZXvspRzodyPhFQGUOcoBY5nvSb0mHdvJM5lUXSzSD0IIIUTTSUWiDckuriQvPJpFo26vWeZ73NZ4bBXB5IccprxntlGFSF0I3y4yvqD+fg8H7ze+D5t7Oh+GEEKIdkQSiTOcd3NGXmkEh7qMZODuSipUNC4mYquwUxyaz6ELvzlWhdiyjM1bM9hR6ukXkQR5dnjs/uPOnbN/H/bYngghhBBNJYnEGc7TnFHcoxPp0aOpDLJjDjiMclQRqvyIDT5CXMcd9M88ApmLjCpE1hZ2lCaRU2ltMFGwx/ak3/kXnq6HIoQQoh2SROIM412BOOAXxyHXGEzJEzjQGSxHwykIziN99H8BmJS5l6lZ+6BzHQtp5dmxd4k6fo4IIYQQoplJInGG8Z7a+ldiKA/uTLnfEUqqqgkMLGGM/zbGZ7pnD8/aV/+Ii1rNGEIIIURLkETiDOBdhfAkET3eWszee9/CxWFWJ66iR/WvXFFcyED/XkCgcaDM+SCEEKKVSSJxBihasYI9uWEc6XoeJE+gPNTCkQffpWNZBOVBGfxIBeTly3wPQgghzjiSSLSC2hNLVaSlcST5LgqCoimwQIU6hKuqkqDAEqKDvzV2kuqDEEKIM5AkEq3A0w8ie8DlZPj1gqSLyXVkUHH0MyqDMqhSEKgVvaqqcBYFk2IeZBx4cCd84lvfBxnaKYQQ4nSQROI0qKsCURjTk3WdRmEtd9HJbx8VBVtwOQpQKEKUIgIT5gArZqu9SdeUoZ1CCCFOB0kkToPj+kAAJE+g1KTpVFqK1ZKF6v4kR6p6Y9JBDJr7Bted0711AxZCCCF8JInEaXKk63k1fSAAulXuoYM6Sr/oQzzdqRO2PdAtvLMkEUIIIdoUSSRaSO0hnSRdTJj6leHW1wm2mNkYkMHyDh35JGYQO/Mt9LSEYg9uWjOGEEII0Vpk9c8W4ulQucXRi28S76DQ306gq5xgi5n+XcJZ3akT+yzG0x8fEU9EYEQrRyyEEEKcPKlINJO6OlQGJiSwKfJCgkqddLbsJzxkN5vGvkv/c7rDqrnEg7FaJ5Dyo8xEKYQQou2RRKKZ1ExtHdOBA6beZCT+Fr9gM51KS3EEZvJlv/lgCYGCIr5YBTvzdxIfEd/aYQshhBCnRBKJU+SpRHgqEIHDMziyZwCF1TGYHN9TVb6W4spiIn+JIdgUAH5HAehJJBGBpppKhMz7IIQQoi2SROIUeVcijoRHcGDPOWQ5Ysm25lNVvIkOWlMYUI3VEtpgBULmfRBCCNEWSSLRRHVVIg7s6UtudSx5IdkciNpInyo/qgMgZ6Kd4b0mMS1uWmuHLYQQQjQrSSSaqGjFCiq2bSawkyIsYh8rq9PZ5+9PZUA+nw58lSR7P+JLjArEXyfMa+VohRBCiJYhicRJqD03hKmDJm9If9ZVXMz+w06CK2Lw61BIkr0fk3pNwvXj+laOWAghhGhZMo/ESfA0ZQAExnTAFn2Eb6ouJMcRTbnJREnoUS6bcAELJyyUZgwhhBBnBalInKTdfSaxKfJCekT8SohrCq6qGAqshzl80bdM6jWJ/nExrR2iEEIIcdpIIuGjgn/+gbKffyZ3xPmElJVyKLgaF4GUmw5T2fNIzcRSQgghxNlEEok6bFuXwa6fso/bVrGtP67kfpQEx5AXkk56/9chxE7Hw+H02hdCymMnzkwpc0MIIYRo7ySRqMOun7LJTS+hg86iOv8oVWjM1ZqqAEVmaCYHbOm8PScVgJTH7ifnyD6IPXHBLZkbQgghRHsniUQ9bF2tDFn1v5RnlbO3s4lKk2ZzQiirE7sxJvqS4/a1x/ZkxiMyxFMIIcTZRxIJgNSF/LxoE7uLEqlCUx4Qg6Uqg/wj5WR2NvHA9VaGRPVn4YSFPNLasQohhBBnEBn+CbBlGXsKEyi2ROME/KrSCSlOJdNu4udEK12D+zCp16TWjlIIIYQ445xxFQml1ATgecAMvK61btE2g9WPXE3+5ijyI+PwL/uVBRe/UVN9AJD0QQghhKjfGVWRUEqZgReAiUAicK1SKrElr+n8bgcVgcMByApLk+qDEEIIcRLOtIrECGCP1novgFLq38AVwPbmvtC/Zt6Ew+nAFDEUp1qPo2wj8b07EL+jO64d60nBt+mtZYinEEKIs9kZVZEAYoBDXj+nu7fVUErdopRKVUql5uTknPIFXUqhVTWWEP8mHS9DPIUQQpzNzrSKhKpjmz7uB61fBV4FGDZsmK5jf5/c8c4bTT1UCCGEEG5nWkUiHejm9XNX4HArxSKEEEKIRpxpicTPQF+lVE+llAW4BviolWMSQgghRD3OqKYNrbVDKXUH8BnG8M//01pva+WwhBBCCFGPMyqRANBarwRWtnYcQgghhGjcmda0IYQQQog2RBIJIYQQQjSZJBJCCCGEaDJJJIQQQgjRZErrJs/p1OqUUjnAgVM4hQ3IbaZwWorE2DwkxuYhMTaP1o6xh9ba3orXF+1Im04kTpVSKlVrPay142iIxNg8JMbmITE2j7YQoxC+kqYNIYQQQjSZJBJCCCGEaLKzPZF4tbUD8IHE2DwkxuYhMTaPthCjED45q/tICCGEEOLUnO0VCSGEEEKcAkkkhBBCCNFkbTaRUEpNUErtVErtUUrd77V9kFLqe6XUFqXUx0qpsDqOjVVKlSulflFK7VBK/aSUmt1CcXZTSn3lvs42pdQfvO5LVkr9oJTaqJRKVUqNqCfWrS0Rm/v8/6eUOlL7GifxPGql1BNe22xKqWql1L+aKb76Xmdfn7sWja/W9Rp6rVPcsW5USu1XSm2sJ97T/lq777vT/TxvU0r9s4Fz3K2UqlBKhbdgnPW95o8qpTK8nsdJ9RzfXyn1X6XULqXUbqXUw0op1cg1/+JjbPW+xl77/Mn9e2er4z7P7+SdXtv+pZSa48v1hTgjaa3b3BfGEuO/Ar0AC7AJSHTf9zNwgfv2jcATdRwfC2z1+rkXsBGY2wKxdgGGuG+HAru8Yv0cmOi+PQlY01isLRDfGGBI7WucxPP4K/CL17bb3c/lv04iBr8mvM6+PnenHF9zvNa19psP/PUMeq0vAlYDAe6fOzdwjp+AdcCcFoqxodf8UeBPjRwf5D7+EvfPwcCnwO8bOa6kOV5joBvwGcZEebZ6XuNsYA9gcW/7V0s9n/IlX6fjq61WJEYAe7TWe7XWVcC/gSvc98UDa923vwCuauxkWuu9wB+B/wFQSoW4P7397K5aXOHeblZKPe3+lL7Z+1NFA+fO1FpvcN8uBnYAMZ67Ac8n/XDgcEPncn+aWaeU2uD+Os+9/UKl1Bql1DKlVJpS6p3GPoF5xbcWyK/jLl+fx3Jgh1LKM7nODGCJV8yXKaV+dD+Pq5VSke7tjyqlXlVKfQ4srufcDb3Ovj53Jx2fUsrk/iRrd+9jcn86PuETprdGXmvP9RQwHXivoXMppeZ4V02UUiuUUhe6b5copf6mlNrkrspENnQur/jqe61vB+ZprSvd+x2pJ6begBV4CLjWx1hvclcG1iilXvOhEtTQa+6L64Bvtdafux9LGXAHcL87HqtSaqHX3/BVSql5QJC7yvFOQyf34TV+Fvgzxu9nfXKAL4ETqqDqWKVts1JquVKqo1Kqn1LqJ699YpVSmxt/KoQ4PdpqIhEDHPL6OZ1jf8xbgcvdt6dhfELwxQYgwX37QeC/WuvhGJ/WnlJKhQC3AD2BwVrrgUCD/3RqU0rFAoOBH92b7nKf+xDwNPBAI6c4AozXWg/BeENc4HXfYPf5EjE+zZ1/MrHV4WSex38D1yilugJOjn9T/wYYqbUe7N7vz173DQWu0FpfV895G3qd78L35+6k4tNau4C3gZnufcYBm7TWPk9pXMdr7TEayNZa7/b1XHUIAX7QWg/CSPZuPoVzAcQBo90J1ddKqeH17HctRgK0DohXSnVu6KRKqWjgYWAkMJ5jf18Naeg1B7jD/Sb7f0qpjnUc3x9Y771Ba/0rYFVG89zDQKHWOsn9N/xfrfX9QLnWOllrPfPEU9b7+GLxeo2VUpcDGVrrTT4cPg+4RyllrrV9MXCfO7YtwCNa6x2ARSnVy73PccmwEK2trSYSdX3a9nwCuBH4vVJqPUbpsaoJ57wEuF8Z7dhrgECgO8YbystaaweA1rquT3d1n1wpK/A+cJfWusi9+Xbgbq11N+Bu4I1GTuMPvKaU2gIsxUgaPH7SWqe73wQ3YpRQT8XJPI+rMN4orgVSat3XFfjMHfO9GP/oPT7SWpc3cN6GXueTee6aEt//ATe4b98ILGzg/McHXfdr7eF5Mz4VVcAK9+31nPpr7Qd0xHjDvxdYUk9F6xrg3+7fsf9gJJgNGQF8rbXO11pXY/zONqah1/wloDeQDGRiNBHVdXx91QCN8Tf8Qs0GrQt8iOnEi9R6jZVSwRgfQP7qy/Fa630YzUQ1SbQy+p100Fp/7d70JkZzFBiJw3T37Rmc+HssRKtpq4lEOsd/Qu6K+1Om1jpNa32J1nooxj/sX30852CMMiUY/4yucn9CSdZad3d/Kmjon1S9lFL+GP903tFa/8frrtkY/5DB+Cd7QofBWu7GaF8dBAzDaEP2qPS67cR4c2iyk3ke3SXo9cA9GI/T2//D6I+QBNyKkZR5lDYSRr2vMyfx3DUlPq31ISBbKXUxcA5GO3ujGnitUUr5AVfi25uAg+P/Pr2ft2qttef38JRfa4zn+T/a8BPgwlhUqoZSaiDQF/hCKbUfI6nwNG/UF6tPzWt1xFLf33a21trpTmReo+7XfBvG34Z37L0w+kAU08S/4Vrnq+s17o1Rrdzkfn66AhuUUlENnOrvwH349n84BZiulIoD9ClWtIRoVm01kfgZ6KuU6qmUsmD8U/sIwFNuVUqZMNpyX27sZO4S5dMYbypgdJa60/OpTCk12L39c+A29xsCSqkIH86tMD4t79BaP1Pr7sPABe7bFwON/XMIBzLd/0ivx+iY1iKa8DzOxyjJ5tXaHg5kuG+f7MiYel9nTv65a0p8r2M0cSzRWjsbC7aR1xqMT8NpWuv0xs4F7AeS3f0zutF4knkqPsB4DnG/UVk4cWXKa4FHtdax7q9oIEYp1aOBWH8CLnC38/vhQ38lGv7b7uK131SM5rfa3gFGKaXGuY8JwmgC9IxE+RyjzwTu+z3NI9XuBKFB9b3GWustWuvOnucHIyEaorXOqu9cWus0YDswxf1zIVCglBrt3uV64Gv3fb9iJI0PI9UIcYZpk4mEu2nhDow3/B0Y/+i3ue++Vim1C0jDeLOpryTdW7mHf2KUDf+f1tqz7xMYzQiblTFUzjN88HXgoHv7JrzKkg04H+MfwsXqxGFrNwPz3ef6O0YfjNr8OFZteBGYrZT6AaNdu7FP9I1SSr0HfI/R5p2ulLrJfZevzyMAWuttWus367jrUWCpUmodJ7lsciOvsy/P3anG9xFG50JfmzUaeq3BeFNsqFnD+7X+FtiH0U7+NEYfnlPSwGv9f0Av9+/6v4HZXhUP79iX19q23L29zli11hkYr82PGKNCtgOFDcXYyGv+T08nSYy+S3fXcXw5RufMh5RSO90x/YwxMgLgSaCjUmqr+3fnIvf2VzH+rhvr99TYa3yy/oZRvfCYjdH3ZzNGE87jXvelALOQ/hHiDCNTZJ/hlDFiZKbWenqjO4tmpYyRHs9qrUc3unPzXK/dvdZKKavWusRdkVgO/J/WunZCIoRow061bVW0IKXU4xifrua0cihnHWVMhHQ7x0ZutPT12utr/ai7mSEQo1nhg9YNRwjR3KQiIYQQQogma5N9JIQQQghxZpBEQgghhBBNJomEEEIIIZpMEgkhToJSyuke8rdNGWtd/NE910ZDx8QqpXwZKiyEEG2OJBJCnBzPmgz9MabdngQ80sgxsfg254gQQrQ5MmpDiJOglCrRWlu9fu6FMeGRDegBvIWxqBbAHVrr79wTiPXDmLTpTYyZFucBFwIBwAta61dO24MQQohmJImEECehdiLh3laAsbJlMeDSWlcopfoC72mthyljSe0/aa2nuPe/BeistX5SKRWAMTPkNPdCTkII0abIhFRCnDrP4lT+wL+UUskY6yLE1bP/JcBApdTV7p/DMRbEkkRCCNHmSCIhxClwN204gSMYfSU8q7OagIr6DgPu1Fp/dlqCFEKIFiSdLYVoIqWUHWNV1H+5F7mqb3XWYiDU69DPgNs9q00qpeKUUiEIIUQbJBUJIU5OkFJqI0YzhgOjc6VnOekXgfeVUtOArzi2OutmwOFebXIR8DzGSI4N7mWpc4DfnJ7whRCieUlnSyGEEEI0mTRtCCGEEKLJJJEQQgghRJNJIiGEEEKIJpNEQgghhBBNJomEEEIIIZpMEgkhhBBCNJkkEkIIIYRosv8P4BJyk1UiFXUAAAAASUVORK5CYII=", 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", 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", 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c91C1F7ooLCy0vLy8FXPmzGl1++23dzzjjDM+mz59+hHNmjUr/uyzz5ZnZ2c3GzZsWB+AjRs3Npo2bVqHRYsWfdayZcvi3/zmN+3vuOOOdtOnT98I0LRp0+Lc3NyV0V7nzjvvbPvwww+3279/f4N//etfKwHWr1/fuFOnTvtKHnPkkUfuW79+feOqxK+kLCJSk8pJxs8UjWRe7vrShDzn6qEVP49Uy9ixY78ByMrK2jVp0qQmAG+//XbziRMnfg3BFJ09e/bcDbBgwYLDvvzyy6aDBw/uBbB//3477rjjdpY812WXXfZNea8zefLkgsmTJxc88sgjradOndph7ty5q6PN+1FSRcdKSVlEpCZUkoyzV+UBlPawrhMOoqKtrkaNGnlxcWnrMXv37j3gMmzTpk099DiKiopKM2K05OjuDB8+fPsrr7yyqsxOoEWLFsXRtoe76qqrtk6aNKkzQKdOnfYvXLiwRcm+9evXNznxxBNjW7c2RNeURURqQt4LsCkvSMaj7ocrXuWZopHc8mIe2au2ktmttXpY14BOnToVbt26tdGmTZsa7tmzx/75z39Wes12+PDhO59++unWAIsXL2762WefHQowYsSIXTk5Oc2XLl16CMCOHTsafPLJJ4dU9nx5eXmlj5kzZ06rLl26fAdw3nnnbVu4cGHLgoKChgUFBQ0XLlzY8rzzzttWlfenSllE5GCUVMib8qB9Gs/0+RPzctdD7ntkr9oKaDKQmnTIIYf4L3/5y42DBw/u3alTp++OPvrovZUdc9NNN3190UUXdevZs2efvn377k5LS9sF0LFjx8JHH3109UUXXdR93759BjB16tT1/fv3/66i55sxY8YRb731VstGjRp5q1atCp988slVAO3atSuaNGnShuOOO643wK9+9asNkUtHVkZzX4uIVFfEFJnzirKYlh/MypXZrTVAQicD0dzXyUtzX4uI1ISSyhi+v3486v7SXtWZ3VpqVi6pNiVlEZFYROnIVVIdzw8b5qRe1XIwlJRFRCoT1kwd3qv6lhdLelRTN8Ydx6a4uLjYGjRokPzXPpNUcXGxAVF7dispi4iUJ7I6HnV/mSFO9bAT19KCgoI+bdu23abEXHXFxcVWUFDQClgabX9ck7KZ3QD8FHAgD7gCOBSYA3QFVgMXuHu5A7RFRGpdlKbq7OYnMyO3V5nxxvUsIVNYWPjTTZs2Pb5p06Z+aFhtdRQDSwsLC38abWfcel+b2ZHA20Afd99jZs8Bfwf6AFvd/S4zuxn4gbv/uqLnUu9rEak1EU3V2c1PZsbWrNLhTamUjOPR+1riK97N142AZma2n6BC3gBMBkaE9j8FLAAqTMoiInFXTlN1cN14a0olY0ldcUvK7r7ezKYDa4E9wOvu/rqZtXP3jaHHbDSzI6Idb2YTgAkAnTvrSyAicVRJR656eN1YEiRuSdnMfgCcC3QDvgWeN7NLYz3e3WcCMyFovo5HjCJSz0VUx9l9pzBjaxbkUp87ckkCxbP5+hRglbsXAJjZXCALyDezDqEquQPwdRxjEBGJLsq14wtze1HSVK3makmEeCbltcAQMzuUoPl6JJAD7AIuB+4K/Z4XxxhERMoKT8gHXDtWZSyJFc9rytlm9gLwIVAIfETQHN0ceM7MriRI3GPjFYOISKko02Nm951ywDAnJWRJNC1IISL1w6yzSldyAiBtDBeGTY9ZF5uqNSQq9WhGLxGpu8Kr45KEfMWrPJO9lnm56zVftSQdJWURqZsihzm1TwsmAnn0vTITgYgkCyVlEalbypuvesl6snO3oolAJJkpKYtI3aD5qqUOUFIWkdQXZUYuMq5gxqPvsXzjdiVjSRlKyiKSuipYWpHc99SRS1KOkrKIpJ4oTdWR81VndmtdOtRJJFUoKYtIailnaUXNVy11gZKyiKSGGJZW1LVjSXVKyiKS/KJVx5oeU+ogJWURSV7lLK2o8cZSVykpi0jyKWfMcfjSikrGUhfFnJTN7AdAR4JlGFe7e3HcohKR+qucjlxBdaymaqnbKkzKZtYK+DlwMdAEKACaAu3M7H3gYXd/M+5RikjdF0NHLlXHUtdVVim/APwPcLy7fxu+w8yOA/7TzLq7+xNxik9E6gN15BIBKknK7n5qBftygdwaj0hE6pewhKyOXFLfxXRN2cwMGAd0d/fbzawz0N7dP4hrdCJSN4Wvcxxqrp7ZaiLT1JFL6rlYO3o9DBQDJwO3AzuAvwKD4hSXiNRVYZXxsiZp0CSNp3cN5tn8IUrGUu/FmpQz3f1YM/sIwN2/MbMmcYxLROqisIT8X0xgeZsfB9vbwDQlY5GYk/J+M2sIOICZtSWonEVEKvRM9lrmLVnPyN1/Z8K2B4BQQu7wY63eJBIh1qT8APAicISZ/R4YA9wat6hEpG7ImcWA+U/QY18Rg1gOBNeOlx/6I63eJBJFTEnZ3WebWS4wEjDgPHdfEdfIRCSlZT9/H5nLbqcvoWvHHYLlFSdkXMGERAcnkqRi7X39B2COuz8U53hEpA4oScgQVMbNs66ir64Xi1Qq1ubrD4FbzawnQTP2HHfPiV9YIpJqnsley853H2PYnjfJ3BdM+pHddwoTxv4ywZGJpI5Ym6+fAp4ys9bA+cDdZtbZ3XvENToRSQnPZK8l7+X7ubNxMLnfsiZp7OwxmkwlZJEqqeoqUUcDvYCuEOq1ISL1Wvbz99E973kuaRzqZjLqfvpmXJHYoERSVKzXlO8Gfgx8CTwH3BE5F7aI1DM5s8h/92kyt+ZAA8hvnUG7rEtBCVmk2mKtlFcBQ919czyDEZEUEZoEpB3wfnFvLG2smqpFakBlSzf2cvdPgQ+AzqE5r0u5+4fxDE5EkkzE8oqT919J2jnXayYukRpSWaV8IzABuC/KPieYC1tE6oHwYU7vF/dmXlGWErJIDats6caSMf5nuvve8H1m1jRuUYlI8ghVx5lhqznND83IpYQsUrNivab8LnBsDNtEpC4IdeLavPM7+obGHC+mDx+1OoUJN9yhGblE4qSya8rtgSOBZmY2kGCKTYCWwKFxjk1EEiT/3adptmU5O7wLy5qm8U6zk0qrYxGJn8oq5dOB8UAnYEbY9h3ALZU9uZn9B/A40I/gGvRPgJXAHIKxzquBC9z9mypFLSLxEaqQm21ZznLvwldnPcclmZ3pC6qORWpBZdeUS2byOt/d/1qN5/8D8Jq7jwmtv3woQTKf7+53mdnNwM3Ar6vx3CJSEyKaqtsB73swzEnXjEVqV6zTbP7VzM4C+gJNw7bfXt4xZtYSOIGg0sbd9wH7zOxcYEToYU8BC1BSFql9YcOb2gGrinuXNlU3z7pKCVkkAWKd0esRgir3JILm6DEEY5cr0h0oAGaZ2QAgF/gF0M7dNwK4+0YzO6Kc15xAqMWsc2f95yBSo0KTf0DZ4U19ExuZSL3WIMbHZbn7ZcA37v5fwFDgqEqOaUTQO/tP7j4Q2EXQVB0Td5/p7hnuntG2bdtYDxORiuTMgllnlSbkyfuv5KJ9v9V4Y5EkEeuQqD2h37vNrCOwBehWyTHrgHXunh26/wJBUs43sw6hKrkD8HVVgxaRKoqYiaukOv6q81imabyxSNKINSn/LdST+l6CtZWdoBm7XO6+ycz+bWbHuPtKYCTBylLLgcuBu0K/51UzdhGJRVhT9bImaTy9azDPFo1k2ug07lQyFkkq5u5VO8DsEKCpu2+L4bHpBMm7CfAVcAVBk/lzQGdgLTDW3bdW9DwZGRmek5NTpThF6rWSyhgOmKf6q85jATQbVz1hZrnunpHoOCR2lU0e8uMK9uHucys63t2XANE+ECNjik5Eqi6iMt4R1pFLlbFIcqus+frsCvY5UGFSFpFaEqUy/i8msLxN8He1KmOR1FDZ5CFarVwk2YVVxvmtM9jcJI0X9g1leYcfM+fqoYmNTUSqJNZxylOiba9o8hARibOIHtXZfadwYW4vADK7tdY81SIpKNbe17vCbjcFRgEraj4cEalURDKmy3Cym59cmpCnjU5TU7VIiop1ms37wu+b2XTg5bhEJCLlC2uqLknGM7ZmkZ0bDGBQQhZJbbFWypEOJZhGU0RqQ2R1POp+nikayS0v5gFbS5urlZBFUlus15TzCHpbAzQE2gK6nixSG6JVx7m9yF6VB6g6FqlLYq2UR4XdLgTy3b0wDvGISIkoHbm+b6pWdSxSF8V6TXmNmf2AYBGKRkC70OQhH8Y1OpH6KCIZ57fOYF5RFtNye6FkLFK3xdp8fQfBushf8n0ztgMnxycskXoqYszxvKIspm0YAqBkLFIPxNp8fQHwQ3ffF89gROqtGMYcKxmL1H2xJuWlwH+gZRZFal7EXNXvNDsp1FStTlwi9U2sSflO4CMzWwp8V7LR3c+JS1Qi9UVYQp68/0qe3TuSzDatyeym+apF6qNYk/JTwN1AHlAcv3BE6omI5urJ+68sXeNYiVik/oo1KW929wfiGolIXRdlJadlTdJ4etdgJWQRAWJPyrlmdifB1JrhzdcaEiVSmShDnDaXJOO9I8ns1pppaqoWEWJPygNDv4eEbdOQKJHKRJmNK7xXtZKxiISLdfKQk+IdiEidE56QD5irWr2qRSQ6racsEg9hCTm77xTNVS0iMdF6yiI1KeL68cxWEzU9pojETOspi9SUiElAnt41mGfzhygZi0jMtJ6ySE2INgmIOnKJSBVpPWWR6ooy7liTgIjIwdB6yiLVEdFUvaO4N/OKsviq81hVxyJSbbEm5Q7AMnffAWBmzc2sr7tnxy80kSQUbXrMUFP1uelHcqeSsYgchFiT8p+AY8Pu746yTaTuikjGdBnOzG+P5dn8IWqqFpEaE2tSNncvuaaMuxebWXU7iYmkliizcs3YmsXybdvJ7NZSCVlEakysifUrM5tIUB0D/D/gq/iEJJIkIqrj7L5TmLE1i+zcrYSPOxYRqSmxJuVrgAeAWwl6Yc8HJsQrKJGEi+jI9U6zkzQJiIjEXayTh3wNXBTnWEQSr7yOXG1ak9kNJWMRiasKk7KZ3Qo87O5by9l/MnCou/8tHsGJ1Bp15BKRJFBZpZwHvGJme4EPgQKCua97AOnAG8C0eAYoEldR1jqeV5TF/H0/UkcuEal1FSZld58HzDOzHsAwgvHK24GngQnuvif+IYrESYVrHUOfDi3VkUtEalWs15Q/Bz6vzguYWUMgB1jv7qPMrDUwB+gKrAYucPdvqvPcItUWubRiaa9qLa0oIonToBZe4xccuMzjzcB8d+9B0Iv75lqIQeR74RXyqPuDMccbtwcLSCghi0gCxXUCEDPrBJwF/B64MbT5XGBE6PZTwALg1/GMQwSIPu44txfLN26nT4eWzLl6aIIDFJH6LtZVooa5+zuVbYvifuBXQIuwbe3cfSOAu280syPKec0JhMZCd+6sykUOUrnXjzUJiIgkj1gr5QcpO891tG2lzGwU8LW755rZiKoG5u4zgZkAGRkZXsnDRcqKsrQio+7nmaKR3PJiHqDrxyKSXCobpzwUyALamtmNYbtaEqyrXJFhwDlm9iOCYVQtzexpIN/MOoSq5A7A19UPX6QcEZVx6VCn3F5kr1JCFpHkVFlHryZAc4Lk3SLsZzswpqID3X2yu3dy964Es4H9n7tfCrwMXB562OXAvGpHLxJNREcurniViYf8jge3DQdQhy4RSVqVjVNeCCw0syfdfU0NveZdwHNmdiWwFhhbQ88r9VmUpuqSjlzkvqfOXCKSEmK9pnyImc0kGFtceoy7nxzLwe6+gKCXNe6+BRhZlSBFyhVleky6DIe0MQf0rNZEICKSCmJNys8DjwCPA0XxC0ekCiKuG5M2BjKuAOCZ7LVkr8ojs1trVccikjJiTcqF7v6nyh8mUksirhs/UzSSebnrIfc9ALJXBbNzqToWkVQSa1J+xcz+H/Ai8F3JxvJWjxKJm8jm6oghTpndWpf+1jKLIpJqYk3KJb2lJ4Vtc6B7zYYjUo7yVnPSECcRqUNiXZCiW7wDEalQ3guwKS/qak6qikWkroh1ms1DCeau7uzuE0JLOR7j7n+La3RSv4UPc9qUB+3TeKbPnzQbl4jUWbGuEjUL2EcwuxfAOuB3cYlIBL7vyFXSXH1YD2Z+e6wSsojUabFeU/6hu19oZhcDuPseM7M4xiX1WbS1jjcEfQrVVC0idVmsSXmfmTUj6NyFmf2QsF7YIgctyoxcM1tNZFrESk5KxiJSl8WalKcCrwFHmdlsgsUmxscrKKlnoiwecX/+AJ7NH6JkLCL1Sqy9r/9lZh8CQwADfuHum+MamdQPYQl5ZquJzN/3o9Kmal03FpH6Jtbe16MJVnl6NXT/P8zsPHd/KZ7BSR0WMe548v4rQ5WxrhuLSP0Vc/O1u79YcsfdvzWzqcBLcYlK6q6IZPx+cW/mFWXxVeexTFMiFpF6LtakHG3oVKzHigTCmqqXNUnj6V2DebZoJNNGp3GnkrGISMyJNcfMZgAPEfTAvg7IjVtUUndE6VU9ef+VfNVhLLRB1bGISJhYk/J1wG+BOaH7rwO3xiUiqVPy332a5t+sYHXj7uwINVWnnXO9KmMRkSgqTcpm1hCY5+6n1EI8UheEquP8HXtptmU5ed6F/25/L4A6cImIVKDSpOzuRWa228xaufu22ghKUljYdeNVxb2BLljaWOaMHZrQsEREUkGszdd7gTwz+xewq2Sju0+MS1SSeqINcQp14lJlLCISm1iT8quhH5Gywqrj0tm4lJBFRKos1hm9ngrNfd3Z3VfGOSZJJREzck3bMATQbFwiItUR64xeZwPTgSZANzNLB25393PiGJsksyjN1V8d+iMyu6kzl4hIdcXafH0bMBhYAODuS8ysW5xikmQXVh2/r2FOIiI1JtakXOju2yKWUPY4xCPJLGcW+e8+TbutOUCoOu48VpWxiEgNiTUpLzWzS4CGZtYDmAi8G7+wJKmEJeN2BNXxJz84lbSsq1Qdi4jUoKrM6PUb4DvgGeCfwO/iFZQkj+zn7yNz2e0HJOPmWVcxQclYRKTGVZiUzawpcA1wNJAHDHX3wtoITBIobEauzFBT9cxWE5WMRUTirLJK+SlgP/AWcCbQG7g+zjFJApVUxhDMyLWK3ljaWCaM/WWCIxMRqfsqS8p93D0NwMyeAD6If0iSCNnP30fzz18kc18eEFTG8w/9kTpxiYjUosqS8v6SG+5eGNH7WuqCUCeukmbqZU3S2NljNBPG/pIJCQ5NRKS+qSwpDzCz7aHbBjQL3TfA3b1lXKOTuIrsxGVpY8lUM7WISMJUmJTdvWFtBSK1J1pTdfOsq9RMLSKSYLEOiaoyMzsK+B+gPVAMzHT3P5hZa2AO0BVYDVzg7t/EKw75XmQyDm+qFhGRxItbUgYKgV+6+4dm1gLIDS39OB6Y7+53mdnNwM3Ar+MYh3Bgr+qSZKymahGR5BK3pOzuG4GNods7zGwFcCRwLjAi9LCnCObTVlKOk8jqOLvvFCVjEZEkFc9KuZSZdQUGAtlAu1DCxt03mtkRtRFDffNM9lp2vvsYE7Y9AKg6FhFJBXFPymbWHPgrcL27b491WJWZTYBgVE7nzuqAVBXZz99H97znGdJgRXBf1bGISEqIa1I2s8YECXm2u88Nbc43sw6hKrkD8HW0Y919JjATICMjQytSxeCA6rgB5LfOoF3WpWRmXJHo0EREJAbx7H1twBPACnefEbbrZeBy4K7Q73nxiqFeyZnFgPlP0FfXjkVEUlY8K+VhwH8CeWa2JLTtFoJk/JyZXQmsBcbGMYY6r6QjV999efQluHbc97QrVR2LiKSgePa+fptg5q9oRsbrdeuLaB253ml2Es2zrqJvhq7Bi4ikolrpfS0155nstcxbsp7ua5/nzsZPAN83VfdNcGwiInJwlJRTyDPZa8l7+X5uaPguQxoHPasZdb+aqkVE6ggl5RRRkpBLqmO6DIe0MaCELCJSZygpJ7mSjlzd9xZySVh1rGQsIlL3KCknqTKLRzRNI795MO5YCVlEpG5SUk5Cz2SvpXve8xxla1h2iKbHFBGpL5SUk0jJMKf+3/yLPraGPW360Hfi/ESHJSIitURJOUkc0JErbIpMERGpP5SUEyy8Og7vyNVO141FROodJeUEKTMJSHh1rIQsIlIvKSknyLwl6+mzcS5TS8YdqzoWEan3lJRrUUl1DAQJOViZUuOORUQEUFKuNeFTZLZo2oi+BOOPlZBFRKSEknItyH7+PrrnPf99R64OwwFNkykiIgdSUo6jA5ZXVEcuERGphJJynJRUx0MaBNVxyfKKIiIi5VFSrmHlVcdaXlFERCqjpFyDVB2LiMjBUFI+COFDnEbu/ruqYxEROShKytVUZohTaIlFVcciIlJdSspVVGZ6TDhgiJOqYxERqS4l5SoIr46HhC0eoSFOIiJSE5SUY3TA0ooAXTT5h4iI1Cwl5RiUmZFL1bGIiMSBknJFcmaR/+7TZG7N0YxcIiISd0rKUYRPANIOeL+4N5Y2Vr2qRUQkrpSUw5Qk4/7f/Kt0ApCZrSbSPOsqLsnsnODoRESkrlNSDhNteswJaqoWEZFaoqRM0JGr+ecvMmHf92sct1MyFhGRWlavk/IBi0cAy5qksbPHaE0AIiIiCVEvk3K0a8eaHlNERBKt3iXlAyYB0eIRIiKSROpVUi4zK5euHYuISBJJSFI2szOAPwANgcfd/a54vl54c7Vm5RIRkWRV60nZzBoCDwGnAuuAxWb2srsvj9drRhvqpIQsIiLJJhGV8mDgC3f/CsDM/hc4F6jxpPz+w1fR4tsVGuokIiIpoUECXvNI4N9h99eFth3AzCaYWY6Z5RQUFBzUCy5rkkZ23ymqjkVEJKklolK2KNu8zAb3mcBMgIyMjDL7YzHk/z1WncNEREQSIhGV8jrgqLD7nYANCYhDREQkqSQiKS8GephZNzNrAlwEvJyAOERERJJKrTdfu3uhmV0L/JNgSNSf3X1ZbcchIiKSbBIyTtnd/w78PRGvLSIikqwS0XwtIiIiUSgpi4iIJAklZRERkSShpCwiIpIkzL1a83LUKjMrANZU8/DDgc01GE5dpHNUMZ2fyukcVSxR56eLu7dNwOtKNaVEUj4YZpbj7hmJjiOZ6RxVTOencjpHFdP5kVip+VpERCRJKCmLiIgkifqQlGcmOoAUoHNUMZ2fyukcVUznR2JS568pi4iIpIr6UCmLiIikBCVlERGRJJH0SdnMzjCzlWb2hZndHLZ9gJm9Z2Z5ZvaKmbWMcmxXM9tjZh+Z2Qoz+8DMLq/ddxBfZvZnM/vazJZGbI/1/LiZ3RG27XAz229mf6yN+GuDmR1lZm+GPgPLzOwXYfvmmNmS0M9qM1sS5fiukee3rqnge3abma0PO0c/Kuf4vmb2f2b2mZl9bma/NTOr5DVvqen3EU8VfNfuMLNPQufndTPrGOXYOv8Zkhri7kn7Q7C045dAd6AJ8DHQJ7RvMXBi6PZPgDuiHN8VWBp2vzuwBLgi0e+tBs/RCcCx4e+ziufnS+CjsG0/C52jP1YhhkaJPg+VxNcBODZ0uwXwWcnnKOJx9wFTKvsc1bWfSr5ntwE3VXJ8s9Dxp4XuHwr8A/h5JcftTPR7r+J5Ku+71jLs9kTgkfr2GdJPzf0ke6U8GPjC3b9y933A/wLnhvYdAywK3f4XcH5lT+buXwE3EnxxMLPDQn/9Lg5V0+eGtjc0s+mhKvMTM7uuht9XjXH3RcDWKLtiPT97gBVmVjKxwYXAcyU7zexsM8sOnZ83zKxdaPttZjbTzF4H/qcm3ku8uPtGd/8wdHsHsAI4MvwxoaruAuDZip7LzMaHtyKY2d/MbETo9k4z+72ZfWxm75ecqxRQ0fcsFpcA77j76wDuvhu4FrgZwMyam9mssO/T+WZ2F9AsVF3Ortm3Ex/lfdfcfXvY3cOACnvPhqrmt8zsw9BPVmj7CDNbYGYvmNmnZja7stYGqXuSPSkfCfw77P46vv/PdClwTuj2WOCoGJ/zQ6BX6PZvgP9z90HAScC9ZnYYMAHoBgx09/5ASvynEaEq5+d/gYvMrBNQBGwI2/c2MMTdB4Ye96uwfccB57r7JTUWdZyZWVdgIJAdset4IN/dPz+Ipz8MeN/dBxD8QXTVQTxXbaroewZwbSiZ/tnMfhDl+L5AbvgGd/8SaB66bPJbYJu7p4W+T//n7jcDe9w93d3H1ei7SYDQH2P/BsYBUyp5+NfAqe5+LMEfwQ+E7RsIXA/0IWi5GFbz0UoyS/akHO2vxJK/Qn8C/NzMcgmaJPdV4zlPA24OXUdcADQFOgOnEDRBFQK4e7RKNNlV5fy8BpwKXAzMidjXCfinmeUBkwj+Ay7xsrvvqbmQ48vMmgN/Ba6PqG4geO8VVskx2Af8LXQ7l6DJMhVU9D37E/BDIB3YSNDEH+348qpDJ/g+PVS6wf2b6gaarNz9N+5+FMEf8NdW8vDGwGOh79TzBAm4xAfuvs7diwkuI3WNQ7iSxBolOoBKrOPACq8ToSrO3T8lSKqYWU/grBifcyBB8yUE/5mc7+4rwx8QajJK6QHcVTk/7r4vlLx/SZB0zw7b/SAww91fDjXT3ha2b1fNRh0/ZtaYICHPdve5EfsaAT8mqPwrU8iBf8w2Dbu9391LPjdFJP/3q0RF37P8ko1m9hjf/9ERbhnB9VbCHtud4JrxjrrwfaqCZ4BXgakVPOYGIB8YQPBZ2hu277uw26n0GZIakuyV8mKgh5l1M7MmwEXAywBmdkTodwPgVuCRyp4s1HQ5nSDRAPwTuK7kuo2ZDQxtfx24JvSfNWbWuqbeUG2pxvm5D/i1u2+J2N4KWB+6nZI910P/vk8AK9x9RpSHnAJ86u7rYni61UC6mTUws6MIrsemuoq+Zx3CHjea4LJIpNnAcDM7JXRMM4Im2XtC+18nrHoMawLfH/pjKaWZWY+wu+cAn1ZySCtgY6ga/k+CjnYiQJIn5VDz8bUEyXMF8Jy7LwvtvtjMPiP4AmwAZpXzND8MdVJaQdCB6UF3L3nsHQRNSZ+EhiuUDA16HFgb2v4xQUeWpGRmzwLvAceY2TozuzK0K9bzA4C7L3P3p6Lsug143szeInWX5htG8J/fyRZ9aM9FVNx03YjvK5h3gFVAHsEfeB/GId5aVcn37J6SDloE/S5uiHL8HoKOYbea2UqCc7MYKOkQ9zvgB2a2NPR9Oim0fSbBdywl+mxU8F27K/TePiFonfpFlMPDP0MPA5eb2ftAT1KoxUniT9NsilQi1Ct/nLtfkOhYJDXpMySx0vUKkQqY2e0EVeD4BIciKUqfIakKVcoiIiJJIqmvKYuIiNQnSsoiIiJJQklZREQkSSgpi0Qws6LQsKlloXmsbwyN967omK5mlrRD50QkNSgpi5RVMidzX4LpR39ExTM0QTAdopKyiBwU9b4WiWBmO929edj97gSTYRwOdAH+QrD4BMC17v5uaCKI3gQTizxFMKPVXcAI4BDgIXd/tNbehIikJCVlkQiRSTm07RuC1cV2AMXuvjc0veKz7p4Rmhf8JncfFXr8BOAId/+dmR1CMBPYWHdfVZvvRURSiyYPEYlNyUpKjYE/mlk6wYIBPct5/GlAfzMbE7rfCuhBUEmLiESlpCxSiVDzdRHBOrhTKX+FnwMOA65z93/WSpAiUieoo5dIBcysLcEKW38MLctY3go/OwjWrS7xT+BnJasgmVlPMzsMEZEKqFIWKauZmS0haKouJOjYVbLk48PAX81sLPAm36/w8wlQGFoF6UngDwQ9sj8MLR1ZAJxXO+GLSKpSRy8REZEkoeZrERGRJKGkLCIikiSUlEVERJKEkrKIiEiSUFIWERFJEkrKIiIiSUJJWUREJEn8f3nFl6kB7jMEAAAAAElFTkSuQmCC", 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", 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", 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", + "image/png": 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", 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", + "image/png": 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", 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vv71TaWmpjRgx4uMmTZr4xIkTDx03btznbdq0KVu9enWTpk2b+jfffGPt27cvvfLKKz9v3bp12bRp0w6p7rGUQEVEakH5DkLHdTuY47odTLc9LenQulmGo6s/mjVr5oMGDdp+4IEH7s3JyeG8887bvmzZsmb9+/c/CqBFixZl06dPX71ixYoDbrjhhs6NGjUiJyfH77///k+qeywlUBGRNIqVOPdr55yq5JlKe/fuZdGiRa2eeuqpVZFlN99886ZIz9yIXr167RkxYsTymhxLCVREJA3iJk5JuYULFzYbNmzYEWedddYX+fn5e9J9PCVQEZEU00AImXHMMcfsXrduXa1NrqoEKiKSIhoIgbKysjJr1KhR9k7zFaWsrMyAssrWK4GKiMSzYCoUzaxyk40lu+m+ZSfXAK1zc2jb6gA6LG8G8VrZNhRBXn7KQs2wpZs3b+7Zrl27bdmeRMvKymzz5s1tgKWVbaMEKiIST9HMShPdxpLdbNmxh5LdpUBwSUq1etXm5UP+yFRFmlGlpaX/uWHDhikbNmw4muyf7asMWFpaWvqflW2QkQRqZtcA/wk4UASMBVoAM4CuwBrgfHev1riEIiJpk5dfYdLrWG2dDfl6zmOOOWYTMDTTcdSWWk+gZtYJ+CnQ092/MrMngQuBnsBcd59kZhOACcD1tR2fiEhVyg+EAA2yrVPIXBE7B2huZjkEJc/PgGHAtHD9NOD7mQlNRCS2SIkz+tIUJc+Gq9ZLoO6+3szuBNYCXwGz3X22mXVw9+Jwm2Izax/r8WY2DhgH0KWL3rQiUjs2luzeV12rpCmQgRKomR1EUNrsBhwKtDSzSxJ9vLtPdvdCdy9s165dusIUEeGx+Wu54H/fZlnxNlbX10HfJWmZ6EQ0BFjt7psBzOwZYBCw0cw6hqXPjsCmqnYiIpJO0R2EyIXWzXL4zdlKnvKtTCTQtcAAM2tBUIV7KrAA2AlcCkwK/z+XgdhERPZLnr8Znk+v5W0A6KXkKVEy0QY638xmAouAUuCfwGSgFfCkmf2IIMmOqu3YRKRhq3QkoRoNOS71VUauA3X3W4Fbyy3eQ1AaFRGpVRr4XZKhkYhEpMF7bvF6lhdvV+KUalECFZEGJ3owBIDlxdvp2TGXGZcPzGBUkm2yfaxCEZFqi5Q4I3p2zGVYQacMRiTZSCVQEWlQHpu/lvmrP+e4bgerxCk1ogQqIg1C+Y5CKnFKTSmBiki9ph62ki5KoCJSr6mHraSLEqiI1Ftq75R0UgIVkbphwVQomlnj3Wws2c2WHXsA6L67lCeaQrc9LWFqs+R3uqEomFBbJIouYxGRuqFoZpCoamBjyW5Wb9lJye5SIBgAvlvblnRoXYPkCUHyzB9Zs31IvaMSqIjUHXn5MPbFpB5afgB4tXVKuiWcQMN5PA8lmEFljbuXpS0qEZEEVToAvEiaVZlAzawN8BPgIqApsBloBnQws3eA+939lbRHKSISQ3SpU71spbbFK4HOBP4MHO/uX0avMLNjgB+YWXd3fyhN8YmIxKQqW8m0KhOou59WxbqFwMKURyQiUonoQeBVZSuZllAbqJkZMBro7u6/MrMuQJ67v5vW6EREQuWra1VlK5mWaCei+4Ey4BTgV0AJ8DTQP01xiYioxCl1WqIJ9Dh372dm/wRw9y/MrGka4xKRBk4lTqnrEk2g35hZY8ABzKwdQYlURCSldFmKZItEE+g9wCygvZndDowEbkpbVCLS4ESG4LtxpS5LkeyQUAJ19+lmthA4FTDg++7+QVojE5EG47H5a+m+ZSegxCnZI9FeuH8EZrj7fWmOR0QamEhb5xNNoVvblpo1RbJGolW4i4CbzKwHQVXuDHdfkL6wRKS+K9/WmZJB30VqUaJVuNOAaWZ2MDAC+K2ZdXH3I9IanYjUS7GG4OuwXMlTskt1Z2P5DnAU0BVYnvJoRKTeq3QIPn2jSJZJtA30t8B5wCrgSeC28mPjiohURgMiSH2UaAl0NTDQ3bekMxgRqX80IILUV/GmMzvK3VcA7wJdwjFw93H3RekMTkRq0YKpUDQzZbuLXNfZfXfpvh62HZqG7ZzLqVhlu6EomFBbJEvEK4H+HBgH/D7GOicYG1dE6oOimSlJYpHEWbK7FIDWzXJo2+qA+D1s8/Ihf2SNji1Sm+JNZzYuvHmWu++OXmdm6jInUt/k5cPYF5N+uCa4loYk0TbQt4B+CSwTkQZKE1xLQxOvDTQP6AQ0N7O+BMP4AeQCLdIcm4hkAQ3+Lg1VvBLoGcAYoDNwV9TyEuDGZA9qZgcCU4CjCdpSfwisBGYQXGO6Bjjf3b9I9hgikn6qspWGLF4baGQEohHu/nQKj/tH4GV3HxnOK9qCICHPdfdJZjYBmABcn8JjikiKqNQpkvhQfk+b2dlAL6BZ1PJfVfeAZpYLnEBQssXdvwa+NrNhwEnhZtOAeSiBitQp5ROnSp3SkCU6EtEDBKXEkwmqXkcSXBuajO7AZmCqmfUBFgI/Azq4ezGAuxebWfsk9y8iaaDqWpH9JdoLd5C79zaz9939/5nZ74FnanDMfsB4d58fTpU2IdEHm9k4gmtT6dJFH16RdFN1rUhsiSbQr8L/u8zsUGAr0C3JY64D1rn7/PD+TIIEutHMOoalz47AplgPdvfJwGSAwsJCTzIGEYlD1bUiVUs0gf417Dl7B8HcoE5QlVtt7r7BzD41syPdfSVwKt8O7HUpMCn8/1wy+xeR1Hhu8XqWF29X4hSpRKKdiG4Lbz5tZn8Fmrn7thocdzwwPeyB+zEwFmgEPGlmPwLWAqNqsH8RSVKk5Lm8eDs9O+Yy4/KBmQ5JpE6KN5DCeVWsw92Tagd198VAYYxVpyazPxGpmcfmr6VPcfCb+MaV+3cUEpHY4pVAz61inZN8RyIRqUOeW7yeI77eS4umjVVlK5KgeAMpjK2tQESkdkVPcr28eDstmjamV8c2zBirKluRRCR6HegtsZYnM5CCiGRWrN61PTvm0nbPARmOTCS7JNoLd2fU7WbAOcAHqQ9HRNIl7mUpUzVDoUh1JNoLd78Jtc3sTuD5tEQkIiml6zlF0iPREmh5LQiG5BOROiqSOLuvfYprGr9F69wc2rY6gA5Nm3175XW0DUXBhNoikpBE20CLCHrdAjQG2gFq/xSpg8qXOG/JfZcjytbRtGOfqh+Ylw/5I2shQpH6IdES6DlRt0uBje5emoZ4RKQGYg343mt5G6APjH0xs8GJ1DOJtoF+YmYHAYeFj+kQDqSwKK3RiUjCopPnfgO+l6+qFZGUSLQK9zaC+TtX8W1VrgOnpCcsEUmUZksRyYxEq3DPBw4PJ78WkTpCc3SKZE6iCXQpcCCVTDEmIrVLpU6RzEs0gf438E8zWwrsiSx096FpiUpEYtI1nSJ1R6IJdBrwW6AIKEtfOCISixKnSN2TaALd4u73pDUSEalAiVOk7ko0gS40s/8mGL4vugpXl7GIpIk6CInUbYkm0L7h/wFRy3QZi0iKRU8xpg5CInVbogMpnJzuQEQauvIlTpU6Reo2zQcqkmG6JEUkO2k+UJEMiFVVqxKnSHbRfKAiGfDc4vUsL95Oz465SpwiWUrzgYrUssfmr2X+6s85rtvBzLh8YKbDEZEkaT5QkVoQq8p2WEGnTIYkIjWk+UBF0ky9a0Xqp0QTaEdgmbuXAJhZKzPr5e7z0xeaSHaKLm1CDa/nXDAVimbWLKANRZCXX7N9iEgFjRLc7k/Ajqj7u8JlIhIlUtqMJE0ISp1JX5pSNDNIgDWRlw/5I2u2DxGpINESqLl7pA0Udy8zs2Q7IInUO2m9ljMvH8a+mJp9iUjKJJoEPzazn/JtqfNK4OP0hCSSPTTYu0jDlWgCvQK4B7iJoDfuXGBcuoISqeuUOEUk0YEUNgEXpjkWkaygWVJEBOIkUDO7Cbjf3T+vZP0pQAt3/2s6ghOpSzRmrYhEi1cCLQJeMLPdwCJgM8FYuEcABcAc4DfpDFCkLlCpU0TKqzKBuvtzwHNmdgQwmOB60O3Ao8A4d/8q/SGKZIbm5hSRqiTaBvoh8GEqD2xmjYEFwHp3P8fMDgZmAF2BNcD57v5FKo8pkiiNHiQi8WTyWs6fEUyJlhvenwDMdfdJZjYhvH99poKThkclThGpjkRHIkopM+sMnA1MiVo8DJgW3p4GfL+Ww5IGrPwIQjUaPUhEGoREZ2MZ7O5vxltWDX8AfgG0jlrWwd2LAdy92MzaVxLLOMJrULt00Zeb1Ix61opIshKtwv0foF8Cy+Iys3OATe6+0MxOqu7j3X0yMBmgsLDQ42wuEpMGQhCRmop3HehAYBDQzsx+HrUql2Be0GQMBoaa2fcILonJNbNHgY1m1jEsfXYENiW5f5FKKXGKSKrEK4E2BVqF20VXt24Hkprewd1vAG4ACEug17r7JWZ2B3ApMCn8/1wy+xeJRYlTRFIt3nWgrwKvmtkj7v5JmmOZBDxpZj8C1gKj0nw8aQCUOEUkXRJtAz3AzCYTXKO57zHufkpNDu7u84B54e2twKk12Z9IhBKniKRbogn0KeABgstO9qYvHJGaUeIUkdqSaAItdfc/xd9MJHNqNF7tgqlQNDON0SVpQ1EwobaI1DmJJtAXzOxKYBawJ7KwsllaRGpbdPJM6lrOopl1M1nl5UN+Uv31RCTNEk2gl4b/r4ta5kD31IYjUn01Tp4Refkw9sUURiYi9Vmig8l3S3cgItWlUYREJJMSHcqvBfBzoIu7jwunNztSE2lLpmh+ThHJtESrcKcCCwlGJQJYR9AzVwlUal3KqmxFRGog0QR6uLtfYGYXAbj7V2ZmaYxLpAJV2YpIXZJoAv3azJoTdBzCzA4nqjeuSLqpylZE6ppEE+itwMvAYWY2nWBA+DHpCkokQqVOEamrEu2F+3czWwQMAAz4mbtvSWtk0uCp1CkidVmivXCHA/9w9xfD+wea2ffd/dl0BicNlzoKiUhdl3AVrrvPitxx9y/N7Fbg2bREJQ2WqmxFJFskmkAb1eCxInFpEHgRyTaJJsEFZnYXcB9BT9zxBNeFitSIEqeIZKtEE+h44GZgRnh/NnBTWiKSBkOdhEQkm8VNoGbWGHjO3YfUQjzSQKiTkIhku1htm/tx973ALjNrUwvxSAOg5Cki9UGiVbi7gSIz+zuwM7LQ3X+alqikXlIPWxGpTxJNoC+GfyLVpo5CIlIfJToS0bRwLNwu7r4yzTFJNlkwFYpmVrp6Y8luum/ZyTVA69wc2rY6gA5Nm8Fygr+6YkNRMKG2iEiC4raBApjZucBigvFwMbMCM3s+jXFJtiiaGSSfcjaW7GZZ8TZWbwlq/Lu1bUmvjm3o0LpZbUeYmLx8yB+Z6ShEJIskWoU7ETgWmAfg7ovNrFuaYpJsk5cPY7+t4Y91ecoAVdeKSD2TaAItdfdt5aYA9TTEI1lOPWxFpKFINIEuNbOLgcZmdgTwU+Ct9IUl2WRjyW5++r9vA6iHrYg0GAm1gRKMRNSLYBLtx4BtwNVpikmyyMaS3azesnO/HrZKniLSEFRZAjWzZsAVwHeAImCgu5fWRmBSt0UuTbkm7CSkpCkiDU28KtxpwDfA68BZwL+jkmeDVv6azsilKeokJCINTbwE2tPd8wHM7CHg3fSHJHVRZYMh9FquER5FpGGKl0C/idxw99JyvXClAYg7ilBdGgxBRKQWxUugfcxse3jbgObhfQPc3XPTGp1klKYbExGpXJUJ1N0b11YgUrfoek4Rkaoleh2oNBCaMUVEJDG1nkDN7DDgz0AeUAZMdvc/mtnBwAygK7AGON/dv6jt+BoqzZgiIlI9mSiBlgL/5e6LzKw1sDCcZ3QMMNfdJ5nZBGACcH0G4mtQlDhFRJJT6wnU3YuB4vB2iZl9AHQChgEnhZtNIxi4Xgk0jdRJSEQkeRltAzWzrkBfYD7QIUyuuHuxmbWv5DHjgHEAXbroyz5Z6iQkIlIzGUugZtYKeBq42t23J3qNqbtPBiYDFBYWakaYalInIRGR1MhIAjWzJgTJc7q7PxMu3mhmHcPSZ0dgUyZiq89UZSsikjqZ6IVrwEPAB+5+V9Sq54FLgUnh/+dqO7b6KrrUeVHjuVzdYQkdmjYLRhGq6UhCG4qCCbVFRBqYTJRABwM/AIrMbHG47EaCxPmkmf0IWAuMykBs9UYkaQL79bC9es8SOuz8EFqnKOnl5UP+yNTsS0Qki2SiF+4bBEMBxnJqbcZSX5Wvqt2vunZqsyB5jn0xw1GKiGQ3jURUj6iDkIhI7VECrQc0GIKISO1TAs1y6lkrIpIZSqBZStW1IiKZpQSaRSrrWatSp4hI7VMCzSLPLV7P8uLt9OyYq8QpIpJhSqBZIFLyjCTPGZcPzHRIIiINnhJoHVZZ71oREck8JdA6Sr1rRUTqNiXQOka9a0VEsoMSaB2hwRBERLKLEmgdoOpaEZHsowSaQaquFRHJXkqgGaJSp4hIdlMCrUWxRhJSqVNEJDspgdaSKufoTIcFU6FoZsXlG4qCSbBFRKRGlEDTLGPtnEUzYyfLvHzIH5n+44uI1HNKoGmU8XbOvHwY+2LtHU9EpAFRAk0D9a4VEan/lEBTLOOlThERqRVKoCkUnTxV6hQRqd+UQFNAVbYiIg2PEmgNqcpWRKRhUgKtAVXZiog0XI0yHUA2i4wqpOQpItLwqARaTdHD8S0v3s5x3Q5W8hQRaYBUAq2GSJVtpLNQz465DCvolOGoREQkE1QCTYB62YqISHlKoFUonzjVy1ZERCKUQCuhy1NERKQqSqBRNF+niIgkSgmU2FW1KnWKiEhV6lwCNbMzgT8CjYEp7j4pncdTVa2IiCSjTiVQM2sM3AecBqwD3jOz5919eaqPpZ61IiJSE3UqgQLHAh+5+8cAZvYEMAxIeQI98NWbuWbHSlrn5tC21QF0WN4sDUfJoA1FwYTaIiKSFnUtgXYCPo26vw44LnoDMxsHjAPo0iX5EuPBrZqS16gZXQ9pmfQ+6rS8fMgfmekoRETqrbqWQC3GMt/vjvtkYDJAYWGhx9g+IQOufDDZh4qIiNS5ofzWAYdF3e8MfJahWERERCpV1xLoe8ARZtbNzJoCFwLPZzgmERGRCupUFa67l5rZVcD/EVzG8rC7L8twWCIiIhXUqQQK4O5/A/6W6ThERESqUteqcEVERLKCEqiIiEgSlEBFRESSoAQqIiKSBHNPeiyCjDOzzcAnNdhFW2BLisJJF8WYGooxNRRjamQ6xn9z93YZPH69kNUJtKbMbIG7F2Y6jqooxtRQjKmhGFMjG2KU+FSFKyIikgQlUBERkSQ09AQ6OdMBJEAxpoZiTA3FmBrZEKPE0aDbQEVERJLV0EugIiIiSVECFRERSULWJlAzO9PMVprZR2Y2IWp5HzN728yKzOwFM8uN8diuZvaVmf3TzD4ws3fN7NI0xXmYmb0SHmeZmf0sal2Bmb1jZovNbIGZHVtJrEvTEVu4/4fNbFP5Y1TjdXQzuy1qWVsz+8bM7k1RfJWd50Rfu7TGV+54VZ3rGWGsi81sjZktriTeWj/X4brx4eu8zMx+V8U+rjGz3WbWJo1xVnbOJ5rZ+qjX8XuVPL6Xmf3DzP5lZh+a2c1mZnGOeWOCsVV6jqO2uTZ837WNsS7ynhwftexeMxuTyPGljnH3rPsjmOpsFdAdaAosAXqG694DTgxv/xC4LcbjuwJLo+53BxYDY9MQa0egX3i7NfCvqFhnA2eFt78HzIsXaxriOwHoV/4Y1XgdVwH/jFr24/C1vLcaMeQkcZ4Tfe1qHF8qznW57X4P3FKHzvXJwBzggPB++yr28S7wOjAmTTFWdc4nAtfGeXzz8PGnh/dbAC8BP4nzuB2pOMfAYQTTMX4CtK3kHG8EPgKahsvuTdfrqb/0/mVrCfRY4CN3/9jdvwaeAIaF644EXgtv/x0YEW9n7v4x8HPgpwBm1jL8tf5eWEodFi5vbGZ3hqWy96N/RVax72J3XxTeLgE+ADpFVgORkl0b4LOq9hX+en3dzBaFf4PC5SeZ2Twzm2lmK8xserxf3FHxvQZ8HmNVoq/jV8AHZha5KPwC4MmomM81s/nh6zjHzDqEyyea2WQzmw38uZJ9V3WeE33tqh2fmTUKSy7twm0ahaWhCiWKaHHOdeR4BpwPPF7VvsxsTHQp2cz+amYnhbd3mNntZrYkLIV3qGpfUfFVdq5/DExy9z3hdpsqielwoBVwE3BRgrH+KCwJzjOzBxMo+Vd1zhNxMfCmu88On8su4CpgQhhPKzObGvUZHmFmk4DmYal2elU7T+Ac3w38guD9WZnNwFygQq2XfVuz8r6ZzTKzg8zs383s3ahtuprZ+/FfCkm3bE2gnYBPo+6v49s38VJgaHh7FMEvwkQsAo4Kb/8S+Ie79yf4dX6HmbUExgHdgL7u3huo8sNWnpl1BfoC88NFV4f7/hS4E7ghzi42Aae5ez+CRHBP1Lq+4f56Evx6H1yd2GKozuv4BHChmXUG9rJ/MnsDGODufcPtfhG17hhgmLtfXMl+qzrPV5P4a1et+Ny9DHgUGB1uMwRY4u4JD70W41xHHA9sdPcPE91XDC2Bd9y9D8GPnMtqsC+AHsDx4Q+JV82sfyXbXUSQ+F8HjjSz9lXt1MwOBW4GBgCn8e3nqypVnXOAq8Lk8rCZHRTj8b2AhdEL3H0V0MqCZoibgW3unh9+hv/h7hOAr9y9wN1HV9xlpc+vK1Hn2MyGAuvdfUkCD58E/JeZNS63/M/A9WFsRcCt7v4B0NTMuofb7PcjUDInWxNorNJV5BffD4GfmNlCgiqWr5PY5+nABAvaqeYBzYAuBF+kD7h7KYC7x/o1H3vnZq2Ap4Gr3X17uPjHwDXufhhwDfBQnN00AR40syLgKYJkGfGuu68Lv/wXE1QV1UR1XseXCb4gLwJmlFvXGfi/MObrCL7gIp5396+q2G9V57k6r10y8T0M/Ed4+4fA1Cr2v3/Qsc91RCQJ1cTXwF/D2wup+bnOAQ4iSHTXAU9WUoNxIfBE+B57huCHVVWOBV5198/d/RuC92w8VZ3zPwGHAwVAMUFVeKzHV1b6c4LP8H37Frh/kUBMFQ9S7hybWQuCH963JPJ4d19NUB2+78ejBe3KB7r7q+GiaQTV7hAkzPPD2xdQ8X0sGZCtCXQd+5eIOhOWKtx9hbuf7u7HEHxRrUpwn30JqmMg+BCOCH+RFrh7l/BXYFUfzkqZWROCD9t0d38matWlBF9EEHy5VOgIU841BO0nfYBCgjaiiD1Rt/cSfCkmrTqvY1jVthD4L4LnGe1/CNob84HLCX6MROyME0al55lqvHbJxOfunwIbzewU4DiCdrS4qjjXmFkOcB6JffmVsv/nM/p1+8bdI+/DGp9rgtf5GQ+8C5QRDHa+j5n1Bo4A/m5mawiSaaQat7JYE2pGiBFLZZ/tje6+N0zgDxL7nC8j+GxEx96doI2zhCQ/w+X2F+scH05QO7UkfH06A4vMLK+KXf0GuJ7EvodnAOebWQ/Aa1iDISmSrQn0PeAIM+tmZk0JPszPA0SqlcysEUFbzQPxdhZWxdxJ8GUKQSeA8ZFf4WbWN1w+G7gi/CLEzA5OYN9GUDr6wN3vKrf6M+DE8PYpQLwPRRugOPwC+QFBh4u0SOJ1/D1B1dPWcsvbAOvD29Xt6Vzpeab6r10y8U0hqMp90t33xgs2zrmGoPSzwt3XxdsXsAYoCNtfDyP+j6uaeJbgNST8gm5KxZlCLgImunvX8O9QoJOZ/VsVsb4LnBi24+WQQH8Eqv5sd4zabjhBM0N504HvmtmQ8DHNCZo6Ij2LZxO0iRKuj1QDfxMmxipVdo7dvcjd20deH4IfAv3cfUNl+3L3FcBy4Jzw/jbgCzM7PtzkB8Cr4bpVBD+WbkalzzojKxNoWIV6FUGi+4DgC25ZuPoiM/sXsILgS7ayqrfDLbyMhaB65H/cPbLtbQTVpe9b0OU/chnEFGBtuHwJUdUvVRhM8EE4xSp2v78M+H24r98QtLGWl8O3pcv7gUvN7B2Cdqt4Jbi4zOxx4G2CNq11ZvajcFWiryMA7r7M3afFWDUReMrMXqea0zfFOc+JvHY1je95gk4ziVbfVnWuIUgGVVXfRp/rN4HVBO1gdxK00ddIFef6YaB7+F5/Arg0qoQbHfuscstmhctjxuru6wnOzXyCXr7LgW1VxRjnnP8u0vmHoG/CNTEe/xVBp6ObzGxlGNN7BD1dAX4NHGRmS8P3zsnh8skEn+t4/RrinePqup2gtBpxKUHb/vsEVdW/ilo3A7gEtX/WGRrKr46zoAfwaHc/P+7GklIW9Ny9292Pj7txao5X7861mbVy9x1hCXQW8LC7l0/EIlmppm0nkkZm9iuCX9NjMhxKg2PBBfw/5tueuOk+Xn091xPD6tRmBNWnz2Y2HJHUUQlUREQkCVnZBioiIpJpSqAiIiJJUAIVERFJghKoSDWY2d7w0oVlFoxF+/PwWtmqHtPVzBK55ElEsogSqEj1RMZM7UUwPOD3gFvjPKYriV0zLCJZRL1wRarBzHa4e6uo+90JLtRvC/wb8BeCwd4BrnL3t8KBL/6dYLCBaQQj40wCTgIOAO5z9/+ttSchIimhBCpSDeUTaLjsC4KZRkqAMnffbWZHAI+7e6EFU3td6+7nhNuPI5hz89dmdgDBSD6jwgHGRSRLaCAFkZqLDJreBLjXzAoIxi3tUcn2pwO9zWxkeL8NwUDtSqAiWUQJVKQGwircvQRztd7Kt7PlNAJ2V/YwYLy7/1+tBCkiaaFORCJJMrN2BLPU3BsOvl7ZbDklBHOqRvwf8OPI7B9m1sOCCdtFJIuoBCpSPc0tmGi9CcE8mH8BItNa3Q88bWajgFf4drac94HScPaPR4A/EvTMXRROj7UZ+H7thC8iqaJORCIiIklQFa6IiEgSlEBFRESSoAQqIiKSBCVQERGRJCiBioiIJEEJVEREJAlKoCIiIkn4/9wc1flg/Kx7AAAAAElFTkSuQmCC", + "image/png": 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", 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lcKa7Rx79QESksqn0uJcFGzdu7NqyZcstNSFRFhUV2caNG5sDCxKtz1iSNLN2wG+Bru7+jZk9BZwNdAVecfdxZjYGGANclak4RETKqnhyrMWlxz0KCwt/vW7dugnr1q3rTs0Y/7sIWFBYWPjrRCszXd1aD2hoZrsISpCfA1cDx4XrJwEzUZIUkSpEyTG5ww8/fAMwONtxVJaMJUl3X2Nm44FVwDfAdHefbmat3X1tuM1aM2uVaH8zGwmMBOjQQW9MEck8JUcpLpPVrfsBQ4BOwFfA02Z2btT93f0B4AEI7pPMRIwiIjHqlCOJZLK6tT+wwt03ApjZc0BfYL2ZtQ1LkW2BDRmMQUQkLd3zKMlkMkmuAvqYWSOC6tYTgA+Ar4HzgHHh/9MyGIOISFLqtSrpZLJNcpaZPQPMAQqBDwmqT5sAT5nZrwgS6bBMxSAikoyqVyWKjPZudfcbgBuKLd5JUKoUEal0Kj1KaWjEHRGpFdRzVcpCSVJEajxVrUpZKUmKSI2lqlUpLyVJEalxVLUqFUVJUkSqrg8egfnPlGqX9QU76Lzpay4HmjarR4sm+9C6QQ4sIvhX3bTJhVPGZTuKWktJUkSqrvnPwLr5QaKIYH3BDlZs+hqATi0a07ppTiajk1pASVJEqrY2uXD+S2k3Kz5qTh9VrUoFqAnTnIhILadh5SRTlCRFpFpTgpRMUnWriFRLur1DKoOSpIhUK7q9QyqTkqSIVBsaOUcqm5KkiFR5qlqVbImcJM1sP+AAgrkhV7p7UcaiEhEJrS/YodKjZE3KJGlmzYHfAOcADYCNQA7Q2szeBe5191czHqWI1DqPz1pF3totFOwoBFR6lOxIV5J8BvgbcLS7fxW/wswOB35uZp3d/aEMxScitUx81eqTDQppmlOPPw1UgpTsSJkk3f3EFOtmA7MrPCIRqZUS9VrttDMYWq6bEqRkSaQ2STMzYDjQ2d1vNLMOQBt3fy+j0YlIjRZLjEDiWzoe0dirkl1RO+7cCxQBPwZuBAqAZ4HeGYpLRGq44rdzqFOOVEVRk+SR7t7TzD4EcPcvzaxBBuMSkRouVoJUhxypyqImyV1mVhdwADNrSVCyFBGJLL56ddHarRzZaX8lSKnSog5wfhcwFWhlZn8E3gT+lLGoRKTGiVWvxtoeu7ZtxpD8dlmOSiS1SCVJd59sZrOBEwADfuruizMamYjUGJqpQ6qrqL1b7wSmuPs9GY5HRGoYJUipzqK2Sc4BrjWzLgTVrlPc/YPMhSUi1Z3GW5WaIGp16yRgkpntD5wO/NnMOrj7wRmNTkSqJc3WITVFaWcB+QFwKNARWFTh0YhItZVoYACVHqW6i9om+WfgNGA58BRwU/GxXEWkdko0nJxKj1JTRC1JrgCOcvdNmQxGRKqfaXPX7LnnUYlRapp0U2Ud6u5LgPeADuGYrXu4+5xMBiciVVPxQQG6tm3GlAuPynJUIhUvXUnyCmAkcFuCdU4wlquI1BKJqlY1KIDUZOmmyhoZPjzF3XfErzMzDc8vUsuoalVqm6htkm8DPSMsE5EaKFaCVNWq1Dbp2iTbAO2AhmbWg2BIOoBmQKN0BzezfYEJQHeC6tlfAkuBKQS3kawEznT3L8sUvYhkVKLqVVWtSm2SriR5MjACaA/cHre8ALgmwvHvBF529zPCqbUahfu94u7jzGwMMAa4qrSBi0hmaUAAkfRtkrGRdk5392dLc2AzawYcQ5BkcfdvgW/NbAhwXLjZJGAmSpIiVYaGkxP5TtRh6Z41s4FANyAnbvmNKXbrDGwEHjGzPGA28DugtbuvDfdfa2atEu1sZiMJetbSoYM+oCKZlqxqVQlSarOoI+7cT1BVejxBG+MZBPdOpjt2T2CUu88KZxIZEzUwd38AeACgV69eHnU/ESk9Va2KJBa1d2tfdz/MzD5y9/9nZrcBz6XZZzWw2t1nhc+fIUiS682sbViKbAtsKFvoIlJeqloVSS1qkvwm/H+7mR0AbAY6pdrB3deZ2Wdmdoi7LyWYsHlR+O88YFz4/7QyRS4i5aLSo0h6UZPki+HtHLcSzC3pBNWu6YwCJoc9Wz8BzgfqAE+Z2a+AVcCw0gYtIuWjiZBFoonaceem8OGzZvYikOPuWyLsNxfolWDVCZEjFJEKo+pVkdJJN5jAaSnW4e7p2iVFpIpQ9apI6aUrSZ6aYp2TvvOOiGSRJkIWKZ90gwmcX1mBiEjF0UTIIhUj6n2S1ydanmYwARHJAlWrilScqL1bv457nAMMAhZXfDgiUlbqlCNS8aL2bt1r0mUzGw/8PSMRiUipaDg5kcyJWpIsrhHB2KwikkWqWhXJrKhtkvMJerMC1AVaAmqPFMkC9VgVqTxRS5KD4h4XAuvdvTAD8YhICsVLjio9imRW1DbJT81sP+DAcJ/W4WACczIanYjsoaHkRCpf1OrWmwgmT17Od9WuDvw4M2GJSIx6rYpkT9Tq1jOBg9z920wGIyJ7U8cckeyKmiQXAPuiuR9FKo2qV0WyL2qS/F/gQzNbAOyMLXT3wRmJSqQWiu+1Cuq5KlIVRE2Sk4A/A/OBosyFI5LGB4/A/GeyHUVG5K3dwsHf7qZRg7rBgmbQosk+tF6UE0xVXhutmw9tcrMdhdRiUZPkJne/K6ORiEQx/5ka9cW5vmAHm7YFlTPbwwTZrW3zLEdVhbTJhdwzsh2F1GJRk+RsM/tfgqHo4qtbdQuIVL42uXD+S9mOotyKd8oBGJLfjm6qWhWpMqImyR7h/33ilukWEJEyUqcckeoh6mACx2c6EJGaTsPJiVQ/mk9SpBJoODmR6knzSYpkkEbLEaneNJ+kSAZojkeRmkHzSYpUMA0lJ1JzaD5JkQqkXqsiNYvmkxQpBw0lJ1KzRU2SbYGF7l4AYGZNzKybu8/KXGgiVVeiNsfY/6peFak5oibJ+4Cecc+3J1gmUiuozVGk9oiaJM3dY22SuHuRmZW1049ItaTbOURqn6iJ7hMz+y1B6RHgEuCTzIQkUrXodg6R2itqkrwIuAu4lqCX6yvAyEwFJVJVqGpVpHaLOpjABuDsDMciUmWoalVEIE2SNLNrgXvd/Ysk638MNHL3FzMRnEg2qPQoIjHpSpLzgRfMbAcwB9hIMHbrwUA+MAP4UyYDFKksKj2KSHEpk6S7TwOmmdnBQD+C+yW3Ao8BI939m3QnMLO6wAfAGncfZGb7A1OAjsBK4Ex3/7I8f4RIWSWavkqlRxGJidom+THwcRnP8TuCGUOahc/HAK+4+zgzGxM+v6qMxxYpM01fJSLpZPReRzNrDwwE/ghcES4eAhwXPp4EzERJUiqRqlVFJKpMDwjwF+D3QNO4Za3dfS2Au681s1aJdjSzkYS3mXTooC8wKT/d7ygipRV1FpB+7v5WumXF1g8CNrj7bDM7rrSBufsDwAMAvXr18jSbiySl5CgiZRW1JPlXSo7TmmhZvH7AYDP7CUGP2GZm9hiw3szahqXItsCG0gYtEoWSo4iUV7r7JI8C+gItzeyKuFXNCOaVTMrdrwauDo9zHHClu59rZrcC5wHjwv+nlTV4kUSUHEWkoqQrSTYAmoTbxbcrbgXOKOM5xwFPmdmvgFXAsDIeR6QEDQQgIhUp3X2SrwGvmdlEd/+0rCdx95kEvVhx983ACWU9lkhxie51VI9VEakIUdsk9zGzBwgGANizj7v/OBNBiUSlex1FJJOiJsmngfuBCcDuzIUjEo3udRSRyhA1SRa6+33pNxPJrPUFO9i0bSfXLFW7o4hkXtQk+YKZXQJMBXbGFiabHUQkEx6ftYrOm74GlBxFpHJETZLnhf+PjlvmQOeKDUcksVjb45MNoFOLxky58KhshyQitUDUAc47ZToQkUSKtz12atGY1k1zshyViNQWUYela0QwQHkHdx8ZTp11iCZblkybNncNi9Zu3VO92nqREqSIVJ6o1a2PALMJRt8BWE3Q41VJUjIiVoJctHYrXds2+656dVF24xKR2iVqkjzI3c8ys3MA3P0bM7MMxiW1VLIh5UREsiFqkvzWzBoSdNbBzA4irperSEXQkHIiUtVETZI3AC8DB5rZZIIZPkZkKiipfeITpAYGEJGqImrv1n+b2RygD2DA79x9U0YjkxpPY66KSFVXJ8pGZjaUYNSdl8IerYVm9tOMRiY1XqxjDgTVq0qQIlLVRK5udfepsSfu/pWZ3QA8n5GopEZL2nNVRKSKiZokE5U4o+4rAqjnqohUP1ET3QdmdjtwD0EP11EE902KRKKeqyJSHUVNkqOA64Ap4fPpwLUZiUhqFE1pJSLVWdokaWZ1gWnu3r8S4pEaIlnVqhKkiFQnaZOku+82s+1m1tzdt1RGUFL9FR9zVclRRKqjqNWtO4D5ZvZv4OvYQnf/bUaikmpLPVdFpCaJmiRfCv+JJJWoc46ISHUWdcSdSeHYrR3cfWmGY5JqRp1zRKSmijqf5KnAeKAB0MnM8oEb3X1wBmOTKk6dc0Skpota3ToWOAKYCeDuc82sU4ZikmpA9z2KSG0QNUkWuvuWYlNIegbikSpOVasiUptETZILzOxnQF0zOxj4LfB25sKq5T54BOY/k+0o9rK+YAebtu2k845CLgeaNqtHiyb70HpRDiyqxEDWzYc2uZV4QhGpzSLNAkIw4k43gomWHwe2AJdlKCaZ/0yQDKqI9QU7WLHpawp2FNI0px6dWjSmW9vmtG6aU/nBtMmF3DMq/7wiUiulLEmaWQ5wEfADYD5wlLsXVkZgtV6bXDg/+3fdaDJkEanN0lW3TgJ2AW8ApwA/RCXIGk+TIYuIBNIlya7ungtgZg8B72U+JMmWRLd0qOeqiNRm6ZLkrtgDdy8s1rtVahDd0iEiUlK6JJlnZlvDxwY0DJ8b4O7eLKPRSaVQu6OISGIpk6S7162sQKTy6Z5HEZHUot4nWWpmdiDwN6ANUAQ84O53mtn+BJM3dwRWAme6+5eZikMSU/WqiEh6GUuSQCHwP+4+x8yaArPDqbZGAK+4+zgzGwOMAa7KYBwSUq9VEZHSyViSdPe1wNrwcYGZLQbaAUOA48LNJhGMB6skmWHFS44qPYqIpJfJkuQeZtYR6AHMAlqHCRR3X2tmrZLsMxIYCdChg77Iy0rtjiIiZZfxJGlmTYBngcvcfWvU20jc/QHgAYBevXppMPUyULujiEj5ZDRJmll9ggQ52d2fCxevN7O2YSmyLbAhkzHUVrqtQ0Sk/KIOcF5qFhQZHwIWu/vtcav+DpwXPj4PmJapGGorJUgRkYqRyZJkP+DnwHwzmxsuuwYYBzxlZr8CVgHDMhhDraGeqyIiFS+TvVvfJBiZJ5ETMnXe2kbjrYqIZE6l9G6VipcoOSoxiohULCXJaki9VkVEKoeSZDWjTjkiIpVHSbIaUKccEZHsUJKs4jScnIhI9ihJVlHrC3bw2/97RyVHEZEsUpKsYh6ftYq8tVso2FHIrG+/UMlRRCSLlCSrkFjV6pMNCmmaU48/DVTpUUQkm5Qkq4j4tsdOLRrTumkO3ZQgRUSySkkyyxJNZdV6UU6WoxIREVCSzJqUI+YsynJwIiICKElmhUbMERGpHpQkK1GiqlUlRxGRqktJspKo9CgiUv0oSWaQhpMTEanelCQzRMPJiYhUf0qSFUztjiIiNYeSZAXRJMgiIjWPkmQFUKccEZGaSUmynDQJsohIzaUkWQbqtSoiUjsoSZaSeq2KiNQeSpKlFCtBquQoIlLzKUlGEF+9umjtVo7stL8SpIhILVAn2wFUB9PmrmHR2q0AdG3bjCH57bIckYiIVAaVJNN4fNYqZq34giM77c+UC4/KdjgiIlKJlCSTKD44gEqPIiK1j5JkAhocQEREQElyLxp3VURE4ilJonFXRUQksVqdJJUcRUQklVqbJNXuKCIi6dSaJBk/IABozFUREUkvK4MJmNkAM1tqZsvMbExlnDN+QAAISo9KkCIikkqllyTNrC5wD3AisBp438z+7u6LMnG+WAly0dqtdG3bTAMCiIhIZNmobj0CWObunwCY2ZPAEKDCk+S7915A53XzuRxomlOPFjv3gUdyKvo0FW/dfGiTm+0oRERqvWwkyXbAZ3HPVwNHFt/IzEYCIwE6dCh7lWjTnHq0aLIPrZtWg+QY0yYXcs/IdhQiIrVeNpKkJVjmJRa4PwA8ANCrV68S66Poc8mDZdlNREQEyE7HndXAgXHP2wOfZyEOERGRlLKRJN8HDjazTmbWADgb+HsW4hAREUmp0qtb3b3QzC4F/gXUBR5294WVHYeIiEg6WRlMwN3/AfwjG+cWERGJKiuDCYiIiFQHSpIiIiJJKEmKiIgkoSQpIiKShLmX6T79SmVmG4FPy7h7C2BTBYaTCYqxYijGiqEYK0ZViPH77t4yyzFUa9UiSZaHmX3g7r2yHUcqirFiKMaKoRgrRnWIUdJTdauIiEgSSpIiIiJJ1IYk+UC2A4hAMVYMxVgxFGPFqA4xSho1vk1SRESkrGpDSVJERKRMlCRFRESSqPJJ0swGmNlSM1tmZmPilueZ2TtmNt/MXjCzZgn27Whm35jZh2a22MzeM7PzMhTngWb2aniehWb2u7h1+Wb2rpnNNbMPzOyIJLEuyERs4fEfNrMNxc9RitfRzeymuGUtzGyXmd1dQfElu85RX7uMxhd33FTXeUoY51wzW2lmc5PEmrHrHJ4j4bUO140KX+eFZnZLimNcbmY7zKx5BuNMds3HmtmauNfyJ0n272Zm/zGz/5rZx2Z2nZklmtQ9fp9rIsaW9DrHbXNl+L5rkWBd7D05Km7Z3WY2Isr5pQpx9yr7j2AqreVAZ6ABMA/oGq57Hzg2fPxL4KYE+3cEFsQ97wzMBc7PQKxtgZ7h46bAf+NinQ6cEj7+CTAzXawZiO8YoGfxc5TidVwOfBi37OLwtby7FDHUK8N1jvralTu+8l7nYtvdBlxf2dc5zbU+HpgB7BM+b5XiGO8BbwAjMhRjqms+Frgyzf4Nw/1PCp83Av4J/CbNftsq4joTTBz/L4JBTlokuc7rgWVAg3DZ3Zl6PfUvc/+qeknyCGCZu3/i7t8CTwJDwnWHAK+Hj/8NnJ7uYO7+CXAF8FsAM2sc/up+PyxtDgmX1zWz8WHp6qP4X4Mpjr3W3eeEjwuAxUC72GogVkJrDnye6ljhr9A3zGxO+K9vuPw4M5tpZs+Y2RIzm5zul3NcfK8DXyRYFfV1/AZYbGaxm6PPAp6Ki/lUM5sVvo4zzKx1uHysmT1gZtOBvyU5dqrrHPW1K3V8ZlYnLIG0DLepE5ZqSpQMYtJc59i5DDgTeCLZccLtRsSXdM3sRTM7Lny8zcz+aGbzwpJ061THKhZjsmt9MTDO3XeG221IEtdBQBPgWuCciPH+KizRzTSzByOU4FNd8yh+Brzl7tPDv2U7cCkwJoyniZk9EvcZPt3MxgENw9Lp5FQHj3Cd7wB+T/D+TGYj8ApQovbKvqsh+cjMpprZfmb2QzN7L26bjmb2UfqXQjKpqifJdsBncc9X890bdQEwOHw8jOCXXRRzgEPDx38A/uPuvQl+Zd9qZo2BkUAnoIe7Hwak/EAVZ2YdgR7ArHDRZeGxPwPGA1enOcQG4ER370nwZX9X3Loe4fG6EvwK71ea2BIozev4JHC2mbUHdrN3wnoT6OPuPcLtfh+37nBgiLv/LMlxU13ny4j+2pUqPncvAh4Dhofb9AfmuXukocQSXOeYo4H17v5xlOMk0Rh4193zCH7EXFCOY8V0AY4Ofyy8Zma9k2x3DkGCfwM4xMxapTqomR0AXAf0AU7ku89XKqmuOcClYQJ52Mz2S7B/N2B2/AJ3Xw40saDJ4Dpgi7vnhp/h/7j7GOAbd8939+ElD5n07+tI3HU2s8HAGnefF2H3ccD/mFndYsv/BlwVxjYfuMHdFwMNzKxzuM1eP/QkO6p6kkxUSor9cvsl8Bszm01QHfJtGY55EjDGgrajmUAO0IHgy/J+dy8EcPdEv8oTH9ysCfAscJm7bw0XXwxc7u4HApcDD6U5TH3gQTObDzxNkBBj3nP31eEX/FyCap3yKM3r+DLBl+A5wJRi69oD/wpjHk3wJRbzd3f/JsVxU13n0rx2ZYnvYeAX4eNfAo+kOP53ASe+zjGxJFMe3wIvho9nU/7rDMEk6/sRJLPRwFNJaiLOBp4M32PPEfx4SuUI4DV3/8LddxG8Z9NJdc3vAw4C8oG1BFXXifZPVopzgs/wPXsWuH8ZIaaSJyl2nc2sEcGP6+uj7O/uKwiqrvf8QLSgnXdfd38tXDSJoIocgqR4Zvj4LEq+j6WSVfUkuZq9SzbtCUsH7r7E3U9y98MJvpCWRzxmD4KqEwg+aKeHvyzz3b1D+Gsu1QcwKTOrT/CBmuzuz8WtOo/gywaCL5ASnU+KuZygPSMP6EXQZhOzM+7xboIvvjIrzesYVovNBv6H4O+M91eC9r9c4EKCHxwxX6cJI+l1phSvXVnic/fPgPVm9mPgSIJ2rZRSXGfMrB5wGtG+3ArZ+zMY/5rtcvfYe7Dc1zm0GnjOA+8BRQSDcO9hZocBBwP/NrOVBAkzVuWaLN5IVf4JYkn22V7v7rvDJP0gia/5QoLPRnzsnQnaHAso42e42PESXeeDCGqZ5oWvT3tgjpm1SXGoPwFXEe37dgpwppl1AbyctRFSAap6knwfONjMOplZA4IP7N8BYlVAZlaHoO3k/nQHC6tNxhN8YULQ8D4q9mvazHqEy6cDF4VfeJjZ/hGObQSlnMXufnux1Z8Dx4aPfwyke+M3B9aGXxI/J+jkkBFleB1vI6gm2lxseXNgTfi4tD2Ik15nSv/alSW+CQTVrk+5++5UB09znSEowSxx99Vp4gRYCeSHbaEHkv7HU3k9T/AaEn4JN6DkLBXnAGPdvWP47wCgnZl9P0W87wHHhu1q9YjQP4DUn+22cdsNJWgSKG4y8CMz6x/u05CgWSLWY3c6QRsl4fpYle2uMPmllOw6u/t8d28Ve30Ikn1Pd1+X7FjuvgRYBAwKn28BvjSzo8NNfg68Fq5bTvCj6DpUiqwSqnSSDKs7LyVIZosJvsQWhqvPMbP/AksIvkiTVZMdZOEtIARVGX9199i2NxFUbX5kQXf52C0EE4BV4fJ5xFWVpNCP4M3+YyvZdf0C4LbwWH8iaPMsrh7flRLvBc4zs3cJ2pHSlcTSMrMngHcI2phWm9mvwlVRX0cA3H2hu09KsGos8LSZvUEppwdKc52jvHblje/vBB1VolS1prrOEHzZp6pqjb/ObwErCNqkxhO0l5dbimv9MNA5fK8/CZwXV1qNj39qsWVTw+UJ43X3NQTXZhZB79lFwJZUMaa55rfEOtwQ9BW4PMH+3xB09LnWzJaGMb1P0IMU4GZgPzNbEL53jg+XP0DwuU7XzyDddS6tPxKUOmPOI2hr/4igWvnGuHVTgHNRe2SVoGHpqggLetYOd/cz024sFcqCHrF3uPvRaTcu/7lq5HU2sybuvi0sSU4FHnb34slWpNqpiHYOKSczu5HgV/GILIdS61hwE/vFfNfDNZPnqsnXeWxY9ZlDUNX5fHbDEakYKkmKiIgkUaXbJEVERLJJSVJERCQJJUkREZEklCRFijGz3WGX/4UWjJ16RXgfaap9OppZlFuFRKQaUZIUKSk2vmc3gmHufgLckGafjkS7n1ZEqhH1bhUpxsy2uXuTuOedCW5UbwF8H3iUYABygEvd/e1w4IcfEtxsP4lg9JdxwHHAPsA97v5/lfZHiEiFUJIUKaZ4kgyXfUkwu0UBUOTuO8zsYOAJd+9lwZRRV7r7oHD7kQTzNd5sZvsQjFYzLBzwWkSqCQ0mIBJNbBDv+sDdZpZPMMZmlyTbnwQcZmZnhM+bEwwcriQpUo0oSYqkEVa37iaY5/MGvpuhpQ6wI9luwCh3/1elBCkiGaGOOyIpmFlLgplR7g4HA082Q0sBwXycMf8CLo7NOGFmXSyY0FtEqhGVJEVKamjBRNz1CeZQfBSITZd0L/CsmQ0DXuW7GVo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", 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", 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", 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" ] @@ -10968,7 +11022,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **65-69** population up to 15 Dec 2021" + " ## COVID vaccination rollout among **65-69** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -10999,7 +11053,7 @@ }, { "data": { - "image/png": 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", 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", 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", 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", 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", + "image/png": 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", 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", 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", 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", + "image/png": 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", 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", + "image/png": 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", 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", + "image/png": 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", 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", + "image/png": 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", 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", + "image/png": 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xsQHFidblRPnCZvYrM1tsZovM7Ckzq2dmR5rZP8zs4+D3EVHGICJyqEquP76/8t90atUk2zvmLCosLGwaJJa0V1xcbIWFhU2BRYnWR1ZJmllr4JdAJ3ffZWZPAxcCnYDX3H2smY0GRgPXRxWHiEhl6frjwYqKiv5rw4YN4zds2NCFiAutalIMLCoqKvqvRCujbm6tDdQ3s71AA2AdcANwarB+EjATJUkRqWFK91699sh3OGnJQ7CkmgPJzYOzx1bzi5bthBNO2AQMTHUc1SWyJOnua83sHmA1sAuY7u7Tzaylu68PtllvZi0S7W9mI4ARAG3bZvdfbiJSfcqsHifcCRsWxpKWZI0om1uPAAYB7YEvgWfM7OKw+7v7OGAcxO6TjCJGEZF4SWfryM2DS6elKDpJhSibW/sCK929EMDMngd6AxvNrFVQRbYCNkUYg4hIKPEJUtcepUSUF11XAz3NrIGZGXA6sBR4Cbgk2OYSYGqEMYiIJKUEKWWJ8prk+2b2LDAPKAI+JNZ82gh42sx+RiyRDo0qBhGR8qj3qiQTae9Wd78NuK3U4j3EqkoRkZQonRw1eo6URSPuiEhWSdo5RySOkqSIZAU1rUplKEmKSMZT9SiVpSQpIhlL1aMcKiVJEclIqh6lKihJikhGUfUoVUlJUkQygm7rkCgoSYpIWlNylCgpSYpI2tJ1R4makqSIpB1dd5TqoiQpImlF1aNUJyVJEUkLqh4lFZQkRaTGKkmMgDrmSEqETpJmdgRwFLALWOXuxZFFJSJZr3SzqpKjpEK5SdLMmgK/AC4C6gKFQD2gpZm9Bzzk7q9HHqWIZBVNgiw1RbJK8lngT8D33f3L+BVmdgLwEzPr4O6PRRSfiGQRXXeUmqbcJOnuZ5Szbi4wt8ojEpGspF6rUhOFuiZpZgYMAzq4++1m1hbIdfcPIo1ORDKeqkepycJ23HkIKAZ+ANwObAeeA3pEFJeIZAFVj1LThU2SJ7l7NzP7EMDdvzCzuhHGJSIZTNWjpIuwSXKvmdUCHMDMmhOrLEVEQtE9j5KOwibJB4AXgBZm9htgCHBzZFGJSMaZOn8tS9Zvo1OrJkqOkjZCJUl3n2xmc4HTAQN+5O5LI41MRDJCSQVZkiCnXN4r1SGJhBa2d+v9wBR3fzDieEQkA5TXtCqSTsI2t84DbjazjsSaXae4+5zowhKRdKXh5CSThG1unQRMMrMjgfOA35pZW3c/JtLoRCRtqMeqZKKKzgLyXeA4oB2wpMqjEZG0Uzo5qnKUTBL2muRvgXOBFcDTwB2lx3IVkeyjwQAk04WtJFcCvdx9c5TBiEh6UNOqZItkU2Ud5+7LgA+AtsGYrfu5+7wogxORmkfVo2STZJXktcAI4HcJ1jmxsVxFJAuoepRslGyqrBHBw7PdfXf8OjOrF1lUIlJjqGOOZLOw1yTfAbqFWCYiGaZktBwlR8lGya5J5gKtgfpm1pXYkHQATYAGyQ5uZocD44EuxJpnfwosB6YQu41kFXC+u39RqehFJBLxI+ZoODnJZskqybOA4UAb4N645duBG0Mc/37gVXcfEkyt1SDY7zV3H2tmo4HRwPUVDVxEql6iptVOrZpoODnJWubuyTcyO8/dn6vQgc2aAAuADh73Ima2HDjV3debWStgprsfW96xunfv7nPmaBQ8yVJzJsDCZyN/mY3bd7Ny81cANK5Xm2aNDqNlY3U92G/DQsjNg0unpTqS0Mxsrrt3T3Uc6SzssHTPmVl/oDNQL2757eXs1gEoBCaYWT4wF7gaaOnu64P915tZi0Q7m9kIYj1radtW10Akiy189pv/oCMSnyDbN2uo5JhIbh7kDUl1FFLNwo648wixptLTiF1jHELs3slkx+4GjHT394OZREaHDczdxwHjIFZJht1PJCNFWMHE3/f4P4Pz6KmOOSL7he3d2tvdjzezj9z9/5nZ74Dnk+yzBljj7u8Hz58lliQ3mlmruObWTZULXUQOhe57FEkubJLcFfzeaWZHAVuA9uXt4O4bzOxzMzvW3ZcTm7B5SfBzCTA2+D21UpGLSKXovkeR8MImyVeC2znuJja3pBNrdk1mJDA56Nn6KXApkAM8bWY/A1YDQysatIhUnJKjSMWF7bhzR/DwOTN7Bajn7ltD7DcfSNSz6vTQEYrIIVFyFKm8ZIMJnFvOOtw92XVJEUkxjZgjUnnJKslzylnnJO+8IyIpUlJBasQckcpLNsD5pdUViIhUnUTTWYlIxYW9T/LWRMuTDCYgItVMt3WIVK2wvVu/intcDxgALK36cESkMtQ5RyQaYXu3HjDpspndA7wUSUQiUiGJmlaVHEWqRthKsrQGxMZmFZEUUdOqSPTCXpNcSKw3K0AtoDmg65EiKaLqUaR6hK0kB8Q9LgI2untRBPGISDlUPYpUr7DXJD8zsyOAo4N9WgaDCcyLNDoR2U/Vo0j1C9vcegcwHFjBN82uDvwgmrBEpMTG7bvZvGMPNy7/ZjorJUeR6hG2ufV84Dvu/nWUwYjIgf78/mo6BJMhq3oUqX5hk+Qi4HA096NItYi/9viXutC+WUMNKyeSAmGT5P8CH5rZImBPyUJ3HxhJVCJZKtGgAO33NKRl43opjkwkO4VNkpOA3wILgeLowhHJTuWOmDNBCVIkVcImyc3u/kCkkYhkKfVaFam5wibJuWb2v8SGootvbtUtICKVpHseRWq+sEmya/C7Z9wy3QIiUkmqHkXSQ9jBBE6LOhCRbKDqUSS9aD5JkWqi6lEk/Wg+SZGIqXoUSV+aT1IkQqoeRdKb5pMUiUh8glT1KJKeNJ+kSBVT86pI5tB8kiJVSM2rIpklbJJsBSx29+0AZtbIzDq7+/vRhSaSPlQ9imSmsEnyYaBb3POdCZaJZCVVjyKZK2ySNHcvuSaJuxebWWU7/YhkBFWPIpkvbKL71Mx+Sax6BLgS+DSakERqtnJn7BCRjBI2SV4BPADcTKyX62vAiKiCEqmJlBxFsk/YwQQ2ARdGHItIjaXrjiLZqdwkaWY3Aw+5+7/LWP8DoIG7vxJFcCI1gQYFEMleySrJhcDLZrYbmAcUEhu79RigAJgB/E+UAYqkijrmiEi5SdLdpwJTzewYoA+x+yW3AU8CI9x9V7IXMLNawBxgrbsPMLMjgSlAO2AVcL67f3Eob0KkKunao4iUCHtN8mPg40q+xtXEZgxpEjwfDbzm7mPNbHTw/PpKHlukSunao4jEi/ReRzNrA/QHfgNcGyweBJwaPJ4EzERJUqrCnAmw8NlK7bpx+24279hDh91F/KUutG/WkJZ168ESYj+ptGEh5OalOAiR7JQT8fF/D/waKI5b1tLd1wMEv1sk2tHMRpjZHDObU1hYGHGYkhEWPhtLKBW0cftuVm7+iu27i2hcr3YsQTauF0GAlZSbB3lDUh2FSFYKOwtIH3eflWxZqfUDgE3uPtfMTq1oYO4+DhgH0L17d0+yuUhMbh5cOi3UpvuvPa5TxxwRSSxsc+sfOHic1kTL4vUBBprZD4n1iG1iZk8CG82slbuvN7NWwKaKBi1yKNQxR0TCSnafZC+gN9DczK6NW9WE2LySZXL3G4AbguOcClzn7heb2d3AJcDY4PfUygYvUlHqmCMiFZGskqwLNAq2axy3fBtQ2YskY4GnzexnwGpgaCWPIxKa7nkUkcpIdp/kG8AbZjbR3T+r7Iu4+0xivVhx9y3A6ZU9lkhFqXoUkcoKe03yMDMbR2wAgP37uPsPoghKpCqoehSRQxU2ST4DPAKMB/ZFF45I1VD1KCJVIWySLHL3h5NvJpJ6GpBcRKpK2CT5spldCbwA7ClZWNbsICLV7c/vryZ//VYAblyuBCkiVSNskrwk+D0qbpkDHao2HJGKK6kc/1I3NmKOmldFpKqEHeC8fdSBiFRU6Y45JcPJTbm0V4ojE5FMEXZYugbEBihv6+4jgqmzjtVky5IqiTrmtFxSg8ZbFZGMELa5dQIwl9joOwBriPV4VZKUalXubR2pnq1DRDJO2CT5HXe/wMwuAnD3XWZmEcYlcgCNtyoiqRA2SX5tZvWJddbBzL5DXC9XkahNnb+WJeu3KTmKSLUKmyRvA14FjjazycRm+BgeVVAiJUoqyCXrt9GpVROmXK5OOSJSfcL2bv2Hmc0DegIGXO3umyONTLJeos45IiLVKWzv1sHAP919WvD8cDP7kbu/GGVwkp005qqI1BShm1vd/YWSJ+7+pZndBrwYSVSStTTmqojUJGGTZM4h7CuSlKpHEamJwia6OWZ2L/AgsR6uI4ndNylySHRrh4jUZGGT5EjgFmBK8Hw6cHMkEUnWUNOqiNR0SZOkmdUCprp732qIR7KAmlZFJF0kTZLuvs/MdppZU3ffWh1BSWZS06qIpJuwza27gYVm9g/gq5KF7v7LSKKSjKOmVRFJR2GT5LTgR6RC1LQqIuks7Ig7k4KxW9u6+/KIY5IMoKZVEckEYUfcOQe4B6gLtDezAuB2dx8YYWySptS0KiKZImxz6xjgRGAmgLvPN7P2EcUkaaikcgTUtCoiGSNskixy962lppD0COKRNJOoWVXVo4hkirBJcpGZ/RioZWbHAL8E3okuLEkHalYVkUxXkRF3biI20fKfgb8Dd0YVlNRs6rEqItmi3CRpZvWAK4DvAguBXu5eVB2BSc2jHqsikm2SVZKTgL3AW8DZwH8A10Qck9QwSo4ikq2SJclO7p4HYGaPAR9EH5LUJLruKCLZLFmS3FvywN2LSvVulQym644iIsmTZL6ZbQseG1A/eG6Au3uTSKOTlFD1KCISU26SdPda1RWIpJ6qRxGRA4W9BaTCzOxo4E9ALlAMjHP3+83sSGKTN7cDVgHnu/sXUcUh4ah6FBE5WGRJEigC/tvd55lZY2BuMNXWcOA1dx9rZqOB0cD1EcYh5VD1KCJStsiSpLuvB9YHj7eb2VKgNTAIODXYbBKx8WCVJKtZqNs65kyAhc+mKMJK2LAQcvNSHYWIZJAoK8n9zKwd0BV4H2gZJFDcfb2ZtShjnxHACIC2bVXZVKXQTasLn02vxJObB3lDUh2FiGSQyJOkmTUCngOucfdtYW8jcfdxwDiA7t27azD1KlCpptXcPLhU822LSHaKNEmaWR1iCXKyuz8fLN5oZq2CKrIVsCnKGEQj5oiIVFaUvVsNeAxY6u73xq16CbgEGBv8nhpVDKJeqyIihyLKSrIP8BNgoZnND5bdSCw5Pm1mPwNWA0MjjCEraQJkEZGqEWXv1reJjcyTyOlRvW62K105qnoUEam8aundKtUjPkGqchQROXRKkmlOTasiItFRkkxTiXqsqmlVRKRqKUmmGd3OISJSfZQk04SSo4hI9VOSrOGUHEVEUkdJsoZSchQRST0lyRpIo+SIiNQMSpI1iOZ2FBGpWZQkUyzRfY6qHkVEagYlyRTSEHIiIjWbkmSKaAg5EZGaLyfVAWQjJUgRkfSgSrIaqWOOiEh6UZKsBrrnUUQkPSlJRkz3PIqIpC8lyYioaVVEJP0pSVYxNa2KiGQOJckqouQoIpJ5lCSrgK47iohkJiXJQ6DrjiIimU1JspJUPYqIZD4lyQpINBi5qkcRkcylJBlCok45qh5FRDKfkmQ51GNVRCS7KUmWQdccRURESbIU9VgVEZESSpJxVD2KiEg8JUlUPYqISGJZnyRVPYqISFmyNkmqehQRkWSyLknqtg4REQkrq5KkmlZFRKQiUpIkzawfcD9QCxjv7mOjfs34BKmmVRERCaPak6SZ1QIeBM4A1gCzzewld18Sxevp2qOIiFRWKirJE4FP3P1TADP7CzAIqPIk+d5Dl9Fhw0J+BTRuUptmjQ6j5ZJ6EbxShtqwEHLzUh2FiEjKpCJJtgY+j3u+Bjip9EZmNgIYAdC2beUrv8b1guTYuF6lj5G1cvMgb0iqoxARSZlUJElLsMwPWuA+DhgH0L1794PWh9Hzykcrs5uIiAgAOSl4zTXA0XHP2wDrUhCHiIhIuVKRJGcDx5hZezOrC1wIvJSCOERERMpV7c2t7l5kZlcBfyd2C8jj7r64uuMQERFJJiX3Sbr7X4G/puK1RUREwkpFc6uIiEhaUJIUEREpg5KkiIhIGZQkRUREymDulbpPv1qZWSHwWSV3bwZsrsJwMpHOUfl0fpLTOSpfqs7Pt929eQpeN2OkRZI8FGY2x927pzqOmkznqHw6P8npHJVP5yd9qblVRESkDEqSIiIiZciGJDku1QGkAZ2j8un8JKdzVD6dnzSV8dckRUREKisbKkkREZFKUZIUEREpQ41PkmbWz8yWm9knZjY6bnm+mb1rZgvN7GUza5Jg33ZmtsvMPjSzpWb2gZldUr3vIFpm9riZbTKzRaWWhz0/bmZ3xC1rZmZ7zeyP1RF/dTCzo83s9eAzsNjMro5bN8XM5gc/q8xsfoL925U+v5mmnO/ZGDNbG3eOfljG/p3N7J9m9i8z+9jMbjGzRBOsx+9zY1W/jyiV8127w8w+Cs7PdDM7KsG+Gf8ZyljuXmN/iE2ltQLoANQFFgCdgnWzgVOCxz8F7kiwfztgUdzzDsB84NJUv7cqPEcnA93i32cFz88K4MO4ZT8PztEfKxBD7VSfhyTxtQK6BY8bA/8q+RyV2u53wK3JPkeZ9pPkezYGuC7J/vWD/c8MnjcA/gb8Isl+O1L93it4nsr6rjWJe/xL4JFs+wxl8k9NryRPBD5x90/d/WvgL8CgYN2xwJvB438A5yU7mLt/ClxL7IOMmTUM/jqcHVSbg4LltczsnqAK+8jMRlbx+6oy7v4m8O8Eq8Ken13AUjMrudH5AuDpkpVmdo6ZvR+cnxlm1jJYPsbMxpnZdOBPVfFeouLu6919XvB4O7AUaB2/TVD1nA88Vd6xzGx4fJVtZq+Y2anB4x1m9hszW2Bm75WcqzRQ3vcsjB8Ds9x9OoC77wSuAkYDmFkjM5sQ9306z8zGAvWD6mty1b6daJT1XXP3bXFPGwLl9oYMqsq3zGxe8NM7WH6qmc00s2fNbJmZTU5WjUv0anqSbA18Hvd8Dd/857YIGBg8HgocHfKY84Djgsc3Af909x7AacDdZtYQGAG0B7q6+/FAWnyJS6nI+fkLcKGZtQH2Aevi1r0N9HT3rsF2v45bdwIwyN1/XGVRR8zM2gFdgfdLrfo+sNHdPz6EwzcE3nP3fGJ/oFx2CMeqTuV9zwCuCpLb42Z2RIL9OwNz4xe4+wqgUdDMfwuw1d3zgu/TP919NLDL3QvcfViVvpsUCP44+hwYBtyaZPNNwBnu3o3YH6UPxK3rClwDdCJW2fep+milImp6kkz0V1TJX2k/BX5hZnOJNaF9XYljngmMDq5DzQTqAW2BvsSaTIoA3D1RpVbTVeT8vAqcAVwETCm1rg3wdzNbCIwi9h9iiZfcfVfVhRwtM2sEPAdcU+qvf4i993KryBC+Bl4JHs8l1sSWDsr7nj0MfAcoANYTa5JOtH9Z1ZMT+z49uH+B+xeVDbSmcveb3P1oYn9QX5Vk8zrAo8F36hliCbHEB+6+xt2LiV32aBdBuFIBtVMdQBJrOLACakNQ5bj7MmJJDjPrCPQPecyuxJrbIPblPs/dl8dvEDRxpPUNpBU5P+7+dZBM/5tYEjwnbvUfgHvd/aWgWXFM3Lqvqjbq6JhZHWIJcrK7P19qXW3gXGKVcTJFHPjHZb24x3vdveRzs4+a//0qUd73bGPJQjN7lG/+CIi3mNj1OuK27UDsmuP2TPg+VcCfgWnAbeVs8ytgI5BP7LO0O27dnrjH6fQZylg1vZKcDRxjZu3NrC5wIfASgJm1CH7nADcDjyQ7WNDUdg+x//gB/g6MLGn3N7OuwfLpwBXBf56Y2ZFV9YaqSyXOz++A6919S6nlTYG1weO07Bkc/Ps+Bix193sTbNIXWObua0IcbhVQYGY5ZnY0set56a6871mruO0GE2vGL20y8D0z6xvsU59YE+JdwfrpxFVXcU22e4M/XtKamR0T93QgsCzJLk2B9UG1+BNiHaekhqrRSTJo7ryKWDJbCjzt7ouD1ReZ2b+IfSDXARPKOMx3gk4nS4l1SPmDu5dsewexpo+Pgu7ZJbdCjAdWB8sXEOuYUCOZ2VPAu8CxZrbGzH4WrAp7fgBw98XuPinBqjHAM2b2Fuk7FVIfYv8Z/cAS38pwIeU3tdbmm7/wZwErgYXE/uCaF0G81SrJ9+yukg43xK7b/yrB/ruIdfS52cyWEzs3s4GSDk53AkeY2aLg+3RasHwcse9YWlzzL+e7NjZ4bx8Ra725OsHu8Z+hh4BLzOw9oCNp1CKTjTQsnUgSQa/nYe5+fqpjkfSkz1D6Unu3SDnM7HZiVdLwFIciaUqfofSmSlJERKQMNfqapIiISCopSYqIiJRBSVJERKQMSpIipZjZvuA2kcXBOKzXBveblrdPOzOrsbcKiUjlKEmKHKxkTNHOxIbr+yHlj6ACseHDlCRFMox6t4qUYmY73L1R3PMOxG6ObwZ8G3iC2GDmAFe5+zvBjeH/QWyggUnERpwZC5wKHAY86O7/V21vQkSqhJKkSCmlk2Sw7Atis8dsB4rdfXcwHNlT7t49GNf2OncfEGw/Amjh7nea2WHERuoZ6u4rq/O9iMih0WACIuGUzJRRB/ijmRUQG4C6Yxnbnwkcb2ZDgudNgWOIVZoikiaUJEWSCJpb9xGbB/A2yp7B4YDdgJHu/vdqCVJEIqGOOyLlMLPmxGZQ+WMwDVZZMzhsJzZvZ4m/Az8vmeXCzDoGE3qLSBpRJSlysPrBRNx1iM0f+QRQMsXWQ8BzZjYUeJ1vZnD4CCgKZrmYCNxPrMfrvGCqrkLgR9UTvohUFXXcERERKYOaW0VERMqgJCkiIlIGJUkREZEyKEmKiIiUQUlSRESkDEqSIiIiZVCSFBERKcP/ByXmQaM3NS1oAAAAAElFTkSuQmCC", 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", 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", 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" ] @@ -11301,7 +11355,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **shielding (aged 16-69)** population up to 15 Dec 2021" + " ## COVID vaccination rollout among **shielding (aged 16-69)** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -11332,7 +11386,7 @@ }, { "data": { - "image/png": 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", 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", 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7TwOmAZSUlGR156uI5Ia6+vxSlkHzrNyZbzJZDj0XeM/dywHM7EngdOAjM+sRtgJ7AAc15Y2ISH3Ue+JradEymQTXAaeaWXuCcuhQoAz4FLgSmBr+PyuDMYhInosvgSZtBdbV76c+vxYvY7e3uvtC4AlgMcHwiFYE5c2pwHlmtho4L3wuIpIR8YPfk5Y8U01zBurzywMZvTvU3ScDkxM27yZoFYqINIm0JVD1++UtzRgjIvkjP2d4kTpk+2h/EZEGeWThOkb/fkHNeUCTlT5V8sxragmKSIuUcgYYlT4ljpKgiLRYGg4h6SgJikhOSzYLzNDK55hQ8SLtCwugtMuBHer/kwTqExSRnJZs/b8hu+bSz96na8c2NQ9W/58kUEtQRHJerbJnaRdgEB3U9ydpKAmKSM5JnAVmfJdXoHTKgQNU9pSIVA4VkZxTaxaYgvk1hz6o7CkRqSUoIjmpRgm0tC100tAHqT8lQRHJOnWt+wcpJsIWaQAlQRHJOnWt+wcwvssrjNg9P2gBgvoApcEiJ8FwkdwjCZZFWuvu+zMWlYjkvToHupdOgU2rgxIoqA9QGqzOJGhmXYAfAJcChUA50BY4wsxeA+5297kZj1JEJJGmP5NGkK4l+ATwf8AZ7r49foeZnQR828z6uPv9GYpPRPJAYh9gdSk01YK3Kn9KI6kzCbr7eXXsWwQsavSIRCTvJPYBVk96vXRK8oSn8qc0kkh9gmZmwOVAH3e/2cx6Ad3d/fWMRicieSNpH+AKVPaUjIp6Y8zdwH7gHOBmYAfwJ+DkDMUlIi1UsuEPGvIgzSVqEjzF3b9sZm8CuPs2MyvMYFwi0kIlG/5QY82/+H5A9f1JhkVNgnvMrABwADPrRtAyFBGptzqHP8RWf+8+QH1/knFRk+AdwEzgcDP7JTAKmJSxqESkxUh552dd1A8oTSRSEnT36Wa2CBgKGPANd1+Z0chEpEVILH/Wmu0lkUqg0oSi3h36v8AMd78rw/GISAtUc7LrhNleEqkEKk0oajl0MTDJzPoSlEVnuHtZ5sISkVwU+c5PlTslS0RaT9DdH3T3rwODgX8CvzKz1RmNTERyTvw6fzE17vwUyTL1XUXii8DxQBHBMFYRkRrGd3mFsYWLa25cwYHfGOrzkywSqSVoZrGW383AcuAkd78oo5GJSE4asmtuzVXeE6nPT7JI1Jbge8Bp7r4lk8GISPara8HbFRs/CdabUZ+f5Ih0Sykd7+5vA68DvcI5Q6u5++LkZ4pISzVryQb6bXySUYULau8shGP3rwUGNnVYIg2SriV4HTAW+HWSfU4wl6iI5JlRhQvob+tS9O0NVLlTcka6pZTGhg+/5u6fxe8zsxQjXUWkpUg15EElT2kpIt0YA8yPuE1EWpBUQx66dmzTTBGJNK50fYLdgaOAdmY2iGDKNIDOQPsMxyYizSVcyeHGrRVQCP0Lu9Tc/3EdM76I5JB0fYIXAGOAo4Hb47bvAH6W7uJm9jngPuAEgj7E7wCrgBkEYw3XApe4+7Z6RS0ijSqx7Hnj1vsp2rOGSv8C7QsLap+gYQ7SQqTrE3wQeNDMvunuf2rA9f8XeN7dR4XrD7YnSJ5z3H2qmU0EJgLXN+DaItJIkq3xt7Z1H2477FZGFB9F/1N61XG2SO4yd492oNm/AP2B6hti3P3mOo7vDLwF9PG4FzGzVcBZ7r7RzHoA89z9uLpeu6SkxMvKNFWpSKMLy57LN1YA0L9HWPaMzeqiG19ympktcveS5o4jm0VdReIeglbc2QTlzVEEYwfr0gcoB0rNbCCwCPgRcIS7bwQIE+HhKV5zLMHwDHr10l+hIgcr2Z2eKcueKndKnog6Y8zp7n6imf3D3X9uZr8Gnoxw7S8D4919Ybgc08Sogbn7NGAaBC3BqOeJSHLJSp6gsqfkt6hJcFf4f6WZHQlsBXqnOWc9sN7dF4bPnyBIgh+ZWY+4cujm+gYtIg1TY10/gNKg/DnjqtNSnCHSskVNgs+Ed3reSrC2oBOURVNy901m9oGZHefuqwhWpY/NJX8lMDX8f1YDYxeRehha+VwwuXVp3HAHreggeS5SEnT3X4QP/2RmzwBt3b0iwqnjgenhnaFrgKsIBug/ZmZXA+uAi+sftoikkmqC6wkVL1Jk7wODDmxU35/kuXSD5f+1jn24e539gu6+BEh2Z9LQSNGJSL2l6vtrX1jAzo5fooPu+BSplq4lWNeagU76m2NEpIkNrXyOGwvn1p7lxdZplheRBOkGy1/VVIGISMMklj+Tlj1BpU+RJKKOE7wx2fa6BsuLSNNILH+q7CkSXdS7Qz+Ne9wWGAasbPxwRKQhagx9KO1S98EiUi3q3aE1FtU1s9uAP2ckIhGpIdXdnrEhDxOq9gWzvZQmTHkmImlFXU8wUXuCadFEJMOSrekHMGTXXIr2rKF9YUHN9f3U9ycSWdQ+waUEd4MCFADdAPUHijSRWjO9QNjyG0R/9f2JNFjUPsFhcY/3Ah+5+94MxCMiCZLO9AIqe4o0gqh9gu+b2eeBnuE5R4SD5RdnNDqRPJGq3w805EEkk6KWQ39BsML8uxwoizpwTmbCEskvqWZ5AQ15EMmkqOXQS4Bj3L0qk8GI5LOk/X6gIQ8iGRQ1CS4DPoeWPRI5KKnKnis2fsL4Lq9A6ZTaJ6nvTyRjoibB/wHeNLNlwO7YRncfnpGoRFqoVGXPfj06M2L3fNi0unbCU9+fSMZETYIPAr8ClgL7MxeOSMuXuuzZNpjgWn1/Ik0mahLc4u53ZDQSkRYmWelTZU+R7BJ1xphFZvY/ZnaamX059i+jkYnkuGQzvfTr0ZkRBfODhJdIZU+RJhe1JRgboHRq3DYNkRBJI/lMLyp7imSLqIPlz850ICItRawMmmrcn4hkD60nKNLIds6/lwkVLwYTW+9uE7T84qnvTyRraD1BkUY2ZNdciux9OvQYlPwA9f2JZA2tJyiSAWtb99HqDiI5IGpLMJHWE5T8VVbKR/MfZsvO3Ul396x6lw8Kj2nioESkIbSeoEh9LX2CjttWss6/EKzonuCDwmPYeezIZghMROpL6wmKNMDa1n247bBbk8/8IiI5I2oS7AEsd/cdAGbW0cz6u/vCzIUmkkXiSqBFe9ZQ6V9o7ohEpBFEnTHmd8DOuOeV4TaR/BCWQCur9rG2dR/e7HIuI4qPau6oROQgRW0JmrvH+gRx9/1m1tCbakRyUnwJtH9zByMijSJqIltjZj/kQOvvP4A1mQlJpHklm/j6xq0VVFbta6aIRCRToibBccAdwCSCu0TnAGMzFZRIc4qf8SWmaM8a1hb2UQlUpIWJOlh+M/CtDMcikhWSz/gyiP4DRtG/pFezxSUija/OJGhmk4C73f3jFPvPAdq7+zOZCE6kKSSWPydU7WNtoWZ8EckH6VqCS4GnzewzYDFQTjB36LFAMfAi8N+ZDFAkY8pKYekTDNxYwbFV+6rLn0X2Pjs7fqmZgxORplBnEnT3WcAsMzsWGEIwXvAT4GFgrLvvynyIIhmy9IlwcdtetC8soH+PLuGOQXTQBNcieSFqn+BqYHVDXsDMCoAyYIO7DzOzQ4EZQBGwFrjE3bc15NoiB637AG6umgTAjKs0+4tIvmmKsX4/Ilh2Kba66ERgjrtPNbOJ4fPrmyAOkRr9fzdurQBgRZUWvxXJVxlNgmZ2NPAvwC+B68LNI4CzwscPAvNQEpSmUFbKwDn3V/f/Fe1Zw9rWfejXo7OGPojkqairSAxx91fTbUviN8B/AZ3ith3h7hsB3H2jmR2e4jXHEo5F7NVLt6VLI1j6RPV4v6D/Lxj2MKNEZVCRfBW1Jfhb4MsRtlUzs2HAZndfZGZn1Tcwd58GTAMoKSnxNIeLJJVY/qz0LwRTn6n/T0RIP07wNOB0oJuZXRe3qzPBuoJ1GQIMN7OvEwyr6GxmDwMfmVmPsBXYA9jc8PBFUkgy/EGzvohIonSrSBQCHQmSZae4f58Add5D7u4/dfej3b2IYLaZv7n7FcCfgSvDw64EZjU4epFUqoc/UD38oUOvQfQ//2ouO0XldREJpBsn+BLwkpk94O7vN9JrTgUeM7OrgXXAxY10XcljibO+BHd+9uJbVTfQr0dnlT9FJKmofYJtzGwawdi+6nPc/ZwoJ7v7PIK7QHH3rcDQ+gQpks6sJRtYsbH2UAfd+SkidYmaBB8H7gHuA7SejDS/sM8v5satFVAI/QvDWV9sHXQfoBagiNQpahLc6+5aSV6aXazseePW+6vH+QFUxs39CUD3AaCpz0QkjahJ8Gkz+w9gJrA7tjHV6hIimRIre1IYrPR+82G3Vu8bUXwU/XXTi4jUQ9QkGLub8ydx2xzo07jhiCRIVfZUuVNEGkHUCbR7ZzoQkaRiQx26D6i5XeVOEWkEUadNa08w92cvdx8bLq10nBbTlcaUOMwBDgx1iK30EJvsWi1AEWkM6QbLx5QCVQSzxwCsB6ZkJCLJW9X9fXXQkAcRaUxR+wSPcffRZnYpgLvvMjPLYFySb8pKuXHr/TWHOYCGOohIRkVtCVaZWTuCm2Ews2OIu0tU5GA8snAdy2ffT8+qd2vvVN+fiGRQ1JbgZOB5oKeZTSeYHHtMpoKS/DJryQaOrdrHB4XH8NbQRzTMQUSaTNS7Q18ws8XAqYABP3L3LRmNTFqmhCEPENz8UmTv06HHICVAEWlSUe8OHUmwCsSz4fPPmdk33P2pTAYnLcsjC9cxcE7NmV4gmO1lbWEf+qvsKSJNLHI51N1nxp64+3Yzmww8lZGopEWKlT3XFtac6QXC2V5K1AoUkaYVNQkmu4Em6rki1WJr++luTxHJBlETWZmZ3Q7cRXCH6HhgUcaikpyVbMD70MrnGLJrLhOq9lFk7wODmic4EZEEUYdIjCcYLD8DeAzYBfwgU0FJ7ko24H3IrrkU7VlD+8ICdn7+SxryICJZI21L0MwKgFnufm4TxCMtQL8enZnxvbhyZ2kXYBD9r3q22WISEUkmbUvQ3fcBlWbWJd2xIjWUlULpvwQTYIuIZKGofYKfAUvN7AXg09hGd/9hRqKSrJas3y9mxcZggmug5goQKoGKSBaKmgSfDf+JVPf7VSe7OLUmuO4+AFQGFZEsFXXGmAfDuUN7ufuqDMckOaBWv5+ISA6KOmPMRcBtQCHQ28yKgZvdfXgGY5NmFLnkGS9xSrRki+GKiGSRqEMkbgIGA9sB3H0JoNXmW7C61vZLuaZfrA8wRn2BIpLlovYJ7nX3ioQlBD0D8UgWaVDJU32AIpJDoibBZWZ2GVBgZscCPwTmZy4saWqJ5c+UJc+YJKtBqPwpIrmmPjPG9CdYSPcRoAK4NkMxSTNILH+mLHnGJJY+QeVPEck5dbYEzawtMA74IrAUOM3d9zZFYNL06l3+VOlTRHJcunLog8Ae4O/A14AvoRZgTkt112fa8qeISAuULgn2c/cBAGZ2P/B65kOSTEo10D1t+VPDH0SkBUqXBPfEHrj73oS7QyVHNeiuz/gp0ED9fyLSIqRLggPNLHa3hAHtwucGuLurfpZP1AcoIi1MnUnQ3QuaKhDJjEYZ+gAqf4pIixR1iES9mVlPM5trZivNbLmZ/SjcfqiZvWBmq8P/P5+pGKSRhj6Ayp8i0iJFHSzfEHuB/3T3xWbWCVgULsU0Bpjj7lPNbCIwEbg+g3HkPQ19EBFJLmMtQXff6O6Lw8c7gJXAUcAIgqEXhP9/I1Mx5LtHFq5j4XsfN3cYIiJZK5MtwWpmVgQMAhYCR7j7RggSpZkd3hQx5KNYX6CGPoiIJJexlmCMmXUE/gRc6+7JlyVIft5YMyszs7Ly8vLMBdjCndL7UC47pVfqA7Tyg4jksYy2BM2sNUECnO7uT4abPzKzHmErsAewOdm57j4NmAZQUlKiFSvqcNCzwKgPUETyVMaSoAUj6+8HVrr77XG7/gxcCUwN/5+VqRjyReRZYLTyg4hIDZlsCQ4Bvg0sNbMl4bafESS/x8zsamAdcHEGY8gbke4ATZz1BVT+FJG8lrEk6O6vEMwsk8zQTL1uS9Yok1+r9CkiUi3jN8ZI40kc+B6TdgC8iIgk1SRDJKTxpCx7lpVCaZLpzuKp/09EpAa1BFuKVNOdxVP/n4hIDWoJZrn4fsC0fX/q7xMRqRclwSwXP/yhX4/OXHfofCidUvtAlTpFROpNSTAH1OgHLJ2SPOGp1CkiUm9Kglkm0vp/KnuKiDQK3RiTZeq9/p+IiDSYWoJZqEb5s6wUlk6BFeFO9f2JiDQaJcFmlGwGmFrlz8SpztT3JyLSaJQEm1Gyia+Tlj/VBygikhFKgs2sX4/OzDjp7ZqrO6xA5U8RkSagG2OyQV2zvaj8KSKSMWoJNqE6hz+o5Cki0uSUBJvQzvn3MqHiRdoXFgQbCqHr7jbw8WqVPEVEmoGSYBMasmsuRfY+HXoMqrmjk0qeIiLNQUkwgxLLnxOq9rG2sA/9VfYUEckKujEmgxJnf2lfWEDXjm2aMSIREYmnlmBjKCutOcQhdOPWCiiE/oVdgg22Lih9iohIVlASbAxLn6Bqw1usblVUY3Nl1b4DN8GAhjuIiGQZJcFGsrpVEd+quqHWig8jio+i/ym9mikqERGpi5JgfaQoewYD3XvVnPhaRESynpJgRI8sXMfAOfdTtGcNa1v3SdjbiyeqlPxERHKNkmBEs5Zs4NhwiMPNh92a9Bit+ycikluUBOuhfWEB/Xt0YcZVavWJiLQESoLxUvX5EQx3KNqzBhiUdL+IiOQeJcF4cQvYfrTjM7bs3F29qzI224uGOIiItBhKgonC1Rx++PsFrPi45oK3I4qPon+JhjuIiLQUSoIxZaXw/ivwha9Ub9KQBxGRli1vk2Di5NY3br2f/sC07V9mzu8X1FzrT0REWqS8nUA7cXJrgOWFA5jT/utA0ArUkAcRkZYtb1uCkFDuLA0mudbwBxGR/JFXSTC+BLpi4yeM7/IKlE4JdoZ3hYqISP5olnKomV1oZqvM7B0zm9hUrxtfAu3XozMjCuaH836iFR5ERPJQk7cEzawAuAs4D1gPvGFmf3b3FU3x+jVLoG2D9f200ruISF5qjnLoYOAdd18DYGZ/BEYAjZ4EX7v7u3TavrL6+YTY+n5h/59KoCIi+a05yqFHAR/EPV8fbqvBzMaaWZmZlZWXlzfKC7cvLKBrxzYHNqgEKiKS15qjJWhJtnmtDe7TgGkAJSUltfZHcep/3NuQ00REJE80R0twPdAz7vnRwIfNEIeIiOS55kiCbwDHmllvMysEvgX8uRniEBGRPNfk5VB332tm1wB/BQqAP7j78qaOQ0REpFkGy7v7c8BzzfHaIiIiMXk7d6iIiIiSoIiI5C0lQRERyVtKgiIikrfMvUHj0JuUmZUD7zfw9K7AlkYMJ5NyKVbIrXgVa2bkUqyQW/E2RqxfcPdujRFMS5UTSfBgmFmZu5c0dxxR5FKskFvxKtbMyKVYIbfizaVYc5nKoSIikreUBEVEJG/lQxKc1twB1EMuxQq5Fa9izYxcihVyK95cijVntfg+QRERkVTyoSUoIiKSlJKgiIjkraxPgmZ2oZmtMrN3zGxi3PaBZrbAzJaa2dNm1jnJuUVmtsvM3jSzlWb2upldmQPxLon7V1jHa601s64HEesfzGyzmS1L2H6xmS03s/1mVuct2mb2YzP7zMy6NDSOqA4m3vC9XZZsXyPHmPT7H+4bH+5bbma31HGNJntPw9dL9Zm91czeNrN/mNlMM/tcivP7m9nfzOyfZrbazG4ws2SLZ8ef87N6xtjTzOaGP8fLzexHcfui/my5mY2P23anmY2pTxz1jLlt+DvnrTDmn8fty5rPbN5z96z9R7DU0rtAH6AQeAvoF+57A/hq+Pg7wC+SnF8ELIt73gdYAlyVC/FGeL21QNeDiPdM4MuJrwl8CTgOmAeUpLnG68DfgTH1fG0DWjVVvPV9bzPw/T8beBFoEz4/vLHf0wzEfD5wSPj4V8CvkpzfLjz//PB5e+AvwA/SvO7OesbZA/hy+LgT8M8G/Gx9BLwDFIbb7szkexx+xjuGj1sDC4FTs+kzq3+e9S3BwcA77r7G3auAPwIjwn3HAS+Hj18AvpnuYu6+BrgO+CGAmXUIWxdvhK3FEeH2AjO7LfzL8h/xfz02ZbwxZnZ++JfuYjN73Mw6xu3+SfjX5utm9sWo1wRw95eBj5NsX+nuqyLEdQzQEZgEXBq3fYyZzTKz58MWxuRwe1H4l/zdwGKgZ1PGmxDfnXHPnzGzs8LHO83sl+Ff76+Z2RH1CLGu7//3ganuvjuMeXOK2Op6T1PFfHXYCptnZvfGH3cwMbv7bHffGx73GnB0kvMvA15199nhOZXANcDEMLaOZlYa97P0TTObCrSzoNIxPUqQ7r7R3ReHj3cAK4Gjwt1Rf7bKgTlArWqQmRWH3+9Yq/fzZvYlM3s97pgiM/tHlHjDON3dd4ZPW4f/PNxX389skZn9PfwdsNjMTg+3nxV+358IW+3T07XCpaZsT4JHAR/EPV/PgQ/+MmB4+Phiov9CXQwcHz7+f8Df3P1kgr/UbzWzDsBYoDcwyN1PBCL9oDZSvMfYgVLoXRaUOycB57r7l4EygkQe84m7Dyb4q/Y3EeNsLJcCjxK0Wo4zs8Pj9g0GLgeKgYvjSj7HAf/n7oPcvaFT4WVSB+A1dx9I8Iv1u/U4t67vf1/gDDNbaGYvmdnJKa5R13tai5kdCdwAnAqcx4HPdmPEHO87BC28RP2BRfEb3P1doGNYlrwBqHD3AeHP0t/cfSKwy92L3f3yesaLmRUBgwhaVlC/3wVTgf80s4KE7f8HXB/GuBSY7O4rgUIz6xMeMxp4rJ6xFpjZEmAz8IK7L0xzSiqbgfPC3wGjgTvi9g0CrgX6EbTohzTwNfJStifBZH/RxMZ0fAf4gZktIiiPVDXgmucDE8MP6TygLdALOBe4J/ZXsLvXan1kMN53w18Oxe7+A4Jfbv2AV8M4rwS+EHf8o3H/nxYxzsbyLeCP7r4feJLgF1DMC+6+1d13hfu+Em5/391fa+I466MKeCZ8vIigJBVVXd//Q4DPE3w/fwI8luIv9rre02QGAy+5+8fuvgd4vB7xpos5OMDs/wF7Sf7HoCUen3Cdc4G7qje4b6tnfDVfLKiC/Am41t0/CTdH/l3g7u8RlJsvi7tmF+Bz7v5SuOlBgtI7BEnvkvDxaGBGfeJ1933uXkzQih5sZifU5/w4rYF7zWwpwfe4X9y+1919ffiZWUL9PrN5r1lWlq+H9dT8q+5o4EMAd3+bIIlhZn2Bf4l4zUEEpRQIfoC/mViWCH85NWQAZSbiNYKEcmmK/Z7icUaZ2YnAscAL4e/yQmANB37hJcYSe/5pkwRYt73U/AOwbdzjPe4ei3Uf9fsZSfn9D/c9GV77dTPbTzBBcnns4DTvaaqYD7b0VVfMWHAj2TBgaNz7Em85BxJG7Jw+BH1+Ow7iZ6kWM2tNkACnu/uTse0N+Nn6b+AJDpRQ6zIDeNzMngxeylc3JHZ3325m84ALCVqu9fVjgj7NgQSfg8/i9u2Oe1zfz2zey/aW4BvAsWbW24K7JL8F/BkgViYys1YE5cJ70l0sLKPcBvw23PRXYHzsL3IzGxRunw2MM7NDwu2HNke8odeAIbH+PjNrH/6gx4yO+39BxGs2hkuBm9y9KPx3JHCUmcVaqeeZ2aFm1g74BvBqE8aWzlqg2MxamVlPgtZUY0j5/QeeAs6B6l/UhdReIaCu9zRVzK8DXw37sA6hHn3N6WI2swuB64HhYV9fMtOBr5jZueE57QhKdbG7X2cT9BES7v98+HBPmNQiCX9G7wdWuvvtCfvq9bMVJs0VBMkdd68AtpnZGeEh3wZeCve9S5BYbqCerUAz62bhHbXh+3Iu8HZ9rhGnC7AxbO19m+CGJmkEWZ0Ew3LkNQTJaiXwmLsvD3dfamb/JPhQfQiUprjMMRYOkSAobfzW3WPH/oKgzPAPC25F/kW4/T5gXbj9LeJKJ00Qb+I1y4ExwKNhp/xr1Oz3aWNmC4EfEfy1GJmZPUqQOI8zs/VmdnW4faSZrScorz5rZn9Ncvq3gJkJ22aG2wFeAR4iKM/8yd3L6hNbBuI9hAN/Mb8KvEfQ93MbQT/xQUvz/f8D0Cf8nP0RuDJJy6qu9zRpzO6+gaBls5Dg7tMVQEUjxXwnQXnxhbCPulZyCcvdI4BJZrYqjO+N8FyAKcDnzWxZ+LN0drh9GsHPV9T+9iEEv/zPiesz/3q4ryE/W7+k5o0+VxLcE/APgn7sm+P2zQCuoJ79gQR3tM4Nr/kGQUXnGWjQZ/Zu4Eoze42gfzkbKiotgqZNk0ZnwdirEne/Jt2xTcWCO38vd/dL0h6cY8yso7vvDFuCM4E/uHtiMpUc05I/s9lEtWNp8czsZoLWyphmDiVTbgrLkW0Jyo9PNW84crDy4DObNdQSFBGRvJXVfYIiIiKZpCQoIiJ5S0lQRETylpKgSAIz2xfegr/cgjlErwvHoNV1TpGZRRpKIyLZQ0lQpLbYvJb9Cebj/DowOc05RUQcTyoi2UN3h4okMLOd7t4x7nkfgsHOXQnmbX2IYKJtgGvcfX44iPlLBAPaHySYNWUqcBbQBrjL3X/fZF+EiESiJCiSIDEJhtu2EczUswPY7+6fmdmxwKPuXmLBskYT3H1YePxYgjUDp5hZG4IZXy4OJ3AWkSyhwfIi0cQmqm4N3GlmxQRzSvZNcfz5wIlmNip83oVgcmwlQZEsoiQokkZYDt1HsKbbZFLP5l/jNGC8uyebE1JEsoRujBGpg5l1I1iV4M5wwutUs/nvIJhsOuavwPdjKyWYWV8LFmwWkSyilqBIbe0sWMC4NcE6fg8BseV77gb+ZGYXA3M5MJv/P4C94UoJDwD/S3DH6OJwGaBygiWlRCSL6MYYERHJWyqHiohI3lISFBGRvKUkKCIieUtJUERE8paSoIiI5C0lQRERyVtKgiIikrf+P9lZDO8xZBFlAAAAAElFTkSuQmCC", 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" ] @@ -11396,7 +11450,7 @@ }, { "data": { - "image/png": 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", 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", 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", 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", 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", 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9vbDfiBEjeOihh7j55psJCAjg6NGjeHt7Y7PZCA4OZvr06QQEBLB06dJi+5e8tBEREUFiYiL79++nR48evP3221x55ZWANTfg1ltv5Y033ij8RD5kyBDuuuuuwv6ZmZkcOXKk8FN/Uenp6bRr1468vDzeffddOnTo4NLPIDAwkI4dO/Lxxx/zhz/8gZycHPLz8xk6dCivvfYas2bNIjU1lQ0bNvDUU0+RkJDg9DjlfW8llfz5lictLa3we1m2bFmxY5w9e37O03XXXceLL75YOKdl27ZtREdHu3QOperCzo1H2bu59AhoeUI6BXDF5NK//0rVNk0k7G6++WbGjh3LgAEDiI6OJiIiAoBWrVpx2WWX0adPH0aNGsVTTz3F7t27Cy8rBAQE8M4777B//37mzp2Lh4cH3t7evPLKKwDcfvvtjBo1inbt2rFu3brC8/n5+bFkyRImTZqEzWZj4MCB3HHHHYCVqY4ZM4alS5cWvmGGhoaydOlSbrrppsKJi48//rjTROKxxx5j8ODBdOnShb59+7r8Rg3w9ttvM2fOHB5++GG8vb358MMPGTduHD/88AP9+vVDRHjyySdp27ZtmYlEed9bSbNnz+aOO+6gWbNmFY4iLFiwgEmTJtGhQweGDBnC779bHzzGjh3LxIkTWbVqFf/6179YvHgxd911FxdeeCE2m42hQ4fy6quvuvwzUKq27d18glNHMrjANwtbimsfEjOPG9BEotEZM2ZM+pgxY1z/o10PSEXD0PXZgAEDTFxcXF2HoZRSVbLyma0AXLTtebITEvCzf5Apj2/vCNo+8IBb5xORLcYY5zOcq2D79u2J/fr1K3M+gmq4tm/fHtKvX78wZ9t0REIppeoRv4gIury9vK7DUMplWkdCKaWUUm5r0CMSKSkphZMaHaKiohg4cGDhRMOSoqOjiY6OJjMzkw8++KDU9gEDBtCnTx/S0tJYuXJlqe2XXHIJvXr14tSpU6xevbrU9qFDh9KtWzeOHz/OmjVrSm0fNmwYnTp14vDhw6xdu7bU9pEjR9K2bVsOHDjAhg0bSm0fM2YMISEh7Nmzhx9++KHU9nHjxhEUFER8fDzOLvtMnjwZf39/tm3bVlgbo6ibb74Zb29vfv75Z3bu3Flq++zZswH4/vvv2bt3b7FtXl5eTJ8+HYBvv/22cA6DQ7NmzQonj3799dccOXKk2PbAwEDGjx8PwJo1azh+/Hix7a1atSoszvXpp5+SUuJactu2bRk5ciQAH330UbEJmAAdO3bk2muvBSA2NrZUAayuXbsWTgp95513cNSkdwgPDy+snlnydQf62tPXnvuvvSO/5RHV/WIAVh44wAUlXl81/dpTqip0REIppVSjsX//fu/BgweHd+vWLapHjx5Rjz32WOuK91JVoZMtlVKqjhWdbAmUOUfiPz8dYtU2q+xAZPtAHhkb5db5GvNky4MHD3ofPnzY+/LLL888ffq0R//+/SP/+9//7q8Py203ZOVNttQRCaWUaiBWbTvKrqRy14lq8rp06ZJ3+eWXZwK0bNmyoHv37lmHDh3yqeu4GrMGPUdCKaVqiztFo1x16kgGIR0DAEjOSmbBmhin/RJ9zuLfBfzbBeIXHAG4NyLRVOzZs8dn165d/ldeeWVGxb2VuzSRUEopFziKRjne8B1syckuF5EqSwDQKv4A2QkJpLSGPalp9AruVaVj1rmP7+rEyV3Vuow4rSMz+cNLLi0GlpaW5jF+/PjuixYtOlx0ZU9V/TSRUEopF4V0DGDcfRcVazs4Y6bLRaQqFBHB7q6n6BXchiUjl5TaPOU1626ZJSMvKbVNnZeTkyOjR4/uPmnSpNRZs2adqet4GjtNJJRSqoqqs4jU9jIuazQ4Lo4cVLeCggKmTp3aJTw8PHvBggU1cy1KFaOJhFJK1Za4JbBjRfl9xP7et2R0qU0Pp6TZtwVB274walE1B9jwffXVVwEff/xxq549e2ZFREREAixcuPDolClT0uo6tsZKEwmllKotO1bA8R1WEqBqxIgRIzKMMVvqOo6mRBMJpZSqTW37QsxnhU+L1oYASPR5GoApufeX2nVX7lki2wUSG6NzJFT9oXUklFKqDlWmNkRku0BujO5QwxEpVTk6IqGUqtd+/XoNuzetr9ZjnjuTS1Z6bqX2ycvJx9vXk9iFxdeqyM6zkgC/hfOLtSdnJpOanVr8ILl51tdt4wqbwnJshAHNT1t/jrvmZeLv7U+v4FXOA1kDsWugdZduXD379kp9D0rVBB2RUErVa7s3rSc58feKO1ZCVnoueTn5ldrH29eTZi1cL5CYmp1KZl5mZUPD39ufYL/gSu+nVF3REQmlVL0XGtaVKY9U3x0KjrUtHDUhTsd+wFknK6qWkgOUWEki+7dj1u2fJeKLWRMDXFC8HoTjToyY86u7OmpDxM7ReQ+qYdIRCaVUk3d29WqyExLc2tcvIoLAMWOqOSKlGo46GZEQkXuB2wAD7ABiAH8gFggDEoHJxpjTdRGfUqrpqc6iUqruZGZmyuDBgyNyc3MlPz9fxo4de/q55547VtdxNWa1nkiISAfgL0CkMSZLRD4ApgKRwFpjzCIRmQ/MB+bVdnxKKeWSiopLOSsspTUkapyfn5/57rvv9gQFBRXk5OTIwIEDe61duzZt2LBh5+o6tsaqruZIeAHNRCQPayTiGPB34Cr79mXAejSRUErVV06KS51Iz+ZURg4A50JsAOw8VbSgYmc2nbmItfZ5EQC7kqzaEKp6eHh4EBQUVACQm5srNptNRKSuw2rUaj2RMMYcFZGngUNAFvClMeZLEWljjEmy90kSkda1HZtSSlVKieJSf3ntB3alWonBQW+rsNSjrUoXlipKa0NUP5vNRp8+fSIPHTrkO2vWrJPXXHONjkbUoLq4tNESuBHoCpwBPhSR6ZXY/3bgdoDOnTvXRIhKKeW2yHaBxM65hJg11ihDU12p86FND3Xaf3p/tS4j3qNlj8zHLnuswsXAvLy8SEhI2HXq1CnP0aNHd//555/9Bg4cmF2dsajz6uLSxrXA78aYZAAR+Qi4FDghIu3soxHtgJPOdjbGvA68DjBgwABTSzErpeqZnRuPsneze4s7njqSQUjHgErt8+HeD/n8wOfnGxxzIIqs1pnoYxWnilkTyJ7UPfQK7uVWfKp6hISE5F9++eXpn376aZAmEjWnLhKJQ8AQEfHHurQxDIgDzgGzgEX2r2WUdVNKKdi7+YRbCQFASMcAwge1qdQ+nx/4vFLJQa/gXlzf7fpKx9ZYuDJyUBOOHTvm5ePjY0JCQvIzMjJk/fr1gffff//xuoilqaiLORI/icgKYCtgA37BGmEIAD4QkVuxko1JtR2bUqphCekYUFhUqixlFpvaBgdftx5mJyTgFxFR4fl6Bfc6X2DKcTdGkYJTjuJSTfVyRn1w+PBh79mzZ3fNz8/HGCM33nhj6k033aRLiNegOrlrwxjzCPBIieYcrNEJpZSqNo5iU+UlClpUqvEYPHhw1u7du3fVdRxNiZbIVko1elpsSqmao4mEUkqV4z8/HWLVtqOFEykdly8eTrFGyx/VmhCqidNEQinV9FRUlbKIfklp9MzN56n2WQA8nDIXgLC8AyR6dyvWV2tCqKZIEwmlVNPjpCplefx9PGnuY/25jGoXZG/tT1TficQO0ImVqmnTREIp1TSVqEpZFselC/+29ls8ii4LrpTSREIpVT85Ck6dOpwBwMpnthbb7m4NibKUKjhl55gb4ZmapAWmlHLCo64DUEopZxwFp8riTlGp8jgKTpWlqReYakhsNhu9e/eOvPrqq3vUdSxNgY5IKKXqjaLFo7L9RhIA5GYcAeCibc+X3mHb+aJSZXG12BSUKDhlp0WmGp7HH3+8TY8ePbIyMjI86zqWpkBHJJRS9YajeFR10mJTTctvv/3m/cUXXwT98Y9/PFXXsTQVOiKhlKpXHMWjttrnRHhkWKMJXR5ZVC3H/89Ph+iXVLoGRMk6EQ5aG6Jhueuuuzo9+eSTR9LS0nQ0opa4nEjYl/9uj7XQVqIxpqDGolJKqRqyattReubm4+/j2vuM1oZwz7EH/tEpZ9++al1G3Ldnz8z2/++fZS4G9t577wWFhITYrrjiiszVq1e3qM5zq7KVm0iISBBwF3AT4AMkA35AGxH5EXjZGLOuxqNUSqlq5O/jSVS7IGJjzs97iFljjTroXIiG67vvvgv46quvLujQoUNQTk6Ox7lz5zxuvPHGrqtWrfq9rmNrzCoakVgBLAeuMMacKbpBRC4GZohIN2PMWzUUn1JKuc6FipUPp6QRlncA6F87MTVR5Y0c1JSXXnrp6EsvvXQUYPXq1S2eeeaZNppE1LxyEwljzPBytm0BtlR7REqpRs1RH8KZbL+RAGx9Zqt7dSKKVKz8kAw+l3OlupwLsQGtaR5QAGtiCtv3pO7ROhFKucGluzbEMl1EHrY/7ywig2o2NKVUY1RRfQgHt+tE2CtWft6uG3t8fKznRf4d9O7OQe/u0KJtsd20TkTjMmbMmPR169btr+s4mgJXJ1u+DBQA1wCPAunAf4GBNRSXUqoRC+kYwLj7LirVfnDG8wB0uW9aYVv8N+6fR+tCKFXzXE0kBhtjLhKRXwCMMadFxKcG41JKNTKOYlOOyxeOpKGoyhSPUkrVD64mEnki4gkYABEJxRqhUEoplxQWm4oeWWYfd4pH/eenQ6zadhSwJlKCVR9C60IoVTtcTSQWAyuB1iLyT2Ai8GCNRaWUapT8IiIKRxyKXr6oilXbjlYqOdC6EEpVL5cSCWPMuyKyBRgGCPAHY8zuGo1MKaVcFNkukNg5l8CSIABiYy7RuhBK1RKXEgkReQGINca8VMPxKKWUUqoBcXXRrq3AgyKyX0SeEpEBNRmUUkop5Y4OHTr0DQ8Pj4yIiIjs06dPb2d9/va3v7V/+OGHq28N+iIWL17cKjEx0buifnv27PHp2bNnVHWdd8qUKV22bNniV9XjLF68uNXMmTM7V2YfVy9tLAOWiUgwMAF4QkQ6G2N6uhGnUqoa/fr1GnZvWl8n5z53Jpes9FyX+hbkW39u8re9gbevJ7ELPyjclpyZTGp2KthyoSCv2H5+Z73IDrQRs9T55xcjNgBilnpB3jnwaQ5rYrTAVBP27bff7m3Xrp2tLs79zjvvhERHR2eFhYXlVdy7ethsNmJjYw/W1vlKquwy4j2ACCAMqN61fpVSbtm9aT3JiXVTBTgrPZe8nPxK7ePt60mzFsXvHk/NTiUzL9NKIgqKHy870MaZdlmuHdynOTQPBbTAlKq8hx56qE2fPn16h4eHR957773tHe3XXntt96ioqN49evSIevrpp0PAevOeMGFCWM+ePaPCw8MjFy5c2HrJkiUt4+Pj/WfOnNktIiIiMiMjQ4oef+PGjf69evWKjI6Ojnj22WdbO9ptNhtz5szp6Dj3U089FQJWme8BAwb0Gj58ePfu3btHTZs2rXN+vvX74e/v3/+ee+5pf+GFF0asXbs2YNCgQb02bNjg/8QTT4TecccdHR3HXrx4catZs2Z1Anj55ZeD+/bt2zsiIiJy2rRpXWw2K9d64YUXWoWFhfUZOHBgr++//76S5WRdnyPxBDAe+A34AHis5NobSqm6ExrWlSnVtMx2Zay0L/XtrLhUSQdnzASgy5svltoWsyYGuIAlSScBb4j5rHBb4e2dOc6Pu9t+x8aS2TqpUlmGDRvWU0SIiYlJvv/++0+5ss9HH30UuH//fr9ff/11tzGGa6+9tsf//ve/gFGjRmW8++67iW3atMnPyMiQ/v37R06fPv30vn37fJOSkrz37du3E+DUqVOeISEh+a+88krrp59++vDQoUMzS57j1ltvDXvuuecOjR49OmPOnDmFb/bPP/98SFBQUH58fPzurKwsGThwYMTYsWPPAuzYsaP5L7/8Eh8eHp47dOjQnsuXL28ZExNzOisry6NPnz5Zzz///DGAhx56CIAZM2acHjJkSARwBGDFihXB//jHP5K2bt3qt2LFiuC4uLgEX19fM3369M6vvvpqq7Fjx55dtGhR+y1btuwODg7Ov/TSS3v16dOnVOzlcfX2z9+BS4wxLv2HKKUaF0cxqZLKKy5Vqq+bxaYqur1Tb+esn9Yu390p9WhGtS4jHtwhIHPYzN7lLga2adOmhLCwsLyjR496XXPNNeFRUVHZo0aNqrAm+5o1awI3bNgQGBkZGQmQmZnpkZCQ4Ddq1KiMJ554os1nn312AcDx48e9d+7c6XfhhRdmHz582HfWrFmdxo4dmzZu3Liz5R0/JSXFMz093XP06NEZALfcckvKN998EwTw9ddfByYkJPh/8sknLQHS09M9d+3a5efj42P69u17LjIyMhdg8uTJqRs3bgyIiYk57enpyezZs0+XPE/79u1tnTp1ylm7dm3zqKio7AMHDvgNHz48Y9GiRaHx8fH+/fr16w2QnZ3t0bp1a9uGDRuaDxkyJL19+/Y2gPHjx6fu3bu3UnMtKlpGPMIYkwBsBjqLSLEJGMaYrZU5mVKqYXIUk6pK1Ul3ik05FN7eqVQFHHMTOnToYBs9evSZH374obkriYQxhnvuuSdp7ty5xT4wr169usW3337bIi4uLqFFixYFgwYN6pWVleURGhqaHx8fv2vlypWBL7/8cuvY2NjgDz/8MLG844tIWdvkmWeeOTRhwoRiycjq1atblNzH8dzHx6fAy8v5W/jEiRNPv/feey0jIiKyR40addrDwwNjjEyaNCnFsTqqw9tvv31BWXG5qqIRib8BtwPPONlmsNbeUEo1AX4REXR5e3mxtq32SxvVVVxKNR4VjRzUhLNnz3rk5+fTsmXLgrNnz3qsW7cu8B//+McxV/YdNWrU2QULFrS//fbbU4OCggp+//13bx8fH3PmzBnPoKCg/BYtWhT88ssvftu3b28OkJSU5OXr61swe/bsM+Hh4Tm33HJLV4CAgID8tLQ0z5LHDwkJyQ8ICMj/4osvAkaMGJGxdOnSYMe24cOHp73yyiuhY8aMSff19TW//vqrryMh2rFjR/OEhASfnj175q5YsSL4tttuS67oe5k+ffrp/v37R+7YsSNn0aJFRwBGjhx5dvz48T0eeOCBEx06dLCdOHHCMy0tzXPo0KHn5s2b1+n48eOeLVu2LFi5cmXLqKgoFyclWSpaRvx2+8NRxpjsottEpMq3mSillFLV5ciRI17jxo3rAZCfny8TJkxImThxotNLDs8991y71157rfAW0BMnTvy6c+dOv4EDB0YA+Pv7F7z77ru/T5gwIe31118PDQ8Pj+zevXt2v379zgEkJiZ633rrrWEFBQUC8Oijjx4BmDlz5qm77767y9y5cwvi4uJ2BwQEGMc53nrrrcTbbrstrFmzZgXXXHNNYVz33nvvqcTERN++ffv2NsZIcHBw3ueff/4bQHR0dMZ9993XMSEhodngwYPTZ8yYcaain0NoaGh+z549s/bt29fs6quvzgS4+OKLsx988MGjw4YNCy8oKMDb29ssXrz40LBhw87Nmzfv2JAhQ3qHhobmXXjhhZn5+fmVGqIQY0zFnUS2GmMuqqittg0YMMDExcXVZQhK1bnYhfMBanSyZeFEyRIjEpWZbFkea7Il9smWFJts6VgrQy9tVB8R2WKMqfZ6QNu3b0/s16+fzqWrJqtXr27xzDPPtKkPy6Fv3749pF+/fmHOtlU0R6It0AFoJiL9scpjAwQC1TqJRilVu3ZuPMrezSdc6uuYVOm4lAGQnJVM1nFDVlAqMWv+VaVYtOaDUg1XRXMkRgCzgY7As0Xa04EHaigmpVQt2Lv5BKeOZBDSsdK3jQOQmpVCZvMssjq5loyUp7DmQ9LSKh9LqcZizJgx6WPGjEmv6zgqUtEcCUdFywnGmP/WUkxKqVoS0jHAtRoQf5gP55LpcmlhjR5iWlkJxBLTBpLK3vdEejanMsooAlHU1hc4l3eARO9uPFpk6W9d9lup+s3VEtn/FZHRQBTgV6T9UXdOKiIXAG8CfbDu/rgF2APEYlXNTAQmG2NK3SOrlKoD55Ih95xbu57KyCEzNx9/n1IT2UtJ9O7GpmZXF2vTOhFK1W+uVrZ8FWtOxNVYCcBErNoS7noBWGOMmSgiPvZjPwCsNcYsEpH5wHxgXhXOoVSTV1YhKahkMamTufi1bl5sEiT2CZKMXFLuvo9WcrJkFNY950qphsHVtTYuNcbMBE4bYxYClwCd3DmhiAQCQ4G3AIwxufZy2zcCy+zdlgF/cOf4SqnzHIWkqsqvtQ+Bke7NpVBKNW6ulsh2FKfIFJH2QArQ1c1zdgOSgSUi0g/YAvwVaGOMSQIwxiSJSOtyjqGUcpGzQlJQyWJSS0ZXd1hK1Yg9e/b4jBkzpqdjDQywlg0PCAjIf/TRR53ODF68eHGruLi45suXLz9Ue5E2Hq6OSKy2z2t4CtiKNYfhfTfP6QVcBLxijOkPnMO6jOESEbldROJEJC45ucICX0oppZSqQS4lEsaYx4wxZ+x3bnQBIowxD7l5ziPAEWPMT/bnK7ASixMi0g7A/vVkGbG8bowZYIwZEBoa6mYISimlmppBgwb1+tOf/tShb9++vcPCwvqsWbOm1PW6999/Pyg6OjoiKSnJa8KECWGzZ8/u1L9//4iOHTv2XbJkSUuAgoIC5syZ09GxhPgbb7zREmD69Omd33333SCA4cOHd580aVIYwHPPPRfyl7/8pf2ePXt8unXrFjV16tQuPXr0iLrssst6llxqvCGqqCDV+HK2YYz5qLInNMYcF5HDItLLGLMHGAbssv+bBSyyf11V2WMr1di4UjTq1GFrPaKVz5ReQ89ZIanC/UrUkPhw74d8fuBz5ycRewyOCZZoESnVMNlsNtmxY8fu2NjYoEcffbT9yJEj9zq2LV++/IIXXnihzVdffbUvNDQ0H+DEiRPecXFxCdu2bfMbN25cj5iYmNPLly+/YMeOHc127969MykpyWvQoEG9r7vuuoyhQ4emb9iwocXNN9+cdvz4cZ+TJ08agE2bNgXcdNNNqQCHDh3ye+eddw5ceumlB6+//vpuy5cvb3nnnXem1s1Po3pUNEdibDnbDFDpRMLubuBd+x0bB4AYrNGRD0TkVuAQMMnNYyvVaFS1aFR5QjoGED7IWmrgPz8d4oVd75Mth/EzpedRd8mzAXAwqeiyBe04eiSisIR1WbQORNP0xSvPdzp1+GC1VkAO6dQlc8Sf7il3MbCyVrJ0tE+aNOk0wKWXXnpu7ty5Po7t33//fYvt27f7r1u3bm9wcHCBo/2GG2444+npycUXX5ydkpLiDbBx48YWkydPTvXy8qJTp062wYMHZ3z33Xf+w4cPz3jppZfabNmyxS88PDzrzJkzngcPHvTesmVL8zfeeOPQyZMnvTp06JBz6aWXZgH0798/MzEx0beqP5e6VlFBqpjytrvLGLMNcFbnfVhNnE+phqyiolGxCz8AnK934bi1s9wJlXFL6Lf2LToFp+PhITxyqvQISFjeSatQVKv7Kxc8WgdC1a42bdrYSq6+mZqa6tm1a9ccAD8/PwPg5eVF0cWpOnfunHPo0CHf+Ph4v6FDh2Y62h39wVoKvOjXkrp27ZqXlpbm9emnnwZdccUV6ampqV7Lly9v2bx584KWLVsWnDx5Eh8fn8KdPT09TVZWlqtzFestV+tIPOys3d2CVEqpemTHCsLyDuDh0ZrmPl5EtQty0qk/UX0nEjtAF85Srqlo5KCmBAUFFbRu3Tpv1apVLW688cb0EydOeK5fvz5o7ty5J99+++2Qsvbr2LFj7nPPPXd4/PjxPWJjY38bMGBAdll9r7zyyvQ33ngj9M9//nPKyZMnvTZv3hywePHiwwAXX3xxxmuvvdb6q6++2nvy5EmvadOmdR89enSjLq7o6u2fRUva+QFjgN3VH45SqjzOCkxl51mXGxwrdBbblpCAX0REhcdN9O7GQe82RLYNrLDAlFL13bJly36/8847O8+bN68TwLx5845FRUVVWKe9X79+OcuXLz8wZcqU7p988kmZK27OmDHjzPfffx/Qu3fvKBExCxcuPNK5c2cbwOWXX56xcePGwD59+uTk5OTkpqWleQ4dOrTer5dRFS4tI15qJxFf4BNjzIjqD8l1uoy4auxKLtN9cMbMUsnBensicZW383kIgWPG0HLK5LJPsmQ0O5PSuKVdGyLbBbJEE4lGT5cRV5Xl9jLi5fDHKiyllKplJQtM+S20yrB0eWRRXYWklGrCXJ0jsQPrLg0ATyAU0PkRSimlVBPn6ojEmCKPbcAJY4ytBuJRSimlVAPi6jLiB0WkJdZCXV5AG3tBqtJVbpRSLhWScoUrNSSSM5NJzU4lZk3Zd2ufPJvDqXPO55p1yTtKQbAhW3Kx1t5Uym0FBQUF4uHhUfnJd6reKigoEKCgrO2uXtp4DJgN/Mb5SxwGuKaK8SnVKFVXIamiRaPKkpqdSmZeJnBBmX1OncshM8eGv6/zX3kPD6Gjfw+u73Z9FaJVivjk5OTI0NDQNE0mGoeCggJJTk4OAuLL6uPqpY3JQHdjTG61RKZUE1BRIanq5O/tX+7dFlNe+wEEYmOc1IFwrOw5+T81FJ1qKmw2223Hjx9/8/jx431wfVFIVb8VAPE2m+22sjq4mkjEY33ccbqQllKqHohbAjtWON30cEqa9WCJk2JTx3dA2741GJhqKi6++OKTwA11HYeqXa4mEv8f8IuIxAOFF1qNMfqCUaoaOSs4VVS5BaZ2rHAvKWjbF/pOrNw+Sill52oisQx4AthBORMulFJVc3b16nKTBb+ICALHjHG6DbCSgpjPSjU/al9Yy+mlDaWUqgJXE4lTxpjFNRqJUgooXXBKKaXqM1cTiS0i8v8Bn1D80obe/qmUUko1Ya4mEv3tX4cUadPbP1Wd+vXrNezetL7WznfuTC5Z6a7duJSXk4+3ryexCz8orPPgitAsa328o3fdSF6+a1cRL0jP50wLT3YmWRMqHZcxitqVdJbIds7X4lBKqapwtSDV1TUdiFKVtXvTepITfyc0rGutnC8rPbcwQaiIt68nzVr4AOfrPPh7+7t8rrz8AgqMwUOkwr5nWniS3LY7UPYCdpHtArkxuoPL51dKKVe5WpDqYWftxhhdb0PVqdCwrkyppcWqSq7E6Sqr4uQFLq2q6VgK/P/6/wmA2DmVmBxprwehEyqVUrXJ1Usb54o89sNae2N39YejlFJKqYbE1UsbzxR9LiJPY028VEoppVQT5uqIREn+QLfqDESpxsZRXGpqagIAB9+dWbxD+nE4l1ysKftkLn6tfXg4Za7V4KwSZVm0QqVSqg64OkdiB+cX6/IEQgGdH6FUORzFpWhdRodzyZB7DnyaFzb5tfYhMDKADNxY70grVCql6oCrIxJFS+nZgBPGGFsNxKNUo+IXEcH7N1t3eZSabOlYLMtJJco7tBKlUqqBcDWRaAfsNMakA4hIgIhEGWN+qrnQlGrYTqTnkJKRw64kK5GYUqK+g2MhLa37oJRqyFxNJF4Bit7zlumkTakGbefGo+zdfKLweXJWMqlZKYXPm6UFkxWUSsyaf7l0vBvO7SffGLLFCz/TqVKxaN0HpVRD4WoiIcaYwou2xpgCEXF3oqZS9dLezSc4dSSDkI4BAKRmpZBpy8LfqxkAWUGppHRKrNQxPT2Ei9pGcX2365kUXuIyhX0ipV6+UEo1ZK4mAwdE5C9YoxAAdwIHaiYkpepOSMeAwoJTjpEHVwpJOfO/p/9Qpf2VUqoh8HCx3x3ApcBR4AgwGLi9poJSSimlVMPgakGqk8DUGo5FKaWUUg1MuYmEiDwIvGyMcbp0oYhcA/gbY1bXRHBK1TZbcnLhehdlFpJyUdvkQxwP7VxtsSmlVH1U0YjEDuBTEckGtgLJWGtt9ASiga+B/1eTASpVm2wpKWQnJOAXEVHlYx0P7cyOXoMZBRC3BHasKNFBK1EqpRq+chMJY8wqYJWI9AQuw6oncRZ4B7jdGJNV8yEqVbv8IiLo8vZyFqyJAZxPlvzPT4dYte1ouccpVgtix4rSiYNWolRKNQKuzpHYB+yr4ViUqjHLV3zCsV8yyu3TLC2YgLxMElITWLAmhj2pe+gV3Mtp31XbjlZYNKpULYi2fZ1WsVRKqYaszmpBiIgnEAccNcaMEZFgIBYIAxKBycaY03UVn2pcjv2Sge+ZIHIuSCuzT1ZQKu1Obit83iu4F9d3u77M/pHtAomdozUglFJNW10WlforsBtwfKSbD6w1xiwSkfn25/PqKjjV+ORckMb8f04rt8/BGWvAN0JrPyillItcqiMhIpe50uYqEekIjAbeLNJ8I7DM/ngZ8Ad3j6+UUkqp2uFqQSpniwu4tuCAc88D/wcUFGlrY4xJArB/LWvxZaWUUkrVExXVkbgEq6JlqIj8rcimQMDTnROKyBjgpDFmi4hc5cb+t2Ovqtm5s96jr5RSStWliuZI+AAB9n4tirSfBdy9b+0y4AYRuR6rJkWgiLwDnBCRdsaYJBFpB5x0trMx5nXgdYABAwYYZ31U03Y69gPOri5eIy3UcyhAYbGpslRXDQmllGoqKqoj8S3wrYgsNcYcrI4TGmP+DvwdwD4icb8xZrqIPAXMAhbZv66qjvOppufs6tUuJwQn0nNIycg53xDUnh2Bvdny2g/l7lfRrZ9KKdVUuHrXhq+IvI51a2bhPsaYa6oxlkXAByJyK3AImFSNx1ZNjKOolEPyP/4DQJd/Li/W7/9e+8GlpGBY5udclrXufIMPhOT4whI/1wLSKpZKqUbK1UTiQ+BVrLss8qvr5MaY9cB6++MUYFh1HVs1Ljs3HmXv5hPF2k4dtgpMvf74F6RmpRS2Oy5jOJIHoNwaEi7Vg1jyOGQfcj8Z0CqWSqlGytVEwmaMeaVGI1GqHHs3n+DUkQxCOgaU2paalUKmLQt/r2Zl7p9zQRrt+5fet1K0MqVSSpXiaiLxqYjcCawECi8ol7UqqFI1IaRjAOPuu6jweezCDwCIG/wVcH5NDMeEypKXMZRSSlU/VxOJWfavc4u0GaBb9YajlFJKqYbE1UW7utZ0IEoppZRqeFwtke0vIg/a79xARHraC0sppZRSqglz9dLGEmALVpVLgCNYd3KsLnMPpcrhrGhUebL9RgJwcMbzhbUfUgNtANzwXRIA/3v6DwC0TT7E8dDO/F8FtSBA60EopVRVubrWRndjzJNAHoAxJguQGotKNXqOolHuSMnI4VyOrcztx0M7s6PXYJeOFdkukBujO7gVh1JKKddHJHJFpBnWBEtEpDtF7t5Qyh0li0aVZ+szWwHoct+0wpGG8cet4qefDA4FKLb096jqDFQppVSZXE0kHgHWAJ1E5F2s9TJm11RQqnFxVkwqxaMHWXmJ5N8yh7z8vAqP4ZHvRYGnjUf/epow+2jEwXOQHezFntQT9Aru5XzHuCWwY0WVvwetTKmUUs65dGnDGPMVMB4reXgPGGCvSqlUhRzFpIrKykskL/80efl5FJiCMvY8r8DThs0vu1hbdrAXZ7r50iu4F9d3u975jjtWWElAVWllSqWUcsqlEQkRGQd8Y4z5zP78AhH5gzHm45oMTjUeJYtJLZuaCgLrbzKAsGTkv10+1hT7pY0Ky1o7aEVKpZSqMa5OtnzEGFO4UIEx5gzW5Q6llFJKNWGuJhLO+rk6v0IppZRSjZSryUCciDwLvIR158bdWHUllKo2//npEKu2Ha2wn9Z+UEqp+sPVROJu4CEg1v78S+DBGolINTq25GRsKSkcnPF8YVtBZiYe/v7F+q3adtSlJEFrPyilVP1RYSIhIp7AKmPMtbUQj2qEbCkpFGRmFrtA5uHvj1erVkDxOzYi2wW6PolSKaVUnaswkTDG5ItIpogEFZ1wqZoeZ/UgypKclUxqVgoAQRKEj3cmC6Z6Fm7v+j8BUsuvAaGUUqrec/XSRjawQ0S+As45Go0xf6mRqFS95KgHEdIxoMK+qVkpZNqy8Pdqhk9uEi0ytzntV24NCKh6QSktJKWUUjXK1UTiM/s/1cSVrAdRlpg1/wKsstUHZ8wEX5g88nw57Nif5gPw8MhF5R/IUVDK3WRAC0kppVSNcimRMMYss6+10dkYs6eGY1KqOC0opZRS9ZZLdSREZCywDWu9DUQkWkQ+qcG4lFJKKdUAuHppYwEwCFgPYIzZJiJdaygm1QCVrAGR6HMWsMpZz06yHjtW7QSIOHZ+u4PWh1BKqYbH1cqWNid3bJjqDkY1XI4aEFWh9SGUUqrhcXVEIl5EpgGeItIT+Avwfc2FpeorW3KyNXmyBMeog2NEISH1MAARwa+QnXYMv4iIYvUhYheuAmCh1oxQSqkGzdURibuBKCAH+A+QBtxTQzGpesyWkkJ2QkKl9vGLiCBwzJgaikgppVRdKndEQkT8gDuAHsAO4BJjjK02AlN1o7yiU6eOZOBbkEtia3j/Zs9i23YlWc8j21lf96R60Su4F0tGLqnZgJVSStWpikYklgEDsJKIUcDTNR6RqlOOolPOhHQMwC89jkxbVoXHqbDQlFJKqUahojkSkcaYvgAi8hawueZDUnWtzKJTcUv4Ys06AJYknSy2aWeSNRc3iuzzjUlLYdNS5ydJsn9dMrr8YLQypVJK1WsVjUjkOR7oJQ3FjhVgCiruV520MqVSStVrFY1I9BMRxz19AjSzPxfAGGP0pv9GqmRdCICHU9LIR8jBjym5xVeR35Vr1YCIjXHxLoxDVolsYiooka2UUqpeKzeRMMZ4lrddNV6OuhCuFojSGhBKKdU0uVpHQjVBke0Ci9V+YEkQR+Q0/j6exduVUko1WbWeSIhIJ2A50BYoAF43xrwgIsFALBAGJAKTjTGnazu+puJ07AecXb26VHu230gAZv/+AQAHvysyInH8GK1PFnCyY62EqJRSqgGoixEJG3CfMWariLQAtojIV8BsYK0xZpGIzAfmA/PqIL5Gy1EjIjkrGc/9Z/HJv4xcn+JXr3IlCJ/cJPzEqkyZkFp0ey6ZrYWDF4cwohbjVkopVX/VeiJhjEnCfvOfMSZdRHYDHYAbgavs3ZZhLRCmiUQ1ctSISPVPoZXJJ9fHk+QO/iV6pZHS6SQbfMMAis+ROL4DgOsvjamdgJVSStV7dTpHQkTCgP7AT0Abe5KBMSZJRFrXZWyNVUjHAL6P+oqp/9pJRHAEXf653Gk/x6qcS0YWnSNhr/kQPqmmw1RKKdVAuLrWRrUTkQDgv8A9xhiXl40UkdtFJE5E4pKTk2suQKWUUkpVqE5GJETEGyuJeNcY85G9+YSItLOPRrQDTjrb1xjzOvA6wIABA3Qp8xKc1X9wuDApB4BdwWfJzM1nV9JZvnjuIS7LWleq7/25+fj7eMKSoPONWmVSKaVUCbU+IiEiArwF7DbGPFtk0yfALPvjWcCq2o6tMXDUf3DVZVnrCMs7UKrd38eTkADf4o1aZVIppVQJdTEicRkwA9ghItvsbQ8Ai4APRORW4BCgF+LdVKr+g93KZ7YCsL9dIP4+nkQEB9KlXR7Qn6iYz2o5SqWUUo1BXdy18R1WiW1nhtVmLI2Joy7EbPtoRLH6D3aOGhFTv9lJ66OZEFyrISqllGqE6myypapeZ1evJjshweX+Jzv4EzhmTA1GpJRSqinQEtkNlKO4FGAVmPIcClFDSQy15jVs9ym9TEqztGCyglL519Ve9AruxYiRk2HJsmqJ59ev17B703qX+ycn/k5oWNdqObdSSqm6oyMSDZSjuBRAalYKBSa/wn2yglJJ6ZRIr+BeXN/t+mqNZ/em9SQn/u5y/9CwrvS+7KpqjUEppVTt0xGJBiykYwDj7ruImDX/Kiww9X89/gRQJ4tqhYZ1Zcojuiy4Uko1JZpINADOakM4akK8/9oPJPqcrwtRmaW/lVJKqarSSxsNQGVqQ0S2C+TG6A41HJFSSill0RGJBqKwNkTcEtixgpUyGYB/+HxAjJzAn2wi5CCxPo/DLqx/rtBqlUoppapARyQamh0rClfhrBZarVIppVQV6IhEA3I69gPO/ucY0IrsMG8ADn7TiqmpybROFujbF2Kcr+aplFJK1QQdkWhAzq5eTfbJXKfbtMCUUkqpuqAjEnWkaEGpkpKzkknNSil8Hp5r1Yj42nMoRF9GcmsPmmVZxaW+vMKTPalFCkwppZRStUhHJOpI0YJSJaVmpZBpyyp3f0dxKaBGCkwppZRSrtARiRrmrAYE2OtAeMLXATmltiUG/xeAsNz7AQprQ9x2/BU4voMuV7UHXa1TKaVUPaAjEjWsMjUgyqK1IZRSStVXOiJRCwprQBSx8pmtAPxjzkWl+sessSpTLhlZfJ+DL9ZQgEoppZSbdERCKaWUUm7TEYmaFLeEh1Pesh4vCSq+7bj9DoslD5XeT+x3cywZXWKfY5B7rnpjVEoppapAE4matGMFYXkHSPTuVmqTLcOGLTOfg9uOldo2FatWxEGKb8s+mYtf6+ZaiVIppVS9oYlENShZE6KwDkTuH8g3N5ItzWh+zrPYPkH5QQTkHSHBx7vU8TJtNvy9mkFwRLF2v7ZYRacGaL0IpZRS9YMmEi4q6zZOgAv35RCQVUBGM2vKSbacpIAc/I3BGEBK7+OTm4SvbQfv3x3l9JjXd7ueLuGTqit8pZRSqkZoIuEix22cke0CnW7PaObBrz19AUj0+RiAfydZoxTbh/2HaYM7F+t/cMZM8IXJI3VtDKWUUg2XJhKV4Ow2Tih9K6fj9s0osq2vJZIIpZRSqrHQ2z+VUkop5TZNJJRSSinlNk0klFJKKeU2TSSUUkop5TadbFnNTj/5V6Z+tRmAg7l54NMcvplZql92QgJ+ERGl2pVSSqmGRBOJCvznp0P89PVBepxKxsPrHIv+8XupPs3SgskKSiVmzb+Y+tVmQk4WcKq1h5VENA91ely/iAiruJRSSinVgGkiUYFV247S43gOIQXNSPFOBfxL9ckKSiWlU2Lh81OtPTj70gItKKWUUqrR00TCBf6+XuT4nuToFZtYMnJJuX0PPtMfQJMIpZRSTYJOtlRKKaWU2zSRUEoppZTb6l0iISIjRWSPiOwXkfl1HY9SSimlylavEgkR8QReAkYBkcBNIhJZt1EppZRSqiz1KpEABgH7jTEHjDG5wPvAjXUck1JKKaXKUN/u2ugAHC7y/AgwuCZO9OLNt2LLt1XY7xLAePggBbkM2n2EZa8PL7d/gW8wHj4e+C1sWldlkhN/JzSsa12HoZRSqpbVtxEJcdJminUQuV1E4kQkLjk5uXaCKsjFKz8db6fhFefh44FXy6BaiKp+CQ3rSu/LrqrrMJRSStWy+jYicQToVOR5R+BY0Q7GmNeB1wEGDBhQLMmojD+/+5a7uyqllFLKrr6NSPwM9BSRriLiA0wFPqnjmJRSSilVhno1ImGMsYnIn4EvAE/g38aYnXUcllJKKaXKUK8SCQBjzOfA53Udh1JKKaUqVt8ubSillFKqAdFEQimllFJu00RCKaWUUm7TREIppZRSbtNEQimllFJuE2PcrulU50QkGThYhUOEAKeqKZyaprHWDI215jSkeJtarF2MMaHVEYxSDTqRqCoRiTPGDKjrOFyhsdYMjbXmNKR4NVal3KeXNpRSSinlNk0klFJKKeW2pp5IvF7XAVSCxlozNNaa05Di1ViVclOTniOhlFJKqapp6iMSSimllKqCBptIiMhIEdkjIvtFZH6R9n4i8oOI7BCRT0Uk0Mm+YSKSJSK/iMhuEdksIrMaQLzbivzzKedciSISUoVY/y0iJ0UkvkT7JBHZKSIFIlLurHERuVdEskUkyN04XFWVeO0/23hn22ogTqevAfu2u+3bdorIk+UcozZ/rmW9Zp8SkQQR+VVEVorIBWXsHyUi34jIXhHZJyIPiYhUcM4HKhljJxFZZ/893ikify2yzdXfLSMidxdpe1FEZlcmjsoSET/7353t9rgXFtlWr163SlXIGNPg/mEtMf4b0A3wAbYDkfZtPwNX2h/fAjzmZP8wIL7I827ANiCmIcTrwvkSgZAqxDsUuKjkOYHeQC9gPTCggmNsBjYCsyt5bgE8aiveyv5sa+g1cDXwNeBrf966un+u1RzvdYCX/fETwBNO9m9m3/86+3N/4H/AXRWcN6OScbYDLrI/bgHsdeN36wSwH/Cxt71YCz9fAQLsj72Bn4Ah9e11q//0nyv/GuqIxCBgvzHmgDEmF3gfuNG+rRewwf74K2BCRQczxhwA/gb8BUBEmts/5f5sH7W40d7uKSJP2z/h/Fr0U0xtxusgItfZP3FtFZEPRSSgyOa59k88m0Wkh6vHBDDGbABSnbTvNsbscSGu7kAA8CBwU5H22SKySkTW2D/pPmJvD7N/onwZ2Ap0qs14S8T3YpHnq0XkKvvjDBH5p/0T5I8i0qYyMVL+a+BPwCJjTI497pNlxFfez7WsuG+1jwisF5E3ivZzN15jzJfGGJu9349ARyf7TwM2GWO+tO+TCfwZmG+PK0BElhT5XZogIouAZmKNuL3rSpDGmCRjzFb743RgN9DBvtnV361kYC1QalRSRKLt/9+O0ZeWItJbRDYX6RMmIr+6Em+RuI0xJsP+1Nv+z9i3VfZ1GyYiG+1/B7aKyKX29qvs/+8r7CNI71Y0IqSUOxpqItEBOFzk+RHO//GIB26wP56E629KW4EI++N/AN8YYwZifVp8SkSaA7cDXYH+xpgLAZf+2FVTvN3l/GWNl8S6dPEgcK0x5iIgDisZcjhrjBmE9enqeRfjrC43Ae9hfXLuJSKti2wbBNwMRAOTigzd9gKWG2P6G2OqUq20pjQHfjTG9MN6c/pjJfcv7zUQDlwhIj+JyLciMrCMY5T3cy1FRNoDDwFDgOGcf31XNd6ibsEaaSgpCthStMEY8xsQYL/E8BCQZozpa/9d+sYYMx/IMsZEG2NurkSsgPWGCvTH+nQPlftbsAi4T0Q8S7QvB+bZY9wBPGKM2Q34iEg3e58pwAduxOspItuAk8BXxpifKtilLCeB4fa/A1OAxUW29QfuASKxRpcuc/McSpWpoSYSzrJqx+0ntwB3icgWrKHOXDeOeR0w3/5Lvh7wAzoD1wKvOj6NGWNKfQquwXh/s/+BjTbG3IX15hAJbLLHOQvoUqT/e0W+XuJinNVlKvC+MaYA+Ajrj7jDV8aYFGNMln3b5fb2g8aYH2s5zsrIBVbbH2/BGlqujPJeA15AS6z/07nAB2V8cizv5+rMIOBbY0yqMSYP+LCa4rU6iPwDsOE8oZaS/Usc51rgpcIGY05XIrbSJ7NG4/4L3GOMOWtvdvlvgTHmd6zLRtOKHDMIuMAY8629aRnWZTSwEofJ9sdTgNjKxmyMyTfGRGON6AwSkT6VPYadN/CGiOzA+j+OLLJtszHmiP01s43Kv26VqpBXXQfgpiMU/3TRETgGYIxJwEoEEJFwYLSLx+yPNSwK1h/BCSWHF+1/3N25X7Ym4hWsN+Wbythuynhco0TkQqAn8JX9vdAHOMD5N42SsTien6uVAMtno3hy7VfkcZ4xxhFrPpX/3SnzNWDf9pH9+JtFpABrPYVkR+cKfq5lxV2VYezy4kWsycljgGFFfi5F7eT8m65jn25YcyDSq/C7VIqIeGMlEe8aYz5ytLvxu/X/gBWcvxxSnljgQxH5yDqV2edO7PY4z4jIemAk1ihKZd2LNc+jH9brILvItpwij9153SpVoYY6IvEz0FNEuop198JU4BMAx3CviHhgDf2/WtHB7EOiTwP/sjd9Adzt+FQoIv3t7V8Cd4iIl709uC7itfsRuMwx/0FE/O1/LB2mFPn6g4vHrA43AQuMMWH2f+2BDiLiGC0ZLiLBItIM+AOwqRZjq0giEC0iHiLSCesTfXUp8zUAfAxcA4VveD6UXpSpvJ9rWXFvBq60X9f3ohLzb8qLV0RGAvOAG+xzH5x5F7hcRK6179MMa8jdcUfKl1hzJrBvb2l/mGdPDFxi/x19C9htjHm2xLZK/W7ZE49dWAkSxpg04LSIXGHvMgP41r7tN6w35odwYzRCRELFfreL/WdzLZBQ2ePYBQFJ9lGHGVgTZZWqNQ0ykbBfWvgz1hv+buADY8xO++abRGQv1i/lMWBJGYfpLvbbP7GGKf9ljHH0fQxruPBXsW6xesze/iZwyN6+nSLDoLUQb8ljJgOzgffsE71+pPg1cF8R+Qn4K9YnFpeJyHtYyUcvETkiIrfa28eJyBGsSyWficgXTnafCqws0bbS3g7wHfA21jDrf40xcZWJrQbi9eL8p7ZNwO9Y18Kfxpo3Uy0qeA38G+hmf629D8xy8im/vJ+r07iNMUexPmX/hHVXyC4grRrifRHrUsFX9jk7pd6g7ZeubgQeFJE99th+tu8L8DjQUkTi7b9LV9vbX8f6/XJ1/tFlWG+e1xSZQ3S9fZs7v1v/pPjk0VlYc6R+xZrX82iRbbHAdNyYH4F1t8k6+3F/xhpdXA1uvW5fBmaJyI9Y823qw+ieakK0sqWqNWLdmz/AGPPnivrWFrHuyLnZGDO5ws4NkIgEGGMy7CMSK4F/G2NKJiSqgWnsr1vVsOj1MtVkicijWJ+aZ9dxKDVpgf3ygh/W5YSP6zYcVVVN5HWrGhAdkVBKKaWU2xrkHAmllFJK1Q+aSCillFLKbZpIKKWUUsptmkgoVQkikm+/xXCnWOtu/M1ep6C8fcJExKVbhZVSqqHRREKpynGsBRGFtX7F9cAjFewThos1R5RSqqHRuzaUqgQRyTDGBBR53g2roFAI1lonb2Mt8AXwZ2PM9/ZCQb2xikYtw6rwuAi4CvAFXjLGvFZr34RSSlUjTSSUqoSSiYS97TRWVdF0oMAYky0iPYH3jDEDxFrS+35jzBh7/9uB1saYx0XEF6sy5ST7wlFKKdWgaEEqparOsTiWN/CiiERjrcMQXkb/64ALRWSi/XkQ1oJcmkgopRocTSSUqgL7pY184CTWXImyVmEsthtwtzHG2RoKSinVoOhkS6XcJCKhWCtKvmhfZKusVRjTsRa5cvgC+JNjlUsRCReR5iilVAOkIxJKVU4zEdmGdRnDhjW50rF89cvAf0VkErCO86sw/grY7KtcLgVewLqTY6t9GexkrCXVlVKqwdHJlkoppZRym17aUEoppZTbNJFQSimllNs0kVBKKaWU2zSRUEoppZTbNJFQSimllNs0kVBKKaWU2zSRUEoppZTbNJFQSimllNv+fwpFPZuWwDh4AAAAAElFTkSuQmCC", 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", 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0bNiQxYsXk+jLxYUXXkjdunVZsGBBwtLmsGHDqFmzJnPmzGHJkiUHrR8+fDgAH3zwwUEl5Bo1anDppZcC8O6777Jy5coD1tepUye/JD1t2jTWrDmwytKgQQPOP/98AN566y3Wr19/wPojjjgi/5ae1157jc2bNx+wvmnTppx99tkAvPzyy2zfvv2A9S1btqRv374ATJ48+aAWb5s2bfJLzc888wx5eXkHrG/Xrl3+vaYF33eg915GvvfeD342aPhyxrz3rrzxT3yyegvND6/DT7ODSxqlfe+lSl5e3i/Xr18/Yf369Z3I/ArnfmBxXl7eLwvbIKMTqIhIVfPJ6i18uelbmh9e8TrJHX/88RuBhK21ykglXBGpujKkhPvs7NW8umAtAEvXbadDswZMvrJXMXsVLl0l3Kom05vYIiKV3qsL1rJ0XVAW7tCsAeeFpVspXyrhiohUQKludUrqKYGKiFQQ8Ulz9spvAOjZppFanRWUEqiISAURK9V2aNaAnm0acV52Cy7p2aq8w5JCKIGKiJST+BYnqFSbaZRARUTKSMGEGV+mBXUQyjRKoCIiZSS+RAuoTJvhlEBFRNJEJdrKTQlURCTFYolTJdrKTQlURCTFYqValWgrNyVQEZFSUqm2atJQfiIipfDs7NXcMGVRfrkWVKqtKtQCFREphVjL8/ZBWSrVVjHlkkDN7LfALwEHFgGXA3WByUBrYBVwobtvKY/4RESKUnCc2p5tGil5VkFlnkDNrAXwG6CDu39nZs8DFwEdgOnuPt7MxgJjgTFlHZ+ISCIap1YKKq8Sbg2gjpl9T9Dy/Bq4Hjg1XP8UMAMlUBGpIDROrRRU5gnU3dea2d3AauA7YKq7TzWzo9x9XbjNOjM7MtH+ZjYCGAHQqpXevCKSfs/OXs3sld/Qs00j9ayVfGXeC9fMDgfOA9oAzYFDzezSqPu7+6PunuPuOU2aNElXmCIi+WKlW5VqJV7kFmiY+JoTtBpXufv+JM/ZF1jp7rnhcV8GegMbzKxZ2PpsBmxM8vgiIqWS6L5OdRSSgopMoGbWEPg1cDFQC8gFagNHmdlHwMPu/k4Jz7kaOMHM6hIk4zOAucC3wGXA+PDnqyU8rohI0grrJAS6r1MSK64F+iLwF+Akd98av8LMjgd+ZmZt3f3xqCd099lm9iIwH8gDPgEeBeoBz5vZLwiS7JDIv4WISCmpk5CUVJEJ1N37FbFuHjAvmZO6+03ATQUW7yFojYqIlJkNO3bzm//7UMPvSYlFugZqZgYMA9q6+y1m1gpo6u4fpzU6EZE0iJVr/7B5Gzt25zF77zf5rU6RqKJ2InoY2A+cDtwC7ABeArqnKS4RkbSJlWupBfVr1+D2/hqGT0ouagLt6e7dzOwTAHffYma10hiXiEhaxN/T2bFWQwA6KnlKEqIm0O/NrDrB2LWYWROCFqmISIWXqIftedktYGl5RiWZLupACg8AU4Ajzew24H3g9rRFJSKSQvklW4JbUzRziqRCpBaou08ys3kEvWQN+Km7L0trZCIipVBwxhT1sJVUi9oL935gsrs/lOZ4RERSIv6+Tg2EIOkQ9RrofGCcmbUjKOVOdve56QtLRKT01OqUdIpawn0KeMrMGgGDgTvMrJW7H5vW6ERESiBR2VYkXUo6G8uPgOOA1sBnKY9GRKQU4jsLqWwr6Rb1GugdwPnACuB54NaCY+OKiJSlgjOmgDoLSdmKeg10JdDL3TelMxgRkeLEEmfBGVNArU4pW8VNZ3acu38GfAy0CsfAzefu89MZnIhIQbEyrWZMkfJWXAv0d8AI4E8J1jnB2LgiImkXa3mqTCsVRXHTmY0IH57j7rvj15lZ7bRFJSISSlSyVZlWKoKo10A/ALpFWCYiklIq2UpFVdw10KZAC6COmXUlGMYPoAFQN82xiUgVVLB3rUq2UlEV1wI9CxgOtATuiVu+A7ghTTGJSBVUWO9a9ayViqq4a6CxEYgGu/tLZRSTiFRBKtVKpok6lN9LZtYf6AjUjlt+S7oCE5HKTzOmSCaLOhLRIwTXPE8DJgAXENwbKiJSIokmt+7ZppFKtZJxovbC7e3unc3sU3f/bzP7E/ByOgMTkcop/l5OlWslk0VNoN+FP3eZWXNgM9AmPSGJSGWh8WqlMouaQF83s8OAuwjmBnWCUq6IyAEKK9HGqFQrlUXUTkS3hg9fMrPXgdruvi19YYlIplKJVqqK4gZSOL+Idbi7roOKVHEa+ECqquJaoOcWsc5RRyKRKi++xQkq0UrVUdxACpeXVSAiklk0O4pUdVHvA/1DouUaSEGkaimsg5BanFIVRe2F+23c49rAAGBZsicNe/ROADoRlIJ/DiwHJgOtgVXAhe6+JdlziEjqqYOQyA+i9sI9YEJtM7sb+Fspzns/8Ja7X2BmtQhGOboBmO7u481sLDAWGFOKc4hICmi4PZHEorZAC6oLtE1mRzNrAJxMMMsL7r4X2Gtm5wGnhps9BcxACVSkzBXsVavh9kQSi3oNdBFBqRWgOtAESPb6Z1sgF3jSzLoA84BrgaPcfR2Au68zsyMLiWUEMAKgVSuVjkRSrWCvWpVqRRKL2gIdEPc4D9jg7nmlOGc3YKS7zzaz+wnKtZG4+6PAowA5OTlezOYiEoHKtCIlF/Ua6FdmdjhwdLjPUeFACvOTOOcaYI27zw6fv0iQQDeYWbOw9dkM2JjEsUWkBBJNYq0yrUg0UUu4txJcs1zBD6VcB04v6Qndfb2Z/dvM2rv7cuAMYGn47zJgfPjz1ZIeW0RKRpNYiyQvagn3QuCYsMNPKowEJoU9cL8ELgeqAc+b2S+A1cCQFJ1LROKoXCuSGlET6GLgMFJUVnX3BUBOglVnpOL4InIgTWItknpRE+j/AJ+Y2WJgT2yhuw9MS1QiklIaAEEk9aIm0KeAO4BFwP70hSMiqaTxakXSJ2oC3eTuD6Q1EhFJufjkqVKtSGpFTaDzzOx/CIbviy/hJnMbi4ikkToJiZSNqAm0a/jzhLhlSd3GIiKppaH3RMpH1IEUTkt3ICKSHA29J1I+NB+oSAZSmVak/JXLfKAiUjIq04pUPOU1H6iIlIDKtCIVT5nPByoixSvY4lSZVqTiKY/5QEWkEIlmRwFUphWpgMpjPlARKYRmRxHJHFETaDNgibvvADCzembWMW5OTxFJQpUp1c59Eha9WN5RHGz9ImiaVd5RSIaKmkD/DHSLe74rwTIRiajKlWoXvVgxk1XTLMi6oLyjkAwVNYGau8eugeLu+80s2Q5IIlVelSzVNs2Cy98o7yhEUiZqEvzSzH5D0OoEuJpgImwRiUiDH4hULlET6FXAA8A4gt6404ER6QpKpLLQRNYilVfUgRQ2AhelORaRSkcTWYtUXkUmUDMbBzzs7t8Usv50oK67v56O4EQykUq1IlVDcS3QRcBrZrYbmA/kEoyFeyyQDUwDbk9ngCKZJr7VqVKtSOVVZAJ191eBV83sWKAPwf2g24FngBHu/l36QxTJDLGWp1qdIlVD1GugnwOfpzkWkYyU6J5OtTpFKj/dyylSSlXynk4RUQIVKY1nZ69m9spv6NmmkUq2IlVM1NlY+rj7rOKWiVRmBcethR/u7VTJVqTqqRZxu/+NuEyk0oqVauP1bNOI2wdlqWwrUgUVdx9oL6A30MTMfhe3qgHBvKAilZ5614pIIsWVcGsB9cLt6sct3w5oCgOptAobgk+lWhGJKe4+0HeBd81sort/VUYxiZQ7DcEnIsWJ2gv3EDN7FGgdv4+7n57sic2sOjAXWOvuA8ysETA5PMcq4EJ335Ls8UWSoXKtiEQVNYG+ADwCTAD2pejc1wLLCK6nAowFprv7eDMbGz4fk6JziRTr2dmruWHKIkDlWhEpXtQEmufufy5+s2jMrCXQH7gNiHVOOg84NXz8FDADJVApQ7FrnupVKyJRRE2gr5nZ1cAUYE9sYWGztERwH/BfHNgx6Sh3Xxced52ZHZloRzMbQTgXaatW+iMnpVNw5pSebRopeYpIJFHvA70MGA18AMwL/81N5oRmNgDY6O7zktnf3R919xx3z2nSpEkyhxDJF39vp2ZOEZGSiDqYfJsUnrMPMNDMfkIwNVoDM3sG2GBmzcLWZzNgYwrPKXIAdRYSkdKKOpRfXYJrla3cfUQ4vVn7ZCbSdvfrgevD454KXOful5rZXQQt3fHhz1dLemyRwhQchk/3dopIaUW9BvokQdm2d/h8DUHP3BIn0CKMB543s18Aq4EhKTy2VHHxrU1A93aKSKlFTaDHuPtQM7sYwN2/MzMr7cndfQZBb1vcfTNwRmmPKRJTsIOQSrUikkpRE+heM6sDOICZHUNcb1yRiiTRBNfqICQiqRY1gd4EvAUcbWaTCDoCDU9XUCKloQmuRaQsRO2F+7aZzQdOAAy41t03pTUykYgKdhBSuVZEykLUXriDgH+6+xvh88PM7Kfu/ko6gxNJpKgetaD7OUWkbEQu4br7lNgTd99qZjcBr6QlKpEiqEetiFQEURNoohGLou4rUmrqUSsiFU3UJDjXzO4BHiLoiTuS4L5QkbRSj1oRqaiiJtCRwI0E83UCTAXGpSUikTjqUSsiFVWxCTSc+PpVd+9bBvGIqFwrIhmh2ATq7vvMbJeZNXT3bWURlFRNKteKSCaJWsLdDSwys7eBb2ML3f03aYlKqiSVa0Ukk0RNoG+E/0RSSuVaEclUUUcieiocC7eVuy9Pc0xShcTf06lyrYhkkqgjEZ0L3A3UAtqYWTZwi7sPTGNsUolpQmsRyXRRS7g3Az34YeqxBWbWJk0xSSX37OzV3DBlEaAJrUUkc0VNoHnuvq3AFKCehnikCohd87x9UJY6ColIxoqaQBeb2SVAdTM7FvgN8EH6wpLKJNFsKT3bNFLyFJGMVpKRiH5PMIn2s8A/gD+mKyipHBLd1wmaLUVEKociE6iZ1QauAn4ELAJ6uXteWQQmmU/3dYpIZVZcC/Qp4HvgPeAc4MfAqDTHJBlM93WKSFVRXALt4O5ZAGb2OPBx+kOSTBOfNDUMn4hUFcUl0O9jD9w9r0AvXBHgwMEQVK4VkaqiuATaxcy2h48NqBM+N8DdvUFao5MKS6VaEanqikyg7l69rAKRik+lWhGRH0S9jUVEpVoRkThKoFIsjVsrInKwauUdgFR88clTpVoRkYBaoJKQOgmJiBStzBOomR0N/AVoCuwHHnX3+82sETAZaA2sAi509y1lHV9Vl2j4PbU8RUQOVh4t0Dzg/7n7fDOrD8wzs7eB4cB0dx9vZmOBscCYcoivStPweyIi0ZR5AnX3dcC68PEOM1sGtADOA04NN3uKYO5RJdAyoHKtiEjJles1UDNrDXQFZgNHhckVd19nZkeWZ2yVne7pFBEpnXJLoGZWD3gJGOXu26MOE2hmI4ARAK1aqbyYLN3TKSJSOuWSQM2sJkHynOTuL4eLN5hZs7D12QzYmGhfd38UeBQgJyfHyyTgSkqlWhGR5JVHL1wDHgeWufs9cav+BlwGjA9/vlrWsVVm8SVb+OFap4iIJKc8BlLoA/wMON3MFoT/fkKQOPuZ2edAv/C5pEisZBuja50iIqVTHr1w3yeYzSWRM8oylspOvWtFRNJHIxFVIgXLtOpdKyKSPkqglUh8z1pAvWtFRNJICTTDqUwrIlI+NBtLBnt29mpumLIov1SrMq2ISNlRCzSDxVqetw/KUplWRKSMKYFmoPgJrnu2aaTkKSJSDlTCzUCa4FpEpPypBZoh1FlIRKRiUQKtwDRjiohIxaUEWoFpxhQRkYpLCbQCiu8kpFKtiEjFpARagcQSZ3y5VqVaEZGKSQm0Aom/NUXlWhGRik0JtJypd62ISGZSAi0H6l0rIpL5lEDLgXrXiohkPiXQMlBwnk6VakVEMp8SaBol6lULmjVFRKQyUAJNI/WqFRGpvJRAU0ilWhGRqkMJtJQK61ELKtWKiFRmSqClpB61IiJVkxJoEjT4gYiIaELtJMRanaAyrYhIVaUWaERqdYqISDwl0GIkupdTrU4REVECLYbu5RQRkUSUQBNQuVZERIqjBBpH5VoREYmqwiVQMzsbuB+oDkxw9/FldW6Va0VEJKoKlUDNrDrwENAPWAPMMbO/ufvSdJ431vJUuVZERKKqUAkU6AF84e5fApjZX4HzgJQn0I8evoL6W5cB0HZ3Hr8F6teuQeM9h8CTtVN9OpGqbf0iaJpV3lGIpFRFS6AtgH/HPV8D9IzfwMxGACMAWrVKTYm1fu0aNK53CEfVV+IUSYumWZB1QXlHIZJSFS2BWoJlfsAT90eBRwFycnI8wfaRnHD1Y8nuKiIiUuGG8lsDHB33vCXwdTnFIiIiUqiKlkDnAMeaWRszqwVcBPytnGMSERE5SIUq4bp7npldA/yD4DaWJ9x9STmHJSIicpAKlUAB3P3vwN/LOw4REZGiVLQSroiISEZQAhUREUmCEqiIiEgSlEBFRESSYO5Jj0VQ7swsF/iqFIdoDGxKUTjppljTQ7GmTybFW9Vi/Q93b5KKYKqyjE6gpWVmc909p7zjiEKxpodiTZ9MilexSjJUwhUREUmCEqiIiEgSqnoCfbS8AygBxZoeijV9MilexSolVqWvgYqIiCSrqrdARUREkqIEKiIikoSMTaBmdraZLTezL8xsbNzyLmb2oZktMrPXzKxBgn1bm9l3ZvaJmS0zs4/N7LIMiHdB3L9aRZxrlZk1LkWsT5jZRjNbXGD5EDNbYmb7zazIbvRm9lsz221mDZONI6rSxBu+tosTrUtDnAnfA+G6keG6JWZ2ZxHHKMvXtbD37F1m9pmZfWpmU8zssEL272hm/zSzf5nZ52Z2o5lZMee8oYQxHm1m74Sf4yVmdm3cuqifLTezkXHLHjSz4SWJo6TMrHb4d2dhGPd/x62rUO9bKYK7Z9w/gqnOVgBtgVrAQqBDuG4OcEr4+OfArQn2bw0sjnveFlgAXJ4J8UY43yqgcSniPRnoVvCcwI+B9sAMIKeYY3wMvAcML+G5DahWVvGW9LVN03vgNGAacEj4/MhUv64pjvdMoEb4+A7gjgT71wn3PzN8Xhd4E/h1MefdWcI4mwHdwsf1gX8l8dnaAHwB1AqXPVgGr68B9cLHNYHZwAkV7X2rf0X/y9QWaA/gC3f/0t33An8FzgvXtQdmho/fBgYXdzB3/xL4HfAbADM7NGzVzAlbqeeFy6ub2d3hN9pP47+1lmW8MWZ2ZvgNe76ZvWBm9eJWjw6/4X5sZj+KekwAd58JfJNg+TJ3Xx4hrmOAesA44OK45cPN7FUzeyts2dwULm8dtiAeBuYDR5dlvAXiezDu+etmdmr4eKeZ3Ra2GD4ys6NKEiNFvwd+BYx39z1h3BsLia+o17WwuH8RtgBnmNlj8dslG6+7T3X3vHC7j4CWCfa/BJjl7lPDfXYB1wBjw7jqmdmTcZ+lwWY2HqhjQYVlUpQg3X2du88PH+8AlgEtwtVRP1u5wHTgoCqUmWWH/9+x1vbhZvZjM/s4bpvWZvZplHjj4nZ33xk+rRn+83BdSd+3rc3svfDvwHwz6x0uPzX8f38xrBhMKq4CICWTqQm0BfDvuOdr+OFDsxgYGD4eQvQ/xvOB48LHvwf+6e7dCVoHd5nZocAIoA3Q1d07A5E+5CmK9xj7oXz7kAUl2nFAX3fvBswl+BIQs93dexB8m74vYpypcjHwHEFLqb2ZHRm3rgcwDMgGhsSVqNoDf3H3ru5emuEZ0+VQ4CN370LwR/mKEu5f1HugHXCSmc02s3fNrHshxyjqdT2ImTUHbgROAPrxw/u7tPHG+zlBy7KgjsC8+AXuvgKoF5ZSbwS2uXtW+Fn6p7uPBb5z92x3H1aCWIEgkQBdCVpzULK/BeOB/2dm1Qss/wswJoxxEXCTuy8DaplZ23CbocDzScRb3cwWABuBt919djG7FGYj0C/8OzAUeCBuXVdgFNCBoJrQJ8lzSAKZmkATfYuK3Y/zc+DXZjaPoKSzN4ljngmMDd/cM4DaQCugL/BI7Nu3ux/U6kljvCvCPyzZ7v5rgj+KHYBZYZyXAf8Rt/1zcT97RYwzVS4C/uru+4GXCf54xbzt7pvd/btw3Ynh8q/c/aMyjrMk9gKvh4/nEZTQSqKo90AN4HCC/9PRwPOFtBSKel0T6QG86+7fuPv3wAspijfYwOz3QB6Jv0hawe0LHKcv8FD+AvctJYjt4JMF1ZeXgFHuvj1cHPlvgbuvJCiPXxJ3zIbAYe7+brjoKYLLBRAkzAvDx0OBySWN2d33uXs2QQu+h5l1KukxQjWBx8xsEcH/cYe4dR+7+5rwPbOAkr9vpQg1yjuAJK3hwG+TLYGvAdz9M4IEiJm1A/pHPGZXgvIPBB/+wQXLKOEftWRunE1HvEaQjC4uZL0X8jitzKwzcCzwdpgDagFf8sMfy4KxxJ5/WyYBFi2PA79U1o57/L27x2LdR8k/O4W+B8J1L4fH/9jM9hMMGJ4b27iY17WwuEtTrisqXizodDcAOCPudYm3hB+STWyftgTXOHeU4rN0EDOrSZA8J7n7y7HlSXy2bgde5Ieyb1EmAy+Y2cvBqfzzZGIP49xqZjOAswlazSX1W4LruF0I3ge749btiXuczPtWipCpLdA5wLFm1saC3qgXAX8DiJW1zKwaQYnzkeIOFpZ+7gb+N1z0D2BkrBVgZl3D5VOBq8ysRri8UXnEG/oI6BO7vmlmdcM/EjFD435+GPGYqXAxcLO7tw7/NQdamFmsddzPzBqZWR3gp8CsMoytOKuAbDOrZmZHE7TgUqXQ9wDwCnA65P+hr8XBs20U9boWFvfHwCnhdbsalOD6elHxmtnZwBhgYHhtM5FJwIlm1jfcpw5BaTHWw3gqwTVRwvWHhw+/DxNiJOFn9HFgmbvfU2BdiT5bYcJdSvDFAHffBmwxs5PCTX4GvBuuW0GQkG4kidanmTWxsPdy+Nr0BT4r6XFCDYF1YSvzZwQdwKQMZGQCDUuo1xAkumXA8+6+JFx9sZn9i+DN+DXwZCGHOcbC21gIyjH/6+6xbW8lKIt8akFX8VvD5ROA1eHyhcSVe8og3oLHzAWGA8+FHRg+4sBrXIeY2WzgWoJvqJGZ2XMESbe9ma0xs1+EyweZ2RqCkvAbZvaPBLtfBEwpsGxKuBzgfeBpgnLSS+4+tySxpSHeGvzwLX0WsJLgWtfdBNfFU6KY98ATQNvwvfZX4LIErbqiXteEcbv7WoJW1WyCXr5LgW0piPdBgpLo2+E1+YMSU1iiPw8YZ2bLw9jmhPsC/BE43MwWh5+l08LljxJ8vqL2L+hDkDROj+sj8JNwXTKfrds4sFPUZQR9ID4luG5/S9y6ycClJHH9k6D38DvhcecQVJNeh6Tetw8Dl5nZRwTX0ytCNadK0FB+UmYsuLcux92vKW7bsmJBD+th7n5hsRtnIDOr5+47wxboFOAJdy+YiCXDVPb3baZQPVyqLDO7haCVNLycQ0mnm8Myam2Csukr5RuOlFYVed9mBLVARUREkpCR10BFRETKmxKoiIhIEpRARUREkqAEKlICZrYvvFViiQXj4v4uvM+wqH1am1mkW55EJHMogYqUTGys1o4E48v+BLipmH1aE/GeYRHJHOqFK1ICZrbT3evFPW9LcCN8Y4KxiJ8mGHge4Bp3/yC8wf3HBIMdPEUwIs944FTgEOAhd/+/MvslRCQllEBFSqBgAg2XbSEYBWoHsN/dd5vZscBz7p5jwdRi17n7gHD7EQRzfv7RzA4hGEloSDiguYhkCA2kIFJ6sUHbawIPmlk2wTip7QrZ/kygs5ldED5vSDBQvBKoSAZRAhUphbCEu49gTsabKHxWjAN2A0a6e6IxTkUkQ6gTkUiSzKwJwQwfD4aDvxc2K8YOgsHXY/4B/Co264iZtbNgwnYRySBqgYqUTB0LJjCvSTAP59NAbBqth4GXzGwI8A4/zIrxKZAXzjoyEbifoGfu/HA6rlyCqd1EJIOoE5GIiEgSVMIVERFJghKoiIhIEpRARUREkqAEKiIikgQlUBERkSQogYqIiCRBCVRERCQJ/x+ZDbssND+dcAAAAABJRU5ErkJggg==", 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", 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", 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" ] @@ -11538,7 +11592,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **60-64** population up to 15 Dec 2021" + " ## COVID vaccination rollout among **60-64** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -11569,7 +11623,7 @@ }, { "data": { - "image/png": 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", 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", 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", + "image/png": 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", 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", 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", 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", 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", 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", + "image/png": 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dfPPNnS6//PIOI0eO3HL66afXeHB5JVARkTrUYPp1VlFSTKQJEyZsevTRR1tv3Lix6YQJE7564403Mq+55pr866+//oABHhYvXrz8mWeeaXnzzTd3eOONN7bee++9+TW5lhKoiEgdUL/OunHxxRdvvuuuuzoUFxfbqFGjPm/atKlPnjz5OxMnTvy6ZcuWJatWrWrarFkz37t3r7Vt27b4iiuu+DozM7Nk5syZh9f0WkqgIiIJpMRZtzIyMnzw4MFbDz300H1NmjTh3HPP3bps2bKMAQMGdAc45JBDSmbNmrVqxYoVB914440dGzVqRJMmTfyhhx76oqbXUgIVEUkAJc7k2LdvH4sXL27x9NNPf1a67tZbb91Y2jK3VM+ePXePGjWqVk+clUBFROIsngO/S/QWLVqUMXLkyCPPOOOMb3JycnYn+npKoCIicRSZPOttA6EUdcwxx+xau3ZtXl1dTwlURCQOGkzr2qqVlJSUWKNGjdJ3nswIJSUlBpRUtl0JVEQkWgunQ96cA1ZvKNpFt03buRbIzGpC6xYHBQMixPKErSAPsnNqHWqSLC0sLOzRpk2bLemeREtKSqywsLAlsLSyfZRARUSilTenLMFtKNrFpm3BY7bSwd9Lh+GrlewcyBld20iTori4+McFBQWPFhQU9CL9x1ovAZYWFxf/uLIdkpJAzexa4MeAA3nABOAQYDbQBVgNnOfuNRqXUEQk4bJzeKLH7/drJAQwMrcDAxtele1+jjnmmI3AWcmOo67UeQI1sw7Az4Ae7r7TzJ4CLgB6AG+6+xQzmwRMAm6o6/hERKoSOVdnA33OKaFkFbGbAAebWROCkud6YCQwM9w+Ezg7OaGJiFRsQ9EuVm3aDih5ShISqLuvA+4F1gD5wBZ3nwu0c/f8cJ98oG1Fx5vZRDNbaGYLCwsL6ypsEWnAnpi/hvP/8IGSp+wnGVW4hxGUNrsCm4GnzeyiaI9392nANID+/fundSsvEUl9kf06S1vYNvRnnRJIRiOiYcAqdy8EMLNngcHABjNr7+75ZtYe2FjVSUREEqmifp09l7dMclSSSpKRQNcAA83sEGAnMBRYCGwHxgFTwt8vJCE2ERHN1SlRqfME6u7zzWwOsBgoBv5NUCXbAnjKzC4hSLJj6jo2ERENxSfRSko/UHe/Hbi93OrdBKVREZE6p6H4pKY0EpGINGiadkxipQQqIg2Wph2T2lACFZEGR9W1Eg9KoCLSoKjUKfGiBCoiDYJKnRJvSqAiUq+pkZAkihKoiNRbqq6VRFICFZF6pbTECai6VhJKCVRE6o0n5q8h78X7ubbx+2RmNIEsaN3iINotz4jPMHwFeZCdE4cTSX2gBCoiaS/yOedfmr1Pv2Zrada+T/wvlJ0DOaPjf15JS0qgIpK2Kmog1HV3c5pl9oEJryQ5Oqnvok6g4Tye3yGYQWW1u5ckLCoRkSpU2bJ2ekaSo5OGosoEamYtgSuBC4FmQCGQAbQzs38CD7n7WwmPUkQkpJa1kiqqK4HOAf4MnODumyM3mNkxwMVm1s3d/5ig+EREAA2EIKmnygTq7qdWsW0RsCjuEYmIlKNSp6SiqJ6BmpkBY4Fu7n6HmXUGst39XwmNTkQaNJU6JZVF24joIaAEOAW4AygCngEGJCguEWngVOqUVBdtAj3O3fuZ2b8B3P0bM2uWwLhEpIFSqVPSRbQJdK+ZNQYcwMzaEJRIRUTiRqVOSSfRJtCpwHNAWzO7CxgN3JKwqESkQVGpU9JRVAnU3WeZ2SJgKGDA2e7+cUIjE5F6T1ONSTqLthXuA8Bsd38wwfGISAOh6lpJd9FW4S4GbjGzowiqcme7+8LEhSUi9ZWqa6W+iLYKdyYw08xaAaOAX5tZZ3c/MqHRiUi9oepaqW9qOhvL94DuQBfiM7ueiDQAqq6V+ijaZ6C/Bs4FPgOeAu4sPzauiEh5qq6V+izaEugqYJC7b0pkMCJSf6jUKfVdddOZdXf3FcC/gM7hGLhl3H1xIoMTkfRTo1LnwumQNye+ARTkQXZOfM8pUoHqSqDXAROB31SwzQnGxhURia2RUN6c+Ce87BzIGR2/84lUorrpzCaGi2e4+67IbWamad9FpPata7NzYMIrCYxQJDGifQb6PtAvinUi0oDoOac0ZNU9A80GOgAHm1lfgmH8ALKAQxIcm4ikKLWuFam+BPp9YDzQEfhtxPoi4KZYL2pmhwKPAr0InqX+CFgJzCboY7oaOM/dv4n1GiKSGCp1igSqewZaOgLRKHd/Jo7XfQB4zd1Hh/OKHkKQkN909ylmNgmYBNwQx2uKSIxKS5yASp0ioWiH8nvGzIYDPYGMiPV31PSCZpYFnEhQssXd9wB7zGwkcFK420xgHkqgIklXvsSpUqdIINqRiB4mKCWeTFD1Opqgb2gsugGFwHQz6wMsAq4G2rl7PoC755tZ2xjPLyJxoOecIlWLthXuYHfvbWYfufsvzew3wLO1uGY/4Cp3nx9OlTYp2oPNbCJB31Q6d9aXWSTeNOi7SHSiTaA7w987zOw7wFdA1xivuRZY6+7zw9dzCBLoBjNrH5Y+2wMbKzrY3acB0wD69+/vMcYgIuUocYrUTLQJ9OWw5ew9BHODOkFVbo25e4GZfWlmR7v7SmAowcwuy4FxwJTw9wuxnF9Eak4ta0VqLtpGRHeGi8+Y2ctAhrtvqcV1rwJmhS1wPwcmAI2Ap8zsEmANMKYW5xeRKOg5p0jsqhtI4dwqtuHuMT0HdfclQP8KNg2N5XwiUjOqrhWpvepKoGdWsc2JvSGRiCSJqmtF4qO6gRQm1FUgIpJYqq4Via9o+4HeVtH6WAZSEJG6pepakcSIthXu9ojlDGAE8HH8wxGReHthyTqW529V4hSJs2hb4e43obaZ3Qu8mJCIRKTWIseuXZ6/lR7ts5j9k0FJjkqkfom2BFreIQRD8olICqmouvaqlv9g5O73YXpGNUcnQUFeMKG2SBqK9hloHkGrW4DGQBtAzz9FUkilrWun/woKPoHMFExU2TmQMzrZUYjEJNoS6IiI5WJgg7sXJyAeEamhqFrXZufAhFeSEJ1I/RXtM9AvzOwwoFN4TLtwIIXFCY1ORKqkPp0iyRNtFe6dBPN3fsa3VbkOnJKYsESkKurTKZJ80VbhngccEU5+LSJJpq4pIskXbQJdChxKJVOMiUjiqWuKSGqJNoH+L/BvM1sK7C5d6e5nJSQqESlTUdeUHu2zGJnbIcmRiTRs0SbQmcCvgTygJHHhiEgkNRISSV3RJtBN7j41oZGISBk1EhJJfdEm0EVm9r8Ew/dFVuGqG4tIHGngd5H0EW0C7Rv+HhixTt1YROJI1bUi6SXagRROTnQgIg2VqmtF0pPmAxVJgsguKaquFUlPmg9UpI6Vr6pV4hRJT5oPVKQORSZPVdWKpDfNByqSYBVV1yp5iqQ/zQcqkkCqrhWpvzQfqEgCqGWtSP0XbQJtDyxz9yIAM2thZj3dfX7iQhNJT5Glzpva/ZORjd+n3fIMWJ6kgAryggm1RSSuok2gvwf6RbzeUcE6kQatwlLn8oeg4BPITGICy86BnNHJu75IPRVtAjV3L30GiruXmFmsDZBE6p1KRxFaTpDAJryS3ABFJO6iTYKfm9nPCEqdAFcAnycmJJH0oWedIg1XtAn0MmAqcAtBa9w3gYmJCkok1WnQdxGJdiCFjcAFCY5FJOUpcYpIqSoTqJndAjzk7l9Xsv0U4BB3fzkRwYmkCiVOESmvuhJoHvCSme0CFgOFBGPhHgnkAm8A/5PIAEWSTdOMiUhFqkyg7v4C8IKZHQkcT9AfdCvwODDR3XcmPkSRuqfh90SkOtE+A/0E+CSeFzazxsBCYJ27jzCzVsBsoAuwGjjP3b+J5zVFoqHh90QkGsnsy3k1wZRoWeHrScCb7j7FzCaFr29IVnDS8KhLiojURFISqJl1BIYDdwHXhatHAieFyzOBeSiBSh1QAyERiUW0s7Ec7+7vVbeuBu4HfgFkRqxr5+75AO6eb2ZtK4llImEf1M6d9R+cxE6JU0RqI9oS6P9x4Li3Fa2rlpmNADa6+yIzO6mmx7v7NGAaQP/+/b2a3UUqpJa1IlJb1fUDHQQMBtqY2XURm7II5gWNxfHAWWb2A4IuMVlm9jiwwczah6XP9sDGGM8vUik95xSReGlUzfZmQAuCRJsZ8bMViGl6B3e/0d07unsXgtGN/u7uFwEvAuPC3cYBL8RyfpHKlJY656/6muO6tlLyFJFaqa4f6NvA22Y2w92/SHAsU4CnzOwSYA0wJsHXkwZCpU4RSYRon4EeZGbTCPpolh3j7qfU5uLuPo+gtS3u/hUwtDbnE4mkRkIikkjRJtCngYeBR4F9iQtHJD7USEhEEi3aBFrs7r+vfjeROrRwOuTNOWD1hqJddNu0nb80g66tm9OuWUYwsfXyug+RgrxgQm0RqXeqa0RU6iUzu8LM2ptZq9KfhEYmUp28OUGCCm0o2sWy/C2s2rQdCJNnZkayogtk50BOTO3tRCTFRVsCLW0de33EOge6xTcckRrKzuGJHr8PnnWu3/9Z50BV2YpIAkU7mHzXRAciEosNRbv0rFNEkiLaofwOIRiztrO7TwynNztaE2lLsjwxfw198rdQtKsYUNcUEal70VbhTgcWEYxKBLCWoGWuEqjUqciuKX9pVkxmRhP+Z7iSp4jUvWgT6BHufr6ZXQjg7jvNzBIYl8gByndN6bo7aCTUU8lTRJIg2gS6x8wOJmg4hJkdAexOWFQi5UQmz7Lq2ulJbmErIg1atAn0duA1oJOZzSIYEH58ooISgW+rawENwyciKSfaVrh/M7PFwEDAgKvdfVNCI5MGrXx1rVrYikiqibYV7jkEs6a8Er4+1MzOdvfnExmcNDwa+F1E0kXUVbju/lzpC3ffbGa3A88nJCppcDTwu4ikm2gTaEVD/kV7rEiVNPC7iKSjaJPgQjP7LfAgQUvcqwj6hYrETNW1IpLOok2gVwG3ArPD13OBWxISkdR7qq4Vkfqg2gRqZo2BF9x9WB3EI/WYEqeI1CfVJlB332dmO8yspbtvqYugpP7Rc04RqW+ircLdBeSZ2d+A7aUr3f1nCYlK6pUKRxESEUlz0SbQV8IfkaipkZCI1GfRjkQ0MxwLt7O7r0xwTJJMC6dD3pxan2ZD0S66bdrOtUBmVhNatziIdsszYHntQyxTkAfZOXE8oYhI9Crq33kAMzsTWEIwHi5mlmtmLyYwLkmWvDlBYqqFDUW7WLUpqOnv2ro5Pdu3pF1mAgZ+z86BnNHxP6+ISBSircKdDBwLzANw9yVm1jVBMUmyZefAhJrX2JdV2a7/tsp2oKpsRaSeijaBFrv7lnJTgHoC4pE0pVa2ItLQRJtAl5rZD4HGZnYk8DPg/cSFJelA042JSENWk5GIbiaYRPsJ4HXgV4kKSlJbRQMiqNQpIg1NlQnUzDKAy4DvAXnAIHcvrovAJHW9sGQdy/O3KmmKSINWXQl0JrAXeBc4A/gv4JoExyQpKLK6dnn+Vnq0z2L2TwYlOSoRkeSpLoH2cPccADP7I/CvxIckqaSi6toe7bMYmdshyZGJiCRXdQl0b+mCuxeXa4Ur9ZgGfhcRqVp1CbSPmW0Nlw04OHxtgLt7VkKjk6TYULRLXVJERKpRZQJ198Z1FYikhshRhNQlRUSkctF2Y5F6rrTK9lolTxGRqNR5AjWzTsCfgWygBJjm7g+YWStgNtAFWA2c5+7f1HV8DVHkKEKlA79rCD4RkaolowRaDPw/d19sZpnAonCe0fHAm+4+xcwmAZOAG5IQX4NR0XRjPZe3THJUIiLpoc4TqLvnA/nhcpGZfQx0AEYCJ4W7zSQYuF4JNAGqbGEbz+nGRETqsaQ+AzWzLkBfYD7QLkyuuHu+mbWt5JiJwESAzp1VzVhTGvRdRCQ+kpZAzawF8AxwjbtvjbaPqbtPA6YB9O/fXzPCRKmi6lolThGR2CUlgZpZU4LkOcvdnw1XbzCz9mHpsz2wMRmx1TcaEEFEJDGS0QrXgD8CH7v7byM2vQiMA6aEv1+o69hS2sLpkDcn6t03FO1i07bddNtVzLV827q2XbOM4DlnZc86C/KCCbVFRKRKySiBHg9cDOSZ2ZJw3U0EifMpM7sEWAOMSUJsqStvTlTJrTRxFu0KJs3JzAgTZ2ZGdNfJzoGc0bWNVkSk3ktGK9x/EAwFWJGhdRlL2snOgQmvVLpZDYREROqORiKqJyKTpxoIiYgknhJomlPrWhGR5FACTWOqshURSR4l0DSkUqeISPIpgaaRDUW7+NkfPlCfThGRFKAEmiZK5+mcv+drJU4RkRSgBJriNE+niEhqUgJNYZqnU0QkdSmBpiDN0ykikvqUQFOI5ukUEUkfSqApQn06RUTSixJokqlPp4hIelICTSKVOkVE0pcSaBKo1Ckikv6UQOuYSp0iIvWDEmgdimrKsYXTg8mzy4tiMm0REak7SqB1oEZVtnlzKk6W2TmQMzrBkYqISLSUQBOoyn6dVcnOgQmv1EGEIiISKyXQBIg5cYqISNpQAo0zNRISEWkYlEDjKKpGQiIiUi8ogdZSaXUtoH6dIiINiBJoLb2wZB3L87fSo32WqmxFRBoQJdAYlZY8S5Pn7J8MSnZIIiJSh5RAY1BRQyEREWlYlEBrQGPYiohIKSXQalTUSEjPOkVERAm0CuWrapU4RUSklBJoJdSnU0REqqIEWo6ec4qISDSUQCNoGD4REYmWEigqdYqISM2lXAI1s9OBB4DGwKPuPiWR11OpU0REYpFSCdTMGgMPAqcCa4EFZvaiuy+P97VU6hQRkdpIqQQKHAt86u6fA5jZX4CRQNwT6KFv38q121aSmdWE1i0Oot3yjARcJQYFecGE2iIiktJSLYF2AL6MeL0WOC5yBzObCEwE6Nw59hJjqxbNyG6UQZfDm8d8joTIzoGc0cmOQkREqpFqCdQqWOf7vXCfBkwD6N+/v1ewf1QGXvFIrIeKiIjQKNkBlLMW6BTxuiOwPkmxiIiIVCrVEugC4Egz62pmzYALgBeTHJOIiMgBUqoK192LzeynwOsE3Vj+5O7LkhyWiIjIAVIqgQK4+1+BvyY7DhERkaqkWhWuiIhIWlACFRERiYESqIiISAyUQEVERGJg7jGPRZB0ZlYIfFGLU7QGNsUpnPpI96dquj/V0z2qWrLuz3fdvU0SrluvpHUCrS0zW+ju/ZMdR6rS/ama7k/1dI+qpvuT3lSFKyIiEgMlUBERkRg09AQ6LdkBpDjdn6rp/lRP96hquj9prEE/AxUREYlVQy+BioiIxEQJVEREJAZpm0DN7HQzW2lmn5rZpIj1fczsAzPLM7OXzCyrgmO7mNlOM/u3mX1sZv8ys3F1+w4Sz8z+ZGYbzWxpufXR3iM3szsj1rU2s71m9ru6iL8umFknM3sr/BwsM7OrI7bNNrMl4c9qM1tSwfFdyt/f+qSK79lkM1sXcX9+UMnxPc3s72b2HzP7xMxuNTOr5po3xft9JFoV37U7zeyj8B7NNbPvVHBsvf4M1WvunnY/BFOdfQZ0A5oBHwI9wm0LgCHh8o+AOys4vguwNOJ1N2AJMCHZ7y3O9+lEoF/ke63hPfoM+HfEusvD+/S7GsTQJNn3oZr42gP9wuVM4D+ln6Vy+/0GuK26z1J9+qnmezYZ+Hk1xx8cHn9a+PoQ4FXgymqO25bs9x7Dvarsu5YVsfwz4OGG9Bmq7z/pWgI9FvjU3T939z3AX4CR4bajgXfC5b8Bo6o7mbt/DlxH8AHHzJqHf1EuCEupI8P1jc3s3rDk9pGZXRXn9xVX7v4O8HUFm6K9RzuBj82stKP3+cBTpRvN7Ewzmx/eozfMrF24frKZTTOzucCf4/FeEsXd8919cbhcBHwMdIjcJywxnQc8WdW5zGx8ZOnczF42s5PC5W1mdpeZfWhm/yy9Vymuqu9ZNH4IvOfucwHcfQfwU2ASgJm1MLPpEd+nUWY2BTg4LLHNiu/bSZzKvmvuvjXiZXOgylabYWn0XTNbHP4MDtefZGbzzGyOma0ws1nVleQl8dI1gXYAvox4vZZv/9NbCpwVLo8BOkV5zsVA93D5ZuDv7j4AOBm4x8yaAxOBrkBfd+8NpM0XvJya3KO/ABeYWUdgH7A+Yts/gIHu3jfc7xcR244BRrr7D+MWdYKZWRegLzC/3KYTgA3u/kktTt8c+Ke79yH44+XSWpyrrlT1PQP4aZj4/mRmh1VwfE9gUeQKd/8MaBE+NrgV2OLuOeH36e/uPgnY6e657j42ru8mScI/nL4ExgK3VbP7RuBUd+9H8Afr1IhtfYFrgB4EtQLHxz9aqYl0TaAV/eVV+pfdj4ArzWwRQZXcnhjOeRowKXzmNQ/IADoDwwiqYIoB3L2i0l06qMk9eg04FbgQmF1uW0fgdTPLA64n+A+z1IvuvjN+ISeWmbUAngGuKVdqgOC9V1n6jMIe4OVweRFBtV2qq+p79nvgCCAXyCeo4q7o+MpKXE7wfXqwbIX7N7EGmsrc/WZ370TwB/dPq9m9KfBI+J16miBZlvqXu6919xKCRyldEhCu1ECTZAcQo7XsX2rqSFgycvcVBAkQMzsKGB7lOfsSVN9B8MUf5e4rI3cIq0zSvuNsTe6Ru+8JE+3/I0iQZ0Zs/j/gt+7+YlhVOTli2/b4Rp04ZtaUIHnOcvdny21rApxLUKKuTjH7/1GaEbG8191LPzv7SI/vXlXfsw2lK83sEb794yDSMoJng0Ts243gGWdRffk+1cATwCvA7VXscy2wAehD8FnaFbFtd8RyunyG6rV0LYEuAI40s65m1gy4AHgRwMzahr8bAbcAD1d3srDq7l6ChADwOnBV6TMGM+sbrp8LXBb+p4qZtYrXG6pLMdyj3wA3uPtX5da3BNaFy2nZijn8N/4j8LG7/7aCXYYBK9x9bRSnWw3kmlkjM+tE8AwxnVX1PWsfsd85BI8FypsF/LeZDQuPOZigSvLucPtcIkpkEdXAe8M/atKemR0Z8fIsYEU1h7QE8sNS5sUEDbkkRaVlAg2rUH9KkOg+Bp5y92Xh5gvN7D8EH9T1wPRKTnNE2PjlY4KGMf/n7qX73klQlfJR2Ly8tCvHo8CacP2HBI0kUpaZPQl8ABxtZmvN7JJwU7T3CAB3X+buMyvYNBl42szeJX2nrDqe4D+qU6ziLhkXUHX1bRO+LRm8B6wC8gj+IFucgHjrTDXfs7tLG/8QtBO4toLjdxI0OrrFzFYS3JcFQGlDq18Bh5nZ0vD7dHK4fhrBdyxt2hhU8V2bEr6/jwhqfa6u4PDIz9BDwDgz+ydwFGlUk9MQaSg/kVoIW2iPdffzkh2LpCd9htKX6tBFYmRmdxCUsMYnORRJU/oMpTeVQEVERGKQls9ARUREkk0JVEREJAZKoCIiIjFQAhWpATPbF3Z1WRaOa3td2J+2qmO6mFlKd3kSkZpTAhWpmdJxWnsSDHH4A6oeWQaCIdeUQEXqGbXCFakBM9vm7i0iXncjGBygNfBd4DGCgeMBfuru74ed4v+LYJCFmQSj8UwBTgIOAh509z/U2ZsQkbhQAhWpgfIJNFz3DcFMPkVAibvvCodwe9Ld+4fjBP/c3UeE+08E2rr7r8zsIIIRjMa4+6q6fC8iUjsaSEGk9kpnLWkK/M7McgkG+z6qkv1PA3qb2ejwdUvgSIISqoikCSVQkVoIq3D3EczjeDuVz6Sx32HAVe7+ep0EKSIJoUZEIjEyszYEM9n8LpyqrLKZNIoI5l0t9TpweemMI2Z2VDhhu4ikEZVARWrm4HCi9aYE838+BpROg/YQ8IyZjQHe4tuZND4CisMZR2YADxC0zF0cTqdWCJxdN+GLSLyoEZGIiEgMVIUrIiISAyVQERGRGCiBioiIxEAJVEREJAZKoCIiIjFQAhUREYmBEqiIiEgM/j8CD3jz8CEJcgAAAABJRU5ErkJggg==", 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", + "image/png": 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", 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", + "image/png": 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", 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", 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", 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" ] @@ -11807,7 +11861,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **55-59** population up to 15 Dec 2021" + " ## COVID vaccination rollout among **55-59** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -11838,7 +11892,7 @@ }, { "data": { - "image/png": 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", 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", 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", 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", 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", 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", 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", 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", + "image/png": 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", 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", 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", 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", 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" ] @@ -12044,7 +12098,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **50-54** population up to 15 Dec 2021" + " ## COVID vaccination rollout among **50-54** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -12075,7 +12129,7 @@ }, { "data": { - "image/png": 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5Pye1P4+OP/74z4CzGjqOupLI6tBDgbFAb+ArINfMJsX7eHe/F7gXIDs7O6mL3CLSRITJL2NrQbmSX/+Gjk0SIpHVoaOBte6+BcDMngSGA0Vm1jUsBXYFajXQUUSkThTMgWenlSS/dw89VSW/FJDIJLgeGGpmbQiqQ0cBBcDXwGTglvD3ggTGICISl6K8h8kArtl3EZlnTWOqkl9KSGSbYL6ZzQPeAfYD/ySo3mwHPGFmFxEkyvGJikFEpCLRa/6N2vUcU7cVsKT4GDLPmqbSXwpJaO9Qd58JzCyzeQ9BqVBEpF5FJ74+63MPrvS+N1jp3TLHKwGmGM0YIyIp4dH89cyYHyS7GRlLDi50G7XSe46mPEs5SoIi0uRFJ8Dfn53J+avuDtb602TXKU9JUESatOiFbnt3akvGqlawuTCY8FoJMOUpCYpIkxLd7geUXuev/Yjgd5fMYMUHSXlKgiLSpCxYtpFVm7ZzWcfXOWH3y/RvEVSDqupTYlESFJEmIVIC7LfpSa5v+Sb9t4XJT+v8SSWUBEWk0Yt0fJnQbBEzW9wPe1Hyk7goCYpIoxadAEva/lT1KXFSEhSRRilS/dlnfS6Pt8wrWeVdCVCqQ0lQRBqVSPLLX7u1dOlP1Z9SA0qCItJoRMb8XdEsj/YdDk53ptKf1JSSoIg0GjvzZh8s+UVNd6YEKDWlJCgiSe/R/PXszJvN1G2zgg0q+UkdURIUkaSVn3s77d6fT59v9pd0fMnvf70mupY6E3cSNLNDge8QLJC7zt2LExaViKS0siW/la0yKWqXTcbwSUqAUqcqTYJm1hH4BTABaAlsAVoBGWa2BLjb3V9OeJQikhIiyW/Aly+WLvmN/1UDRyZNVVUlwXnA/wEnuvtX0TvM7HjgAjPr4+73Jyg+EUkRkZ6fN7e4H9KgKF0lP0m8SpOgu59ayb6lwNI6j0hEUkp06e/8FgcHvGco+Uk9iKtN0MwMmAj0cfcbzawn0MXd30podCLSJEUvd1Sy1FFU6U89P6W+xNsx5m6gGDgFuBHYAfwVGJyguESkCYqe7QVgRsYSpkbN96nSn9S3eJNgjrsfZ2b/BHD3L82sZQLjEpEmpGzyy+mdzvT0PHJWatyfNKx4k+A+M2sGOICZdSYoGYqIVCqyygMEJb+xzfLIaNkKVr4eHKAEKA0o3iQ4C5gPHGZmvwPGAdcmLCoRaTIWLNvIhGaLmJaxnIytBcHG9iM04bUkhbiSoLs/YmZLgVGAAT9y99UJjUxEGqXoTi8A/TY9GSx0uxUlPkk68fYO/RMw193vSnA8ItKIRS9wO6lt0Hm8P1rpQZJXvNWh7wDXmtlRBNWic929IHFhiUhjEnONv70EJT+t9CBJLN7q0AeBB80sHTgH+IOZ9XT3IxManYgkvejS3/Ud3tIaf9KoVHcVie8CfYFewKo6j0ZEGpXoBFiq9KeSnzQS8bYJ/gH4MfAh8ARwU9m5REUkNUR3fClV/Qkq/UmjE29JcC0wzN0/T2QwIpLcosf85fROJ6d3OtP2LA96fioBSiNU1VJKfd39PeAtoGc4Z2gJd38nkcGJSPKIToBzj3+PnJ3/CHZsfT+oAlUClEaoqpLgdGAqcHuMfU4wl6iINHH5ubfTpzCXx1tC705tyVgZdg4/fAR0yQzaAEUaoaqWUpoa3vyBu38Tvc/MWiUsKhFJCvm5t9Pu/fnk7C08uMpD+1bBjC/q/CJNQLxtgnnAcXFsK8XMvgXcBxxLUHL8KbAGmEvQw3QdcK67fxlvwCKSWNEdX67YmEsP+5iVh2Sy88iztcK7NDlVtQl2AboBrc1sEMGUaQAdgDZxnP9PwPPuPi5cdaINMANY5O63mNnVwNXAVTX9A0Sk9squ73dFszzat2pOr2br2XloP/pfvqiBIxRJjKpKgt8HpgDdgf+K2r6DIJlVyMw6AN8LH4+77wX2mtlY4KTwsAeBxSgJijSIStf36zoCGERbtfdJE1ZVm2Bkpphz3P2v1Tx3H2ALMMfMBgJLgX8HMtx9U3j+TWZ2WKwHm9lUgk459OzZM9YhIlILZYc7aH0/SUXxTpv2VzM7A+gPtIrafmMV5z4OuMzd88NJuK+ONzB3vxe4FyA7O9vjfZyIxKfUEkda309SVLwzxtxD0J53MkFHl3EEYwcrswHY4O754f15BEmwyMy6hqXArsBnNYpcRGokUgVaaokjre8nKSre3qHD3X2Amb3r7v9pZrcDT1b2AHffbGafmNnR7r6GYC3CVeHPZOCW8PeCWsQvInGIJL5Ru55jwJcvcgUwNC1cElQlP0lh8SbB3eHvXWb2HeALoHccj7sMeCTsGfoRcCGQBjxhZhcB64Hx1QtZRKorUvKbyr0l4/001k8k/iT4bDjm71aCtQWdoFq0Uu6+DMiOsWtUnM8rIrWUn3s7V2zMLVXyy1DiEwHi7xhzU3jzr2b2LNDK3bclLiwRqbWCORTlPUzO1oKDs70Mn6SSn0iUqgbL/7iSfbh7pe2CItIAwuSXsbWADGBJ8TFY5njN9iISQ1UlwTMr2edU0TlGROpZwRx4dlpJ8nv30FNpN/xizs/RWFuRWKoaLK96E5HGIKr0B3DNvovIPGsaU5X8RCoV7zjB62Ntr2KwvIgkWoyqz3cPPZVMlf5E4hJv79Cvo263AsYAq+s+HBGpUsEcKJwX3P74dTKAt+nHPzuOpt3wi1X6E6mGeHuHllpU18xuA55OSEQiUrGwzQ9gZctMaJnJvL3DWNX1x8z9+bCGjU2kEYq3JFhWG4IJskWkPkRKfx8H83tes+8iHvtmFDm90wEYm9WtIaMTabTibRMsJOgNCtAM6AyoPVCkPkSV/pYUH8OCA8P5qOd4fp/VTe1+IrUUb0lwTNTt/UCRu+9PQDwiEi0qAV6z7yIeOzCK35+dyc1KfiJ1It42wY/N7FCgR/iYjHCw/DsJjU4kVcWo/lTpT6TuxVsdehPBCvEfcrBa1IFTEhOWSAoq0+sTDlZ/Zp41TaU/kQSItzr0XOAId9+byGBEUllR3sO0+3I161r0gZaZPPz1kJLqT5X+RBIj3iS4AvgWWgBXpG6Fpb+iHd/Q+otVFPrh3NHl1mDft1H1p0iCxZsEbwb+aWYrgD2Rje5+VkKiEkkFUZ1e1hYfAxyOZY5n7niN9xOpL/EmwQeBPwCFQHHiwhFJERX0+lSpT6R+xZsEP3f3WQmNRCQVxBr0rgQo0mDiTYJLzexmgqnSoqtDNURCJB5lkt9KdXwRSQrxJsFB4e+hUds0REKkKmWSX8mML13Hq+OLSBKId7D8yYkORKTJqWC6s7FZ3TTmTyRJaD1BkboUY8C7pjsTSV5aT1CkrkSV/IrSs/lc7X4iSU/rCYrUhagEeG/Hy/n9p0HzeU7vdLX7iSQxrScoUltlxvx91OaH5PQO1vhT8hNJblpPUKSmYoz500TXIo2L1hMUqY4YHV8iY/4yz5qmkp9IIxNvEuwKrHT3HQBm1s7M+rt7fuJCE0lChfNgcyF0yYTDR5Df7hTOW9qXnN7pKgGKNELxJsH/AY6Lur8rxjaRpissAe7duJz303px495rAchfuhUI2v9EpPGJNwmau0faBHH3YjOraacakcajTLvfO8XHsODAEPh2sDund7o6wIg0YvEmso/M7HKC0h/AvwEfJSYkkSQSVn8WpWdzZ9FADXoXaWLiTYKXALOAawl6iS4CpiYqKJEGFykBbi6kqO2R5Hw6HUCD3kWamHgHy38G/CTBsYgkhzIzv9xZNBBQAhRpiipNgmZ2LXC3u2+tYP8pQBt3fzYRwYnUq4I5FOU9TMbWAqD0zC9KgCJNU1UlwULgGTP7BngH2EIwd+iRQBbwEvD7RAYokjBhlWfRjm/4fOce+u8tJINgxYd3Dz2VRZr5RaTJqzQJuvsCYIGZHQmcQDBecDvwMDDV3XdX9QRm1gwoADa6+xgzSwfmAr2AdcC57v5lbf4IkRoJhzys3dsdgJWtMnmj9cm0G34xU3N6qtFbJAXE2yb4PvB+DZ/j3wlWnOgQ3r8aWOTut5jZ1eH9q2p4bpGaKZgDH7/OO8XH8JO915VUd/Zv6LhEpF6lJfLkZtYdOAO4L2rzWODB8PaDwI8SGYNIKQVzKJo1qqTjy4IDw9XeJ5LCEj3g/U7gP4D2Udsy3H0TgLtvMrPDYj3QzKYSDsPo2VMfUFJLUZ1eotv9ModfrAQoksLiXUXiBHd/o6ptZfaPAT5z96VmdlJ1A3P3e4F7AbKzs72Kw0Uq9Gj+egYuup8eez5kiQfJL9LuJyKpLd6S4H9Tfp7QWNuinQCcZWY/JOhR2sHMHgaKzKxrWArsCnxW3aBF4vFo/np25s1mwJcv0sM+5pNDjuCjUY8q+YlIiarGCQ4DhgOdzWx61K4OBOsKVsjdrwGuCc9zEvBrd59kZrcCk4Fbwt8Lahq8SEXyc2+nT2EuQ9NWQ1ow6L3/8En0z1YCFJGDqioJtgTahcdFt+ttB8bV8DlvAZ4ws4uA9cD4Gp5HpJRH89ezYNlGAK7YmEs/+5ii9Gwyhk8iI/vCBo5ORJJRVeMEXwFeMbMH3P3jmj6Juy8GFoe3vwBG1fRcIrE8mr+eGfMLAZiRsYShaauDBHj5ogaOTESSWbxtgoeY2b0EA9xLHuPupyQiKJGqRJf6APLXBjP7zT3+PXJWzgIgY/ikBolNRBqPeJNgLnAPwXi/A4kLR6Rq0aW+nN7pQFD6G9ssj4yVwbyfjLkTVAUqIlWINwnud/f/qfowkcSKToAlg9wL5sCzQemPw0dA5jglQBGJS7xJ8Bkz+zdgPrAnsrGi1SVE6lqk+jNS7VlqlpfCecFvlf5EpJriTYKTw99XRm1zoE/dhiNSWtnkl9M7nenpeeSsuhtWhQdtLgxKgEqAIlJN8U6g3TvRgYhERHd6iU5+Y7O6cX6zRfDsjcGBh48IfnfJDKpARUSqKd5p09oA04Ge7j41XFrpaC2mK3UpVqmvJPmVtP1NCw5W1aeI1IF4q0PnAEsJZo8B2EDQY1RJUOrMgmUbWbVpe+nEB0HymzMPPn49uK8EKCJ1JN4keIS7n2dmEwDcfbeZWQLjkhQRXfW5atN2+nXtwNyfDzt4QHTpTz0/RaSOxZsE95pZa4LOMJjZEUT1EhWpibLj/fp17cDYrG4HD1D1p4gkWLxJcCbwPNDDzB4hWCFiSqKCkqat0uEOECS/QlV/ikjixds79EUzewcYChjw7+7+eUIjkyYnVseXkh6fc+YdPDCS/FT9KSIJFm/v0LOBf7j738L73zKzH7n7U4kMTpqOslWfJcmv8Lelk17kt5KfiNSDuKtD3X1+5I67f2VmM4GnEhKVNCkVT3U2LThASU9EGki8STCtFo+VFBadAOce/97BmV7U3iciSSDeRFZgZv8F3EXQQ/QygnGDIjGVbf8LljiKmulFpT8RSQLxJsHLgOuAueH9hcC1CYlIGr2y7X/T0/MOJkCV/EQkiVSZBM2sGbDA3UfXQzzSyJVr/4ue61MJUESSTJVJ0N0PmNkuM+vo7tvqIyhpnGK2/6ntT0SSWLzVod8AhWb2IvB1ZKO7X56QqKTRyc+9nT6FuTzeEnp3antwhXe1/YlIEos3Cf4t/BEp5dH89ezMm83UbbMgDYrSs8lo3wraK/mJSPKLd8aYB8O5Q3u6+5oExySNRKT0NzRtdXC///XkjP9VA0clIhK/eGeMORO4DWgJ9DazLOBGdz8rgbFJksrPvZ12788nZ2/hwdLf8EnkqNQnIo1MvNWhNwBDgMUA7r7MzLTafArKz729ZLjDypaZ7DzybJX+RKTRijcJ7nf3bWWWEPQExCNJKjL4/YqNuZCmqk8RaRriTYIrzOx8oJmZHQlcDuQlLixJFpHk12d9Llc0yyOz2XqKDs1WAhSRJqE6M8b8hmAh3UeBF4DfJiooaXhlk9/QFkHnF3qOoG3muIYNTkSkjlSaBM2sFXAJ8F2gEBjm7vvrIzCpf5HEB5C/disTmi3i5hb3Bzs13k9EmqCqSoIPAvuA14AfAMcA0xIckzSAsvN9zshYwtRtYQLUbC8i0kRVlQT7uXsmgJndD7yV+JCkPsVc7WHnP2CTpjsTkaavqiS4L3LD3feX6R0qjVjZ5DcjYwljm+VpujMRSSlVJcGBZrY9vG1A6/C+Ae7uHRIandS5ssnv4FJHs4IDlPxEJIVUmgTdvVl9BSKJV7bdb2xWNy11JCIpLd4hEtVmZj2A/wO6AMXAve7+JzNLJ1ictxewDjjX3b9MVBwSiLnOX+FvtdSRiKS0tASeez/wK3c/BhgK/MLM+gFXA4vc/UhgUXhfEij2QrfTggR4+AglQBFJWQkrCbr7JmBTeHuHma0GugFjgZPCwx4kmI/0qkTFkcpi9vzUQrciIiUSlgSjmVkvYBCQD2SECRJ332Rmh1XwmKnAVICePXvWR5hNQtkB7xDd+SVs+1PnFxERoB6SoJm1A/4KTHP37fEOs3D3e4F7AbKzszVZdxzKdnwpSX47/wErVfoTESkroUnQzFoQJMBH3P3JcHORmXUNS4Fdgc8SGUOqiN3xZd7B5KfSn4hIOYnsHWrA/cBqd/+vqF1PA5OBW8LfCxIVQ6qIToDl2v2U/EREKpTIkuAJwAVAoZktC7fNIEh+T5jZRcB6YHwCY2jyyiVAtfuJiMQtkb1DXyeYWSaWUYl63lQR3fNzQrNFTMtYfnDKM7X7iYjEpV56h0rdiTXt2bQ9y8n4+n2V/kREqklJsJFZsGwjqzZtPzjtWU5PmNMK2mfChX9r6PBERBqVRM4YI3Xs0fz15K/dSr+uHZj782FBD9A5Z8DmwoYOTUSkUVJJsBEoWwU6NqsbFMwJpj6Dg9WgIiJSLUqCSa7sAPjp6Xma+kxEpI4oCSaxcsMfomd+UScYEZFaUxJMUhr/JyKSeEqCSajCBKiqTxGROqUkmEQ0AF5EpH4pCSaJ6NLfjIwlTN12P2xF1Z8iIgmkJJgEIgmwpPS3VaU/EZH6oCTYgMpWf97cQqU/EZH6pCTYQGJWf4JKfyIi9UhJsAE8mr+ewqfv5PGWefTu1FbVnyIiDURJsJ5Eqj5H7XqOAV++yPktVgc72o8IflT9KSJS75QEE6xsu9/UFvdDGhSlZ5MxfJISn4hIA1ISTKDK2v0ylPxERBqckmCClJ/1ZVawQ+1+IiJJQ0mwjkSqPSM064uISPJTEqylsmv95fROBzTri4hIY6AkWAPRpb7o5Dc9PS9Y7ghgk9b7ExFJdkqC1VR2kdtSyS96rT+V/kREkp6SYDVFSoC/PzuT85stgsJ5WuhWRKSRUhKMU6QKdNWm7eT0Tg8S4LPTgp1KfiIijZKSYBXKdnyZkbGEsXvy4Fn1+BQRaeyUBCsQq9fn9PS8g+P9VPoTEWn0lARjKNv5ZWxWt7D688bgAJX+RESaBCXBMsqt8NCyFawCPtaQBxGRpkZJMEokAd7cIpzjs/2IgztV/Ski0uSkfBKMHvjeZ33uwQSoEp+ISJOX0kkwUvK7olke7Vs1p3+LoB1QCVBEJDWkdBLcmTf7YMmv6whAVZ4iIqkkJZNgfu7ttHt/PlP3quQnIpLKGiQJmtnpwJ+AZsB97n5Lwp+0YA4UzqNoxzfkbA0Guq9smcnOI88mRwlQRCQl1XsSNLNmwF3AqcAG4G0ze9rdVyXsSQvmlExxtrb4GNZyDJY5npzxv0rYU4qISPJriJLgEOADd/8IwMweB8YSjMarU0vuvpj2X62mf1jtec2+i/io5/hg8HtOz7p+OhERaWQaIgl2Az6Jur8ByCl7kJlNBaYC9OxZu4S1smUmb7Q+mczhF3Ozkp+IiIQaIglajG1eboP7vcC9ANnZ2eX2x2Pov80uud2/JicQEZEmLa0BnnMD0CPqfnfg0waIQ0REUlxDJMG3gSPNrLeZtQR+AjzdAHGIiEiKq/fqUHffb2a/BF4gGCLxF3dfWd9xiIiINMg4QXd/DniuIZ5bREQkoiGqQ0VERJKCkqCIiKQsJUEREUlZSoIiIpKyzL1G49DrlZltAT6u4cM7AZ/XYTiJoBjrhmKsG4qxbiRDjIe7e+cGjiGpNYokWBtmVuDu2Q0dR2UUY91QjHVDMdaNxhCjqDpURERSmJKgiIikrFRIgvc2dABxUIx1QzHWDcVYNxpDjCmvybcJioiIVCQVSoIiIiIxKQmKiEjKSvokaGanm9kaM/vAzK6O2j7QzN40s0Ize8bMOsR4bC8z221m/zSz1Wb2lplNTlCcPczs5fB5VprZv0ftyzKzJWa2zMwKzGxIBbGuSERs4fn/YmaflX2OaryObmY3RW3rZGb7zOzPdRRfRdc53tcuofFFnbey6zw3jHOZma0zs2UVxJqw6xw+R8xrHe67LHydV5rZHys5xxVm9o2ZdUxgnBVd8xvMbGPUa/nDCh7f38z+YWb/MrP3zew6M4u1aHf0Y2bEGVuF1znqmF+H77tOMfZF3pOXRW37s5lNief5pR65e9L+ECy19CHQB2gJLAf6hfveBkaGt38K3BTj8b2AFVH3+wDLgAsTEGtX4LjwdnvgX1GxLgR+EN7+IbC4qlgTEN/3gOPKPkc1XscPgX9Gbbs0fC3/XI0YmtfgOsf72tU6vtpe5zLH3Q5cX9/XuYprfTLwEnBIeP+wSs7xFvAaMCVBMVZ2zW8Afl3F41uHjz8tvN8G+Dvwiyoet7MurjPBwuAvEEzi0amC61wEfAC0DLf9OVGvp35q/pPsJcEhwAfu/pG77wUeB8aG+44GXg1vvwicU9XJ3P0jYDpwOYCZtQ2/Nb8dlhbHhtubmdltYeno3ehvc5Wce5O7vxPe3gGsBrpFdgORElZH4NPKzhV+i3zNzN4Jf4aH208ys8VmNs/M3jOzR6r65hsV36vA1hi74n0ddwOrzSwy+Pc84ImomM80s/zwdXzJzDLC7TeY2b1mthD4vwrOXdl1jve1q3Z8ZpYWliA6h8ekhaWSct/sI6q4zpHnMuBc4LGKzhMeNyW6pGpmz5rZSeHtnWb2OzNbHpaEMyo7V5kYK7rWlwK3uPue8LjPKojrCKAdcC0wIc54LwpLZIvNbHYcJfDKrnk8zgfecPeF4d+yC/glcHUYTzszmxP1P3yOmd0CtA5Ll49UdvI4rvMdwH8QvD8rsgVYBJSrfbKDNRzvmtl8MzvUzI4xs7eijullZu9W/VJIbSR7EuwGfBJ1fwMH34grgLPC2+MJvpnF4x2gb3j7N8A/3H0wwbfkW82sLTAV6A0McvcBQKX/MGWZWS9gEJAfbpoWnvsT4DbgmipO8RlwqrsfR/BhPitq36DwfP0IvkWfUJ3YYqjO6/g48BMz6w4coHRCeh0Y6u6DwuP+I2rf8cBYdz+/gvNWdp2nEf9rV6343L0YeBiYGB4zGlju7nFNdRXjOkecCBS5+/vxnKcCbYEl7j6Q4EvKxbU4V8RRwInhl4FXzGxwBcdNIEjgrwFHm9lhlZ3UzL4DXAcMBU7l4P9XZSq75gC/DBPEX8zs0BiP7w8sjd7g7h8C7Syo0r8O2ObumeH/8D/c/Wpgt7tnufvE8qes8O/rRdR1NrOzgI3uvjyOh98C/MrMmpXZ/n/AVWFshcBMd18NtDSzPuExpb7ISWIkexKMVcqJfPP6KfALM1tKUF2xtwbnPA242oK2m8VAK6AnwYfhPe6+H8DdY32rjn1ys3bAX4Fp7r493HwpcIW79wCuAO6v4jQtgNlmVgjkEiS8iLfcfUP4Ab6MoNqlNqrzOj5P8CE3AZhbZl934IUw5isJPqQinnb33ZWct7LrXJ3Xribx/QX4f+HtnwJzKjn/wYBjX+eISBKpjb3As+HtpdT+OkOwiPahBMnqSuCJCmoSfgI8Hr7HniT4clSZIcAr7r7V3fcRvGerUtk1/x/gCCAL2ERQtRzr8RWVwpzgf/iukg3uX8YRU/knKXOdzawNwZfn6+N5vLuvJahaLvkCaEE767fc/ZVw04MEVdgQJL1zw9vnUf59LHUs2ZPgBkqXTLoTfrt39/fc/TR3P57gA+fDOM85iKBqA4J/pHPCb4ZZ7t4z/DZW2T9YhcysBcE/zCPu/mTUrskEHyYQfECU69xRxhUE7QkDgWyCNpOIPVG3DxB8sNVYdV7HsNpqKfArgr8z2n8TtL9lAj8n+EIR8XUVYVR4nanGa1eT+Nz9E6DIzE4BcgjalSpVyXXGzJoDPya+D6/9lP4fjH7N9rl75D1Y6+sc2gA86YG3gGKCSZ5LmNkA4EjgRTNbR5AQI1WiFcUbV5V8jFgq+t8ucvcDYRKeTexrvpLgfyM69j4EbX47qOH/cJnzxbrORxDUEi0PX5/uwDtm1qWSU/0euIr4Pm/nAuea2VGA17I2QeKQ7EnwbeBIM+ttZi0J/iGfBohU0ZhZGkHbxT1VnSys1riN4AMRgobtyyLfhs1sULh9IXBJ+IGGmaXHcW4jKKWsdvf/KrP7U2BkePsUoKo3dkdgU/ghcAFBJ4KEqMHreDtBNc4XZbZ3BDaGt6vbA7fC60z1X7uaxHcfQbXoE+5+oLKTV3GdISiBvOfuG6qIE2AdkBW2Rfag6i9HtfUUwWtI+CHbkvKrHEwAbnD3XuHPd4BuZnZ4JfG+BYwM27WaE0f7PJX/b3eNOu5sgir7sh4BRpjZ6PAxrQmaDSI9XhcStBES7o9Uqe4Lk1ulKrrO7l7o7odFXh+CZH6cu2+u6Fzu/h6wChgT3t8GfGlmJ4aHXAC8Eu77kOBLz3WoFFgvkjoJhtWRvyRIVqsJPqRWhrsnmNm/gPcIPigrqsY6wsIhEgRVDf/t7pFjbyKoenzXgu7kkS729wHrw+3LiarKqMQJBG/mU6x81+6LgdvDc/2eoM2xrOYcLOXdDUw2syUE7ThVlaSqZGaPAW8StPFsMLOLwl3xvo4AuPtKd38wxq4bgFwze41qLh9TxXWO57WrbXxPE3QEiacqtLLrDMGHeWVVodHX+Q1gLUGb0G0E7dW1Vsm1/gvQJ3yvPw5MjiptRsc/v8y2+eH2mPG6+0aCa5NP0Pt0FbCtshiruOZ/jHRoIWirvyLG43cTdKS51szWhDG9TdADE+C3wKFmtiJ875wcbr+X4P+6qnb+qq5zdf2OoNQYMZmgrftdgmrfG6P2zQUmofbAeqFp05KEBT1TJ7r7uVUeLHXKgh6ld7j7iVUeXPvnapLX2czaufvOsCQ4H/iLu5dNpiJJpy7aGaSWzOxGgm+1Uxo4lJRjwSDtSznYQzSRz9WUr/MNYdVkK4KqyKcaNhyR+KgkKCIiKSup2wRFREQSSUlQRERSlpKgiIikLCVBkTLM7EDYJX6lBXN3Tg/HUVb2mF5mFs9QGhFJIkqCIuVF5pfsTzAN2w+BmVU8phfxjScVkSSi3qEiZZjZTndvF3W/D8FA7E7A4cBDBBNcA/zS3fPCiQ2OIRhM/iDB7CW3ACcBhwB3ufv/1tsfISJxURIUKaNsEgy3fUmwOsIOoNjdvzGzI4HH3D3bgiWFfu3uY8LjpxKs1/dbMzuEYLaV8eGEyiKSJDRYXiQ+kUmiWwB/NrMsgjkej6rg+NOAAWY2LrzfkWBiaiVBkSSiJChShbA69ADBOo8zObjCRxrwTUUPAy5z9xfqJUgRqRF1jBGphAWrzt9DsAyTU/EKHzsI1mOMeAG4NLJigZkdZcGCzSKSRFQSFCmvtQULLbcgWEPvISCynM7dwF/NbDzwMgdX+HgX2B+uWPAA8CeCHqPvhMvybAF+VD/hi0i81DFGRERSlqpDRUQkZSkJiohIylISFBGRlKUkKCIiKUtJUEREUpaSoIiIpCwlQRERSVn/H8uQmFmQk1aIAAAAAElFTkSuQmCC", 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", 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", 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", 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328hJPktIVO1JtBBtQcZI2BUWFhIaGoq7uztbt27l3LlzAPj5+VFc/NPlqRtvvJF//OMfVeMT0tPTyc7OJiMjA29vbxYuXMgjjzzCvn37at3fITY2luTkZE6dsiWQ77//PldffTVgGxuwb98+3nrrrapP5OPGjeO7776r2r6srIwTJ07U+rUUFxcTHh5OZWUlH374odOvgb+/Pz179uTTTz8FwGg0UlZWxqRJk1izZg0Wi4WcnBy2b9/OmDFj6jxOfV9bTXW9PrUpLCwkMjISgPfee6/OY9xwww288sorVc8dl6WE6AxCovoSMfBu3LyvaetQRCuYMWNGcW2VhfZMEgm7BQsWkJCQwKhRo/jwww+JjY0FoHv37kyYMIHBgwfz6KOPcsMNN3DHHXdw5ZVXEh8fz5w5cyguLubw4cOMGTOGYcOG8be//Y0nnngCgKVLlzJt2rRLBlt6enqyatUq5s6dS3x8PC4uLjzwwAOA7ZP9jBkz+M9//lN1e2VISAjvvvsut99+O0OGDGHcuHEcO3as1q/lL3/5C2PHjmXKlClVX4ez3n//fVasWMGQIUMYP348WVlZzJo1iyFDhjB06FCuu+46nnnmGcLCwuo8Rn1fW02LFy/mgQceqHWwZU3Lli1j7ty5TJw48aIxJzNnzmT9+vVVgy1XrFhBQkICQ4YMIS4ujtdff71Rr4EQ7V1uagm5qSVtHYYQAKiGytDt2ahRo3RCQkJbhyGEEK3qyI50Tuw5T8bRfwBg8JtHcE9fZv12RJOOp5Taq7WufYRzMxw8eDB56NChdQ5sFB3XwYMHg4cOHRpV2zqpSAghRDt3Ys95ctPsFQiLiWC3s0R7y23Non3o0IMt8/LyePfddy9aNmjQIEaPHl3n+IBhw4YxbNgwysrK+Pjjjy9ZP2rUKAYPHkxhYSHr16+/ZP2VV15JTEwMubm5bNiw4ZL1kyZNol+/fmRlZbFp06ZL1k+ePJlevXqRmprKli1bLlk/depUwsLCOHPmDNu3b79k/YwZMwgODub48ePs2rXrkvWzZs0iICCAxMREaqvWzJs3D29vbw4cOFDr2IEFCxbg7u7Ojz/+yJEjRy5Zv3jxYgC+//77S8ZouLm5sXDhQgC+/fZbzp69ePC0l5dX1ZiPzZs3k5aWdtF6f39/br31VgA2bdpEVlbWReu7d+9e1VPjiy++IC/v4gHHYWFhTJ06FYB///vfFBVd1OeFnj17cv311wOwZs2aSy6l9O3bt2osxwcffICjJ71DdHR0VdOrmt93IN978r3Xct9755JyyDpTWLXeR4cydsw4TCW+bNv2H3wK3udHy3X8+K7tTqTmfu8J0RxSkRBCiHYm60whJfnGqucBoV5cCHEnKaMIo9lKultPPrVKJ9fanDp1yn3s2LHR/fr1G3TFFVcM+stf/hLa8F6iOWSMhBBCtKDqvR6ayjGQMriXbS4gc3YOZRnplLm50K2ygtEFOZwccCO3vP1ck47fmcdInDt3zj01NdX9qquuKisoKHAZPnx43CeffHKqPUy33ZHJGAkhhLhMHL0emqL0gonc1BIqjRZMFitJGUUkZRRRlHke18pKDBYjBnMZqV6uuHpf0q9IYOtKedVVV5UBBAYGWvv371+ekpJiaOu4OrMOPUZCCCHao5Covsz/8/JG77f28a+oLLUQ5JJGSH4CYfnf4+KiIN9CSg8ry+YYGBg2EoDYoFiaN/duK/v0F73ITmrZ2QpD48r4n5VOTwZ2/PhxQ1JSkvfVV18t98q2IkkkhBCiDThu6XTILq7AmmfFvySVsenPkeFqIMVD46oUhCm2DXJjoE8kq6auasOoO47CwkKXW2+9tf/y5ctTq8/sKVqeJBJCCNEGHLd0Bvf0heIsfAoyocJMZOluyqf24LfhPbC4pRMfMrBqn5v63dSGETdSIyoHLc1oNKrp06f3nzt3bv6iRYsutFUcXYUkEkIIcZlUr0LkppXQzaOcyB0r8S1IwsNaQWmhG5k9XHhuQG9cKzOJCxooFYhGslqt3HbbbX2io6Mrli1bdunMi6LFyWBLIYS4TKoaSxVnEex2lh4nPsX39GE8rBUYXTxJifBl6xBP8AsjJiimY1Ug2olvvvnG99NPP+2+c+dOv9jY2LjY2Ni4NWvWBLR1XJ2ZVCSEEKIVVa9C5JzNx8+YzYjEZ7EaSygvcCc/WLHidh98AsM5XllITFCMVCGa4cYbbyzRWu9t6zi6EqlICCFEK6re3tqvLI3Q5K1gKqVceZLUrR+fD+nBGS+pQoiOSyoSQoguryWaSDnkJJ8lJKrvRcuqxkKcPoxnYCUlU3uwznQlSeG34t3nTeJBqhCiw5KKhBCiy2tOE6maQqL6MnDCNT8tKM7CnHkO39OHKQk2s3aIJ3eH92BjnzOUBP4fx/OPt8h5hWgrUpEQQgia3kSqLl8tfx3r5k2UhU8Ds8bazYXnbvcmzcuNuBD/qu1CkcsZomOTREIIIZqhZmMph7yjBgwh0yj1jMRgSmf1iFDOeJURHyK3dIrORRIJIYRoBsdgym4e5Zgd04tbTHiYTFQYoDAgjbyQw+QO7UM8HayplBBOaJNEQin1MHAvoIHDwBLAG1gDRAHJwDytdUFbxCeEEA1xVCIc3SlHHHibgsSDnA12w0OXY1SajBg3Hh/UG+LnwKglbR1yl1BWVqbGjh0bazKZlMViUTNnzix48cUXM9o6rs7ssicSSqlI4FdAnNa6XCn1MXAbEAds0VovV0o9DjwOPHa54xNCCGdUTyKix/SAA5DaXfP/bjcRW2mlQnnSp8/P4Mb72zrULsXT01Pv3LnzeEBAgNVoNKrRo0fHbNmypXDy5MmlbR1bZ9VWlzbcAC+lVCW2SkQG8HvgGvv694BtSCIhhGgnao6FyE0rociniJMpy2BTIb2zK6gMtRJbqVlt6C9ViDbi4uJCQECAFcBkMimz2ayUUm0dVqd22RMJrXW6Uuo5IAUoB77WWn+tlOqhtc60b5OplAq93LEJITqu5vSCqK33Q00XTbIFBAeUkGjYwNW7M+mTDVkhiuRozdXWIFjyZZPi6Eye/O7JXqcKTrXoNOJXBF5R9pcJf2lwMjCz2czgwYPjUlJSPBYtWpR93XXXSTWiFbXFpY1A4BagL3ABWKuUWtiI/ZcCSwF69+7dGiEKITogRy+IhhKC2lzS+6EW2cUV5Lpa2exrBOBPh/+EV2oJobmK7qGejLgjgpvAVokQbcrNzY1jx44l5ebmuk6fPr3/jz/+6Dl69OiKto6rs2qLSxvXA2e11jkASql/A+OB80qpcHs1IhzIrm1nrfWbwJsAo0aN0pcpZiFEB9ASvSDqup2zIqcCF0MGWj0HQGpaBSG5ioxwX/oueRTmz2vWeTsbZyoHrS04ONhy1VVXFX/xxRcBkki0nrZIJFKAcUopb2yXNiYDCUApsAhYbv//szaITQjRxVW/hJFdXIExKxuf8iK8rJoepTuJTTTijQuhOYrscA/KV/yOwOi5bR22sMvIyHAzGAw6ODjYUlJSorZt2+b/yCOPZLV1XJ1ZW4yR2K2UWgfsA8zAfmwVBl/gY6XUPdiSDfnJFEK0qtqqD44kYtZvRzD/jV3M/fYF+ubnkRHiillV4o0LsWEjIQyiZsyQJKKdSU1NdV+8eHFfi8WC1lrdcsst+bfffnthW8fVmbXJXRta6z8Df66x2IitOiGEEJeFo/pgDXCrqjy4AKZzx/nPf55mrtFM36I8UsJc+Px2A1SUc1O/GfS54cW2Dl3UYezYseVHjx5Naus4uhLpbCmE6PTqGvfgqD78y9fI3C1v078og6wQ2yDuSi7g6lnMOS9IGejCqsxsCIsHSSKEuIgkEkKITq/mrZsA5pwcfEvycE84wa0pP9K/JJOgIYMZ/v5qAJZsWsLx/OPEmBQ3FRaAf7zckSFELSSREEK0ueb0gHBo6NZPx7gHh3N33kXFsWOcCYgAoLLvAPxnzLhon5igGFslwr+H9IYQog6SSAgh2lxzekA41NYLovp8GNYAN+a/satq3eLMIgiI4HdX/Yy4cH/mXJvGa2c2wtpVUJrDcUzEYIAs+yUNIUStJJEQQrQLLdEDoqbqlzS2VZSSlFnGnTn7iD++m7CcFLJCehMX7s8twyLZeOZN+6UME5hKiTH4cJP2sSURcklDiDpJIiGE6HQclYjMc0UUGGCzr5Gk4jLiwv2Zf/ooFYUZeA4ZTN7ocLyDnuaboz9VIKoGVS6WSxlCOEMSCSFEp+OoRJhNF+iVvJsRB44C0N3Xg4r0s3jGxtLn/dUs27SE41npxJgqpQLRiZjNZuLj4+PCwsJMW7duPdXW8XR2kkgIITo8RwUiu7iC3BITvuVWSrxciDliu6UzaMjgqm1z+nTnP+FnOPjuKFsVwlTJKvd+UoHoRP7617/2uOKKK8pLSkpc2zqWrkASCSFEh+eoQBjL8wkpLcTVRRGWeZz+RRlU9h1AH/stncClVQj3QKlAdCKnT592/+qrrwJ+//vfZ7744os92jqersDpRMI+a2cEtvkxkrXW1laLSgghGlC9yZRjLMRFFQgfYMhgTo4OZ8mmJVCc9dPdGFKFaHUZf/hjL+PJky06jbjHgAFlEf/7t3onA/vFL37R65lnnkkrLCyUasRlUm8ioZQKAH4B3A4YgBzAE+ihlPoBeFVrvbXVoxRCdGgN9Yloyq2fJ/acJ+dsPn7GbDxMZnoVHK27AlHzbgypQnRKH330UUBwcLB54sSJZRs2bPBr63i6ioYqEuuA1cBErfWF6iuUUiOBO5VS/bTW77RSfEKITqChPhG19YBwhp8xmxEHXqpqKhU0ZPAlTaUoziLGZJK7MS6zhioHrWHnzp2+33zzTbfIyMgAo9HoUlpa6nLLLbf0/eyzz85e7li6knoTCa31lHrW7QX2tnhEQohOqbl9Io7sSCfpy0TMeXlUWqyUunbHt6SUM9WaSq25/0rWnljLxk1LqvY7XmobDyF3Y3R+K1euTF+5cmU6wIYNG/yef/75HpJEtD6nxkgopRSwAOintX5aKdUbCNNa72nV6IQQwu7EnvPkF2h8y8qodDPgWpmNwZjM4ZixVU2lSFjFxsSVP3WlBGJMldzkHiotroVoJc4OtnwVsALXAU8DxcAnwOhWiksIIQD45+4Udm8+R3RqJZ4V2QSd31CtArHoom3XrnqXBBcjo7QHq7R9wL47UonogmbMmFE8Y8aM4raOoytwNpEYq7UeoZTaD6C1LlBKGVoxLiGEACBt9YcMKoqg0qcXERm2uTKqKhA1bFSlANw0/jGInntZ4xSiq3I2kahUSrkCGkApFYKtQiGEEC3uyI50dm45R26JiZCiCKwewQRZsogLK8V/xh1Mm38lgG08xJmNP93aqSsYhSdzJYkQ4rJxNpFYAawHQpVSfwPmAE+0WlRCiC6pYM3HFG3YwCHPqVgJJKQiGy+zCe1ewJAl19Jn4h0Xbb/xzMZLb+2MmNhG0QvRNTmVSGitP1RK7QUmAwr4H6310VaNTAjR6VVvKgVQccyMxTKRYgJxrcimV+Z64sL98b9xBpt7fM9zmzbaNqzeXEom2hKiTTl718bLwBqt9cpWjkcI0YE01GjKobYeEgVrPubQZjNFLkH4W/MBsJaVYXT3IM3TnZKofvj+cgV9xvYGYKOjsVRQDJTmyFTfQrQTzl7a2Ac8oZSKxnaJY43WOqH1whJCdAQNNZpyqK3hVNGGDVitk/DysNItZV3V8q/ChpI5eABr7r8SElbBKvs6dZ4YsFUfsqQCIUR74eyljfeA95RSQcBs4O9Kqd5a6wGtGp0Qot1rTKOpgjUfc3jTCdLd+mG1TqLEtye5fp4829t2O6eD446MtYffZWNlNhh8LuoNIRUIUZfIyMh4Hx8fi4uLC25ubjoxMfGSy/C/+c1vInx9fS1PP/30+dqO0RwrVqzofvPNNxdFRUVV1rfd8ePHDTNmzBhw8uTJIy1x3vnz5/f53e9+d37kyJEVzTnOihUruickJPisXr06xdl9Gjv75xVALBAFJDVyXyFEF1e0YQOp1kmUGILw8rBiVBUcdHGp6kpJwio4vM722yUJNlZmc9zgTkxYPDHATf1ukts6RYO+/fbbE+Hh4ea2OPcHH3wQPGzYsPKGEomWZDabWbNmzbnLdb6anB0j8XfgVuA08DHwl5pzbwghRF0cgyorPKdS4hJEaHQo//INICmziLhwP24ZFmm7lTNxJVSWgsEHwJZE+ESyauqqNv4KRFfw5JNP9li/fn2QyWRS06dPv/Diiy9mAFx//fX9MzMzDUaj0eWBBx44/8gjj+SazWbmz58fdejQIR+llF6wYEFu7969KxMTE73vuuuufp6entaEhISjvr6+2nH8HTt2eN97771RXl5e1rFjx5Y4lpvNZn7xi1/0/O677/xMJpO67777sh999NHcDRs2+C1btiwiMDDQfObMGc+xY8cWv//++ymurq54e3sPX7p06fn//ve//s8++2zak08+Gfncc8+l7tq1y+fs2bMer7/+ehrYKgx79+71fu+991JfffXVoNdee61HZWWlGjFiROnq1avPubm58fLLL3d/8cUXw0NCQir79+9fYTAY9KWvTt2crUicBa7UWuc25uBCiK6t+u2chSoQn5JS3AxmtlX4kFRcZqtEjDwGh//KEnWe47qCGIN98CT8VIUQHc6W1Ud75aeXtOg04kGRvmWT7xrY4GRgkydPHqCUYsmSJTmPPPKIU3+3/v3vf/ufOnXK89ChQ0e11lx//fVX/Oc///GdNm1ayYcffpjco0cPS0lJiRo+fHjcwoULC06ePOmRmZnp7rg0kZub6xocHGx57bXXQp977rnUSZMmldU8xz333BP14osvpkyfPr3k/vvv7+lY/tJLLwUHBARYEhMTj5aXl6vRo0fHzpw5swjg8OHDPvv370+Mjo42TZo0acDq1asDlyxZUlBeXu4yePDg8pdeeikD4MknnwTgzjvvLBg3blwskAawbt26oD/+8Y+Z+/bt81y3bl1QQkLCMQ8PD71w4cLer7/+eveZM2cWLV++PGLv3r1Hg4KCLOPHj48ZPHjwJbHXp6FpxGO11seAPUBv+xwbVbTW+xpzMiFE13FkRzqHNpttYyFcgnCvyMYr7TMyh0wgK3gA4a4HKPE/yJLEE1BZaqs+KE9WDf4FjFrS8AmEqMV33313LCoqqjI9Pd3tuuuuix40aFDFtGnTShrab9OmTf7bt2/3j4uLiwMoKytzOXbsmOe0adNK/v73v/f48ssvuwFkZWW5HzlyxHPIkCEVqampHosWLeo1c+bMwlmzZhXVd/y8vDzX4uJi1+nTp5cA3H333Xn//e9/AwA2b97sf+zYMe/PP/88EKC4uNg1KSnJ02Aw6Pj4+NK4uDgTwLx58/J37Njhu2TJkgJXV1cWL15cUPM8ERER5l69ehm3bNniM2jQoIozZ854TpkypWT58uUhiYmJ3kOHDh0IUFFR4RIaGmrevn27z7hx44ojIiLMALfeemv+iRMnPBvxkjdYkfgNsBR4vpZ1GtvcG0IIAfxUgQA45DmVIh2Aj3sFPp7pBAYcJCrmAnPCdwI7bRWIMhOhpkow+BATFi9jIDoRZyoHrcExNiEyMtI8ffr0C7t27fJxJpHQWvPQQw9lPvrooxdVMDZs2OD37bff+iUkJBzz8/OzjhkzJqa8vNwlJCTEkpiYmLR+/Xr/V199NXTNmjVBa9euTa7v+Lb5L2tdp55//vmU2bNnX5SMbNiwwa/mPo7nBoPB6uZW+5/wOXPmFHz00UeBsbGxFdOmTStwcXFBa63mzp2b55gd1eH999/vVldczmpoGvGl9ofTtNYXjQRVSjUqYxFCtC/O9oCoT/VbP6tXIFy8vav6QwzhVXoFprOqWy/+6WfGoGy/SqqaSbn3gsFzpAohmq2oqMjFYrEQGBhoLSoqctm6dav/H//4xwxn9p02bVrRsmXLIpYuXZofEBBgPXv2rLvBYNAXLlxwDQgIsPj5+Vn379/vefDgQR+AzMxMNw8PD+vixYsvREdHG+++++6+AL6+vpbCwkLXmscPDg62+Pr6Wr766ivfG2+8seTdd98NcqybMmVK4WuvvRYyY8aMYg8PD33o0CEPR0J0+PBhn2PHjhkGDBhgWrduXdC9996b09DXsnDhwoLhw4fHHT582Lh8+fI0gKlTpxbdeuutV/zhD384HxkZaT5//rxrYWGh66RJk0ofe+yxXllZWa6BgYHW9evXBw4aNKjcuVfcxtkxEt8DI5xYJoToIJztAVGf6v0hkr5MpEj74+ZmJisgwrYssBdXVLqTaujPgdgBnHU0lAK5C0O0uLS0NLdZs2ZdAWCxWNTs2bPz5syZU+slhxdffDH8jTfe6OF4fv78+UNHjhzxHD16dCyAt7e39cMPPzw7e/bswjfffDMkOjo6rn///hVDhw4tBUhOTna/5557oqxWqwJ4+umn0wDuuuuu3AcffLDPo48+eslgy3feeSfZMdjyuuuuq4rr4Ycfzk1OTvaIj48fqLVWQUFBlRs3bjwNMGzYsJLf/va3PY8dO+Y1duzY4jvvvPNCQ69DSEiIZcCAAeUnT570uvbaa8sARo4cWfHEE0+kT548OdpqteLu7q5XrFiRMnny5NLHHnssY9y4cQNDQkIqhwwZUmaxWBpVolBa1z04UykVBkQCHwB3YGuPDeAPvK61jm3MyVraqFGjdEKC9MUSoinWPPU4gNM9IBry0X3/xFpcxI9umWROnMrkso1MKN9KVOUZSgIH8ni0bYiV3IHR9pRSe7XWo1r6uAcPHkweOnSoDMpvIRs2bPB7/vnne2zduvVUW8dy8ODB4KFDh0bVtq6hisSNwGKgJ/BCteXFwB9aIjghRMd0ZEc6P6zbDxds7a0r3bvj4l5J5lVTbT0hVv2VtS6ZPBcQAT6Gn9pbCyE6lYbGSDg6Ws7WWn9ymWISQnQAJ/acx1Tmio+pAu3uiqcxjVDDIVYYV8MqT8g6zMbwUI4bDMT4hRFDmNzKKUQjzJgxo3jGjBnFbR1HQ5xtkf2JUmo6MAjwrLb86aacVCnVDXgbGIzt7o+7gePAGmxdM5OBeVrrS25tEUJcXo47Mc65RZPu1q9qeZFLED4lqfjlvsHnCxSYbI2k/glAIYSHctwVYoJi5HKGEJ2YizMbKaVeB+YDD2IbJzEX6NOM874MbLKPsRgKHAUeB7bY5+/YYn8uhGhjRRs2UHHsGMkqigsEUmYyYzKW41t2DkPFj+yKq6hKIgiLv+hfTEi8VCGE6OScvWtjvNZ6iFLqkNb6KaXU88C/m3JCpZQ/MAnb2Au01ibApJS6BbjGvtl7wDbgsaacQwjRMo7sSOeQ51QYNpV8QzA5nllsHvwZfSpP46krOG5w5wqrBx+6hMstnEJ0Uc4mEo57SsuUUhFAHtDUe8b6ATnAKqXUUGAv8Gugh9Y6E0BrnamUCm3i8YXokhrbF6K+Wz+/Wv461s2byIi8lUr37niZsijxT+ZcaAJx6hxgBA9f4qSJlBBdnrOJxAb7uIZngX3YxjW83YxzjgAe1FrvVkq9TCMuYyillmLrtknv3r0b2FqIrqOxfSGq94BwWHtiLXv+e5LooyF4hEzDaOiOuymDLP8VfDnYSj+rB6t0OLgjFQjRLtU2PXdD04Y3Zeps8RNnB1v+xf7wE6XUBsBTa13YxHOmAWla69325+uwJRLnlVLh9mpEOJBdRyxvAm+CrY9EE2MQolMKierbpL4Q/9ydwmcH0umT9BoDLszH4h5OJekUdcsgL/gAuYFmYpUPN018TKoPQoiL1DvYUil1a81/wHRgsv1xo2mts4BUpZTjhvLJQBLwObDIvmwR8FlTji+EaLzPDqSTlFnElUmFeJrAz5jOLSzn8bhPeTY0mVXu/Vg1+BfMlSRCdGBjxoyJ+dnPfhYZHx8/MCoqavCmTZt8a27zr3/9K2DYsGGxmZmZbrNnz45avHhxr+HDh8f27NkzftWqVYEAVquV+++/v+eAAQMGRUdHx7311luBAAsXLuz94YcfBgBMmTKl/9y5c6MAXnzxxeBf/epXEcePHzf069dv0G233dbniiuuGDRhwoQBJSUlzZvooh1oqCIxs551miYOuMR298eHSikDcAZYgi2p+VgpdQ+Qgu3OECFEK3r0qzfIPJDG2LO9uaHcSnHwfZT6RhLmnULwsDhY8mVbhyg6qK9ee6lXbuq5Fp1GPLhXn7Ibf/ZQsyYDM5vN6vDhw0fXrFkT8PTTT0dMnTr1hGPd6tWru7388ss9vvnmm5MhISEWgPPnz7snJCQcO3DggOesWbOuWLJkScHq1au7HT582Ovo0aNHMjMz3caMGTPwhhtuKJk0aVLx9u3b/RYsWFCYlZVlyM7O1gDfffed7+23354PkJKS4vnBBx+cGT9+/Lmbbrqp3+rVqwN//vOf5zfna2prDTWkapULoFrrA0Bt7Vknt8b5hBC1257xNdfnTsXLEo7BlIbJoPBwyyI6IgXi57R1eEI0Wl0zWTqWz507twBg/PjxpY8++qjBsf7777/3O3jwoPfWrVtPBAUFWR3Lb7755guurq6MHDmyIi8vzx1gx44dfvPmzct3c3OjV69e5rFjx5bs3LnTe8qUKSUrV67ssXfvXs/o6OjyCxcuuJ47d8597969Pm+99VZKdna2W2RkpHH8+PHlAMOHDy9LTk72aL1X4/JwaoyEUupPtS1vakMqIUTbOLIjnU1f7Ye8HPzLzNzDDZgNEfiXpHFV7hv0+WZ/W4coOonmVg6aqkePHuaas2/m5+e79u3b1wjg6empAdzc3Kg+OVXv3r2NKSkpHomJiZ6TJk0qcyx3bA+2qcCr/19T3759KwsLC92++OKLgIkTJxbn5+e7rV69OtDHx8caGBhozc7OxmAwVO3s6uqqy8vLnern1J45+wWUVvtnAaZh60AphOhATuw5j0uBK35lJjxMVhQueJmz6WU8gH/cJZeLhehwAgICrKGhoZWfffaZH8D58+ddt23bFnDdddeV1Ldfz549TZ988smpJUuW9E1ISPCsb9urr766eN26dUFms5mMjAy3PXv2+E6cOLEUYOTIkSVvvPFG6PXXX19yzTXXlKxcuTJs7Nix9Z67o3P2ro3nqz9XSj2HbXCkEMJJje3z0Fi13fp5ZEc6332bSFZJLj6FJrzMofiY0hh5YAXBQ0bS573Vtg1XrcM2qa8QHd9777139uc//3nvxx57rBfAY489ljFo0CBjQ/sNHTrUuHr16jPz58/v//nnn9c54+add9554fvvv/cdOHDgIKWUfuqpp9J69+5tBrjqqqtKduzY4T948GCj0Wg0FRYWuk6aNKndz5fRHPVOI17nTkoFAnvs7azbjEwjLjqSNU893qg+D00xcMI1DLl+atXz9c/vI+VsNtleafQ5r/GstOJu3Effwu+JGdyNwGH25CHrsK2ttQyu7BJkGnHRWM2ZRhwApdRhbHdpALgCIYCMjxCikZra58FZa0+s5f3X/5fuqVGYLBq/4iByvdP5vP8XPLNfERfuT58b8iCrEMKqNXQLi5fBlUKIJnG2s+WMao/NwHmttbkV4hFCNMPGMxvpdfYqvEqDcLdk4lOaRlhmAjclnKZ7nhWUB2TlSfVBCNFinB0jcc5+OaOXfZ8eSim01vtaNTohhFMcnSmTDUX0tBoo8fQkZvcn9C/KIChUg9UEPXxsAyrDIqT6IFqL1Wq1KhcXF+k63IlYrVYFWOta7+yljb9gm63zND9d4tDAdc2MTwjRDI65McIOhjO51AzqBsyGIHyMp4m7cAb3EHf6XFcgFQhxuSTm5OTEhYSEFEoy0TlYrVaVk5MTACTWtY2zlzbmAf3tU34LIdrYTxWIf3H96Wl4mUPxrEyj0sMVT2sOUSUJ+ASZ8Y/vDmE9pQIhLguz2XxvVlbW21lZWYNxvr2AaN+sQKLZbL63rg2cTSQSgW7UMZGWEKL1rD2xlo1nNlY9D04egOfpXlxh1YwuuwEfcxj+JWmMOf8qA+7sadtI7sIQbWDkyJHZwM1tHYe4vJxNJP4fsF8plQhU3YurtZZvGNFlNLcPRFNv/dx4ZiPH848T6BZFbqmRG073IrA0mAKfXALLwMOURi/jQYLjq/WBkLswhBCXibOJxHvA34HD1DPgQojO7Oh325rVByIkqi8DJ1zj9PaOSsTx/OPEBMXgv/dupmRl4Wn2xteSxsy9r2DNMeIZ5iWtrYUQbcbZRCJXa72iVSMRogNo7T4Q1b17YD1pZafw1L1IT4slIsuIp9mbHoZzdE89jDXPjGeYF/5TJl2WeIQQojbOJhJ7lVL/D1tb7OqXNuT2TyFaQM1xEABpZaeISZvCVWmj8SkvwmSoxN+YzohTb1FxwR3PISPp8/7qNopYCCFsnE0khtv/H1dtmdz+KUQLqX4Jw8FT92LQhdF4WA14msrxJpXIwh9s62Jj8Z8xo67DCSHEZeNsQ6prWzsQIbq6mKAYVk1dVXVrZ1lmEW544G88wfiM5+mz2D61TfyvYNSStg1WCCHsnG1I9afalmutZb4NIZqo+uUMyxE/4vLHsf6HjVgLMplu1cw0akp1BFaTFQw+ciunEKJdcvbSRmm1x57Y5t442vLhCNF1bDyzkcM5R3E1R3JD1nV4lgVT6paKp7WcChcvXI1WfO23dsqASiFEe+XspY3nqz9XSj2HbeClEMIJtQ2mPJ5/HFdzJH2O3k9YsRsBHmeZFfQkyWcjKL3Qn4D0s3jGxtLnIxlQKYRov5ytSNTkDfRryUCEaAuNaTLVnB4S1asPPwmnLH8IQ60GwMpwn2349B6O7/5K3OxJhAyoFEK0d86OkTjMT5N1uQIhgIyPEB1eY5pMNbWhFPxUfSg7t5S4cH/Ccs3Ep6TgVVZCiWcp/hWp+J5O5FxqPBXpx2yVCLm1UwjRAThbkaj+scgMnNdam1shHiEuu9ZqMlW9tbXFaKs+xIX7s+b+K1n//D6yrd3AXIy/KZ3I0oPgEwLIrZ1CiI7F2UQiHDiitS4GUEr5KqUGaa13t15oQnQ8NasQMUExlJ1bysTTP9LzghcuFYf56PvDFBki8S1J5arcN6S9tRCiQ3N2mtfXgJJqz8vsy4QQ1TjGQiRlFmExhpOeFktSZhE9jT6U6nB0pe0Kob8pXe7GEEJ0Cs5WJJTW2jFGAq21VSnV1IGaQnRqjrEQDwbsZEL5F2D4guP6dlxNGYx3+44+78nYByFE5+FsMnBGKfUrfqpC/Bw40zohCdGxrD2xlncPrCe31EiFSsVqDCcu3J+lhn1QkcKP6beSaR5It8pTtqHKQgjRiTh7aeMBYDyQDqQBY4GlrRWUEB3JxjMbSSs7hbcxhxiTiXsrMllhfAKyDkNYPKeMYwDo5ZEtgyiFEJ2Osw2psoHbWjkWIZqlMT0hHBrTG6K2plLZRUbSyk5hrQjnlfw8KInnROX1bC8xYy6zwEkDRS4BBFmymLTqiUbFJoQQHUG9FQml1BNKqaB61l+nlJKPWKJdcPSEaIzG9IZw3M5ZXW6pEWtFOOFu4wn29eBE5fXkmvtiNnthNbuAqwF/VcgVcT6NiksIITqKhioSh4EvlFIVwD4gB9tcGwOAYcBm4H9bM0AhGqMle0LUrEA4buecEvgUnx1IJyzXzO1ZWQS7FOFjcON702xyjMH4WdIYceAlW1Opt2RgpRCic6u3IqG1/kxrPQHbGIkj2IaKFQEfAGO01g9rrXNaP0whLr+aFYiYoBhu6ncTnx1IJymziNACC55mb7x1hW0Dgw9+phxC076XplJCiC7D2TESJ4GTrRyLEO1OTFAMq6auAmD32ufxXfcyj5gseBtcOaHuw2wpY+SptyEsHoCKY9LeWgjRtUgvCCGoe3bOmKAYjuxI58Se85SmdMPTehsVLl64u7pQZAzB15hGRZ7GM8y2j1QihBBdTZslEkopVyABSNdaz7AP6lwDRAHJwDytdUFbxSe6FsdljJigmKpl4RZvhh07wv6zmygxhRHsVk6FixceXj0x5+XhywVCsw/hOWiIVCCEEF2Ws7N/TtBaf9fQskb6NXAU8Lc/fxzYorVerpR63P78sWYcX4g61TWQ0nEZ48iOdPb/ZxOe1nJyzWH4GrIY2ONflAyYRdjn31ZdwiAYqUAIIbo0ZysS/weMcGKZU5RSPYHpwN+A39gX3wJcY3/8HrANSSS6rNbuCVGzAuEYSEnCKji8jhNJ8ygzhYIhmx5XhBM9ZhiDJt4DwLnP75JxEEIIYVdvIqGUuhJbR8sQpdRvqq3yp3nNfl8Cfgf4VVvWQ2udCaC1zlRKhdYR01LsXTV79+7djBBEe+boCeFsYgDO9YRwVCJqViBWrT7Mic15fFBZhKe+idzKYLzdMvEv28rQA9/CATj3pu0YVdUIIYQQDVYkDICvfbvqf/SLgDlNOaG9gVW21nqvUuqaxu6vtX4TeBNg1KhRuoHNRQfWkj0hHKonEdUrEO4HbqW7KQxP9woqlCd5Pj4cDYxhwY/fUJF+8qLEQQZUCiHET+pNJLTW3wLfKqXe1Vqfa6FzTgBuVkrdhK25lb9S6gPgvFIq3F6NCAeyW+h8ogurbSzEhKIZjM+cCkdgTfpBXM03UVJpGwcxZ9hGCnKuoOjwt3AeKtLPymUMIYSoh7OTdnkopd5USn2tlPqv419TTqi1/r3WuqfWOgrb/B3/1VovBD4HFtk3WwR81pTjC1FdbU2lBqRdQe6ZLMg6jKu5jDLtQZ6PD5Ujx8CSLyk6XEDFsWOAVB+EEKIhzg62XAu8DrwNWFopluXAx0qpe4AUYG4rnUd0MdXHQgCs+XoVrq45RAd+RJnJwv6A6/l5hD9FG/7BuW+kqZQQQjSGs4mEWWv9WkufXGu9DdvdGWit84DJLX0O0XU401QKoKA8FG+3TJ7u/iwAtwyLpOiVJ6oSCKlCCCGE85xNJL5QSv0cWA8YHQu11vmtEpUQTVDzls7sIiMWYzjpabF8euwk3cqMBLinEexWTkDZUZ7Zud22406pQgghRFM5m0g4xi48Wm2ZBvq1bDiiM2hKD4ianL31s3oVouYtnfPf2IXP6WKGWg34llsJcE9jVtCTJLv3w7rdnYq80qq7MaQKIYQQTePspF3O38wvurym9ICoyZmeEHBxFSImKIZgNY75b+wCICmziNusHoSUGfErPUfkhR/ITeqBb1g/KvKkAiGEEC3B2RbZ3tg6UPbWWi9VSg0AYrTWG1o1OtFhtUYPCIf6qhC//tsOrsgqxdvDjSF4EGgCv9JzjNj3Ap5hXuATAkgFQgghWoqzlzZWAXuxdbkESMN2J4ckEuKyq16FCHSLIj0tlvlv7GJy2UZGZvWhzBxOD89028Ye0P3CD3iGedHnm/1tG7gQQnRCziYS/bXW85VStwNorcuVUqoV4xLiInVVIea/sQt9upghViPelVGUmUMJ9MpmVtw6AAoOFJF1PBdie7Vl+EII0Wk5m0iYlFJe2AZYopTqT7W7N4RobdWrEI7pvY/su4pHTBaOG++l3ByOj5sRH998om++ASYuAaDozruAXPxvv7dtvwAhhOiknE0k/gxsAnoppT7E1uZ6cWsFJURtHFWII/97Fb1MqaQa+uNtcMXd1QUfQw6z4r60tbd+c8tFE2x5jx5N4Px5bRu8EEJ0Us7etfGNUmofMA5QwK+11rmtGpno8taeWMu7B9aTW2qkQqUSbvbmyP9eRfmF3nxuXIJP7+EAFOkSgsN8Yckiiu6866LZOWVQpRBCtC5n79qYhW1OjC/tz7sppf5Ha/1pawYnuraNZzaSVnYKqzEcb49eTCtJJaoyjfUXFlFCOK72+TB8ge6JZzh350vSWEoIIS4zpy9taK3XO55orS8opf4MfNoqUYl2r76mU83pIbH2xFr+tfsNXMtzOeduYYDRhafy8xgUHsCR7Bi+rvwFpaoHfiVpjHfZfsn+UoEQQojLy9lEorZZQp3dV3RC9TWdcraZVG02ntlImvk8MdZKbt3rzlVHLBhUMedcSzkUcQtFHiH4lqbRy5BFn1VSdRBCiLbmbDKQoJR6AViJ7c6NB7H1lRBdWEs1nXKMhQg8258+uRPob72SKLMrrkYvkiPKSPH2BqDIJQh/az7jXbbjP1WqDkII0R44m0g8CDwJrLE//xp4olUiEl1Lwio2Jq5k0P5yYgquxuQRho8xDRfAainDxdv7p4GTQPSYePpMvKNNQxZCCPGTBhMJpZQr8JnW+vrLEI/oIlav+5yM/SVgMtOL++hzAcyGSLqZMhif+YatlbVfGP7XzyBw/oi2DlcIIUQdGkwktNYWpVSZUipAa114OYISnV9GQj4exSFUeBXhgQsW7YZbZT5D7p1On4lL2zo8IYQQTnL20kYFcFgp9Q1Q6liotf5Vq0QlOj9LJW6WVGbufoVit0A880up7DuAQRPvauvIhBBCNIKzicSX9n9CNMmRHel899V35BsLsQJeZeF4l6VTWWQgYkhf6InctimEEB2Qs50t37PPtdFba328lWMSl0F9fSCc0dheESf2nMeU60P38nxcUKDTiczcS2XfAdI8SgghOjBnO1vOBJ4DDEBfpdQw4Gmt9c2tGJtoRfX1gXCGM70i/rk7hd2bz9EzPwVDRTe8y1MZeeBlzvj3x8fDjYHh/vjPmN2k8wshhGgfnL20sQwYA2wD0FofUEo17S+QaDdaqg9ETQVrPqZowwYCM4sYFD4Li2d33Eyp9MxIID/Yl7Xz/sgtwyLpM7Z3i59bCCHE5eVsImHWWhcqpaov060Qj+jg/rk7Bb+PvqfIawKVEWDx6I6bKY3eGf9HbNhI/Gc8yvXzr2zrMIUQQrQQZxOJRKXUHYCrUmoA8Cvg+9YLS3Q01asQ+SFTKfGNJDcggwqVQUXwYbotuIE+N7zY1mEKIYRoYY3pbPlHwAj8E/gK+GtrBSU6jt1rn6dofwrZqXFo83iMEQqTRyRmtwy+HPEuMUExrJq6qq3DFEII0UrqTSSUUp7AA8AVwGHgSq21+XIEJjoG35PrSS2+jRLPSNxM6SSHgheZFESeJiYohpv63dTWIQohhGhFDVUk3gMqgR3ANGAg8FArxyTasX/uTuGzA+mMPLSN+OO76WW8gDHKHV9rFsEX3mHn7YOkAiGEEF1IQ4lEnNY6HkAp9Q6wp/VDEi2hoT4Rjbn188iOdE7sOQ/A2cwirjTmEFIURH7INHLcNaUekRgqs9gaa2mJ0IUQQnQgDSUSlY4HWmtzjbs2RDvWUJ8IZ/pAOOzcco6KnApKvFwoM5rpY7wAlRoXDxdSQ10oU5mU98shN2qIXMoQQogupqFEYqhSqsj+WAFe9ucK0Fpr/1aNTjRLc/pEVK9CVORUoF3y+J+glwHw3nSeimw3vprXl89jL8iASiGE6MLqTSS01q6XKxDRvpzYc56sU3kYyjLxsmr6FX2H76FsMPhQUWggJcqdj+1JhFQhhBCi63L29k/RRTgqEbnn8vEvOcPwAy9BkBteuoIcDy/yDO7Q052tsRapRAghhJBEQlws6ctE8vKt+JWnEJa5B4LciFtsa2X9tK+V45WFxATFAEglQgghxOVPJJRSvYDVQBhgBd7UWr+slAoC1gBRQDIwT2tdcLnj64qqT/EdcCEc35I0ume/hFG5sG5sT86GhwJwPP+4VCGEEEJcpC0qEmbgt1rrfUopP2CvUuobYDGwRWu9XCn1OPA48FgbxNdlONpaH/KcigV/upvy8TSl4V6xl3/M98QnMBz8wqq2l/EQQggharrsiYTWOhPItD8uVkodBSKBW4Br7Ju9h22mUUkkamioP4RDvX0iElbB4XUU/TODimwTDLsKA0WEp6+gzNiPM0Mm8D9Dn+QOmZ1TCCFEA9p0jIRSKgoYDuwGetiTDLTWmUqp0Dr2WQosBejdu+v9oWuoP4RD9T4R1W/lBCDLBUzTKY5wozJCU+IbSZ53OmsnhhJg+SNr7pfZOYUQQjinzRIJpZQv8AnwkNa6yNlmV1rrN4E3AUaNGtUlpzJvbH+IpE++I7/UB39Tum2B1QoubqhKjdUdCv0ucCYwlfTCawnwbaWghRBCdEptkkgopdyxJREfaq3/bV98XikVbq9GhAPZbRFbZ+KoROSX+uBbksr43DcAyMFCnqsLZdpC3theHIl8kqTMYOLC/bllWGQbRy2EEKIjaYu7NhTwDnBUa/1CtVWfA4uA5fb/P7vcsXU2J/acJ+dsPr7FqfQyHaTPN/sBWLZpCYdzjuJqjiTAMobMtCLiwv3lkoYQQohGa4uKxATgTuCwUuqAfdkfsCUQHyul7gFSgLltEFuHdck4CCD3XD5+xWcYduBlvppqYNWmJYDtNk5XcyRl55YSFe5PYDhSiRBCCNEkbXHXxk5sc3XUZvLljKUzObHnPLlpJQT39MWck4M5Lw9fUwmh6btJ6eXCxyPdiQGyi4xYjOGU5Q+RKoQQQohmk86WHVxVS2t7EjHrtyNImDEe19QCskPArFzYOsSTmJB4Vk1dxfw3dpGSWSTjIYQQQrQISSTaiab2h6ieRPR0SeXcnS/hmlpAcih8vsAHfELI1oFUpsUy/41dJGXKeAghhBAtRxKJdqIp/SEcggNKmBX0d87ZG0xlh8C5QQZWLU4AqEogAsORSoQQQogWJYlEO9JQfwjHZYzTB+H0wX2Yc3LIL9D4V6RxbutJii+4kR6qeGqBOzE+EfxzdwqfHUiXKoQQQohWI4lEB1L9MgZgG1BZWkJkyfdg8CHdMb132BBu6ncT67b+lERIFUIIIURrkESigziyI52MkxeIGNCNWb8dAUDCnD+SV5jCqtkm6H4FxysLCXS7At9zS1l3DqlECCGEaHWSSHQQjh4R3RM3cu7Ol6A4C9ezqZSFAp4B4BdGDGGkp8VWJRBSiRBCCNHaJJFop2o2mMpNKyHIkkXQoU84FuYOplLKQuH0QHeuLJjGFqNteu9MqUIIIYS4jCSRaKdqjofoprMIPPVf0oNMPDXXQozJahsXYZ5LZtow4rxt+0kVQgghxOUkiUQ75mgwBXBuyj2UZVbw1VQDMbizyr0Xu32uY/7eWMb2lQqEEEKItiGJRDM520iqITnJZ/HuFsn65/cBkJmSj8WazlfTHwAgNLuC7F4ufDzGh5igGJi6ihfe2AXkSwVCCCFEm3Fp6wA6OkcjqeYKieqLqyGW3LQSAIp8swnM2EloWjGYSskOgaOD3Ah0iyK9WpfKsX2DuGNs72afXwghhGgKqUi0gIYaSdWl+oDKnPIcyks1Luos3v9dSYy5nKgsM0HdLAy/ox8AN8bPYdfeWOlSKYQQot2QRKINVR9QmV+eR5lPOYNP/0hoWjHZoS5Yulvxj+8BS760dancK10qhRBCtC+SSLQRR4Mpz4ozeJ94kxhzOd5uXkSlleJZrQpB/ByAi1pdSxVCCCFEeyGJRBtxXNIIT98NBvBWrnQ3VeDZrRL/YbYqBGCrRMisnUIIIdopSSQuk0vGQ2RpvMvP4Wo4yI1f7oFV0yHrMITFV1UhQCoRQggh2jdJJC6TpC8TbTN1WvNxrSzDW1vomfEj3am4OImwVyKqk0qEEEKI9koSiUaorWdETvJZQqL6NrivOS8P37Iyxrts51j+MTCVEmuyX8YAzvsM4LMLI9jyxq6L9nNUI4QQQoj2SBKJRnD0jKieOIRE9WXghGsu2bZgzccUbdjAObdokgmnzLUH7m7FLLs2ieOYiDFZWeU+oKoC8SvHOAjvi48jlzSEEEK0Z5JINJKzPSOKNmyg4tgx0odNpRR/3ExplPgdACAGA1dZfHmz9KcKhAymFEII0RFJItFCNq94DMtXWwEo9BqB0X08prgJlBgCyPNOI3XQ26xanFC1/fw3dpFUWCSTbQkhhOjQJJFoIZavthKcVkJuT1+KfYZjMkRS6ZpOiVc6hYH78SsbyPxq4x+kAiGEEKIzkESiCRzjHwCOWMPJdB+Au/89pA13JSh+BJWnMvFxy+TLwUPse8RfcgypQAghhOgMJJFoAsf4B8/YWDLd+2N0DwOdjvbUlKbsJ9itnAC/k6y5/962DlUIIYRoVZJINEJOWQ75FfkoYyTFg5aSE+mNx4UAjF6pPD7oC45kFlJmsuBtcKVkwKy2DlcIIYRodZJINKB67whjShbdTUaMHvEY3cOxGNOp8CrCxzeR+aYnSDLJuAchhBBdi0tbB9DeOXpHAHhXVtIntwSTuxd+ZPCQ3zJuDvoAz4BAQMY9CCGE6HqkIlGPdU/9H5nHMgFPSs72w8c9ivNRikrv7gS4J+PTeziDlnzJIGBpWwcrhBBCtAGpSNSj8KwXWhlsT7Sm0gBmT4WvIYvI7mcvmlxLCCGE6IqkIlHNkQ/WsmvnBVS5FYBK90hUhQl/7/PM7/MUSboPz4W/IGMghBBCCDupSFRz4mAZlZZw3E0aAPfKdFxcigFIdu/H/oDrZQyEEEIIUU27q0gopaYCLwOuwNta64YntmimIzvS2fnRZqyV3fEpScMv9y1mfbMXgDVP2QZaDvrDcga1diBCCCFEB9OuKhJKKVdgJTANiANuV0rFtfZ5T+w5X5VEuBv3kzdeLl0IIYQQzmhvFYkxwCmt9RkApdS/gFuApJY+0SsL7sFsMQOgXQy4WoyUVqYTNHQ0fsCapx4HuGTacCGEEEL8pF1VJIBIILXa8zT7sipKqaVKqQSlVEJOTk6LnFRZTShrCWZfr0vWhUT1ZeCEa1rkPEIIIURn094qEqqWZfqiJ1q/CbwJMGrUKF3L9k755YfvNHVXIYQQQti1t4pEGtCr2vOeQEYbxSKEEEKIBrS3ROJHYIBSqq9SygDcBnzexjEJIYQQog7t6tKG1tqslPol8BW22z//obU+0sZhCSGEEKIO7SqRANBabwQ2tnUcQgghhGhYe7u0IYQQQogORBIJIYQQQjSZJBJCCCGEaDJJJIQQQgjRZErrJvd0anNKqRzgXDMOEQzktlA4rUVibBkSY8uQGFtGW8fYR2sd0obnF51Ih04kmksplaC1HtXWcdRHYmwZEmPLkBhbRkeIUQhnyaUNIYQQQjSZJBJCCCGEaLKunki82dYBOEFibBkSY8uQGFtGR4hRCKd06TESQgghhGierl6REEIIIUQzdNhEQik1VSl1XCl1Sin1eLXlQ5VSu5RSh5VSXyil/GvZN0opVa6U2q+UOqqU2qOUWtRKcfZSSm21n+eIUurX1dYNU0r9oJQ6oJRKUEqNqSPWxNaIzX78fyilsmueoxGvo1ZK/aXasmClVKVS6pUWiq+u99nZ165V46txvvre6zX2WA8opZKVUgfqiPeyv9f2dQ/aX+cjSqln6jnGw0qpCqVUQCvGWdd7vkwplV7tdbypjv0HKaX+q5Q6oZQ6qZR6UimlGjjnH5yMrc73uNo2j9i/74JrWef4nnyw2rJXlFKLnTm/EO2S1rrD/cM2M+hpoB9gAA4CcfZ1PwJX2x/fDfyllv2jgMRqz/sBB4AlrRBrODDC/tgPOFEt1q+BafbHNwHbGoq1FeKbBIyoeY5GvI6ngf3Vlv3M/lq+0ogY3JrwPjv72jU7vpZ4r2ts9zzwp3b0Xl8LbAY87M9D6znGHmAHsLiVYqzvPV8GPNLA/l72/W+wP/cG/gP8ooH9SlriPQZ6YZu9+BwQXMd7fB44BRjsy15prddT/sm/y/Gvo1YkxgCntNZntNYm4F/ALfZ1McB2++NvgNkNHUxrfQb4DfArAKWUj/3T24/2qsUt9uWuSqnn7J/SD1X/VFHPsTO11vvsj4uBo0CkYzXg+KQfAGTUdyz7p5kdSql99n/j7cuvUUptU0qtU0odU0p92NAnsGrxbQfya1nl7OtYDhxVSjnuiZ8PfFwt5plKqd3213GzUqqHffkypdSbSqmvgdV1HLu+99nZ167R8SmlXOyfZEPs27jYPx1f8gmzugbea8f5FDAP+Ki+YymlFlevmiilNiilrrE/LlFK/U0pddBelelR37GqxVfXe/0zYLnW2mjfLruOmPoDvsATwO1OxnqPvTKwTSn1lhOVoPrec2fcAXyntf7a/rWUAb8EHrfH46uUWlXtZ3i2Umo54GWvcnxY38GdeI9fBH6H7fuzLjnAFuCSKqj6qdJ2SCm1XikVqJQaqJTaU22bKKXUoYZfCiEuj46aSEQCqdWep/HTD3MicLP98VxsnxCcsQ+ItT/+I/BfrfVobJ/WnlVK+QBLgb7AcK31EKDeXzo1KaWigOHAbvuih+zHTgWeA37fwCGygSla6xHY/iCuqLZuuP14cdg+zU1oTGy1aMzr+C/gNqVUT8DCxX/UdwLjtNbD7dv9rtq6kcAtWus76jhufe/zQzj/2jUqPq21FfgAWGDf5nrgoNba6U6EtbzXDhOB81rrk84eqxY+wA9a66HYkr37mnEsgGhgoj2h+lYpNbqO7W7HlgDtAGKUUqH1HVQpFQE8CYwDpvDTz1d96nvPAX5p/yP7D6VUYC37DwL2Vl+gtT4N+Crb5bkngUKtdbz9Z/i/WuvHgXKt9TCt9YJLD1nn1xdFtfdYKXUzkK61PujE7suB3yqlXGssXw08Zo/tMPBnrfVRwKCU6mff5qJkWIi21lETido+bTs+AdwN/EIptRdb6dHUhGPeADyubNextwGeQG9sf1Be11qbAbTWtX26q/3gSvkCnwAPaa2L7It/Bjyste4FPAy808Bh3IG3lFKHgbXYkgaHPVrrNPsfwQPYSqjN0ZjXcRO2PxS3A2tqrOsJfGWP+VFsv+gdPtdal9dz3Pre58a8dk2J7x/AXfbHdwOr6jn+xUHX/l47OP4YN4cJ2GB/vJfmv9duQCC2P/iPAh/XUdG6DfiX/Xvs39gSzPqMAb7VWudrrSuxfc82pL73/DWgPzAMyMR2iai2/euqBmhsP8MrqxZoXeBETJeepMZ7rJTyxvYB5E/O7K+1PovtMlFVEq1s4066aa2/tS96D9vlKLAlDvPsj+dz6fexEG2moyYSaVz8Cbkn9k+ZWutjWusbtNYjsf3CPu3kMYdjK1OC7ZfRbPsnlGFa6972TwX1/ZKqk1LKHdsvnQ+11v+utmoRtl/IYPsle8mAwRoexnZ9dSgwCts1ZAdjtccWbH8cmqwxr6O9BL0X+C22r7O6/8M2HiEeuB9bUuZQ2kAYdb7PNOK1a0p8WutU4LxS6jpgLLbr7A2q571GKeUG3IpzfwTMXPzzWf11q9RaO74Pm/1eY3ud/61t9gBWbHNBVFFKDQEGAN8opZKxJRWOyxt1xerU5bVaYqnrZ/u81tpiT2Teovb3/Ai2n43qsffDNgaimCb+DNc4Xm3vcX9s1cqD9tenJ7BPKRVWz6H+F3gM534PrwHmKaWiAd3MipYQLaqjJhI/AgOUUn2VUgZsv9Q+B3CUW5VSLtiu5b7e0MHsJcrnsP1RAdtgqQcdn8qUUsPty78GHrD/QUApFeTEsRW2T8tHtdYv1FidAVxtf3wd0NAvhwAg0/6L9E5sA9NaRRNex+exlWTzaiwPANLtjxt7Z0yd7zONf+2aEt/b2C5xfKy1tjQUbAPvNdg+DR/TWqc1dCwgGRhmH5/Ri4aTzOb4FNtriP0PlYFLJ5S6HVimtY6y/4sAIpVSfeqJdQ9wtf06vxtOjFei/p/t8GrbzcJ2+a2mD4GrlFLX2/fxwnYJ0HEnytfYxkxgX++4PFJpTxDqVdd7rLU+rLUOdbw+2BKiEVrrrLqOpbU+BiQBM+zPC4ECpdRE+yZ3At/a153GljQ+iVQjRDvTIRMJ+6WFX2L7g38U2y/6I/bVtyulTgDHsP2xqask3V/Zb//EVjb8P621Y9u/YLuMcEjZbpVz3D74NpBiX36QamXJekzA9gvhOnXpbWv3Ac/bj/W/2MZg1OTGT9WGV4FFSqkfsF3XbugTfYOUUh8Bu7Bd805TSt1jX+Xs6wiA1vqI1vq9WlYtA9YqpXbQyNkOG3ifnXntmhvf59gGFzp7WaO+9xpsfxTru6xR/b3+DjiL7Tr5c9jG8DRLPe/1P4B+9u/1fwGLqlU8qse+vsay9fbltcaqtU7H9t7sxnZXSBJQWF+MDbznzzgGSWIbu/RwLfuXYxuc+YRS6rg9ph+x3RkB8FcgUCmVaP/euda+/E1sP9cNjXtq6D1urL9hq144LMI29ucQtks4T1dbtwZYiIyPEO2MdLZs55TtjpEFWut5DW4sWpSy3enxotZ6YoMbt8z5Ot17rZTy1VqX2CsS64F/aK1rJiRCiA6suddWRStSSj2N7dPV4jYOpctRtkZIP+OnOzda+3yd9b1eZr/M4IntssKnbRuOEKKlSUVCCCGEEE3WIcdICCGEEKJ9kERCCCGEEE0miYQQQgghmkwSCSEaQSllsd/yd0TZ5rr4jb3XRn37RCmlnLlVWAghOhxJJIRoHMecDIOwtd2+CfhzA/tE4VzPESGE6HDkrg0hGkEpVaK19q32vB+2hkfBQB/gfWyTagH8Umv9vb2B2EBsTZvew9ZpcTlwDeABrNRav3HZvgghhGhBkkgI0Qg1Ewn7sgJsM1sWA1atdYVSagDwkdZ6lLJNqf2I1nqGffulQKjW+q9KKQ9snSHn2idyEkKIDkUaUgnRfI7JqdyBV5RSw7DNixBdx/Y3AEOUUnPszwOwTYgliYQQosORREKIZrBf2rAA2djGSjhmZ3UBKuraDXhQa/3VZQlSCCFakQy2FKKJlFIh2GZFfcU+yVVds7MWA37Vdv0K+JljtkmlVLRSygchhOiApCIhRON4KaUOYLuMYcY2uNIxnfSrwCdKqbnAVn6anfUQYLbPNvku8DK2Ozn22aelzgH+5/KEL4QQLUsGWwohhBCiyeTShhBCCCGaTBIJIYQQQjSZJBJCCCGEaDJJJIQQQgjRZJJICCGEEKLJJJEQQgghRJNJIiGEEEKIJpNEQgghhBBN9v8BYFKttQf62VMAAAAASUVORK5CYII=", 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GG284/B4I0Vbt37Cew9s31z7v2qMnV829u/UCaoM+++yzE00d8+KLLzY4NevHH39Mrnk8f/78vPnz5+fV3X/55ZeXHTp06JwBUXPnzi2YO3duQUPXHDt2bGlycnJtH2nNaxsMBl599dU0IK3+OR4eHtWff/758frbS0tLfzpfvACbNm06Vv+cu+66K/+uu+46Z9zDH//4x9w//vGPuQ3FfCFUU03LbUFsbKxOSEho7TCEEKLFxS98jOyUE5giIqk8mYq/hxdTX/vnBV1LKbVba93waOMLtG/fvpTBgwfnNOc1O5t169YZlyxZEtTQH//Wtm/fvsDBgwdHNLSvU7UwCCFEW2c5k42xrIKRP+2hNOkUnr26tHZIoplNnTrVPHXqVMebhduIdpEw5Obm8u677561rX///sTFxZ23D3/IkCEMGTKE0tLS2vUO6oqNjWXAgAEUFhayZs2ac/Zffvnl9OnTh5ycHNatW3fO/nHjxtGzZ08yMzNZv379OfvHjx9PeHg4p06dYuPGjefsnzhxIsHBwRw/fpwtW7acs3/q1KkEBgaSnJzMjh07ztk/ffp0fH19SUxMpKHWl5tuuglPT8/aQYH1zZ49GxcXF3bt2sXBgwfP2T937lwAvv/++3PGUTg7OzNnzhwAvvvuu9pugxoeHh614zI2bNjA6dOnz9rv4+PDDTfcAMD69evJzMw8a3+XLl2YNm0aAJ999hm5uWe3qAUHBzNx4kQAPvnkE4qKzp711K1bN6655hoA4uPjKSsrO2t/ZGRk7XiLDz744JwFo6Kjoxk1ahTAOb93IL978rvXcr97wamnqExJAWDV0f22ezL44GX/PbzY3z0hLka7SBiEEKKjSU3cz6kkW8JUbTZjLS4myOBE11ATbq5l/HecFyV4oFy68IdWjlUIkDEMQghxyeXHr+TTNR9RqK34KgPV9kHLTm5OlLlX8U3fCo50L2bk0bl4Gnx4eeFdF/Q6MoZB/FoyhkEIIdqA/PiVFK1bR+muXVT3CsXXaORKFx9wKcWnRxn+wSeZ3TWQI85V9D5yL0Ny++AcfNGFCoVoFpIwCCHEJVK0bh3lSUl4xsXh6uOCc1cTPZ5cTNYr4zmR1p0Pz9xORL6VHlYPwkpsq6uOGd+jlaNue44dO+Yye/bsyOzsbBcnJyduv/327CeeeOJMa8fV0UnCIIQQLaDuegqWM9lYcnOpLi3FqVco7r1DyU85gclsJeuV8Xxd+TMnLbPwrAwGlzS6eAQQGupH9PAg+o8Na90baYNcXFxYsmTJ6TFjxpTm5+c7DR06tN/kyZOL2koZ6I5KEgYhhGgBh7dv5szRZHws+pcxCkYjzl3s0yR9qtnpmch610JKyn/DFSW9MXfJZMjtAcyMntqKkbd9PXr0qOrRo0cVgL+/f3WvXr3KUlNTXSVhaFmSMAghRAuwnMnGO7+I4T+n4xkXx9G4ED6MPgPmdCjZR0JEBX2zLqff0ZGYSiIAmDbxCvpHt6MWhf/eF86ZQ81a3pqu/Ur5n9ccLmqVnJzseujQIc8rrriiuFnjEOeQhEEIIZpRzcDGyjzbasDBCxeywX8HizK+gCyILSsnMGcss/JH4l/SGwDnYHfGjO8h3Q+/UmFhodMNN9zQa/HixafqVqIULUMSBiGEuEANjlOwdz+YvT1x9fHgT07LSciwLSD1u3wPeqZdSarZVl6+3ScKv6IloLlVVFSoKVOm9Jo5c2be7bffXtBacXQmkjAIIcQFOrx9M9kpJ/D39K5dobFmnEJQVxM73feTbE5lYvoI/HOuJr0qCGerrULylbP7tN9EoZVVV1fz29/+tkd0dHT5U089ldXa8XQWkjAIIcRFMEVEMvJYOqU/pxO8cCFfRoxk7d408g1b8MvrxnUHp2Es6QNAl2B3uhrdZfbDRfrmm2+8//vf/3aJiooqi4mJ6QewcOHCtFmzZhW2dmwdmSQMQghxAfLjV1J+2Fb+vfzndMwxg3iqIBzDdw9j8Ukmw6WauJz78S7r1v67HtqYa6+9tlhrvbu14+hsJGEQQggH1B+vUJmSQpGHK37ObrjHxJDsbuXhjD+x0rkvHj/fSxxO+JSGEdIVpj81qnWDF6IZSMIghBAOaGi8QqCvFwN7lPFj+Em+qEgnMGcsEadt1TRDo/wAiB4e1EoRC9G8JGEQQggHWM5kYyyr4LIdtrLTnlf48mP0YZZ6eVGSfRVRObcQWhQFgPGaYqbPuLo1wxWi2UnCIIQQ51GzpgJQu66Cc6grgaFn8A9J54WymwnLvIwQs6ynIDq+Fk0YlFIPAb8DNHAAmAd4AvFABJAC3KS1zm/JOIQQwlE7Fj/Dkb0JAL8s6ezphtnTlS6GUpL6jSOvfDAlhf7ElPkDtu4HmfkgOroWSxiUUmHAH4B+WusypdRK4LdAP2Cj1nqxUuox4DHg0ZaKQwghmlK3JSEpL802mFEpnNyccPY04OxShDtw3HUkPubJAJh9Mil1PUFZZBb3zf9rK0YvxKXR0l0SzoCHUqoKW8tCOvAX4Er7/veAzUjCIIRoRTVlp91jYnDydCPQrZrZvb8HICsglh9PDeVA1Qh8y0MB+K7nv/EaVAXA5J6TWy3uzqq0tFSNGDEiprKyUlmtVjVt2rT8pUuXprd2XB1diyUMWus0pdQLQCpQBnyttf5aKRWktc6wH5OhlOraUjEIIcT57N+wngNrVp1Tdtp8JBeTazlZAbGstY7i7+kjmVXqSoiykOVra1GYefUEZkbPbO1b6LTc3d31tm3bkn19fasrKipUXFxcn40bNxaOHz++pLVj68haskvCH7geiAQKgFVKqTm/4vy7gbsBunfv3hIhCiE6qfz4lfy05iMKLBX4lFXalnP2cqby9D4CXEvx9TcwIv1PDDWkcqs1jy4qkDyvdE5dtY3lE5e3dvidnpOTE76+vtUAlZWVymKxKKVUa4fV4bVkl8Q1wAmtdTaAUuoTYBSQpZQKsbcuhABnGjpZa/0W8BZAbGysbsE4hRCdRM1YhdJdu6juFYqfpxvX9a7Ef0gVnNwEwC768ZPvNUwoz2LISduSzuYumZSFZ0n3Qz1PbH8i/Fj+sWYtb93bv3fp06OfbrKolcViYcCAAf1SU1Pdbr/99jNXX321tC60sJZMGFKBkUopT2xdEuOBBKAEuB1YbP+5tgVjEEKIsxIFAM+YcFy9nXB2KcLf/wAwhqyAWF7KGszuyCAGW6wMSY4AbGsq3DfjltYLXjTI2dmZpKSkQzk5OYYpU6b02rVrl3tcXFx5a8fVkbXkGIadSqnVwB7AAvyErcXAG1iplLoTW1IhHYFCiBZRM0WydnrkkD44eznjXJ1Jfrk3Jm9fdvZfwIt5o9iZngfARHMCEcljAVuycNuM61ot/rbOkZaAlhYYGGgdM2aM+bPPPvOVhKFltegsCa31k8CT9TZXYGttEEKIFlHTolA7RdI+RsHZpQwqcgBwCwhka5fLeXR3BC5+XzLGXxOdH0MXe7Ig5afbrvT0dGdXV1cdGBhoLS4uVps3b/Z5+OGHM1s7ro5OVnoUQnQ4NdMknXqFEtilC7PnjYF1DwL8MvshayQunjsZ45VJj9xutcs6m7tkEjrUW5KFNuzUqVMuc+fOjbRarWit1fXXX5938803S2nrFiYJgxCiQ3KPicE9yAmKM2uThbd8/8Df00fi4reTMf4/nJUouHSrYvQVA+g/VmpAtHUjRowoO3z48KHWjqOzkYRBCNEh1JSftpzJpjIvDSejkcL0KgLdijnoOpAPSoazukIR1OdflDodocfB++la2qNOoiAtCkI0RhIGIUSHcGDNKnJzzmAsLgUg2+CJr0sunkZY1OV58rtuwd3lA3pkXc5lhX/Bp6IrIZEBTP/zZa0cuRDtgyQMQoh2Lz9+JZUpKRiBqwPCiPfpS5kpjx7GzazyC8Yz7C30fhficu6v7YIIsReMEkI4RhIGIUS7VLdgVOmuXdArlPLgMP53+O/pl/EJT/IW87y6csLVidEpUcQeHwlIZUkhLpQkDEKIdmfH4mdI2mpbmdHq6YXu24NSVyc8rVk8lPYQp3xTmefVlWQvX0aX3EDEXluyIFMlhbhwkjAIIdqdI3sTKPJwxdvTA+1Ugo8qwQdID3biHz0q2e/chb5Zl3PdqSsx5gYDkiwIcbEkYRBCtBs13RDVJSX4Omvm9vylBPWWmEH8K2MDABPLbiZCuiA6PIvFwsCBA/sFBwdXbtq06Vhrx9PRScIghGgX8p/7I5n/+hoAp5hgnN2qec6rNzuD/fExhZNgTxYWXL4A5896kU6BtCp0cM8880xQ7969y4qLiw2tHUtnIAmDEKLN2vHIPJKPnUIDVGroFYrV24lCgwt5PppPu+ZBdRaxhBMbFMvknpPplzWKzUeTCY3yk2ShA/v5559dvvrqK9+//OUvGUuXLpXpLpeAJAxCiDYnP34lRR+/TVKVlSIPV4yWKpSroszDC2tIT0osKaQEFZyVJBz5MQsOwuajyQAyZfISSP/r38Irjh5t1vLWblFRpaF//78mi1rdd9994c8999zpwsJCaV24RBxOGJRS/kAotlLVKVrr6haLSgjRaeXHryTzSVvNOqeYYJSzC19NWED8PZfXHjNv/Txc8eNhr2c48llWbZIQGuUnYxY6gY8//tg3MDDQMnbs2NJ169YZWzuezqLRhEEp5QvcB9wMuALZgDsQpJT6AXhda72pxaMUQnR4NQMaS3ftAiA4toB898HkGwK4fkgYq46s4ovjXwBgPWikX95INuf+kihIknDpOdIS0BK2bdvm/c033/iFhYX5VlRUOJWUlDhdf/31kWvXrj3RGvF0Fk21MKwGVgBjtdYFdXcopYYBtyqlemqt32mh+IQQHVxtKeqfk0j3N0LfMJzdLFS59sDZqjF1qeCb/CdJSEoA7DMgjsoMiM7stddeS3vttdfSANatW2dcsmRJkCQLLa/RhEFrPaGRfbuB3c0ekRCiU6kpRZ3WvQslzpqunsWUKG+sHoHg7cYm70McySpmYtnNROUMo+q0CyDrKghxqTk0hkEppYDZQE+t9SKlVHcgWGv9Y4tGJ4TokGqXdTZnUnb8NNX+Brx8zHgBEZOnM2Lmn1l1ZBWLdiwC4BGv/8O8w5sqpFVBnG3q1KnmqVOnmls7js7A0UGPrwPVwNXAIsAM/AeIa6G4hBAdzDm1HwBPUwUevpDTza+2VaF+smBbV6EbZllXQYhW5WjCMEJrfZlS6icArXW+Usq1BeMSQnQQ9QcznozwIysmGGf3aio8PShy8sPgG0JVTgrFziXMWz+PhCzbeIVHvP4P58+6kXO6WNZVEKKVOZowVCmlDGBbP0UpZcLW4iCEEA2qnyjoIGdCwnPY79KFgnJPPAP88enaDS8guzSbDE8zxwNL8MGvdryC+bQLZgpquyGEEK3H0YThFWAN0FUp9X/ADODxFotKCNFu1U8UnENdCQw9g3/vUg66DoS83gQbg5n15GIADm5N47P13+FqNHOtisB00ET60QIZryBEG+NQwqC1/lAptRsYDyjgf7TWh1s0MiFEu1F/fEJqgJHMft1wdq3E2cOKmWCKT/tj8A1B5aVjsi+1s2L1p5g3eGMkGLqAycMESKIgRFvk6CyJl4F4rfVrLRyPEKIdqpka6R4Tg2dcHJnWLIq0wsvDgzTtQ4lrIP1CfWwH+0RS4OHP4r99VFt6OmXIDwy/Oorp0Ze14l0IIRrj5OBxe4DHlVLHlFLPK6ViWzIoIUTblx+/kpO33sbJW2+jPCmJwrBI/nfM7/nqsh64u5Xg7qb5asST7B75EH3ueIxZTy7G6eZhJAT5YDkehzE3GHOXTIzXFPP8/L8yM3pma9+SaCfCwsIGRkdH94uJiek3YMCAvg0d86c//Sl0wYIFLTLw5ZVXXumSkpLi0tRxycnJrlFRUf2b63VnzZrVY/fu3e4Xe51XXnmly2233db9157naJfEe8B7SqkA4EbgWaVUd6111K99QSFE+1e33oNnXByFYZEkelh5KO0hRjodJp6B4GU6q/5DzVTJ647fD4DxmmLum3FLq8Qv2r/vvvvuSEhIiKU1XvuDDz4IHDJkSFlERETVpXpNi8VCfHz8yUv1eg35tdUqewMxQARwqNmjEUK0WXXHKST9nER6r1DKg8OoUJV4GQrwUSWcPOXMSbcxZFtdMXXtBlBbA6JkvwvX5dxPWEUvQqL8mD7j6ta8HdFJPfHEE0Fr1qwJqKysVFOmTClYunRpOsA111zTKyMjw7WiosJp/vz5WQ8//HCOxWJh1qxZEfv37/dSSunZs2fndO/evSoxMdHztttu6+nu7l6dkJBw2NvbW9dcf+vWrZ6/+93vIjw8PKpHjBhRXLPdYrFw3333ddu+fbuxsrJS3XXXXWceeeSRnHXr1hmfeuqpUH9/f8vx48fdR4wYYX7//fdTDQYDnp6eQ+++++6sb7/91uf5558//cQTT4S98MILp3bs2OF14sQJtzfeeOM02FoMdu/e7fnee++dev311wOWLVsWVFVVpS677LKSFStWnHR2dubll1/usnTp0hCTyVTVq1evcldXV33uu9M4R8cwPAvcAPwMrASerl9bQgjRMdWf9eAZF8epsGAKDAqLpYxIpwxQUOlsxNU3CIzBmIDS3kbmrZ9HyX4XonJGElpka5AMkSmSHcbGFYfD89KKm7W8dUCYd+n42/o2WdRq/PjxUUop5s2bl/3www/nOHLtTz75xOfYsWPu+/fvP6y15pprrun95Zdfek+aNKn4ww8/TAkKCrIWFxeroUOH9pszZ07+0aNH3TIyMlyOHj16ECAnJ8cQGBhoXbZsWdcXXnjh1Lhx40rrv8add94ZsXTp0tQpU6YU33PPPd1qtr/00kuBvr6+1sTExMNlZWUqLi4uZtq0aUUABw4c8Prpp58So6OjK8eNGxe1YsUK/3nz5uWXlZU5DRgwoOyll15KB3jiiScAuPXWW/NHjhwZA5wGWL16dcDf/va3jD179rivXr06ICEhIcnNzU3PmTOn+xtvvNFl2rRpRYsXLw7dvXv34YCAAOuoUaP6DBgw4JzYm+JoC8MJ4HKttUP/U4QQ7V9DiYLP1Kn4z7qJ4t/9Fj9rPr/rsdl28NSXIHbeWefPWz8P60EjVxz/H0BmPojms3379qSIiIiqtLQ056uvvjq6f//+5ZMmTSpu6rz169f7bNmyxadfv379AEpLS52SkpLcJ02aVPzss88Gff75534AmZmZLgcPHnQfNGhQ+alTp9xuv/328GnTphVOnz69qLHr5+bmGsxms2HKlCnFAHfccUfut99+6wuwYcMGn6SkJM9PP/3UH8BsNhsOHTrk7urqqgcOHFjSr1+/SoCbbropb+vWrd7z5s3LNxgMzJ07N7/+64SGhlrCw8MrNm7c6NW/f//y48ePu0+YMKF48eLFpsTERM/Bgwf3BSgvL3fq2rWrZcuWLV4jR440h4aGWgBuuOGGvCNHjvzqsRBNlbeO0VonAT8C3e01JGpprff82hcUQrR99cco+EydypcRI1m7N43xS58gxHradmCPMTBwxlnJwsGtaWz/LpHQol9aFWRJ547JkZaAllAzdiAsLMwyZcqUgh07dng5kjBorXnwwQczHnnkkbO+/K5bt8743XffGRMSEpKMRmP18OHD+5SVlTmZTCZrYmLioTVr1vi8/vrrXePj4wNWrVqV0tj1baWXGtynlixZknrjjTeelXSsW7fOWP+cmueurq7Vzs4N/5meMWNG/scff+wfExNTPmnSpHwnJye01mrmzJm5NZU8a7z//vt+54vr12hqlsSf7D+XNPDfCxf96kKINqlo3TpSA4zsGT+KH3qH8sGPO0h9/c9cs+MpfPdvIrvcmyLPCJj3OcTO4+DWNNYs2cNbz3zF5g+TaytKunSrkmRBNKuioiKn/Px8p5rHmzZt8hk0aFCZI+dOmjSp6P333w8sLCx0Ajhx4oRLWlqac0FBgcHX19dqNBqrf/rpJ/d9+/Z5AWRkZDhbrVbmzp1b8Mwzz6QdOHDAE8Db29taWFhoqH/9wMBAq7e3t/Wrr77yBnj33XcDavZNmDChcNmyZaaKigoFsH//freioiInsHVJJCUluVqtVlavXh0wduzYJotpzZkzJ3/9+vX+q1atCrjlllvyACZOnFi0bt06/7S0NGeArKwsw5EjR1zHjRtX8sMPPxgzMzMNFRUVas2aNf6OvF/1NVXe+m77w0la6/K6+5RSFz21QwjRttR0Q9SUmzbnZWIsS8O9WtPVqcR2kJsvpi4mfHtdy5oltkbG9KMFtp8+KeADlT1zGX51FDOjr22dGxEd1unTp52nT5/eG8Bqtaobb7wxd8aMGQ12FSxdujTkzTffrB0wk5WVtf/gwYPucXFxMQCenp7VH3744Ykbb7yx8K233jJFR0f369WrV/ngwYNLAFJSUlzuvPPOiOrqagWwaNGi0wC33XZbzgMPPNDjkUceOWfQ4zvvvJNSM+jx6quvro3roYceyklJSXEbOHBgX621CggIqPriiy9+BhgyZEjxn//8525JSUkeI0aMMN96660FTb0PJpPJGhUVVXb06FGPq666qhRg2LBh5Y8//nja+PHjo6urq3FxcdGvvPJK6vjx40seffTR9JEjR/Y1mUxVgwYNKrVarb+6yUFp3fRASaXUHq31ZU1taymxsbE6ISHhUryUEJ1S/fEK5phB7HfLw9OjksHRVgACvd0IGjWHg2W/4ciPWbVJgrlLJgB7fDdzOGgHCy5fIGsqtBFKqd1a62ZdN2ffvn0pgwcPlvFszWTdunXGJUuWBG3atOlYa8cCsG/fvsDBgwdHNLSvqTEMwUAY4KGUGoptWWgAH6BZR8YKIVpH3fEK5phBbA4bQr5fNkPS06h0NtL/r1+edfyRJXvISM0j3ednjgbuxmuQbSq6F7CgpyQLQnRUTc2SuBaYC3QDXqyz3Qz8tamLK6X8gLeBAdgqXd4BJAPx2NZySAFu0lqfMwpUCNGy6rYqpAYYOd43hkJLGV1KNtOjtITscm9MYbbW3JqBjHlluXgUBnDG8ySf9n9VWhOEuEhTp041T506tckxC21BU2MYalZ4vFFr/Z8LuP7LwHqt9QyllCu2Vom/Ahu11ouVUo8BjwGPXsC1hRAXqP4siOOukF9ajMmtBKNTBbiePU7B1v3gQqlvGfjmURmeK8mCEJ2Mo0tD/0cpNQXoD7jX2b7ofOcopXyAcdhaKNBaVwKVSqnrgSvth70HbEYSBiEumbrJQvDChfj3KsHt9XhMbprbex/ENWwwB3u/xZEfs/h5XwFQgLlLJocCfsDQ38zyictbNX4hROtwdKXHN7C1DlyFrYthBra1GRrTE8gGliulBgO7gT8CQVrrDACtdYZSqut5XvNu4G6A7t1/dY0MIUQd9ctPAwTf8Rsqs96Ewwl46YHk62A+L/w/sJhI35kM2AY01gxmjA2KZXLPya12D0KI1uXoSo+jtNaDlFL7tdYLlVJLgE8cuPZlwANa6532EtmPORqY1vot4C2wzZJw9DwhxLlqy0+H+eEZ7s7xMB/2H94NQK51AmWV1ShDIOnmcEKD/XBxzmaD639qEwUZzCiEcDRhqFkUo1QpFQrkApFNnHMaOK213ml/vhpbwpCllAqxty6EAGd+bdBCCMflx6+kdNcuPGPC6THE9nH8OmUkJeUGtFsg2uqJMoBrUBQp0T+QEHGUhCzbNGYZpyDaouTkZNepU6dG1dR4AFs5a29vb+uiRYuyGjrnlVde6ZKQkOC1YsWK1EsXacfiaMKwzj7j4XlgD7YZD283doLWOlMpdUop1UdrnQyMx1bh8hBwO7DY/nPtBcYuhGhEfvxKjn78H4xJ+wHw8T4AwDPmhbhVJ+Hs7oSr2wxwh5QhP7De410AYomt7X6QZEEIUcPRQY9P2x/+Rym1DnDXWhc6cOoDwIf2GRLHgXnYlqNeqZS6E0gF5F8kIZpR3emSRsDTVIFPjzLS+/VilcdVmBhO2ZlkUNZfxih47JAkQXQIw4cP7zNs2LDibdu2+ZjNZsMbb7yRMnHixLPqTPz73//2Xbx4cciXX3557P777+9mNBqt+/bt88rOznZ5+umnT8+bNy+/urqa3//+992+/fZbX6WUfuSRRzLuuuuu/Dlz5nSfNGlS4ezZswsnTJjQy8/Pz7pq1aqUpUuXBp44ccL1vvvuy5k0aVLU8OHDixMSEryDgoIqv/rqq2N1V4Nsr5pauOmGRvahtW50HIPWei/Q0Cpj4x2KTgjxq9TMgEgNMJIWE4aLuwWMHrj6BlGSHUCVOZ+qivfR1mzMAVbW93+VPgF9ZIyCuCBfLXspPOfUyWZdxC8wvEfptb9/8KKKWlksFnXgwIHD8fHxvosWLQqdOHHikZp9K1as8Hv55ZeDvvnmm6Mmk8kKkJWV5ZKQkJC0d+9e9+nTp/eeN29e/ooVK/wOHDjgcfjw4YMZGRnOw4cP7/ub3/ymeNy4ceYtW7YYZ8+eXZiZmel65swZDbB9+3bvm2++OQ8gNTXV/YMPPjg+atSok5MnT+65YsUK/3vvvTfvYu6pLWiqhWFaI/s0TQ98FEK0sIZmQCSFB2FwqsLX24Uq774UFVRSUVYKgNW5EounK8lBGfQJ6CPTJEW7c77KizXbZ86cmQ8watSokkceecS1Zv/3339v3Ldvn+emTZuOBAQEVNdsv+666woMBgPDhg0rz83NdQHYunWr8aabbspzdnYmPDzcMmLEiOJt27Z5Tpgwofi1114L2r17t3t0dHRZQUGB4eTJky67d+/2+uc//5l65swZ57CwsIpRo0aVAQwdOrQ0JSXFreXejUunqYWb5jW2XwjROhpKEjzj4igICcQ9rIRgl3xKrP54h/2e9Ex3cIbKiJopkruIDYrFlQiZJikuysW2BFyooKAgS/1qkXl5eYbIyMgKAHd3dw3g7OxM3SJL3bt3r0hNTXVLTEx0HzduXGnN9prjwVaiuu7P+iIjI6sKCwudP/vsM9+xY8ea8/LynFesWOHv5eVV7e/vX33mzBlcXV1rTzYYDLqsrKypytDtgkM3oZRa0NB/LR2cEKJhNdMkwZYolF03huK+x/GJCyLFfy4Z1t4UWMNIz3Qn3eco3/X8N8ljv8FrUBULLl/A8onLWT5xuXRDiHbJ19e3umvXrlVr1641gq2M8+bNm32vvvrq4sbO69atW+V//vOfY/PmzYtMSEhotOLyFVdcYV69enWAxWIhPT3d+ccff/QeO3ZsCcCwYcOK33zzza7XXHNN8ZVXXln82muvBY8YMaLR1+4IHJ0lUVLnsTswFTjc/OEIIRpTt/x0YVgkC8b8nrEnVmDKOkBJpj8F1kDgEFZrAVZXXzKG/EBOxFFmymBG0cG89957J+69997ujz76aDjAo48+mt6/f/+Kps4bPHhwxYoVK47PmjWr16effnreCpG33nprwffff+/dt2/f/kopvXDhwtPdu3e3AIwZM6Z469atPgMGDKioqKioLCwsNIwbN65d1IO4GA6Vtz7nJKXcgE+11pek2L2Utxbi7CWdU7r1IcPkTL+o0/yYGkRlucLJEAxAofsZDN6a8OGxzJv9t9YMWbQyKW8tfq0LLm/dCE9sSz8LIS6BusnCjqH96Rd1mmLfVN708qJPSh9cDK5URowjNzyF4VePl9YEIUSzc7SWxAFssyIADIAJOG/hKSFE8/hoZyqnV3zItI0rSA0wcircF6N7JidPOXM87XJiqrxxrjRj8DTx5/+7pbXDFUJ0YI62MEyt89gCZGmtLS0QjxDC7qOdqfx1zQGW77PNhsjp7kG5MlDqFEKFxQu3StuYLTdvI72GjW7NUEXnUl1dXa2cnJza/UJE4mzV1dUKqD7ffkdXejyplPIHwu3nBNkXbtrTPGEKIcCWJKzdmwZAwKYvePbUHkLM+XgEWXH286Za+2NQd+DpYqskGTrUm9tmXNfKUYtOJjE7O7ufyWQqlKSh46iurlbZ2dm+QOL5jnG0S+JpYC7wM790TWjg6ouMUQhRx9q9aRzKKKJfiA+3ZW3G35zLmciRZIWOJqPiR6orFAYjGK8p5r4Z0gUhLj2LxfK7zMzMtzMzMwfg4NR80S5UA4kWi+V35zvA0S6Jm4BeWuvKZglLCFGrbqtCyNb1zM3cR78QH37w6k5CUCRVBlco2oXVmoXV1ZfAa4qlVUG0mmHDhp0B5BewE3I0YUgE/JBS1EI0u9MrPmTm/u14uTkTcToZgJM+V5Lmq9HWbKoMijIXMwZvRfjwaEkWhBCtwtGE4f8BPymlEoHahTG01vIvlxC/Uk2LwrD9mxmYvJNp9iTBM9ydk9EjOBYynDIVA+aVFHlpPhm3hwWXS3EoIUTrcjRheA94FjhAIyMohRCNq5n5ADA3eSfdzhyvLT/tP/4y9hy6CnOZiVyvE3joIgzuWpIFIUSb4GjCkKO1fqVFIxGig/toZypbl/6TZ0/tIdLkjW9eCu6+xfQYn8vB3m+zKsWHsjJNrlcaxaHf4JtSTM9+AyRZEEK0CY4mDLuVUv8P+JSzuyRkWqUQTfhq8RtUb1iPoayKP+QeB8DT0x28ijjTayRfWf6Hqm1dADjjc5TKyFx6nvCigmL6jr6yFSMXQohfOJowDLX/HFlnm0yrFKIRdVdpBFv9B0tEMN0Ck0gPHc12PZkqcwTkQLrPUSp75jL86ihmRt9D/MLHoJ+JQddMbN2bEEIIO0cXbrqqpQMRoqNZuzeNmfu3A3DgxgW4BPThWOYBdliKqSrqC5ybKAghRFvl6MJNCxrarrWWehJC1FF/TYX+2T+TfflssnODILcAs3cZZhdncDmKwf0gIRUlmLJMVH+8m3h2114nO+UEpojI1roNIYQ4h6NdEiV1Hrtjqy1xuPnDEaJ9W7s3jZCt67k2cx8u1kD2DPkjBW7RAHzX898cDtpBrGc3Jg++g+qPPck+kwURpnOuY4qIlPELQog2xdEuiSV1nyulXsA2AFIIwS8DG2dWWOif/TNpIaNJ7mNbutnslcwh0x68Ik+zYPAvUyTj2Y0pIpJZTy5uzdCFEMIhjrYw1OcJ9GzOQIRor75a/Abd330ZgIKQQJxDXcnvczloSOn2Adu7JdDHK4zlM79s5UiFEOLCOTqG4QC/FJ0yACZAxi+ITqtmBsTA5J21yzmXXTcGH/JJLJtJdnUI6V5HWR++i9igWMbl9rbNfKhDxikIIdoTR1sYptZ5bAGytNaWFohHiDatJlHosXcb0+xrKhSEBFIVPYTcsijSqwYAttkPRwN3167SGL/wsXMSBBmnIIRoTxxNGEKAg1prM4BSylsp1V9rvbPlQhOibag782HniTye3buN6OIMLBHBlPceTKbqaUsUqsAlMIcNPhs4HLTjnCWdZbyCEKI9czRhWAZcVud5aQPbhOiQ1u5N41BGEbdm72Fu8k56lJzGq6sTxYO68GORrf5aaHA55gEWni95GkDqPwghOhxHEwalta4Zw4DWulopdaEDJoVo0+q2KAC1yULNio3Z0SM4GBRLerYFa+VK/Lp6klZWyMmNJ5lIED18elCdIusqCCE6Fkf/6B9XSv0BW6sCwL3A8ZYJSYjWUZMo7DyRx6SUH7gu50DtvpqBjcXXXMsBi61VwVl/Ak65ePn5cTovD4AePj0wecq6CkKIjsfRhGE+8ArwOLbZEhuBu1sqKCEutbplp+8172fa3tUAeMbF2Q7wDsenRxmbiQYLXDm7D5vWlVFYbmHviCyS87LoE9CH5ye+01q3IIQQLcrRhZvOAL9t4ViEuOTqtioAvOl3iu7/tXU9BC9ciP+smyBhOax7kIOlE0gvisElMIcXSt4nsOiU/Sp+9Anow+Sek1vpLoQQouU1mjAopR4HXtda551n/9WAp9Z6XUsEJ0RLqZ8ojIgM4I78fbULMAVfG4h/6Xuw/D04uY2DpRPYkD0Ga+VKzlSdIXBtEaZiDzxDu0qrghCiU2iqheEA8JlSqhzYA2RjqyURBQwBNgB/b8kAhWhudbsfRkQGcP2QMG4Z0Z2Tty6jFAiOLcDfP52DZ37PkZy+wE2km8OxVq6kSqdR6lpmG6sQbJJxCUKITqPRhEFrvRZYq5SKAkZjW4+hCPgAuFtrXdbyIQpx8eqvpQDw9+kDmZTyA0WvLuPkq1CelIRnuDv+vUs52PttNm/rAoC5SyZmn6M4V53B4O3M8PvukSmTQohOx9ExDEeBoxfyAkopA5AApGmtpyqlAoB4IAJIAW7SWudfyLWFcFTNWgr9QnxqWxUmpfxA5pNPkhpgJDMsEMJ9Mbt7U3Z8EIajGwEodD+DoVjjBnhbICygjyQLQohO6VKspfBHbKWwfezPHwM2aq0XK6Uesz9/9BLEITqpj3amsvNEHvea9zPrZ3tV9m2QuWsXADk9AyiwOOHsFkyl9sJgBatzJRb3ckx+/r9MkwxAuiCEEJ1WiyYMSqluwBTg/4A/2TdfD1xpf/wesBlJGEQL+WhnKluX/pNnT+1hUO5xSgHPmHAoySY7egRZQbEUVOzGanDD2fsmcn2OUtkzl+fn/7W1QxdCiDbF0WqVo7XW25va1oCXgP8FjHW2BWmtMwC01hlKqa7nec27sa/10L17d0fCFOIsXy1+A8Nnn/EHe5Eoz7g4fKZOtc1+yMxlT95VFFSEgU7CqbqK73r+u7YGhBBCiLM52sLwD86tG9HQtlpKqanAGa31bqXUlb82MK31W8BbALGxsbqJw4WoVVNRctrGFXQHzDGDiBoVjL/pGPuT3+PrlBJK1EgKynfg5uGMtmZT5FPJ4aBjUgNCCCHOo6l1GC4HRgEmpdSf6uzyAQxNXHs0cJ1SajK2qZg+SqkPgCylVIi9dSEEOHPh4QtxtppWhZrS06lz/8i1j82H5VMg8wCH0weSWe6DVQUAUGTIo8qrkuSgAmKDYiVZEEKI82iqhcEV8LYfV7dboQiY0diJWuu/AH8BsLcwPKy1nqOUeh64HVhs/7n2QgIXoq6aaZM3fPYZPQvTba0KN99I314lsHwKB48GcKTqaXIsu7AqC27Gm+xdEAeIDYrFFT9ZqVEIIRrR1DoM3wHfKaXe1VqfbKbXXAysVErdCaQC8pVOXJC6aysEbPqCG07tIbo4g6re0Qz/bzwHP1jF5vfMwLWkVw2wn7ULJzd91ngFaVUQQoimOTqGwU0p9Ra2tRNqz9FaX+3IyVrrzdhmQ6C1zgXG/5oghWjI2r1phGxdz7WZ+3AqTSfd38j+8O5Uubuw67Z5VFjdAHBzrQbDETyMrpQWyHgFIYS4EI4mDKuAN4C3AWvLhSNE02paFkK2rueehJUA/DikD4VOTri4BVJR6QSAm6ECD28nvIJMZJdmc7o8DXyQ8QpCCHEBHE0YLFrrZS0aiRBNqEkUarofBtkHNgYvXIj7ri9wOaNwdZ9GqPcJokeE0H+OLSFYdWQVb+5YBCDjFYQQ4gI5mjB8ppS6F1gDVNRsPF8VSyGaS0PjFAbVWVfhzGU3svmwCzmZVqq0O6HeeUyfZYTYmaw6soovjn9BQlYCgHRBCCHERXA0Ybjd/vOROts00LN5wxHiF3WrSt5r3s+0vauBXxZgSg8dzff/WoW1MgllNePq4UH0ddewyud7vlg/rzZRiA2KZXLPyZIsCCHERXC0+FRkSwciBJy/quToV+M5GjKa/BEzcTaZ4DSkb0rGWpmEwXqaYD9N3xk3cCjoexbV6X6QREEIIZqHo0tDe2KrBdFda323vdx1H631uhaNTnQqdVsURkQGMCIygDvy9xHzajzHcnxI7nMDFECovRZUaHA5+aVpeLkW4HRDHEst8STskO4HIYRoCY52SSwHdmNb9RHgNLaZE5IwiGZT07Lw9+kDuWVEd3YtXcuRvbCNURT0iAbgyjG59K9aYjvBvI14w0Do0psvqgtIzkuWVgUhhGghjiYMvbTWs5RSNwNorcuUUqoF4xKdTE0J6hGRAQyuNLDqsa84U2AEPyNd/aoIdS8n2mML1l1riC8ygZsvMIZsqysYDCRk/UhsUCzLJy5v7VsRQogOydGEoVIp5YFtoCNKqV7UmS0hxIVoaLzC9UPCOLQmkbycKvyKTxAdmERcn6NwchuUQXyFLUkwhfQhuzSbPLc89nkfApCpkkII0YIcTRieBNYD4UqpD7EVlprbUkGJjq/+eIV7zfu5Mm0vQa+6sa1qFN7AZOeF+AeWAmOgxxgYOAM+T8YEON087Ky1FRZIN4QQQrQoR2dJfKOU2gOMBBTwR611TotGJjqsusnCm36niNkWT+muXaSFjOZn09UUe/gRoI/jH1YKU1+C2Hm/nPz5Y2SXZtcmCzK4UQghLg1HZ0lMB77VWn9uf+6nlPofrfV/WzI40fHUTRb+Pn0gMa/GU56UxMG4a0itroLSLbipEsxOBcQXT4fPk2uThLzyPNzzLGR7lwGSLAghxKWktNZNH6TUXq31kHrbftJaD22pwOqKjY3VCQkJl+KlRAs6p2Xh4Pccy/HhTLdRZJRuQVuz8XetxMuzmmw3T/Kw1J5rrjQDYHQ1UtDTjcsn3SjJghBNUErt1lrHtnYcomNwdAyD00WcKzq5msGNO0/kMSnlB+aVH8GYtJ9S4MzYJzC7dcWtogIPQyV3/OEGiJ3HvPXzSM5Lpk9AH/tV/GS6pBBCtCJH/+gnKKVeBF7DNlPiAWzrMgjRpJrKkssy9xFxOtk2VmHsEzh36UJxhQcm32IqS47apkrWGa/QJ6CPTJMUQog2wtGE4QHgCSDe/vxr4PEWiUi0e3WnS8b++G/G5v6MV1UZmW5waugQip2cbWMVtDNYK8nPzaC0yht8PJm33pYwnN26IIQQorU1mTAopQzAWq31NZcgHtGO1e16AFvBqMDMRAo8PTF7dMfJ1ZVKi229Lz/3PLycS8BaCAYo9Q9hU+BpjmQVExsUS5+APrKughBCtCFNJgxaa6tSqlQp5au1LrwUQYn2p/66Cnfk76P7f1fwQ69QXDxDcQuYTWA3bzBnEl36L/p7fgM9xrAKA194e5JQmgTIzAchhGirHO2SKAcOKKW+AUpqNmqt/9AiUYl2pSZZ6F90iKkVB/BMKSLdbCa9VyiFvr5UWxRhvsVMD3gWzNvAE1aNuoMvqgtIyEqF0jypASGEEG2cownD5/b/hDhL3ZaFiR7pVOXmU11WgZPRSJW3ieoyAwbXGKJL/wUnt7GqxxBbi0LGBkBKUAshRHvh6EqP79lrSXTXWie3cEyijatfA6JmquRh9wrKLK64B92Me5gf6ZnuuBnhSp/XOdQ3mxe8R5FQelpaFIQQoh1ydKXHacALgCsQqZQaAizSWl/XgrGJNqihGhDT9q4mLWQ0RZ5eVLm7YjUEE5qbSKgLRHdLp//4KbyQs0XKTwshRDvmaJfEU8BwYDOA1nqvUiqyhWISbdjavWnMOrGOqOo0XFKcKKtQfDM4DouzM9qajbt3CFdGfk3/smUw9SVW+QzjheNf1E6TlHUVhBCifXI0YbBorQuVUnW3Nb2mtOhQPtqZSsCmL4gpPkKBpyfOTgFUeboC4OZajYeTgdjuJ+hffcA2ViFnCwkHbUt617QsCCGEaJ8cTRgSlVK3AAalVBTwB+D7lgtLtDUf7Uxl69J/8oe9q3+ZKuk7k25uaUQHHra1KACEj2EVkSxyyoMsGasghBAdxa9Z6fFvQAXwEfAV8ExLBSXajq8Wv0H1hvUYyqr4Q+5xAKymECqrFGH6ENO9noCuY1iFbfYDxq62qZLImgpCCNGRNJowKKXcgflAb+AAcLnW2tLYOaL92b9hPYe3b659fqaogpziCgACs07i4V5JlY8b34UNwOLiRUW5GWXwJrpbOquG1ltPwRgsrQpCCNEBNdXC8B5QBWwFJgF9gQdbOCZxiR3evpnslBOYIiI5U1TB8Rzb2lxhlmK8q8op8zahPX2oqLQVLXV3VfTqE86h6dEs2rEIkPUUhBCio2sqYeintR4IoJR6B/ix5UMSrcEUEYl14r0sWXOASRW2dRWKCo1kBc2k1C8agEjvRKJHhNB/ji0pqCkUJV0PQgjR8TWVMFTVPNBaW+rNkhAdwEc7U0lOLwLgzNJ/8uypPXRxDeFo0FUUBNsShVCXRPt6Cn0gdiarjqziC/tUydigWEkWhBCiE2gqYRislCqyP1aAh/25ArTW2qdFoxPNqv5YBYDk9CK8C9Jwr3Yn2jAIS3gYyX4NJQqLbYnC+nkkZMlUSSGE6GwaTRi01oZLFYhoeXXHKoBtcKNHYTFu+FLtfRkFbtF0VScIdU0iOjS1NlEAWHVklYxXEEKITszRaZWigzBFROLnFkH1hvVQVoUlfBrFxm4EBLrQb0Au/Y/9CXqMgXm2WmM13Q81rQoyXkEIITqnFksYlFLhwAogGKgG3tJav6yUCgDigQggBbhJa53fUnGIX9RMl+yZloIyTabK1Z0qt0C6GDKY2ecTOLbNduDAGeckCtKqIIQQnVtLtjBYgD9rrfcopYzAbqXUN8BcYKPWerFS6jHgMeDRFoyjU3v7nx9xKsGWCHgWZmJ0CqC4228ACI3yg8wDRLtsZhXFfBERBV4maGBJZ0kUhBCic2uxhEFrnQFk2B+blVKHgTDgeuBK+2HvYStoJQlDM6spQR29bTM+VTkYDAFg6IrBNQa/giNEByYRF3AUKg9A8EBeCOlpKxBlDAYkURBCCHG2SzKGQSkVAQwFdgJB9mQCrXWGUqrrec65G7gboHv37pcizA6hJlEoSyqkb6UB/2onMHQlyDoEgPDCfQz0/C/+gaXAGFYFR/KFd7VUkxRCCNGoFk8YlFLewH+AB7XWRY6u5aC1fgt4CyA2NlYqYzpg+YoDJO3MZFhFEV7O/gBYLaW4VpoZoz/haGAyy2NdwT3M1vVQU/ehNE+mSAohhGhUiyYMSikXbMnCh1rrT+ybs5RSIfbWhRDgTEvG0NEd3JrGkR+zACg9WkB3DDhXHKDCfAJ3p0qsugijl5UfhyayKLALALFBA2vPl64HIYQQjmjJWRIKeAc4rLV+sc6uT4HbgcX2n2tbKobOYNvGk5Rnl6OsRbiXFOJbcoRSyy4q3F3w9YVKSzG7Q0v4xp4syLRIIYQQF6IlWxhGA7cCB5RSe+3b/ootUViplLoTSAXkr9cF+GhnKjs3nCQ6s4oKSz7Ttj0OgCUimD2eznRxKsYp6ihv1rYqSEuCEEKIC9eSsyS2YVtCuiHjW+p1O4OPdqby738f4toyVwD6lRwAIO3e6/jQZyORO3zByY1V0qoghBCimchKj+3I8hUHSN+fS1FZFddabclCUMkaskuSyR0YycnDPxGk/XAvdqU80E1aFYQQQjQbSRjagdruh1NV+AHBZRm4V5QSlJVAWlAOZncXujgVQ7UBTydneoR0pe/E3zLomomtHboQQogOQhKGNq5mqmS01VYHrE/yR4RlbMczLo6j40o5eaYUqi38NDSdZC9f+pgGskDWUhBCCNHMJGFog2paFLrmW/HO3UtQZVLtegppQZqsfqPIdy7i5JkCAopcqfIBuvSmjzFY1lIQQgjRIiRhaGMObk3jxNrjRBdXA2At3YOqzsfXYKAs0JWTriVQfQpzpW2/MdCLcdPulO4HIYQQLUoShjbko52pnFh7HI8SK1bM9EtexynPNFwjIpg9bwzzEl8jubqMPpWV4O7L5NCxzPzN0tYOWwghRCcgCUMrq6n9AFCWVMi1Za4UeBuYcOxjjBn7OTayN6eqTzEv4e8ku7rSx8mD5bEPQ+y8Vo5cCCFEZyIJQyupXyTKx8MF74IkKiqTCLJYOViVg1O/bhRVWSh1t4K7L328TEwefAfINEkhhBCXmCQMl1j9RKG7fT2Frs4VZFbsR1tzMWQUA5DjWU2esYrKCDeWz01ozbCFEEJ0cpIwXEI1UyQj4JdEwa+KoKxdmP77IcW9QrF6OBNamcmX/WHjUCepIimEEKJNkIThEqhZodGvuNpWTTLYnYByc22iAJDay0heFxcyvSy8PM2JWO3GghAZ1CiEEKJtkIShBdVfobHA24kotwxG/Pwlpbt2AfBDbyPp/kas3gbcixTG6moWhFwjiYIQQog2RRKGFlJ/PQXPUSZucTtM5pOLKAUOdodt/ZwIqDLhnW8lrLwYjL70jRvNoN883brBCyGEEPVIwtAC6q6nUOBt4H+uj+JQ0Pf8+NALdAfenOhE4cThTHbyo/rjXeAGs+67U6ZKCiGEaLMkYWhGNTMgdp7IY1aZK3i5EDmzJ6Ep2zm9+AUCTxeT2svI6HsfYWZRMax7kHgGQpfekiwIIYRo0yRhaCYf7Uzl3/8+RN9KA4M8vPA3gMm5guGvPk7mrl0QYOTH3mH4eBhwfvFd4isKgYFkW02YjMGtHb4QQgjRKEkYmkFNsnBtmW2qZGiID/lpx/HfuZ7SjF0c7A7JQUY8rAYCXIoBX3DzBW9bstB39JWtGr8QQgjRFEkYLkLdRZhqkoWBFd/TY++R2lkQX90Uyb5RQQz7bwamimIZqyCEEKJdkoTBQXVrPtSov1pjn+SPMGVsJ6mXkdIezpwcEc6Di76AhOXEV7xja1WQZEEIIUQ7JAmDAz7amcpf1xwAYERkAADBORai7a0KHp55dP9pPdaK/XwSF4o1wAeAgEJn4udPgYpCssu9MXUxtc4NCCGEEBdJEgYH1LQs/H36QG4Z0Z38+JWsT7CQZwjGlPcJAzdvBOCLkT3xsBoIq6i0nViRbfvp5oupi4m+E3/bGuELIYQQF00ShkbUdEMcyihiRGQAt4zoDsCB9UfIcxuFe/lxXAq/I7WXEcO1V9EtNQtyjzEr+AD0GAP4wsAZ0g0hhBCi3ZOE4TzqdkNcb/Rh0KFcPr7rI6qqKzG7jQLgu767MFzpxnJtAhKJzy20nTz1JUkShBBCdCiSMDSgJlkYVGFgiq8PllPllONJddF2SpSte8JqMNP7eCEBJwKJt5+XXemLKcQkyYIQQogORxKGOuqu1DiowsC1Za5YysrxKzhCUFYCO7udwKnaDaNHCSFWKxh7Q51Fl0whyJoKQgghOiRJGOzqd0FEF1QBtqmSBS7bWTfYiYCyIHytJdw/2lvGJgghhOhUJGHgl5UaZ1W60tPkheVUOWBLFtYN3kHhEC8mF+ZTfdgD/Eww793WDVgIIYS4xDp1wvDRzlR2bjiJe3o511pdsVTspyz5J5yqNa6VZnZ2K6J3eTimLeVUuwaRXeGNKUTqPgghhOh8OnXCsHZvGr0zK+iKAWNlOiWFWyg3lOFiraTEU+Pr5YoJA7h62eo+hEjdByGEEJ1Tp00YVv7tY64+WUm1R1e8LOkM3PMC3/cKxRygeWikh4xREEIIIerodAnDyr99jPl0FcVOeVh1Ek7mMqqqi9jeK5QKVzcC3L1g3qrWDlMIIYRoUzpNwnBwaxo/rP6J8oog8ABdsIFq8in2LQEgwL0L3QJ6SZeDEEII0YBWSRiUUhOBlwED8LbWenFLvt7Kv31Mdm4Q4IlfwRGSA3fj7HuaAKuVh0fKFEkhhBCiKZc8YVBKGYDXgAnAaWCXUupTrfWhlni95SsOUJobBIAx+yOyg7cwMLKY6qNDZYqkEEII4aDWaGEYDhzTWh8HUEr9G7geaPaE4dXZd1KJCwDOVVkUmcoIsUZRnWEiu6JMpkgKIYQQDmqNhCEMOFXn+WlgRP2DlFJ3A3cDdO/e/YJfzMlahrPVjLOXBf+QIbXbTUZZxlkIIYRwVGskDKqBbfqcDVq/BbwFEBsbe85+R9z/4TsXcpoQQggh6nFqhdc8DYTXed4NSG+FOIQQQgjhoNZIGHYBUUqpSKWUK/Bb4NNWiEMIIYQQDrrkXRJaa4tS6n7gK2zTKv+ltT54qeMQQgghhONaZR0GrfUXwBet8dpCCCGE+PVao0tCCCGEEO2MJAxCCCGEaJIkDEIIIYRokiQMQgghhGiS0vqC1kS6pJRS2cDJCzw9EMhpxnA6InmPGifvT9PkPWpca70/PbTWplZ4XdEBtYuE4WIopRK01rGtHUdbJu9R4+T9aZq8R42T90d0BNIlIYQQQogmScIghBBCiCZ1hoThrdYOoB2Q96hx8v40Td6jxsn7I9q9Dj+GQQghhBAXrzO0MAghhBDiIknCIIQQQogmtfmEQSk1USmVrJQ6ppR6rM72wUqpHUqpA0qpz5RSPg2cG6GUKlNK/aSUOqyU+lEpdfulvYOWpZT6l1LqjFIqsd52R98frZR6us62QKVUlVLq1UsR/6WglApXSm2y/w4cVEr9sc6+eKXUXvt/KUqpvQ2cH1H//e1oGvmcPaWUSqvzHk0+z/n9lVLfKqWOKKWOKqWeUEqpJl7zr819Hy2pkc/a00qp/fb352ulVGgD53b43yHR8bXphEEpZQBeAyYB/YCblVL97LvfBh7TWg8E1gCPnOcyP2uth2qt+wK/BR5SSs1r4dAvpXeBiQ1sd/T9OQ5MrfN8JvCryo0rpVql6umvYAH+bP8dGAncV/N7pLWepbUeorUeAvwH+KT1wmwdTXzOAJbWvEf2SrP1z/cAPgUWa62jgcHAKODeJl66XSUMnP+z9rzWepD9d2gdsOBSBiXEpdKmEwZgOHBMa31ca10J/Bu43r6vD7DF/vgb4MamLqa1Pg78CfgDgFLKy/6tYZe9FeJ6+3aDUuoF+7fz/UqpB5r5vpqN1noLkNfALkffnzLgsFKqZlGZWcDKmp1KqWlKqZ3292eDUirIvv0ppdRbSqmvgRXNcS8tRWudobXeY39sBg4DYXWPsX8bvgn4uLFrKaXm1m19UUqtU0pdaX9crJT6P6XUPqXUDzXvVTvQ2OfMEbcA27XWXwNorUuB+4HHAJRS3kqp5XU+TzcqpRYDHvZv5R827+20jPN91rTWRXWeegGNjiS3tzZsVUrtsf83yr79SqXUZqXUaqVUklLqw6ZaaYS4lNp6whAGnKrz/DS//EOfCFxnfzwTCHfwmnuAGPvjvwHfaq3jgKuA55VSXsDdQCQwVGs9CGgX/6DV82ven38Dv1VKdQOsQHqdfduAkVrrofbj/rfOvmHA9VrrW5ot6hamlIoAhgI76+0aC2RprY9exOW9gB+01oOxJWt3XcS1LqXGPmcA99v/0P9LKeXfwPn9gd11N2itfwa87V1hTwCFWuuB9s/Tt1rrx4Aye6vF7Ga9m1ZgTxRPAbNpuoXhDDBBa30ZtgT9lTr7hgIPYmvp6QmMbv5ohbgwbT1haCi7rsne78DWtLwbMAKVF3DN3wCP2futNwPuQHfgGuANrbUFQGvd0Df4tu7XvD/rgQnAzUB8vX3dgK+UUgewdWv0r7PvU611WfOF3LKUUt7Yuh0erPetEGz33mjrggMqsTVJg+0PaMRFXu9SaexztgzoBQwBMoAl5zn/fN+qNbbP02u1G7TOv9BA2yqt9d+01uHYvlzc38ThLsA/7Z+pVdiSgxo/aq1Pa62rgb20n98h0Qm09b7n05z9zbgb9m+/WuskbH/wUUpFA1McvOZQbE3SYPuH7katdXLdA+zNgO16gYpf8/5orSvticWfsSUE0+rs/gfwotb6U3vT+1N19pU0b9QtRynlgi1Z+FBr/Um9fc7ADdhaTJpi4exE273O4yr9y8ImVtr+56tGY5+zrJqNSql/8ktCVNdBYFzdDUqpnkCx1trcET5Pv8JHwOfAk40c8xCQhW2shxNQXmdfRZ3H7el3SHQCbb2FYRcQpZSKVEq5Yhu0+CmAUqqr/acT8DjwRlMXszdHv4DtjyDAV8ADNf2ESqmh9u1fA/NrBvMppQKa64YulQt4f5YAj2qtc+tt9wXS7I/b5QwT+//fd4DDWusXGzjkGiBJa33agculAEOUUk5KqXBs/f/tXWOfs5A6x03H1tVV34fAGKXUNfZzPLA1sz9n3/81db511+nWqLIncu2aUiqqztPrgKQmTvEFMuytCLcChpaKTYjm1KYTBnuXwP3Y/rAfBlZqrWtG8N+slDqC7cOZDiw/z2V62QfsHcY2mO8fWuuaY5/G1jy43z7lqWZ64dtAqn37PmyDutokpdTHwA6gj1LqtFLqTvsuR98fALTWB7XW7zWw6ylglVJqK+23fPFobP8wX60anh74WxrvjnDml29+24ETwAFsyeeeFoj3kmric/ZczWBFbON8Hmrg/DJsgyQfV0olY3tvdgE1g0OfAfyVUon2z9NV9u1vYfuMtYsxQo181hbb720/tla9PzZwet3fodeB25VSPwDRtKOWOtG5ydLQQjTBPntmttb6ptaORbRP8jskOgLpHxOiEUqpRdi+Pc9t5VBEOyW/Q6KjkBYGIYQQQjSpTY9hEEIIIUTbIAmDEEIIIZokCYMQQgghmiQJgxD1KKWs9qmXB+11If5kX8+isXMilFJtdvqtEEJcLEkYhDhXTY2D/tiWzJ5M4yv3gW0JX0kYhBAdlsySEKIepVSx1tq7zvOe2BYiCgR6AO9jKzQFcL/W+nv7Ijx9sS3q9B62lQ4XA1cCbsBrWus3L9lNCCFEM5OEQYh66icM9m352KqcmoFqrXW5fUngj7XWsfY6Gw9rrafaj78b6Kq1fkYp5YZthciZWusTl/JehBCiucjCTUI4pqaiowvwqlJqCLbiQNHnOf43wCCl1Az7c18gClsLhBBCtDuSMAjRBHuXhBU4g20sw/kqDZ51GvCA1vqrSxKkEEK0MBn0KEQjlFImbJU+X7WXrj5fpUEzYKxz6lfA72uqMSqlopVSXgghRDslLQxCnMtDKbUXW/eDBdsgx5qy2K8D/1FKzQQ28Uulwf2AxV6N8V3gZWwzJ/bYy2tnA/9zacIXQojmJ4MehRBCCNEk6ZIQQgghRJMkYRBCCCFEkyRhEEIIIUSTJGEQQgghRJMkYRBCCCFEkyRhEEIIIUSTJGEQQgghRJP+P7IfwtflOVtlAAAAAElFTkSuQmCC", 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", 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QYNnZ2Wvnzp3b7O67725z3nnnfTl9+vQTGzVqVPTll1+uycjIaDR06NCeANu3b6977733tl6yZMmXTZs2Lfrd737X6p577kmYPn36doCGDRsWZWVlrSvtde67776WTzzxRMKhQ4fi3n333XUAW7durdeuXbv8wDFt27bN37p1a72KxK+kLCJShTLmPUz8V6/QKz+bBLwxx58ffzaJqdermroapKWlfQ+Qmpq6d9KkSfUBli5dGj9hwoRvwZuis1u3bvsAFi1a1Hj9+vUNBw0a1B3g0KFDNmDAgD2Ba1199dXfH+11pkyZkjtlypTcJ598svm0adNaz58/f2Np834EStGhUlIWEakiL2Rspkv2PNrbJlY3SOTDRmcQn3p9zSkZl3QMJdrKqlu3risqKq495sCBA4c1wzZs2ND5x1FYWFicEUtLjs45hg0b9uPrr7++4YidQJMmTYpK2x7s+uuv3zVp0qQOAO3atTu0ePHiJoF9W7durX/66aeHtm6tT23KIiJVIGPew3R581J62ib2t+hJrzuWkn7LPWozrmLt2rUr2LVrV90dO3bU2b9/v7399tvlttkOGzZsz+zZs5sDLF++vOGXX355HMDw4cP3ZmZmxq9ataoBQF5eXtznn3/eoLzrZWdnFx8zd+7cZh07djwIcNFFF+1evHhx09zc3Dq5ubl1Fi9e3PSiiy7aXZH3p5KyiEglvZCxmQUrtjJi379I3/0oxEFO82QSUq+KdGg1VoMGDdxtt922fdCgQT3atWt38OSTTz5Q3jm33377t5dffnnnbt269ezVq9e+xMTEvQBt2rQpeOqppzZefvnlXfLz8w1g2rRpW/v06XOwrOvNmDHjxA8++KBp3bp1XbNmzQqee+65DQAJCQmFkyZN2jZgwIAeAL/5zW+2lVw6sjya+1pEpBJeyNhM9muPMLrOMgbHrQUgo9dUUtJui3BkP9Hc19FLc1+LiFQFv1d1l517ubKel4zpOAwSx5KSfG1kY5OYp6QsIhKijHkPk7L6bhKADfT4qapayViqSFiTspndAvwCcEA2cC1wHDAX6ARsBC51zh2127mISDQIJGSAmc0mEJ96PYNrZyeuoqKiIouLi4v+ts8oVVRUZECpPbvDlpTNrC0wAejpnNtvZi8BlwM9gYXOufvNbDIwGfhtuOIQEam0oOkxU/xJQDJ6TSU9itqNI2BVbm5uz5YtW+5WYq64oqIiy83NbQasKm1/uKuv6wKNzOwQXgl5GzAFGO7vfx5YhJKyiESZ4JLxhqIebKAHlpgWVR25IqGgoOAXO3bseGbHjh290bDayigCVhUUFPyitJ1hS8rOua1mNh3YDOwH3nHOvWNmCc657f4x283sxNLON7N0IB2gQ4daWUUkIhFSsqp64XE/Y3RSW405BgYMGPAtMCrScdRU4ay+Ph4YDXQGfgDmmVnIg/ecczOBmeANiQpHjCIih/F7Vpesqk6PcFhSe4Sz+vosYINzLhfAzOYDqUCOmbX2S8mtgW/DGIOISJlKTgASmK9aVdUSCeFMypuBwWZ2HF719QggE9gLXAPc7/9dEMYYRERK9ULGZvYse5o+37/LLVA8AUigZ7WqqiUSwtmmnGFmLwOfAgXAZ3jV0fHAS2Z2HV7iTgtXDCIipQnMxnVfvWeLp8akiTcBSLrGHEsEhbX3tXNuGjCtxOaDeKVmEZGI2LPsaS8hA4x8hAQlYokSmtFLRGqNwFrH6fnZ3oaRj2g2LokqSsoiUvOV6FW9un4ie7qO0VzVEnWUlEWk5vKTccKuTPWqlpigpCwiNdILGZvpu/BZ2h9cz8euB58ff7Z6VUvUU1IWkRonY97DdMmeR3vbxDcNTuLrES+QrmQsMUBJWURqlsxZ3hSZ/lCnXqlX0StZCVlig5KyiNQIgZ7Vvfye1TObTSB9wj0RjkqkYpSURSRmBWblGrr/fVL8ZLy6fiIfNjqD+NTrIxydSMUpKYtITDpsVi6Chjml3UavCMcmUllKyiISUwILSHTZPO+wWbl6acyx1ABKyiISMwKl41vqLGNwPW8BCc3KJTWJkrKIxITAMKcrA8m4o7eAhBKy1CRKyiIStUqudRwY5pSQepWSsdRISsoiEnWC241vqbOseK3jjF5TNUWm1GghJ2UzOx5oA+wHNjrnisIWlYjUanuWPc3tu99jYL013ga/qloLSEhNV2ZSNrNmwK+AK4D6QC7QEEgws4+BJ5xz74c9ShGp8Y6oqga1G0utU15J+WXgf4BTnXM/BO8wswHAf5tZF+fcs2GKT0RqgcN6VauqWmqxMpOyc+7sMvZlAVlVHpGI1ColJwFRVbXUZiG1KZuZAeOALs65u82sA9DKOfdJWKMTkRorMEVmn+/f/WmYk8YcSy0XakevJ4Ai4EzgbiAP+CcwMExxiUgNFhhzPDhurYY5iQQJNSmnOOf6m9lnAM65782sfhjjEpEaKLCSU0p+9mHJOEHJWAQIPSkfMrM6gAMws5Z4JWcRkXIFqqoDvaqDF48QkZ+EmpQfBV4BTjSzPwFjgTvDFpWI1BiHVVWjXtUiZQkpKTvn5phZFjACMOAi59zasEYmIrErcxZkv0xO3gFSdmUeVlWtXtUiRxdq7+u/AHOdc4+HOR4RiXWZs+CNiQBsKOrBBnpgiWkqHYuEINTq60+BO82sG1419lznXGb4whKRmOOXjtm0FIAph67j6w5pjE5qy5UpHSIcnEhsCLX6+nngeTNrDlwCPGBmHZxzXcManYhEvxLJ+OOiHiwoTCVx1ETuUzIWqZCKrhJ1MtAd6ASsqfJoRCS2BFVVB5KxSscilRdqm/IDwMXAeuAl4J6Sc2GLSC2SOYucZbNJ2OW1YgVXVat0LFJ5oZaUNwBDnHM7wxmMiESxQDU1wKalJOCVjj8//mwSU69XMhapAuUt3djdOfcF8AnQwZ/zuphz7tNwBiciUSKomnp1/UTygtqN05WMRapMeSXlW4F04OFS9jm8ubBFpKYqpUf1iwdGkNK5udqNRcKgvKUb0/2H5zvnDgTvM7OGYYtKRCKrRDJeXT+R2XsH8WLhCO4dk6hkLBImobYpLwP6h7BNRGJdiarq2XsHFZeO71XpWCSsymtTbgW0BRqZWT+8KTYBmgLHlXdxM/sv4BmgN15198+BdcBcvGFVG4FLnXPfVyp6Eak6pfWobp0GLVAyFqkm5ZWUzwXGA+2AGUHb84A7Qrj+X4C3nHNj/aUej/PPW+icu9/MJgOTgd9WNHARqUJ+6TgBWE5PPmt2lnpUi0SAOefKP8jsEufcPyt0YbOmwEqgiwt6ETNbBwx3zm03s9bAIufcKWVdKzk52WVmalZPkbAIqq7+A+msaX0xc28YEtmYpEqYWZZzLjnScUjoQp1m859mdgHQC2gYtP3uMk7rAuQCs8ysL5AF/BpIcM5t98/fbmYnlnaymaXj9fymQwf9WhepUiXGHENgApCLGZ3UNoKBidRuoc7o9SRe1fMZeG3EY/HGLpd37f7Azc65DH+lqcmhBuacmwnMBK+kHOp5IhKC7JdhRzY5jbuyQXNVi0SNUHtfpzrn+pjZ5865P5jZw8D8cs7ZAmxxzmX4z1/GS8o5ZtY6qPr628qFLiIVlTHvYeK/eoVOh75mY70uXLDtVgANcxKJEqEm5f3+331m1gb4Duhc1gnOuR1m9o2ZneKcWweMwFvEYg1wDXC//3dBpSIXkdD4vap37jlISn424A11+rDRGaS00CQgItEk1KT8hj+86SG8tZUdXjV2eW4G5vg9r78GrgXigJfM7DpgM5BW0aBFJDQZ8x4mZfXdJAAbinqwumEie7qOISXtNnrhd9oQkagRUu/rw04wawA0dM7tDk9IR1Lva5GKCVRT9/JLxjObTSA+9XqViGsZ9b6OPeVNHnJxGftwzpXXriwi1eiFjM3sWfY06bsfBbxq6j1dx5CedluEIxORUJRXfX1hGfsc5Xf2EpFq8ELGZhas2EqXzfO4r96zAGT0mkqKkrFITClvQYprqysQEamYQCIG6LJ5HrfUWcbgemu9nSMfISVZX1+RWBPqOOWppW0vZ/IQEQmjBSu20nP7fMbW/4he9by2YzoOg8SxoIQsEpNC7X29N+hxQ2AksLbqwxGR8gTajW/f/R4DWQP5KBmL1BChTrP5cPBzM5sOvBaWiETkqDLmPUyX7HkMjvN+E+c0TyYh9SolY5EaItSScknH4c1tLSJhFmg7HrHvX16v6rifknGCkrFIjRJqm3I2Xm9rgDpAS0DtySLVINB2nO5NBa9e1SI1WKgl5ZFBjwuAHOdcQRjiEZEgL2RspsvmeUzzhzmpV7VIzRZqm/ImMzseaO+fk+BPHvJpWKMTqcUC7cdXBg1zUtuxSM0WavX1PcB4YD0/VWM74MzwhCVSex02K1ecOnOJ1CahVl9fCpzknMsPZzAitZq/mlOXnXuLe1er/Vikdgk1Ka8C/gutfSxS5YIXj0gANtCjuHSs9mOR2iXUpHwf8JmZrQIOBjY650aFJSqRWiKwtCL8tMZxfOr1DNZqTiK1UqhJ+XngASAbKApfOCK1R3BCDlRT94pwTCISWaEm5Z3OuUfDGolILRDoxDV0//uk+Gsdq91YRAJCTcpZZnYf3tSawdXXGhIlEqIXMjaT/dojxUsrBtY6VkIWkYBQk3I//+/goG0aEiUSgkDpuM/37x425riXOnGJSAmhTh5yRrgDEalpAnNWd9k8zysda8yxiJRD6ymLhEnx8or11ngbRj6iBSREpExaT1mkigXGHaf7Hbm01rGIhErrKYtUkcOmx0QduUSk4rSeskgVCCweoekxReRYaD1lkWNUPAlIUEcuTY8pIpWh9ZRFKinQdqxJQESkqoSalFsDq51zeQBmFm9mvZxzGeELTSRK+as5pezKBNR2LCJVJ9Sk/Degf9DzfaVsE6n5MmfBGxNJAD4u6oElpikZi0iVCTUpm3Mu0KaMc67IzCrbSUwk5pTsWT3l0HUkjprIlVrNSUSqUFyIx31tZhPMrJ7/79fA1+EMTCRaBOasDiTkmc0mKCGLSFiEWtq9EXgUuBOvF/ZCID1cQYlEg0BHri4HCg6bszpdPatFJExCnTzkW+DyMMciEnGlLa24umEiOfGas1pEwq/MpGxmdwJPOOd2HWX/mcBxzrk3whGcSHXS0ooiEmnllZSzgdfN7ADwKZCLN/d1VyAJeA+4N5wBilSHkglZSyuKSCSUmZSdcwuABWbWFRiKN175R2A2kO6c21/eC5hZHSAT2OqcG2lmzYG5QCdgI3Cpc+77Y3kTIpV1tHZjVVOLSCSE2qb8FfBVJV/j13grSjX1n08GFjrn7jezyf7z31by2iKVVjw9Jmo3FpHoENaxxmbWDrgA+BNwq795NDDcf/w8sAglZalOmbMg+2VSNi0FND2miESPcE8A8gjwG6BJ0LYE59x2AOfcdjM7sbQTzSwdf9hVhw4aDypVxJ+RC2A5Pfms2VmkKyGLSJQIafIQMxsayrYS+0cC3zrnsioTmHNupnMu2TmX3LJly8pcQuQnmbNg1gXFCfkPpDO99QziU6+PbFwiIkFCLSk/xpHzXJe2LdhQYJSZ/Qyvx3ZTM5sN5JhZa7+U3Br4tqJBi4TMr6rGr6peXT+Rl/OHsKb1xcy9YUiEgxMROVx545SHAKlASzO7NWhXU7x1lY/KOTcFmOJfZzhwu3PuKjN7CLgGuN//u6CywYuUKaiq+uOiHiwoTOXr1mkAjE5qG8HARERKV15JuT4Q7x8X3C78IzC2kq95P/CSmV0HbAbSKnkdkdKVKB1POXQdX3dIY3RSW+7TfNUiEsXKG6e8GFhsZs855zZV9kWcc4vwelnjnPsOGFHZa4mUK/tl8reu5FO/dJw4aqKSsYjEhFDblBuY2Uy8CT+Kz3HOnRmOoEQqzC8d5+QdIP77tWQXduDy/N9z75hEreYkIjEj1KQ8D3gSeAYoDF84IpUQ1Ha8oagH0IHPjz+be1OVkEUktoSalAucc38LayQiFVWi7fgPpLOm7cWMTmpLupKxiMSgUJPy62b2/4BXgIOBjUdbPUok7IJKxxrmJCI1RahJ+Rr/76SgbQ7oUrXhiIQgKCH/gXTWtLgY0DAnEYl9oS5I0TncgYiUq7TqapWORaQGCSkpm9lxeAtKdHDOpftLOZ7inHsjrNGJ+IJXdCqeCKTDxSodi0iNEmr19SwgC292L4AteD2ylZQlbAJrHQOk5GcDMLPZBBYe9zNNBCIiNVKoSfkk59xlZnYFgHNuv5lZGOOSWu6wtY7rJ7K6fiJ7uo4hPe02b+kwEZEaKNSknG9mjfA6d2FmJxHUC1ukKgUnZK11LCK1SahJeRrwFtDezObgrQA1PlxBSS2VOYucZbNJ2ZUJKCGLSO0Tau/rd83sU2AwYMCvnXM7wxqZ1C7+MKcEvI5clpimhCwitU6ova/HAP/nnHvTf/5fZnaRc+7VcAYntUApKzoljpqo6TFFpFaKC/G4ac653YEnzrkf8Kq0RY5JzrLZ7N38GR8X9VBCFpFaL9Q25dKSd6jnihzObzveuecg7Q+uJ9t15M9t/8zopLZKyCJSq4WaWDPNbAbwOF4P7Jvxxi2LVFjOstk0+m4Nea4j3zQ8Ces6hrlpmpVLRCTUpHwz8Htgrv/8HeDOsEQkNdILGZvZs+xphu5/n/YH17PGdeTrC15SyVhEJEi5SdnM6gALnHNnVUM8UgNlzHuYLtnzGBy3FoDVDRKxrmOUkEVESig3KTvnCs1sn5k1C+7sJVKu4HHHcZDTPJmE1KvolXxtpCMTEYlKoVZfHwCyzexdYG9go3NuQliikpgXmJVL445FREIXalJ+0/8nUrYSs3LNbDaB+NTrVVUtIhKCUGf0et6f+7qDc25dmGOSWOQn44RdmYeVjtNVOhYRCVmoM3pdCEwH6gOdzSwJuNs5NyqMsUksKCUZf3782Sodi4hUQqjV13cBg4BFAM65FWbWOUwxSawoMV91IBmnKxmLiFRKqEm5wDm3u8QSyi4M8UgsOMp81UrGIiLHJtSkvMrMrgTqmFlXYAKwLHxhSVQqkYxX10/k5fwhfN3hYu5TQhYROWYVmdHrd8BB4AXgbeCP4QpKolT2y7AjuzgZr2lxMQCjk9pGODARkZqhzKRsZg2BG4GTgWxgiHOuoDoCkygRKB0D7Mgmp3FXLth2KymdmzP3Bs1XLSJSlcorKT8PHAI+AM4HegATwxyTRBO/dJzTuCs7XQdm5/QFVDoWEQmH8pJyT+dcIoCZPQt8Ev6QJOKCSsf5W1fyVVwnLth2KwApnZtzr5ZYFBEJi/KS8qHAA+dcQYne11IT+cOcwOvIlZffjgWFg0jp3FzrHYuIhFl5Sbmvmf3oPzagkf/cAOecaxrW6KR6BLcbBw1zevHAiOJkrN7VIiLhV2ZSds7Vqa5AJEKCSsY5zZPZUNSDBYWpfN0hTdXUIiLVLNQhURVmZu2B/wFaAUXATOfcX8ysOTAX6ARsBC51zn0frjjkKEqMOZ7ZbAL3bhsMwL1jElUyFhGJgLAlZaAAuM0596mZNQGy/KUfxwMLnXP3m9lkYDLw2zDGIcFKmQBk9t5BvJgzWO3GIiIRFrak7JzbDmz3H+eZ2VqgLTAaGO4f9jzefNpKytUhqKr640A1des0aIGqqkVEokA4S8rFzKwT0A/IABL8hI1zbruZnXiUc9KBdIAOHZQsKu1onbgKR6iaWkQkyoQ9KZtZPPBPYKJz7sdQh1U552YCMwGSk5O1+EVllBjeRKCq2k/IKhmLiESXsCZlM6uHl5DnOOfm+5tzzKy1X0puDXwbzhhqpVJWcQoMb1JVtYhI9Apn72sDngXWOudmBO16DbgGuN//uyBcMdQ6JZIxHYcx84f+vJgzWCVjEZEYEM6S8lDgv4FsM1vhb7sDLxm/ZGbXAZuBtDDGUHsEVVXTcRgZ8WcyY1cqa3b/SErnpkrIIiIxIJy9r5fizfxVmhHhet1ap2TpeOQjvFA4gjteyQZ2FQ9zEhGR6Fctva8lDEqpqiZxbFBCRlXWIiIxRkk5FpWYGnNBYSoL838GWZCxQQlZRCRWKSnHkhKl44xeU7ksqzsAKZ3x/2pWLhGRWKWkHCtK6cgVSMgqFYuI1AxKytGulIUjFub/jIysXYASsohITaKkHK2OMub4sd3D6HmcqqlFRGoiJeVoVKKqOtCr+t5Xsknp3JS5NwyJaHgiIhIeSsrRpJSOXDN2pR7Wq1pjjkVEai4l5UgrZRWnwztyeROAqLpaRKTmU1KOtOyXYUc2tErUBCAiIrWcknKkBErIgYR87Zu8kLGZBVlbNQGIiEgtpaRc3Uq0G+c0T2bBD/1Z+NRHZGzwhjmpqlpEpHZSUq5OpfSqnpDVnTXbf9QwJxERUVKuFkdZyWlB1lYvIbfWMCcREVFSDr9SSsckX8uCpz4qTsga5iQiIqCkHD5llI7J+kglZBEROYKScjiUsnjEjKzuxb2qUzo3VwlZRESOoKRclY5SOvbGHO9SRy4RESmTknJVOcp81ZoEREREQqWkXBWCE/LIRyD5Wl7I2KyELCIiFaKkXFmlzFmd0WsqM7K6Q9ZPE4EoIYuISKiUlCujRFV1TvNkFhSmcq8WkBARkWOgpFwRpXTkIvlaJvhjjlM6N1UiFhGRSlNSDkVp81UXprLQr6rWmGMREakKSsplOUoyvnfbYABSOnuHacyxiIhUBSXlowlqNz4yGau9WEREqp6ScmmCEvLMZhOUjEVEpFooKQcrUV095dB1vJgzWMlYRESqhZJyQInq6kdy+vJi4QiNMxYRkWpTu5NyKROABFdXKyGLiEh1qr1JuUTJeGf9RGbvHaTqahERiZjal5RLtBtn9JrKZVndAa8j171KxiIiEiG1LinnLJtN/Pdr2Vg/kQ8bneFPjamqahERibyIJGUzOw/4C1AHeMY5d384Xy9j3sPEf/UKAO0PrifbdeTPrR4CvAlAVFUtIiLRoNqTspnVAR4Hzga2AMvN7DXn3JpwvN4LGZvpkj2P9raJbxqcxDcNTsK6jmFumqbEFBGR6BKJkvIg4D/Oua8BzOx/gdFAlSflj5+4ni47sulpm9jfoie9Jiys6pcQERGpMnEReM22wDdBz7f42w5jZulmlmlmmbm5uZV+sSYN67K/RU8SUq+q9DVERESqQyRKylbKNnfEBudmAjMBkpOTj9gfisH/7+nKnCYiIhIRkSgpbwHaBz1vB2yLQBwiIiJRJRJJeTnQ1cw6m1l94HLgtQjEISIiElWqvfraOVdgZjcBb+MNifq7c251dcchIiISbSIyTtk59y/gX5F4bRERkWgVieprERERKYWSsoiISJRQUhYREYkSSsoiIiJRwpyr1Lwc1crMcoFNlTz9BGBnFYZTE+kelU33p3y6R2WL1P3p6JxrGYHXlUqKiaR8LMws0zmXHOk4opnuUdl0f8qne1Q23R8JlaqvRUREooSSsoiISJSoDUl5ZqQDiAG6R2XT/Smf7lHZdH8kJDW+TVlERCRW1IaSsoiISExQUhYREYkSUZ+Uzew8M1tnZv8xs8lB2/ua2Udmlm1mr5tZ01LO7WRm+83sMzNba2afmNk11fsOwsvM/m5m35rZqhLbQ70/zszuCdp2gpkdMrO/Vkf81cHM2pvZ+/5nYLWZ/Tpo31wzW+H/22hmK0o5v1PJ+1vTlPE9u8vMtgbdo58d5fxeZvZ/ZvalmX1lZr83MyvnNe+o6vcRTmV81+4xs8/9+/OOmbUp5dwa/xmSKuKci9p/eEs7rge6APWBlUBPf99y4HT/8c+Be0o5vxOwKuh5F2AFcG2k31sV3qPTgP7B77OC92c98FnQtl/69+ivFYihbqTvQznxtQb6+4+bAF8GPkcljnsYmFre56im/Svne3YXcHs55zfyzz/Hf34c8G/gV+WctyfS772C9+lo37WmQY8nAE/Wts+Q/lXdv2gvKQ8C/uOc+9o5lw/8LzDa33cKsMR//C5wSXkXc859DdyK98XBzBr7v36X+6Xp0f72OmY23S9lfm5mN1fx+6oyzrklwK5SdoV6f/YDa80sMLHBZcBLgZ1mdqGZZfj35z0zS/C332VmM83sHeB/quK9hItzbrtz7lP/cR6wFmgbfIxfqrsUeLGsa5nZ+OBaBDN7w8yG+4/3mNmfzGylmX0cuFcxoKzvWSiuBD50zr0D4JzbB9wETAYws3gzmxX0fbrEzO4HGvmlyzlV+3bC42jfNefcj0FPGwNl9p71S80fmNmn/r9Uf/twM1tkZi+b2RdmNqe82gapeaI9KbcFvgl6voWf/me6ChjlP04D2od4zU+B7v7j3wH/55wbCJwBPGRmjYF0oDPQzznXB4iJ/2mUUJH787/A5WbWDigEtgXtWwoMds7184/7TdC+AcBo59yVVRZ1mJlZJ6AfkFFi16lAjnPuq2O4fGPgY+dcX7wfRNcfw7WqU1nfM4Cb/GT6dzM7vpTzewFZwRucc+uBeL/Z5PfAbudcov99+j/n3GRgv3MuyTk3rkrfTQT4P8a+AcYBU8s5/FvgbOdcf7wfwY8G7esHTAR64tVcDK36aCWaRXtSLu1XYuBX6M+BX5lZFl6VZH4lrnkOMNlvR1wENAQ6AGfhVUEVADjnSiuJRruK3J+3gLOBK4C5Jfa1A942s2xgEt7/gANec87tr7qQw8vM4oF/AhNLlG7Ae+9llpJDkA+84T/OwquyjAVlfc/+BpwEJAHb8ar4Szv/aKVDh/d9erx4g3PfVzbQaOWc+51zrj3eD/ibyjm8HvC0/52ah5eAAz5xzm1xzhXhNSN1CkO4EsXqRjqAcmzh8BJeO/xSnHPuC7ykipl1Ay4I8Zr98KovwfufySXOuXXBB/hVRjE9gLsi98c5l+8n79vwku6FQbsfA2Y4517zq2nvCtq3t2qjDh8zq4eXkOc45+aX2FcXuBiv5F+eAg7/Mdsw6PEh51zgc1NI9H+/Asr6nuUENprZ0/z0oyPYarz2VoKO7YLXZpxXE75PFfAC8CYwrYxjbgFygL54n6UDQfsOBj2Opc+QVJFoLykvB7qaWWczqw9cDrwGYGYn+n/jgDuBJ8u7mF91OR0v0QC8DdwcaLcxs37+9neAG/3/WWNmzavqDVWXStyfh4HfOue+K7G9GbDVfxyTPdf9/77PAmudczNKOeQs4Avn3JYQLrcRSDKzODNrj9ceG+vK+p61DjpuDF6zSElzgGFmdpZ/TiO8KtkH/f3vEFR6DKoCP+T/WIppZtY16Oko4ItyTmkGbPdLw/+N19FOBIjypOxXH9+ElzzXAi8551b7u68wsy/xvgDbgFlHucxJfieltXgdmB5zzgWOvQevKulzf7hCYGjQM8Bmf/tKvI4sUcnMXgQ+Ak4xsy1mdp2/K9T7A4BzbrVz7vlSdt0FzDOzD4jdpfmG4v3P70wrfWjP5ZRddV2Xn0owHwIbgGy8H3ifhiHealXO9+zBQActvH4Xt5Ry/n68jmF3mtk6vHuzHAh0iPsjcLyZrfK/T2f422fifcdios9GGd+1+/339jle7dSvSzk9+DP0BHCNmX0MdCOGapwk/DTNpkg5/F7545xzl0Y6FolN+gxJqNReIVIGM7sbrxQ4PsKhSIzSZ0gqQiVlERGRKBHVbcoiIiK1iZKyiIhIlFBSFhERiRJKyiIlmFmhP2xqtT+P9a3+eO+yzulkZlE7dE5EYoOSssiRAnMy98KbfvRnlD1DE3jTISopi8gxUe9rkRLMbI9zLj7oeRe8yTBOADoC/8BbfALgJufcMn8iiB54E4s8jzej1f3AcKAB8Lhz7qlqexMiEpOUlEVKKJmU/W3f460ulgcUOecO+NMrvuicS/bnBb/dOTfSPz4dONE590cza4A3E1iac25Ddb4XEYktmjxEJDSBlZTqAX81syS8BQO6HeX4c4A+ZjbWf94M6IpXkhYRKZWSskg5/OrrQrx1cKdx9BV+DjsNuNk593a1BCkiNYI6eomUwcxa4q2w9Vd/WcajrfCTh7dudcDbwC8DqyCZWTcza4yISBlUUhY5UiMzW4FXVV2A17ErsOTjE8A/zSwNeJ+fVvj5HCjwV0F6DvgLXo/sT/2lI3OBi6onfBGJVeroJSIiEiVUfS0iIhIllJRFRESihJKyiIhIlFBSFhERiRJKyiIiIlFCSVlERCRKKCmLiIhEif8Py9AnEsQPth4AAAAASUVORK5CYII=", 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", 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", 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", + "image/png": 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", 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", 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", 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" ] @@ -12281,7 +12335,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **40-49** population up to 15 Dec 2021" + " ## COVID vaccination rollout among **40-49** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -12312,7 +12366,7 @@ }, { "data": { - "image/png": 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", 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", 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", 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", 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", 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6+vRpRz8/v74LFizwqen4hx56KHPYsGGX1Ad07dq1dM6cOUnXX399SM+ePXv37du3YPr06Vnx8fH2w4YN6xEaGtrr/vvv7/bKK68kAtx3330ZTzzxRNeqii0/++yz+CeffDIwPDw81NnZuSLV8fTTT2eEhoYWhYWF9QwODu794IMPdi0tLVUA4eHheX/5y186h4SE9A4MDCy+9957s2p7376+vmXBwcGFSUlJjjfeeGMBwIABA4peeOGFpFGjRoWEhIT0GjlyZMjZs2ftu3btWvrcc8+dGzx4cM9hw4aF9O3b96qGFqra0tDNWWRkpI6NjW3qZgghRKPZv34th7dupEPXa7hx5kN1uoZSarfWuuoK56uwb9+++H79+mXU93XbkpiYGPf58+f7/fLLLyeaui2W9u3b59OvX7+gqvZJRkIIIVqQw1s3kngorqmbIUSFFl1sef78eb744otLtvXu3ZuoqKhq6wPCw8MJDw+noKCA5cuXX7Y/MjKSPn36kJ2dzapVqy7bf91119GjRw8yMjKIiYm5bP+IESO45pprSElJYe3atZftHzVqFF26dOHs2bNs2LDhsv1jx46lY8eOnDp16pKRDmYTJkzAx8eHo0ePsm3btsv233777Xh6ehIXF0dV2ZrJkyfj4uLC3r17q6wdmDZtGvb29uzatavKUREzZ84E4LfffrusRsPOzo7p06cD8Ouvv3L69OlL9js7O1fUfKxfv57ExMRL9nt4eHDHHXcAsHbtWlJSUi7Z3759+4o5Nb777jvOnz9/yf6OHTsyduxYAL755htyci6pYaJz586MHj0agOjo6Mu6Urp161ZRy/Hll19eNglWSEgIQ4YMAbjs9w7kd09+9xr+dy8zejk/rVlHCU6ci97NGb4Arv53TzQfEyZMyJ0wYUKLGmbWogMJIYRoC+KWfMHxhW9QnptLfnk52s6R8/klTd0sIQCpkRBCiGYtM3o50V8vo8BBY6M8KLd1wdYhlPMhSbzytzfrdE2pkRBXqqYaCclICCFEM7R//VoOrFpB7rkL5DvaoGx9KerYD+/ycvy7uvJn00yxQjQ1CSSEEKKZ2bVgNdt3raa07AK4dEQBWX7Z3OK6CBU2iUGTHmvqJgpRQQIJIYRoAuZhnJbys0oozC2huNCALs/GVnlS5hFBSsAOir3tODVgOVMH1Xm15zbhxIkT9tOmTeuWnp5ub2Njw4wZM9JffPHFtKZuV2smgYQQQjSBw1s3kh5/Gt+gboAxiMhKM84LZGcoxKa8nG19jlLkt5e/tr+PQZP+0pTNbTHs7e2ZP39+4rBhwwoyMzNtIiIiet1yyy05zWG57dZK5pEQQogm4hvUjT4jn8DBbTKFhRNwdJ9M33MG/DN3ciLgGOcDnLim26MSRFyBrl27lppnqmzXrl159+7dCxMSEhyaul2tmWQkhBCiEVTuykg5cRI7Rz82Lj0KgFfWMfxSY4npt430MGf+0OV63rlpQRO1th7877EupB2q12XE6dCrgD+8Z/ViYEePHnU4dOiQy/XXX59Xr+0Ql5BAQgghGoFlV4YhLR1lcKPcJgjvPGMAkWW/lZh+NvgPGso793zc1M1t8bKzs23uuOOO7vPmzTtrubKnqH8SSAghRAOonIEwBxGqpB+cz8bRrTOuxUkEpf6LFf00GyLsmHPdHCaFTGq6RtenK8gc1Lfi4mI1fvz47pMmTbowY8aMrKZqR1shgYQQQjSAysWUtjaOlO08hHYPIs+tM8r2HPtCd/L6aAUo5nQa3XqCiCZUXl7O3Xff3TUkJKRo7ty5qU3dnrZAAgkhhKgH1WUgprw0j+X/WIZHfhDaHXLcO1Nqd45PBv8LgEi/SG655hYJIurJTz/95Pa///2vfXBwcGFoaGgvgJdffjlpypQp2U3dttZKAgkhhKgHlTMQLl4BnE/05rMZiyly7gxefjjrIyR6JnHcZzeR2pFb/IczqSUXVDZDN998c57WendTt6MtkUBCCCHqiTkD8dWOBPI+34OjtsOpOBGlT5Lruo0F1+0CMNVCSEGlaB0kkBBCiDqoqivDxSuAj+b+RnZiMp444paXyDDPL5gbcZ6jDg5EugRyS7/7pRtDtCoSSAghRB1YdmXkZ5WgbH3JzQrErrCIgLx0ABw9dzL3OgNHcaaHawCfT/qhiVstRP2TQEIIIaxQXQbCwW0yGclZYAfFZNL76FcEJG/lx9HwWZTxT6y5oFKI1kgCCSGEsEJ1GYjCwiwcdTKByb/S5dhmABbdpEjt70Kki690ZYhWr0kCCaXU08AfAQ0cAGYBLkA0EATEA5O11plN0T4hhKiKeW2MjUuPgh0ouxw6Ja2m5/F1AJzpYsPG3orUoV2kG0O0GY0eSCilAoAngV5a60Kl1HLgbqAXsEFrPU8p9TzwPPBcY7dPCCHg0q6M/KwSslMTcHDpWLE2RrvyLURsWmbc38nAl/0c2BBhI90YTaygoEANGjQotKSkRJWVlamJEydmLliw4FxTt6s1a6quDTvAWSlVijETcQ74G3CDaf8iYCMSSAghmkjs9+sqgofiQgMoH1wcumFbdA7HrMP0PfQNAD+OdeCzCOOf0lY1xXUL5eTkpLds2XLU09OzvLi4WEVFRfXYsGFD9qhRo/Kbum2tVaMHElrrJKXUW0ACUAis01qvU0r5aa2TTcckK6U6VHW+Uuoh4CGAwMDAxmq2EKINsMxCZKcmoGx98e95PwClF44S9t9XAMjoaMPBQNjSy4bssf2JBJmdspmwsbHB09OzHKCkpEQZDAallGrqZrVqTdG10Q64DegGZAErlFLTrT1fa/0x8DFAZGSkbog2CiHaJssshLL1pZ1/BIXDfHD79G+Ebt4DQNKwAp4e7gHYGNfHkJkpq/Ti1he7nMg8Ua/LiF/b7tqCV4e+WutiYAaDgT59+vRKSEhwnDFjRtrIkSMlG9GAmqJrYzRwWmudDqCU+gYYAqQqpTqZshGdgLQmaJsQoo2oPJwzP6uEzOQzFVmItNwizqceIuIv99Ax4wIA399kz6IBHoB0YzRndnZ2HDly5FBGRobt+PHju+/atcspKiqqqKnb1Vo1RSCRAAxWSrlg7NoYBcQC+cAMYJ7p5+omaJsQoo2oPJwzK60AZetLr2HXc6G/D/bvPMO43w8ClsWUWhbZspI1mYOG5uPjUzZs2LDc7777zlMCiYbTFDUSO5RSK4E9gAH4HWNXhRuwXCn1AMZgQz6lQogGZTmhlKM7uAzxZf+OGLp++SXXnT8FQNLN7jzdvxCQLERLcO7cOTsHBwft4+NTlpeXpzZu3Ojx7LPPpjR1u1qzJhm1obV+CXip0uZijNkJIYSod5W7MlJOnKSsvD2FhVnYdXTikH0Zqw8l8Pm+GPxyMsnrVM7Wfk58FiFBREty9uxZ+5kzZ3YrKytDa61uu+22C/fcc48sId6AZGZLIUSbYO7KcPEKoDC3hLLy9tg6hOIyxJeda5Zzw9k93O2Qg3d2Brk+5dw/0wkol66MFmbQoEGFhw8fPtTU7WhLJJAQQrQqlTMPZiknTmLn6Edh4QSwg279vSi9cBT90fM8aerGyO9kIL6DLT+EOQCShRDCGhJICCFaFcsiSjCOxjBnICi7lsCeXoQM9MN/2xuk/Nc4tXV+JwNbeik+G+gEGBfZmiNZCCGsIoGEEKLFs8xCmIOIKS/N4+DmpIp1Mbr1NwYQiVu/I2fOUmySMwD4drQdX1ZapVMCCCGsJ4GEEKLFs8xC+AZ1o+fQGy4GEcAN03rQ23kdZz75iMBfjXV3CQGaH8Js2RAhAYQQV0MCCSFEq2CZhTi2M5Vzxy8GEcXfzeXMtg0UpDsC8NFYm4oFtqQLQ4irI4GEEKLFMndpmLMRllkI/2AvnM6uQ73wZ5xTDRTgyInO9mzoU8aGCBsppBSinkggIYRosSyDCM8O/S52ZXRbh9uxjRSYujEuLrA1AECyEK2cwWAgLCysV8eOHUt++eWXE03dntZOAgkhRItReWinOYjoM/KJiiBiYNGnuMVsv6wbQzIQbcdrr73md+211xbm5eXZNnVb2gKbpm6AEEJYy5yBMPMN6oannfulQcT23ylId+RgoDGIyB47UIKINuTkyZP2P/74o+eDDz6Y0dRtaSskIyGEaLaqy0BUFFVu2MfJs8a5H3okf43b0d+BiwGEjMRoOuf+/o8uxceP1+sy4o7BwQX+//fPGhcDe+yxx7q88cYbidnZ2ZKNaCRWBxJKqXaAP8YVO+O11uUN1iohhODyyaXMtRCr5u/h3PEswIkOZYdod2IvAclbK2ohhj46VwKINmjZsmWePj4+huHDhxfExMS4N3V72ooaAwmllCfwGHAP4ACkA06An1JqO/C+1vqXBm+lEKLNMmcgAA5+uYKNW9oDWXQoO4Rfaiy+x3YAUgvR3NSWOWgIW7Zscfvpp5+8AgICPIuLi23y8/Ntbrvttm6rV68+XfvZoq5qy0isBBYDw7XWWZY7lFIDgHuVUtdorT9roPYJIdqgysM6wTKIgF6py+l4+FcA4gKc2RpWLEGE4L333kt67733kgBiYmLc58+f7ydBRMOrMZDQWo+pYd9uYHe9t0gI0eZZrtRZdKE9q2Yv4lxuFwCCM2JwO76DA36+/BZxng0RpUT6DZQhnUI0EatqJJRSCpgGXKO1fkUpFQh01FrvbNDWCSHajKrWy3Bwm0zGqRQgHm99CrfUONqd+JXT7d159f5MQLIQomoTJkzInTBhQm5Tt6MtsLbY8n2gHBgJvALkAv8FohqoXUKINsayK8PF2Y2iFEeydTLu+Wfpk/QRhnMlABzv7MdvfdKRIEKI5sHaQGKQ1rq/Uup3AK11plLKoQHbJYRog3yDunFNaQd2lt8EgFfWMXxTY0ksdSOtvRe5o7vx7jW/IkGEEM2HtYFEqVLKFtAASilfjBkKIYSwSuU5IS6Rm0J6cjpOypmdbsYgolPSakovnGBP+DDWRwRj77GPhEJjgaUEEUI0H9YGEguBVUAHpdQ/gbuAFxqsVUKIVqfyKAwAclMgL538AhvQ3uQ7DMAOcCr6legJdxMYtJ8MvZ3k1FgolOW+hWiOrAoktNZLlVK7gVGAAv6gtT7coC0TQrRoNc1KaXbw9ec5lDOIQpceKMAn6xhH9TGOXjeW6IevY9bajzl64agEEEI0Y9aO2ngXiNZav9fA7RFCtBJVzUrZc+gNEPs5HFjJrt3B7DTcCjbGWghDXjxb3Oy5cN0tBAbtrwgienj34POxnzftmxFCVMvaro09wAtKqRCMXRzRWuvYhmuWEKKlsSYDAZD55+EciA/mQKdbAQhM+ZY1Tu780Gc4/3d7GPbtdvDKtn8DF7syhLBWQEBAmKura5mNjQ12dnY6Li7usuz5M8884+/m5lb2yiuvpNb36y9cuLD9rbfemhMUFFRa03FHjx51mDBhQvDx48cP1sfrTpkypetf//rX1AEDBhRdzXUWLlzYPjY21nXx4sUJ1p5jbdfGImCRUsobuBN4XSkVqLUOrmNbhRCtTLUZCJPMN/5Mzk+bOG4YwNEeUwFIKjjCm6FjGNTNm0lB+/kpcyWxR4zfUaSgUtTVr7/+eqxTp06GpnjtL7/80ic8PLywtkCiPhkMBqKjo8801utVdqWrf14LhAJBwKF6b40QokWrKgNB7OdkLvkPu/f3INXvYbK8QgA41sWeFJ8I/i88oMoshAQRorG9+OKLfqtWrfIuKSlR48ePz1qwYME5gNGjR3dPTk52KC4utnnkkUdSn3322QyDwcCUKVOC9u/f76qU0tOmTcsIDAwsjYuLc7nvvvuucXJyKo+NjT3s5uamzdffvHmzyx//+McgZ2fn8kGDBuWZtxsMBh577LHOW7dudS8pKVEPPvhg2uzZszNiYmLc586d69+uXTvDqVOnnAYNGpS7ZMmSBFtbW1xcXCIeeuih1J9//tnjzTffTHzxxRcD3nrrrbPbtm1zPX36tOOHH36YCMYMw+7du10WLVp09v333/f+4IMP/EpLS1X//v3zFy9efMbOzo533323/YIFCzr5+vqWdu/evcjBwUFffneqZ22NxOvAHcBJYDnwauW1N4QQbU9Vs1Fa2vPXB2m/bQPH7UZWZCHO2ZeT19GRd/8xHIAVx1bwyrZXAMlCtCYbFh/uciEpr16XEfcOcCsYdV/PWhcDGzVqVLBSilmzZqU/++yzGdZc+5tvvvE4ceKE0/79+w9rrRk9evS1P/zwg9u4cePyli5dGu/n51eWl5enIiIiek2fPj3z+PHjjsnJyfbmromMjAxbHx+fsg8++KDDW2+9dXbEiBEFlV/jgQceCFqwYEHC+PHj8x5++OHO5u3vvPOOj6enZ1lcXNzhwsJCFRUVFTpx4sQcgAMHDrj+/vvvcSEhISUjRowIXrx4cbtZs2ZlFhYW2vTp06fwnXfeOQfw4osvAnDvvfdmDh48OBRIBFi5cqX3P/7xj+Q9e/Y4rVy50js2NvaIo6Ojnj59euCHH37YfuLEiTnz5s3z371792Fvb++yIUOG9OjTp89lba+JtRmJ08B1Wmur/ocIIdoGy+4My64MczfGBcMADgf8tVIWwo7bwgMACSJE/du6deuRoKCg0qSkJLuRI0eG9O7du2jcuHF5tZ23du1aj02bNnn06tWrF0BBQYHNkSNHnMaNG5f3+uuv+33//fdeACkpKfYHDx506tu3b9HZs2cdZ8yY0WXixInZt99+e05N1z9//rxtbm6u7fjx4/MA7r///vM///yzJ8D69es9jhw54vLtt9+2A8jNzbU9dOiQk4ODgw4LC8vv1atXCcDkyZMvbN682W3WrFmZtra2zJw5M7Py6/j7+xu6dOlSvGHDBtfevXsXnTp1ymnMmDF58+bN842Li3Pp169fT4CioiKbDh06GDZt2uQ6ePDgXH9/fwPAHXfcceHYsWNOV3DLa11GPFRrfQTYCQSa1tiooLXecyUvJoRo2WoqqMyMXk7Ooq848++3KThylqROQyuyEP7BXoQM9OOx4RcDiFlrXyI2VeohWitrMgcNwVybEBAQYBg/fnzWtm3bXK0JJLTWPPXUU8mzZ8++5AtzTEyM+6+//uoeGxt7xN3dvXzgwIE9CgsLbXx9fcvi4uIOrVq1yuP999/vEB0d7b1ixYr4mq5vXLaqyn1q/vz5CXfeeeclwUhMTIx75XPMzx0cHMrt7Kr+J/yuu+7KXLZsWbvQ0NCicePGZdrY2KC1VpMmTTpvXh3VbMmSJV7VtctaNrXsf8b0c34V/711Va8shGhxzBkIM9+gbgQ6unHm3vtIeeklCnbt4ky5P3ujnqwIIlyG+HL7X/rTe/ilWYjY1Fgi/SIliBD1JicnxyYzM9PG/PiXX37x6Nu3b6E1544bNy5nyZIlPtnZ2TYAp0+ftk9KSrLLysqy9fT0LHN3dy///fffnfbt2+cKkJycbFdWVsbMmTOzXnvttaQDBw64ALi5uZVlZ2fbVr6+j49PmZubW9mPP/7oBvDFF194m/eNGTMm+4MPPvAtLi5WAPv373fMycmxAWPXxpEjRxzKyspYuXKl9/Dhw2tdiGz69OmZa9eubbdixQrvqVOnXgAYO3ZsTkxMTLukpCQ7gNTUVNtjx445jBgxIn/79u3uKSkptsXFxWrVqlXtrLlflmpbRvwh08NxWutLhpQopa4o9SGEaDmqm8668pDOzOjlxgACcAntQpqXDwec7gPArqMTw0Z1pffwAFYcW8GaU2sAJAshGkxiYqLd7bfffi1AWVmZuvPOO8/fddddVXY5LFiwoNNHH33kZ36empq6/+DBg05RUVGhAC4uLuVLly49feedd2Z//PHHviEhIb26d+9e1K9fv3yA+Ph4+wceeCCovLxcAbzyyiuJAPfdd1/GE0880XX27NmXFVt+9tln8eZiy5EjR1a06+mnn86Ij493DAsL66m1Vt7e3qVr1qw5CRAeHp73l7/8pfORI0ecBw0alHvvvfdm1XYffH19y4KDgwuPHz/ufOONNxYADBgwoOiFF15IGjVqVEh5eTn29vZ64cKFCaNGjcp/7rnnzg0ePLinr69vad++fQvKysquKEWhtK69OFMptUdr3b+2bY0tMjJSx8bKdBZC1Lfol5+vsngSoOfQG+g7eiwAZ/5wEwVHztLxZh/OOfqxMedRwJiFmHVfWEUAYQ4eIv0iAWRURhNTSu3WWkfW93X37dsX369fP6mlqycxMTHu8+fP9/vll19ONHVb9u3b59OvX7+gqvbVViPREQgAnJVSERinxwbwAOq1GlcI0bxUOZTTxFxMWZRSQHrIdexmONk5xqDDZYgvboOPMGvt25cEEBI8CNE61TZq42ZgJtAZeNtiey7w97q+qFLKC/gU6INxRdH7gaNANMY5KuKByVrryypShRANo7ahnBViP+fAlmzO+jwMHRVZrsFQDFluNvj3bY/b4CMVIzEkgBCi7iZMmJA7YcKEWmsimlptNRLmGS3v1Fr/tx5f911grdb6LqWUA8bsxt+BDVrreUqp54Hngefq8TWFEDWobiinWeYbfyZj7UaS3SI44G+sg0iwLcPD2RhAdBh8hDWnFhG7TWoghGhLrJ0i+79KqfFAb8DJYvsrV/qCSikPYATGTAda6xKgRCl1G3CD6bBFwEYkkBCiQVWVhaiuO2PvtmLO+f2JLE/jnBDF6hT97rsJ+3Y7LgkgJAshRNti7cyWH2LMGtyIsUviLoxzS9TFNUA68LlSqh+wG/gz4Ke1TgbQWicrpTrU8fpCCCvVlIXIjF5OTkwMOelnsS3M4Jz/Y+S6dbYYjTHykgmlJIAQom2ydmbLIVrrvkqp/Vrrl5VS84FvruI1+wNPaK13mJYof97ak5VSDwEPAQQGBtZytBACrB/OaZb5xp9J+c86kjoNJb3zZADynDrj6pDLvXMnADIrpRDCqLYJqczME3oUKKX8gVKgmkqsWiUCiVrrHabnKzEGFqlKqU4App9pVZ2stf5Yax2ptY709fWtYxOEaFsqTyRlVlUW4swfbqoIIo72mMoF1x6UBPjTIdSf/nePACSIEM3X0aNHHYKDg3tbbnvmmWf858yZ41fdOQsXLmx/3333yTfTOrI2IxFjGmnxJrAH40iLT+vyglrrFKXUWaVUD631UWAUxpVEDwEzgHmmn6vrcn0hRNVqHM4ZvZycZZ9ScMQ4q3F6yCCO+l+cmXLGfcZujLdO/QvWyqRSQoiLrC22fNX08L9KqRjASWudfRWv+wSw1DRi4xQwC2N2ZLlS6gEgAZC/TkJcBWuHc5pnpwRjABHfYSi5dt0BuGFaDw75/XbZnBBSDyFaooEDB/YYMGBA3pYtWzxyc3NtP/zww/ixY8desg7H119/7Tlv3rxOP/zww4nHH3+8s7u7e9m+fftc09PT7V999dXEWbNmZZaXl/OnP/2p888//+yplNKzZ89OfvDBBzOnT58eOG7cuOxp06ZljxkzpruXl1fZihUr4hcsWOBz+vRph8ceeyxj3LhxwQMHDsyLjY118/PzK/nxxx9PWM5+2RLVNiHVHTXsQ2tdpzoJrfVeoKpZ1UbV5XpCiMvVNpwTLq2FyLw2nDTbXoBxka3crom8lf+CjMYQdfLjB+90yTh7pl4nLvTp0rXg5j89dVWLgRkMBnXgwIHD0dHRnq+88or/2LFjj5n3LV682Ovdd9/1++mnn477+vqWAaSmptrHxsYe2bt3r9Ptt99+7axZszIXL17sdeDAAefDhw8fTE5Oths4cGDPm266KW/EiBG5mzZtcp82bVp2SkqKQ1pamgbYunWr2z333HMBICEhwenLL788NWTIkDO33HLLNYsXL2736KOPXria99TUastITKxhn6buBZdCiHpW08qcl4n9nMwl/yHlx4xLVuk0j8g45Pcbb257BfIlgBAtS3UrWZq3T5o0KRNgyJAh+bNnz3Yw7//tt9/c9+3b5/LLL78c8/b2Ljdvv/XWW7NsbW0ZMGBA0fnz5+0BNm/e7D558uQLdnZ2dOnSxTBo0KC8LVu2uIwZMybvvffe89u9e7dTSEhIYVZWlu2ZM2fsd+/e7frJJ58kpKWl2QUEBBQPGTKkECAiIqIgPj7eseHuRuOobUKqWY3VECHE1bHMQMDlhZRARQCRsyeJ43YjSQ2fRpaXcV6IG6b1qFhgSwopxdW62sxBXfn5+Rkqr7554cIF227duhUDODk5aQA7OzssF6cKDAwsTkhIcIyLi3MaMWJEgXm7+XgwLgVu+bOybt26lWZnZ9t99913nsOHD8+9cOGC3eLFi9u5urqWt2vXrjwtLQ0HB4eKk21tbXVhYaG1gx6aLWvnkZhT1fa6TEglhGg4ta6P8d13FKQ7ktRpZJVZiLfWrpFCStGieXp6lnfo0KF09erV7rfddltuamqq7caNGz1nz56dtmTJEp/qzuvcuXPJggULzt5xxx3XRkdHn4yMjCyq7tjrr78+95NPPvF9/PHHz6elpdnt3LnTbeHChWcBBgwYkPfRRx91+Omnn46lpaXZTZ06tfv48eNb9XIP1o7ayLd47ARMAA7Xf3OEEFfK3KVRa0Hlf9aR1GkkZ6Ouo8DVeFxGeCrxQevYno/UQohWY9GiRacfffTRwOeee64LwHPPPXeud+/exbWd169fv+LFixefmjJlSvdvv/222hU377333qzffvvNrWfPnr2VUvrll19ODAwMNAAMGzYsb/PmzR59+vQpLi4uLsnOzrYdMWJEs18v42pYtYz4ZScp5Qh8q7W+uf6bZD1ZRlyIS5f8tlziGy6uj3FGR5HqF1nRjeEf7EXIQD/eyn+BoxeO0sO7ByDLe7cVsoy4uFJ1Xka8Bi4Yp7oWQjQBa9bI2PPXB3H+dsslxZRuXrlEjo80dmOc+ldFEPH52M8b+y0IIVoJa2skDmAcpQFgC/gCUh8hRBOpcY2MN/5sXGDLcQCED6ixmNLcjSGEEHVlbUZigsVjA5CqtTY0QHuEEJVUtU5G5SzEVzsSiH9wGtce249KNXAu/M/kuhvXxvC/xtiNIcWUohGUl5eXKxsbmxY9wZK4VHl5uQLKq9tv7cyWZ5RS7YAupnP8TBNS7amfZgohqlNVIaVlFuKrHQlsXvAJT+7dQ1KnoaRGRZHtEohtJ0+cphby7al/gRRTisYRl56e3svX1zdbgonWoby8XKWnp3sCcdUdY23XxqvATOAkF7s4NDDyKtsohLBCVTUQX+1IYO1j/4+ofTE8mXHhkloI+86lHPfZyNptywCZ1lo0DoPB8MeUlJRPU1JS+mD9opCieSsH4gwGwx+rO8Daro3JQHetdUm9NEsIUa3qZqi0dDELsZKkTkPZGzWAC67GkRfx4dtZ63wxgJDgQTSWAQMGpAG3NnU7ROOyNpCIA7yoZmlvIUT9qW6Gyq92JLB6bxID9m8kal8Md9r3ZE/4nyuKKe07l7Le4b8cdt4mAYQQotFYG0j8P+B3pVQcUDGph9ZaIk8h6qiqIkqoupDyn3uTuHnjM7yQeIRUu8Gc63zvxQDCJ4PjnU9UZCGkiFII0ZisDSQWAa8DB6ihclMIYb3qZqOsPJxz9d4kJmxeQOTvBy+tg6gUQEgWQgjRFKwNJDK01gsbtCVCtHJXtDonxkxE4uKl3H02hQKXkewJH1mRhXAfnceb+a8CEkAIIZqWtYHEbqXU/wO+5dKuDRn+KYSVrFqd08RcTHlnanJFBsLZPolcjxTOd4lnbb50YwghmgdrA4kI08/BFttk+KcQV6imDARczEJcm5DCMNeeHO1xIwA3DDvPWz4/V0xpHYlkIYQQzYO1E1Ld2NANEaI1qmpNjKp8tSOBlC/W0S5PEVDajuSAQQB0UKcpDM/hLZ/9si6GEKJZsnZCqjlVbdday3obQtSgpjUxzL7akUDRO8/gp0eT59YZJ87irE5xuMdxYkPTjFNap8q6GEKI5snaro18i8dOGNfeOFz/zRGidTBnIqorqLScE+LahBS0qzGI8LZPZdIjTszK2GTMQNBDiimFEM2atV0b8y2fK6Xewlh4KYSogmUQUVUWYvXeJA4l5zA9KZWEgNsAYzHlzt6prMk4Lt0YQogWw9qMRGUuwDX12RAhWjJrh3aaMxE3bVvLrWX+JHQ0zul2STElPejh3UO6MYQQLYK1NRIHuLhYly3gC0h9hBAm1gzt/GpHAnHvxTBWO1Lgej1FgHfhCew7JPKWz1nJQgghWiRrMxITLB4bgFSttaEB2iNEi1Xd0M6vdiSwY/0ZAk6nEeASSgHgXnCUTO8jrPtDjhRTCiFaNGsDiU7AQa11LoBSyk0p1VtrvaPhmiZE81XbCp3mLgyAUVt/IMTlBrBrh1fWMRzdf+PlUb8DEIks7y2EaNmsDSQ+APpbPC+oYpsQbUZNXRlf7Ujg668P0bPEloCyfEpdjNvD0lZQ0mU3T/cvBGRWSiFE62BtIKG01uYaCbTW5UqpuhZqCtHiXEkx5d9XHeDR3CI8bJxxz0kBUnD0iePzh4qITZUgQgjRulgbDJxSSj2JMQsB8ChwqmGaJETzY+06GTvWn2FKrgMeNgr33ASGJb3B8f4+xixEqiywJYRofawNJB4BFgIvYBy9sQF4qKEaJURzZM1KneE5HShx8sM1LxH7ol3MfbIHsQWJgGQhhBCtk7UTUqUBdzdwW4RoVmpbJ8McPAw/tAYf955ol/7kufnhXHwWp/ML2dLLBtwHEuneUbIQQohWq8ZAQin1AvC+1vpCNftHAi5a65iGaJwQTammdTLMc0L0LmnHKb9pZHmFAFCuTrAh5HcOj7KTDIQQok2oLSNxAPhOKVUE7AHSMa61EQyEA+uB/2vIBgrRWKwpqDQP6xy19QcCXG4gywWc9RHOeRznuM9uXPuW4grMuUaCCCFE21BjIKG1Xg2sVkoFA0MxzieRA3wJPKS1Lmz4JgrROGorqDy4OYnTq09xY3ZixZBOP7tveDnqV0BqIIQQbZO1NRLHgeP1+cJKKVsgFkjSWk9QSnkD0UAQEA9M1lpn1udrClE562CpuiGdny8+wLn95/HKK8cLcM/NA46R0fEwL0dIECGEaNuaci6IP2NcitzD9Px5YIPWep5S6nnT8+eaqnGidaqcdbBUeVKp1XuT6JhhIORsKV6AV/5x/BJ3EZC8lY/G2rAhwkaGcwoh2rwmCSSUUp2B8cA/gWdMm28DbjA9XgRsRAIJ0QBqGsYJxgzEkR0pBAGBZbYA9Dj6FQHJWzkYCDFjbcgeO5A5EkAIIYTVq38O1VpvrW3bFXgH+CvgbrHNT2udDKC1TlZKdaimLQ9hmsMiMDCwji8v2ora1sQwq5yBCMSWdgUnULoM38Tdl2QhpBtDCCEusjYj8S8uX1ejqm21UkpNANK01ruVUjdc6fla64+BjwEiIyN1LYeLNs6aAsotG85wKj2/ygxEQhcbyhztJYgQQohq1DaPxHXAEMBXKfWMxS4PwLaOrzkUuFUpdQvGoaQeSqkvgVSlVCdTNqITkFbH64s2rqqJpKrqyvh88QEKfks3PrGFELtiXAoz8D29pVIdRASAdGUIIUQVastIOABupuMsuyFygLvq8oJa678BfwMwZSSe1VpPV0q9CcwA5pl+rq7L9YWoaSIpMGYhju1MpeB4FgDF6hR3Jv2E+5H9AOR3MvDRWAfJQAghhBVqm0fiV+BXpdQXWuszDdyWecBypdQDQAIgf72F1azNQhzcnMTGpUcBOGdfTu/i34jYtAwwBhBbeik+G+gEyJBOIYSwhrU1Eo5KqY8xzvFQcY7WeuTVvLjWeiPG0Rlorc8Do67meqLtqi0LAZcGEd2KVnDj4S2oVAMAP4514LMI46+2DOkUQgjrWRtIrAA+BD4FyhquOULUXU1ZiGM7Uzln6soIPvc1XY5tBiC/iz1f9i5jQ0S5BBBCCFEH1gYSBq31Bw3aEiGuUHWrc5oDB4C03CIMKUUAuBtO4n9yBwHJW8nvYs+W6zrzWfezgNRCCCFEXVkbSHynlHoUWAUUmzdWtyqoEI2hqu4My+6LLDcbcgpLCTKk0DttA77HdgDmboxy4KxkIYQQ4ipZG0jMMP2cbbFNA9fUb3OEuDLm7oyL3RfGIOJH5xImBGzlD/t+wGZ7PgAJQY78EFoq3RhCCFGPrF206/KpAIVoJiyzEAm2Zbg7HeSTrt/hsPMQKbFeAPx4a3uWh5fTw7uHzAchhBD1yNopsl0wrokRqLV+yLSseA+tdUyDtk4Ik6pW7Uw5cRI7R7+KIOJH5xJ6u6zjsTPLyNnpzIV0L+P2yd1YHppFD+8efD7280ZuuRBCtG7Wdm18DuzGOMslQCLGkRwSSIhGYa6HcPEKoDC3BICy8vZQdi3nHMs47FDGH/OW0C92GymmACKhuzs/BOezoftZIr2NXRlCCCHql7WBRHet9RSl1D0AWutCpZRqwHYJcRkXrwAKCyeAHfgHe3EoOYd9NiVMz/yCPx6Ow3CuhAIcyb+2HV9em82GiEIi/WSVTiGEaEjWBhIlSilnjAWWKKW6YzF6Q4iGYu7SSDlxkrLy9ji6g8sQX74uzKOX2/e8FP8LNtvzMWCcE2JLhAef9c5GhnQKIUTjsDaQeAlYC3RRSi3FuPDWzIZqlBBgLKLc/HUMJQUpaOWDrUMox7rYs/pQAvfYbuDJM8suKaY0BhDZMiJDCCEakbWjNn5SSu0BBgMK+LPWOqNBWybanMoFlRln8yjKS8bJrRN2nafyfXYOvQtW8b3HTvwPnawIIj4aa8OG3hJACCFEU7B21MbtwM9a6+9Nz72UUn/QWv+vIRsn2hZzF4adox8ApcVl2Dj7oX3K6Ff+DP3cocepM5xMciMl2QswBhHZY6UOQgghmorVXRta61XmJ1rrLKXUS8D/GqRVos05uDmJjLN5lJW3x87uDrLcbGhXdp4udhuZ6LSYzBMuZJzrQMo5L1yBg4GQOLgbQ6fPkgBCCCGakLWBhM1VnCtEldZ+sIyTu7cCUFxoQJelY+PsZ5wPwnEd/7D/DIBU70jOZhVieyGHk4GwpZcNQx+dy1MSQAghRJOzNhiIVUq9DbyHceTGExjnlRDiipmnsz6951d0WTpObp1wdLbDYO9Ppm0+f3efy2Cbw2SecCEnLwzcO2KbuId4P8X3Tw+WOgghhGhGrA0kngBeBKJNz9cBLzRIi0SrtvaDZRza8isASmfg1akr9y94mx0r5qMPrKgIIM6kXkPB2SLgLAndsyjwU5wZ1EVmphRCiGam1kBCKWULrNZaj26E9ohW7ODmJA5tMWYh2nXqSr5NFwrsCzn4f8MYVHKAzFMuHD8XhOFcCVDEQVM3RvbY3gAyM6UQQjRDtQYSWusypVSBUspTa53dGI0SrY85E2EOIpzuforj377D/7P/CkrgYHwwNrH5QIlFADFQujGEEKKZs7Zrowg4oJT6Ccg3b9RaP9kgrRKtgrkWAqioh7BxcsXfZi9e309mqv1hADJdZmKzfR1gmhMiQmalFEKIlsLaQOJ7039CWMVyaW//YC+Ugw0GgzN/CVpt3O8QxpkzPSHVg4IjxiBi0XgXssf0lTkhhBCiBbF2ZstFprU2ArXWRxu4TaKFsyyo9PIsJe/IOVSRoqtTjvGACe/gf9KVlMUvAdkkdHfnl9AyUsf0lWJKIYRoYayd2XIi8BbgAHRTSoUDr2itb23AtokWpKpuDGd3d1wLTwDg6uhKQCcXMl1mkvPuLxTs2gUYsxCpY6SYUgghWipruzbmAgOBjQBa671KqW4N1CbRgpgDiIS4TZSVHMHR2Q7K03B1tOGRAONkqB97PknX4gC6HPyNlG+M3Rj5fYL4snMC2ZKFEEKIFs3aQMKgtc5WSllu0w3QHtGCWNZB2NmeoIwMSrEjwCmNnh7pHHQIIy/4diaVdyHlpZcowBhAbOml+Kz7WcCGOZKFEEKIFs3aQCJOKTUVsFVKBQNPAr81XLNEc7V//Vpiv19HYW4JxYUGALw6uJCTnoi7fSEPdt4OwJ6CyXgeLsbt8D5Sdn0KQMeXX+YZzx84euEokd6yUqcQQrQGVzKz5T+AYuAr4EfgtYZqlGi+Dm/dSHZqAsrWF0dnO5TKg+x4Otnn0dMjnVTvSByK+uD89ToKAJeoKFyiojge1Yk3TEFED+8e0p0hhBCtRI2BhFLKCXgEuBY4AFyntTY0RsNE82Kuhcg4m4ey9cW5+70ozx94KHuJcb9DGHnBD+Fg6sYAYwZifYRizak1xKaugVSI9IuUokohhGhFastILAJKgc3AOKAn8FQDt0k0E/vXr+Xw1o3kZ5WQlVYAGNfHsLFvh3/+MiayGIAdvecQUt6FnG9jLunGWB+heGXbK8DFAEK6MoQQonWpLZDopbUOA1BKfQbsbPgmieYi9vt1ZKcmoJUPAO4O57FVeUS6H6Cva0pFN0bHby/WQZiLKfd5/kDstlgAmaVSCCFasdoCiVLzA621odKoDdEKWRZTFuUlo2x9Kex0NwMdVjHIfguHdFdsE9w5cNQfD98ALuwyDuc010E87bkGgEj8JAshhBBtQG2BRD+llGk6QhTgbHquAK219mjQ1olGZ1lM6eTWiXJXN4a7/Y1e6gzx9t05Neorhv77BYrOHwHfiwHE0pA0Yx0EkoEQQoi2pMZAQmtt21gNEU3DXAcBkJ9VUhFEXCymXGg8MHAY/unX4vbvFyg6coTcru2ZN83461G5kFKCCCGEaDusHf4pWqnDWzeSHn8aF68AY0Gl8sHWuUuVxZQp/zGOxnCJiuKHbhkVQzklgBBCiLar0QMJpVQXYDHQESgHPtZav6uU8gaigSAgHpistc5s7Pa1NflZJcY6iMIJOLpDoPsqJrq+DkCqdyR+Q6YzKHIWZ+69D4AfJ3dj3xBbjl7IkvkghBBCNElGwgD8RWu9RynlDuxWSv0EzAQ2aK3nKaWeB54HnmuC9rV6VRVUOnXI5Hr7ZfR2+akigHA46UrsvM85X/gBHZIKOBkIn3U/SyR+9PDuIfNBCCGEaPxAQmudDCSbHucqpQ4DAcBtwA2mwxZhXCBMAokGEPv9OjKTz6BsfbGzc8PbvZB7Pe8HjN0Ygyb9hczo5aS89BKuQHwgEOBO4gAf5lw3S7owhBBCVGjSGgmlVBAQAewA/ExBBlrrZKVUh2rOeQh4CCAwMLCRWtpyVS6mtMxC3ByQUZGBwH0YhN3FoMhZrF/4HAHvfwvAR2NtGProXG4OmcTNTfg+hBBCNE9NFkgopdyA/wJPaa1zrJ2jQmv9MfAxQGRkpKxAWovDWzeScuIkdo5+FYtsOdi7E+yWQm+XXyoyEACZ0cs5OW8cAXHxgLEeYuh0yUAIIYSoXpMEEkope4xBxFKt9TemzalKqU6mbEQnIK0p2tba5GeVUFbeHju7O+jW34uOeV/Ru3w1h3TXS7oxTq74HNe4eFyBg4HgNeFWnnry9aZuvhBCiGauKUZtKOAz4LDW+m2LXd8CM4B5pp+rG7ttrYXlGhnmWghbvyOEFH9Fl/KTHNJdyXaZSei3vxEbPe6SACJxcDcCps9itGQhhBBCWKEpMhJDgXuBA0qpvaZtf8cYQCxXSj0AJADyL1kdHNycxOavYygpSEErH5StL74ehdyr/gYlcNAxDIesngQuf5cCTIWUFgHEUxJACCGEuAJNMWpjC8YptqsyqjHb0lpYDucsLjSgy9JxcuuEm88YIsuXVBRUOhT1we1AJja7tgDGQsoNETbMuW6OBBBCCCHqRGa2bAUsh3M6OtuhlDvXeBxirNMSAPYUTKb9yeKKBbYOBsKWXjZkjx3IHJmRUgghxFWQQKIFO7g5idiY78k8dwxl15mbx43C58KH+F2IJfOEC4diAylz9sE5fgsFQEJ3d34Izq/IQkgAIYQQ4mpJINECHdycxLGdqZw7nkVx7h4AOgR2wH/tk+ScceYAXbBLL0NhoLiPE+cqAohCIv0kCyGEEKL+SCDRQpiDB4Bzx7MA8Hc/S2bpBextyhh/9hNSYr0AKAztjV+QIx4TJvCM5w8cvZBND28JIIQQQtQ/CSRaiGM7U8lIzMOnsxtujrspy9xESXEmuQUeuBeXknLEC4COL79MXITig1NrgB8qVuiUxbWEEEI0BJumboCo2cHNSayav6ciiLj9+n045aymoLSUlIJ2eOQVE5CWQ25oXzq+/DLtpkxmzak1HL1wFEAW1xJCCNGgJCPRTFnWQQC4Oe4mI24n0XHJpBW44VCsGXXkBGDMQqw3ZyHWShZCCCFE45FAohk6uDmJjUuNGQX/jkV0VD9z6vAusstcsC11wq20FP/MXFyiojge1Yk3PH8gdlssAJF+kZKFEEII0WgkkGhGKmchbhh2nrJdL3A4x5eMMg/cC0voY9ceP29Hjt/cibkhacSmroFUYwBxixRTCiGEaGQSSDQTllkIN69c/G1+pveJL1iaGk56mSseRQa6eXhzZu5dfHBqjQQQQgghmgUJJJoByyDihm7r6F34gXG7QxgFxc54GAz0dbRly7V5fLbtFUACCCGEEM2DBBJN6LKuDI/36V34EzHHwkgudMPB0YkC2xIcbMuZNTERkABCCCFE8yKBRBOxzEL4uJzhmgs/4XZwD7/oPqR7OlLgrDAYCrAtLyPRJ18CCCGEEM2SBBJNwDKI6N9pDUHHV7D/lB9x7bpR5uJKrjJQ5FjK3mmdAbjlmlv4pwQQQgghmiEJJBpR5a6MkNL/0mH9OrLSXTjX3Z0LHk7kd7CloLSYkh7tZR4IIYQQzZ4EEo3EMgvRoewQKmMLiSXpJHoEUtrBjmx7G9K8iskY1wHwknkghBBCtAgSSDSwylmIsHOL8T22g+3d/cl2daLMBVKci4Eyeg27kVlj/9Gk7RVCCCGuhAQSDcgyC+GVdQy/1Fi6GjZxPKA96e0dSXctZu3gVCmkFEII0WJJINEAKmchehz9CoPjQRI6unPaewjJdvnYZxTj7uDOnOselgBCCCFEiyWBRD06uDmJQ9/HkZZlD1zMQmQFx3LIuRtOFwwU2eVTUFqAi48Lf5j4MH1DxjZxq4UQQoi6k0CiHh3671ZSL8RTXhyHU1kOxYY8jnRSnLH1wTujmCIfR06P88JcTClBhBBCiJZOAomrdHBzEof+u5XSC1nkOvhTXhxHORlccHVFewVwoSQJAPfOnRgxZhJ9R0vwIIQQovWQQOIqZL7xZ/bF9SbXwR+3kgu46iQK7IpIcbclbqQ9CYV7AJhz3RypgxBCCNEqSSBRB+YsRElKT/Lc/HEtTqLccQOJXi6QkUe5KqGDhw8dPGQ0hhBCiNZNAokrtOuFt9mZEQ744MUFysnk5FAP1GED9hnpXPAokfkghBBCtBkSSFyBi0EEBCQv46DvUQod21G8Lx/vHAdKfRwZ+NgsyUAIIYRoMySQqEVm9HIOrD1GgvYn2ykcgCz1Xz68Yztjt/vhm1NOkbc77p29jcWUMhJDCCFEGyKBRDUyo5eTExPD8UQHjvaYCoDK/YlcdZQs9xwm7bkWtwIIuLYHU16a18StFUIIIZqGBBJVyIxezu4P15HqN4SsHiEA/HrN13Q9fQrfPGe6enTF18UXvKHn0BuatrFCCCFEE5JAwsKuBas5cSif8twcskxZiHMexznusxvXvqV0Pd8V346+koEQQgghTCSQsHDiUD452hNHh1wKiteTZ3ME+5xcRhR74VvYnfS00xDk29TNFEIIIZoNm6ZuQHOQGb2c/931BBdsO2JXcpb5o/5NmtNOPEsM9Ow0AF/v7gD4BnWTrgwhhBDCQrPLSCilxgLvArbAp1rrBulHOLg5ie0rf0dlJuNYUkaWz+0YiveTVbaJ27d3wavAUQophRBCiFo0q0BCKWULvAeMARKBXUqpb7XWh+r7tX5dvgVd6otXSRn5jlDGcQy2u3B0sKd3R2OBpWQfhBBCiJo1q0ACGAic0FqfAlBKfQ3cBtR7IEHaWigrIMUxA0dne/w6hZMeb8A3qJtkIYQQQggrNbcaiQDgrMXzRNO2Ckqph5RSsUqp2PT09Dq/kK2KB9vzdHZ3wtetIyA1EEIIIcSVam4ZCVXFNn3JE60/Bj4GiIyM1FUcb5WHv/6lrqcKIYQQwqS5ZSQSgS4WzzsD55qoLUIIIYSoRXMLJHYBwUqpbkopB+Bu4NsmbpMQQgghqtGsuja01gal1OPAjxiHf/5Ha32wiZslhBBCiGo0q0ACQGu9BljT1O0QQgghRO2aW9eGEEIIIVoQCSSEEEIIUWcSSAghhBCiziSQEEIIIUSdKa3rPKdTk1NKpQNnruISPkBGPTWnNZL7UzO5P7WTe1Szpro/XbXWvk3wuqIVatGBxNVSSsVqrSObuh3Nldyfmsn9qZ3co5rJ/RGtgXRtCCGEEKLOJJAQQgghRJ219UDi46ZuQDMn96dmcn9qJ/eoZnJ/RIvXpmskhBBCCHF12npGQgghhBBXQQIJIYQQQtRZiw0klFJjlVJHlVInlFLPW2zvp5TappQ6oJT6TinlUcW5QUqpQqXU70qpw0qpnUqpGY37DhqeUuo/Sqk0pVRcpe3W3iOtlHrVYpuPUqpUKfXvxmh/Y1BKdVFK/WL6PTiolPqzxb5opdRe03/xSqm9VZwfVPn+tiY1fM7mKqWSLO7PLdWc31sp9bNS6phS6rhS6kWllKrlNf9e3++jodXwWXtVKbXfdI/WKaX8qzi3Vf8OidavRQYSSilb4D1gHNALuEcp1cu0+1Pgea11GLAKmF3NZU5qrSO01j2Bu4GnlVKzGrjpje0LYGwV2629R6eACRbPJwFXtKy7UqrZrTBbiQH4i+n3YDDwmPl3SWs9RWsdrrUOB/4LfNN0zWx8tXzOABaY749p1d7K5zsD3wLztNYhQD9gCPBoLS/d4gIJqv+svam17mv6HYoB5jRmo4RoDC0ykAAGAie01qe01iXA18Btpn09gE2mxz8Bd9Z2Ma31KeAZ4EkApZSr6RvGLlPW4jbTdlul1Fumb/L7lVJP1PP7qlda603AhSp2WXuPCoHDSinzhDlTgOXmnUqpiUqpHaZ7tF4p5WfaPlcp9bFSah2wuD7eS0PRWidrrfeYHucCh4EAy2NM36AnA8tqupZSaqZltkYpFaOUusH0OE8p9U+l1D6l1HbzvWrmavqcWWMqsFVrvQ5Aa10APA48D6CUclNKfW7xebpTKTUPcDZ9g19av2+n4VT3WdNa51g8dQVqrG43ZSc2K6X2mP4bYtp+g1Jqo1JqpVLqiFJqaW2ZHSEaS0sNJAKAsxbPE7n4xz8OuNX0eBLQxcpr7gFCTY//AfystY4CbgTeVEq5Ag8B3YAIrXVfoMX8oavkSu7R18DdSqnOQBlwzmLfFmCw1jrCdNxfLfYNAG7TWk+tt1Y3MKVUEBAB7Ki0aziQqrU+fhWXdwW2a637YQziHryKazWWmj5nAI+bAoD/KKXaVXF+b2C35Qat9UnAzdSd9iKQrbUOM32eftZaPw8UmrIc0+r13TQRUwB5FphG7RmJNGCM1ro/xsB9ocW+COApjNmha4Ch9d9aIa5cSw0kqorEzZH+/RjT07sBd6CkDte8CXje1Ce+EXACAoHRwIdaawOA1rqqb/stwZXco7XAGOAeILrSvs7Aj0qpAxi7R3pb7PtWa11Yf01uWEopN4zdF09V+hYJxvdeYzbCCiUYU9tg/Mc16Cqv1xhq+px9AHQHwoFkYH4151f3DVxj/Dy9V7FB68y6NrQ501r/Q2vdBeMXj8drOdwe+MT0mVqBMWgw26m1TtRalwN7aRm/Q6INaO7919VJ5NJv0Z0xfVPWWh/BGAiglAoBxlt5zQiMaW0w/gG8U2t91PIAUyqxxU+8cSX3SGtdYgo4/oIxUJhosftfwNta629NKfy5Fvvy67fVDUcpZY8xiFiqtf6m0j474A6MGZbaGLg0OHeyeFyqL07aUkbL+OzV9DlLNW9USn3CxSDJ0kFghOUGpdQ1QJ7WOre1fJ6uwFfA98BLNRzzNJCKsZ7EBiiy2Fds8bil/A6JNqClZiR2AcFKqW5KKQeMxZLfAiilOph+2gAvAB/WdjFTSvstjP8wAvwIPGHug1RKRZi2rwMeMRcQKqW86+sNNaY63KP5wHNa6/OVtnsCSabHLXLUi+n/8WfAYa3121UcMho4orVOtOJy8UC4UspGKdUFY41BS1bT56yTxXG3Y+wuq2wpMEwpNdp0jjPGVP0bpv3rsPiGbtE9UmoK7lo8pVSwxdNbgSO1nOIJJJuyDvcCtg3VNiHqS4sMJExdC49j/Af/MLBca20eTXCPUuoYxg/sOeDzai7T3VQkeBhjAeG/tNbmY1/FmGLcbxqWZR4C+SmQYNq+D2MxWbOllFoGbAN6KKUSlVIPmHZZe48A0Fof1FovqmLXXGCFUmozLXep6KEY/2CPVFUPZbybmrs17Lj4TXErcBo4gDEw3dMA7W00tXzO3jAXSWKsI3q6ivMLMRZnvqCUOorxvuwCzAWprwHtlFJxps/TjabtH2P8jLWYGqQaPmvzTO9vP8Ys4J+rON3yd+h9YIZSajsQQgvK7Im2S6bIFuIqmEb0TNNaT27qtoiWSX6HREsnfWxC1JFS6hWM37hnNnFTRAslv0OiNZCMhBBCCCHqrEXWSAghhBCieZBAQgghhBB1JoGEEEIIIepMAgkhroBSqsw0RPSgad2MZ0zzcdR0TpBSqlkPFRZCiLqSQEKIK2NeB6I3xqnDb6HmmQrBOJWxBBJCiFZJRm0IcQWUUnlaazeL59dgnGTJB+gKLMG4QBfA41rr30yTC/XEOFnVIoyzO84DbgAcgfe01h812psQQoh6JIGEEFegciBh2paJceXYXKBca11kmhp5mdY60rQOybNa6wmm4x8COmitX1NKOWKcEXOS1vp0Y74XIYSoDzIhlRBXz7xKpj3wb6VUOMZFlUKqOf4moK9S6i7Tc08gGGPGQgghWhQJJIS4CqaujTIgDWOtRHUrN15yGvCE1vrHRmmkEEI0ICm2FKKOlFK+GFdO/bdpifDqVm7MBdwtTv0R+JN5hUulVIhSyhUhhGiBJCMhxJVxVkrtxdiNYcBYXGlefvx94L9KqUnAL1xcuXE/YDCtcPkF8C7GkRx7TMuYpwN/aJzmCyFE/ZJiSyGEEELUmXRtCCGEEKLOJJAQQgghRJ1JICGEEEKIOpNAQgghhBB1JoGEEEIIIepMAgkhhBBC1JkEEkIIIYSos/8PYEJtsh5jyZUAAAAASUVORK5CYII=", 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", 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", 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", 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Y165ddw4aNKjSN9koSYqIVFC5BclnjYX5z1Rsh+vmBzVaJZLZs2c3HDBgwOFnnHHGFzk5OTvjPJaSpIhIBSRtPc5/puJJr00O5JxTzZFmr6OPPnrHqlWr5tfEsZQkRUQiqNB0Vm1yIHvrsBYVFRVZnTp10n8y4oiKiooMKCptXaxJ0syuBn4JODAfuBhoDEwEOgArgHPdPXL1AxGRmqZrj3tZUFBQ0KVVq1absyFRFhUVWUFBQQtgQWnrY0uSZtYO+A3Qxd2/NrOngfOBLsBr7j7azEYAI4Dr44pDRKSyNBnyvgoLC3+5bt26MevWresG1El1PNWgCFhQWFj4y9JWxt3dWg9oZGa7CFqQa4AbgJPC9eOBaShJikgaKeu2jtqeIAGOPvroDUD/VMdRU2JLku6+2szuBlYCXwNT3H2KmbV297Xha9aa2UGlbW9mw4BhAIceqg+miNQMda1Koji7Ww8ABgAdgS+BSWZ2YdTt3f0R4BGA/Pz8jO/3FpH0pq5VKU2c3a19gOXuXgBgZs8BvYD1ZtY2bEW2BTaUtxMRkbip9ShliTNJrgSOM7PGBN2tpwCzgK+Ai4DR4e/JMcYgIlImtR4lmTivSb5nZs8Ac4BC4EOC7tOmwNNm9guCRDo4rhhEREqjgTkSVayjW939VuDWEot3ErQqRURqnLpWpSJUcUdEagV1rUplKEmKSFYrTo6dVk7i6rozaNa8Hi2b7kfrRQ2h0nNDlEPFyrOKkqSIZK3ErtWRzd/n8KJVNGibG+9BVaw8qyhJikjWKa1rteuiFkBuNhcelxgoSYpIVilzYE4cXauS9ZQkRSQraGCOxEFJUkQymu55lDgpSYpIRlJylJqgJCkiGUcFAaSmKEmKSEZJTJC67ihxU5IUkYyggTmSCkqSIpL21L0qqaIkKSJpS61HSbXISdLMDgAOJpgbcoW7F8UWlYjUeomtxxtbz2RA3RlVq7eqmqpSCXXKW2lmLczsRjObD8wE/g94GvjMzCaZ2ck1EaSI1C4lB+cM238Orb/6uGo7VU1VqYRkLclngL8AP3T3LxNXmNnRwM/MrJO7PxZTfCJSi5TZvbqIIMmp7qrUsHKTpLufWs662cDsao9IRGodFQaQdBXpmqSZGTAE6OTut5nZoUAbd38/1uhEJOtp5Kqks6gDdx4EioAfAbcBW4FngZ4xxSUiWU4jVyUTRE2Sx7p7DzP7EMDdvzCzBjHGJSJZTK1HyRRRk+QuM6sLOICZtSJoWYqIRKbWo2SaqEnyfuB54CAz+x1wDnBzbFGJSNZR61EyUaQk6e4TzGw2cApgwE/cfXGskYlIVlDrUTJZ1NGt9wET3f2BmOMRkSyi1qNkuqjdrXOAm82sM0G360R3nxVfWCKSydR6lGwRtbt1PDDezA4EBgG/N7ND3f3wWKMTkYxSWlGAaw6cwbGLHqx8zVVQ3VVJmYrOAvI94EigA1X7yItIlimza3XsHVVPcqq7KikS9Zrk74GzgWUEBc5vL1nLVURqp0hdq6q7KhkqaktyOXC8u2+MMxgRySwamCPZrtwkaWZHuvsS4H3g0LBm6x7uPifO4EQkPWlgjtQWyVqS1wDDgD+Uss4JarmKSC2h2Tqktkk2Vdaw8OEZ7r4jcZ2ZNYwtKhFJO+paldoo6jXJGUCPCMtEJMuoa1Vqs2TXJNsA7YBGZtadoCQdQHOgcbKdm9n+wBigG0H37M+BpcBEgttIVgDnuvsXlYpeRGKl1qPUdslakqcDQ4H2wD0Jy7cCN0bY/33Aq+5+Tji1VuNwu9fcfbSZjQBGANdXNHARiY9ajyKBZNckiyvtDHL3ZyuyYzNrDpxAkGRx92+Ab8xsAHBS+LLxwDSUJEXSggbmiOwtalm6Z83sTKAr0DBh+W3lbNYJKADGmlkuMBu4Emjt7mvD7dea2UGlbWxmwwhG1nLoofqCisRNXasi+4pacedhgq7SkwmuMZ5DcO9ksn33AIa7+3vhTCIjogbm7o8AjwDk5+d71O1EpGLUtSpStqijW3u5+1Fm9pG7/z8z+wPwXJJtVgGr3P298PkzBElyvZm1DVuRbYENlQtdRKqiODl2WjmJq+vOoFnzerRsuh+tFzWs3srMKk4uGaxOxNd9Hf7ebmYHA7uAjuVt4O7rgM/N7Ihw0SkEX70XgYvCZRcBkysUsYhUWXHX6nvL/8OFTd6nR4NVdG3bgtbNYrj9WcXJJYNFbUm+HN7OcRfB3JJO0O2azHBgQjiy9VPgYoLE/LSZ/QJYCQyuaNAiUjmlda12XdQCyFUBcpFSRB24c3v48Fkzexlo6O6bI2w3F8gvZdUpkSMUkWpR5sAcTXonUqZkxQTOLmcd7p7suqSIpJgG5ohUXrKW5FnlrHOSD94RkRTSbR0iVZOsmMDFNRWIiFQftR5FqkfU+yRHlrY8STEBEalhqpgjUr2ijm79KuFxQ6AfsLj6wxGRylByFIlH1NGte026bGZ3E9zvKCIppuuOIvGJ2pIsqTFBbVYRSRFddxSJX9RrkvMJRrMC1AVaAboeKZIC6loVqTlRW5L9Eh4XAuvdvTCGeESkHBXqWp01FuY/k3ynqq0qUqao1yQ/M7MDgEPCbVqHxQTmxBqdiACV7Fqd/0y0BKjaqiJlitrdejvB5MnL+Lbb1YEfxROWiBSr0sCcNjmqySpSBVG7W88FDnP3b+IMRkS+pYE5IqkXNUkuAPZHcz+KxE4Dc0TSR9Qk+b/Ah2a2ANhZvNDd+8cSlUgtpXseRdJL1CQ5Hvg9MB8oii8ckdpJXasi6Slqktzo7vfHGolILaXWo0j6ipokZ5vZ/xKUokvsbtUtICKVpNajSPqLmiS7h7+PS1imW0BEKkEDc0QyR9RiAifHHYhIbaCuVZHMovkkRWJW3HIE1LUqkmE0n6RIzCbPXc2itVvo0rZ59bYek9VmVU1WkSrTfJIiMSluQRYnyImXHl+9B0hWm1U1WUWqTPNJilSzsgbmxEK1WUVipfkkRaqRBuaIZBfNJylSDXTPo0h2ipok2wIL3X0rgJk1NbOu7v5efKGJZAa1HkWyV9Qk+RDQI+H59lKWidQqaj2KZL+oSdLcvfiaJO5eZGaVHfQjkvHUehSpHaImuk/N7DcErUeAy4FP4wlJJH2p9ShSu0RNkpcB9wM3E4xyfQ0YFldQIulG9VZFaqeoxQQ2AOfHHItIWlLXqkjtVW6SNLObgQfd/T9lrP8R0NjdX44jOJFUUteqiCRrSc4HXjKzHcAcoICgduvhQB4wFfifOAMUSQW1HkUEkiRJd58MTDazw4HeBPdLbgGeBIa5+9fJDmBmdYFZwGp372dmBwITgQ7ACuBcd/+iKm9CpLrE2npMVpC8olTAXCR2Ua9Jfgx8XMljXEkwY0jz8PkI4DV3H21mI8Ln11dy3yLVokYG5iQrSF5RKmAuErtY73U0s/bAmcDvgGvCxQOAk8LH44FpKElKitT4qFUVJBfJKHEXBPgj8FugWcKy1u6+FsDd15rZQaVtaGbDCG8zOfRQXQuS6qfrjiKSTNRZQHq7+/Rky0qs7wdscPfZZnZSRQNz90eARwDy8/M9yctFItOoVRGJKmpL8k/sW6e1tGWJegP9zezHBCNim5vZk8B6M2sbtiLbAhsqGrRIZagggIhUVLL7JI8HegGtzOyahFXNCeaVLJO73wDcEO7nJOBad7/QzO4CLgJGh78nVzZ4kajUtSoilZGsJdkAaBq+LvG64hagssPqRgNPm9kvgJXA4EruRyQpda2KSFUku0/yTeBNMxvn7p9V9iDuPo1gFCvuvgk4pbL7EolCXasiUh2iXpPcz8weISgAsGcbd/9RHEGJVIW6VkWkukRNkpOAh4ExwO74whGpPHWtikh1i5okC939oeQvE0kNtR5FJA5Rk+RLZnY58Dyws3hhWbODiNSUSrUeq7uGalSqtSqScaImyYvC39clLHOgU/WGIxJNlQbmVHcN1ahUa1Uk40QtcN4x7kBEoqqWrlXVUBWRCKKWpWtMUKD8UHcfFk6ddYQmW5aapIE5IlLTona3jgVmE1TfAVhFMOJVSVJqhAbmiEgqRE2Sh7n7eWZ2AYC7f21mFmNcIoBajyKSWlGT5Ddm1ohgsA5mdhgJo1xF4qDWo4ikWtQkeSvwKnCImU0gmOFjaFxBSe2m1qOIpIuoo1v/ZWZzgOMAA650942xRia1juqtiki6iTq6dSDwuru/Ej7f38x+4u4vxBmc1B7qWhWRdBS5u9Xdny9+4u5fmtmtwAuxRCW1hrpWRSSdRU2Sdaqwrcg+1LUqIpkgaqKbZWb3AA8QjHAdTnDfpEiFlJYcrzlwBsduex0WEfzETTVURSSiqElyOHALMDF8PgW4OZaIJGuVed1x7B01m7hUQ1VEIkqaJM2sLjDZ3fvUQDyShSJdd1QtVRFJQ0mTpLvvNrPtZtbC3TfXRFCSPTRqVUQyWdTu1h3AfDP7F/BV8UJ3/00sUUnG06hVEckGUZPkK+GPSFJqPYpItohacWd8WLv1UHdfGnNMkoGKW46AWo8ikjVKu/9xH2Z2FjCXoH4rZpZnZi/GGJdkkOKWY+JtHUqQIpINona3jgKOAaYBuPtcM+sYU0ySQRK7VpUYRSTbRE2She6+ucQUkh5DPJIhNDBHRGqDqElygZn9FKhrZocDvwFmxBeWpCuVkxOR2qQiFXduIpho+a/AP4E74gpK0pNGrYpIbVNukjSzhsBlwPeA+cDx7l5YE4FJetCoVRGpzZK1JMcDu4C3gTOA7wNXxRyTpImSLcc9xcgXPVi9hchVcFxE0lSyJNnF3XMAzOwx4P34Q5JUK3dQThzFyFVwXETSVLIkuav4gbsXlhjdKlko0nVHFSMXkVoiWZLMNbMt4WMDGoXPDXB3bx5rdFKjdM+jiMjeyk2S7l63pgKR1NDAHBGRskUqS1cZZnaImb1hZovNbKGZXRkuP9DM/mVmH4e/D4grBimfysmJiJQv6n2SlVEI/Le7zzGzZsDscKqtocBr7j7azEYAI4DrY4xDSlC1HBGRaGJLku6+FlgbPt5qZouBdsAA4KTwZeMJ6sEqSdYQFQQQEYkuzpbkHmbWAegOvAe0DhMo7r7WzA4qY5thwDCAQw/Vf+JVpdajiEjFxZ4kzawp8CxwlbtviXobibs/AjwCkJ+fr2LqlaRaqyIilRdrkjSz+gQJcoK7PxcuXm9mbcNWZFtgQ5wx1GbqWhURqZrYkqQFTcbHgMXufk/CqheBi4DR4e/JccVQW6lrVUSkesTZkuwN/AyYb2Zzw2U3EiTHp83sF8BKYHCMMaS/WWNh/jPVtrv1W3fQaeNXXA00a16Plk33o/WihtVXa1V1VkWkFolzdOs7BJV5SnNKXMfNOPOfqbbEs37rDpZv/AqAji2b0LpZwyrvcx+qsyoitUiNjG6VJKpYC3VP9+qab7tXj1P3qohIlSlJZjCNXBURiZeSZAZSchQRqRlKkhlEyVFEpGYpSWYI3fMoIlLzlCTTnO55FBFJHSXJNKWuVRGR1FOSTEPqWhURSQ9KkmlEXasiIulFSTINrN+6g9/837vqWhURSTNKkilWXEruvW/+o+QoIpJmlCRrQilFzNdv3cHGbTs5ZOcy4LvqWhURSUNKkjUhoYh5cXLcuqMQgM8bHoYdPlAJUkQkDSlJ1pQ2Ofy1y0MatSoikkGUJGtAcevxxqVBglTXqohIZlCSjNlf31tJp3COR7UeRUQyi5JkTBLvefxbg2AS5ImXHp/qsEREpAKUJGNQsmJOx51NaN2sYYqjEhGRilKSrCbFLUdg34o5Y5UgRUQykZJkNSjZctS1RxGR7KAkWQWqtSoikt2UJCtJM3WIiGQ/JckKKPe6o4iIZB0lyYjKve5YSm3WvYQl6UREJLMoSUaQmCBLbTkm1GYtVZscyDkn5ihFRKS6KUmWocJdq21y4OJXaio8ERGpAUqSpdAtHSIiAkqSe9EtHSIikkhJMqRbOkREpCQlSSIMzBERkVqp1iZJ3fMoIiLJ1MokqYE5IiISRa1LkupaFRGRqFKSJM2sL3AfUBcY4+6j4zyeulZFRKQyajxJmlld4AHgVGAV8IGZvejui+I4nrpWRUSkslLRkjwG+MTdPwUws78BA4BqT5IzH7yETuvm87cG0LFlE1o3CCc/XlTNR1NtVhGRrFQnBcdsB3ye8HxVuGwvZjbMzGaZ2ayCgoJKH6xZw3pBgmzWsNL7SEq1WUVEslIqWpJWyjLfZ4H7I8AjAPn5+fusj+K4yx+tzGYiIiJAalqSq4BDEp63B9akIA4REZFypSJJfgAcbmYdzawBcD7wYgriEBERKVeNd7e6e6GZXQH8k+AWkMfdfWFNxyEiIpJMSu6TdPe/A39PxbFFRESiSkV3q4iISEZQkhQRESmDkqSIiEgZlCRFRETKYO6Vuk+/RplZAfBZJTdvCWysxnCykc5R+XR+ktM5Kl+qzs933b1VCo6bNTIiSVaFmc1y9/xUx5HOdI7Kp/OTnM5R+XR+Mpe6W0VERMqgJCkiIlKG2pAkH0l1ABlA56h8Oj/J6RyVT+cnQ2X9NUkREZHKqg0tSRERkUpRkhQRESlD2idJM+trZkvN7BMzG5GwPNfM3jWz+Wb2kpk1L2XbDmb2tZl9aGaLzex9M7uoZt9BvMzscTPbYGYLSiyPen7czG5PWNbSzHaZ2Z9rIv6aYGaHmNkb4WdgoZldmbBuopnNDX9WmNncUrbvUPL8ZptyvmejzGx1wjn6cRnbdzWz183s32b2sZndYmalTbCeuM2N1f0+4lTOd+12M/soPD9TzOzgUrbN+s9Q1nL3tP0hmEprGdAJaADMA7qE6z4ATgwf/xy4vZTtOwALEp53AuYCF6f6vVXjOToB6JH4Pit4fpYBHyYs+1V4jv5cgRjqpfo8JImvLdAjfNwM+Hfx56jE6/4AjEz2Ocq2nyTfs1HAtUm2bxRuf1r4vDHwD+DXSbbblur3XsHzVNZ3rXnC498AD9e2z1A2/6R7S/IY4BN3/9TdvwH+BgwI1x0BvBU+/hcwKNnO3P1T4BqCDzJm1iT86/CDsLU5IFxe18zuDlthH5nZ8Gp+X9XG3d8C/lPKqqjn52tgsZkV3+h8HvB08UozO8vM3gvPz1Qzax0uH2Vmj5jZFOAv1fFe4uLua919Tvh4K7AYaJf4mrDVcy7wVHn7MrOhia1sM3vZzE4KH28zs9+Z2Twzm1l8rjJAed+zKH4KTHf3KQDuvh24AhgBYGZNzWxswvdpkJmNBhqFra8J1ft24lHWd83dtyQ8bQKUOxoybFW+bWZzwp9e4fKTzGyamT1jZkvMbEKy1rjEL92TZDvg84Tnq/j2P7cFQP/w8WDgkIj7nAMcGT6+CXjd3XsCJwN3mVkTYBjQEeju7kcBGfElLqEi5+dvwPlm1h7YDaxJWPcOcJy7dw9f99uEdUcDA9z9p9UWdczMrAPQHXivxKofAuvd/eMq7L4JMNPdcwn+QLmkCvuqSeV9zwCuCJPb42Z2QCnbdwVmJy5w92VA07Cb/xZgs7vnhN+n1919BPC1u+e5+5BqfTcpEP5x9DkwBBiZ5OUbgFPdvQfBH6X3J6zrDlwFdCFo2feu/milItI9SZb2V1TxX2k/B35tZrMJutC+qcQ+TwNGhNehpgENgUOBPgRdJoUA7l5aSy3dVeT8vAqcClwATCyxrj3wTzObD1xH8B9isRfd/evqCzleZtYUeBa4qsRf/xC893JbkRF8A7wcPp5N0MWWCcr7nj0EHAbkAWsJuqRL276s1pMTfJ8e2LPA/YvKBpqu3P0mdz+E4A/qK5K8vD7waPidmkSQEIu97+6r3L2I4LJHhxjClQqol+oAkljF3i2g9oStHHdfQpDkMLPOwJkR99mdoLsNgi/3IHdfmviCsIsjo28grcj5cfdvwmT63wRJ8KyE1X8C7nH3F8NuxVEJ676q3qjjY2b1CRLkBHd/rsS6esDZBC3jZArZ+4/LhgmPd7l78edmN+n//SpW3vdsffFCM3uUb/8ISLSQ4HodCa/tRHDNcWs2fJ8q4K/AK8Ct5bzmamA9kEvwWdqRsG5nwuNM+gxlrXRvSX4AHG5mHc2sAXA+8CKAmR0U/q4D3Aw8nGxnYVfb3QT/8QP8Exhe3O9vZt3D5VOAy8L/PDGzA6vrDdWUSpyfPwDXu/umEstbAKvDxxk5Mjj8930MWOzu95Tykj7AEndfFWF3K4A8M6tjZocQXM/LdOV9z9omvG4gQTd+SROAH5hZn3CbRgRdiHeG66eQ0LpK6LLdFf7xktHM7PCEp/2BJUk2aQGsDVuLPyMYOCVpKq2TZNjdeQVBMlsMPO3uC8PVF5jZvwk+kGuAsWXs5rBw0MliggEpf3L34tfeTtD18VE4PLv4VogxwMpw+TyCgQlpycyeAt4FjjCzVWb2i3BV1PMDgLsvdPfxpawaBUwys7fJ3KmQehP8Z/QjK/1WhvMpv6u1Ht/+hT8dWA7MJ/iDa04M8daoJN+zO4sH3BBct7+6lO2/Jhjoc7OZLSU4Nx8AxQOc7gAOMLMF4ffp5HD5IwTfsYy45l/Od210+N4+Iui9ubKUzRM/Qw8CF5nZTKAzGdQjUxupLJ1IEuGo5yHufm6qY5HMpM9Q5lJ/t0g5zOw2glbS0BSHIhlKn6HMppakiIhIGdL6mqSIiEgqKUmKiIiUQUlSRESkDEqSIiWY2e7wNpGFYR3Wa8L7TcvbpoOZpe2tQiJSOUqSIvsqrinalaBc348pv4IKBOXDlCRFsoxGt4qUYGbb3L1pwvNOBDfHtwS+CzxBUMwc4Ap3nxHeGP59gkID4wkqzowGTgL2Ax5w9/+rsTchItVCSVKkhJJJMlz2BcHsMVuBInffEZYje8rd88O6tte6e7/w9cOAg9z9DjPbj6BSz2B3X16T70VEqkbFBESiKZ4poz7wZzPLIyhA3bmM158GHGVm54TPWwCHE7Q0RSRDKEmKJBF2t+4mmAfwVsqewWGvzYDh7v7PGglSRGKhgTsi5TCzVgQzqPw5nAarrBkcthLM21nsn8Cvime5MLPO4YTeIpJB1JIU2VejcCLu+gTzRz4BFE+x9SDwrJkNBt7g2xkcPgIKw1kuxgH3EYx4nRNO1VUA/KRmwheR6qKBOyIiImVQd6uIiEgZlCRFRETKoCQpIiJSBiVJERGRMihJioiIlEFJUkREpAxKkiIiImX4/1tOfmAFZr/3AAAAAElFTkSuQmCC", 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", + "image/png": 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", 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", 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", 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" ] @@ -12518,7 +12572,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **30-39** population up to 15 Dec 2021" + " ## COVID vaccination rollout among **30-39** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -12549,7 +12603,7 @@ }, { "data": { - "image/png": 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", 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", 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+ "image/png": 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", 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", 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", 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" ] @@ -12627,7 +12681,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **18-29** population up to 15 Dec 2021" + " ## COVID vaccination rollout among **18-29** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -12658,7 +12712,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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", 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", 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", 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", 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", "text/plain": [ "
" ] @@ -12734,27 +12788,25 @@ } ], "source": [ + "\n", + "\n", "plot_dem_charts(summ_stat_results, df_dict_cum, formatted_latest_date, pop_subgroups=[\"80+\", \"70-79\", \"65-69\",\"shielding (aged 16-69)\", \"60-64\", \"55-59\", \"50-54\", \"40-49\", \"30-39\", \"18-29\"], groups_dict=features_dict,\n", " groups_to_exclude=[\"ethnicity_16_groups\", \"current_copd\", \"chronic_cardiac_disease\", \"dmards\", \"chemo_or_radio\", \"lung_cancer\", \"cancer_excl_lung_and_haem\", \"haematological_cancer\"],\n", - " savepath=savepath, savepath_figure_csvs=savepath_figure_csvs, suffix=suffix)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Completeness of ethnicity recording" + " savepath=savepath, savepath_figure_csvs=savepath_figure_csvs, suffix=suffix)\n", + "\n", + "\n", + "# ## Completeness of ethnicity recording" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "Total **80+** population with ethnicity recorded 1,792 (83.7%)" + "Total **80+** population with ethnicity recorded 3,619 (85.7%)" ], "text/plain": [ "" @@ -12766,7 +12818,7 @@ { "data": { "text/markdown": [ - "Total **70-79** population with ethnicity recorded 2,982 (85.7%)" + "Total **70-79** population with ethnicity recorded 5,831 (85.0%)" ], "text/plain": [ "" @@ -12778,7 +12830,7 @@ { "data": { "text/markdown": [ - "Total **care home** population with ethnicity recorded 1,183 (84.9%)" + "Total **care home** population with ethnicity recorded 2,380 (84.4%)" ], "text/plain": [ "" @@ -12790,7 +12842,7 @@ { "data": { "text/markdown": [ - "Total **shielding (aged 16-69)** population with ethnicity recorded 364 (86.7%)" + "Total **shielding (aged 16-69)** population with ethnicity recorded 749 (86.3%)" ], "text/plain": [ "" @@ -12802,7 +12854,7 @@ { "data": { "text/markdown": [ - "Total **65-69** population with ethnicity recorded 1,834 (84.5%)" + "Total **65-69** population with ethnicity recorded 3,710 (84.0%)" ], "text/plain": [ "" @@ -12814,7 +12866,7 @@ { "data": { "text/markdown": [ - "Total **LD (aged 16-64)** population with ethnicity recorded 679 (84.3%)" + "Total **LD (aged 16-64)** population with ethnicity recorded 1,372 (85.6%)" ], "text/plain": [ "" @@ -12826,7 +12878,7 @@ { "data": { "text/markdown": [ - "Total **60-64** population with ethnicity recorded 2,310 (86.4%)" + "Total **60-64** population with ethnicity recorded 4,634 (85.0%)" ], "text/plain": [ "" @@ -12838,7 +12890,7 @@ { "data": { "text/markdown": [ - "Total **55-59** population with ethnicity recorded 2,765 (86.8%)" + "Total **55-59** population with ethnicity recorded 5,271 (84.7%)" ], "text/plain": [ "" @@ -12850,7 +12902,7 @@ { "data": { "text/markdown": [ - "Total **50-54** population with ethnicity recorded 2,933 (84.8%)" + "Total **50-54** population with ethnicity recorded 5,733 (85.2%)" ], "text/plain": [ "" @@ -12862,7 +12914,7 @@ { "data": { "text/markdown": [ - "Total **40-49** population with ethnicity recorded 5,236 (85.3%)" + "Total **40-49** population with ethnicity recorded 10,353 (84.5%)" ], "text/plain": [ "" @@ -12874,7 +12926,7 @@ { "data": { "text/markdown": [ - "Total **30-39** population with ethnicity recorded 5,418 (85.0%)" + "Total **30-39** population with ethnicity recorded 11,039 (85.2%)" ], "text/plain": [ "" @@ -12886,7 +12938,7 @@ { "data": { "text/markdown": [ - "Total **18-29** population with ethnicity recorded 6,258 (84.3%)" + "Total **18-29** population with ethnicity recorded 12,733 (85.1%)" ], "text/plain": [ "" @@ -12898,7 +12950,7 @@ { "data": { "text/markdown": [ - "Total **16-17** population with ethnicity recorded 8,764 (84.7%)" + "Total **16-17** population with ethnicity recorded 17,598 (85.3%)" ], "text/plain": [ "" @@ -12909,27 +12961,27 @@ } ], "source": [ + "\n", + "\n", "from data_quality import *\n", "\n", - "ethnicity_completeness(df=df, groups_of_interest=population_subgroups)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Second doses" + "ethnicity_completeness(df=df, groups_of_interest=population_subgroups)\n", + "\n", + "\n", + "# # Second doses" ] }, { "cell_type": "code", - "execution_count": 29, - "metadata": {}, + "execution_count": 30, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [ { "data": { "text/markdown": [ - "08 Sep 2021" + "27 Oct 2021" ], "text/plain": [ "" @@ -12940,6 +12992,8 @@ } ], "source": [ + "\n", + "\n", "# only count second doses where the first dose was given at least 14 weeks ago \n", "# to allow comparison of the first dose situation 14w ago with the second dose situation now\n", "# otherwise bias could be introduced from any second doses given early in certain subgroups\n", @@ -12972,17 +13026,19 @@ " \n", "\n", "date_14w, formatted_date_14w = subtract_from_date(s=df[\"covid_vacc_date\"], unit=\"weeks\", number=14,\n", - " description=\"latest_date_of_first_dose_for_due_second_doses\")\n" + " description=\"latest_date_of_first_dose_for_due_second_doses\")" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 31, "metadata": { "lines_to_next_cell": 2 }, "outputs": [], "source": [ + "\n", + "\n", "# filter data\n", "df_s = df.copy()\n", "# replace any second doses not yet \"due\" with \"0\"\n", @@ -12996,10 +13052,14 @@ }, { "cell_type": "code", - "execution_count": 31, - "metadata": {}, + "execution_count": 32, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [], "source": [ + "\n", + "\n", "# add \"brand of first dose\" to list of features to break down by\n", "import copy\n", "features_dict_2 = copy.deepcopy(features_dict)\n", @@ -13012,8 +13072,10 @@ }, { "cell_type": "code", - "execution_count": 32, - "metadata": {}, + "execution_count": 33, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [ { "name": "stderr", @@ -13044,7 +13106,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **80+** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **80+** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -13110,732 +13172,723 @@ " \n", " overall\n", " overall\n", - " 1176\n", + " 2317\n", " 54.9\n", - " 2142\n", - " 54.2\n", - " 0.7\n", + " 4221\n", + " 53.7\n", + " 1.2\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 616\n", - " 54.7\n", - " 1127\n", - " 54.0\n", - " 0.7\n", + " 1204\n", + " 55.3\n", + " 2177\n", + " 54.3\n", + " 1.0\n", " unknown\n", " \n", " \n", " M\n", - " 560\n", - " 55.2\n", - " 1015\n", - " 54.5\n", - " 0.7\n", + " 1106\n", + " 54.1\n", + " 2044\n", + " 53.1\n", + " 1.0\n", " unknown\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 14\n", + " 35\n", " 50.0\n", - " 28\n", + " 70\n", " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 0-15\n", - " 63\n", - " 56.2\n", - " 112\n", - " 56.2\n", + " 133\n", + " 51.4\n", + " 259\n", + " 51.4\n", " 0.0\n", " unknown\n", " \n", " \n", " 16-17\n", - " 77\n", - " 55.0\n", " 140\n", - " 50.0\n", - " 5.0\n", - " 02-Feb\n", + " 57.1\n", + " 245\n", + " 54.3\n", + " 2.8\n", + " 25-Apr\n", " \n", " \n", " 18-29\n", - " 70\n", - " 52.6\n", - " 133\n", - " 52.6\n", + " 154\n", + " 57.9\n", + " 266\n", + " 57.9\n", " 0.0\n", " unknown\n", " \n", " \n", " 30-34\n", - " 77\n", - " 55.0\n", - " 140\n", - " 50.0\n", - " 5.0\n", - " 02-Feb\n", + " 154\n", + " 56.4\n", + " 273\n", + " 53.8\n", + " 2.6\n", + " 03-May\n", " \n", " \n", " 35-39\n", - " 77\n", - " 52.4\n", - " 147\n", - " 52.4\n", + " 154\n", + " 57.9\n", + " 266\n", + " 57.9\n", " 0.0\n", " unknown\n", " \n", " \n", " 40-44\n", - " 91\n", - " 61.9\n", - " 147\n", - " 61.9\n", - " 0.0\n", - " unknown\n", + " 154\n", + " 56.4\n", + " 273\n", + " 53.8\n", + " 2.6\n", + " 03-May\n", " \n", " \n", " 45-49\n", - " 70\n", - " 52.6\n", - " 133\n", - " 52.6\n", + " 161\n", + " 57.5\n", + " 280\n", + " 57.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 50-54\n", - " 77\n", - " 50.0\n", - " 154\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 140\n", + " 54.1\n", + " 259\n", + " 51.4\n", + " 2.7\n", + " 06-May\n", " \n", " \n", " 55-59\n", - " 77\n", - " 50.0\n", - " 154\n", - " 50.0\n", + " 168\n", + " 55.8\n", + " 301\n", + " 55.8\n", " 0.0\n", " unknown\n", " \n", " \n", " 60-64\n", - " 63\n", + " 133\n", " 50.0\n", - " 126\n", + " 266\n", " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 65-69\n", - " 91\n", - " 65.0\n", - " 140\n", - " 65.0\n", - " 0.0\n", - " unknown\n", + " 154\n", + " 55.0\n", + " 280\n", + " 52.5\n", + " 2.5\n", + " 11-May\n", " \n", " \n", " 70-74\n", - " 70\n", - " 50.0\n", - " 140\n", - " 50.0\n", + " 161\n", + " 54.8\n", + " 294\n", + " 54.8\n", " 0.0\n", " unknown\n", " \n", " \n", " 75-79\n", - " 63\n", - " 47.4\n", - " 133\n", - " 47.4\n", - " 0.0\n", - " unknown\n", + " 161\n", + " 57.5\n", + " 280\n", + " 55.0\n", + " 2.5\n", + " 04-May\n", " \n", " \n", " 80-84\n", - " 91\n", - " 65.0\n", - " 140\n", - " 60.0\n", - " 5.0\n", - " 19-Jan\n", + " 147\n", + " 53.8\n", + " 273\n", + " 53.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 85-89\n", - " 91\n", - " 59.1\n", " 154\n", - " 59.1\n", - " 0.0\n", - " unknown\n", + " 52.4\n", + " 294\n", + " 50.0\n", + " 2.4\n", + " 22-May\n", " \n", " \n", " 90+\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 14\n", + " 40.0\n", + " 35\n", + " 40.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 189\n", - " 52.9\n", - " 357\n", - " 52.9\n", - " 0.0\n", - " unknown\n", + " 406\n", + " 55.2\n", + " 735\n", + " 53.3\n", + " 1.9\n", + " 10-Jun\n", " \n", " \n", " Mixed\n", - " 196\n", - " 56.0\n", - " 350\n", + " 378\n", " 54.0\n", + " 700\n", + " 52.0\n", " 2.0\n", - " 13-Apr\n", + " 08-Jun\n", " \n", " \n", " Other\n", - " 182\n", - " 54.2\n", - " 336\n", - " 54.2\n", - " 0.0\n", + " 406\n", + " 55.8\n", + " 728\n", + " 54.8\n", + " 1.0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 203\n", - " 55.8\n", - " 364\n", - " 55.8\n", - " 0.0\n", + " 392\n", + " 52.3\n", + " 749\n", + " 51.4\n", + " 0.9\n", " unknown\n", " \n", " \n", " Unknown\n", - " 182\n", - " 53.1\n", - " 343\n", - " 51.0\n", - " 2.1\n", - " 17-Apr\n", + " 336\n", + " 55.2\n", + " 609\n", + " 54.0\n", + " 1.2\n", + " unknown\n", " \n", " \n", " White\n", - " 224\n", - " 57.1\n", " 392\n", - " 55.4\n", - " 1.7\n", - " 29-Apr\n", + " 54.9\n", + " 714\n", + " 53.9\n", + " 1.0\n", + " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 63\n", - " 60.0\n", - " 105\n", - " 53.3\n", - " 6.7\n", - " 15-Jan\n", + " 133\n", + " 61.3\n", + " 217\n", + " 58.1\n", + " 3.2\n", + " 05-Apr\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 56\n", - " 47.1\n", - " 119\n", - " 47.1\n", + " 105\n", + " 50.0\n", + " 210\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 63\n", - " 64.3\n", - " 98\n", - " 64.3\n", + " 126\n", + " 58.1\n", + " 217\n", + " 58.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Chinese\n", - " 49\n", - " 46.7\n", " 105\n", - " 46.7\n", + " 48.4\n", + " 217\n", + " 48.4\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 77\n", - " 68.8\n", - " 112\n", - " 62.5\n", - " 6.3\n", - " 07-Jan\n", + " 147\n", + " 61.8\n", + " 238\n", + " 61.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other Asian\n", - " 63\n", - " 56.2\n", - " 112\n", - " 56.2\n", - " 0.0\n", - " unknown\n", + " 126\n", + " 60.0\n", + " 210\n", + " 56.7\n", + " 3.3\n", + " 06-Apr\n", " \n", " \n", " British or Mixed British\n", - " 77\n", - " 57.9\n", - " 133\n", - " 57.9\n", + " 112\n", + " 51.6\n", + " 217\n", + " 51.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 63\n", - " 60.0\n", - " 105\n", - " 60.0\n", + " 119\n", + " 53.1\n", + " 224\n", + " 53.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 70\n", - " 58.8\n", - " 119\n", - " 58.8\n", + " 133\n", + " 57.6\n", + " 231\n", + " 57.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 42\n", - " 50.0\n", - " 84\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 112\n", + " 51.6\n", + " 217\n", + " 48.4\n", + " 3.2\n", + " 27-Apr\n", " \n", " \n", " Other White\n", - " 63\n", - " 52.9\n", - " 119\n", - " 52.9\n", + " 133\n", + " 55.9\n", + " 238\n", + " 55.9\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 49\n", - " 46.7\n", - " 105\n", - " 40.0\n", - " 6.7\n", - " 29-Jan\n", + " 98\n", + " 48.3\n", + " 203\n", + " 48.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 56\n", - " 50.0\n", - " 112\n", - " 50.0\n", + " 105\n", + " 46.9\n", + " 224\n", + " 46.9\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 175\n", - " 51.0\n", - " 343\n", - " 51.0\n", - " 0.0\n", + " 364\n", + " 54.2\n", + " 672\n", + " 53.1\n", + " 1.1\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 63\n", - " 52.9\n", - " 119\n", - " 52.9\n", - " 0.0\n", - " unknown\n", + " 126\n", + " 56.2\n", + " 224\n", + " 53.1\n", + " 3.1\n", + " 19-Apr\n", " \n", " \n", " White + Black African\n", - " 56\n", - " 53.3\n", - " 105\n", - " 53.3\n", + " 119\n", + " 56.7\n", + " 210\n", + " 56.7\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 84\n", - " 60.0\n", - " 140\n", - " 60.0\n", - " 0.0\n", - " unknown\n", + " 147\n", + " 58.3\n", + " 252\n", + " 55.6\n", + " 2.7\n", + " 25-Apr\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 231\n", - " 55.0\n", - " 420\n", - " 55.0\n", - " 0.0\n", - " unknown\n", + " 441\n", + " 54.8\n", + " 805\n", + " 53.0\n", + " 1.8\n", + " 18-Jun\n", " \n", " \n", " 2\n", - " 224\n", - " 55.2\n", - " 406\n", - " 55.2\n", - " 0.0\n", + " 434\n", + " 53.9\n", + " 805\n", + " 53.0\n", + " 0.9\n", " unknown\n", " \n", " \n", " 3\n", - " 224\n", - " 57.1\n", - " 392\n", - " 57.1\n", - " 0.0\n", + " 427\n", + " 55.0\n", + " 777\n", + " 54.1\n", + " 0.9\n", " unknown\n", " \n", " \n", " 4\n", - " 231\n", - " 54.1\n", - " 427\n", - " 52.5\n", - " 1.6\n", - " 21-May\n", + " 448\n", + " 54.7\n", + " 819\n", + " 53.8\n", + " 0.9\n", + " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 210\n", - " 53.6\n", - " 392\n", - " 53.6\n", - " 0.0\n", - " unknown\n", + " 448\n", + " 55.2\n", + " 812\n", + " 53.4\n", + " 1.8\n", + " 17-Jun\n", " \n", " \n", " Unknown\n", - " 63\n", - " 60.0\n", - " 105\n", - " 53.3\n", - " 6.7\n", - " 15-Jan\n", + " 119\n", + " 56.7\n", + " 210\n", + " 56.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 315\n", - " 52.9\n", - " 595\n", - " 51.8\n", + " 686\n", + " 53.0\n", + " 1295\n", + " 51.9\n", " 1.1\n", " unknown\n", " \n", " \n", " under 30\n", - " 868\n", - " 56.1\n", - " 1547\n", - " 55.2\n", - " 0.9\n", + " 1624\n", + " 55.5\n", + " 2926\n", + " 54.5\n", + " 1.0\n", " unknown\n", " \n", " \n", " housebound\n", " no\n", - " 1155\n", - " 54.6\n", - " 2114\n", - " 54.0\n", - " 0.6\n", + " 2289\n", + " 54.8\n", + " 4179\n", + " 53.6\n", + " 1.2\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", - " 75.0\n", " 28\n", - " 75.0\n", + " 66.7\n", + " 42\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1162\n", + " 2296\n", " 54.8\n", - " 2121\n", - " 54.1\n", - " 0.7\n", + " 4186\n", + " 53.7\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", " 21\n", - " 66.7\n", + " 60.0\n", + " 35\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1169\n", - " 55.3\n", - " 2114\n", - " 54.3\n", + " 2289\n", + " 54.8\n", + " 4179\n", + " 53.8\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", " 21\n", - " 33.3\n", + " 42.9\n", + " 49\n", + " 42.9\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1162\n", - " 55.0\n", - " 2114\n", - " 54.3\n", - " 0.7\n", + " 2289\n", + " 54.9\n", + " 4172\n", + " 53.7\n", + " 1.2\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", " 28\n", - " 50.0\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 1169\n", - " 55.1\n", - " 2121\n", - " 54.1\n", + " 2289\n", + " 54.8\n", + " 4179\n", + " 53.8\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", " 21\n", - " 33.3\n", + " 50.0\n", + " 42\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1162\n", + " 2289\n", " 54.8\n", - " 2121\n", - " 54.1\n", - " 0.7\n", + " 4179\n", + " 53.8\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", + " 28\n", " 66.7\n", - " 0.0\n", - " unknown\n", + " 42\n", + " 50.0\n", + " 16.7\n", + " 11-Feb\n", " \n", " \n", " LD\n", " no\n", - " 1162\n", - " 55.3\n", - " 2100\n", - " 54.3\n", - " 1.0\n", + " 2254\n", + " 54.6\n", + " 4130\n", + " 53.4\n", + " 1.2\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", - " 50.0\n", - " 42\n", - " 33.3\n", - " 16.7\n", - " 31-Dec\n", + " 63\n", + " 64.3\n", + " 98\n", + " 64.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1169\n", - " 54.9\n", - " 2128\n", - " 54.3\n", - " 0.6\n", + " 2282\n", + " 54.6\n", + " 4179\n", + " 53.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 50.0\n", - " 14\n", - " 50.0\n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 1169\n", - " 55.1\n", - " 2121\n", - " 54.5\n", - " 0.6\n", + " 2296\n", + " 54.8\n", + " 4186\n", + " 53.7\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", " 21\n", - " 0.0\n", + " 50.0\n", + " 42\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1162\n", + " 2296\n", " 54.8\n", - " 2121\n", - " 54.1\n", - " 0.7\n", + " 4193\n", + " 53.6\n", + " 1.2\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", " 21\n", - " 66.7\n", + " 60.0\n", + " 35\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1169\n", - " 55.1\n", - " 2121\n", - " 54.1\n", + " 2296\n", + " 54.8\n", + " 4193\n", + " 53.8\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", " 21\n", - " 33.3\n", - " 0.0\n", - " unknown\n", + " 60.0\n", + " 35\n", + " 40.0\n", + " 20.0\n", + " 12-Feb\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1162\n", + " 2289\n", " 54.8\n", - " 2121\n", - " 54.1\n", - " 0.7\n", + " 4179\n", + " 53.8\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", " 21\n", - " 66.7\n", + " 50.0\n", + " 42\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 945\n", - " 54.9\n", - " 1722\n", - " 54.1\n", - " 0.8\n", + " 1890\n", + " 55.7\n", + " 3395\n", + " 54.4\n", + " 1.3\n", " unknown\n", " \n", " \n", " yes\n", - " 231\n", - " 55.0\n", - " 420\n", - " 53.3\n", - " 1.7\n", - " 08-May\n", - " \n", - " \n", - " brand_of_first_dose\n", - " Moderna\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", - " 0.0\n", + " 427\n", + " 51.7\n", + " 826\n", + " 50.8\n", + " 0.9\n", " unknown\n", " \n", " \n", + " brand_of_first_dose\n", " Oxford-AZ\n", " 0\n", " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", @@ -13850,12 +13903,12 @@ " \n", " \n", " Unknown\n", - " 1169\n", - " 60.5\n", - " 1932\n", + " 2310\n", + " 61.1\n", + " 3780\n", " 59.8\n", - " 0.7\n", - " unknown\n", + " 1.3\n", + " 07-Jul\n", " \n", " \n", "\n", @@ -13864,339 +13917,335 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1176 \n", - "sex F 616 \n", - " M 560 \n", - "ageband_5yr 0 14 \n", - " 0-15 63 \n", - " 16-17 77 \n", - " 18-29 70 \n", - " 30-34 77 \n", - " 35-39 77 \n", - " 40-44 91 \n", - " 45-49 70 \n", - " 50-54 77 \n", - " 55-59 77 \n", - " 60-64 63 \n", - " 65-69 91 \n", - " 70-74 70 \n", - " 75-79 63 \n", - " 80-84 91 \n", - " 85-89 91 \n", - " 90+ 7 \n", - "ethnicity_6_groups Black 189 \n", - " Mixed 196 \n", - " Other 182 \n", - " South Asian 203 \n", - " Unknown 182 \n", - " White 224 \n", - "ethnicity_16_groups African 63 \n", - " Bangladeshi or British Bangladeshi 56 \n", - " Caribbean 63 \n", - " Chinese 49 \n", - " Other 77 \n", - " Other Asian 63 \n", - " British or Mixed British 77 \n", - " Indian or British Indian 63 \n", - " Irish 70 \n", - " Other Black 42 \n", - " Other White 63 \n", - " Other mixed 49 \n", - " Pakistani or British Pakistani 56 \n", - " Unknown 175 \n", - " White + Asian 63 \n", - " White + Black African 56 \n", - " White + Black Caribbean 84 \n", - "imd_categories 1 Most deprived 231 \n", - " 2 224 \n", - " 3 224 \n", - " 4 231 \n", - " 5 Least deprived 210 \n", - " Unknown 63 \n", - "bmi 30+ 315 \n", - " under 30 868 \n", - "housebound no 1155 \n", + "overall overall 2317 \n", + "sex F 1204 \n", + " M 1106 \n", + "ageband_5yr 0 35 \n", + " 0-15 133 \n", + " 16-17 140 \n", + " 18-29 154 \n", + " 30-34 154 \n", + " 35-39 154 \n", + " 40-44 154 \n", + " 45-49 161 \n", + " 50-54 140 \n", + " 55-59 168 \n", + " 60-64 133 \n", + " 65-69 154 \n", + " 70-74 161 \n", + " 75-79 161 \n", + " 80-84 147 \n", + " 85-89 154 \n", + " 90+ 14 \n", + "ethnicity_6_groups Black 406 \n", + " Mixed 378 \n", + " Other 406 \n", + " South Asian 392 \n", + " Unknown 336 \n", + " White 392 \n", + "ethnicity_16_groups African 133 \n", + " Bangladeshi or British Bangladeshi 105 \n", + " Caribbean 126 \n", + " Chinese 105 \n", + " Other 147 \n", + " Other Asian 126 \n", + " British or Mixed British 112 \n", + " Indian or British Indian 119 \n", + " Irish 133 \n", + " Other Black 112 \n", + " Other White 133 \n", + " Other mixed 98 \n", + " Pakistani or British Pakistani 105 \n", + " Unknown 364 \n", + " White + Asian 126 \n", + " White + Black African 119 \n", + " White + Black Caribbean 147 \n", + "imd_categories 1 Most deprived 441 \n", + " 2 434 \n", + " 3 427 \n", + " 4 448 \n", + " 5 Least deprived 448 \n", + " Unknown 119 \n", + "bmi 30+ 686 \n", + " under 30 1624 \n", + "housebound no 2289 \n", + " yes 28 \n", + "chronic_cardiac_disease no 2296 \n", " yes 21 \n", - "chronic_cardiac_disease no 1162 \n", - " yes 14 \n", - "current_copd no 1169 \n", - " yes 7 \n", - "dmards no 1162 \n", - " yes 14 \n", - "dementia no 1169 \n", - " yes 7 \n", - "psychosis_schiz_bipolar no 1162 \n", - " yes 14 \n", - "LD no 1162 \n", + "current_copd no 2289 \n", " yes 21 \n", - "ssri no 1169 \n", - " yes 7 \n", - "chemo_or_radio no 1169 \n", - " yes 0 \n", - "lung_cancer no 1162 \n", - " yes 14 \n", - "cancer_excl_lung_and_haem no 1169 \n", - " yes 7 \n", - "haematological_cancer no 1162 \n", - " yes 14 \n", - "ckd no 945 \n", - " yes 231 \n", - "brand_of_first_dose Moderna 0 \n", - " Oxford-AZ 0 \n", + "dmards no 2289 \n", + " yes 28 \n", + "dementia no 2289 \n", + " yes 21 \n", + "psychosis_schiz_bipolar no 2289 \n", + " yes 28 \n", + "LD no 2254 \n", + " yes 63 \n", + "ssri no 2282 \n", + " yes 28 \n", + "chemo_or_radio no 2296 \n", + " yes 21 \n", + "lung_cancer no 2296 \n", + " yes 21 \n", + "cancer_excl_lung_and_haem no 2296 \n", + " yes 21 \n", + "haematological_cancer no 2289 \n", + " yes 21 \n", + "ckd no 1890 \n", + " yes 427 \n", + "brand_of_first_dose Oxford-AZ 0 \n", " Pfizer 0 \n", - " Unknown 1169 \n", + " Unknown 2310 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 54.9 2142 \n", - "sex F 54.7 1127 \n", - " M 55.2 1015 \n", - "ageband_5yr 0 50.0 28 \n", - " 0-15 56.2 112 \n", - " 16-17 55.0 140 \n", - " 18-29 52.6 133 \n", - " 30-34 55.0 140 \n", - " 35-39 52.4 147 \n", - " 40-44 61.9 147 \n", - " 45-49 52.6 133 \n", - " 50-54 50.0 154 \n", - " 55-59 50.0 154 \n", - " 60-64 50.0 126 \n", - " 65-69 65.0 140 \n", - " 70-74 50.0 140 \n", - " 75-79 47.4 133 \n", - " 80-84 65.0 140 \n", - " 85-89 59.1 154 \n", - " 90+ 33.3 21 \n", - "ethnicity_6_groups Black 52.9 357 \n", - " Mixed 56.0 350 \n", - " Other 54.2 336 \n", - " South Asian 55.8 364 \n", - " Unknown 53.1 343 \n", - " White 57.1 392 \n", - "ethnicity_16_groups African 60.0 105 \n", - " Bangladeshi or British Bangladeshi 47.1 119 \n", - " Caribbean 64.3 98 \n", - " Chinese 46.7 105 \n", - " Other 68.8 112 \n", - " Other Asian 56.2 112 \n", - " British or Mixed British 57.9 133 \n", - " Indian or British Indian 60.0 105 \n", - " Irish 58.8 119 \n", - " Other Black 50.0 84 \n", - " Other White 52.9 119 \n", - " Other mixed 46.7 105 \n", - " Pakistani or British Pakistani 50.0 112 \n", - " Unknown 51.0 343 \n", - " White + Asian 52.9 119 \n", - " White + Black African 53.3 105 \n", - " White + Black Caribbean 60.0 140 \n", - "imd_categories 1 Most deprived 55.0 420 \n", - " 2 55.2 406 \n", - " 3 57.1 392 \n", - " 4 54.1 427 \n", - " 5 Least deprived 53.6 392 \n", - " Unknown 60.0 105 \n", - "bmi 30+ 52.9 595 \n", - " under 30 56.1 1547 \n", - "housebound no 54.6 2114 \n", - " yes 75.0 28 \n", - "chronic_cardiac_disease no 54.8 2121 \n", - " yes 66.7 21 \n", - "current_copd no 55.3 2114 \n", - " yes 33.3 21 \n", - "dmards no 55.0 2114 \n", - " yes 50.0 28 \n", - "dementia no 55.1 2121 \n", - " yes 33.3 21 \n", - "psychosis_schiz_bipolar no 54.8 2121 \n", - " yes 66.7 21 \n", - "LD no 55.3 2100 \n", + "overall overall 54.9 4221 \n", + "sex F 55.3 2177 \n", + " M 54.1 2044 \n", + "ageband_5yr 0 50.0 70 \n", + " 0-15 51.4 259 \n", + " 16-17 57.1 245 \n", + " 18-29 57.9 266 \n", + " 30-34 56.4 273 \n", + " 35-39 57.9 266 \n", + " 40-44 56.4 273 \n", + " 45-49 57.5 280 \n", + " 50-54 54.1 259 \n", + " 55-59 55.8 301 \n", + " 60-64 50.0 266 \n", + " 65-69 55.0 280 \n", + " 70-74 54.8 294 \n", + " 75-79 57.5 280 \n", + " 80-84 53.8 273 \n", + " 85-89 52.4 294 \n", + " 90+ 40.0 35 \n", + "ethnicity_6_groups Black 55.2 735 \n", + " Mixed 54.0 700 \n", + " Other 55.8 728 \n", + " South Asian 52.3 749 \n", + " Unknown 55.2 609 \n", + " White 54.9 714 \n", + "ethnicity_16_groups African 61.3 217 \n", + " Bangladeshi or British Bangladeshi 50.0 210 \n", + " Caribbean 58.1 217 \n", + " Chinese 48.4 217 \n", + " Other 61.8 238 \n", + " Other Asian 60.0 210 \n", + " British or Mixed British 51.6 217 \n", + " Indian or British Indian 53.1 224 \n", + " Irish 57.6 231 \n", + " Other Black 51.6 217 \n", + " Other White 55.9 238 \n", + " Other mixed 48.3 203 \n", + " Pakistani or British Pakistani 46.9 224 \n", + " Unknown 54.2 672 \n", + " White + Asian 56.2 224 \n", + " White + Black African 56.7 210 \n", + " White + Black Caribbean 58.3 252 \n", + "imd_categories 1 Most deprived 54.8 805 \n", + " 2 53.9 805 \n", + " 3 55.0 777 \n", + " 4 54.7 819 \n", + " 5 Least deprived 55.2 812 \n", + " Unknown 56.7 210 \n", + "bmi 30+ 53.0 1295 \n", + " under 30 55.5 2926 \n", + "housebound no 54.8 4179 \n", + " yes 66.7 42 \n", + "chronic_cardiac_disease no 54.8 4186 \n", + " yes 60.0 35 \n", + "current_copd no 54.8 4179 \n", + " yes 42.9 49 \n", + "dmards no 54.9 4172 \n", + " yes 57.1 49 \n", + "dementia no 54.8 4179 \n", " yes 50.0 42 \n", - "ssri no 54.9 2128 \n", - " yes 50.0 14 \n", - "chemo_or_radio no 55.1 2121 \n", - " yes 0.0 21 \n", - "lung_cancer no 54.8 2121 \n", - " yes 66.7 21 \n", - "cancer_excl_lung_and_haem no 55.1 2121 \n", - " yes 33.3 21 \n", - "haematological_cancer no 54.8 2121 \n", - " yes 66.7 21 \n", - "ckd no 54.9 1722 \n", - " yes 55.0 420 \n", - "brand_of_first_dose Moderna 0.0 0 \n", - " Oxford-AZ 0.0 0 \n", + "psychosis_schiz_bipolar no 54.8 4179 \n", + " yes 66.7 42 \n", + "LD no 54.6 4130 \n", + " yes 64.3 98 \n", + "ssri no 54.6 4179 \n", + " yes 57.1 49 \n", + "chemo_or_radio no 54.8 4186 \n", + " yes 50.0 42 \n", + "lung_cancer no 54.8 4193 \n", + " yes 60.0 35 \n", + "cancer_excl_lung_and_haem no 54.8 4193 \n", + " yes 60.0 35 \n", + "haematological_cancer no 54.8 4179 \n", + " yes 50.0 42 \n", + "ckd no 55.7 3395 \n", + " yes 51.7 826 \n", + "brand_of_first_dose Oxford-AZ 0.0 7 \n", " Pfizer 0.0 0 \n", - " Unknown 60.5 1932 \n", + " Unknown 61.1 3780 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 54.2 \n", - "sex F 54.0 \n", - " M 54.5 \n", + "overall overall 53.7 \n", + "sex F 54.3 \n", + " M 53.1 \n", "ageband_5yr 0 50.0 \n", - " 0-15 56.2 \n", - " 16-17 50.0 \n", - " 18-29 52.6 \n", - " 30-34 50.0 \n", - " 35-39 52.4 \n", - " 40-44 61.9 \n", - " 45-49 52.6 \n", - " 50-54 50.0 \n", - " 55-59 50.0 \n", + " 0-15 51.4 \n", + " 16-17 54.3 \n", + " 18-29 57.9 \n", + " 30-34 53.8 \n", + " 35-39 57.9 \n", + " 40-44 53.8 \n", + " 45-49 57.5 \n", + " 50-54 51.4 \n", + " 55-59 55.8 \n", " 60-64 50.0 \n", - " 65-69 65.0 \n", - " 70-74 50.0 \n", - " 75-79 47.4 \n", - " 80-84 60.0 \n", - " 85-89 59.1 \n", - " 90+ 33.3 \n", - "ethnicity_6_groups Black 52.9 \n", - " Mixed 54.0 \n", - " Other 54.2 \n", - " South Asian 55.8 \n", - " Unknown 51.0 \n", - " White 55.4 \n", - "ethnicity_16_groups African 53.3 \n", - " Bangladeshi or British Bangladeshi 47.1 \n", - " Caribbean 64.3 \n", - " Chinese 46.7 \n", - " Other 62.5 \n", - " Other Asian 56.2 \n", - " British or Mixed British 57.9 \n", - " Indian or British Indian 60.0 \n", - " Irish 58.8 \n", - " Other Black 50.0 \n", - " Other White 52.9 \n", - " Other mixed 40.0 \n", - " Pakistani or British Pakistani 50.0 \n", - " Unknown 51.0 \n", - " White + Asian 52.9 \n", - " White + Black African 53.3 \n", - " White + Black Caribbean 60.0 \n", - "imd_categories 1 Most deprived 55.0 \n", - " 2 55.2 \n", - " 3 57.1 \n", - " 4 52.5 \n", - " 5 Least deprived 53.6 \n", - " Unknown 53.3 \n", - "bmi 30+ 51.8 \n", - " under 30 55.2 \n", - "housebound no 54.0 \n", - " yes 75.0 \n", - "chronic_cardiac_disease no 54.1 \n", + " 65-69 52.5 \n", + " 70-74 54.8 \n", + " 75-79 55.0 \n", + " 80-84 53.8 \n", + " 85-89 50.0 \n", + " 90+ 40.0 \n", + "ethnicity_6_groups Black 53.3 \n", + " Mixed 52.0 \n", + " Other 54.8 \n", + " South Asian 51.4 \n", + " Unknown 54.0 \n", + " White 53.9 \n", + "ethnicity_16_groups African 58.1 \n", + " Bangladeshi or British Bangladeshi 50.0 \n", + " Caribbean 58.1 \n", + " Chinese 48.4 \n", + " Other 61.8 \n", + " Other Asian 56.7 \n", + " British or Mixed British 51.6 \n", + " Indian or British Indian 53.1 \n", + " Irish 57.6 \n", + " Other Black 48.4 \n", + " Other White 55.9 \n", + " Other mixed 48.3 \n", + " Pakistani or British Pakistani 46.9 \n", + " Unknown 53.1 \n", + " White + Asian 53.1 \n", + " White + Black African 56.7 \n", + " White + Black Caribbean 55.6 \n", + "imd_categories 1 Most deprived 53.0 \n", + " 2 53.0 \n", + " 3 54.1 \n", + " 4 53.8 \n", + " 5 Least deprived 53.4 \n", + " Unknown 56.7 \n", + "bmi 30+ 51.9 \n", + " under 30 54.5 \n", + "housebound no 53.6 \n", " yes 66.7 \n", - "current_copd no 54.3 \n", - " yes 33.3 \n", - "dmards no 54.3 \n", + "chronic_cardiac_disease no 53.7 \n", + " yes 60.0 \n", + "current_copd no 53.8 \n", + " yes 42.9 \n", + "dmards no 53.7 \n", + " yes 57.1 \n", + "dementia no 53.8 \n", " yes 50.0 \n", - "dementia no 54.1 \n", - " yes 33.3 \n", - "psychosis_schiz_bipolar no 54.1 \n", - " yes 66.7 \n", - "LD no 54.3 \n", - " yes 33.3 \n", - "ssri no 54.3 \n", + "psychosis_schiz_bipolar no 53.8 \n", " yes 50.0 \n", - "chemo_or_radio no 54.5 \n", - " yes 0.0 \n", - "lung_cancer no 54.1 \n", - " yes 66.7 \n", - "cancer_excl_lung_and_haem no 54.1 \n", - " yes 33.3 \n", - "haematological_cancer no 54.1 \n", - " yes 66.7 \n", - "ckd no 54.1 \n", - " yes 53.3 \n", - "brand_of_first_dose Moderna NaN \n", - " Oxford-AZ NaN \n", + "LD no 53.4 \n", + " yes 64.3 \n", + "ssri no 53.6 \n", + " yes 57.1 \n", + "chemo_or_radio no 53.7 \n", + " yes 50.0 \n", + "lung_cancer no 53.6 \n", + " yes 60.0 \n", + "cancer_excl_lung_and_haem no 53.8 \n", + " yes 40.0 \n", + "haematological_cancer no 53.8 \n", + " yes 50.0 \n", + "ckd no 54.4 \n", + " yes 50.8 \n", + "brand_of_first_dose Oxford-AZ 0.0 \n", " Pfizer NaN \n", " Unknown 59.8 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 0.7 \n", - "sex F 0.7 \n", - " M 0.7 \n", + "overall overall 1.2 \n", + "sex F 1.0 \n", + " M 1.0 \n", "ageband_5yr 0 0.0 \n", " 0-15 0.0 \n", - " 16-17 5.0 \n", + " 16-17 2.8 \n", " 18-29 0.0 \n", - " 30-34 5.0 \n", + " 30-34 2.6 \n", " 35-39 0.0 \n", - " 40-44 0.0 \n", + " 40-44 2.6 \n", " 45-49 0.0 \n", - " 50-54 0.0 \n", + " 50-54 2.7 \n", " 55-59 0.0 \n", " 60-64 0.0 \n", - " 65-69 0.0 \n", + " 65-69 2.5 \n", " 70-74 0.0 \n", - " 75-79 0.0 \n", - " 80-84 5.0 \n", - " 85-89 0.0 \n", + " 75-79 2.5 \n", + " 80-84 0.0 \n", + " 85-89 2.4 \n", " 90+ 0.0 \n", - "ethnicity_6_groups Black 0.0 \n", + "ethnicity_6_groups Black 1.9 \n", " Mixed 2.0 \n", - " Other 0.0 \n", - " South Asian 0.0 \n", - " Unknown 2.1 \n", - " White 1.7 \n", - "ethnicity_16_groups African 6.7 \n", + " Other 1.0 \n", + " South Asian 0.9 \n", + " Unknown 1.2 \n", + " White 1.0 \n", + "ethnicity_16_groups African 3.2 \n", " Bangladeshi or British Bangladeshi 0.0 \n", " Caribbean 0.0 \n", " Chinese 0.0 \n", - " Other 6.3 \n", - " Other Asian 0.0 \n", + " Other 0.0 \n", + " Other Asian 3.3 \n", " British or Mixed British 0.0 \n", " Indian or British Indian 0.0 \n", " Irish 0.0 \n", - " Other Black 0.0 \n", + " Other Black 3.2 \n", " Other White 0.0 \n", - " Other mixed 6.7 \n", + " Other mixed 0.0 \n", " Pakistani or British Pakistani 0.0 \n", - " Unknown 0.0 \n", - " White + Asian 0.0 \n", + " Unknown 1.1 \n", + " White + Asian 3.1 \n", " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 0.0 \n", - " 2 0.0 \n", - " 3 0.0 \n", - " 4 1.6 \n", - " 5 Least deprived 0.0 \n", - " Unknown 6.7 \n", + " White + Black Caribbean 2.7 \n", + "imd_categories 1 Most deprived 1.8 \n", + " 2 0.9 \n", + " 3 0.9 \n", + " 4 0.9 \n", + " 5 Least deprived 1.8 \n", + " Unknown 0.0 \n", "bmi 30+ 1.1 \n", - " under 30 0.9 \n", - "housebound no 0.6 \n", + " under 30 1.0 \n", + "housebound no 1.2 \n", " yes 0.0 \n", - "chronic_cardiac_disease no 0.7 \n", + "chronic_cardiac_disease no 1.1 \n", " yes 0.0 \n", "current_copd no 1.0 \n", " yes 0.0 \n", - "dmards no 0.7 \n", + "dmards no 1.2 \n", " yes 0.0 \n", "dementia no 1.0 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 0.7 \n", - " yes 0.0 \n", - "LD no 1.0 \n", + "psychosis_schiz_bipolar no 1.0 \n", " yes 16.7 \n", - "ssri no 0.6 \n", + "LD no 1.2 \n", " yes 0.0 \n", - "chemo_or_radio no 0.6 \n", + "ssri no 1.0 \n", " yes 0.0 \n", - "lung_cancer no 0.7 \n", + "chemo_or_radio no 1.1 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.0 \n", + "lung_cancer no 1.2 \n", " yes 0.0 \n", - "haematological_cancer no 0.7 \n", + "cancer_excl_lung_and_haem no 1.0 \n", + " yes 20.0 \n", + "haematological_cancer no 1.0 \n", " yes 0.0 \n", - "ckd no 0.8 \n", - " yes 1.7 \n", - "brand_of_first_dose Moderna 0.0 \n", - " Oxford-AZ 0.0 \n", + "ckd no 1.3 \n", + " yes 0.9 \n", + "brand_of_first_dose Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 0.7 \n", + " Unknown 1.3 \n", "\n", " Date projected to reach 90% \n", "category group \n", @@ -14205,50 +14254,50 @@ " M unknown \n", "ageband_5yr 0 unknown \n", " 0-15 unknown \n", - " 16-17 02-Feb \n", + " 16-17 25-Apr \n", " 18-29 unknown \n", - " 30-34 02-Feb \n", + " 30-34 03-May \n", " 35-39 unknown \n", - " 40-44 unknown \n", + " 40-44 03-May \n", " 45-49 unknown \n", - " 50-54 unknown \n", + " 50-54 06-May \n", " 55-59 unknown \n", " 60-64 unknown \n", - " 65-69 unknown \n", + " 65-69 11-May \n", " 70-74 unknown \n", - " 75-79 unknown \n", - " 80-84 19-Jan \n", - " 85-89 unknown \n", + " 75-79 04-May \n", + " 80-84 unknown \n", + " 85-89 22-May \n", " 90+ unknown \n", - "ethnicity_6_groups Black unknown \n", - " Mixed 13-Apr \n", + "ethnicity_6_groups Black 10-Jun \n", + " Mixed 08-Jun \n", " Other unknown \n", " South Asian unknown \n", - " Unknown 17-Apr \n", - " White 29-Apr \n", - "ethnicity_16_groups African 15-Jan \n", + " Unknown unknown \n", + " White unknown \n", + "ethnicity_16_groups African 05-Apr \n", " Bangladeshi or British Bangladeshi unknown \n", " Caribbean unknown \n", " Chinese unknown \n", - " Other 07-Jan \n", - " Other Asian unknown \n", + " Other unknown \n", + " Other Asian 06-Apr \n", " British or Mixed British unknown \n", " Indian or British Indian unknown \n", " Irish unknown \n", - " Other Black unknown \n", + " Other Black 27-Apr \n", " Other White unknown \n", - " Other mixed 29-Jan \n", + " Other mixed unknown \n", " Pakistani or British Pakistani unknown \n", " Unknown unknown \n", - " White + Asian unknown \n", + " White + Asian 19-Apr \n", " White + Black African unknown \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived unknown \n", + " White + Black Caribbean 25-Apr \n", + "imd_categories 1 Most deprived 18-Jun \n", " 2 unknown \n", " 3 unknown \n", - " 4 21-May \n", - " 5 Least deprived unknown \n", - " Unknown 15-Jan \n", + " 4 unknown \n", + " 5 Least deprived 17-Jun \n", + " Unknown unknown \n", "bmi 30+ unknown \n", " under 30 unknown \n", "housebound no unknown \n", @@ -14262,9 +14311,9 @@ "dementia no unknown \n", " yes unknown \n", "psychosis_schiz_bipolar no unknown \n", - " yes unknown \n", + " yes 11-Feb \n", "LD no unknown \n", - " yes 31-Dec \n", + " yes unknown \n", "ssri no unknown \n", " yes unknown \n", "chemo_or_radio no unknown \n", @@ -14272,15 +14321,14 @@ "lung_cancer no unknown \n", " yes unknown \n", "cancer_excl_lung_and_haem no unknown \n", - " yes unknown \n", + " yes 12-Feb \n", "haematological_cancer no unknown \n", " yes unknown \n", "ckd no unknown \n", - " yes 08-May \n", - "brand_of_first_dose Moderna unknown \n", - " Oxford-AZ unknown \n", + " yes unknown \n", + "brand_of_first_dose Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown unknown " + " Unknown 07-Jul " ] }, "metadata": {}, @@ -14309,7 +14357,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **70-79** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **70-79** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -14375,579 +14423,579 @@ " \n", " overall\n", " overall\n", - " 1813\n", - " 52.1\n", - " 3479\n", - " 51.1\n", - " 1.0\n", + " 3773\n", + " 55.0\n", + " 6860\n", + " 54.1\n", + " 0.9\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 931\n", - " 53.0\n", - " 1757\n", - " 51.8\n", + " 1967\n", + " 55.5\n", + " 3542\n", + " 54.3\n", " 1.2\n", " unknown\n", " \n", " \n", " M\n", - " 882\n", - " 51.2\n", - " 1722\n", - " 50.4\n", - " 0.8\n", + " 1806\n", + " 54.4\n", + " 3318\n", + " 53.8\n", + " 0.6\n", " unknown\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 21\n", - " 50.0\n", - " 42\n", - " 50.0\n", + " 49\n", + " 58.3\n", + " 84\n", + " 58.3\n", " 0.0\n", " unknown\n", " \n", " \n", " 0-15\n", - " 119\n", - " 56.7\n", - " 210\n", - " 56.7\n", - " 0.0\n", - " unknown\n", + " 245\n", + " 57.4\n", + " 427\n", + " 55.7\n", + " 1.7\n", + " 16-Jun\n", " \n", " \n", " 16-17\n", - " 140\n", - " 52.6\n", - " 266\n", - " 52.6\n", - " 0.0\n", + " 238\n", + " 52.3\n", + " 455\n", + " 50.8\n", + " 1.5\n", " unknown\n", " \n", " \n", " 18-29\n", - " 112\n", - " 48.5\n", - " 231\n", - " 48.5\n", - " 0.0\n", - " unknown\n", + " 238\n", + " 54.8\n", + " 434\n", + " 53.2\n", + " 1.6\n", + " 06-Jul\n", " \n", " \n", " 30-34\n", - " 147\n", - " 56.8\n", " 259\n", - " 54.1\n", - " 2.7\n", - " 11-Mar\n", + " 55.2\n", + " 469\n", + " 55.2\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 35-39\n", - " 112\n", - " 51.6\n", - " 217\n", - " 51.6\n", - " 0.0\n", - " unknown\n", + " 252\n", + " 54.5\n", + " 462\n", + " 53.0\n", + " 1.5\n", + " 17-Jul\n", " \n", " \n", " 40-44\n", - " 98\n", - " 46.7\n", - " 210\n", - " 46.7\n", - " 0.0\n", + " 217\n", + " 50.0\n", + " 434\n", + " 48.4\n", + " 1.6\n", " unknown\n", " \n", " \n", " 45-49\n", - " 126\n", - " 54.5\n", - " 231\n", - " 54.5\n", + " 245\n", + " 54.7\n", + " 448\n", + " 54.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 50-54\n", - " 105\n", - " 48.4\n", - " 217\n", - " 48.4\n", - " 0.0\n", - " unknown\n", + " 259\n", + " 59.7\n", + " 434\n", + " 58.1\n", + " 1.6\n", + " 14-Jun\n", " \n", " \n", " 55-59\n", - " 105\n", - " 50.0\n", - " 210\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 245\n", + " 53.8\n", + " 455\n", + " 52.3\n", + " 1.5\n", + " 20-Jul\n", " \n", " \n", " 60-64\n", - " 126\n", - " 52.9\n", - " 238\n", - " 52.9\n", + " 245\n", + " 54.7\n", + " 448\n", + " 54.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 65-69\n", - " 119\n", - " 53.1\n", - " 224\n", - " 53.1\n", - " 0.0\n", - " unknown\n", + " 252\n", + " 56.2\n", + " 448\n", + " 54.7\n", + " 1.5\n", + " 09-Jul\n", " \n", " \n", " 70-74\n", - " 105\n", - " 53.6\n", - " 196\n", - " 50.0\n", - " 3.6\n", - " 23-Feb\n", - " \n", - " \n", - " 75-79\n", - " 119\n", - " 50.0\n", " 238\n", - " 47.1\n", - " 2.9\n", - " 21-Mar\n", + " 54.8\n", + " 434\n", + " 54.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", - " 80-84\n", - " 126\n", - " 52.9\n", - " 238\n", - " 52.9\n", + " 75-79\n", + " 245\n", + " 53.8\n", + " 455\n", + " 53.8\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " 80-84\n", + " 245\n", + " 55.6\n", + " 441\n", + " 55.6\n", " 0.0\n", " unknown\n", " \n", " \n", " 85-89\n", - " 112\n", - " 51.6\n", - " 217\n", - " 51.6\n", + " 252\n", + " 56.2\n", + " 448\n", + " 56.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 90+\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 49\n", + " 58.3\n", + " 84\n", + " 58.3\n", " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 322\n", - " 52.9\n", - " 609\n", - " 50.6\n", - " 2.3\n", - " 06-Apr\n", + " 637\n", + " 55.2\n", + " 1155\n", + " 53.9\n", + " 1.3\n", + " unknown\n", " \n", " \n", " Mixed\n", - " 322\n", - " 52.3\n", - " 616\n", - " 52.3\n", - " 0.0\n", + " 658\n", + " 55.3\n", + " 1190\n", + " 54.7\n", + " 0.6\n", " unknown\n", " \n", " \n", " Other\n", - " 308\n", - " 53.7\n", - " 574\n", - " 52.4\n", - " 1.3\n", + " 644\n", + " 54.8\n", + " 1176\n", + " 53.6\n", + " 1.2\n", " unknown\n", " \n", " \n", " South Asian\n", - " 280\n", - " 49.4\n", - " 567\n", - " 48.1\n", - " 1.3\n", + " 672\n", + " 55.8\n", + " 1204\n", + " 54.7\n", + " 1.1\n", " unknown\n", " \n", " \n", " Unknown\n", - " 266\n", - " 52.8\n", - " 504\n", - " 51.4\n", - " 1.4\n", + " 581\n", + " 56.5\n", + " 1029\n", + " 55.8\n", + " 0.7\n", " unknown\n", " \n", " \n", " White\n", - " 322\n", + " 588\n", + " 53.5\n", + " 1099\n", " 52.9\n", - " 609\n", - " 51.7\n", - " 1.2\n", + " 0.6\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 112\n", - " 55.2\n", - " 203\n", - " 55.2\n", + " 196\n", + " 54.9\n", + " 357\n", + " 54.9\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 84\n", - " 42.9\n", - " 196\n", - " 42.9\n", - " 0.0\n", - " unknown\n", + " 182\n", + " 52.0\n", + " 350\n", + " 50.0\n", + " 2.0\n", + " 15-Jun\n", " \n", " \n", " Caribbean\n", - " 98\n", - " 56.0\n", - " 175\n", - " 56.0\n", - " 0.0\n", - " unknown\n", + " 210\n", + " 56.6\n", + " 371\n", + " 54.7\n", + " 1.9\n", + " 05-Jun\n", " \n", " \n", " Chinese\n", - " 91\n", - " 59.1\n", - " 154\n", - " 54.5\n", - " 4.6\n", - " 31-Jan\n", + " 210\n", + " 57.7\n", + " 364\n", + " 55.8\n", + " 1.9\n", + " 01-Jun\n", " \n", " \n", " Other\n", - " 91\n", - " 54.2\n", - " 168\n", - " 54.2\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 50.9\n", + " 371\n", + " 49.1\n", + " 1.8\n", + " 04-Jul\n", " \n", " \n", " Other Asian\n", - " 91\n", - " 50.0\n", - " 182\n", - " 50.0\n", + " 203\n", + " 55.8\n", + " 364\n", + " 55.8\n", " 0.0\n", " unknown\n", " \n", " \n", " British or Mixed British\n", - " 84\n", - " 44.4\n", - " 189\n", - " 44.4\n", - " 0.0\n", - " unknown\n", + " 196\n", + " 57.1\n", + " 343\n", + " 55.1\n", + " 2.0\n", + " 28-May\n", " \n", " \n", " Indian or British Indian\n", - " 91\n", - " 48.1\n", " 189\n", - " 44.4\n", - " 3.7\n", - " 04-Mar\n", + " 50.9\n", + " 371\n", + " 50.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Irish\n", - " 84\n", - " 50.0\n", - " 168\n", - " 50.0\n", + " 210\n", + " 57.7\n", + " 364\n", + " 57.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 105\n", - " 57.7\n", - " 182\n", - " 57.7\n", + " 189\n", + " 51.9\n", + " 364\n", + " 51.9\n", " 0.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 91\n", - " 46.4\n", " 196\n", - " 46.4\n", + " 53.8\n", + " 364\n", + " 53.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 98\n", - " 51.9\n", " 189\n", - " 51.9\n", - " 0.0\n", - " unknown\n", + " 54.0\n", + " 350\n", + " 52.0\n", + " 2.0\n", + " 08-Jun\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 98\n", - " 53.8\n", " 182\n", - " 50.0\n", - " 3.8\n", - " 19-Feb\n", + " 55.3\n", + " 329\n", + " 55.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 294\n", - " 52.5\n", - " 560\n", - " 52.5\n", - " 0.0\n", - " unknown\n", + " 567\n", + " 55.9\n", + " 1015\n", + " 54.5\n", + " 1.4\n", + " 22-Jul\n", " \n", " \n", " White + Asian\n", - " 105\n", - " 51.7\n", - " 203\n", - " 51.7\n", - " 0.0\n", - " unknown\n", + " 224\n", + " 58.2\n", + " 385\n", + " 56.4\n", + " 1.8\n", + " 05-Jun\n", " \n", " \n", " White + Black African\n", - " 105\n", - " 57.7\n", - " 182\n", - " 57.7\n", - " 0.0\n", - " unknown\n", + " 217\n", + " 55.4\n", + " 392\n", + " 53.6\n", + " 1.8\n", + " 16-Jun\n", " \n", " \n", " White + Black Caribbean\n", - " 84\n", - " 48.0\n", - " 175\n", - " 48.0\n", - " 0.0\n", - " unknown\n", + " 224\n", + " 56.1\n", + " 399\n", + " 54.4\n", + " 1.7\n", + " 21-Jun\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 322\n", - " 50.0\n", - " 644\n", - " 48.9\n", + " 721\n", + " 55.4\n", + " 1302\n", + " 54.3\n", " 1.1\n", " unknown\n", " \n", " \n", " 2\n", - " 343\n", - " 50.0\n", - " 686\n", - " 49.0\n", - " 1.0\n", + " 721\n", + " 53.6\n", + " 1344\n", + " 53.1\n", + " 0.5\n", " unknown\n", " \n", " \n", " 3\n", - " 371\n", + " 700\n", + " 54.6\n", + " 1281\n", " 54.1\n", - " 686\n", - " 53.1\n", - " 1.0\n", + " 0.5\n", " unknown\n", " \n", " \n", " 4\n", - " 364\n", - " 55.3\n", - " 658\n", - " 54.3\n", - " 1.0\n", + " 735\n", + " 55.9\n", + " 1316\n", + " 54.8\n", + " 1.1\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 308\n", - " 50.0\n", - " 616\n", - " 48.9\n", - " 1.1\n", + " 700\n", + " 54.6\n", + " 1281\n", + " 54.1\n", + " 0.5\n", " unknown\n", " \n", " \n", " Unknown\n", - " 98\n", - " 51.9\n", " 189\n", - " 51.9\n", + " 57.4\n", + " 329\n", + " 57.4\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 567\n", - " 51.9\n", - " 1092\n", - " 51.3\n", + " 1120\n", + " 54.2\n", + " 2065\n", + " 53.6\n", " 0.6\n", " unknown\n", " \n", " \n", " under 30\n", - " 1239\n", - " 51.9\n", - " 2387\n", - " 51.0\n", - " 0.9\n", + " 2653\n", + " 55.4\n", + " 4788\n", + " 54.4\n", + " 1.0\n", " unknown\n", " \n", " \n", " housebound\n", " no\n", - " 1799\n", - " 52.1\n", - " 3451\n", - " 51.1\n", + " 3731\n", + " 55.0\n", + " 6783\n", + " 54.0\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 42\n", + " 60.0\n", + " 70\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1799\n", - " 52.1\n", - " 3451\n", - " 51.1\n", + " 3752\n", + " 55.2\n", + " 6797\n", + " 54.2\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 21\n", + " 33.3\n", + " 63\n", + " 33.3\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1792\n", - " 52.0\n", - " 3444\n", - " 51.0\n", + " 3724\n", + " 55.0\n", + " 6776\n", + " 54.0\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", - " 50.0\n", - " 42\n", - " 50.0\n", + " 49\n", + " 58.3\n", + " 84\n", + " 58.3\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1799\n", - " 52.2\n", - " 3444\n", - " 51.2\n", + " 3731\n", + " 54.9\n", + " 6790\n", + " 53.9\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 42\n", + " 60.0\n", + " 70\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 1792\n", - " 52.0\n", - " 3444\n", - " 51.0\n", + " 3731\n", + " 55.1\n", + " 6776\n", + " 54.1\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", - " 50.0\n", " 42\n", - " 50.0\n", + " 54.5\n", + " 77\n", + " 54.5\n", " 0.0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1792\n", - " 52.0\n", - " 3444\n", - " 51.0\n", + " 3738\n", + " 55.1\n", + " 6790\n", + " 54.1\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", + " 35\n", " 50.0\n", - " 42\n", + " 70\n", " 50.0\n", " 0.0\n", " unknown\n", @@ -14955,37 +15003,37 @@ " \n", " LD\n", " no\n", - " 1771\n", - " 52.1\n", - " 3402\n", - " 51.0\n", - " 1.1\n", + " 3703\n", + " 55.0\n", + " 6727\n", + " 54.0\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 42\n", - " 54.5\n", " 77\n", - " 54.5\n", - " 0.0\n", - " unknown\n", + " 57.9\n", + " 133\n", + " 52.6\n", + " 5.3\n", + " 16-Mar\n", " \n", " \n", " ssri\n", " no\n", - " 1799\n", - " 52.1\n", - " 3451\n", - " 51.1\n", + " 3738\n", + " 55.1\n", + " 6790\n", + " 54.1\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", + " 35\n", " 50.0\n", - " 28\n", + " 70\n", " 50.0\n", " 0.0\n", " unknown\n", @@ -14993,18 +15041,18 @@ " \n", " chemo_or_radio\n", " no\n", - " 1792\n", - " 51.9\n", - " 3451\n", - " 50.9\n", - " 1.0\n", + " 3738\n", + " 55.1\n", + " 6790\n", + " 54.0\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", + " 42\n", " 60.0\n", - " 35\n", + " 70\n", " 60.0\n", " 0.0\n", " unknown\n", @@ -15012,37 +15060,37 @@ " \n", " lung_cancer\n", " no\n", - " 1792\n", - " 52.0\n", - " 3444\n", - " 51.0\n", + " 3738\n", + " 55.1\n", + " 6790\n", + " 54.1\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", " 35\n", - " 40.0\n", + " 55.6\n", + " 63\n", + " 55.6\n", " 0.0\n", " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1792\n", - " 52.0\n", - " 3444\n", - " 51.0\n", - " 1.0\n", + " 3738\n", + " 55.1\n", + " 6790\n", + " 54.0\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", + " 42\n", " 60.0\n", - " 35\n", + " 70\n", " 60.0\n", " 0.0\n", " unknown\n", @@ -15050,39 +15098,39 @@ " \n", " haematological_cancer\n", " no\n", - " 1785\n", - " 51.9\n", - " 3437\n", - " 50.9\n", - " 1.0\n", + " 3731\n", + " 55.0\n", + " 6783\n", + " 54.1\n", + " 0.9\n", " unknown\n", " \n", " \n", " yes\n", - " 28\n", - " 66.7\n", " 42\n", - " 66.7\n", + " 60.0\n", + " 70\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1442\n", - " 52.6\n", - " 2744\n", - " 51.5\n", - " 1.1\n", + " 3024\n", + " 55.2\n", + " 5481\n", + " 54.0\n", + " 1.2\n", " unknown\n", " \n", " \n", " yes\n", - " 371\n", - " 50.5\n", - " 735\n", - " 49.5\n", - " 1.0\n", + " 756\n", + " 54.8\n", + " 1379\n", + " 54.3\n", + " 0.5\n", " unknown\n", " \n", " \n", @@ -15099,8 +15147,8 @@ " Oxford-AZ\n", " 0\n", " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", @@ -15108,17 +15156,17 @@ " Pfizer\n", " 0\n", " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 1806\n", - " 57.8\n", - " 3122\n", - " 56.7\n", + " 3759\n", + " 61.0\n", + " 6167\n", + " 59.9\n", " 1.1\n", " unknown\n", " \n", @@ -15129,309 +15177,309 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1813 \n", - "sex F 931 \n", - " M 882 \n", - "ageband_5yr 0 21 \n", - " 0-15 119 \n", - " 16-17 140 \n", - " 18-29 112 \n", - " 30-34 147 \n", - " 35-39 112 \n", - " 40-44 98 \n", - " 45-49 126 \n", - " 50-54 105 \n", - " 55-59 105 \n", - " 60-64 126 \n", - " 65-69 119 \n", - " 70-74 105 \n", - " 75-79 119 \n", - " 80-84 126 \n", - " 85-89 112 \n", - " 90+ 14 \n", - "ethnicity_6_groups Black 322 \n", - " Mixed 322 \n", - " Other 308 \n", - " South Asian 280 \n", - " Unknown 266 \n", - " White 322 \n", - "ethnicity_16_groups African 112 \n", - " Bangladeshi or British Bangladeshi 84 \n", - " Caribbean 98 \n", - " Chinese 91 \n", - " Other 91 \n", - " Other Asian 91 \n", - " British or Mixed British 84 \n", - " Indian or British Indian 91 \n", - " Irish 84 \n", - " Other Black 105 \n", - " Other White 91 \n", - " Other mixed 98 \n", - " Pakistani or British Pakistani 98 \n", - " Unknown 294 \n", - " White + Asian 105 \n", - " White + Black African 105 \n", - " White + Black Caribbean 84 \n", - "imd_categories 1 Most deprived 322 \n", - " 2 343 \n", - " 3 371 \n", - " 4 364 \n", - " 5 Least deprived 308 \n", - " Unknown 98 \n", - "bmi 30+ 567 \n", - " under 30 1239 \n", - "housebound no 1799 \n", - " yes 14 \n", - "chronic_cardiac_disease no 1799 \n", - " yes 14 \n", - "current_copd no 1792 \n", - " yes 21 \n", - "dmards no 1799 \n", - " yes 14 \n", - "dementia no 1792 \n", - " yes 21 \n", - "psychosis_schiz_bipolar no 1792 \n", - " yes 21 \n", - "LD no 1771 \n", + "overall overall 3773 \n", + "sex F 1967 \n", + " M 1806 \n", + "ageband_5yr 0 49 \n", + " 0-15 245 \n", + " 16-17 238 \n", + " 18-29 238 \n", + " 30-34 259 \n", + " 35-39 252 \n", + " 40-44 217 \n", + " 45-49 245 \n", + " 50-54 259 \n", + " 55-59 245 \n", + " 60-64 245 \n", + " 65-69 252 \n", + " 70-74 238 \n", + " 75-79 245 \n", + " 80-84 245 \n", + " 85-89 252 \n", + " 90+ 49 \n", + "ethnicity_6_groups Black 637 \n", + " Mixed 658 \n", + " Other 644 \n", + " South Asian 672 \n", + " Unknown 581 \n", + " White 588 \n", + "ethnicity_16_groups African 196 \n", + " Bangladeshi or British Bangladeshi 182 \n", + " Caribbean 210 \n", + " Chinese 210 \n", + " Other 189 \n", + " Other Asian 203 \n", + " British or Mixed British 196 \n", + " Indian or British Indian 189 \n", + " Irish 210 \n", + " Other Black 189 \n", + " Other White 196 \n", + " Other mixed 189 \n", + " Pakistani or British Pakistani 182 \n", + " Unknown 567 \n", + " White + Asian 224 \n", + " White + Black African 217 \n", + " White + Black Caribbean 224 \n", + "imd_categories 1 Most deprived 721 \n", + " 2 721 \n", + " 3 700 \n", + " 4 735 \n", + " 5 Least deprived 700 \n", + " Unknown 189 \n", + "bmi 30+ 1120 \n", + " under 30 2653 \n", + "housebound no 3731 \n", " yes 42 \n", - "ssri no 1799 \n", - " yes 14 \n", - "chemo_or_radio no 1792 \n", - " yes 21 \n", - "lung_cancer no 1792 \n", - " yes 14 \n", - "cancer_excl_lung_and_haem no 1792 \n", + "chronic_cardiac_disease no 3752 \n", " yes 21 \n", - "haematological_cancer no 1785 \n", - " yes 28 \n", - "ckd no 1442 \n", - " yes 371 \n", - "brand_of_first_dose Moderna 0 \n", - " Oxford-AZ 0 \n", - " Pfizer 0 \n", - " Unknown 1806 \n", + "current_copd no 3724 \n", + " yes 49 \n", + "dmards no 3731 \n", + " yes 42 \n", + "dementia no 3731 \n", + " yes 42 \n", + "psychosis_schiz_bipolar no 3738 \n", + " yes 35 \n", + "LD no 3703 \n", + " yes 77 \n", + "ssri no 3738 \n", + " yes 35 \n", + "chemo_or_radio no 3738 \n", + " yes 42 \n", + "lung_cancer no 3738 \n", + " yes 35 \n", + "cancer_excl_lung_and_haem no 3738 \n", + " yes 42 \n", + "haematological_cancer no 3731 \n", + " yes 42 \n", + "ckd no 3024 \n", + " yes 756 \n", + "brand_of_first_dose Moderna 0 \n", + " Oxford-AZ 0 \n", + " Pfizer 0 \n", + " Unknown 3759 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 52.1 3479 \n", - "sex F 53.0 1757 \n", - " M 51.2 1722 \n", - "ageband_5yr 0 50.0 42 \n", - " 0-15 56.7 210 \n", - " 16-17 52.6 266 \n", - " 18-29 48.5 231 \n", - " 30-34 56.8 259 \n", - " 35-39 51.6 217 \n", - " 40-44 46.7 210 \n", - " 45-49 54.5 231 \n", - " 50-54 48.4 217 \n", - " 55-59 50.0 210 \n", - " 60-64 52.9 238 \n", - " 65-69 53.1 224 \n", - " 70-74 53.6 196 \n", - " 75-79 50.0 238 \n", - " 80-84 52.9 238 \n", - " 85-89 51.6 217 \n", - " 90+ 50.0 28 \n", - "ethnicity_6_groups Black 52.9 609 \n", - " Mixed 52.3 616 \n", - " Other 53.7 574 \n", - " South Asian 49.4 567 \n", - " Unknown 52.8 504 \n", - " White 52.9 609 \n", - "ethnicity_16_groups African 55.2 203 \n", - " Bangladeshi or British Bangladeshi 42.9 196 \n", - " Caribbean 56.0 175 \n", - " Chinese 59.1 154 \n", - " Other 54.2 168 \n", - " Other Asian 50.0 182 \n", - " British or Mixed British 44.4 189 \n", - " Indian or British Indian 48.1 189 \n", - " Irish 50.0 168 \n", - " Other Black 57.7 182 \n", - " Other White 46.4 196 \n", - " Other mixed 51.9 189 \n", - " Pakistani or British Pakistani 53.8 182 \n", - " Unknown 52.5 560 \n", - " White + Asian 51.7 203 \n", - " White + Black African 57.7 182 \n", - " White + Black Caribbean 48.0 175 \n", - "imd_categories 1 Most deprived 50.0 644 \n", - " 2 50.0 686 \n", - " 3 54.1 686 \n", - " 4 55.3 658 \n", - " 5 Least deprived 50.0 616 \n", - " Unknown 51.9 189 \n", - "bmi 30+ 51.9 1092 \n", - " under 30 51.9 2387 \n", - "housebound no 52.1 3451 \n", - " yes 50.0 28 \n", - "chronic_cardiac_disease no 52.1 3451 \n", - " yes 50.0 28 \n", - "current_copd no 52.0 3444 \n", - " yes 50.0 42 \n", - "dmards no 52.2 3444 \n", - " yes 40.0 35 \n", - "dementia no 52.0 3444 \n", - " yes 50.0 42 \n", - "psychosis_schiz_bipolar no 52.0 3444 \n", - " yes 50.0 42 \n", - "LD no 52.1 3402 \n", + "overall overall 55.0 6860 \n", + "sex F 55.5 3542 \n", + " M 54.4 3318 \n", + "ageband_5yr 0 58.3 84 \n", + " 0-15 57.4 427 \n", + " 16-17 52.3 455 \n", + " 18-29 54.8 434 \n", + " 30-34 55.2 469 \n", + " 35-39 54.5 462 \n", + " 40-44 50.0 434 \n", + " 45-49 54.7 448 \n", + " 50-54 59.7 434 \n", + " 55-59 53.8 455 \n", + " 60-64 54.7 448 \n", + " 65-69 56.2 448 \n", + " 70-74 54.8 434 \n", + " 75-79 53.8 455 \n", + " 80-84 55.6 441 \n", + " 85-89 56.2 448 \n", + " 90+ 58.3 84 \n", + "ethnicity_6_groups Black 55.2 1155 \n", + " Mixed 55.3 1190 \n", + " Other 54.8 1176 \n", + " South Asian 55.8 1204 \n", + " Unknown 56.5 1029 \n", + " White 53.5 1099 \n", + "ethnicity_16_groups African 54.9 357 \n", + " Bangladeshi or British Bangladeshi 52.0 350 \n", + " Caribbean 56.6 371 \n", + " Chinese 57.7 364 \n", + " Other 50.9 371 \n", + " Other Asian 55.8 364 \n", + " British or Mixed British 57.1 343 \n", + " Indian or British Indian 50.9 371 \n", + " Irish 57.7 364 \n", + " Other Black 51.9 364 \n", + " Other White 53.8 364 \n", + " Other mixed 54.0 350 \n", + " Pakistani or British Pakistani 55.3 329 \n", + " Unknown 55.9 1015 \n", + " White + Asian 58.2 385 \n", + " White + Black African 55.4 392 \n", + " White + Black Caribbean 56.1 399 \n", + "imd_categories 1 Most deprived 55.4 1302 \n", + " 2 53.6 1344 \n", + " 3 54.6 1281 \n", + " 4 55.9 1316 \n", + " 5 Least deprived 54.6 1281 \n", + " Unknown 57.4 329 \n", + "bmi 30+ 54.2 2065 \n", + " under 30 55.4 4788 \n", + "housebound no 55.0 6783 \n", + " yes 60.0 70 \n", + "chronic_cardiac_disease no 55.2 6797 \n", + " yes 33.3 63 \n", + "current_copd no 55.0 6776 \n", + " yes 58.3 84 \n", + "dmards no 54.9 6790 \n", + " yes 60.0 70 \n", + "dementia no 55.1 6776 \n", " yes 54.5 77 \n", - "ssri no 52.1 3451 \n", - " yes 50.0 28 \n", - "chemo_or_radio no 51.9 3451 \n", - " yes 60.0 35 \n", - "lung_cancer no 52.0 3444 \n", - " yes 40.0 35 \n", - "cancer_excl_lung_and_haem no 52.0 3444 \n", - " yes 60.0 35 \n", - "haematological_cancer no 51.9 3437 \n", - " yes 66.7 42 \n", - "ckd no 52.6 2744 \n", - " yes 50.5 735 \n", + "psychosis_schiz_bipolar no 55.1 6790 \n", + " yes 50.0 70 \n", + "LD no 55.0 6727 \n", + " yes 57.9 133 \n", + "ssri no 55.1 6790 \n", + " yes 50.0 70 \n", + "chemo_or_radio no 55.1 6790 \n", + " yes 60.0 70 \n", + "lung_cancer no 55.1 6790 \n", + " yes 55.6 63 \n", + "cancer_excl_lung_and_haem no 55.1 6790 \n", + " yes 60.0 70 \n", + "haematological_cancer no 55.0 6783 \n", + " yes 60.0 70 \n", + "ckd no 55.2 5481 \n", + " yes 54.8 1379 \n", "brand_of_first_dose Moderna 0.0 0 \n", - " Oxford-AZ 0.0 0 \n", - " Pfizer 0.0 0 \n", - " Unknown 57.8 3122 \n", + " Oxford-AZ 0.0 7 \n", + " Pfizer 0.0 7 \n", + " Unknown 61.0 6167 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 51.1 \n", - "sex F 51.8 \n", - " M 50.4 \n", - "ageband_5yr 0 50.0 \n", - " 0-15 56.7 \n", - " 16-17 52.6 \n", - " 18-29 48.5 \n", - " 30-34 54.1 \n", - " 35-39 51.6 \n", - " 40-44 46.7 \n", - " 45-49 54.5 \n", - " 50-54 48.4 \n", - " 55-59 50.0 \n", - " 60-64 52.9 \n", - " 65-69 53.1 \n", - " 70-74 50.0 \n", - " 75-79 47.1 \n", - " 80-84 52.9 \n", - " 85-89 51.6 \n", - " 90+ 50.0 \n", - "ethnicity_6_groups Black 50.6 \n", - " Mixed 52.3 \n", - " Other 52.4 \n", - " South Asian 48.1 \n", - " Unknown 51.4 \n", - " White 51.7 \n", - "ethnicity_16_groups African 55.2 \n", - " Bangladeshi or British Bangladeshi 42.9 \n", - " Caribbean 56.0 \n", - " Chinese 54.5 \n", - " Other 54.2 \n", - " Other Asian 50.0 \n", - " British or Mixed British 44.4 \n", - " Indian or British Indian 44.4 \n", - " Irish 50.0 \n", - " Other Black 57.7 \n", - " Other White 46.4 \n", - " Other mixed 51.9 \n", - " Pakistani or British Pakistani 50.0 \n", - " Unknown 52.5 \n", - " White + Asian 51.7 \n", - " White + Black African 57.7 \n", - " White + Black Caribbean 48.0 \n", - "imd_categories 1 Most deprived 48.9 \n", - " 2 49.0 \n", - " 3 53.1 \n", - " 4 54.3 \n", - " 5 Least deprived 48.9 \n", - " Unknown 51.9 \n", - "bmi 30+ 51.3 \n", - " under 30 51.0 \n", - "housebound no 51.1 \n", - " yes 50.0 \n", - "chronic_cardiac_disease no 51.1 \n", - " yes 50.0 \n", - "current_copd no 51.0 \n", - " yes 50.0 \n", - "dmards no 51.2 \n", - " yes 40.0 \n", - "dementia no 51.0 \n", - " yes 50.0 \n", - "psychosis_schiz_bipolar no 51.0 \n", - " yes 50.0 \n", - "LD no 51.0 \n", + "overall overall 54.1 \n", + "sex F 54.3 \n", + " M 53.8 \n", + "ageband_5yr 0 58.3 \n", + " 0-15 55.7 \n", + " 16-17 50.8 \n", + " 18-29 53.2 \n", + " 30-34 55.2 \n", + " 35-39 53.0 \n", + " 40-44 48.4 \n", + " 45-49 54.7 \n", + " 50-54 58.1 \n", + " 55-59 52.3 \n", + " 60-64 54.7 \n", + " 65-69 54.7 \n", + " 70-74 54.8 \n", + " 75-79 53.8 \n", + " 80-84 55.6 \n", + " 85-89 56.2 \n", + " 90+ 58.3 \n", + "ethnicity_6_groups Black 53.9 \n", + " Mixed 54.7 \n", + " Other 53.6 \n", + " South Asian 54.7 \n", + " Unknown 55.8 \n", + " White 52.9 \n", + "ethnicity_16_groups African 54.9 \n", + " Bangladeshi or British Bangladeshi 50.0 \n", + " Caribbean 54.7 \n", + " Chinese 55.8 \n", + " Other 49.1 \n", + " Other Asian 55.8 \n", + " British or Mixed British 55.1 \n", + " Indian or British Indian 50.9 \n", + " Irish 57.7 \n", + " Other Black 51.9 \n", + " Other White 53.8 \n", + " Other mixed 52.0 \n", + " Pakistani or British Pakistani 55.3 \n", + " Unknown 54.5 \n", + " White + Asian 56.4 \n", + " White + Black African 53.6 \n", + " White + Black Caribbean 54.4 \n", + "imd_categories 1 Most deprived 54.3 \n", + " 2 53.1 \n", + " 3 54.1 \n", + " 4 54.8 \n", + " 5 Least deprived 54.1 \n", + " Unknown 57.4 \n", + "bmi 30+ 53.6 \n", + " under 30 54.4 \n", + "housebound no 54.0 \n", + " yes 60.0 \n", + "chronic_cardiac_disease no 54.2 \n", + " yes 33.3 \n", + "current_copd no 54.0 \n", + " yes 58.3 \n", + "dmards no 53.9 \n", + " yes 60.0 \n", + "dementia no 54.1 \n", " yes 54.5 \n", - "ssri no 51.1 \n", + "psychosis_schiz_bipolar no 54.1 \n", + " yes 50.0 \n", + "LD no 54.0 \n", + " yes 52.6 \n", + "ssri no 54.1 \n", " yes 50.0 \n", - "chemo_or_radio no 50.9 \n", + "chemo_or_radio no 54.0 \n", " yes 60.0 \n", - "lung_cancer no 51.0 \n", - " yes 40.0 \n", - "cancer_excl_lung_and_haem no 51.0 \n", + "lung_cancer no 54.1 \n", + " yes 55.6 \n", + "cancer_excl_lung_and_haem no 54.0 \n", " yes 60.0 \n", - "haematological_cancer no 50.9 \n", - " yes 66.7 \n", - "ckd no 51.5 \n", - " yes 49.5 \n", + "haematological_cancer no 54.1 \n", + " yes 60.0 \n", + "ckd no 54.0 \n", + " yes 54.3 \n", "brand_of_first_dose Moderna NaN \n", - " Oxford-AZ NaN \n", - " Pfizer NaN \n", - " Unknown 56.7 \n", + " Oxford-AZ 0.0 \n", + " Pfizer 0.0 \n", + " Unknown 59.9 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.0 \n", + "overall overall 0.9 \n", "sex F 1.2 \n", - " M 0.8 \n", + " M 0.6 \n", "ageband_5yr 0 0.0 \n", - " 0-15 0.0 \n", - " 16-17 0.0 \n", - " 18-29 0.0 \n", - " 30-34 2.7 \n", - " 35-39 0.0 \n", - " 40-44 0.0 \n", + " 0-15 1.7 \n", + " 16-17 1.5 \n", + " 18-29 1.6 \n", + " 30-34 0.0 \n", + " 35-39 1.5 \n", + " 40-44 1.6 \n", " 45-49 0.0 \n", - " 50-54 0.0 \n", - " 55-59 0.0 \n", + " 50-54 1.6 \n", + " 55-59 1.5 \n", " 60-64 0.0 \n", - " 65-69 0.0 \n", - " 70-74 3.6 \n", - " 75-79 2.9 \n", + " 65-69 1.5 \n", + " 70-74 0.0 \n", + " 75-79 0.0 \n", " 80-84 0.0 \n", " 85-89 0.0 \n", " 90+ 0.0 \n", - "ethnicity_6_groups Black 2.3 \n", - " Mixed 0.0 \n", - " Other 1.3 \n", - " South Asian 1.3 \n", - " Unknown 1.4 \n", - " White 1.2 \n", + "ethnicity_6_groups Black 1.3 \n", + " Mixed 0.6 \n", + " Other 1.2 \n", + " South Asian 1.1 \n", + " Unknown 0.7 \n", + " White 0.6 \n", "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", - " Chinese 4.6 \n", - " Other 0.0 \n", + " Bangladeshi or British Bangladeshi 2.0 \n", + " Caribbean 1.9 \n", + " Chinese 1.9 \n", + " Other 1.8 \n", " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 3.7 \n", + " British or Mixed British 2.0 \n", + " Indian or British Indian 0.0 \n", " Irish 0.0 \n", " Other Black 0.0 \n", " Other White 0.0 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 3.8 \n", - " Unknown 0.0 \n", - " White + Asian 0.0 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", + " Other mixed 2.0 \n", + " Pakistani or British Pakistani 0.0 \n", + " Unknown 1.4 \n", + " White + Asian 1.8 \n", + " White + Black African 1.8 \n", + " White + Black Caribbean 1.7 \n", "imd_categories 1 Most deprived 1.1 \n", - " 2 1.0 \n", - " 3 1.0 \n", - " 4 1.0 \n", - " 5 Least deprived 1.1 \n", + " 2 0.5 \n", + " 3 0.5 \n", + " 4 1.1 \n", + " 5 Least deprived 0.5 \n", " Unknown 0.0 \n", "bmi 30+ 0.6 \n", - " under 30 0.9 \n", + " under 30 1.0 \n", "housebound no 1.0 \n", " yes 0.0 \n", "chronic_cardiac_disease no 1.0 \n", @@ -15444,20 +15492,20 @@ " yes 0.0 \n", "psychosis_schiz_bipolar no 1.0 \n", " yes 0.0 \n", - "LD no 1.1 \n", - " yes 0.0 \n", + "LD no 1.0 \n", + " yes 5.3 \n", "ssri no 1.0 \n", " yes 0.0 \n", - "chemo_or_radio no 1.0 \n", + "chemo_or_radio no 1.1 \n", " yes 0.0 \n", "lung_cancer no 1.0 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.0 \n", + "cancer_excl_lung_and_haem no 1.1 \n", " yes 0.0 \n", - "haematological_cancer no 1.0 \n", + "haematological_cancer no 0.9 \n", " yes 0.0 \n", - "ckd no 1.1 \n", - " yes 1.0 \n", + "ckd no 1.2 \n", + " yes 0.5 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", @@ -15469,45 +15517,45 @@ "sex F unknown \n", " M unknown \n", "ageband_5yr 0 unknown \n", - " 0-15 unknown \n", + " 0-15 16-Jun \n", " 16-17 unknown \n", - " 18-29 unknown \n", - " 30-34 11-Mar \n", - " 35-39 unknown \n", + " 18-29 06-Jul \n", + " 30-34 unknown \n", + " 35-39 17-Jul \n", " 40-44 unknown \n", " 45-49 unknown \n", - " 50-54 unknown \n", - " 55-59 unknown \n", + " 50-54 14-Jun \n", + " 55-59 20-Jul \n", " 60-64 unknown \n", - " 65-69 unknown \n", - " 70-74 23-Feb \n", - " 75-79 21-Mar \n", + " 65-69 09-Jul \n", + " 70-74 unknown \n", + " 75-79 unknown \n", " 80-84 unknown \n", " 85-89 unknown \n", " 90+ unknown \n", - "ethnicity_6_groups Black 06-Apr \n", + "ethnicity_6_groups Black unknown \n", " Mixed unknown \n", " Other unknown \n", " South Asian unknown \n", " Unknown unknown \n", " White unknown \n", "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean unknown \n", - " Chinese 31-Jan \n", - " Other unknown \n", + " Bangladeshi or British Bangladeshi 15-Jun \n", + " Caribbean 05-Jun \n", + " Chinese 01-Jun \n", + " Other 04-Jul \n", " Other Asian unknown \n", - " British or Mixed British unknown \n", - " Indian or British Indian 04-Mar \n", + " British or Mixed British 28-May \n", + " Indian or British Indian unknown \n", " Irish unknown \n", " Other Black unknown \n", " Other White unknown \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani 19-Feb \n", - " Unknown unknown \n", - " White + Asian unknown \n", - " White + Black African unknown \n", - " White + Black Caribbean unknown \n", + " Other mixed 08-Jun \n", + " Pakistani or British Pakistani unknown \n", + " Unknown 22-Jul \n", + " White + Asian 05-Jun \n", + " White + Black African 16-Jun \n", + " White + Black Caribbean 21-Jun \n", "imd_categories 1 Most deprived unknown \n", " 2 unknown \n", " 3 unknown \n", @@ -15529,7 +15577,7 @@ "psychosis_schiz_bipolar no unknown \n", " yes unknown \n", "LD no unknown \n", - " yes unknown \n", + " yes 16-Mar \n", "ssri no unknown \n", " yes unknown \n", "chemo_or_radio no unknown \n", @@ -15574,7 +15622,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **care home** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **care home** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -15640,257 +15688,257 @@ " \n", " overall\n", " overall\n", - " 749\n", - " 53.8\n", - " 1393\n", - " 52.8\n", - " 1.0\n", + " 1533\n", + " 54.3\n", + " 2821\n", + " 53.1\n", + " 1.2\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 399\n", - " 55.3\n", - " 721\n", - " 53.4\n", - " 1.9\n", - " 21-Apr\n", + " 749\n", + " 52.5\n", + " 1428\n", + " 52.0\n", + " 0.5\n", + " unknown\n", " \n", " \n", " M\n", - " 350\n", - " 52.1\n", - " 672\n", - " 52.1\n", - " 0.0\n", - " unknown\n", + " 777\n", + " 56.1\n", + " 1386\n", + " 54.5\n", + " 1.6\n", + " 30-Jun\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 7\n", - " 50.0\n", - " 14\n", + " 21\n", + " 75.0\n", + " 28\n", " 50.0\n", - " 0.0\n", - " unknown\n", + " 25.0\n", + " 06-Feb\n", " \n", " \n", " 0-15\n", - " 56\n", - " 61.5\n", - " 91\n", - " 61.5\n", + " 98\n", + " 56.0\n", + " 175\n", + " 56.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 16-17\n", - " 49\n", - " 50.0\n", - " 98\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 119\n", + " 60.7\n", + " 196\n", + " 57.1\n", + " 3.6\n", + " 30-Mar\n", " \n", " \n", " 18-29\n", - " 42\n", - " 50.0\n", - " 84\n", - " 50.0\n", + " 91\n", + " 54.2\n", + " 168\n", + " 54.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 30-34\n", - " 42\n", - " 50.0\n", - " 84\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 105\n", + " 55.6\n", + " 189\n", + " 51.9\n", + " 3.7\n", + " 08-Apr\n", " \n", " \n", " 35-39\n", - " 49\n", - " 50.0\n", - " 98\n", - " 50.0\n", + " 105\n", + " 55.6\n", + " 189\n", + " 55.6\n", " 0.0\n", " unknown\n", " \n", " \n", " 40-44\n", - " 49\n", + " 84\n", " 50.0\n", - " 98\n", - " 42.9\n", - " 7.1\n", - " 23-Jan\n", + " 168\n", + " 50.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 45-49\n", - " 49\n", - " 53.8\n", " 91\n", - " 53.8\n", + " 50.0\n", + " 182\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 50-54\n", - " 49\n", - " 58.3\n", - " 84\n", - " 58.3\n", + " 105\n", + " 57.7\n", + " 182\n", + " 57.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 55-59\n", - " 49\n", - " 53.8\n", - " 91\n", - " 53.8\n", + " 98\n", + " 50.0\n", + " 196\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 60-64\n", - " 49\n", - " 53.8\n", - " 91\n", - " 46.2\n", - " 7.6\n", - " 17-Jan\n", + " 98\n", + " 50.0\n", + " 196\n", + " 50.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 65-69\n", - " 49\n", - " 58.3\n", - " 84\n", - " 50.0\n", - " 8.3\n", - " 10-Jan\n", + " 98\n", + " 53.8\n", + " 182\n", + " 53.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 70-74\n", - " 56\n", - " 53.3\n", - " 105\n", - " 53.3\n", + " 91\n", + " 48.1\n", + " 189\n", + " 48.1\n", " 0.0\n", " unknown\n", " \n", " \n", " 75-79\n", - " 56\n", - " 61.5\n", " 91\n", - " 61.5\n", + " 52.0\n", + " 175\n", + " 52.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 80-84\n", - " 35\n", - " 45.5\n", - " 77\n", - " 45.5\n", + " 105\n", + " 57.7\n", + " 182\n", + " 57.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 85-89\n", - " 49\n", - " 50.0\n", - " 98\n", - " 50.0\n", + " 105\n", + " 60.0\n", + " 175\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 90+\n", - " 0\n", - " 0.0\n", - " 14\n", - " 0.0\n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 133\n", - " 59.4\n", - " 224\n", - " 59.4\n", - " 0.0\n", - " unknown\n", + " 238\n", + " 53.1\n", + " 448\n", + " 51.6\n", + " 1.5\n", + " 24-Jul\n", " \n", " \n", " Mixed\n", - " 133\n", - " 52.8\n", - " 252\n", - " 52.8\n", - " 0.0\n", - " unknown\n", + " 259\n", + " 56.1\n", + " 462\n", + " 54.5\n", + " 1.6\n", + " 30-Jun\n", " \n", " \n", " Other\n", - " 119\n", - " 56.7\n", - " 210\n", - " 53.3\n", - " 3.4\n", - " 21-Feb\n", + " 266\n", + " 52.8\n", + " 504\n", + " 51.4\n", + " 1.4\n", + " unknown\n", " \n", " \n", " South Asian\n", - " 140\n", - " 52.6\n", - " 266\n", - " 50.0\n", - " 2.6\n", - " 25-Mar\n", + " 259\n", + " 55.2\n", + " 469\n", + " 53.7\n", + " 1.5\n", + " 14-Jul\n", " \n", " \n", " Unknown\n", - " 105\n", - " 50.0\n", - " 210\n", - " 50.0\n", + " 245\n", + " 56.5\n", + " 434\n", + " 56.5\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", - " 119\n", - " 51.5\n", - " 231\n", - " 51.5\n", + " 259\n", + " 52.9\n", + " 490\n", + " 52.9\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 749\n", - " 54.3\n", - " 1379\n", - " 52.8\n", - " 1.5\n", - " 30-May\n", + " 1512\n", + " 54.1\n", + " 2793\n", + " 53.1\n", + " 1.0\n", + " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", " 14\n", - " 0.0\n", + " 50.0\n", + " 28\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", @@ -15915,12 +15963,12 @@ " \n", " \n", " Unknown\n", - " 749\n", - " 59.8\n", - " 1253\n", - " 58.1\n", - " 1.7\n", - " 18-Apr\n", + " 1526\n", + " 60.4\n", + " 2527\n", + " 59.0\n", + " 1.4\n", + " 30-Jun\n", " \n", " \n", "\n", @@ -15929,139 +15977,139 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 749 53.8 1393 \n", - "sex F 399 55.3 721 \n", - " M 350 52.1 672 \n", - "ageband_5yr 0 7 50.0 14 \n", - " 0-15 56 61.5 91 \n", - " 16-17 49 50.0 98 \n", - " 18-29 42 50.0 84 \n", - " 30-34 42 50.0 84 \n", - " 35-39 49 50.0 98 \n", - " 40-44 49 50.0 98 \n", - " 45-49 49 53.8 91 \n", - " 50-54 49 58.3 84 \n", - " 55-59 49 53.8 91 \n", - " 60-64 49 53.8 91 \n", - " 65-69 49 58.3 84 \n", - " 70-74 56 53.3 105 \n", - " 75-79 56 61.5 91 \n", - " 80-84 35 45.5 77 \n", - " 85-89 49 50.0 98 \n", - " 90+ 0 0.0 14 \n", - "ethnicity_6_groups Black 133 59.4 224 \n", - " Mixed 133 52.8 252 \n", - " Other 119 56.7 210 \n", - " South Asian 140 52.6 266 \n", - " Unknown 105 50.0 210 \n", - " White 119 51.5 231 \n", - "dementia no 749 54.3 1379 \n", - " yes 0 0.0 14 \n", + "overall overall 1533 54.3 2821 \n", + "sex F 749 52.5 1428 \n", + " M 777 56.1 1386 \n", + "ageband_5yr 0 21 75.0 28 \n", + " 0-15 98 56.0 175 \n", + " 16-17 119 60.7 196 \n", + " 18-29 91 54.2 168 \n", + " 30-34 105 55.6 189 \n", + " 35-39 105 55.6 189 \n", + " 40-44 84 50.0 168 \n", + " 45-49 91 50.0 182 \n", + " 50-54 105 57.7 182 \n", + " 55-59 98 50.0 196 \n", + " 60-64 98 50.0 196 \n", + " 65-69 98 53.8 182 \n", + " 70-74 91 48.1 189 \n", + " 75-79 91 52.0 175 \n", + " 80-84 105 57.7 182 \n", + " 85-89 105 60.0 175 \n", + " 90+ 28 57.1 49 \n", + "ethnicity_6_groups Black 238 53.1 448 \n", + " Mixed 259 56.1 462 \n", + " Other 266 52.8 504 \n", + " South Asian 259 55.2 469 \n", + " Unknown 245 56.5 434 \n", + " White 259 52.9 490 \n", + "dementia no 1512 54.1 2793 \n", + " yes 14 50.0 28 \n", "brand_of_first_dose Oxford-AZ 0 0.0 0 \n", " Pfizer 0 0.0 0 \n", - " Unknown 749 59.8 1253 \n", + " Unknown 1526 60.4 2527 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 52.8 \n", - "sex F 53.4 \n", - " M 52.1 \n", + "overall overall 53.1 \n", + "sex F 52.0 \n", + " M 54.5 \n", "ageband_5yr 0 50.0 \n", - " 0-15 61.5 \n", - " 16-17 50.0 \n", - " 18-29 50.0 \n", - " 30-34 50.0 \n", - " 35-39 50.0 \n", - " 40-44 42.9 \n", - " 45-49 53.8 \n", - " 50-54 58.3 \n", - " 55-59 53.8 \n", - " 60-64 46.2 \n", - " 65-69 50.0 \n", - " 70-74 53.3 \n", - " 75-79 61.5 \n", - " 80-84 45.5 \n", - " 85-89 50.0 \n", - " 90+ 0.0 \n", - "ethnicity_6_groups Black 59.4 \n", - " Mixed 52.8 \n", - " Other 53.3 \n", - " South Asian 50.0 \n", - " Unknown 50.0 \n", - " White 51.5 \n", - "dementia no 52.8 \n", - " yes 0.0 \n", + " 0-15 56.0 \n", + " 16-17 57.1 \n", + " 18-29 54.2 \n", + " 30-34 51.9 \n", + " 35-39 55.6 \n", + " 40-44 50.0 \n", + " 45-49 50.0 \n", + " 50-54 57.7 \n", + " 55-59 50.0 \n", + " 60-64 50.0 \n", + " 65-69 53.8 \n", + " 70-74 48.1 \n", + " 75-79 52.0 \n", + " 80-84 57.7 \n", + " 85-89 60.0 \n", + " 90+ 57.1 \n", + "ethnicity_6_groups Black 51.6 \n", + " Mixed 54.5 \n", + " Other 51.4 \n", + " South Asian 53.7 \n", + " Unknown 56.5 \n", + " White 52.9 \n", + "dementia no 53.1 \n", + " yes 50.0 \n", "brand_of_first_dose Oxford-AZ NaN \n", " Pfizer NaN \n", - " Unknown 58.1 \n", + " Unknown 59.0 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.0 \n", - "sex F 1.9 \n", - " M 0.0 \n", - "ageband_5yr 0 0.0 \n", + "overall overall 1.2 \n", + "sex F 0.5 \n", + " M 1.6 \n", + "ageband_5yr 0 25.0 \n", " 0-15 0.0 \n", - " 16-17 0.0 \n", + " 16-17 3.6 \n", " 18-29 0.0 \n", - " 30-34 0.0 \n", + " 30-34 3.7 \n", " 35-39 0.0 \n", - " 40-44 7.1 \n", + " 40-44 0.0 \n", " 45-49 0.0 \n", " 50-54 0.0 \n", " 55-59 0.0 \n", - " 60-64 7.6 \n", - " 65-69 8.3 \n", + " 60-64 0.0 \n", + " 65-69 0.0 \n", " 70-74 0.0 \n", " 75-79 0.0 \n", " 80-84 0.0 \n", " 85-89 0.0 \n", " 90+ 0.0 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 0.0 \n", - " Other 3.4 \n", - " South Asian 2.6 \n", + "ethnicity_6_groups Black 1.5 \n", + " Mixed 1.6 \n", + " Other 1.4 \n", + " South Asian 1.5 \n", " Unknown 0.0 \n", " White 0.0 \n", - "dementia no 1.5 \n", + "dementia no 1.0 \n", " yes 0.0 \n", "brand_of_first_dose Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 1.7 \n", + " Unknown 1.4 \n", "\n", " Date projected to reach 90% \n", "category group \n", "overall overall unknown \n", - "sex F 21-Apr \n", - " M unknown \n", - "ageband_5yr 0 unknown \n", + "sex F unknown \n", + " M 30-Jun \n", + "ageband_5yr 0 06-Feb \n", " 0-15 unknown \n", - " 16-17 unknown \n", + " 16-17 30-Mar \n", " 18-29 unknown \n", - " 30-34 unknown \n", + " 30-34 08-Apr \n", " 35-39 unknown \n", - " 40-44 23-Jan \n", + " 40-44 unknown \n", " 45-49 unknown \n", " 50-54 unknown \n", " 55-59 unknown \n", - " 60-64 17-Jan \n", - " 65-69 10-Jan \n", + " 60-64 unknown \n", + " 65-69 unknown \n", " 70-74 unknown \n", " 75-79 unknown \n", " 80-84 unknown \n", " 85-89 unknown \n", " 90+ unknown \n", - "ethnicity_6_groups Black unknown \n", - " Mixed unknown \n", - " Other 21-Feb \n", - " South Asian 25-Mar \n", + "ethnicity_6_groups Black 24-Jul \n", + " Mixed 30-Jun \n", + " Other unknown \n", + " South Asian 14-Jul \n", " Unknown unknown \n", " White unknown \n", - "dementia no 30-May \n", + "dementia no unknown \n", " yes unknown \n", "brand_of_first_dose Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 18-Apr " + " Unknown 30-Jun " ] }, "metadata": {}, @@ -16090,7 +16138,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **shielding (aged 16-69)** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **shielding (aged 16-69)** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -16156,260 +16204,260 @@ " \n", " overall\n", " overall\n", - " 217\n", - " 51.7\n", - " 420\n", - " 50.0\n", - " 1.7\n", - " 21-May\n", + " 483\n", + " 55.6\n", + " 868\n", + " 55.6\n", + " 0.0\n", + " unknown\n", " \n", " \n", " newly_shielded_since_feb_15\n", " no\n", - " 217\n", - " 52.5\n", - " 413\n", - " 50.8\n", - " 1.7\n", - " 18-May\n", + " 476\n", + " 55.3\n", + " 861\n", + " 55.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 100.0\n", + " 7\n", + " 100.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " sex\n", " F\n", - " 119\n", - " 54.8\n", - " 217\n", - " 51.6\n", - " 3.2\n", - " 02-Mar\n", + " 259\n", + " 57.8\n", + " 448\n", + " 56.2\n", + " 1.6\n", + " 22-Jun\n", " \n", " \n", " M\n", - " 98\n", - " 48.3\n", - " 203\n", - " 48.3\n", + " 231\n", + " 55.0\n", + " 420\n", + " 55.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ageband\n", " 16-29\n", - " 28\n", - " 50.0\n", - " 56\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 63\n", + " 60.0\n", + " 105\n", + " 53.3\n", + " 6.7\n", + " 05-Mar\n", " \n", " \n", " 30-39\n", - " 28\n", - " 50.0\n", " 56\n", - " 50.0\n", + " 53.3\n", + " 105\n", + " 53.3\n", " 0.0\n", " unknown\n", " \n", " \n", " 40-49\n", - " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", + " 63\n", + " 56.2\n", + " 112\n", + " 56.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 50-59\n", - " 35\n", - " 50.0\n", " 70\n", + " 55.6\n", + " 126\n", " 50.0\n", - " 0.0\n", - " unknown\n", + " 5.6\n", + " 17-Mar\n", " \n", " \n", " 60-69\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", + " 63\n", + " 56.2\n", + " 112\n", + " 56.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-79\n", - " 56\n", - " 61.5\n", - " 91\n", - " 61.5\n", + " 105\n", + " 51.7\n", + " 203\n", + " 51.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 80+\n", - " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", + " 70\n", + " 62.5\n", + " 112\n", + " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 42\n", - " 60.0\n", - " 70\n", - " 60.0\n", + " 77\n", + " 55.0\n", + " 140\n", + " 55.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Mixed\n", - " 35\n", - " 50.0\n", - " 70\n", - " 50.0\n", + " 84\n", + " 52.2\n", + " 161\n", + " 52.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 35\n", - " 50.0\n", - " 70\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 91\n", + " 65.0\n", + " 140\n", + " 60.0\n", + " 5.0\n", + " 09-Mar\n", " \n", " \n", " South Asian\n", - " 35\n", - " 55.6\n", - " 63\n", - " 55.6\n", + " 84\n", + " 57.1\n", + " 147\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 28\n", - " 50.0\n", - " 56\n", - " 50.0\n", + " 70\n", + " 58.8\n", + " 119\n", + " 58.8\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", - " 42\n", - " 46.2\n", - " 91\n", - " 38.5\n", - " 7.7\n", - " 23-Jan\n", + " 77\n", + " 47.8\n", + " 161\n", + " 47.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 35\n", - " 41.7\n", - " 84\n", - " 41.7\n", + " 98\n", + " 53.8\n", + " 182\n", + " 53.8\n", " 0.0\n", " unknown\n", " \n", " \n", " 2\n", - " 42\n", - " 60.0\n", - " 70\n", - " 60.0\n", + " 84\n", + " 57.1\n", + " 147\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " 3\n", - " 42\n", - " 50.0\n", - " 84\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 98\n", + " 58.3\n", + " 168\n", + " 54.2\n", + " 4.1\n", + " 28-Mar\n", " \n", " \n", " 4\n", - " 42\n", - " 50.0\n", - " 84\n", - " 50.0\n", + " 91\n", + " 56.5\n", + " 161\n", + " 56.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 42\n", - " 54.5\n", - " 77\n", - " 54.5\n", + " 98\n", + " 58.3\n", + " 168\n", + " 58.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 28\n", + " 66.7\n", + " 42\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " LD\n", " no\n", - " 210\n", - " 50.8\n", - " 413\n", - " 50.8\n", + " 476\n", + " 55.7\n", + " 854\n", + " 55.7\n", " 0.0\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 50.0\n", + " 14\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 168\n", - " 52.2\n", - " 322\n", - " 52.2\n", + " 399\n", + " 55.3\n", + " 721\n", + " 55.3\n", " 0.0\n", " unknown\n", " \n", " \n", " yes\n", - " 42\n", - " 42.9\n", - " 98\n", - " 42.9\n", + " 84\n", + " 57.1\n", + " 147\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", @@ -16425,12 +16473,12 @@ " \n", " \n", " Unknown\n", - " 217\n", - " 59.6\n", - " 364\n", - " 57.7\n", - " 1.9\n", - " 06-Apr\n", + " 483\n", + " 62.2\n", + " 777\n", + " 62.2\n", + " 0.0\n", + " unknown\n", " \n", " \n", "\n", @@ -16439,93 +16487,93 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 217 51.7 420 \n", - "newly_shielded_since_feb_15 no 217 52.5 413 \n", - " yes 0 0.0 0 \n", - "sex F 119 54.8 217 \n", - " M 98 48.3 203 \n", - "ageband 16-29 28 50.0 56 \n", - " 30-39 28 50.0 56 \n", - " 40-49 21 42.9 49 \n", - " 50-59 35 50.0 70 \n", - " 60-69 28 57.1 49 \n", - " 70-79 56 61.5 91 \n", - " 80+ 21 42.9 49 \n", - "ethnicity_6_groups Black 42 60.0 70 \n", - " Mixed 35 50.0 70 \n", - " Other 35 50.0 70 \n", - " South Asian 35 55.6 63 \n", - " Unknown 28 50.0 56 \n", - " White 42 46.2 91 \n", - "imd_categories 1 Most deprived 35 41.7 84 \n", - " 2 42 60.0 70 \n", - " 3 42 50.0 84 \n", - " 4 42 50.0 84 \n", - " 5 Least deprived 42 54.5 77 \n", - " Unknown 7 33.3 21 \n", - "LD no 210 50.8 413 \n", - " yes 0 0.0 0 \n", - "ckd no 168 52.2 322 \n", - " yes 42 42.9 98 \n", + "overall overall 483 55.6 868 \n", + "newly_shielded_since_feb_15 no 476 55.3 861 \n", + " yes 7 100.0 7 \n", + "sex F 259 57.8 448 \n", + " M 231 55.0 420 \n", + "ageband 16-29 63 60.0 105 \n", + " 30-39 56 53.3 105 \n", + " 40-49 63 56.2 112 \n", + " 50-59 70 55.6 126 \n", + " 60-69 63 56.2 112 \n", + " 70-79 105 51.7 203 \n", + " 80+ 70 62.5 112 \n", + "ethnicity_6_groups Black 77 55.0 140 \n", + " Mixed 84 52.2 161 \n", + " Other 91 65.0 140 \n", + " South Asian 84 57.1 147 \n", + " Unknown 70 58.8 119 \n", + " White 77 47.8 161 \n", + "imd_categories 1 Most deprived 98 53.8 182 \n", + " 2 84 57.1 147 \n", + " 3 98 58.3 168 \n", + " 4 91 56.5 161 \n", + " 5 Least deprived 98 58.3 168 \n", + " Unknown 28 66.7 42 \n", + "LD no 476 55.7 854 \n", + " yes 7 50.0 14 \n", + "ckd no 399 55.3 721 \n", + " yes 84 57.1 147 \n", "brand_of_first_dose Pfizer 0 0.0 0 \n", - " Unknown 217 59.6 364 \n", + " Unknown 483 62.2 777 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 50.0 \n", - "newly_shielded_since_feb_15 no 50.8 \n", - " yes NaN \n", - "sex F 51.6 \n", - " M 48.3 \n", - "ageband 16-29 50.0 \n", - " 30-39 50.0 \n", - " 40-49 42.9 \n", + "overall overall 55.6 \n", + "newly_shielded_since_feb_15 no 55.3 \n", + " yes 100.0 \n", + "sex F 56.2 \n", + " M 55.0 \n", + "ageband 16-29 53.3 \n", + " 30-39 53.3 \n", + " 40-49 56.2 \n", " 50-59 50.0 \n", - " 60-69 57.1 \n", - " 70-79 61.5 \n", - " 80+ 42.9 \n", - "ethnicity_6_groups Black 60.0 \n", - " Mixed 50.0 \n", - " Other 50.0 \n", - " South Asian 55.6 \n", - " Unknown 50.0 \n", - " White 38.5 \n", - "imd_categories 1 Most deprived 41.7 \n", - " 2 60.0 \n", - " 3 50.0 \n", - " 4 50.0 \n", - " 5 Least deprived 54.5 \n", - " Unknown 33.3 \n", - "LD no 50.8 \n", - " yes NaN \n", - "ckd no 52.2 \n", - " yes 42.9 \n", + " 60-69 56.2 \n", + " 70-79 51.7 \n", + " 80+ 62.5 \n", + "ethnicity_6_groups Black 55.0 \n", + " Mixed 52.2 \n", + " Other 60.0 \n", + " South Asian 57.1 \n", + " Unknown 58.8 \n", + " White 47.8 \n", + "imd_categories 1 Most deprived 53.8 \n", + " 2 57.1 \n", + " 3 54.2 \n", + " 4 56.5 \n", + " 5 Least deprived 58.3 \n", + " Unknown 66.7 \n", + "LD no 55.7 \n", + " yes 50.0 \n", + "ckd no 55.3 \n", + " yes 57.1 \n", "brand_of_first_dose Pfizer NaN \n", - " Unknown 57.7 \n", + " Unknown 62.2 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.7 \n", - "newly_shielded_since_feb_15 no 1.7 \n", + "overall overall 0.0 \n", + "newly_shielded_since_feb_15 no 0.0 \n", " yes 0.0 \n", - "sex F 3.2 \n", + "sex F 1.6 \n", " M 0.0 \n", - "ageband 16-29 0.0 \n", + "ageband 16-29 6.7 \n", " 30-39 0.0 \n", " 40-49 0.0 \n", - " 50-59 0.0 \n", + " 50-59 5.6 \n", " 60-69 0.0 \n", " 70-79 0.0 \n", " 80+ 0.0 \n", "ethnicity_6_groups Black 0.0 \n", " Mixed 0.0 \n", - " Other 0.0 \n", + " Other 5.0 \n", " South Asian 0.0 \n", " Unknown 0.0 \n", - " White 7.7 \n", + " White 0.0 \n", "imd_categories 1 Most deprived 0.0 \n", " 2 0.0 \n", - " 3 0.0 \n", + " 3 4.1 \n", " 4 0.0 \n", " 5 Least deprived 0.0 \n", " Unknown 0.0 \n", @@ -16534,31 +16582,31 @@ "ckd no 0.0 \n", " yes 0.0 \n", "brand_of_first_dose Pfizer 0.0 \n", - " Unknown 1.9 \n", + " Unknown 0.0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 21-May \n", - "newly_shielded_since_feb_15 no 18-May \n", - " yes unknown \n", - "sex F 02-Mar \n", + "overall overall unknown \n", + "newly_shielded_since_feb_15 no unknown \n", + " yes reached \n", + "sex F 22-Jun \n", " M unknown \n", - "ageband 16-29 unknown \n", + "ageband 16-29 05-Mar \n", " 30-39 unknown \n", " 40-49 unknown \n", - " 50-59 unknown \n", + " 50-59 17-Mar \n", " 60-69 unknown \n", " 70-79 unknown \n", " 80+ unknown \n", "ethnicity_6_groups Black unknown \n", " Mixed unknown \n", - " Other unknown \n", + " Other 09-Mar \n", " South Asian unknown \n", " Unknown unknown \n", - " White 23-Jan \n", + " White unknown \n", "imd_categories 1 Most deprived unknown \n", " 2 unknown \n", - " 3 unknown \n", + " 3 28-Mar \n", " 4 unknown \n", " 5 Least deprived unknown \n", " Unknown unknown \n", @@ -16567,7 +16615,7 @@ "ckd no unknown \n", " yes unknown \n", "brand_of_first_dose Pfizer unknown \n", - " Unknown 06-Apr " + " Unknown unknown " ] }, "metadata": {}, @@ -16596,7 +16644,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **65-69** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **65-69** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -16662,368 +16710,368 @@ " \n", " overall\n", " overall\n", - " 1141\n", - " 52.6\n", - " 2170\n", - " 51.6\n", - " 1.0\n", + " 2415\n", + " 54.7\n", + " 4417\n", + " 53.9\n", + " 0.8\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 560\n", - " 52.3\n", - " 1071\n", - " 51.6\n", + " 1197\n", + " 53.8\n", + " 2226\n", + " 53.1\n", " 0.7\n", " unknown\n", " \n", " \n", " M\n", - " 581\n", - " 52.9\n", - " 1099\n", - " 51.6\n", - " 1.3\n", + " 1218\n", + " 55.6\n", + " 2191\n", + " 54.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 210\n", - " 56.6\n", - " 371\n", - " 54.7\n", - " 1.9\n", - " 17-Apr\n", + " 434\n", + " 57.4\n", + " 756\n", + " 56.5\n", + " 0.9\n", + " unknown\n", " \n", " \n", " Mixed\n", - " 182\n", - " 52.0\n", - " 350\n", - " 50.0\n", - " 2.0\n", - " 27-Apr\n", + " 420\n", + " 54.5\n", + " 770\n", + " 53.6\n", + " 0.9\n", + " unknown\n", " \n", " \n", " Other\n", - " 189\n", - " 54.0\n", - " 350\n", - " 52.0\n", - " 2.0\n", - " 20-Apr\n", + " 399\n", + " 53.3\n", + " 749\n", + " 53.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " South Asian\n", - " 203\n", - " 50.9\n", - " 399\n", - " 50.9\n", - " 0.0\n", + " 371\n", + " 52.5\n", + " 707\n", + " 51.5\n", + " 1.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 168\n", - " 50.0\n", - " 336\n", - " 47.9\n", - " 2.1\n", - " 27-Apr\n", + " 392\n", + " 56.0\n", + " 700\n", + " 55.0\n", + " 1.0\n", + " unknown\n", " \n", " \n", " White\n", - " 189\n", - " 51.9\n", - " 364\n", - " 51.9\n", - " 0.0\n", + " 406\n", + " 55.2\n", + " 735\n", + " 54.3\n", + " 0.9\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 70\n", - " 62.5\n", - " 112\n", - " 56.2\n", - " 6.3\n", - " 14-Jan\n", + " 133\n", + " 59.4\n", + " 224\n", + " 59.4\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 63\n", - " 50.0\n", - " 126\n", - " 50.0\n", + " 119\n", + " 51.5\n", + " 231\n", + " 51.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 49\n", - " 46.7\n", - " 105\n", - " 40.0\n", - " 6.7\n", - " 29-Jan\n", + " 133\n", + " 55.9\n", + " 238\n", + " 55.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Chinese\n", - " 56\n", - " 50.0\n", - " 112\n", - " 50.0\n", + " 140\n", + " 57.1\n", + " 245\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 70\n", - " 52.6\n", - " 133\n", - " 52.6\n", + " 161\n", + " 60.5\n", + " 266\n", + " 60.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 63\n", - " 50.0\n", - " 126\n", - " 50.0\n", + " 112\n", + " 51.6\n", + " 217\n", + " 51.6\n", " 0.0\n", " unknown\n", " \n", " \n", " British or Mixed British\n", - " 56\n", - " 50.0\n", - " 112\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 140\n", + " 58.8\n", + " 238\n", + " 55.9\n", + " 2.9\n", + " 18-Apr\n", " \n", " \n", " Indian or British Indian\n", - " 56\n", - " 53.3\n", - " 105\n", - " 53.3\n", - " 0.0\n", - " unknown\n", + " 126\n", + " 51.4\n", + " 245\n", + " 48.6\n", + " 2.8\n", + " 09-May\n", " \n", " \n", " Irish\n", - " 63\n", - " 56.2\n", - " 112\n", - " 56.2\n", - " 0.0\n", - " unknown\n", + " 133\n", + " 57.6\n", + " 231\n", + " 54.5\n", + " 3.1\n", + " 16-Apr\n", " \n", " \n", " Other Black\n", - " 56\n", - " 50.0\n", - " 112\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 140\n", + " 58.8\n", + " 238\n", + " 55.9\n", + " 2.9\n", + " 18-Apr\n", " \n", " \n", " Other White\n", - " 63\n", - " 56.2\n", - " 112\n", - " 50.0\n", - " 6.2\n", - " 22-Jan\n", + " 126\n", + " 52.9\n", + " 238\n", + " 52.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other mixed\n", - " 42\n", - " 46.2\n", - " 91\n", - " 46.2\n", + " 126\n", + " 50.0\n", + " 252\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 77\n", - " 57.9\n", " 133\n", - " 52.6\n", - " 5.3\n", - " 26-Jan\n", + " 55.9\n", + " 238\n", + " 55.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 161\n", - " 48.9\n", " 329\n", - " 46.8\n", - " 2.1\n", - " 01-May\n", + " 52.8\n", + " 623\n", + " 52.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Asian\n", - " 63\n", - " 56.2\n", " 112\n", " 50.0\n", - " 6.2\n", - " 22-Jan\n", + " 224\n", + " 50.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black African\n", - " 63\n", - " 52.9\n", " 119\n", - " 47.1\n", - " 5.8\n", - " 28-Jan\n", + " 60.7\n", + " 196\n", + " 60.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 77\n", - " 61.1\n", - " 126\n", - " 61.1\n", - " 0.0\n", - " unknown\n", + " 133\n", + " 51.4\n", + " 259\n", + " 48.6\n", + " 2.8\n", + " 09-May\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 203\n", - " 51.8\n", - " 392\n", - " 50.0\n", - " 1.8\n", - " 12-May\n", + " 448\n", + " 54.7\n", + " 819\n", + " 54.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 2\n", - " 238\n", - " 53.1\n", - " 448\n", - " 51.6\n", - " 1.5\n", - " 05-Jun\n", + " 441\n", + " 52.5\n", + " 840\n", + " 51.7\n", + " 0.8\n", + " unknown\n", " \n", " \n", " 3\n", - " 217\n", - " 52.5\n", - " 413\n", - " 52.5\n", - " 0.0\n", + " 476\n", + " 55.7\n", + " 854\n", + " 54.9\n", + " 0.8\n", " unknown\n", " \n", " \n", " 4\n", - " 224\n", - " 55.2\n", - " 406\n", - " 55.2\n", - " 0.0\n", + " 469\n", + " 55.8\n", + " 840\n", + " 55.0\n", + " 0.8\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 203\n", - " 50.0\n", - " 406\n", - " 48.3\n", - " 1.7\n", - " 28-May\n", + " 462\n", + " 55.0\n", + " 840\n", + " 54.2\n", + " 0.8\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 56\n", - " 53.3\n", - " 105\n", - " 53.3\n", - " 0.0\n", - " unknown\n", + " 126\n", + " 58.1\n", + " 217\n", + " 54.8\n", + " 3.3\n", + " 10-Apr\n", " \n", " \n", " bmi\n", " 30+\n", - " 308\n", - " 50.0\n", - " 616\n", - " 50.0\n", - " 0.0\n", + " 770\n", + " 56.4\n", + " 1365\n", + " 55.9\n", + " 0.5\n", " unknown\n", " \n", " \n", " under 30\n", - " 833\n", - " 53.6\n", - " 1554\n", - " 52.3\n", - " 1.3\n", + " 1645\n", + " 53.9\n", + " 3052\n", + " 53.2\n", + " 0.7\n", " unknown\n", " \n", " \n", " housebound\n", " no\n", - " 1134\n", - " 52.6\n", - " 2156\n", - " 51.6\n", - " 1.0\n", + " 2394\n", + " 54.9\n", + " 4361\n", + " 54.1\n", + " 0.8\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 50.0\n", - " 14\n", - " 50.0\n", - " 0.0\n", - " unknown\n", - " \n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", + " 0.0\n", + " unknown\n", + " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1120\n", - " 52.5\n", - " 2135\n", - " 51.5\n", - " 1.0\n", + " 2394\n", + " 54.8\n", + " 4368\n", + " 54.0\n", + " 0.8\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1127\n", - " 52.4\n", - " 2149\n", - " 51.5\n", - " 0.9\n", + " 2387\n", + " 54.6\n", + " 4375\n", + " 53.9\n", + " 0.7\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", + " 28\n", " 66.7\n", - " 21\n", + " 42\n", " 66.7\n", " 0.0\n", " unknown\n", @@ -17031,192 +17079,192 @@ " \n", " dmards\n", " no\n", - " 1134\n", - " 52.8\n", - " 2149\n", - " 51.8\n", - " 1.0\n", + " 2387\n", + " 54.6\n", + " 4368\n", + " 53.8\n", + " 0.8\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 1134\n", - " 52.8\n", - " 2149\n", - " 51.8\n", - " 1.0\n", + " 2394\n", + " 54.8\n", + " 4368\n", + " 54.0\n", + " 0.8\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", " 21\n", - " 33.3\n", - " 33.4\n", - " 19-Dec\n", + " 50.0\n", + " 42\n", + " 50.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1134\n", - " 52.8\n", - " 2149\n", - " 51.5\n", - " 1.3\n", + " 2394\n", + " 54.8\n", + " 4368\n", + " 54.0\n", + " 0.8\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", " 21\n", - " 66.7\n", + " 42.9\n", + " 49\n", + " 42.9\n", " 0.0\n", " unknown\n", " \n", " \n", " LD\n", " no\n", - " 1120\n", - " 52.6\n", - " 2128\n", - " 51.6\n", - " 1.0\n", + " 2359\n", + " 54.7\n", + " 4312\n", + " 54.1\n", + " 0.6\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", - " 50.0\n", - " 42\n", - " 50.0\n", + " 56\n", + " 53.3\n", + " 105\n", + " 53.3\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1127\n", - " 52.4\n", - " 2149\n", - " 51.5\n", - " 0.9\n", + " 2401\n", + " 54.9\n", + " 4375\n", + " 54.1\n", + " 0.8\n", " unknown\n", " \n", " \n", " yes\n", " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 40.0\n", + " 35\n", + " 40.0\n", " 0.0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 1134\n", - " 52.8\n", - " 2149\n", - " 51.8\n", - " 1.0\n", + " 2394\n", + " 54.7\n", + " 4375\n", + " 53.9\n", + " 0.8\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", " 21\n", - " 33.3\n", + " 50.0\n", + " 42\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1127\n", - " 52.4\n", - " 2149\n", - " 51.5\n", - " 0.9\n", + " 2394\n", + " 54.6\n", + " 4382\n", + " 54.0\n", + " 0.6\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", " 21\n", - " 66.7\n", + " 60.0\n", + " 35\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1134\n", - " 52.8\n", - " 2149\n", - " 51.8\n", - " 1.0\n", + " 2394\n", + " 54.7\n", + " 4375\n", + " 53.9\n", + " 0.8\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", " 21\n", - " 0.0\n", + " 60.0\n", + " 35\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1134\n", - " 52.8\n", - " 2149\n", - " 51.8\n", - " 1.0\n", + " 2394\n", + " 54.8\n", + " 4368\n", + " 54.0\n", + " 0.8\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 28\n", + " 66.7\n", + " 42\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 896\n", - " 51.6\n", - " 1736\n", - " 50.8\n", + " 1897\n", + " 54.6\n", + " 3472\n", + " 53.8\n", " 0.8\n", " unknown\n", " \n", " \n", " yes\n", - " 245\n", - " 56.5\n", - " 434\n", - " 54.8\n", - " 1.7\n", - " 01-May\n", + " 525\n", + " 56.0\n", + " 938\n", + " 54.5\n", + " 1.5\n", + " 10-Jul\n", " \n", " \n", " brand_of_first_dose\n", @@ -17248,11 +17296,11 @@ " \n", " \n", " Unknown\n", - " 1141\n", - " 58.6\n", - " 1946\n", - " 57.6\n", - " 1.0\n", + " 2408\n", + " 60.7\n", + " 3969\n", + " 60.0\n", + " 0.7\n", " unknown\n", " \n", " \n", @@ -17262,306 +17310,306 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1141 \n", - "sex F 560 \n", - " M 581 \n", - "ethnicity_6_groups Black 210 \n", - " Mixed 182 \n", - " Other 189 \n", - " South Asian 203 \n", - " Unknown 168 \n", - " White 189 \n", - "ethnicity_16_groups African 70 \n", - " Bangladeshi or British Bangladeshi 63 \n", - " Caribbean 49 \n", - " Chinese 56 \n", - " Other 70 \n", - " Other Asian 63 \n", - " British or Mixed British 56 \n", - " Indian or British Indian 56 \n", - " Irish 63 \n", - " Other Black 56 \n", - " Other White 63 \n", - " Other mixed 42 \n", - " Pakistani or British Pakistani 77 \n", - " Unknown 161 \n", - " White + Asian 63 \n", - " White + Black African 63 \n", - " White + Black Caribbean 77 \n", - "imd_categories 1 Most deprived 203 \n", - " 2 238 \n", - " 3 217 \n", - " 4 224 \n", - " 5 Least deprived 203 \n", - " Unknown 56 \n", - "bmi 30+ 308 \n", - " under 30 833 \n", - "housebound no 1134 \n", - " yes 7 \n", - "chronic_cardiac_disease no 1120 \n", + "overall overall 2415 \n", + "sex F 1197 \n", + " M 1218 \n", + "ethnicity_6_groups Black 434 \n", + " Mixed 420 \n", + " Other 399 \n", + " South Asian 371 \n", + " Unknown 392 \n", + " White 406 \n", + "ethnicity_16_groups African 133 \n", + " Bangladeshi or British Bangladeshi 119 \n", + " Caribbean 133 \n", + " Chinese 140 \n", + " Other 161 \n", + " Other Asian 112 \n", + " British or Mixed British 140 \n", + " Indian or British Indian 126 \n", + " Irish 133 \n", + " Other Black 140 \n", + " Other White 126 \n", + " Other mixed 126 \n", + " Pakistani or British Pakistani 133 \n", + " Unknown 329 \n", + " White + Asian 112 \n", + " White + Black African 119 \n", + " White + Black Caribbean 133 \n", + "imd_categories 1 Most deprived 448 \n", + " 2 441 \n", + " 3 476 \n", + " 4 469 \n", + " 5 Least deprived 462 \n", + " Unknown 126 \n", + "bmi 30+ 770 \n", + " under 30 1645 \n", + "housebound no 2394 \n", + " yes 28 \n", + "chronic_cardiac_disease no 2394 \n", + " yes 28 \n", + "current_copd no 2387 \n", + " yes 28 \n", + "dmards no 2387 \n", + " yes 28 \n", + "dementia no 2394 \n", " yes 21 \n", - "current_copd no 1127 \n", - " yes 14 \n", - "dmards no 1134 \n", - " yes 7 \n", - "dementia no 1134 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1134 \n", - " yes 14 \n", - "LD no 1120 \n", + "psychosis_schiz_bipolar no 2394 \n", " yes 21 \n", - "ssri no 1127 \n", + "LD no 2359 \n", + " yes 56 \n", + "ssri no 2401 \n", " yes 14 \n", - "chemo_or_radio no 1134 \n", - " yes 7 \n", - "lung_cancer no 1127 \n", - " yes 14 \n", - "cancer_excl_lung_and_haem no 1134 \n", - " yes 0 \n", - "haematological_cancer no 1134 \n", - " yes 7 \n", - "ckd no 896 \n", - " yes 245 \n", + "chemo_or_radio no 2394 \n", + " yes 21 \n", + "lung_cancer no 2394 \n", + " yes 21 \n", + "cancer_excl_lung_and_haem no 2394 \n", + " yes 21 \n", + "haematological_cancer no 2394 \n", + " yes 28 \n", + "ckd no 1897 \n", + " yes 525 \n", "brand_of_first_dose Moderna 0 \n", " Oxford-AZ 0 \n", " Pfizer 0 \n", - " Unknown 1141 \n", + " Unknown 2408 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 52.6 2170 \n", - "sex F 52.3 1071 \n", - " M 52.9 1099 \n", - "ethnicity_6_groups Black 56.6 371 \n", - " Mixed 52.0 350 \n", - " Other 54.0 350 \n", - " South Asian 50.9 399 \n", - " Unknown 50.0 336 \n", - " White 51.9 364 \n", - "ethnicity_16_groups African 62.5 112 \n", - " Bangladeshi or British Bangladeshi 50.0 126 \n", - " Caribbean 46.7 105 \n", - " Chinese 50.0 112 \n", - " Other 52.6 133 \n", - " Other Asian 50.0 126 \n", - " British or Mixed British 50.0 112 \n", - " Indian or British Indian 53.3 105 \n", - " Irish 56.2 112 \n", - " Other Black 50.0 112 \n", - " Other White 56.2 112 \n", - " Other mixed 46.2 91 \n", - " Pakistani or British Pakistani 57.9 133 \n", - " Unknown 48.9 329 \n", - " White + Asian 56.2 112 \n", - " White + Black African 52.9 119 \n", - " White + Black Caribbean 61.1 126 \n", - "imd_categories 1 Most deprived 51.8 392 \n", - " 2 53.1 448 \n", - " 3 52.5 413 \n", - " 4 55.2 406 \n", - " 5 Least deprived 50.0 406 \n", - " Unknown 53.3 105 \n", - "bmi 30+ 50.0 616 \n", - " under 30 53.6 1554 \n", - "housebound no 52.6 2156 \n", - " yes 50.0 14 \n", - "chronic_cardiac_disease no 52.5 2135 \n", - " yes 60.0 35 \n", - "current_copd no 52.4 2149 \n", - " yes 66.7 21 \n", - "dmards no 52.8 2149 \n", - " yes 33.3 21 \n", - "dementia no 52.8 2149 \n", - " yes 66.7 21 \n", - "psychosis_schiz_bipolar no 52.8 2149 \n", - " yes 66.7 21 \n", - "LD no 52.6 2128 \n", + "overall overall 54.7 4417 \n", + "sex F 53.8 2226 \n", + " M 55.6 2191 \n", + "ethnicity_6_groups Black 57.4 756 \n", + " Mixed 54.5 770 \n", + " Other 53.3 749 \n", + " South Asian 52.5 707 \n", + " Unknown 56.0 700 \n", + " White 55.2 735 \n", + "ethnicity_16_groups African 59.4 224 \n", + " Bangladeshi or British Bangladeshi 51.5 231 \n", + " Caribbean 55.9 238 \n", + " Chinese 57.1 245 \n", + " Other 60.5 266 \n", + " Other Asian 51.6 217 \n", + " British or Mixed British 58.8 238 \n", + " Indian or British Indian 51.4 245 \n", + " Irish 57.6 231 \n", + " Other Black 58.8 238 \n", + " Other White 52.9 238 \n", + " Other mixed 50.0 252 \n", + " Pakistani or British Pakistani 55.9 238 \n", + " Unknown 52.8 623 \n", + " White + Asian 50.0 224 \n", + " White + Black African 60.7 196 \n", + " White + Black Caribbean 51.4 259 \n", + "imd_categories 1 Most deprived 54.7 819 \n", + " 2 52.5 840 \n", + " 3 55.7 854 \n", + " 4 55.8 840 \n", + " 5 Least deprived 55.0 840 \n", + " Unknown 58.1 217 \n", + "bmi 30+ 56.4 1365 \n", + " under 30 53.9 3052 \n", + "housebound no 54.9 4361 \n", + " yes 57.1 49 \n", + "chronic_cardiac_disease no 54.8 4368 \n", + " yes 57.1 49 \n", + "current_copd no 54.6 4375 \n", + " yes 66.7 42 \n", + "dmards no 54.6 4368 \n", + " yes 57.1 49 \n", + "dementia no 54.8 4368 \n", + " yes 50.0 42 \n", + "psychosis_schiz_bipolar no 54.8 4368 \n", + " yes 42.9 49 \n", + "LD no 54.7 4312 \n", + " yes 53.3 105 \n", + "ssri no 54.9 4375 \n", + " yes 40.0 35 \n", + "chemo_or_radio no 54.7 4375 \n", " yes 50.0 42 \n", - "ssri no 52.4 2149 \n", - " yes 66.7 21 \n", - "chemo_or_radio no 52.8 2149 \n", - " yes 33.3 21 \n", - "lung_cancer no 52.4 2149 \n", - " yes 66.7 21 \n", - "cancer_excl_lung_and_haem no 52.8 2149 \n", - " yes 0.0 21 \n", - "haematological_cancer no 52.8 2149 \n", - " yes 33.3 21 \n", - "ckd no 51.6 1736 \n", - " yes 56.5 434 \n", + "lung_cancer no 54.6 4382 \n", + " yes 60.0 35 \n", + "cancer_excl_lung_and_haem no 54.7 4375 \n", + " yes 60.0 35 \n", + "haematological_cancer no 54.8 4368 \n", + " yes 66.7 42 \n", + "ckd no 54.6 3472 \n", + " yes 56.0 938 \n", "brand_of_first_dose Moderna 0.0 0 \n", " Oxford-AZ 0.0 0 \n", " Pfizer 0.0 0 \n", - " Unknown 58.6 1946 \n", + " Unknown 60.7 3969 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 51.6 \n", - "sex F 51.6 \n", - " M 51.6 \n", - "ethnicity_6_groups Black 54.7 \n", - " Mixed 50.0 \n", - " Other 52.0 \n", - " South Asian 50.9 \n", - " Unknown 47.9 \n", - " White 51.9 \n", - "ethnicity_16_groups African 56.2 \n", - " Bangladeshi or British Bangladeshi 50.0 \n", - " Caribbean 40.0 \n", - " Chinese 50.0 \n", - " Other 52.6 \n", - " Other Asian 50.0 \n", - " British or Mixed British 50.0 \n", - " Indian or British Indian 53.3 \n", - " Irish 56.2 \n", - " Other Black 50.0 \n", - " Other White 50.0 \n", - " Other mixed 46.2 \n", - " Pakistani or British Pakistani 52.6 \n", - " Unknown 46.8 \n", + "overall overall 53.9 \n", + "sex F 53.1 \n", + " M 54.6 \n", + "ethnicity_6_groups Black 56.5 \n", + " Mixed 53.6 \n", + " Other 53.3 \n", + " South Asian 51.5 \n", + " Unknown 55.0 \n", + " White 54.3 \n", + "ethnicity_16_groups African 59.4 \n", + " Bangladeshi or British Bangladeshi 51.5 \n", + " Caribbean 55.9 \n", + " Chinese 57.1 \n", + " Other 60.5 \n", + " Other Asian 51.6 \n", + " British or Mixed British 55.9 \n", + " Indian or British Indian 48.6 \n", + " Irish 54.5 \n", + " Other Black 55.9 \n", + " Other White 52.9 \n", + " Other mixed 50.0 \n", + " Pakistani or British Pakistani 55.9 \n", + " Unknown 52.8 \n", " White + Asian 50.0 \n", - " White + Black African 47.1 \n", - " White + Black Caribbean 61.1 \n", - "imd_categories 1 Most deprived 50.0 \n", - " 2 51.6 \n", - " 3 52.5 \n", - " 4 55.2 \n", - " 5 Least deprived 48.3 \n", - " Unknown 53.3 \n", - "bmi 30+ 50.0 \n", - " under 30 52.3 \n", - "housebound no 51.6 \n", - " yes 50.0 \n", - "chronic_cardiac_disease no 51.5 \n", - " yes 60.0 \n", - "current_copd no 51.5 \n", - " yes 66.7 \n", - "dmards no 51.8 \n", - " yes 33.3 \n", - "dementia no 51.8 \n", - " yes 33.3 \n", - "psychosis_schiz_bipolar no 51.5 \n", + " White + Black African 60.7 \n", + " White + Black Caribbean 48.6 \n", + "imd_categories 1 Most deprived 54.7 \n", + " 2 51.7 \n", + " 3 54.9 \n", + " 4 55.0 \n", + " 5 Least deprived 54.2 \n", + " Unknown 54.8 \n", + "bmi 30+ 55.9 \n", + " under 30 53.2 \n", + "housebound no 54.1 \n", + " yes 57.1 \n", + "chronic_cardiac_disease no 54.0 \n", + " yes 57.1 \n", + "current_copd no 53.9 \n", " yes 66.7 \n", - "LD no 51.6 \n", + "dmards no 53.8 \n", + " yes 57.1 \n", + "dementia no 54.0 \n", " yes 50.0 \n", - "ssri no 51.5 \n", - " yes 66.7 \n", - "chemo_or_radio no 51.8 \n", - " yes 33.3 \n", - "lung_cancer no 51.5 \n", + "psychosis_schiz_bipolar no 54.0 \n", + " yes 42.9 \n", + "LD no 54.1 \n", + " yes 53.3 \n", + "ssri no 54.1 \n", + " yes 40.0 \n", + "chemo_or_radio no 53.9 \n", + " yes 50.0 \n", + "lung_cancer no 54.0 \n", + " yes 60.0 \n", + "cancer_excl_lung_and_haem no 53.9 \n", + " yes 60.0 \n", + "haematological_cancer no 54.0 \n", " yes 66.7 \n", - "cancer_excl_lung_and_haem no 51.8 \n", - " yes 0.0 \n", - "haematological_cancer no 51.8 \n", - " yes 33.3 \n", - "ckd no 50.8 \n", - " yes 54.8 \n", + "ckd no 53.8 \n", + " yes 54.5 \n", "brand_of_first_dose Moderna NaN \n", " Oxford-AZ NaN \n", " Pfizer NaN \n", - " Unknown 57.6 \n", + " Unknown 60.0 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.0 \n", + "overall overall 0.8 \n", "sex F 0.7 \n", - " M 1.3 \n", - "ethnicity_6_groups Black 1.9 \n", - " Mixed 2.0 \n", - " Other 2.0 \n", - " South Asian 0.0 \n", - " Unknown 2.1 \n", - " White 0.0 \n", - "ethnicity_16_groups African 6.3 \n", + " M 1.0 \n", + "ethnicity_6_groups Black 0.9 \n", + " Mixed 0.9 \n", + " Other 0.0 \n", + " South Asian 1.0 \n", + " Unknown 1.0 \n", + " White 0.9 \n", + "ethnicity_16_groups African 0.0 \n", " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 6.7 \n", + " Caribbean 0.0 \n", " Chinese 0.0 \n", " Other 0.0 \n", " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 0.0 \n", - " Irish 0.0 \n", - " Other Black 0.0 \n", - " Other White 6.2 \n", + " British or Mixed British 2.9 \n", + " Indian or British Indian 2.8 \n", + " Irish 3.1 \n", + " Other Black 2.9 \n", + " Other White 0.0 \n", " Other mixed 0.0 \n", - " Pakistani or British Pakistani 5.3 \n", - " Unknown 2.1 \n", - " White + Asian 6.2 \n", - " White + Black African 5.8 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 1.8 \n", - " 2 1.5 \n", - " 3 0.0 \n", - " 4 0.0 \n", - " 5 Least deprived 1.7 \n", + " Pakistani or British Pakistani 0.0 \n", " Unknown 0.0 \n", - "bmi 30+ 0.0 \n", - " under 30 1.3 \n", - "housebound no 1.0 \n", + " White + Asian 0.0 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 2.8 \n", + "imd_categories 1 Most deprived 0.0 \n", + " 2 0.8 \n", + " 3 0.8 \n", + " 4 0.8 \n", + " 5 Least deprived 0.8 \n", + " Unknown 3.3 \n", + "bmi 30+ 0.5 \n", + " under 30 0.7 \n", + "housebound no 0.8 \n", " yes 0.0 \n", - "chronic_cardiac_disease no 1.0 \n", + "chronic_cardiac_disease no 0.8 \n", " yes 0.0 \n", - "current_copd no 0.9 \n", + "current_copd no 0.7 \n", " yes 0.0 \n", - "dmards no 1.0 \n", + "dmards no 0.8 \n", " yes 0.0 \n", - "dementia no 1.0 \n", - " yes 33.4 \n", - "psychosis_schiz_bipolar no 1.3 \n", + "dementia no 0.8 \n", " yes 0.0 \n", - "LD no 1.0 \n", + "psychosis_schiz_bipolar no 0.8 \n", " yes 0.0 \n", - "ssri no 0.9 \n", + "LD no 0.6 \n", " yes 0.0 \n", - "chemo_or_radio no 1.0 \n", + "ssri no 0.8 \n", " yes 0.0 \n", - "lung_cancer no 0.9 \n", + "chemo_or_radio no 0.8 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.0 \n", + "lung_cancer no 0.6 \n", " yes 0.0 \n", - "haematological_cancer no 1.0 \n", + "cancer_excl_lung_and_haem no 0.8 \n", + " yes 0.0 \n", + "haematological_cancer no 0.8 \n", " yes 0.0 \n", "ckd no 0.8 \n", - " yes 1.7 \n", + " yes 1.5 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 1.0 \n", + " Unknown 0.7 \n", "\n", " Date projected to reach 90% \n", "category group \n", "overall overall unknown \n", "sex F unknown \n", " M unknown \n", - "ethnicity_6_groups Black 17-Apr \n", - " Mixed 27-Apr \n", - " Other 20-Apr \n", + "ethnicity_6_groups Black unknown \n", + " Mixed unknown \n", + " Other unknown \n", " South Asian unknown \n", - " Unknown 27-Apr \n", + " Unknown unknown \n", " White unknown \n", - "ethnicity_16_groups African 14-Jan \n", + "ethnicity_16_groups African unknown \n", " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean 29-Jan \n", + " Caribbean unknown \n", " Chinese unknown \n", " Other unknown \n", " Other Asian unknown \n", - " British or Mixed British unknown \n", - " Indian or British Indian unknown \n", - " Irish unknown \n", - " Other Black unknown \n", - " Other White 22-Jan \n", + " British or Mixed British 18-Apr \n", + " Indian or British Indian 09-May \n", + " Irish 16-Apr \n", + " Other Black 18-Apr \n", + " Other White unknown \n", " Other mixed unknown \n", - " Pakistani or British Pakistani 26-Jan \n", - " Unknown 01-May \n", - " White + Asian 22-Jan \n", - " White + Black African 28-Jan \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived 12-May \n", - " 2 05-Jun \n", + " Pakistani or British Pakistani unknown \n", + " Unknown unknown \n", + " White + Asian unknown \n", + " White + Black African unknown \n", + " White + Black Caribbean 09-May \n", + "imd_categories 1 Most deprived unknown \n", + " 2 unknown \n", " 3 unknown \n", " 4 unknown \n", - " 5 Least deprived 28-May \n", - " Unknown unknown \n", + " 5 Least deprived unknown \n", + " Unknown 10-Apr \n", "bmi 30+ unknown \n", " under 30 unknown \n", "housebound no unknown \n", @@ -17573,7 +17621,7 @@ "dmards no unknown \n", " yes unknown \n", "dementia no unknown \n", - " yes 19-Dec \n", + " yes unknown \n", "psychosis_schiz_bipolar no unknown \n", " yes unknown \n", "LD no unknown \n", @@ -17589,7 +17637,7 @@ "haematological_cancer no unknown \n", " yes unknown \n", "ckd no unknown \n", - " yes 01-May \n", + " yes 10-Jul \n", "brand_of_first_dose Moderna unknown \n", " Oxford-AZ unknown \n", " Pfizer unknown \n", @@ -17622,7 +17670,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **LD (aged 16-64)** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **LD (aged 16-64)** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -17688,243 +17736,243 @@ " \n", " overall\n", " overall\n", - " 413\n", - " 51.3\n", - " 805\n", - " 50.4\n", + " 931\n", + " 58.1\n", + " 1603\n", + " 57.2\n", " 0.9\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 210\n", - " 50.8\n", - " 413\n", - " 50.8\n", - " 0.0\n", + " 448\n", + " 56.6\n", + " 791\n", + " 55.8\n", + " 0.8\n", " unknown\n", " \n", " \n", " M\n", - " 203\n", - " 51.8\n", - " 392\n", - " 50.0\n", - " 1.8\n", - " 12-May\n", + " 483\n", + " 59.5\n", + " 812\n", + " 58.6\n", + " 0.9\n", + " unknown\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 0\n", - " 0.0\n", - " 7\n", - " 0.0\n", + " 14\n", + " 66.7\n", + " 21\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 0-15\n", - " 21\n", - " 42.9\n", " 49\n", - " 28.6\n", - " 14.3\n", - " 07-Jan\n", + " 46.7\n", + " 105\n", + " 46.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 16-17\n", - " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", + " 70\n", + " 62.5\n", + " 112\n", + " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 18-29\n", - " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", + " 63\n", + " 60.0\n", + " 105\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 30-34\n", - " 21\n", - " 50.0\n", - " 42\n", - " 50.0\n", + " 63\n", + " 64.3\n", + " 98\n", + " 64.3\n", " 0.0\n", " unknown\n", " \n", " \n", " 35-39\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", + " 63\n", + " 60.0\n", + " 105\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 40-44\n", - " 35\n", - " 71.4\n", " 49\n", - " 71.4\n", + " 58.3\n", + " 84\n", + " 58.3\n", " 0.0\n", " unknown\n", " \n", " \n", " 45-49\n", - " 28\n", - " 50.0\n", - " 56\n", - " 50.0\n", + " 70\n", + " 58.8\n", + " 119\n", + " 58.8\n", " 0.0\n", " unknown\n", " \n", " \n", " 50-54\n", - " 35\n", - " 62.5\n", - " 56\n", - " 62.5\n", + " 70\n", + " 52.6\n", + " 133\n", + " 52.6\n", " 0.0\n", " unknown\n", " \n", " \n", " 55-59\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", + " 63\n", + " 60.0\n", + " 105\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 60-64\n", - " 28\n", - " 50.0\n", - " 56\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 63\n", + " 64.3\n", + " 98\n", + " 57.1\n", + " 7.2\n", + " 26-Feb\n", " \n", " \n", " 65-69\n", - " 35\n", - " 55.6\n", - " 63\n", - " 55.6\n", + " 49\n", + " 50.0\n", + " 98\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-74\n", - " 28\n", - " 57.1\n", " 49\n", - " 57.1\n", + " 53.8\n", + " 91\n", + " 53.8\n", " 0.0\n", " unknown\n", " \n", " \n", " 75-79\n", - " 21\n", - " 33.3\n", - " 63\n", - " 33.3\n", + " 70\n", + " 66.7\n", + " 105\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 80-84\n", - " 28\n", + " 56\n", " 57.1\n", - " 49\n", + " 98\n", " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " 85-89\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", + " 63\n", + " 60.0\n", + " 105\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 90+\n", - " 0\n", - " 0.0\n", " 7\n", - " 0.0\n", + " 50.0\n", + " 14\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 70\n", - " 55.6\n", - " 126\n", - " 55.6\n", + " 147\n", + " 53.8\n", + " 273\n", + " 53.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Mixed\n", - " 77\n", - " 47.8\n", " 161\n", - " 47.8\n", + " 57.5\n", + " 280\n", + " 57.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 63\n", - " 47.4\n", - " 133\n", - " 47.4\n", - " 0.0\n", - " unknown\n", + " 182\n", + " 61.9\n", + " 294\n", + " 59.5\n", + " 2.4\n", + " 24-Apr\n", " \n", " \n", " South Asian\n", - " 63\n", - " 47.4\n", - " 133\n", - " 47.4\n", + " 140\n", + " 51.3\n", + " 273\n", + " 51.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 70\n", - " 55.6\n", - " 126\n", - " 55.6\n", + " 133\n", + " 59.4\n", + " 224\n", + " 59.4\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", - " 70\n", - " 55.6\n", - " 126\n", - " 55.6\n", - " 0.0\n", - " unknown\n", + " 168\n", + " 64.9\n", + " 259\n", + " 62.2\n", + " 2.7\n", + " 08-Apr\n", " \n", " \n", - " brand_of_first_dose\n", + " brand_of_first_dose\n", " Oxford-AZ\n", " 0\n", " 0.0\n", @@ -17934,11 +17982,20 @@ " unknown\n", " \n", " \n", + " Pfizer\n", + " 0\n", + " 0.0\n", + " 0\n", + " NaN\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", " Unknown\n", - " 413\n", - " 56.7\n", - " 728\n", - " 55.8\n", + " 931\n", + " 63.9\n", + " 1456\n", + " 63.0\n", " 0.9\n", " unknown\n", " \n", @@ -17949,73 +18006,75 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 413 51.3 805 \n", - "sex F 210 50.8 413 \n", - " M 203 51.8 392 \n", - "ageband_5yr 0 0 0.0 7 \n", - " 0-15 21 42.9 49 \n", - " 16-17 21 42.9 49 \n", - " 18-29 21 42.9 49 \n", - " 30-34 21 50.0 42 \n", - " 35-39 28 57.1 49 \n", - " 40-44 35 71.4 49 \n", - " 45-49 28 50.0 56 \n", - " 50-54 35 62.5 56 \n", - " 55-59 28 57.1 49 \n", - " 60-64 28 50.0 56 \n", - " 65-69 35 55.6 63 \n", - " 70-74 28 57.1 49 \n", - " 75-79 21 33.3 63 \n", - " 80-84 28 57.1 49 \n", - " 85-89 28 57.1 49 \n", - " 90+ 0 0.0 7 \n", - "ethnicity_6_groups Black 70 55.6 126 \n", - " Mixed 77 47.8 161 \n", - " Other 63 47.4 133 \n", - " South Asian 63 47.4 133 \n", - " Unknown 70 55.6 126 \n", - " White 70 55.6 126 \n", + "overall overall 931 58.1 1603 \n", + "sex F 448 56.6 791 \n", + " M 483 59.5 812 \n", + "ageband_5yr 0 14 66.7 21 \n", + " 0-15 49 46.7 105 \n", + " 16-17 70 62.5 112 \n", + " 18-29 63 60.0 105 \n", + " 30-34 63 64.3 98 \n", + " 35-39 63 60.0 105 \n", + " 40-44 49 58.3 84 \n", + " 45-49 70 58.8 119 \n", + " 50-54 70 52.6 133 \n", + " 55-59 63 60.0 105 \n", + " 60-64 63 64.3 98 \n", + " 65-69 49 50.0 98 \n", + " 70-74 49 53.8 91 \n", + " 75-79 70 66.7 105 \n", + " 80-84 56 57.1 98 \n", + " 85-89 63 60.0 105 \n", + " 90+ 7 50.0 14 \n", + "ethnicity_6_groups Black 147 53.8 273 \n", + " Mixed 161 57.5 280 \n", + " Other 182 61.9 294 \n", + " South Asian 140 51.3 273 \n", + " Unknown 133 59.4 224 \n", + " White 168 64.9 259 \n", "brand_of_first_dose Oxford-AZ 0 0.0 0 \n", - " Unknown 413 56.7 728 \n", + " Pfizer 0 0.0 0 \n", + " Unknown 931 63.9 1456 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 50.4 \n", - "sex F 50.8 \n", - " M 50.0 \n", - "ageband_5yr 0 0.0 \n", - " 0-15 28.6 \n", - " 16-17 42.9 \n", - " 18-29 42.9 \n", - " 30-34 50.0 \n", - " 35-39 57.1 \n", - " 40-44 71.4 \n", - " 45-49 50.0 \n", - " 50-54 62.5 \n", - " 55-59 57.1 \n", - " 60-64 50.0 \n", - " 65-69 55.6 \n", - " 70-74 57.1 \n", - " 75-79 33.3 \n", + "overall overall 57.2 \n", + "sex F 55.8 \n", + " M 58.6 \n", + "ageband_5yr 0 66.7 \n", + " 0-15 46.7 \n", + " 16-17 62.5 \n", + " 18-29 60.0 \n", + " 30-34 64.3 \n", + " 35-39 60.0 \n", + " 40-44 58.3 \n", + " 45-49 58.8 \n", + " 50-54 52.6 \n", + " 55-59 60.0 \n", + " 60-64 57.1 \n", + " 65-69 50.0 \n", + " 70-74 53.8 \n", + " 75-79 66.7 \n", " 80-84 57.1 \n", - " 85-89 57.1 \n", - " 90+ 0.0 \n", - "ethnicity_6_groups Black 55.6 \n", - " Mixed 47.8 \n", - " Other 47.4 \n", - " South Asian 47.4 \n", - " Unknown 55.6 \n", - " White 55.6 \n", + " 85-89 60.0 \n", + " 90+ 50.0 \n", + "ethnicity_6_groups Black 53.8 \n", + " Mixed 57.5 \n", + " Other 59.5 \n", + " South Asian 51.3 \n", + " Unknown 59.4 \n", + " White 62.2 \n", "brand_of_first_dose Oxford-AZ NaN \n", - " Unknown 55.8 \n", + " Pfizer NaN \n", + " Unknown 63.0 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", "overall overall 0.9 \n", - "sex F 0.0 \n", - " M 1.8 \n", + "sex F 0.8 \n", + " M 0.9 \n", "ageband_5yr 0 0.0 \n", - " 0-15 14.3 \n", + " 0-15 0.0 \n", " 16-17 0.0 \n", " 18-29 0.0 \n", " 30-34 0.0 \n", @@ -18024,7 +18083,7 @@ " 45-49 0.0 \n", " 50-54 0.0 \n", " 55-59 0.0 \n", - " 60-64 0.0 \n", + " 60-64 7.2 \n", " 65-69 0.0 \n", " 70-74 0.0 \n", " 75-79 0.0 \n", @@ -18033,20 +18092,21 @@ " 90+ 0.0 \n", "ethnicity_6_groups Black 0.0 \n", " Mixed 0.0 \n", - " Other 0.0 \n", + " Other 2.4 \n", " South Asian 0.0 \n", " Unknown 0.0 \n", - " White 0.0 \n", + " White 2.7 \n", "brand_of_first_dose Oxford-AZ 0.0 \n", + " Pfizer 0.0 \n", " Unknown 0.9 \n", "\n", " Date projected to reach 90% \n", "category group \n", "overall overall unknown \n", "sex F unknown \n", - " M 12-May \n", + " M unknown \n", "ageband_5yr 0 unknown \n", - " 0-15 07-Jan \n", + " 0-15 unknown \n", " 16-17 unknown \n", " 18-29 unknown \n", " 30-34 unknown \n", @@ -18055,7 +18115,7 @@ " 45-49 unknown \n", " 50-54 unknown \n", " 55-59 unknown \n", - " 60-64 unknown \n", + " 60-64 26-Feb \n", " 65-69 unknown \n", " 70-74 unknown \n", " 75-79 unknown \n", @@ -18064,11 +18124,12 @@ " 90+ unknown \n", "ethnicity_6_groups Black unknown \n", " Mixed unknown \n", - " Other unknown \n", + " Other 24-Apr \n", " South Asian unknown \n", " Unknown unknown \n", - " White unknown \n", + " White 08-Apr \n", "brand_of_first_dose Oxford-AZ unknown \n", + " Pfizer unknown \n", " Unknown unknown " ] }, @@ -18098,7 +18159,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **60-64** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **60-64** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -18164,83 +18225,83 @@ " \n", " overall\n", " overall\n", - " 1393\n", - " 52.1\n", - " 2674\n", - " 51.0\n", - " 1.1\n", + " 2982\n", + " 54.7\n", + " 5453\n", + " 53.7\n", + " 1.0\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 693\n", - " 52.1\n", - " 1330\n", - " 51.6\n", - " 0.5\n", + " 1526\n", + " 54.4\n", + " 2807\n", + " 53.1\n", + " 1.3\n", " unknown\n", " \n", " \n", " M\n", - " 700\n", - " 52.1\n", - " 1344\n", - " 50.5\n", - " 1.6\n", - " 29-May\n", + " 1456\n", + " 55.0\n", + " 2646\n", + " 54.2\n", + " 0.8\n", + " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 252\n", - " 53.7\n", - " 469\n", - " 52.2\n", - " 1.5\n", - " 02-Jun\n", + " 539\n", + " 56.2\n", + " 959\n", + " 55.5\n", + " 0.7\n", + " unknown\n", " \n", " \n", " Mixed\n", - " 259\n", - " 56.1\n", - " 462\n", - " 56.1\n", - " 0.0\n", - " unknown\n", + " 532\n", + " 56.3\n", + " 945\n", + " 54.8\n", + " 1.5\n", + " 09-Jul\n", " \n", " \n", " Other\n", - " 238\n", - " 53.1\n", - " 448\n", - " 51.6\n", + " 497\n", + " 56.3\n", + " 882\n", + " 54.8\n", " 1.5\n", - " 05-Jun\n", + " 09-Jul\n", " \n", " \n", " South Asian\n", - " 224\n", - " 49.2\n", - " 455\n", - " 47.7\n", - " 1.5\n", - " unknown\n", + " 483\n", + " 52.7\n", + " 917\n", + " 51.1\n", + " 1.6\n", + " 15-Jul\n", " \n", " \n", " Unknown\n", - " 182\n", - " 50.0\n", - " 364\n", - " 50.0\n", - " 0.0\n", + " 448\n", + " 54.7\n", + " 819\n", + " 53.8\n", + " 0.9\n", " unknown\n", " \n", " \n", " White\n", - " 245\n", + " 490\n", " 52.2\n", - " 469\n", + " 938\n", " 50.7\n", " 1.5\n", " unknown\n", @@ -18248,444 +18309,462 @@ " \n", " ethnicity_16_groups\n", " African\n", - " 56\n", - " 47.1\n", - " 119\n", - " 47.1\n", + " 154\n", + " 55.0\n", + " 280\n", + " 55.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 84\n", - " 54.5\n", " 154\n", - " 50.0\n", - " 4.5\n", - " 08-Feb\n", + " 51.2\n", + " 301\n", + " 48.8\n", + " 2.4\n", + " 26-May\n", " \n", " \n", " Caribbean\n", - " 70\n", - " 47.6\n", - " 147\n", - " 47.6\n", - " 0.0\n", - " unknown\n", + " 175\n", + " 58.1\n", + " 301\n", + " 55.8\n", + " 2.3\n", + " 10-May\n", " \n", " \n", " Chinese\n", - " 84\n", - " 54.5\n", " 154\n", - " 50.0\n", - " 4.5\n", - " 08-Feb\n", + " 51.2\n", + " 301\n", + " 48.8\n", + " 2.4\n", + " 26-May\n", " \n", " \n", " Other\n", - " 84\n", - " 54.5\n", " 154\n", - " 54.5\n", + " 51.2\n", + " 301\n", + " 51.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 70\n", - " 55.6\n", - " 126\n", - " 50.0\n", - " 5.6\n", - " 27-Jan\n", + " 189\n", + " 62.8\n", + " 301\n", + " 60.5\n", + " 2.3\n", + " 25-Apr\n", " \n", " \n", " British or Mixed British\n", - " 70\n", - " 47.6\n", - " 147\n", - " 47.6\n", + " 133\n", + " 51.4\n", + " 259\n", + " 51.4\n", " 0.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 70\n", - " 52.6\n", - " 133\n", - " 52.6\n", - " 0.0\n", - " unknown\n", + " 161\n", + " 59.0\n", + " 273\n", + " 56.4\n", + " 2.6\n", + " 26-Apr\n", " \n", " \n", " Irish\n", - " 91\n", - " 59.1\n", - " 154\n", - " 59.1\n", + " 147\n", + " 52.5\n", + " 280\n", + " 52.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 70\n", - " 55.6\n", - " 126\n", - " 55.6\n", - " 0.0\n", - " unknown\n", + " 168\n", + " 58.5\n", + " 287\n", + " 56.1\n", + " 2.4\n", + " 04-May\n", " \n", " \n", " Other White\n", - " 77\n", - " 47.8\n", - " 161\n", - " 47.8\n", + " 147\n", + " 53.8\n", + " 273\n", + " 53.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 77\n", - " 52.4\n", " 147\n", - " 52.4\n", + " 55.3\n", + " 266\n", + " 55.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 77\n", - " 52.4\n", - " 147\n", - " 47.6\n", - " 4.8\n", - " 07-Feb\n", + " 175\n", + " 58.1\n", + " 301\n", + " 55.8\n", + " 2.3\n", + " 10-May\n", " \n", " \n", " Unknown\n", - " 217\n", - " 53.4\n", - " 406\n", - " 53.4\n", + " 427\n", + " 51.3\n", + " 833\n", + " 51.3\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 70\n", - " 52.6\n", - " 133\n", - " 47.4\n", - " 5.2\n", - " 03-Feb\n", + " 161\n", + " 56.1\n", + " 287\n", + " 56.1\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black African\n", - " 63\n", - " 47.4\n", - " 133\n", - " 47.4\n", + " 175\n", + " 58.1\n", + " 301\n", + " 58.1\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 70\n", - " 55.6\n", - " 126\n", - " 55.6\n", - " 0.0\n", - " unknown\n", + " 161\n", + " 51.1\n", + " 315\n", + " 48.9\n", + " 2.2\n", + " 05-Jun\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 266\n", - " 52.8\n", - " 504\n", - " 51.4\n", - " 1.4\n", + " 532\n", + " 52.4\n", + " 1015\n", + " 51.7\n", + " 0.7\n", " unknown\n", " \n", " \n", " 2\n", - " 273\n", - " 50.0\n", - " 546\n", - " 48.7\n", + " 574\n", + " 55.4\n", + " 1036\n", + " 54.1\n", " 1.3\n", " unknown\n", " \n", " \n", " 3\n", - " 245\n", - " 48.6\n", - " 504\n", - " 47.2\n", - " 1.4\n", + " 609\n", + " 56.9\n", + " 1071\n", + " 55.6\n", + " 1.3\n", " unknown\n", " \n", " \n", " 4\n", - " 259\n", - " 53.6\n", - " 483\n", - " 53.6\n", - " 0.0\n", + " 546\n", + " 54.5\n", + " 1001\n", + " 53.1\n", + " 1.4\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 273\n", - " 54.2\n", - " 504\n", - " 52.8\n", - " 1.4\n", + " 574\n", + " 54.3\n", + " 1057\n", + " 53.0\n", + " 1.3\n", " unknown\n", " \n", " \n", " Unknown\n", - " 77\n", - " 57.9\n", - " 133\n", - " 57.9\n", + " 147\n", + " 52.5\n", + " 280\n", + " 52.5\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 427\n", - " 51.7\n", - " 826\n", - " 50.8\n", - " 0.9\n", + " 882\n", + " 54.3\n", + " 1624\n", + " 53.0\n", + " 1.3\n", " unknown\n", " \n", " \n", " under 30\n", - " 959\n", - " 51.9\n", - " 1848\n", - " 51.5\n", - " 0.4\n", + " 2107\n", + " 55.0\n", + " 3829\n", + " 53.9\n", + " 1.1\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1372\n", - " 52.0\n", - " 2639\n", - " 51.2\n", - " 0.8\n", + " 2961\n", + " 54.7\n", + " 5411\n", + " 53.7\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 50.0\n", + " 42\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1379\n", - " 52.0\n", - " 2653\n", - " 51.2\n", - " 0.8\n", + " 2954\n", + " 54.7\n", + " 5397\n", + " 53.7\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 28\n", + " 50.0\n", + " 56\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1379\n", - " 52.0\n", - " 2653\n", - " 51.2\n", - " 0.8\n", + " 2954\n", + " 54.7\n", + " 5397\n", + " 53.7\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 28\n", + " 50.0\n", + " 56\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 1372\n", - " 51.9\n", - " 2646\n", - " 51.1\n", - " 0.8\n", + " 2940\n", + " 54.7\n", + " 5376\n", + " 53.6\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 42\n", + " 54.5\n", + " 77\n", + " 54.5\n", " 0.0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1379\n", - " 52.1\n", - " 2646\n", - " 51.1\n", - " 1.0\n", + " 2954\n", + " 54.7\n", + " 5404\n", + " 53.6\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", " 28\n", - " 50.0\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1379\n", - " 52.1\n", - " 2646\n", - " 51.1\n", - " 1.0\n", + " 2961\n", + " 54.8\n", + " 5404\n", + " 53.6\n", + " 1.2\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", " 28\n", - " 50.0\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 1372\n", - " 51.9\n", - " 2646\n", - " 51.1\n", - " 0.8\n", + " 2947\n", + " 54.6\n", + " 5397\n", + " 53.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", " 35\n", - " 40.0\n", + " 55.6\n", + " 63\n", + " 55.6\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1379\n", - " 52.0\n", - " 2653\n", - " 51.2\n", - " 0.8\n", + " 2954\n", + " 54.6\n", + " 5411\n", + " 53.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 33.3\n", - " 33.4\n", - " 19-Dec\n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", + " 0.0\n", + " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1386\n", - " 52.2\n", - " 2653\n", - " 51.2\n", - " 1.0\n", + " 2954\n", + " 54.7\n", + " 5397\n", + " 53.6\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 35\n", + " 62.5\n", + " 56\n", + " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1372\n", - " 51.9\n", - " 2646\n", - " 51.1\n", - " 0.8\n", + " 2954\n", + " 54.7\n", + " 5404\n", + " 53.6\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1099\n", - " 52.0\n", - " 2114\n", - " 51.0\n", - " 1.0\n", + " 2401\n", + " 54.5\n", + " 4403\n", + " 53.4\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 294\n", - " 52.5\n", - " 560\n", - " 51.2\n", - " 1.3\n", + " 581\n", + " 55.0\n", + " 1057\n", + " 54.3\n", + " 0.7\n", " unknown\n", " \n", " \n", - " brand_of_first_dose\n", - " Pfizer\n", - " 0\n", + " brand_of_first_dose\n", + " Moderna\n", + " 0\n", + " 0.0\n", + " 0\n", + " NaN\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " Oxford-AZ\n", + " 0\n", + " 0.0\n", + " 0\n", + " NaN\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " Pfizer\n", + " 0\n", " 0.0\n", " 0\n", " NaN\n", @@ -18694,11 +18773,11 @@ " \n", " \n", " Unknown\n", - " 1386\n", - " 57.9\n", - " 2394\n", - " 57.0\n", - " 0.9\n", + " 2975\n", + " 60.5\n", + " 4914\n", + " 59.4\n", + " 1.1\n", " unknown\n", " \n", " \n", @@ -18708,276 +18787,284 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1393 \n", - "sex F 693 \n", - " M 700 \n", - "ethnicity_6_groups Black 252 \n", - " Mixed 259 \n", - " Other 238 \n", - " South Asian 224 \n", - " Unknown 182 \n", - " White 245 \n", - "ethnicity_16_groups African 56 \n", - " Bangladeshi or British Bangladeshi 84 \n", - " Caribbean 70 \n", - " Chinese 84 \n", - " Other 84 \n", - " Other Asian 70 \n", - " British or Mixed British 70 \n", - " Indian or British Indian 70 \n", - " Irish 91 \n", - " Other Black 70 \n", - " Other White 77 \n", - " Other mixed 77 \n", - " Pakistani or British Pakistani 77 \n", - " Unknown 217 \n", - " White + Asian 70 \n", - " White + Black African 63 \n", - " White + Black Caribbean 70 \n", - "imd_categories 1 Most deprived 266 \n", - " 2 273 \n", - " 3 245 \n", - " 4 259 \n", - " 5 Least deprived 273 \n", - " Unknown 77 \n", - "bmi 30+ 427 \n", - " under 30 959 \n", - "chronic_cardiac_disease no 1372 \n", + "overall overall 2982 \n", + "sex F 1526 \n", + " M 1456 \n", + "ethnicity_6_groups Black 539 \n", + " Mixed 532 \n", + " Other 497 \n", + " South Asian 483 \n", + " Unknown 448 \n", + " White 490 \n", + "ethnicity_16_groups African 154 \n", + " Bangladeshi or British Bangladeshi 154 \n", + " Caribbean 175 \n", + " Chinese 154 \n", + " Other 154 \n", + " Other Asian 189 \n", + " British or Mixed British 133 \n", + " Indian or British Indian 161 \n", + " Irish 147 \n", + " Other Black 168 \n", + " Other White 147 \n", + " Other mixed 147 \n", + " Pakistani or British Pakistani 175 \n", + " Unknown 427 \n", + " White + Asian 161 \n", + " White + Black African 175 \n", + " White + Black Caribbean 161 \n", + "imd_categories 1 Most deprived 532 \n", + " 2 574 \n", + " 3 609 \n", + " 4 546 \n", + " 5 Least deprived 574 \n", + " Unknown 147 \n", + "bmi 30+ 882 \n", + " under 30 2107 \n", + "chronic_cardiac_disease no 2961 \n", " yes 21 \n", - "current_copd no 1379 \n", - " yes 7 \n", - "dmards no 1379 \n", - " yes 7 \n", - "dementia no 1372 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1379 \n", - " yes 14 \n", - "ssri no 1379 \n", - " yes 14 \n", - "chemo_or_radio no 1372 \n", - " yes 14 \n", - "lung_cancer no 1379 \n", - " yes 14 \n", - "cancer_excl_lung_and_haem no 1386 \n", - " yes 7 \n", - "haematological_cancer no 1372 \n", - " yes 14 \n", - "ckd no 1099 \n", - " yes 294 \n", - "brand_of_first_dose Pfizer 0 \n", - " Unknown 1386 \n", + "current_copd no 2954 \n", + " yes 28 \n", + "dmards no 2954 \n", + " yes 28 \n", + "dementia no 2940 \n", + " yes 42 \n", + "psychosis_schiz_bipolar no 2954 \n", + " yes 28 \n", + "ssri no 2961 \n", + " yes 28 \n", + "chemo_or_radio no 2947 \n", + " yes 35 \n", + "lung_cancer no 2954 \n", + " yes 28 \n", + "cancer_excl_lung_and_haem no 2954 \n", + " yes 35 \n", + "haematological_cancer no 2954 \n", + " yes 28 \n", + "ckd no 2401 \n", + " yes 581 \n", + "brand_of_first_dose Moderna 0 \n", + " Oxford-AZ 0 \n", + " Pfizer 0 \n", + " Unknown 2975 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 52.1 2674 \n", - "sex F 52.1 1330 \n", - " M 52.1 1344 \n", - "ethnicity_6_groups Black 53.7 469 \n", - " Mixed 56.1 462 \n", - " Other 53.1 448 \n", - " South Asian 49.2 455 \n", - " Unknown 50.0 364 \n", - " White 52.2 469 \n", - "ethnicity_16_groups African 47.1 119 \n", - " Bangladeshi or British Bangladeshi 54.5 154 \n", - " Caribbean 47.6 147 \n", - " Chinese 54.5 154 \n", - " Other 54.5 154 \n", - " Other Asian 55.6 126 \n", - " British or Mixed British 47.6 147 \n", - " Indian or British Indian 52.6 133 \n", - " Irish 59.1 154 \n", - " Other Black 55.6 126 \n", - " Other White 47.8 161 \n", - " Other mixed 52.4 147 \n", - " Pakistani or British Pakistani 52.4 147 \n", - " Unknown 53.4 406 \n", - " White + Asian 52.6 133 \n", - " White + Black African 47.4 133 \n", - " White + Black Caribbean 55.6 126 \n", - "imd_categories 1 Most deprived 52.8 504 \n", - " 2 50.0 546 \n", - " 3 48.6 504 \n", - " 4 53.6 483 \n", - " 5 Least deprived 54.2 504 \n", - " Unknown 57.9 133 \n", - "bmi 30+ 51.7 826 \n", - " under 30 51.9 1848 \n", - "chronic_cardiac_disease no 52.0 2639 \n", - " yes 60.0 35 \n", - "current_copd no 52.0 2653 \n", - " yes 33.3 21 \n", - "dmards no 52.0 2653 \n", - " yes 33.3 21 \n", - "dementia no 51.9 2646 \n", - " yes 50.0 28 \n", - "psychosis_schiz_bipolar no 52.1 2646 \n", - " yes 50.0 28 \n", - "ssri no 52.1 2646 \n", - " yes 50.0 28 \n", - "chemo_or_radio no 51.9 2646 \n", - " yes 40.0 35 \n", - "lung_cancer no 52.0 2653 \n", - " yes 66.7 21 \n", - "cancer_excl_lung_and_haem no 52.2 2653 \n", - " yes 33.3 21 \n", - "haematological_cancer no 51.9 2646 \n", - " yes 40.0 35 \n", - "ckd no 52.0 2114 \n", - " yes 52.5 560 \n", - "brand_of_first_dose Pfizer 0.0 0 \n", - " Unknown 57.9 2394 \n", + "overall overall 54.7 5453 \n", + "sex F 54.4 2807 \n", + " M 55.0 2646 \n", + "ethnicity_6_groups Black 56.2 959 \n", + " Mixed 56.3 945 \n", + " Other 56.3 882 \n", + " South Asian 52.7 917 \n", + " Unknown 54.7 819 \n", + " White 52.2 938 \n", + "ethnicity_16_groups African 55.0 280 \n", + " Bangladeshi or British Bangladeshi 51.2 301 \n", + " Caribbean 58.1 301 \n", + " Chinese 51.2 301 \n", + " Other 51.2 301 \n", + " Other Asian 62.8 301 \n", + " British or Mixed British 51.4 259 \n", + " Indian or British Indian 59.0 273 \n", + " Irish 52.5 280 \n", + " Other Black 58.5 287 \n", + " Other White 53.8 273 \n", + " Other mixed 55.3 266 \n", + " Pakistani or British Pakistani 58.1 301 \n", + " Unknown 51.3 833 \n", + " White + Asian 56.1 287 \n", + " White + Black African 58.1 301 \n", + " White + Black Caribbean 51.1 315 \n", + "imd_categories 1 Most deprived 52.4 1015 \n", + " 2 55.4 1036 \n", + " 3 56.9 1071 \n", + " 4 54.5 1001 \n", + " 5 Least deprived 54.3 1057 \n", + " Unknown 52.5 280 \n", + "bmi 30+ 54.3 1624 \n", + " under 30 55.0 3829 \n", + "chronic_cardiac_disease no 54.7 5411 \n", + " yes 50.0 42 \n", + "current_copd no 54.7 5397 \n", + " yes 50.0 56 \n", + "dmards no 54.7 5397 \n", + " yes 50.0 56 \n", + "dementia no 54.7 5376 \n", + " yes 54.5 77 \n", + "psychosis_schiz_bipolar no 54.7 5404 \n", + " yes 57.1 49 \n", + "ssri no 54.8 5404 \n", + " yes 57.1 49 \n", + "chemo_or_radio no 54.6 5397 \n", + " yes 55.6 63 \n", + "lung_cancer no 54.6 5411 \n", + " yes 57.1 49 \n", + "cancer_excl_lung_and_haem no 54.7 5397 \n", + " yes 62.5 56 \n", + "haematological_cancer no 54.7 5404 \n", + " yes 57.1 49 \n", + "ckd no 54.5 4403 \n", + " yes 55.0 1057 \n", + "brand_of_first_dose Moderna 0.0 0 \n", + " Oxford-AZ 0.0 0 \n", + " Pfizer 0.0 0 \n", + " Unknown 60.5 4914 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 51.0 \n", - "sex F 51.6 \n", - " M 50.5 \n", - "ethnicity_6_groups Black 52.2 \n", - " Mixed 56.1 \n", - " Other 51.6 \n", - " South Asian 47.7 \n", - " Unknown 50.0 \n", + "overall overall 53.7 \n", + "sex F 53.1 \n", + " M 54.2 \n", + "ethnicity_6_groups Black 55.5 \n", + " Mixed 54.8 \n", + " Other 54.8 \n", + " South Asian 51.1 \n", + " Unknown 53.8 \n", " White 50.7 \n", - "ethnicity_16_groups African 47.1 \n", - " Bangladeshi or British Bangladeshi 50.0 \n", - " Caribbean 47.6 \n", - " Chinese 50.0 \n", - " Other 54.5 \n", - " Other Asian 50.0 \n", - " British or Mixed British 47.6 \n", - " Indian or British Indian 52.6 \n", - " Irish 59.1 \n", - " Other Black 55.6 \n", - " Other White 47.8 \n", - " Other mixed 52.4 \n", - " Pakistani or British Pakistani 47.6 \n", - " Unknown 53.4 \n", - " White + Asian 47.4 \n", - " White + Black African 47.4 \n", - " White + Black Caribbean 55.6 \n", - "imd_categories 1 Most deprived 51.4 \n", - " 2 48.7 \n", - " 3 47.2 \n", - " 4 53.6 \n", - " 5 Least deprived 52.8 \n", - " Unknown 57.9 \n", - "bmi 30+ 50.8 \n", - " under 30 51.5 \n", - "chronic_cardiac_disease no 51.2 \n", - " yes 60.0 \n", - "current_copd no 51.2 \n", - " yes 33.3 \n", - "dmards no 51.2 \n", - " yes 33.3 \n", - "dementia no 51.1 \n", + "ethnicity_16_groups African 55.0 \n", + " Bangladeshi or British Bangladeshi 48.8 \n", + " Caribbean 55.8 \n", + " Chinese 48.8 \n", + " Other 51.2 \n", + " Other Asian 60.5 \n", + " British or Mixed British 51.4 \n", + " Indian or British Indian 56.4 \n", + " Irish 52.5 \n", + " Other Black 56.1 \n", + " Other White 53.8 \n", + " Other mixed 55.3 \n", + " Pakistani or British Pakistani 55.8 \n", + " Unknown 51.3 \n", + " White + Asian 56.1 \n", + " White + Black African 58.1 \n", + " White + Black Caribbean 48.9 \n", + "imd_categories 1 Most deprived 51.7 \n", + " 2 54.1 \n", + " 3 55.6 \n", + " 4 53.1 \n", + " 5 Least deprived 53.0 \n", + " Unknown 52.5 \n", + "bmi 30+ 53.0 \n", + " under 30 53.9 \n", + "chronic_cardiac_disease no 53.7 \n", " yes 50.0 \n", - "psychosis_schiz_bipolar no 51.1 \n", + "current_copd no 53.7 \n", " yes 50.0 \n", - "ssri no 51.1 \n", + "dmards no 53.7 \n", " yes 50.0 \n", - "chemo_or_radio no 51.1 \n", - " yes 40.0 \n", - "lung_cancer no 51.2 \n", - " yes 33.3 \n", - "cancer_excl_lung_and_haem no 51.2 \n", - " yes 33.3 \n", - "haematological_cancer no 51.1 \n", - " yes 40.0 \n", - "ckd no 51.0 \n", - " yes 51.2 \n", - "brand_of_first_dose Pfizer NaN \n", - " Unknown 57.0 \n", + "dementia no 53.6 \n", + " yes 54.5 \n", + "psychosis_schiz_bipolar no 53.6 \n", + " yes 57.1 \n", + "ssri no 53.6 \n", + " yes 57.1 \n", + "chemo_or_radio no 53.6 \n", + " yes 55.6 \n", + "lung_cancer no 53.6 \n", + " yes 57.1 \n", + "cancer_excl_lung_and_haem no 53.6 \n", + " yes 62.5 \n", + "haematological_cancer no 53.6 \n", + " yes 57.1 \n", + "ckd no 53.4 \n", + " yes 54.3 \n", + "brand_of_first_dose Moderna NaN \n", + " Oxford-AZ NaN \n", + " Pfizer NaN \n", + " Unknown 59.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.1 \n", - "sex F 0.5 \n", - " M 1.6 \n", - "ethnicity_6_groups Black 1.5 \n", - " Mixed 0.0 \n", + "overall overall 1.0 \n", + "sex F 1.3 \n", + " M 0.8 \n", + "ethnicity_6_groups Black 0.7 \n", + " Mixed 1.5 \n", " Other 1.5 \n", - " South Asian 1.5 \n", - " Unknown 0.0 \n", + " South Asian 1.6 \n", + " Unknown 0.9 \n", " White 1.5 \n", "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 4.5 \n", - " Caribbean 0.0 \n", - " Chinese 4.5 \n", + " Bangladeshi or British Bangladeshi 2.4 \n", + " Caribbean 2.3 \n", + " Chinese 2.4 \n", " Other 0.0 \n", - " Other Asian 5.6 \n", + " Other Asian 2.3 \n", " British or Mixed British 0.0 \n", - " Indian or British Indian 0.0 \n", + " Indian or British Indian 2.6 \n", " Irish 0.0 \n", - " Other Black 0.0 \n", + " Other Black 2.4 \n", " Other White 0.0 \n", " Other mixed 0.0 \n", - " Pakistani or British Pakistani 4.8 \n", + " Pakistani or British Pakistani 2.3 \n", " Unknown 0.0 \n", - " White + Asian 5.2 \n", + " White + Asian 0.0 \n", " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 1.4 \n", + " White + Black Caribbean 2.2 \n", + "imd_categories 1 Most deprived 0.7 \n", " 2 1.3 \n", - " 3 1.4 \n", - " 4 0.0 \n", - " 5 Least deprived 1.4 \n", + " 3 1.3 \n", + " 4 1.4 \n", + " 5 Least deprived 1.3 \n", " Unknown 0.0 \n", - "bmi 30+ 0.9 \n", - " under 30 0.4 \n", - "chronic_cardiac_disease no 0.8 \n", + "bmi 30+ 1.3 \n", + " under 30 1.1 \n", + "chronic_cardiac_disease no 1.0 \n", " yes 0.0 \n", - "current_copd no 0.8 \n", + "current_copd no 1.0 \n", " yes 0.0 \n", - "dmards no 0.8 \n", + "dmards no 1.0 \n", " yes 0.0 \n", - "dementia no 0.8 \n", + "dementia no 1.1 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.0 \n", + "psychosis_schiz_bipolar no 1.1 \n", " yes 0.0 \n", - "ssri no 1.0 \n", + "ssri no 1.2 \n", " yes 0.0 \n", - "chemo_or_radio no 0.8 \n", + "chemo_or_radio no 1.0 \n", " yes 0.0 \n", - "lung_cancer no 0.8 \n", - " yes 33.4 \n", - "cancer_excl_lung_and_haem no 1.0 \n", + "lung_cancer no 1.0 \n", " yes 0.0 \n", - "haematological_cancer no 0.8 \n", + "cancer_excl_lung_and_haem no 1.1 \n", " yes 0.0 \n", - "ckd no 1.0 \n", - " yes 1.3 \n", - "brand_of_first_dose Pfizer 0.0 \n", - " Unknown 0.9 \n", + "haematological_cancer no 1.1 \n", + " yes 0.0 \n", + "ckd no 1.1 \n", + " yes 0.7 \n", + "brand_of_first_dose Moderna 0.0 \n", + " Oxford-AZ 0.0 \n", + " Pfizer 0.0 \n", + " Unknown 1.1 \n", "\n", " Date projected to reach 90% \n", "category group \n", "overall overall unknown \n", "sex F unknown \n", - " M 29-May \n", - "ethnicity_6_groups Black 02-Jun \n", - " Mixed unknown \n", - " Other 05-Jun \n", - " South Asian unknown \n", + " M unknown \n", + "ethnicity_6_groups Black unknown \n", + " Mixed 09-Jul \n", + " Other 09-Jul \n", + " South Asian 15-Jul \n", " Unknown unknown \n", " White unknown \n", "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi 08-Feb \n", - " Caribbean unknown \n", - " Chinese 08-Feb \n", + " Bangladeshi or British Bangladeshi 26-May \n", + " Caribbean 10-May \n", + " Chinese 26-May \n", " Other unknown \n", - " Other Asian 27-Jan \n", + " Other Asian 25-Apr \n", " British or Mixed British unknown \n", - " Indian or British Indian unknown \n", + " Indian or British Indian 26-Apr \n", " Irish unknown \n", - " Other Black unknown \n", + " Other Black 04-May \n", " Other White unknown \n", " Other mixed unknown \n", - " Pakistani or British Pakistani 07-Feb \n", + " Pakistani or British Pakistani 10-May \n", " Unknown unknown \n", - " White + Asian 03-Feb \n", + " White + Asian unknown \n", " White + Black African unknown \n", - " White + Black Caribbean unknown \n", + " White + Black Caribbean 05-Jun \n", "imd_categories 1 Most deprived unknown \n", " 2 unknown \n", " 3 unknown \n", @@ -19001,14 +19088,16 @@ "chemo_or_radio no unknown \n", " yes unknown \n", "lung_cancer no unknown \n", - " yes 19-Dec \n", + " yes unknown \n", "cancer_excl_lung_and_haem no unknown \n", " yes unknown \n", "haematological_cancer no unknown \n", " yes unknown \n", "ckd no unknown \n", " yes unknown \n", - "brand_of_first_dose Pfizer unknown \n", + "brand_of_first_dose Moderna unknown \n", + " Oxford-AZ unknown \n", + " Pfizer unknown \n", " Unknown unknown " ] }, @@ -19038,7 +19127,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **55-59** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **55-59** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -19104,427 +19193,427 @@ " \n", " overall\n", " overall\n", - " 1708\n", - " 53.6\n", - " 3185\n", - " 52.5\n", - " 1.1\n", + " 3472\n", + " 55.8\n", + " 6223\n", + " 54.8\n", + " 1.0\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 910\n", - " 56.0\n", - " 1624\n", - " 54.7\n", + " 1764\n", + " 55.0\n", + " 3206\n", + " 53.7\n", " 1.3\n", " unknown\n", " \n", " \n", " M\n", - " 798\n", - " 51.1\n", - " 1561\n", - " 50.2\n", - " 0.9\n", + " 1701\n", + " 56.4\n", + " 3017\n", + " 55.7\n", + " 0.7\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 308\n", - " 53.7\n", - " 574\n", - " 53.7\n", - " 0.0\n", - " unknown\n", + " 581\n", + " 56.1\n", + " 1036\n", + " 54.7\n", + " 1.4\n", + " 21-Jul\n", " \n", " \n", " Mixed\n", - " 308\n", - " 53.7\n", - " 574\n", - " 52.4\n", + " 567\n", + " 53.3\n", + " 1064\n", + " 52.0\n", " 1.3\n", " unknown\n", " \n", " \n", " Other\n", - " 259\n", - " 50.0\n", - " 518\n", - " 48.6\n", - " 1.4\n", - " unknown\n", + " 630\n", + " 58.1\n", + " 1085\n", + " 56.8\n", + " 1.3\n", + " 23-Jul\n", " \n", " \n", " South Asian\n", - " 287\n", - " 53.2\n", - " 539\n", - " 53.2\n", - " 0.0\n", + " 574\n", + " 56.2\n", + " 1022\n", + " 55.5\n", + " 0.7\n", " unknown\n", " \n", " \n", " Unknown\n", - " 231\n", - " 55.0\n", - " 420\n", - " 53.3\n", - " 1.7\n", - " 08-May\n", + " 518\n", + " 54.4\n", + " 952\n", + " 53.7\n", + " 0.7\n", + " unknown\n", " \n", " \n", " White\n", - " 308\n", - " 55.7\n", - " 553\n", - " 55.7\n", - " 0.0\n", + " 595\n", + " 55.6\n", + " 1071\n", + " 54.9\n", + " 0.7\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 105\n", - " 60.0\n", - " 175\n", - " 60.0\n", + " 168\n", + " 52.2\n", + " 322\n", + " 52.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 91\n", - " 54.2\n", - " 168\n", - " 54.2\n", + " 161\n", + " 53.5\n", + " 301\n", + " 53.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 98\n", - " 60.9\n", - " 161\n", - " 56.5\n", - " 4.4\n", - " 30-Jan\n", + " 189\n", + " 57.4\n", + " 329\n", + " 55.3\n", + " 2.1\n", + " 21-May\n", " \n", " \n", " Chinese\n", - " 91\n", - " 50.0\n", - " 182\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 161\n", + " 54.8\n", + " 294\n", + " 52.4\n", + " 2.4\n", + " 15-May\n", " \n", " \n", " Other\n", - " 77\n", - " 52.4\n", - " 147\n", - " 52.4\n", - " 0.0\n", - " unknown\n", + " 196\n", + " 59.6\n", + " 329\n", + " 55.3\n", + " 4.3\n", + " 23-Mar\n", " \n", " \n", " Other Asian\n", - " 77\n", - " 47.8\n", - " 161\n", - " 47.8\n", - " 0.0\n", - " unknown\n", + " 175\n", + " 56.8\n", + " 308\n", + " 54.5\n", + " 2.3\n", + " 14-May\n", " \n", " \n", " British or Mixed British\n", - " 91\n", - " 56.5\n", - " 161\n", - " 56.5\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 56.2\n", + " 336\n", + " 54.2\n", + " 2.0\n", + " 31-May\n", " \n", " \n", " Indian or British Indian\n", - " 84\n", - " 50.0\n", - " 168\n", - " 50.0\n", + " 175\n", + " 54.3\n", + " 322\n", + " 54.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 91\n", - " 52.0\n", - " 175\n", - " 52.0\n", + " 182\n", + " 54.2\n", + " 336\n", + " 54.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 91\n", - " 59.1\n", - " 154\n", - " 59.1\n", - " 0.0\n", - " unknown\n", + " 203\n", + " 59.2\n", + " 343\n", + " 57.1\n", + " 2.1\n", + " 15-May\n", " \n", " \n", " Other White\n", - " 84\n", - " 54.5\n", - " 154\n", - " 54.5\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 54.0\n", + " 350\n", + " 52.0\n", + " 2.0\n", + " 08-Jun\n", " \n", " \n", " Other mixed\n", - " 91\n", - " 50.0\n", - " 182\n", - " 46.2\n", - " 3.8\n", - " 26-Feb\n", + " 189\n", + " 61.4\n", + " 308\n", + " 59.1\n", + " 2.3\n", + " 30-Apr\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 112\n", - " 59.3\n", - " 189\n", - " 59.3\n", - " 0.0\n", - " unknown\n", + " 210\n", + " 58.8\n", + " 357\n", + " 56.9\n", + " 1.9\n", + " 27-May\n", " \n", " \n", " Unknown\n", - " 252\n", - " 52.2\n", - " 483\n", - " 50.7\n", - " 1.5\n", + " 518\n", + " 54.4\n", + " 952\n", + " 53.7\n", + " 0.7\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 91\n", - " 54.2\n", - " 168\n", - " 54.2\n", + " 175\n", + " 52.1\n", + " 336\n", + " 52.1\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black African\n", - " 91\n", - " 56.5\n", - " 161\n", - " 56.5\n", - " 0.0\n", - " unknown\n", + " 217\n", + " 57.4\n", + " 378\n", + " 55.6\n", + " 1.8\n", + " 08-Jun\n", " \n", " \n", " White + Black Caribbean\n", - " 84\n", - " 46.2\n", " 182\n", - " 46.2\n", + " 55.3\n", + " 329\n", + " 55.3\n", " 0.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 336\n", - " 55.2\n", - " 609\n", - " 54.0\n", - " 1.2\n", + " 679\n", + " 55.4\n", + " 1225\n", + " 54.9\n", + " 0.5\n", " unknown\n", " \n", " \n", " 2\n", - " 336\n", - " 52.2\n", " 644\n", - " 51.1\n", - " 1.1\n", + " 56.4\n", + " 1141\n", + " 55.8\n", + " 0.6\n", " unknown\n", " \n", " \n", " 3\n", - " 315\n", - " 53.6\n", - " 588\n", - " 53.6\n", - " 0.0\n", + " 686\n", + " 56.6\n", + " 1211\n", + " 55.5\n", + " 1.1\n", " unknown\n", " \n", " \n", " 4\n", - " 322\n", - " 53.5\n", - " 602\n", - " 52.3\n", + " 672\n", + " 56.8\n", + " 1183\n", + " 55.6\n", " 1.2\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 301\n", - " 53.1\n", - " 567\n", - " 51.9\n", + " 623\n", + " 54.6\n", + " 1141\n", + " 53.4\n", " 1.2\n", " unknown\n", " \n", " \n", " Unknown\n", - " 98\n", - " 56.0\n", - " 175\n", - " 52.0\n", - " 4.0\n", - " 12-Feb\n", + " 168\n", + " 52.2\n", + " 322\n", + " 50.0\n", + " 2.2\n", + " 02-Jun\n", " \n", " \n", " bmi\n", " 30+\n", - " 546\n", - " 56.9\n", - " 959\n", - " 55.5\n", - " 1.4\n", - " 29-May\n", + " 1015\n", + " 56.2\n", + " 1806\n", + " 55.4\n", + " 0.8\n", + " unknown\n", " \n", " \n", " under 30\n", - " 1162\n", - " 52.2\n", - " 2226\n", - " 51.3\n", - " 0.9\n", + " 2450\n", + " 55.5\n", + " 4417\n", + " 54.4\n", + " 1.1\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1687\n", - " 53.7\n", - " 3143\n", - " 52.8\n", - " 0.9\n", + " 3430\n", + " 55.7\n", + " 6153\n", + " 54.7\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", - " 50.0\n", " 42\n", - " 50.0\n", + " 54.5\n", + " 77\n", + " 54.5\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1687\n", - " 53.6\n", - " 3150\n", - " 52.7\n", - " 0.9\n", + " 3444\n", + " 55.8\n", + " 6174\n", + " 54.8\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 21\n", + " 37.5\n", + " 56\n", + " 37.5\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1694\n", - " 53.8\n", - " 3150\n", - " 52.7\n", - " 1.1\n", + " 3430\n", + " 55.7\n", + " 6160\n", + " 54.7\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 42\n", + " 60.0\n", + " 70\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1694\n", - " 53.8\n", - " 3150\n", - " 52.7\n", + " 3437\n", + " 55.7\n", + " 6167\n", + " 54.6\n", " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", " 35\n", - " 40.0\n", - " 0.0\n", + " 55.6\n", + " 63\n", + " 55.6\n", + " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1687\n", - " 53.7\n", - " 3143\n", - " 52.8\n", - " 0.9\n", + " 3437\n", + " 55.8\n", + " 6160\n", + " 54.7\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", + " 35\n", " 50.0\n", - " 42\n", - " 33.3\n", - " 16.7\n", - " 31-Dec\n", + " 70\n", + " 50.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1393\n", - " 53.6\n", - " 2597\n", - " 52.6\n", - " 1.0\n", + " 2779\n", + " 56.2\n", + " 4942\n", + " 55.1\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 315\n", - " 53.6\n", - " 588\n", - " 52.4\n", - " 1.2\n", + " 693\n", + " 53.8\n", + " 1288\n", + " 52.7\n", + " 1.1\n", " unknown\n", " \n", " \n", @@ -19548,11 +19637,11 @@ " \n", " \n", " Unknown\n", - " 1701\n", - " 59.6\n", - " 2856\n", - " 58.6\n", - " 1.0\n", + " 3465\n", + " 61.8\n", + " 5607\n", + " 60.7\n", + " 1.1\n", " unknown\n", " \n", " \n", @@ -19562,247 +19651,247 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1708 \n", - "sex F 910 \n", - " M 798 \n", - "ethnicity_6_groups Black 308 \n", - " Mixed 308 \n", - " Other 259 \n", - " South Asian 287 \n", - " Unknown 231 \n", - " White 308 \n", - "ethnicity_16_groups African 105 \n", - " Bangladeshi or British Bangladeshi 91 \n", - " Caribbean 98 \n", - " Chinese 91 \n", - " Other 77 \n", - " Other Asian 77 \n", - " British or Mixed British 91 \n", - " Indian or British Indian 84 \n", - " Irish 91 \n", - " Other Black 91 \n", - " Other White 84 \n", - " Other mixed 91 \n", - " Pakistani or British Pakistani 112 \n", - " Unknown 252 \n", - " White + Asian 91 \n", - " White + Black African 91 \n", - " White + Black Caribbean 84 \n", - "imd_categories 1 Most deprived 336 \n", - " 2 336 \n", - " 3 315 \n", - " 4 322 \n", - " 5 Least deprived 301 \n", - " Unknown 98 \n", - "bmi 30+ 546 \n", - " under 30 1162 \n", - "chronic_cardiac_disease no 1687 \n", - " yes 21 \n", - "current_copd no 1687 \n", - " yes 14 \n", - "dmards no 1694 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1694 \n", - " yes 14 \n", - "ssri no 1687 \n", + "overall overall 3472 \n", + "sex F 1764 \n", + " M 1701 \n", + "ethnicity_6_groups Black 581 \n", + " Mixed 567 \n", + " Other 630 \n", + " South Asian 574 \n", + " Unknown 518 \n", + " White 595 \n", + "ethnicity_16_groups African 168 \n", + " Bangladeshi or British Bangladeshi 161 \n", + " Caribbean 189 \n", + " Chinese 161 \n", + " Other 196 \n", + " Other Asian 175 \n", + " British or Mixed British 189 \n", + " Indian or British Indian 175 \n", + " Irish 182 \n", + " Other Black 203 \n", + " Other White 189 \n", + " Other mixed 189 \n", + " Pakistani or British Pakistani 210 \n", + " Unknown 518 \n", + " White + Asian 175 \n", + " White + Black African 217 \n", + " White + Black Caribbean 182 \n", + "imd_categories 1 Most deprived 679 \n", + " 2 644 \n", + " 3 686 \n", + " 4 672 \n", + " 5 Least deprived 623 \n", + " Unknown 168 \n", + "bmi 30+ 1015 \n", + " under 30 2450 \n", + "chronic_cardiac_disease no 3430 \n", + " yes 42 \n", + "current_copd no 3444 \n", " yes 21 \n", - "ckd no 1393 \n", - " yes 315 \n", + "dmards no 3430 \n", + " yes 42 \n", + "psychosis_schiz_bipolar no 3437 \n", + " yes 35 \n", + "ssri no 3437 \n", + " yes 35 \n", + "ckd no 2779 \n", + " yes 693 \n", "brand_of_first_dose Oxford-AZ 0 \n", " Pfizer 0 \n", - " Unknown 1701 \n", + " Unknown 3465 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 53.6 3185 \n", - "sex F 56.0 1624 \n", - " M 51.1 1561 \n", - "ethnicity_6_groups Black 53.7 574 \n", - " Mixed 53.7 574 \n", - " Other 50.0 518 \n", - " South Asian 53.2 539 \n", - " Unknown 55.0 420 \n", - " White 55.7 553 \n", - "ethnicity_16_groups African 60.0 175 \n", - " Bangladeshi or British Bangladeshi 54.2 168 \n", - " Caribbean 60.9 161 \n", - " Chinese 50.0 182 \n", - " Other 52.4 147 \n", - " Other Asian 47.8 161 \n", - " British or Mixed British 56.5 161 \n", - " Indian or British Indian 50.0 168 \n", - " Irish 52.0 175 \n", - " Other Black 59.1 154 \n", - " Other White 54.5 154 \n", - " Other mixed 50.0 182 \n", - " Pakistani or British Pakistani 59.3 189 \n", - " Unknown 52.2 483 \n", - " White + Asian 54.2 168 \n", - " White + Black African 56.5 161 \n", - " White + Black Caribbean 46.2 182 \n", - "imd_categories 1 Most deprived 55.2 609 \n", - " 2 52.2 644 \n", - " 3 53.6 588 \n", - " 4 53.5 602 \n", - " 5 Least deprived 53.1 567 \n", - " Unknown 56.0 175 \n", - "bmi 30+ 56.9 959 \n", - " under 30 52.2 2226 \n", - "chronic_cardiac_disease no 53.7 3143 \n", - " yes 50.0 42 \n", - "current_copd no 53.6 3150 \n", - " yes 40.0 35 \n", - "dmards no 53.8 3150 \n", - " yes 40.0 35 \n", - "psychosis_schiz_bipolar no 53.8 3150 \n", - " yes 40.0 35 \n", - "ssri no 53.7 3143 \n", - " yes 50.0 42 \n", - "ckd no 53.6 2597 \n", - " yes 53.6 588 \n", + "overall overall 55.8 6223 \n", + "sex F 55.0 3206 \n", + " M 56.4 3017 \n", + "ethnicity_6_groups Black 56.1 1036 \n", + " Mixed 53.3 1064 \n", + " Other 58.1 1085 \n", + " South Asian 56.2 1022 \n", + " Unknown 54.4 952 \n", + " White 55.6 1071 \n", + "ethnicity_16_groups African 52.2 322 \n", + " Bangladeshi or British Bangladeshi 53.5 301 \n", + " Caribbean 57.4 329 \n", + " Chinese 54.8 294 \n", + " Other 59.6 329 \n", + " Other Asian 56.8 308 \n", + " British or Mixed British 56.2 336 \n", + " Indian or British Indian 54.3 322 \n", + " Irish 54.2 336 \n", + " Other Black 59.2 343 \n", + " Other White 54.0 350 \n", + " Other mixed 61.4 308 \n", + " Pakistani or British Pakistani 58.8 357 \n", + " Unknown 54.4 952 \n", + " White + Asian 52.1 336 \n", + " White + Black African 57.4 378 \n", + " White + Black Caribbean 55.3 329 \n", + "imd_categories 1 Most deprived 55.4 1225 \n", + " 2 56.4 1141 \n", + " 3 56.6 1211 \n", + " 4 56.8 1183 \n", + " 5 Least deprived 54.6 1141 \n", + " Unknown 52.2 322 \n", + "bmi 30+ 56.2 1806 \n", + " under 30 55.5 4417 \n", + "chronic_cardiac_disease no 55.7 6153 \n", + " yes 54.5 77 \n", + "current_copd no 55.8 6174 \n", + " yes 37.5 56 \n", + "dmards no 55.7 6160 \n", + " yes 60.0 70 \n", + "psychosis_schiz_bipolar no 55.7 6167 \n", + " yes 55.6 63 \n", + "ssri no 55.8 6160 \n", + " yes 50.0 70 \n", + "ckd no 56.2 4942 \n", + " yes 53.8 1288 \n", "brand_of_first_dose Oxford-AZ 0.0 0 \n", " Pfizer 0.0 7 \n", - " Unknown 59.6 2856 \n", + " Unknown 61.8 5607 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 52.5 \n", - "sex F 54.7 \n", - " M 50.2 \n", - "ethnicity_6_groups Black 53.7 \n", - " Mixed 52.4 \n", - " Other 48.6 \n", - " South Asian 53.2 \n", - " Unknown 53.3 \n", - " White 55.7 \n", - "ethnicity_16_groups African 60.0 \n", - " Bangladeshi or British Bangladeshi 54.2 \n", - " Caribbean 56.5 \n", - " Chinese 50.0 \n", - " Other 52.4 \n", - " Other Asian 47.8 \n", - " British or Mixed British 56.5 \n", - " Indian or British Indian 50.0 \n", - " Irish 52.0 \n", - " Other Black 59.1 \n", - " Other White 54.5 \n", - " Other mixed 46.2 \n", - " Pakistani or British Pakistani 59.3 \n", - " Unknown 50.7 \n", - " White + Asian 54.2 \n", - " White + Black African 56.5 \n", - " White + Black Caribbean 46.2 \n", - "imd_categories 1 Most deprived 54.0 \n", - " 2 51.1 \n", - " 3 53.6 \n", - " 4 52.3 \n", - " 5 Least deprived 51.9 \n", - " Unknown 52.0 \n", - "bmi 30+ 55.5 \n", - " under 30 51.3 \n", - "chronic_cardiac_disease no 52.8 \n", + "overall overall 54.8 \n", + "sex F 53.7 \n", + " M 55.7 \n", + "ethnicity_6_groups Black 54.7 \n", + " Mixed 52.0 \n", + " Other 56.8 \n", + " South Asian 55.5 \n", + " Unknown 53.7 \n", + " White 54.9 \n", + "ethnicity_16_groups African 52.2 \n", + " Bangladeshi or British Bangladeshi 53.5 \n", + " Caribbean 55.3 \n", + " Chinese 52.4 \n", + " Other 55.3 \n", + " Other Asian 54.5 \n", + " British or Mixed British 54.2 \n", + " Indian or British Indian 54.3 \n", + " Irish 54.2 \n", + " Other Black 57.1 \n", + " Other White 52.0 \n", + " Other mixed 59.1 \n", + " Pakistani or British Pakistani 56.9 \n", + " Unknown 53.7 \n", + " White + Asian 52.1 \n", + " White + Black African 55.6 \n", + " White + Black Caribbean 55.3 \n", + "imd_categories 1 Most deprived 54.9 \n", + " 2 55.8 \n", + " 3 55.5 \n", + " 4 55.6 \n", + " 5 Least deprived 53.4 \n", + " Unknown 50.0 \n", + "bmi 30+ 55.4 \n", + " under 30 54.4 \n", + "chronic_cardiac_disease no 54.7 \n", + " yes 54.5 \n", + "current_copd no 54.8 \n", + " yes 37.5 \n", + "dmards no 54.7 \n", + " yes 60.0 \n", + "psychosis_schiz_bipolar no 54.6 \n", + " yes 55.6 \n", + "ssri no 54.7 \n", " yes 50.0 \n", - "current_copd no 52.7 \n", - " yes 40.0 \n", - "dmards no 52.7 \n", - " yes 40.0 \n", - "psychosis_schiz_bipolar no 52.7 \n", - " yes 40.0 \n", - "ssri no 52.8 \n", - " yes 33.3 \n", - "ckd no 52.6 \n", - " yes 52.4 \n", + "ckd no 55.1 \n", + " yes 52.7 \n", "brand_of_first_dose Oxford-AZ NaN \n", " Pfizer 0.0 \n", - " Unknown 58.6 \n", + " Unknown 60.7 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.1 \n", + "overall overall 1.0 \n", "sex F 1.3 \n", - " M 0.9 \n", - "ethnicity_6_groups Black 0.0 \n", + " M 0.7 \n", + "ethnicity_6_groups Black 1.4 \n", " Mixed 1.3 \n", - " Other 1.4 \n", - " South Asian 0.0 \n", - " Unknown 1.7 \n", - " White 0.0 \n", + " Other 1.3 \n", + " South Asian 0.7 \n", + " Unknown 0.7 \n", + " White 0.7 \n", "ethnicity_16_groups African 0.0 \n", " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 4.4 \n", - " Chinese 0.0 \n", - " Other 0.0 \n", - " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", + " Caribbean 2.1 \n", + " Chinese 2.4 \n", + " Other 4.3 \n", + " Other Asian 2.3 \n", + " British or Mixed British 2.0 \n", " Indian or British Indian 0.0 \n", " Irish 0.0 \n", - " Other Black 0.0 \n", - " Other White 0.0 \n", - " Other mixed 3.8 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 1.5 \n", + " Other Black 2.1 \n", + " Other White 2.0 \n", + " Other mixed 2.3 \n", + " Pakistani or British Pakistani 1.9 \n", + " Unknown 0.7 \n", " White + Asian 0.0 \n", - " White + Black African 0.0 \n", + " White + Black African 1.8 \n", " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 1.2 \n", - " 2 1.1 \n", - " 3 0.0 \n", + "imd_categories 1 Most deprived 0.5 \n", + " 2 0.6 \n", + " 3 1.1 \n", " 4 1.2 \n", " 5 Least deprived 1.2 \n", - " Unknown 4.0 \n", - "bmi 30+ 1.4 \n", - " under 30 0.9 \n", - "chronic_cardiac_disease no 0.9 \n", + " Unknown 2.2 \n", + "bmi 30+ 0.8 \n", + " under 30 1.1 \n", + "chronic_cardiac_disease no 1.0 \n", " yes 0.0 \n", - "current_copd no 0.9 \n", + "current_copd no 1.0 \n", " yes 0.0 \n", - "dmards no 1.1 \n", + "dmards no 1.0 \n", " yes 0.0 \n", "psychosis_schiz_bipolar no 1.1 \n", " yes 0.0 \n", - "ssri no 0.9 \n", - " yes 16.7 \n", - "ckd no 1.0 \n", - " yes 1.2 \n", + "ssri no 1.1 \n", + " yes 0.0 \n", + "ckd no 1.1 \n", + " yes 1.1 \n", "brand_of_first_dose Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 1.0 \n", + " Unknown 1.1 \n", "\n", " Date projected to reach 90% \n", "category group \n", "overall overall unknown \n", "sex F unknown \n", " M unknown \n", - "ethnicity_6_groups Black unknown \n", + "ethnicity_6_groups Black 21-Jul \n", " Mixed unknown \n", - " Other unknown \n", + " Other 23-Jul \n", " South Asian unknown \n", - " Unknown 08-May \n", + " Unknown unknown \n", " White unknown \n", "ethnicity_16_groups African unknown \n", " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean 30-Jan \n", - " Chinese unknown \n", - " Other unknown \n", - " Other Asian unknown \n", - " British or Mixed British unknown \n", + " Caribbean 21-May \n", + " Chinese 15-May \n", + " Other 23-Mar \n", + " Other Asian 14-May \n", + " British or Mixed British 31-May \n", " Indian or British Indian unknown \n", " Irish unknown \n", - " Other Black unknown \n", - " Other White unknown \n", - " Other mixed 26-Feb \n", - " Pakistani or British Pakistani unknown \n", + " Other Black 15-May \n", + " Other White 08-Jun \n", + " Other mixed 30-Apr \n", + " Pakistani or British Pakistani 27-May \n", " Unknown unknown \n", " White + Asian unknown \n", - " White + Black African unknown \n", + " White + Black African 08-Jun \n", " White + Black Caribbean unknown \n", "imd_categories 1 Most deprived unknown \n", " 2 unknown \n", " 3 unknown \n", " 4 unknown \n", " 5 Least deprived unknown \n", - " Unknown 12-Feb \n", - "bmi 30+ 29-May \n", + " Unknown 02-Jun \n", + "bmi 30+ unknown \n", " under 30 unknown \n", "chronic_cardiac_disease no unknown \n", " yes unknown \n", @@ -19813,7 +19902,7 @@ "psychosis_schiz_bipolar no unknown \n", " yes unknown \n", "ssri no unknown \n", - " yes 31-Dec \n", + " yes unknown \n", "ckd no unknown \n", " yes unknown \n", "brand_of_first_dose Oxford-AZ unknown \n", @@ -19847,7 +19936,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **50-54** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **50-54** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -19913,431 +20002,440 @@ " \n", " overall\n", " overall\n", - " 1778\n", - " 51.4\n", - " 3458\n", - " 50.6\n", - " 0.8\n", + " 3647\n", + " 54.2\n", + " 6727\n", + " 53.2\n", + " 1.0\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 924\n", - " 52.2\n", - " 1771\n", - " 51.4\n", - " 0.8\n", + " 1855\n", + " 54.5\n", + " 3402\n", + " 53.5\n", + " 1.0\n", " unknown\n", " \n", " \n", " M\n", - " 854\n", - " 50.6\n", - " 1687\n", - " 49.8\n", - " 0.8\n", + " 1799\n", + " 54.1\n", + " 3325\n", + " 52.8\n", + " 1.3\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 294\n", - " 49.4\n", - " 595\n", - " 49.4\n", - " 0.0\n", + " 637\n", + " 53.2\n", + " 1197\n", + " 52.0\n", + " 1.2\n", " unknown\n", " \n", " \n", " Mixed\n", - " 294\n", - " 50.0\n", - " 588\n", - " 47.6\n", - " 2.4\n", - " 10-Apr\n", + " 637\n", + " 54.2\n", + " 1176\n", + " 53.6\n", + " 0.6\n", + " unknown\n", " \n", " \n", " Other\n", - " 315\n", - " 51.1\n", - " 616\n", - " 51.1\n", - " 0.0\n", + " 609\n", + " 54.4\n", + " 1120\n", + " 53.1\n", + " 1.3\n", " unknown\n", " \n", " \n", " South Asian\n", - " 294\n", - " 52.5\n", - " 560\n", - " 52.5\n", - " 0.0\n", + " 588\n", + " 54.5\n", + " 1078\n", + " 53.2\n", + " 1.3\n", " unknown\n", " \n", " \n", " Unknown\n", - " 273\n", - " 52.0\n", - " 525\n", - " 50.7\n", - " 1.3\n", - " unknown\n", + " 532\n", + " 53.5\n", + " 994\n", + " 51.4\n", + " 2.1\n", + " 03-Jun\n", " \n", " \n", " White\n", - " 308\n", - " 53.7\n", - " 574\n", - " 52.4\n", - " 1.3\n", + " 651\n", + " 56.0\n", + " 1162\n", + " 54.8\n", + " 1.2\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 98\n", - " 48.3\n", - " 203\n", - " 48.3\n", + " 189\n", + " 51.9\n", + " 364\n", + " 51.9\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 84\n", - " 50.0\n", - " 168\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 54.0\n", + " 350\n", + " 52.0\n", + " 2.0\n", + " 08-Jun\n", " \n", " \n", " Caribbean\n", - " 105\n", - " 55.6\n", - " 189\n", - " 55.6\n", - " 0.0\n", - " unknown\n", + " 196\n", + " 56.0\n", + " 350\n", + " 54.0\n", + " 2.0\n", + " 01-Jun\n", " \n", " \n", " Chinese\n", - " 105\n", - " 57.7\n", - " 182\n", - " 57.7\n", - " 0.0\n", - " unknown\n", + " 196\n", + " 57.1\n", + " 343\n", + " 55.1\n", + " 2.0\n", + " 28-May\n", " \n", " \n", " Other\n", - " 105\n", - " 55.6\n", - " 189\n", - " 51.9\n", - " 3.7\n", - " 18-Feb\n", - " \n", - " \n", - " Other Asian\n", - " 84\n", - " 46.2\n", " 182\n", - " 46.2\n", + " 52.0\n", + " 350\n", + " 52.0\n", " 0.0\n", " unknown\n", " \n", " \n", + " Other Asian\n", + " 203\n", + " 53.7\n", + " 378\n", + " 51.9\n", + " 1.8\n", + " 23-Jun\n", + " \n", + " \n", " British or Mixed British\n", - " 84\n", - " 42.9\n", " 196\n", - " 42.9\n", - " 0.0\n", - " unknown\n", + " 56.0\n", + " 350\n", + " 54.0\n", + " 2.0\n", + " 01-Jun\n", " \n", " \n", " Indian or British Indian\n", - " 84\n", - " 46.2\n", - " 182\n", - " 46.2\n", + " 224\n", + " 57.1\n", + " 392\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 91\n", - " 50.0\n", - " 182\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 55.1\n", + " 343\n", + " 53.1\n", + " 2.0\n", + " 04-Jun\n", " \n", " \n", " Other Black\n", - " 84\n", - " 48.0\n", - " 175\n", - " 48.0\n", + " 203\n", + " 55.8\n", + " 364\n", + " 55.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 84\n", - " 48.0\n", - " 175\n", - " 48.0\n", + " 168\n", + " 49.0\n", + " 343\n", + " 49.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 91\n", - " 54.2\n", - " 168\n", - " 54.2\n", + " 175\n", + " 50.0\n", + " 350\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 105\n", - " 57.7\n", - " 182\n", - " 57.7\n", - " 0.0\n", - " unknown\n", + " 217\n", + " 57.4\n", + " 378\n", + " 55.6\n", + " 1.8\n", + " 08-Jun\n", " \n", " \n", " Unknown\n", - " 280\n", - " 56.3\n", - " 497\n", - " 54.9\n", + " 560\n", + " 55.2\n", + " 1015\n", + " 53.8\n", " 1.4\n", - " 01-Jun\n", + " 26-Jul\n", " \n", " \n", " White + Asian\n", - " 91\n", - " 48.1\n", - " 189\n", - " 48.1\n", + " 168\n", + " 48.0\n", + " 350\n", + " 48.0\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black African\n", - " 112\n", - " 51.6\n", - " 217\n", - " 51.6\n", + " 189\n", + " 54.0\n", + " 350\n", + " 54.0\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 91\n", - " 54.2\n", - " 168\n", - " 50.0\n", - " 4.2\n", - " 12-Feb\n", + " 203\n", + " 55.8\n", + " 364\n", + " 53.8\n", + " 2.0\n", + " 01-Jun\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 343\n", - " 50.0\n", - " 686\n", - " 49.0\n", - " 1.0\n", - " unknown\n", + " 693\n", + " 54.4\n", + " 1274\n", + " 52.7\n", + " 1.7\n", + " 28-Jun\n", " \n", " \n", " 2\n", - " 336\n", - " 50.5\n", - " 665\n", - " 50.5\n", - " 0.0\n", - " unknown\n", + " 700\n", + " 53.8\n", + " 1302\n", + " 52.2\n", + " 1.6\n", + " 10-Jul\n", " \n", " \n", " 3\n", - " 329\n", - " 51.6\n", - " 637\n", - " 51.6\n", - " 0.0\n", + " 686\n", + " 54.7\n", + " 1253\n", + " 53.6\n", + " 1.1\n", " unknown\n", " \n", " \n", " 4\n", - " 343\n", - " 52.7\n", - " 651\n", - " 51.6\n", - " 1.1\n", + " 707\n", + " 56.1\n", + " 1260\n", + " 55.6\n", + " 0.5\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 329\n", - " 51.6\n", - " 637\n", - " 49.5\n", - " 2.1\n", - " 22-Apr\n", + " 651\n", + " 51.4\n", + " 1267\n", + " 50.8\n", + " 0.6\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 98\n", - " 56.0\n", - " 175\n", - " 56.0\n", + " 210\n", + " 55.6\n", + " 378\n", + " 55.6\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 532\n", - " 53.1\n", - " 1001\n", - " 51.7\n", - " 1.4\n", + " 1071\n", + " 54.6\n", + " 1960\n", + " 53.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " under 30\n", - " 1246\n", - " 50.7\n", - " 2457\n", - " 50.1\n", - " 0.6\n", + " 2583\n", + " 54.2\n", + " 4767\n", + " 53.0\n", + " 1.2\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1764\n", - " 51.4\n", - " 3430\n", - " 50.4\n", + " 3619\n", + " 54.3\n", + " 6664\n", + " 53.3\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 35\n", + " 55.6\n", + " 63\n", + " 55.6\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1764\n", - " 51.5\n", - " 3423\n", - " 50.7\n", - " 0.8\n", + " 3612\n", + " 54.3\n", + " 6650\n", + " 53.2\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 42\n", + " 54.5\n", + " 77\n", + " 54.5\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1764\n", - " 51.4\n", - " 3430\n", - " 50.6\n", - " 0.8\n", + " 3619\n", + " 54.3\n", + " 6664\n", + " 53.3\n", + " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", " 28\n", " 50.0\n", + " 56\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1764\n", - " 51.5\n", - " 3423\n", - " 50.7\n", - " 0.8\n", + " 3612\n", + " 54.3\n", + " 6657\n", + " 53.2\n", + " 1.1\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", " 35\n", - " 40.0\n", + " 50.0\n", + " 70\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1757\n", - " 51.4\n", - " 3416\n", - " 50.6\n", - " 0.8\n", + " 3612\n", + " 54.3\n", + " 6657\n", + " 53.1\n", + " 1.2\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 42\n", + " 66.7\n", + " 63\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1421\n", - " 51.0\n", - " 2786\n", - " 50.0\n", + " 2926\n", + " 54.4\n", + " 5376\n", + " 53.4\n", " 1.0\n", " unknown\n", " \n", " \n", " yes\n", - " 357\n", - " 53.1\n", - " 672\n", - " 53.1\n", + " 728\n", + " 53.9\n", + " 1351\n", + " 52.3\n", + " 1.6\n", + " 09-Jul\n", + " \n", + " \n", + " brand_of_first_dose\n", + " Moderna\n", + " 0\n", + " 0.0\n", + " 0\n", + " NaN\n", " 0.0\n", " unknown\n", " \n", " \n", - " brand_of_first_dose\n", " Oxford-AZ\n", " 0\n", " 0.0\n", @@ -20357,12 +20455,12 @@ " \n", " \n", " Unknown\n", - " 1771\n", - " 57.6\n", - " 3073\n", - " 56.7\n", - " 0.9\n", - " unknown\n", + " 3640\n", + " 60.7\n", + " 5999\n", + " 59.5\n", + " 1.2\n", + " 22-Jul\n", " \n", " \n", "\n", @@ -20371,211 +20469,215 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1778 \n", - "sex F 924 \n", - " M 854 \n", - "ethnicity_6_groups Black 294 \n", - " Mixed 294 \n", - " Other 315 \n", - " South Asian 294 \n", - " Unknown 273 \n", - " White 308 \n", - "ethnicity_16_groups African 98 \n", - " Bangladeshi or British Bangladeshi 84 \n", - " Caribbean 105 \n", - " Chinese 105 \n", - " Other 105 \n", - " Other Asian 84 \n", - " British or Mixed British 84 \n", - " Indian or British Indian 84 \n", - " Irish 91 \n", - " Other Black 84 \n", - " Other White 84 \n", - " Other mixed 91 \n", - " Pakistani or British Pakistani 105 \n", - " Unknown 280 \n", - " White + Asian 91 \n", - " White + Black African 112 \n", - " White + Black Caribbean 91 \n", - "imd_categories 1 Most deprived 343 \n", - " 2 336 \n", - " 3 329 \n", - " 4 343 \n", - " 5 Least deprived 329 \n", - " Unknown 98 \n", - "bmi 30+ 532 \n", - " under 30 1246 \n", - "chronic_cardiac_disease no 1764 \n", - " yes 14 \n", - "current_copd no 1764 \n", - " yes 14 \n", - "dmards no 1764 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1764 \n", - " yes 14 \n", - "ssri no 1757 \n", - " yes 21 \n", - "ckd no 1421 \n", - " yes 357 \n", - "brand_of_first_dose Oxford-AZ 0 \n", + "overall overall 3647 \n", + "sex F 1855 \n", + " M 1799 \n", + "ethnicity_6_groups Black 637 \n", + " Mixed 637 \n", + " Other 609 \n", + " South Asian 588 \n", + " Unknown 532 \n", + " White 651 \n", + "ethnicity_16_groups African 189 \n", + " Bangladeshi or British Bangladeshi 189 \n", + " Caribbean 196 \n", + " Chinese 196 \n", + " Other 182 \n", + " Other Asian 203 \n", + " British or Mixed British 196 \n", + " Indian or British Indian 224 \n", + " Irish 189 \n", + " Other Black 203 \n", + " Other White 168 \n", + " Other mixed 175 \n", + " Pakistani or British Pakistani 217 \n", + " Unknown 560 \n", + " White + Asian 168 \n", + " White + Black African 189 \n", + " White + Black Caribbean 203 \n", + "imd_categories 1 Most deprived 693 \n", + " 2 700 \n", + " 3 686 \n", + " 4 707 \n", + " 5 Least deprived 651 \n", + " Unknown 210 \n", + "bmi 30+ 1071 \n", + " under 30 2583 \n", + "chronic_cardiac_disease no 3619 \n", + " yes 35 \n", + "current_copd no 3612 \n", + " yes 42 \n", + "dmards no 3619 \n", + " yes 28 \n", + "psychosis_schiz_bipolar no 3612 \n", + " yes 35 \n", + "ssri no 3612 \n", + " yes 42 \n", + "ckd no 2926 \n", + " yes 728 \n", + "brand_of_first_dose Moderna 0 \n", + " Oxford-AZ 0 \n", " Pfizer 0 \n", - " Unknown 1771 \n", + " Unknown 3640 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 51.4 3458 \n", - "sex F 52.2 1771 \n", - " M 50.6 1687 \n", - "ethnicity_6_groups Black 49.4 595 \n", - " Mixed 50.0 588 \n", - " Other 51.1 616 \n", - " South Asian 52.5 560 \n", - " Unknown 52.0 525 \n", - " White 53.7 574 \n", - "ethnicity_16_groups African 48.3 203 \n", - " Bangladeshi or British Bangladeshi 50.0 168 \n", - " Caribbean 55.6 189 \n", - " Chinese 57.7 182 \n", - " Other 55.6 189 \n", - " Other Asian 46.2 182 \n", - " British or Mixed British 42.9 196 \n", - " Indian or British Indian 46.2 182 \n", - " Irish 50.0 182 \n", - " Other Black 48.0 175 \n", - " Other White 48.0 175 \n", - " Other mixed 54.2 168 \n", - " Pakistani or British Pakistani 57.7 182 \n", - " Unknown 56.3 497 \n", - " White + Asian 48.1 189 \n", - " White + Black African 51.6 217 \n", - " White + Black Caribbean 54.2 168 \n", - "imd_categories 1 Most deprived 50.0 686 \n", - " 2 50.5 665 \n", - " 3 51.6 637 \n", - " 4 52.7 651 \n", - " 5 Least deprived 51.6 637 \n", - " Unknown 56.0 175 \n", - "bmi 30+ 53.1 1001 \n", - " under 30 50.7 2457 \n", - "chronic_cardiac_disease no 51.4 3430 \n", - " yes 50.0 28 \n", - "current_copd no 51.5 3423 \n", - " yes 40.0 35 \n", - "dmards no 51.4 3430 \n", - " yes 50.0 28 \n", - "psychosis_schiz_bipolar no 51.5 3423 \n", - " yes 40.0 35 \n", - "ssri no 51.4 3416 \n", - " yes 60.0 35 \n", - "ckd no 51.0 2786 \n", - " yes 53.1 672 \n", - "brand_of_first_dose Oxford-AZ 0.0 0 \n", + "overall overall 54.2 6727 \n", + "sex F 54.5 3402 \n", + " M 54.1 3325 \n", + "ethnicity_6_groups Black 53.2 1197 \n", + " Mixed 54.2 1176 \n", + " Other 54.4 1120 \n", + " South Asian 54.5 1078 \n", + " Unknown 53.5 994 \n", + " White 56.0 1162 \n", + "ethnicity_16_groups African 51.9 364 \n", + " Bangladeshi or British Bangladeshi 54.0 350 \n", + " Caribbean 56.0 350 \n", + " Chinese 57.1 343 \n", + " Other 52.0 350 \n", + " Other Asian 53.7 378 \n", + " British or Mixed British 56.0 350 \n", + " Indian or British Indian 57.1 392 \n", + " Irish 55.1 343 \n", + " Other Black 55.8 364 \n", + " Other White 49.0 343 \n", + " Other mixed 50.0 350 \n", + " Pakistani or British Pakistani 57.4 378 \n", + " Unknown 55.2 1015 \n", + " White + Asian 48.0 350 \n", + " White + Black African 54.0 350 \n", + " White + Black Caribbean 55.8 364 \n", + "imd_categories 1 Most deprived 54.4 1274 \n", + " 2 53.8 1302 \n", + " 3 54.7 1253 \n", + " 4 56.1 1260 \n", + " 5 Least deprived 51.4 1267 \n", + " Unknown 55.6 378 \n", + "bmi 30+ 54.6 1960 \n", + " under 30 54.2 4767 \n", + "chronic_cardiac_disease no 54.3 6664 \n", + " yes 55.6 63 \n", + "current_copd no 54.3 6650 \n", + " yes 54.5 77 \n", + "dmards no 54.3 6664 \n", + " yes 50.0 56 \n", + "psychosis_schiz_bipolar no 54.3 6657 \n", + " yes 50.0 70 \n", + "ssri no 54.3 6657 \n", + " yes 66.7 63 \n", + "ckd no 54.4 5376 \n", + " yes 53.9 1351 \n", + "brand_of_first_dose Moderna 0.0 0 \n", + " Oxford-AZ 0.0 0 \n", " Pfizer 0.0 7 \n", - " Unknown 57.6 3073 \n", + " Unknown 60.7 5999 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 50.6 \n", - "sex F 51.4 \n", - " M 49.8 \n", - "ethnicity_6_groups Black 49.4 \n", - " Mixed 47.6 \n", - " Other 51.1 \n", - " South Asian 52.5 \n", - " Unknown 50.7 \n", - " White 52.4 \n", - "ethnicity_16_groups African 48.3 \n", - " Bangladeshi or British Bangladeshi 50.0 \n", - " Caribbean 55.6 \n", - " Chinese 57.7 \n", - " Other 51.9 \n", - " Other Asian 46.2 \n", - " British or Mixed British 42.9 \n", - " Indian or British Indian 46.2 \n", - " Irish 50.0 \n", - " Other Black 48.0 \n", - " Other White 48.0 \n", - " Other mixed 54.2 \n", - " Pakistani or British Pakistani 57.7 \n", - " Unknown 54.9 \n", - " White + Asian 48.1 \n", - " White + Black African 51.6 \n", - " White + Black Caribbean 50.0 \n", - "imd_categories 1 Most deprived 49.0 \n", - " 2 50.5 \n", - " 3 51.6 \n", - " 4 51.6 \n", - " 5 Least deprived 49.5 \n", - " Unknown 56.0 \n", - "bmi 30+ 51.7 \n", - " under 30 50.1 \n", - "chronic_cardiac_disease no 50.4 \n", + "overall overall 53.2 \n", + "sex F 53.5 \n", + " M 52.8 \n", + "ethnicity_6_groups Black 52.0 \n", + " Mixed 53.6 \n", + " Other 53.1 \n", + " South Asian 53.2 \n", + " Unknown 51.4 \n", + " White 54.8 \n", + "ethnicity_16_groups African 51.9 \n", + " Bangladeshi or British Bangladeshi 52.0 \n", + " Caribbean 54.0 \n", + " Chinese 55.1 \n", + " Other 52.0 \n", + " Other Asian 51.9 \n", + " British or Mixed British 54.0 \n", + " Indian or British Indian 57.1 \n", + " Irish 53.1 \n", + " Other Black 55.8 \n", + " Other White 49.0 \n", + " Other mixed 50.0 \n", + " Pakistani or British Pakistani 55.6 \n", + " Unknown 53.8 \n", + " White + Asian 48.0 \n", + " White + Black African 54.0 \n", + " White + Black Caribbean 53.8 \n", + "imd_categories 1 Most deprived 52.7 \n", + " 2 52.2 \n", + " 3 53.6 \n", + " 4 55.6 \n", + " 5 Least deprived 50.8 \n", + " Unknown 55.6 \n", + "bmi 30+ 53.6 \n", + " under 30 53.0 \n", + "chronic_cardiac_disease no 53.3 \n", + " yes 55.6 \n", + "current_copd no 53.2 \n", + " yes 54.5 \n", + "dmards no 53.3 \n", " yes 50.0 \n", - "current_copd no 50.7 \n", - " yes 40.0 \n", - "dmards no 50.6 \n", + "psychosis_schiz_bipolar no 53.2 \n", " yes 50.0 \n", - "psychosis_schiz_bipolar no 50.7 \n", - " yes 40.0 \n", - "ssri no 50.6 \n", - " yes 60.0 \n", - "ckd no 50.0 \n", - " yes 53.1 \n", - "brand_of_first_dose Oxford-AZ NaN \n", + "ssri no 53.1 \n", + " yes 66.7 \n", + "ckd no 53.4 \n", + " yes 52.3 \n", + "brand_of_first_dose Moderna NaN \n", + " Oxford-AZ NaN \n", " Pfizer 0.0 \n", - " Unknown 56.7 \n", + " Unknown 59.5 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 0.8 \n", - "sex F 0.8 \n", - " M 0.8 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 2.4 \n", - " Other 0.0 \n", - " South Asian 0.0 \n", - " Unknown 1.3 \n", - " White 1.3 \n", + "overall overall 1.0 \n", + "sex F 1.0 \n", + " M 1.3 \n", + "ethnicity_6_groups Black 1.2 \n", + " Mixed 0.6 \n", + " Other 1.3 \n", + " South Asian 1.3 \n", + " Unknown 2.1 \n", + " White 1.2 \n", "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", - " Chinese 0.0 \n", - " Other 3.7 \n", - " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", + " Bangladeshi or British Bangladeshi 2.0 \n", + " Caribbean 2.0 \n", + " Chinese 2.0 \n", + " Other 0.0 \n", + " Other Asian 1.8 \n", + " British or Mixed British 2.0 \n", " Indian or British Indian 0.0 \n", - " Irish 0.0 \n", + " Irish 2.0 \n", " Other Black 0.0 \n", " Other White 0.0 \n", " Other mixed 0.0 \n", - " Pakistani or British Pakistani 0.0 \n", + " Pakistani or British Pakistani 1.8 \n", " Unknown 1.4 \n", " White + Asian 0.0 \n", " White + Black African 0.0 \n", - " White + Black Caribbean 4.2 \n", - "imd_categories 1 Most deprived 1.0 \n", - " 2 0.0 \n", - " 3 0.0 \n", - " 4 1.1 \n", - " 5 Least deprived 2.1 \n", + " White + Black Caribbean 2.0 \n", + "imd_categories 1 Most deprived 1.7 \n", + " 2 1.6 \n", + " 3 1.1 \n", + " 4 0.5 \n", + " 5 Least deprived 0.6 \n", " Unknown 0.0 \n", - "bmi 30+ 1.4 \n", - " under 30 0.6 \n", + "bmi 30+ 1.0 \n", + " under 30 1.2 \n", "chronic_cardiac_disease no 1.0 \n", " yes 0.0 \n", - "current_copd no 0.8 \n", + "current_copd no 1.1 \n", " yes 0.0 \n", - "dmards no 0.8 \n", + "dmards no 1.0 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 0.8 \n", + "psychosis_schiz_bipolar no 1.1 \n", " yes 0.0 \n", - "ssri no 0.8 \n", + "ssri no 1.2 \n", " yes 0.0 \n", "ckd no 1.0 \n", - " yes 0.0 \n", - "brand_of_first_dose Oxford-AZ 0.0 \n", + " yes 1.6 \n", + "brand_of_first_dose Moderna 0.0 \n", + " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 0.9 \n", + " Unknown 1.2 \n", "\n", " Date projected to reach 90% \n", "category group \n", @@ -20583,33 +20685,33 @@ "sex F unknown \n", " M unknown \n", "ethnicity_6_groups Black unknown \n", - " Mixed 10-Apr \n", + " Mixed unknown \n", " Other unknown \n", " South Asian unknown \n", - " Unknown unknown \n", + " Unknown 03-Jun \n", " White unknown \n", "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean unknown \n", - " Chinese unknown \n", - " Other 18-Feb \n", - " Other Asian unknown \n", - " British or Mixed British unknown \n", + " Bangladeshi or British Bangladeshi 08-Jun \n", + " Caribbean 01-Jun \n", + " Chinese 28-May \n", + " Other unknown \n", + " Other Asian 23-Jun \n", + " British or Mixed British 01-Jun \n", " Indian or British Indian unknown \n", - " Irish unknown \n", + " Irish 04-Jun \n", " Other Black unknown \n", " Other White unknown \n", " Other mixed unknown \n", - " Pakistani or British Pakistani unknown \n", - " Unknown 01-Jun \n", + " Pakistani or British Pakistani 08-Jun \n", + " Unknown 26-Jul \n", " White + Asian unknown \n", " White + Black African unknown \n", - " White + Black Caribbean 12-Feb \n", - "imd_categories 1 Most deprived unknown \n", - " 2 unknown \n", + " White + Black Caribbean 01-Jun \n", + "imd_categories 1 Most deprived 28-Jun \n", + " 2 10-Jul \n", " 3 unknown \n", " 4 unknown \n", - " 5 Least deprived 22-Apr \n", + " 5 Least deprived unknown \n", " Unknown unknown \n", "bmi 30+ unknown \n", " under 30 unknown \n", @@ -20624,10 +20726,11 @@ "ssri no unknown \n", " yes unknown \n", "ckd no unknown \n", - " yes unknown \n", - "brand_of_first_dose Oxford-AZ unknown \n", + " yes 09-Jul \n", + "brand_of_first_dose Moderna unknown \n", + " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown unknown " + " Unknown 22-Jul " ] }, "metadata": {}, @@ -20656,7 +20759,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **40-49** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **40-49** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -20722,427 +20825,427 @@ " \n", " overall\n", " overall\n", - " 3269\n", - " 53.2\n", - " 6139\n", - " 52.1\n", - " 1.1\n", + " 6734\n", + " 54.9\n", + " 12257\n", + " 54.1\n", + " 0.8\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 1666\n", - " 52.7\n", - " 3164\n", - " 51.3\n", - " 1.4\n", + " 3521\n", + " 55.1\n", + " 6391\n", + " 54.3\n", + " 0.8\n", " unknown\n", " \n", " \n", " M\n", - " 1610\n", - " 54.1\n", - " 2975\n", - " 52.7\n", - " 1.4\n", + " 3213\n", + " 54.8\n", + " 5866\n", + " 53.8\n", + " 1.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 525\n", - " 52.1\n", - " 1008\n", - " 51.4\n", - " 0.7\n", + " 1162\n", + " 55.5\n", + " 2093\n", + " 54.5\n", + " 1.0\n", " unknown\n", " \n", " \n", " Mixed\n", - " 581\n", - " 55.0\n", - " 1057\n", - " 53.6\n", - " 1.4\n", + " 1134\n", + " 54.4\n", + " 2086\n", + " 53.4\n", + " 1.0\n", " unknown\n", " \n", " \n", " Other\n", - " 553\n", - " 54.1\n", - " 1022\n", - " 52.7\n", + " 1099\n", + " 53.4\n", + " 2058\n", + " 52.0\n", " 1.4\n", " unknown\n", " \n", " \n", " South Asian\n", - " 574\n", - " 54.3\n", - " 1057\n", - " 53.0\n", - " 1.3\n", + " 1134\n", + " 55.1\n", + " 2058\n", + " 54.1\n", + " 1.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 455\n", - " 50.4\n", - " 903\n", - " 49.6\n", - " 0.8\n", + " 1078\n", + " 56.8\n", + " 1897\n", + " 56.1\n", + " 0.7\n", " unknown\n", " \n", " \n", " White\n", - " 574\n", - " 52.6\n", - " 1092\n", - " 51.9\n", + " 1134\n", + " 54.9\n", + " 2065\n", + " 54.2\n", " 0.7\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 168\n", - " 52.2\n", - " 322\n", - " 52.2\n", + " 364\n", + " 57.1\n", + " 637\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 168\n", - " 54.5\n", - " 308\n", - " 52.3\n", - " 2.2\n", - " 06-Apr\n", + " 329\n", + " 51.1\n", + " 644\n", + " 50.0\n", + " 1.1\n", + " unknown\n", " \n", " \n", " Caribbean\n", - " 168\n", - " 52.2\n", - " 322\n", - " 52.2\n", - " 0.0\n", + " 399\n", + " 55.9\n", + " 714\n", + " 54.9\n", + " 1.0\n", " unknown\n", " \n", " \n", " Chinese\n", - " 196\n", - " 57.1\n", " 343\n", - " 55.1\n", - " 2.0\n", - " 09-Apr\n", + " 53.8\n", + " 637\n", + " 52.7\n", + " 1.1\n", + " unknown\n", " \n", " \n", " Other\n", - " 175\n", - " 50.0\n", - " 350\n", - " 50.0\n", - " 0.0\n", + " 371\n", + " 54.6\n", + " 679\n", + " 53.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 175\n", - " 53.2\n", - " 329\n", - " 53.2\n", - " 0.0\n", + " 336\n", + " 53.9\n", + " 623\n", + " 52.8\n", + " 1.1\n", " unknown\n", " \n", " \n", " British or Mixed British\n", - " 175\n", - " 51.0\n", - " 343\n", - " 51.0\n", - " 0.0\n", + " 357\n", + " 55.4\n", + " 644\n", + " 54.3\n", + " 1.1\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 161\n", - " 54.8\n", - " 294\n", - " 52.4\n", - " 2.4\n", - " 27-Mar\n", + " 357\n", + " 55.4\n", + " 644\n", + " 53.3\n", + " 2.1\n", + " 28-May\n", " \n", " \n", " Irish\n", - " 182\n", - " 53.1\n", - " 343\n", - " 53.1\n", - " 0.0\n", + " 399\n", + " 57.6\n", + " 693\n", + " 56.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 189\n", - " 57.4\n", - " 329\n", - " 55.3\n", - " 2.1\n", - " 02-Apr\n", + " 357\n", + " 53.1\n", + " 672\n", + " 53.1\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other White\n", - " 175\n", - " 55.6\n", - " 315\n", - " 55.6\n", - " 0.0\n", + " 385\n", + " 56.1\n", + " 686\n", + " 55.1\n", + " 1.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 154\n", - " 50.0\n", - " 308\n", - " 47.7\n", - " 2.3\n", - " 15-Apr\n", + " 357\n", + " 56.7\n", + " 630\n", + " 56.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 154\n", - " 47.8\n", - " 322\n", - " 47.8\n", - " 0.0\n", + " 343\n", + " 55.7\n", + " 616\n", + " 54.5\n", + " 1.2\n", " unknown\n", " \n", " \n", " Unknown\n", - " 511\n", - " 54.5\n", - " 938\n", - " 53.7\n", - " 0.8\n", + " 994\n", + " 54.6\n", + " 1820\n", + " 53.5\n", + " 1.1\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 182\n", - " 56.5\n", - " 322\n", - " 54.3\n", - " 2.2\n", - " 31-Mar\n", + " 315\n", + " 52.9\n", + " 595\n", + " 52.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black African\n", - " 168\n", - " 52.2\n", - " 322\n", - " 52.2\n", - " 0.0\n", + " 357\n", + " 54.8\n", + " 651\n", + " 53.8\n", + " 1.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 161\n", - " 48.9\n", - " 329\n", - " 48.9\n", - " 0.0\n", + " 378\n", + " 56.8\n", + " 665\n", + " 55.8\n", + " 1.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 581\n", - " 49.7\n", - " 1169\n", - " 49.1\n", - " 0.6\n", + " 1281\n", + " 55.1\n", + " 2324\n", + " 53.9\n", + " 1.2\n", " unknown\n", " \n", " \n", " 2\n", - " 623\n", - " 54.3\n", - " 1148\n", - " 52.4\n", - " 1.9\n", - " 25-Apr\n", + " 1295\n", + " 56.1\n", + " 2310\n", + " 55.2\n", + " 0.9\n", + " unknown\n", " \n", " \n", " 3\n", - " 623\n", - " 53.6\n", - " 1162\n", - " 53.0\n", - " 0.6\n", + " 1253\n", + " 53.8\n", + " 2331\n", + " 52.9\n", + " 0.9\n", " unknown\n", " \n", " \n", " 4\n", - " 609\n", - " 52.7\n", - " 1155\n", - " 51.5\n", - " 1.2\n", + " 1267\n", + " 54.5\n", + " 2324\n", + " 53.9\n", + " 0.6\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 665\n", - " 55.6\n", - " 1197\n", - " 53.8\n", - " 1.8\n", - " 27-Apr\n", + " 1302\n", + " 55.4\n", + " 2352\n", + " 54.5\n", + " 0.9\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 161\n", - " 53.5\n", - " 301\n", - " 53.5\n", - " 0.0\n", + " 336\n", + " 54.5\n", + " 616\n", + " 53.4\n", + " 1.1\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 1015\n", - " 53.5\n", - " 1897\n", - " 52.0\n", - " 1.5\n", - " 03-Jun\n", + " 2058\n", + " 56.2\n", + " 3661\n", + " 55.3\n", + " 0.9\n", + " unknown\n", " \n", " \n", " under 30\n", - " 2261\n", - " 53.3\n", - " 4242\n", - " 52.1\n", - " 1.2\n", + " 4683\n", + " 54.5\n", + " 8589\n", + " 53.5\n", + " 1.0\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 3234\n", - " 53.2\n", - " 6076\n", - " 52.1\n", - " 1.1\n", + " 6657\n", + " 54.9\n", + " 12117\n", + " 54.0\n", + " 0.9\n", " unknown\n", " \n", " \n", " yes\n", - " 35\n", - " 55.6\n", - " 63\n", - " 55.6\n", + " 84\n", + " 60.0\n", + " 140\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 3241\n", - " 53.3\n", - " 6076\n", - " 52.1\n", - " 1.2\n", + " 6671\n", + " 54.9\n", + " 12145\n", + " 54.1\n", + " 0.8\n", " unknown\n", " \n", " \n", " yes\n", - " 35\n", - " 62.5\n", - " 56\n", - " 50.0\n", - " 12.5\n", - " 30-Dec\n", + " 63\n", + " 56.2\n", + " 112\n", + " 56.2\n", + " 0.0\n", + " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 3241\n", - " 53.4\n", - " 6069\n", - " 52.1\n", - " 1.3\n", + " 6664\n", + " 55.0\n", + " 12117\n", + " 54.1\n", + " 0.9\n", " unknown\n", " \n", " \n", " yes\n", - " 35\n", - " 50.0\n", - " 70\n", - " 40.0\n", - " 10.0\n", - " 12-Jan\n", + " 77\n", + " 55.0\n", + " 140\n", + " 55.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 3241\n", - " 53.3\n", - " 6076\n", - " 52.1\n", - " 1.2\n", + " 6678\n", + " 55.0\n", + " 12138\n", + " 54.1\n", + " 0.9\n", " unknown\n", " \n", " \n", " yes\n", - " 28\n", - " 50.0\n", " 56\n", - " 50.0\n", + " 47.1\n", + " 119\n", + " 47.1\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 3255\n", - " 53.4\n", - " 6090\n", - " 52.2\n", - " 1.2\n", + " 6685\n", + " 55.0\n", + " 12159\n", + " 54.1\n", + " 0.9\n", " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 28.6\n", " 49\n", - " 28.6\n", + " 50.0\n", + " 98\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 2604\n", - " 53.4\n", - " 4879\n", - " 52.1\n", - " 1.3\n", + " 5411\n", + " 55.0\n", + " 9835\n", + " 54.1\n", + " 0.9\n", " unknown\n", " \n", " \n", " yes\n", - " 665\n", - " 52.8\n", - " 1260\n", - " 51.7\n", - " 1.1\n", + " 1323\n", + " 54.6\n", + " 2422\n", + " 54.0\n", + " 0.6\n", " unknown\n", " \n", " \n", @@ -21159,28 +21262,28 @@ " Oxford-AZ\n", " 0\n", " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Pfizer\n", - " 0\n", - " 0.0\n", " 7\n", - " 0.0\n", + " 50.0\n", + " 14\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 3262\n", - " 59.1\n", - " 5516\n", - " 57.7\n", - " 1.4\n", - " 18-May\n", + " 6720\n", + " 61.2\n", + " 10983\n", + " 60.2\n", + " 1.0\n", + " unknown\n", " \n", " \n", "\n", @@ -21189,215 +21292,215 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 3269 \n", - "sex F 1666 \n", - " M 1610 \n", - "ethnicity_6_groups Black 525 \n", - " Mixed 581 \n", - " Other 553 \n", - " South Asian 574 \n", - " Unknown 455 \n", - " White 574 \n", - "ethnicity_16_groups African 168 \n", - " Bangladeshi or British Bangladeshi 168 \n", - " Caribbean 168 \n", - " Chinese 196 \n", - " Other 175 \n", - " Other Asian 175 \n", - " British or Mixed British 175 \n", - " Indian or British Indian 161 \n", - " Irish 182 \n", - " Other Black 189 \n", - " Other White 175 \n", - " Other mixed 154 \n", - " Pakistani or British Pakistani 154 \n", - " Unknown 511 \n", - " White + Asian 182 \n", - " White + Black African 168 \n", - " White + Black Caribbean 161 \n", - "imd_categories 1 Most deprived 581 \n", - " 2 623 \n", - " 3 623 \n", - " 4 609 \n", - " 5 Least deprived 665 \n", - " Unknown 161 \n", - "bmi 30+ 1015 \n", - " under 30 2261 \n", - "chronic_cardiac_disease no 3234 \n", - " yes 35 \n", - "current_copd no 3241 \n", - " yes 35 \n", - "dmards no 3241 \n", - " yes 35 \n", - "psychosis_schiz_bipolar no 3241 \n", - " yes 28 \n", - "ssri no 3255 \n", - " yes 14 \n", - "ckd no 2604 \n", - " yes 665 \n", + "overall overall 6734 \n", + "sex F 3521 \n", + " M 3213 \n", + "ethnicity_6_groups Black 1162 \n", + " Mixed 1134 \n", + " Other 1099 \n", + " South Asian 1134 \n", + " Unknown 1078 \n", + " White 1134 \n", + "ethnicity_16_groups African 364 \n", + " Bangladeshi or British Bangladeshi 329 \n", + " Caribbean 399 \n", + " Chinese 343 \n", + " Other 371 \n", + " Other Asian 336 \n", + " British or Mixed British 357 \n", + " Indian or British Indian 357 \n", + " Irish 399 \n", + " Other Black 357 \n", + " Other White 385 \n", + " Other mixed 357 \n", + " Pakistani or British Pakistani 343 \n", + " Unknown 994 \n", + " White + Asian 315 \n", + " White + Black African 357 \n", + " White + Black Caribbean 378 \n", + "imd_categories 1 Most deprived 1281 \n", + " 2 1295 \n", + " 3 1253 \n", + " 4 1267 \n", + " 5 Least deprived 1302 \n", + " Unknown 336 \n", + "bmi 30+ 2058 \n", + " under 30 4683 \n", + "chronic_cardiac_disease no 6657 \n", + " yes 84 \n", + "current_copd no 6671 \n", + " yes 63 \n", + "dmards no 6664 \n", + " yes 77 \n", + "psychosis_schiz_bipolar no 6678 \n", + " yes 56 \n", + "ssri no 6685 \n", + " yes 49 \n", + "ckd no 5411 \n", + " yes 1323 \n", "brand_of_first_dose Moderna 0 \n", " Oxford-AZ 0 \n", - " Pfizer 0 \n", - " Unknown 3262 \n", + " Pfizer 7 \n", + " Unknown 6720 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 53.2 6139 \n", - "sex F 52.7 3164 \n", - " M 54.1 2975 \n", - "ethnicity_6_groups Black 52.1 1008 \n", - " Mixed 55.0 1057 \n", - " Other 54.1 1022 \n", - " South Asian 54.3 1057 \n", - " Unknown 50.4 903 \n", - " White 52.6 1092 \n", - "ethnicity_16_groups African 52.2 322 \n", - " Bangladeshi or British Bangladeshi 54.5 308 \n", - " Caribbean 52.2 322 \n", - " Chinese 57.1 343 \n", - " Other 50.0 350 \n", - " Other Asian 53.2 329 \n", - " British or Mixed British 51.0 343 \n", - " Indian or British Indian 54.8 294 \n", - " Irish 53.1 343 \n", - " Other Black 57.4 329 \n", - " Other White 55.6 315 \n", - " Other mixed 50.0 308 \n", - " Pakistani or British Pakistani 47.8 322 \n", - " Unknown 54.5 938 \n", - " White + Asian 56.5 322 \n", - " White + Black African 52.2 322 \n", - " White + Black Caribbean 48.9 329 \n", - "imd_categories 1 Most deprived 49.7 1169 \n", - " 2 54.3 1148 \n", - " 3 53.6 1162 \n", - " 4 52.7 1155 \n", - " 5 Least deprived 55.6 1197 \n", - " Unknown 53.5 301 \n", - "bmi 30+ 53.5 1897 \n", - " under 30 53.3 4242 \n", - "chronic_cardiac_disease no 53.2 6076 \n", - " yes 55.6 63 \n", - "current_copd no 53.3 6076 \n", - " yes 62.5 56 \n", - "dmards no 53.4 6069 \n", - " yes 50.0 70 \n", - "psychosis_schiz_bipolar no 53.3 6076 \n", - " yes 50.0 56 \n", - "ssri no 53.4 6090 \n", - " yes 28.6 49 \n", - "ckd no 53.4 4879 \n", - " yes 52.8 1260 \n", + "overall overall 54.9 12257 \n", + "sex F 55.1 6391 \n", + " M 54.8 5866 \n", + "ethnicity_6_groups Black 55.5 2093 \n", + " Mixed 54.4 2086 \n", + " Other 53.4 2058 \n", + " South Asian 55.1 2058 \n", + " Unknown 56.8 1897 \n", + " White 54.9 2065 \n", + "ethnicity_16_groups African 57.1 637 \n", + " Bangladeshi or British Bangladeshi 51.1 644 \n", + " Caribbean 55.9 714 \n", + " Chinese 53.8 637 \n", + " Other 54.6 679 \n", + " Other Asian 53.9 623 \n", + " British or Mixed British 55.4 644 \n", + " Indian or British Indian 55.4 644 \n", + " Irish 57.6 693 \n", + " Other Black 53.1 672 \n", + " Other White 56.1 686 \n", + " Other mixed 56.7 630 \n", + " Pakistani or British Pakistani 55.7 616 \n", + " Unknown 54.6 1820 \n", + " White + Asian 52.9 595 \n", + " White + Black African 54.8 651 \n", + " White + Black Caribbean 56.8 665 \n", + "imd_categories 1 Most deprived 55.1 2324 \n", + " 2 56.1 2310 \n", + " 3 53.8 2331 \n", + " 4 54.5 2324 \n", + " 5 Least deprived 55.4 2352 \n", + " Unknown 54.5 616 \n", + "bmi 30+ 56.2 3661 \n", + " under 30 54.5 8589 \n", + "chronic_cardiac_disease no 54.9 12117 \n", + " yes 60.0 140 \n", + "current_copd no 54.9 12145 \n", + " yes 56.2 112 \n", + "dmards no 55.0 12117 \n", + " yes 55.0 140 \n", + "psychosis_schiz_bipolar no 55.0 12138 \n", + " yes 47.1 119 \n", + "ssri no 55.0 12159 \n", + " yes 50.0 98 \n", + "ckd no 55.0 9835 \n", + " yes 54.6 2422 \n", "brand_of_first_dose Moderna 0.0 0 \n", - " Oxford-AZ 0.0 0 \n", - " Pfizer 0.0 7 \n", - " Unknown 59.1 5516 \n", + " Oxford-AZ 0.0 7 \n", + " Pfizer 50.0 14 \n", + " Unknown 61.2 10983 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 52.1 \n", - "sex F 51.3 \n", - " M 52.7 \n", - "ethnicity_6_groups Black 51.4 \n", - " Mixed 53.6 \n", - " Other 52.7 \n", - " South Asian 53.0 \n", - " Unknown 49.6 \n", - " White 51.9 \n", - "ethnicity_16_groups African 52.2 \n", - " Bangladeshi or British Bangladeshi 52.3 \n", - " Caribbean 52.2 \n", - " Chinese 55.1 \n", - " Other 50.0 \n", - " Other Asian 53.2 \n", - " British or Mixed British 51.0 \n", - " Indian or British Indian 52.4 \n", - " Irish 53.1 \n", - " Other Black 55.3 \n", - " Other White 55.6 \n", - " Other mixed 47.7 \n", - " Pakistani or British Pakistani 47.8 \n", - " Unknown 53.7 \n", - " White + Asian 54.3 \n", - " White + Black African 52.2 \n", - " White + Black Caribbean 48.9 \n", - "imd_categories 1 Most deprived 49.1 \n", - " 2 52.4 \n", - " 3 53.0 \n", - " 4 51.5 \n", - " 5 Least deprived 53.8 \n", + "overall overall 54.1 \n", + "sex F 54.3 \n", + " M 53.8 \n", + "ethnicity_6_groups Black 54.5 \n", + " Mixed 53.4 \n", + " Other 52.0 \n", + " South Asian 54.1 \n", + " Unknown 56.1 \n", + " White 54.2 \n", + "ethnicity_16_groups African 57.1 \n", + " Bangladeshi or British Bangladeshi 50.0 \n", + " Caribbean 54.9 \n", + " Chinese 52.7 \n", + " Other 53.6 \n", + " Other Asian 52.8 \n", + " British or Mixed British 54.3 \n", + " Indian or British Indian 53.3 \n", + " Irish 56.6 \n", + " Other Black 53.1 \n", + " Other White 55.1 \n", + " Other mixed 56.7 \n", + " Pakistani or British Pakistani 54.5 \n", " Unknown 53.5 \n", - "bmi 30+ 52.0 \n", - " under 30 52.1 \n", - "chronic_cardiac_disease no 52.1 \n", - " yes 55.6 \n", - "current_copd no 52.1 \n", - " yes 50.0 \n", - "dmards no 52.1 \n", - " yes 40.0 \n", - "psychosis_schiz_bipolar no 52.1 \n", + " White + Asian 52.9 \n", + " White + Black African 53.8 \n", + " White + Black Caribbean 55.8 \n", + "imd_categories 1 Most deprived 53.9 \n", + " 2 55.2 \n", + " 3 52.9 \n", + " 4 53.9 \n", + " 5 Least deprived 54.5 \n", + " Unknown 53.4 \n", + "bmi 30+ 55.3 \n", + " under 30 53.5 \n", + "chronic_cardiac_disease no 54.0 \n", + " yes 60.0 \n", + "current_copd no 54.1 \n", + " yes 56.2 \n", + "dmards no 54.1 \n", + " yes 55.0 \n", + "psychosis_schiz_bipolar no 54.1 \n", + " yes 47.1 \n", + "ssri no 54.1 \n", " yes 50.0 \n", - "ssri no 52.2 \n", - " yes 28.6 \n", - "ckd no 52.1 \n", - " yes 51.7 \n", + "ckd no 54.1 \n", + " yes 54.0 \n", "brand_of_first_dose Moderna NaN \n", - " Oxford-AZ NaN \n", - " Pfizer 0.0 \n", - " Unknown 57.7 \n", + " Oxford-AZ 0.0 \n", + " Pfizer 50.0 \n", + " Unknown 60.2 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.1 \n", - "sex F 1.4 \n", - " M 1.4 \n", - "ethnicity_6_groups Black 0.7 \n", - " Mixed 1.4 \n", + "overall overall 0.8 \n", + "sex F 0.8 \n", + " M 1.0 \n", + "ethnicity_6_groups Black 1.0 \n", + " Mixed 1.0 \n", " Other 1.4 \n", - " South Asian 1.3 \n", - " Unknown 0.8 \n", + " South Asian 1.0 \n", + " Unknown 0.7 \n", " White 0.7 \n", "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 2.2 \n", - " Caribbean 0.0 \n", - " Chinese 2.0 \n", - " Other 0.0 \n", - " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 2.4 \n", - " Irish 0.0 \n", - " Other Black 2.1 \n", - " Other White 0.0 \n", - " Other mixed 2.3 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 0.8 \n", - " White + Asian 2.2 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 0.6 \n", - " 2 1.9 \n", - " 3 0.6 \n", - " 4 1.2 \n", - " 5 Least deprived 1.8 \n", - " Unknown 0.0 \n", - "bmi 30+ 1.5 \n", - " under 30 1.2 \n", - "chronic_cardiac_disease no 1.1 \n", + " Bangladeshi or British Bangladeshi 1.1 \n", + " Caribbean 1.0 \n", + " Chinese 1.1 \n", + " Other 1.0 \n", + " Other Asian 1.1 \n", + " British or Mixed British 1.1 \n", + " Indian or British Indian 2.1 \n", + " Irish 1.0 \n", + " Other Black 0.0 \n", + " Other White 1.0 \n", + " Other mixed 0.0 \n", + " Pakistani or British Pakistani 1.2 \n", + " Unknown 1.1 \n", + " White + Asian 0.0 \n", + " White + Black African 1.0 \n", + " White + Black Caribbean 1.0 \n", + "imd_categories 1 Most deprived 1.2 \n", + " 2 0.9 \n", + " 3 0.9 \n", + " 4 0.6 \n", + " 5 Least deprived 0.9 \n", + " Unknown 1.1 \n", + "bmi 30+ 0.9 \n", + " under 30 1.0 \n", + "chronic_cardiac_disease no 0.9 \n", " yes 0.0 \n", - "current_copd no 1.2 \n", - " yes 12.5 \n", - "dmards no 1.3 \n", - " yes 10.0 \n", - "psychosis_schiz_bipolar no 1.2 \n", + "current_copd no 0.8 \n", " yes 0.0 \n", - "ssri no 1.2 \n", + "dmards no 0.9 \n", " yes 0.0 \n", - "ckd no 1.3 \n", - " yes 1.1 \n", + "psychosis_schiz_bipolar no 0.9 \n", + " yes 0.0 \n", + "ssri no 0.9 \n", + " yes 0.0 \n", + "ckd no 0.9 \n", + " yes 0.6 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 1.4 \n", + " Unknown 1.0 \n", "\n", " Date projected to reach 90% \n", "category group \n", @@ -21411,36 +21514,36 @@ " Unknown unknown \n", " White unknown \n", "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi 06-Apr \n", + " Bangladeshi or British Bangladeshi unknown \n", " Caribbean unknown \n", - " Chinese 09-Apr \n", + " Chinese unknown \n", " Other unknown \n", " Other Asian unknown \n", " British or Mixed British unknown \n", - " Indian or British Indian 27-Mar \n", + " Indian or British Indian 28-May \n", " Irish unknown \n", - " Other Black 02-Apr \n", + " Other Black unknown \n", " Other White unknown \n", - " Other mixed 15-Apr \n", + " Other mixed unknown \n", " Pakistani or British Pakistani unknown \n", " Unknown unknown \n", - " White + Asian 31-Mar \n", + " White + Asian unknown \n", " White + Black African unknown \n", " White + Black Caribbean unknown \n", "imd_categories 1 Most deprived unknown \n", - " 2 25-Apr \n", + " 2 unknown \n", " 3 unknown \n", " 4 unknown \n", - " 5 Least deprived 27-Apr \n", + " 5 Least deprived unknown \n", " Unknown unknown \n", - "bmi 30+ 03-Jun \n", + "bmi 30+ unknown \n", " under 30 unknown \n", "chronic_cardiac_disease no unknown \n", " yes unknown \n", "current_copd no unknown \n", - " yes 30-Dec \n", + " yes unknown \n", "dmards no unknown \n", - " yes 12-Jan \n", + " yes unknown \n", "psychosis_schiz_bipolar no unknown \n", " yes unknown \n", "ssri no unknown \n", @@ -21450,7 +21553,7 @@ "brand_of_first_dose Moderna unknown \n", " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 18-May " + " Unknown unknown " ] }, "metadata": {}, @@ -21479,7 +21582,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **30-39** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **30-39** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -21545,295 +21648,295 @@ " \n", " overall\n", " overall\n", - " 3353\n", - " 52.6\n", - " 6377\n", - " 51.8\n", + " 7168\n", + " 55.3\n", + " 12957\n", + " 54.5\n", " 0.8\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 1736\n", - " 52.7\n", - " 3297\n", - " 51.8\n", + " 3752\n", + " 55.8\n", + " 6727\n", + " 54.9\n", " 0.9\n", " unknown\n", " \n", " \n", " M\n", - " 1617\n", - " 52.5\n", - " 3080\n", - " 51.6\n", - " 0.9\n", + " 3409\n", + " 54.7\n", + " 6230\n", + " 53.9\n", + " 0.8\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 518\n", - " 48.4\n", - " 1071\n", - " 47.7\n", + " 1225\n", + " 54.9\n", + " 2233\n", + " 54.2\n", " 0.7\n", " unknown\n", " \n", " \n", " Mixed\n", - " 581\n", - " 54.2\n", - " 1071\n", - " 52.9\n", + " 1204\n", + " 54.6\n", + " 2205\n", + " 53.3\n", " 1.3\n", " unknown\n", " \n", " \n", " Other\n", - " 602\n", - " 53.8\n", - " 1120\n", - " 53.1\n", - " 0.7\n", + " 1169\n", + " 54.9\n", + " 2128\n", + " 54.3\n", + " 0.6\n", " unknown\n", " \n", " \n", " South Asian\n", - " 574\n", - " 51.2\n", - " 1120\n", - " 50.6\n", + " 1225\n", + " 54.3\n", + " 2254\n", + " 53.7\n", " 0.6\n", " unknown\n", " \n", " \n", " Unknown\n", - " 504\n", - " 52.6\n", - " 959\n", - " 51.1\n", - " 1.5\n", - " 07-Jun\n", + " 1078\n", + " 56.2\n", + " 1918\n", + " 55.1\n", + " 1.1\n", + " unknown\n", " \n", " \n", " White\n", - " 581\n", - " 56.1\n", - " 1036\n", - " 54.7\n", - " 1.4\n", - " 02-Jun\n", + " 1260\n", + " 56.6\n", + " 2226\n", + " 55.7\n", + " 0.9\n", + " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 168\n", - " 50.0\n", - " 336\n", - " 50.0\n", - " 0.0\n", + " 371\n", + " 53.0\n", + " 700\n", + " 52.0\n", + " 1.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 175\n", - " 53.2\n", - " 329\n", - " 53.2\n", + " 385\n", + " 56.1\n", + " 686\n", + " 56.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 168\n", - " 51.1\n", - " 329\n", - " 48.9\n", - " 2.2\n", - " 17-Apr\n", + " 350\n", + " 53.2\n", + " 658\n", + " 53.2\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Chinese\n", - " 196\n", - " 54.9\n", - " 357\n", - " 54.9\n", - " 0.0\n", + " 371\n", + " 53.0\n", + " 700\n", + " 52.0\n", + " 1.0\n", " unknown\n", " \n", " \n", " Other\n", - " 210\n", - " 56.6\n", - " 371\n", - " 54.7\n", - " 1.9\n", - " 17-Apr\n", + " 385\n", + " 56.7\n", + " 679\n", + " 55.7\n", + " 1.0\n", + " unknown\n", " \n", " \n", " Other Asian\n", - " 182\n", - " 54.2\n", - " 336\n", - " 52.1\n", - " 2.1\n", - " 13-Apr\n", + " 392\n", + " 54.9\n", + " 714\n", + " 52.9\n", + " 2.0\n", + " 04-Jun\n", " \n", " \n", " British or Mixed British\n", - " 189\n", - " 57.4\n", - " 329\n", - " 55.3\n", - " 2.1\n", - " 02-Apr\n", + " 371\n", + " 52.0\n", + " 714\n", + " 52.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 203\n", - " 54.7\n", - " 371\n", - " 52.8\n", - " 1.9\n", - " 24-Apr\n", + " 364\n", + " 53.1\n", + " 686\n", + " 52.0\n", + " 1.1\n", + " unknown\n", " \n", " \n", " Irish\n", - " 161\n", - " 51.1\n", - " 315\n", - " 51.1\n", + " 371\n", + " 57.6\n", + " 644\n", + " 57.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 168\n", - " 55.8\n", - " 301\n", - " 53.5\n", - " 2.3\n", - " 29-Mar\n", + " 385\n", + " 55.6\n", + " 693\n", + " 55.6\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other White\n", - " 189\n", - " 52.9\n", - " 357\n", - " 51.0\n", - " 1.9\n", - " 30-Apr\n", + " 385\n", + " 58.5\n", + " 658\n", + " 58.5\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other mixed\n", - " 196\n", - " 53.8\n", - " 364\n", - " 53.8\n", - " 0.0\n", + " 392\n", + " 56.6\n", + " 693\n", + " 55.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 168\n", - " 50.0\n", - " 336\n", - " 50.0\n", - " 0.0\n", + " 413\n", + " 56.2\n", + " 735\n", + " 55.2\n", + " 1.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 483\n", - " 51.9\n", - " 931\n", - " 51.1\n", - " 0.8\n", + " 1071\n", + " 56.0\n", + " 1911\n", + " 54.9\n", + " 1.1\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 161\n", - " 51.1\n", - " 315\n", - " 48.9\n", - " 2.2\n", - " 17-Apr\n", + " 371\n", + " 53.5\n", + " 693\n", + " 53.5\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black African\n", - " 168\n", - " 50.0\n", - " 336\n", - " 50.0\n", - " 0.0\n", + " 406\n", + " 56.3\n", + " 721\n", + " 55.3\n", + " 1.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 182\n", - " 52.0\n", - " 350\n", - " 50.0\n", - " 2.0\n", - " 27-Apr\n", + " 371\n", + " 55.8\n", + " 665\n", + " 55.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 637\n", - " 53.2\n", - " 1197\n", - " 52.6\n", - " 0.6\n", + " 1351\n", + " 54.7\n", + " 2471\n", + " 53.8\n", + " 0.9\n", " unknown\n", " \n", " \n", " 2\n", - " 623\n", - " 50.9\n", - " 1225\n", - " 49.7\n", - " 1.2\n", + " 1365\n", + " 55.1\n", + " 2478\n", + " 54.0\n", + " 1.1\n", " unknown\n", " \n", " \n", " 3\n", - " 658\n", - " 53.7\n", - " 1225\n", - " 52.6\n", - " 1.1\n", + " 1358\n", + " 55.4\n", + " 2450\n", + " 54.9\n", + " 0.5\n", " unknown\n", " \n", " \n", " 4\n", - " 644\n", - " 51.4\n", - " 1253\n", - " 50.8\n", - " 0.6\n", + " 1351\n", + " 55.1\n", + " 2450\n", + " 54.3\n", + " 0.8\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 630\n", - " 55.2\n", - " 1141\n", - " 54.0\n", - " 1.2\n", + " 1386\n", + " 56.9\n", + " 2436\n", + " 56.0\n", + " 0.9\n", " unknown\n", " \n", " \n", " Unknown\n", - " 168\n", - " 51.1\n", - " 329\n", - " 48.9\n", - " 2.2\n", - " 17-Apr\n", + " 357\n", + " 53.1\n", + " 672\n", + " 53.1\n", + " 0.0\n", + " unknown\n", " \n", " \n", " brand_of_first_dose\n", @@ -21849,8 +21952,8 @@ " Oxford-AZ\n", " 0\n", " 0.0\n", - " 7\n", - " 0.0\n", + " 0\n", + " NaN\n", " 0.0\n", " unknown\n", " \n", @@ -21865,11 +21968,11 @@ " \n", " \n", " Unknown\n", - " 3346\n", - " 58.7\n", - " 5698\n", - " 57.7\n", - " 1.0\n", + " 7154\n", + " 61.2\n", + " 11683\n", + " 60.3\n", + " 0.9\n", " unknown\n", " \n", " \n", @@ -21879,159 +21982,159 @@ "text/plain": [ " vaccinated percent \\\n", "category group \n", - "overall overall 3353 52.6 \n", - "sex F 1736 52.7 \n", - " M 1617 52.5 \n", - "ethnicity_6_groups Black 518 48.4 \n", - " Mixed 581 54.2 \n", - " Other 602 53.8 \n", - " South Asian 574 51.2 \n", - " Unknown 504 52.6 \n", - " White 581 56.1 \n", - "ethnicity_16_groups African 168 50.0 \n", - " Bangladeshi or British Bangladeshi 175 53.2 \n", - " Caribbean 168 51.1 \n", - " Chinese 196 54.9 \n", - " Other 210 56.6 \n", - " Other Asian 182 54.2 \n", - " British or Mixed British 189 57.4 \n", - " Indian or British Indian 203 54.7 \n", - " Irish 161 51.1 \n", - " Other Black 168 55.8 \n", - " Other White 189 52.9 \n", - " Other mixed 196 53.8 \n", - " Pakistani or British Pakistani 168 50.0 \n", - " Unknown 483 51.9 \n", - " White + Asian 161 51.1 \n", - " White + Black African 168 50.0 \n", - " White + Black Caribbean 182 52.0 \n", - "imd_categories 1 Most deprived 637 53.2 \n", - " 2 623 50.9 \n", - " 3 658 53.7 \n", - " 4 644 51.4 \n", - " 5 Least deprived 630 55.2 \n", - " Unknown 168 51.1 \n", + "overall overall 7168 55.3 \n", + "sex F 3752 55.8 \n", + " M 3409 54.7 \n", + "ethnicity_6_groups Black 1225 54.9 \n", + " Mixed 1204 54.6 \n", + " Other 1169 54.9 \n", + " South Asian 1225 54.3 \n", + " Unknown 1078 56.2 \n", + " White 1260 56.6 \n", + "ethnicity_16_groups African 371 53.0 \n", + " Bangladeshi or British Bangladeshi 385 56.1 \n", + " Caribbean 350 53.2 \n", + " Chinese 371 53.0 \n", + " Other 385 56.7 \n", + " Other Asian 392 54.9 \n", + " British or Mixed British 371 52.0 \n", + " Indian or British Indian 364 53.1 \n", + " Irish 371 57.6 \n", + " Other Black 385 55.6 \n", + " Other White 385 58.5 \n", + " Other mixed 392 56.6 \n", + " Pakistani or British Pakistani 413 56.2 \n", + " Unknown 1071 56.0 \n", + " White + Asian 371 53.5 \n", + " White + Black African 406 56.3 \n", + " White + Black Caribbean 371 55.8 \n", + "imd_categories 1 Most deprived 1351 54.7 \n", + " 2 1365 55.1 \n", + " 3 1358 55.4 \n", + " 4 1351 55.1 \n", + " 5 Least deprived 1386 56.9 \n", + " Unknown 357 53.1 \n", "brand_of_first_dose Moderna 0 0.0 \n", " Oxford-AZ 0 0.0 \n", " Pfizer 0 0.0 \n", - " Unknown 3346 58.7 \n", + " Unknown 7154 61.2 \n", "\n", " total \\\n", "category group \n", - "overall overall 6377 \n", - "sex F 3297 \n", - " M 3080 \n", - "ethnicity_6_groups Black 1071 \n", - " Mixed 1071 \n", - " Other 1120 \n", - " South Asian 1120 \n", - " Unknown 959 \n", - " White 1036 \n", - "ethnicity_16_groups African 336 \n", - " Bangladeshi or British Bangladeshi 329 \n", - " Caribbean 329 \n", - " Chinese 357 \n", - " Other 371 \n", - " Other Asian 336 \n", - " British or Mixed British 329 \n", - " Indian or British Indian 371 \n", - " Irish 315 \n", - " Other Black 301 \n", - " Other White 357 \n", - " Other mixed 364 \n", - " Pakistani or British Pakistani 336 \n", - " Unknown 931 \n", - " White + Asian 315 \n", - " White + Black African 336 \n", - " White + Black Caribbean 350 \n", - "imd_categories 1 Most deprived 1197 \n", - " 2 1225 \n", - " 3 1225 \n", - " 4 1253 \n", - " 5 Least deprived 1141 \n", - " Unknown 329 \n", + "overall overall 12957 \n", + "sex F 6727 \n", + " M 6230 \n", + "ethnicity_6_groups Black 2233 \n", + " Mixed 2205 \n", + " Other 2128 \n", + " South Asian 2254 \n", + " Unknown 1918 \n", + " White 2226 \n", + "ethnicity_16_groups African 700 \n", + " Bangladeshi or British Bangladeshi 686 \n", + " Caribbean 658 \n", + " Chinese 700 \n", + " Other 679 \n", + " Other Asian 714 \n", + " British or Mixed British 714 \n", + " Indian or British Indian 686 \n", + " Irish 644 \n", + " Other Black 693 \n", + " Other White 658 \n", + " Other mixed 693 \n", + " Pakistani or British Pakistani 735 \n", + " Unknown 1911 \n", + " White + Asian 693 \n", + " White + Black African 721 \n", + " White + Black Caribbean 665 \n", + "imd_categories 1 Most deprived 2471 \n", + " 2 2478 \n", + " 3 2450 \n", + " 4 2450 \n", + " 5 Least deprived 2436 \n", + " Unknown 672 \n", "brand_of_first_dose Moderna 0 \n", - " Oxford-AZ 7 \n", + " Oxford-AZ 0 \n", " Pfizer 14 \n", - " Unknown 5698 \n", + " Unknown 11683 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 51.8 \n", - "sex F 51.8 \n", - " M 51.6 \n", - "ethnicity_6_groups Black 47.7 \n", - " Mixed 52.9 \n", - " Other 53.1 \n", - " South Asian 50.6 \n", - " Unknown 51.1 \n", - " White 54.7 \n", - "ethnicity_16_groups African 50.0 \n", - " Bangladeshi or British Bangladeshi 53.2 \n", - " Caribbean 48.9 \n", - " Chinese 54.9 \n", - " Other 54.7 \n", - " Other Asian 52.1 \n", - " British or Mixed British 55.3 \n", - " Indian or British Indian 52.8 \n", - " Irish 51.1 \n", - " Other Black 53.5 \n", - " Other White 51.0 \n", - " Other mixed 53.8 \n", - " Pakistani or British Pakistani 50.0 \n", - " Unknown 51.1 \n", - " White + Asian 48.9 \n", - " White + Black African 50.0 \n", - " White + Black Caribbean 50.0 \n", - "imd_categories 1 Most deprived 52.6 \n", - " 2 49.7 \n", - " 3 52.6 \n", - " 4 50.8 \n", - " 5 Least deprived 54.0 \n", - " Unknown 48.9 \n", + "overall overall 54.5 \n", + "sex F 54.9 \n", + " M 53.9 \n", + "ethnicity_6_groups Black 54.2 \n", + " Mixed 53.3 \n", + " Other 54.3 \n", + " South Asian 53.7 \n", + " Unknown 55.1 \n", + " White 55.7 \n", + "ethnicity_16_groups African 52.0 \n", + " Bangladeshi or British Bangladeshi 56.1 \n", + " Caribbean 53.2 \n", + " Chinese 52.0 \n", + " Other 55.7 \n", + " Other Asian 52.9 \n", + " British or Mixed British 52.0 \n", + " Indian or British Indian 52.0 \n", + " Irish 57.6 \n", + " Other Black 55.6 \n", + " Other White 58.5 \n", + " Other mixed 55.6 \n", + " Pakistani or British Pakistani 55.2 \n", + " Unknown 54.9 \n", + " White + Asian 53.5 \n", + " White + Black African 55.3 \n", + " White + Black Caribbean 55.8 \n", + "imd_categories 1 Most deprived 53.8 \n", + " 2 54.0 \n", + " 3 54.9 \n", + " 4 54.3 \n", + " 5 Least deprived 56.0 \n", + " Unknown 53.1 \n", "brand_of_first_dose Moderna NaN \n", - " Oxford-AZ 0.0 \n", + " Oxford-AZ NaN \n", " Pfizer 0.0 \n", - " Unknown 57.7 \n", + " Unknown 60.3 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", "overall overall 0.8 \n", "sex F 0.9 \n", - " M 0.9 \n", + " M 0.8 \n", "ethnicity_6_groups Black 0.7 \n", " Mixed 1.3 \n", - " Other 0.7 \n", + " Other 0.6 \n", " South Asian 0.6 \n", - " Unknown 1.5 \n", - " White 1.4 \n", - "ethnicity_16_groups African 0.0 \n", + " Unknown 1.1 \n", + " White 0.9 \n", + "ethnicity_16_groups African 1.0 \n", " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 2.2 \n", - " Chinese 0.0 \n", - " Other 1.9 \n", - " Other Asian 2.1 \n", - " British or Mixed British 2.1 \n", - " Indian or British Indian 1.9 \n", + " Caribbean 0.0 \n", + " Chinese 1.0 \n", + " Other 1.0 \n", + " Other Asian 2.0 \n", + " British or Mixed British 0.0 \n", + " Indian or British Indian 1.1 \n", " Irish 0.0 \n", - " Other Black 2.3 \n", - " Other White 1.9 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 0.8 \n", - " White + Asian 2.2 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 2.0 \n", - "imd_categories 1 Most deprived 0.6 \n", - " 2 1.2 \n", - " 3 1.1 \n", - " 4 0.6 \n", - " 5 Least deprived 1.2 \n", - " Unknown 2.2 \n", + " Other Black 0.0 \n", + " Other White 0.0 \n", + " Other mixed 1.0 \n", + " Pakistani or British Pakistani 1.0 \n", + " Unknown 1.1 \n", + " White + Asian 0.0 \n", + " White + Black African 1.0 \n", + " White + Black Caribbean 0.0 \n", + "imd_categories 1 Most deprived 0.9 \n", + " 2 1.1 \n", + " 3 0.5 \n", + " 4 0.8 \n", + " 5 Least deprived 0.9 \n", + " Unknown 0.0 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 1.0 \n", + " Unknown 0.9 \n", "\n", " Date projected to reach 90% \n", "category group \n", @@ -22042,31 +22145,31 @@ " Mixed unknown \n", " Other unknown \n", " South Asian unknown \n", - " Unknown 07-Jun \n", - " White 02-Jun \n", + " Unknown unknown \n", + " White unknown \n", "ethnicity_16_groups African unknown \n", " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean 17-Apr \n", + " Caribbean unknown \n", " Chinese unknown \n", - " Other 17-Apr \n", - " Other Asian 13-Apr \n", - " British or Mixed British 02-Apr \n", - " Indian or British Indian 24-Apr \n", + " Other unknown \n", + " Other Asian 04-Jun \n", + " British or Mixed British unknown \n", + " Indian or British Indian unknown \n", " Irish unknown \n", - " Other Black 29-Mar \n", - " Other White 30-Apr \n", + " Other Black unknown \n", + " Other White unknown \n", " Other mixed unknown \n", " Pakistani or British Pakistani unknown \n", " Unknown unknown \n", - " White + Asian 17-Apr \n", + " White + Asian unknown \n", " White + Black African unknown \n", - " White + Black Caribbean 27-Apr \n", + " White + Black Caribbean unknown \n", "imd_categories 1 Most deprived unknown \n", " 2 unknown \n", " 3 unknown \n", " 4 unknown \n", " 5 Least deprived unknown \n", - " Unknown 17-Apr \n", + " Unknown unknown \n", "brand_of_first_dose Moderna unknown \n", " Oxford-AZ unknown \n", " Pfizer unknown \n", @@ -22099,7 +22202,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **18-29** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **18-29** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -22165,294 +22268,294 @@ " \n", " overall\n", " overall\n", - " 3864\n", - " 52.1\n", - " 7420\n", - " 50.9\n", - " 1.2\n", + " 8260\n", + " 55.2\n", + " 14966\n", + " 54.2\n", + " 1.0\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 1981\n", - " 52.1\n", - " 3801\n", - " 50.6\n", - " 1.5\n", + " 4242\n", + " 55.2\n", + " 7686\n", + " 54.2\n", + " 1.0\n", " unknown\n", " \n", " \n", " M\n", - " 1890\n", - " 52.3\n", - " 3612\n", - " 51.4\n", - " 0.9\n", + " 4025\n", + " 55.2\n", + " 7287\n", + " 54.1\n", + " 1.1\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 672\n", - " 52.7\n", - " 1274\n", - " 51.6\n", - " 1.1\n", - " unknown\n", + " 1435\n", + " 56.2\n", + " 2555\n", + " 54.8\n", + " 1.4\n", + " 21-Jul\n", " \n", " \n", " Mixed\n", - " 630\n", - " 53.3\n", - " 1183\n", - " 52.1\n", - " 1.2\n", + " 1407\n", + " 54.6\n", + " 2576\n", + " 53.5\n", + " 1.1\n", " unknown\n", " \n", " \n", " Other\n", - " 658\n", - " 51.4\n", - " 1281\n", - " 50.3\n", - " 1.1\n", + " 1379\n", + " 53.8\n", + " 2562\n", + " 53.0\n", + " 0.8\n", " unknown\n", " \n", " \n", " South Asian\n", - " 651\n", - " 52.0\n", - " 1253\n", - " 50.3\n", - " 1.7\n", - " 20-May\n", - " \n", - " \n", - " Unknown\n", - " 595\n", - " 51.5\n", - " 1155\n", - " 50.3\n", - " 1.2\n", + " 1428\n", + " 56.8\n", + " 2513\n", + " 55.7\n", + " 1.1\n", " unknown\n", " \n", " \n", - " White\n", - " 658\n", - " 51.9\n", + " Unknown\n", " 1267\n", - " 51.4\n", - " 0.5\n", + " 56.7\n", + " 2233\n", + " 55.8\n", + " 0.9\n", + " unknown\n", + " \n", + " \n", + " White\n", + " 1351\n", + " 53.6\n", + " 2520\n", + " 52.5\n", + " 1.1\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 203\n", - " 53.7\n", - " 378\n", - " 51.9\n", - " 1.8\n", - " 05-May\n", + " 441\n", + " 56.2\n", + " 784\n", + " 55.4\n", + " 0.8\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 196\n", - " 49.1\n", - " 399\n", - " 47.4\n", - " 1.7\n", - " 01-Jun\n", + " 448\n", + " 55.7\n", + " 805\n", + " 54.8\n", + " 0.9\n", + " unknown\n", " \n", " \n", " Caribbean\n", - " 182\n", - " 50.0\n", - " 364\n", - " 48.1\n", - " 1.9\n", - " 11-May\n", + " 420\n", + " 53.6\n", + " 784\n", + " 52.7\n", + " 0.9\n", + " unknown\n", " \n", " \n", " Chinese\n", - " 210\n", - " 53.6\n", - " 392\n", - " 51.8\n", - " 1.8\n", - " 05-May\n", + " 455\n", + " 56.0\n", + " 812\n", + " 55.2\n", + " 0.8\n", + " unknown\n", " \n", " \n", " Other\n", - " 175\n", - " 47.2\n", - " 371\n", - " 45.3\n", - " 1.9\n", - " 21-May\n", + " 448\n", + " 56.1\n", + " 798\n", + " 54.4\n", + " 1.7\n", + " 21-Jun\n", " \n", " \n", " Other Asian\n", - " 217\n", - " 51.7\n", " 420\n", - " 50.0\n", - " 1.7\n", - " 21-May\n", + " 53.6\n", + " 784\n", + " 52.7\n", + " 0.9\n", + " unknown\n", " \n", " \n", " British or Mixed British\n", - " 210\n", - " 51.7\n", - " 406\n", - " 50.0\n", - " 1.7\n", - " 21-May\n", + " 420\n", + " 55.0\n", + " 763\n", + " 53.2\n", + " 1.8\n", + " 18-Jun\n", " \n", " \n", " Indian or British Indian\n", - " 182\n", - " 46.4\n", - " 392\n", - " 46.4\n", + " 441\n", + " 53.4\n", + " 826\n", + " 53.4\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 217\n", - " 52.5\n", - " 413\n", - " 50.8\n", - " 1.7\n", - " 18-May\n", + " 448\n", + " 58.2\n", + " 770\n", + " 56.4\n", + " 1.8\n", + " 05-Jun\n", " \n", " \n", " Other Black\n", - " 217\n", - " 50.0\n", - " 434\n", - " 48.4\n", - " 1.6\n", - " unknown\n", + " 448\n", + " 56.1\n", + " 798\n", + " 54.4\n", + " 1.7\n", + " 21-Jun\n", " \n", " \n", " Other White\n", - " 231\n", - " 55.9\n", - " 413\n", - " 54.2\n", - " 1.7\n", - " 04-May\n", + " 427\n", + " 54.0\n", + " 791\n", + " 53.1\n", + " 0.9\n", + " unknown\n", " \n", " \n", " Other mixed\n", - " 217\n", - " 54.4\n", - " 399\n", - " 52.6\n", - " 1.8\n", - " 02-May\n", + " 469\n", + " 59.3\n", + " 791\n", + " 58.4\n", + " 0.9\n", + " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 224\n", - " 56.1\n", - " 399\n", - " 54.4\n", - " 1.7\n", - " 03-May\n", + " 427\n", + " 56.0\n", + " 763\n", + " 55.0\n", + " 1.0\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 588\n", - " 53.5\n", - " 1099\n", - " 52.9\n", - " 0.6\n", + " 1246\n", + " 54.8\n", + " 2275\n", + " 53.8\n", + " 1.0\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 196\n", - " 52.8\n", - " 371\n", - " 50.9\n", - " 1.9\n", - " 01-May\n", + " 441\n", + " 53.4\n", + " 826\n", + " 52.5\n", + " 0.9\n", + " unknown\n", " \n", " \n", " White + Black African\n", - " 231\n", - " 54.1\n", - " 427\n", - " 52.5\n", - " 1.6\n", - " 21-May\n", + " 420\n", + " 52.2\n", + " 805\n", + " 52.2\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 182\n", - " 52.0\n", - " 350\n", - " 50.0\n", - " 2.0\n", - " 27-Apr\n", + " 441\n", + " 55.8\n", + " 791\n", + " 54.9\n", + " 0.9\n", + " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 735\n", - " 50.7\n", - " 1449\n", - " 49.3\n", - " 1.4\n", + " 1596\n", + " 54.3\n", + " 2940\n", + " 53.1\n", + " 1.2\n", " unknown\n", " \n", " \n", " 2\n", - " 721\n", - " 51.5\n", - " 1400\n", - " 50.5\n", - " 1.0\n", + " 1554\n", + " 54.8\n", + " 2835\n", + " 53.6\n", + " 1.2\n", " unknown\n", " \n", " \n", " 3\n", - " 749\n", - " 52.7\n", - " 1421\n", - " 51.7\n", + " 1547\n", + " 54.4\n", + " 2842\n", + " 53.4\n", " 1.0\n", " unknown\n", " \n", " \n", " 4\n", - " 707\n", - " 53.2\n", - " 1330\n", - " 50.5\n", - " 2.7\n", - " 20-Mar\n", + " 1617\n", + " 56.6\n", + " 2856\n", + " 55.9\n", + " 0.7\n", + " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 749\n", - " 51.7\n", - " 1449\n", - " 51.2\n", - " 0.5\n", - " unknown\n", + " 1568\n", + " 56.4\n", + " 2779\n", + " 54.9\n", + " 1.5\n", + " 08-Jul\n", " \n", " \n", " Unknown\n", - " 203\n", - " 54.7\n", - " 371\n", - " 54.7\n", - " 0.0\n", + " 385\n", + " 53.4\n", + " 721\n", + " 52.4\n", + " 1.0\n", " unknown\n", " \n", " \n", @@ -22467,30 +22570,30 @@ " \n", " \n", " Oxford-AZ\n", - " 0\n", - " 0.0\n", " 7\n", + " 50.0\n", + " 14\n", " 0.0\n", - " 0.0\n", - " unknown\n", + " 50.0\n", + " 07-Feb\n", " \n", " \n", " Pfizer\n", - " 0\n", - " 0.0\n", " 14\n", - " 0.0\n", + " 66.7\n", + " 21\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 3850\n", - " 57.7\n", - " 6678\n", - " 56.4\n", - " 1.3\n", - " 06-Jun\n", + " 8239\n", + " 61.5\n", + " 13398\n", + " 60.4\n", + " 1.1\n", + " unknown\n", " \n", " \n", "\n", @@ -22499,198 +22602,198 @@ "text/plain": [ " vaccinated percent \\\n", "category group \n", - "overall overall 3864 52.1 \n", - "sex F 1981 52.1 \n", - " M 1890 52.3 \n", - "ethnicity_6_groups Black 672 52.7 \n", - " Mixed 630 53.3 \n", - " Other 658 51.4 \n", - " South Asian 651 52.0 \n", - " Unknown 595 51.5 \n", - " White 658 51.9 \n", - "ethnicity_16_groups African 203 53.7 \n", - " Bangladeshi or British Bangladeshi 196 49.1 \n", - " Caribbean 182 50.0 \n", - " Chinese 210 53.6 \n", - " Other 175 47.2 \n", - " Other Asian 217 51.7 \n", - " British or Mixed British 210 51.7 \n", - " Indian or British Indian 182 46.4 \n", - " Irish 217 52.5 \n", - " Other Black 217 50.0 \n", - " Other White 231 55.9 \n", - " Other mixed 217 54.4 \n", - " Pakistani or British Pakistani 224 56.1 \n", - " Unknown 588 53.5 \n", - " White + Asian 196 52.8 \n", - " White + Black African 231 54.1 \n", - " White + Black Caribbean 182 52.0 \n", - "imd_categories 1 Most deprived 735 50.7 \n", - " 2 721 51.5 \n", - " 3 749 52.7 \n", - " 4 707 53.2 \n", - " 5 Least deprived 749 51.7 \n", - " Unknown 203 54.7 \n", + "overall overall 8260 55.2 \n", + "sex F 4242 55.2 \n", + " M 4025 55.2 \n", + "ethnicity_6_groups Black 1435 56.2 \n", + " Mixed 1407 54.6 \n", + " Other 1379 53.8 \n", + " South Asian 1428 56.8 \n", + " Unknown 1267 56.7 \n", + " White 1351 53.6 \n", + "ethnicity_16_groups African 441 56.2 \n", + " Bangladeshi or British Bangladeshi 448 55.7 \n", + " Caribbean 420 53.6 \n", + " Chinese 455 56.0 \n", + " Other 448 56.1 \n", + " Other Asian 420 53.6 \n", + " British or Mixed British 420 55.0 \n", + " Indian or British Indian 441 53.4 \n", + " Irish 448 58.2 \n", + " Other Black 448 56.1 \n", + " Other White 427 54.0 \n", + " Other mixed 469 59.3 \n", + " Pakistani or British Pakistani 427 56.0 \n", + " Unknown 1246 54.8 \n", + " White + Asian 441 53.4 \n", + " White + Black African 420 52.2 \n", + " White + Black Caribbean 441 55.8 \n", + "imd_categories 1 Most deprived 1596 54.3 \n", + " 2 1554 54.8 \n", + " 3 1547 54.4 \n", + " 4 1617 56.6 \n", + " 5 Least deprived 1568 56.4 \n", + " Unknown 385 53.4 \n", "brand_of_first_dose Moderna 0 0.0 \n", - " Oxford-AZ 0 0.0 \n", - " Pfizer 0 0.0 \n", - " Unknown 3850 57.7 \n", + " Oxford-AZ 7 50.0 \n", + " Pfizer 14 66.7 \n", + " Unknown 8239 61.5 \n", "\n", " total \\\n", "category group \n", - "overall overall 7420 \n", - "sex F 3801 \n", - " M 3612 \n", - "ethnicity_6_groups Black 1274 \n", - " Mixed 1183 \n", - " Other 1281 \n", - " South Asian 1253 \n", - " Unknown 1155 \n", - " White 1267 \n", - "ethnicity_16_groups African 378 \n", - " Bangladeshi or British Bangladeshi 399 \n", - " Caribbean 364 \n", - " Chinese 392 \n", - " Other 371 \n", - " Other Asian 420 \n", - " British or Mixed British 406 \n", - " Indian or British Indian 392 \n", - " Irish 413 \n", - " Other Black 434 \n", - " Other White 413 \n", - " Other mixed 399 \n", - " Pakistani or British Pakistani 399 \n", - " Unknown 1099 \n", - " White + Asian 371 \n", - " White + Black African 427 \n", - " White + Black Caribbean 350 \n", - "imd_categories 1 Most deprived 1449 \n", - " 2 1400 \n", - " 3 1421 \n", - " 4 1330 \n", - " 5 Least deprived 1449 \n", - " Unknown 371 \n", + "overall overall 14966 \n", + "sex F 7686 \n", + " M 7287 \n", + "ethnicity_6_groups Black 2555 \n", + " Mixed 2576 \n", + " Other 2562 \n", + " South Asian 2513 \n", + " Unknown 2233 \n", + " White 2520 \n", + "ethnicity_16_groups African 784 \n", + " Bangladeshi or British Bangladeshi 805 \n", + " Caribbean 784 \n", + " Chinese 812 \n", + " Other 798 \n", + " Other Asian 784 \n", + " British or Mixed British 763 \n", + " Indian or British Indian 826 \n", + " Irish 770 \n", + " Other Black 798 \n", + " Other White 791 \n", + " Other mixed 791 \n", + " Pakistani or British Pakistani 763 \n", + " Unknown 2275 \n", + " White + Asian 826 \n", + " White + Black African 805 \n", + " White + Black Caribbean 791 \n", + "imd_categories 1 Most deprived 2940 \n", + " 2 2835 \n", + " 3 2842 \n", + " 4 2856 \n", + " 5 Least deprived 2779 \n", + " Unknown 721 \n", "brand_of_first_dose Moderna 0 \n", - " Oxford-AZ 7 \n", - " Pfizer 14 \n", - " Unknown 6678 \n", + " Oxford-AZ 14 \n", + " Pfizer 21 \n", + " Unknown 13398 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 50.9 \n", - "sex F 50.6 \n", - " M 51.4 \n", - "ethnicity_6_groups Black 51.6 \n", - " Mixed 52.1 \n", - " Other 50.3 \n", - " South Asian 50.3 \n", - " Unknown 50.3 \n", - " White 51.4 \n", - "ethnicity_16_groups African 51.9 \n", - " Bangladeshi or British Bangladeshi 47.4 \n", - " Caribbean 48.1 \n", - " Chinese 51.8 \n", - " Other 45.3 \n", - " Other Asian 50.0 \n", - " British or Mixed British 50.0 \n", - " Indian or British Indian 46.4 \n", - " Irish 50.8 \n", - " Other Black 48.4 \n", - " Other White 54.2 \n", - " Other mixed 52.6 \n", - " Pakistani or British Pakistani 54.4 \n", - " Unknown 52.9 \n", - " White + Asian 50.9 \n", - " White + Black African 52.5 \n", - " White + Black Caribbean 50.0 \n", - "imd_categories 1 Most deprived 49.3 \n", - " 2 50.5 \n", - " 3 51.7 \n", - " 4 50.5 \n", - " 5 Least deprived 51.2 \n", - " Unknown 54.7 \n", + "overall overall 54.2 \n", + "sex F 54.2 \n", + " M 54.1 \n", + "ethnicity_6_groups Black 54.8 \n", + " Mixed 53.5 \n", + " Other 53.0 \n", + " South Asian 55.7 \n", + " Unknown 55.8 \n", + " White 52.5 \n", + "ethnicity_16_groups African 55.4 \n", + " Bangladeshi or British Bangladeshi 54.8 \n", + " Caribbean 52.7 \n", + " Chinese 55.2 \n", + " Other 54.4 \n", + " Other Asian 52.7 \n", + " British or Mixed British 53.2 \n", + " Indian or British Indian 53.4 \n", + " Irish 56.4 \n", + " Other Black 54.4 \n", + " Other White 53.1 \n", + " Other mixed 58.4 \n", + " Pakistani or British Pakistani 55.0 \n", + " Unknown 53.8 \n", + " White + Asian 52.5 \n", + " White + Black African 52.2 \n", + " White + Black Caribbean 54.9 \n", + "imd_categories 1 Most deprived 53.1 \n", + " 2 53.6 \n", + " 3 53.4 \n", + " 4 55.9 \n", + " 5 Least deprived 54.9 \n", + " Unknown 52.4 \n", "brand_of_first_dose Moderna NaN \n", " Oxford-AZ 0.0 \n", - " Pfizer 0.0 \n", - " Unknown 56.4 \n", + " Pfizer 66.7 \n", + " Unknown 60.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.2 \n", - "sex F 1.5 \n", - " M 0.9 \n", - "ethnicity_6_groups Black 1.1 \n", - " Mixed 1.2 \n", - " Other 1.1 \n", - " South Asian 1.7 \n", - " Unknown 1.2 \n", - " White 0.5 \n", - "ethnicity_16_groups African 1.8 \n", - " Bangladeshi or British Bangladeshi 1.7 \n", - " Caribbean 1.9 \n", - " Chinese 1.8 \n", - " Other 1.9 \n", - " Other Asian 1.7 \n", - " British or Mixed British 1.7 \n", + "overall overall 1.0 \n", + "sex F 1.0 \n", + " M 1.1 \n", + "ethnicity_6_groups Black 1.4 \n", + " Mixed 1.1 \n", + " Other 0.8 \n", + " South Asian 1.1 \n", + " Unknown 0.9 \n", + " White 1.1 \n", + "ethnicity_16_groups African 0.8 \n", + " Bangladeshi or British Bangladeshi 0.9 \n", + " Caribbean 0.9 \n", + " Chinese 0.8 \n", + " Other 1.7 \n", + " Other Asian 0.9 \n", + " British or Mixed British 1.8 \n", " Indian or British Indian 0.0 \n", - " Irish 1.7 \n", - " Other Black 1.6 \n", - " Other White 1.7 \n", - " Other mixed 1.8 \n", - " Pakistani or British Pakistani 1.7 \n", - " Unknown 0.6 \n", - " White + Asian 1.9 \n", - " White + Black African 1.6 \n", - " White + Black Caribbean 2.0 \n", - "imd_categories 1 Most deprived 1.4 \n", - " 2 1.0 \n", + " Irish 1.8 \n", + " Other Black 1.7 \n", + " Other White 0.9 \n", + " Other mixed 0.9 \n", + " Pakistani or British Pakistani 1.0 \n", + " Unknown 1.0 \n", + " White + Asian 0.9 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 0.9 \n", + "imd_categories 1 Most deprived 1.2 \n", + " 2 1.2 \n", " 3 1.0 \n", - " 4 2.7 \n", - " 5 Least deprived 0.5 \n", - " Unknown 0.0 \n", + " 4 0.7 \n", + " 5 Least deprived 1.5 \n", + " Unknown 1.0 \n", "brand_of_first_dose Moderna 0.0 \n", - " Oxford-AZ 0.0 \n", + " Oxford-AZ 50.0 \n", " Pfizer 0.0 \n", - " Unknown 1.3 \n", + " Unknown 1.1 \n", "\n", " Date projected to reach 90% \n", "category group \n", "overall overall unknown \n", "sex F unknown \n", " M unknown \n", - "ethnicity_6_groups Black unknown \n", + "ethnicity_6_groups Black 21-Jul \n", " Mixed unknown \n", " Other unknown \n", - " South Asian 20-May \n", + " South Asian unknown \n", " Unknown unknown \n", " White unknown \n", - "ethnicity_16_groups African 05-May \n", - " Bangladeshi or British Bangladeshi 01-Jun \n", - " Caribbean 11-May \n", - " Chinese 05-May \n", - " Other 21-May \n", - " Other Asian 21-May \n", - " British or Mixed British 21-May \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi unknown \n", + " Caribbean unknown \n", + " Chinese unknown \n", + " Other 21-Jun \n", + " Other Asian unknown \n", + " British or Mixed British 18-Jun \n", " Indian or British Indian unknown \n", - " Irish 18-May \n", - " Other Black unknown \n", - " Other White 04-May \n", - " Other mixed 02-May \n", - " Pakistani or British Pakistani 03-May \n", + " Irish 05-Jun \n", + " Other Black 21-Jun \n", + " Other White unknown \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani unknown \n", " Unknown unknown \n", - " White + Asian 01-May \n", - " White + Black African 21-May \n", - " White + Black Caribbean 27-Apr \n", + " White + Asian unknown \n", + " White + Black African unknown \n", + " White + Black Caribbean unknown \n", "imd_categories 1 Most deprived unknown \n", " 2 unknown \n", " 3 unknown \n", - " 4 20-Mar \n", - " 5 Least deprived unknown \n", + " 4 unknown \n", + " 5 Least deprived 08-Jul \n", " Unknown unknown \n", "brand_of_first_dose Moderna unknown \n", - " Oxford-AZ unknown \n", + " Oxford-AZ 07-Feb \n", " Pfizer unknown \n", - " Unknown 06-Jun " + " Unknown unknown " ] }, "metadata": {}, @@ -22719,7 +22822,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose) among **16-17** population up to 15 Dec 2021" + "## COVID vaccination rollout (second dose) among **16-17** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -22785,149 +22888,149 @@ " \n", " overall\n", " overall\n", - " 5509\n", - " 53.2\n", - " 10346\n", - " 52.2\n", - " 1.0\n", + " 11354\n", + " 55.0\n", + " 20636\n", + " 54.2\n", + " 0.8\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 2765\n", - " 52.2\n", - " 5292\n", - " 51.3\n", + " 5796\n", + " 55.1\n", + " 10514\n", + " 54.2\n", " 0.9\n", " unknown\n", " \n", " \n", " M\n", - " 2751\n", - " 54.5\n", - " 5047\n", - " 53.1\n", - " 1.4\n", + " 5565\n", + " 55.0\n", + " 10115\n", + " 54.3\n", + " 0.7\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 952\n", - " 54.2\n", - " 1757\n", - " 53.0\n", - " 1.2\n", + " 1932\n", + " 55.2\n", + " 3500\n", + " 54.4\n", + " 0.8\n", " unknown\n", " \n", " \n", " Mixed\n", - " 917\n", - " 51.6\n", - " 1778\n", - " 50.4\n", - " 1.2\n", + " 1918\n", + " 54.0\n", + " 3549\n", + " 53.3\n", + " 0.7\n", " unknown\n", " \n", " \n", " Other\n", - " 931\n", - " 53.4\n", - " 1743\n", - " 52.2\n", - " 1.2\n", + " 1988\n", + " 56.3\n", + " 3528\n", + " 55.2\n", + " 1.1\n", " unknown\n", " \n", " \n", " South Asian\n", - " 931\n", + " 1904\n", " 53.6\n", - " 1736\n", - " 52.8\n", - " 0.8\n", + " 3549\n", + " 52.9\n", + " 0.7\n", " unknown\n", " \n", " \n", " Unknown\n", - " 847\n", - " 53.8\n", - " 1575\n", - " 52.9\n", - " 0.9\n", + " 1715\n", + " 56.6\n", + " 3031\n", + " 55.4\n", + " 1.2\n", " unknown\n", " \n", " \n", " White\n", - " 938\n", - " 53.6\n", - " 1750\n", - " 52.4\n", - " 1.2\n", + " 1904\n", + " 54.8\n", + " 3472\n", + " 54.2\n", + " 0.6\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 1001\n", - " 53.8\n", - " 1862\n", - " 53.0\n", - " 0.8\n", + " 2156\n", + " 54.2\n", + " 3976\n", + " 53.5\n", + " 0.7\n", " unknown\n", " \n", " \n", " 2\n", - " 1078\n", - " 54.4\n", - " 1981\n", - " 53.4\n", - " 1.0\n", + " 2128\n", + " 54.8\n", + " 3885\n", + " 54.1\n", + " 0.7\n", " unknown\n", " \n", " \n", " 3\n", - " 1029\n", - " 51.4\n", - " 2002\n", - " 50.0\n", - " 1.4\n", + " 2247\n", + " 57.1\n", + " 3934\n", + " 56.2\n", + " 0.9\n", " unknown\n", " \n", " \n", " 4\n", - " 1071\n", - " 52.9\n", - " 2023\n", - " 51.6\n", - " 1.3\n", + " 2093\n", + " 53.3\n", + " 3927\n", + " 52.6\n", + " 0.7\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 1043\n", - " 53.2\n", - " 1960\n", - " 52.1\n", + " 2149\n", + " 55.5\n", + " 3871\n", + " 54.4\n", " 1.1\n", " unknown\n", " \n", " \n", " Unknown\n", - " 294\n", - " 56.8\n", - " 518\n", - " 55.4\n", - " 1.4\n", - " 30-May\n", + " 581\n", + " 55.3\n", + " 1050\n", + " 54.7\n", + " 0.6\n", + " unknown\n", " \n", " \n", " brand_of_first_dose\n", " Moderna\n", " 0\n", " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", @@ -22942,20 +23045,20 @@ " \n", " \n", " Pfizer\n", - " 14\n", - " 66.7\n", " 21\n", - " 66.7\n", + " 50.0\n", + " 42\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 5488\n", - " 58.9\n", - " 9317\n", - " 57.7\n", - " 1.2\n", + " 11319\n", + " 61.2\n", + " 18487\n", + " 60.3\n", + " 0.9\n", " unknown\n", " \n", " \n", @@ -22965,69 +23068,69 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 5509 53.2 10346 \n", - "sex F 2765 52.2 5292 \n", - " M 2751 54.5 5047 \n", - "ethnicity_6_groups Black 952 54.2 1757 \n", - " Mixed 917 51.6 1778 \n", - " Other 931 53.4 1743 \n", - " South Asian 931 53.6 1736 \n", - " Unknown 847 53.8 1575 \n", - " White 938 53.6 1750 \n", - "imd_categories 1 Most deprived 1001 53.8 1862 \n", - " 2 1078 54.4 1981 \n", - " 3 1029 51.4 2002 \n", - " 4 1071 52.9 2023 \n", - " 5 Least deprived 1043 53.2 1960 \n", - " Unknown 294 56.8 518 \n", - "brand_of_first_dose Moderna 0 0.0 0 \n", + "overall overall 11354 55.0 20636 \n", + "sex F 5796 55.1 10514 \n", + " M 5565 55.0 10115 \n", + "ethnicity_6_groups Black 1932 55.2 3500 \n", + " Mixed 1918 54.0 3549 \n", + " Other 1988 56.3 3528 \n", + " South Asian 1904 53.6 3549 \n", + " Unknown 1715 56.6 3031 \n", + " White 1904 54.8 3472 \n", + "imd_categories 1 Most deprived 2156 54.2 3976 \n", + " 2 2128 54.8 3885 \n", + " 3 2247 57.1 3934 \n", + " 4 2093 53.3 3927 \n", + " 5 Least deprived 2149 55.5 3871 \n", + " Unknown 581 55.3 1050 \n", + "brand_of_first_dose Moderna 0 0.0 7 \n", " Oxford-AZ 7 50.0 14 \n", - " Pfizer 14 66.7 21 \n", - " Unknown 5488 58.9 9317 \n", + " Pfizer 21 50.0 42 \n", + " Unknown 11319 61.2 18487 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 52.2 \n", - "sex F 51.3 \n", - " M 53.1 \n", - "ethnicity_6_groups Black 53.0 \n", - " Mixed 50.4 \n", - " Other 52.2 \n", - " South Asian 52.8 \n", - " Unknown 52.9 \n", - " White 52.4 \n", - "imd_categories 1 Most deprived 53.0 \n", - " 2 53.4 \n", - " 3 50.0 \n", - " 4 51.6 \n", - " 5 Least deprived 52.1 \n", + "overall overall 54.2 \n", + "sex F 54.2 \n", + " M 54.3 \n", + "ethnicity_6_groups Black 54.4 \n", + " Mixed 53.3 \n", + " Other 55.2 \n", + " South Asian 52.9 \n", " Unknown 55.4 \n", - "brand_of_first_dose Moderna NaN \n", + " White 54.2 \n", + "imd_categories 1 Most deprived 53.5 \n", + " 2 54.1 \n", + " 3 56.2 \n", + " 4 52.6 \n", + " 5 Least deprived 54.4 \n", + " Unknown 54.7 \n", + "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 50.0 \n", - " Pfizer 66.7 \n", - " Unknown 57.7 \n", + " Pfizer 50.0 \n", + " Unknown 60.3 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.0 \n", + "overall overall 0.8 \n", "sex F 0.9 \n", - " M 1.4 \n", - "ethnicity_6_groups Black 1.2 \n", - " Mixed 1.2 \n", - " Other 1.2 \n", - " South Asian 0.8 \n", - " Unknown 0.9 \n", - " White 1.2 \n", - "imd_categories 1 Most deprived 0.8 \n", - " 2 1.0 \n", - " 3 1.4 \n", - " 4 1.3 \n", + " M 0.7 \n", + "ethnicity_6_groups Black 0.8 \n", + " Mixed 0.7 \n", + " Other 1.1 \n", + " South Asian 0.7 \n", + " Unknown 1.2 \n", + " White 0.6 \n", + "imd_categories 1 Most deprived 0.7 \n", + " 2 0.7 \n", + " 3 0.9 \n", + " 4 0.7 \n", " 5 Least deprived 1.1 \n", - " Unknown 1.4 \n", + " Unknown 0.6 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 1.2 \n", + " Unknown 0.9 \n", "\n", " Date projected to reach 90% \n", "category group \n", @@ -23045,7 +23148,7 @@ " 3 unknown \n", " 4 unknown \n", " 5 Least deprived unknown \n", - " Unknown 30-May \n", + " Unknown unknown \n", "brand_of_first_dose Moderna unknown \n", " Oxford-AZ unknown \n", " Pfizer unknown \n", @@ -23065,6 +23168,8 @@ } ], "source": [ + "\n", + "\n", "# data processing / summarising\n", "df_dict_cum_second_dose = cumulative_sums(df_s, groups_of_interest=population_subgroups, features_dict=features_dict_2, \n", " latest_date=latest_date, reference_column_name=\"covid_vacc_second_dose_date\")\n", @@ -23081,7 +23186,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 34, "metadata": {}, "outputs": [ { @@ -23113,7 +23218,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **80+** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **80+** population up to 2021-10-27" ], "text/plain": [ "" @@ -23179,560 +23284,560 @@ " \n", " overall\n", " overall\n", - " 1456\n", - " 68.0\n", - " 2142\n", - " 66.7\n", - " 1.3\n", - " 04-Jan\n", + " 2933\n", + " 69.5\n", + " 4221\n", + " 67.8\n", + " 1.7\n", + " 19-Jan\n", " \n", " \n", " sex\n", " F\n", - " 777\n", - " 68.9\n", - " 1127\n", - " 67.1\n", - " 1.8\n", - " 29-Nov\n", + " 1512\n", + " 69.5\n", + " 2177\n", + " 68.2\n", + " 1.3\n", + " 14-Feb\n", " \n", " \n", " M\n", - " 679\n", - " 66.9\n", - " 1015\n", - " 65.5\n", - " 1.4\n", - " 01-Jan\n", + " 1421\n", + " 69.5\n", + " 2044\n", + " 67.8\n", + " 1.7\n", + " 19-Jan\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", + " 42\n", + " 60.0\n", + " 70\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 0-15\n", - " 77\n", - " 68.8\n", - " 112\n", - " 68.8\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 16-17\n", - " 91\n", - " 65.0\n", - " 140\n", - " 65.0\n", + " 182\n", + " 70.3\n", + " 259\n", + " 67.6\n", + " 2.7\n", + " 17-Dec\n", + " \n", + " \n", + " 16-17\n", + " 175\n", + " 71.4\n", + " 245\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " 18-29\n", - " 84\n", - " 63.2\n", - " 133\n", - " 63.2\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 71.1\n", + " 266\n", + " 68.4\n", + " 2.7\n", + " 15-Dec\n", " \n", " \n", " 30-34\n", - " 98\n", - " 70.0\n", - " 140\n", - " 65.0\n", - " 5.0\n", - " 06-Oct\n", + " 182\n", + " 66.7\n", + " 273\n", + " 66.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 35-39\n", - " 98\n", - " 66.7\n", - " 147\n", - " 66.7\n", + " 189\n", + " 71.1\n", + " 266\n", + " 71.1\n", " 0.0\n", " unknown\n", " \n", " \n", " 40-44\n", - " 105\n", - " 71.4\n", - " 147\n", - " 71.4\n", + " 196\n", + " 71.8\n", + " 273\n", + " 71.8\n", " 0.0\n", " unknown\n", " \n", " \n", " 45-49\n", - " 91\n", - " 68.4\n", - " 133\n", - " 63.2\n", - " 5.2\n", - " 07-Oct\n", + " 196\n", + " 70.0\n", + " 280\n", + " 70.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 50-54\n", - " 98\n", - " 63.6\n", - " 154\n", - " 63.6\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 73.0\n", + " 259\n", + " 70.3\n", + " 2.7\n", + " 10-Dec\n", " \n", " \n", " 55-59\n", - " 105\n", - " 68.2\n", - " 154\n", - " 63.6\n", - " 4.6\n", - " 11-Oct\n", + " 210\n", + " 69.8\n", + " 301\n", + " 69.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 60-64\n", - " 84\n", - " 66.7\n", - " 126\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 182\n", + " 68.4\n", + " 266\n", + " 63.2\n", + " 5.2\n", + " 25-Nov\n", " \n", " \n", " 65-69\n", - " 112\n", - " 80.0\n", - " 140\n", - " 75.0\n", - " 5.0\n", - " 22-Sep\n", + " 189\n", + " 67.5\n", + " 280\n", + " 65.0\n", + " 2.5\n", + " 29-Dec\n", " \n", " \n", " 70-74\n", - " 91\n", - " 65.0\n", - " 140\n", - " 60.0\n", - " 5.0\n", - " 13-Oct\n", + " 203\n", + " 69.0\n", + " 294\n", + " 69.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 75-79\n", - " 84\n", - " 63.2\n", - " 133\n", - " 63.2\n", - " 0.0\n", - " unknown\n", + " 203\n", + " 72.5\n", + " 280\n", + " 70.0\n", + " 2.5\n", + " 15-Dec\n", " \n", " \n", " 80-84\n", - " 105\n", - " 75.0\n", - " 140\n", - " 70.0\n", - " 5.0\n", - " 29-Sep\n", + " 189\n", + " 69.2\n", + " 273\n", + " 66.7\n", + " 2.5\n", + " 24-Dec\n", " \n", " \n", " 85-89\n", - " 105\n", - " 68.2\n", - " 154\n", - " 68.2\n", - " 0.0\n", - " unknown\n", + " 203\n", + " 69.0\n", + " 294\n", + " 66.7\n", + " 2.3\n", + " 29-Dec\n", " \n", " \n", " 90+\n", " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 40.0\n", + " 35\n", + " 40.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 224\n", - " 62.7\n", - " 357\n", - " 62.7\n", - " 0.0\n", - " unknown\n", + " 504\n", + " 68.6\n", + " 735\n", + " 66.7\n", + " 1.9\n", + " 13-Jan\n", " \n", " \n", " Mixed\n", - " 238\n", - " 68.0\n", - " 350\n", + " 476\n", " 68.0\n", - " 0.0\n", - " unknown\n", + " 700\n", + " 66.0\n", + " 2.0\n", + " 12-Jan\n", " \n", " \n", " Other\n", - " 231\n", - " 68.8\n", - " 336\n", - " 68.8\n", - " 0.0\n", - " unknown\n", + " 525\n", + " 72.1\n", + " 728\n", + " 70.2\n", + " 1.9\n", + " 31-Dec\n", " \n", " \n", " South Asian\n", - " 252\n", + " 518\n", " 69.2\n", - " 364\n", + " 749\n", " 67.3\n", " 1.9\n", - " 23-Nov\n", + " 11-Jan\n", " \n", " \n", " Unknown\n", - " 231\n", - " 67.3\n", - " 343\n", - " 65.3\n", - " 2.0\n", - " 26-Nov\n", + " 427\n", + " 70.1\n", + " 609\n", + " 69.0\n", + " 1.1\n", + " 02-Mar\n", " \n", " \n", " White\n", - " 273\n", - " 69.6\n", - " 392\n", - " 67.9\n", - " 1.7\n", - " 01-Dec\n", + " 490\n", + " 68.6\n", + " 714\n", + " 66.7\n", + " 1.9\n", + " 13-Jan\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 70\n", - " 66.7\n", - " 105\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 168\n", + " 77.4\n", + " 217\n", + " 74.2\n", + " 3.2\n", + " 23-Nov\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 77\n", - " 64.7\n", - " 119\n", - " 64.7\n", + " 133\n", + " 63.3\n", + " 210\n", + " 63.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 77\n", - " 78.6\n", - " 98\n", - " 78.6\n", - " 0.0\n", - " unknown\n", + " 161\n", + " 74.2\n", + " 217\n", + " 71.0\n", + " 3.2\n", + " 30-Nov\n", " \n", " \n", " Chinese\n", - " 70\n", - " 66.7\n", - " 105\n", - " 60.0\n", - " 6.7\n", - " 02-Oct\n", + " 133\n", + " 61.3\n", + " 217\n", + " 61.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other\n", - " 84\n", - " 75.0\n", - " 112\n", - " 75.0\n", + " 182\n", + " 76.5\n", + " 238\n", + " 76.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 77\n", - " 68.8\n", - " 112\n", - " 68.8\n", - " 0.0\n", - " unknown\n", + " 147\n", + " 70.0\n", + " 210\n", + " 66.7\n", + " 3.3\n", + " 08-Dec\n", " \n", " \n", " British or Mixed British\n", - " 91\n", - " 68.4\n", - " 133\n", - " 68.4\n", - " 0.0\n", - " unknown\n", + " 147\n", + " 67.7\n", + " 217\n", + " 64.5\n", + " 3.2\n", + " 14-Dec\n", " \n", " \n", " Indian or British Indian\n", - " 77\n", - " 73.3\n", - " 105\n", - " 73.3\n", - " 0.0\n", - " unknown\n", + " 147\n", + " 65.6\n", + " 224\n", + " 62.5\n", + " 3.1\n", + " 21-Dec\n", " \n", " \n", " Irish\n", - " 84\n", - " 70.6\n", - " 119\n", - " 70.6\n", + " 161\n", + " 69.7\n", + " 231\n", + " 69.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 49\n", - " 58.3\n", - " 84\n", - " 58.3\n", + " 147\n", + " 67.7\n", + " 217\n", + " 67.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 84\n", - " 70.6\n", - " 119\n", - " 70.6\n", + " 161\n", + " 67.6\n", + " 238\n", + " 67.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 70\n", - " 66.7\n", - " 105\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 140\n", + " 69.0\n", + " 203\n", + " 65.5\n", + " 3.5\n", + " 08-Dec\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 70\n", - " 62.5\n", - " 112\n", - " 62.5\n", - " 0.0\n", - " unknown\n", + " 154\n", + " 68.8\n", + " 224\n", + " 65.6\n", + " 3.2\n", + " 12-Dec\n", " \n", " \n", " Unknown\n", - " 231\n", - " 67.3\n", - " 343\n", - " 67.3\n", - " 0.0\n", - " unknown\n", + " 462\n", + " 68.8\n", + " 672\n", + " 66.7\n", + " 2.1\n", + " 05-Jan\n", " \n", " \n", " White + Asian\n", - " 77\n", - " 64.7\n", - " 119\n", - " 64.7\n", - " 0.0\n", - " unknown\n", + " 154\n", + " 68.8\n", + " 224\n", + " 65.6\n", + " 3.2\n", + " 12-Dec\n", " \n", " \n", " White + Black African\n", - " 70\n", - " 66.7\n", - " 105\n", - " 60.0\n", - " 6.7\n", - " 02-Oct\n", + " 161\n", + " 76.7\n", + " 210\n", + " 76.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 98\n", - " 70.0\n", - " 140\n", - " 70.0\n", + " 175\n", + " 69.4\n", + " 252\n", + " 69.4\n", " 0.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 294\n", - " 70.0\n", - " 420\n", - " 68.3\n", - " 1.7\n", - " 29-Nov\n", + " 560\n", + " 69.6\n", + " 805\n", + " 67.8\n", + " 1.8\n", + " 14-Jan\n", " \n", " \n", " 2\n", - " 273\n", - " 67.2\n", - " 406\n", - " 65.5\n", + " 574\n", + " 71.3\n", + " 805\n", + " 69.6\n", " 1.7\n", - " 10-Dec\n", + " 12-Jan\n", " \n", " \n", " 3\n", - " 280\n", - " 71.4\n", - " 392\n", - " 69.6\n", - " 1.8\n", - " 19-Nov\n", + " 539\n", + " 69.4\n", + " 777\n", + " 68.5\n", + " 0.9\n", + " 05-Apr\n", " \n", " \n", " 4\n", - " 280\n", - " 65.6\n", - " 427\n", - " 63.9\n", + " 567\n", + " 69.2\n", + " 819\n", + " 67.5\n", " 1.7\n", - " 17-Dec\n", + " 20-Jan\n", " \n", " \n", " 5 Least deprived\n", - " 252\n", - " 64.3\n", - " 392\n", - " 64.3\n", - " 0.0\n", + " 546\n", + " 67.2\n", + " 812\n", + " 66.4\n", + " 0.8\n", " unknown\n", " \n", " \n", " Unknown\n", - " 77\n", - " 73.3\n", - " 105\n", - " 73.3\n", - " 0.0\n", - " unknown\n", + " 147\n", + " 70.0\n", + " 210\n", + " 66.7\n", + " 3.3\n", + " 08-Dec\n", " \n", " \n", " bmi\n", " 30+\n", - " 406\n", - " 68.2\n", - " 595\n", - " 67.1\n", - " 1.1\n", - " 24-Jan\n", + " 896\n", + " 69.2\n", + " 1295\n", + " 67.6\n", + " 1.6\n", + " 26-Jan\n", " \n", " \n", " under 30\n", - " 1050\n", + " 2037\n", + " 69.6\n", + " 2926\n", " 67.9\n", - " 1547\n", - " 66.1\n", - " 1.8\n", - " 02-Dec\n", + " 1.7\n", + " 19-Jan\n", " \n", " \n", " housebound\n", " no\n", - " 1435\n", - " 67.9\n", - " 2114\n", - " 66.6\n", - " 1.3\n", - " 05-Jan\n", + " 2898\n", + " 69.3\n", + " 4179\n", + " 67.7\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " yes\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", + " 35\n", + " 83.3\n", + " 42\n", + " 83.3\n", " 0.0\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1442\n", - " 68.0\n", - " 2121\n", - " 66.7\n", - " 1.3\n", - " 04-Jan\n", + " 2905\n", + " 69.4\n", + " 4186\n", + " 67.7\n", + " 1.7\n", + " 19-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 28\n", + " 80.0\n", + " 35\n", + " 80.0\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1442\n", - " 68.2\n", - " 2114\n", - " 66.9\n", - " 1.3\n", - " 03-Jan\n", + " 2898\n", + " 69.3\n", + " 4179\n", + " 67.7\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 71.4\n", + " 49\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1442\n", - " 68.2\n", - " 2114\n", - " 66.6\n", - " 1.6\n", - " 12-Dec\n", + " 2898\n", + " 69.5\n", + " 4172\n", + " 67.8\n", + " 1.7\n", + " 19-Jan\n", " \n", " \n", " yes\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", + " 35\n", + " 71.4\n", + " 49\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 1449\n", - " 68.3\n", - " 2121\n", - " 66.7\n", - " 1.6\n", - " 11-Dec\n", + " 2905\n", + " 69.5\n", + " 4179\n", + " 67.8\n", + " 1.7\n", + " 19-Jan\n", " \n", " \n", " yes\n", - " 14\n", + " 28\n", " 66.7\n", - " 21\n", + " 42\n", " 66.7\n", " 0.0\n", " unknown\n", @@ -23740,132 +23845,132 @@ " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1442\n", - " 68.0\n", - " 2121\n", - " 66.7\n", - " 1.3\n", - " 04-Jan\n", + " 2898\n", + " 69.3\n", + " 4179\n", + " 67.8\n", + " 1.5\n", + " 31-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", + " 35\n", + " 83.3\n", + " 42\n", " 66.7\n", - " 0.0\n", - " unknown\n", + " 16.6\n", + " 29-Oct\n", " \n", " \n", " LD\n", " no\n", - " 1435\n", - " 68.3\n", - " 2100\n", - " 66.7\n", - " 1.6\n", - " 11-Dec\n", + " 2863\n", + " 69.3\n", + " 4130\n", + " 67.6\n", + " 1.7\n", + " 20-Jan\n", " \n", " \n", " yes\n", - " 28\n", - " 66.7\n", - " 42\n", - " 66.7\n", + " 70\n", + " 71.4\n", + " 98\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1449\n", - " 68.1\n", - " 2128\n", - " 66.4\n", - " 1.7\n", - " 07-Dec\n", + " 2898\n", + " 69.3\n", + " 4179\n", + " 67.7\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 100.0\n", - " 14\n", - " 100.0\n", + " 35\n", + " 71.4\n", + " 49\n", + " 71.4\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 1449\n", - " 68.3\n", - " 2121\n", - " 67.0\n", - " 1.3\n", - " 02-Jan\n", + " 2905\n", + " 69.4\n", + " 4186\n", + " 67.7\n", + " 1.7\n", + " 19-Jan\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 28\n", + " 66.7\n", + " 42\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1442\n", - " 68.0\n", - " 2121\n", - " 66.7\n", - " 1.3\n", - " 04-Jan\n", + " 2912\n", + " 69.4\n", + " 4193\n", + " 67.8\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", " 21\n", - " 66.7\n", + " 60.0\n", + " 35\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1442\n", - " 68.0\n", - " 2121\n", - " 66.7\n", - " 1.3\n", - " 04-Jan\n", + " 2912\n", + " 69.4\n", + " 4193\n", + " 67.8\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", " 21\n", - " 66.7\n", + " 60.0\n", + " 35\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1449\n", - " 68.3\n", - " 2121\n", - " 66.7\n", - " 1.6\n", - " 11-Dec\n", + " 2905\n", + " 69.5\n", + " 4179\n", + " 67.8\n", + " 1.7\n", + " 19-Jan\n", " \n", " \n", " yes\n", - " 14\n", + " 28\n", " 66.7\n", - " 21\n", + " 42\n", " 66.7\n", " 0.0\n", " unknown\n", @@ -23873,21 +23978,21 @@ " \n", " ckd\n", " no\n", - " 1183\n", - " 68.7\n", - " 1722\n", - " 67.1\n", - " 1.6\n", - " 10-Dec\n", + " 2387\n", + " 70.3\n", + " 3395\n", + " 68.9\n", + " 1.4\n", + " 02-Feb\n", " \n", " \n", " yes\n", - " 280\n", - " 66.7\n", - " 420\n", - " 65.0\n", + " 546\n", + " 66.1\n", + " 826\n", + " 64.4\n", " 1.7\n", - " 12-Dec\n", + " 02-Feb\n", " \n", " \n", " brand_of_first_dose\n", @@ -23903,8 +24008,8 @@ " Oxford-AZ\n", " 0\n", " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", @@ -23919,12 +24024,12 @@ " \n", " \n", " Unknown\n", - " 1456\n", - " 75.4\n", - " 1932\n", - " 73.6\n", + " 2926\n", + " 77.4\n", + " 3780\n", + " 75.6\n", " 1.8\n", - " 03-Nov\n", + " 15-Dec\n", " \n", " \n", "\n", @@ -23933,334 +24038,334 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1456 \n", - "sex F 777 \n", - " M 679 \n", - "ageband_5yr 0 21 \n", - " 0-15 77 \n", - " 16-17 91 \n", - " 18-29 84 \n", - " 30-34 98 \n", - " 35-39 98 \n", - " 40-44 105 \n", - " 45-49 91 \n", - " 50-54 98 \n", - " 55-59 105 \n", - " 60-64 84 \n", - " 65-69 112 \n", - " 70-74 91 \n", - " 75-79 84 \n", - " 80-84 105 \n", - " 85-89 105 \n", + "overall overall 2933 \n", + "sex F 1512 \n", + " M 1421 \n", + "ageband_5yr 0 42 \n", + " 0-15 182 \n", + " 16-17 175 \n", + " 18-29 189 \n", + " 30-34 182 \n", + " 35-39 189 \n", + " 40-44 196 \n", + " 45-49 196 \n", + " 50-54 189 \n", + " 55-59 210 \n", + " 60-64 182 \n", + " 65-69 189 \n", + " 70-74 203 \n", + " 75-79 203 \n", + " 80-84 189 \n", + " 85-89 203 \n", " 90+ 14 \n", - "ethnicity_6_groups Black 224 \n", - " Mixed 238 \n", - " Other 231 \n", - " South Asian 252 \n", - " Unknown 231 \n", - " White 273 \n", - "ethnicity_16_groups African 70 \n", - " Bangladeshi or British Bangladeshi 77 \n", - " Caribbean 77 \n", - " Chinese 70 \n", - " Other 84 \n", - " Other Asian 77 \n", - " British or Mixed British 91 \n", - " Indian or British Indian 77 \n", - " Irish 84 \n", - " Other Black 49 \n", - " Other White 84 \n", - " Other mixed 70 \n", - " Pakistani or British Pakistani 70 \n", - " Unknown 231 \n", - " White + Asian 77 \n", - " White + Black African 70 \n", - " White + Black Caribbean 98 \n", - "imd_categories 1 Most deprived 294 \n", - " 2 273 \n", - " 3 280 \n", - " 4 280 \n", - " 5 Least deprived 252 \n", - " Unknown 77 \n", - "bmi 30+ 406 \n", - " under 30 1050 \n", - "housebound no 1435 \n", + "ethnicity_6_groups Black 504 \n", + " Mixed 476 \n", + " Other 525 \n", + " South Asian 518 \n", + " Unknown 427 \n", + " White 490 \n", + "ethnicity_16_groups African 168 \n", + " Bangladeshi or British Bangladeshi 133 \n", + " Caribbean 161 \n", + " Chinese 133 \n", + " Other 182 \n", + " Other Asian 147 \n", + " British or Mixed British 147 \n", + " Indian or British Indian 147 \n", + " Irish 161 \n", + " Other Black 147 \n", + " Other White 161 \n", + " Other mixed 140 \n", + " Pakistani or British Pakistani 154 \n", + " Unknown 462 \n", + " White + Asian 154 \n", + " White + Black African 161 \n", + " White + Black Caribbean 175 \n", + "imd_categories 1 Most deprived 560 \n", + " 2 574 \n", + " 3 539 \n", + " 4 567 \n", + " 5 Least deprived 546 \n", + " Unknown 147 \n", + "bmi 30+ 896 \n", + " under 30 2037 \n", + "housebound no 2898 \n", + " yes 35 \n", + "chronic_cardiac_disease no 2905 \n", + " yes 28 \n", + "current_copd no 2898 \n", + " yes 35 \n", + "dmards no 2898 \n", + " yes 35 \n", + "dementia no 2905 \n", + " yes 28 \n", + "psychosis_schiz_bipolar no 2898 \n", + " yes 35 \n", + "LD no 2863 \n", + " yes 70 \n", + "ssri no 2898 \n", + " yes 35 \n", + "chemo_or_radio no 2905 \n", + " yes 28 \n", + "lung_cancer no 2912 \n", " yes 21 \n", - "chronic_cardiac_disease no 1442 \n", - " yes 14 \n", - "current_copd no 1442 \n", - " yes 14 \n", - "dmards no 1442 \n", + "cancer_excl_lung_and_haem no 2912 \n", " yes 21 \n", - "dementia no 1449 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1442 \n", - " yes 14 \n", - "LD no 1435 \n", + "haematological_cancer no 2905 \n", " yes 28 \n", - "ssri no 1449 \n", - " yes 14 \n", - "chemo_or_radio no 1449 \n", - " yes 7 \n", - "lung_cancer no 1442 \n", - " yes 14 \n", - "cancer_excl_lung_and_haem no 1442 \n", - " yes 14 \n", - "haematological_cancer no 1449 \n", - " yes 14 \n", - "ckd no 1183 \n", - " yes 280 \n", + "ckd no 2387 \n", + " yes 546 \n", "brand_of_first_dose Moderna 0 \n", " Oxford-AZ 0 \n", " Pfizer 0 \n", - " Unknown 1456 \n", + " Unknown 2926 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 68.0 2142 \n", - "sex F 68.9 1127 \n", - " M 66.9 1015 \n", - "ageband_5yr 0 75.0 28 \n", - " 0-15 68.8 112 \n", - " 16-17 65.0 140 \n", - " 18-29 63.2 133 \n", - " 30-34 70.0 140 \n", - " 35-39 66.7 147 \n", - " 40-44 71.4 147 \n", - " 45-49 68.4 133 \n", - " 50-54 63.6 154 \n", - " 55-59 68.2 154 \n", - " 60-64 66.7 126 \n", - " 65-69 80.0 140 \n", - " 70-74 65.0 140 \n", - " 75-79 63.2 133 \n", - " 80-84 75.0 140 \n", - " 85-89 68.2 154 \n", - " 90+ 66.7 21 \n", - "ethnicity_6_groups Black 62.7 357 \n", - " Mixed 68.0 350 \n", - " Other 68.8 336 \n", - " South Asian 69.2 364 \n", - " Unknown 67.3 343 \n", - " White 69.6 392 \n", - "ethnicity_16_groups African 66.7 105 \n", - " Bangladeshi or British Bangladeshi 64.7 119 \n", - " Caribbean 78.6 98 \n", - " Chinese 66.7 105 \n", - " Other 75.0 112 \n", - " Other Asian 68.8 112 \n", - " British or Mixed British 68.4 133 \n", - " Indian or British Indian 73.3 105 \n", - " Irish 70.6 119 \n", - " Other Black 58.3 84 \n", - " Other White 70.6 119 \n", - " Other mixed 66.7 105 \n", - " Pakistani or British Pakistani 62.5 112 \n", - " Unknown 67.3 343 \n", - " White + Asian 64.7 119 \n", - " White + Black African 66.7 105 \n", - " White + Black Caribbean 70.0 140 \n", - "imd_categories 1 Most deprived 70.0 420 \n", - " 2 67.2 406 \n", - " 3 71.4 392 \n", - " 4 65.6 427 \n", - " 5 Least deprived 64.3 392 \n", - " Unknown 73.3 105 \n", - "bmi 30+ 68.2 595 \n", - " under 30 67.9 1547 \n", - "housebound no 67.9 2114 \n", - " yes 75.0 28 \n", - "chronic_cardiac_disease no 68.0 2121 \n", - " yes 66.7 21 \n", - "current_copd no 68.2 2114 \n", - " yes 66.7 21 \n", - "dmards no 68.2 2114 \n", - " yes 75.0 28 \n", - "dementia no 68.3 2121 \n", - " yes 66.7 21 \n", - "psychosis_schiz_bipolar no 68.0 2121 \n", - " yes 66.7 21 \n", - "LD no 68.3 2100 \n", + "overall overall 69.5 4221 \n", + "sex F 69.5 2177 \n", + " M 69.5 2044 \n", + "ageband_5yr 0 60.0 70 \n", + " 0-15 70.3 259 \n", + " 16-17 71.4 245 \n", + " 18-29 71.1 266 \n", + " 30-34 66.7 273 \n", + " 35-39 71.1 266 \n", + " 40-44 71.8 273 \n", + " 45-49 70.0 280 \n", + " 50-54 73.0 259 \n", + " 55-59 69.8 301 \n", + " 60-64 68.4 266 \n", + " 65-69 67.5 280 \n", + " 70-74 69.0 294 \n", + " 75-79 72.5 280 \n", + " 80-84 69.2 273 \n", + " 85-89 69.0 294 \n", + " 90+ 40.0 35 \n", + "ethnicity_6_groups Black 68.6 735 \n", + " Mixed 68.0 700 \n", + " Other 72.1 728 \n", + " South Asian 69.2 749 \n", + " Unknown 70.1 609 \n", + " White 68.6 714 \n", + "ethnicity_16_groups African 77.4 217 \n", + " Bangladeshi or British Bangladeshi 63.3 210 \n", + " Caribbean 74.2 217 \n", + " Chinese 61.3 217 \n", + " Other 76.5 238 \n", + " Other Asian 70.0 210 \n", + " British or Mixed British 67.7 217 \n", + " Indian or British Indian 65.6 224 \n", + " Irish 69.7 231 \n", + " Other Black 67.7 217 \n", + " Other White 67.6 238 \n", + " Other mixed 69.0 203 \n", + " Pakistani or British Pakistani 68.8 224 \n", + " Unknown 68.8 672 \n", + " White + Asian 68.8 224 \n", + " White + Black African 76.7 210 \n", + " White + Black Caribbean 69.4 252 \n", + "imd_categories 1 Most deprived 69.6 805 \n", + " 2 71.3 805 \n", + " 3 69.4 777 \n", + " 4 69.2 819 \n", + " 5 Least deprived 67.2 812 \n", + " Unknown 70.0 210 \n", + "bmi 30+ 69.2 1295 \n", + " under 30 69.6 2926 \n", + "housebound no 69.3 4179 \n", + " yes 83.3 42 \n", + "chronic_cardiac_disease no 69.4 4186 \n", + " yes 80.0 35 \n", + "current_copd no 69.3 4179 \n", + " yes 71.4 49 \n", + "dmards no 69.5 4172 \n", + " yes 71.4 49 \n", + "dementia no 69.5 4179 \n", + " yes 66.7 42 \n", + "psychosis_schiz_bipolar no 69.3 4179 \n", + " yes 83.3 42 \n", + "LD no 69.3 4130 \n", + " yes 71.4 98 \n", + "ssri no 69.3 4179 \n", + " yes 71.4 49 \n", + "chemo_or_radio no 69.4 4186 \n", + " yes 66.7 42 \n", + "lung_cancer no 69.4 4193 \n", + " yes 60.0 35 \n", + "cancer_excl_lung_and_haem no 69.4 4193 \n", + " yes 60.0 35 \n", + "haematological_cancer no 69.5 4179 \n", " yes 66.7 42 \n", - "ssri no 68.1 2128 \n", - " yes 100.0 14 \n", - "chemo_or_radio no 68.3 2121 \n", - " yes 33.3 21 \n", - "lung_cancer no 68.0 2121 \n", - " yes 66.7 21 \n", - "cancer_excl_lung_and_haem no 68.0 2121 \n", - " yes 66.7 21 \n", - "haematological_cancer no 68.3 2121 \n", - " yes 66.7 21 \n", - "ckd no 68.7 1722 \n", - " yes 66.7 420 \n", + "ckd no 70.3 3395 \n", + " yes 66.1 826 \n", "brand_of_first_dose Moderna 0.0 0 \n", - " Oxford-AZ 0.0 0 \n", + " Oxford-AZ 0.0 7 \n", " Pfizer 0.0 0 \n", - " Unknown 75.4 1932 \n", + " Unknown 77.4 3780 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 66.7 \n", - "sex F 67.1 \n", - " M 65.5 \n", - "ageband_5yr 0 75.0 \n", - " 0-15 68.8 \n", - " 16-17 65.0 \n", - " 18-29 63.2 \n", - " 30-34 65.0 \n", - " 35-39 66.7 \n", - " 40-44 71.4 \n", - " 45-49 63.2 \n", - " 50-54 63.6 \n", - " 55-59 63.6 \n", - " 60-64 66.7 \n", - " 65-69 75.0 \n", - " 70-74 60.0 \n", - " 75-79 63.2 \n", - " 80-84 70.0 \n", - " 85-89 68.2 \n", - " 90+ 66.7 \n", - "ethnicity_6_groups Black 62.7 \n", - " Mixed 68.0 \n", - " Other 68.8 \n", + "overall overall 67.8 \n", + "sex F 68.2 \n", + " M 67.8 \n", + "ageband_5yr 0 60.0 \n", + " 0-15 67.6 \n", + " 16-17 71.4 \n", + " 18-29 68.4 \n", + " 30-34 66.7 \n", + " 35-39 71.1 \n", + " 40-44 71.8 \n", + " 45-49 70.0 \n", + " 50-54 70.3 \n", + " 55-59 69.8 \n", + " 60-64 63.2 \n", + " 65-69 65.0 \n", + " 70-74 69.0 \n", + " 75-79 70.0 \n", + " 80-84 66.7 \n", + " 85-89 66.7 \n", + " 90+ 40.0 \n", + "ethnicity_6_groups Black 66.7 \n", + " Mixed 66.0 \n", + " Other 70.2 \n", " South Asian 67.3 \n", - " Unknown 65.3 \n", - " White 67.9 \n", - "ethnicity_16_groups African 66.7 \n", - " Bangladeshi or British Bangladeshi 64.7 \n", - " Caribbean 78.6 \n", - " Chinese 60.0 \n", - " Other 75.0 \n", - " Other Asian 68.8 \n", - " British or Mixed British 68.4 \n", - " Indian or British Indian 73.3 \n", - " Irish 70.6 \n", - " Other Black 58.3 \n", - " Other White 70.6 \n", - " Other mixed 66.7 \n", - " Pakistani or British Pakistani 62.5 \n", - " Unknown 67.3 \n", - " White + Asian 64.7 \n", - " White + Black African 60.0 \n", - " White + Black Caribbean 70.0 \n", - "imd_categories 1 Most deprived 68.3 \n", - " 2 65.5 \n", - " 3 69.6 \n", - " 4 63.9 \n", - " 5 Least deprived 64.3 \n", - " Unknown 73.3 \n", - "bmi 30+ 67.1 \n", - " under 30 66.1 \n", - "housebound no 66.6 \n", - " yes 75.0 \n", - "chronic_cardiac_disease no 66.7 \n", - " yes 66.7 \n", - "current_copd no 66.9 \n", - " yes 66.7 \n", - "dmards no 66.6 \n", - " yes 75.0 \n", - "dementia no 66.7 \n", - " yes 66.7 \n", - "psychosis_schiz_bipolar no 66.7 \n", - " yes 66.7 \n", - "LD no 66.7 \n", + " Unknown 69.0 \n", + " White 66.7 \n", + "ethnicity_16_groups African 74.2 \n", + " Bangladeshi or British Bangladeshi 63.3 \n", + " Caribbean 71.0 \n", + " Chinese 61.3 \n", + " Other 76.5 \n", + " Other Asian 66.7 \n", + " British or Mixed British 64.5 \n", + " Indian or British Indian 62.5 \n", + " Irish 69.7 \n", + " Other Black 67.7 \n", + " Other White 67.6 \n", + " Other mixed 65.5 \n", + " Pakistani or British Pakistani 65.6 \n", + " Unknown 66.7 \n", + " White + Asian 65.6 \n", + " White + Black African 76.7 \n", + " White + Black Caribbean 69.4 \n", + "imd_categories 1 Most deprived 67.8 \n", + " 2 69.6 \n", + " 3 68.5 \n", + " 4 67.5 \n", + " 5 Least deprived 66.4 \n", + " Unknown 66.7 \n", + "bmi 30+ 67.6 \n", + " under 30 67.9 \n", + "housebound no 67.7 \n", + " yes 83.3 \n", + "chronic_cardiac_disease no 67.7 \n", + " yes 80.0 \n", + "current_copd no 67.7 \n", + " yes 71.4 \n", + "dmards no 67.8 \n", + " yes 71.4 \n", + "dementia no 67.8 \n", " yes 66.7 \n", - "ssri no 66.4 \n", - " yes 100.0 \n", - "chemo_or_radio no 67.0 \n", - " yes 33.3 \n", - "lung_cancer no 66.7 \n", + "psychosis_schiz_bipolar no 67.8 \n", " yes 66.7 \n", - "cancer_excl_lung_and_haem no 66.7 \n", + "LD no 67.6 \n", + " yes 71.4 \n", + "ssri no 67.7 \n", + " yes 71.4 \n", + "chemo_or_radio no 67.7 \n", " yes 66.7 \n", - "haematological_cancer no 66.7 \n", + "lung_cancer no 67.8 \n", + " yes 60.0 \n", + "cancer_excl_lung_and_haem no 67.8 \n", + " yes 60.0 \n", + "haematological_cancer no 67.8 \n", " yes 66.7 \n", - "ckd no 67.1 \n", - " yes 65.0 \n", + "ckd no 68.9 \n", + " yes 64.4 \n", "brand_of_first_dose Moderna NaN \n", - " Oxford-AZ NaN \n", + " Oxford-AZ 0.0 \n", " Pfizer NaN \n", - " Unknown 73.6 \n", + " Unknown 75.6 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.3 \n", - "sex F 1.8 \n", - " M 1.4 \n", + "overall overall 1.7 \n", + "sex F 1.3 \n", + " M 1.7 \n", "ageband_5yr 0 0.0 \n", - " 0-15 0.0 \n", + " 0-15 2.7 \n", " 16-17 0.0 \n", - " 18-29 0.0 \n", - " 30-34 5.0 \n", + " 18-29 2.7 \n", + " 30-34 0.0 \n", " 35-39 0.0 \n", " 40-44 0.0 \n", - " 45-49 5.2 \n", - " 50-54 0.0 \n", - " 55-59 4.6 \n", - " 60-64 0.0 \n", - " 65-69 5.0 \n", - " 70-74 5.0 \n", - " 75-79 0.0 \n", - " 80-84 5.0 \n", - " 85-89 0.0 \n", + " 45-49 0.0 \n", + " 50-54 2.7 \n", + " 55-59 0.0 \n", + " 60-64 5.2 \n", + " 65-69 2.5 \n", + " 70-74 0.0 \n", + " 75-79 2.5 \n", + " 80-84 2.5 \n", + " 85-89 2.3 \n", " 90+ 0.0 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 0.0 \n", - " Other 0.0 \n", + "ethnicity_6_groups Black 1.9 \n", + " Mixed 2.0 \n", + " Other 1.9 \n", " South Asian 1.9 \n", - " Unknown 2.0 \n", - " White 1.7 \n", - "ethnicity_16_groups African 0.0 \n", + " Unknown 1.1 \n", + " White 1.9 \n", + "ethnicity_16_groups African 3.2 \n", " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", - " Chinese 6.7 \n", + " Caribbean 3.2 \n", + " Chinese 0.0 \n", " Other 0.0 \n", - " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 0.0 \n", + " Other Asian 3.3 \n", + " British or Mixed British 3.2 \n", + " Indian or British Indian 3.1 \n", " Irish 0.0 \n", " Other Black 0.0 \n", " Other White 0.0 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 0.0 \n", - " White + Asian 0.0 \n", - " White + Black African 6.7 \n", + " Other mixed 3.5 \n", + " Pakistani or British Pakistani 3.2 \n", + " Unknown 2.1 \n", + " White + Asian 3.2 \n", + " White + Black African 0.0 \n", " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 1.7 \n", + "imd_categories 1 Most deprived 1.8 \n", " 2 1.7 \n", - " 3 1.8 \n", + " 3 0.9 \n", " 4 1.7 \n", - " 5 Least deprived 0.0 \n", - " Unknown 0.0 \n", - "bmi 30+ 1.1 \n", - " under 30 1.8 \n", - "housebound no 1.3 \n", - " yes 0.0 \n", - "chronic_cardiac_disease no 1.3 \n", + " 5 Least deprived 0.8 \n", + " Unknown 3.3 \n", + "bmi 30+ 1.6 \n", + " under 30 1.7 \n", + "housebound no 1.6 \n", " yes 0.0 \n", - "current_copd no 1.3 \n", + "chronic_cardiac_disease no 1.7 \n", " yes 0.0 \n", - "dmards no 1.6 \n", + "current_copd no 1.6 \n", " yes 0.0 \n", - "dementia no 1.6 \n", + "dmards no 1.7 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.3 \n", + "dementia no 1.7 \n", " yes 0.0 \n", - "LD no 1.6 \n", + "psychosis_schiz_bipolar no 1.5 \n", + " yes 16.6 \n", + "LD no 1.7 \n", " yes 0.0 \n", - "ssri no 1.7 \n", + "ssri no 1.6 \n", " yes 0.0 \n", - "chemo_or_radio no 1.3 \n", + "chemo_or_radio no 1.7 \n", " yes 0.0 \n", - "lung_cancer no 1.3 \n", + "lung_cancer no 1.6 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.3 \n", + "cancer_excl_lung_and_haem no 1.6 \n", " yes 0.0 \n", - "haematological_cancer no 1.6 \n", + "haematological_cancer no 1.7 \n", " yes 0.0 \n", - "ckd no 1.6 \n", + "ckd no 1.4 \n", " yes 1.7 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", @@ -24269,87 +24374,87 @@ "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 04-Jan \n", - "sex F 29-Nov \n", - " M 01-Jan \n", + "overall overall 19-Jan \n", + "sex F 14-Feb \n", + " M 19-Jan \n", "ageband_5yr 0 unknown \n", - " 0-15 unknown \n", + " 0-15 17-Dec \n", " 16-17 unknown \n", - " 18-29 unknown \n", - " 30-34 06-Oct \n", + " 18-29 15-Dec \n", + " 30-34 unknown \n", " 35-39 unknown \n", " 40-44 unknown \n", - " 45-49 07-Oct \n", - " 50-54 unknown \n", - " 55-59 11-Oct \n", - " 60-64 unknown \n", - " 65-69 22-Sep \n", - " 70-74 13-Oct \n", - " 75-79 unknown \n", - " 80-84 29-Sep \n", - " 85-89 unknown \n", + " 45-49 unknown \n", + " 50-54 10-Dec \n", + " 55-59 unknown \n", + " 60-64 25-Nov \n", + " 65-69 29-Dec \n", + " 70-74 unknown \n", + " 75-79 15-Dec \n", + " 80-84 24-Dec \n", + " 85-89 29-Dec \n", " 90+ unknown \n", - "ethnicity_6_groups Black unknown \n", - " Mixed unknown \n", - " Other unknown \n", - " South Asian 23-Nov \n", - " Unknown 26-Nov \n", - " White 01-Dec \n", - "ethnicity_16_groups African unknown \n", + "ethnicity_6_groups Black 13-Jan \n", + " Mixed 12-Jan \n", + " Other 31-Dec \n", + " South Asian 11-Jan \n", + " Unknown 02-Mar \n", + " White 13-Jan \n", + "ethnicity_16_groups African 23-Nov \n", " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean unknown \n", - " Chinese 02-Oct \n", + " Caribbean 30-Nov \n", + " Chinese unknown \n", " Other unknown \n", - " Other Asian unknown \n", - " British or Mixed British unknown \n", - " Indian or British Indian unknown \n", + " Other Asian 08-Dec \n", + " British or Mixed British 14-Dec \n", + " Indian or British Indian 21-Dec \n", " Irish unknown \n", " Other Black unknown \n", " Other White unknown \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani unknown \n", - " Unknown unknown \n", - " White + Asian unknown \n", - " White + Black African 02-Oct \n", + " Other mixed 08-Dec \n", + " Pakistani or British Pakistani 12-Dec \n", + " Unknown 05-Jan \n", + " White + Asian 12-Dec \n", + " White + Black African unknown \n", " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived 29-Nov \n", - " 2 10-Dec \n", - " 3 19-Nov \n", - " 4 17-Dec \n", + "imd_categories 1 Most deprived 14-Jan \n", + " 2 12-Jan \n", + " 3 05-Apr \n", + " 4 20-Jan \n", " 5 Least deprived unknown \n", - " Unknown unknown \n", - "bmi 30+ 24-Jan \n", - " under 30 02-Dec \n", - "housebound no 05-Jan \n", + " Unknown 08-Dec \n", + "bmi 30+ 26-Jan \n", + " under 30 19-Jan \n", + "housebound no 25-Jan \n", " yes unknown \n", - "chronic_cardiac_disease no 04-Jan \n", + "chronic_cardiac_disease no 19-Jan \n", " yes unknown \n", - "current_copd no 03-Jan \n", + "current_copd no 25-Jan \n", " yes unknown \n", - "dmards no 12-Dec \n", + "dmards no 19-Jan \n", " yes unknown \n", - "dementia no 11-Dec \n", + "dementia no 19-Jan \n", " yes unknown \n", - "psychosis_schiz_bipolar no 04-Jan \n", + "psychosis_schiz_bipolar no 31-Jan \n", + " yes 29-Oct \n", + "LD no 20-Jan \n", " yes unknown \n", - "LD no 11-Dec \n", + "ssri no 25-Jan \n", " yes unknown \n", - "ssri no 07-Dec \n", - " yes reached \n", - "chemo_or_radio no 02-Jan \n", + "chemo_or_radio no 19-Jan \n", " yes unknown \n", - "lung_cancer no 04-Jan \n", + "lung_cancer no 25-Jan \n", " yes unknown \n", - "cancer_excl_lung_and_haem no 04-Jan \n", + "cancer_excl_lung_and_haem no 25-Jan \n", " yes unknown \n", - "haematological_cancer no 11-Dec \n", + "haematological_cancer no 19-Jan \n", " yes unknown \n", - "ckd no 10-Dec \n", - " yes 12-Dec \n", + "ckd no 02-Feb \n", + " yes 02-Feb \n", "brand_of_first_dose Moderna unknown \n", " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 03-Nov " + " Unknown 15-Dec " ] }, "metadata": {}, @@ -24378,7 +24483,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **70-79** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **70-79** population up to 2021-10-27" ], "text/plain": [ "" @@ -24444,715 +24549,715 @@ " \n", " overall\n", " overall\n", - " 2275\n", - " 65.4\n", - " 3479\n", - " 63.8\n", + " 4753\n", + " 69.3\n", + " 6860\n", + " 67.7\n", " 1.6\n", - " 24-Dec\n", + " 25-Jan\n", " \n", " \n", " sex\n", " F\n", - " 1162\n", - " 66.1\n", - " 1757\n", - " 64.9\n", - " 1.2\n", - " 25-Jan\n", + " 2478\n", + " 70.0\n", + " 3542\n", + " 68.6\n", + " 1.4\n", + " 04-Feb\n", " \n", " \n", " M\n", - " 1106\n", - " 64.2\n", - " 1722\n", - " 62.6\n", - " 1.6\n", - " 29-Dec\n", + " 2268\n", + " 68.4\n", + " 3318\n", + " 66.7\n", + " 1.7\n", + " 23-Jan\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 28\n", - " 66.7\n", - " 42\n", - " 66.7\n", + " 63\n", + " 75.0\n", + " 84\n", + " 75.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 0-15\n", - " 147\n", - " 70.0\n", - " 210\n", - " 66.7\n", - " 3.3\n", - " 20-Oct\n", + " 294\n", + " 68.9\n", + " 427\n", + " 68.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 16-17\n", - " 168\n", - " 63.2\n", - " 266\n", - " 63.2\n", + " 301\n", + " 66.2\n", + " 455\n", + " 66.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 18-29\n", - " 140\n", - " 60.6\n", - " 231\n", - " 60.6\n", - " 0.0\n", - " unknown\n", + " 287\n", + " 66.1\n", + " 434\n", + " 64.5\n", + " 1.6\n", + " 08-Feb\n", " \n", " \n", " 30-34\n", - " 175\n", - " 67.6\n", - " 259\n", - " 64.9\n", - " 2.7\n", - " 05-Nov\n", + " 343\n", + " 73.1\n", + " 469\n", + " 70.1\n", + " 3.0\n", + " 05-Dec\n", " \n", " \n", " 35-39\n", - " 140\n", - " 64.5\n", - " 217\n", - " 64.5\n", - " 0.0\n", - " unknown\n", + " 308\n", + " 66.7\n", + " 462\n", + " 65.2\n", + " 1.5\n", + " 12-Feb\n", " \n", " \n", " 40-44\n", - " 140\n", - " 66.7\n", - " 210\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 287\n", + " 66.1\n", + " 434\n", + " 64.5\n", + " 1.6\n", + " 08-Feb\n", " \n", " \n", " 45-49\n", - " 161\n", - " 69.7\n", - " 231\n", - " 69.7\n", - " 0.0\n", - " unknown\n", + " 308\n", + " 68.8\n", + " 448\n", + " 67.2\n", + " 1.6\n", + " 27-Jan\n", " \n", " \n", " 50-54\n", - " 126\n", - " 58.1\n", - " 217\n", - " 58.1\n", - " 0.0\n", - " unknown\n", + " 322\n", + " 74.2\n", + " 434\n", + " 71.0\n", + " 3.2\n", + " 30-Nov\n", " \n", " \n", " 55-59\n", - " 133\n", - " 63.3\n", - " 210\n", - " 63.3\n", - " 0.0\n", - " unknown\n", + " 308\n", + " 67.7\n", + " 455\n", + " 64.6\n", + " 3.1\n", + " 16-Dec\n", " \n", " \n", " 60-64\n", - " 161\n", - " 67.6\n", - " 238\n", - " 67.6\n", - " 0.0\n", - " unknown\n", + " 315\n", + " 70.3\n", + " 448\n", + " 68.8\n", + " 1.5\n", + " 26-Jan\n", " \n", " \n", " 65-69\n", - " 147\n", - " 65.6\n", - " 224\n", - " 62.5\n", - " 3.1\n", - " 02-Nov\n", + " 315\n", + " 70.3\n", + " 448\n", + " 68.8\n", + " 1.5\n", + " 26-Jan\n", " \n", " \n", " 70-74\n", - " 126\n", - " 64.3\n", - " 196\n", - " 60.7\n", - " 3.6\n", - " 27-Oct\n", + " 301\n", + " 69.4\n", + " 434\n", + " 69.4\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 75-79\n", - " 147\n", - " 61.8\n", - " 238\n", - " 58.8\n", - " 3.0\n", - " 12-Nov\n", + " 315\n", + " 69.2\n", + " 455\n", + " 67.7\n", + " 1.5\n", + " 01-Feb\n", " \n", " \n", " 80-84\n", - " 168\n", - " 70.6\n", - " 238\n", - " 70.6\n", + " 301\n", + " 68.3\n", + " 441\n", + " 68.3\n", " 0.0\n", " unknown\n", " \n", " \n", " 85-89\n", - " 147\n", - " 67.7\n", - " 217\n", - " 64.5\n", - " 3.2\n", - " 26-Oct\n", + " 322\n", + " 71.9\n", + " 448\n", + " 70.3\n", + " 1.6\n", + " 14-Jan\n", " \n", " \n", " 90+\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 63\n", + " 75.0\n", + " 84\n", + " 66.7\n", + " 8.3\n", + " 08-Nov\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 406\n", - " 66.7\n", - " 609\n", - " 65.5\n", + " 805\n", + " 69.7\n", + " 1155\n", + " 68.5\n", " 1.2\n", - " 21-Jan\n", + " 22-Feb\n", " \n", " \n", " Mixed\n", - " 413\n", - " 67.0\n", - " 616\n", - " 64.8\n", - " 2.2\n", - " 20-Nov\n", + " 826\n", + " 69.4\n", + " 1190\n", + " 67.1\n", + " 2.3\n", + " 28-Dec\n", " \n", " \n", " Other\n", - " 378\n", - " 65.9\n", - " 574\n", - " 63.4\n", - " 2.5\n", - " 14-Nov\n", + " 826\n", + " 70.2\n", + " 1176\n", + " 68.5\n", + " 1.7\n", + " 16-Jan\n", " \n", " \n", " South Asian\n", - " 357\n", - " 63.0\n", - " 567\n", - " 61.7\n", - " 1.3\n", - " 31-Jan\n", + " 826\n", + " 68.6\n", + " 1204\n", + " 66.9\n", + " 1.7\n", + " 23-Jan\n", " \n", " \n", " Unknown\n", - " 322\n", - " 63.9\n", - " 504\n", - " 62.5\n", + " 721\n", + " 70.1\n", + " 1029\n", + " 68.7\n", " 1.4\n", - " 16-Jan\n", + " 03-Feb\n", " \n", " \n", " White\n", - " 392\n", - " 64.4\n", - " 609\n", - " 63.2\n", - " 1.2\n", - " 04-Feb\n", + " 742\n", + " 67.5\n", + " 1099\n", + " 66.9\n", + " 0.6\n", + " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 133\n", - " 65.5\n", - " 203\n", - " 65.5\n", - " 0.0\n", - " unknown\n", + " 252\n", + " 70.6\n", + " 357\n", + " 68.6\n", + " 2.0\n", + " 02-Jan\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 112\n", - " 57.1\n", - " 196\n", - " 53.6\n", - " 3.5\n", - " 12-Nov\n", + " 245\n", + " 70.0\n", + " 350\n", + " 70.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Caribbean\n", - " 112\n", - " 64.0\n", - " 175\n", - " 64.0\n", - " 0.0\n", - " unknown\n", + " 259\n", + " 69.8\n", + " 371\n", + " 67.9\n", + " 1.9\n", + " 09-Jan\n", " \n", " \n", " Chinese\n", - " 112\n", - " 72.7\n", - " 154\n", - " 68.2\n", - " 4.5\n", - " 04-Oct\n", + " 245\n", + " 67.3\n", + " 364\n", + " 65.4\n", + " 1.9\n", + " 18-Jan\n", " \n", " \n", " Other\n", - " 119\n", - " 70.8\n", - " 168\n", - " 66.7\n", - " 4.1\n", - " 10-Oct\n", + " 252\n", + " 67.9\n", + " 371\n", + " 66.0\n", + " 1.9\n", + " 16-Jan\n", " \n", " \n", " Other Asian\n", - " 119\n", - " 65.4\n", - " 182\n", - " 61.5\n", - " 3.9\n", - " 22-Oct\n", + " 259\n", + " 71.2\n", + " 364\n", + " 69.2\n", + " 2.0\n", + " 31-Dec\n", " \n", " \n", " British or Mixed British\n", - " 112\n", - " 59.3\n", - " 189\n", - " 55.6\n", - " 3.7\n", - " 05-Nov\n", + " 238\n", + " 69.4\n", + " 343\n", + " 67.3\n", + " 2.1\n", + " 03-Jan\n", " \n", " \n", " Indian or British Indian\n", - " 112\n", - " 59.3\n", - " 189\n", - " 59.3\n", - " 0.0\n", - " unknown\n", + " 259\n", + " 69.8\n", + " 371\n", + " 67.9\n", + " 1.9\n", + " 09-Jan\n", " \n", " \n", " Irish\n", - " 112\n", - " 66.7\n", - " 168\n", - " 62.5\n", - " 4.2\n", - " 16-Oct\n", + " 252\n", + " 69.2\n", + " 364\n", + " 67.3\n", + " 1.9\n", + " 11-Jan\n", " \n", " \n", " Other Black\n", - " 126\n", + " 252\n", " 69.2\n", - " 182\n", - " 65.4\n", - " 3.8\n", - " 16-Oct\n", + " 364\n", + " 67.3\n", + " 1.9\n", + " 11-Jan\n", " \n", " \n", " Other White\n", - " 126\n", - " 64.3\n", - " 196\n", - " 60.7\n", - " 3.6\n", - " 27-Oct\n", + " 252\n", + " 69.2\n", + " 364\n", + " 67.3\n", + " 1.9\n", + " 11-Jan\n", " \n", " \n", " Other mixed\n", - " 126\n", - " 66.7\n", - " 189\n", - " 66.7\n", + " 231\n", + " 66.0\n", + " 350\n", + " 66.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 126\n", - " 69.2\n", - " 182\n", - " 65.4\n", - " 3.8\n", - " 16-Oct\n", + " 224\n", + " 68.1\n", + " 329\n", + " 66.0\n", + " 2.1\n", + " 08-Jan\n", " \n", " \n", " Unknown\n", - " 371\n", - " 66.2\n", - " 560\n", - " 65.0\n", - " 1.2\n", - " 24-Jan\n", + " 707\n", + " 69.7\n", + " 1015\n", + " 68.3\n", + " 1.4\n", + " 05-Feb\n", " \n", " \n", " White + Asian\n", - " 133\n", - " 65.5\n", - " 203\n", - " 62.1\n", - " 3.4\n", - " 28-Oct\n", + " 266\n", + " 69.1\n", + " 385\n", + " 69.1\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black African\n", - " 119\n", - " 65.4\n", - " 182\n", - " 65.4\n", + " 273\n", + " 69.6\n", + " 392\n", + " 69.6\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 112\n", - " 64.0\n", - " 175\n", - " 60.0\n", - " 4.0\n", - " 23-Oct\n", + " 273\n", + " 68.4\n", + " 399\n", + " 66.7\n", + " 1.7\n", + " 23-Jan\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 420\n", - " 65.2\n", - " 644\n", - " 64.1\n", - " 1.1\n", - " 12-Feb\n", + " 889\n", + " 68.3\n", + " 1302\n", + " 66.7\n", + " 1.6\n", + " 29-Jan\n", " \n", " \n", " 2\n", - " 434\n", - " 63.3\n", - " 686\n", - " 61.2\n", - " 2.1\n", - " 06-Dec\n", + " 931\n", + " 69.3\n", + " 1344\n", + " 67.7\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " 3\n", - " 469\n", - " 68.4\n", - " 686\n", - " 66.3\n", - " 2.1\n", - " 19-Nov\n", + " 889\n", + " 69.4\n", + " 1281\n", + " 67.2\n", + " 2.2\n", + " 31-Dec\n", " \n", " \n", " 4\n", - " 434\n", - " 66.0\n", - " 658\n", - " 63.8\n", - " 2.2\n", - " 23-Nov\n", + " 903\n", + " 68.6\n", + " 1316\n", + " 67.6\n", + " 1.0\n", + " 25-Mar\n", " \n", " \n", " 5 Least deprived\n", - " 385\n", - " 62.5\n", - " 616\n", - " 62.5\n", - " 0.0\n", - " unknown\n", + " 903\n", + " 70.5\n", + " 1281\n", + " 68.3\n", + " 2.2\n", + " 28-Dec\n", " \n", " \n", " Unknown\n", - " 126\n", - " 66.7\n", - " 189\n", - " 63.0\n", - " 3.7\n", - " 22-Oct\n", + " 231\n", + " 70.2\n", + " 329\n", + " 70.2\n", + " 0.0\n", + " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 728\n", - " 66.7\n", - " 1092\n", - " 65.4\n", + " 1421\n", + " 68.8\n", + " 2065\n", + " 67.5\n", " 1.3\n", - " 11-Jan\n", + " 18-Feb\n", " \n", " \n", " under 30\n", - " 1547\n", - " 64.8\n", - " 2387\n", - " 63.0\n", + " 3332\n", + " 69.6\n", + " 4788\n", + " 67.8\n", " 1.8\n", - " 15-Dec\n", + " 14-Jan\n", " \n", " \n", " housebound\n", " no\n", - " 2261\n", - " 65.5\n", - " 3451\n", - " 63.9\n", - " 1.6\n", - " 24-Dec\n", + " 4697\n", + " 69.2\n", + " 6783\n", + " 67.7\n", + " 1.5\n", + " 01-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 56\n", + " 80.0\n", + " 70\n", + " 70.0\n", + " 10.0\n", + " 03-Nov\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 2254\n", - " 65.3\n", - " 3451\n", - " 63.9\n", - " 1.4\n", - " 09-Jan\n", + " 4711\n", + " 69.3\n", + " 6797\n", + " 67.7\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 42\n", + " 66.7\n", + " 63\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 2247\n", - " 65.2\n", - " 3444\n", - " 63.6\n", - " 1.6\n", - " 25-Dec\n", + " 4690\n", + " 69.2\n", + " 6776\n", + " 67.7\n", + " 1.5\n", + " 01-Feb\n", " \n", " \n", " yes\n", - " 28\n", - " 66.7\n", - " 42\n", + " 63\n", + " 75.0\n", + " 84\n", " 66.7\n", - " 0.0\n", - " unknown\n", + " 8.3\n", + " 08-Nov\n", " \n", " \n", " dmards\n", " no\n", - " 2254\n", - " 65.4\n", - " 3444\n", - " 64.0\n", - " 1.4\n", - " 09-Jan\n", + " 4697\n", + " 69.2\n", + " 6790\n", + " 67.5\n", + " 1.7\n", + " 20-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 56\n", + " 80.0\n", + " 70\n", + " 80.0\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 2247\n", - " 65.2\n", - " 3444\n", - " 63.8\n", - " 1.4\n", - " 10-Jan\n", + " 4697\n", + " 69.3\n", + " 6776\n", + " 67.7\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " yes\n", - " 28\n", - " 66.7\n", - " 42\n", - " 50.0\n", - " 16.7\n", - " 17-Sep\n", + " 56\n", + " 72.7\n", + " 77\n", + " 72.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 2247\n", - " 65.2\n", - " 3444\n", - " 63.8\n", - " 1.4\n", - " 10-Jan\n", + " 4704\n", + " 69.3\n", + " 6790\n", + " 67.6\n", + " 1.7\n", + " 20-Jan\n", " \n", " \n", " yes\n", - " 21\n", - " 50.0\n", - " 42\n", - " 50.0\n", + " 49\n", + " 70.0\n", + " 70\n", + " 70.0\n", " 0.0\n", " unknown\n", " \n", " \n", " LD\n", " no\n", - " 2219\n", - " 65.2\n", - " 3402\n", - " 63.8\n", - " 1.4\n", - " 10-Jan\n", + " 4662\n", + " 69.3\n", + " 6727\n", + " 67.7\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " yes\n", - " 49\n", - " 63.6\n", - " 77\n", - " 63.6\n", - " 0.0\n", - " unknown\n", + " 91\n", + " 68.4\n", + " 133\n", + " 63.2\n", + " 5.2\n", + " 25-Nov\n", " \n", " \n", " ssri\n", " no\n", - " 2261\n", - " 65.5\n", - " 3451\n", - " 63.9\n", - " 1.6\n", - " 24-Dec\n", + " 4704\n", + " 69.3\n", + " 6790\n", + " 67.6\n", + " 1.7\n", + " 20-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 49\n", + " 70.0\n", + " 70\n", + " 70.0\n", " 0.0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 2254\n", - " 65.3\n", - " 3451\n", - " 63.7\n", + " 4697\n", + " 69.2\n", + " 6790\n", + " 67.6\n", " 1.6\n", - " 25-Dec\n", + " 26-Jan\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 49\n", + " 70.0\n", + " 70\n", + " 70.0\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 2247\n", - " 65.2\n", - " 3444\n", - " 63.8\n", - " 1.4\n", - " 10-Jan\n", + " 4704\n", + " 69.3\n", + " 6790\n", + " 67.7\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", - " 0.0\n", - " unknown\n", + " 49\n", + " 77.8\n", + " 63\n", + " 66.7\n", + " 11.1\n", + " 03-Nov\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 2247\n", - " 65.2\n", - " 3444\n", - " 63.6\n", - " 1.6\n", - " 25-Dec\n", + " 4704\n", + " 69.3\n", + " 6790\n", + " 67.6\n", + " 1.7\n", + " 20-Jan\n", " \n", " \n", " yes\n", - " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 49\n", + " 70.0\n", + " 70\n", + " 70.0\n", " 0.0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 2240\n", - " 65.2\n", - " 3437\n", - " 63.7\n", - " 1.5\n", - " 01-Jan\n", + " 4704\n", + " 69.3\n", + " 6783\n", + " 67.7\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " yes\n", - " 28\n", - " 66.7\n", - " 42\n", - " 66.7\n", + " 49\n", + " 70.0\n", + " 70\n", + " 70.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1799\n", - " 65.6\n", - " 2744\n", - " 64.3\n", - " 1.3\n", - " 17-Jan\n", + " 3794\n", + " 69.2\n", + " 5481\n", + " 67.6\n", + " 1.6\n", + " 26-Jan\n", " \n", " \n", " yes\n", - " 469\n", - " 63.8\n", - " 735\n", - " 61.9\n", - " 1.9\n", - " 13-Dec\n", + " 959\n", + " 69.5\n", + " 1379\n", + " 68.0\n", + " 1.5\n", + " 30-Jan\n", " \n", " \n", " brand_of_first_dose\n", @@ -25168,8 +25273,8 @@ " Oxford-AZ\n", " 0\n", " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", @@ -25177,19 +25282,19 @@ " Pfizer\n", " 0\n", " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 2268\n", - " 72.6\n", - " 3122\n", - " 70.9\n", + " 4732\n", + " 76.7\n", + " 6167\n", + " 75.0\n", " 1.7\n", - " 18-Nov\n", + " 20-Dec\n", " \n", " \n", "\n", @@ -25198,335 +25303,335 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 2275 \n", - "sex F 1162 \n", - " M 1106 \n", - "ageband_5yr 0 28 \n", - " 0-15 147 \n", - " 16-17 168 \n", - " 18-29 140 \n", - " 30-34 175 \n", - " 35-39 140 \n", - " 40-44 140 \n", - " 45-49 161 \n", - " 50-54 126 \n", - " 55-59 133 \n", - " 60-64 161 \n", - " 65-69 147 \n", - " 70-74 126 \n", - " 75-79 147 \n", - " 80-84 168 \n", - " 85-89 147 \n", - " 90+ 14 \n", - "ethnicity_6_groups Black 406 \n", - " Mixed 413 \n", - " Other 378 \n", - " South Asian 357 \n", - " Unknown 322 \n", - " White 392 \n", - "ethnicity_16_groups African 133 \n", - " Bangladeshi or British Bangladeshi 112 \n", - " Caribbean 112 \n", - " Chinese 112 \n", - " Other 119 \n", - " Other Asian 119 \n", - " British or Mixed British 112 \n", - " Indian or British Indian 112 \n", - " Irish 112 \n", - " Other Black 126 \n", - " Other White 126 \n", - " Other mixed 126 \n", - " Pakistani or British Pakistani 126 \n", - " Unknown 371 \n", - " White + Asian 133 \n", - " White + Black African 119 \n", - " White + Black Caribbean 112 \n", - "imd_categories 1 Most deprived 420 \n", - " 2 434 \n", - " 3 469 \n", - " 4 434 \n", - " 5 Least deprived 385 \n", - " Unknown 126 \n", - "bmi 30+ 728 \n", - " under 30 1547 \n", - "housebound no 2261 \n", - " yes 14 \n", - "chronic_cardiac_disease no 2254 \n", - " yes 14 \n", - "current_copd no 2247 \n", - " yes 28 \n", - "dmards no 2254 \n", - " yes 14 \n", - "dementia no 2247 \n", - " yes 28 \n", - "psychosis_schiz_bipolar no 2247 \n", - " yes 21 \n", - "LD no 2219 \n", + "overall overall 4753 \n", + "sex F 2478 \n", + " M 2268 \n", + "ageband_5yr 0 63 \n", + " 0-15 294 \n", + " 16-17 301 \n", + " 18-29 287 \n", + " 30-34 343 \n", + " 35-39 308 \n", + " 40-44 287 \n", + " 45-49 308 \n", + " 50-54 322 \n", + " 55-59 308 \n", + " 60-64 315 \n", + " 65-69 315 \n", + " 70-74 301 \n", + " 75-79 315 \n", + " 80-84 301 \n", + " 85-89 322 \n", + " 90+ 63 \n", + "ethnicity_6_groups Black 805 \n", + " Mixed 826 \n", + " Other 826 \n", + " South Asian 826 \n", + " Unknown 721 \n", + " White 742 \n", + "ethnicity_16_groups African 252 \n", + " Bangladeshi or British Bangladeshi 245 \n", + " Caribbean 259 \n", + " Chinese 245 \n", + " Other 252 \n", + " Other Asian 259 \n", + " British or Mixed British 238 \n", + " Indian or British Indian 259 \n", + " Irish 252 \n", + " Other Black 252 \n", + " Other White 252 \n", + " Other mixed 231 \n", + " Pakistani or British Pakistani 224 \n", + " Unknown 707 \n", + " White + Asian 266 \n", + " White + Black African 273 \n", + " White + Black Caribbean 273 \n", + "imd_categories 1 Most deprived 889 \n", + " 2 931 \n", + " 3 889 \n", + " 4 903 \n", + " 5 Least deprived 903 \n", + " Unknown 231 \n", + "bmi 30+ 1421 \n", + " under 30 3332 \n", + "housebound no 4697 \n", + " yes 56 \n", + "chronic_cardiac_disease no 4711 \n", + " yes 42 \n", + "current_copd no 4690 \n", + " yes 63 \n", + "dmards no 4697 \n", + " yes 56 \n", + "dementia no 4697 \n", + " yes 56 \n", + "psychosis_schiz_bipolar no 4704 \n", " yes 49 \n", - "ssri no 2261 \n", - " yes 14 \n", - "chemo_or_radio no 2254 \n", - " yes 21 \n", - "lung_cancer no 2247 \n", - " yes 21 \n", - "cancer_excl_lung_and_haem no 2247 \n", - " yes 28 \n", - "haematological_cancer no 2240 \n", - " yes 28 \n", - "ckd no 1799 \n", - " yes 469 \n", + "LD no 4662 \n", + " yes 91 \n", + "ssri no 4704 \n", + " yes 49 \n", + "chemo_or_radio no 4697 \n", + " yes 49 \n", + "lung_cancer no 4704 \n", + " yes 49 \n", + "cancer_excl_lung_and_haem no 4704 \n", + " yes 49 \n", + "haematological_cancer no 4704 \n", + " yes 49 \n", + "ckd no 3794 \n", + " yes 959 \n", "brand_of_first_dose Moderna 0 \n", " Oxford-AZ 0 \n", " Pfizer 0 \n", - " Unknown 2268 \n", + " Unknown 4732 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 65.4 3479 \n", - "sex F 66.1 1757 \n", - " M 64.2 1722 \n", - "ageband_5yr 0 66.7 42 \n", - " 0-15 70.0 210 \n", - " 16-17 63.2 266 \n", - " 18-29 60.6 231 \n", - " 30-34 67.6 259 \n", - " 35-39 64.5 217 \n", - " 40-44 66.7 210 \n", - " 45-49 69.7 231 \n", - " 50-54 58.1 217 \n", - " 55-59 63.3 210 \n", - " 60-64 67.6 238 \n", - " 65-69 65.6 224 \n", - " 70-74 64.3 196 \n", - " 75-79 61.8 238 \n", - " 80-84 70.6 238 \n", - " 85-89 67.7 217 \n", - " 90+ 50.0 28 \n", - "ethnicity_6_groups Black 66.7 609 \n", - " Mixed 67.0 616 \n", - " Other 65.9 574 \n", - " South Asian 63.0 567 \n", - " Unknown 63.9 504 \n", - " White 64.4 609 \n", - "ethnicity_16_groups African 65.5 203 \n", - " Bangladeshi or British Bangladeshi 57.1 196 \n", - " Caribbean 64.0 175 \n", - " Chinese 72.7 154 \n", - " Other 70.8 168 \n", - " Other Asian 65.4 182 \n", - " British or Mixed British 59.3 189 \n", - " Indian or British Indian 59.3 189 \n", - " Irish 66.7 168 \n", - " Other Black 69.2 182 \n", - " Other White 64.3 196 \n", - " Other mixed 66.7 189 \n", - " Pakistani or British Pakistani 69.2 182 \n", - " Unknown 66.2 560 \n", - " White + Asian 65.5 203 \n", - " White + Black African 65.4 182 \n", - " White + Black Caribbean 64.0 175 \n", - "imd_categories 1 Most deprived 65.2 644 \n", - " 2 63.3 686 \n", - " 3 68.4 686 \n", - " 4 66.0 658 \n", - " 5 Least deprived 62.5 616 \n", - " Unknown 66.7 189 \n", - "bmi 30+ 66.7 1092 \n", - " under 30 64.8 2387 \n", - "housebound no 65.5 3451 \n", - " yes 50.0 28 \n", - "chronic_cardiac_disease no 65.3 3451 \n", - " yes 50.0 28 \n", - "current_copd no 65.2 3444 \n", - " yes 66.7 42 \n", - "dmards no 65.4 3444 \n", - " yes 40.0 35 \n", - "dementia no 65.2 3444 \n", - " yes 66.7 42 \n", - "psychosis_schiz_bipolar no 65.2 3444 \n", - " yes 50.0 42 \n", - "LD no 65.2 3402 \n", - " yes 63.6 77 \n", - "ssri no 65.5 3451 \n", - " yes 50.0 28 \n", - "chemo_or_radio no 65.3 3451 \n", - " yes 60.0 35 \n", - "lung_cancer no 65.2 3444 \n", - " yes 60.0 35 \n", - "cancer_excl_lung_and_haem no 65.2 3444 \n", - " yes 80.0 35 \n", - "haematological_cancer no 65.2 3437 \n", - " yes 66.7 42 \n", - "ckd no 65.6 2744 \n", - " yes 63.8 735 \n", + "overall overall 69.3 6860 \n", + "sex F 70.0 3542 \n", + " M 68.4 3318 \n", + "ageband_5yr 0 75.0 84 \n", + " 0-15 68.9 427 \n", + " 16-17 66.2 455 \n", + " 18-29 66.1 434 \n", + " 30-34 73.1 469 \n", + " 35-39 66.7 462 \n", + " 40-44 66.1 434 \n", + " 45-49 68.8 448 \n", + " 50-54 74.2 434 \n", + " 55-59 67.7 455 \n", + " 60-64 70.3 448 \n", + " 65-69 70.3 448 \n", + " 70-74 69.4 434 \n", + " 75-79 69.2 455 \n", + " 80-84 68.3 441 \n", + " 85-89 71.9 448 \n", + " 90+ 75.0 84 \n", + "ethnicity_6_groups Black 69.7 1155 \n", + " Mixed 69.4 1190 \n", + " Other 70.2 1176 \n", + " South Asian 68.6 1204 \n", + " Unknown 70.1 1029 \n", + " White 67.5 1099 \n", + "ethnicity_16_groups African 70.6 357 \n", + " Bangladeshi or British Bangladeshi 70.0 350 \n", + " Caribbean 69.8 371 \n", + " Chinese 67.3 364 \n", + " Other 67.9 371 \n", + " Other Asian 71.2 364 \n", + " British or Mixed British 69.4 343 \n", + " Indian or British Indian 69.8 371 \n", + " Irish 69.2 364 \n", + " Other Black 69.2 364 \n", + " Other White 69.2 364 \n", + " Other mixed 66.0 350 \n", + " Pakistani or British Pakistani 68.1 329 \n", + " Unknown 69.7 1015 \n", + " White + Asian 69.1 385 \n", + " White + Black African 69.6 392 \n", + " White + Black Caribbean 68.4 399 \n", + "imd_categories 1 Most deprived 68.3 1302 \n", + " 2 69.3 1344 \n", + " 3 69.4 1281 \n", + " 4 68.6 1316 \n", + " 5 Least deprived 70.5 1281 \n", + " Unknown 70.2 329 \n", + "bmi 30+ 68.8 2065 \n", + " under 30 69.6 4788 \n", + "housebound no 69.2 6783 \n", + " yes 80.0 70 \n", + "chronic_cardiac_disease no 69.3 6797 \n", + " yes 66.7 63 \n", + "current_copd no 69.2 6776 \n", + " yes 75.0 84 \n", + "dmards no 69.2 6790 \n", + " yes 80.0 70 \n", + "dementia no 69.3 6776 \n", + " yes 72.7 77 \n", + "psychosis_schiz_bipolar no 69.3 6790 \n", + " yes 70.0 70 \n", + "LD no 69.3 6727 \n", + " yes 68.4 133 \n", + "ssri no 69.3 6790 \n", + " yes 70.0 70 \n", + "chemo_or_radio no 69.2 6790 \n", + " yes 70.0 70 \n", + "lung_cancer no 69.3 6790 \n", + " yes 77.8 63 \n", + "cancer_excl_lung_and_haem no 69.3 6790 \n", + " yes 70.0 70 \n", + "haematological_cancer no 69.3 6783 \n", + " yes 70.0 70 \n", + "ckd no 69.2 5481 \n", + " yes 69.5 1379 \n", "brand_of_first_dose Moderna 0.0 0 \n", - " Oxford-AZ 0.0 0 \n", - " Pfizer 0.0 0 \n", - " Unknown 72.6 3122 \n", + " Oxford-AZ 0.0 7 \n", + " Pfizer 0.0 7 \n", + " Unknown 76.7 6167 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 63.8 \n", - "sex F 64.9 \n", - " M 62.6 \n", - "ageband_5yr 0 66.7 \n", - " 0-15 66.7 \n", - " 16-17 63.2 \n", - " 18-29 60.6 \n", - " 30-34 64.9 \n", - " 35-39 64.5 \n", - " 40-44 66.7 \n", - " 45-49 69.7 \n", - " 50-54 58.1 \n", - " 55-59 63.3 \n", - " 60-64 67.6 \n", - " 65-69 62.5 \n", - " 70-74 60.7 \n", - " 75-79 58.8 \n", - " 80-84 70.6 \n", - " 85-89 64.5 \n", - " 90+ 50.0 \n", - "ethnicity_6_groups Black 65.5 \n", - " Mixed 64.8 \n", - " Other 63.4 \n", - " South Asian 61.7 \n", - " Unknown 62.5 \n", - " White 63.2 \n", - "ethnicity_16_groups African 65.5 \n", - " Bangladeshi or British Bangladeshi 53.6 \n", - " Caribbean 64.0 \n", - " Chinese 68.2 \n", - " Other 66.7 \n", - " Other Asian 61.5 \n", - " British or Mixed British 55.6 \n", - " Indian or British Indian 59.3 \n", - " Irish 62.5 \n", - " Other Black 65.4 \n", - " Other White 60.7 \n", - " Other mixed 66.7 \n", - " Pakistani or British Pakistani 65.4 \n", - " Unknown 65.0 \n", - " White + Asian 62.1 \n", - " White + Black African 65.4 \n", - " White + Black Caribbean 60.0 \n", - "imd_categories 1 Most deprived 64.1 \n", - " 2 61.2 \n", - " 3 66.3 \n", - " 4 63.8 \n", - " 5 Least deprived 62.5 \n", - " Unknown 63.0 \n", - "bmi 30+ 65.4 \n", - " under 30 63.0 \n", - "housebound no 63.9 \n", - " yes 50.0 \n", - "chronic_cardiac_disease no 63.9 \n", - " yes 50.0 \n", - "current_copd no 63.6 \n", + "overall overall 67.7 \n", + "sex F 68.6 \n", + " M 66.7 \n", + "ageband_5yr 0 75.0 \n", + " 0-15 68.9 \n", + " 16-17 66.2 \n", + " 18-29 64.5 \n", + " 30-34 70.1 \n", + " 35-39 65.2 \n", + " 40-44 64.5 \n", + " 45-49 67.2 \n", + " 50-54 71.0 \n", + " 55-59 64.6 \n", + " 60-64 68.8 \n", + " 65-69 68.8 \n", + " 70-74 69.4 \n", + " 75-79 67.7 \n", + " 80-84 68.3 \n", + " 85-89 70.3 \n", + " 90+ 66.7 \n", + "ethnicity_6_groups Black 68.5 \n", + " Mixed 67.1 \n", + " Other 68.5 \n", + " South Asian 66.9 \n", + " Unknown 68.7 \n", + " White 66.9 \n", + "ethnicity_16_groups African 68.6 \n", + " Bangladeshi or British Bangladeshi 70.0 \n", + " Caribbean 67.9 \n", + " Chinese 65.4 \n", + " Other 66.0 \n", + " Other Asian 69.2 \n", + " British or Mixed British 67.3 \n", + " Indian or British Indian 67.9 \n", + " Irish 67.3 \n", + " Other Black 67.3 \n", + " Other White 67.3 \n", + " Other mixed 66.0 \n", + " Pakistani or British Pakistani 66.0 \n", + " Unknown 68.3 \n", + " White + Asian 69.1 \n", + " White + Black African 69.6 \n", + " White + Black Caribbean 66.7 \n", + "imd_categories 1 Most deprived 66.7 \n", + " 2 67.7 \n", + " 3 67.2 \n", + " 4 67.6 \n", + " 5 Least deprived 68.3 \n", + " Unknown 70.2 \n", + "bmi 30+ 67.5 \n", + " under 30 67.8 \n", + "housebound no 67.7 \n", + " yes 70.0 \n", + "chronic_cardiac_disease no 67.7 \n", " yes 66.7 \n", - "dmards no 64.0 \n", - " yes 40.0 \n", - "dementia no 63.8 \n", - " yes 50.0 \n", - "psychosis_schiz_bipolar no 63.8 \n", - " yes 50.0 \n", - "LD no 63.8 \n", - " yes 63.6 \n", - "ssri no 63.9 \n", - " yes 50.0 \n", - "chemo_or_radio no 63.7 \n", - " yes 60.0 \n", - "lung_cancer no 63.8 \n", - " yes 60.0 \n", - "cancer_excl_lung_and_haem no 63.6 \n", + "current_copd no 67.7 \n", + " yes 66.7 \n", + "dmards no 67.5 \n", " yes 80.0 \n", - "haematological_cancer no 63.7 \n", + "dementia no 67.7 \n", + " yes 72.7 \n", + "psychosis_schiz_bipolar no 67.6 \n", + " yes 70.0 \n", + "LD no 67.7 \n", + " yes 63.2 \n", + "ssri no 67.6 \n", + " yes 70.0 \n", + "chemo_or_radio no 67.6 \n", + " yes 70.0 \n", + "lung_cancer no 67.7 \n", " yes 66.7 \n", - "ckd no 64.3 \n", - " yes 61.9 \n", + "cancer_excl_lung_and_haem no 67.6 \n", + " yes 70.0 \n", + "haematological_cancer no 67.7 \n", + " yes 70.0 \n", + "ckd no 67.6 \n", + " yes 68.0 \n", "brand_of_first_dose Moderna NaN \n", - " Oxford-AZ NaN \n", - " Pfizer NaN \n", - " Unknown 70.9 \n", + " Oxford-AZ 0.0 \n", + " Pfizer 0.0 \n", + " Unknown 75.0 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", "overall overall 1.6 \n", - "sex F 1.2 \n", - " M 1.6 \n", + "sex F 1.4 \n", + " M 1.7 \n", "ageband_5yr 0 0.0 \n", - " 0-15 3.3 \n", + " 0-15 0.0 \n", " 16-17 0.0 \n", - " 18-29 0.0 \n", - " 30-34 2.7 \n", - " 35-39 0.0 \n", - " 40-44 0.0 \n", - " 45-49 0.0 \n", - " 50-54 0.0 \n", - " 55-59 0.0 \n", - " 60-64 0.0 \n", - " 65-69 3.1 \n", - " 70-74 3.6 \n", - " 75-79 3.0 \n", + " 18-29 1.6 \n", + " 30-34 3.0 \n", + " 35-39 1.5 \n", + " 40-44 1.6 \n", + " 45-49 1.6 \n", + " 50-54 3.2 \n", + " 55-59 3.1 \n", + " 60-64 1.5 \n", + " 65-69 1.5 \n", + " 70-74 0.0 \n", + " 75-79 1.5 \n", " 80-84 0.0 \n", - " 85-89 3.2 \n", - " 90+ 0.0 \n", + " 85-89 1.6 \n", + " 90+ 8.3 \n", "ethnicity_6_groups Black 1.2 \n", - " Mixed 2.2 \n", - " Other 2.5 \n", - " South Asian 1.3 \n", + " Mixed 2.3 \n", + " Other 1.7 \n", + " South Asian 1.7 \n", " Unknown 1.4 \n", - " White 1.2 \n", - "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 3.5 \n", - " Caribbean 0.0 \n", - " Chinese 4.5 \n", - " Other 4.1 \n", - " Other Asian 3.9 \n", - " British or Mixed British 3.7 \n", - " Indian or British Indian 0.0 \n", - " Irish 4.2 \n", - " Other Black 3.8 \n", - " Other White 3.6 \n", + " White 0.6 \n", + "ethnicity_16_groups African 2.0 \n", + " Bangladeshi or British Bangladeshi 0.0 \n", + " Caribbean 1.9 \n", + " Chinese 1.9 \n", + " Other 1.9 \n", + " Other Asian 2.0 \n", + " British or Mixed British 2.1 \n", + " Indian or British Indian 1.9 \n", + " Irish 1.9 \n", + " Other Black 1.9 \n", + " Other White 1.9 \n", " Other mixed 0.0 \n", - " Pakistani or British Pakistani 3.8 \n", - " Unknown 1.2 \n", - " White + Asian 3.4 \n", + " Pakistani or British Pakistani 2.1 \n", + " Unknown 1.4 \n", + " White + Asian 0.0 \n", " White + Black African 0.0 \n", - " White + Black Caribbean 4.0 \n", - "imd_categories 1 Most deprived 1.1 \n", - " 2 2.1 \n", - " 3 2.1 \n", - " 4 2.2 \n", - " 5 Least deprived 0.0 \n", - " Unknown 3.7 \n", + " White + Black Caribbean 1.7 \n", + "imd_categories 1 Most deprived 1.6 \n", + " 2 1.6 \n", + " 3 2.2 \n", + " 4 1.0 \n", + " 5 Least deprived 2.2 \n", + " Unknown 0.0 \n", "bmi 30+ 1.3 \n", " under 30 1.8 \n", - "housebound no 1.6 \n", - " yes 0.0 \n", - "chronic_cardiac_disease no 1.4 \n", - " yes 0.0 \n", - "current_copd no 1.6 \n", + "housebound no 1.5 \n", + " yes 10.0 \n", + "chronic_cardiac_disease no 1.6 \n", " yes 0.0 \n", - "dmards no 1.4 \n", + "current_copd no 1.5 \n", + " yes 8.3 \n", + "dmards no 1.7 \n", " yes 0.0 \n", - "dementia no 1.4 \n", - " yes 16.7 \n", - "psychosis_schiz_bipolar no 1.4 \n", + "dementia no 1.6 \n", " yes 0.0 \n", - "LD no 1.4 \n", + "psychosis_schiz_bipolar no 1.7 \n", " yes 0.0 \n", - "ssri no 1.6 \n", + "LD no 1.6 \n", + " yes 5.2 \n", + "ssri no 1.7 \n", " yes 0.0 \n", "chemo_or_radio no 1.6 \n", " yes 0.0 \n", - "lung_cancer no 1.4 \n", - " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.6 \n", + "lung_cancer no 1.6 \n", + " yes 11.1 \n", + "cancer_excl_lung_and_haem no 1.7 \n", " yes 0.0 \n", - "haematological_cancer no 1.5 \n", + "haematological_cancer no 1.6 \n", " yes 0.0 \n", - "ckd no 1.3 \n", - " yes 1.9 \n", + "ckd no 1.6 \n", + " yes 1.5 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", @@ -25534,87 +25639,87 @@ "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 24-Dec \n", - "sex F 25-Jan \n", - " M 29-Dec \n", + "overall overall 25-Jan \n", + "sex F 04-Feb \n", + " M 23-Jan \n", "ageband_5yr 0 unknown \n", - " 0-15 20-Oct \n", + " 0-15 unknown \n", " 16-17 unknown \n", - " 18-29 unknown \n", - " 30-34 05-Nov \n", - " 35-39 unknown \n", - " 40-44 unknown \n", - " 45-49 unknown \n", - " 50-54 unknown \n", - " 55-59 unknown \n", - " 60-64 unknown \n", - " 65-69 02-Nov \n", - " 70-74 27-Oct \n", - " 75-79 12-Nov \n", + " 18-29 08-Feb \n", + " 30-34 05-Dec \n", + " 35-39 12-Feb \n", + " 40-44 08-Feb \n", + " 45-49 27-Jan \n", + " 50-54 30-Nov \n", + " 55-59 16-Dec \n", + " 60-64 26-Jan \n", + " 65-69 26-Jan \n", + " 70-74 unknown \n", + " 75-79 01-Feb \n", " 80-84 unknown \n", - " 85-89 26-Oct \n", - " 90+ unknown \n", - "ethnicity_6_groups Black 21-Jan \n", - " Mixed 20-Nov \n", - " Other 14-Nov \n", - " South Asian 31-Jan \n", - " Unknown 16-Jan \n", - " White 04-Feb \n", - "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi 12-Nov \n", - " Caribbean unknown \n", - " Chinese 04-Oct \n", - " Other 10-Oct \n", - " Other Asian 22-Oct \n", - " British or Mixed British 05-Nov \n", - " Indian or British Indian unknown \n", - " Irish 16-Oct \n", - " Other Black 16-Oct \n", - " Other White 27-Oct \n", + " 85-89 14-Jan \n", + " 90+ 08-Nov \n", + "ethnicity_6_groups Black 22-Feb \n", + " Mixed 28-Dec \n", + " Other 16-Jan \n", + " South Asian 23-Jan \n", + " Unknown 03-Feb \n", + " White unknown \n", + "ethnicity_16_groups African 02-Jan \n", + " Bangladeshi or British Bangladeshi unknown \n", + " Caribbean 09-Jan \n", + " Chinese 18-Jan \n", + " Other 16-Jan \n", + " Other Asian 31-Dec \n", + " British or Mixed British 03-Jan \n", + " Indian or British Indian 09-Jan \n", + " Irish 11-Jan \n", + " Other Black 11-Jan \n", + " Other White 11-Jan \n", " Other mixed unknown \n", - " Pakistani or British Pakistani 16-Oct \n", - " Unknown 24-Jan \n", - " White + Asian 28-Oct \n", + " Pakistani or British Pakistani 08-Jan \n", + " Unknown 05-Feb \n", + " White + Asian unknown \n", " White + Black African unknown \n", - " White + Black Caribbean 23-Oct \n", - "imd_categories 1 Most deprived 12-Feb \n", - " 2 06-Dec \n", - " 3 19-Nov \n", - " 4 23-Nov \n", - " 5 Least deprived unknown \n", - " Unknown 22-Oct \n", - "bmi 30+ 11-Jan \n", - " under 30 15-Dec \n", - "housebound no 24-Dec \n", - " yes unknown \n", - "chronic_cardiac_disease no 09-Jan \n", - " yes unknown \n", - "current_copd no 25-Dec \n", - " yes unknown \n", - "dmards no 09-Jan \n", + " White + Black Caribbean 23-Jan \n", + "imd_categories 1 Most deprived 29-Jan \n", + " 2 25-Jan \n", + " 3 31-Dec \n", + " 4 25-Mar \n", + " 5 Least deprived 28-Dec \n", + " Unknown unknown \n", + "bmi 30+ 18-Feb \n", + " under 30 14-Jan \n", + "housebound no 01-Feb \n", + " yes 03-Nov \n", + "chronic_cardiac_disease no 25-Jan \n", " yes unknown \n", - "dementia no 10-Jan \n", - " yes 17-Sep \n", - "psychosis_schiz_bipolar no 10-Jan \n", + "current_copd no 01-Feb \n", + " yes 08-Nov \n", + "dmards no 20-Jan \n", " yes unknown \n", - "LD no 10-Jan \n", + "dementia no 25-Jan \n", " yes unknown \n", - "ssri no 24-Dec \n", + "psychosis_schiz_bipolar no 20-Jan \n", " yes unknown \n", - "chemo_or_radio no 25-Dec \n", + "LD no 25-Jan \n", + " yes 25-Nov \n", + "ssri no 20-Jan \n", " yes unknown \n", - "lung_cancer no 10-Jan \n", + "chemo_or_radio no 26-Jan \n", " yes unknown \n", - "cancer_excl_lung_and_haem no 25-Dec \n", + "lung_cancer no 25-Jan \n", + " yes 03-Nov \n", + "cancer_excl_lung_and_haem no 20-Jan \n", " yes unknown \n", - "haematological_cancer no 01-Jan \n", + "haematological_cancer no 25-Jan \n", " yes unknown \n", - "ckd no 17-Jan \n", - " yes 13-Dec \n", + "ckd no 26-Jan \n", + " yes 30-Jan \n", "brand_of_first_dose Moderna unknown \n", " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 18-Nov " + " Unknown 20-Dec " ] }, "metadata": {}, @@ -25643,7 +25748,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **care home** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **care home** population up to 2021-10-27" ], "text/plain": [ "" @@ -25709,262 +25814,271 @@ " \n", " overall\n", " overall\n", - " 938\n", - " 67.3\n", - " 1393\n", - " 65.3\n", - " 2.0\n", - " 26-Nov\n", + " 1960\n", + " 69.5\n", + " 2821\n", + " 67.7\n", + " 1.8\n", + " 14-Jan\n", " \n", " \n", " sex\n", " F\n", - " 490\n", - " 68.0\n", - " 721\n", - " 66.0\n", - " 2.0\n", - " 24-Nov\n", + " 987\n", + " 69.1\n", + " 1428\n", + " 67.6\n", + " 1.5\n", + " 01-Feb\n", " \n", " \n", " M\n", - " 455\n", - " 67.7\n", - " 672\n", - " 64.6\n", - " 3.1\n", - " 28-Oct\n", + " 966\n", + " 69.7\n", + " 1386\n", + " 68.2\n", + " 1.5\n", + " 29-Jan\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 7\n", - " 50.0\n", - " 14\n", - " 50.0\n", + " 21\n", + " 75.0\n", + " 28\n", + " 75.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 0-15\n", - " 63\n", - " 69.2\n", - " 91\n", - " 69.2\n", + " 126\n", + " 72.0\n", + " 175\n", + " 72.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 16-17\n", - " 63\n", - " 64.3\n", - " 98\n", - " 64.3\n", - " 0.0\n", - " unknown\n", + " 140\n", + " 71.4\n", + " 196\n", + " 67.9\n", + " 3.5\n", + " 03-Dec\n", " \n", " \n", " 18-29\n", - " 56\n", - " 66.7\n", - " 84\n", + " 119\n", + " 70.8\n", + " 168\n", " 66.7\n", - " 0.0\n", - " unknown\n", + " 4.1\n", + " 28-Nov\n", " \n", " \n", " 30-34\n", - " 56\n", - " 66.7\n", - " 84\n", - " 58.3\n", - " 8.4\n", - " 27-Sep\n", + " 140\n", + " 74.1\n", + " 189\n", + " 74.1\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 35-39\n", - " 63\n", - " 64.3\n", - " 98\n", - " 64.3\n", + " 126\n", + " 66.7\n", + " 189\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 40-44\n", - " 56\n", - " 57.1\n", - " 98\n", - " 57.1\n", - " 0.0\n", - " unknown\n", + " 112\n", + " 66.7\n", + " 168\n", + " 62.5\n", + " 4.2\n", + " 04-Dec\n", " \n", " \n", " 45-49\n", - " 63\n", - " 69.2\n", - " 91\n", + " 126\n", " 69.2\n", - " 0.0\n", - " unknown\n", + " 182\n", + " 65.4\n", + " 3.8\n", + " 04-Dec\n", " \n", " \n", " 50-54\n", - " 63\n", - " 75.0\n", - " 84\n", - " 75.0\n", + " 126\n", + " 69.2\n", + " 182\n", + " 69.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 55-59\n", - " 63\n", - " 69.2\n", - " 91\n", - " 69.2\n", + " 133\n", + " 67.9\n", + " 196\n", + " 67.9\n", " 0.0\n", " unknown\n", " \n", " \n", " 60-64\n", - " 56\n", - " 61.5\n", - " 91\n", - " 61.5\n", + " 126\n", + " 64.3\n", + " 196\n", + " 64.3\n", " 0.0\n", " unknown\n", " \n", " \n", " 65-69\n", - " 63\n", - " 75.0\n", - " 84\n", - " 75.0\n", + " 126\n", + " 69.2\n", + " 182\n", + " 69.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-74\n", - " 70\n", + " 126\n", " 66.7\n", - " 105\n", + " 189\n", " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 75-79\n", - " 70\n", - " 76.9\n", - " 91\n", - " 76.9\n", - " 0.0\n", - " unknown\n", + " 119\n", + " 68.0\n", + " 175\n", + " 64.0\n", + " 4.0\n", + " 04-Dec\n", " \n", " \n", " 80-84\n", - " 56\n", - " 72.7\n", - " 77\n", - " 63.6\n", - " 9.1\n", - " 21-Sep\n", + " 126\n", + " 69.2\n", + " 182\n", + " 65.4\n", + " 3.8\n", + " 04-Dec\n", " \n", " \n", " 85-89\n", - " 70\n", - " 71.4\n", - " 98\n", - " 71.4\n", + " 126\n", + " 72.0\n", + " 175\n", + " 72.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 90+\n", - " 7\n", - " 50.0\n", - " 14\n", + " 42\n", + " 85.7\n", + " 49\n", + " 85.7\n", " 0.0\n", - " 50.0\n", - " 13-Sep\n", + " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 154\n", - " 68.8\n", - " 224\n", + " 308\n", " 68.8\n", - " 0.0\n", - " unknown\n", + " 448\n", + " 65.6\n", + " 3.2\n", + " 12-Dec\n", " \n", " \n", " Mixed\n", - " 175\n", - " 69.4\n", - " 252\n", - " 66.7\n", - " 2.7\n", - " 31-Oct\n", + " 336\n", + " 72.7\n", + " 462\n", + " 71.2\n", + " 1.5\n", + " 15-Jan\n", " \n", " \n", " Other\n", - " 147\n", - " 70.0\n", - " 210\n", + " 343\n", + " 68.1\n", + " 504\n", " 66.7\n", - " 3.3\n", - " 20-Oct\n", + " 1.4\n", + " 13-Feb\n", " \n", " \n", " South Asian\n", - " 175\n", - " 65.8\n", - " 266\n", - " 63.2\n", - " 2.6\n", - " 12-Nov\n", + " 329\n", + " 70.1\n", + " 469\n", + " 68.7\n", + " 1.4\n", + " 03-Feb\n", " \n", " \n", " Unknown\n", - " 133\n", - " 63.3\n", - " 210\n", - " 63.3\n", + " 308\n", + " 71.0\n", + " 434\n", + " 71.0\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", - " 154\n", - " 66.7\n", - " 231\n", - " 63.6\n", - " 3.1\n", - " 30-Oct\n", + " 329\n", + " 67.1\n", + " 490\n", + " 65.7\n", + " 1.4\n", + " 18-Feb\n", " \n", " \n", " dementia\n", " no\n", - " 931\n", - " 67.5\n", - " 1379\n", - " 65.5\n", - " 2.0\n", - " 25-Nov\n", + " 1939\n", + " 69.4\n", + " 2793\n", + " 67.9\n", + " 1.5\n", + " 31-Jan\n", " \n", " \n", " yes\n", - " 0\n", + " 21\n", + " 75.0\n", + " 28\n", + " 75.0\n", " 0.0\n", - " 14\n", + " unknown\n", + " \n", + " \n", + " brand_of_first_dose\n", + " Moderna\n", + " 0\n", " 0.0\n", + " 0\n", + " NaN\n", " 0.0\n", " unknown\n", " \n", " \n", - " brand_of_first_dose\n", " Oxford-AZ\n", " 0\n", " 0.0\n", @@ -25984,12 +26098,12 @@ " \n", " \n", " Unknown\n", - " 938\n", - " 74.9\n", - " 1253\n", - " 72.6\n", - " 2.3\n", - " 23-Oct\n", + " 1953\n", + " 77.3\n", + " 2527\n", + " 75.6\n", + " 1.7\n", + " 18-Dec\n", " \n", " \n", "\n", @@ -25998,139 +26112,143 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 938 67.3 1393 \n", - "sex F 490 68.0 721 \n", - " M 455 67.7 672 \n", - "ageband_5yr 0 7 50.0 14 \n", - " 0-15 63 69.2 91 \n", - " 16-17 63 64.3 98 \n", - " 18-29 56 66.7 84 \n", - " 30-34 56 66.7 84 \n", - " 35-39 63 64.3 98 \n", - " 40-44 56 57.1 98 \n", - " 45-49 63 69.2 91 \n", - " 50-54 63 75.0 84 \n", - " 55-59 63 69.2 91 \n", - " 60-64 56 61.5 91 \n", - " 65-69 63 75.0 84 \n", - " 70-74 70 66.7 105 \n", - " 75-79 70 76.9 91 \n", - " 80-84 56 72.7 77 \n", - " 85-89 70 71.4 98 \n", - " 90+ 7 50.0 14 \n", - "ethnicity_6_groups Black 154 68.8 224 \n", - " Mixed 175 69.4 252 \n", - " Other 147 70.0 210 \n", - " South Asian 175 65.8 266 \n", - " Unknown 133 63.3 210 \n", - " White 154 66.7 231 \n", - "dementia no 931 67.5 1379 \n", - " yes 0 0.0 14 \n", - "brand_of_first_dose Oxford-AZ 0 0.0 0 \n", + "overall overall 1960 69.5 2821 \n", + "sex F 987 69.1 1428 \n", + " M 966 69.7 1386 \n", + "ageband_5yr 0 21 75.0 28 \n", + " 0-15 126 72.0 175 \n", + " 16-17 140 71.4 196 \n", + " 18-29 119 70.8 168 \n", + " 30-34 140 74.1 189 \n", + " 35-39 126 66.7 189 \n", + " 40-44 112 66.7 168 \n", + " 45-49 126 69.2 182 \n", + " 50-54 126 69.2 182 \n", + " 55-59 133 67.9 196 \n", + " 60-64 126 64.3 196 \n", + " 65-69 126 69.2 182 \n", + " 70-74 126 66.7 189 \n", + " 75-79 119 68.0 175 \n", + " 80-84 126 69.2 182 \n", + " 85-89 126 72.0 175 \n", + " 90+ 42 85.7 49 \n", + "ethnicity_6_groups Black 308 68.8 448 \n", + " Mixed 336 72.7 462 \n", + " Other 343 68.1 504 \n", + " South Asian 329 70.1 469 \n", + " Unknown 308 71.0 434 \n", + " White 329 67.1 490 \n", + "dementia no 1939 69.4 2793 \n", + " yes 21 75.0 28 \n", + "brand_of_first_dose Moderna 0 0.0 0 \n", + " Oxford-AZ 0 0.0 0 \n", " Pfizer 0 0.0 0 \n", - " Unknown 938 74.9 1253 \n", + " Unknown 1953 77.3 2527 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 65.3 \n", - "sex F 66.0 \n", - " M 64.6 \n", - "ageband_5yr 0 50.0 \n", - " 0-15 69.2 \n", - " 16-17 64.3 \n", + "overall overall 67.7 \n", + "sex F 67.6 \n", + " M 68.2 \n", + "ageband_5yr 0 75.0 \n", + " 0-15 72.0 \n", + " 16-17 67.9 \n", " 18-29 66.7 \n", - " 30-34 58.3 \n", - " 35-39 64.3 \n", - " 40-44 57.1 \n", - " 45-49 69.2 \n", - " 50-54 75.0 \n", - " 55-59 69.2 \n", - " 60-64 61.5 \n", - " 65-69 75.0 \n", + " 30-34 74.1 \n", + " 35-39 66.7 \n", + " 40-44 62.5 \n", + " 45-49 65.4 \n", + " 50-54 69.2 \n", + " 55-59 67.9 \n", + " 60-64 64.3 \n", + " 65-69 69.2 \n", " 70-74 66.7 \n", - " 75-79 76.9 \n", - " 80-84 63.6 \n", - " 85-89 71.4 \n", - " 90+ 0.0 \n", - "ethnicity_6_groups Black 68.8 \n", - " Mixed 66.7 \n", + " 75-79 64.0 \n", + " 80-84 65.4 \n", + " 85-89 72.0 \n", + " 90+ 85.7 \n", + "ethnicity_6_groups Black 65.6 \n", + " Mixed 71.2 \n", " Other 66.7 \n", - " South Asian 63.2 \n", - " Unknown 63.3 \n", - " White 63.6 \n", - "dementia no 65.5 \n", - " yes 0.0 \n", - "brand_of_first_dose Oxford-AZ NaN \n", + " South Asian 68.7 \n", + " Unknown 71.0 \n", + " White 65.7 \n", + "dementia no 67.9 \n", + " yes 75.0 \n", + "brand_of_first_dose Moderna NaN \n", + " Oxford-AZ NaN \n", " Pfizer NaN \n", - " Unknown 72.6 \n", + " Unknown 75.6 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 2.0 \n", - "sex F 2.0 \n", - " M 3.1 \n", + "overall overall 1.8 \n", + "sex F 1.5 \n", + " M 1.5 \n", "ageband_5yr 0 0.0 \n", " 0-15 0.0 \n", - " 16-17 0.0 \n", - " 18-29 0.0 \n", - " 30-34 8.4 \n", + " 16-17 3.5 \n", + " 18-29 4.1 \n", + " 30-34 0.0 \n", " 35-39 0.0 \n", - " 40-44 0.0 \n", - " 45-49 0.0 \n", + " 40-44 4.2 \n", + " 45-49 3.8 \n", " 50-54 0.0 \n", " 55-59 0.0 \n", " 60-64 0.0 \n", " 65-69 0.0 \n", " 70-74 0.0 \n", - " 75-79 0.0 \n", - " 80-84 9.1 \n", + " 75-79 4.0 \n", + " 80-84 3.8 \n", " 85-89 0.0 \n", - " 90+ 50.0 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 2.7 \n", - " Other 3.3 \n", - " South Asian 2.6 \n", + " 90+ 0.0 \n", + "ethnicity_6_groups Black 3.2 \n", + " Mixed 1.5 \n", + " Other 1.4 \n", + " South Asian 1.4 \n", " Unknown 0.0 \n", - " White 3.1 \n", - "dementia no 2.0 \n", + " White 1.4 \n", + "dementia no 1.5 \n", " yes 0.0 \n", - "brand_of_first_dose Oxford-AZ 0.0 \n", + "brand_of_first_dose Moderna 0.0 \n", + " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 2.3 \n", + " Unknown 1.7 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 26-Nov \n", - "sex F 24-Nov \n", - " M 28-Oct \n", + "overall overall 14-Jan \n", + "sex F 01-Feb \n", + " M 29-Jan \n", "ageband_5yr 0 unknown \n", " 0-15 unknown \n", - " 16-17 unknown \n", - " 18-29 unknown \n", - " 30-34 27-Sep \n", + " 16-17 03-Dec \n", + " 18-29 28-Nov \n", + " 30-34 unknown \n", " 35-39 unknown \n", - " 40-44 unknown \n", - " 45-49 unknown \n", + " 40-44 04-Dec \n", + " 45-49 04-Dec \n", " 50-54 unknown \n", " 55-59 unknown \n", " 60-64 unknown \n", " 65-69 unknown \n", " 70-74 unknown \n", - " 75-79 unknown \n", - " 80-84 21-Sep \n", + " 75-79 04-Dec \n", + " 80-84 04-Dec \n", " 85-89 unknown \n", - " 90+ 13-Sep \n", - "ethnicity_6_groups Black unknown \n", - " Mixed 31-Oct \n", - " Other 20-Oct \n", - " South Asian 12-Nov \n", + " 90+ unknown \n", + "ethnicity_6_groups Black 12-Dec \n", + " Mixed 15-Jan \n", + " Other 13-Feb \n", + " South Asian 03-Feb \n", " Unknown unknown \n", - " White 30-Oct \n", - "dementia no 25-Nov \n", + " White 18-Feb \n", + "dementia no 31-Jan \n", " yes unknown \n", - "brand_of_first_dose Oxford-AZ unknown \n", + "brand_of_first_dose Moderna unknown \n", + " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 23-Oct " + " Unknown 18-Dec " ] }, "metadata": {}, @@ -26159,7 +26277,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **shielding (aged 16-69)** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **shielding (aged 16-69)** population up to 2021-10-27" ], "text/plain": [ "" @@ -26225,221 +26343,221 @@ " \n", " overall\n", " overall\n", - " 259\n", - " 61.7\n", - " 420\n", - " 60.0\n", - " 1.7\n", - " 02-Jan\n", + " 588\n", + " 67.7\n", + " 868\n", + " 66.9\n", + " 0.8\n", + " unknown\n", " \n", " \n", " newly_shielded_since_feb_15\n", " no\n", - " 259\n", - " 62.7\n", - " 413\n", - " 61.0\n", - " 1.7\n", - " 29-Dec\n", + " 574\n", + " 66.7\n", + " 861\n", + " 66.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 100.0\n", + " 7\n", + " 100.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " sex\n", " F\n", - " 147\n", - " 67.7\n", - " 217\n", - " 67.7\n", + " 308\n", + " 68.8\n", + " 448\n", + " 68.8\n", " 0.0\n", " unknown\n", " \n", " \n", " M\n", - " 112\n", - " 55.2\n", - " 203\n", - " 55.2\n", + " 280\n", + " 66.7\n", + " 420\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " ageband\n", " 16-29\n", - " 35\n", - " 62.5\n", - " 56\n", - " 62.5\n", + " 70\n", + " 66.7\n", + " 105\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 30-39\n", - " 35\n", - " 62.5\n", - " 56\n", - " 62.5\n", + " 70\n", + " 66.7\n", + " 105\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 40-49\n", - " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", + " 77\n", + " 68.8\n", + " 112\n", + " 68.8\n", " 0.0\n", " unknown\n", " \n", " \n", " 50-59\n", - " 42\n", - " 60.0\n", - " 70\n", - " 50.0\n", - " 10.0\n", - " 29-Sep\n", + " 77\n", + " 61.1\n", + " 126\n", + " 61.1\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 60-69\n", - " 35\n", - " 71.4\n", - " 49\n", - " 71.4\n", + " 70\n", + " 62.5\n", + " 112\n", + " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-79\n", - " 63\n", - " 69.2\n", - " 91\n", - " 69.2\n", + " 133\n", + " 65.5\n", + " 203\n", + " 65.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 80+\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", + " 84\n", + " 75.0\n", + " 112\n", + " 75.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 49\n", + " 98\n", " 70.0\n", - " 70\n", - " 60.0\n", - " 10.0\n", - " 22-Sep\n", + " 140\n", + " 70.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Mixed\n", - " 42\n", - " 60.0\n", - " 70\n", - " 60.0\n", + " 105\n", + " 65.2\n", + " 161\n", + " 65.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 42\n", - " 60.0\n", - " 70\n", - " 60.0\n", + " 105\n", + " 75.0\n", + " 140\n", + " 75.0\n", " 0.0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 42\n", - " 66.7\n", - " 63\n", - " 55.6\n", - " 11.1\n", - " 22-Sep\n", + " 105\n", + " 71.4\n", + " 147\n", + " 71.4\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 35\n", - " 62.5\n", - " 56\n", - " 62.5\n", + " 77\n", + " 64.7\n", + " 119\n", + " 64.7\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", - " 56\n", - " 61.5\n", - " 91\n", - " 61.5\n", + " 98\n", + " 60.9\n", + " 161\n", + " 60.9\n", " 0.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 56\n", - " 66.7\n", - " 84\n", - " 58.3\n", - " 8.4\n", - " 27-Sep\n", + " 112\n", + " 61.5\n", + " 182\n", + " 61.5\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 2\n", - " 49\n", - " 70.0\n", - " 70\n", - " 60.0\n", - " 10.0\n", - " 22-Sep\n", + " 98\n", + " 66.7\n", + " 147\n", + " 61.9\n", + " 4.8\n", + " 29-Nov\n", " \n", " \n", " 3\n", - " 49\n", - " 58.3\n", - " 84\n", - " 58.3\n", + " 112\n", + " 66.7\n", + " 168\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 4\n", - " 49\n", - " 58.3\n", - " 84\n", - " 58.3\n", + " 119\n", + " 73.9\n", + " 161\n", + " 73.9\n", " 0.0\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 56\n", - " 72.7\n", - " 77\n", - " 72.7\n", + " 119\n", + " 70.8\n", + " 168\n", + " 70.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 14\n", + " 28\n", " 66.7\n", - " 21\n", + " 42\n", " 66.7\n", " 0.0\n", " unknown\n", @@ -26447,52 +26565,43 @@ " \n", " LD\n", " no\n", - " 259\n", - " 62.7\n", - " 413\n", - " 61.0\n", - " 1.7\n", - " 29-Dec\n", + " 581\n", + " 68.0\n", + " 854\n", + " 67.2\n", + " 0.8\n", + " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 50.0\n", + " 14\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 203\n", - " 63.0\n", - " 322\n", - " 60.9\n", - " 2.1\n", - " 07-Dec\n", + " 490\n", + " 68.0\n", + " 721\n", + " 67.0\n", + " 1.0\n", + " 30-Mar\n", " \n", " \n", " yes\n", - " 56\n", - " 57.1\n", " 98\n", - " 57.1\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " brand_of_first_dose\n", - " Moderna\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", + " 66.7\n", + " 147\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", + " brand_of_first_dose\n", " Pfizer\n", " 0\n", " 0.0\n", @@ -26503,12 +26612,12 @@ " \n", " \n", " Unknown\n", - " 259\n", - " 71.2\n", - " 364\n", - " 69.2\n", - " 2.0\n", - " 12-Nov\n", + " 581\n", + " 74.8\n", + " 777\n", + " 74.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", "\n", @@ -26517,139 +26626,135 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 259 61.7 420 \n", - "newly_shielded_since_feb_15 no 259 62.7 413 \n", - " yes 0 0.0 0 \n", - "sex F 147 67.7 217 \n", - " M 112 55.2 203 \n", - "ageband 16-29 35 62.5 56 \n", - " 30-39 35 62.5 56 \n", - " 40-49 21 42.9 49 \n", - " 50-59 42 60.0 70 \n", - " 60-69 35 71.4 49 \n", - " 70-79 63 69.2 91 \n", - " 80+ 28 57.1 49 \n", - "ethnicity_6_groups Black 49 70.0 70 \n", - " Mixed 42 60.0 70 \n", - " Other 42 60.0 70 \n", - " South Asian 42 66.7 63 \n", - " Unknown 35 62.5 56 \n", - " White 56 61.5 91 \n", - "imd_categories 1 Most deprived 56 66.7 84 \n", - " 2 49 70.0 70 \n", - " 3 49 58.3 84 \n", - " 4 49 58.3 84 \n", - " 5 Least deprived 56 72.7 77 \n", - " Unknown 14 66.7 21 \n", - "LD no 259 62.7 413 \n", - " yes 0 0.0 0 \n", - "ckd no 203 63.0 322 \n", - " yes 56 57.1 98 \n", - "brand_of_first_dose Moderna 0 0.0 0 \n", - " Pfizer 0 0.0 0 \n", - " Unknown 259 71.2 364 \n", + "overall overall 588 67.7 868 \n", + "newly_shielded_since_feb_15 no 574 66.7 861 \n", + " yes 7 100.0 7 \n", + "sex F 308 68.8 448 \n", + " M 280 66.7 420 \n", + "ageband 16-29 70 66.7 105 \n", + " 30-39 70 66.7 105 \n", + " 40-49 77 68.8 112 \n", + " 50-59 77 61.1 126 \n", + " 60-69 70 62.5 112 \n", + " 70-79 133 65.5 203 \n", + " 80+ 84 75.0 112 \n", + "ethnicity_6_groups Black 98 70.0 140 \n", + " Mixed 105 65.2 161 \n", + " Other 105 75.0 140 \n", + " South Asian 105 71.4 147 \n", + " Unknown 77 64.7 119 \n", + " White 98 60.9 161 \n", + "imd_categories 1 Most deprived 112 61.5 182 \n", + " 2 98 66.7 147 \n", + " 3 112 66.7 168 \n", + " 4 119 73.9 161 \n", + " 5 Least deprived 119 70.8 168 \n", + " Unknown 28 66.7 42 \n", + "LD no 581 68.0 854 \n", + " yes 7 50.0 14 \n", + "ckd no 490 68.0 721 \n", + " yes 98 66.7 147 \n", + "brand_of_first_dose Pfizer 0 0.0 0 \n", + " Unknown 581 74.8 777 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 60.0 \n", - "newly_shielded_since_feb_15 no 61.0 \n", - " yes NaN \n", - "sex F 67.7 \n", - " M 55.2 \n", - "ageband 16-29 62.5 \n", - " 30-39 62.5 \n", - " 40-49 42.9 \n", - " 50-59 50.0 \n", - " 60-69 71.4 \n", - " 70-79 69.2 \n", - " 80+ 57.1 \n", - "ethnicity_6_groups Black 60.0 \n", - " Mixed 60.0 \n", - " Other 60.0 \n", - " South Asian 55.6 \n", - " Unknown 62.5 \n", - " White 61.5 \n", - "imd_categories 1 Most deprived 58.3 \n", - " 2 60.0 \n", - " 3 58.3 \n", - " 4 58.3 \n", - " 5 Least deprived 72.7 \n", + "overall overall 66.9 \n", + "newly_shielded_since_feb_15 no 66.7 \n", + " yes 100.0 \n", + "sex F 68.8 \n", + " M 66.7 \n", + "ageband 16-29 66.7 \n", + " 30-39 66.7 \n", + " 40-49 68.8 \n", + " 50-59 61.1 \n", + " 60-69 62.5 \n", + " 70-79 65.5 \n", + " 80+ 75.0 \n", + "ethnicity_6_groups Black 70.0 \n", + " Mixed 65.2 \n", + " Other 75.0 \n", + " South Asian 71.4 \n", + " Unknown 64.7 \n", + " White 60.9 \n", + "imd_categories 1 Most deprived 61.5 \n", + " 2 61.9 \n", + " 3 66.7 \n", + " 4 73.9 \n", + " 5 Least deprived 70.8 \n", " Unknown 66.7 \n", - "LD no 61.0 \n", - " yes NaN \n", - "ckd no 60.9 \n", - " yes 57.1 \n", - "brand_of_first_dose Moderna NaN \n", - " Pfizer NaN \n", - " Unknown 69.2 \n", + "LD no 67.2 \n", + " yes 50.0 \n", + "ckd no 67.0 \n", + " yes 66.7 \n", + "brand_of_first_dose Pfizer NaN \n", + " Unknown 74.8 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.7 \n", - "newly_shielded_since_feb_15 no 1.7 \n", + "overall overall 0.8 \n", + "newly_shielded_since_feb_15 no 0.0 \n", " yes 0.0 \n", "sex F 0.0 \n", " M 0.0 \n", "ageband 16-29 0.0 \n", " 30-39 0.0 \n", " 40-49 0.0 \n", - " 50-59 10.0 \n", + " 50-59 0.0 \n", " 60-69 0.0 \n", " 70-79 0.0 \n", " 80+ 0.0 \n", - "ethnicity_6_groups Black 10.0 \n", + "ethnicity_6_groups Black 0.0 \n", " Mixed 0.0 \n", " Other 0.0 \n", - " South Asian 11.1 \n", + " South Asian 0.0 \n", " Unknown 0.0 \n", " White 0.0 \n", - "imd_categories 1 Most deprived 8.4 \n", - " 2 10.0 \n", + "imd_categories 1 Most deprived 0.0 \n", + " 2 4.8 \n", " 3 0.0 \n", " 4 0.0 \n", " 5 Least deprived 0.0 \n", " Unknown 0.0 \n", - "LD no 1.7 \n", + "LD no 0.8 \n", " yes 0.0 \n", - "ckd no 2.1 \n", + "ckd no 1.0 \n", " yes 0.0 \n", - "brand_of_first_dose Moderna 0.0 \n", - " Pfizer 0.0 \n", - " Unknown 2.0 \n", + "brand_of_first_dose Pfizer 0.0 \n", + " Unknown 0.0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 02-Jan \n", - "newly_shielded_since_feb_15 no 29-Dec \n", - " yes unknown \n", + "overall overall unknown \n", + "newly_shielded_since_feb_15 no unknown \n", + " yes reached \n", "sex F unknown \n", " M unknown \n", "ageband 16-29 unknown \n", " 30-39 unknown \n", " 40-49 unknown \n", - " 50-59 29-Sep \n", + " 50-59 unknown \n", " 60-69 unknown \n", " 70-79 unknown \n", " 80+ unknown \n", - "ethnicity_6_groups Black 22-Sep \n", + "ethnicity_6_groups Black unknown \n", " Mixed unknown \n", " Other unknown \n", - " South Asian 22-Sep \n", + " South Asian unknown \n", " Unknown unknown \n", " White unknown \n", - "imd_categories 1 Most deprived 27-Sep \n", - " 2 22-Sep \n", + "imd_categories 1 Most deprived unknown \n", + " 2 29-Nov \n", " 3 unknown \n", " 4 unknown \n", " 5 Least deprived unknown \n", " Unknown unknown \n", - "LD no 29-Dec \n", + "LD no unknown \n", " yes unknown \n", - "ckd no 07-Dec \n", + "ckd no 30-Mar \n", " yes unknown \n", - "brand_of_first_dose Moderna unknown \n", - " Pfizer unknown \n", - " Unknown 12-Nov " + "brand_of_first_dose Pfizer unknown \n", + " Unknown unknown " ] }, "metadata": {}, @@ -26678,7 +26783,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **65-69** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **65-69** population up to 2021-10-27" ], "text/plain": [ "" @@ -26744,406 +26849,406 @@ " \n", " overall\n", " overall\n", - " 1442\n", - " 66.5\n", - " 2170\n", - " 65.2\n", + " 3017\n", + " 68.3\n", + " 4417\n", + " 67.0\n", " 1.3\n", - " 12-Jan\n", + " 20-Feb\n", " \n", " \n", " sex\n", " F\n", - " 714\n", - " 66.7\n", - " 1071\n", - " 65.4\n", - " 1.3\n", - " 11-Jan\n", + " 1505\n", + " 67.6\n", + " 2226\n", + " 66.0\n", + " 1.6\n", + " 02-Feb\n", " \n", " \n", " M\n", - " 728\n", - " 66.2\n", - " 1099\n", - " 65.0\n", + " 1519\n", + " 69.3\n", + " 2191\n", + " 68.1\n", " 1.2\n", - " 24-Jan\n", + " 24-Feb\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 259\n", - " 69.8\n", - " 371\n", - " 67.9\n", - " 1.9\n", - " 21-Nov\n", + " 518\n", + " 68.5\n", + " 756\n", + " 67.6\n", + " 0.9\n", + " 12-Apr\n", " \n", " \n", " Mixed\n", - " 231\n", - " 66.0\n", - " 350\n", - " 64.0\n", - " 2.0\n", - " 01-Dec\n", + " 532\n", + " 69.1\n", + " 770\n", + " 68.2\n", + " 0.9\n", + " 07-Apr\n", " \n", " \n", " Other\n", - " 238\n", - " 68.0\n", - " 350\n", - " 68.0\n", - " 0.0\n", - " unknown\n", + " 504\n", + " 67.3\n", + " 749\n", + " 65.4\n", + " 1.9\n", + " 18-Jan\n", " \n", " \n", " South Asian\n", - " 259\n", - " 64.9\n", - " 399\n", - " 63.2\n", - " 1.7\n", - " 20-Dec\n", + " 469\n", + " 66.3\n", + " 707\n", + " 65.3\n", + " 1.0\n", + " 10-Apr\n", " \n", " \n", " Unknown\n", - " 210\n", - " 62.5\n", - " 336\n", - " 62.5\n", - " 0.0\n", - " unknown\n", + " 490\n", + " 70.0\n", + " 700\n", + " 69.0\n", + " 1.0\n", + " 16-Mar\n", " \n", " \n", " White\n", - " 245\n", - " 67.3\n", - " 364\n", - " 65.4\n", - " 1.9\n", - " 30-Nov\n", + " 504\n", + " 68.6\n", + " 735\n", + " 67.6\n", + " 1.0\n", + " 25-Mar\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 70\n", - " 62.5\n", - " 112\n", - " 62.5\n", - " 0.0\n", - " unknown\n", + " 168\n", + " 75.0\n", + " 224\n", + " 71.9\n", + " 3.1\n", + " 29-Nov\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 77\n", - " 61.1\n", - " 126\n", - " 61.1\n", + " 154\n", + " 66.7\n", + " 231\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 63\n", - " 60.0\n", - " 105\n", - " 60.0\n", - " 0.0\n", - " unknown\n", + " 175\n", + " 73.5\n", + " 238\n", + " 70.6\n", + " 2.9\n", + " 05-Dec\n", " \n", " \n", " Chinese\n", - " 70\n", - " 62.5\n", - " 112\n", - " 62.5\n", + " 168\n", + " 68.6\n", + " 245\n", + " 68.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 98\n", - " 73.7\n", - " 133\n", - " 73.7\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 71.1\n", + " 266\n", + " 68.4\n", + " 2.7\n", + " 15-Dec\n", " \n", " \n", " Other Asian\n", - " 84\n", - " 66.7\n", - " 126\n", - " 66.7\n", + " 140\n", + " 64.5\n", + " 217\n", + " 64.5\n", " 0.0\n", " unknown\n", " \n", " \n", " British or Mixed British\n", - " 70\n", - " 62.5\n", - " 112\n", - " 62.5\n", + " 161\n", + " 67.6\n", + " 238\n", + " 67.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 70\n", - " 66.7\n", - " 105\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 168\n", + " 68.6\n", + " 245\n", + " 65.7\n", + " 2.9\n", + " 17-Dec\n", " \n", " \n", " Irish\n", - " 77\n", - " 68.8\n", - " 112\n", - " 62.5\n", - " 6.3\n", - " 01-Oct\n", + " 175\n", + " 75.8\n", + " 231\n", + " 72.7\n", + " 3.1\n", + " 28-Nov\n", " \n", " \n", " Other Black\n", - " 77\n", - " 68.8\n", - " 112\n", - " 62.5\n", - " 6.3\n", - " 01-Oct\n", + " 168\n", + " 70.6\n", + " 238\n", + " 67.6\n", + " 3.0\n", + " 11-Dec\n", " \n", " \n", " Other White\n", - " 77\n", - " 68.8\n", - " 112\n", - " 68.8\n", + " 168\n", + " 70.6\n", + " 238\n", + " 70.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 56\n", - " 61.5\n", - " 91\n", - " 61.5\n", + " 154\n", + " 61.1\n", + " 252\n", + " 61.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 91\n", - " 68.4\n", - " 133\n", - " 68.4\n", + " 161\n", + " 67.6\n", + " 238\n", + " 67.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 210\n", - " 63.8\n", - " 329\n", - " 63.8\n", - " 0.0\n", - " unknown\n", + " 413\n", + " 66.3\n", + " 623\n", + " 64.0\n", + " 2.3\n", + " 07-Jan\n", " \n", " \n", " White + Asian\n", - " 77\n", - " 68.8\n", - " 112\n", - " 68.8\n", - " 0.0\n", - " unknown\n", + " 147\n", + " 65.6\n", + " 224\n", + " 62.5\n", + " 3.1\n", + " 21-Dec\n", " \n", " \n", " White + Black African\n", - " 77\n", - " 64.7\n", - " 119\n", - " 64.7\n", + " 140\n", + " 71.4\n", + " 196\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 91\n", - " 72.2\n", - " 126\n", - " 72.2\n", + " 168\n", + " 64.9\n", + " 259\n", + " 64.9\n", " 0.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 259\n", - " 66.1\n", - " 392\n", - " 64.3\n", - " 1.8\n", - " 09-Dec\n", + " 574\n", + " 70.1\n", + " 819\n", + " 68.4\n", + " 1.7\n", + " 16-Jan\n", " \n", " \n", " 2\n", - " 301\n", - " 67.2\n", - " 448\n", - " 65.6\n", - " 1.6\n", - " 16-Dec\n", + " 546\n", + " 65.0\n", + " 840\n", + " 64.2\n", + " 0.8\n", + " unknown\n", " \n", " \n", " 3\n", - " 280\n", - " 67.8\n", - " 413\n", - " 67.8\n", - " 0.0\n", - " unknown\n", + " 595\n", + " 69.7\n", + " 854\n", + " 68.0\n", + " 1.7\n", + " 18-Jan\n", " \n", " \n", " 4\n", - " 273\n", - " 67.2\n", - " 406\n", - " 65.5\n", - " 1.7\n", - " 10-Dec\n", + " 567\n", + " 67.5\n", + " 840\n", + " 66.7\n", + " 0.8\n", + " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 259\n", - " 63.8\n", - " 406\n", - " 62.1\n", + " 581\n", + " 69.2\n", + " 840\n", + " 67.5\n", " 1.7\n", - " 24-Dec\n", + " 20-Jan\n", " \n", " \n", " Unknown\n", - " 70\n", - " 66.7\n", - " 105\n", - " 66.7\n", + " 154\n", + " 71.0\n", + " 217\n", + " 71.0\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 399\n", - " 64.8\n", - " 616\n", - " 62.5\n", - " 2.3\n", - " 23-Nov\n", + " 952\n", + " 69.7\n", + " 1365\n", + " 68.7\n", + " 1.0\n", + " 18-Mar\n", " \n", " \n", " under 30\n", - " 1043\n", - " 67.1\n", - " 1554\n", - " 66.2\n", - " 0.9\n", - " unknown\n", + " 2065\n", + " 67.7\n", + " 3052\n", + " 66.3\n", + " 1.4\n", + " 15-Feb\n", " \n", " \n", " housebound\n", " no\n", - " 1435\n", - " 66.6\n", - " 2156\n", - " 65.3\n", - " 1.3\n", - " 12-Jan\n", + " 2989\n", + " 68.5\n", + " 4361\n", + " 67.3\n", + " 1.2\n", + " 01-Mar\n", " \n", " \n", " yes\n", - " 7\n", - " 50.0\n", - " 14\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 35\n", + " 71.4\n", + " 49\n", + " 57.1\n", + " 14.3\n", + " 05-Nov\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1414\n", - " 66.2\n", - " 2135\n", - " 64.9\n", + " 2989\n", + " 68.4\n", + " 4368\n", + " 67.1\n", " 1.3\n", - " 14-Jan\n", + " 20-Feb\n", " \n", " \n", " yes\n", " 28\n", - " 80.0\n", - " 35\n", - " 80.0\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1428\n", - " 66.4\n", - " 2149\n", - " 65.1\n", + " 2982\n", + " 68.2\n", + " 4375\n", + " 66.9\n", " 1.3\n", - " 13-Jan\n", + " 21-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 83.3\n", + " 42\n", + " 83.3\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1428\n", - " 66.4\n", - " 2149\n", - " 65.1\n", + " 2982\n", + " 68.3\n", + " 4368\n", + " 67.0\n", " 1.3\n", - " 13-Jan\n", + " 20-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 71.4\n", + " 49\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 1421\n", - " 66.1\n", - " 2149\n", - " 65.1\n", - " 1.0\n", - " 22-Feb\n", + " 2989\n", + " 68.4\n", + " 4368\n", + " 67.1\n", + " 1.3\n", + " 20-Feb\n", " \n", " \n", " yes\n", - " 14\n", + " 28\n", " 66.7\n", - " 21\n", + " 42\n", " 66.7\n", " 0.0\n", " unknown\n", @@ -27151,132 +27256,132 @@ " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1428\n", - " 66.4\n", - " 2149\n", - " 65.1\n", + " 2989\n", + " 68.4\n", + " 4368\n", + " 67.1\n", " 1.3\n", - " 13-Jan\n", + " 20-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " LD\n", " no\n", - " 1414\n", - " 66.4\n", - " 2128\n", - " 65.1\n", + " 2947\n", + " 68.3\n", + " 4312\n", + " 67.0\n", " 1.3\n", - " 13-Jan\n", + " 20-Feb\n", " \n", " \n", " yes\n", - " 28\n", + " 70\n", " 66.7\n", - " 42\n", - " 50.0\n", - " 16.7\n", - " 17-Sep\n", + " 105\n", + " 66.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1428\n", - " 66.4\n", - " 2149\n", - " 65.1\n", + " 2996\n", + " 68.5\n", + " 4375\n", + " 67.2\n", " 1.3\n", - " 13-Jan\n", + " 19-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", " 21\n", - " 66.7\n", + " 60.0\n", + " 35\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 1428\n", - " 66.4\n", - " 2149\n", - " 65.1\n", + " 2989\n", + " 68.3\n", + " 4375\n", + " 67.0\n", " 1.3\n", - " 13-Jan\n", + " 20-Feb\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 28\n", + " 66.7\n", + " 42\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1428\n", - " 66.4\n", - " 2149\n", - " 65.1\n", + " 2996\n", + " 68.4\n", + " 4382\n", + " 67.1\n", " 1.3\n", - " 13-Jan\n", + " 20-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", " 21\n", - " 66.7\n", + " 60.0\n", + " 35\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1435\n", - " 66.8\n", - " 2149\n", - " 65.5\n", + " 2989\n", + " 68.3\n", + " 4375\n", + " 67.0\n", " 1.3\n", - " 10-Jan\n", + " 20-Feb\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 28\n", + " 80.0\n", + " 35\n", + " 80.0\n", " 0.0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1428\n", - " 66.4\n", - " 2149\n", - " 65.1\n", + " 2989\n", + " 68.4\n", + " 4368\n", + " 67.1\n", " 1.3\n", - " 13-Jan\n", + " 20-Feb\n", " \n", " \n", " yes\n", - " 14\n", + " 28\n", " 66.7\n", - " 21\n", + " 42\n", " 66.7\n", " 0.0\n", " unknown\n", @@ -27284,21 +27389,21 @@ " \n", " ckd\n", " no\n", - " 1141\n", - " 65.7\n", - " 1736\n", - " 64.5\n", - " 1.2\n", - " 27-Jan\n", + " 2373\n", + " 68.3\n", + " 3472\n", + " 66.9\n", + " 1.4\n", + " 12-Feb\n", " \n", " \n", " yes\n", - " 301\n", + " 651\n", " 69.4\n", - " 434\n", - " 67.7\n", - " 1.7\n", - " 01-Dec\n", + " 938\n", + " 67.9\n", + " 1.5\n", + " 31-Jan\n", " \n", " \n", " brand_of_first_dose\n", @@ -27330,12 +27435,12 @@ " \n", " \n", " Unknown\n", - " 1435\n", - " 73.7\n", - " 1946\n", - " 72.3\n", + " 3010\n", + " 75.8\n", + " 3969\n", + " 74.4\n", " 1.4\n", - " 28-Nov\n", + " 06-Jan\n", " \n", " \n", "\n", @@ -27344,255 +27449,255 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1442 \n", - "sex F 714 \n", - " M 728 \n", - "ethnicity_6_groups Black 259 \n", - " Mixed 231 \n", - " Other 238 \n", - " South Asian 259 \n", - " Unknown 210 \n", - " White 245 \n", - "ethnicity_16_groups African 70 \n", - " Bangladeshi or British Bangladeshi 77 \n", - " Caribbean 63 \n", - " Chinese 70 \n", - " Other 98 \n", - " Other Asian 84 \n", - " British or Mixed British 70 \n", - " Indian or British Indian 70 \n", - " Irish 77 \n", - " Other Black 77 \n", - " Other White 77 \n", - " Other mixed 56 \n", - " Pakistani or British Pakistani 91 \n", - " Unknown 210 \n", - " White + Asian 77 \n", - " White + Black African 77 \n", - " White + Black Caribbean 91 \n", - "imd_categories 1 Most deprived 259 \n", - " 2 301 \n", - " 3 280 \n", - " 4 273 \n", - " 5 Least deprived 259 \n", - " Unknown 70 \n", - "bmi 30+ 399 \n", - " under 30 1043 \n", - "housebound no 1435 \n", - " yes 7 \n", - "chronic_cardiac_disease no 1414 \n", + "overall overall 3017 \n", + "sex F 1505 \n", + " M 1519 \n", + "ethnicity_6_groups Black 518 \n", + " Mixed 532 \n", + " Other 504 \n", + " South Asian 469 \n", + " Unknown 490 \n", + " White 504 \n", + "ethnicity_16_groups African 168 \n", + " Bangladeshi or British Bangladeshi 154 \n", + " Caribbean 175 \n", + " Chinese 168 \n", + " Other 189 \n", + " Other Asian 140 \n", + " British or Mixed British 161 \n", + " Indian or British Indian 168 \n", + " Irish 175 \n", + " Other Black 168 \n", + " Other White 168 \n", + " Other mixed 154 \n", + " Pakistani or British Pakistani 161 \n", + " Unknown 413 \n", + " White + Asian 147 \n", + " White + Black African 140 \n", + " White + Black Caribbean 168 \n", + "imd_categories 1 Most deprived 574 \n", + " 2 546 \n", + " 3 595 \n", + " 4 567 \n", + " 5 Least deprived 581 \n", + " Unknown 154 \n", + "bmi 30+ 952 \n", + " under 30 2065 \n", + "housebound no 2989 \n", + " yes 35 \n", + "chronic_cardiac_disease no 2989 \n", " yes 28 \n", - "current_copd no 1428 \n", - " yes 14 \n", - "dmards no 1428 \n", - " yes 14 \n", - "dementia no 1421 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1428 \n", - " yes 14 \n", - "LD no 1414 \n", + "current_copd no 2982 \n", + " yes 35 \n", + "dmards no 2982 \n", + " yes 35 \n", + "dementia no 2989 \n", " yes 28 \n", - "ssri no 1428 \n", - " yes 14 \n", - "chemo_or_radio no 1428 \n", - " yes 7 \n", - "lung_cancer no 1428 \n", - " yes 14 \n", - "cancer_excl_lung_and_haem no 1435 \n", - " yes 7 \n", - "haematological_cancer no 1428 \n", - " yes 14 \n", - "ckd no 1141 \n", - " yes 301 \n", + "psychosis_schiz_bipolar no 2989 \n", + " yes 28 \n", + "LD no 2947 \n", + " yes 70 \n", + "ssri no 2996 \n", + " yes 21 \n", + "chemo_or_radio no 2989 \n", + " yes 28 \n", + "lung_cancer no 2996 \n", + " yes 21 \n", + "cancer_excl_lung_and_haem no 2989 \n", + " yes 28 \n", + "haematological_cancer no 2989 \n", + " yes 28 \n", + "ckd no 2373 \n", + " yes 651 \n", "brand_of_first_dose Moderna 0 \n", " Oxford-AZ 0 \n", " Pfizer 0 \n", - " Unknown 1435 \n", + " Unknown 3010 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 66.5 2170 \n", - "sex F 66.7 1071 \n", - " M 66.2 1099 \n", - "ethnicity_6_groups Black 69.8 371 \n", - " Mixed 66.0 350 \n", - " Other 68.0 350 \n", - " South Asian 64.9 399 \n", - " Unknown 62.5 336 \n", - " White 67.3 364 \n", - "ethnicity_16_groups African 62.5 112 \n", - " Bangladeshi or British Bangladeshi 61.1 126 \n", - " Caribbean 60.0 105 \n", - " Chinese 62.5 112 \n", - " Other 73.7 133 \n", - " Other Asian 66.7 126 \n", - " British or Mixed British 62.5 112 \n", - " Indian or British Indian 66.7 105 \n", - " Irish 68.8 112 \n", - " Other Black 68.8 112 \n", - " Other White 68.8 112 \n", - " Other mixed 61.5 91 \n", - " Pakistani or British Pakistani 68.4 133 \n", - " Unknown 63.8 329 \n", - " White + Asian 68.8 112 \n", - " White + Black African 64.7 119 \n", - " White + Black Caribbean 72.2 126 \n", - "imd_categories 1 Most deprived 66.1 392 \n", - " 2 67.2 448 \n", - " 3 67.8 413 \n", - " 4 67.2 406 \n", - " 5 Least deprived 63.8 406 \n", - " Unknown 66.7 105 \n", - "bmi 30+ 64.8 616 \n", - " under 30 67.1 1554 \n", - "housebound no 66.6 2156 \n", - " yes 50.0 14 \n", - "chronic_cardiac_disease no 66.2 2135 \n", + "overall overall 68.3 4417 \n", + "sex F 67.6 2226 \n", + " M 69.3 2191 \n", + "ethnicity_6_groups Black 68.5 756 \n", + " Mixed 69.1 770 \n", + " Other 67.3 749 \n", + " South Asian 66.3 707 \n", + " Unknown 70.0 700 \n", + " White 68.6 735 \n", + "ethnicity_16_groups African 75.0 224 \n", + " Bangladeshi or British Bangladeshi 66.7 231 \n", + " Caribbean 73.5 238 \n", + " Chinese 68.6 245 \n", + " Other 71.1 266 \n", + " Other Asian 64.5 217 \n", + " British or Mixed British 67.6 238 \n", + " Indian or British Indian 68.6 245 \n", + " Irish 75.8 231 \n", + " Other Black 70.6 238 \n", + " Other White 70.6 238 \n", + " Other mixed 61.1 252 \n", + " Pakistani or British Pakistani 67.6 238 \n", + " Unknown 66.3 623 \n", + " White + Asian 65.6 224 \n", + " White + Black African 71.4 196 \n", + " White + Black Caribbean 64.9 259 \n", + "imd_categories 1 Most deprived 70.1 819 \n", + " 2 65.0 840 \n", + " 3 69.7 854 \n", + " 4 67.5 840 \n", + " 5 Least deprived 69.2 840 \n", + " Unknown 71.0 217 \n", + "bmi 30+ 69.7 1365 \n", + " under 30 67.7 3052 \n", + "housebound no 68.5 4361 \n", + " yes 71.4 49 \n", + "chronic_cardiac_disease no 68.4 4368 \n", + " yes 57.1 49 \n", + "current_copd no 68.2 4375 \n", + " yes 83.3 42 \n", + "dmards no 68.3 4368 \n", + " yes 71.4 49 \n", + "dementia no 68.4 4368 \n", + " yes 66.7 42 \n", + "psychosis_schiz_bipolar no 68.4 4368 \n", + " yes 57.1 49 \n", + "LD no 68.3 4312 \n", + " yes 66.7 105 \n", + "ssri no 68.5 4375 \n", + " yes 60.0 35 \n", + "chemo_or_radio no 68.3 4375 \n", + " yes 66.7 42 \n", + "lung_cancer no 68.4 4382 \n", + " yes 60.0 35 \n", + "cancer_excl_lung_and_haem no 68.3 4375 \n", " yes 80.0 35 \n", - "current_copd no 66.4 2149 \n", - " yes 66.7 21 \n", - "dmards no 66.4 2149 \n", - " yes 66.7 21 \n", - "dementia no 66.1 2149 \n", - " yes 66.7 21 \n", - "psychosis_schiz_bipolar no 66.4 2149 \n", - " yes 66.7 21 \n", - "LD no 66.4 2128 \n", + "haematological_cancer no 68.4 4368 \n", " yes 66.7 42 \n", - "ssri no 66.4 2149 \n", - " yes 66.7 21 \n", - "chemo_or_radio no 66.4 2149 \n", - " yes 33.3 21 \n", - "lung_cancer no 66.4 2149 \n", - " yes 66.7 21 \n", - "cancer_excl_lung_and_haem no 66.8 2149 \n", - " yes 33.3 21 \n", - "haematological_cancer no 66.4 2149 \n", - " yes 66.7 21 \n", - "ckd no 65.7 1736 \n", - " yes 69.4 434 \n", + "ckd no 68.3 3472 \n", + " yes 69.4 938 \n", "brand_of_first_dose Moderna 0.0 0 \n", " Oxford-AZ 0.0 0 \n", " Pfizer 0.0 0 \n", - " Unknown 73.7 1946 \n", + " Unknown 75.8 3969 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 65.2 \n", - "sex F 65.4 \n", - " M 65.0 \n", - "ethnicity_6_groups Black 67.9 \n", - " Mixed 64.0 \n", - " Other 68.0 \n", - " South Asian 63.2 \n", - " Unknown 62.5 \n", - " White 65.4 \n", - "ethnicity_16_groups African 62.5 \n", - " Bangladeshi or British Bangladeshi 61.1 \n", - " Caribbean 60.0 \n", - " Chinese 62.5 \n", - " Other 73.7 \n", - " Other Asian 66.7 \n", - " British or Mixed British 62.5 \n", - " Indian or British Indian 66.7 \n", - " Irish 62.5 \n", - " Other Black 62.5 \n", - " Other White 68.8 \n", - " Other mixed 61.5 \n", - " Pakistani or British Pakistani 68.4 \n", - " Unknown 63.8 \n", - " White + Asian 68.8 \n", - " White + Black African 64.7 \n", - " White + Black Caribbean 72.2 \n", - "imd_categories 1 Most deprived 64.3 \n", - " 2 65.6 \n", - " 3 67.8 \n", - " 4 65.5 \n", - " 5 Least deprived 62.1 \n", - " Unknown 66.7 \n", - "bmi 30+ 62.5 \n", - " under 30 66.2 \n", - "housebound no 65.3 \n", - " yes 50.0 \n", - "chronic_cardiac_disease no 64.9 \n", - " yes 80.0 \n", - "current_copd no 65.1 \n", - " yes 66.7 \n", - "dmards no 65.1 \n", - " yes 66.7 \n", - "dementia no 65.1 \n", - " yes 66.7 \n", - "psychosis_schiz_bipolar no 65.1 \n", + "overall overall 67.0 \n", + "sex F 66.0 \n", + " M 68.1 \n", + "ethnicity_6_groups Black 67.6 \n", + " Mixed 68.2 \n", + " Other 65.4 \n", + " South Asian 65.3 \n", + " Unknown 69.0 \n", + " White 67.6 \n", + "ethnicity_16_groups African 71.9 \n", + " Bangladeshi or British Bangladeshi 66.7 \n", + " Caribbean 70.6 \n", + " Chinese 68.6 \n", + " Other 68.4 \n", + " Other Asian 64.5 \n", + " British or Mixed British 67.6 \n", + " Indian or British Indian 65.7 \n", + " Irish 72.7 \n", + " Other Black 67.6 \n", + " Other White 70.6 \n", + " Other mixed 61.1 \n", + " Pakistani or British Pakistani 67.6 \n", + " Unknown 64.0 \n", + " White + Asian 62.5 \n", + " White + Black African 71.4 \n", + " White + Black Caribbean 64.9 \n", + "imd_categories 1 Most deprived 68.4 \n", + " 2 64.2 \n", + " 3 68.0 \n", + " 4 66.7 \n", + " 5 Least deprived 67.5 \n", + " Unknown 71.0 \n", + "bmi 30+ 68.7 \n", + " under 30 66.3 \n", + "housebound no 67.3 \n", + " yes 57.1 \n", + "chronic_cardiac_disease no 67.1 \n", + " yes 57.1 \n", + "current_copd no 66.9 \n", + " yes 83.3 \n", + "dmards no 67.0 \n", + " yes 71.4 \n", + "dementia no 67.1 \n", " yes 66.7 \n", - "LD no 65.1 \n", - " yes 50.0 \n", - "ssri no 65.1 \n", + "psychosis_schiz_bipolar no 67.1 \n", + " yes 57.1 \n", + "LD no 67.0 \n", " yes 66.7 \n", - "chemo_or_radio no 65.1 \n", - " yes 33.3 \n", - "lung_cancer no 65.1 \n", + "ssri no 67.2 \n", + " yes 60.0 \n", + "chemo_or_radio no 67.0 \n", " yes 66.7 \n", - "cancer_excl_lung_and_haem no 65.5 \n", - " yes 33.3 \n", - "haematological_cancer no 65.1 \n", + "lung_cancer no 67.1 \n", + " yes 60.0 \n", + "cancer_excl_lung_and_haem no 67.0 \n", + " yes 80.0 \n", + "haematological_cancer no 67.1 \n", " yes 66.7 \n", - "ckd no 64.5 \n", - " yes 67.7 \n", + "ckd no 66.9 \n", + " yes 67.9 \n", "brand_of_first_dose Moderna NaN \n", " Oxford-AZ NaN \n", " Pfizer NaN \n", - " Unknown 72.3 \n", + " Unknown 74.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", "overall overall 1.3 \n", - "sex F 1.3 \n", + "sex F 1.6 \n", " M 1.2 \n", - "ethnicity_6_groups Black 1.9 \n", - " Mixed 2.0 \n", - " Other 0.0 \n", - " South Asian 1.7 \n", - " Unknown 0.0 \n", - " White 1.9 \n", - "ethnicity_16_groups African 0.0 \n", + "ethnicity_6_groups Black 0.9 \n", + " Mixed 0.9 \n", + " Other 1.9 \n", + " South Asian 1.0 \n", + " Unknown 1.0 \n", + " White 1.0 \n", + "ethnicity_16_groups African 3.1 \n", " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", + " Caribbean 2.9 \n", " Chinese 0.0 \n", - " Other 0.0 \n", + " Other 2.7 \n", " Other Asian 0.0 \n", " British or Mixed British 0.0 \n", - " Indian or British Indian 0.0 \n", - " Irish 6.3 \n", - " Other Black 6.3 \n", + " Indian or British Indian 2.9 \n", + " Irish 3.1 \n", + " Other Black 3.0 \n", " Other White 0.0 \n", " Other mixed 0.0 \n", " Pakistani or British Pakistani 0.0 \n", - " Unknown 0.0 \n", - " White + Asian 0.0 \n", + " Unknown 2.3 \n", + " White + Asian 3.1 \n", " White + Black African 0.0 \n", " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 1.8 \n", - " 2 1.6 \n", - " 3 0.0 \n", - " 4 1.7 \n", + "imd_categories 1 Most deprived 1.7 \n", + " 2 0.8 \n", + " 3 1.7 \n", + " 4 0.8 \n", " 5 Least deprived 1.7 \n", " Unknown 0.0 \n", - "bmi 30+ 2.3 \n", - " under 30 0.9 \n", - "housebound no 1.3 \n", - " yes 0.0 \n", + "bmi 30+ 1.0 \n", + " under 30 1.4 \n", + "housebound no 1.2 \n", + " yes 14.3 \n", "chronic_cardiac_disease no 1.3 \n", " yes 0.0 \n", "current_copd no 1.3 \n", " yes 0.0 \n", "dmards no 1.3 \n", " yes 0.0 \n", - "dementia no 1.0 \n", + "dementia no 1.3 \n", " yes 0.0 \n", "psychosis_schiz_bipolar no 1.3 \n", " yes 0.0 \n", "LD no 1.3 \n", - " yes 16.7 \n", + " yes 0.0 \n", "ssri no 1.3 \n", " yes 0.0 \n", "chemo_or_radio no 1.3 \n", @@ -27603,8 +27708,8 @@ " yes 0.0 \n", "haematological_cancer no 1.3 \n", " yes 0.0 \n", - "ckd no 1.2 \n", - " yes 1.7 \n", + "ckd no 1.4 \n", + " yes 1.5 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", @@ -27612,70 +27717,70 @@ "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 12-Jan \n", - "sex F 11-Jan \n", - " M 24-Jan \n", - "ethnicity_6_groups Black 21-Nov \n", - " Mixed 01-Dec \n", - " Other unknown \n", - " South Asian 20-Dec \n", - " Unknown unknown \n", - " White 30-Nov \n", - "ethnicity_16_groups African unknown \n", + "overall overall 20-Feb \n", + "sex F 02-Feb \n", + " M 24-Feb \n", + "ethnicity_6_groups Black 12-Apr \n", + " Mixed 07-Apr \n", + " Other 18-Jan \n", + " South Asian 10-Apr \n", + " Unknown 16-Mar \n", + " White 25-Mar \n", + "ethnicity_16_groups African 29-Nov \n", " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean unknown \n", + " Caribbean 05-Dec \n", " Chinese unknown \n", - " Other unknown \n", + " Other 15-Dec \n", " Other Asian unknown \n", " British or Mixed British unknown \n", - " Indian or British Indian unknown \n", - " Irish 01-Oct \n", - " Other Black 01-Oct \n", + " Indian or British Indian 17-Dec \n", + " Irish 28-Nov \n", + " Other Black 11-Dec \n", " Other White unknown \n", " Other mixed unknown \n", " Pakistani or British Pakistani unknown \n", - " Unknown unknown \n", - " White + Asian unknown \n", + " Unknown 07-Jan \n", + " White + Asian 21-Dec \n", " White + Black African unknown \n", " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived 09-Dec \n", - " 2 16-Dec \n", - " 3 unknown \n", - " 4 10-Dec \n", - " 5 Least deprived 24-Dec \n", + "imd_categories 1 Most deprived 16-Jan \n", + " 2 unknown \n", + " 3 18-Jan \n", + " 4 unknown \n", + " 5 Least deprived 20-Jan \n", " Unknown unknown \n", - "bmi 30+ 23-Nov \n", - " under 30 unknown \n", - "housebound no 12-Jan \n", + "bmi 30+ 18-Mar \n", + " under 30 15-Feb \n", + "housebound no 01-Mar \n", + " yes 05-Nov \n", + "chronic_cardiac_disease no 20-Feb \n", " yes unknown \n", - "chronic_cardiac_disease no 14-Jan \n", + "current_copd no 21-Feb \n", " yes unknown \n", - "current_copd no 13-Jan \n", + "dmards no 20-Feb \n", " yes unknown \n", - "dmards no 13-Jan \n", + "dementia no 20-Feb \n", " yes unknown \n", - "dementia no 22-Feb \n", + "psychosis_schiz_bipolar no 20-Feb \n", " yes unknown \n", - "psychosis_schiz_bipolar no 13-Jan \n", + "LD no 20-Feb \n", " yes unknown \n", - "LD no 13-Jan \n", - " yes 17-Sep \n", - "ssri no 13-Jan \n", + "ssri no 19-Feb \n", " yes unknown \n", - "chemo_or_radio no 13-Jan \n", + "chemo_or_radio no 20-Feb \n", " yes unknown \n", - "lung_cancer no 13-Jan \n", + "lung_cancer no 20-Feb \n", " yes unknown \n", - "cancer_excl_lung_and_haem no 10-Jan \n", + "cancer_excl_lung_and_haem no 20-Feb \n", " yes unknown \n", - "haematological_cancer no 13-Jan \n", + "haematological_cancer no 20-Feb \n", " yes unknown \n", - "ckd no 27-Jan \n", - " yes 01-Dec \n", + "ckd no 12-Feb \n", + " yes 31-Jan \n", "brand_of_first_dose Moderna unknown \n", " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 28-Nov " + " Unknown 06-Jan " ] }, "metadata": {}, @@ -27704,7 +27809,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **LD (aged 16-64)** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **LD (aged 16-64)** population up to 2021-10-27" ], "text/plain": [ "" @@ -27770,243 +27875,243 @@ " \n", " overall\n", " overall\n", - " 532\n", - " 66.1\n", - " 805\n", - " 64.3\n", + " 1155\n", + " 72.1\n", + " 1603\n", + " 70.3\n", " 1.8\n", - " 09-Dec\n", + " 04-Jan\n", " \n", " \n", " sex\n", " F\n", - " 273\n", - " 66.1\n", - " 413\n", - " 64.4\n", - " 1.7\n", - " 15-Dec\n", + " 567\n", + " 71.7\n", + " 791\n", + " 69.9\n", + " 1.8\n", + " 06-Jan\n", " \n", " \n", " M\n", - " 266\n", - " 67.9\n", - " 392\n", - " 64.3\n", - " 3.6\n", - " 20-Oct\n", + " 588\n", + " 72.4\n", + " 812\n", + " 70.7\n", + " 1.7\n", + " 07-Jan\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 7\n", - " 100.0\n", - " 7\n", - " 100.0\n", + " 14\n", + " 66.7\n", + " 21\n", + " 66.7\n", " 0.0\n", - " reached\n", + " unknown\n", " \n", " \n", " 0-15\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", + " 70\n", + " 66.7\n", + " 105\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 16-17\n", - " 35\n", - " 71.4\n", - " 49\n", - " 57.1\n", - " 14.3\n", - " 17-Sep\n", + " 84\n", + " 75.0\n", + " 112\n", + " 75.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 18-29\n", - " 35\n", - " 71.4\n", - " 49\n", - " 71.4\n", - " 0.0\n", - " unknown\n", + " 77\n", + " 73.3\n", + " 105\n", + " 66.7\n", + " 6.6\n", + " 13-Nov\n", " \n", " \n", " 30-34\n", - " 28\n", - " 66.7\n", - " 42\n", - " 66.7\n", + " 70\n", + " 71.4\n", + " 98\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " 35-39\n", - " 42\n", - " 85.7\n", - " 49\n", - " 71.4\n", - " 14.3\n", - " 10-Sep\n", + " 77\n", + " 73.3\n", + " 105\n", + " 73.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 40-44\n", - " 35\n", - " 71.4\n", - " 49\n", - " 71.4\n", + " 63\n", + " 75.0\n", + " 84\n", + " 75.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 45-49\n", - " 42\n", - " 75.0\n", - " 56\n", - " 75.0\n", + " 84\n", + " 70.6\n", + " 119\n", + " 70.6\n", " 0.0\n", " unknown\n", " \n", " \n", " 50-54\n", - " 42\n", - " 75.0\n", - " 56\n", - " 62.5\n", - " 12.5\n", - " 16-Sep\n", + " 84\n", + " 63.2\n", + " 133\n", + " 63.2\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 55-59\n", - " 35\n", - " 71.4\n", - " 49\n", - " 57.1\n", - " 14.3\n", - " 17-Sep\n", + " 77\n", + " 73.3\n", + " 105\n", + " 73.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 60-64\n", - " 42\n", - " 75.0\n", - " 56\n", - " 62.5\n", - " 12.5\n", - " 16-Sep\n", + " 77\n", + " 78.6\n", + " 98\n", + " 78.6\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 65-69\n", - " 42\n", - " 66.7\n", " 63\n", - " 66.7\n", + " 64.3\n", + " 98\n", + " 64.3\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-74\n", - " 35\n", - " 71.4\n", - " 49\n", - " 71.4\n", + " 56\n", + " 61.5\n", + " 91\n", + " 61.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 75-79\n", - " 28\n", - " 44.4\n", - " 63\n", - " 44.4\n", + " 84\n", + " 80.0\n", + " 105\n", + " 80.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 80-84\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", + " 70\n", + " 71.4\n", + " 98\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " 85-89\n", - " 35\n", - " 71.4\n", - " 49\n", - " 71.4\n", + " 84\n", + " 80.0\n", + " 105\n", + " 80.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 90+\n", - " 0\n", - " 0.0\n", - " 7\n", - " 0.0\n", - " 0.0\n", - " unknown\n", + " 14\n", + " 100.0\n", + " 14\n", + " 50.0\n", + " 50.0\n", + " reached\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 91\n", - " 72.2\n", - " 126\n", + " 189\n", + " 69.2\n", + " 273\n", " 66.7\n", - " 5.5\n", - " 30-Sep\n", + " 2.5\n", + " 24-Dec\n", " \n", " \n", " Mixed\n", - " 91\n", - " 56.5\n", - " 161\n", - " 56.5\n", - " 0.0\n", - " unknown\n", + " 203\n", + " 72.5\n", + " 280\n", + " 70.0\n", + " 2.5\n", + " 15-Dec\n", " \n", " \n", " Other\n", - " 91\n", - " 68.4\n", - " 133\n", - " 63.2\n", - " 5.2\n", - " 07-Oct\n", + " 224\n", + " 76.2\n", + " 294\n", + " 71.4\n", + " 4.8\n", + " 16-Nov\n", " \n", " \n", " South Asian\n", - " 84\n", - " 63.2\n", - " 133\n", - " 63.2\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 69.2\n", + " 273\n", + " 66.7\n", + " 2.5\n", + " 24-Dec\n", " \n", " \n", " Unknown\n", - " 91\n", - " 72.2\n", - " 126\n", - " 66.7\n", - " 5.5\n", - " 30-Sep\n", + " 161\n", + " 71.9\n", + " 224\n", + " 71.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White\n", - " 91\n", - " 72.2\n", - " 126\n", - " 66.7\n", - " 5.5\n", - " 30-Sep\n", + " 196\n", + " 75.7\n", + " 259\n", + " 73.0\n", + " 2.7\n", + " 03-Dec\n", " \n", " \n", - " brand_of_first_dose\n", + " brand_of_first_dose\n", " Oxford-AZ\n", " 0\n", " 0.0\n", @@ -28016,13 +28121,22 @@ " unknown\n", " \n", " \n", + " Pfizer\n", + " 0\n", + " 0.0\n", + " 0\n", + " NaN\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", " Unknown\n", - " 532\n", - " 73.1\n", - " 728\n", - " 70.2\n", - " 2.9\n", - " 18-Oct\n", + " 1155\n", + " 79.3\n", + " 1456\n", + " 76.9\n", + " 2.4\n", + " 27-Nov\n", " \n", " \n", "\n", @@ -28031,127 +28145,131 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 532 66.1 805 \n", - "sex F 273 66.1 413 \n", - " M 266 67.9 392 \n", - "ageband_5yr 0 7 100.0 7 \n", - " 0-15 28 57.1 49 \n", - " 16-17 35 71.4 49 \n", - " 18-29 35 71.4 49 \n", - " 30-34 28 66.7 42 \n", - " 35-39 42 85.7 49 \n", - " 40-44 35 71.4 49 \n", - " 45-49 42 75.0 56 \n", - " 50-54 42 75.0 56 \n", - " 55-59 35 71.4 49 \n", - " 60-64 42 75.0 56 \n", - " 65-69 42 66.7 63 \n", - " 70-74 35 71.4 49 \n", - " 75-79 28 44.4 63 \n", - " 80-84 28 57.1 49 \n", - " 85-89 35 71.4 49 \n", - " 90+ 0 0.0 7 \n", - "ethnicity_6_groups Black 91 72.2 126 \n", - " Mixed 91 56.5 161 \n", - " Other 91 68.4 133 \n", - " South Asian 84 63.2 133 \n", - " Unknown 91 72.2 126 \n", - " White 91 72.2 126 \n", + "overall overall 1155 72.1 1603 \n", + "sex F 567 71.7 791 \n", + " M 588 72.4 812 \n", + "ageband_5yr 0 14 66.7 21 \n", + " 0-15 70 66.7 105 \n", + " 16-17 84 75.0 112 \n", + " 18-29 77 73.3 105 \n", + " 30-34 70 71.4 98 \n", + " 35-39 77 73.3 105 \n", + " 40-44 63 75.0 84 \n", + " 45-49 84 70.6 119 \n", + " 50-54 84 63.2 133 \n", + " 55-59 77 73.3 105 \n", + " 60-64 77 78.6 98 \n", + " 65-69 63 64.3 98 \n", + " 70-74 56 61.5 91 \n", + " 75-79 84 80.0 105 \n", + " 80-84 70 71.4 98 \n", + " 85-89 84 80.0 105 \n", + " 90+ 14 100.0 14 \n", + "ethnicity_6_groups Black 189 69.2 273 \n", + " Mixed 203 72.5 280 \n", + " Other 224 76.2 294 \n", + " South Asian 189 69.2 273 \n", + " Unknown 161 71.9 224 \n", + " White 196 75.7 259 \n", "brand_of_first_dose Oxford-AZ 0 0.0 0 \n", - " Unknown 532 73.1 728 \n", + " Pfizer 0 0.0 0 \n", + " Unknown 1155 79.3 1456 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 64.3 \n", - "sex F 64.4 \n", - " M 64.3 \n", - "ageband_5yr 0 100.0 \n", - " 0-15 57.1 \n", - " 16-17 57.1 \n", - " 18-29 71.4 \n", - " 30-34 66.7 \n", - " 35-39 71.4 \n", - " 40-44 71.4 \n", - " 45-49 75.0 \n", - " 50-54 62.5 \n", - " 55-59 57.1 \n", - " 60-64 62.5 \n", - " 65-69 66.7 \n", - " 70-74 71.4 \n", - " 75-79 44.4 \n", - " 80-84 57.1 \n", - " 85-89 71.4 \n", - " 90+ 0.0 \n", + "overall overall 70.3 \n", + "sex F 69.9 \n", + " M 70.7 \n", + "ageband_5yr 0 66.7 \n", + " 0-15 66.7 \n", + " 16-17 75.0 \n", + " 18-29 66.7 \n", + " 30-34 71.4 \n", + " 35-39 73.3 \n", + " 40-44 75.0 \n", + " 45-49 70.6 \n", + " 50-54 63.2 \n", + " 55-59 73.3 \n", + " 60-64 78.6 \n", + " 65-69 64.3 \n", + " 70-74 61.5 \n", + " 75-79 80.0 \n", + " 80-84 71.4 \n", + " 85-89 80.0 \n", + " 90+ 50.0 \n", "ethnicity_6_groups Black 66.7 \n", - " Mixed 56.5 \n", - " Other 63.2 \n", - " South Asian 63.2 \n", - " Unknown 66.7 \n", - " White 66.7 \n", + " Mixed 70.0 \n", + " Other 71.4 \n", + " South Asian 66.7 \n", + " Unknown 71.9 \n", + " White 73.0 \n", "brand_of_first_dose Oxford-AZ NaN \n", - " Unknown 70.2 \n", + " Pfizer NaN \n", + " Unknown 76.9 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", "overall overall 1.8 \n", - "sex F 1.7 \n", - " M 3.6 \n", + "sex F 1.8 \n", + " M 1.7 \n", "ageband_5yr 0 0.0 \n", " 0-15 0.0 \n", - " 16-17 14.3 \n", - " 18-29 0.0 \n", + " 16-17 0.0 \n", + " 18-29 6.6 \n", " 30-34 0.0 \n", - " 35-39 14.3 \n", + " 35-39 0.0 \n", " 40-44 0.0 \n", " 45-49 0.0 \n", - " 50-54 12.5 \n", - " 55-59 14.3 \n", - " 60-64 12.5 \n", + " 50-54 0.0 \n", + " 55-59 0.0 \n", + " 60-64 0.0 \n", " 65-69 0.0 \n", " 70-74 0.0 \n", " 75-79 0.0 \n", " 80-84 0.0 \n", " 85-89 0.0 \n", - " 90+ 0.0 \n", - "ethnicity_6_groups Black 5.5 \n", - " Mixed 0.0 \n", - " Other 5.2 \n", - " South Asian 0.0 \n", - " Unknown 5.5 \n", - " White 5.5 \n", + " 90+ 50.0 \n", + "ethnicity_6_groups Black 2.5 \n", + " Mixed 2.5 \n", + " Other 4.8 \n", + " South Asian 2.5 \n", + " Unknown 0.0 \n", + " White 2.7 \n", "brand_of_first_dose Oxford-AZ 0.0 \n", - " Unknown 2.9 \n", + " Pfizer 0.0 \n", + " Unknown 2.4 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 09-Dec \n", - "sex F 15-Dec \n", - " M 20-Oct \n", - "ageband_5yr 0 reached \n", + "overall overall 04-Jan \n", + "sex F 06-Jan \n", + " M 07-Jan \n", + "ageband_5yr 0 unknown \n", " 0-15 unknown \n", - " 16-17 17-Sep \n", - " 18-29 unknown \n", + " 16-17 unknown \n", + " 18-29 13-Nov \n", " 30-34 unknown \n", - " 35-39 10-Sep \n", + " 35-39 unknown \n", " 40-44 unknown \n", " 45-49 unknown \n", - " 50-54 16-Sep \n", - " 55-59 17-Sep \n", - " 60-64 16-Sep \n", + " 50-54 unknown \n", + " 55-59 unknown \n", + " 60-64 unknown \n", " 65-69 unknown \n", " 70-74 unknown \n", " 75-79 unknown \n", " 80-84 unknown \n", " 85-89 unknown \n", - " 90+ unknown \n", - "ethnicity_6_groups Black 30-Sep \n", - " Mixed unknown \n", - " Other 07-Oct \n", - " South Asian unknown \n", - " Unknown 30-Sep \n", - " White 30-Sep \n", + " 90+ reached \n", + "ethnicity_6_groups Black 24-Dec \n", + " Mixed 15-Dec \n", + " Other 16-Nov \n", + " South Asian 24-Dec \n", + " Unknown unknown \n", + " White 03-Dec \n", "brand_of_first_dose Oxford-AZ unknown \n", - " Unknown 18-Oct " + " Pfizer unknown \n", + " Unknown 27-Nov " ] }, "metadata": {}, @@ -28180,7 +28298,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **60-64** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **60-64** population up to 2021-10-27" ], "text/plain": [ "" @@ -28246,526 +28364,526 @@ " \n", " overall\n", " overall\n", - " 1750\n", - " 65.4\n", - " 2674\n", - " 63.6\n", - " 1.8\n", - " 12-Dec\n", + " 3752\n", + " 68.8\n", + " 5453\n", + " 67.1\n", + " 1.7\n", + " 22-Jan\n", " \n", " \n", " sex\n", " F\n", - " 861\n", - " 64.7\n", - " 1330\n", - " 63.2\n", - " 1.5\n", - " 04-Jan\n", + " 1918\n", + " 68.3\n", + " 2807\n", + " 66.6\n", + " 1.7\n", + " 24-Jan\n", " \n", " \n", " M\n", - " 889\n", - " 66.1\n", - " 1344\n", - " 64.6\n", - " 1.5\n", - " 28-Dec\n", + " 1827\n", + " 69.0\n", + " 2646\n", + " 67.7\n", + " 1.3\n", + " 17-Feb\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 308\n", - " 65.7\n", - " 469\n", - " 65.7\n", - " 0.0\n", - " unknown\n", + " 665\n", + " 69.3\n", + " 959\n", + " 67.2\n", + " 2.1\n", + " 04-Jan\n", " \n", " \n", " Mixed\n", - " 315\n", - " 68.2\n", - " 462\n", - " 65.2\n", - " 3.0\n", - " 28-Oct\n", + " 658\n", + " 69.6\n", + " 945\n", + " 68.9\n", + " 0.7\n", + " unknown\n", " \n", " \n", " Other\n", - " 294\n", - " 65.6\n", - " 448\n", - " 64.1\n", - " 1.5\n", - " 30-Dec\n", + " 623\n", + " 70.6\n", + " 882\n", + " 68.3\n", + " 2.3\n", + " 25-Dec\n", " \n", " \n", " South Asian\n", - " 294\n", - " 64.6\n", - " 455\n", - " 63.1\n", - " 1.5\n", + " 616\n", + " 67.2\n", + " 917\n", + " 64.9\n", + " 2.3\n", " 04-Jan\n", " \n", " \n", " Unknown\n", - " 231\n", - " 63.5\n", - " 364\n", - " 61.5\n", - " 2.0\n", - " 09-Dec\n", + " 553\n", + " 67.5\n", + " 819\n", + " 65.8\n", + " 1.7\n", + " 27-Jan\n", " \n", " \n", " White\n", - " 308\n", - " 65.7\n", - " 469\n", - " 64.2\n", - " 1.5\n", - " 30-Dec\n", + " 637\n", + " 67.9\n", + " 938\n", + " 67.2\n", + " 0.7\n", + " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 77\n", - " 64.7\n", - " 119\n", - " 58.8\n", - " 5.9\n", - " 08-Oct\n", + " 196\n", + " 70.0\n", + " 280\n", + " 67.5\n", + " 2.5\n", + " 22-Dec\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 105\n", - " 68.2\n", - " 154\n", - " 68.2\n", - " 0.0\n", - " unknown\n", + " 196\n", + " 65.1\n", + " 301\n", + " 62.8\n", + " 2.3\n", + " 10-Jan\n", " \n", " \n", " Caribbean\n", - " 91\n", - " 61.9\n", - " 147\n", - " 61.9\n", + " 217\n", + " 72.1\n", + " 301\n", + " 72.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Chinese\n", - " 98\n", - " 63.6\n", - " 154\n", - " 63.6\n", + " 196\n", + " 65.1\n", + " 301\n", + " 65.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 105\n", - " 68.2\n", - " 154\n", - " 68.2\n", - " 0.0\n", - " unknown\n", + " 189\n", + " 62.8\n", + " 301\n", + " 60.5\n", + " 2.3\n", + " 17-Jan\n", " \n", " \n", " Other Asian\n", - " 84\n", - " 66.7\n", - " 126\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 217\n", + " 72.1\n", + " 301\n", + " 69.8\n", + " 2.3\n", + " 20-Dec\n", " \n", " \n", " British or Mixed British\n", - " 91\n", - " 61.9\n", - " 147\n", - " 57.1\n", - " 4.8\n", - " 18-Oct\n", + " 168\n", + " 64.9\n", + " 259\n", + " 64.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 84\n", - " 63.2\n", - " 133\n", - " 63.2\n", + " 196\n", + " 71.8\n", + " 273\n", + " 71.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 98\n", - " 63.6\n", - " 154\n", - " 63.6\n", - " 0.0\n", - " unknown\n", + " 182\n", + " 65.0\n", + " 280\n", + " 62.5\n", + " 2.5\n", + " 05-Jan\n", " \n", " \n", " Other Black\n", - " 91\n", - " 72.2\n", - " 126\n", - " 66.7\n", - " 5.5\n", - " 30-Sep\n", + " 196\n", + " 68.3\n", + " 287\n", + " 65.9\n", + " 2.4\n", + " 29-Dec\n", " \n", " \n", " Other White\n", - " 98\n", - " 60.9\n", - " 161\n", - " 60.9\n", + " 189\n", + " 69.2\n", + " 273\n", + " 69.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 98\n", - " 66.7\n", - " 147\n", - " 66.7\n", + " 189\n", + " 71.1\n", + " 266\n", + " 71.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 98\n", - " 66.7\n", - " 147\n", - " 61.9\n", - " 4.8\n", - " 11-Oct\n", + " 224\n", + " 74.4\n", + " 301\n", + " 72.1\n", + " 2.3\n", + " 13-Dec\n", " \n", " \n", " Unknown\n", - " 273\n", - " 67.2\n", - " 406\n", - " 65.5\n", + " 553\n", + " 66.4\n", + " 833\n", + " 64.7\n", " 1.7\n", - " 10-Dec\n", + " 01-Feb\n", " \n", " \n", " White + Asian\n", - " 77\n", - " 57.9\n", - " 133\n", - " 57.9\n", - " 0.0\n", - " unknown\n", + " 203\n", + " 70.7\n", + " 287\n", + " 68.3\n", + " 2.4\n", + " 22-Dec\n", " \n", " \n", " White + Black African\n", - " 84\n", - " 63.2\n", - " 133\n", - " 63.2\n", - " 0.0\n", - " unknown\n", + " 217\n", + " 72.1\n", + " 301\n", + " 69.8\n", + " 2.3\n", + " 20-Dec\n", " \n", " \n", " White + Black Caribbean\n", - " 84\n", - " 66.7\n", - " 126\n", + " 210\n", " 66.7\n", - " 0.0\n", - " unknown\n", + " 315\n", + " 64.4\n", + " 2.3\n", + " 05-Jan\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 329\n", - " 65.3\n", - " 504\n", - " 63.9\n", - " 1.4\n", - " 09-Jan\n", + " 679\n", + " 66.9\n", + " 1015\n", + " 66.2\n", + " 0.7\n", + " unknown\n", " \n", " \n", " 2\n", - " 343\n", - " 62.8\n", - " 546\n", - " 61.5\n", - " 1.3\n", - " 01-Feb\n", + " 721\n", + " 69.6\n", + " 1036\n", + " 67.6\n", + " 2.0\n", + " 06-Jan\n", " \n", " \n", " 3\n", - " 322\n", - " 63.9\n", - " 504\n", - " 62.5\n", - " 1.4\n", - " 16-Jan\n", + " 749\n", + " 69.9\n", + " 1071\n", + " 68.0\n", + " 1.9\n", + " 09-Jan\n", " \n", " \n", " 4\n", - " 315\n", - " 65.2\n", - " 483\n", - " 62.3\n", - " 2.9\n", - " 06-Nov\n", + " 679\n", + " 67.8\n", + " 1001\n", + " 66.4\n", + " 1.4\n", + " 15-Feb\n", " \n", " \n", " 5 Least deprived\n", - " 343\n", - " 68.1\n", - " 504\n", - " 65.3\n", - " 2.8\n", - " 01-Nov\n", + " 721\n", + " 68.2\n", + " 1057\n", + " 66.9\n", + " 1.3\n", + " 21-Feb\n", " \n", " \n", " Unknown\n", - " 98\n", - " 73.7\n", - " 133\n", - " 68.4\n", - " 5.3\n", - " 29-Sep\n", + " 196\n", + " 70.0\n", + " 280\n", + " 67.5\n", + " 2.5\n", + " 22-Dec\n", " \n", " \n", " bmi\n", " 30+\n", - " 525\n", - " 63.6\n", - " 826\n", - " 61.9\n", - " 1.7\n", - " 25-Dec\n", + " 1120\n", + " 69.0\n", + " 1624\n", + " 67.2\n", + " 1.8\n", + " 16-Jan\n", " \n", " \n", " under 30\n", - " 1218\n", - " 65.9\n", - " 1848\n", - " 64.4\n", + " 2625\n", + " 68.6\n", + " 3829\n", + " 67.1\n", " 1.5\n", - " 29-Dec\n", + " 03-Feb\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1729\n", - " 65.5\n", - " 2639\n", - " 63.7\n", - " 1.8\n", - " 12-Dec\n", + " 3717\n", + " 68.7\n", + " 5411\n", + " 67.1\n", + " 1.6\n", + " 28-Jan\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 28\n", + " 66.7\n", + " 42\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1729\n", - " 65.2\n", - " 2653\n", - " 63.6\n", - " 1.6\n", - " 25-Dec\n", + " 3717\n", + " 68.9\n", + " 5397\n", + " 67.2\n", + " 1.7\n", + " 21-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 62.5\n", + " 56\n", + " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1736\n", - " 65.4\n", - " 2653\n", - " 63.6\n", - " 1.8\n", - " 12-Dec\n", + " 3710\n", + " 68.7\n", + " 5397\n", + " 67.1\n", + " 1.6\n", + " 28-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 42\n", + " 75.0\n", + " 56\n", + " 75.0\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 1729\n", - " 65.3\n", - " 2646\n", - " 63.8\n", - " 1.5\n", - " 01-Jan\n", + " 3703\n", + " 68.9\n", + " 5376\n", + " 67.3\n", + " 1.6\n", + " 27-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 49\n", + " 63.6\n", + " 77\n", + " 63.6\n", " 0.0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1729\n", - " 65.3\n", - " 2646\n", - " 63.8\n", - " 1.5\n", - " 01-Jan\n", + " 3710\n", + " 68.7\n", + " 5404\n", + " 67.1\n", + " 1.6\n", + " 28-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 35\n", + " 71.4\n", + " 49\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1729\n", - " 65.3\n", - " 2646\n", - " 63.8\n", - " 1.5\n", - " 01-Jan\n", + " 3717\n", + " 68.8\n", + " 5404\n", + " 67.2\n", + " 1.6\n", + " 27-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 35\n", + " 71.4\n", + " 49\n", + " 57.1\n", + " 14.3\n", + " 05-Nov\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 1729\n", - " 65.3\n", - " 2646\n", - " 63.8\n", + " 3703\n", + " 68.6\n", + " 5397\n", + " 67.1\n", " 1.5\n", - " 01-Jan\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 40.0\n", - " 20.0\n", - " 18-Sep\n", + " 49\n", + " 77.8\n", + " 63\n", + " 77.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1736\n", - " 65.4\n", - " 2653\n", - " 63.6\n", - " 1.8\n", - " 12-Dec\n", + " 3717\n", + " 68.7\n", + " 5411\n", + " 67.0\n", + " 1.7\n", + " 22-Jan\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 71.4\n", + " 49\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1736\n", - " 65.4\n", - " 2653\n", - " 63.9\n", + " 3710\n", + " 68.7\n", + " 5397\n", + " 67.2\n", " 1.5\n", - " 31-Dec\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 62.5\n", + " 56\n", + " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1722\n", - " 65.1\n", - " 2646\n", - " 63.5\n", - " 1.6\n", - " 25-Dec\n", + " 3710\n", + " 68.7\n", + " 5404\n", + " 67.2\n", + " 1.5\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", " 35\n", - " 60.0\n", + " 71.4\n", + " 49\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1386\n", - " 65.6\n", - " 2114\n", - " 63.9\n", - " 1.7\n", - " 17-Dec\n", + " 3024\n", + " 68.7\n", + " 4403\n", + " 67.1\n", + " 1.6\n", + " 28-Jan\n", " \n", " \n", " yes\n", - " 357\n", - " 63.7\n", - " 560\n", - " 62.5\n", - " 1.2\n", - " 08-Feb\n", + " 721\n", + " 68.2\n", + " 1057\n", + " 66.9\n", + " 1.3\n", + " 21-Feb\n", " \n", " \n", - " brand_of_first_dose\n", + " brand_of_first_dose\n", " Moderna\n", " 0\n", " 0.0\n", @@ -28775,6 +28893,15 @@ " unknown\n", " \n", " \n", + " Oxford-AZ\n", + " 0\n", + " 0.0\n", + " 0\n", + " NaN\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", " Pfizer\n", " 0\n", " 0.0\n", @@ -28785,12 +28912,12 @@ " \n", " \n", " Unknown\n", - " 1743\n", - " 72.8\n", - " 2394\n", - " 71.1\n", + " 3738\n", + " 76.1\n", + " 4914\n", + " 74.4\n", " 1.7\n", - " 17-Nov\n", + " 23-Dec\n", " \n", " \n", "\n", @@ -28799,313 +28926,318 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1750 \n", - "sex F 861 \n", - " M 889 \n", - "ethnicity_6_groups Black 308 \n", - " Mixed 315 \n", - " Other 294 \n", - " South Asian 294 \n", - " Unknown 231 \n", - " White 308 \n", - "ethnicity_16_groups African 77 \n", - " Bangladeshi or British Bangladeshi 105 \n", - " Caribbean 91 \n", - " Chinese 98 \n", - " Other 105 \n", - " Other Asian 84 \n", - " British or Mixed British 91 \n", - " Indian or British Indian 84 \n", - " Irish 98 \n", - " Other Black 91 \n", - " Other White 98 \n", - " Other mixed 98 \n", - " Pakistani or British Pakistani 98 \n", - " Unknown 273 \n", - " White + Asian 77 \n", - " White + Black African 84 \n", - " White + Black Caribbean 84 \n", - "imd_categories 1 Most deprived 329 \n", - " 2 343 \n", - " 3 322 \n", - " 4 315 \n", - " 5 Least deprived 343 \n", - " Unknown 98 \n", - "bmi 30+ 525 \n", - " under 30 1218 \n", - "chronic_cardiac_disease no 1729 \n", - " yes 21 \n", - "current_copd no 1729 \n", - " yes 14 \n", - "dmards no 1736 \n", - " yes 14 \n", - "dementia no 1729 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1729 \n", - " yes 14 \n", - "ssri no 1729 \n", - " yes 14 \n", - "chemo_or_radio no 1729 \n", - " yes 21 \n", - "lung_cancer no 1736 \n", - " yes 14 \n", - "cancer_excl_lung_and_haem no 1736 \n", - " yes 14 \n", - "haematological_cancer no 1722 \n", - " yes 21 \n", - "ckd no 1386 \n", - " yes 357 \n", + "overall overall 3752 \n", + "sex F 1918 \n", + " M 1827 \n", + "ethnicity_6_groups Black 665 \n", + " Mixed 658 \n", + " Other 623 \n", + " South Asian 616 \n", + " Unknown 553 \n", + " White 637 \n", + "ethnicity_16_groups African 196 \n", + " Bangladeshi or British Bangladeshi 196 \n", + " Caribbean 217 \n", + " Chinese 196 \n", + " Other 189 \n", + " Other Asian 217 \n", + " British or Mixed British 168 \n", + " Indian or British Indian 196 \n", + " Irish 182 \n", + " Other Black 196 \n", + " Other White 189 \n", + " Other mixed 189 \n", + " Pakistani or British Pakistani 224 \n", + " Unknown 553 \n", + " White + Asian 203 \n", + " White + Black African 217 \n", + " White + Black Caribbean 210 \n", + "imd_categories 1 Most deprived 679 \n", + " 2 721 \n", + " 3 749 \n", + " 4 679 \n", + " 5 Least deprived 721 \n", + " Unknown 196 \n", + "bmi 30+ 1120 \n", + " under 30 2625 \n", + "chronic_cardiac_disease no 3717 \n", + " yes 28 \n", + "current_copd no 3717 \n", + " yes 35 \n", + "dmards no 3710 \n", + " yes 42 \n", + "dementia no 3703 \n", + " yes 49 \n", + "psychosis_schiz_bipolar no 3710 \n", + " yes 35 \n", + "ssri no 3717 \n", + " yes 35 \n", + "chemo_or_radio no 3703 \n", + " yes 49 \n", + "lung_cancer no 3717 \n", + " yes 35 \n", + "cancer_excl_lung_and_haem no 3710 \n", + " yes 35 \n", + "haematological_cancer no 3710 \n", + " yes 35 \n", + "ckd no 3024 \n", + " yes 721 \n", "brand_of_first_dose Moderna 0 \n", + " Oxford-AZ 0 \n", " Pfizer 0 \n", - " Unknown 1743 \n", + " Unknown 3738 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 65.4 2674 \n", - "sex F 64.7 1330 \n", - " M 66.1 1344 \n", - "ethnicity_6_groups Black 65.7 469 \n", - " Mixed 68.2 462 \n", - " Other 65.6 448 \n", - " South Asian 64.6 455 \n", - " Unknown 63.5 364 \n", - " White 65.7 469 \n", - "ethnicity_16_groups African 64.7 119 \n", - " Bangladeshi or British Bangladeshi 68.2 154 \n", - " Caribbean 61.9 147 \n", - " Chinese 63.6 154 \n", - " Other 68.2 154 \n", - " Other Asian 66.7 126 \n", - " British or Mixed British 61.9 147 \n", - " Indian or British Indian 63.2 133 \n", - " Irish 63.6 154 \n", - " Other Black 72.2 126 \n", - " Other White 60.9 161 \n", - " Other mixed 66.7 147 \n", - " Pakistani or British Pakistani 66.7 147 \n", - " Unknown 67.2 406 \n", - " White + Asian 57.9 133 \n", - " White + Black African 63.2 133 \n", - " White + Black Caribbean 66.7 126 \n", - "imd_categories 1 Most deprived 65.3 504 \n", - " 2 62.8 546 \n", - " 3 63.9 504 \n", - " 4 65.2 483 \n", - " 5 Least deprived 68.1 504 \n", - " Unknown 73.7 133 \n", - "bmi 30+ 63.6 826 \n", - " under 30 65.9 1848 \n", - "chronic_cardiac_disease no 65.5 2639 \n", - " yes 60.0 35 \n", - "current_copd no 65.2 2653 \n", - " yes 66.7 21 \n", - "dmards no 65.4 2653 \n", - " yes 66.7 21 \n", - "dementia no 65.3 2646 \n", - " yes 50.0 28 \n", - "psychosis_schiz_bipolar no 65.3 2646 \n", - " yes 50.0 28 \n", - "ssri no 65.3 2646 \n", - " yes 50.0 28 \n", - "chemo_or_radio no 65.3 2646 \n", - " yes 60.0 35 \n", - "lung_cancer no 65.4 2653 \n", - " yes 66.7 21 \n", - "cancer_excl_lung_and_haem no 65.4 2653 \n", - " yes 66.7 21 \n", - "haematological_cancer no 65.1 2646 \n", - " yes 60.0 35 \n", - "ckd no 65.6 2114 \n", - " yes 63.7 560 \n", + "overall overall 68.8 5453 \n", + "sex F 68.3 2807 \n", + " M 69.0 2646 \n", + "ethnicity_6_groups Black 69.3 959 \n", + " Mixed 69.6 945 \n", + " Other 70.6 882 \n", + " South Asian 67.2 917 \n", + " Unknown 67.5 819 \n", + " White 67.9 938 \n", + "ethnicity_16_groups African 70.0 280 \n", + " Bangladeshi or British Bangladeshi 65.1 301 \n", + " Caribbean 72.1 301 \n", + " Chinese 65.1 301 \n", + " Other 62.8 301 \n", + " Other Asian 72.1 301 \n", + " British or Mixed British 64.9 259 \n", + " Indian or British Indian 71.8 273 \n", + " Irish 65.0 280 \n", + " Other Black 68.3 287 \n", + " Other White 69.2 273 \n", + " Other mixed 71.1 266 \n", + " Pakistani or British Pakistani 74.4 301 \n", + " Unknown 66.4 833 \n", + " White + Asian 70.7 287 \n", + " White + Black African 72.1 301 \n", + " White + Black Caribbean 66.7 315 \n", + "imd_categories 1 Most deprived 66.9 1015 \n", + " 2 69.6 1036 \n", + " 3 69.9 1071 \n", + " 4 67.8 1001 \n", + " 5 Least deprived 68.2 1057 \n", + " Unknown 70.0 280 \n", + "bmi 30+ 69.0 1624 \n", + " under 30 68.6 3829 \n", + "chronic_cardiac_disease no 68.7 5411 \n", + " yes 66.7 42 \n", + "current_copd no 68.9 5397 \n", + " yes 62.5 56 \n", + "dmards no 68.7 5397 \n", + " yes 75.0 56 \n", + "dementia no 68.9 5376 \n", + " yes 63.6 77 \n", + "psychosis_schiz_bipolar no 68.7 5404 \n", + " yes 71.4 49 \n", + "ssri no 68.8 5404 \n", + " yes 71.4 49 \n", + "chemo_or_radio no 68.6 5397 \n", + " yes 77.8 63 \n", + "lung_cancer no 68.7 5411 \n", + " yes 71.4 49 \n", + "cancer_excl_lung_and_haem no 68.7 5397 \n", + " yes 62.5 56 \n", + "haematological_cancer no 68.7 5404 \n", + " yes 71.4 49 \n", + "ckd no 68.7 4403 \n", + " yes 68.2 1057 \n", "brand_of_first_dose Moderna 0.0 0 \n", + " Oxford-AZ 0.0 0 \n", " Pfizer 0.0 0 \n", - " Unknown 72.8 2394 \n", + " Unknown 76.1 4914 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 63.6 \n", - "sex F 63.2 \n", - " M 64.6 \n", - "ethnicity_6_groups Black 65.7 \n", - " Mixed 65.2 \n", - " Other 64.1 \n", - " South Asian 63.1 \n", - " Unknown 61.5 \n", - " White 64.2 \n", - "ethnicity_16_groups African 58.8 \n", - " Bangladeshi or British Bangladeshi 68.2 \n", - " Caribbean 61.9 \n", - " Chinese 63.6 \n", - " Other 68.2 \n", - " Other Asian 66.7 \n", - " British or Mixed British 57.1 \n", - " Indian or British Indian 63.2 \n", - " Irish 63.6 \n", - " Other Black 66.7 \n", - " Other White 60.9 \n", - " Other mixed 66.7 \n", - " Pakistani or British Pakistani 61.9 \n", - " Unknown 65.5 \n", - " White + Asian 57.9 \n", - " White + Black African 63.2 \n", - " White + Black Caribbean 66.7 \n", - "imd_categories 1 Most deprived 63.9 \n", - " 2 61.5 \n", - " 3 62.5 \n", - " 4 62.3 \n", - " 5 Least deprived 65.3 \n", - " Unknown 68.4 \n", - "bmi 30+ 61.9 \n", - " under 30 64.4 \n", - "chronic_cardiac_disease no 63.7 \n", - " yes 60.0 \n", - "current_copd no 63.6 \n", - " yes 66.7 \n", - "dmards no 63.6 \n", - " yes 66.7 \n", - "dementia no 63.8 \n", - " yes 50.0 \n", - "psychosis_schiz_bipolar no 63.8 \n", - " yes 50.0 \n", - "ssri no 63.8 \n", - " yes 50.0 \n", - "chemo_or_radio no 63.8 \n", - " yes 40.0 \n", - "lung_cancer no 63.6 \n", - " yes 66.7 \n", - "cancer_excl_lung_and_haem no 63.9 \n", + "overall overall 67.1 \n", + "sex F 66.6 \n", + " M 67.7 \n", + "ethnicity_6_groups Black 67.2 \n", + " Mixed 68.9 \n", + " Other 68.3 \n", + " South Asian 64.9 \n", + " Unknown 65.8 \n", + " White 67.2 \n", + "ethnicity_16_groups African 67.5 \n", + " Bangladeshi or British Bangladeshi 62.8 \n", + " Caribbean 72.1 \n", + " Chinese 65.1 \n", + " Other 60.5 \n", + " Other Asian 69.8 \n", + " British or Mixed British 64.9 \n", + " Indian or British Indian 71.8 \n", + " Irish 62.5 \n", + " Other Black 65.9 \n", + " Other White 69.2 \n", + " Other mixed 71.1 \n", + " Pakistani or British Pakistani 72.1 \n", + " Unknown 64.7 \n", + " White + Asian 68.3 \n", + " White + Black African 69.8 \n", + " White + Black Caribbean 64.4 \n", + "imd_categories 1 Most deprived 66.2 \n", + " 2 67.6 \n", + " 3 68.0 \n", + " 4 66.4 \n", + " 5 Least deprived 66.9 \n", + " Unknown 67.5 \n", + "bmi 30+ 67.2 \n", + " under 30 67.1 \n", + "chronic_cardiac_disease no 67.1 \n", " yes 66.7 \n", - "haematological_cancer no 63.5 \n", - " yes 60.0 \n", - "ckd no 63.9 \n", + "current_copd no 67.2 \n", + " yes 62.5 \n", + "dmards no 67.1 \n", + " yes 75.0 \n", + "dementia no 67.3 \n", + " yes 63.6 \n", + "psychosis_schiz_bipolar no 67.1 \n", + " yes 71.4 \n", + "ssri no 67.2 \n", + " yes 57.1 \n", + "chemo_or_radio no 67.1 \n", + " yes 77.8 \n", + "lung_cancer no 67.0 \n", + " yes 71.4 \n", + "cancer_excl_lung_and_haem no 67.2 \n", " yes 62.5 \n", + "haematological_cancer no 67.2 \n", + " yes 71.4 \n", + "ckd no 67.1 \n", + " yes 66.9 \n", "brand_of_first_dose Moderna NaN \n", + " Oxford-AZ NaN \n", " Pfizer NaN \n", - " Unknown 71.1 \n", + " Unknown 74.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.8 \n", - "sex F 1.5 \n", - " M 1.5 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 3.0 \n", - " Other 1.5 \n", - " South Asian 1.5 \n", - " Unknown 2.0 \n", - " White 1.5 \n", - "ethnicity_16_groups African 5.9 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", + "overall overall 1.7 \n", + "sex F 1.7 \n", + " M 1.3 \n", + "ethnicity_6_groups Black 2.1 \n", + " Mixed 0.7 \n", + " Other 2.3 \n", + " South Asian 2.3 \n", + " Unknown 1.7 \n", + " White 0.7 \n", + "ethnicity_16_groups African 2.5 \n", + " Bangladeshi or British Bangladeshi 2.3 \n", " Caribbean 0.0 \n", " Chinese 0.0 \n", - " Other 0.0 \n", - " Other Asian 0.0 \n", - " British or Mixed British 4.8 \n", + " Other 2.3 \n", + " Other Asian 2.3 \n", + " British or Mixed British 0.0 \n", " Indian or British Indian 0.0 \n", - " Irish 0.0 \n", - " Other Black 5.5 \n", + " Irish 2.5 \n", + " Other Black 2.4 \n", " Other White 0.0 \n", " Other mixed 0.0 \n", - " Pakistani or British Pakistani 4.8 \n", + " Pakistani or British Pakistani 2.3 \n", " Unknown 1.7 \n", - " White + Asian 0.0 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 1.4 \n", - " 2 1.3 \n", - " 3 1.4 \n", - " 4 2.9 \n", - " 5 Least deprived 2.8 \n", - " Unknown 5.3 \n", - "bmi 30+ 1.7 \n", + " White + Asian 2.4 \n", + " White + Black African 2.3 \n", + " White + Black Caribbean 2.3 \n", + "imd_categories 1 Most deprived 0.7 \n", + " 2 2.0 \n", + " 3 1.9 \n", + " 4 1.4 \n", + " 5 Least deprived 1.3 \n", + " Unknown 2.5 \n", + "bmi 30+ 1.8 \n", " under 30 1.5 \n", - "chronic_cardiac_disease no 1.8 \n", - " yes 0.0 \n", - "current_copd no 1.6 \n", + "chronic_cardiac_disease no 1.6 \n", " yes 0.0 \n", - "dmards no 1.8 \n", + "current_copd no 1.7 \n", " yes 0.0 \n", - "dementia no 1.5 \n", + "dmards no 1.6 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.5 \n", + "dementia no 1.6 \n", " yes 0.0 \n", - "ssri no 1.5 \n", + "psychosis_schiz_bipolar no 1.6 \n", " yes 0.0 \n", + "ssri no 1.6 \n", + " yes 14.3 \n", "chemo_or_radio no 1.5 \n", - " yes 20.0 \n", - "lung_cancer no 1.8 \n", + " yes 0.0 \n", + "lung_cancer no 1.7 \n", " yes 0.0 \n", "cancer_excl_lung_and_haem no 1.5 \n", " yes 0.0 \n", - "haematological_cancer no 1.6 \n", + "haematological_cancer no 1.5 \n", " yes 0.0 \n", - "ckd no 1.7 \n", - " yes 1.2 \n", + "ckd no 1.6 \n", + " yes 1.3 \n", "brand_of_first_dose Moderna 0.0 \n", + " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", " Unknown 1.7 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 12-Dec \n", - "sex F 04-Jan \n", - " M 28-Dec \n", - "ethnicity_6_groups Black unknown \n", - " Mixed 28-Oct \n", - " Other 30-Dec \n", + "overall overall 22-Jan \n", + "sex F 24-Jan \n", + " M 17-Feb \n", + "ethnicity_6_groups Black 04-Jan \n", + " Mixed unknown \n", + " Other 25-Dec \n", " South Asian 04-Jan \n", - " Unknown 09-Dec \n", - " White 30-Dec \n", - "ethnicity_16_groups African 08-Oct \n", - " Bangladeshi or British Bangladeshi unknown \n", + " Unknown 27-Jan \n", + " White unknown \n", + "ethnicity_16_groups African 22-Dec \n", + " Bangladeshi or British Bangladeshi 10-Jan \n", " Caribbean unknown \n", " Chinese unknown \n", - " Other unknown \n", - " Other Asian unknown \n", - " British or Mixed British 18-Oct \n", + " Other 17-Jan \n", + " Other Asian 20-Dec \n", + " British or Mixed British unknown \n", " Indian or British Indian unknown \n", - " Irish unknown \n", - " Other Black 30-Sep \n", + " Irish 05-Jan \n", + " Other Black 29-Dec \n", " Other White unknown \n", " Other mixed unknown \n", - " Pakistani or British Pakistani 11-Oct \n", - " Unknown 10-Dec \n", - " White + Asian unknown \n", - " White + Black African unknown \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived 09-Jan \n", - " 2 01-Feb \n", - " 3 16-Jan \n", - " 4 06-Nov \n", - " 5 Least deprived 01-Nov \n", - " Unknown 29-Sep \n", - "bmi 30+ 25-Dec \n", - " under 30 29-Dec \n", - "chronic_cardiac_disease no 12-Dec \n", + " Pakistani or British Pakistani 13-Dec \n", + " Unknown 01-Feb \n", + " White + Asian 22-Dec \n", + " White + Black African 20-Dec \n", + " White + Black Caribbean 05-Jan \n", + "imd_categories 1 Most deprived unknown \n", + " 2 06-Jan \n", + " 3 09-Jan \n", + " 4 15-Feb \n", + " 5 Least deprived 21-Feb \n", + " Unknown 22-Dec \n", + "bmi 30+ 16-Jan \n", + " under 30 03-Feb \n", + "chronic_cardiac_disease no 28-Jan \n", " yes unknown \n", - "current_copd no 25-Dec \n", + "current_copd no 21-Jan \n", " yes unknown \n", - "dmards no 12-Dec \n", + "dmards no 28-Jan \n", " yes unknown \n", - "dementia no 01-Jan \n", + "dementia no 27-Jan \n", " yes unknown \n", - "psychosis_schiz_bipolar no 01-Jan \n", + "psychosis_schiz_bipolar no 28-Jan \n", " yes unknown \n", - "ssri no 01-Jan \n", + "ssri no 27-Jan \n", + " yes 05-Nov \n", + "chemo_or_radio no 03-Feb \n", " yes unknown \n", - "chemo_or_radio no 01-Jan \n", - " yes 18-Sep \n", - "lung_cancer no 12-Dec \n", + "lung_cancer no 22-Jan \n", " yes unknown \n", - "cancer_excl_lung_and_haem no 31-Dec \n", + "cancer_excl_lung_and_haem no 03-Feb \n", " yes unknown \n", - "haematological_cancer no 25-Dec \n", + "haematological_cancer no 03-Feb \n", " yes unknown \n", - "ckd no 17-Dec \n", - " yes 08-Feb \n", + "ckd no 28-Jan \n", + " yes 21-Feb \n", "brand_of_first_dose Moderna unknown \n", + " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 17-Nov " + " Unknown 23-Dec " ] }, "metadata": {}, @@ -29134,7 +29266,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **55-59** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **55-59** population up to 2021-10-27" ], "text/plain": [ "" @@ -29200,440 +29332,431 @@ " \n", " overall\n", " overall\n", - " 2121\n", - " 66.6\n", - " 3185\n", - " 65.1\n", - " 1.5\n", - " 26-Dec\n", + " 4333\n", + " 69.6\n", + " 6223\n", + " 68.4\n", + " 1.2\n", + " 23-Feb\n", " \n", " \n", " sex\n", " F\n", - " 1113\n", - " 68.5\n", - " 1624\n", - " 66.8\n", - " 1.7\n", - " 05-Dec\n", + " 2240\n", + " 69.9\n", + " 3206\n", + " 68.6\n", + " 1.3\n", + " 12-Feb\n", " \n", " \n", " M\n", - " 1008\n", - " 64.6\n", - " 1561\n", - " 63.2\n", + " 2100\n", + " 69.6\n", + " 3017\n", + " 68.2\n", " 1.4\n", - " 13-Jan\n", + " 06-Feb\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 385\n", - " 67.1\n", - " 574\n", - " 65.9\n", - " 1.2\n", - " 19-Jan\n", + " 735\n", + " 70.9\n", + " 1036\n", + " 70.3\n", + " 0.6\n", + " unknown\n", " \n", " \n", " Mixed\n", - " 385\n", - " 67.1\n", - " 574\n", - " 65.9\n", - " 1.2\n", - " 19-Jan\n", + " 707\n", + " 66.4\n", + " 1064\n", + " 65.1\n", + " 1.3\n", + " 03-Mar\n", " \n", " \n", " Other\n", - " 329\n", - " 63.5\n", - " 518\n", - " 62.2\n", + " 784\n", + " 72.3\n", + " 1085\n", + " 71.0\n", " 1.3\n", - " 28-Jan\n", + " 30-Jan\n", " \n", " \n", " South Asian\n", - " 357\n", - " 66.2\n", - " 539\n", - " 63.6\n", - " 2.6\n", - " 11-Nov\n", + " 721\n", + " 70.5\n", + " 1022\n", + " 68.5\n", + " 2.0\n", + " 03-Jan\n", " \n", " \n", " Unknown\n", - " 287\n", - " 68.3\n", - " 420\n", - " 66.7\n", - " 1.6\n", - " 11-Dec\n", + " 651\n", + " 68.4\n", + " 952\n", + " 67.6\n", + " 0.8\n", + " unknown\n", " \n", " \n", " White\n", - " 385\n", - " 69.6\n", - " 553\n", - " 68.4\n", - " 1.2\n", - " 05-Jan\n", + " 742\n", + " 69.3\n", + " 1071\n", + " 68.0\n", + " 1.3\n", + " 15-Feb\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 126\n", - " 72.0\n", - " 175\n", - " 72.0\n", + " 217\n", + " 67.4\n", + " 322\n", + " 67.4\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 112\n", - " 66.7\n", - " 168\n", - " 62.5\n", - " 4.2\n", - " 16-Oct\n", + " 224\n", + " 74.4\n", + " 301\n", + " 72.1\n", + " 2.3\n", + " 13-Dec\n", " \n", " \n", " Caribbean\n", - " 112\n", - " 69.6\n", - " 161\n", - " 69.6\n", + " 231\n", + " 70.2\n", + " 329\n", + " 70.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Chinese\n", - " 112\n", - " 61.5\n", - " 182\n", - " 57.7\n", - " 3.8\n", - " 30-Oct\n", + " 189\n", + " 64.3\n", + " 294\n", + " 64.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other\n", - " 98\n", - " 66.7\n", - " 147\n", - " 66.7\n", + " 231\n", + " 70.2\n", + " 329\n", + " 70.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 98\n", - " 60.9\n", - " 161\n", - " 60.9\n", - " 0.0\n", - " unknown\n", + " 217\n", + " 70.5\n", + " 308\n", + " 68.2\n", + " 2.3\n", + " 25-Dec\n", " \n", " \n", " British or Mixed British\n", - " 119\n", - " 73.9\n", - " 161\n", - " 73.9\n", - " 0.0\n", - " unknown\n", + " 238\n", + " 70.8\n", + " 336\n", + " 68.8\n", + " 2.0\n", + " 02-Jan\n", " \n", " \n", " Indian or British Indian\n", - " 112\n", - " 66.7\n", - " 168\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 224\n", + " 69.6\n", + " 322\n", + " 67.4\n", + " 2.2\n", + " 30-Dec\n", " \n", " \n", " Irish\n", - " 112\n", - " 64.0\n", - " 175\n", - " 60.0\n", - " 4.0\n", - " 23-Oct\n", + " 231\n", + " 68.8\n", + " 336\n", + " 66.7\n", + " 2.1\n", + " 05-Jan\n", " \n", " \n", " Other Black\n", - " 105\n", - " 68.2\n", - " 154\n", - " 68.2\n", + " 245\n", + " 71.4\n", + " 343\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 98\n", - " 63.6\n", - " 154\n", - " 63.6\n", + " 231\n", + " 66.0\n", + " 350\n", + " 66.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 119\n", - " 65.4\n", - " 182\n", - " 61.5\n", - " 3.9\n", - " 22-Oct\n", + " 231\n", + " 75.0\n", + " 308\n", + " 72.7\n", + " 2.3\n", + " 11-Dec\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 133\n", - " 70.4\n", - " 189\n", - " 66.7\n", - " 3.7\n", - " 15-Oct\n", + " 259\n", + " 72.5\n", + " 357\n", + " 70.6\n", + " 1.9\n", + " 30-Dec\n", " \n", " \n", " Unknown\n", - " 308\n", - " 63.8\n", - " 483\n", - " 62.3\n", - " 1.5\n", - " 08-Jan\n", + " 644\n", + " 67.6\n", + " 952\n", + " 66.2\n", + " 1.4\n", + " 16-Feb\n", " \n", " \n", " White + Asian\n", - " 112\n", - " 66.7\n", - " 168\n", - " 66.7\n", + " 217\n", + " 64.6\n", + " 336\n", + " 64.6\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black African\n", - " 119\n", - " 73.9\n", - " 161\n", - " 73.9\n", + " 259\n", + " 68.5\n", + " 378\n", + " 68.5\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 112\n", - " 61.5\n", - " 182\n", - " 61.5\n", - " 0.0\n", - " unknown\n", + " 238\n", + " 72.3\n", + " 329\n", + " 70.2\n", + " 2.1\n", + " 25-Dec\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 413\n", - " 67.8\n", - " 609\n", - " 65.5\n", - " 2.3\n", - " 14-Nov\n", + " 847\n", + " 69.1\n", + " 1225\n", + " 68.0\n", + " 1.1\n", + " 09-Mar\n", " \n", " \n", " 2\n", - " 427\n", - " 66.3\n", - " 644\n", - " 64.1\n", - " 2.2\n", - " 22-Nov\n", + " 798\n", + " 69.9\n", + " 1141\n", + " 68.1\n", + " 1.8\n", + " 13-Jan\n", " \n", " \n", " 3\n", - " 385\n", - " 65.5\n", - " 588\n", - " 64.3\n", - " 1.2\n", - " 28-Jan\n", + " 854\n", + " 70.5\n", + " 1211\n", + " 69.4\n", + " 1.1\n", + " 28-Feb\n", " \n", " \n", " 4\n", - " 399\n", - " 66.3\n", - " 602\n", - " 65.1\n", + " 840\n", + " 71.0\n", + " 1183\n", + " 69.8\n", " 1.2\n", - " 24-Jan\n", + " 14-Feb\n", " \n", " \n", " 5 Least deprived\n", - " 378\n", - " 66.7\n", - " 567\n", - " 65.4\n", - " 1.3\n", - " 11-Jan\n", + " 777\n", + " 68.1\n", + " 1141\n", + " 66.9\n", + " 1.2\n", + " 03-Mar\n", " \n", " \n", " Unknown\n", - " 126\n", - " 72.0\n", - " 175\n", - " 68.0\n", - " 4.0\n", - " 09-Oct\n", + " 217\n", + " 67.4\n", + " 322\n", + " 65.2\n", + " 2.2\n", + " 06-Jan\n", " \n", " \n", " bmi\n", " 30+\n", - " 658\n", - " 68.6\n", - " 959\n", - " 67.2\n", - " 1.4\n", - " 24-Dec\n", + " 1274\n", + " 70.5\n", + " 1806\n", + " 69.8\n", + " 0.7\n", + " unknown\n", " \n", " \n", " under 30\n", - " 1463\n", - " 65.7\n", - " 2226\n", - " 64.2\n", + " 3059\n", + " 69.3\n", + " 4417\n", + " 67.8\n", " 1.5\n", - " 30-Dec\n", + " 31-Jan\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 2093\n", - " 66.6\n", - " 3143\n", - " 65.0\n", - " 1.6\n", - " 19-Dec\n", + " 4291\n", + " 69.7\n", + " 6153\n", + " 68.4\n", + " 1.3\n", + " 13-Feb\n", " \n", " \n", " yes\n", - " 28\n", - " 66.7\n", - " 42\n", - " 66.7\n", + " 49\n", + " 63.6\n", + " 77\n", + " 63.6\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 2100\n", - " 66.7\n", - " 3150\n", - " 65.1\n", - " 1.6\n", - " 18-Dec\n", + " 4305\n", + " 69.7\n", + " 6174\n", + " 68.5\n", + " 1.2\n", + " 22-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 28\n", + " 50.0\n", + " 56\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 2100\n", - " 66.7\n", - " 3150\n", - " 65.1\n", - " 1.6\n", - " 18-Dec\n", + " 4284\n", + " 69.5\n", + " 6160\n", + " 68.3\n", + " 1.2\n", + " 23-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 49\n", + " 70.0\n", + " 70\n", + " 70.0\n", " 0.0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 2100\n", - " 66.7\n", - " 3150\n", - " 65.1\n", - " 1.6\n", - " 18-Dec\n", + " 4291\n", + " 69.6\n", + " 6167\n", + " 68.3\n", + " 1.3\n", + " 13-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 40.0\n", - " 20.0\n", - " 18-Sep\n", + " 42\n", + " 66.7\n", + " 63\n", + " 66.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 2093\n", - " 66.6\n", - " 3143\n", - " 65.0\n", - " 1.6\n", - " 19-Dec\n", + " 4284\n", + " 69.5\n", + " 6160\n", + " 68.3\n", + " 1.2\n", + " 23-Feb\n", " \n", " \n", " yes\n", - " 28\n", - " 66.7\n", - " 42\n", - " 66.7\n", + " 49\n", + " 70.0\n", + " 70\n", + " 70.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1729\n", - " 66.6\n", - " 2597\n", - " 65.0\n", - " 1.6\n", - " 19-Dec\n", + " 3458\n", + " 70.0\n", + " 4942\n", + " 68.7\n", + " 1.3\n", + " 11-Feb\n", " \n", " \n", " yes\n", - " 392\n", - " 66.7\n", - " 588\n", - " 65.5\n", - " 1.2\n", - " 21-Jan\n", - " \n", - " \n", - " brand_of_first_dose\n", - " Moderna\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", - " 0.0\n", - " unknown\n", + " 875\n", + " 67.9\n", + " 1288\n", + " 66.8\n", + " 1.1\n", + " 16-Mar\n", " \n", " \n", + " brand_of_first_dose\n", " Oxford-AZ\n", " 0\n", " 0.0\n", @@ -29653,12 +29776,12 @@ " \n", " \n", " Unknown\n", - " 2114\n", - " 74.0\n", - " 2856\n", - " 72.3\n", - " 1.7\n", - " 12-Nov\n", + " 4326\n", + " 77.2\n", + " 5607\n", + " 75.8\n", + " 1.4\n", + " 30-Dec\n", " \n", " \n", "\n", @@ -29667,268 +29790,263 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 2121 \n", - "sex F 1113 \n", - " M 1008 \n", - "ethnicity_6_groups Black 385 \n", - " Mixed 385 \n", - " Other 329 \n", - " South Asian 357 \n", - " Unknown 287 \n", - " White 385 \n", - "ethnicity_16_groups African 126 \n", - " Bangladeshi or British Bangladeshi 112 \n", - " Caribbean 112 \n", - " Chinese 112 \n", - " Other 98 \n", - " Other Asian 98 \n", - " British or Mixed British 119 \n", - " Indian or British Indian 112 \n", - " Irish 112 \n", - " Other Black 105 \n", - " Other White 98 \n", - " Other mixed 119 \n", - " Pakistani or British Pakistani 133 \n", - " Unknown 308 \n", - " White + Asian 112 \n", - " White + Black African 119 \n", - " White + Black Caribbean 112 \n", - "imd_categories 1 Most deprived 413 \n", - " 2 427 \n", - " 3 385 \n", - " 4 399 \n", - " 5 Least deprived 378 \n", - " Unknown 126 \n", - "bmi 30+ 658 \n", - " under 30 1463 \n", - "chronic_cardiac_disease no 2093 \n", - " yes 28 \n", - "current_copd no 2100 \n", - " yes 21 \n", - "dmards no 2100 \n", - " yes 21 \n", - "psychosis_schiz_bipolar no 2100 \n", - " yes 21 \n", - "ssri no 2093 \n", + "overall overall 4333 \n", + "sex F 2240 \n", + " M 2100 \n", + "ethnicity_6_groups Black 735 \n", + " Mixed 707 \n", + " Other 784 \n", + " South Asian 721 \n", + " Unknown 651 \n", + " White 742 \n", + "ethnicity_16_groups African 217 \n", + " Bangladeshi or British Bangladeshi 224 \n", + " Caribbean 231 \n", + " Chinese 189 \n", + " Other 231 \n", + " Other Asian 217 \n", + " British or Mixed British 238 \n", + " Indian or British Indian 224 \n", + " Irish 231 \n", + " Other Black 245 \n", + " Other White 231 \n", + " Other mixed 231 \n", + " Pakistani or British Pakistani 259 \n", + " Unknown 644 \n", + " White + Asian 217 \n", + " White + Black African 259 \n", + " White + Black Caribbean 238 \n", + "imd_categories 1 Most deprived 847 \n", + " 2 798 \n", + " 3 854 \n", + " 4 840 \n", + " 5 Least deprived 777 \n", + " Unknown 217 \n", + "bmi 30+ 1274 \n", + " under 30 3059 \n", + "chronic_cardiac_disease no 4291 \n", + " yes 49 \n", + "current_copd no 4305 \n", " yes 28 \n", - "ckd no 1729 \n", - " yes 392 \n", - "brand_of_first_dose Moderna 0 \n", - " Oxford-AZ 0 \n", + "dmards no 4284 \n", + " yes 49 \n", + "psychosis_schiz_bipolar no 4291 \n", + " yes 42 \n", + "ssri no 4284 \n", + " yes 49 \n", + "ckd no 3458 \n", + " yes 875 \n", + "brand_of_first_dose Oxford-AZ 0 \n", " Pfizer 0 \n", - " Unknown 2114 \n", + " Unknown 4326 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 66.6 3185 \n", - "sex F 68.5 1624 \n", - " M 64.6 1561 \n", - "ethnicity_6_groups Black 67.1 574 \n", - " Mixed 67.1 574 \n", - " Other 63.5 518 \n", - " South Asian 66.2 539 \n", - " Unknown 68.3 420 \n", - " White 69.6 553 \n", - "ethnicity_16_groups African 72.0 175 \n", - " Bangladeshi or British Bangladeshi 66.7 168 \n", - " Caribbean 69.6 161 \n", - " Chinese 61.5 182 \n", - " Other 66.7 147 \n", - " Other Asian 60.9 161 \n", - " British or Mixed British 73.9 161 \n", - " Indian or British Indian 66.7 168 \n", - " Irish 64.0 175 \n", - " Other Black 68.2 154 \n", - " Other White 63.6 154 \n", - " Other mixed 65.4 182 \n", - " Pakistani or British Pakistani 70.4 189 \n", - " Unknown 63.8 483 \n", - " White + Asian 66.7 168 \n", - " White + Black African 73.9 161 \n", - " White + Black Caribbean 61.5 182 \n", - "imd_categories 1 Most deprived 67.8 609 \n", - " 2 66.3 644 \n", - " 3 65.5 588 \n", - " 4 66.3 602 \n", - " 5 Least deprived 66.7 567 \n", - " Unknown 72.0 175 \n", - "bmi 30+ 68.6 959 \n", - " under 30 65.7 2226 \n", - "chronic_cardiac_disease no 66.6 3143 \n", - " yes 66.7 42 \n", - "current_copd no 66.7 3150 \n", - " yes 60.0 35 \n", - "dmards no 66.7 3150 \n", - " yes 60.0 35 \n", - "psychosis_schiz_bipolar no 66.7 3150 \n", - " yes 60.0 35 \n", - "ssri no 66.6 3143 \n", - " yes 66.7 42 \n", - "ckd no 66.6 2597 \n", - " yes 66.7 588 \n", - "brand_of_first_dose Moderna 0.0 0 \n", - " Oxford-AZ 0.0 0 \n", + "overall overall 69.6 6223 \n", + "sex F 69.9 3206 \n", + " M 69.6 3017 \n", + "ethnicity_6_groups Black 70.9 1036 \n", + " Mixed 66.4 1064 \n", + " Other 72.3 1085 \n", + " South Asian 70.5 1022 \n", + " Unknown 68.4 952 \n", + " White 69.3 1071 \n", + "ethnicity_16_groups African 67.4 322 \n", + " Bangladeshi or British Bangladeshi 74.4 301 \n", + " Caribbean 70.2 329 \n", + " Chinese 64.3 294 \n", + " Other 70.2 329 \n", + " Other Asian 70.5 308 \n", + " British or Mixed British 70.8 336 \n", + " Indian or British Indian 69.6 322 \n", + " Irish 68.8 336 \n", + " Other Black 71.4 343 \n", + " Other White 66.0 350 \n", + " Other mixed 75.0 308 \n", + " Pakistani or British Pakistani 72.5 357 \n", + " Unknown 67.6 952 \n", + " White + Asian 64.6 336 \n", + " White + Black African 68.5 378 \n", + " White + Black Caribbean 72.3 329 \n", + "imd_categories 1 Most deprived 69.1 1225 \n", + " 2 69.9 1141 \n", + " 3 70.5 1211 \n", + " 4 71.0 1183 \n", + " 5 Least deprived 68.1 1141 \n", + " Unknown 67.4 322 \n", + "bmi 30+ 70.5 1806 \n", + " under 30 69.3 4417 \n", + "chronic_cardiac_disease no 69.7 6153 \n", + " yes 63.6 77 \n", + "current_copd no 69.7 6174 \n", + " yes 50.0 56 \n", + "dmards no 69.5 6160 \n", + " yes 70.0 70 \n", + "psychosis_schiz_bipolar no 69.6 6167 \n", + " yes 66.7 63 \n", + "ssri no 69.5 6160 \n", + " yes 70.0 70 \n", + "ckd no 70.0 4942 \n", + " yes 67.9 1288 \n", + "brand_of_first_dose Oxford-AZ 0.0 0 \n", " Pfizer 0.0 7 \n", - " Unknown 74.0 2856 \n", + " Unknown 77.2 5607 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 65.1 \n", - "sex F 66.8 \n", - " M 63.2 \n", - "ethnicity_6_groups Black 65.9 \n", - " Mixed 65.9 \n", - " Other 62.2 \n", - " South Asian 63.6 \n", - " Unknown 66.7 \n", - " White 68.4 \n", - "ethnicity_16_groups African 72.0 \n", - " Bangladeshi or British Bangladeshi 62.5 \n", - " Caribbean 69.6 \n", - " Chinese 57.7 \n", - " Other 66.7 \n", - " Other Asian 60.9 \n", - " British or Mixed British 73.9 \n", - " Indian or British Indian 66.7 \n", - " Irish 60.0 \n", - " Other Black 68.2 \n", - " Other White 63.6 \n", - " Other mixed 61.5 \n", - " Pakistani or British Pakistani 66.7 \n", - " Unknown 62.3 \n", - " White + Asian 66.7 \n", - " White + Black African 73.9 \n", - " White + Black Caribbean 61.5 \n", - "imd_categories 1 Most deprived 65.5 \n", - " 2 64.1 \n", - " 3 64.3 \n", - " 4 65.1 \n", - " 5 Least deprived 65.4 \n", - " Unknown 68.0 \n", - "bmi 30+ 67.2 \n", - " under 30 64.2 \n", - "chronic_cardiac_disease no 65.0 \n", - " yes 66.7 \n", - "current_copd no 65.1 \n", - " yes 60.0 \n", - "dmards no 65.1 \n", - " yes 60.0 \n", - "psychosis_schiz_bipolar no 65.1 \n", - " yes 40.0 \n", - "ssri no 65.0 \n", + "overall overall 68.4 \n", + "sex F 68.6 \n", + " M 68.2 \n", + "ethnicity_6_groups Black 70.3 \n", + " Mixed 65.1 \n", + " Other 71.0 \n", + " South Asian 68.5 \n", + " Unknown 67.6 \n", + " White 68.0 \n", + "ethnicity_16_groups African 67.4 \n", + " Bangladeshi or British Bangladeshi 72.1 \n", + " Caribbean 70.2 \n", + " Chinese 64.3 \n", + " Other 70.2 \n", + " Other Asian 68.2 \n", + " British or Mixed British 68.8 \n", + " Indian or British Indian 67.4 \n", + " Irish 66.7 \n", + " Other Black 71.4 \n", + " Other White 66.0 \n", + " Other mixed 72.7 \n", + " Pakistani or British Pakistani 70.6 \n", + " Unknown 66.2 \n", + " White + Asian 64.6 \n", + " White + Black African 68.5 \n", + " White + Black Caribbean 70.2 \n", + "imd_categories 1 Most deprived 68.0 \n", + " 2 68.1 \n", + " 3 69.4 \n", + " 4 69.8 \n", + " 5 Least deprived 66.9 \n", + " Unknown 65.2 \n", + "bmi 30+ 69.8 \n", + " under 30 67.8 \n", + "chronic_cardiac_disease no 68.4 \n", + " yes 63.6 \n", + "current_copd no 68.5 \n", + " yes 50.0 \n", + "dmards no 68.3 \n", + " yes 70.0 \n", + "psychosis_schiz_bipolar no 68.3 \n", " yes 66.7 \n", - "ckd no 65.0 \n", - " yes 65.5 \n", - "brand_of_first_dose Moderna NaN \n", - " Oxford-AZ NaN \n", + "ssri no 68.3 \n", + " yes 70.0 \n", + "ckd no 68.7 \n", + " yes 66.8 \n", + "brand_of_first_dose Oxford-AZ NaN \n", " Pfizer 0.0 \n", - " Unknown 72.3 \n", + " Unknown 75.8 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.5 \n", - "sex F 1.7 \n", + "overall overall 1.2 \n", + "sex F 1.3 \n", " M 1.4 \n", - "ethnicity_6_groups Black 1.2 \n", - " Mixed 1.2 \n", + "ethnicity_6_groups Black 0.6 \n", + " Mixed 1.3 \n", " Other 1.3 \n", - " South Asian 2.6 \n", - " Unknown 1.6 \n", - " White 1.2 \n", + " South Asian 2.0 \n", + " Unknown 0.8 \n", + " White 1.3 \n", "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 4.2 \n", + " Bangladeshi or British Bangladeshi 2.3 \n", " Caribbean 0.0 \n", - " Chinese 3.8 \n", + " Chinese 0.0 \n", " Other 0.0 \n", - " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 0.0 \n", - " Irish 4.0 \n", + " Other Asian 2.3 \n", + " British or Mixed British 2.0 \n", + " Indian or British Indian 2.2 \n", + " Irish 2.1 \n", " Other Black 0.0 \n", " Other White 0.0 \n", - " Other mixed 3.9 \n", - " Pakistani or British Pakistani 3.7 \n", - " Unknown 1.5 \n", + " Other mixed 2.3 \n", + " Pakistani or British Pakistani 1.9 \n", + " Unknown 1.4 \n", " White + Asian 0.0 \n", " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 2.3 \n", - " 2 2.2 \n", - " 3 1.2 \n", + " White + Black Caribbean 2.1 \n", + "imd_categories 1 Most deprived 1.1 \n", + " 2 1.8 \n", + " 3 1.1 \n", " 4 1.2 \n", - " 5 Least deprived 1.3 \n", - " Unknown 4.0 \n", - "bmi 30+ 1.4 \n", + " 5 Least deprived 1.2 \n", + " Unknown 2.2 \n", + "bmi 30+ 0.7 \n", " under 30 1.5 \n", - "chronic_cardiac_disease no 1.6 \n", + "chronic_cardiac_disease no 1.3 \n", " yes 0.0 \n", - "current_copd no 1.6 \n", + "current_copd no 1.2 \n", " yes 0.0 \n", - "dmards no 1.6 \n", + "dmards no 1.2 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.6 \n", - " yes 20.0 \n", - "ssri no 1.6 \n", + "psychosis_schiz_bipolar no 1.3 \n", " yes 0.0 \n", - "ckd no 1.6 \n", - " yes 1.2 \n", - "brand_of_first_dose Moderna 0.0 \n", - " Oxford-AZ 0.0 \n", + "ssri no 1.2 \n", + " yes 0.0 \n", + "ckd no 1.3 \n", + " yes 1.1 \n", + "brand_of_first_dose Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 1.7 \n", + " Unknown 1.4 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 26-Dec \n", - "sex F 05-Dec \n", - " M 13-Jan \n", - "ethnicity_6_groups Black 19-Jan \n", - " Mixed 19-Jan \n", - " Other 28-Jan \n", - " South Asian 11-Nov \n", - " Unknown 11-Dec \n", - " White 05-Jan \n", + "overall overall 23-Feb \n", + "sex F 12-Feb \n", + " M 06-Feb \n", + "ethnicity_6_groups Black unknown \n", + " Mixed 03-Mar \n", + " Other 30-Jan \n", + " South Asian 03-Jan \n", + " Unknown unknown \n", + " White 15-Feb \n", "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi 16-Oct \n", + " Bangladeshi or British Bangladeshi 13-Dec \n", " Caribbean unknown \n", - " Chinese 30-Oct \n", + " Chinese unknown \n", " Other unknown \n", - " Other Asian unknown \n", - " British or Mixed British unknown \n", - " Indian or British Indian unknown \n", - " Irish 23-Oct \n", + " Other Asian 25-Dec \n", + " British or Mixed British 02-Jan \n", + " Indian or British Indian 30-Dec \n", + " Irish 05-Jan \n", " Other Black unknown \n", " Other White unknown \n", - " Other mixed 22-Oct \n", - " Pakistani or British Pakistani 15-Oct \n", - " Unknown 08-Jan \n", + " Other mixed 11-Dec \n", + " Pakistani or British Pakistani 30-Dec \n", + " Unknown 16-Feb \n", " White + Asian unknown \n", " White + Black African unknown \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived 14-Nov \n", - " 2 22-Nov \n", - " 3 28-Jan \n", - " 4 24-Jan \n", - " 5 Least deprived 11-Jan \n", - " Unknown 09-Oct \n", - "bmi 30+ 24-Dec \n", - " under 30 30-Dec \n", - "chronic_cardiac_disease no 19-Dec \n", + " White + Black Caribbean 25-Dec \n", + "imd_categories 1 Most deprived 09-Mar \n", + " 2 13-Jan \n", + " 3 28-Feb \n", + " 4 14-Feb \n", + " 5 Least deprived 03-Mar \n", + " Unknown 06-Jan \n", + "bmi 30+ unknown \n", + " under 30 31-Jan \n", + "chronic_cardiac_disease no 13-Feb \n", " yes unknown \n", - "current_copd no 18-Dec \n", + "current_copd no 22-Feb \n", " yes unknown \n", - "dmards no 18-Dec \n", + "dmards no 23-Feb \n", " yes unknown \n", - "psychosis_schiz_bipolar no 18-Dec \n", - " yes 18-Sep \n", - "ssri no 19-Dec \n", + "psychosis_schiz_bipolar no 13-Feb \n", " yes unknown \n", - "ckd no 19-Dec \n", - " yes 21-Jan \n", - "brand_of_first_dose Moderna unknown \n", - " Oxford-AZ unknown \n", + "ssri no 23-Feb \n", + " yes unknown \n", + "ckd no 11-Feb \n", + " yes 16-Mar \n", + "brand_of_first_dose Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 12-Nov " + " Unknown 30-Dec " ] }, "metadata": {}, @@ -29957,7 +30075,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **50-54** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **50-54** population up to 2021-10-27" ], "text/plain": [ "" @@ -30023,387 +30141,387 @@ " \n", " overall\n", " overall\n", - " 2275\n", - " 65.8\n", - " 3458\n", - " 64.0\n", - " 1.8\n", - " 11-Dec\n", + " 4613\n", + " 68.6\n", + " 6727\n", + " 67.1\n", + " 1.5\n", + " 03-Feb\n", " \n", " \n", " sex\n", " F\n", - " 1169\n", - " 66.0\n", - " 1771\n", - " 64.4\n", - " 1.6\n", - " 22-Dec\n", + " 2345\n", + " 68.9\n", + " 3402\n", + " 67.5\n", + " 1.4\n", + " 09-Feb\n", " \n", " \n", " M\n", - " 1106\n", - " 65.6\n", - " 1687\n", - " 63.5\n", - " 2.1\n", - " 28-Nov\n", + " 2268\n", + " 68.2\n", + " 3325\n", + " 66.7\n", + " 1.5\n", + " 05-Feb\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 385\n", - " 64.7\n", - " 595\n", - " 63.5\n", - " 1.2\n", - " 02-Feb\n", + " 826\n", + " 69.0\n", + " 1197\n", + " 67.3\n", + " 1.7\n", + " 21-Jan\n", " \n", " \n", " Mixed\n", - " 371\n", - " 63.1\n", - " 588\n", - " 60.7\n", - " 2.4\n", - " 25-Nov\n", + " 798\n", + " 67.9\n", + " 1176\n", + " 66.7\n", + " 1.2\n", + " 04-Mar\n", " \n", " \n", " Other\n", - " 413\n", - " 67.0\n", - " 616\n", - " 64.8\n", - " 2.2\n", - " 20-Nov\n", + " 777\n", + " 69.4\n", + " 1120\n", + " 68.1\n", + " 1.3\n", + " 14-Feb\n", " \n", " \n", " South Asian\n", - " 364\n", - " 65.0\n", - " 560\n", - " 63.7\n", - " 1.3\n", - " 20-Jan\n", + " 749\n", + " 69.5\n", + " 1078\n", + " 67.5\n", + " 2.0\n", + " 06-Jan\n", " \n", " \n", " Unknown\n", - " 350\n", - " 66.7\n", - " 525\n", - " 65.3\n", - " 1.4\n", - " 02-Jan\n", + " 658\n", + " 66.2\n", + " 994\n", + " 64.1\n", + " 2.1\n", + " 14-Jan\n", " \n", " \n", " White\n", - " 392\n", - " 68.3\n", - " 574\n", - " 65.9\n", - " 2.4\n", - " 10-Nov\n", + " 812\n", + " 69.9\n", + " 1162\n", + " 68.1\n", + " 1.8\n", + " 13-Jan\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 126\n", - " 62.1\n", - " 203\n", - " 62.1\n", + " 245\n", + " 67.3\n", + " 364\n", + " 67.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 112\n", - " 66.7\n", - " 168\n", - " 66.7\n", + " 245\n", + " 70.0\n", + " 350\n", + " 70.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 133\n", - " 70.4\n", - " 189\n", - " 70.4\n", - " 0.0\n", - " unknown\n", + " 245\n", + " 70.0\n", + " 350\n", + " 68.0\n", + " 2.0\n", + " 05-Jan\n", " \n", " \n", " Chinese\n", - " 126\n", - " 69.2\n", - " 182\n", - " 69.2\n", - " 0.0\n", - " unknown\n", + " 238\n", + " 69.4\n", + " 343\n", + " 67.3\n", + " 2.1\n", + " 03-Jan\n", " \n", " \n", " Other\n", - " 126\n", - " 66.7\n", - " 189\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 238\n", + " 68.0\n", + " 350\n", + " 66.0\n", + " 2.0\n", + " 12-Jan\n", " \n", " \n", " Other Asian\n", - " 105\n", - " 57.7\n", - " 182\n", - " 57.7\n", - " 0.0\n", - " unknown\n", + " 259\n", + " 68.5\n", + " 378\n", + " 66.7\n", + " 1.8\n", + " 18-Jan\n", " \n", " \n", " British or Mixed British\n", - " 119\n", - " 60.7\n", - " 196\n", - " 57.1\n", - " 3.6\n", - " 03-Nov\n", + " 245\n", + " 70.0\n", + " 350\n", + " 70.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 105\n", - " 57.7\n", - " 182\n", - " 53.8\n", - " 3.9\n", - " 04-Nov\n", + " 280\n", + " 71.4\n", + " 392\n", + " 67.9\n", + " 3.5\n", + " 03-Dec\n", " \n", " \n", " Irish\n", - " 119\n", - " 65.4\n", - " 182\n", - " 65.4\n", + " 231\n", + " 67.3\n", + " 343\n", + " 67.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 105\n", - " 60.0\n", - " 175\n", - " 60.0\n", - " 0.0\n", - " unknown\n", + " 252\n", + " 69.2\n", + " 364\n", + " 67.3\n", + " 1.9\n", + " 11-Jan\n", " \n", " \n", " Other White\n", - " 119\n", - " 68.0\n", - " 175\n", - " 64.0\n", - " 4.0\n", - " 16-Oct\n", + " 231\n", + " 67.3\n", + " 343\n", + " 67.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other mixed\n", - " 119\n", - " 70.8\n", - " 168\n", - " 70.8\n", + " 224\n", + " 64.0\n", + " 350\n", + " 64.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 133\n", - " 73.1\n", - " 182\n", - " 69.2\n", - " 3.9\n", - " 08-Oct\n", + " 259\n", + " 68.5\n", + " 378\n", + " 66.7\n", + " 1.8\n", + " 18-Jan\n", " \n", " \n", " Unknown\n", - " 343\n", + " 700\n", " 69.0\n", - " 497\n", - " 66.2\n", - " 2.8\n", - " 30-Oct\n", + " 1015\n", + " 67.6\n", + " 1.4\n", + " 09-Feb\n", " \n", " \n", " White + Asian\n", - " 119\n", - " 63.0\n", - " 189\n", - " 63.0\n", - " 0.0\n", - " unknown\n", + " 231\n", + " 66.0\n", + " 350\n", + " 64.0\n", + " 2.0\n", + " 19-Jan\n", " \n", " \n", " White + Black African\n", - " 140\n", - " 64.5\n", - " 217\n", - " 61.3\n", - " 3.2\n", - " 02-Nov\n", + " 238\n", + " 68.0\n", + " 350\n", + " 66.0\n", + " 2.0\n", + " 12-Jan\n", " \n", " \n", " White + Black Caribbean\n", - " 119\n", - " 70.8\n", - " 168\n", - " 66.7\n", - " 4.1\n", - " 10-Oct\n", + " 252\n", + " 69.2\n", + " 364\n", + " 65.4\n", + " 3.8\n", + " 04-Dec\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 448\n", - " 65.3\n", - " 686\n", - " 63.3\n", - " 2.0\n", - " 03-Dec\n", + " 882\n", + " 69.2\n", + " 1274\n", + " 68.1\n", + " 1.1\n", + " 08-Mar\n", " \n", " \n", " 2\n", - " 427\n", - " 64.2\n", - " 665\n", - " 63.2\n", - " 1.0\n", - " unknown\n", + " 903\n", + " 69.4\n", + " 1302\n", + " 67.7\n", + " 1.7\n", + " 19-Jan\n", " \n", " \n", " 3\n", - " 406\n", - " 63.7\n", - " 637\n", - " 62.6\n", - " 1.1\n", - " 22-Feb\n", + " 840\n", + " 67.0\n", + " 1253\n", + " 65.4\n", + " 1.6\n", + " 04-Feb\n", " \n", " \n", " 4\n", - " 434\n", - " 66.7\n", - " 651\n", - " 65.6\n", + " 882\n", + " 70.0\n", + " 1260\n", + " 68.9\n", " 1.1\n", - " 03-Feb\n", + " 03-Mar\n", " \n", " \n", " 5 Least deprived\n", - " 427\n", - " 67.0\n", - " 637\n", - " 64.8\n", - " 2.2\n", - " 20-Nov\n", + " 847\n", + " 66.9\n", + " 1267\n", + " 65.2\n", + " 1.7\n", + " 30-Jan\n", " \n", " \n", " Unknown\n", - " 126\n", - " 72.0\n", - " 175\n", - " 68.0\n", - " 4.0\n", - " 09-Oct\n", + " 259\n", + " 68.5\n", + " 378\n", + " 66.7\n", + " 1.8\n", + " 18-Jan\n", " \n", " \n", " bmi\n", " 30+\n", - " 665\n", - " 66.4\n", - " 1001\n", - " 64.3\n", - " 2.1\n", - " 25-Nov\n", + " 1351\n", + " 68.9\n", + " 1960\n", + " 67.1\n", + " 1.8\n", + " 17-Jan\n", " \n", " \n", " under 30\n", - " 1610\n", - " 65.5\n", - " 2457\n", - " 63.8\n", - " 1.7\n", - " 17-Dec\n", + " 3262\n", + " 68.4\n", + " 4767\n", + " 67.1\n", + " 1.3\n", + " 20-Feb\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 2254\n", - " 65.7\n", - " 3430\n", - " 63.9\n", - " 1.8\n", - " 11-Dec\n", + " 4564\n", + " 68.5\n", + " 6664\n", + " 67.0\n", + " 1.5\n", + " 04-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", + " 49\n", + " 77.8\n", + " 63\n", + " 77.8\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 2254\n", - " 65.8\n", - " 3423\n", - " 64.0\n", - " 1.8\n", - " 11-Dec\n", + " 4557\n", + " 68.5\n", + " 6650\n", + " 67.1\n", + " 1.4\n", + " 11-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 56\n", + " 72.7\n", + " 77\n", + " 72.7\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 2254\n", - " 65.7\n", - " 3430\n", - " 63.9\n", - " 1.8\n", - " 11-Dec\n", + " 4578\n", + " 68.7\n", + " 6664\n", + " 67.2\n", + " 1.5\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", + " 35\n", + " 62.5\n", + " 56\n", + " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 2254\n", - " 65.8\n", - " 3423\n", - " 64.0\n", - " 1.8\n", - " 11-Dec\n", + " 4571\n", + " 68.7\n", + " 6657\n", + " 67.2\n", + " 1.5\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 21\n", + " 42\n", " 60.0\n", - " 35\n", + " 70\n", " 60.0\n", " 0.0\n", " unknown\n", @@ -30411,43 +30529,52 @@ " \n", " ssri\n", " no\n", - " 2254\n", - " 66.0\n", - " 3416\n", - " 64.1\n", - " 1.9\n", - " 05-Dec\n", + " 4564\n", + " 68.6\n", + " 6657\n", + " 67.1\n", + " 1.5\n", + " 03-Feb\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 49\n", + " 77.8\n", + " 63\n", + " 77.8\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1820\n", - " 65.3\n", - " 2786\n", - " 63.3\n", - " 2.0\n", - " 03-Dec\n", + " 3682\n", + " 68.5\n", + " 5376\n", + " 66.9\n", + " 1.6\n", + " 29-Jan\n", " \n", " \n", " yes\n", - " 455\n", - " 67.7\n", - " 672\n", - " 66.7\n", + " 931\n", + " 68.9\n", + " 1351\n", + " 67.9\n", " 1.0\n", - " 11-Feb\n", + " 23-Mar\n", + " \n", + " \n", + " brand_of_first_dose\n", + " Moderna\n", + " 0\n", + " 0.0\n", + " 0\n", + " NaN\n", + " 0.0\n", + " unknown\n", " \n", " \n", - " brand_of_first_dose\n", " Oxford-AZ\n", " 0\n", " 0.0\n", @@ -30467,12 +30594,12 @@ " \n", " \n", " Unknown\n", - " 2268\n", - " 73.8\n", - " 3073\n", - " 71.8\n", - " 2.0\n", - " 03-Nov\n", + " 4606\n", + " 76.8\n", + " 5999\n", + " 75.1\n", + " 1.7\n", + " 20-Dec\n", " \n", " \n", "\n", @@ -30481,263 +30608,268 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 2275 \n", - "sex F 1169 \n", - " M 1106 \n", - "ethnicity_6_groups Black 385 \n", - " Mixed 371 \n", - " Other 413 \n", - " South Asian 364 \n", - " Unknown 350 \n", - " White 392 \n", - "ethnicity_16_groups African 126 \n", - " Bangladeshi or British Bangladeshi 112 \n", - " Caribbean 133 \n", - " Chinese 126 \n", - " Other 126 \n", - " Other Asian 105 \n", - " British or Mixed British 119 \n", - " Indian or British Indian 105 \n", - " Irish 119 \n", - " Other Black 105 \n", - " Other White 119 \n", - " Other mixed 119 \n", - " Pakistani or British Pakistani 133 \n", - " Unknown 343 \n", - " White + Asian 119 \n", - " White + Black African 140 \n", - " White + Black Caribbean 119 \n", - "imd_categories 1 Most deprived 448 \n", - " 2 427 \n", - " 3 406 \n", - " 4 434 \n", - " 5 Least deprived 427 \n", - " Unknown 126 \n", - "bmi 30+ 665 \n", - " under 30 1610 \n", - "chronic_cardiac_disease no 2254 \n", - " yes 21 \n", - "current_copd no 2254 \n", - " yes 21 \n", - "dmards no 2254 \n", - " yes 21 \n", - "psychosis_schiz_bipolar no 2254 \n", - " yes 21 \n", - "ssri no 2254 \n", - " yes 21 \n", - "ckd no 1820 \n", - " yes 455 \n", - "brand_of_first_dose Oxford-AZ 0 \n", + "overall overall 4613 \n", + "sex F 2345 \n", + " M 2268 \n", + "ethnicity_6_groups Black 826 \n", + " Mixed 798 \n", + " Other 777 \n", + " South Asian 749 \n", + " Unknown 658 \n", + " White 812 \n", + "ethnicity_16_groups African 245 \n", + " Bangladeshi or British Bangladeshi 245 \n", + " Caribbean 245 \n", + " Chinese 238 \n", + " Other 238 \n", + " Other Asian 259 \n", + " British or Mixed British 245 \n", + " Indian or British Indian 280 \n", + " Irish 231 \n", + " Other Black 252 \n", + " Other White 231 \n", + " Other mixed 224 \n", + " Pakistani or British Pakistani 259 \n", + " Unknown 700 \n", + " White + Asian 231 \n", + " White + Black African 238 \n", + " White + Black Caribbean 252 \n", + "imd_categories 1 Most deprived 882 \n", + " 2 903 \n", + " 3 840 \n", + " 4 882 \n", + " 5 Least deprived 847 \n", + " Unknown 259 \n", + "bmi 30+ 1351 \n", + " under 30 3262 \n", + "chronic_cardiac_disease no 4564 \n", + " yes 49 \n", + "current_copd no 4557 \n", + " yes 56 \n", + "dmards no 4578 \n", + " yes 35 \n", + "psychosis_schiz_bipolar no 4571 \n", + " yes 42 \n", + "ssri no 4564 \n", + " yes 49 \n", + "ckd no 3682 \n", + " yes 931 \n", + "brand_of_first_dose Moderna 0 \n", + " Oxford-AZ 0 \n", " Pfizer 0 \n", - " Unknown 2268 \n", + " Unknown 4606 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 65.8 3458 \n", - "sex F 66.0 1771 \n", - " M 65.6 1687 \n", - "ethnicity_6_groups Black 64.7 595 \n", - " Mixed 63.1 588 \n", - " Other 67.0 616 \n", - " South Asian 65.0 560 \n", - " Unknown 66.7 525 \n", - " White 68.3 574 \n", - "ethnicity_16_groups African 62.1 203 \n", - " Bangladeshi or British Bangladeshi 66.7 168 \n", - " Caribbean 70.4 189 \n", - " Chinese 69.2 182 \n", - " Other 66.7 189 \n", - " Other Asian 57.7 182 \n", - " British or Mixed British 60.7 196 \n", - " Indian or British Indian 57.7 182 \n", - " Irish 65.4 182 \n", - " Other Black 60.0 175 \n", - " Other White 68.0 175 \n", - " Other mixed 70.8 168 \n", - " Pakistani or British Pakistani 73.1 182 \n", - " Unknown 69.0 497 \n", - " White + Asian 63.0 189 \n", - " White + Black African 64.5 217 \n", - " White + Black Caribbean 70.8 168 \n", - "imd_categories 1 Most deprived 65.3 686 \n", - " 2 64.2 665 \n", - " 3 63.7 637 \n", - " 4 66.7 651 \n", - " 5 Least deprived 67.0 637 \n", - " Unknown 72.0 175 \n", - "bmi 30+ 66.4 1001 \n", - " under 30 65.5 2457 \n", - "chronic_cardiac_disease no 65.7 3430 \n", - " yes 75.0 28 \n", - "current_copd no 65.8 3423 \n", - " yes 60.0 35 \n", - "dmards no 65.7 3430 \n", - " yes 75.0 28 \n", - "psychosis_schiz_bipolar no 65.8 3423 \n", - " yes 60.0 35 \n", - "ssri no 66.0 3416 \n", - " yes 60.0 35 \n", - "ckd no 65.3 2786 \n", - " yes 67.7 672 \n", - "brand_of_first_dose Oxford-AZ 0.0 0 \n", + "overall overall 68.6 6727 \n", + "sex F 68.9 3402 \n", + " M 68.2 3325 \n", + "ethnicity_6_groups Black 69.0 1197 \n", + " Mixed 67.9 1176 \n", + " Other 69.4 1120 \n", + " South Asian 69.5 1078 \n", + " Unknown 66.2 994 \n", + " White 69.9 1162 \n", + "ethnicity_16_groups African 67.3 364 \n", + " Bangladeshi or British Bangladeshi 70.0 350 \n", + " Caribbean 70.0 350 \n", + " Chinese 69.4 343 \n", + " Other 68.0 350 \n", + " Other Asian 68.5 378 \n", + " British or Mixed British 70.0 350 \n", + " Indian or British Indian 71.4 392 \n", + " Irish 67.3 343 \n", + " Other Black 69.2 364 \n", + " Other White 67.3 343 \n", + " Other mixed 64.0 350 \n", + " Pakistani or British Pakistani 68.5 378 \n", + " Unknown 69.0 1015 \n", + " White + Asian 66.0 350 \n", + " White + Black African 68.0 350 \n", + " White + Black Caribbean 69.2 364 \n", + "imd_categories 1 Most deprived 69.2 1274 \n", + " 2 69.4 1302 \n", + " 3 67.0 1253 \n", + " 4 70.0 1260 \n", + " 5 Least deprived 66.9 1267 \n", + " Unknown 68.5 378 \n", + "bmi 30+ 68.9 1960 \n", + " under 30 68.4 4767 \n", + "chronic_cardiac_disease no 68.5 6664 \n", + " yes 77.8 63 \n", + "current_copd no 68.5 6650 \n", + " yes 72.7 77 \n", + "dmards no 68.7 6664 \n", + " yes 62.5 56 \n", + "psychosis_schiz_bipolar no 68.7 6657 \n", + " yes 60.0 70 \n", + "ssri no 68.6 6657 \n", + " yes 77.8 63 \n", + "ckd no 68.5 5376 \n", + " yes 68.9 1351 \n", + "brand_of_first_dose Moderna 0.0 0 \n", + " Oxford-AZ 0.0 0 \n", " Pfizer 0.0 7 \n", - " Unknown 73.8 3073 \n", + " Unknown 76.8 5999 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 64.0 \n", - "sex F 64.4 \n", - " M 63.5 \n", - "ethnicity_6_groups Black 63.5 \n", - " Mixed 60.7 \n", - " Other 64.8 \n", - " South Asian 63.7 \n", - " Unknown 65.3 \n", - " White 65.9 \n", - "ethnicity_16_groups African 62.1 \n", - " Bangladeshi or British Bangladeshi 66.7 \n", - " Caribbean 70.4 \n", - " Chinese 69.2 \n", - " Other 66.7 \n", - " Other Asian 57.7 \n", - " British or Mixed British 57.1 \n", - " Indian or British Indian 53.8 \n", - " Irish 65.4 \n", - " Other Black 60.0 \n", - " Other White 64.0 \n", - " Other mixed 70.8 \n", - " Pakistani or British Pakistani 69.2 \n", - " Unknown 66.2 \n", - " White + Asian 63.0 \n", - " White + Black African 61.3 \n", - " White + Black Caribbean 66.7 \n", - "imd_categories 1 Most deprived 63.3 \n", - " 2 63.2 \n", - " 3 62.6 \n", - " 4 65.6 \n", - " 5 Least deprived 64.8 \n", - " Unknown 68.0 \n", - "bmi 30+ 64.3 \n", - " under 30 63.8 \n", - "chronic_cardiac_disease no 63.9 \n", - " yes 75.0 \n", - "current_copd no 64.0 \n", - " yes 60.0 \n", - "dmards no 63.9 \n", - " yes 75.0 \n", - "psychosis_schiz_bipolar no 64.0 \n", - " yes 60.0 \n", - "ssri no 64.1 \n", + "overall overall 67.1 \n", + "sex F 67.5 \n", + " M 66.7 \n", + "ethnicity_6_groups Black 67.3 \n", + " Mixed 66.7 \n", + " Other 68.1 \n", + " South Asian 67.5 \n", + " Unknown 64.1 \n", + " White 68.1 \n", + "ethnicity_16_groups African 67.3 \n", + " Bangladeshi or British Bangladeshi 70.0 \n", + " Caribbean 68.0 \n", + " Chinese 67.3 \n", + " Other 66.0 \n", + " Other Asian 66.7 \n", + " British or Mixed British 70.0 \n", + " Indian or British Indian 67.9 \n", + " Irish 67.3 \n", + " Other Black 67.3 \n", + " Other White 67.3 \n", + " Other mixed 64.0 \n", + " Pakistani or British Pakistani 66.7 \n", + " Unknown 67.6 \n", + " White + Asian 64.0 \n", + " White + Black African 66.0 \n", + " White + Black Caribbean 65.4 \n", + "imd_categories 1 Most deprived 68.1 \n", + " 2 67.7 \n", + " 3 65.4 \n", + " 4 68.9 \n", + " 5 Least deprived 65.2 \n", + " Unknown 66.7 \n", + "bmi 30+ 67.1 \n", + " under 30 67.1 \n", + "chronic_cardiac_disease no 67.0 \n", + " yes 77.8 \n", + "current_copd no 67.1 \n", + " yes 72.7 \n", + "dmards no 67.2 \n", + " yes 62.5 \n", + "psychosis_schiz_bipolar no 67.2 \n", " yes 60.0 \n", - "ckd no 63.3 \n", - " yes 66.7 \n", - "brand_of_first_dose Oxford-AZ NaN \n", + "ssri no 67.1 \n", + " yes 77.8 \n", + "ckd no 66.9 \n", + " yes 67.9 \n", + "brand_of_first_dose Moderna NaN \n", + " Oxford-AZ NaN \n", " Pfizer 0.0 \n", - " Unknown 71.8 \n", + " Unknown 75.1 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.8 \n", - "sex F 1.6 \n", - " M 2.1 \n", - "ethnicity_6_groups Black 1.2 \n", - " Mixed 2.4 \n", - " Other 2.2 \n", - " South Asian 1.3 \n", - " Unknown 1.4 \n", - " White 2.4 \n", + "overall overall 1.5 \n", + "sex F 1.4 \n", + " M 1.5 \n", + "ethnicity_6_groups Black 1.7 \n", + " Mixed 1.2 \n", + " Other 1.3 \n", + " South Asian 2.0 \n", + " Unknown 2.1 \n", + " White 1.8 \n", "ethnicity_16_groups African 0.0 \n", " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", - " Chinese 0.0 \n", - " Other 0.0 \n", - " Other Asian 0.0 \n", - " British or Mixed British 3.6 \n", - " Indian or British Indian 3.9 \n", + " Caribbean 2.0 \n", + " Chinese 2.1 \n", + " Other 2.0 \n", + " Other Asian 1.8 \n", + " British or Mixed British 0.0 \n", + " Indian or British Indian 3.5 \n", " Irish 0.0 \n", - " Other Black 0.0 \n", - " Other White 4.0 \n", + " Other Black 1.9 \n", + " Other White 0.0 \n", " Other mixed 0.0 \n", - " Pakistani or British Pakistani 3.9 \n", - " Unknown 2.8 \n", - " White + Asian 0.0 \n", - " White + Black African 3.2 \n", - " White + Black Caribbean 4.1 \n", - "imd_categories 1 Most deprived 2.0 \n", - " 2 1.0 \n", - " 3 1.1 \n", + " Pakistani or British Pakistani 1.8 \n", + " Unknown 1.4 \n", + " White + Asian 2.0 \n", + " White + Black African 2.0 \n", + " White + Black Caribbean 3.8 \n", + "imd_categories 1 Most deprived 1.1 \n", + " 2 1.7 \n", + " 3 1.6 \n", " 4 1.1 \n", - " 5 Least deprived 2.2 \n", - " Unknown 4.0 \n", - "bmi 30+ 2.1 \n", - " under 30 1.7 \n", - "chronic_cardiac_disease no 1.8 \n", + " 5 Least deprived 1.7 \n", + " Unknown 1.8 \n", + "bmi 30+ 1.8 \n", + " under 30 1.3 \n", + "chronic_cardiac_disease no 1.5 \n", " yes 0.0 \n", - "current_copd no 1.8 \n", + "current_copd no 1.4 \n", " yes 0.0 \n", - "dmards no 1.8 \n", + "dmards no 1.5 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.8 \n", + "psychosis_schiz_bipolar no 1.5 \n", " yes 0.0 \n", - "ssri no 1.9 \n", + "ssri no 1.5 \n", " yes 0.0 \n", - "ckd no 2.0 \n", + "ckd no 1.6 \n", " yes 1.0 \n", - "brand_of_first_dose Oxford-AZ 0.0 \n", + "brand_of_first_dose Moderna 0.0 \n", + " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 2.0 \n", + " Unknown 1.7 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 11-Dec \n", - "sex F 22-Dec \n", - " M 28-Nov \n", - "ethnicity_6_groups Black 02-Feb \n", - " Mixed 25-Nov \n", - " Other 20-Nov \n", - " South Asian 20-Jan \n", - " Unknown 02-Jan \n", - " White 10-Nov \n", + "overall overall 03-Feb \n", + "sex F 09-Feb \n", + " M 05-Feb \n", + "ethnicity_6_groups Black 21-Jan \n", + " Mixed 04-Mar \n", + " Other 14-Feb \n", + " South Asian 06-Jan \n", + " Unknown 14-Jan \n", + " White 13-Jan \n", "ethnicity_16_groups African unknown \n", " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean unknown \n", - " Chinese unknown \n", - " Other unknown \n", - " Other Asian unknown \n", - " British or Mixed British 03-Nov \n", - " Indian or British Indian 04-Nov \n", + " Caribbean 05-Jan \n", + " Chinese 03-Jan \n", + " Other 12-Jan \n", + " Other Asian 18-Jan \n", + " British or Mixed British unknown \n", + " Indian or British Indian 03-Dec \n", " Irish unknown \n", - " Other Black unknown \n", - " Other White 16-Oct \n", + " Other Black 11-Jan \n", + " Other White unknown \n", " Other mixed unknown \n", - " Pakistani or British Pakistani 08-Oct \n", - " Unknown 30-Oct \n", - " White + Asian unknown \n", - " White + Black African 02-Nov \n", - " White + Black Caribbean 10-Oct \n", - "imd_categories 1 Most deprived 03-Dec \n", - " 2 unknown \n", - " 3 22-Feb \n", - " 4 03-Feb \n", - " 5 Least deprived 20-Nov \n", - " Unknown 09-Oct \n", - "bmi 30+ 25-Nov \n", - " under 30 17-Dec \n", - "chronic_cardiac_disease no 11-Dec \n", + " Pakistani or British Pakistani 18-Jan \n", + " Unknown 09-Feb \n", + " White + Asian 19-Jan \n", + " White + Black African 12-Jan \n", + " White + Black Caribbean 04-Dec \n", + "imd_categories 1 Most deprived 08-Mar \n", + " 2 19-Jan \n", + " 3 04-Feb \n", + " 4 03-Mar \n", + " 5 Least deprived 30-Jan \n", + " Unknown 18-Jan \n", + "bmi 30+ 17-Jan \n", + " under 30 20-Feb \n", + "chronic_cardiac_disease no 04-Feb \n", " yes unknown \n", - "current_copd no 11-Dec \n", + "current_copd no 11-Feb \n", " yes unknown \n", - "dmards no 11-Dec \n", + "dmards no 03-Feb \n", " yes unknown \n", - "psychosis_schiz_bipolar no 11-Dec \n", + "psychosis_schiz_bipolar no 03-Feb \n", " yes unknown \n", - "ssri no 05-Dec \n", + "ssri no 03-Feb \n", " yes unknown \n", - "ckd no 03-Dec \n", - " yes 11-Feb \n", - "brand_of_first_dose Oxford-AZ unknown \n", + "ckd no 29-Jan \n", + " yes 23-Mar \n", + "brand_of_first_dose Moderna unknown \n", + " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 03-Nov " + " Unknown 20-Dec " ] }, "metadata": {}, @@ -30766,7 +30898,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **40-49** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **40-49** population up to 2021-10-27" ], "text/plain": [ "" @@ -30832,368 +30964,368 @@ " \n", " overall\n", " overall\n", - " 4067\n", - " 66.2\n", - " 6139\n", - " 64.3\n", - " 1.9\n", - " 04-Dec\n", + " 8393\n", + " 68.5\n", + " 12257\n", + " 66.8\n", + " 1.7\n", + " 23-Jan\n", " \n", " \n", " sex\n", " F\n", - " 2086\n", - " 65.9\n", - " 3164\n", - " 63.9\n", + " 4410\n", + " 69.0\n", + " 6391\n", + " 67.0\n", " 2.0\n", - " 01-Dec\n", + " 08-Jan\n", " \n", " \n", " M\n", - " 1981\n", - " 66.6\n", - " 2975\n", - " 64.7\n", - " 1.9\n", - " 03-Dec\n", + " 3983\n", + " 67.9\n", + " 5866\n", + " 66.3\n", + " 1.6\n", + " 31-Jan\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 658\n", - " 65.3\n", - " 1008\n", - " 62.5\n", - " 2.8\n", - " 08-Nov\n", + " 1442\n", + " 68.9\n", + " 2093\n", + " 67.2\n", + " 1.7\n", + " 21-Jan\n", " \n", " \n", " Mixed\n", - " 707\n", - " 66.9\n", - " 1057\n", - " 65.6\n", - " 1.3\n", - " 10-Jan\n", + " 1442\n", + " 69.1\n", + " 2086\n", + " 67.1\n", + " 2.0\n", + " 08-Jan\n", " \n", " \n", " Other\n", - " 679\n", - " 66.4\n", - " 1022\n", - " 64.4\n", - " 2.0\n", - " 29-Nov\n", + " 1372\n", + " 66.7\n", + " 2058\n", + " 65.3\n", + " 1.4\n", + " 20-Feb\n", " \n", " \n", " South Asian\n", - " 714\n", - " 67.5\n", - " 1057\n", - " 65.6\n", - " 1.9\n", - " 29-Nov\n", + " 1421\n", + " 69.0\n", + " 2058\n", + " 67.0\n", + " 2.0\n", + " 08-Jan\n", " \n", " \n", " Unknown\n", - " 595\n", - " 65.9\n", - " 903\n", - " 64.3\n", - " 1.6\n", - " 22-Dec\n", + " 1309\n", + " 69.0\n", + " 1897\n", + " 67.9\n", + " 1.1\n", + " 09-Mar\n", " \n", " \n", " White\n", - " 714\n", - " 65.4\n", - " 1092\n", - " 63.5\n", - " 1.9\n", - " 07-Dec\n", + " 1407\n", + " 68.1\n", + " 2065\n", + " 66.1\n", + " 2.0\n", + " 11-Jan\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 210\n", - " 65.2\n", - " 322\n", - " 63.0\n", + " 455\n", + " 71.4\n", + " 637\n", + " 69.2\n", " 2.2\n", - " 25-Nov\n", + " 25-Dec\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 203\n", - " 65.9\n", - " 308\n", - " 63.6\n", - " 2.3\n", - " 20-Nov\n", + " 434\n", + " 67.4\n", + " 644\n", + " 66.3\n", + " 1.1\n", + " 19-Mar\n", " \n", " \n", " Caribbean\n", - " 203\n", - " 63.0\n", - " 322\n", - " 63.0\n", - " 0.0\n", - " unknown\n", + " 483\n", + " 67.6\n", + " 714\n", + " 65.7\n", + " 1.9\n", + " 17-Jan\n", " \n", " \n", " Chinese\n", - " 245\n", - " 71.4\n", - " 343\n", - " 71.4\n", - " 0.0\n", - " unknown\n", + " 434\n", + " 68.1\n", + " 637\n", + " 67.0\n", + " 1.1\n", + " 15-Mar\n", " \n", " \n", " Other\n", - " 224\n", - " 64.0\n", - " 350\n", - " 62.0\n", - " 2.0\n", - " 08-Dec\n", + " 455\n", + " 67.0\n", + " 679\n", + " 66.0\n", + " 1.0\n", + " 06-Apr\n", " \n", " \n", " Other Asian\n", - " 217\n", - " 66.0\n", - " 329\n", - " 63.8\n", + " 427\n", + " 68.5\n", + " 623\n", + " 66.3\n", " 2.2\n", - " 23-Nov\n", + " 03-Jan\n", " \n", " \n", " British or Mixed British\n", - " 224\n", - " 65.3\n", - " 343\n", - " 63.3\n", - " 2.0\n", - " 03-Dec\n", + " 434\n", + " 67.4\n", + " 644\n", + " 65.2\n", + " 2.2\n", + " 06-Jan\n", " \n", " \n", " Indian or British Indian\n", - " 196\n", - " 66.7\n", - " 294\n", - " 64.3\n", - " 2.4\n", - " 14-Nov\n", + " 441\n", + " 68.5\n", + " 644\n", + " 66.3\n", + " 2.2\n", + " 03-Jan\n", " \n", " \n", " Irish\n", - " 238\n", - " 69.4\n", - " 343\n", - " 65.3\n", - " 4.1\n", - " 13-Oct\n", + " 476\n", + " 68.7\n", + " 693\n", + " 66.7\n", + " 2.0\n", + " 09-Jan\n", " \n", " \n", " Other Black\n", - " 224\n", - " 68.1\n", - " 329\n", - " 63.8\n", - " 4.3\n", - " 13-Oct\n", + " 455\n", + " 67.7\n", + " 672\n", + " 66.7\n", + " 1.0\n", + " 01-Apr\n", " \n", " \n", " Other White\n", - " 217\n", - " 68.9\n", - " 315\n", - " 66.7\n", - " 2.2\n", - " 14-Nov\n", + " 476\n", + " 69.4\n", + " 686\n", + " 67.3\n", + " 2.1\n", + " 03-Jan\n", " \n", " \n", " Other mixed\n", - " 196\n", - " 63.6\n", - " 308\n", - " 61.4\n", + " 448\n", + " 71.1\n", + " 630\n", + " 68.9\n", " 2.2\n", - " 01-Dec\n", + " 26-Dec\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 210\n", - " 65.2\n", - " 322\n", - " 63.0\n", - " 2.2\n", - " 25-Nov\n", + " 427\n", + " 69.3\n", + " 616\n", + " 68.2\n", + " 1.1\n", + " 07-Mar\n", " \n", " \n", " Unknown\n", - " 637\n", - " 67.9\n", - " 938\n", - " 64.9\n", - " 3.0\n", - " 29-Oct\n", + " 1232\n", + " 67.7\n", + " 1820\n", + " 65.8\n", + " 1.9\n", + " 17-Jan\n", " \n", " \n", " White + Asian\n", - " 217\n", - " 67.4\n", - " 322\n", - " 67.4\n", - " 0.0\n", - " unknown\n", + " 399\n", + " 67.1\n", + " 595\n", + " 65.9\n", + " 1.2\n", + " 09-Mar\n", " \n", " \n", " White + Black African\n", - " 203\n", - " 63.0\n", - " 322\n", - " 63.0\n", - " 0.0\n", - " unknown\n", + " 448\n", + " 68.8\n", + " 651\n", + " 67.7\n", + " 1.1\n", + " 10-Mar\n", " \n", " \n", " White + Black Caribbean\n", - " 203\n", - " 61.7\n", - " 329\n", - " 61.7\n", - " 0.0\n", - " unknown\n", + " 462\n", + " 69.5\n", + " 665\n", + " 68.4\n", + " 1.1\n", + " 06-Mar\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 749\n", - " 64.1\n", - " 1169\n", - " 61.7\n", - " 2.4\n", - " 22-Nov\n", + " 1589\n", + " 68.4\n", + " 2324\n", + " 66.6\n", + " 1.8\n", + " 19-Jan\n", " \n", " \n", " 2\n", - " 777\n", - " 67.7\n", - " 1148\n", - " 65.9\n", - " 1.8\n", - " 03-Dec\n", + " 1596\n", + " 69.1\n", + " 2310\n", + " 67.9\n", + " 1.2\n", + " 25-Feb\n", " \n", " \n", " 3\n", - " 777\n", - " 66.9\n", - " 1162\n", - " 65.1\n", + " 1554\n", + " 66.7\n", + " 2331\n", + " 64.9\n", " 1.8\n", - " 06-Dec\n", + " 25-Jan\n", " \n", " \n", " 4\n", - " 756\n", - " 65.5\n", - " 1155\n", - " 63.6\n", - " 1.9\n", - " 07-Dec\n", + " 1596\n", + " 68.7\n", + " 2324\n", + " 66.9\n", + " 1.8\n", + " 17-Jan\n", " \n", " \n", " 5 Least deprived\n", - " 812\n", - " 67.8\n", - " 1197\n", - " 65.5\n", - " 2.3\n", - " 14-Nov\n", + " 1624\n", + " 69.0\n", + " 2352\n", + " 67.3\n", + " 1.7\n", + " 21-Jan\n", " \n", " \n", " Unknown\n", - " 196\n", - " 65.1\n", - " 301\n", - " 65.1\n", - " 0.0\n", - " unknown\n", + " 434\n", + " 70.5\n", + " 616\n", + " 68.2\n", + " 2.3\n", + " 25-Dec\n", " \n", " \n", " bmi\n", " 30+\n", - " 1253\n", - " 66.1\n", - " 1897\n", - " 63.8\n", - " 2.3\n", - " 19-Nov\n", + " 2534\n", + " 69.2\n", + " 3661\n", + " 67.5\n", + " 1.7\n", + " 20-Jan\n", " \n", " \n", " under 30\n", - " 2814\n", - " 66.3\n", - " 4242\n", - " 64.4\n", - " 1.9\n", - " 04-Dec\n", + " 5852\n", + " 68.1\n", + " 8589\n", + " 66.5\n", + " 1.6\n", + " 30-Jan\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 4025\n", - " 66.2\n", - " 6076\n", - " 64.3\n", - " 1.9\n", - " 04-Dec\n", + " 8295\n", + " 68.5\n", + " 12117\n", + " 66.7\n", + " 1.8\n", + " 18-Jan\n", " \n", " \n", " yes\n", - " 42\n", - " 66.7\n", - " 63\n", - " 66.7\n", + " 98\n", + " 70.0\n", + " 140\n", + " 70.0\n", " 0.0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 4032\n", - " 66.4\n", - " 6076\n", - " 64.4\n", - " 2.0\n", - " 29-Nov\n", + " 8302\n", + " 68.4\n", + " 12145\n", + " 66.7\n", + " 1.7\n", + " 23-Jan\n", " \n", " \n", " yes\n", - " 35\n", - " 62.5\n", - " 56\n", - " 62.5\n", + " 84\n", + " 75.0\n", + " 112\n", + " 75.0\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 4018\n", - " 66.2\n", - " 6069\n", - " 64.2\n", - " 2.0\n", - " 30-Nov\n", + " 8288\n", + " 68.4\n", + " 12117\n", + " 66.7\n", + " 1.7\n", + " 23-Jan\n", " \n", " \n", " yes\n", - " 49\n", + " 98\n", " 70.0\n", - " 70\n", + " 140\n", " 70.0\n", " 0.0\n", " unknown\n", @@ -31201,59 +31333,59 @@ " \n", " psychosis_schiz_bipolar\n", " no\n", - " 4025\n", - " 66.2\n", - " 6076\n", - " 64.3\n", - " 1.9\n", - " 04-Dec\n", + " 8316\n", + " 68.5\n", + " 12138\n", + " 66.8\n", + " 1.7\n", + " 23-Jan\n", " \n", " \n", " yes\n", - " 42\n", - " 75.0\n", - " 56\n", - " 75.0\n", + " 77\n", + " 64.7\n", + " 119\n", + " 64.7\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 4039\n", - " 66.3\n", - " 6090\n", - " 64.4\n", - " 1.9\n", - " 04-Dec\n", + " 8330\n", + " 68.5\n", + " 12159\n", + " 66.8\n", + " 1.7\n", + " 23-Jan\n", " \n", " \n", " yes\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", + " 63\n", + " 64.3\n", + " 98\n", + " 64.3\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 3220\n", - " 66.0\n", - " 4879\n", - " 64.1\n", - " 1.9\n", - " 05-Dec\n", + " 6727\n", + " 68.4\n", + " 9835\n", + " 66.8\n", + " 1.6\n", + " 29-Jan\n", " \n", " \n", " yes\n", - " 840\n", - " 66.7\n", - " 1260\n", - " 65.0\n", + " 1659\n", + " 68.5\n", + " 2422\n", + " 66.8\n", " 1.7\n", - " 12-Dec\n", + " 23-Jan\n", " \n", " \n", " brand_of_first_dose\n", @@ -31267,30 +31399,30 @@ " \n", " \n", " Oxford-AZ\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 100.0\n", + " 7\n", + " 100.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " Pfizer\n", - " 0\n", - " 0.0\n", - " 7\n", - " 0.0\n", + " 14\n", + " 100.0\n", + " 14\n", + " 100.0\n", " 0.0\n", - " unknown\n", + " reached\n", " \n", " \n", " Unknown\n", - " 4060\n", - " 73.6\n", - " 5516\n", - " 71.4\n", - " 2.2\n", - " 30-Oct\n", + " 8365\n", + " 76.2\n", + " 10983\n", + " 74.3\n", + " 1.9\n", + " 16-Dec\n", " \n", " \n", "\n", @@ -31299,268 +31431,268 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 4067 \n", - "sex F 2086 \n", - " M 1981 \n", - "ethnicity_6_groups Black 658 \n", - " Mixed 707 \n", - " Other 679 \n", - " South Asian 714 \n", - " Unknown 595 \n", - " White 714 \n", - "ethnicity_16_groups African 210 \n", - " Bangladeshi or British Bangladeshi 203 \n", - " Caribbean 203 \n", - " Chinese 245 \n", - " Other 224 \n", - " Other Asian 217 \n", - " British or Mixed British 224 \n", - " Indian or British Indian 196 \n", - " Irish 238 \n", - " Other Black 224 \n", - " Other White 217 \n", - " Other mixed 196 \n", - " Pakistani or British Pakistani 210 \n", - " Unknown 637 \n", - " White + Asian 217 \n", - " White + Black African 203 \n", - " White + Black Caribbean 203 \n", - "imd_categories 1 Most deprived 749 \n", - " 2 777 \n", - " 3 777 \n", - " 4 756 \n", - " 5 Least deprived 812 \n", - " Unknown 196 \n", - "bmi 30+ 1253 \n", - " under 30 2814 \n", - "chronic_cardiac_disease no 4025 \n", - " yes 42 \n", - "current_copd no 4032 \n", - " yes 35 \n", - "dmards no 4018 \n", - " yes 49 \n", - "psychosis_schiz_bipolar no 4025 \n", - " yes 42 \n", - "ssri no 4039 \n", - " yes 28 \n", - "ckd no 3220 \n", - " yes 840 \n", + "overall overall 8393 \n", + "sex F 4410 \n", + " M 3983 \n", + "ethnicity_6_groups Black 1442 \n", + " Mixed 1442 \n", + " Other 1372 \n", + " South Asian 1421 \n", + " Unknown 1309 \n", + " White 1407 \n", + "ethnicity_16_groups African 455 \n", + " Bangladeshi or British Bangladeshi 434 \n", + " Caribbean 483 \n", + " Chinese 434 \n", + " Other 455 \n", + " Other Asian 427 \n", + " British or Mixed British 434 \n", + " Indian or British Indian 441 \n", + " Irish 476 \n", + " Other Black 455 \n", + " Other White 476 \n", + " Other mixed 448 \n", + " Pakistani or British Pakistani 427 \n", + " Unknown 1232 \n", + " White + Asian 399 \n", + " White + Black African 448 \n", + " White + Black Caribbean 462 \n", + "imd_categories 1 Most deprived 1589 \n", + " 2 1596 \n", + " 3 1554 \n", + " 4 1596 \n", + " 5 Least deprived 1624 \n", + " Unknown 434 \n", + "bmi 30+ 2534 \n", + " under 30 5852 \n", + "chronic_cardiac_disease no 8295 \n", + " yes 98 \n", + "current_copd no 8302 \n", + " yes 84 \n", + "dmards no 8288 \n", + " yes 98 \n", + "psychosis_schiz_bipolar no 8316 \n", + " yes 77 \n", + "ssri no 8330 \n", + " yes 63 \n", + "ckd no 6727 \n", + " yes 1659 \n", "brand_of_first_dose Moderna 0 \n", - " Oxford-AZ 0 \n", - " Pfizer 0 \n", - " Unknown 4060 \n", + " Oxford-AZ 7 \n", + " Pfizer 14 \n", + " Unknown 8365 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 66.2 6139 \n", - "sex F 65.9 3164 \n", - " M 66.6 2975 \n", - "ethnicity_6_groups Black 65.3 1008 \n", - " Mixed 66.9 1057 \n", - " Other 66.4 1022 \n", - " South Asian 67.5 1057 \n", - " Unknown 65.9 903 \n", - " White 65.4 1092 \n", - "ethnicity_16_groups African 65.2 322 \n", - " Bangladeshi or British Bangladeshi 65.9 308 \n", - " Caribbean 63.0 322 \n", - " Chinese 71.4 343 \n", - " Other 64.0 350 \n", - " Other Asian 66.0 329 \n", - " British or Mixed British 65.3 343 \n", - " Indian or British Indian 66.7 294 \n", - " Irish 69.4 343 \n", - " Other Black 68.1 329 \n", - " Other White 68.9 315 \n", - " Other mixed 63.6 308 \n", - " Pakistani or British Pakistani 65.2 322 \n", - " Unknown 67.9 938 \n", - " White + Asian 67.4 322 \n", - " White + Black African 63.0 322 \n", - " White + Black Caribbean 61.7 329 \n", - "imd_categories 1 Most deprived 64.1 1169 \n", - " 2 67.7 1148 \n", - " 3 66.9 1162 \n", - " 4 65.5 1155 \n", - " 5 Least deprived 67.8 1197 \n", - " Unknown 65.1 301 \n", - "bmi 30+ 66.1 1897 \n", - " under 30 66.3 4242 \n", - "chronic_cardiac_disease no 66.2 6076 \n", - " yes 66.7 63 \n", - "current_copd no 66.4 6076 \n", - " yes 62.5 56 \n", - "dmards no 66.2 6069 \n", - " yes 70.0 70 \n", - "psychosis_schiz_bipolar no 66.2 6076 \n", - " yes 75.0 56 \n", - "ssri no 66.3 6090 \n", - " yes 57.1 49 \n", - "ckd no 66.0 4879 \n", - " yes 66.7 1260 \n", + "overall overall 68.5 12257 \n", + "sex F 69.0 6391 \n", + " M 67.9 5866 \n", + "ethnicity_6_groups Black 68.9 2093 \n", + " Mixed 69.1 2086 \n", + " Other 66.7 2058 \n", + " South Asian 69.0 2058 \n", + " Unknown 69.0 1897 \n", + " White 68.1 2065 \n", + "ethnicity_16_groups African 71.4 637 \n", + " Bangladeshi or British Bangladeshi 67.4 644 \n", + " Caribbean 67.6 714 \n", + " Chinese 68.1 637 \n", + " Other 67.0 679 \n", + " Other Asian 68.5 623 \n", + " British or Mixed British 67.4 644 \n", + " Indian or British Indian 68.5 644 \n", + " Irish 68.7 693 \n", + " Other Black 67.7 672 \n", + " Other White 69.4 686 \n", + " Other mixed 71.1 630 \n", + " Pakistani or British Pakistani 69.3 616 \n", + " Unknown 67.7 1820 \n", + " White + Asian 67.1 595 \n", + " White + Black African 68.8 651 \n", + " White + Black Caribbean 69.5 665 \n", + "imd_categories 1 Most deprived 68.4 2324 \n", + " 2 69.1 2310 \n", + " 3 66.7 2331 \n", + " 4 68.7 2324 \n", + " 5 Least deprived 69.0 2352 \n", + " Unknown 70.5 616 \n", + "bmi 30+ 69.2 3661 \n", + " under 30 68.1 8589 \n", + "chronic_cardiac_disease no 68.5 12117 \n", + " yes 70.0 140 \n", + "current_copd no 68.4 12145 \n", + " yes 75.0 112 \n", + "dmards no 68.4 12117 \n", + " yes 70.0 140 \n", + "psychosis_schiz_bipolar no 68.5 12138 \n", + " yes 64.7 119 \n", + "ssri no 68.5 12159 \n", + " yes 64.3 98 \n", + "ckd no 68.4 9835 \n", + " yes 68.5 2422 \n", "brand_of_first_dose Moderna 0.0 0 \n", - " Oxford-AZ 0.0 0 \n", - " Pfizer 0.0 7 \n", - " Unknown 73.6 5516 \n", + " Oxford-AZ 100.0 7 \n", + " Pfizer 100.0 14 \n", + " Unknown 76.2 10983 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 64.3 \n", - "sex F 63.9 \n", - " M 64.7 \n", - "ethnicity_6_groups Black 62.5 \n", - " Mixed 65.6 \n", - " Other 64.4 \n", - " South Asian 65.6 \n", - " Unknown 64.3 \n", - " White 63.5 \n", - "ethnicity_16_groups African 63.0 \n", - " Bangladeshi or British Bangladeshi 63.6 \n", - " Caribbean 63.0 \n", - " Chinese 71.4 \n", - " Other 62.0 \n", - " Other Asian 63.8 \n", - " British or Mixed British 63.3 \n", - " Indian or British Indian 64.3 \n", - " Irish 65.3 \n", - " Other Black 63.8 \n", - " Other White 66.7 \n", - " Other mixed 61.4 \n", - " Pakistani or British Pakistani 63.0 \n", - " Unknown 64.9 \n", - " White + Asian 67.4 \n", - " White + Black African 63.0 \n", - " White + Black Caribbean 61.7 \n", - "imd_categories 1 Most deprived 61.7 \n", - " 2 65.9 \n", - " 3 65.1 \n", - " 4 63.6 \n", - " 5 Least deprived 65.5 \n", - " Unknown 65.1 \n", - "bmi 30+ 63.8 \n", - " under 30 64.4 \n", - "chronic_cardiac_disease no 64.3 \n", - " yes 66.7 \n", - "current_copd no 64.4 \n", - " yes 62.5 \n", - "dmards no 64.2 \n", + "overall overall 66.8 \n", + "sex F 67.0 \n", + " M 66.3 \n", + "ethnicity_6_groups Black 67.2 \n", + " Mixed 67.1 \n", + " Other 65.3 \n", + " South Asian 67.0 \n", + " Unknown 67.9 \n", + " White 66.1 \n", + "ethnicity_16_groups African 69.2 \n", + " Bangladeshi or British Bangladeshi 66.3 \n", + " Caribbean 65.7 \n", + " Chinese 67.0 \n", + " Other 66.0 \n", + " Other Asian 66.3 \n", + " British or Mixed British 65.2 \n", + " Indian or British Indian 66.3 \n", + " Irish 66.7 \n", + " Other Black 66.7 \n", + " Other White 67.3 \n", + " Other mixed 68.9 \n", + " Pakistani or British Pakistani 68.2 \n", + " Unknown 65.8 \n", + " White + Asian 65.9 \n", + " White + Black African 67.7 \n", + " White + Black Caribbean 68.4 \n", + "imd_categories 1 Most deprived 66.6 \n", + " 2 67.9 \n", + " 3 64.9 \n", + " 4 66.9 \n", + " 5 Least deprived 67.3 \n", + " Unknown 68.2 \n", + "bmi 30+ 67.5 \n", + " under 30 66.5 \n", + "chronic_cardiac_disease no 66.7 \n", " yes 70.0 \n", - "psychosis_schiz_bipolar no 64.3 \n", + "current_copd no 66.7 \n", " yes 75.0 \n", - "ssri no 64.4 \n", - " yes 57.1 \n", - "ckd no 64.1 \n", - " yes 65.0 \n", + "dmards no 66.7 \n", + " yes 70.0 \n", + "psychosis_schiz_bipolar no 66.8 \n", + " yes 64.7 \n", + "ssri no 66.8 \n", + " yes 64.3 \n", + "ckd no 66.8 \n", + " yes 66.8 \n", "brand_of_first_dose Moderna NaN \n", - " Oxford-AZ NaN \n", - " Pfizer 0.0 \n", - " Unknown 71.4 \n", + " Oxford-AZ 100.0 \n", + " Pfizer 100.0 \n", + " Unknown 74.3 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.9 \n", + "overall overall 1.7 \n", "sex F 2.0 \n", - " M 1.9 \n", - "ethnicity_6_groups Black 2.8 \n", - " Mixed 1.3 \n", - " Other 2.0 \n", - " South Asian 1.9 \n", - " Unknown 1.6 \n", - " White 1.9 \n", + " M 1.6 \n", + "ethnicity_6_groups Black 1.7 \n", + " Mixed 2.0 \n", + " Other 1.4 \n", + " South Asian 2.0 \n", + " Unknown 1.1 \n", + " White 2.0 \n", "ethnicity_16_groups African 2.2 \n", - " Bangladeshi or British Bangladeshi 2.3 \n", - " Caribbean 0.0 \n", - " Chinese 0.0 \n", - " Other 2.0 \n", + " Bangladeshi or British Bangladeshi 1.1 \n", + " Caribbean 1.9 \n", + " Chinese 1.1 \n", + " Other 1.0 \n", " Other Asian 2.2 \n", - " British or Mixed British 2.0 \n", - " Indian or British Indian 2.4 \n", - " Irish 4.1 \n", - " Other Black 4.3 \n", - " Other White 2.2 \n", + " British or Mixed British 2.2 \n", + " Indian or British Indian 2.2 \n", + " Irish 2.0 \n", + " Other Black 1.0 \n", + " Other White 2.1 \n", " Other mixed 2.2 \n", - " Pakistani or British Pakistani 2.2 \n", - " Unknown 3.0 \n", - " White + Asian 0.0 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 2.4 \n", - " 2 1.8 \n", + " Pakistani or British Pakistani 1.1 \n", + " Unknown 1.9 \n", + " White + Asian 1.2 \n", + " White + Black African 1.1 \n", + " White + Black Caribbean 1.1 \n", + "imd_categories 1 Most deprived 1.8 \n", + " 2 1.2 \n", " 3 1.8 \n", - " 4 1.9 \n", - " 5 Least deprived 2.3 \n", - " Unknown 0.0 \n", - "bmi 30+ 2.3 \n", - " under 30 1.9 \n", - "chronic_cardiac_disease no 1.9 \n", + " 4 1.8 \n", + " 5 Least deprived 1.7 \n", + " Unknown 2.3 \n", + "bmi 30+ 1.7 \n", + " under 30 1.6 \n", + "chronic_cardiac_disease no 1.8 \n", " yes 0.0 \n", - "current_copd no 2.0 \n", + "current_copd no 1.7 \n", " yes 0.0 \n", - "dmards no 2.0 \n", + "dmards no 1.7 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.9 \n", + "psychosis_schiz_bipolar no 1.7 \n", " yes 0.0 \n", - "ssri no 1.9 \n", + "ssri no 1.7 \n", " yes 0.0 \n", - "ckd no 1.9 \n", + "ckd no 1.6 \n", " yes 1.7 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 2.2 \n", + " Unknown 1.9 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 04-Dec \n", - "sex F 01-Dec \n", - " M 03-Dec \n", - "ethnicity_6_groups Black 08-Nov \n", - " Mixed 10-Jan \n", - " Other 29-Nov \n", - " South Asian 29-Nov \n", - " Unknown 22-Dec \n", - " White 07-Dec \n", - "ethnicity_16_groups African 25-Nov \n", - " Bangladeshi or British Bangladeshi 20-Nov \n", - " Caribbean unknown \n", - " Chinese unknown \n", - " Other 08-Dec \n", - " Other Asian 23-Nov \n", - " British or Mixed British 03-Dec \n", - " Indian or British Indian 14-Nov \n", - " Irish 13-Oct \n", - " Other Black 13-Oct \n", - " Other White 14-Nov \n", - " Other mixed 01-Dec \n", - " Pakistani or British Pakistani 25-Nov \n", - " Unknown 29-Oct \n", - " White + Asian unknown \n", - " White + Black African unknown \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived 22-Nov \n", - " 2 03-Dec \n", - " 3 06-Dec \n", - " 4 07-Dec \n", - " 5 Least deprived 14-Nov \n", - " Unknown unknown \n", - "bmi 30+ 19-Nov \n", - " under 30 04-Dec \n", - "chronic_cardiac_disease no 04-Dec \n", + "overall overall 23-Jan \n", + "sex F 08-Jan \n", + " M 31-Jan \n", + "ethnicity_6_groups Black 21-Jan \n", + " Mixed 08-Jan \n", + " Other 20-Feb \n", + " South Asian 08-Jan \n", + " Unknown 09-Mar \n", + " White 11-Jan \n", + "ethnicity_16_groups African 25-Dec \n", + " Bangladeshi or British Bangladeshi 19-Mar \n", + " Caribbean 17-Jan \n", + " Chinese 15-Mar \n", + " Other 06-Apr \n", + " Other Asian 03-Jan \n", + " British or Mixed British 06-Jan \n", + " Indian or British Indian 03-Jan \n", + " Irish 09-Jan \n", + " Other Black 01-Apr \n", + " Other White 03-Jan \n", + " Other mixed 26-Dec \n", + " Pakistani or British Pakistani 07-Mar \n", + " Unknown 17-Jan \n", + " White + Asian 09-Mar \n", + " White + Black African 10-Mar \n", + " White + Black Caribbean 06-Mar \n", + "imd_categories 1 Most deprived 19-Jan \n", + " 2 25-Feb \n", + " 3 25-Jan \n", + " 4 17-Jan \n", + " 5 Least deprived 21-Jan \n", + " Unknown 25-Dec \n", + "bmi 30+ 20-Jan \n", + " under 30 30-Jan \n", + "chronic_cardiac_disease no 18-Jan \n", " yes unknown \n", - "current_copd no 29-Nov \n", + "current_copd no 23-Jan \n", " yes unknown \n", - "dmards no 30-Nov \n", + "dmards no 23-Jan \n", " yes unknown \n", - "psychosis_schiz_bipolar no 04-Dec \n", + "psychosis_schiz_bipolar no 23-Jan \n", " yes unknown \n", - "ssri no 04-Dec \n", + "ssri no 23-Jan \n", " yes unknown \n", - "ckd no 05-Dec \n", - " yes 12-Dec \n", + "ckd no 29-Jan \n", + " yes 23-Jan \n", "brand_of_first_dose Moderna unknown \n", - " Oxford-AZ unknown \n", - " Pfizer unknown \n", - " Unknown 30-Oct " + " Oxford-AZ reached \n", + " Pfizer reached \n", + " Unknown 16-Dec " ] }, "metadata": {}, @@ -31589,7 +31721,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **30-39** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **30-39** population up to 2021-10-27" ], "text/plain": [ "" @@ -31655,295 +31787,295 @@ " \n", " overall\n", " overall\n", - " 4228\n", - " 66.3\n", - " 6377\n", - " 64.5\n", - " 1.8\n", - " 09-Dec\n", + " 8946\n", + " 69.0\n", + " 12957\n", + " 67.5\n", + " 1.5\n", + " 02-Feb\n", " \n", " \n", " sex\n", " F\n", - " 2184\n", - " 66.2\n", - " 3297\n", - " 64.5\n", - " 1.7\n", - " 15-Dec\n", + " 4662\n", + " 69.3\n", + " 6727\n", + " 67.7\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " M\n", - " 2044\n", - " 66.4\n", - " 3080\n", - " 64.5\n", - " 1.9\n", - " 03-Dec\n", - " \n", - " \n", - " ethnicity_6_groups\n", + " 4284\n", + " 68.8\n", + " 6230\n", + " 67.3\n", + " 1.5\n", + " 02-Feb\n", + " \n", + " \n", + " ethnicity_6_groups\n", " Black\n", - " 672\n", - " 62.7\n", - " 1071\n", - " 61.4\n", + " 1505\n", + " 67.4\n", + " 2233\n", + " 66.1\n", " 1.3\n", - " 02-Feb\n", + " 25-Feb\n", " \n", " \n", " Mixed\n", - " 721\n", - " 67.3\n", - " 1071\n", - " 65.4\n", - " 1.9\n", - " 30-Nov\n", + " 1505\n", + " 68.3\n", + " 2205\n", + " 67.0\n", + " 1.3\n", + " 20-Feb\n", " \n", " \n", " Other\n", - " 749\n", - " 66.9\n", - " 1120\n", - " 65.0\n", - " 1.9\n", - " 02-Dec\n", + " 1463\n", + " 68.8\n", + " 2128\n", + " 67.4\n", + " 1.4\n", + " 10-Feb\n", " \n", " \n", " South Asian\n", - " 742\n", - " 66.2\n", - " 1120\n", - " 64.4\n", + " 1540\n", + " 68.3\n", + " 2254\n", + " 66.5\n", " 1.8\n", - " 09-Dec\n", + " 19-Jan\n", " \n", " \n", " Unknown\n", - " 630\n", - " 65.7\n", - " 959\n", - " 65.0\n", - " 0.7\n", - " unknown\n", + " 1351\n", + " 70.4\n", + " 1918\n", + " 69.3\n", + " 1.1\n", + " 28-Feb\n", " \n", " \n", " White\n", - " 714\n", - " 68.9\n", - " 1036\n", - " 66.2\n", - " 2.7\n", - " 01-Nov\n", + " 1568\n", + " 70.4\n", + " 2226\n", + " 69.2\n", + " 1.2\n", + " 18-Feb\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 217\n", - " 64.6\n", - " 336\n", - " 64.6\n", - " 0.0\n", - " unknown\n", + " 476\n", + " 68.0\n", + " 700\n", + " 66.0\n", + " 2.0\n", + " 12-Jan\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 217\n", - " 66.0\n", - " 329\n", - " 63.8\n", - " 2.2\n", - " 23-Nov\n", + " 490\n", + " 71.4\n", + " 686\n", + " 69.4\n", + " 2.0\n", + " 31-Dec\n", " \n", " \n", " Caribbean\n", - " 210\n", - " 63.8\n", - " 329\n", - " 63.8\n", - " 0.0\n", - " unknown\n", + " 448\n", + " 68.1\n", + " 658\n", + " 66.0\n", + " 2.1\n", + " 08-Jan\n", " \n", " \n", " Chinese\n", - " 245\n", - " 68.6\n", - " 357\n", - " 66.7\n", - " 1.9\n", - " 25-Nov\n", + " 476\n", + " 68.0\n", + " 700\n", + " 67.0\n", + " 1.0\n", + " 30-Mar\n", " \n", " \n", " Other\n", - " 259\n", - " 69.8\n", - " 371\n", + " 469\n", + " 69.1\n", + " 679\n", " 66.0\n", - " 3.8\n", - " 15-Oct\n", + " 3.1\n", + " 13-Dec\n", " \n", " \n", " Other Asian\n", - " 224\n", - " 66.7\n", - " 336\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 497\n", + " 69.6\n", + " 714\n", + " 67.6\n", + " 2.0\n", + " 06-Jan\n", " \n", " \n", " British or Mixed British\n", - " 224\n", - " 68.1\n", - " 329\n", - " 66.0\n", - " 2.1\n", - " 20-Nov\n", + " 476\n", + " 66.7\n", + " 714\n", + " 65.7\n", + " 1.0\n", + " 08-Apr\n", " \n", " \n", " Indian or British Indian\n", - " 245\n", - " 66.0\n", - " 371\n", - " 64.2\n", - " 1.8\n", - " 10-Dec\n", + " 469\n", + " 68.4\n", + " 686\n", + " 67.3\n", + " 1.1\n", + " 13-Mar\n", " \n", " \n", " Irish\n", - " 203\n", - " 64.4\n", - " 315\n", - " 62.2\n", + " 455\n", + " 70.7\n", + " 644\n", + " 68.5\n", " 2.2\n", - " 28-Nov\n", + " 27-Dec\n", " \n", " \n", " Other Black\n", - " 217\n", - " 72.1\n", - " 301\n", - " 69.8\n", - " 2.3\n", - " 01-Nov\n", + " 469\n", + " 67.7\n", + " 693\n", + " 66.7\n", + " 1.0\n", + " 01-Apr\n", " \n", " \n", " Other White\n", - " 238\n", - " 66.7\n", - " 357\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 462\n", + " 70.2\n", + " 658\n", + " 68.1\n", + " 2.1\n", + " 01-Jan\n", " \n", " \n", " Other mixed\n", - " 252\n", - " 69.2\n", - " 364\n", - " 67.3\n", - " 1.9\n", - " 23-Nov\n", + " 490\n", + " 70.7\n", + " 693\n", + " 69.7\n", + " 1.0\n", + " 11-Mar\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 217\n", - " 64.6\n", - " 336\n", - " 62.5\n", - " 2.1\n", - " 01-Dec\n", + " 504\n", + " 68.6\n", + " 735\n", + " 66.7\n", + " 1.9\n", + " 13-Jan\n", " \n", " \n", " Unknown\n", - " 602\n", - " 64.7\n", - " 931\n", - " 63.2\n", - " 1.5\n", - " 04-Jan\n", + " 1323\n", + " 69.2\n", + " 1911\n", + " 67.8\n", + " 1.4\n", + " 08-Feb\n", " \n", " \n", " White + Asian\n", - " 203\n", - " 64.4\n", - " 315\n", - " 62.2\n", - " 2.2\n", - " 28-Nov\n", + " 476\n", + " 68.7\n", + " 693\n", + " 67.7\n", + " 1.0\n", + " 25-Mar\n", " \n", " \n", " White + Black African\n", - " 217\n", - " 64.6\n", - " 336\n", - " 64.6\n", - " 0.0\n", - " unknown\n", + " 483\n", + " 67.0\n", + " 721\n", + " 66.0\n", + " 1.0\n", + " 06-Apr\n", " \n", " \n", " White + Black Caribbean\n", - " 231\n", - " 66.0\n", - " 350\n", - " 64.0\n", - " 2.0\n", - " 01-Dec\n", + " 483\n", + " 72.6\n", + " 665\n", + " 70.5\n", + " 2.1\n", + " 24-Dec\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 812\n", - " 67.8\n", - " 1197\n", - " 66.7\n", - " 1.1\n", - " 27-Jan\n", + " 1715\n", + " 69.4\n", + " 2471\n", + " 67.7\n", + " 1.7\n", + " 19-Jan\n", " \n", " \n", " 2\n", - " 798\n", - " 65.1\n", - " 1225\n", - " 63.4\n", + " 1729\n", + " 69.8\n", + " 2478\n", + " 68.1\n", " 1.7\n", - " 19-Dec\n", + " 18-Jan\n", " \n", " \n", " 3\n", - " 812\n", - " 66.3\n", - " 1225\n", - " 64.6\n", - " 1.7\n", - " 14-Dec\n", + " 1701\n", + " 69.4\n", + " 2450\n", + " 68.0\n", + " 1.4\n", + " 07-Feb\n", " \n", " \n", " 4\n", - " 812\n", - " 64.8\n", - " 1253\n", - " 63.1\n", + " 1680\n", + " 68.6\n", + " 2450\n", + " 66.9\n", " 1.7\n", - " 20-Dec\n", + " 23-Jan\n", " \n", " \n", " 5 Least deprived\n", - " 784\n", - " 68.7\n", - " 1141\n", - " 66.3\n", - " 2.4\n", - " 09-Nov\n", + " 1680\n", + " 69.0\n", + " 2436\n", + " 67.8\n", + " 1.2\n", + " 26-Feb\n", " \n", " \n", " Unknown\n", - " 210\n", - " 63.8\n", - " 329\n", - " 61.7\n", - " 2.1\n", - " 04-Dec\n", + " 448\n", + " 66.7\n", + " 672\n", + " 65.6\n", + " 1.1\n", + " 24-Mar\n", " \n", " \n", " brand_of_first_dose\n", @@ -31959,8 +32091,8 @@ " Oxford-AZ\n", " 0\n", " 0.0\n", - " 7\n", - " 0.0\n", + " 0\n", + " NaN\n", " 0.0\n", " unknown\n", " \n", @@ -31975,12 +32107,12 @@ " \n", " \n", " Unknown\n", - " 4207\n", - " 73.8\n", - " 5698\n", - " 72.0\n", - " 1.8\n", - " 10-Nov\n", + " 8932\n", + " 76.5\n", + " 11683\n", + " 74.8\n", + " 1.7\n", + " 21-Dec\n", " \n", " \n", "\n", @@ -31989,198 +32121,198 @@ "text/plain": [ " vaccinated percent \\\n", "category group \n", - "overall overall 4228 66.3 \n", - "sex F 2184 66.2 \n", - " M 2044 66.4 \n", - "ethnicity_6_groups Black 672 62.7 \n", - " Mixed 721 67.3 \n", - " Other 749 66.9 \n", - " South Asian 742 66.2 \n", - " Unknown 630 65.7 \n", - " White 714 68.9 \n", - "ethnicity_16_groups African 217 64.6 \n", - " Bangladeshi or British Bangladeshi 217 66.0 \n", - " Caribbean 210 63.8 \n", - " Chinese 245 68.6 \n", - " Other 259 69.8 \n", - " Other Asian 224 66.7 \n", - " British or Mixed British 224 68.1 \n", - " Indian or British Indian 245 66.0 \n", - " Irish 203 64.4 \n", - " Other Black 217 72.1 \n", - " Other White 238 66.7 \n", - " Other mixed 252 69.2 \n", - " Pakistani or British Pakistani 217 64.6 \n", - " Unknown 602 64.7 \n", - " White + Asian 203 64.4 \n", - " White + Black African 217 64.6 \n", - " White + Black Caribbean 231 66.0 \n", - "imd_categories 1 Most deprived 812 67.8 \n", - " 2 798 65.1 \n", - " 3 812 66.3 \n", - " 4 812 64.8 \n", - " 5 Least deprived 784 68.7 \n", - " Unknown 210 63.8 \n", + "overall overall 8946 69.0 \n", + "sex F 4662 69.3 \n", + " M 4284 68.8 \n", + "ethnicity_6_groups Black 1505 67.4 \n", + " Mixed 1505 68.3 \n", + " Other 1463 68.8 \n", + " South Asian 1540 68.3 \n", + " Unknown 1351 70.4 \n", + " White 1568 70.4 \n", + "ethnicity_16_groups African 476 68.0 \n", + " Bangladeshi or British Bangladeshi 490 71.4 \n", + " Caribbean 448 68.1 \n", + " Chinese 476 68.0 \n", + " Other 469 69.1 \n", + " Other Asian 497 69.6 \n", + " British or Mixed British 476 66.7 \n", + " Indian or British Indian 469 68.4 \n", + " Irish 455 70.7 \n", + " Other Black 469 67.7 \n", + " Other White 462 70.2 \n", + " Other mixed 490 70.7 \n", + " Pakistani or British Pakistani 504 68.6 \n", + " Unknown 1323 69.2 \n", + " White + Asian 476 68.7 \n", + " White + Black African 483 67.0 \n", + " White + Black Caribbean 483 72.6 \n", + "imd_categories 1 Most deprived 1715 69.4 \n", + " 2 1729 69.8 \n", + " 3 1701 69.4 \n", + " 4 1680 68.6 \n", + " 5 Least deprived 1680 69.0 \n", + " Unknown 448 66.7 \n", "brand_of_first_dose Moderna 0 0.0 \n", " Oxford-AZ 0 0.0 \n", " Pfizer 7 50.0 \n", - " Unknown 4207 73.8 \n", + " Unknown 8932 76.5 \n", "\n", " total \\\n", "category group \n", - "overall overall 6377 \n", - "sex F 3297 \n", - " M 3080 \n", - "ethnicity_6_groups Black 1071 \n", - " Mixed 1071 \n", - " Other 1120 \n", - " South Asian 1120 \n", - " Unknown 959 \n", - " White 1036 \n", - "ethnicity_16_groups African 336 \n", - " Bangladeshi or British Bangladeshi 329 \n", - " Caribbean 329 \n", - " Chinese 357 \n", - " Other 371 \n", - " Other Asian 336 \n", - " British or Mixed British 329 \n", - " Indian or British Indian 371 \n", - " Irish 315 \n", - " Other Black 301 \n", - " Other White 357 \n", - " Other mixed 364 \n", - " Pakistani or British Pakistani 336 \n", - " Unknown 931 \n", - " White + Asian 315 \n", - " White + Black African 336 \n", - " White + Black Caribbean 350 \n", - "imd_categories 1 Most deprived 1197 \n", - " 2 1225 \n", - " 3 1225 \n", - " 4 1253 \n", - " 5 Least deprived 1141 \n", - " Unknown 329 \n", + "overall overall 12957 \n", + "sex F 6727 \n", + " M 6230 \n", + "ethnicity_6_groups Black 2233 \n", + " Mixed 2205 \n", + " Other 2128 \n", + " South Asian 2254 \n", + " Unknown 1918 \n", + " White 2226 \n", + "ethnicity_16_groups African 700 \n", + " Bangladeshi or British Bangladeshi 686 \n", + " Caribbean 658 \n", + " Chinese 700 \n", + " Other 679 \n", + " Other Asian 714 \n", + " British or Mixed British 714 \n", + " Indian or British Indian 686 \n", + " Irish 644 \n", + " Other Black 693 \n", + " Other White 658 \n", + " Other mixed 693 \n", + " Pakistani or British Pakistani 735 \n", + " Unknown 1911 \n", + " White + Asian 693 \n", + " White + Black African 721 \n", + " White + Black Caribbean 665 \n", + "imd_categories 1 Most deprived 2471 \n", + " 2 2478 \n", + " 3 2450 \n", + " 4 2450 \n", + " 5 Least deprived 2436 \n", + " Unknown 672 \n", "brand_of_first_dose Moderna 0 \n", - " Oxford-AZ 7 \n", + " Oxford-AZ 0 \n", " Pfizer 14 \n", - " Unknown 5698 \n", + " Unknown 11683 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 64.5 \n", - "sex F 64.5 \n", - " M 64.5 \n", - "ethnicity_6_groups Black 61.4 \n", - " Mixed 65.4 \n", - " Other 65.0 \n", - " South Asian 64.4 \n", - " Unknown 65.0 \n", - " White 66.2 \n", - "ethnicity_16_groups African 64.6 \n", - " Bangladeshi or British Bangladeshi 63.8 \n", - " Caribbean 63.8 \n", - " Chinese 66.7 \n", + "overall overall 67.5 \n", + "sex F 67.7 \n", + " M 67.3 \n", + "ethnicity_6_groups Black 66.1 \n", + " Mixed 67.0 \n", + " Other 67.4 \n", + " South Asian 66.5 \n", + " Unknown 69.3 \n", + " White 69.2 \n", + "ethnicity_16_groups African 66.0 \n", + " Bangladeshi or British Bangladeshi 69.4 \n", + " Caribbean 66.0 \n", + " Chinese 67.0 \n", " Other 66.0 \n", - " Other Asian 66.7 \n", - " British or Mixed British 66.0 \n", - " Indian or British Indian 64.2 \n", - " Irish 62.2 \n", - " Other Black 69.8 \n", - " Other White 66.7 \n", - " Other mixed 67.3 \n", - " Pakistani or British Pakistani 62.5 \n", - " Unknown 63.2 \n", - " White + Asian 62.2 \n", - " White + Black African 64.6 \n", - " White + Black Caribbean 64.0 \n", - "imd_categories 1 Most deprived 66.7 \n", - " 2 63.4 \n", - " 3 64.6 \n", - " 4 63.1 \n", - " 5 Least deprived 66.3 \n", - " Unknown 61.7 \n", + " Other Asian 67.6 \n", + " British or Mixed British 65.7 \n", + " Indian or British Indian 67.3 \n", + " Irish 68.5 \n", + " Other Black 66.7 \n", + " Other White 68.1 \n", + " Other mixed 69.7 \n", + " Pakistani or British Pakistani 66.7 \n", + " Unknown 67.8 \n", + " White + Asian 67.7 \n", + " White + Black African 66.0 \n", + " White + Black Caribbean 70.5 \n", + "imd_categories 1 Most deprived 67.7 \n", + " 2 68.1 \n", + " 3 68.0 \n", + " 4 66.9 \n", + " 5 Least deprived 67.8 \n", + " Unknown 65.6 \n", "brand_of_first_dose Moderna NaN \n", - " Oxford-AZ 0.0 \n", + " Oxford-AZ NaN \n", " Pfizer 50.0 \n", - " Unknown 72.0 \n", + " Unknown 74.8 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.8 \n", - "sex F 1.7 \n", - " M 1.9 \n", + "overall overall 1.5 \n", + "sex F 1.6 \n", + " M 1.5 \n", "ethnicity_6_groups Black 1.3 \n", - " Mixed 1.9 \n", - " Other 1.9 \n", + " Mixed 1.3 \n", + " Other 1.4 \n", " South Asian 1.8 \n", - " Unknown 0.7 \n", - " White 2.7 \n", - "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 2.2 \n", - " Caribbean 0.0 \n", - " Chinese 1.9 \n", - " Other 3.8 \n", - " Other Asian 0.0 \n", - " British or Mixed British 2.1 \n", - " Indian or British Indian 1.8 \n", + " Unknown 1.1 \n", + " White 1.2 \n", + "ethnicity_16_groups African 2.0 \n", + " Bangladeshi or British Bangladeshi 2.0 \n", + " Caribbean 2.1 \n", + " Chinese 1.0 \n", + " Other 3.1 \n", + " Other Asian 2.0 \n", + " British or Mixed British 1.0 \n", + " Indian or British Indian 1.1 \n", " Irish 2.2 \n", - " Other Black 2.3 \n", - " Other White 0.0 \n", - " Other mixed 1.9 \n", - " Pakistani or British Pakistani 2.1 \n", - " Unknown 1.5 \n", - " White + Asian 2.2 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 2.0 \n", - "imd_categories 1 Most deprived 1.1 \n", + " Other Black 1.0 \n", + " Other White 2.1 \n", + " Other mixed 1.0 \n", + " Pakistani or British Pakistani 1.9 \n", + " Unknown 1.4 \n", + " White + Asian 1.0 \n", + " White + Black African 1.0 \n", + " White + Black Caribbean 2.1 \n", + "imd_categories 1 Most deprived 1.7 \n", " 2 1.7 \n", - " 3 1.7 \n", + " 3 1.4 \n", " 4 1.7 \n", - " 5 Least deprived 2.4 \n", - " Unknown 2.1 \n", + " 5 Least deprived 1.2 \n", + " Unknown 1.1 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 1.8 \n", + " Unknown 1.7 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 09-Dec \n", - "sex F 15-Dec \n", - " M 03-Dec \n", - "ethnicity_6_groups Black 02-Feb \n", - " Mixed 30-Nov \n", - " Other 02-Dec \n", - " South Asian 09-Dec \n", - " Unknown unknown \n", - " White 01-Nov \n", - "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi 23-Nov \n", - " Caribbean unknown \n", - " Chinese 25-Nov \n", - " Other 15-Oct \n", - " Other Asian unknown \n", - " British or Mixed British 20-Nov \n", - " Indian or British Indian 10-Dec \n", - " Irish 28-Nov \n", - " Other Black 01-Nov \n", - " Other White unknown \n", - " Other mixed 23-Nov \n", - " Pakistani or British Pakistani 01-Dec \n", - " Unknown 04-Jan \n", - " White + Asian 28-Nov \n", - " White + Black African unknown \n", - " White + Black Caribbean 01-Dec \n", - "imd_categories 1 Most deprived 27-Jan \n", - " 2 19-Dec \n", - " 3 14-Dec \n", - " 4 20-Dec \n", - " 5 Least deprived 09-Nov \n", - " Unknown 04-Dec \n", + "overall overall 02-Feb \n", + "sex F 25-Jan \n", + " M 02-Feb \n", + "ethnicity_6_groups Black 25-Feb \n", + " Mixed 20-Feb \n", + " Other 10-Feb \n", + " South Asian 19-Jan \n", + " Unknown 28-Feb \n", + " White 18-Feb \n", + "ethnicity_16_groups African 12-Jan \n", + " Bangladeshi or British Bangladeshi 31-Dec \n", + " Caribbean 08-Jan \n", + " Chinese 30-Mar \n", + " Other 13-Dec \n", + " Other Asian 06-Jan \n", + " British or Mixed British 08-Apr \n", + " Indian or British Indian 13-Mar \n", + " Irish 27-Dec \n", + " Other Black 01-Apr \n", + " Other White 01-Jan \n", + " Other mixed 11-Mar \n", + " Pakistani or British Pakistani 13-Jan \n", + " Unknown 08-Feb \n", + " White + Asian 25-Mar \n", + " White + Black African 06-Apr \n", + " White + Black Caribbean 24-Dec \n", + "imd_categories 1 Most deprived 19-Jan \n", + " 2 18-Jan \n", + " 3 07-Feb \n", + " 4 23-Jan \n", + " 5 Least deprived 26-Feb \n", + " Unknown 24-Mar \n", "brand_of_first_dose Moderna unknown \n", " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 10-Nov " + " Unknown 21-Dec " ] }, "metadata": {}, @@ -32209,7 +32341,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **18-29** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **18-29** population up to 2021-10-27" ], "text/plain": [ "" @@ -32275,295 +32407,295 @@ " \n", " overall\n", " overall\n", - " 4879\n", - " 65.8\n", - " 7420\n", - " 64.0\n", - " 1.8\n", - " 11-Dec\n", + " 10325\n", + " 69.0\n", + " 14966\n", + " 67.4\n", + " 1.6\n", + " 26-Jan\n", " \n", " \n", " sex\n", " F\n", - " 2471\n", - " 65.0\n", - " 3801\n", - " 63.2\n", - " 1.8\n", - " 14-Dec\n", + " 5285\n", + " 68.8\n", + " 7686\n", + " 67.4\n", + " 1.4\n", + " 10-Feb\n", " \n", " \n", " M\n", - " 2401\n", - " 66.5\n", - " 3612\n", - " 64.9\n", - " 1.6\n", - " 19-Dec\n", + " 5033\n", + " 69.1\n", + " 7287\n", + " 67.4\n", + " 1.7\n", + " 21-Jan\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 840\n", - " 65.9\n", - " 1274\n", - " 64.3\n", + " 1799\n", + " 70.4\n", + " 2555\n", + " 68.8\n", " 1.6\n", - " 22-Dec\n", + " 20-Jan\n", " \n", " \n", " Mixed\n", - " 791\n", - " 66.9\n", - " 1183\n", - " 65.1\n", - " 1.8\n", - " 06-Dec\n", + " 1757\n", + " 68.2\n", + " 2576\n", + " 66.8\n", + " 1.4\n", + " 13-Feb\n", " \n", " \n", " Other\n", - " 826\n", - " 64.5\n", - " 1281\n", - " 62.8\n", - " 1.7\n", - " 22-Dec\n", + " 1750\n", + " 68.3\n", + " 2562\n", + " 66.7\n", + " 1.6\n", + " 29-Jan\n", " \n", " \n", " South Asian\n", - " 826\n", - " 65.9\n", - " 1253\n", - " 64.2\n", - " 1.7\n", - " 16-Dec\n", + " 1750\n", + " 69.6\n", + " 2513\n", + " 67.7\n", + " 1.9\n", + " 10-Jan\n", " \n", " \n", " Unknown\n", - " 763\n", - " 66.1\n", - " 1155\n", - " 64.2\n", - " 1.9\n", - " 05-Dec\n", + " 1575\n", + " 70.5\n", + " 2233\n", + " 69.3\n", + " 1.2\n", + " 17-Feb\n", " \n", " \n", " White\n", - " 833\n", - " 65.7\n", - " 1267\n", - " 63.5\n", - " 2.2\n", - " 24-Nov\n", + " 1701\n", + " 67.5\n", + " 2520\n", + " 65.8\n", + " 1.7\n", + " 27-Jan\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 252\n", - " 66.7\n", - " 378\n", - " 64.8\n", - " 1.9\n", - " 02-Dec\n", + " 553\n", + " 70.5\n", + " 784\n", + " 68.8\n", + " 1.7\n", + " 15-Jan\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 245\n", - " 61.4\n", - " 399\n", - " 59.6\n", + " 560\n", + " 69.6\n", + " 805\n", + " 67.8\n", " 1.8\n", - " 28-Dec\n", + " 14-Jan\n", " \n", " \n", " Caribbean\n", - " 224\n", - " 61.5\n", - " 364\n", - " 59.6\n", - " 1.9\n", - " 22-Dec\n", + " 539\n", + " 68.8\n", + " 784\n", + " 67.0\n", + " 1.8\n", + " 17-Jan\n", " \n", " \n", " Chinese\n", - " 266\n", - " 67.9\n", - " 392\n", - " 66.1\n", + " 560\n", + " 69.0\n", + " 812\n", + " 67.2\n", " 1.8\n", - " 02-Dec\n", + " 16-Jan\n", " \n", " \n", " Other\n", - " 224\n", - " 60.4\n", - " 371\n", - " 58.5\n", - " 1.9\n", - " 26-Dec\n", + " 567\n", + " 71.1\n", + " 798\n", + " 69.3\n", + " 1.8\n", + " 08-Jan\n", " \n", " \n", " Other Asian\n", - " 280\n", - " 66.7\n", - " 420\n", - " 63.3\n", - " 3.4\n", - " 25-Oct\n", + " 532\n", + " 67.9\n", + " 784\n", + " 67.0\n", + " 0.9\n", + " 16-Apr\n", " \n", " \n", " British or Mixed British\n", - " 266\n", - " 65.5\n", - " 406\n", - " 65.5\n", - " 0.0\n", - " unknown\n", + " 511\n", + " 67.0\n", + " 763\n", + " 64.2\n", + " 2.8\n", + " 23-Dec\n", " \n", " \n", " Indian or British Indian\n", - " 252\n", - " 64.3\n", - " 392\n", - " 62.5\n", - " 1.8\n", - " 16-Dec\n", + " 546\n", + " 66.1\n", + " 826\n", + " 65.3\n", + " 0.8\n", + " unknown\n", " \n", " \n", " Irish\n", - " 273\n", - " 66.1\n", - " 413\n", - " 64.4\n", - " 1.7\n", - " 15-Dec\n", + " 553\n", + " 71.8\n", + " 770\n", + " 70.0\n", + " 1.8\n", + " 05-Jan\n", " \n", " \n", " Other Black\n", - " 280\n", - " 64.5\n", - " 434\n", - " 62.9\n", - " 1.6\n", - " 28-Dec\n", + " 553\n", + " 69.3\n", + " 798\n", + " 67.5\n", + " 1.8\n", + " 15-Jan\n", " \n", " \n", " Other White\n", - " 273\n", - " 66.1\n", - " 413\n", - " 62.7\n", - " 3.4\n", - " 27-Oct\n", + " 539\n", + " 68.1\n", + " 791\n", + " 66.4\n", + " 1.7\n", + " 25-Jan\n", " \n", " \n", " Other mixed\n", - " 273\n", - " 68.4\n", - " 399\n", - " 66.7\n", - " 1.7\n", - " 05-Dec\n", + " 560\n", + " 70.8\n", + " 791\n", + " 69.0\n", + " 1.8\n", + " 09-Jan\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 266\n", - " 66.7\n", - " 399\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 532\n", + " 69.7\n", + " 763\n", + " 67.9\n", + " 1.8\n", + " 13-Jan\n", " \n", " \n", " Unknown\n", - " 742\n", - " 67.5\n", - " 1099\n", - " 65.0\n", - " 2.5\n", - " 10-Nov\n", + " 1561\n", + " 68.6\n", + " 2275\n", + " 67.4\n", + " 1.2\n", + " 28-Feb\n", " \n", " \n", " White + Asian\n", - " 252\n", - " 67.9\n", - " 371\n", - " 64.2\n", - " 3.7\n", - " 19-Oct\n", + " 560\n", + " 67.8\n", + " 826\n", + " 66.1\n", + " 1.7\n", + " 26-Jan\n", " \n", " \n", " White + Black African\n", - " 280\n", - " 65.6\n", - " 427\n", - " 65.6\n", - " 0.0\n", + " 532\n", + " 66.1\n", + " 805\n", + " 65.2\n", + " 0.9\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 231\n", - " 66.0\n", - " 350\n", - " 64.0\n", - " 2.0\n", - " 01-Dec\n", + " 560\n", + " 70.8\n", + " 791\n", + " 69.0\n", + " 1.8\n", + " 09-Jan\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 938\n", - " 64.7\n", - " 1449\n", - " 62.8\n", - " 1.9\n", - " 10-Dec\n", + " 2002\n", + " 68.1\n", + " 2940\n", + " 66.7\n", + " 1.4\n", + " 13-Feb\n", " \n", " \n", " 2\n", - " 910\n", - " 65.0\n", - " 1400\n", - " 63.5\n", - " 1.5\n", - " 02-Jan\n", + " 1953\n", + " 68.9\n", + " 2835\n", + " 67.7\n", + " 1.2\n", + " 27-Feb\n", " \n", " \n", " 3\n", - " 931\n", - " 65.5\n", - " 1421\n", - " 64.0\n", - " 1.5\n", - " 31-Dec\n", + " 1946\n", + " 68.5\n", + " 2842\n", + " 66.7\n", + " 1.8\n", + " 18-Jan\n", " \n", " \n", " 4\n", - " 889\n", - " 66.8\n", - " 1330\n", - " 64.7\n", - " 2.1\n", - " 24-Nov\n", + " 1988\n", + " 69.6\n", + " 2856\n", + " 68.4\n", + " 1.2\n", + " 23-Feb\n", " \n", " \n", " 5 Least deprived\n", - " 959\n", - " 66.2\n", - " 1449\n", - " 64.3\n", - " 1.9\n", - " 04-Dec\n", + " 1946\n", + " 70.0\n", + " 2779\n", + " 68.0\n", + " 2.0\n", + " 05-Jan\n", " \n", " \n", " Unknown\n", - " 252\n", - " 67.9\n", - " 371\n", + " 490\n", + " 68.0\n", + " 721\n", " 66.0\n", - " 1.9\n", - " 28-Nov\n", + " 2.0\n", + " 12-Jan\n", " \n", " \n", " brand_of_first_dose\n", @@ -32577,30 +32709,30 @@ " \n", " \n", " Oxford-AZ\n", - " 0\n", - " 0.0\n", " 7\n", - " 0.0\n", + " 50.0\n", + " 14\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Pfizer\n", - " 7\n", - " 50.0\n", " 14\n", - " 50.0\n", + " 66.7\n", + " 21\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 4858\n", - " 72.7\n", - " 6678\n", - " 70.8\n", - " 1.9\n", - " 10-Nov\n", + " 10297\n", + " 76.9\n", + " 13398\n", + " 75.1\n", + " 1.8\n", + " 16-Dec\n", " \n", " \n", "\n", @@ -32609,198 +32741,198 @@ "text/plain": [ " vaccinated percent \\\n", "category group \n", - "overall overall 4879 65.8 \n", - "sex F 2471 65.0 \n", - " M 2401 66.5 \n", - "ethnicity_6_groups Black 840 65.9 \n", - " Mixed 791 66.9 \n", - " Other 826 64.5 \n", - " South Asian 826 65.9 \n", - " Unknown 763 66.1 \n", - " White 833 65.7 \n", - "ethnicity_16_groups African 252 66.7 \n", - " Bangladeshi or British Bangladeshi 245 61.4 \n", - " Caribbean 224 61.5 \n", - " Chinese 266 67.9 \n", - " Other 224 60.4 \n", - " Other Asian 280 66.7 \n", - " British or Mixed British 266 65.5 \n", - " Indian or British Indian 252 64.3 \n", - " Irish 273 66.1 \n", - " Other Black 280 64.5 \n", - " Other White 273 66.1 \n", - " Other mixed 273 68.4 \n", - " Pakistani or British Pakistani 266 66.7 \n", - " Unknown 742 67.5 \n", - " White + Asian 252 67.9 \n", - " White + Black African 280 65.6 \n", - " White + Black Caribbean 231 66.0 \n", - "imd_categories 1 Most deprived 938 64.7 \n", - " 2 910 65.0 \n", - " 3 931 65.5 \n", - " 4 889 66.8 \n", - " 5 Least deprived 959 66.2 \n", - " Unknown 252 67.9 \n", + "overall overall 10325 69.0 \n", + "sex F 5285 68.8 \n", + " M 5033 69.1 \n", + "ethnicity_6_groups Black 1799 70.4 \n", + " Mixed 1757 68.2 \n", + " Other 1750 68.3 \n", + " South Asian 1750 69.6 \n", + " Unknown 1575 70.5 \n", + " White 1701 67.5 \n", + "ethnicity_16_groups African 553 70.5 \n", + " Bangladeshi or British Bangladeshi 560 69.6 \n", + " Caribbean 539 68.8 \n", + " Chinese 560 69.0 \n", + " Other 567 71.1 \n", + " Other Asian 532 67.9 \n", + " British or Mixed British 511 67.0 \n", + " Indian or British Indian 546 66.1 \n", + " Irish 553 71.8 \n", + " Other Black 553 69.3 \n", + " Other White 539 68.1 \n", + " Other mixed 560 70.8 \n", + " Pakistani or British Pakistani 532 69.7 \n", + " Unknown 1561 68.6 \n", + " White + Asian 560 67.8 \n", + " White + Black African 532 66.1 \n", + " White + Black Caribbean 560 70.8 \n", + "imd_categories 1 Most deprived 2002 68.1 \n", + " 2 1953 68.9 \n", + " 3 1946 68.5 \n", + " 4 1988 69.6 \n", + " 5 Least deprived 1946 70.0 \n", + " Unknown 490 68.0 \n", "brand_of_first_dose Moderna 0 0.0 \n", - " Oxford-AZ 0 0.0 \n", - " Pfizer 7 50.0 \n", - " Unknown 4858 72.7 \n", + " Oxford-AZ 7 50.0 \n", + " Pfizer 14 66.7 \n", + " Unknown 10297 76.9 \n", "\n", " total \\\n", "category group \n", - "overall overall 7420 \n", - "sex F 3801 \n", - " M 3612 \n", - "ethnicity_6_groups Black 1274 \n", - " Mixed 1183 \n", - " Other 1281 \n", - " South Asian 1253 \n", - " Unknown 1155 \n", - " White 1267 \n", - "ethnicity_16_groups African 378 \n", - " Bangladeshi or British Bangladeshi 399 \n", - " Caribbean 364 \n", - " Chinese 392 \n", - " Other 371 \n", - " Other Asian 420 \n", - " British or Mixed British 406 \n", - " Indian or British Indian 392 \n", - " Irish 413 \n", - " Other Black 434 \n", - " Other White 413 \n", - " Other mixed 399 \n", - " Pakistani or British Pakistani 399 \n", - " Unknown 1099 \n", - " White + Asian 371 \n", - " White + Black African 427 \n", - " White + Black Caribbean 350 \n", - "imd_categories 1 Most deprived 1449 \n", - " 2 1400 \n", - " 3 1421 \n", - " 4 1330 \n", - " 5 Least deprived 1449 \n", - " Unknown 371 \n", + "overall overall 14966 \n", + "sex F 7686 \n", + " M 7287 \n", + "ethnicity_6_groups Black 2555 \n", + " Mixed 2576 \n", + " Other 2562 \n", + " South Asian 2513 \n", + " Unknown 2233 \n", + " White 2520 \n", + "ethnicity_16_groups African 784 \n", + " Bangladeshi or British Bangladeshi 805 \n", + " Caribbean 784 \n", + " Chinese 812 \n", + " Other 798 \n", + " Other Asian 784 \n", + " British or Mixed British 763 \n", + " Indian or British Indian 826 \n", + " Irish 770 \n", + " Other Black 798 \n", + " Other White 791 \n", + " Other mixed 791 \n", + " Pakistani or British Pakistani 763 \n", + " Unknown 2275 \n", + " White + Asian 826 \n", + " White + Black African 805 \n", + " White + Black Caribbean 791 \n", + "imd_categories 1 Most deprived 2940 \n", + " 2 2835 \n", + " 3 2842 \n", + " 4 2856 \n", + " 5 Least deprived 2779 \n", + " Unknown 721 \n", "brand_of_first_dose Moderna 0 \n", - " Oxford-AZ 7 \n", - " Pfizer 14 \n", - " Unknown 6678 \n", + " Oxford-AZ 14 \n", + " Pfizer 21 \n", + " Unknown 13398 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 64.0 \n", - "sex F 63.2 \n", - " M 64.9 \n", - "ethnicity_6_groups Black 64.3 \n", - " Mixed 65.1 \n", - " Other 62.8 \n", - " South Asian 64.2 \n", - " Unknown 64.2 \n", - " White 63.5 \n", - "ethnicity_16_groups African 64.8 \n", - " Bangladeshi or British Bangladeshi 59.6 \n", - " Caribbean 59.6 \n", - " Chinese 66.1 \n", - " Other 58.5 \n", - " Other Asian 63.3 \n", - " British or Mixed British 65.5 \n", - " Indian or British Indian 62.5 \n", - " Irish 64.4 \n", - " Other Black 62.9 \n", - " Other White 62.7 \n", - " Other mixed 66.7 \n", - " Pakistani or British Pakistani 66.7 \n", - " Unknown 65.0 \n", - " White + Asian 64.2 \n", - " White + Black African 65.6 \n", - " White + Black Caribbean 64.0 \n", - "imd_categories 1 Most deprived 62.8 \n", - " 2 63.5 \n", - " 3 64.0 \n", - " 4 64.7 \n", - " 5 Least deprived 64.3 \n", + "overall overall 67.4 \n", + "sex F 67.4 \n", + " M 67.4 \n", + "ethnicity_6_groups Black 68.8 \n", + " Mixed 66.8 \n", + " Other 66.7 \n", + " South Asian 67.7 \n", + " Unknown 69.3 \n", + " White 65.8 \n", + "ethnicity_16_groups African 68.8 \n", + " Bangladeshi or British Bangladeshi 67.8 \n", + " Caribbean 67.0 \n", + " Chinese 67.2 \n", + " Other 69.3 \n", + " Other Asian 67.0 \n", + " British or Mixed British 64.2 \n", + " Indian or British Indian 65.3 \n", + " Irish 70.0 \n", + " Other Black 67.5 \n", + " Other White 66.4 \n", + " Other mixed 69.0 \n", + " Pakistani or British Pakistani 67.9 \n", + " Unknown 67.4 \n", + " White + Asian 66.1 \n", + " White + Black African 65.2 \n", + " White + Black Caribbean 69.0 \n", + "imd_categories 1 Most deprived 66.7 \n", + " 2 67.7 \n", + " 3 66.7 \n", + " 4 68.4 \n", + " 5 Least deprived 68.0 \n", " Unknown 66.0 \n", "brand_of_first_dose Moderna NaN \n", - " Oxford-AZ 0.0 \n", - " Pfizer 50.0 \n", - " Unknown 70.8 \n", + " Oxford-AZ 50.0 \n", + " Pfizer 66.7 \n", + " Unknown 75.1 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.8 \n", - "sex F 1.8 \n", - " M 1.6 \n", + "overall overall 1.6 \n", + "sex F 1.4 \n", + " M 1.7 \n", "ethnicity_6_groups Black 1.6 \n", - " Mixed 1.8 \n", - " Other 1.7 \n", - " South Asian 1.7 \n", - " Unknown 1.9 \n", - " White 2.2 \n", - "ethnicity_16_groups African 1.9 \n", + " Mixed 1.4 \n", + " Other 1.6 \n", + " South Asian 1.9 \n", + " Unknown 1.2 \n", + " White 1.7 \n", + "ethnicity_16_groups African 1.7 \n", " Bangladeshi or British Bangladeshi 1.8 \n", - " Caribbean 1.9 \n", + " Caribbean 1.8 \n", " Chinese 1.8 \n", - " Other 1.9 \n", - " Other Asian 3.4 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 1.8 \n", - " Irish 1.7 \n", - " Other Black 1.6 \n", - " Other White 3.4 \n", - " Other mixed 1.7 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 2.5 \n", - " White + Asian 3.7 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 2.0 \n", - "imd_categories 1 Most deprived 1.9 \n", - " 2 1.5 \n", - " 3 1.5 \n", - " 4 2.1 \n", - " 5 Least deprived 1.9 \n", - " Unknown 1.9 \n", + " Other 1.8 \n", + " Other Asian 0.9 \n", + " British or Mixed British 2.8 \n", + " Indian or British Indian 0.8 \n", + " Irish 1.8 \n", + " Other Black 1.8 \n", + " Other White 1.7 \n", + " Other mixed 1.8 \n", + " Pakistani or British Pakistani 1.8 \n", + " Unknown 1.2 \n", + " White + Asian 1.7 \n", + " White + Black African 0.9 \n", + " White + Black Caribbean 1.8 \n", + "imd_categories 1 Most deprived 1.4 \n", + " 2 1.2 \n", + " 3 1.8 \n", + " 4 1.2 \n", + " 5 Least deprived 2.0 \n", + " Unknown 2.0 \n", "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 0.0 \n", " Pfizer 0.0 \n", - " Unknown 1.9 \n", + " Unknown 1.8 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 11-Dec \n", - "sex F 14-Dec \n", - " M 19-Dec \n", - "ethnicity_6_groups Black 22-Dec \n", - " Mixed 06-Dec \n", - " Other 22-Dec \n", - " South Asian 16-Dec \n", - " Unknown 05-Dec \n", - " White 24-Nov \n", - "ethnicity_16_groups African 02-Dec \n", - " Bangladeshi or British Bangladeshi 28-Dec \n", - " Caribbean 22-Dec \n", - " Chinese 02-Dec \n", - " Other 26-Dec \n", - " Other Asian 25-Oct \n", - " British or Mixed British unknown \n", - " Indian or British Indian 16-Dec \n", - " Irish 15-Dec \n", - " Other Black 28-Dec \n", - " Other White 27-Oct \n", - " Other mixed 05-Dec \n", - " Pakistani or British Pakistani unknown \n", - " Unknown 10-Nov \n", - " White + Asian 19-Oct \n", + "overall overall 26-Jan \n", + "sex F 10-Feb \n", + " M 21-Jan \n", + "ethnicity_6_groups Black 20-Jan \n", + " Mixed 13-Feb \n", + " Other 29-Jan \n", + " South Asian 10-Jan \n", + " Unknown 17-Feb \n", + " White 27-Jan \n", + "ethnicity_16_groups African 15-Jan \n", + " Bangladeshi or British Bangladeshi 14-Jan \n", + " Caribbean 17-Jan \n", + " Chinese 16-Jan \n", + " Other 08-Jan \n", + " Other Asian 16-Apr \n", + " British or Mixed British 23-Dec \n", + " Indian or British Indian unknown \n", + " Irish 05-Jan \n", + " Other Black 15-Jan \n", + " Other White 25-Jan \n", + " Other mixed 09-Jan \n", + " Pakistani or British Pakistani 13-Jan \n", + " Unknown 28-Feb \n", + " White + Asian 26-Jan \n", " White + Black African unknown \n", - " White + Black Caribbean 01-Dec \n", - "imd_categories 1 Most deprived 10-Dec \n", - " 2 02-Jan \n", - " 3 31-Dec \n", - " 4 24-Nov \n", - " 5 Least deprived 04-Dec \n", - " Unknown 28-Nov \n", + " White + Black Caribbean 09-Jan \n", + "imd_categories 1 Most deprived 13-Feb \n", + " 2 27-Feb \n", + " 3 18-Jan \n", + " 4 23-Feb \n", + " 5 Least deprived 05-Jan \n", + " Unknown 12-Jan \n", "brand_of_first_dose Moderna unknown \n", " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 10-Nov " + " Unknown 16-Dec " ] }, "metadata": {}, @@ -32829,7 +32961,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (first dose 14w ago) among **16-17** population up to 2021-09-08" + "## COVID vaccination rollout (first dose 14w ago) among **16-17** population up to 2021-10-27" ], "text/plain": [ "" @@ -32895,149 +33027,149 @@ " \n", " overall\n", " overall\n", - " 6902\n", - " 66.7\n", - " 10346\n", - " 65.2\n", - " 1.5\n", - " 25-Dec\n", + " 14322\n", + " 69.4\n", + " 20636\n", + " 67.8\n", + " 1.6\n", + " 25-Jan\n", " \n", " \n", " sex\n", " F\n", - " 3507\n", - " 66.3\n", - " 5292\n", - " 64.9\n", - " 1.4\n", - " 04-Jan\n", + " 7266\n", + " 69.1\n", + " 10514\n", + " 67.8\n", + " 1.3\n", + " 16-Feb\n", " \n", " \n", " M\n", - " 3395\n", - " 67.3\n", - " 5047\n", - " 65.6\n", - " 1.7\n", - " 10-Dec\n", + " 7049\n", + " 69.7\n", + " 10115\n", + " 67.9\n", + " 1.8\n", + " 13-Jan\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 1176\n", - " 66.9\n", - " 1757\n", - " 65.7\n", - " 1.2\n", - " 20-Jan\n", + " 2415\n", + " 69.0\n", + " 3500\n", + " 67.0\n", + " 2.0\n", + " 08-Jan\n", " \n", " \n", " Mixed\n", - " 1169\n", - " 65.7\n", - " 1778\n", - " 64.6\n", - " 1.1\n", - " 09-Feb\n", + " 2436\n", + " 68.6\n", + " 3549\n", + " 66.9\n", + " 1.7\n", + " 23-Jan\n", " \n", " \n", " Other\n", - " 1176\n", - " 67.5\n", - " 1743\n", - " 65.9\n", - " 1.6\n", - " 15-Dec\n", + " 2457\n", + " 69.6\n", + " 3528\n", + " 68.3\n", + " 1.3\n", + " 13-Feb\n", " \n", " \n", " South Asian\n", - " 1141\n", - " 65.7\n", - " 1736\n", - " 64.1\n", - " 1.6\n", - " 23-Dec\n", + " 2457\n", + " 69.2\n", + " 3549\n", + " 68.0\n", + " 1.2\n", + " 25-Feb\n", " \n", " \n", " Unknown\n", - " 1057\n", - " 67.1\n", - " 1575\n", - " 65.3\n", - " 1.8\n", - " 06-Dec\n", + " 2149\n", + " 70.9\n", + " 3031\n", + " 69.5\n", + " 1.4\n", + " 30-Jan\n", " \n", " \n", " White\n", - " 1183\n", - " 67.6\n", - " 1750\n", - " 66.4\n", - " 1.2\n", - " 16-Jan\n", + " 2401\n", + " 69.2\n", + " 3472\n", + " 67.7\n", + " 1.5\n", + " 01-Feb\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 1239\n", - " 66.5\n", - " 1862\n", - " 65.0\n", - " 1.5\n", - " 26-Dec\n", + " 2730\n", + " 68.7\n", + " 3976\n", + " 66.9\n", + " 1.8\n", + " 17-Jan\n", " \n", " \n", " 2\n", - " 1351\n", - " 68.2\n", - " 1981\n", - " 66.1\n", - " 2.1\n", - " 19-Nov\n", + " 2660\n", + " 68.5\n", + " 3885\n", + " 67.2\n", + " 1.3\n", + " 19-Feb\n", " \n", " \n", " 3\n", - " 1316\n", - " 65.7\n", - " 2002\n", - " 64.3\n", - " 1.4\n", - " 07-Jan\n", + " 2786\n", + " 70.8\n", + " 3934\n", + " 69.2\n", + " 1.6\n", + " 19-Jan\n", " \n", " \n", " 4\n", - " 1337\n", - " 66.1\n", - " 2023\n", - " 64.7\n", - " 1.4\n", - " 05-Jan\n", + " 2702\n", + " 68.8\n", + " 3927\n", + " 67.0\n", + " 1.8\n", + " 17-Jan\n", " \n", " \n", " 5 Least deprived\n", - " 1309\n", - " 66.8\n", - " 1960\n", - " 65.4\n", + " 2723\n", + " 70.3\n", + " 3871\n", + " 68.9\n", " 1.4\n", - " 02-Jan\n", + " 02-Feb\n", " \n", " \n", " Unknown\n", - " 350\n", - " 67.6\n", - " 518\n", - " 66.2\n", + " 721\n", + " 68.7\n", + " 1050\n", + " 67.3\n", " 1.4\n", - " 29-Dec\n", + " 10-Feb\n", " \n", " \n", " brand_of_first_dose\n", " Moderna\n", " 0\n", " 0.0\n", - " 0\n", - " NaN\n", + " 7\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", @@ -33052,21 +33184,21 @@ " \n", " \n", " Pfizer\n", - " 14\n", + " 28\n", " 66.7\n", - " 21\n", + " 42\n", " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 6874\n", - " 73.8\n", - " 9317\n", - " 72.1\n", + " 14280\n", + " 77.2\n", + " 18487\n", + " 75.5\n", " 1.7\n", - " 13-Nov\n", + " 18-Dec\n", " \n", " \n", "\n", @@ -33075,63 +33207,63 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 6902 66.7 10346 \n", - "sex F 3507 66.3 5292 \n", - " M 3395 67.3 5047 \n", - "ethnicity_6_groups Black 1176 66.9 1757 \n", - " Mixed 1169 65.7 1778 \n", - " Other 1176 67.5 1743 \n", - " South Asian 1141 65.7 1736 \n", - " Unknown 1057 67.1 1575 \n", - " White 1183 67.6 1750 \n", - "imd_categories 1 Most deprived 1239 66.5 1862 \n", - " 2 1351 68.2 1981 \n", - " 3 1316 65.7 2002 \n", - " 4 1337 66.1 2023 \n", - " 5 Least deprived 1309 66.8 1960 \n", - " Unknown 350 67.6 518 \n", - "brand_of_first_dose Moderna 0 0.0 0 \n", + "overall overall 14322 69.4 20636 \n", + "sex F 7266 69.1 10514 \n", + " M 7049 69.7 10115 \n", + "ethnicity_6_groups Black 2415 69.0 3500 \n", + " Mixed 2436 68.6 3549 \n", + " Other 2457 69.6 3528 \n", + " South Asian 2457 69.2 3549 \n", + " Unknown 2149 70.9 3031 \n", + " White 2401 69.2 3472 \n", + "imd_categories 1 Most deprived 2730 68.7 3976 \n", + " 2 2660 68.5 3885 \n", + " 3 2786 70.8 3934 \n", + " 4 2702 68.8 3927 \n", + " 5 Least deprived 2723 70.3 3871 \n", + " Unknown 721 68.7 1050 \n", + "brand_of_first_dose Moderna 0 0.0 7 \n", " Oxford-AZ 7 50.0 14 \n", - " Pfizer 14 66.7 21 \n", - " Unknown 6874 73.8 9317 \n", + " Pfizer 28 66.7 42 \n", + " Unknown 14280 77.2 18487 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 65.2 \n", - "sex F 64.9 \n", - " M 65.6 \n", - "ethnicity_6_groups Black 65.7 \n", - " Mixed 64.6 \n", - " Other 65.9 \n", - " South Asian 64.1 \n", - " Unknown 65.3 \n", - " White 66.4 \n", - "imd_categories 1 Most deprived 65.0 \n", - " 2 66.1 \n", - " 3 64.3 \n", - " 4 64.7 \n", - " 5 Least deprived 65.4 \n", - " Unknown 66.2 \n", - "brand_of_first_dose Moderna NaN \n", + "overall overall 67.8 \n", + "sex F 67.8 \n", + " M 67.9 \n", + "ethnicity_6_groups Black 67.0 \n", + " Mixed 66.9 \n", + " Other 68.3 \n", + " South Asian 68.0 \n", + " Unknown 69.5 \n", + " White 67.7 \n", + "imd_categories 1 Most deprived 66.9 \n", + " 2 67.2 \n", + " 3 69.2 \n", + " 4 67.0 \n", + " 5 Least deprived 68.9 \n", + " Unknown 67.3 \n", + "brand_of_first_dose Moderna 0.0 \n", " Oxford-AZ 50.0 \n", " Pfizer 66.7 \n", - " Unknown 72.1 \n", + " Unknown 75.5 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.5 \n", - "sex F 1.4 \n", - " M 1.7 \n", - "ethnicity_6_groups Black 1.2 \n", - " Mixed 1.1 \n", - " Other 1.6 \n", - " South Asian 1.6 \n", - " Unknown 1.8 \n", - " White 1.2 \n", - "imd_categories 1 Most deprived 1.5 \n", - " 2 2.1 \n", - " 3 1.4 \n", - " 4 1.4 \n", + "overall overall 1.6 \n", + "sex F 1.3 \n", + " M 1.8 \n", + "ethnicity_6_groups Black 2.0 \n", + " Mixed 1.7 \n", + " Other 1.3 \n", + " South Asian 1.2 \n", + " Unknown 1.4 \n", + " White 1.5 \n", + "imd_categories 1 Most deprived 1.8 \n", + " 2 1.3 \n", + " 3 1.6 \n", + " 4 1.8 \n", " 5 Least deprived 1.4 \n", " Unknown 1.4 \n", "brand_of_first_dose Moderna 0.0 \n", @@ -33141,25 +33273,25 @@ "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 25-Dec \n", - "sex F 04-Jan \n", - " M 10-Dec \n", - "ethnicity_6_groups Black 20-Jan \n", - " Mixed 09-Feb \n", - " Other 15-Dec \n", - " South Asian 23-Dec \n", - " Unknown 06-Dec \n", - " White 16-Jan \n", - "imd_categories 1 Most deprived 26-Dec \n", - " 2 19-Nov \n", - " 3 07-Jan \n", - " 4 05-Jan \n", - " 5 Least deprived 02-Jan \n", - " Unknown 29-Dec \n", + "overall overall 25-Jan \n", + "sex F 16-Feb \n", + " M 13-Jan \n", + "ethnicity_6_groups Black 08-Jan \n", + " Mixed 23-Jan \n", + " Other 13-Feb \n", + " South Asian 25-Feb \n", + " Unknown 30-Jan \n", + " White 01-Feb \n", + "imd_categories 1 Most deprived 17-Jan \n", + " 2 19-Feb \n", + " 3 19-Jan \n", + " 4 17-Jan \n", + " 5 Least deprived 02-Feb \n", + " Unknown 10-Feb \n", "brand_of_first_dose Moderna unknown \n", " Oxford-AZ unknown \n", " Pfizer unknown \n", - " Unknown 13-Nov " + " Unknown 18-Dec " ] }, "metadata": {}, @@ -33175,6 +33307,8 @@ } ], "source": [ + "\n", + "\n", "# latest date of 14 weeks ago is entered as the latest_date when calculating cumulative sums below.\n", "\n", "# Seperately, we also ensure that first dose was dated after the start of the campaign, \n", @@ -33196,25 +33330,23 @@ "\n", "create_detailed_summary_uptake(summarised_data_dict_14w, formatted_latest_date=date_14w, \n", " groups=groups,\n", - " savepath=savepath, vaccine_type=\"first_dose_14w_ago\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Booster/third doses" + " savepath=savepath, vaccine_type=\"first_dose_14w_ago\")\n", + "\n", + "\n", + "# # Booster/third doses" ] }, { "cell_type": "code", - "execution_count": 34, - "metadata": {}, + "execution_count": 35, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [ { "data": { "text/markdown": [ - "08 Sep 2021" + "27 Oct 2021" ], "text/plain": [ "" @@ -33225,6 +33357,8 @@ } ], "source": [ + "\n", + "\n", "# Only want to count third doses where the second dose was given some period of time ago.\n", "# This period of time is defined by the variables booster_delay_number and booster_delay_unit.\n", "\n", @@ -33233,18 +33367,19 @@ "booster_delay_unit_short = abbreviate_time_period( booster_delay_unit )\n", "\n", "date_3rdDUE, formatted_date_3rdDUE = subtract_from_date(s=df[\"covid_vacc_date\"], unit=booster_delay_unit, number=booster_delay_number,\n", - " description=\"latest_date_of_second_dose_for_due_third_doses\")\n", - "\n" + " description=\"latest_date_of_second_dose_for_due_third_doses\")" ] }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 36, "metadata": { "lines_to_next_cell": 2 }, "outputs": [], "source": [ + "\n", + "\n", "# filtering for third doses that are \"due\"\n", "\n", "df_t = df.copy()\n", @@ -33259,8 +33394,10 @@ }, { "cell_type": "code", - "execution_count": 36, - "metadata": {}, + "execution_count": 37, + "metadata": { + "lines_to_next_cell": 2 + }, "outputs": [ { "name": "stderr", @@ -33291,7 +33428,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (third dose) among **80+** population up to 15 Dec 2021" + "## COVID vaccination rollout (third dose) among **80+** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -33357,220 +33494,238 @@ " \n", " overall\n", " overall\n", - " 126\n", - " 5.9\n", - " 2142\n", - " 5.6\n", - " 0.3\n", + " 252\n", + " 6.0\n", + " 4221\n", + " 5.8\n", + " 0.2\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 70\n", - " 6.2\n", - " 1127\n", - " 5.6\n", - " 0.6\n", + " 119\n", + " 5.5\n", + " 2177\n", + " 5.5\n", + " 0.0\n", " unknown\n", " \n", " \n", " M\n", - " 56\n", - " 5.5\n", - " 1015\n", - " 5.5\n", - " 0.0\n", + " 133\n", + " 6.5\n", + " 2044\n", + " 6.2\n", + " 0.3\n", " unknown\n", " \n", " \n", - " ageband_5yr\n", - " 0-15\n", + " ageband_5yr\n", + " 0\n", " 0\n", " 0.0\n", - " 112\n", + " 70\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", + " 0-15\n", + " 14\n", + " 5.4\n", + " 259\n", + " 5.4\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", " 16-17\n", " 7\n", - " 5.0\n", - " 140\n", - " 5.0\n", + " 2.9\n", + " 245\n", + " 2.9\n", " 0.0\n", " unknown\n", " \n", " \n", " 18-29\n", - " 7\n", + " 14\n", " 5.3\n", - " 133\n", - " 0.0\n", + " 266\n", " 5.3\n", - " 05-Apr\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 30-34\n", - " 7\n", - " 5.0\n", - " 140\n", - " 5.0\n", + " 21\n", + " 7.7\n", + " 273\n", + " 7.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 35-39\n", - " 14\n", - " 9.5\n", - " 147\n", - " 4.8\n", - " 4.7\n", - " 13-Apr\n", + " 21\n", + " 7.9\n", + " 266\n", + " 7.9\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 40-44\n", - " 7\n", - " 4.8\n", - " 147\n", - " 4.8\n", + " 21\n", + " 7.7\n", + " 273\n", + " 7.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 45-49\n", - " 0\n", - " 0.0\n", - " 133\n", - " 0.0\n", + " 14\n", + " 5.0\n", + " 280\n", + " 5.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 50-54\n", - " 7\n", - " 4.5\n", - " 154\n", - " 4.5\n", + " 14\n", + " 5.4\n", + " 259\n", + " 5.4\n", " 0.0\n", " unknown\n", " \n", " \n", " 55-59\n", - " 7\n", - " 4.5\n", - " 154\n", - " 4.5\n", + " 14\n", + " 4.7\n", + " 301\n", + " 4.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 60-64\n", - " 0\n", - " 0.0\n", - " 126\n", - " 0.0\n", - " 0.0\n", + " 21\n", + " 7.9\n", + " 266\n", + " 5.3\n", + " 2.6\n", " unknown\n", " \n", " \n", " 65-69\n", - " 7\n", - " 5.0\n", - " 140\n", - " 5.0\n", + " 21\n", + " 7.5\n", + " 280\n", + " 7.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-74\n", - " 7\n", - " 5.0\n", - " 140\n", - " 5.0\n", + " 14\n", + " 4.8\n", + " 294\n", + " 4.8\n", " 0.0\n", " unknown\n", " \n", " \n", " 75-79\n", - " 7\n", - " 5.3\n", - " 133\n", - " 5.3\n", + " 14\n", + " 5.0\n", + " 280\n", + " 5.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 80-84\n", " 14\n", - " 10.0\n", - " 140\n", - " 10.0\n", + " 5.1\n", + " 273\n", + " 5.1\n", " 0.0\n", " unknown\n", " \n", " \n", " 85-89\n", - " 7\n", - " 4.5\n", - " 154\n", - " 4.5\n", + " 14\n", + " 4.8\n", + " 294\n", + " 4.8\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " 90+\n", + " 0\n", + " 0.0\n", + " 35\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 14\n", - " 3.9\n", - " 357\n", - " 3.9\n", + " 42\n", + " 5.7\n", + " 735\n", + " 5.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Mixed\n", - " 21\n", - " 6.0\n", - " 350\n", + " 35\n", + " 5.0\n", + " 700\n", " 4.0\n", - " 2.0\n", + " 1.0\n", " unknown\n", " \n", " \n", " Other\n", - " 14\n", - " 4.2\n", - " 336\n", - " 4.2\n", + " 49\n", + " 6.7\n", + " 728\n", + " 6.7\n", " 0.0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 28\n", - " 7.7\n", - " 364\n", - " 7.7\n", - " 0.0\n", + " 42\n", + " 5.6\n", + " 749\n", + " 4.7\n", + " 0.9\n", " unknown\n", " \n", " \n", " Unknown\n", - " 28\n", - " 8.2\n", - " 343\n", - " 8.2\n", + " 42\n", + " 6.9\n", + " 609\n", + " 6.9\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", - " 21\n", - " 5.4\n", - " 392\n", - " 5.4\n", + " 42\n", + " 5.9\n", + " 714\n", + " 5.9\n", " 0.0\n", " unknown\n", " \n", @@ -33578,237 +33733,237 @@ " ethnicity_16_groups\n", " African\n", " 7\n", - " 6.7\n", - " 105\n", - " 6.7\n", + " 3.2\n", + " 217\n", + " 3.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 7\n", - " 5.9\n", - " 119\n", - " 5.9\n", + " 14\n", + " 6.7\n", + " 210\n", + " 6.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 0\n", - " 0.0\n", - " 98\n", - " 0.0\n", + " 14\n", + " 6.5\n", + " 217\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Chinese\n", - " 0\n", - " 0.0\n", - " 105\n", - " 0.0\n", + " 14\n", + " 6.5\n", + " 217\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 7\n", - " 6.2\n", - " 112\n", + " 21\n", + " 8.8\n", + " 238\n", + " 8.8\n", " 0.0\n", - " 6.2\n", - " 19-Mar\n", + " unknown\n", " \n", " \n", " Other Asian\n", - " 7\n", - " 6.2\n", - " 112\n", - " 6.2\n", + " 14\n", + " 6.7\n", + " 210\n", + " 6.7\n", " 0.0\n", " unknown\n", " \n", " \n", " British or Mixed British\n", " 14\n", - " 10.5\n", - " 133\n", - " 10.5\n", + " 6.5\n", + " 217\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 0\n", - " 0.0\n", - " 105\n", - " 0.0\n", + " 14\n", + " 6.2\n", + " 224\n", + " 6.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 7\n", - " 5.9\n", - " 119\n", - " 5.9\n", + " 14\n", + " 6.1\n", + " 231\n", + " 6.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 0\n", - " 0.0\n", - " 84\n", - " 0.0\n", + " 14\n", + " 6.5\n", + " 217\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 0\n", - " 0.0\n", - " 119\n", - " 0.0\n", + " 7\n", + " 2.9\n", + " 238\n", + " 2.9\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 0\n", - " 0.0\n", - " 105\n", - " 0.0\n", + " 21\n", + " 10.3\n", + " 203\n", + " 10.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 0\n", - " 0.0\n", - " 112\n", - " 0.0\n", + " 14\n", + " 6.2\n", + " 224\n", + " 6.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 14\n", - " 4.1\n", - " 343\n", - " 4.1\n", + " 35\n", + " 5.2\n", + " 672\n", + " 5.2\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 0\n", - " 0.0\n", - " 119\n", - " 0.0\n", + " 14\n", + " 6.2\n", + " 224\n", + " 6.2\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black African\n", " 14\n", - " 13.3\n", - " 105\n", - " 13.3\n", + " 6.7\n", + " 210\n", + " 6.7\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", " 7\n", - " 5.0\n", - " 140\n", - " 5.0\n", + " 2.8\n", + " 252\n", + " 2.8\n", " 0.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 21\n", - " 5.0\n", - " 420\n", - " 5.0\n", - " 0.0\n", + " 56\n", + " 7.0\n", + " 805\n", + " 6.1\n", + " 0.9\n", " unknown\n", " \n", " \n", " 2\n", - " 28\n", - " 6.9\n", - " 406\n", + " 42\n", " 5.2\n", - " 1.7\n", + " 805\n", + " 5.2\n", + " 0.0\n", " unknown\n", " \n", " \n", " 3\n", - " 21\n", - " 5.4\n", - " 392\n", - " 5.4\n", + " 56\n", + " 7.2\n", + " 777\n", + " 7.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 4\n", - " 28\n", - " 6.6\n", - " 427\n", - " 4.9\n", - " 1.7\n", + " 49\n", + " 6.0\n", + " 819\n", + " 6.0\n", + " 0.0\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 21\n", - " 5.4\n", - " 392\n", - " 5.4\n", - " 0.0\n", + " 49\n", + " 6.0\n", + " 812\n", + " 5.2\n", + " 0.8\n", " unknown\n", " \n", " \n", " Unknown\n", " 7\n", - " 6.7\n", - " 105\n", - " 6.7\n", + " 3.3\n", + " 210\n", + " 3.3\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 35\n", - " 5.9\n", - " 595\n", - " 5.9\n", - " 0.0\n", + " 70\n", + " 5.4\n", + " 1295\n", + " 4.9\n", + " 0.5\n", " unknown\n", " \n", " \n", " under 30\n", - " 91\n", - " 5.9\n", - " 1547\n", - " 5.4\n", - " 0.5\n", + " 189\n", + " 6.5\n", + " 2926\n", + " 6.2\n", + " 0.3\n", " unknown\n", " \n", " \n", " housebound\n", " no\n", - " 119\n", - " 5.6\n", - " 2114\n", - " 5.3\n", + " 252\n", + " 6.0\n", + " 4179\n", + " 5.7\n", " 0.3\n", " unknown\n", " \n", @@ -33816,7 +33971,7 @@ " yes\n", " 0\n", " 0.0\n", - " 28\n", + " 42\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -33824,18 +33979,18 @@ " \n", " chronic_cardiac_disease\n", " no\n", - " 126\n", + " 245\n", " 5.9\n", - " 2121\n", - " 5.6\n", - " 0.3\n", + " 4186\n", + " 5.7\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 35\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -33843,37 +33998,37 @@ " \n", " current_copd\n", " no\n", - " 119\n", - " 5.6\n", - " 2114\n", - " 5.3\n", - " 0.3\n", + " 245\n", + " 5.9\n", + " 4179\n", + " 5.7\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 21\n", - " 0.0\n", + " 7\n", + " 14.3\n", + " 49\n", + " 14.3\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 126\n", + " 252\n", " 6.0\n", - " 2114\n", - " 5.6\n", - " 0.4\n", + " 4172\n", + " 5.9\n", + " 0.1\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 28\n", + " 49\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -33881,10 +34036,10 @@ " \n", " dementia\n", " no\n", - " 126\n", - " 5.9\n", - " 2121\n", - " 5.6\n", + " 252\n", + " 6.0\n", + " 4179\n", + " 5.7\n", " 0.3\n", " unknown\n", " \n", @@ -33892,7 +34047,7 @@ " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 42\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -33900,105 +34055,123 @@ " \n", " psychosis_schiz_bipolar\n", " no\n", - " 126\n", + " 252\n", + " 6.0\n", + " 4179\n", " 5.9\n", - " 2121\n", - " 5.6\n", - " 0.3\n", + " 0.1\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 42\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " LD\n", + " LD\n", " no\n", - " 119\n", + " 252\n", + " 6.1\n", + " 4130\n", + " 5.9\n", + " 0.2\n", + " unknown\n", + " \n", + " \n", + " ssri\n", + " no\n", + " 252\n", + " 6.0\n", + " 4179\n", " 5.7\n", - " 2100\n", - " 5.3\n", - " 0.4\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 42\n", + " 49\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " ssri\n", + " chemo_or_radio\n", " no\n", - " 126\n", + " 252\n", + " 6.0\n", + " 4186\n", " 5.9\n", - " 2128\n", - " 5.6\n", - " 0.3\n", + " 0.1\n", " unknown\n", " \n", " \n", - " chemo_or_radio\n", + " yes\n", + " 0\n", + " 0.0\n", + " 42\n", + " 0.0\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " lung_cancer\n", " no\n", - " 126\n", - " 5.9\n", - " 2121\n", - " 5.6\n", - " 0.3\n", + " 252\n", + " 6.0\n", + " 4193\n", + " 5.8\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 35\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " lung_cancer\n", + " cancer_excl_lung_and_haem\n", " no\n", - " 126\n", - " 5.9\n", - " 2121\n", - " 5.6\n", - " 0.3\n", + " 252\n", + " 6.0\n", + " 4193\n", + " 5.8\n", + " 0.2\n", " unknown\n", " \n", " \n", - " cancer_excl_lung_and_haem\n", - " no\n", - " 126\n", - " 5.9\n", - " 2121\n", - " 5.6\n", - " 0.3\n", + " yes\n", + " 0\n", + " 0.0\n", + " 35\n", + " 0.0\n", + " 0.0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 126\n", - " 5.9\n", - " 2121\n", - " 5.3\n", - " 0.6\n", + " 252\n", + " 6.0\n", + " 4179\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 42\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -34006,20 +34179,20 @@ " \n", " ckd\n", " no\n", - " 105\n", - " 6.1\n", - " 1722\n", - " 5.7\n", - " 0.4\n", + " 189\n", + " 5.6\n", + " 3395\n", + " 5.4\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", - " 5.0\n", - " 420\n", - " 5.0\n", - " 0.0\n", + " 63\n", + " 7.6\n", + " 826\n", + " 6.8\n", + " 0.8\n", " unknown\n", " \n", " \n", @@ -34029,260 +34202,274 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 126 \n", - "sex F 70 \n", - " M 56 \n", - "ageband_5yr 0-15 0 \n", + "overall overall 252 \n", + "sex F 119 \n", + " M 133 \n", + "ageband_5yr 0 0 \n", + " 0-15 14 \n", " 16-17 7 \n", - " 18-29 7 \n", - " 30-34 7 \n", - " 35-39 14 \n", - " 40-44 7 \n", - " 45-49 0 \n", - " 50-54 7 \n", - " 55-59 7 \n", - " 60-64 0 \n", - " 65-69 7 \n", - " 70-74 7 \n", - " 75-79 7 \n", + " 18-29 14 \n", + " 30-34 21 \n", + " 35-39 21 \n", + " 40-44 21 \n", + " 45-49 14 \n", + " 50-54 14 \n", + " 55-59 14 \n", + " 60-64 21 \n", + " 65-69 21 \n", + " 70-74 14 \n", + " 75-79 14 \n", " 80-84 14 \n", - " 85-89 7 \n", - "ethnicity_6_groups Black 14 \n", - " Mixed 21 \n", - " Other 14 \n", - " South Asian 28 \n", - " Unknown 28 \n", - " White 21 \n", + " 85-89 14 \n", + " 90+ 0 \n", + "ethnicity_6_groups Black 42 \n", + " Mixed 35 \n", + " Other 49 \n", + " South Asian 42 \n", + " Unknown 42 \n", + " White 42 \n", "ethnicity_16_groups African 7 \n", - " Bangladeshi or British Bangladeshi 7 \n", - " Caribbean 0 \n", - " Chinese 0 \n", - " Other 7 \n", - " Other Asian 7 \n", + " Bangladeshi or British Bangladeshi 14 \n", + " Caribbean 14 \n", + " Chinese 14 \n", + " Other 21 \n", + " Other Asian 14 \n", " British or Mixed British 14 \n", - " Indian or British Indian 0 \n", - " Irish 7 \n", - " Other Black 0 \n", - " Other White 0 \n", - " Other mixed 0 \n", - " Pakistani or British Pakistani 0 \n", - " Unknown 14 \n", - " White + Asian 0 \n", + " Indian or British Indian 14 \n", + " Irish 14 \n", + " Other Black 14 \n", + " Other White 7 \n", + " Other mixed 21 \n", + " Pakistani or British Pakistani 14 \n", + " Unknown 35 \n", + " White + Asian 14 \n", " White + Black African 14 \n", " White + Black Caribbean 7 \n", - "imd_categories 1 Most deprived 21 \n", - " 2 28 \n", - " 3 21 \n", - " 4 28 \n", - " 5 Least deprived 21 \n", + "imd_categories 1 Most deprived 56 \n", + " 2 42 \n", + " 3 56 \n", + " 4 49 \n", + " 5 Least deprived 49 \n", " Unknown 7 \n", - "bmi 30+ 35 \n", - " under 30 91 \n", - "housebound no 119 \n", + "bmi 30+ 70 \n", + " under 30 189 \n", + "housebound no 252 \n", " yes 0 \n", - "chronic_cardiac_disease no 126 \n", + "chronic_cardiac_disease no 245 \n", " yes 0 \n", - "current_copd no 119 \n", + "current_copd no 245 \n", + " yes 7 \n", + "dmards no 252 \n", " yes 0 \n", - "dmards no 126 \n", + "dementia no 252 \n", " yes 0 \n", - "dementia no 126 \n", + "psychosis_schiz_bipolar no 252 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 126 \n", + "LD no 252 \n", + "ssri no 252 \n", " yes 0 \n", - "LD no 119 \n", + "chemo_or_radio no 252 \n", " yes 0 \n", - "ssri no 126 \n", - "chemo_or_radio no 126 \n", + "lung_cancer no 252 \n", " yes 0 \n", - "lung_cancer no 126 \n", - "cancer_excl_lung_and_haem no 126 \n", - "haematological_cancer no 126 \n", + "cancer_excl_lung_and_haem no 252 \n", " yes 0 \n", - "ckd no 105 \n", - " yes 21 \n", + "haematological_cancer no 252 \n", + " yes 0 \n", + "ckd no 189 \n", + " yes 63 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 5.9 2142 \n", - "sex F 6.2 1127 \n", - " M 5.5 1015 \n", - "ageband_5yr 0-15 0.0 112 \n", - " 16-17 5.0 140 \n", - " 18-29 5.3 133 \n", - " 30-34 5.0 140 \n", - " 35-39 9.5 147 \n", - " 40-44 4.8 147 \n", - " 45-49 0.0 133 \n", - " 50-54 4.5 154 \n", - " 55-59 4.5 154 \n", - " 60-64 0.0 126 \n", - " 65-69 5.0 140 \n", - " 70-74 5.0 140 \n", - " 75-79 5.3 133 \n", - " 80-84 10.0 140 \n", - " 85-89 4.5 154 \n", - "ethnicity_6_groups Black 3.9 357 \n", - " Mixed 6.0 350 \n", - " Other 4.2 336 \n", - " South Asian 7.7 364 \n", - " Unknown 8.2 343 \n", - " White 5.4 392 \n", - "ethnicity_16_groups African 6.7 105 \n", - " Bangladeshi or British Bangladeshi 5.9 119 \n", - " Caribbean 0.0 98 \n", - " Chinese 0.0 105 \n", - " Other 6.2 112 \n", - " Other Asian 6.2 112 \n", - " British or Mixed British 10.5 133 \n", - " Indian or British Indian 0.0 105 \n", - " Irish 5.9 119 \n", - " Other Black 0.0 84 \n", - " Other White 0.0 119 \n", - " Other mixed 0.0 105 \n", - " Pakistani or British Pakistani 0.0 112 \n", - " Unknown 4.1 343 \n", - " White + Asian 0.0 119 \n", - " White + Black African 13.3 105 \n", - " White + Black Caribbean 5.0 140 \n", - "imd_categories 1 Most deprived 5.0 420 \n", - " 2 6.9 406 \n", - " 3 5.4 392 \n", - " 4 6.6 427 \n", - " 5 Least deprived 5.4 392 \n", - " Unknown 6.7 105 \n", - "bmi 30+ 5.9 595 \n", - " under 30 5.9 1547 \n", - "housebound no 5.6 2114 \n", - " yes 0.0 28 \n", - "chronic_cardiac_disease no 5.9 2121 \n", - " yes 0.0 21 \n", - "current_copd no 5.6 2114 \n", - " yes 0.0 21 \n", - "dmards no 6.0 2114 \n", - " yes 0.0 28 \n", - "dementia no 5.9 2121 \n", - " yes 0.0 21 \n", - "psychosis_schiz_bipolar no 5.9 2121 \n", - " yes 0.0 21 \n", - "LD no 5.7 2100 \n", + "overall overall 6.0 4221 \n", + "sex F 5.5 2177 \n", + " M 6.5 2044 \n", + "ageband_5yr 0 0.0 70 \n", + " 0-15 5.4 259 \n", + " 16-17 2.9 245 \n", + " 18-29 5.3 266 \n", + " 30-34 7.7 273 \n", + " 35-39 7.9 266 \n", + " 40-44 7.7 273 \n", + " 45-49 5.0 280 \n", + " 50-54 5.4 259 \n", + " 55-59 4.7 301 \n", + " 60-64 7.9 266 \n", + " 65-69 7.5 280 \n", + " 70-74 4.8 294 \n", + " 75-79 5.0 280 \n", + " 80-84 5.1 273 \n", + " 85-89 4.8 294 \n", + " 90+ 0.0 35 \n", + "ethnicity_6_groups Black 5.7 735 \n", + " Mixed 5.0 700 \n", + " Other 6.7 728 \n", + " South Asian 5.6 749 \n", + " Unknown 6.9 609 \n", + " White 5.9 714 \n", + "ethnicity_16_groups African 3.2 217 \n", + " Bangladeshi or British Bangladeshi 6.7 210 \n", + " Caribbean 6.5 217 \n", + " Chinese 6.5 217 \n", + " Other 8.8 238 \n", + " Other Asian 6.7 210 \n", + " British or Mixed British 6.5 217 \n", + " Indian or British Indian 6.2 224 \n", + " Irish 6.1 231 \n", + " Other Black 6.5 217 \n", + " Other White 2.9 238 \n", + " Other mixed 10.3 203 \n", + " Pakistani or British Pakistani 6.2 224 \n", + " Unknown 5.2 672 \n", + " White + Asian 6.2 224 \n", + " White + Black African 6.7 210 \n", + " White + Black Caribbean 2.8 252 \n", + "imd_categories 1 Most deprived 7.0 805 \n", + " 2 5.2 805 \n", + " 3 7.2 777 \n", + " 4 6.0 819 \n", + " 5 Least deprived 6.0 812 \n", + " Unknown 3.3 210 \n", + "bmi 30+ 5.4 1295 \n", + " under 30 6.5 2926 \n", + "housebound no 6.0 4179 \n", + " yes 0.0 42 \n", + "chronic_cardiac_disease no 5.9 4186 \n", + " yes 0.0 35 \n", + "current_copd no 5.9 4179 \n", + " yes 14.3 49 \n", + "dmards no 6.0 4172 \n", + " yes 0.0 49 \n", + "dementia no 6.0 4179 \n", + " yes 0.0 42 \n", + "psychosis_schiz_bipolar no 6.0 4179 \n", " yes 0.0 42 \n", - "ssri no 5.9 2128 \n", - "chemo_or_radio no 5.9 2121 \n", - " yes 0.0 21 \n", - "lung_cancer no 5.9 2121 \n", - "cancer_excl_lung_and_haem no 5.9 2121 \n", - "haematological_cancer no 5.9 2121 \n", - " yes 0.0 21 \n", - "ckd no 6.1 1722 \n", - " yes 5.0 420 \n", + "LD no 6.1 4130 \n", + "ssri no 6.0 4179 \n", + " yes 0.0 49 \n", + "chemo_or_radio no 6.0 4186 \n", + " yes 0.0 42 \n", + "lung_cancer no 6.0 4193 \n", + " yes 0.0 35 \n", + "cancer_excl_lung_and_haem no 6.0 4193 \n", + " yes 0.0 35 \n", + "haematological_cancer no 6.0 4179 \n", + " yes 0.0 42 \n", + "ckd no 5.6 3395 \n", + " yes 7.6 826 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 5.6 \n", - "sex F 5.6 \n", - " M 5.5 \n", - "ageband_5yr 0-15 0.0 \n", - " 16-17 5.0 \n", - " 18-29 0.0 \n", - " 30-34 5.0 \n", - " 35-39 4.8 \n", - " 40-44 4.8 \n", - " 45-49 0.0 \n", - " 50-54 4.5 \n", - " 55-59 4.5 \n", - " 60-64 0.0 \n", - " 65-69 5.0 \n", - " 70-74 5.0 \n", - " 75-79 5.3 \n", - " 80-84 10.0 \n", - " 85-89 4.5 \n", - "ethnicity_6_groups Black 3.9 \n", + "overall overall 5.8 \n", + "sex F 5.5 \n", + " M 6.2 \n", + "ageband_5yr 0 0.0 \n", + " 0-15 5.4 \n", + " 16-17 2.9 \n", + " 18-29 5.3 \n", + " 30-34 7.7 \n", + " 35-39 7.9 \n", + " 40-44 7.7 \n", + " 45-49 5.0 \n", + " 50-54 5.4 \n", + " 55-59 4.7 \n", + " 60-64 5.3 \n", + " 65-69 7.5 \n", + " 70-74 4.8 \n", + " 75-79 5.0 \n", + " 80-84 5.1 \n", + " 85-89 4.8 \n", + " 90+ 0.0 \n", + "ethnicity_6_groups Black 5.7 \n", " Mixed 4.0 \n", - " Other 4.2 \n", - " South Asian 7.7 \n", - " Unknown 8.2 \n", - " White 5.4 \n", - "ethnicity_16_groups African 6.7 \n", - " Bangladeshi or British Bangladeshi 5.9 \n", - " Caribbean 0.0 \n", - " Chinese 0.0 \n", - " Other 0.0 \n", - " Other Asian 6.2 \n", - " British or Mixed British 10.5 \n", - " Indian or British Indian 0.0 \n", - " Irish 5.9 \n", - " Other Black 0.0 \n", - " Other White 0.0 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 4.1 \n", - " White + Asian 0.0 \n", - " White + Black African 13.3 \n", - " White + Black Caribbean 5.0 \n", - "imd_categories 1 Most deprived 5.0 \n", + " Other 6.7 \n", + " South Asian 4.7 \n", + " Unknown 6.9 \n", + " White 5.9 \n", + "ethnicity_16_groups African 3.2 \n", + " Bangladeshi or British Bangladeshi 6.7 \n", + " Caribbean 6.5 \n", + " Chinese 6.5 \n", + " Other 8.8 \n", + " Other Asian 6.7 \n", + " British or Mixed British 6.5 \n", + " Indian or British Indian 6.2 \n", + " Irish 6.1 \n", + " Other Black 6.5 \n", + " Other White 2.9 \n", + " Other mixed 10.3 \n", + " Pakistani or British Pakistani 6.2 \n", + " Unknown 5.2 \n", + " White + Asian 6.2 \n", + " White + Black African 6.7 \n", + " White + Black Caribbean 2.8 \n", + "imd_categories 1 Most deprived 6.1 \n", " 2 5.2 \n", - " 3 5.4 \n", - " 4 4.9 \n", - " 5 Least deprived 5.4 \n", - " Unknown 6.7 \n", - "bmi 30+ 5.9 \n", - " under 30 5.4 \n", - "housebound no 5.3 \n", + " 3 7.2 \n", + " 4 6.0 \n", + " 5 Least deprived 5.2 \n", + " Unknown 3.3 \n", + "bmi 30+ 4.9 \n", + " under 30 6.2 \n", + "housebound no 5.7 \n", " yes 0.0 \n", - "chronic_cardiac_disease no 5.6 \n", + "chronic_cardiac_disease no 5.7 \n", " yes 0.0 \n", - "current_copd no 5.3 \n", + "current_copd no 5.7 \n", + " yes 14.3 \n", + "dmards no 5.9 \n", " yes 0.0 \n", - "dmards no 5.6 \n", + "dementia no 5.7 \n", " yes 0.0 \n", - "dementia no 5.6 \n", + "psychosis_schiz_bipolar no 5.9 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 5.6 \n", + "LD no 5.9 \n", + "ssri no 5.7 \n", " yes 0.0 \n", - "LD no 5.3 \n", + "chemo_or_radio no 5.9 \n", " yes 0.0 \n", - "ssri no 5.6 \n", - "chemo_or_radio no 5.6 \n", + "lung_cancer no 5.8 \n", " yes 0.0 \n", - "lung_cancer no 5.6 \n", - "cancer_excl_lung_and_haem no 5.6 \n", - "haematological_cancer no 5.3 \n", + "cancer_excl_lung_and_haem no 5.8 \n", " yes 0.0 \n", - "ckd no 5.7 \n", - " yes 5.0 \n", + "haematological_cancer no 5.7 \n", + " yes 0.0 \n", + "ckd no 5.4 \n", + " yes 6.8 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 0.3 \n", - "sex F 0.6 \n", - " M 0.0 \n", - "ageband_5yr 0-15 0.0 \n", + "overall overall 0.2 \n", + "sex F 0.0 \n", + " M 0.3 \n", + "ageband_5yr 0 0.0 \n", + " 0-15 0.0 \n", " 16-17 0.0 \n", - " 18-29 5.3 \n", + " 18-29 0.0 \n", " 30-34 0.0 \n", - " 35-39 4.7 \n", + " 35-39 0.0 \n", " 40-44 0.0 \n", " 45-49 0.0 \n", " 50-54 0.0 \n", " 55-59 0.0 \n", - " 60-64 0.0 \n", + " 60-64 2.6 \n", " 65-69 0.0 \n", " 70-74 0.0 \n", " 75-79 0.0 \n", " 80-84 0.0 \n", " 85-89 0.0 \n", + " 90+ 0.0 \n", "ethnicity_6_groups Black 0.0 \n", - " Mixed 2.0 \n", + " Mixed 1.0 \n", " Other 0.0 \n", - " South Asian 0.0 \n", + " South Asian 0.9 \n", " Unknown 0.0 \n", " White 0.0 \n", "ethnicity_16_groups African 0.0 \n", " Bangladeshi or British Bangladeshi 0.0 \n", " Caribbean 0.0 \n", " Chinese 0.0 \n", - " Other 6.2 \n", + " Other 0.0 \n", " Other Asian 0.0 \n", " British or Mixed British 0.0 \n", " Indian or British Indian 0.0 \n", @@ -34295,48 +34482,51 @@ " White + Asian 0.0 \n", " White + Black African 0.0 \n", " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 0.0 \n", - " 2 1.7 \n", + "imd_categories 1 Most deprived 0.9 \n", + " 2 0.0 \n", " 3 0.0 \n", - " 4 1.7 \n", - " 5 Least deprived 0.0 \n", + " 4 0.0 \n", + " 5 Least deprived 0.8 \n", " Unknown 0.0 \n", - "bmi 30+ 0.0 \n", - " under 30 0.5 \n", + "bmi 30+ 0.5 \n", + " under 30 0.3 \n", "housebound no 0.3 \n", " yes 0.0 \n", - "chronic_cardiac_disease no 0.3 \n", + "chronic_cardiac_disease no 0.2 \n", " yes 0.0 \n", - "current_copd no 0.3 \n", + "current_copd no 0.2 \n", " yes 0.0 \n", - "dmards no 0.4 \n", + "dmards no 0.1 \n", " yes 0.0 \n", "dementia no 0.3 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 0.3 \n", - " yes 0.0 \n", - "LD no 0.4 \n", + "psychosis_schiz_bipolar no 0.1 \n", " yes 0.0 \n", + "LD no 0.2 \n", "ssri no 0.3 \n", - "chemo_or_radio no 0.3 \n", " yes 0.0 \n", - "lung_cancer no 0.3 \n", - "cancer_excl_lung_and_haem no 0.3 \n", - "haematological_cancer no 0.6 \n", + "chemo_or_radio no 0.1 \n", " yes 0.0 \n", - "ckd no 0.4 \n", + "lung_cancer no 0.2 \n", " yes 0.0 \n", + "cancer_excl_lung_and_haem no 0.2 \n", + " yes 0.0 \n", + "haematological_cancer no 0.3 \n", + " yes 0.0 \n", + "ckd no 0.2 \n", + " yes 0.8 \n", "\n", " Date projected to reach 90% \n", "category group \n", "overall overall unknown \n", "sex F unknown \n", " M unknown \n", - "ageband_5yr 0-15 unknown \n", + "ageband_5yr 0 unknown \n", + " 0-15 unknown \n", " 16-17 unknown \n", - " 18-29 05-Apr \n", + " 18-29 unknown \n", " 30-34 unknown \n", - " 35-39 13-Apr \n", + " 35-39 unknown \n", " 40-44 unknown \n", " 45-49 unknown \n", " 50-54 unknown \n", @@ -34347,6 +34537,7 @@ " 75-79 unknown \n", " 80-84 unknown \n", " 85-89 unknown \n", + " 90+ unknown \n", "ethnicity_6_groups Black unknown \n", " Mixed unknown \n", " Other unknown \n", @@ -34357,7 +34548,7 @@ " Bangladeshi or British Bangladeshi unknown \n", " Caribbean unknown \n", " Chinese unknown \n", - " Other 19-Mar \n", + " Other unknown \n", " Other Asian unknown \n", " British or Mixed British unknown \n", " Indian or British Indian unknown \n", @@ -34391,12 +34582,14 @@ "psychosis_schiz_bipolar no unknown \n", " yes unknown \n", "LD no unknown \n", - " yes unknown \n", "ssri no unknown \n", + " yes unknown \n", "chemo_or_radio no unknown \n", " yes unknown \n", "lung_cancer no unknown \n", + " yes unknown \n", "cancer_excl_lung_and_haem no unknown \n", + " yes unknown \n", "haematological_cancer no unknown \n", " yes unknown \n", "ckd no unknown \n", @@ -34429,7 +34622,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (third dose) among **70-79** population up to 15 Dec 2021" + "## COVID vaccination rollout (third dose) among **70-79** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -34495,30 +34688,30 @@ " \n", " overall\n", " overall\n", - " 189\n", - " 5.4\n", - " 3479\n", - " 5.0\n", - " 0.4\n", + " 406\n", + " 5.9\n", + " 6860\n", + " 5.6\n", + " 0.3\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 98\n", - " 5.6\n", - " 1757\n", - " 4.8\n", - " 0.8\n", + " 224\n", + " 6.3\n", + " 3542\n", + " 5.9\n", + " 0.4\n", " unknown\n", " \n", " \n", " M\n", - " 98\n", + " 189\n", " 5.7\n", - " 1722\n", - " 5.3\n", - " 0.4\n", + " 3318\n", + " 5.5\n", + " 0.2\n", " unknown\n", " \n", " \n", @@ -34526,453 +34719,453 @@ " 0\n", " 0\n", " 0.0\n", - " 42\n", + " 84\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 0-15\n", - " 14\n", - " 6.7\n", - " 210\n", - " 3.3\n", - " 3.4\n", - " 04-Jun\n", + " 28\n", + " 6.6\n", + " 427\n", + " 6.6\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 16-17\n", - " 14\n", - " 5.3\n", - " 266\n", - " 5.3\n", - " 0.0\n", + " 28\n", + " 6.2\n", + " 455\n", + " 4.6\n", + " 1.6\n", " unknown\n", " \n", " \n", " 18-29\n", - " 7\n", - " 3.0\n", - " 231\n", - " 3.0\n", - " 0.0\n", + " 28\n", + " 6.5\n", + " 434\n", + " 4.8\n", + " 1.7\n", " unknown\n", " \n", " \n", " 30-34\n", - " 14\n", - " 5.4\n", - " 259\n", - " 2.7\n", - " 2.7\n", + " 21\n", + " 4.5\n", + " 469\n", + " 4.5\n", + " 0.0\n", " unknown\n", " \n", " \n", " 35-39\n", - " 14\n", - " 6.5\n", - " 217\n", - " 6.5\n", + " 28\n", + " 6.1\n", + " 462\n", + " 6.1\n", " 0.0\n", " unknown\n", " \n", " \n", " 40-44\n", - " 7\n", - " 3.3\n", - " 210\n", - " 3.3\n", + " 28\n", + " 6.5\n", + " 434\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 45-49\n", " 28\n", - " 12.1\n", - " 231\n", - " 9.1\n", - " 3.0\n", + " 6.2\n", + " 448\n", + " 6.2\n", + " 0.0\n", " unknown\n", " \n", " \n", " 50-54\n", - " 14\n", + " 28\n", " 6.5\n", - " 217\n", + " 434\n", " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 55-59\n", - " 14\n", - " 6.7\n", - " 210\n", - " 3.3\n", - " 3.4\n", - " 04-Jun\n", + " 21\n", + " 4.6\n", + " 455\n", + " 4.6\n", + " 0.0\n", + " unknown\n", " \n", " \n", " 60-64\n", - " 7\n", - " 2.9\n", - " 238\n", - " 2.9\n", + " 28\n", + " 6.2\n", + " 448\n", + " 6.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 65-69\n", " 14\n", - " 6.2\n", - " 224\n", - " 6.2\n", + " 3.1\n", + " 448\n", + " 3.1\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-74\n", - " 7\n", - " 3.6\n", - " 196\n", - " 3.6\n", + " 28\n", + " 6.5\n", + " 434\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 75-79\n", - " 14\n", - " 5.9\n", - " 238\n", - " 5.9\n", + " 21\n", + " 4.6\n", + " 455\n", + " 4.6\n", " 0.0\n", " unknown\n", " \n", " \n", " 80-84\n", - " 14\n", - " 5.9\n", - " 238\n", - " 5.9\n", - " 0.0\n", + " 35\n", + " 7.9\n", + " 441\n", + " 6.3\n", + " 1.6\n", " unknown\n", " \n", " \n", " 85-89\n", - " 14\n", - " 6.5\n", - " 217\n", - " 6.5\n", + " 28\n", + " 6.2\n", + " 448\n", + " 6.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 90+\n", - " 0\n", - " 0.0\n", - " 28\n", - " 0.0\n", + " 7\n", + " 8.3\n", + " 84\n", " 0.0\n", - " unknown\n", + " 8.3\n", + " 11-Apr\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 42\n", - " 6.9\n", - " 609\n", - " 5.7\n", - " 1.2\n", + " 70\n", + " 6.1\n", + " 1155\n", + " 5.5\n", + " 0.6\n", " unknown\n", " \n", " \n", " Mixed\n", - " 28\n", - " 4.5\n", - " 616\n", - " 4.5\n", - " 0.0\n", + " 70\n", + " 5.9\n", + " 1190\n", + " 5.3\n", + " 0.6\n", " unknown\n", " \n", " \n", " Other\n", - " 35\n", - " 6.1\n", - " 574\n", - " 6.1\n", + " 77\n", + " 6.5\n", + " 1176\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 28\n", - " 4.9\n", - " 567\n", - " 3.7\n", - " 1.2\n", + " 70\n", + " 5.8\n", + " 1204\n", + " 5.2\n", + " 0.6\n", " unknown\n", " \n", " \n", " Unknown\n", - " 35\n", - " 6.9\n", - " 504\n", - " 6.9\n", - " 0.0\n", + " 56\n", + " 5.4\n", + " 1029\n", + " 4.8\n", + " 0.6\n", " unknown\n", " \n", " \n", " White\n", - " 28\n", - " 4.6\n", - " 609\n", - " 3.4\n", - " 1.2\n", + " 77\n", + " 7.0\n", + " 1099\n", + " 7.0\n", + " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 7\n", - " 3.4\n", - " 203\n", - " 3.4\n", + " 28\n", + " 7.8\n", + " 357\n", + " 7.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 7\n", - " 3.6\n", - " 196\n", - " 3.6\n", + " 14\n", + " 4.0\n", + " 350\n", + " 4.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 14\n", - " 8.0\n", - " 175\n", - " 8.0\n", - " 0.0\n", + " 21\n", + " 5.7\n", + " 371\n", + " 3.8\n", + " 1.9\n", " unknown\n", " \n", " \n", " Chinese\n", - " 0\n", - " 0.0\n", - " 154\n", - " 0.0\n", + " 28\n", + " 7.7\n", + " 364\n", + " 7.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 0\n", - " 0.0\n", - " 168\n", - " 0.0\n", + " 21\n", + " 5.7\n", + " 371\n", + " 5.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 14\n", - " 7.7\n", - " 182\n", - " 3.8\n", - " 3.9\n", - " 11-May\n", + " 21\n", + " 5.8\n", + " 364\n", + " 5.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " British or Mixed British\n", - " 14\n", - " 7.4\n", - " 189\n", - " 7.4\n", + " 21\n", + " 6.1\n", + " 343\n", + " 6.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 14\n", - " 7.4\n", - " 189\n", - " 3.7\n", - " 3.7\n", - " 20-May\n", + " 35\n", + " 9.4\n", + " 371\n", + " 9.4\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Irish\n", - " 7\n", - " 4.2\n", - " 168\n", - " 4.2\n", + " 21\n", + " 5.8\n", + " 364\n", + " 5.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 7\n", - " 3.8\n", - " 182\n", - " 3.8\n", + " 21\n", + " 5.8\n", + " 364\n", + " 5.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 14\n", - " 7.1\n", - " 196\n", - " 3.6\n", - " 3.5\n", - " 29-May\n", + " 28\n", + " 7.7\n", + " 364\n", + " 7.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other mixed\n", - " 7\n", - " 3.7\n", - " 189\n", - " 3.7\n", + " 21\n", + " 6.0\n", + " 350\n", + " 6.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", " 14\n", - " 7.7\n", - " 182\n", - " 3.8\n", - " 3.9\n", - " 11-May\n", + " 4.3\n", + " 329\n", + " 4.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 35\n", - " 6.2\n", - " 560\n", - " 5.0\n", - " 1.2\n", + " 49\n", + " 4.8\n", + " 1015\n", + " 4.8\n", + " 0.0\n", " unknown\n", " \n", " \n", " White + Asian\n", " 14\n", - " 6.9\n", - " 203\n", - " 3.4\n", - " 3.5\n", - " 30-May\n", + " 3.6\n", + " 385\n", + " 3.6\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black African\n", - " 14\n", - " 7.7\n", - " 182\n", - " 7.7\n", + " 28\n", + " 7.1\n", + " 392\n", + " 7.1\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 14\n", - " 8.0\n", - " 175\n", - " 4.0\n", - " 4.0\n", - " 07-May\n", + " 21\n", + " 5.3\n", + " 399\n", + " 5.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 28\n", - " 4.3\n", - " 644\n", - " 4.3\n", + " 84\n", + " 6.5\n", + " 1302\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " 2\n", - " 35\n", - " 5.1\n", - " 686\n", - " 5.1\n", - " 0.0\n", + " 91\n", + " 6.8\n", + " 1344\n", + " 6.2\n", + " 0.6\n", " unknown\n", " \n", " \n", " 3\n", - " 42\n", - " 6.1\n", - " 686\n", - " 5.1\n", - " 1.0\n", + " 70\n", + " 5.5\n", + " 1281\n", + " 4.9\n", + " 0.6\n", " unknown\n", " \n", " \n", " 4\n", - " 35\n", - " 5.3\n", - " 658\n", - " 5.3\n", + " 77\n", + " 5.9\n", + " 1316\n", + " 5.9\n", " 0.0\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 35\n", - " 5.7\n", - " 616\n", - " 5.7\n", - " 0.0\n", + " 70\n", + " 5.5\n", + " 1281\n", + " 4.9\n", + " 0.6\n", " unknown\n", " \n", " \n", " Unknown\n", " 14\n", - " 7.4\n", - " 189\n", - " 7.4\n", + " 4.3\n", + " 329\n", + " 4.3\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 42\n", - " 3.8\n", - " 1092\n", - " 3.2\n", - " 0.6\n", + " 126\n", + " 6.1\n", + " 2065\n", + " 5.8\n", + " 0.3\n", " unknown\n", " \n", " \n", " under 30\n", - " 147\n", - " 6.2\n", - " 2387\n", - " 5.9\n", - " 0.3\n", + " 280\n", + " 5.8\n", + " 4788\n", + " 5.6\n", + " 0.2\n", " unknown\n", " \n", " \n", " housebound\n", " no\n", - " 189\n", - " 5.5\n", - " 3451\n", - " 5.1\n", - " 0.4\n", + " 406\n", + " 6.0\n", + " 6783\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 28\n", + " 70\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -34980,18 +35173,18 @@ " \n", " chronic_cardiac_disease\n", " no\n", - " 189\n", - " 5.5\n", - " 3451\n", - " 5.1\n", - " 0.4\n", + " 406\n", + " 6.0\n", + " 6797\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 28\n", + " 63\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -34999,18 +35192,18 @@ " \n", " current_copd\n", " no\n", - " 189\n", - " 5.5\n", - " 3444\n", - " 5.1\n", - " 0.4\n", + " 406\n", + " 6.0\n", + " 6776\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 42\n", + " 84\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -35018,37 +35211,37 @@ " \n", " dmards\n", " no\n", - " 189\n", - " 5.5\n", - " 3444\n", - " 5.1\n", - " 0.4\n", + " 399\n", + " 5.9\n", + " 6790\n", + " 5.6\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 35\n", - " 0.0\n", + " 7\n", + " 10.0\n", + " 70\n", + " 10.0\n", " 0.0\n", " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 189\n", - " 5.5\n", - " 3444\n", - " 5.1\n", - " 0.4\n", + " 406\n", + " 6.0\n", + " 6776\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 42\n", + " 77\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -35056,18 +35249,18 @@ " \n", " psychosis_schiz_bipolar\n", " no\n", - " 189\n", - " 5.5\n", - " 3444\n", - " 5.1\n", - " 0.4\n", + " 406\n", + " 6.0\n", + " 6790\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 42\n", + " 70\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -35075,18 +35268,18 @@ " \n", " LD\n", " no\n", - " 189\n", - " 5.6\n", - " 3402\n", - " 5.1\n", - " 0.5\n", + " 406\n", + " 6.0\n", + " 6727\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 77\n", + " 133\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -35094,56 +35287,56 @@ " \n", " ssri\n", " no\n", - " 189\n", - " 5.5\n", - " 3451\n", - " 5.1\n", - " 0.4\n", + " 399\n", + " 5.9\n", + " 6790\n", + " 5.6\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 28\n", - " 0.0\n", + " 7\n", + " 10.0\n", + " 70\n", + " 10.0\n", " 0.0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 189\n", - " 5.5\n", - " 3451\n", - " 5.1\n", - " 0.4\n", + " 399\n", + " 5.9\n", + " 6790\n", + " 5.6\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 35\n", - " 0.0\n", + " 7\n", + " 10.0\n", + " 70\n", + " 10.0\n", " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 189\n", - " 5.5\n", - " 3444\n", - " 5.1\n", - " 0.4\n", + " 406\n", + " 6.0\n", + " 6790\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 63\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -35151,18 +35344,18 @@ " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 189\n", - " 5.5\n", - " 3444\n", - " 5.1\n", - " 0.4\n", + " 406\n", + " 6.0\n", + " 6790\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 70\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -35170,18 +35363,18 @@ " \n", " haematological_cancer\n", " no\n", - " 189\n", - " 5.5\n", - " 3437\n", - " 5.1\n", - " 0.4\n", + " 406\n", + " 6.0\n", + " 6783\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 42\n", + " 70\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -35189,19 +35382,19 @@ " \n", " ckd\n", " no\n", - " 154\n", - " 5.6\n", - " 2744\n", - " 5.4\n", - " 0.2\n", + " 343\n", + " 6.3\n", + " 5481\n", + " 5.9\n", + " 0.4\n", " unknown\n", " \n", " \n", " yes\n", - " 35\n", - " 4.8\n", - " 735\n", - " 4.8\n", + " 70\n", + " 5.1\n", + " 1379\n", + " 5.1\n", " 0.0\n", " unknown\n", " \n", @@ -35212,322 +35405,322 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 189 \n", - "sex F 98 \n", - " M 98 \n", + "overall overall 406 \n", + "sex F 224 \n", + " M 189 \n", "ageband_5yr 0 0 \n", - " 0-15 14 \n", - " 16-17 14 \n", - " 18-29 7 \n", - " 30-34 14 \n", - " 35-39 14 \n", - " 40-44 7 \n", + " 0-15 28 \n", + " 16-17 28 \n", + " 18-29 28 \n", + " 30-34 21 \n", + " 35-39 28 \n", + " 40-44 28 \n", " 45-49 28 \n", - " 50-54 14 \n", - " 55-59 14 \n", - " 60-64 7 \n", + " 50-54 28 \n", + " 55-59 21 \n", + " 60-64 28 \n", " 65-69 14 \n", - " 70-74 7 \n", - " 75-79 14 \n", - " 80-84 14 \n", - " 85-89 14 \n", - " 90+ 0 \n", - "ethnicity_6_groups Black 42 \n", - " Mixed 28 \n", - " Other 35 \n", - " South Asian 28 \n", - " Unknown 35 \n", - " White 28 \n", - "ethnicity_16_groups African 7 \n", - " Bangladeshi or British Bangladeshi 7 \n", - " Caribbean 14 \n", - " Chinese 0 \n", - " Other 0 \n", - " Other Asian 14 \n", - " British or Mixed British 14 \n", - " Indian or British Indian 14 \n", - " Irish 7 \n", - " Other Black 7 \n", - " Other White 14 \n", - " Other mixed 7 \n", + " 70-74 28 \n", + " 75-79 21 \n", + " 80-84 35 \n", + " 85-89 28 \n", + " 90+ 7 \n", + "ethnicity_6_groups Black 70 \n", + " Mixed 70 \n", + " Other 77 \n", + " South Asian 70 \n", + " Unknown 56 \n", + " White 77 \n", + "ethnicity_16_groups African 28 \n", + " Bangladeshi or British Bangladeshi 14 \n", + " Caribbean 21 \n", + " Chinese 28 \n", + " Other 21 \n", + " Other Asian 21 \n", + " British or Mixed British 21 \n", + " Indian or British Indian 35 \n", + " Irish 21 \n", + " Other Black 21 \n", + " Other White 28 \n", + " Other mixed 21 \n", " Pakistani or British Pakistani 14 \n", - " Unknown 35 \n", + " Unknown 49 \n", " White + Asian 14 \n", - " White + Black African 14 \n", - " White + Black Caribbean 14 \n", - "imd_categories 1 Most deprived 28 \n", - " 2 35 \n", - " 3 42 \n", - " 4 35 \n", - " 5 Least deprived 35 \n", + " White + Black African 28 \n", + " White + Black Caribbean 21 \n", + "imd_categories 1 Most deprived 84 \n", + " 2 91 \n", + " 3 70 \n", + " 4 77 \n", + " 5 Least deprived 70 \n", " Unknown 14 \n", - "bmi 30+ 42 \n", - " under 30 147 \n", - "housebound no 189 \n", - " yes 0 \n", - "chronic_cardiac_disease no 189 \n", - " yes 0 \n", - "current_copd no 189 \n", - " yes 0 \n", - "dmards no 189 \n", + "bmi 30+ 126 \n", + " under 30 280 \n", + "housebound no 406 \n", " yes 0 \n", - "dementia no 189 \n", + "chronic_cardiac_disease no 406 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 189 \n", + "current_copd no 406 \n", " yes 0 \n", - "LD no 189 \n", + "dmards no 399 \n", + " yes 7 \n", + "dementia no 406 \n", " yes 0 \n", - "ssri no 189 \n", + "psychosis_schiz_bipolar no 406 \n", " yes 0 \n", - "chemo_or_radio no 189 \n", + "LD no 406 \n", " yes 0 \n", - "lung_cancer no 189 \n", + "ssri no 399 \n", + " yes 7 \n", + "chemo_or_radio no 399 \n", + " yes 7 \n", + "lung_cancer no 406 \n", " yes 0 \n", - "cancer_excl_lung_and_haem no 189 \n", + "cancer_excl_lung_and_haem no 406 \n", " yes 0 \n", - "haematological_cancer no 189 \n", + "haematological_cancer no 406 \n", " yes 0 \n", - "ckd no 154 \n", - " yes 35 \n", + "ckd no 343 \n", + " yes 70 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 5.4 3479 \n", - "sex F 5.6 1757 \n", - " M 5.7 1722 \n", - "ageband_5yr 0 0.0 42 \n", - " 0-15 6.7 210 \n", - " 16-17 5.3 266 \n", - " 18-29 3.0 231 \n", - " 30-34 5.4 259 \n", - " 35-39 6.5 217 \n", - " 40-44 3.3 210 \n", - " 45-49 12.1 231 \n", - " 50-54 6.5 217 \n", - " 55-59 6.7 210 \n", - " 60-64 2.9 238 \n", - " 65-69 6.2 224 \n", - " 70-74 3.6 196 \n", - " 75-79 5.9 238 \n", - " 80-84 5.9 238 \n", - " 85-89 6.5 217 \n", - " 90+ 0.0 28 \n", - "ethnicity_6_groups Black 6.9 609 \n", - " Mixed 4.5 616 \n", - " Other 6.1 574 \n", - " South Asian 4.9 567 \n", - " Unknown 6.9 504 \n", - " White 4.6 609 \n", - "ethnicity_16_groups African 3.4 203 \n", - " Bangladeshi or British Bangladeshi 3.6 196 \n", - " Caribbean 8.0 175 \n", - " Chinese 0.0 154 \n", - " Other 0.0 168 \n", - " Other Asian 7.7 182 \n", - " British or Mixed British 7.4 189 \n", - " Indian or British Indian 7.4 189 \n", - " Irish 4.2 168 \n", - " Other Black 3.8 182 \n", - " Other White 7.1 196 \n", - " Other mixed 3.7 189 \n", - " Pakistani or British Pakistani 7.7 182 \n", - " Unknown 6.2 560 \n", - " White + Asian 6.9 203 \n", - " White + Black African 7.7 182 \n", - " White + Black Caribbean 8.0 175 \n", - "imd_categories 1 Most deprived 4.3 644 \n", - " 2 5.1 686 \n", - " 3 6.1 686 \n", - " 4 5.3 658 \n", - " 5 Least deprived 5.7 616 \n", - " Unknown 7.4 189 \n", - "bmi 30+ 3.8 1092 \n", - " under 30 6.2 2387 \n", - "housebound no 5.5 3451 \n", - " yes 0.0 28 \n", - "chronic_cardiac_disease no 5.5 3451 \n", - " yes 0.0 28 \n", - "current_copd no 5.5 3444 \n", - " yes 0.0 42 \n", - "dmards no 5.5 3444 \n", - " yes 0.0 35 \n", - "dementia no 5.5 3444 \n", - " yes 0.0 42 \n", - "psychosis_schiz_bipolar no 5.5 3444 \n", - " yes 0.0 42 \n", - "LD no 5.6 3402 \n", + "overall overall 5.9 6860 \n", + "sex F 6.3 3542 \n", + " M 5.7 3318 \n", + "ageband_5yr 0 0.0 84 \n", + " 0-15 6.6 427 \n", + " 16-17 6.2 455 \n", + " 18-29 6.5 434 \n", + " 30-34 4.5 469 \n", + " 35-39 6.1 462 \n", + " 40-44 6.5 434 \n", + " 45-49 6.2 448 \n", + " 50-54 6.5 434 \n", + " 55-59 4.6 455 \n", + " 60-64 6.2 448 \n", + " 65-69 3.1 448 \n", + " 70-74 6.5 434 \n", + " 75-79 4.6 455 \n", + " 80-84 7.9 441 \n", + " 85-89 6.2 448 \n", + " 90+ 8.3 84 \n", + "ethnicity_6_groups Black 6.1 1155 \n", + " Mixed 5.9 1190 \n", + " Other 6.5 1176 \n", + " South Asian 5.8 1204 \n", + " Unknown 5.4 1029 \n", + " White 7.0 1099 \n", + "ethnicity_16_groups African 7.8 357 \n", + " Bangladeshi or British Bangladeshi 4.0 350 \n", + " Caribbean 5.7 371 \n", + " Chinese 7.7 364 \n", + " Other 5.7 371 \n", + " Other Asian 5.8 364 \n", + " British or Mixed British 6.1 343 \n", + " Indian or British Indian 9.4 371 \n", + " Irish 5.8 364 \n", + " Other Black 5.8 364 \n", + " Other White 7.7 364 \n", + " Other mixed 6.0 350 \n", + " Pakistani or British Pakistani 4.3 329 \n", + " Unknown 4.8 1015 \n", + " White + Asian 3.6 385 \n", + " White + Black African 7.1 392 \n", + " White + Black Caribbean 5.3 399 \n", + "imd_categories 1 Most deprived 6.5 1302 \n", + " 2 6.8 1344 \n", + " 3 5.5 1281 \n", + " 4 5.9 1316 \n", + " 5 Least deprived 5.5 1281 \n", + " Unknown 4.3 329 \n", + "bmi 30+ 6.1 2065 \n", + " under 30 5.8 4788 \n", + "housebound no 6.0 6783 \n", + " yes 0.0 70 \n", + "chronic_cardiac_disease no 6.0 6797 \n", + " yes 0.0 63 \n", + "current_copd no 6.0 6776 \n", + " yes 0.0 84 \n", + "dmards no 5.9 6790 \n", + " yes 10.0 70 \n", + "dementia no 6.0 6776 \n", " yes 0.0 77 \n", - "ssri no 5.5 3451 \n", - " yes 0.0 28 \n", - "chemo_or_radio no 5.5 3451 \n", - " yes 0.0 35 \n", - "lung_cancer no 5.5 3444 \n", - " yes 0.0 35 \n", - "cancer_excl_lung_and_haem no 5.5 3444 \n", - " yes 0.0 35 \n", - "haematological_cancer no 5.5 3437 \n", - " yes 0.0 42 \n", - "ckd no 5.6 2744 \n", - " yes 4.8 735 \n", + "psychosis_schiz_bipolar no 6.0 6790 \n", + " yes 0.0 70 \n", + "LD no 6.0 6727 \n", + " yes 0.0 133 \n", + "ssri no 5.9 6790 \n", + " yes 10.0 70 \n", + "chemo_or_radio no 5.9 6790 \n", + " yes 10.0 70 \n", + "lung_cancer no 6.0 6790 \n", + " yes 0.0 63 \n", + "cancer_excl_lung_and_haem no 6.0 6790 \n", + " yes 0.0 70 \n", + "haematological_cancer no 6.0 6783 \n", + " yes 0.0 70 \n", + "ckd no 6.3 5481 \n", + " yes 5.1 1379 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 5.0 \n", - "sex F 4.8 \n", - " M 5.3 \n", + "overall overall 5.6 \n", + "sex F 5.9 \n", + " M 5.5 \n", "ageband_5yr 0 0.0 \n", - " 0-15 3.3 \n", - " 16-17 5.3 \n", - " 18-29 3.0 \n", - " 30-34 2.7 \n", - " 35-39 6.5 \n", - " 40-44 3.3 \n", - " 45-49 9.1 \n", + " 0-15 6.6 \n", + " 16-17 4.6 \n", + " 18-29 4.8 \n", + " 30-34 4.5 \n", + " 35-39 6.1 \n", + " 40-44 6.5 \n", + " 45-49 6.2 \n", " 50-54 6.5 \n", - " 55-59 3.3 \n", - " 60-64 2.9 \n", - " 65-69 6.2 \n", - " 70-74 3.6 \n", - " 75-79 5.9 \n", - " 80-84 5.9 \n", - " 85-89 6.5 \n", + " 55-59 4.6 \n", + " 60-64 6.2 \n", + " 65-69 3.1 \n", + " 70-74 6.5 \n", + " 75-79 4.6 \n", + " 80-84 6.3 \n", + " 85-89 6.2 \n", " 90+ 0.0 \n", - "ethnicity_6_groups Black 5.7 \n", - " Mixed 4.5 \n", - " Other 6.1 \n", - " South Asian 3.7 \n", - " Unknown 6.9 \n", - " White 3.4 \n", - "ethnicity_16_groups African 3.4 \n", - " Bangladeshi or British Bangladeshi 3.6 \n", - " Caribbean 8.0 \n", - " Chinese 0.0 \n", - " Other 0.0 \n", - " Other Asian 3.8 \n", - " British or Mixed British 7.4 \n", - " Indian or British Indian 3.7 \n", - " Irish 4.2 \n", - " Other Black 3.8 \n", - " Other White 3.6 \n", - " Other mixed 3.7 \n", - " Pakistani or British Pakistani 3.8 \n", - " Unknown 5.0 \n", - " White + Asian 3.4 \n", - " White + Black African 7.7 \n", - " White + Black Caribbean 4.0 \n", - "imd_categories 1 Most deprived 4.3 \n", - " 2 5.1 \n", - " 3 5.1 \n", - " 4 5.3 \n", - " 5 Least deprived 5.7 \n", - " Unknown 7.4 \n", - "bmi 30+ 3.2 \n", - " under 30 5.9 \n", - "housebound no 5.1 \n", - " yes 0.0 \n", - "chronic_cardiac_disease no 5.1 \n", - " yes 0.0 \n", - "current_copd no 5.1 \n", - " yes 0.0 \n", - "dmards no 5.1 \n", + "ethnicity_6_groups Black 5.5 \n", + " Mixed 5.3 \n", + " Other 6.5 \n", + " South Asian 5.2 \n", + " Unknown 4.8 \n", + " White 7.0 \n", + "ethnicity_16_groups African 7.8 \n", + " Bangladeshi or British Bangladeshi 4.0 \n", + " Caribbean 3.8 \n", + " Chinese 7.7 \n", + " Other 5.7 \n", + " Other Asian 5.8 \n", + " British or Mixed British 6.1 \n", + " Indian or British Indian 9.4 \n", + " Irish 5.8 \n", + " Other Black 5.8 \n", + " Other White 7.7 \n", + " Other mixed 6.0 \n", + " Pakistani or British Pakistani 4.3 \n", + " Unknown 4.8 \n", + " White + Asian 3.6 \n", + " White + Black African 7.1 \n", + " White + Black Caribbean 5.3 \n", + "imd_categories 1 Most deprived 6.5 \n", + " 2 6.2 \n", + " 3 4.9 \n", + " 4 5.9 \n", + " 5 Least deprived 4.9 \n", + " Unknown 4.3 \n", + "bmi 30+ 5.8 \n", + " under 30 5.6 \n", + "housebound no 5.7 \n", " yes 0.0 \n", - "dementia no 5.1 \n", + "chronic_cardiac_disease no 5.7 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 5.1 \n", + "current_copd no 5.7 \n", " yes 0.0 \n", - "LD no 5.1 \n", + "dmards no 5.6 \n", + " yes 10.0 \n", + "dementia no 5.7 \n", " yes 0.0 \n", - "ssri no 5.1 \n", + "psychosis_schiz_bipolar no 5.7 \n", " yes 0.0 \n", - "chemo_or_radio no 5.1 \n", + "LD no 5.7 \n", " yes 0.0 \n", - "lung_cancer no 5.1 \n", + "ssri no 5.6 \n", + " yes 10.0 \n", + "chemo_or_radio no 5.6 \n", + " yes 10.0 \n", + "lung_cancer no 5.7 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 5.1 \n", + "cancer_excl_lung_and_haem no 5.7 \n", " yes 0.0 \n", - "haematological_cancer no 5.1 \n", + "haematological_cancer no 5.7 \n", " yes 0.0 \n", - "ckd no 5.4 \n", - " yes 4.8 \n", + "ckd no 5.9 \n", + " yes 5.1 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 0.4 \n", - "sex F 0.8 \n", - " M 0.4 \n", + "overall overall 0.3 \n", + "sex F 0.4 \n", + " M 0.2 \n", "ageband_5yr 0 0.0 \n", - " 0-15 3.4 \n", - " 16-17 0.0 \n", - " 18-29 0.0 \n", - " 30-34 2.7 \n", + " 0-15 0.0 \n", + " 16-17 1.6 \n", + " 18-29 1.7 \n", + " 30-34 0.0 \n", " 35-39 0.0 \n", " 40-44 0.0 \n", - " 45-49 3.0 \n", + " 45-49 0.0 \n", " 50-54 0.0 \n", - " 55-59 3.4 \n", + " 55-59 0.0 \n", " 60-64 0.0 \n", " 65-69 0.0 \n", " 70-74 0.0 \n", " 75-79 0.0 \n", - " 80-84 0.0 \n", + " 80-84 1.6 \n", " 85-89 0.0 \n", - " 90+ 0.0 \n", - "ethnicity_6_groups Black 1.2 \n", - " Mixed 0.0 \n", + " 90+ 8.3 \n", + "ethnicity_6_groups Black 0.6 \n", + " Mixed 0.6 \n", " Other 0.0 \n", - " South Asian 1.2 \n", - " Unknown 0.0 \n", - " White 1.2 \n", + " South Asian 0.6 \n", + " Unknown 0.6 \n", + " White 0.0 \n", "ethnicity_16_groups African 0.0 \n", " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", + " Caribbean 1.9 \n", " Chinese 0.0 \n", " Other 0.0 \n", - " Other Asian 3.9 \n", + " Other Asian 0.0 \n", " British or Mixed British 0.0 \n", - " Indian or British Indian 3.7 \n", + " Indian or British Indian 0.0 \n", " Irish 0.0 \n", " Other Black 0.0 \n", - " Other White 3.5 \n", + " Other White 0.0 \n", " Other mixed 0.0 \n", - " Pakistani or British Pakistani 3.9 \n", - " Unknown 1.2 \n", - " White + Asian 3.5 \n", + " Pakistani or British Pakistani 0.0 \n", + " Unknown 0.0 \n", + " White + Asian 0.0 \n", " White + Black African 0.0 \n", - " White + Black Caribbean 4.0 \n", + " White + Black Caribbean 0.0 \n", "imd_categories 1 Most deprived 0.0 \n", - " 2 0.0 \n", - " 3 1.0 \n", + " 2 0.6 \n", + " 3 0.6 \n", " 4 0.0 \n", - " 5 Least deprived 0.0 \n", + " 5 Least deprived 0.6 \n", " Unknown 0.0 \n", - "bmi 30+ 0.6 \n", - " under 30 0.3 \n", - "housebound no 0.4 \n", + "bmi 30+ 0.3 \n", + " under 30 0.2 \n", + "housebound no 0.3 \n", " yes 0.0 \n", - "chronic_cardiac_disease no 0.4 \n", + "chronic_cardiac_disease no 0.3 \n", " yes 0.0 \n", - "current_copd no 0.4 \n", + "current_copd no 0.3 \n", " yes 0.0 \n", - "dmards no 0.4 \n", + "dmards no 0.3 \n", " yes 0.0 \n", - "dementia no 0.4 \n", + "dementia no 0.3 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 0.4 \n", + "psychosis_schiz_bipolar no 0.3 \n", " yes 0.0 \n", - "LD no 0.5 \n", + "LD no 0.3 \n", " yes 0.0 \n", - "ssri no 0.4 \n", + "ssri no 0.3 \n", " yes 0.0 \n", - "chemo_or_radio no 0.4 \n", + "chemo_or_radio no 0.3 \n", " yes 0.0 \n", - "lung_cancer no 0.4 \n", + "lung_cancer no 0.3 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 0.4 \n", + "cancer_excl_lung_and_haem no 0.3 \n", " yes 0.0 \n", - "haematological_cancer no 0.4 \n", + "haematological_cancer no 0.3 \n", " yes 0.0 \n", - "ckd no 0.2 \n", + "ckd no 0.4 \n", " yes 0.0 \n", "\n", " Date projected to reach 90% \n", @@ -35536,7 +35729,7 @@ "sex F unknown \n", " M unknown \n", "ageband_5yr 0 unknown \n", - " 0-15 04-Jun \n", + " 0-15 unknown \n", " 16-17 unknown \n", " 18-29 unknown \n", " 30-34 unknown \n", @@ -35544,14 +35737,14 @@ " 40-44 unknown \n", " 45-49 unknown \n", " 50-54 unknown \n", - " 55-59 04-Jun \n", + " 55-59 unknown \n", " 60-64 unknown \n", " 65-69 unknown \n", " 70-74 unknown \n", " 75-79 unknown \n", " 80-84 unknown \n", " 85-89 unknown \n", - " 90+ unknown \n", + " 90+ 11-Apr \n", "ethnicity_6_groups Black unknown \n", " Mixed unknown \n", " Other unknown \n", @@ -35563,18 +35756,18 @@ " Caribbean unknown \n", " Chinese unknown \n", " Other unknown \n", - " Other Asian 11-May \n", + " Other Asian unknown \n", " British or Mixed British unknown \n", - " Indian or British Indian 20-May \n", + " Indian or British Indian unknown \n", " Irish unknown \n", " Other Black unknown \n", - " Other White 29-May \n", + " Other White unknown \n", " Other mixed unknown \n", - " Pakistani or British Pakistani 11-May \n", + " Pakistani or British Pakistani unknown \n", " Unknown unknown \n", - " White + Asian 30-May \n", + " White + Asian unknown \n", " White + Black African unknown \n", - " White + Black Caribbean 07-May \n", + " White + Black Caribbean unknown \n", "imd_categories 1 Most deprived unknown \n", " 2 unknown \n", " 3 unknown \n", @@ -35637,7 +35830,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (third dose) among **care home** population up to 15 Dec 2021" + "## COVID vaccination rollout (third dose) among **care home** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -35703,93 +35896,102 @@ " \n", " overall\n", " overall\n", - " 70\n", + " 154\n", + " 5.5\n", + " 2821\n", " 5.0\n", - " 1393\n", - " 4.5\n", " 0.5\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 35\n", + " 70\n", " 4.9\n", - " 721\n", + " 1428\n", " 4.9\n", " 0.0\n", " unknown\n", " \n", " \n", " M\n", - " 28\n", - " 4.2\n", - " 672\n", - " 4.2\n", + " 77\n", + " 5.6\n", + " 1386\n", + " 5.6\n", " 0.0\n", " unknown\n", " \n", " \n", - " ageband_5yr\n", - " 0-15\n", + " ageband_5yr\n", + " 0\n", " 0\n", " 0.0\n", - " 91\n", + " 28\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " 16-17\n", - " 0\n", - " 0.0\n", - " 98\n", - " 0.0\n", + " 0-15\n", + " 7\n", + " 4.0\n", + " 175\n", + " 4.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " 18-29\n", - " 0\n", - " 0.0\n", - " 84\n", - " 0.0\n", + " 16-17\n", + " 7\n", + " 3.6\n", + " 196\n", + " 3.6\n", " 0.0\n", " unknown\n", " \n", " \n", - " 30-34\n", + " 18-29\n", " 14\n", - " 16.7\n", - " 84\n", " 8.3\n", - " 8.4\n", - " 14-Feb\n", + " 168\n", + " 4.2\n", + " 4.1\n", + " 21-Jun\n", " \n", " \n", - " 35-39\n", - " 0\n", - " 0.0\n", - " 98\n", - " 0.0\n", + " 30-34\n", + " 7\n", + " 3.7\n", + " 189\n", + " 3.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " 40-44\n", - " 0\n", - " 0.0\n", - " 98\n", - " 0.0\n", + " 35-39\n", + " 7\n", + " 3.7\n", + " 189\n", + " 3.7\n", " 0.0\n", " unknown\n", " \n", " \n", + " 40-44\n", + " 14\n", + " 8.3\n", + " 168\n", + " 4.2\n", + " 4.1\n", + " 21-Jun\n", + " \n", + " \n", " 45-49\n", - " 0\n", - " 0.0\n", - " 91\n", - " 0.0\n", + " 7\n", + " 3.8\n", + " 182\n", + " 3.8\n", " 0.0\n", " unknown\n", " \n", @@ -35797,70 +35999,79 @@ " 50-54\n", " 0\n", " 0.0\n", - " 84\n", + " 182\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 55-59\n", - " 0\n", - " 0.0\n", - " 91\n", - " 0.0\n", + " 7\n", + " 3.6\n", + " 196\n", + " 3.6\n", " 0.0\n", " unknown\n", " \n", " \n", " 60-64\n", - " 0\n", - " 0.0\n", - " 91\n", - " 0.0\n", + " 14\n", + " 7.1\n", + " 196\n", + " 7.1\n", " 0.0\n", " unknown\n", " \n", " \n", " 65-69\n", - " 0\n", - " 0.0\n", - " 84\n", - " 0.0\n", + " 7\n", + " 3.8\n", + " 182\n", + " 3.8\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-74\n", - " 0\n", - " 0.0\n", - " 105\n", - " 0.0\n", + " 7\n", + " 3.7\n", + " 189\n", + " 3.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 75-79\n", - " 0\n", - " 0.0\n", - " 91\n", - " 0.0\n", + " 7\n", + " 4.0\n", + " 175\n", + " 4.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 80-84\n", - " 0\n", - " 0.0\n", - " 77\n", - " 0.0\n", + " 14\n", + " 7.7\n", + " 182\n", + " 7.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 85-89\n", + " 14\n", + " 8.0\n", + " 175\n", + " 8.0\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " 90+\n", " 0\n", " 0.0\n", - " 98\n", + " 49\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -35869,65 +36080,74 @@ " ethnicity_6_groups\n", " Black\n", " 14\n", - " 6.2\n", - " 224\n", - " 6.2\n", + " 3.1\n", + " 448\n", + " 3.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Mixed\n", - " 7\n", - " 2.8\n", - " 252\n", - " 2.8\n", + " 28\n", + " 6.1\n", + " 462\n", + " 6.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 0\n", - " 0.0\n", - " 210\n", - " 0.0\n", - " 0.0\n", + " 35\n", + " 6.9\n", + " 504\n", + " 5.6\n", + " 1.3\n", " unknown\n", " \n", " \n", " South Asian\n", - " 14\n", - " 5.3\n", - " 266\n", - " 5.3\n", + " 21\n", + " 4.5\n", + " 469\n", + " 4.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 14\n", - " 6.7\n", - " 210\n", - " 3.3\n", - " 3.4\n", - " 04-Jun\n", + " 21\n", + " 4.8\n", + " 434\n", + " 4.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White\n", - " 14\n", - " 6.1\n", - " 231\n", - " 6.1\n", - " 0.0\n", + " 28\n", + " 5.7\n", + " 490\n", + " 4.3\n", + " 1.4\n", " unknown\n", " \n", " \n", - " dementia\n", + " dementia\n", " no\n", - " 70\n", - " 5.1\n", - " 1379\n", - " 4.6\n", - " 0.5\n", + " 147\n", + " 5.3\n", + " 2793\n", + " 5.0\n", + " 0.3\n", + " unknown\n", + " \n", + " \n", + " yes\n", + " 0\n", + " 0.0\n", + " 28\n", + " 0.0\n", + " 0.0\n", " unknown\n", " \n", " \n", @@ -35937,71 +36157,78 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 70 5.0 1393 \n", - "sex F 35 4.9 721 \n", - " M 28 4.2 672 \n", - "ageband_5yr 0-15 0 0.0 91 \n", - " 16-17 0 0.0 98 \n", - " 18-29 0 0.0 84 \n", - " 30-34 14 16.7 84 \n", - " 35-39 0 0.0 98 \n", - " 40-44 0 0.0 98 \n", - " 45-49 0 0.0 91 \n", - " 50-54 0 0.0 84 \n", - " 55-59 0 0.0 91 \n", - " 60-64 0 0.0 91 \n", - " 65-69 0 0.0 84 \n", - " 70-74 0 0.0 105 \n", - " 75-79 0 0.0 91 \n", - " 80-84 0 0.0 77 \n", - " 85-89 0 0.0 98 \n", - "ethnicity_6_groups Black 14 6.2 224 \n", - " Mixed 7 2.8 252 \n", - " Other 0 0.0 210 \n", - " South Asian 14 5.3 266 \n", - " Unknown 14 6.7 210 \n", - " White 14 6.1 231 \n", - "dementia no 70 5.1 1379 \n", + "overall overall 154 5.5 2821 \n", + "sex F 70 4.9 1428 \n", + " M 77 5.6 1386 \n", + "ageband_5yr 0 0 0.0 28 \n", + " 0-15 7 4.0 175 \n", + " 16-17 7 3.6 196 \n", + " 18-29 14 8.3 168 \n", + " 30-34 7 3.7 189 \n", + " 35-39 7 3.7 189 \n", + " 40-44 14 8.3 168 \n", + " 45-49 7 3.8 182 \n", + " 50-54 0 0.0 182 \n", + " 55-59 7 3.6 196 \n", + " 60-64 14 7.1 196 \n", + " 65-69 7 3.8 182 \n", + " 70-74 7 3.7 189 \n", + " 75-79 7 4.0 175 \n", + " 80-84 14 7.7 182 \n", + " 85-89 14 8.0 175 \n", + " 90+ 0 0.0 49 \n", + "ethnicity_6_groups Black 14 3.1 448 \n", + " Mixed 28 6.1 462 \n", + " Other 35 6.9 504 \n", + " South Asian 21 4.5 469 \n", + " Unknown 21 4.8 434 \n", + " White 28 5.7 490 \n", + "dementia no 147 5.3 2793 \n", + " yes 0 0.0 28 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 4.5 \n", + "overall overall 5.0 \n", "sex F 4.9 \n", - " M 4.2 \n", - "ageband_5yr 0-15 0.0 \n", - " 16-17 0.0 \n", - " 18-29 0.0 \n", - " 30-34 8.3 \n", - " 35-39 0.0 \n", - " 40-44 0.0 \n", - " 45-49 0.0 \n", + " M 5.6 \n", + "ageband_5yr 0 0.0 \n", + " 0-15 4.0 \n", + " 16-17 3.6 \n", + " 18-29 4.2 \n", + " 30-34 3.7 \n", + " 35-39 3.7 \n", + " 40-44 4.2 \n", + " 45-49 3.8 \n", " 50-54 0.0 \n", - " 55-59 0.0 \n", - " 60-64 0.0 \n", - " 65-69 0.0 \n", - " 70-74 0.0 \n", - " 75-79 0.0 \n", - " 80-84 0.0 \n", - " 85-89 0.0 \n", - "ethnicity_6_groups Black 6.2 \n", - " Mixed 2.8 \n", - " Other 0.0 \n", - " South Asian 5.3 \n", - " Unknown 3.3 \n", - " White 6.1 \n", - "dementia no 4.6 \n", + " 55-59 3.6 \n", + " 60-64 7.1 \n", + " 65-69 3.8 \n", + " 70-74 3.7 \n", + " 75-79 4.0 \n", + " 80-84 7.7 \n", + " 85-89 8.0 \n", + " 90+ 0.0 \n", + "ethnicity_6_groups Black 3.1 \n", + " Mixed 6.1 \n", + " Other 5.6 \n", + " South Asian 4.5 \n", + " Unknown 4.8 \n", + " White 4.3 \n", + "dementia no 5.0 \n", + " yes 0.0 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", "overall overall 0.5 \n", "sex F 0.0 \n", " M 0.0 \n", - "ageband_5yr 0-15 0.0 \n", + "ageband_5yr 0 0.0 \n", + " 0-15 0.0 \n", " 16-17 0.0 \n", - " 18-29 0.0 \n", - " 30-34 8.4 \n", + " 18-29 4.1 \n", + " 30-34 0.0 \n", " 35-39 0.0 \n", - " 40-44 0.0 \n", + " 40-44 4.1 \n", " 45-49 0.0 \n", " 50-54 0.0 \n", " 55-59 0.0 \n", @@ -36011,25 +36238,28 @@ " 75-79 0.0 \n", " 80-84 0.0 \n", " 85-89 0.0 \n", + " 90+ 0.0 \n", "ethnicity_6_groups Black 0.0 \n", " Mixed 0.0 \n", - " Other 0.0 \n", + " Other 1.3 \n", " South Asian 0.0 \n", - " Unknown 3.4 \n", - " White 0.0 \n", - "dementia no 0.5 \n", + " Unknown 0.0 \n", + " White 1.4 \n", + "dementia no 0.3 \n", + " yes 0.0 \n", "\n", " Date projected to reach 90% \n", "category group \n", "overall overall unknown \n", "sex F unknown \n", " M unknown \n", - "ageband_5yr 0-15 unknown \n", + "ageband_5yr 0 unknown \n", + " 0-15 unknown \n", " 16-17 unknown \n", - " 18-29 unknown \n", - " 30-34 14-Feb \n", + " 18-29 21-Jun \n", + " 30-34 unknown \n", " 35-39 unknown \n", - " 40-44 unknown \n", + " 40-44 21-Jun \n", " 45-49 unknown \n", " 50-54 unknown \n", " 55-59 unknown \n", @@ -36039,13 +36269,15 @@ " 75-79 unknown \n", " 80-84 unknown \n", " 85-89 unknown \n", + " 90+ unknown \n", "ethnicity_6_groups Black unknown \n", " Mixed unknown \n", " Other unknown \n", " South Asian unknown \n", - " Unknown 04-Jun \n", + " Unknown unknown \n", " White unknown \n", - "dementia no unknown " + "dementia no unknown \n", + " yes unknown " ] }, "metadata": {}, @@ -36074,7 +36306,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (third dose) among **shielding (aged 16-69)** population up to 15 Dec 2021" + "## COVID vaccination rollout (third dose) among **shielding (aged 16-69)** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -36140,177 +36372,195 @@ " \n", " overall\n", " overall\n", - " 28\n", - " 6.7\n", - " 420\n", - " 6.7\n", - " 0.0\n", + " 56\n", + " 6.5\n", + " 868\n", + " 5.6\n", + " 0.9\n", " unknown\n", " \n", " \n", - " newly_shielded_since_feb_15\n", + " newly_shielded_since_feb_15\n", " no\n", - " 28\n", - " 6.8\n", - " 413\n", - " 6.8\n", + " 49\n", + " 5.7\n", + " 861\n", + " 5.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " sex\n", - " F\n", - " 14\n", - " 6.5\n", - " 217\n", - " 6.5\n", + " yes\n", + " 0\n", + " 0.0\n", + " 7\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " M\n", - " 7\n", - " 3.4\n", - " 203\n", - " 3.4\n", + " sex\n", + " F\n", + " 35\n", + " 7.8\n", + " 448\n", + " 7.8\n", " 0.0\n", " unknown\n", " \n", " \n", - " ageband\n", - " 16-29\n", - " 0\n", - " 0.0\n", - " 56\n", - " 0.0\n", - " 0.0\n", + " M\n", + " 21\n", + " 5.0\n", + " 420\n", + " 3.3\n", + " 1.7\n", " unknown\n", " \n", " \n", - " 30-39\n", + " ageband\n", + " 16-29\n", " 0\n", " 0.0\n", - " 56\n", + " 105\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", + " 30-39\n", + " 7\n", + " 6.7\n", + " 105\n", + " 0.0\n", + " 6.7\n", + " 30-Apr\n", + " \n", + " \n", " 40-49\n", " 0\n", " 0.0\n", - " 49\n", + " 112\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 50-59\n", - " 0\n", - " 0.0\n", - " 70\n", - " 0.0\n", - " 0.0\n", - " unknown\n", + " 14\n", + " 11.1\n", + " 126\n", + " 5.6\n", + " 5.5\n", + " 13-May\n", " \n", " \n", " 60-69\n", - " 0\n", - " 0.0\n", - " 49\n", - " 0.0\n", + " 7\n", + " 6.2\n", + " 112\n", + " 6.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-79\n", - " 7\n", - " 7.7\n", - " 91\n", - " 7.7\n", + " 14\n", + " 6.9\n", + " 203\n", + " 6.9\n", " 0.0\n", " unknown\n", " \n", " \n", - " ethnicity_6_groups\n", - " Black\n", + " 80+\n", " 0\n", " 0.0\n", - " 70\n", + " 112\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " Mixed\n", + " ethnicity_6_groups\n", + " Black\n", " 0\n", " 0.0\n", - " 70\n", + " 140\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " Other\n", - " 0\n", - " 0.0\n", - " 70\n", + " Mixed\n", + " 7\n", + " 4.3\n", + " 161\n", " 0.0\n", + " 4.3\n", + " 21-Jun\n", + " \n", + " \n", + " Other\n", + " 14\n", + " 10.0\n", + " 140\n", + " 10.0\n", " 0.0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 0\n", - " 0.0\n", - " 63\n", - " 0.0\n", + " 7\n", + " 4.8\n", + " 147\n", + " 4.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 0\n", - " 0.0\n", - " 56\n", - " 0.0\n", + " 7\n", + " 5.9\n", + " 119\n", + " 5.9\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", " 7\n", - " 7.7\n", - " 91\n", - " 7.7\n", + " 4.3\n", + " 161\n", + " 4.3\n", " 0.0\n", " unknown\n", " \n", " \n", - " imd_categories\n", + " imd_categories\n", " 1 Most deprived\n", - " 0\n", - " 0.0\n", - " 84\n", - " 0.0\n", + " 14\n", + " 7.7\n", + " 182\n", + " 7.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 2\n", - " 0\n", - " 0.0\n", - " 70\n", - " 0.0\n", - " 0.0\n", - " unknown\n", + " 14\n", + " 9.5\n", + " 147\n", + " 4.8\n", + " 4.7\n", + " 01-Jun\n", " \n", " \n", " 3\n", - " 0\n", - " 0.0\n", - " 84\n", - " 0.0\n", + " 7\n", + " 4.2\n", + " 168\n", + " 4.2\n", " 0.0\n", " unknown\n", " \n", @@ -36318,7 +36568,7 @@ " 4\n", " 0\n", " 0.0\n", - " 84\n", + " 161\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -36326,29 +36576,28 @@ " \n", " 5 Least deprived\n", " 7\n", - " 9.1\n", - " 77\n", - " 9.1\n", + " 4.2\n", + " 168\n", + " 4.2\n", " 0.0\n", " unknown\n", " \n", " \n", - " LD\n", - " no\n", - " 28\n", - " 6.8\n", - " 413\n", - " 6.8\n", + " Unknown\n", + " 0\n", + " 0.0\n", + " 42\n", + " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " ckd\n", + " LD\n", " no\n", - " 21\n", - " 6.5\n", - " 322\n", - " 6.5\n", + " 49\n", + " 5.7\n", + " 854\n", + " 5.7\n", " 0.0\n", " unknown\n", " \n", @@ -36356,8 +36605,27 @@ " yes\n", " 0\n", " 0.0\n", - " 98\n", + " 14\n", + " 0.0\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " ckd\n", + " no\n", + " 42\n", + " 5.8\n", + " 721\n", + " 5.8\n", " 0.0\n", + " unknown\n", + " \n", + " \n", + " yes\n", + " 7\n", + " 4.8\n", + " 147\n", + " 4.8\n", " 0.0\n", " unknown\n", " \n", @@ -36368,82 +36636,94 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 28 6.7 420 \n", - "newly_shielded_since_feb_15 no 28 6.8 413 \n", - "sex F 14 6.5 217 \n", - " M 7 3.4 203 \n", - "ageband 16-29 0 0.0 56 \n", - " 30-39 0 0.0 56 \n", - " 40-49 0 0.0 49 \n", - " 50-59 0 0.0 70 \n", - " 60-69 0 0.0 49 \n", - " 70-79 7 7.7 91 \n", - "ethnicity_6_groups Black 0 0.0 70 \n", - " Mixed 0 0.0 70 \n", - " Other 0 0.0 70 \n", - " South Asian 0 0.0 63 \n", - " Unknown 0 0.0 56 \n", - " White 7 7.7 91 \n", - "imd_categories 1 Most deprived 0 0.0 84 \n", - " 2 0 0.0 70 \n", - " 3 0 0.0 84 \n", - " 4 0 0.0 84 \n", - " 5 Least deprived 7 9.1 77 \n", - "LD no 28 6.8 413 \n", - "ckd no 21 6.5 322 \n", - " yes 0 0.0 98 \n", + "overall overall 56 6.5 868 \n", + "newly_shielded_since_feb_15 no 49 5.7 861 \n", + " yes 0 0.0 7 \n", + "sex F 35 7.8 448 \n", + " M 21 5.0 420 \n", + "ageband 16-29 0 0.0 105 \n", + " 30-39 7 6.7 105 \n", + " 40-49 0 0.0 112 \n", + " 50-59 14 11.1 126 \n", + " 60-69 7 6.2 112 \n", + " 70-79 14 6.9 203 \n", + " 80+ 0 0.0 112 \n", + "ethnicity_6_groups Black 0 0.0 140 \n", + " Mixed 7 4.3 161 \n", + " Other 14 10.0 140 \n", + " South Asian 7 4.8 147 \n", + " Unknown 7 5.9 119 \n", + " White 7 4.3 161 \n", + "imd_categories 1 Most deprived 14 7.7 182 \n", + " 2 14 9.5 147 \n", + " 3 7 4.2 168 \n", + " 4 0 0.0 161 \n", + " 5 Least deprived 7 4.2 168 \n", + " Unknown 0 0.0 42 \n", + "LD no 49 5.7 854 \n", + " yes 0 0.0 14 \n", + "ckd no 42 5.8 721 \n", + " yes 7 4.8 147 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 6.7 \n", - "newly_shielded_since_feb_15 no 6.8 \n", - "sex F 6.5 \n", - " M 3.4 \n", + "overall overall 5.6 \n", + "newly_shielded_since_feb_15 no 5.7 \n", + " yes 0.0 \n", + "sex F 7.8 \n", + " M 3.3 \n", "ageband 16-29 0.0 \n", " 30-39 0.0 \n", " 40-49 0.0 \n", - " 50-59 0.0 \n", - " 60-69 0.0 \n", - " 70-79 7.7 \n", + " 50-59 5.6 \n", + " 60-69 6.2 \n", + " 70-79 6.9 \n", + " 80+ 0.0 \n", "ethnicity_6_groups Black 0.0 \n", " Mixed 0.0 \n", - " Other 0.0 \n", - " South Asian 0.0 \n", - " Unknown 0.0 \n", - " White 7.7 \n", - "imd_categories 1 Most deprived 0.0 \n", - " 2 0.0 \n", - " 3 0.0 \n", + " Other 10.0 \n", + " South Asian 4.8 \n", + " Unknown 5.9 \n", + " White 4.3 \n", + "imd_categories 1 Most deprived 7.7 \n", + " 2 4.8 \n", + " 3 4.2 \n", " 4 0.0 \n", - " 5 Least deprived 9.1 \n", - "LD no 6.8 \n", - "ckd no 6.5 \n", + " 5 Least deprived 4.2 \n", + " Unknown 0.0 \n", + "LD no 5.7 \n", " yes 0.0 \n", + "ckd no 5.8 \n", + " yes 4.8 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 0.0 \n", + "overall overall 0.9 \n", "newly_shielded_since_feb_15 no 0.0 \n", + " yes 0.0 \n", "sex F 0.0 \n", - " M 0.0 \n", + " M 1.7 \n", "ageband 16-29 0.0 \n", - " 30-39 0.0 \n", + " 30-39 6.7 \n", " 40-49 0.0 \n", - " 50-59 0.0 \n", + " 50-59 5.5 \n", " 60-69 0.0 \n", " 70-79 0.0 \n", + " 80+ 0.0 \n", "ethnicity_6_groups Black 0.0 \n", - " Mixed 0.0 \n", + " Mixed 4.3 \n", " Other 0.0 \n", " South Asian 0.0 \n", " Unknown 0.0 \n", " White 0.0 \n", "imd_categories 1 Most deprived 0.0 \n", - " 2 0.0 \n", + " 2 4.7 \n", " 3 0.0 \n", " 4 0.0 \n", " 5 Least deprived 0.0 \n", + " Unknown 0.0 \n", "LD no 0.0 \n", + " yes 0.0 \n", "ckd no 0.0 \n", " yes 0.0 \n", "\n", @@ -36451,26 +36731,30 @@ "category group \n", "overall overall unknown \n", "newly_shielded_since_feb_15 no unknown \n", + " yes unknown \n", "sex F unknown \n", " M unknown \n", "ageband 16-29 unknown \n", - " 30-39 unknown \n", + " 30-39 30-Apr \n", " 40-49 unknown \n", - " 50-59 unknown \n", + " 50-59 13-May \n", " 60-69 unknown \n", " 70-79 unknown \n", + " 80+ unknown \n", "ethnicity_6_groups Black unknown \n", - " Mixed unknown \n", + " Mixed 21-Jun \n", " Other unknown \n", " South Asian unknown \n", " Unknown unknown \n", " White unknown \n", "imd_categories 1 Most deprived unknown \n", - " 2 unknown \n", + " 2 01-Jun \n", " 3 unknown \n", " 4 unknown \n", " 5 Least deprived unknown \n", + " Unknown unknown \n", "LD no unknown \n", + " yes unknown \n", "ckd no unknown \n", " yes unknown " ] @@ -36501,7 +36785,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (third dose) among **65-69** population up to 15 Dec 2021" + "## COVID vaccination rollout (third dose) among **65-69** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -36567,340 +36851,349 @@ " \n", " overall\n", " overall\n", - " 126\n", - " 5.8\n", - " 2170\n", - " 5.5\n", + " 287\n", + " 6.5\n", + " 4417\n", + " 6.2\n", " 0.3\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 77\n", - " 7.2\n", - " 1071\n", - " 5.9\n", - " 1.3\n", + " 154\n", + " 6.9\n", + " 2226\n", + " 6.6\n", + " 0.3\n", " unknown\n", " \n", " \n", " M\n", - " 49\n", - " 4.5\n", - " 1099\n", - " 4.5\n", + " 133\n", + " 6.1\n", + " 2191\n", + " 6.1\n", " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 14\n", - " 3.8\n", - " 371\n", - " 3.8\n", + " 42\n", + " 5.6\n", + " 756\n", + " 5.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Mixed\n", - " 21\n", - " 6.0\n", - " 350\n", - " 6.0\n", - " 0.0\n", + " 56\n", + " 7.3\n", + " 770\n", + " 6.4\n", + " 0.9\n", " unknown\n", " \n", " \n", " Other\n", - " 14\n", - " 4.0\n", - " 350\n", - " 4.0\n", - " 0.0\n", + " 56\n", + " 7.5\n", + " 749\n", + " 6.5\n", + " 1.0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 21\n", - " 5.3\n", - " 399\n", - " 5.3\n", + " 35\n", + " 5.0\n", + " 707\n", + " 5.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 28\n", - " 8.3\n", - " 336\n", - " 6.2\n", - " 2.1\n", + " 49\n", + " 7.0\n", + " 700\n", + " 7.0\n", + " 0.0\n", " unknown\n", " \n", " \n", " White\n", - " 28\n", - " 7.7\n", - " 364\n", - " 5.8\n", - " 1.9\n", + " 56\n", + " 7.6\n", + " 735\n", + " 7.6\n", + " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 0\n", - " 0.0\n", - " 112\n", - " 0.0\n", + " 14\n", + " 6.2\n", + " 224\n", + " 6.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 7\n", - " 5.6\n", - " 126\n", - " 5.6\n", + " 14\n", + " 6.1\n", + " 231\n", + " 6.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 0\n", - " 0.0\n", - " 105\n", - " 0.0\n", + " 14\n", + " 5.9\n", + " 238\n", + " 5.9\n", " 0.0\n", " unknown\n", " \n", " \n", " Chinese\n", - " 7\n", - " 6.2\n", - " 112\n", + " 14\n", + " 5.7\n", + " 245\n", + " 5.7\n", " 0.0\n", - " 6.2\n", - " 19-Mar\n", + " unknown\n", " \n", " \n", " Other\n", - " 0\n", - " 0.0\n", - " 133\n", - " 0.0\n", + " 14\n", + " 5.3\n", + " 266\n", + " 5.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 7\n", - " 5.6\n", - " 126\n", - " 5.6\n", + " 14\n", + " 6.5\n", + " 217\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " British or Mixed British\n", - " 7\n", - " 6.2\n", - " 112\n", - " 6.2\n", + " 21\n", + " 8.8\n", + " 238\n", + " 8.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 7\n", - " 6.7\n", - " 105\n", - " 6.7\n", + " 21\n", + " 8.6\n", + " 245\n", + " 8.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 7\n", - " 6.2\n", - " 112\n", - " 6.2\n", + " 14\n", + " 6.1\n", + " 231\n", + " 6.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 0\n", - " 0.0\n", - " 112\n", - " 0.0\n", - " 0.0\n", + " 21\n", + " 8.8\n", + " 238\n", + " 5.9\n", + " 2.9\n", " unknown\n", " \n", " \n", " Other White\n", - " 0\n", - " 0.0\n", - " 112\n", - " 0.0\n", + " 14\n", + " 5.9\n", + " 238\n", + " 5.9\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 0\n", - " 0.0\n", - " 91\n", - " 0.0\n", + " 14\n", + " 5.6\n", + " 252\n", + " 5.6\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 7\n", - " 5.3\n", - " 133\n", - " 5.3\n", + " 14\n", + " 5.9\n", + " 238\n", + " 5.9\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 14\n", - " 4.3\n", - " 329\n", - " 4.3\n", + " 49\n", + " 7.9\n", + " 623\n", + " 7.9\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 14\n", - " 12.5\n", - " 112\n", - " 6.2\n", - " 6.3\n", - " 11-Mar\n", + " 7\n", + " 3.1\n", + " 224\n", + " 3.1\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black African\n", - " 0\n", - " 0.0\n", - " 119\n", - " 0.0\n", + " 14\n", + " 7.1\n", + " 196\n", + " 7.1\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", " 14\n", - " 11.1\n", - " 126\n", - " 11.1\n", + " 5.4\n", + " 259\n", + " 5.4\n", " 0.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 28\n", - " 7.1\n", - " 392\n", - " 7.1\n", - " 0.0\n", + " 35\n", + " 4.3\n", + " 819\n", + " 3.4\n", + " 0.9\n", " unknown\n", " \n", " \n", " 2\n", - " 21\n", - " 4.7\n", - " 448\n", - " 3.1\n", - " 1.6\n", + " 56\n", + " 6.7\n", + " 840\n", + " 6.7\n", + " 0.0\n", " unknown\n", " \n", " \n", " 3\n", - " 28\n", - " 6.8\n", - " 413\n", - " 6.8\n", + " 63\n", + " 7.4\n", + " 854\n", + " 7.4\n", " 0.0\n", " unknown\n", " \n", " \n", " 4\n", - " 21\n", - " 5.2\n", - " 406\n", - " 5.2\n", + " 70\n", + " 8.3\n", + " 840\n", + " 8.3\n", " 0.0\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 21\n", - " 5.2\n", - " 406\n", - " 3.4\n", - " 1.8\n", + " 49\n", + " 5.8\n", + " 840\n", + " 5.8\n", + " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 0\n", - " 0.0\n", - " 105\n", - " 0.0\n", + " 14\n", + " 6.5\n", + " 217\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 42\n", - " 6.8\n", - " 616\n", - " 6.8\n", + " 91\n", + " 6.7\n", + " 1365\n", + " 6.7\n", " 0.0\n", " unknown\n", " \n", " \n", " under 30\n", - " 84\n", - " 5.4\n", - " 1554\n", - " 5.0\n", - " 0.4\n", + " 196\n", + " 6.4\n", + " 3052\n", + " 6.2\n", + " 0.2\n", " unknown\n", " \n", " \n", - " housebound\n", + " housebound\n", " no\n", - " 126\n", - " 5.8\n", - " 2156\n", - " 5.5\n", + " 287\n", + " 6.6\n", + " 4361\n", + " 6.3\n", " 0.3\n", " unknown\n", " \n", " \n", + " yes\n", + " 0\n", + " 0.0\n", + " 49\n", + " 0.0\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", " chronic_cardiac_disease\n", " no\n", - " 126\n", - " 5.9\n", - " 2135\n", - " 5.2\n", - " 0.7\n", + " 280\n", + " 6.4\n", + " 4368\n", + " 6.2\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 49\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -36908,18 +37201,18 @@ " \n", " current_copd\n", " no\n", - " 126\n", - " 5.9\n", - " 2149\n", - " 5.2\n", - " 0.7\n", + " 287\n", + " 6.6\n", + " 4375\n", + " 6.2\n", + " 0.4\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 42\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -36927,47 +37220,56 @@ " \n", " dmards\n", " no\n", - " 126\n", - " 5.9\n", - " 2149\n", - " 5.2\n", - " 0.7\n", + " 287\n", + " 6.6\n", + " 4368\n", + " 6.2\n", + " 0.4\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 49\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " dementia\n", + " dementia\n", " no\n", - " 126\n", - " 5.9\n", - " 2149\n", - " 5.5\n", + " 287\n", + " 6.6\n", + " 4368\n", + " 6.2\n", " 0.4\n", " unknown\n", " \n", " \n", + " yes\n", + " 0\n", + " 0.0\n", + " 42\n", + " 0.0\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", " psychosis_schiz_bipolar\n", " no\n", - " 126\n", - " 5.9\n", - " 2149\n", - " 5.2\n", - " 0.7\n", + " 280\n", + " 6.4\n", + " 4368\n", + " 6.2\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 49\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -36975,107 +37277,134 @@ " \n", " LD\n", " no\n", - " 126\n", - " 5.9\n", - " 2128\n", - " 5.3\n", - " 0.6\n", + " 280\n", + " 6.5\n", + " 4312\n", + " 6.2\n", + " 0.3\n", + " unknown\n", + " \n", + " \n", + " yes\n", + " 7\n", + " 6.7\n", + " 105\n", + " 6.7\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " ssri\n", + " no\n", + " 287\n", + " 6.6\n", + " 4375\n", + " 6.2\n", + " 0.4\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 42\n", + " 35\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " ssri\n", + " chemo_or_radio\n", " no\n", - " 126\n", - " 5.9\n", - " 2149\n", - " 5.5\n", + " 287\n", + " 6.6\n", + " 4375\n", + " 6.2\n", " 0.4\n", " unknown\n", " \n", " \n", - " chemo_or_radio\n", - " no\n", - " 126\n", - " 5.9\n", - " 2149\n", - " 5.5\n", - " 0.4\n", + " yes\n", + " 0\n", + " 0.0\n", + " 42\n", + " 0.0\n", + " 0.0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 126\n", - " 5.9\n", - " 2149\n", - " 5.2\n", - " 0.7\n", + " 280\n", + " 6.4\n", + " 4382\n", + " 6.1\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 21\n", - " 0.0\n", + " 7\n", + " 20.0\n", + " 35\n", + " 20.0\n", " 0.0\n", " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 126\n", - " 5.9\n", - " 2149\n", - " 5.2\n", - " 0.7\n", + " 287\n", + " 6.6\n", + " 4375\n", + " 6.2\n", + " 0.4\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 35\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " haematological_cancer\n", + " haematological_cancer\n", " no\n", - " 126\n", - " 5.9\n", - " 2149\n", - " 5.5\n", + " 287\n", + " 6.6\n", + " 4368\n", + " 6.2\n", " 0.4\n", " unknown\n", " \n", " \n", + " yes\n", + " 0\n", + " 0.0\n", + " 42\n", + " 0.0\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", " ckd\n", " no\n", - " 105\n", - " 6.0\n", - " 1736\n", - " 5.6\n", - " 0.4\n", + " 231\n", + " 6.7\n", + " 3472\n", + " 6.5\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", - " 21\n", - " 4.8\n", - " 434\n", - " 4.8\n", - " 0.0\n", + " 56\n", + " 6.0\n", + " 938\n", + " 5.2\n", + " 0.8\n", " unknown\n", " \n", " \n", @@ -37085,235 +37414,255 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 126 \n", - "sex F 77 \n", - " M 49 \n", - "ethnicity_6_groups Black 14 \n", - " Mixed 21 \n", - " Other 14 \n", - " South Asian 21 \n", - " Unknown 28 \n", - " White 28 \n", - "ethnicity_16_groups African 0 \n", - " Bangladeshi or British Bangladeshi 7 \n", - " Caribbean 0 \n", - " Chinese 7 \n", - " Other 0 \n", - " Other Asian 7 \n", - " British or Mixed British 7 \n", - " Indian or British Indian 7 \n", - " Irish 7 \n", - " Other Black 0 \n", - " Other White 0 \n", - " Other mixed 0 \n", - " Pakistani or British Pakistani 7 \n", - " Unknown 14 \n", - " White + Asian 14 \n", - " White + Black African 0 \n", + "overall overall 287 \n", + "sex F 154 \n", + " M 133 \n", + "ethnicity_6_groups Black 42 \n", + " Mixed 56 \n", + " Other 56 \n", + " South Asian 35 \n", + " Unknown 49 \n", + " White 56 \n", + "ethnicity_16_groups African 14 \n", + " Bangladeshi or British Bangladeshi 14 \n", + " Caribbean 14 \n", + " Chinese 14 \n", + " Other 14 \n", + " Other Asian 14 \n", + " British or Mixed British 21 \n", + " Indian or British Indian 21 \n", + " Irish 14 \n", + " Other Black 21 \n", + " Other White 14 \n", + " Other mixed 14 \n", + " Pakistani or British Pakistani 14 \n", + " Unknown 49 \n", + " White + Asian 7 \n", + " White + Black African 14 \n", " White + Black Caribbean 14 \n", - "imd_categories 1 Most deprived 28 \n", - " 2 21 \n", - " 3 28 \n", - " 4 21 \n", - " 5 Least deprived 21 \n", - " Unknown 0 \n", - "bmi 30+ 42 \n", - " under 30 84 \n", - "housebound no 126 \n", - "chronic_cardiac_disease no 126 \n", + "imd_categories 1 Most deprived 35 \n", + " 2 56 \n", + " 3 63 \n", + " 4 70 \n", + " 5 Least deprived 49 \n", + " Unknown 14 \n", + "bmi 30+ 91 \n", + " under 30 196 \n", + "housebound no 287 \n", " yes 0 \n", - "current_copd no 126 \n", + "chronic_cardiac_disease no 280 \n", " yes 0 \n", - "dmards no 126 \n", + "current_copd no 287 \n", " yes 0 \n", - "dementia no 126 \n", - "psychosis_schiz_bipolar no 126 \n", + "dmards no 287 \n", " yes 0 \n", - "LD no 126 \n", + "dementia no 287 \n", " yes 0 \n", - "ssri no 126 \n", - "chemo_or_radio no 126 \n", - "lung_cancer no 126 \n", + "psychosis_schiz_bipolar no 280 \n", " yes 0 \n", - "cancer_excl_lung_and_haem no 126 \n", + "LD no 280 \n", + " yes 7 \n", + "ssri no 287 \n", " yes 0 \n", - "haematological_cancer no 126 \n", - "ckd no 105 \n", - " yes 21 \n", + "chemo_or_radio no 287 \n", + " yes 0 \n", + "lung_cancer no 280 \n", + " yes 7 \n", + "cancer_excl_lung_and_haem no 287 \n", + " yes 0 \n", + "haematological_cancer no 287 \n", + " yes 0 \n", + "ckd no 231 \n", + " yes 56 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 5.8 2170 \n", - "sex F 7.2 1071 \n", - " M 4.5 1099 \n", - "ethnicity_6_groups Black 3.8 371 \n", - " Mixed 6.0 350 \n", - " Other 4.0 350 \n", - " South Asian 5.3 399 \n", - " Unknown 8.3 336 \n", - " White 7.7 364 \n", - "ethnicity_16_groups African 0.0 112 \n", - " Bangladeshi or British Bangladeshi 5.6 126 \n", - " Caribbean 0.0 105 \n", - " Chinese 6.2 112 \n", - " Other 0.0 133 \n", - " Other Asian 5.6 126 \n", - " British or Mixed British 6.2 112 \n", - " Indian or British Indian 6.7 105 \n", - " Irish 6.2 112 \n", - " Other Black 0.0 112 \n", - " Other White 0.0 112 \n", - " Other mixed 0.0 91 \n", - " Pakistani or British Pakistani 5.3 133 \n", - " Unknown 4.3 329 \n", - " White + Asian 12.5 112 \n", - " White + Black African 0.0 119 \n", - " White + Black Caribbean 11.1 126 \n", - "imd_categories 1 Most deprived 7.1 392 \n", - " 2 4.7 448 \n", - " 3 6.8 413 \n", - " 4 5.2 406 \n", - " 5 Least deprived 5.2 406 \n", - " Unknown 0.0 105 \n", - "bmi 30+ 6.8 616 \n", - " under 30 5.4 1554 \n", - "housebound no 5.8 2156 \n", - "chronic_cardiac_disease no 5.9 2135 \n", + "overall overall 6.5 4417 \n", + "sex F 6.9 2226 \n", + " M 6.1 2191 \n", + "ethnicity_6_groups Black 5.6 756 \n", + " Mixed 7.3 770 \n", + " Other 7.5 749 \n", + " South Asian 5.0 707 \n", + " Unknown 7.0 700 \n", + " White 7.6 735 \n", + "ethnicity_16_groups African 6.2 224 \n", + " Bangladeshi or British Bangladeshi 6.1 231 \n", + " Caribbean 5.9 238 \n", + " Chinese 5.7 245 \n", + " Other 5.3 266 \n", + " Other Asian 6.5 217 \n", + " British or Mixed British 8.8 238 \n", + " Indian or British Indian 8.6 245 \n", + " Irish 6.1 231 \n", + " Other Black 8.8 238 \n", + " Other White 5.9 238 \n", + " Other mixed 5.6 252 \n", + " Pakistani or British Pakistani 5.9 238 \n", + " Unknown 7.9 623 \n", + " White + Asian 3.1 224 \n", + " White + Black African 7.1 196 \n", + " White + Black Caribbean 5.4 259 \n", + "imd_categories 1 Most deprived 4.3 819 \n", + " 2 6.7 840 \n", + " 3 7.4 854 \n", + " 4 8.3 840 \n", + " 5 Least deprived 5.8 840 \n", + " Unknown 6.5 217 \n", + "bmi 30+ 6.7 1365 \n", + " under 30 6.4 3052 \n", + "housebound no 6.6 4361 \n", + " yes 0.0 49 \n", + "chronic_cardiac_disease no 6.4 4368 \n", + " yes 0.0 49 \n", + "current_copd no 6.6 4375 \n", + " yes 0.0 42 \n", + "dmards no 6.6 4368 \n", + " yes 0.0 49 \n", + "dementia no 6.6 4368 \n", + " yes 0.0 42 \n", + "psychosis_schiz_bipolar no 6.4 4368 \n", + " yes 0.0 49 \n", + "LD no 6.5 4312 \n", + " yes 6.7 105 \n", + "ssri no 6.6 4375 \n", + " yes 0.0 35 \n", + "chemo_or_radio no 6.6 4375 \n", + " yes 0.0 42 \n", + "lung_cancer no 6.4 4382 \n", + " yes 20.0 35 \n", + "cancer_excl_lung_and_haem no 6.6 4375 \n", " yes 0.0 35 \n", - "current_copd no 5.9 2149 \n", - " yes 0.0 21 \n", - "dmards no 5.9 2149 \n", - " yes 0.0 21 \n", - "dementia no 5.9 2149 \n", - "psychosis_schiz_bipolar no 5.9 2149 \n", - " yes 0.0 21 \n", - "LD no 5.9 2128 \n", + "haematological_cancer no 6.6 4368 \n", " yes 0.0 42 \n", - "ssri no 5.9 2149 \n", - "chemo_or_radio no 5.9 2149 \n", - "lung_cancer no 5.9 2149 \n", - " yes 0.0 21 \n", - "cancer_excl_lung_and_haem no 5.9 2149 \n", - " yes 0.0 21 \n", - "haematological_cancer no 5.9 2149 \n", - "ckd no 6.0 1736 \n", - " yes 4.8 434 \n", + "ckd no 6.7 3472 \n", + " yes 6.0 938 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 5.5 \n", - "sex F 5.9 \n", - " M 4.5 \n", - "ethnicity_6_groups Black 3.8 \n", - " Mixed 6.0 \n", - " Other 4.0 \n", - " South Asian 5.3 \n", - " Unknown 6.2 \n", - " White 5.8 \n", - "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 5.6 \n", - " Caribbean 0.0 \n", - " Chinese 0.0 \n", - " Other 0.0 \n", - " Other Asian 5.6 \n", - " British or Mixed British 6.2 \n", - " Indian or British Indian 6.7 \n", - " Irish 6.2 \n", - " Other Black 0.0 \n", - " Other White 0.0 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 5.3 \n", - " Unknown 4.3 \n", - " White + Asian 6.2 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 11.1 \n", - "imd_categories 1 Most deprived 7.1 \n", - " 2 3.1 \n", - " 3 6.8 \n", - " 4 5.2 \n", - " 5 Least deprived 3.4 \n", - " Unknown 0.0 \n", - "bmi 30+ 6.8 \n", - " under 30 5.0 \n", - "housebound no 5.5 \n", - "chronic_cardiac_disease no 5.2 \n", + "overall overall 6.2 \n", + "sex F 6.6 \n", + " M 6.1 \n", + "ethnicity_6_groups Black 5.6 \n", + " Mixed 6.4 \n", + " Other 6.5 \n", + " South Asian 5.0 \n", + " Unknown 7.0 \n", + " White 7.6 \n", + "ethnicity_16_groups African 6.2 \n", + " Bangladeshi or British Bangladeshi 6.1 \n", + " Caribbean 5.9 \n", + " Chinese 5.7 \n", + " Other 5.3 \n", + " Other Asian 6.5 \n", + " British or Mixed British 8.8 \n", + " Indian or British Indian 8.6 \n", + " Irish 6.1 \n", + " Other Black 5.9 \n", + " Other White 5.9 \n", + " Other mixed 5.6 \n", + " Pakistani or British Pakistani 5.9 \n", + " Unknown 7.9 \n", + " White + Asian 3.1 \n", + " White + Black African 7.1 \n", + " White + Black Caribbean 5.4 \n", + "imd_categories 1 Most deprived 3.4 \n", + " 2 6.7 \n", + " 3 7.4 \n", + " 4 8.3 \n", + " 5 Least deprived 5.8 \n", + " Unknown 6.5 \n", + "bmi 30+ 6.7 \n", + " under 30 6.2 \n", + "housebound no 6.3 \n", + " yes 0.0 \n", + "chronic_cardiac_disease no 6.2 \n", + " yes 0.0 \n", + "current_copd no 6.2 \n", + " yes 0.0 \n", + "dmards no 6.2 \n", " yes 0.0 \n", - "current_copd no 5.2 \n", + "dementia no 6.2 \n", " yes 0.0 \n", - "dmards no 5.2 \n", + "psychosis_schiz_bipolar no 6.2 \n", " yes 0.0 \n", - "dementia no 5.5 \n", - "psychosis_schiz_bipolar no 5.2 \n", + "LD no 6.2 \n", + " yes 6.7 \n", + "ssri no 6.2 \n", " yes 0.0 \n", - "LD no 5.3 \n", + "chemo_or_radio no 6.2 \n", " yes 0.0 \n", - "ssri no 5.5 \n", - "chemo_or_radio no 5.5 \n", - "lung_cancer no 5.2 \n", + "lung_cancer no 6.1 \n", + " yes 20.0 \n", + "cancer_excl_lung_and_haem no 6.2 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 5.2 \n", + "haematological_cancer no 6.2 \n", " yes 0.0 \n", - "haematological_cancer no 5.5 \n", - "ckd no 5.6 \n", - " yes 4.8 \n", + "ckd no 6.5 \n", + " yes 5.2 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", "overall overall 0.3 \n", - "sex F 1.3 \n", + "sex F 0.3 \n", " M 0.0 \n", "ethnicity_6_groups Black 0.0 \n", - " Mixed 0.0 \n", - " Other 0.0 \n", + " Mixed 0.9 \n", + " Other 1.0 \n", " South Asian 0.0 \n", - " Unknown 2.1 \n", - " White 1.9 \n", + " Unknown 0.0 \n", + " White 0.0 \n", "ethnicity_16_groups African 0.0 \n", " Bangladeshi or British Bangladeshi 0.0 \n", " Caribbean 0.0 \n", - " Chinese 6.2 \n", + " Chinese 0.0 \n", " Other 0.0 \n", " Other Asian 0.0 \n", " British or Mixed British 0.0 \n", " Indian or British Indian 0.0 \n", " Irish 0.0 \n", - " Other Black 0.0 \n", + " Other Black 2.9 \n", " Other White 0.0 \n", " Other mixed 0.0 \n", " Pakistani or British Pakistani 0.0 \n", " Unknown 0.0 \n", - " White + Asian 6.3 \n", + " White + Asian 0.0 \n", " White + Black African 0.0 \n", " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 0.0 \n", - " 2 1.6 \n", + "imd_categories 1 Most deprived 0.9 \n", + " 2 0.0 \n", " 3 0.0 \n", " 4 0.0 \n", - " 5 Least deprived 1.8 \n", + " 5 Least deprived 0.0 \n", " Unknown 0.0 \n", "bmi 30+ 0.0 \n", - " under 30 0.4 \n", + " under 30 0.2 \n", "housebound no 0.3 \n", - "chronic_cardiac_disease no 0.7 \n", " yes 0.0 \n", - "current_copd no 0.7 \n", + "chronic_cardiac_disease no 0.2 \n", + " yes 0.0 \n", + "current_copd no 0.4 \n", " yes 0.0 \n", - "dmards no 0.7 \n", + "dmards no 0.4 \n", " yes 0.0 \n", "dementia no 0.4 \n", - "psychosis_schiz_bipolar no 0.7 \n", " yes 0.0 \n", - "LD no 0.6 \n", + "psychosis_schiz_bipolar no 0.2 \n", + " yes 0.0 \n", + "LD no 0.3 \n", " yes 0.0 \n", "ssri no 0.4 \n", + " yes 0.0 \n", "chemo_or_radio no 0.4 \n", - "lung_cancer no 0.7 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 0.7 \n", + "lung_cancer no 0.3 \n", + " yes 0.0 \n", + "cancer_excl_lung_and_haem no 0.4 \n", " yes 0.0 \n", "haematological_cancer no 0.4 \n", - "ckd no 0.4 \n", " yes 0.0 \n", + "ckd no 0.2 \n", + " yes 0.8 \n", "\n", " Date projected to reach 90% \n", "category group \n", @@ -37329,7 +37678,7 @@ "ethnicity_16_groups African unknown \n", " Bangladeshi or British Bangladeshi unknown \n", " Caribbean unknown \n", - " Chinese 19-Mar \n", + " Chinese unknown \n", " Other unknown \n", " Other Asian unknown \n", " British or Mixed British unknown \n", @@ -37340,7 +37689,7 @@ " Other mixed unknown \n", " Pakistani or British Pakistani unknown \n", " Unknown unknown \n", - " White + Asian 11-Mar \n", + " White + Asian unknown \n", " White + Black African unknown \n", " White + Black Caribbean unknown \n", "imd_categories 1 Most deprived unknown \n", @@ -37352,6 +37701,7 @@ "bmi 30+ unknown \n", " under 30 unknown \n", "housebound no unknown \n", + " yes unknown \n", "chronic_cardiac_disease no unknown \n", " yes unknown \n", "current_copd no unknown \n", @@ -37359,17 +37709,21 @@ "dmards no unknown \n", " yes unknown \n", "dementia no unknown \n", + " yes unknown \n", "psychosis_schiz_bipolar no unknown \n", " yes unknown \n", "LD no unknown \n", " yes unknown \n", "ssri no unknown \n", + " yes unknown \n", "chemo_or_radio no unknown \n", + " yes unknown \n", "lung_cancer no unknown \n", " yes unknown \n", "cancer_excl_lung_and_haem no unknown \n", " yes unknown \n", "haematological_cancer no unknown \n", + " yes unknown \n", "ckd no unknown \n", " yes unknown " ] @@ -37400,7 +37754,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (third dose) among **LD (aged 16-64)** population up to 15 Dec 2021" + "## COVID vaccination rollout (third dose) among **LD (aged 16-64)** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -37466,38 +37820,38 @@ " \n", " overall\n", " overall\n", - " 56\n", - " 7.0\n", - " 805\n", - " 6.1\n", - " 0.9\n", + " 91\n", + " 5.7\n", + " 1603\n", + " 5.7\n", + " 0.0\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 28\n", - " 6.8\n", - " 413\n", - " 5.1\n", - " 1.7\n", + " 42\n", + " 5.3\n", + " 791\n", + " 5.3\n", + " 0.0\n", " unknown\n", " \n", " \n", " M\n", - " 28\n", - " 7.1\n", - " 392\n", - " 5.4\n", - " 1.7\n", + " 49\n", + " 6.0\n", + " 812\n", + " 6.0\n", + " 0.0\n", " unknown\n", " \n", " \n", - " ageband_5yr\n", + " ageband_5yr\n", " 0\n", " 0\n", " 0.0\n", - " 7\n", + " 21\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -37506,17 +37860,17 @@ " 0-15\n", " 0\n", " 0.0\n", - " 49\n", + " 105\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 16-17\n", - " 0\n", - " 0.0\n", - " 49\n", - " 0.0\n", + " 7\n", + " 6.2\n", + " 112\n", + " 6.2\n", " 0.0\n", " unknown\n", " \n", @@ -37524,7 +37878,7 @@ " 18-29\n", " 0\n", " 0.0\n", - " 49\n", + " 105\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -37533,7 +37887,7 @@ " 30-34\n", " 0\n", " 0.0\n", - " 42\n", + " 98\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -37542,17 +37896,17 @@ " 35-39\n", " 0\n", " 0.0\n", - " 49\n", + " 105\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 40-44\n", - " 0\n", - " 0.0\n", - " 49\n", - " 0.0\n", + " 7\n", + " 8.3\n", + " 84\n", + " 8.3\n", " 0.0\n", " unknown\n", " \n", @@ -37560,7 +37914,7 @@ " 45-49\n", " 0\n", " 0.0\n", - " 56\n", + " 119\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -37569,7 +37923,7 @@ " 50-54\n", " 0\n", " 0.0\n", - " 56\n", + " 133\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -37578,7 +37932,7 @@ " 55-59\n", " 0\n", " 0.0\n", - " 49\n", + " 105\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -37587,7 +37941,7 @@ " 60-64\n", " 0\n", " 0.0\n", - " 56\n", + " 98\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -37595,102 +37949,111 @@ " \n", " 65-69\n", " 7\n", - " 11.1\n", - " 63\n", - " 11.1\n", + " 7.1\n", + " 98\n", + " 7.1\n", " 0.0\n", " unknown\n", " \n", " \n", " 70-74\n", - " 0\n", + " 7\n", + " 7.7\n", + " 91\n", " 0.0\n", - " 49\n", + " 7.7\n", + " 17-Apr\n", + " \n", + " \n", + " 75-79\n", + " 7\n", + " 6.7\n", + " 105\n", + " 6.7\n", " 0.0\n", + " unknown\n", + " \n", + " \n", + " 80-84\n", + " 7\n", + " 7.1\n", + " 98\n", + " 7.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " 75-79\n", + " 85-89\n", " 0\n", " 0.0\n", - " 63\n", + " 105\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " 80-84\n", + " 90+\n", " 0\n", " 0.0\n", - " 49\n", + " 14\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " 85-89\n", - " 7\n", - " 14.3\n", - " 49\n", - " 0.0\n", - " 14.3\n", - " 21-Jan\n", - " \n", - " \n", " ethnicity_6_groups\n", " Black\n", - " 7\n", - " 5.6\n", - " 126\n", - " 0.0\n", - " 5.6\n", - " 30-Mar\n", + " 21\n", + " 7.7\n", + " 273\n", + " 5.1\n", + " 2.6\n", + " unknown\n", " \n", " \n", " Mixed\n", - " 7\n", - " 4.3\n", - " 161\n", - " 4.3\n", + " 14\n", + " 5.0\n", + " 280\n", + " 5.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 7\n", - " 5.3\n", - " 133\n", - " 5.3\n", + " 14\n", + " 4.8\n", + " 294\n", + " 4.8\n", " 0.0\n", " unknown\n", " \n", " \n", " South Asian\n", " 14\n", - " 10.5\n", - " 133\n", - " 5.3\n", - " 5.2\n", - " 01-Apr\n", + " 5.1\n", + " 273\n", + " 5.1\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 7\n", - " 5.6\n", - " 126\n", - " 5.6\n", + " 14\n", + " 6.2\n", + " 224\n", + " 6.2\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", " 14\n", - " 11.1\n", - " 126\n", - " 5.6\n", - " 5.5\n", - " 25-Mar\n", + " 5.4\n", + " 259\n", + " 5.4\n", + " 0.0\n", + " unknown\n", " \n", " \n", "\n", @@ -37699,65 +38062,67 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 56 7.0 805 \n", - "sex F 28 6.8 413 \n", - " M 28 7.1 392 \n", - "ageband_5yr 0 0 0.0 7 \n", - " 0-15 0 0.0 49 \n", - " 16-17 0 0.0 49 \n", - " 18-29 0 0.0 49 \n", - " 30-34 0 0.0 42 \n", - " 35-39 0 0.0 49 \n", - " 40-44 0 0.0 49 \n", - " 45-49 0 0.0 56 \n", - " 50-54 0 0.0 56 \n", - " 55-59 0 0.0 49 \n", - " 60-64 0 0.0 56 \n", - " 65-69 7 11.1 63 \n", - " 70-74 0 0.0 49 \n", - " 75-79 0 0.0 63 \n", - " 80-84 0 0.0 49 \n", - " 85-89 7 14.3 49 \n", - "ethnicity_6_groups Black 7 5.6 126 \n", - " Mixed 7 4.3 161 \n", - " Other 7 5.3 133 \n", - " South Asian 14 10.5 133 \n", - " Unknown 7 5.6 126 \n", - " White 14 11.1 126 \n", + "overall overall 91 5.7 1603 \n", + "sex F 42 5.3 791 \n", + " M 49 6.0 812 \n", + "ageband_5yr 0 0 0.0 21 \n", + " 0-15 0 0.0 105 \n", + " 16-17 7 6.2 112 \n", + " 18-29 0 0.0 105 \n", + " 30-34 0 0.0 98 \n", + " 35-39 0 0.0 105 \n", + " 40-44 7 8.3 84 \n", + " 45-49 0 0.0 119 \n", + " 50-54 0 0.0 133 \n", + " 55-59 0 0.0 105 \n", + " 60-64 0 0.0 98 \n", + " 65-69 7 7.1 98 \n", + " 70-74 7 7.7 91 \n", + " 75-79 7 6.7 105 \n", + " 80-84 7 7.1 98 \n", + " 85-89 0 0.0 105 \n", + " 90+ 0 0.0 14 \n", + "ethnicity_6_groups Black 21 7.7 273 \n", + " Mixed 14 5.0 280 \n", + " Other 14 4.8 294 \n", + " South Asian 14 5.1 273 \n", + " Unknown 14 6.2 224 \n", + " White 14 5.4 259 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 6.1 \n", - "sex F 5.1 \n", - " M 5.4 \n", + "overall overall 5.7 \n", + "sex F 5.3 \n", + " M 6.0 \n", "ageband_5yr 0 0.0 \n", " 0-15 0.0 \n", - " 16-17 0.0 \n", + " 16-17 6.2 \n", " 18-29 0.0 \n", " 30-34 0.0 \n", " 35-39 0.0 \n", - " 40-44 0.0 \n", + " 40-44 8.3 \n", " 45-49 0.0 \n", " 50-54 0.0 \n", " 55-59 0.0 \n", " 60-64 0.0 \n", - " 65-69 11.1 \n", + " 65-69 7.1 \n", " 70-74 0.0 \n", - " 75-79 0.0 \n", - " 80-84 0.0 \n", + " 75-79 6.7 \n", + " 80-84 7.1 \n", " 85-89 0.0 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 4.3 \n", - " Other 5.3 \n", - " South Asian 5.3 \n", - " Unknown 5.6 \n", - " White 5.6 \n", + " 90+ 0.0 \n", + "ethnicity_6_groups Black 5.1 \n", + " Mixed 5.0 \n", + " Other 4.8 \n", + " South Asian 5.1 \n", + " Unknown 6.2 \n", + " White 5.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 0.9 \n", - "sex F 1.7 \n", - " M 1.7 \n", + "overall overall 0.0 \n", + "sex F 0.0 \n", + " M 0.0 \n", "ageband_5yr 0 0.0 \n", " 0-15 0.0 \n", " 16-17 0.0 \n", @@ -37770,16 +38135,17 @@ " 55-59 0.0 \n", " 60-64 0.0 \n", " 65-69 0.0 \n", - " 70-74 0.0 \n", + " 70-74 7.7 \n", " 75-79 0.0 \n", " 80-84 0.0 \n", - " 85-89 14.3 \n", - "ethnicity_6_groups Black 5.6 \n", + " 85-89 0.0 \n", + " 90+ 0.0 \n", + "ethnicity_6_groups Black 2.6 \n", " Mixed 0.0 \n", " Other 0.0 \n", - " South Asian 5.2 \n", + " South Asian 0.0 \n", " Unknown 0.0 \n", - " White 5.5 \n", + " White 0.0 \n", "\n", " Date projected to reach 90% \n", "category group \n", @@ -37798,16 +38164,17 @@ " 55-59 unknown \n", " 60-64 unknown \n", " 65-69 unknown \n", - " 70-74 unknown \n", + " 70-74 17-Apr \n", " 75-79 unknown \n", " 80-84 unknown \n", - " 85-89 21-Jan \n", - "ethnicity_6_groups Black 30-Mar \n", + " 85-89 unknown \n", + " 90+ unknown \n", + "ethnicity_6_groups Black unknown \n", " Mixed unknown \n", " Other unknown \n", - " South Asian 01-Apr \n", + " South Asian unknown \n", " Unknown unknown \n", - " White 25-Mar " + " White unknown " ] }, "metadata": {}, @@ -37836,7 +38203,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (third dose) among **60-64** population up to 15 Dec 2021" + "## COVID vaccination rollout (third dose) among **60-64** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -37902,83 +38269,83 @@ " \n", " overall\n", " overall\n", - " 154\n", + " 329\n", + " 6.0\n", + " 5453\n", " 5.8\n", - " 2674\n", - " 5.5\n", - " 0.3\n", + " 0.2\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 63\n", - " 4.7\n", - " 1330\n", - " 4.7\n", - " 0.0\n", + " 175\n", + " 6.2\n", + " 2807\n", + " 6.0\n", + " 0.2\n", " unknown\n", " \n", " \n", " M\n", - " 84\n", - " 6.2\n", - " 1344\n", - " 6.2\n", - " 0.0\n", + " 154\n", + " 5.8\n", + " 2646\n", + " 5.6\n", + " 0.2\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 21\n", - " 4.5\n", - " 469\n", - " 4.5\n", - " 0.0\n", + " 70\n", + " 7.3\n", + " 959\n", + " 6.6\n", + " 0.7\n", " unknown\n", " \n", " \n", " Mixed\n", - " 28\n", - " 6.1\n", - " 462\n", - " 4.5\n", - " 1.6\n", + " 63\n", + " 6.7\n", + " 945\n", + " 5.9\n", + " 0.8\n", " unknown\n", " \n", " \n", " Other\n", - " 35\n", - " 7.8\n", - " 448\n", - " 7.8\n", + " 42\n", + " 4.8\n", + " 882\n", + " 4.8\n", " 0.0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 28\n", - " 6.2\n", - " 455\n", - " 6.2\n", + " 49\n", + " 5.3\n", + " 917\n", + " 5.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 14\n", - " 3.8\n", - " 364\n", - " 3.8\n", + " 49\n", + " 6.0\n", + " 819\n", + " 6.0\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", - " 28\n", + " 56\n", " 6.0\n", - " 469\n", + " 938\n", " 6.0\n", " 0.0\n", " unknown\n", @@ -37986,238 +38353,238 @@ " \n", " ethnicity_16_groups\n", " African\n", - " 0\n", - " 0.0\n", - " 119\n", - " 0.0\n", + " 14\n", + " 5.0\n", + " 280\n", + " 5.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 7\n", - " 4.5\n", - " 154\n", - " 4.5\n", + " 21\n", + " 7.0\n", + " 301\n", + " 7.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 7\n", - " 4.8\n", - " 147\n", - " 4.8\n", + " 21\n", + " 7.0\n", + " 301\n", + " 7.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Chinese\n", " 14\n", - " 9.1\n", - " 154\n", - " 9.1\n", + " 4.7\n", + " 301\n", + " 4.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 7\n", - " 4.5\n", - " 154\n", - " 4.5\n", - " 0.0\n", - " unknown\n", - " \n", + " 21\n", + " 7.0\n", + " 301\n", + " 4.7\n", + " 2.3\n", + " unknown\n", + " \n", " \n", " Other Asian\n", - " 7\n", - " 5.6\n", - " 126\n", - " 5.6\n", + " 14\n", + " 4.7\n", + " 301\n", + " 4.7\n", " 0.0\n", " unknown\n", " \n", " \n", " British or Mixed British\n", - " 7\n", - " 4.8\n", - " 147\n", - " 4.8\n", + " 21\n", + " 8.1\n", + " 259\n", + " 8.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 7\n", - " 5.3\n", - " 133\n", - " 0.0\n", - " 5.3\n", - " 05-Apr\n", + " 14\n", + " 5.1\n", + " 273\n", + " 2.6\n", + " 2.5\n", + " unknown\n", " \n", " \n", " Irish\n", " 14\n", - " 9.1\n", - " 154\n", - " 9.1\n", + " 5.0\n", + " 280\n", + " 5.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 0\n", - " 0.0\n", - " 126\n", - " 0.0\n", + " 28\n", + " 9.8\n", + " 287\n", + " 9.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 7\n", - " 4.3\n", - " 161\n", - " 4.3\n", + " 21\n", + " 7.7\n", + " 273\n", + " 7.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", " 14\n", - " 9.5\n", - " 147\n", - " 4.8\n", - " 4.7\n", - " 13-Apr\n", + " 5.3\n", + " 266\n", + " 5.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 7\n", - " 4.8\n", - " 147\n", - " 4.8\n", + " 14\n", + " 4.7\n", + " 301\n", + " 4.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 28\n", - " 6.9\n", - " 406\n", - " 6.9\n", + " 42\n", + " 5.0\n", + " 833\n", + " 5.0\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 0\n", - " 0.0\n", - " 133\n", - " 0.0\n", + " 14\n", + " 4.9\n", + " 287\n", + " 4.9\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black African\n", - " 7\n", - " 5.3\n", - " 133\n", - " 5.3\n", + " 21\n", + " 7.0\n", + " 301\n", + " 7.0\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 0\n", - " 0.0\n", - " 126\n", - " 0.0\n", + " 14\n", + " 4.4\n", + " 315\n", + " 4.4\n", " 0.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 28\n", - " 5.6\n", - " 504\n", - " 5.6\n", + " 63\n", + " 6.2\n", + " 1015\n", + " 6.2\n", " 0.0\n", " unknown\n", " \n", " \n", " 2\n", - " 42\n", - " 7.7\n", - " 546\n", - " 6.4\n", - " 1.3\n", + " 56\n", + " 5.4\n", + " 1036\n", + " 5.4\n", + " 0.0\n", " unknown\n", " \n", " \n", " 3\n", - " 21\n", - " 4.2\n", - " 504\n", - " 4.2\n", + " 63\n", + " 5.9\n", + " 1071\n", + " 5.9\n", " 0.0\n", " unknown\n", " \n", " \n", " 4\n", - " 28\n", - " 5.8\n", - " 483\n", - " 5.8\n", + " 56\n", + " 5.6\n", + " 1001\n", + " 5.6\n", " 0.0\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 28\n", - " 5.6\n", - " 504\n", - " 4.2\n", - " 1.4\n", + " 63\n", + " 6.0\n", + " 1057\n", + " 6.0\n", + " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 7\n", - " 5.3\n", - " 133\n", - " 5.3\n", + " 14\n", + " 5.0\n", + " 280\n", + " 5.0\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 42\n", - " 5.1\n", - " 826\n", - " 5.1\n", - " 0.0\n", + " 105\n", + " 6.5\n", + " 1624\n", + " 6.0\n", + " 0.5\n", " unknown\n", " \n", " \n", " under 30\n", - " 105\n", - " 5.7\n", - " 1848\n", + " 224\n", + " 5.9\n", + " 3829\n", " 5.7\n", - " 0.0\n", + " 0.2\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 147\n", - " 5.6\n", - " 2639\n", - " 5.3\n", + " 322\n", + " 6.0\n", + " 5411\n", + " 5.7\n", " 0.3\n", " unknown\n", " \n", @@ -38225,36 +38592,45 @@ " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 42\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " current_copd\n", + " current_copd\n", " no\n", - " 154\n", - " 5.8\n", - " 2653\n", - " 5.5\n", - " 0.3\n", + " 329\n", + " 6.1\n", + " 5397\n", + " 5.7\n", + " 0.4\n", + " unknown\n", + " \n", + " \n", + " yes\n", + " 0\n", + " 0.0\n", + " 56\n", + " 0.0\n", + " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 147\n", - " 5.5\n", - " 2653\n", - " 5.3\n", - " 0.2\n", + " 329\n", + " 6.1\n", + " 5397\n", + " 5.8\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 56\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -38262,29 +38638,29 @@ " \n", " dementia\n", " no\n", - " 147\n", - " 5.6\n", - " 2646\n", - " 5.3\n", + " 322\n", + " 6.0\n", + " 5376\n", + " 5.7\n", " 0.3\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 28\n", - " 0.0\n", + " 7\n", + " 9.1\n", + " 77\n", + " 9.1\n", " 0.0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 147\n", - " 5.6\n", - " 2646\n", - " 5.3\n", + " 329\n", + " 6.1\n", + " 5404\n", + " 5.8\n", " 0.3\n", " unknown\n", " \n", @@ -38292,7 +38668,7 @@ " yes\n", " 0\n", " 0.0\n", - " 28\n", + " 49\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -38300,18 +38676,18 @@ " \n", " ssri\n", " no\n", - " 147\n", - " 5.6\n", - " 2646\n", - " 5.3\n", - " 0.3\n", + " 329\n", + " 6.1\n", + " 5404\n", + " 5.7\n", + " 0.4\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 28\n", + " 49\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -38319,18 +38695,18 @@ " \n", " chemo_or_radio\n", " no\n", - " 147\n", - " 5.6\n", - " 2646\n", - " 5.3\n", - " 0.3\n", + " 329\n", + " 6.1\n", + " 5397\n", + " 5.7\n", + " 0.4\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 63\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -38338,39 +38714,48 @@ " \n", " lung_cancer\n", " no\n", - " 147\n", - " 5.5\n", - " 2653\n", - " 5.3\n", - " 0.2\n", + " 329\n", + " 6.1\n", + " 5411\n", + " 5.7\n", + " 0.4\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 49\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " cancer_excl_lung_and_haem\n", + " cancer_excl_lung_and_haem\n", " no\n", - " 154\n", + " 329\n", + " 6.1\n", + " 5397\n", " 5.8\n", - " 2653\n", - " 5.5\n", " 0.3\n", " unknown\n", " \n", " \n", + " yes\n", + " 0\n", + " 0.0\n", + " 56\n", + " 0.0\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", " haematological_cancer\n", " no\n", - " 147\n", - " 5.6\n", - " 2646\n", - " 5.3\n", + " 329\n", + " 6.1\n", + " 5404\n", + " 5.8\n", " 0.3\n", " unknown\n", " \n", @@ -38378,7 +38763,7 @@ " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 49\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -38386,19 +38771,19 @@ " \n", " ckd\n", " no\n", - " 126\n", + " 266\n", " 6.0\n", - " 2114\n", - " 5.6\n", - " 0.4\n", + " 4403\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", - " 28\n", - " 5.0\n", - " 560\n", - " 5.0\n", + " 63\n", + " 6.0\n", + " 1057\n", + " 6.0\n", " 0.0\n", " unknown\n", " \n", @@ -38409,182 +38794,188 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 154 \n", - "sex F 63 \n", - " M 84 \n", - "ethnicity_6_groups Black 21 \n", - " Mixed 28 \n", - " Other 35 \n", - " South Asian 28 \n", - " Unknown 14 \n", - " White 28 \n", - "ethnicity_16_groups African 0 \n", - " Bangladeshi or British Bangladeshi 7 \n", - " Caribbean 7 \n", + "overall overall 329 \n", + "sex F 175 \n", + " M 154 \n", + "ethnicity_6_groups Black 70 \n", + " Mixed 63 \n", + " Other 42 \n", + " South Asian 49 \n", + " Unknown 49 \n", + " White 56 \n", + "ethnicity_16_groups African 14 \n", + " Bangladeshi or British Bangladeshi 21 \n", + " Caribbean 21 \n", " Chinese 14 \n", - " Other 7 \n", - " Other Asian 7 \n", - " British or Mixed British 7 \n", - " Indian or British Indian 7 \n", + " Other 21 \n", + " Other Asian 14 \n", + " British or Mixed British 21 \n", + " Indian or British Indian 14 \n", " Irish 14 \n", - " Other Black 0 \n", - " Other White 7 \n", + " Other Black 28 \n", + " Other White 21 \n", " Other mixed 14 \n", - " Pakistani or British Pakistani 7 \n", - " Unknown 28 \n", - " White + Asian 0 \n", - " White + Black African 7 \n", - " White + Black Caribbean 0 \n", - "imd_categories 1 Most deprived 28 \n", - " 2 42 \n", - " 3 21 \n", - " 4 28 \n", - " 5 Least deprived 28 \n", - " Unknown 7 \n", - "bmi 30+ 42 \n", - " under 30 105 \n", - "chronic_cardiac_disease no 147 \n", + " Pakistani or British Pakistani 14 \n", + " Unknown 42 \n", + " White + Asian 14 \n", + " White + Black African 21 \n", + " White + Black Caribbean 14 \n", + "imd_categories 1 Most deprived 63 \n", + " 2 56 \n", + " 3 63 \n", + " 4 56 \n", + " 5 Least deprived 63 \n", + " Unknown 14 \n", + "bmi 30+ 105 \n", + " under 30 224 \n", + "chronic_cardiac_disease no 322 \n", " yes 0 \n", - "current_copd no 154 \n", - "dmards no 147 \n", + "current_copd no 329 \n", " yes 0 \n", - "dementia no 147 \n", + "dmards no 329 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 147 \n", + "dementia no 322 \n", + " yes 7 \n", + "psychosis_schiz_bipolar no 329 \n", " yes 0 \n", - "ssri no 147 \n", + "ssri no 329 \n", " yes 0 \n", - "chemo_or_radio no 147 \n", + "chemo_or_radio no 329 \n", " yes 0 \n", - "lung_cancer no 147 \n", + "lung_cancer no 329 \n", " yes 0 \n", - "cancer_excl_lung_and_haem no 154 \n", - "haematological_cancer no 147 \n", + "cancer_excl_lung_and_haem no 329 \n", " yes 0 \n", - "ckd no 126 \n", - " yes 28 \n", + "haematological_cancer no 329 \n", + " yes 0 \n", + "ckd no 266 \n", + " yes 63 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 5.8 2674 \n", - "sex F 4.7 1330 \n", - " M 6.2 1344 \n", - "ethnicity_6_groups Black 4.5 469 \n", - " Mixed 6.1 462 \n", - " Other 7.8 448 \n", - " South Asian 6.2 455 \n", - " Unknown 3.8 364 \n", - " White 6.0 469 \n", - "ethnicity_16_groups African 0.0 119 \n", - " Bangladeshi or British Bangladeshi 4.5 154 \n", - " Caribbean 4.8 147 \n", - " Chinese 9.1 154 \n", - " Other 4.5 154 \n", - " Other Asian 5.6 126 \n", - " British or Mixed British 4.8 147 \n", - " Indian or British Indian 5.3 133 \n", - " Irish 9.1 154 \n", - " Other Black 0.0 126 \n", - " Other White 4.3 161 \n", - " Other mixed 9.5 147 \n", - " Pakistani or British Pakistani 4.8 147 \n", - " Unknown 6.9 406 \n", - " White + Asian 0.0 133 \n", - " White + Black African 5.3 133 \n", - " White + Black Caribbean 0.0 126 \n", - "imd_categories 1 Most deprived 5.6 504 \n", - " 2 7.7 546 \n", - " 3 4.2 504 \n", - " 4 5.8 483 \n", - " 5 Least deprived 5.6 504 \n", - " Unknown 5.3 133 \n", - "bmi 30+ 5.1 826 \n", - " under 30 5.7 1848 \n", - "chronic_cardiac_disease no 5.6 2639 \n", - " yes 0.0 35 \n", - "current_copd no 5.8 2653 \n", - "dmards no 5.5 2653 \n", - " yes 0.0 21 \n", - "dementia no 5.6 2646 \n", - " yes 0.0 28 \n", - "psychosis_schiz_bipolar no 5.6 2646 \n", - " yes 0.0 28 \n", - "ssri no 5.6 2646 \n", - " yes 0.0 28 \n", - "chemo_or_radio no 5.6 2646 \n", - " yes 0.0 35 \n", - "lung_cancer no 5.5 2653 \n", - " yes 0.0 21 \n", - "cancer_excl_lung_and_haem no 5.8 2653 \n", - "haematological_cancer no 5.6 2646 \n", - " yes 0.0 35 \n", - "ckd no 6.0 2114 \n", - " yes 5.0 560 \n", + "overall overall 6.0 5453 \n", + "sex F 6.2 2807 \n", + " M 5.8 2646 \n", + "ethnicity_6_groups Black 7.3 959 \n", + " Mixed 6.7 945 \n", + " Other 4.8 882 \n", + " South Asian 5.3 917 \n", + " Unknown 6.0 819 \n", + " White 6.0 938 \n", + "ethnicity_16_groups African 5.0 280 \n", + " Bangladeshi or British Bangladeshi 7.0 301 \n", + " Caribbean 7.0 301 \n", + " Chinese 4.7 301 \n", + " Other 7.0 301 \n", + " Other Asian 4.7 301 \n", + " British or Mixed British 8.1 259 \n", + " Indian or British Indian 5.1 273 \n", + " Irish 5.0 280 \n", + " Other Black 9.8 287 \n", + " Other White 7.7 273 \n", + " Other mixed 5.3 266 \n", + " Pakistani or British Pakistani 4.7 301 \n", + " Unknown 5.0 833 \n", + " White + Asian 4.9 287 \n", + " White + Black African 7.0 301 \n", + " White + Black Caribbean 4.4 315 \n", + "imd_categories 1 Most deprived 6.2 1015 \n", + " 2 5.4 1036 \n", + " 3 5.9 1071 \n", + " 4 5.6 1001 \n", + " 5 Least deprived 6.0 1057 \n", + " Unknown 5.0 280 \n", + "bmi 30+ 6.5 1624 \n", + " under 30 5.9 3829 \n", + "chronic_cardiac_disease no 6.0 5411 \n", + " yes 0.0 42 \n", + "current_copd no 6.1 5397 \n", + " yes 0.0 56 \n", + "dmards no 6.1 5397 \n", + " yes 0.0 56 \n", + "dementia no 6.0 5376 \n", + " yes 9.1 77 \n", + "psychosis_schiz_bipolar no 6.1 5404 \n", + " yes 0.0 49 \n", + "ssri no 6.1 5404 \n", + " yes 0.0 49 \n", + "chemo_or_radio no 6.1 5397 \n", + " yes 0.0 63 \n", + "lung_cancer no 6.1 5411 \n", + " yes 0.0 49 \n", + "cancer_excl_lung_and_haem no 6.1 5397 \n", + " yes 0.0 56 \n", + "haematological_cancer no 6.1 5404 \n", + " yes 0.0 49 \n", + "ckd no 6.0 4403 \n", + " yes 6.0 1057 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 5.5 \n", - "sex F 4.7 \n", - " M 6.2 \n", - "ethnicity_6_groups Black 4.5 \n", - " Mixed 4.5 \n", - " Other 7.8 \n", - " South Asian 6.2 \n", - " Unknown 3.8 \n", + "overall overall 5.8 \n", + "sex F 6.0 \n", + " M 5.6 \n", + "ethnicity_6_groups Black 6.6 \n", + " Mixed 5.9 \n", + " Other 4.8 \n", + " South Asian 5.3 \n", + " Unknown 6.0 \n", " White 6.0 \n", - "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 4.5 \n", - " Caribbean 4.8 \n", - " Chinese 9.1 \n", - " Other 4.5 \n", - " Other Asian 5.6 \n", - " British or Mixed British 4.8 \n", - " Indian or British Indian 0.0 \n", - " Irish 9.1 \n", - " Other Black 0.0 \n", - " Other White 4.3 \n", - " Other mixed 4.8 \n", - " Pakistani or British Pakistani 4.8 \n", - " Unknown 6.9 \n", - " White + Asian 0.0 \n", - " White + Black African 5.3 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 5.6 \n", - " 2 6.4 \n", - " 3 4.2 \n", - " 4 5.8 \n", - " 5 Least deprived 4.2 \n", - " Unknown 5.3 \n", - "bmi 30+ 5.1 \n", + "ethnicity_16_groups African 5.0 \n", + " Bangladeshi or British Bangladeshi 7.0 \n", + " Caribbean 7.0 \n", + " Chinese 4.7 \n", + " Other 4.7 \n", + " Other Asian 4.7 \n", + " British or Mixed British 8.1 \n", + " Indian or British Indian 2.6 \n", + " Irish 5.0 \n", + " Other Black 9.8 \n", + " Other White 7.7 \n", + " Other mixed 5.3 \n", + " Pakistani or British Pakistani 4.7 \n", + " Unknown 5.0 \n", + " White + Asian 4.9 \n", + " White + Black African 7.0 \n", + " White + Black Caribbean 4.4 \n", + "imd_categories 1 Most deprived 6.2 \n", + " 2 5.4 \n", + " 3 5.9 \n", + " 4 5.6 \n", + " 5 Least deprived 6.0 \n", + " Unknown 5.0 \n", + "bmi 30+ 6.0 \n", " under 30 5.7 \n", - "chronic_cardiac_disease no 5.3 \n", + "chronic_cardiac_disease no 5.7 \n", " yes 0.0 \n", - "current_copd no 5.5 \n", - "dmards no 5.3 \n", + "current_copd no 5.7 \n", " yes 0.0 \n", - "dementia no 5.3 \n", + "dmards no 5.8 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 5.3 \n", + "dementia no 5.7 \n", + " yes 9.1 \n", + "psychosis_schiz_bipolar no 5.8 \n", " yes 0.0 \n", - "ssri no 5.3 \n", + "ssri no 5.7 \n", " yes 0.0 \n", - "chemo_or_radio no 5.3 \n", + "chemo_or_radio no 5.7 \n", " yes 0.0 \n", - "lung_cancer no 5.3 \n", + "lung_cancer no 5.7 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 5.5 \n", - "haematological_cancer no 5.3 \n", + "cancer_excl_lung_and_haem no 5.8 \n", " yes 0.0 \n", - "ckd no 5.6 \n", - " yes 5.0 \n", + "haematological_cancer no 5.8 \n", + " yes 0.0 \n", + "ckd no 5.7 \n", + " yes 6.0 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 0.3 \n", - "sex F 0.0 \n", - " M 0.0 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 1.6 \n", + "overall overall 0.2 \n", + "sex F 0.2 \n", + " M 0.2 \n", + "ethnicity_6_groups Black 0.7 \n", + " Mixed 0.8 \n", " Other 0.0 \n", " South Asian 0.0 \n", " Unknown 0.0 \n", @@ -38593,46 +38984,48 @@ " Bangladeshi or British Bangladeshi 0.0 \n", " Caribbean 0.0 \n", " Chinese 0.0 \n", - " Other 0.0 \n", + " Other 2.3 \n", " Other Asian 0.0 \n", " British or Mixed British 0.0 \n", - " Indian or British Indian 5.3 \n", + " Indian or British Indian 2.5 \n", " Irish 0.0 \n", " Other Black 0.0 \n", " Other White 0.0 \n", - " Other mixed 4.7 \n", + " Other mixed 0.0 \n", " Pakistani or British Pakistani 0.0 \n", " Unknown 0.0 \n", " White + Asian 0.0 \n", " White + Black African 0.0 \n", " White + Black Caribbean 0.0 \n", "imd_categories 1 Most deprived 0.0 \n", - " 2 1.3 \n", + " 2 0.0 \n", " 3 0.0 \n", " 4 0.0 \n", - " 5 Least deprived 1.4 \n", + " 5 Least deprived 0.0 \n", " Unknown 0.0 \n", - "bmi 30+ 0.0 \n", - " under 30 0.0 \n", + "bmi 30+ 0.5 \n", + " under 30 0.2 \n", "chronic_cardiac_disease no 0.3 \n", " yes 0.0 \n", - "current_copd no 0.3 \n", - "dmards no 0.2 \n", + "current_copd no 0.4 \n", + " yes 0.0 \n", + "dmards no 0.3 \n", " yes 0.0 \n", "dementia no 0.3 \n", " yes 0.0 \n", "psychosis_schiz_bipolar no 0.3 \n", " yes 0.0 \n", - "ssri no 0.3 \n", + "ssri no 0.4 \n", " yes 0.0 \n", - "chemo_or_radio no 0.3 \n", + "chemo_or_radio no 0.4 \n", " yes 0.0 \n", - "lung_cancer no 0.2 \n", + "lung_cancer no 0.4 \n", " yes 0.0 \n", "cancer_excl_lung_and_haem no 0.3 \n", + " yes 0.0 \n", "haematological_cancer no 0.3 \n", " yes 0.0 \n", - "ckd no 0.4 \n", + "ckd no 0.3 \n", " yes 0.0 \n", "\n", " Date projected to reach 90% \n", @@ -38653,11 +39046,11 @@ " Other unknown \n", " Other Asian unknown \n", " British or Mixed British unknown \n", - " Indian or British Indian 05-Apr \n", + " Indian or British Indian unknown \n", " Irish unknown \n", " Other Black unknown \n", " Other White unknown \n", - " Other mixed 13-Apr \n", + " Other mixed unknown \n", " Pakistani or British Pakistani unknown \n", " Unknown unknown \n", " White + Asian unknown \n", @@ -38674,6 +39067,7 @@ "chronic_cardiac_disease no unknown \n", " yes unknown \n", "current_copd no unknown \n", + " yes unknown \n", "dmards no unknown \n", " yes unknown \n", "dementia no unknown \n", @@ -38687,6 +39081,7 @@ "lung_cancer no unknown \n", " yes unknown \n", "cancer_excl_lung_and_haem no unknown \n", + " yes unknown \n", "haematological_cancer no unknown \n", " yes unknown \n", "ckd no unknown \n", @@ -38719,7 +39114,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (third dose) among **55-59** population up to 15 Dec 2021" + "## COVID vaccination rollout (third dose) among **55-59** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -38785,330 +39180,330 @@ " \n", " overall\n", " overall\n", - " 196\n", + " 385\n", " 6.2\n", - " 3185\n", - " 5.5\n", - " 0.7\n", + " 6223\n", + " 5.8\n", + " 0.4\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 91\n", - " 5.6\n", - " 1624\n", + " 168\n", " 5.2\n", - " 0.4\n", + " 3206\n", + " 5.2\n", + " 0.0\n", " unknown\n", " \n", " \n", " M\n", - " 105\n", + " 217\n", + " 7.2\n", + " 3017\n", " 6.7\n", - " 1561\n", - " 5.8\n", - " 0.9\n", + " 0.5\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 35\n", - " 6.1\n", - " 574\n", - " 6.1\n", + " 49\n", + " 4.7\n", + " 1036\n", + " 4.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Mixed\n", - " 35\n", - " 6.1\n", - " 574\n", - " 4.9\n", - " 1.2\n", + " 49\n", + " 4.6\n", + " 1064\n", + " 3.9\n", + " 0.7\n", " unknown\n", " \n", " \n", " Other\n", - " 35\n", - " 6.8\n", - " 518\n", - " 5.4\n", - " 1.4\n", + " 70\n", + " 6.5\n", + " 1085\n", + " 6.5\n", + " 0.0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 35\n", - " 6.5\n", - " 539\n", - " 5.2\n", - " 1.3\n", + " 63\n", + " 6.2\n", + " 1022\n", + " 5.5\n", + " 0.7\n", " unknown\n", " \n", " \n", " Unknown\n", - " 21\n", - " 5.0\n", - " 420\n", - " 5.0\n", + " 70\n", + " 7.4\n", + " 952\n", + " 7.4\n", " 0.0\n", " unknown\n", " \n", " \n", " White\n", - " 42\n", - " 7.6\n", - " 553\n", - " 6.3\n", - " 1.3\n", + " 77\n", + " 7.2\n", + " 1071\n", + " 6.5\n", + " 0.7\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", " 21\n", - " 12.0\n", - " 175\n", - " 8.0\n", - " 4.0\n", - " 30-Apr\n", + " 6.5\n", + " 322\n", + " 6.5\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", " 14\n", - " 8.3\n", - " 168\n", - " 8.3\n", + " 4.7\n", + " 301\n", + " 4.7\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 0\n", - " 0.0\n", - " 161\n", - " 0.0\n", + " 21\n", + " 6.4\n", + " 329\n", + " 6.4\n", " 0.0\n", " unknown\n", " \n", " \n", " Chinese\n", - " 14\n", - " 7.7\n", - " 182\n", - " 7.7\n", + " 21\n", + " 7.1\n", + " 294\n", + " 7.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 7\n", - " 4.8\n", - " 147\n", - " 4.8\n", + " 21\n", + " 6.4\n", + " 329\n", + " 6.4\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 7\n", - " 4.3\n", - " 161\n", - " 4.3\n", + " 21\n", + " 6.8\n", + " 308\n", + " 6.8\n", " 0.0\n", " unknown\n", " \n", " \n", " British or Mixed British\n", - " 7\n", - " 4.3\n", - " 161\n", - " 4.3\n", + " 14\n", + " 4.2\n", + " 336\n", + " 4.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 7\n", - " 4.2\n", - " 168\n", - " 4.2\n", + " 14\n", + " 4.3\n", + " 322\n", + " 4.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 14\n", - " 8.0\n", - " 175\n", - " 4.0\n", - " 4.0\n", - " 07-May\n", - " \n", - " \n", - " Other Black\n", - " 7\n", - " 4.5\n", - " 154\n", - " 4.5\n", + " 28\n", + " 8.3\n", + " 336\n", + " 8.3\n", " 0.0\n", " unknown\n", " \n", " \n", - " Other White\n", - " 7\n", - " 4.5\n", - " 154\n", - " 4.5\n", + " Other Black\n", + " 21\n", + " 6.1\n", + " 343\n", + " 6.1\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " Other White\n", + " 28\n", + " 8.0\n", + " 350\n", + " 8.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 7\n", - " 3.8\n", - " 182\n", + " 21\n", + " 6.8\n", + " 308\n", + " 6.8\n", " 0.0\n", - " 3.8\n", - " 22-May\n", + " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 14\n", - " 7.4\n", - " 189\n", - " 7.4\n", + " 28\n", + " 7.8\n", + " 357\n", + " 7.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 35\n", - " 7.2\n", - " 483\n", - " 5.8\n", - " 1.4\n", + " 56\n", + " 5.9\n", + " 952\n", + " 5.1\n", + " 0.8\n", " unknown\n", " \n", " \n", " White + Asian\n", " 14\n", - " 8.3\n", - " 168\n", - " 8.3\n", + " 4.2\n", + " 336\n", + " 4.2\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black African\n", - " 7\n", - " 4.3\n", - " 161\n", - " 4.3\n", + " 21\n", + " 5.6\n", + " 378\n", + " 5.6\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 7\n", - " 3.8\n", - " 182\n", - " 3.8\n", - " 0.0\n", + " 21\n", + " 6.4\n", + " 329\n", + " 4.3\n", + " 2.1\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 42\n", - " 6.9\n", - " 609\n", - " 6.9\n", + " 70\n", + " 5.7\n", + " 1225\n", + " 5.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 2\n", - " 35\n", - " 5.4\n", - " 644\n", - " 5.4\n", - " 0.0\n", + " 70\n", + " 6.1\n", + " 1141\n", + " 5.5\n", + " 0.6\n", " unknown\n", " \n", " \n", " 3\n", - " 35\n", - " 6.0\n", - " 588\n", - " 4.8\n", - " 1.2\n", + " 77\n", + " 6.4\n", + " 1211\n", + " 5.8\n", + " 0.6\n", " unknown\n", " \n", " \n", " 4\n", - " 28\n", - " 4.7\n", - " 602\n", - " 4.7\n", + " 84\n", + " 7.1\n", + " 1183\n", + " 7.1\n", " 0.0\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 49\n", - " 8.6\n", - " 567\n", - " 7.4\n", - " 1.2\n", + " 63\n", + " 5.5\n", + " 1141\n", + " 5.5\n", + " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 7\n", - " 4.0\n", - " 175\n", - " 4.0\n", + " 21\n", + " 6.5\n", + " 322\n", + " 6.5\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 63\n", - " 6.6\n", - " 959\n", + " 112\n", + " 6.2\n", + " 1806\n", " 5.8\n", - " 0.8\n", + " 0.4\n", " unknown\n", " \n", " \n", " under 30\n", - " 140\n", - " 6.3\n", - " 2226\n", - " 5.3\n", - " 1.0\n", + " 273\n", + " 6.2\n", + " 4417\n", + " 5.9\n", + " 0.3\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 196\n", - " 6.2\n", - " 3143\n", - " 5.3\n", - " 0.9\n", + " 378\n", + " 6.1\n", + " 6153\n", + " 5.9\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 42\n", + " 77\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -39116,18 +39511,18 @@ " \n", " current_copd\n", " no\n", - " 196\n", - " 6.2\n", - " 3150\n", - " 5.3\n", - " 0.9\n", + " 378\n", + " 6.1\n", + " 6174\n", + " 5.9\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 56\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -39135,18 +39530,18 @@ " \n", " dmards\n", " no\n", - " 196\n", - " 6.2\n", - " 3150\n", - " 5.3\n", - " 0.9\n", + " 378\n", + " 6.1\n", + " 6160\n", + " 5.9\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 70\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -39154,18 +39549,18 @@ " \n", " psychosis_schiz_bipolar\n", " no\n", - " 196\n", - " 6.2\n", - " 3150\n", - " 5.3\n", - " 0.9\n", + " 378\n", + " 6.1\n", + " 6167\n", + " 5.9\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 63\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -39173,18 +39568,18 @@ " \n", " ssri\n", " no\n", - " 196\n", - " 6.2\n", - " 3143\n", - " 5.3\n", - " 0.9\n", + " 378\n", + " 6.1\n", + " 6160\n", + " 5.9\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 42\n", + " 70\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -39192,20 +39587,20 @@ " \n", " ckd\n", " no\n", - " 161\n", + " 308\n", " 6.2\n", - " 2597\n", - " 5.4\n", - " 0.8\n", + " 4942\n", + " 5.9\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", - " 35\n", + " 77\n", " 6.0\n", - " 588\n", - " 4.8\n", - " 1.2\n", + " 1288\n", + " 5.4\n", + " 0.6\n", " unknown\n", " \n", " \n", @@ -39215,163 +39610,163 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 196 \n", - "sex F 91 \n", - " M 105 \n", - "ethnicity_6_groups Black 35 \n", - " Mixed 35 \n", - " Other 35 \n", - " South Asian 35 \n", - " Unknown 21 \n", - " White 42 \n", + "overall overall 385 \n", + "sex F 168 \n", + " M 217 \n", + "ethnicity_6_groups Black 49 \n", + " Mixed 49 \n", + " Other 70 \n", + " South Asian 63 \n", + " Unknown 70 \n", + " White 77 \n", "ethnicity_16_groups African 21 \n", " Bangladeshi or British Bangladeshi 14 \n", - " Caribbean 0 \n", - " Chinese 14 \n", - " Other 7 \n", - " Other Asian 7 \n", - " British or Mixed British 7 \n", - " Indian or British Indian 7 \n", - " Irish 14 \n", - " Other Black 7 \n", - " Other White 7 \n", - " Other mixed 7 \n", - " Pakistani or British Pakistani 14 \n", - " Unknown 35 \n", + " Caribbean 21 \n", + " Chinese 21 \n", + " Other 21 \n", + " Other Asian 21 \n", + " British or Mixed British 14 \n", + " Indian or British Indian 14 \n", + " Irish 28 \n", + " Other Black 21 \n", + " Other White 28 \n", + " Other mixed 21 \n", + " Pakistani or British Pakistani 28 \n", + " Unknown 56 \n", " White + Asian 14 \n", - " White + Black African 7 \n", - " White + Black Caribbean 7 \n", - "imd_categories 1 Most deprived 42 \n", - " 2 35 \n", - " 3 35 \n", - " 4 28 \n", - " 5 Least deprived 49 \n", - " Unknown 7 \n", - "bmi 30+ 63 \n", - " under 30 140 \n", - "chronic_cardiac_disease no 196 \n", + " White + Black African 21 \n", + " White + Black Caribbean 21 \n", + "imd_categories 1 Most deprived 70 \n", + " 2 70 \n", + " 3 77 \n", + " 4 84 \n", + " 5 Least deprived 63 \n", + " Unknown 21 \n", + "bmi 30+ 112 \n", + " under 30 273 \n", + "chronic_cardiac_disease no 378 \n", " yes 0 \n", - "current_copd no 196 \n", + "current_copd no 378 \n", " yes 0 \n", - "dmards no 196 \n", + "dmards no 378 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 196 \n", + "psychosis_schiz_bipolar no 378 \n", " yes 0 \n", - "ssri no 196 \n", + "ssri no 378 \n", " yes 0 \n", - "ckd no 161 \n", - " yes 35 \n", + "ckd no 308 \n", + " yes 77 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 6.2 3185 \n", - "sex F 5.6 1624 \n", - " M 6.7 1561 \n", - "ethnicity_6_groups Black 6.1 574 \n", - " Mixed 6.1 574 \n", - " Other 6.8 518 \n", - " South Asian 6.5 539 \n", - " Unknown 5.0 420 \n", - " White 7.6 553 \n", - "ethnicity_16_groups African 12.0 175 \n", - " Bangladeshi or British Bangladeshi 8.3 168 \n", - " Caribbean 0.0 161 \n", - " Chinese 7.7 182 \n", - " Other 4.8 147 \n", - " Other Asian 4.3 161 \n", - " British or Mixed British 4.3 161 \n", - " Indian or British Indian 4.2 168 \n", - " Irish 8.0 175 \n", - " Other Black 4.5 154 \n", - " Other White 4.5 154 \n", - " Other mixed 3.8 182 \n", - " Pakistani or British Pakistani 7.4 189 \n", - " Unknown 7.2 483 \n", - " White + Asian 8.3 168 \n", - " White + Black African 4.3 161 \n", - " White + Black Caribbean 3.8 182 \n", - "imd_categories 1 Most deprived 6.9 609 \n", - " 2 5.4 644 \n", - " 3 6.0 588 \n", - " 4 4.7 602 \n", - " 5 Least deprived 8.6 567 \n", - " Unknown 4.0 175 \n", - "bmi 30+ 6.6 959 \n", - " under 30 6.3 2226 \n", - "chronic_cardiac_disease no 6.2 3143 \n", - " yes 0.0 42 \n", - "current_copd no 6.2 3150 \n", - " yes 0.0 35 \n", - "dmards no 6.2 3150 \n", - " yes 0.0 35 \n", - "psychosis_schiz_bipolar no 6.2 3150 \n", - " yes 0.0 35 \n", - "ssri no 6.2 3143 \n", - " yes 0.0 42 \n", - "ckd no 6.2 2597 \n", - " yes 6.0 588 \n", + "overall overall 6.2 6223 \n", + "sex F 5.2 3206 \n", + " M 7.2 3017 \n", + "ethnicity_6_groups Black 4.7 1036 \n", + " Mixed 4.6 1064 \n", + " Other 6.5 1085 \n", + " South Asian 6.2 1022 \n", + " Unknown 7.4 952 \n", + " White 7.2 1071 \n", + "ethnicity_16_groups African 6.5 322 \n", + " Bangladeshi or British Bangladeshi 4.7 301 \n", + " Caribbean 6.4 329 \n", + " Chinese 7.1 294 \n", + " Other 6.4 329 \n", + " Other Asian 6.8 308 \n", + " British or Mixed British 4.2 336 \n", + " Indian or British Indian 4.3 322 \n", + " Irish 8.3 336 \n", + " Other Black 6.1 343 \n", + " Other White 8.0 350 \n", + " Other mixed 6.8 308 \n", + " Pakistani or British Pakistani 7.8 357 \n", + " Unknown 5.9 952 \n", + " White + Asian 4.2 336 \n", + " White + Black African 5.6 378 \n", + " White + Black Caribbean 6.4 329 \n", + "imd_categories 1 Most deprived 5.7 1225 \n", + " 2 6.1 1141 \n", + " 3 6.4 1211 \n", + " 4 7.1 1183 \n", + " 5 Least deprived 5.5 1141 \n", + " Unknown 6.5 322 \n", + "bmi 30+ 6.2 1806 \n", + " under 30 6.2 4417 \n", + "chronic_cardiac_disease no 6.1 6153 \n", + " yes 0.0 77 \n", + "current_copd no 6.1 6174 \n", + " yes 0.0 56 \n", + "dmards no 6.1 6160 \n", + " yes 0.0 70 \n", + "psychosis_schiz_bipolar no 6.1 6167 \n", + " yes 0.0 63 \n", + "ssri no 6.1 6160 \n", + " yes 0.0 70 \n", + "ckd no 6.2 4942 \n", + " yes 6.0 1288 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 5.5 \n", + "overall overall 5.8 \n", "sex F 5.2 \n", - " M 5.8 \n", - "ethnicity_6_groups Black 6.1 \n", - " Mixed 4.9 \n", - " Other 5.4 \n", - " South Asian 5.2 \n", - " Unknown 5.0 \n", - " White 6.3 \n", - "ethnicity_16_groups African 8.0 \n", - " Bangladeshi or British Bangladeshi 8.3 \n", - " Caribbean 0.0 \n", - " Chinese 7.7 \n", - " Other 4.8 \n", - " Other Asian 4.3 \n", - " British or Mixed British 4.3 \n", - " Indian or British Indian 4.2 \n", - " Irish 4.0 \n", - " Other Black 4.5 \n", - " Other White 4.5 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 7.4 \n", - " Unknown 5.8 \n", - " White + Asian 8.3 \n", - " White + Black African 4.3 \n", - " White + Black Caribbean 3.8 \n", - "imd_categories 1 Most deprived 6.9 \n", - " 2 5.4 \n", - " 3 4.8 \n", - " 4 4.7 \n", - " 5 Least deprived 7.4 \n", - " Unknown 4.0 \n", + " M 6.7 \n", + "ethnicity_6_groups Black 4.7 \n", + " Mixed 3.9 \n", + " Other 6.5 \n", + " South Asian 5.5 \n", + " Unknown 7.4 \n", + " White 6.5 \n", + "ethnicity_16_groups African 6.5 \n", + " Bangladeshi or British Bangladeshi 4.7 \n", + " Caribbean 6.4 \n", + " Chinese 7.1 \n", + " Other 6.4 \n", + " Other Asian 6.8 \n", + " British or Mixed British 4.2 \n", + " Indian or British Indian 4.3 \n", + " Irish 8.3 \n", + " Other Black 6.1 \n", + " Other White 8.0 \n", + " Other mixed 6.8 \n", + " Pakistani or British Pakistani 7.8 \n", + " Unknown 5.1 \n", + " White + Asian 4.2 \n", + " White + Black African 5.6 \n", + " White + Black Caribbean 4.3 \n", + "imd_categories 1 Most deprived 5.7 \n", + " 2 5.5 \n", + " 3 5.8 \n", + " 4 7.1 \n", + " 5 Least deprived 5.5 \n", + " Unknown 6.5 \n", "bmi 30+ 5.8 \n", - " under 30 5.3 \n", - "chronic_cardiac_disease no 5.3 \n", + " under 30 5.9 \n", + "chronic_cardiac_disease no 5.9 \n", " yes 0.0 \n", - "current_copd no 5.3 \n", + "current_copd no 5.9 \n", " yes 0.0 \n", - "dmards no 5.3 \n", + "dmards no 5.9 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 5.3 \n", + "psychosis_schiz_bipolar no 5.9 \n", " yes 0.0 \n", - "ssri no 5.3 \n", + "ssri no 5.9 \n", " yes 0.0 \n", - "ckd no 5.4 \n", - " yes 4.8 \n", + "ckd no 5.9 \n", + " yes 5.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 0.7 \n", - "sex F 0.4 \n", - " M 0.9 \n", + "overall overall 0.4 \n", + "sex F 0.0 \n", + " M 0.5 \n", "ethnicity_6_groups Black 0.0 \n", - " Mixed 1.2 \n", - " Other 1.4 \n", - " South Asian 1.3 \n", + " Mixed 0.7 \n", + " Other 0.0 \n", + " South Asian 0.7 \n", " Unknown 0.0 \n", - " White 1.3 \n", - "ethnicity_16_groups African 4.0 \n", + " White 0.7 \n", + "ethnicity_16_groups African 0.0 \n", " Bangladeshi or British Bangladeshi 0.0 \n", " Caribbean 0.0 \n", " Chinese 0.0 \n", @@ -39379,35 +39774,35 @@ " Other Asian 0.0 \n", " British or Mixed British 0.0 \n", " Indian or British Indian 0.0 \n", - " Irish 4.0 \n", + " Irish 0.0 \n", " Other Black 0.0 \n", " Other White 0.0 \n", - " Other mixed 3.8 \n", + " Other mixed 0.0 \n", " Pakistani or British Pakistani 0.0 \n", - " Unknown 1.4 \n", + " Unknown 0.8 \n", " White + Asian 0.0 \n", " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", + " White + Black Caribbean 2.1 \n", "imd_categories 1 Most deprived 0.0 \n", - " 2 0.0 \n", - " 3 1.2 \n", + " 2 0.6 \n", + " 3 0.6 \n", " 4 0.0 \n", - " 5 Least deprived 1.2 \n", + " 5 Least deprived 0.0 \n", " Unknown 0.0 \n", - "bmi 30+ 0.8 \n", - " under 30 1.0 \n", - "chronic_cardiac_disease no 0.9 \n", + "bmi 30+ 0.4 \n", + " under 30 0.3 \n", + "chronic_cardiac_disease no 0.2 \n", " yes 0.0 \n", - "current_copd no 0.9 \n", + "current_copd no 0.2 \n", " yes 0.0 \n", - "dmards no 0.9 \n", + "dmards no 0.2 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 0.9 \n", + "psychosis_schiz_bipolar no 0.2 \n", " yes 0.0 \n", - "ssri no 0.9 \n", + "ssri no 0.2 \n", " yes 0.0 \n", - "ckd no 0.8 \n", - " yes 1.2 \n", + "ckd no 0.3 \n", + " yes 0.6 \n", "\n", " Date projected to reach 90% \n", "category group \n", @@ -39420,7 +39815,7 @@ " South Asian unknown \n", " Unknown unknown \n", " White unknown \n", - "ethnicity_16_groups African 30-Apr \n", + "ethnicity_16_groups African unknown \n", " Bangladeshi or British Bangladeshi unknown \n", " Caribbean unknown \n", " Chinese unknown \n", @@ -39428,10 +39823,10 @@ " Other Asian unknown \n", " British or Mixed British unknown \n", " Indian or British Indian unknown \n", - " Irish 07-May \n", + " Irish unknown \n", " Other Black unknown \n", " Other White unknown \n", - " Other mixed 22-May \n", + " Other mixed unknown \n", " Pakistani or British Pakistani unknown \n", " Unknown unknown \n", " White + Asian unknown \n", @@ -39485,7 +39880,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (third dose) among **50-54** population up to 15 Dec 2021" + "## COVID vaccination rollout (third dose) among **50-54** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -39551,330 +39946,330 @@ " \n", " overall\n", " overall\n", - " 196\n", - " 5.7\n", - " 3458\n", - " 5.3\n", - " 0.4\n", + " 406\n", + " 6.0\n", + " 6727\n", + " 5.8\n", + " 0.2\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 91\n", - " 5.1\n", - " 1771\n", - " 4.7\n", + " 203\n", + " 6.0\n", + " 3402\n", + " 5.6\n", " 0.4\n", " unknown\n", " \n", " \n", " M\n", - " 105\n", - " 6.2\n", - " 1687\n", - " 5.4\n", - " 0.8\n", + " 203\n", + " 6.1\n", + " 3325\n", + " 6.1\n", + " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 28\n", - " 4.7\n", - " 595\n", - " 4.7\n", + " 70\n", + " 5.8\n", + " 1197\n", + " 5.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Mixed\n", - " 28\n", - " 4.8\n", - " 588\n", - " 4.8\n", + " 70\n", + " 6.0\n", + " 1176\n", + " 6.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 49\n", - " 8.0\n", - " 616\n", - " 6.8\n", - " 1.2\n", + " 70\n", + " 6.2\n", + " 1120\n", + " 6.2\n", + " 0.0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 28\n", - " 5.0\n", - " 560\n", - " 3.8\n", - " 1.2\n", + " 56\n", + " 5.2\n", + " 1078\n", + " 5.2\n", + " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 28\n", - " 5.3\n", - " 525\n", - " 5.3\n", - " 0.0\n", + " 63\n", + " 6.3\n", + " 994\n", + " 5.6\n", + " 0.7\n", " unknown\n", " \n", " \n", " White\n", - " 35\n", - " 6.1\n", - " 574\n", - " 4.9\n", - " 1.2\n", + " 77\n", + " 6.6\n", + " 1162\n", + " 6.6\n", + " 0.0\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", " 14\n", - " 6.9\n", - " 203\n", - " 6.9\n", + " 3.8\n", + " 364\n", + " 3.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 14\n", - " 8.3\n", - " 168\n", - " 4.2\n", - " 4.1\n", - " 03-May\n", + " 21\n", + " 6.0\n", + " 350\n", + " 6.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Caribbean\n", - " 14\n", - " 7.4\n", - " 189\n", - " 7.4\n", + " 21\n", + " 6.0\n", + " 350\n", + " 6.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Chinese\n", - " 7\n", - " 3.8\n", - " 182\n", - " 3.8\n", + " 28\n", + " 8.2\n", + " 343\n", + " 8.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 14\n", - " 7.4\n", - " 189\n", - " 3.7\n", - " 3.7\n", - " 20-May\n", + " 21\n", + " 6.0\n", + " 350\n", + " 6.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other Asian\n", - " 14\n", - " 7.7\n", - " 182\n", - " 3.8\n", - " 3.9\n", - " 11-May\n", + " 28\n", + " 7.4\n", + " 378\n", + " 7.4\n", + " 0.0\n", + " unknown\n", " \n", " \n", " British or Mixed British\n", - " 14\n", - " 7.1\n", - " 196\n", - " 7.1\n", + " 21\n", + " 6.0\n", + " 350\n", + " 6.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 7\n", - " 3.8\n", - " 182\n", - " 3.8\n", + " 28\n", + " 7.1\n", + " 392\n", + " 7.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 7\n", - " 3.8\n", - " 182\n", - " 3.8\n", + " 14\n", + " 4.1\n", + " 343\n", + " 4.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 7\n", - " 4.0\n", - " 175\n", - " 4.0\n", + " 21\n", + " 5.8\n", + " 364\n", + " 5.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 7\n", - " 4.0\n", - " 175\n", - " 4.0\n", + " 14\n", + " 4.1\n", + " 343\n", + " 4.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 7\n", - " 4.2\n", - " 168\n", - " 4.2\n", + " 21\n", + " 6.0\n", + " 350\n", + " 6.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 7\n", - " 3.8\n", - " 182\n", - " 3.8\n", - " 0.0\n", + " 28\n", + " 7.4\n", + " 378\n", + " 5.6\n", + " 1.8\n", " unknown\n", " \n", " \n", " Unknown\n", - " 28\n", - " 5.6\n", - " 497\n", - " 5.6\n", - " 0.0\n", + " 63\n", + " 6.2\n", + " 1015\n", + " 5.5\n", + " 0.7\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 14\n", - " 7.4\n", - " 189\n", - " 3.7\n", - " 3.7\n", - " 20-May\n", + " 21\n", + " 6.0\n", + " 350\n", + " 6.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black African\n", - " 14\n", - " 6.5\n", - " 217\n", - " 6.5\n", + " 21\n", + " 6.0\n", + " 350\n", + " 6.0\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 14\n", - " 8.3\n", - " 168\n", - " 4.2\n", - " 4.1\n", - " 03-May\n", + " 21\n", + " 5.8\n", + " 364\n", + " 5.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 42\n", - " 6.1\n", - " 686\n", - " 6.1\n", - " 0.0\n", + " 84\n", + " 6.6\n", + " 1274\n", + " 6.0\n", + " 0.6\n", " unknown\n", " \n", " \n", " 2\n", - " 28\n", - " 4.2\n", - " 665\n", - " 4.2\n", + " 56\n", + " 4.3\n", + " 1302\n", + " 4.3\n", " 0.0\n", " unknown\n", " \n", " \n", " 3\n", - " 35\n", - " 5.5\n", - " 637\n", - " 5.5\n", - " 0.0\n", + " 84\n", + " 6.7\n", + " 1253\n", + " 6.1\n", + " 0.6\n", " unknown\n", " \n", " \n", " 4\n", - " 35\n", - " 5.4\n", - " 651\n", - " 5.4\n", + " 84\n", + " 6.7\n", + " 1260\n", + " 6.7\n", " 0.0\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 42\n", - " 6.6\n", - " 637\n", + " 70\n", " 5.5\n", - " 1.1\n", + " 1267\n", + " 5.5\n", + " 0.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 7\n", - " 4.0\n", - " 175\n", - " 4.0\n", + " 28\n", + " 7.4\n", + " 378\n", + " 7.4\n", " 0.0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 56\n", - " 5.6\n", - " 1001\n", - " 4.9\n", - " 0.7\n", + " 112\n", + " 5.7\n", + " 1960\n", + " 5.7\n", + " 0.0\n", " unknown\n", " \n", " \n", " under 30\n", - " 140\n", - " 5.7\n", - " 2457\n", - " 5.4\n", - " 0.3\n", + " 294\n", + " 6.2\n", + " 4767\n", + " 6.0\n", + " 0.2\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 196\n", - " 5.7\n", - " 3430\n", - " 5.3\n", - " 0.4\n", + " 406\n", + " 6.1\n", + " 6664\n", + " 5.9\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 28\n", + " 63\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -39882,18 +40277,18 @@ " \n", " current_copd\n", " no\n", - " 196\n", - " 5.7\n", - " 3423\n", - " 5.3\n", - " 0.4\n", + " 406\n", + " 6.1\n", + " 6650\n", + " 5.9\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 77\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -39901,18 +40296,18 @@ " \n", " dmards\n", " no\n", - " 196\n", - " 5.7\n", - " 3430\n", - " 5.3\n", - " 0.4\n", + " 406\n", + " 6.1\n", + " 6664\n", + " 5.9\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 28\n", + " 56\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -39920,18 +40315,18 @@ " \n", " psychosis_schiz_bipolar\n", " no\n", - " 196\n", - " 5.7\n", - " 3423\n", - " 5.3\n", - " 0.4\n", + " 399\n", + " 6.0\n", + " 6657\n", + " 5.8\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 70\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -39939,18 +40334,18 @@ " \n", " ssri\n", " no\n", - " 196\n", - " 5.7\n", - " 3416\n", - " 5.3\n", - " 0.4\n", + " 406\n", + " 6.1\n", + " 6657\n", + " 5.9\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 35\n", + " 63\n", " 0.0\n", " 0.0\n", " unknown\n", @@ -39958,19 +40353,19 @@ " \n", " ckd\n", " no\n", - " 168\n", + " 336\n", + " 6.2\n", + " 5376\n", " 6.0\n", - " 2786\n", - " 5.5\n", - " 0.5\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", - " 28\n", - " 4.2\n", - " 672\n", - " 4.2\n", + " 77\n", + " 5.7\n", + " 1351\n", + " 5.7\n", " 0.0\n", " unknown\n", " \n", @@ -39981,198 +40376,198 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 196 \n", - "sex F 91 \n", - " M 105 \n", - "ethnicity_6_groups Black 28 \n", - " Mixed 28 \n", - " Other 49 \n", - " South Asian 28 \n", - " Unknown 28 \n", - " White 35 \n", + "overall overall 406 \n", + "sex F 203 \n", + " M 203 \n", + "ethnicity_6_groups Black 70 \n", + " Mixed 70 \n", + " Other 70 \n", + " South Asian 56 \n", + " Unknown 63 \n", + " White 77 \n", "ethnicity_16_groups African 14 \n", - " Bangladeshi or British Bangladeshi 14 \n", - " Caribbean 14 \n", - " Chinese 7 \n", - " Other 14 \n", - " Other Asian 14 \n", - " British or Mixed British 14 \n", - " Indian or British Indian 7 \n", - " Irish 7 \n", - " Other Black 7 \n", - " Other White 7 \n", - " Other mixed 7 \n", - " Pakistani or British Pakistani 7 \n", + " Bangladeshi or British Bangladeshi 21 \n", + " Caribbean 21 \n", + " Chinese 28 \n", + " Other 21 \n", + " Other Asian 28 \n", + " British or Mixed British 21 \n", + " Indian or British Indian 28 \n", + " Irish 14 \n", + " Other Black 21 \n", + " Other White 14 \n", + " Other mixed 21 \n", + " Pakistani or British Pakistani 28 \n", + " Unknown 63 \n", + " White + Asian 21 \n", + " White + Black African 21 \n", + " White + Black Caribbean 21 \n", + "imd_categories 1 Most deprived 84 \n", + " 2 56 \n", + " 3 84 \n", + " 4 84 \n", + " 5 Least deprived 70 \n", " Unknown 28 \n", - " White + Asian 14 \n", - " White + Black African 14 \n", - " White + Black Caribbean 14 \n", - "imd_categories 1 Most deprived 42 \n", - " 2 28 \n", - " 3 35 \n", - " 4 35 \n", - " 5 Least deprived 42 \n", - " Unknown 7 \n", - "bmi 30+ 56 \n", - " under 30 140 \n", - "chronic_cardiac_disease no 196 \n", + "bmi 30+ 112 \n", + " under 30 294 \n", + "chronic_cardiac_disease no 406 \n", " yes 0 \n", - "current_copd no 196 \n", + "current_copd no 406 \n", " yes 0 \n", - "dmards no 196 \n", + "dmards no 406 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 196 \n", + "psychosis_schiz_bipolar no 399 \n", " yes 0 \n", - "ssri no 196 \n", + "ssri no 406 \n", " yes 0 \n", - "ckd no 168 \n", - " yes 28 \n", + "ckd no 336 \n", + " yes 77 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 5.7 3458 \n", - "sex F 5.1 1771 \n", - " M 6.2 1687 \n", - "ethnicity_6_groups Black 4.7 595 \n", - " Mixed 4.8 588 \n", - " Other 8.0 616 \n", - " South Asian 5.0 560 \n", - " Unknown 5.3 525 \n", - " White 6.1 574 \n", - "ethnicity_16_groups African 6.9 203 \n", - " Bangladeshi or British Bangladeshi 8.3 168 \n", - " Caribbean 7.4 189 \n", - " Chinese 3.8 182 \n", - " Other 7.4 189 \n", - " Other Asian 7.7 182 \n", - " British or Mixed British 7.1 196 \n", - " Indian or British Indian 3.8 182 \n", - " Irish 3.8 182 \n", - " Other Black 4.0 175 \n", - " Other White 4.0 175 \n", - " Other mixed 4.2 168 \n", - " Pakistani or British Pakistani 3.8 182 \n", - " Unknown 5.6 497 \n", - " White + Asian 7.4 189 \n", - " White + Black African 6.5 217 \n", - " White + Black Caribbean 8.3 168 \n", - "imd_categories 1 Most deprived 6.1 686 \n", - " 2 4.2 665 \n", - " 3 5.5 637 \n", - " 4 5.4 651 \n", - " 5 Least deprived 6.6 637 \n", - " Unknown 4.0 175 \n", - "bmi 30+ 5.6 1001 \n", - " under 30 5.7 2457 \n", - "chronic_cardiac_disease no 5.7 3430 \n", - " yes 0.0 28 \n", - "current_copd no 5.7 3423 \n", - " yes 0.0 35 \n", - "dmards no 5.7 3430 \n", - " yes 0.0 28 \n", - "psychosis_schiz_bipolar no 5.7 3423 \n", - " yes 0.0 35 \n", - "ssri no 5.7 3416 \n", - " yes 0.0 35 \n", - "ckd no 6.0 2786 \n", - " yes 4.2 672 \n", + "overall overall 6.0 6727 \n", + "sex F 6.0 3402 \n", + " M 6.1 3325 \n", + "ethnicity_6_groups Black 5.8 1197 \n", + " Mixed 6.0 1176 \n", + " Other 6.2 1120 \n", + " South Asian 5.2 1078 \n", + " Unknown 6.3 994 \n", + " White 6.6 1162 \n", + "ethnicity_16_groups African 3.8 364 \n", + " Bangladeshi or British Bangladeshi 6.0 350 \n", + " Caribbean 6.0 350 \n", + " Chinese 8.2 343 \n", + " Other 6.0 350 \n", + " Other Asian 7.4 378 \n", + " British or Mixed British 6.0 350 \n", + " Indian or British Indian 7.1 392 \n", + " Irish 4.1 343 \n", + " Other Black 5.8 364 \n", + " Other White 4.1 343 \n", + " Other mixed 6.0 350 \n", + " Pakistani or British Pakistani 7.4 378 \n", + " Unknown 6.2 1015 \n", + " White + Asian 6.0 350 \n", + " White + Black African 6.0 350 \n", + " White + Black Caribbean 5.8 364 \n", + "imd_categories 1 Most deprived 6.6 1274 \n", + " 2 4.3 1302 \n", + " 3 6.7 1253 \n", + " 4 6.7 1260 \n", + " 5 Least deprived 5.5 1267 \n", + " Unknown 7.4 378 \n", + "bmi 30+ 5.7 1960 \n", + " under 30 6.2 4767 \n", + "chronic_cardiac_disease no 6.1 6664 \n", + " yes 0.0 63 \n", + "current_copd no 6.1 6650 \n", + " yes 0.0 77 \n", + "dmards no 6.1 6664 \n", + " yes 0.0 56 \n", + "psychosis_schiz_bipolar no 6.0 6657 \n", + " yes 0.0 70 \n", + "ssri no 6.1 6657 \n", + " yes 0.0 63 \n", + "ckd no 6.2 5376 \n", + " yes 5.7 1351 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 5.3 \n", - "sex F 4.7 \n", - " M 5.4 \n", - "ethnicity_6_groups Black 4.7 \n", - " Mixed 4.8 \n", - " Other 6.8 \n", - " South Asian 3.8 \n", - " Unknown 5.3 \n", - " White 4.9 \n", - "ethnicity_16_groups African 6.9 \n", - " Bangladeshi or British Bangladeshi 4.2 \n", - " Caribbean 7.4 \n", - " Chinese 3.8 \n", - " Other 3.7 \n", - " Other Asian 3.8 \n", - " British or Mixed British 7.1 \n", - " Indian or British Indian 3.8 \n", - " Irish 3.8 \n", - " Other Black 4.0 \n", - " Other White 4.0 \n", - " Other mixed 4.2 \n", - " Pakistani or British Pakistani 3.8 \n", + "overall overall 5.8 \n", + "sex F 5.6 \n", + " M 6.1 \n", + "ethnicity_6_groups Black 5.8 \n", + " Mixed 6.0 \n", + " Other 6.2 \n", + " South Asian 5.2 \n", " Unknown 5.6 \n", - " White + Asian 3.7 \n", - " White + Black African 6.5 \n", - " White + Black Caribbean 4.2 \n", - "imd_categories 1 Most deprived 6.1 \n", - " 2 4.2 \n", - " 3 5.5 \n", - " 4 5.4 \n", + " White 6.6 \n", + "ethnicity_16_groups African 3.8 \n", + " Bangladeshi or British Bangladeshi 6.0 \n", + " Caribbean 6.0 \n", + " Chinese 8.2 \n", + " Other 6.0 \n", + " Other Asian 7.4 \n", + " British or Mixed British 6.0 \n", + " Indian or British Indian 7.1 \n", + " Irish 4.1 \n", + " Other Black 5.8 \n", + " Other White 4.1 \n", + " Other mixed 6.0 \n", + " Pakistani or British Pakistani 5.6 \n", + " Unknown 5.5 \n", + " White + Asian 6.0 \n", + " White + Black African 6.0 \n", + " White + Black Caribbean 5.8 \n", + "imd_categories 1 Most deprived 6.0 \n", + " 2 4.3 \n", + " 3 6.1 \n", + " 4 6.7 \n", " 5 Least deprived 5.5 \n", - " Unknown 4.0 \n", - "bmi 30+ 4.9 \n", - " under 30 5.4 \n", - "chronic_cardiac_disease no 5.3 \n", + " Unknown 7.4 \n", + "bmi 30+ 5.7 \n", + " under 30 6.0 \n", + "chronic_cardiac_disease no 5.9 \n", " yes 0.0 \n", - "current_copd no 5.3 \n", + "current_copd no 5.9 \n", " yes 0.0 \n", - "dmards no 5.3 \n", + "dmards no 5.9 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 5.3 \n", + "psychosis_schiz_bipolar no 5.8 \n", " yes 0.0 \n", - "ssri no 5.3 \n", + "ssri no 5.9 \n", " yes 0.0 \n", - "ckd no 5.5 \n", - " yes 4.2 \n", + "ckd no 6.0 \n", + " yes 5.7 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 0.4 \n", + "overall overall 0.2 \n", "sex F 0.4 \n", - " M 0.8 \n", + " M 0.0 \n", "ethnicity_6_groups Black 0.0 \n", " Mixed 0.0 \n", - " Other 1.2 \n", - " South Asian 1.2 \n", - " Unknown 0.0 \n", - " White 1.2 \n", + " Other 0.0 \n", + " South Asian 0.0 \n", + " Unknown 0.7 \n", + " White 0.0 \n", "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 4.1 \n", + " Bangladeshi or British Bangladeshi 0.0 \n", " Caribbean 0.0 \n", " Chinese 0.0 \n", - " Other 3.7 \n", - " Other Asian 3.9 \n", + " Other 0.0 \n", + " Other Asian 0.0 \n", " British or Mixed British 0.0 \n", " Indian or British Indian 0.0 \n", " Irish 0.0 \n", " Other Black 0.0 \n", " Other White 0.0 \n", " Other mixed 0.0 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 0.0 \n", - " White + Asian 3.7 \n", + " Pakistani or British Pakistani 1.8 \n", + " Unknown 0.7 \n", + " White + Asian 0.0 \n", " White + Black African 0.0 \n", - " White + Black Caribbean 4.1 \n", - "imd_categories 1 Most deprived 0.0 \n", + " White + Black Caribbean 0.0 \n", + "imd_categories 1 Most deprived 0.6 \n", " 2 0.0 \n", - " 3 0.0 \n", + " 3 0.6 \n", " 4 0.0 \n", - " 5 Least deprived 1.1 \n", + " 5 Least deprived 0.0 \n", " Unknown 0.0 \n", - "bmi 30+ 0.7 \n", - " under 30 0.3 \n", - "chronic_cardiac_disease no 0.4 \n", + "bmi 30+ 0.0 \n", + " under 30 0.2 \n", + "chronic_cardiac_disease no 0.2 \n", " yes 0.0 \n", - "current_copd no 0.4 \n", + "current_copd no 0.2 \n", " yes 0.0 \n", - "dmards no 0.4 \n", + "dmards no 0.2 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 0.4 \n", + "psychosis_schiz_bipolar no 0.2 \n", " yes 0.0 \n", - "ssri no 0.4 \n", + "ssri no 0.2 \n", " yes 0.0 \n", - "ckd no 0.5 \n", + "ckd no 0.2 \n", " yes 0.0 \n", "\n", " Date projected to reach 90% \n", @@ -40187,11 +40582,11 @@ " Unknown unknown \n", " White unknown \n", "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi 03-May \n", + " Bangladeshi or British Bangladeshi unknown \n", " Caribbean unknown \n", " Chinese unknown \n", - " Other 20-May \n", - " Other Asian 11-May \n", + " Other unknown \n", + " Other Asian unknown \n", " British or Mixed British unknown \n", " Indian or British Indian unknown \n", " Irish unknown \n", @@ -40200,9 +40595,9 @@ " Other mixed unknown \n", " Pakistani or British Pakistani unknown \n", " Unknown unknown \n", - " White + Asian 20-May \n", + " White + Asian unknown \n", " White + Black African unknown \n", - " White + Black Caribbean 03-May \n", + " White + Black Caribbean unknown \n", "imd_categories 1 Most deprived unknown \n", " 2 unknown \n", " 3 unknown \n", @@ -40251,7 +40646,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (third dose) among **40-49** population up to 15 Dec 2021" + "## COVID vaccination rollout (third dose) among **40-49** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -40317,417 +40712,426 @@ " \n", " overall\n", " overall\n", - " 357\n", + " 714\n", " 5.8\n", - " 6139\n", - " 5.2\n", - " 0.6\n", + " 12257\n", + " 5.5\n", + " 0.3\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 182\n", - " 5.8\n", - " 3164\n", - " 5.3\n", - " 0.5\n", + " 399\n", + " 6.2\n", + " 6391\n", + " 5.9\n", + " 0.3\n", " unknown\n", " \n", " \n", " M\n", - " 175\n", - " 5.9\n", - " 2975\n", - " 5.2\n", - " 0.7\n", + " 315\n", + " 5.4\n", + " 5866\n", + " 5.1\n", + " 0.3\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 56\n", - " 5.6\n", - " 1008\n", - " 4.9\n", - " 0.7\n", + " 112\n", + " 5.4\n", + " 2093\n", + " 5.4\n", + " 0.0\n", " unknown\n", " \n", " \n", " Mixed\n", - " 63\n", - " 6.0\n", - " 1057\n", + " 133\n", + " 6.4\n", + " 2086\n", " 6.0\n", - " 0.0\n", + " 0.4\n", " unknown\n", " \n", " \n", " Other\n", - " 49\n", - " 4.8\n", - " 1022\n", - " 4.1\n", - " 0.7\n", + " 126\n", + " 6.1\n", + " 2058\n", + " 5.8\n", + " 0.3\n", " unknown\n", " \n", " \n", " South Asian\n", - " 70\n", - " 6.6\n", - " 1057\n", - " 6.6\n", - " 0.0\n", + " 112\n", + " 5.4\n", + " 2058\n", + " 5.1\n", + " 0.3\n", " unknown\n", " \n", " \n", " Unknown\n", - " 63\n", - " 7.0\n", - " 903\n", - " 6.2\n", - " 0.8\n", + " 105\n", + " 5.5\n", + " 1897\n", + " 5.2\n", + " 0.3\n", " unknown\n", " \n", " \n", " White\n", - " 49\n", - " 4.5\n", - " 1092\n", - " 3.8\n", - " 0.7\n", + " 126\n", + " 6.1\n", + " 2065\n", + " 5.8\n", + " 0.3\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 14\n", - " 4.3\n", - " 322\n", - " 4.3\n", + " 28\n", + " 4.4\n", + " 637\n", + " 4.4\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 21\n", - " 6.8\n", - " 308\n", - " 6.8\n", + " 28\n", + " 4.3\n", + " 644\n", + " 4.3\n", " 0.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 28\n", - " 8.7\n", - " 322\n", - " 6.5\n", - " 2.2\n", + " 42\n", + " 5.9\n", + " 714\n", + " 5.9\n", + " 0.0\n", " unknown\n", " \n", " \n", " Chinese\n", - " 21\n", - " 6.1\n", - " 343\n", - " 4.1\n", - " 2.0\n", + " 35\n", + " 5.5\n", + " 637\n", + " 5.5\n", + " 0.0\n", " unknown\n", " \n", " \n", " Other\n", - " 21\n", - " 6.0\n", - " 350\n", - " 6.0\n", + " 49\n", + " 7.2\n", + " 679\n", + " 7.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 21\n", - " 6.4\n", - " 329\n", - " 6.4\n", + " 28\n", + " 4.5\n", + " 623\n", + " 4.5\n", " 0.0\n", " unknown\n", " \n", " \n", " British or Mixed British\n", - " 14\n", - " 4.1\n", - " 343\n", - " 4.1\n", - " 0.0\n", + " 49\n", + " 7.6\n", + " 644\n", + " 6.5\n", + " 1.1\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 14\n", - " 4.8\n", - " 294\n", - " 4.8\n", + " 35\n", + " 5.4\n", + " 644\n", + " 5.4\n", " 0.0\n", " unknown\n", " \n", " \n", " Irish\n", - " 14\n", - " 4.1\n", - " 343\n", - " 4.1\n", - " 0.0\n", + " 49\n", + " 7.1\n", + " 693\n", + " 6.1\n", + " 1.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 21\n", - " 6.4\n", - " 329\n", - " 6.4\n", + " 28\n", + " 4.2\n", + " 672\n", + " 4.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 21\n", - " 6.7\n", - " 315\n", - " 6.7\n", + " 49\n", + " 7.1\n", + " 686\n", + " 7.1\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 14\n", - " 4.5\n", - " 308\n", - " 4.5\n", - " 0.0\n", + " 42\n", + " 6.7\n", + " 630\n", + " 5.6\n", + " 1.1\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 14\n", - " 4.3\n", - " 322\n", - " 4.3\n", - " 0.0\n", + " 35\n", + " 5.7\n", + " 616\n", + " 4.5\n", + " 1.2\n", " unknown\n", " \n", " \n", " Unknown\n", - " 63\n", - " 6.7\n", - " 938\n", - " 6.7\n", - " 0.0\n", + " 112\n", + " 6.2\n", + " 1820\n", + " 5.8\n", + " 0.4\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 14\n", - " 4.3\n", - " 322\n", - " 4.3\n", - " 0.0\n", + " 35\n", + " 5.9\n", + " 595\n", + " 4.7\n", + " 1.2\n", " unknown\n", " \n", " \n", " White + Black African\n", - " 14\n", - " 4.3\n", - " 322\n", - " 4.3\n", + " 35\n", + " 5.4\n", + " 651\n", + " 5.4\n", " 0.0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 28\n", - " 8.5\n", - " 329\n", - " 6.4\n", - " 2.1\n", + " 35\n", + " 5.3\n", + " 665\n", + " 5.3\n", + " 0.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 77\n", - " 6.6\n", - " 1169\n", + " 140\n", " 6.0\n", - " 0.6\n", + " 2324\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " 2\n", - " 49\n", - " 4.3\n", - " 1148\n", - " 4.3\n", - " 0.0\n", + " 147\n", + " 6.4\n", + " 2310\n", + " 5.8\n", + " 0.6\n", " unknown\n", " \n", " \n", " 3\n", - " 70\n", - " 6.0\n", - " 1162\n", + " 133\n", + " 5.7\n", + " 2331\n", " 5.4\n", - " 0.6\n", + " 0.3\n", " unknown\n", " \n", " \n", " 4\n", - " 70\n", - " 6.1\n", - " 1155\n", - " 5.5\n", - " 0.6\n", + " 126\n", + " 5.4\n", + " 2324\n", + " 5.1\n", + " 0.3\n", " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 70\n", - " 5.8\n", - " 1197\n", - " 5.3\n", - " 0.5\n", + " 140\n", + " 6.0\n", + " 2352\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", " Unknown\n", - " 21\n", - " 7.0\n", - " 301\n", - " 7.0\n", - " 0.0\n", + " 42\n", + " 6.8\n", + " 616\n", + " 5.7\n", + " 1.1\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 105\n", - " 5.5\n", - " 1897\n", + " 217\n", + " 5.9\n", + " 3661\n", " 5.5\n", - " 0.0\n", + " 0.4\n", " unknown\n", " \n", " \n", " under 30\n", - " 245\n", - " 5.8\n", - " 4242\n", - " 5.3\n", - " 0.5\n", + " 504\n", + " 5.9\n", + " 8589\n", + " 5.5\n", + " 0.4\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 350\n", + " 707\n", " 5.8\n", - " 6076\n", - " 5.3\n", - " 0.5\n", + " 12117\n", + " 5.5\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 63\n", - " 0.0\n", + " 14\n", + " 10.0\n", + " 140\n", + " 10.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " current_copd\n", + " current_copd\n", " no\n", - " 357\n", + " 714\n", " 5.9\n", - " 6076\n", - " 5.3\n", - " 0.6\n", - " unknown\n", - " \n", - " \n", - " dmards\n", - " no\n", - " 350\n", - " 5.8\n", - " 6069\n", - " 5.3\n", - " 0.5\n", + " 12145\n", + " 5.5\n", + " 0.4\n", " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 70\n", + " 112\n", " 0.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " psychosis_schiz_bipolar\n", + " dmards\n", " no\n", - " 357\n", - " 5.9\n", - " 6076\n", - " 5.3\n", - " 0.6\n", + " 707\n", + " 5.8\n", + " 12117\n", + " 5.5\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 56\n", + " 7\n", + " 5.0\n", + " 140\n", + " 5.0\n", " 0.0\n", + " unknown\n", + " \n", + " \n", + " psychosis_schiz_bipolar\n", + " no\n", + " 707\n", + " 5.8\n", + " 12138\n", + " 5.5\n", + " 0.3\n", + " unknown\n", + " \n", + " \n", + " yes\n", + " 7\n", + " 5.9\n", + " 119\n", + " 5.9\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 350\n", - " 5.7\n", - " 6090\n", - " 5.3\n", - " 0.4\n", + " 707\n", + " 5.8\n", + " 12159\n", + " 5.5\n", + " 0.3\n", " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 49\n", - " 0.0\n", + " 7\n", + " 7.1\n", + " 98\n", + " 7.1\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 287\n", - " 5.9\n", - " 4879\n", - " 5.3\n", - " 0.6\n", + " 560\n", + " 5.7\n", + " 9835\n", + " 5.5\n", + " 0.2\n", " unknown\n", " \n", " \n", " yes\n", - " 70\n", - " 5.6\n", - " 1260\n", - " 5.0\n", + " 154\n", + " 6.4\n", + " 2422\n", + " 5.8\n", " 0.6\n", " unknown\n", " \n", @@ -40738,194 +41142,198 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 357 \n", - "sex F 182 \n", - " M 175 \n", - "ethnicity_6_groups Black 56 \n", - " Mixed 63 \n", - " Other 49 \n", - " South Asian 70 \n", - " Unknown 63 \n", - " White 49 \n", - "ethnicity_16_groups African 14 \n", - " Bangladeshi or British Bangladeshi 21 \n", - " Caribbean 28 \n", - " Chinese 21 \n", - " Other 21 \n", - " Other Asian 21 \n", - " British or Mixed British 14 \n", - " Indian or British Indian 14 \n", - " Irish 14 \n", - " Other Black 21 \n", - " Other White 21 \n", - " Other mixed 14 \n", - " Pakistani or British Pakistani 14 \n", - " Unknown 63 \n", - " White + Asian 14 \n", - " White + Black African 14 \n", - " White + Black Caribbean 28 \n", - "imd_categories 1 Most deprived 77 \n", - " 2 49 \n", - " 3 70 \n", - " 4 70 \n", - " 5 Least deprived 70 \n", - " Unknown 21 \n", - "bmi 30+ 105 \n", - " under 30 245 \n", - "chronic_cardiac_disease no 350 \n", - " yes 0 \n", - "current_copd no 357 \n", - "dmards no 350 \n", - " yes 0 \n", - "psychosis_schiz_bipolar no 357 \n", - " yes 0 \n", - "ssri no 350 \n", + "overall overall 714 \n", + "sex F 399 \n", + " M 315 \n", + "ethnicity_6_groups Black 112 \n", + " Mixed 133 \n", + " Other 126 \n", + " South Asian 112 \n", + " Unknown 105 \n", + " White 126 \n", + "ethnicity_16_groups African 28 \n", + " Bangladeshi or British Bangladeshi 28 \n", + " Caribbean 42 \n", + " Chinese 35 \n", + " Other 49 \n", + " Other Asian 28 \n", + " British or Mixed British 49 \n", + " Indian or British Indian 35 \n", + " Irish 49 \n", + " Other Black 28 \n", + " Other White 49 \n", + " Other mixed 42 \n", + " Pakistani or British Pakistani 35 \n", + " Unknown 112 \n", + " White + Asian 35 \n", + " White + Black African 35 \n", + " White + Black Caribbean 35 \n", + "imd_categories 1 Most deprived 140 \n", + " 2 147 \n", + " 3 133 \n", + " 4 126 \n", + " 5 Least deprived 140 \n", + " Unknown 42 \n", + "bmi 30+ 217 \n", + " under 30 504 \n", + "chronic_cardiac_disease no 707 \n", + " yes 14 \n", + "current_copd no 714 \n", " yes 0 \n", - "ckd no 287 \n", - " yes 70 \n", + "dmards no 707 \n", + " yes 7 \n", + "psychosis_schiz_bipolar no 707 \n", + " yes 7 \n", + "ssri no 707 \n", + " yes 7 \n", + "ckd no 560 \n", + " yes 154 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 5.8 6139 \n", - "sex F 5.8 3164 \n", - " M 5.9 2975 \n", - "ethnicity_6_groups Black 5.6 1008 \n", - " Mixed 6.0 1057 \n", - " Other 4.8 1022 \n", - " South Asian 6.6 1057 \n", - " Unknown 7.0 903 \n", - " White 4.5 1092 \n", - "ethnicity_16_groups African 4.3 322 \n", - " Bangladeshi or British Bangladeshi 6.8 308 \n", - " Caribbean 8.7 322 \n", - " Chinese 6.1 343 \n", - " Other 6.0 350 \n", - " Other Asian 6.4 329 \n", - " British or Mixed British 4.1 343 \n", - " Indian or British Indian 4.8 294 \n", - " Irish 4.1 343 \n", - " Other Black 6.4 329 \n", - " Other White 6.7 315 \n", - " Other mixed 4.5 308 \n", - " Pakistani or British Pakistani 4.3 322 \n", - " Unknown 6.7 938 \n", - " White + Asian 4.3 322 \n", - " White + Black African 4.3 322 \n", - " White + Black Caribbean 8.5 329 \n", - "imd_categories 1 Most deprived 6.6 1169 \n", - " 2 4.3 1148 \n", - " 3 6.0 1162 \n", - " 4 6.1 1155 \n", - " 5 Least deprived 5.8 1197 \n", - " Unknown 7.0 301 \n", - "bmi 30+ 5.5 1897 \n", - " under 30 5.8 4242 \n", - "chronic_cardiac_disease no 5.8 6076 \n", - " yes 0.0 63 \n", - "current_copd no 5.9 6076 \n", - "dmards no 5.8 6069 \n", - " yes 0.0 70 \n", - "psychosis_schiz_bipolar no 5.9 6076 \n", - " yes 0.0 56 \n", - "ssri no 5.7 6090 \n", - " yes 0.0 49 \n", - "ckd no 5.9 4879 \n", - " yes 5.6 1260 \n", + "overall overall 5.8 12257 \n", + "sex F 6.2 6391 \n", + " M 5.4 5866 \n", + "ethnicity_6_groups Black 5.4 2093 \n", + " Mixed 6.4 2086 \n", + " Other 6.1 2058 \n", + " South Asian 5.4 2058 \n", + " Unknown 5.5 1897 \n", + " White 6.1 2065 \n", + "ethnicity_16_groups African 4.4 637 \n", + " Bangladeshi or British Bangladeshi 4.3 644 \n", + " Caribbean 5.9 714 \n", + " Chinese 5.5 637 \n", + " Other 7.2 679 \n", + " Other Asian 4.5 623 \n", + " British or Mixed British 7.6 644 \n", + " Indian or British Indian 5.4 644 \n", + " Irish 7.1 693 \n", + " Other Black 4.2 672 \n", + " Other White 7.1 686 \n", + " Other mixed 6.7 630 \n", + " Pakistani or British Pakistani 5.7 616 \n", + " Unknown 6.2 1820 \n", + " White + Asian 5.9 595 \n", + " White + Black African 5.4 651 \n", + " White + Black Caribbean 5.3 665 \n", + "imd_categories 1 Most deprived 6.0 2324 \n", + " 2 6.4 2310 \n", + " 3 5.7 2331 \n", + " 4 5.4 2324 \n", + " 5 Least deprived 6.0 2352 \n", + " Unknown 6.8 616 \n", + "bmi 30+ 5.9 3661 \n", + " under 30 5.9 8589 \n", + "chronic_cardiac_disease no 5.8 12117 \n", + " yes 10.0 140 \n", + "current_copd no 5.9 12145 \n", + " yes 0.0 112 \n", + "dmards no 5.8 12117 \n", + " yes 5.0 140 \n", + "psychosis_schiz_bipolar no 5.8 12138 \n", + " yes 5.9 119 \n", + "ssri no 5.8 12159 \n", + " yes 7.1 98 \n", + "ckd no 5.7 9835 \n", + " yes 6.4 2422 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 5.2 \n", - "sex F 5.3 \n", - " M 5.2 \n", - "ethnicity_6_groups Black 4.9 \n", + "overall overall 5.5 \n", + "sex F 5.9 \n", + " M 5.1 \n", + "ethnicity_6_groups Black 5.4 \n", " Mixed 6.0 \n", - " Other 4.1 \n", - " South Asian 6.6 \n", - " Unknown 6.2 \n", - " White 3.8 \n", - "ethnicity_16_groups African 4.3 \n", - " Bangladeshi or British Bangladeshi 6.8 \n", - " Caribbean 6.5 \n", - " Chinese 4.1 \n", - " Other 6.0 \n", - " Other Asian 6.4 \n", - " British or Mixed British 4.1 \n", - " Indian or British Indian 4.8 \n", - " Irish 4.1 \n", - " Other Black 6.4 \n", - " Other White 6.7 \n", - " Other mixed 4.5 \n", - " Pakistani or British Pakistani 4.3 \n", - " Unknown 6.7 \n", - " White + Asian 4.3 \n", - " White + Black African 4.3 \n", - " White + Black Caribbean 6.4 \n", - "imd_categories 1 Most deprived 6.0 \n", - " 2 4.3 \n", + " Other 5.8 \n", + " South Asian 5.1 \n", + " Unknown 5.2 \n", + " White 5.8 \n", + "ethnicity_16_groups African 4.4 \n", + " Bangladeshi or British Bangladeshi 4.3 \n", + " Caribbean 5.9 \n", + " Chinese 5.5 \n", + " Other 7.2 \n", + " Other Asian 4.5 \n", + " British or Mixed British 6.5 \n", + " Indian or British Indian 5.4 \n", + " Irish 6.1 \n", + " Other Black 4.2 \n", + " Other White 7.1 \n", + " Other mixed 5.6 \n", + " Pakistani or British Pakistani 4.5 \n", + " Unknown 5.8 \n", + " White + Asian 4.7 \n", + " White + Black African 5.4 \n", + " White + Black Caribbean 5.3 \n", + "imd_categories 1 Most deprived 5.7 \n", + " 2 5.8 \n", " 3 5.4 \n", - " 4 5.5 \n", - " 5 Least deprived 5.3 \n", - " Unknown 7.0 \n", + " 4 5.1 \n", + " 5 Least deprived 5.7 \n", + " Unknown 5.7 \n", "bmi 30+ 5.5 \n", - " under 30 5.3 \n", - "chronic_cardiac_disease no 5.3 \n", - " yes 0.0 \n", - "current_copd no 5.3 \n", - "dmards no 5.3 \n", - " yes 0.0 \n", - "psychosis_schiz_bipolar no 5.3 \n", + " under 30 5.5 \n", + "chronic_cardiac_disease no 5.5 \n", + " yes 10.0 \n", + "current_copd no 5.5 \n", " yes 0.0 \n", - "ssri no 5.3 \n", - " yes 0.0 \n", - "ckd no 5.3 \n", + "dmards no 5.5 \n", " yes 5.0 \n", + "psychosis_schiz_bipolar no 5.5 \n", + " yes 5.9 \n", + "ssri no 5.5 \n", + " yes 7.1 \n", + "ckd no 5.5 \n", + " yes 5.8 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 0.6 \n", - "sex F 0.5 \n", - " M 0.7 \n", - "ethnicity_6_groups Black 0.7 \n", - " Mixed 0.0 \n", - " Other 0.7 \n", - " South Asian 0.0 \n", - " Unknown 0.8 \n", - " White 0.7 \n", + "overall overall 0.3 \n", + "sex F 0.3 \n", + " M 0.3 \n", + "ethnicity_6_groups Black 0.0 \n", + " Mixed 0.4 \n", + " Other 0.3 \n", + " South Asian 0.3 \n", + " Unknown 0.3 \n", + " White 0.3 \n", "ethnicity_16_groups African 0.0 \n", " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 2.2 \n", - " Chinese 2.0 \n", + " Caribbean 0.0 \n", + " Chinese 0.0 \n", " Other 0.0 \n", " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", + " British or Mixed British 1.1 \n", " Indian or British Indian 0.0 \n", - " Irish 0.0 \n", + " Irish 1.0 \n", " Other Black 0.0 \n", " Other White 0.0 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 0.0 \n", - " White + Asian 0.0 \n", + " Other mixed 1.1 \n", + " Pakistani or British Pakistani 1.2 \n", + " Unknown 0.4 \n", + " White + Asian 1.2 \n", " White + Black African 0.0 \n", - " White + Black Caribbean 2.1 \n", - "imd_categories 1 Most deprived 0.6 \n", - " 2 0.0 \n", - " 3 0.6 \n", - " 4 0.6 \n", - " 5 Least deprived 0.5 \n", - " Unknown 0.0 \n", - "bmi 30+ 0.0 \n", - " under 30 0.5 \n", - "chronic_cardiac_disease no 0.5 \n", + " White + Black Caribbean 0.0 \n", + "imd_categories 1 Most deprived 0.3 \n", + " 2 0.6 \n", + " 3 0.3 \n", + " 4 0.3 \n", + " 5 Least deprived 0.3 \n", + " Unknown 1.1 \n", + "bmi 30+ 0.4 \n", + " under 30 0.4 \n", + "chronic_cardiac_disease no 0.3 \n", + " yes 0.0 \n", + "current_copd no 0.4 \n", " yes 0.0 \n", - "current_copd no 0.6 \n", - "dmards no 0.5 \n", + "dmards no 0.3 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 0.6 \n", + "psychosis_schiz_bipolar no 0.3 \n", " yes 0.0 \n", - "ssri no 0.4 \n", + "ssri no 0.3 \n", " yes 0.0 \n", - "ckd no 0.6 \n", + "ckd no 0.2 \n", " yes 0.6 \n", "\n", " Date projected to reach 90% \n", @@ -40967,6 +41375,7 @@ "chronic_cardiac_disease no unknown \n", " yes unknown \n", "current_copd no unknown \n", + " yes unknown \n", "dmards no unknown \n", " yes unknown \n", "psychosis_schiz_bipolar no unknown \n", @@ -40987,52 +41396,6 @@ "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:644: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", " out_csv = out_csv.drop(\"Date projected to reach 90%\",1)\n" ] - } - ], - "source": [ - "# summarise third doses to date (after filtering above)\n", - "\n", - "# Include 40+ age groups plus priority groups (50+/CEV/Care home etc) only\n", - "population_subgroups_third = {key: value for key, value in population_subgroups.items() if 0 < value < 11}\n", - "\n", - "df_dict_cum_third_dose = cumulative_sums(df_t, groups_of_interest=population_subgroups_third, features_dict=features_dict,\n", - " latest_date=latest_date, reference_column_name=\"covid_vacc_third_dose_date\")\n", - "\n", - "third_dose_summarised_data_dict = summarise_data_by_group(\n", - " df_dict_cum_third_dose, latest_date=latest_date, groups=population_subgroups_third.keys())\n", - "\n", - "create_detailed_summary_uptake(third_dose_summarised_data_dict, formatted_latest_date,\n", - " groups=population_subgroups_third.keys(),\n", - " savepath=savepath, vaccine_type=\"third_dose\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "display(Markdown(f\"## For comparison look at second dose coverate UP TO {booster_delay_number} {booster_delay_unit.upper()} AGO\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:192: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", - " out2 = out2.rename(columns={0:\"overall\"}).drop([\"level_0\"],1)\n", - "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:412: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", - " out = out.transpose().append(date_reached).transpose().drop(\"weeks_to_target\",1)\n", - "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:422: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", - " out2 = out2.loc[out2[reference_column_name]==latest_date].reset_index().set_index(reference_column_name).drop([\"index\"], 1).transpose()\n", - "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:440: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", - " out3 = out3.drop([\"Increase in uptake (%)\"],1)\n" - ] }, { "data": { @@ -41049,7 +41412,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose 14weeks ago) among **80+** population up to 2021-09-08" + "## COVID vaccination rollout (third dose) among **30-39** population up to 02 Feb 2022" ], "text/plain": [ "" @@ -41115,326 +41478,11751 @@ " \n", " overall\n", " overall\n", - " 1232\n", - " 57.5\n", - " 2142\n", - " 55.9\n", - " 1.6\n", - " 28-Jan\n", + " 707\n", + " 5.5\n", + " 12957\n", + " 5.1\n", + " 0.4\n", + " unknown\n", " \n", " \n", " sex\n", " F\n", - " 651\n", - " 57.8\n", - " 1127\n", - " 55.9\n", - " 1.9\n", - " 04-Jan\n", + " 371\n", + " 5.5\n", + " 6727\n", + " 5.3\n", + " 0.2\n", + " unknown\n", " \n", " \n", " M\n", - " 581\n", - " 57.2\n", - " 1015\n", - " 55.9\n", - " 1.3\n", + " 336\n", + " 5.4\n", + " 6230\n", + " 5.1\n", + " 0.3\n", " unknown\n", " \n", " \n", - " ageband_5yr\n", - " 0\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", - " 0.0\n", + " ethnicity_6_groups\n", + " Black\n", + " 126\n", + " 5.6\n", + " 2233\n", + " 5.0\n", + " 0.6\n", " unknown\n", " \n", " \n", - " 0-15\n", - " 63\n", - " 56.2\n", - " 112\n", - " 56.2\n", - " 0.0\n", + " Mixed\n", + " 133\n", + " 6.0\n", + " 2205\n", + " 5.7\n", + " 0.3\n", " unknown\n", " \n", " \n", - " 16-17\n", - " 70\n", - " 50.0\n", - " 140\n", - " 50.0\n", + " Other\n", + " 98\n", + " 4.6\n", + " 2128\n", + " 4.6\n", " 0.0\n", " unknown\n", " \n", " \n", - " 18-29\n", - " 84\n", - " 63.2\n", - " 133\n", - " 57.9\n", - " 5.3\n", - " 13-Oct\n", - " \n", - " \n", - " 30-34\n", - " 77\n", - " 55.0\n", - " 140\n", - " 50.0\n", + " South Asian\n", + " 112\n", + " 5.0\n", + " 2254\n", " 5.0\n", - " 27-Oct\n", - " \n", - " \n", - " 35-39\n", - " 91\n", - " 61.9\n", - " 147\n", - " 61.9\n", " 0.0\n", " unknown\n", " \n", " \n", - " 40-44\n", - " 84\n", - " 57.1\n", - " 147\n", - " 57.1\n", - " 0.0\n", + " Unknown\n", + " 112\n", + " 5.8\n", + " 1918\n", + " 5.5\n", + " 0.3\n", " unknown\n", " \n", " \n", - " 45-49\n", - " 70\n", - " 52.6\n", - " 133\n", - " 47.4\n", - " 5.2\n", - " 28-Oct\n", + " White\n", + " 126\n", + " 5.7\n", + " 2226\n", + " 5.3\n", + " 0.4\n", + " unknown\n", " \n", " \n", - " 50-54\n", - " 91\n", - " 59.1\n", - " 154\n", - " 54.5\n", - " 4.6\n", - " 25-Oct\n", + " ethnicity_16_groups\n", + " African\n", + " 49\n", + " 7.0\n", + " 700\n", + " 6.0\n", + " 1.0\n", + " unknown\n", " \n", " \n", - " 55-59\n", - " 84\n", - " 54.5\n", - " 154\n", - " 54.5\n", + " Bangladeshi or British Bangladeshi\n", + " 35\n", + " 5.1\n", + " 686\n", + " 5.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " 60-64\n", - " 63\n", - " 50.0\n", - " 126\n", - " 50.0\n", + " Caribbean\n", + " 35\n", + " 5.3\n", + " 658\n", + " 5.3\n", " 0.0\n", " unknown\n", " \n", " \n", - " 65-69\n", - " 84\n", - " 60.0\n", - " 140\n", - " 60.0\n", + " Chinese\n", + " 42\n", + " 6.0\n", + " 700\n", + " 6.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " 70-74\n", - " 84\n", - " 60.0\n", - " 140\n", - " 60.0\n", + " Other\n", + " 28\n", + " 4.1\n", + " 679\n", + " 4.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " 75-79\n", - " 77\n", - " 57.9\n", - " 133\n", - " 57.9\n", + " Other Asian\n", + " 42\n", + " 5.9\n", + " 714\n", + " 5.9\n", " 0.0\n", " unknown\n", " \n", " \n", - " 80-84\n", - " 91\n", - " 65.0\n", - " 140\n", - " 65.0\n", + " British or Mixed British\n", + " 49\n", + " 6.9\n", + " 714\n", + " 6.9\n", " 0.0\n", " unknown\n", " \n", " \n", - " 85-89\n", - " 91\n", - " 59.1\n", - " 154\n", - " 54.5\n", - " 4.6\n", - " 25-Oct\n", + " Indian or British Indian\n", + " 35\n", + " 5.1\n", + " 686\n", + " 4.1\n", + " 1.0\n", + " unknown\n", " \n", " \n", - " 90+\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " Irish\n", + " 35\n", + " 5.4\n", + " 644\n", + " 5.4\n", " 0.0\n", " unknown\n", " \n", " \n", - " ethnicity_6_groups\n", - " Black\n", - " 210\n", - " 58.8\n", - " 357\n", - " 56.9\n", - " 1.9\n", - " 31-Dec\n", - " \n", - " \n", - " Mixed\n", - " 203\n", - " 58.0\n", - " 350\n", - " 56.0\n", - " 2.0\n", - " 29-Dec\n", - " \n", - " \n", - " Other\n", - " 175\n", - " 52.1\n", - " 336\n", - " 52.1\n", + " Other Black\n", + " 42\n", + " 6.1\n", + " 693\n", + " 6.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " South Asian\n", - " 224\n", - " 61.5\n", - " 364\n", - " 59.6\n", - " 1.9\n", - " 22-Dec\n", - " \n", - " \n", - " Unknown\n", - " 189\n", - " 55.1\n", - " 343\n", - " 53.1\n", - " 2.0\n", - " 08-Jan\n", - " \n", - " \n", - " White\n", - " 231\n", - " 58.9\n", - " 392\n", - " 58.9\n", + " Other White\n", + " 35\n", + " 5.3\n", + " 658\n", + " 5.3\n", " 0.0\n", " unknown\n", " \n", " \n", - " ethnicity_16_groups\n", - " African\n", - " 63\n", - " 60.0\n", - " 105\n", - " 53.3\n", - " 6.7\n", - " 09-Oct\n", + " Other mixed\n", + " 35\n", + " 5.1\n", + " 693\n", + " 4.0\n", + " 1.1\n", + " unknown\n", " \n", " \n", - " Bangladeshi or British Bangladeshi\n", - " 56\n", - " 47.1\n", - " 119\n", - " 47.1\n", - " 0.0\n", + " Pakistani or British Pakistani\n", + " 35\n", + " 4.8\n", + " 735\n", + " 3.8\n", + " 1.0\n", " unknown\n", " \n", " \n", - " Caribbean\n", - " 56\n", - " 57.1\n", + " Unknown\n", " 98\n", - " 57.1\n", + " 5.1\n", + " 1911\n", + " 5.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " Chinese\n", - " 63\n", - " 60.0\n", - " 105\n", - " 60.0\n", + " White + Asian\n", + " 35\n", + " 5.1\n", + " 693\n", + " 5.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " Other\n", - " 70\n", - " 62.5\n", - " 112\n", - " 56.2\n", - " 6.3\n", - " 08-Oct\n", - " \n", - " \n", - " Other Asian\n", - " 63\n", - " 56.2\n", - " 112\n", - " 56.2\n", + " White + Black African\n", + " 42\n", + " 5.8\n", + " 721\n", + " 5.8\n", " 0.0\n", " unknown\n", " \n", " \n", - " British or Mixed British\n", - " 77\n", - " 57.9\n", - " 133\n", - " 52.6\n", + " White + Black Caribbean\n", + " 35\n", + " 5.3\n", + " 665\n", " 5.3\n", - " 20-Oct\n", - " \n", - " \n", - " Indian or British Indian\n", - " 70\n", - " 66.7\n", - " 105\n", - " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " Irish\n", - " 63\n", - " 52.9\n", - " 119\n", - " 52.9\n", - " 0.0\n", + " imd_categories\n", + " 1 Most deprived\n", + " 140\n", + " 5.7\n", + " 2471\n", + " 5.4\n", + " 0.3\n", " unknown\n", " \n", " \n", - " Other Black\n", - " 49\n", + " 2\n", + " 140\n", + " 5.6\n", + " 2478\n", + " 5.4\n", + " 0.2\n", + " unknown\n", + " \n", + " \n", + " 3\n", + " 119\n", + " 4.9\n", + " 2450\n", + " 4.6\n", + " 0.3\n", + " unknown\n", + " \n", + " \n", + " 4\n", + " 154\n", + " 6.3\n", + " 2450\n", + " 6.0\n", + " 0.3\n", + " unknown\n", + " \n", + " \n", + " 5 Least deprived\n", + " 133\n", + " 5.5\n", + " 2436\n", + " 5.2\n", + " 0.3\n", + " unknown\n", + " \n", + " \n", + " Unknown\n", + " 28\n", + " 4.2\n", + " 672\n", + " 4.2\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + "\n", + "" + ], + "text/plain": [ + " vaccinated percent \\\n", + "category group \n", + "overall overall 707 5.5 \n", + "sex F 371 5.5 \n", + " M 336 5.4 \n", + "ethnicity_6_groups Black 126 5.6 \n", + " Mixed 133 6.0 \n", + " Other 98 4.6 \n", + " South Asian 112 5.0 \n", + " Unknown 112 5.8 \n", + " White 126 5.7 \n", + "ethnicity_16_groups African 49 7.0 \n", + " Bangladeshi or British Bangladeshi 35 5.1 \n", + " Caribbean 35 5.3 \n", + " Chinese 42 6.0 \n", + " Other 28 4.1 \n", + " Other Asian 42 5.9 \n", + " British or Mixed British 49 6.9 \n", + " Indian or British Indian 35 5.1 \n", + " Irish 35 5.4 \n", + " Other Black 42 6.1 \n", + " Other White 35 5.3 \n", + " Other mixed 35 5.1 \n", + " Pakistani or British Pakistani 35 4.8 \n", + " Unknown 98 5.1 \n", + " White + Asian 35 5.1 \n", + " White + Black African 42 5.8 \n", + " White + Black Caribbean 35 5.3 \n", + "imd_categories 1 Most deprived 140 5.7 \n", + " 2 140 5.6 \n", + " 3 119 4.9 \n", + " 4 154 6.3 \n", + " 5 Least deprived 133 5.5 \n", + " Unknown 28 4.2 \n", + "\n", + " total \\\n", + "category group \n", + "overall overall 12957 \n", + "sex F 6727 \n", + " M 6230 \n", + "ethnicity_6_groups Black 2233 \n", + " Mixed 2205 \n", + " Other 2128 \n", + " South Asian 2254 \n", + " Unknown 1918 \n", + " White 2226 \n", + "ethnicity_16_groups African 700 \n", + " Bangladeshi or British Bangladeshi 686 \n", + " Caribbean 658 \n", + " Chinese 700 \n", + " Other 679 \n", + " Other Asian 714 \n", + " British or Mixed British 714 \n", + " Indian or British Indian 686 \n", + " Irish 644 \n", + " Other Black 693 \n", + " Other White 658 \n", + " Other mixed 693 \n", + " Pakistani or British Pakistani 735 \n", + " Unknown 1911 \n", + " White + Asian 693 \n", + " White + Black African 721 \n", + " White + Black Caribbean 665 \n", + "imd_categories 1 Most deprived 2471 \n", + " 2 2478 \n", + " 3 2450 \n", + " 4 2450 \n", + " 5 Least deprived 2436 \n", + " Unknown 672 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 5.1 \n", + "sex F 5.3 \n", + " M 5.1 \n", + "ethnicity_6_groups Black 5.0 \n", + " Mixed 5.7 \n", + " Other 4.6 \n", + " South Asian 5.0 \n", + " Unknown 5.5 \n", + " White 5.3 \n", + "ethnicity_16_groups African 6.0 \n", + " Bangladeshi or British Bangladeshi 5.1 \n", + " Caribbean 5.3 \n", + " Chinese 6.0 \n", + " Other 4.1 \n", + " Other Asian 5.9 \n", + " British or Mixed British 6.9 \n", + " Indian or British Indian 4.1 \n", + " Irish 5.4 \n", + " Other Black 6.1 \n", + " Other White 5.3 \n", + " Other mixed 4.0 \n", + " Pakistani or British Pakistani 3.8 \n", + " Unknown 5.1 \n", + " White + Asian 5.1 \n", + " White + Black African 5.8 \n", + " White + Black Caribbean 5.3 \n", + "imd_categories 1 Most deprived 5.4 \n", + " 2 5.4 \n", + " 3 4.6 \n", + " 4 6.0 \n", + " 5 Least deprived 5.2 \n", + " Unknown 4.2 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 0.4 \n", + "sex F 0.2 \n", + " M 0.3 \n", + "ethnicity_6_groups Black 0.6 \n", + " Mixed 0.3 \n", + " Other 0.0 \n", + " South Asian 0.0 \n", + " Unknown 0.3 \n", + " White 0.4 \n", + "ethnicity_16_groups African 1.0 \n", + " Bangladeshi or British Bangladeshi 0.0 \n", + " Caribbean 0.0 \n", + " Chinese 0.0 \n", + " Other 0.0 \n", + " Other Asian 0.0 \n", + " British or Mixed British 0.0 \n", + " Indian or British Indian 1.0 \n", + " Irish 0.0 \n", + " Other Black 0.0 \n", + " Other White 0.0 \n", + " Other mixed 1.1 \n", + " Pakistani or British Pakistani 1.0 \n", + " Unknown 0.0 \n", + " White + Asian 0.0 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 0.0 \n", + "imd_categories 1 Most deprived 0.3 \n", + " 2 0.2 \n", + " 3 0.3 \n", + " 4 0.3 \n", + " 5 Least deprived 0.3 \n", + " Unknown 0.0 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall unknown \n", + "sex F unknown \n", + " M unknown \n", + "ethnicity_6_groups Black unknown \n", + " Mixed unknown \n", + " Other unknown \n", + " South Asian unknown \n", + " Unknown unknown \n", + " White unknown \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi unknown \n", + " Caribbean unknown \n", + " Chinese unknown \n", + " Other unknown \n", + " Other Asian unknown \n", + " British or Mixed British unknown \n", + " Indian or British Indian unknown \n", + " Irish unknown \n", + " Other Black unknown \n", + " Other White unknown \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani unknown \n", + " Unknown unknown \n", + " White + Asian unknown \n", + " White + Black African unknown \n", + " White + Black Caribbean unknown \n", + "imd_categories 1 Most deprived unknown \n", + " 2 unknown \n", + " 3 unknown \n", + " 4 unknown \n", + " 5 Least deprived unknown \n", + " Unknown unknown " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:644: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out_csv = out_csv.drop(\"Date projected to reach 90%\",1)\n" + ] + }, + { + "data": { + "text/markdown": [ + "## " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## COVID vaccination rollout (third dose) among **18-29** population up to 02 Feb 2022" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- 'Date projected to reach 90%' being 'unknown' indicates projection of >6mo (likely insufficient information)\n", + "- Patient counts rounded to the nearest 7" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall9246.2149665.80.4unknown
sexF4555.976865.60.3unknown
M4696.472876.10.3unknown
ethnicity_6_groupsBlack1616.325556.00.3unknown
Mixed1616.225766.00.2unknown
Other1686.625626.00.6unknown
South Asian1405.625135.30.3unknown
Unknown1336.022335.60.4unknown
White1546.125205.80.3unknown
ethnicity_16_groupsAfrican567.17847.10.0unknown
Bangladeshi or British Bangladeshi354.38054.30.0unknown
Caribbean425.47845.40.0unknown
Chinese637.88127.80.0unknown
Other496.17985.30.8unknown
Other Asian425.47845.40.0unknown
British or Mixed British425.57634.60.9unknown
Indian or British Indian495.98265.90.0unknown
Irish638.27707.30.9unknown
Other Black637.97987.90.0unknown
Other White425.37915.30.0unknown
Other mixed567.17917.10.0unknown
Pakistani or British Pakistani496.47635.50.9unknown
Unknown1195.222754.90.3unknown
White + Asian495.98265.10.8unknown
White + Black African567.08057.00.0unknown
White + Black Caribbean425.37914.40.9unknown
imd_categories1 Most deprived1896.429406.20.2unknown
21756.228355.70.5unknown
31756.228425.90.3unknown
41685.928565.60.3unknown
5 Least deprived1615.827795.30.5unknown
Unknown496.87216.80.0unknown
\n", + "
" + ], + "text/plain": [ + " vaccinated percent \\\n", + "category group \n", + "overall overall 924 6.2 \n", + "sex F 455 5.9 \n", + " M 469 6.4 \n", + "ethnicity_6_groups Black 161 6.3 \n", + " Mixed 161 6.2 \n", + " Other 168 6.6 \n", + " South Asian 140 5.6 \n", + " Unknown 133 6.0 \n", + " White 154 6.1 \n", + "ethnicity_16_groups African 56 7.1 \n", + " Bangladeshi or British Bangladeshi 35 4.3 \n", + " Caribbean 42 5.4 \n", + " Chinese 63 7.8 \n", + " Other 49 6.1 \n", + " Other Asian 42 5.4 \n", + " British or Mixed British 42 5.5 \n", + " Indian or British Indian 49 5.9 \n", + " Irish 63 8.2 \n", + " Other Black 63 7.9 \n", + " Other White 42 5.3 \n", + " Other mixed 56 7.1 \n", + " Pakistani or British Pakistani 49 6.4 \n", + " Unknown 119 5.2 \n", + " White + Asian 49 5.9 \n", + " White + Black African 56 7.0 \n", + " White + Black Caribbean 42 5.3 \n", + "imd_categories 1 Most deprived 189 6.4 \n", + " 2 175 6.2 \n", + " 3 175 6.2 \n", + " 4 168 5.9 \n", + " 5 Least deprived 161 5.8 \n", + " Unknown 49 6.8 \n", + "\n", + " total \\\n", + "category group \n", + "overall overall 14966 \n", + "sex F 7686 \n", + " M 7287 \n", + "ethnicity_6_groups Black 2555 \n", + " Mixed 2576 \n", + " Other 2562 \n", + " South Asian 2513 \n", + " Unknown 2233 \n", + " White 2520 \n", + "ethnicity_16_groups African 784 \n", + " Bangladeshi or British Bangladeshi 805 \n", + " Caribbean 784 \n", + " Chinese 812 \n", + " Other 798 \n", + " Other Asian 784 \n", + " British or Mixed British 763 \n", + " Indian or British Indian 826 \n", + " Irish 770 \n", + " Other Black 798 \n", + " Other White 791 \n", + " Other mixed 791 \n", + " Pakistani or British Pakistani 763 \n", + " Unknown 2275 \n", + " White + Asian 826 \n", + " White + Black African 805 \n", + " White + Black Caribbean 791 \n", + "imd_categories 1 Most deprived 2940 \n", + " 2 2835 \n", + " 3 2842 \n", + " 4 2856 \n", + " 5 Least deprived 2779 \n", + " Unknown 721 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 5.8 \n", + "sex F 5.6 \n", + " M 6.1 \n", + "ethnicity_6_groups Black 6.0 \n", + " Mixed 6.0 \n", + " Other 6.0 \n", + " South Asian 5.3 \n", + " Unknown 5.6 \n", + " White 5.8 \n", + "ethnicity_16_groups African 7.1 \n", + " Bangladeshi or British Bangladeshi 4.3 \n", + " Caribbean 5.4 \n", + " Chinese 7.8 \n", + " Other 5.3 \n", + " Other Asian 5.4 \n", + " British or Mixed British 4.6 \n", + " Indian or British Indian 5.9 \n", + " Irish 7.3 \n", + " Other Black 7.9 \n", + " Other White 5.3 \n", + " Other mixed 7.1 \n", + " Pakistani or British Pakistani 5.5 \n", + " Unknown 4.9 \n", + " White + Asian 5.1 \n", + " White + Black African 7.0 \n", + " White + Black Caribbean 4.4 \n", + "imd_categories 1 Most deprived 6.2 \n", + " 2 5.7 \n", + " 3 5.9 \n", + " 4 5.6 \n", + " 5 Least deprived 5.3 \n", + " Unknown 6.8 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 0.4 \n", + "sex F 0.3 \n", + " M 0.3 \n", + "ethnicity_6_groups Black 0.3 \n", + " Mixed 0.2 \n", + " Other 0.6 \n", + " South Asian 0.3 \n", + " Unknown 0.4 \n", + " White 0.3 \n", + "ethnicity_16_groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 0.0 \n", + " Caribbean 0.0 \n", + " Chinese 0.0 \n", + " Other 0.8 \n", + " Other Asian 0.0 \n", + " British or Mixed British 0.9 \n", + " Indian or British Indian 0.0 \n", + " Irish 0.9 \n", + " Other Black 0.0 \n", + " Other White 0.0 \n", + " Other mixed 0.0 \n", + " Pakistani or British Pakistani 0.9 \n", + " Unknown 0.3 \n", + " White + Asian 0.8 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 0.9 \n", + "imd_categories 1 Most deprived 0.2 \n", + " 2 0.5 \n", + " 3 0.3 \n", + " 4 0.3 \n", + " 5 Least deprived 0.5 \n", + " Unknown 0.0 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall unknown \n", + "sex F unknown \n", + " M unknown \n", + "ethnicity_6_groups Black unknown \n", + " Mixed unknown \n", + " Other unknown \n", + " South Asian unknown \n", + " Unknown unknown \n", + " White unknown \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi unknown \n", + " Caribbean unknown \n", + " Chinese unknown \n", + " Other unknown \n", + " Other Asian unknown \n", + " British or Mixed British unknown \n", + " Indian or British Indian unknown \n", + " Irish unknown \n", + " Other Black unknown \n", + " Other White unknown \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani unknown \n", + " Unknown unknown \n", + " White + Asian unknown \n", + " White + Black African unknown \n", + " White + Black Caribbean unknown \n", + "imd_categories 1 Most deprived unknown \n", + " 2 unknown \n", + " 3 unknown \n", + " 4 unknown \n", + " 5 Least deprived unknown \n", + " Unknown unknown " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:644: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out_csv = out_csv.drop(\"Date projected to reach 90%\",1)\n" + ] + } + ], + "source": [ + "\n", + "\n", + "# summarise third doses to date (after filtering above)\n", + "\n", + "# Include 18+ age groups plus priority groups (50+/CEV/Care home etc) only\n", + "population_subgroups_third = {key: value for key, value in population_subgroups.items() if 0 < value < 13}\n", + "\n", + "df_dict_cum_third_dose = cumulative_sums(df_t, groups_of_interest=population_subgroups_third, features_dict=features_dict,\n", + " latest_date=latest_date, reference_column_name=\"covid_vacc_third_dose_date\")\n", + "\n", + "third_dose_summarised_data_dict = summarise_data_by_group(\n", + " df_dict_cum_third_dose, latest_date=latest_date, groups=population_subgroups_third.keys())\n", + "\n", + "create_detailed_summary_uptake(third_dose_summarised_data_dict, formatted_latest_date,\n", + " groups=population_subgroups_third.keys(),\n", + " savepath=savepath, vaccine_type=\"third_dose\")" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "lines_to_next_cell": 2 + }, + "outputs": [ + { + "data": { + "text/markdown": [ + "## For comparison look at second dose coverate UP TO 14 WEEKS AGO" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "\n", + "display(Markdown(f\"## For comparison look at second dose coverate UP TO {booster_delay_number} {booster_delay_unit.upper()} AGO\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "lines_to_next_cell": 2 + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:192: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out2 = out2.rename(columns={0:\"overall\"}).drop([\"level_0\"],1)\n", + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:412: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out = out.transpose().append(date_reached).transpose().drop(\"weeks_to_target\",1)\n", + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:422: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out2 = out2.loc[out2[reference_column_name]==latest_date].reset_index().set_index(reference_column_name).drop([\"index\"], 1).transpose()\n", + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:440: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out3 = out3.drop([\"Increase in uptake (%)\"],1)\n" + ] + }, + { + "data": { + "text/markdown": [ + "## " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## COVID vaccination rollout (second dose 14w ago) among **80+** population up to 2021-10-27" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- 'Date projected to reach 90%' being 'unknown' indicates projection of >6mo (likely insufficient information)\n", + "- Patient counts rounded to the nearest 7" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall252059.7422158.01.728-Feb
sexF129559.5217758.51.0unknown
M121859.6204457.91.701-Mar
ageband_5yr04970.07060.010.010-Nov
0-1514054.125954.10.0unknown
16-1715462.924562.90.0unknown
18-2915457.926655.32.621-Jan
30-3416159.027359.00.0unknown
35-3917565.826663.22.631-Dec
40-4416159.027356.42.618-Jan
45-4917562.528062.50.0unknown
50-5415459.525956.82.714-Jan
55-5917558.130158.10.0unknown
60-6414755.326655.30.0unknown
65-6917562.528060.02.512-Jan
70-7417559.529457.12.423-Jan
75-7916860.028057.52.519-Jan
80-8416159.027356.42.618-Jan
85-8916857.129457.10.0unknown
90+2160.03560.00.0unknown
ethnicity_6_groupsBlack46963.873561.91.931-Jan
Mixed40658.070055.03.009-Jan
Other44861.572859.61.909-Feb
South Asian42056.174955.11.0unknown
Unknown36459.860958.61.2unknown
White42058.871457.81.0unknown
ethnicity_16_groupsAfrican11251.621751.60.0unknown
Bangladeshi or British Bangladeshi12660.021060.00.0unknown
Caribbean13361.321758.13.228-Dec
Chinese14064.521764.50.0unknown
Other14761.823858.83.031-Dec
Other Asian13363.321060.03.322-Dec
British or Mixed British12658.121754.83.302-Jan
Indian or British Indian14062.522459.43.128-Dec
Irish14060.623157.63.003-Jan
Other Black13361.321758.13.228-Dec
Other White14058.823858.80.0unknown
Other mixed11255.220355.20.0unknown
Pakistani or British Pakistani14062.522459.43.128-Dec
Unknown41361.567259.42.130-Jan
White + Asian12656.222456.20.0unknown
White + Black African11253.321053.30.0unknown
White + Black Caribbean14758.325258.30.0unknown
imd_categories1 Most deprived49761.780559.12.611-Jan
245556.580555.70.8unknown
346960.477759.50.9unknown
447658.181957.30.8unknown
5 Least deprived49761.281259.51.722-Feb
Unknown11956.721056.70.0unknown
bmi30+77760.0129558.41.607-Mar
under 30174359.6292657.91.701-Mar
houseboundno249259.6417958.11.517-Mar
yes2866.74250.016.705-Nov
chronic_cardiac_diseaseno249259.5418658.01.518-Mar
yes2880.03580.00.0unknown
current_copdno249259.6417958.11.517-Mar
yes2857.14957.10.0unknown
dmardsno248559.6417258.11.517-Mar
yes2857.14957.10.0unknown
dementiano249259.6417958.11.517-Mar
yes2866.74266.70.0unknown
psychosis_schiz_bipolarno249259.6417958.11.517-Mar
yes2866.74266.70.0unknown
LDno245059.3413057.81.519-Mar
yes6364.39864.30.0unknown
ssrino249259.6417958.11.517-Mar
yes2857.14957.10.0unknown
chemo_or_radiono249259.5418658.01.518-Mar
yes2866.74266.70.0unknown
lung_cancerno249959.6419358.11.517-Mar
yes1440.03540.00.0unknown
cancer_excl_lung_and_haemno249959.6419358.11.517-Mar
yes2160.03560.00.0unknown
haematological_cancerno248559.5417958.01.518-Mar
yes2866.74266.70.0unknown
ckdno202359.6339558.41.2unknown
yes49059.382657.61.702-Mar
\n", + "
" + ], + "text/plain": [ + " vaccinated \\\n", + "category group \n", + "overall overall 2520 \n", + "sex F 1295 \n", + " M 1218 \n", + "ageband_5yr 0 49 \n", + " 0-15 140 \n", + " 16-17 154 \n", + " 18-29 154 \n", + " 30-34 161 \n", + " 35-39 175 \n", + " 40-44 161 \n", + " 45-49 175 \n", + " 50-54 154 \n", + " 55-59 175 \n", + " 60-64 147 \n", + " 65-69 175 \n", + " 70-74 175 \n", + " 75-79 168 \n", + " 80-84 161 \n", + " 85-89 168 \n", + " 90+ 21 \n", + "ethnicity_6_groups Black 469 \n", + " Mixed 406 \n", + " Other 448 \n", + " South Asian 420 \n", + " Unknown 364 \n", + " White 420 \n", + "ethnicity_16_groups African 112 \n", + " Bangladeshi or British Bangladeshi 126 \n", + " Caribbean 133 \n", + " Chinese 140 \n", + " Other 147 \n", + " Other Asian 133 \n", + " British or Mixed British 126 \n", + " Indian or British Indian 140 \n", + " Irish 140 \n", + " Other Black 133 \n", + " Other White 140 \n", + " Other mixed 112 \n", + " Pakistani or British Pakistani 140 \n", + " Unknown 413 \n", + " White + Asian 126 \n", + " White + Black African 112 \n", + " White + Black Caribbean 147 \n", + "imd_categories 1 Most deprived 497 \n", + " 2 455 \n", + " 3 469 \n", + " 4 476 \n", + " 5 Least deprived 497 \n", + " Unknown 119 \n", + "bmi 30+ 777 \n", + " under 30 1743 \n", + "housebound no 2492 \n", + " yes 28 \n", + "chronic_cardiac_disease no 2492 \n", + " yes 28 \n", + "current_copd no 2492 \n", + " yes 28 \n", + "dmards no 2485 \n", + " yes 28 \n", + "dementia no 2492 \n", + " yes 28 \n", + "psychosis_schiz_bipolar no 2492 \n", + " yes 28 \n", + "LD no 2450 \n", + " yes 63 \n", + "ssri no 2492 \n", + " yes 28 \n", + "chemo_or_radio no 2492 \n", + " yes 28 \n", + "lung_cancer no 2499 \n", + " yes 14 \n", + "cancer_excl_lung_and_haem no 2499 \n", + " yes 21 \n", + "haematological_cancer no 2485 \n", + " yes 28 \n", + "ckd no 2023 \n", + " yes 490 \n", + "\n", + " percent total \\\n", + "category group \n", + "overall overall 59.7 4221 \n", + "sex F 59.5 2177 \n", + " M 59.6 2044 \n", + "ageband_5yr 0 70.0 70 \n", + " 0-15 54.1 259 \n", + " 16-17 62.9 245 \n", + " 18-29 57.9 266 \n", + " 30-34 59.0 273 \n", + " 35-39 65.8 266 \n", + " 40-44 59.0 273 \n", + " 45-49 62.5 280 \n", + " 50-54 59.5 259 \n", + " 55-59 58.1 301 \n", + " 60-64 55.3 266 \n", + " 65-69 62.5 280 \n", + " 70-74 59.5 294 \n", + " 75-79 60.0 280 \n", + " 80-84 59.0 273 \n", + " 85-89 57.1 294 \n", + " 90+ 60.0 35 \n", + "ethnicity_6_groups Black 63.8 735 \n", + " Mixed 58.0 700 \n", + " Other 61.5 728 \n", + " South Asian 56.1 749 \n", + " Unknown 59.8 609 \n", + " White 58.8 714 \n", + "ethnicity_16_groups African 51.6 217 \n", + " Bangladeshi or British Bangladeshi 60.0 210 \n", + " Caribbean 61.3 217 \n", + " Chinese 64.5 217 \n", + " Other 61.8 238 \n", + " Other Asian 63.3 210 \n", + " British or Mixed British 58.1 217 \n", + " Indian or British Indian 62.5 224 \n", + " Irish 60.6 231 \n", + " Other Black 61.3 217 \n", + " Other White 58.8 238 \n", + " Other mixed 55.2 203 \n", + " Pakistani or British Pakistani 62.5 224 \n", + " Unknown 61.5 672 \n", + " White + Asian 56.2 224 \n", + " White + Black African 53.3 210 \n", + " White + Black Caribbean 58.3 252 \n", + "imd_categories 1 Most deprived 61.7 805 \n", + " 2 56.5 805 \n", + " 3 60.4 777 \n", + " 4 58.1 819 \n", + " 5 Least deprived 61.2 812 \n", + " Unknown 56.7 210 \n", + "bmi 30+ 60.0 1295 \n", + " under 30 59.6 2926 \n", + "housebound no 59.6 4179 \n", + " yes 66.7 42 \n", + "chronic_cardiac_disease no 59.5 4186 \n", + " yes 80.0 35 \n", + "current_copd no 59.6 4179 \n", + " yes 57.1 49 \n", + "dmards no 59.6 4172 \n", + " yes 57.1 49 \n", + "dementia no 59.6 4179 \n", + " yes 66.7 42 \n", + "psychosis_schiz_bipolar no 59.6 4179 \n", + " yes 66.7 42 \n", + "LD no 59.3 4130 \n", + " yes 64.3 98 \n", + "ssri no 59.6 4179 \n", + " yes 57.1 49 \n", + "chemo_or_radio no 59.5 4186 \n", + " yes 66.7 42 \n", + "lung_cancer no 59.6 4193 \n", + " yes 40.0 35 \n", + "cancer_excl_lung_and_haem no 59.6 4193 \n", + " yes 60.0 35 \n", + "haematological_cancer no 59.5 4179 \n", + " yes 66.7 42 \n", + "ckd no 59.6 3395 \n", + " yes 59.3 826 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 58.0 \n", + "sex F 58.5 \n", + " M 57.9 \n", + "ageband_5yr 0 60.0 \n", + " 0-15 54.1 \n", + " 16-17 62.9 \n", + " 18-29 55.3 \n", + " 30-34 59.0 \n", + " 35-39 63.2 \n", + " 40-44 56.4 \n", + " 45-49 62.5 \n", + " 50-54 56.8 \n", + " 55-59 58.1 \n", + " 60-64 55.3 \n", + " 65-69 60.0 \n", + " 70-74 57.1 \n", + " 75-79 57.5 \n", + " 80-84 56.4 \n", + " 85-89 57.1 \n", + " 90+ 60.0 \n", + "ethnicity_6_groups Black 61.9 \n", + " Mixed 55.0 \n", + " Other 59.6 \n", + " South Asian 55.1 \n", + " Unknown 58.6 \n", + " White 57.8 \n", + "ethnicity_16_groups African 51.6 \n", + " Bangladeshi or British Bangladeshi 60.0 \n", + " Caribbean 58.1 \n", + " Chinese 64.5 \n", + " Other 58.8 \n", + " Other Asian 60.0 \n", + " British or Mixed British 54.8 \n", + " Indian or British Indian 59.4 \n", + " Irish 57.6 \n", + " Other Black 58.1 \n", + " Other White 58.8 \n", + " Other mixed 55.2 \n", + " Pakistani or British Pakistani 59.4 \n", + " Unknown 59.4 \n", + " White + Asian 56.2 \n", + " White + Black African 53.3 \n", + " White + Black Caribbean 58.3 \n", + "imd_categories 1 Most deprived 59.1 \n", + " 2 55.7 \n", + " 3 59.5 \n", + " 4 57.3 \n", + " 5 Least deprived 59.5 \n", + " Unknown 56.7 \n", + "bmi 30+ 58.4 \n", + " under 30 57.9 \n", + "housebound no 58.1 \n", + " yes 50.0 \n", + "chronic_cardiac_disease no 58.0 \n", + " yes 80.0 \n", + "current_copd no 58.1 \n", + " yes 57.1 \n", + "dmards no 58.1 \n", + " yes 57.1 \n", + "dementia no 58.1 \n", + " yes 66.7 \n", + "psychosis_schiz_bipolar no 58.1 \n", + " yes 66.7 \n", + "LD no 57.8 \n", + " yes 64.3 \n", + "ssri no 58.1 \n", + " yes 57.1 \n", + "chemo_or_radio no 58.0 \n", + " yes 66.7 \n", + "lung_cancer no 58.1 \n", + " yes 40.0 \n", + "cancer_excl_lung_and_haem no 58.1 \n", + " yes 60.0 \n", + "haematological_cancer no 58.0 \n", + " yes 66.7 \n", + "ckd no 58.4 \n", + " yes 57.6 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.7 \n", + "sex F 1.0 \n", + " M 1.7 \n", + "ageband_5yr 0 10.0 \n", + " 0-15 0.0 \n", + " 16-17 0.0 \n", + " 18-29 2.6 \n", + " 30-34 0.0 \n", + " 35-39 2.6 \n", + " 40-44 2.6 \n", + " 45-49 0.0 \n", + " 50-54 2.7 \n", + " 55-59 0.0 \n", + " 60-64 0.0 \n", + " 65-69 2.5 \n", + " 70-74 2.4 \n", + " 75-79 2.5 \n", + " 80-84 2.6 \n", + " 85-89 0.0 \n", + " 90+ 0.0 \n", + "ethnicity_6_groups Black 1.9 \n", + " Mixed 3.0 \n", + " Other 1.9 \n", + " South Asian 1.0 \n", + " Unknown 1.2 \n", + " White 1.0 \n", + "ethnicity_16_groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 0.0 \n", + " Caribbean 3.2 \n", + " Chinese 0.0 \n", + " Other 3.0 \n", + " Other Asian 3.3 \n", + " British or Mixed British 3.3 \n", + " Indian or British Indian 3.1 \n", + " Irish 3.0 \n", + " Other Black 3.2 \n", + " Other White 0.0 \n", + " Other mixed 0.0 \n", + " Pakistani or British Pakistani 3.1 \n", + " Unknown 2.1 \n", + " White + Asian 0.0 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 0.0 \n", + "imd_categories 1 Most deprived 2.6 \n", + " 2 0.8 \n", + " 3 0.9 \n", + " 4 0.8 \n", + " 5 Least deprived 1.7 \n", + " Unknown 0.0 \n", + "bmi 30+ 1.6 \n", + " under 30 1.7 \n", + "housebound no 1.5 \n", + " yes 16.7 \n", + "chronic_cardiac_disease no 1.5 \n", + " yes 0.0 \n", + "current_copd no 1.5 \n", + " yes 0.0 \n", + "dmards no 1.5 \n", + " yes 0.0 \n", + "dementia no 1.5 \n", + " yes 0.0 \n", + "psychosis_schiz_bipolar no 1.5 \n", + " yes 0.0 \n", + "LD no 1.5 \n", + " yes 0.0 \n", + "ssri no 1.5 \n", + " yes 0.0 \n", + "chemo_or_radio no 1.5 \n", + " yes 0.0 \n", + "lung_cancer no 1.5 \n", + " yes 0.0 \n", + "cancer_excl_lung_and_haem no 1.5 \n", + " yes 0.0 \n", + "haematological_cancer no 1.5 \n", + " yes 0.0 \n", + "ckd no 1.2 \n", + " yes 1.7 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 28-Feb \n", + "sex F unknown \n", + " M 01-Mar \n", + "ageband_5yr 0 10-Nov \n", + " 0-15 unknown \n", + " 16-17 unknown \n", + " 18-29 21-Jan \n", + " 30-34 unknown \n", + " 35-39 31-Dec \n", + " 40-44 18-Jan \n", + " 45-49 unknown \n", + " 50-54 14-Jan \n", + " 55-59 unknown \n", + " 60-64 unknown \n", + " 65-69 12-Jan \n", + " 70-74 23-Jan \n", + " 75-79 19-Jan \n", + " 80-84 18-Jan \n", + " 85-89 unknown \n", + " 90+ unknown \n", + "ethnicity_6_groups Black 31-Jan \n", + " Mixed 09-Jan \n", + " Other 09-Feb \n", + " South Asian unknown \n", + " Unknown unknown \n", + " White unknown \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi unknown \n", + " Caribbean 28-Dec \n", + " Chinese unknown \n", + " Other 31-Dec \n", + " Other Asian 22-Dec \n", + " British or Mixed British 02-Jan \n", + " Indian or British Indian 28-Dec \n", + " Irish 03-Jan \n", + " Other Black 28-Dec \n", + " Other White unknown \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani 28-Dec \n", + " Unknown 30-Jan \n", + " White + Asian unknown \n", + " White + Black African unknown \n", + " White + Black Caribbean unknown \n", + "imd_categories 1 Most deprived 11-Jan \n", + " 2 unknown \n", + " 3 unknown \n", + " 4 unknown \n", + " 5 Least deprived 22-Feb \n", + " Unknown unknown \n", + "bmi 30+ 07-Mar \n", + " under 30 01-Mar \n", + "housebound no 17-Mar \n", + " yes 05-Nov \n", + "chronic_cardiac_disease no 18-Mar \n", + " yes unknown \n", + "current_copd no 17-Mar \n", + " yes unknown \n", + "dmards no 17-Mar \n", + " yes unknown \n", + "dementia no 17-Mar \n", + " yes unknown \n", + "psychosis_schiz_bipolar no 17-Mar \n", + " yes unknown \n", + "LD no 19-Mar \n", + " yes unknown \n", + "ssri no 17-Mar \n", + " yes unknown \n", + "chemo_or_radio no 18-Mar \n", + " yes unknown \n", + "lung_cancer no 17-Mar \n", + " yes unknown \n", + "cancer_excl_lung_and_haem no 17-Mar \n", + " yes unknown \n", + "haematological_cancer no 18-Mar \n", + " yes unknown \n", + "ckd no unknown \n", + " yes 02-Mar " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:644: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out_csv = out_csv.drop(\"Date projected to reach 90%\",1)\n" + ] + }, + { + "data": { + "text/markdown": [ + "## " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## COVID vaccination rollout (second dose 14w ago) among **70-79** population up to 2021-10-27" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- 'Date projected to reach 90%' being 'unknown' indicates projection of >6mo (likely insufficient information)\n", + "- Patient counts rounded to the nearest 7" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall406059.2686057.81.430-Mar
sexF210059.3354257.91.429-Mar
M196059.1331857.61.520-Mar
ageband_5yr04958.38458.30.0unknown
0-1525259.042759.00.0unknown
16-1727360.045556.93.102-Jan
18-2926661.343461.30.0unknown
30-3428059.746958.21.517-Mar
35-3928762.146260.61.506-Mar
40-4425258.143456.51.615-Mar
45-4925957.844856.21.616-Mar
50-5425959.743458.11.608-Mar
55-5925255.445553.81.627-Mar
60-6427360.944859.41.511-Mar
65-6926659.444857.81.609-Mar
70-7424556.543456.50.0unknown
75-7927360.045558.51.516-Mar
80-8426660.344158.71.605-Mar
85-8925957.844856.21.616-Mar
90+4958.38458.30.0unknown
ethnicity_6_groupsBlack65857.0115555.81.2unknown
Mixed72861.2119060.01.213-Apr
Other69358.9117657.11.824-Feb
South Asian73561.0120459.91.1unknown
Unknown58857.1102955.81.3unknown
White65159.2109958.01.2unknown
ethnicity_16_groupsAfrican22462.735760.81.904-Feb
Bangladeshi or British Bangladeshi18954.035052.02.002-Mar
Caribbean21758.537156.61.920-Feb
Chinese24567.336465.41.918-Jan
Other21056.637156.60.0unknown
Other Asian21759.636457.71.916-Feb
British or Mixed British22465.334363.32.021-Jan
Indian or British Indian21758.537158.50.0unknown
Irish21057.736455.81.923-Feb
Other Black21057.736455.81.923-Feb
Other White21057.736457.70.0unknown
Other mixed20358.035056.02.016-Feb
Pakistani or British Pakistani19659.632959.60.0unknown
Unknown58157.2101555.22.018-Feb
White + Asian23861.838560.01.813-Feb
White + Black African23860.739258.91.817-Feb
White + Black Caribbean23859.639957.91.701-Mar
imd_categories1 Most deprived77759.7130258.11.608-Mar
277757.8134456.21.616-Mar
374257.9128156.31.616-Mar
481261.7131660.11.627-Feb
5 Least deprived75659.0128158.50.5unknown
Unknown19659.632957.42.231-Jan
bmi30+122559.3206558.31.0unknown
under 30283559.2478857.71.519-Mar
houseboundno401859.2678357.91.310-Apr
yes4260.07060.00.0unknown
chronic_cardiac_diseaseno402559.2679757.81.430-Mar
yes3555.66355.60.0unknown
current_copdno401159.2677657.71.519-Mar
yes4958.38458.30.0unknown
dmardsno401859.2679057.71.519-Mar
yes4970.07070.00.0unknown
dementiano401859.3677657.91.429-Mar
yes4963.67763.60.0unknown
psychosis_schiz_bipolarno403259.4679057.91.518-Mar
yes3550.07050.00.0unknown
LDno399059.3672757.91.429-Mar
yes7052.613352.60.0unknown
ssrino402559.3679057.81.519-Mar
yes4260.07060.00.0unknown
chemo_or_radiono401859.2679057.81.430-Mar
yes4260.07060.00.0unknown
lung_cancerno401859.2679057.71.519-Mar
yes4266.76366.70.0unknown
cancer_excl_lung_and_haemno401859.2679057.71.519-Mar
yes4260.07060.00.0unknown
haematological_cancerno401859.2678357.81.430-Mar
yes4260.07060.00.0unknown
ckdno325559.4548157.91.518-Mar
yes81258.9137957.41.521-Mar
\n", + "
" + ], + "text/plain": [ + " vaccinated \\\n", + "category group \n", + "overall overall 4060 \n", + "sex F 2100 \n", + " M 1960 \n", + "ageband_5yr 0 49 \n", + " 0-15 252 \n", + " 16-17 273 \n", + " 18-29 266 \n", + " 30-34 280 \n", + " 35-39 287 \n", + " 40-44 252 \n", + " 45-49 259 \n", + " 50-54 259 \n", + " 55-59 252 \n", + " 60-64 273 \n", + " 65-69 266 \n", + " 70-74 245 \n", + " 75-79 273 \n", + " 80-84 266 \n", + " 85-89 259 \n", + " 90+ 49 \n", + "ethnicity_6_groups Black 658 \n", + " Mixed 728 \n", + " Other 693 \n", + " South Asian 735 \n", + " Unknown 588 \n", + " White 651 \n", + "ethnicity_16_groups African 224 \n", + " Bangladeshi or British Bangladeshi 189 \n", + " Caribbean 217 \n", + " Chinese 245 \n", + " Other 210 \n", + " Other Asian 217 \n", + " British or Mixed British 224 \n", + " Indian or British Indian 217 \n", + " Irish 210 \n", + " Other Black 210 \n", + " Other White 210 \n", + " Other mixed 203 \n", + " Pakistani or British Pakistani 196 \n", + " Unknown 581 \n", + " White + Asian 238 \n", + " White + Black African 238 \n", + " White + Black Caribbean 238 \n", + "imd_categories 1 Most deprived 777 \n", + " 2 777 \n", + " 3 742 \n", + " 4 812 \n", + " 5 Least deprived 756 \n", + " Unknown 196 \n", + "bmi 30+ 1225 \n", + " under 30 2835 \n", + "housebound no 4018 \n", + " yes 42 \n", + "chronic_cardiac_disease no 4025 \n", + " yes 35 \n", + "current_copd no 4011 \n", + " yes 49 \n", + "dmards no 4018 \n", + " yes 49 \n", + "dementia no 4018 \n", + " yes 49 \n", + "psychosis_schiz_bipolar no 4032 \n", + " yes 35 \n", + "LD no 3990 \n", + " yes 70 \n", + "ssri no 4025 \n", + " yes 42 \n", + "chemo_or_radio no 4018 \n", + " yes 42 \n", + "lung_cancer no 4018 \n", + " yes 42 \n", + "cancer_excl_lung_and_haem no 4018 \n", + " yes 42 \n", + "haematological_cancer no 4018 \n", + " yes 42 \n", + "ckd no 3255 \n", + " yes 812 \n", + "\n", + " percent total \\\n", + "category group \n", + "overall overall 59.2 6860 \n", + "sex F 59.3 3542 \n", + " M 59.1 3318 \n", + "ageband_5yr 0 58.3 84 \n", + " 0-15 59.0 427 \n", + " 16-17 60.0 455 \n", + " 18-29 61.3 434 \n", + " 30-34 59.7 469 \n", + " 35-39 62.1 462 \n", + " 40-44 58.1 434 \n", + " 45-49 57.8 448 \n", + " 50-54 59.7 434 \n", + " 55-59 55.4 455 \n", + " 60-64 60.9 448 \n", + " 65-69 59.4 448 \n", + " 70-74 56.5 434 \n", + " 75-79 60.0 455 \n", + " 80-84 60.3 441 \n", + " 85-89 57.8 448 \n", + " 90+ 58.3 84 \n", + "ethnicity_6_groups Black 57.0 1155 \n", + " Mixed 61.2 1190 \n", + " Other 58.9 1176 \n", + " South Asian 61.0 1204 \n", + " Unknown 57.1 1029 \n", + " White 59.2 1099 \n", + "ethnicity_16_groups African 62.7 357 \n", + " Bangladeshi or British Bangladeshi 54.0 350 \n", + " Caribbean 58.5 371 \n", + " Chinese 67.3 364 \n", + " Other 56.6 371 \n", + " Other Asian 59.6 364 \n", + " British or Mixed British 65.3 343 \n", + " Indian or British Indian 58.5 371 \n", + " Irish 57.7 364 \n", + " Other Black 57.7 364 \n", + " Other White 57.7 364 \n", + " Other mixed 58.0 350 \n", + " Pakistani or British Pakistani 59.6 329 \n", + " Unknown 57.2 1015 \n", + " White + Asian 61.8 385 \n", + " White + Black African 60.7 392 \n", + " White + Black Caribbean 59.6 399 \n", + "imd_categories 1 Most deprived 59.7 1302 \n", + " 2 57.8 1344 \n", + " 3 57.9 1281 \n", + " 4 61.7 1316 \n", + " 5 Least deprived 59.0 1281 \n", + " Unknown 59.6 329 \n", + "bmi 30+ 59.3 2065 \n", + " under 30 59.2 4788 \n", + "housebound no 59.2 6783 \n", + " yes 60.0 70 \n", + "chronic_cardiac_disease no 59.2 6797 \n", + " yes 55.6 63 \n", + "current_copd no 59.2 6776 \n", + " yes 58.3 84 \n", + "dmards no 59.2 6790 \n", + " yes 70.0 70 \n", + "dementia no 59.3 6776 \n", + " yes 63.6 77 \n", + "psychosis_schiz_bipolar no 59.4 6790 \n", + " yes 50.0 70 \n", + "LD no 59.3 6727 \n", + " yes 52.6 133 \n", + "ssri no 59.3 6790 \n", + " yes 60.0 70 \n", + "chemo_or_radio no 59.2 6790 \n", + " yes 60.0 70 \n", + "lung_cancer no 59.2 6790 \n", + " yes 66.7 63 \n", + "cancer_excl_lung_and_haem no 59.2 6790 \n", + " yes 60.0 70 \n", + "haematological_cancer no 59.2 6783 \n", + " yes 60.0 70 \n", + "ckd no 59.4 5481 \n", + " yes 58.9 1379 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 57.8 \n", + "sex F 57.9 \n", + " M 57.6 \n", + "ageband_5yr 0 58.3 \n", + " 0-15 59.0 \n", + " 16-17 56.9 \n", + " 18-29 61.3 \n", + " 30-34 58.2 \n", + " 35-39 60.6 \n", + " 40-44 56.5 \n", + " 45-49 56.2 \n", + " 50-54 58.1 \n", + " 55-59 53.8 \n", + " 60-64 59.4 \n", + " 65-69 57.8 \n", + " 70-74 56.5 \n", + " 75-79 58.5 \n", + " 80-84 58.7 \n", + " 85-89 56.2 \n", + " 90+ 58.3 \n", + "ethnicity_6_groups Black 55.8 \n", + " Mixed 60.0 \n", + " Other 57.1 \n", + " South Asian 59.9 \n", + " Unknown 55.8 \n", + " White 58.0 \n", + "ethnicity_16_groups African 60.8 \n", + " Bangladeshi or British Bangladeshi 52.0 \n", + " Caribbean 56.6 \n", + " Chinese 65.4 \n", + " Other 56.6 \n", + " Other Asian 57.7 \n", + " British or Mixed British 63.3 \n", + " Indian or British Indian 58.5 \n", + " Irish 55.8 \n", + " Other Black 55.8 \n", + " Other White 57.7 \n", + " Other mixed 56.0 \n", + " Pakistani or British Pakistani 59.6 \n", + " Unknown 55.2 \n", + " White + Asian 60.0 \n", + " White + Black African 58.9 \n", + " White + Black Caribbean 57.9 \n", + "imd_categories 1 Most deprived 58.1 \n", + " 2 56.2 \n", + " 3 56.3 \n", + " 4 60.1 \n", + " 5 Least deprived 58.5 \n", + " Unknown 57.4 \n", + "bmi 30+ 58.3 \n", + " under 30 57.7 \n", + "housebound no 57.9 \n", + " yes 60.0 \n", + "chronic_cardiac_disease no 57.8 \n", + " yes 55.6 \n", + "current_copd no 57.7 \n", + " yes 58.3 \n", + "dmards no 57.7 \n", + " yes 70.0 \n", + "dementia no 57.9 \n", + " yes 63.6 \n", + "psychosis_schiz_bipolar no 57.9 \n", + " yes 50.0 \n", + "LD no 57.9 \n", + " yes 52.6 \n", + "ssri no 57.8 \n", + " yes 60.0 \n", + "chemo_or_radio no 57.8 \n", + " yes 60.0 \n", + "lung_cancer no 57.7 \n", + " yes 66.7 \n", + "cancer_excl_lung_and_haem no 57.7 \n", + " yes 60.0 \n", + "haematological_cancer no 57.8 \n", + " yes 60.0 \n", + "ckd no 57.9 \n", + " yes 57.4 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.4 \n", + "sex F 1.4 \n", + " M 1.5 \n", + "ageband_5yr 0 0.0 \n", + " 0-15 0.0 \n", + " 16-17 3.1 \n", + " 18-29 0.0 \n", + " 30-34 1.5 \n", + " 35-39 1.5 \n", + " 40-44 1.6 \n", + " 45-49 1.6 \n", + " 50-54 1.6 \n", + " 55-59 1.6 \n", + " 60-64 1.5 \n", + " 65-69 1.6 \n", + " 70-74 0.0 \n", + " 75-79 1.5 \n", + " 80-84 1.6 \n", + " 85-89 1.6 \n", + " 90+ 0.0 \n", + "ethnicity_6_groups Black 1.2 \n", + " Mixed 1.2 \n", + " Other 1.8 \n", + " South Asian 1.1 \n", + " Unknown 1.3 \n", + " White 1.2 \n", + "ethnicity_16_groups African 1.9 \n", + " Bangladeshi or British Bangladeshi 2.0 \n", + " Caribbean 1.9 \n", + " Chinese 1.9 \n", + " Other 0.0 \n", + " Other Asian 1.9 \n", + " British or Mixed British 2.0 \n", + " Indian or British Indian 0.0 \n", + " Irish 1.9 \n", + " Other Black 1.9 \n", + " Other White 0.0 \n", + " Other mixed 2.0 \n", + " Pakistani or British Pakistani 0.0 \n", + " Unknown 2.0 \n", + " White + Asian 1.8 \n", + " White + Black African 1.8 \n", + " White + Black Caribbean 1.7 \n", + "imd_categories 1 Most deprived 1.6 \n", + " 2 1.6 \n", + " 3 1.6 \n", + " 4 1.6 \n", + " 5 Least deprived 0.5 \n", + " Unknown 2.2 \n", + "bmi 30+ 1.0 \n", + " under 30 1.5 \n", + "housebound no 1.3 \n", + " yes 0.0 \n", + "chronic_cardiac_disease no 1.4 \n", + " yes 0.0 \n", + "current_copd no 1.5 \n", + " yes 0.0 \n", + "dmards no 1.5 \n", + " yes 0.0 \n", + "dementia no 1.4 \n", + " yes 0.0 \n", + "psychosis_schiz_bipolar no 1.5 \n", + " yes 0.0 \n", + "LD no 1.4 \n", + " yes 0.0 \n", + "ssri no 1.5 \n", + " yes 0.0 \n", + "chemo_or_radio no 1.4 \n", + " yes 0.0 \n", + "lung_cancer no 1.5 \n", + " yes 0.0 \n", + "cancer_excl_lung_and_haem no 1.5 \n", + " yes 0.0 \n", + "haematological_cancer no 1.4 \n", + " yes 0.0 \n", + "ckd no 1.5 \n", + " yes 1.5 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 30-Mar \n", + "sex F 29-Mar \n", + " M 20-Mar \n", + "ageband_5yr 0 unknown \n", + " 0-15 unknown \n", + " 16-17 02-Jan \n", + " 18-29 unknown \n", + " 30-34 17-Mar \n", + " 35-39 06-Mar \n", + " 40-44 15-Mar \n", + " 45-49 16-Mar \n", + " 50-54 08-Mar \n", + " 55-59 27-Mar \n", + " 60-64 11-Mar \n", + " 65-69 09-Mar \n", + " 70-74 unknown \n", + " 75-79 16-Mar \n", + " 80-84 05-Mar \n", + " 85-89 16-Mar \n", + " 90+ unknown \n", + "ethnicity_6_groups Black unknown \n", + " Mixed 13-Apr \n", + " Other 24-Feb \n", + " South Asian unknown \n", + " Unknown unknown \n", + " White unknown \n", + "ethnicity_16_groups African 04-Feb \n", + " Bangladeshi or British Bangladeshi 02-Mar \n", + " Caribbean 20-Feb \n", + " Chinese 18-Jan \n", + " Other unknown \n", + " Other Asian 16-Feb \n", + " British or Mixed British 21-Jan \n", + " Indian or British Indian unknown \n", + " Irish 23-Feb \n", + " Other Black 23-Feb \n", + " Other White unknown \n", + " Other mixed 16-Feb \n", + " Pakistani or British Pakistani unknown \n", + " Unknown 18-Feb \n", + " White + Asian 13-Feb \n", + " White + Black African 17-Feb \n", + " White + Black Caribbean 01-Mar \n", + "imd_categories 1 Most deprived 08-Mar \n", + " 2 16-Mar \n", + " 3 16-Mar \n", + " 4 27-Feb \n", + " 5 Least deprived unknown \n", + " Unknown 31-Jan \n", + "bmi 30+ unknown \n", + " under 30 19-Mar \n", + "housebound no 10-Apr \n", + " yes unknown \n", + "chronic_cardiac_disease no 30-Mar \n", + " yes unknown \n", + "current_copd no 19-Mar \n", + " yes unknown \n", + "dmards no 19-Mar \n", + " yes unknown \n", + "dementia no 29-Mar \n", + " yes unknown \n", + "psychosis_schiz_bipolar no 18-Mar \n", + " yes unknown \n", + "LD no 29-Mar \n", + " yes unknown \n", + "ssri no 19-Mar \n", + " yes unknown \n", + "chemo_or_radio no 30-Mar \n", + " yes unknown \n", + "lung_cancer no 19-Mar \n", + " yes unknown \n", + "cancer_excl_lung_and_haem no 19-Mar \n", + " yes unknown \n", + "haematological_cancer no 30-Mar \n", + " yes unknown \n", + "ckd no 18-Mar \n", + " yes 21-Mar " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:644: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out_csv = out_csv.drop(\"Date projected to reach 90%\",1)\n" + ] + }, + { + "data": { + "text/markdown": [ + "## " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## COVID vaccination rollout (second dose 14w ago) among **care home** population up to 2021-10-27" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- 'Date projected to reach 90%' being 'unknown' indicates projection of >6mo (likely insufficient information)\n", + "- Patient counts rounded to the nearest 7" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall168759.8282158.31.516-Mar
sexF84759.3142857.81.519-Mar
M83360.1138658.61.515-Mar
ageband_5yr01450.02850.00.0unknown
0-1510560.017556.04.018-Dec
16-1711960.719657.13.622-Dec
18-2910562.516862.50.0unknown
30-3410555.618955.60.0unknown
35-3911259.318959.30.0unknown
40-4410562.516858.34.211-Dec
45-4910557.718257.70.0unknown
50-5411261.518257.73.818-Dec
55-5911960.719660.70.0unknown
60-6411257.119657.10.0unknown
65-6910557.718253.83.923-Dec
70-749851.918951.90.0unknown
75-799856.017556.00.0unknown
80-8411965.418265.40.0unknown
85-8911968.017568.00.0unknown
90+2857.14957.10.0unknown
ethnicity_6_groupsBlack27360.944857.83.131-Dec
Mixed28060.646259.11.513-Mar
Other30159.750459.70.0unknown
South Asian27358.246956.71.524-Mar
Unknown27362.943461.31.622-Feb
White28758.649057.11.522-Mar
dementiano167359.9279358.41.516-Mar
yes1450.02850.00.0unknown
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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall54662.986862.10.8unknown
newly_shielded_since_feb_15no53962.686161.80.8unknown
yes00.070.00.0unknown
sexF28764.144864.10.0unknown
M25961.742060.01.720-Feb
ageband16-296360.010560.00.0unknown
30-395653.310553.30.0unknown
40-497062.511262.50.0unknown
50-598466.712666.70.0unknown
60-697062.511262.50.0unknown
70-7912662.120362.10.0unknown
80+7062.511262.50.0unknown
ethnicity_6_groupsBlack9165.014060.05.001-Dec
Mixed9860.916160.90.0unknown
Other9165.014065.00.0unknown
South Asian9161.914761.90.0unknown
Unknown7764.711964.70.0unknown
White9860.916160.90.0unknown
imd_categories1 Most deprived11965.418265.40.0unknown
29866.714766.70.0unknown
311266.716866.70.0unknown
49860.916156.54.412-Dec
5 Least deprived10562.516858.34.211-Dec
Unknown2150.04250.00.0unknown
LDno53963.185462.30.8unknown
yes14100.01450.050.0reached
ckdno45563.172162.11.0unknown
yes9866.714761.94.829-Nov
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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall268860.9441759.61.301-Apr
sexF133760.1222658.81.306-Apr
M134461.3219160.11.212-Apr
ethnicity_6_groupsBlack46962.075659.32.707-Jan
Mixed48362.777060.91.810-Feb
Other43457.974957.00.9unknown
South Asian42059.470758.41.0unknown
Unknown43462.070061.01.0unknown
White44160.073560.00.0unknown
ethnicity_16_groupsAfrican14062.522462.50.0unknown
Bangladeshi or British Bangladeshi13357.623154.53.108-Jan
Caribbean14761.823858.83.031-Dec
Chinese16165.724562.92.826-Dec
Other16863.226660.52.704-Jan
Other Asian12658.121758.10.0unknown
British or Mixed British14761.823861.80.0unknown
Indian or British Indian14057.124557.10.0unknown
Irish13357.623157.60.0unknown
Other Black15464.723861.82.927-Dec
Other White14761.823861.80.0unknown
Other mixed13352.825252.80.0unknown
Pakistani or British Pakistani16167.623864.72.920-Dec
Unknown40665.262364.01.220-Mar
White + Asian14062.522459.43.128-Dec
White + Black African11960.719660.70.0unknown
White + Black Caribbean13351.425948.62.831-Jan
imd_categories1 Most deprived48359.081957.31.703-Mar
251160.884060.00.8unknown
353963.185461.51.621-Feb
451160.884060.00.8unknown
5 Least deprived51160.884059.21.603-Mar
Unknown13361.321761.30.0unknown
bmi30+84061.5136560.01.509-Mar
under 30184860.6305259.21.423-Mar
houseboundno265360.8436159.61.215-Apr
yes3571.44957.114.305-Nov
chronic_cardiac_diseaseno265360.7436859.51.215-Apr
yes2857.14957.10.0unknown
current_copdno266060.8437559.71.1unknown
yes2150.04250.00.0unknown
dmardsno265360.7436859.51.215-Apr
yes2857.14957.10.0unknown
dementiano265360.7436859.51.215-Apr
yes2866.74266.70.0unknown
psychosis_schiz_bipolarno265360.7436859.51.215-Apr
yes2857.14957.10.0unknown
LDno262560.9431259.61.301-Apr
yes6360.010560.00.0unknown
ssrino266761.0437559.71.301-Apr
yes2160.03560.00.0unknown
chemo_or_radiono266761.0437559.71.301-Apr
yes2150.04250.00.0unknown
lung_cancerno266760.9438259.61.301-Apr
yes2160.03560.00.0unknown
cancer_excl_lung_and_haemno266060.8437559.51.302-Apr
yes2880.03580.00.0unknown
haematological_cancerno265360.7436859.51.215-Apr
yes2866.74266.70.0unknown
ckdno211460.9347259.51.421-Mar
yes56760.493859.70.7unknown
\n", + "
" + ], + "text/plain": [ + " vaccinated \\\n", + "category group \n", + "overall overall 2688 \n", + "sex F 1337 \n", + " M 1344 \n", + "ethnicity_6_groups Black 469 \n", + " Mixed 483 \n", + " Other 434 \n", + " South Asian 420 \n", + " Unknown 434 \n", + " White 441 \n", + "ethnicity_16_groups African 140 \n", + " Bangladeshi or British Bangladeshi 133 \n", + " Caribbean 147 \n", + " Chinese 161 \n", + " Other 168 \n", + " Other Asian 126 \n", + " British or Mixed British 147 \n", + " Indian or British Indian 140 \n", + " Irish 133 \n", + " Other Black 154 \n", + " Other White 147 \n", + " Other mixed 133 \n", + " Pakistani or British Pakistani 161 \n", + " Unknown 406 \n", + " White + Asian 140 \n", + " White + Black African 119 \n", + " White + Black Caribbean 133 \n", + "imd_categories 1 Most deprived 483 \n", + " 2 511 \n", + " 3 539 \n", + " 4 511 \n", + " 5 Least deprived 511 \n", + " Unknown 133 \n", + "bmi 30+ 840 \n", + " under 30 1848 \n", + "housebound no 2653 \n", + " yes 35 \n", + "chronic_cardiac_disease no 2653 \n", + " yes 28 \n", + "current_copd no 2660 \n", + " yes 21 \n", + "dmards no 2653 \n", + " yes 28 \n", + "dementia no 2653 \n", + " yes 28 \n", + "psychosis_schiz_bipolar no 2653 \n", + " yes 28 \n", + "LD no 2625 \n", + " yes 63 \n", + "ssri no 2667 \n", + " yes 21 \n", + "chemo_or_radio no 2667 \n", + " yes 21 \n", + "lung_cancer no 2667 \n", + " yes 21 \n", + "cancer_excl_lung_and_haem no 2660 \n", + " yes 28 \n", + "haematological_cancer no 2653 \n", + " yes 28 \n", + "ckd no 2114 \n", + " yes 567 \n", + "\n", + " percent total \\\n", + "category group \n", + "overall overall 60.9 4417 \n", + "sex F 60.1 2226 \n", + " M 61.3 2191 \n", + "ethnicity_6_groups Black 62.0 756 \n", + " Mixed 62.7 770 \n", + " Other 57.9 749 \n", + " South Asian 59.4 707 \n", + " Unknown 62.0 700 \n", + " White 60.0 735 \n", + "ethnicity_16_groups African 62.5 224 \n", + " Bangladeshi or British Bangladeshi 57.6 231 \n", + " Caribbean 61.8 238 \n", + " Chinese 65.7 245 \n", + " Other 63.2 266 \n", + " Other Asian 58.1 217 \n", + " British or Mixed British 61.8 238 \n", + " Indian or British Indian 57.1 245 \n", + " Irish 57.6 231 \n", + " Other Black 64.7 238 \n", + " Other White 61.8 238 \n", + " Other mixed 52.8 252 \n", + " Pakistani or British Pakistani 67.6 238 \n", + " Unknown 65.2 623 \n", + " White + Asian 62.5 224 \n", + " White + Black African 60.7 196 \n", + " White + Black Caribbean 51.4 259 \n", + "imd_categories 1 Most deprived 59.0 819 \n", + " 2 60.8 840 \n", + " 3 63.1 854 \n", + " 4 60.8 840 \n", + " 5 Least deprived 60.8 840 \n", + " Unknown 61.3 217 \n", + "bmi 30+ 61.5 1365 \n", + " under 30 60.6 3052 \n", + "housebound no 60.8 4361 \n", + " yes 71.4 49 \n", + "chronic_cardiac_disease no 60.7 4368 \n", + " yes 57.1 49 \n", + "current_copd no 60.8 4375 \n", + " yes 50.0 42 \n", + "dmards no 60.7 4368 \n", + " yes 57.1 49 \n", + "dementia no 60.7 4368 \n", + " yes 66.7 42 \n", + "psychosis_schiz_bipolar no 60.7 4368 \n", + " yes 57.1 49 \n", + "LD no 60.9 4312 \n", + " yes 60.0 105 \n", + "ssri no 61.0 4375 \n", + " yes 60.0 35 \n", + "chemo_or_radio no 61.0 4375 \n", + " yes 50.0 42 \n", + "lung_cancer no 60.9 4382 \n", + " yes 60.0 35 \n", + "cancer_excl_lung_and_haem no 60.8 4375 \n", + " yes 80.0 35 \n", + "haematological_cancer no 60.7 4368 \n", + " yes 66.7 42 \n", + "ckd no 60.9 3472 \n", + " yes 60.4 938 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.6 \n", + "sex F 58.8 \n", + " M 60.1 \n", + "ethnicity_6_groups Black 59.3 \n", + " Mixed 60.9 \n", + " Other 57.0 \n", + " South Asian 58.4 \n", + " Unknown 61.0 \n", + " White 60.0 \n", + "ethnicity_16_groups African 62.5 \n", + " Bangladeshi or British Bangladeshi 54.5 \n", + " Caribbean 58.8 \n", + " Chinese 62.9 \n", + " Other 60.5 \n", + " Other Asian 58.1 \n", + " British or Mixed British 61.8 \n", + " Indian or British Indian 57.1 \n", + " Irish 57.6 \n", + " Other Black 61.8 \n", + " Other White 61.8 \n", + " Other mixed 52.8 \n", + " Pakistani or British Pakistani 64.7 \n", + " Unknown 64.0 \n", + " White + Asian 59.4 \n", + " White + Black African 60.7 \n", + " White + Black Caribbean 48.6 \n", + "imd_categories 1 Most deprived 57.3 \n", + " 2 60.0 \n", + " 3 61.5 \n", + " 4 60.0 \n", + " 5 Least deprived 59.2 \n", + " Unknown 61.3 \n", + "bmi 30+ 60.0 \n", + " under 30 59.2 \n", + "housebound no 59.6 \n", + " yes 57.1 \n", + "chronic_cardiac_disease no 59.5 \n", + " yes 57.1 \n", + "current_copd no 59.7 \n", + " yes 50.0 \n", + "dmards no 59.5 \n", + " yes 57.1 \n", + "dementia no 59.5 \n", + " yes 66.7 \n", + "psychosis_schiz_bipolar no 59.5 \n", + " yes 57.1 \n", + "LD no 59.6 \n", + " yes 60.0 \n", + "ssri no 59.7 \n", + " yes 60.0 \n", + "chemo_or_radio no 59.7 \n", + " yes 50.0 \n", + "lung_cancer no 59.6 \n", + " yes 60.0 \n", + "cancer_excl_lung_and_haem no 59.5 \n", + " yes 80.0 \n", + "haematological_cancer no 59.5 \n", + " yes 66.7 \n", + "ckd no 59.5 \n", + " yes 59.7 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.3 \n", + "sex F 1.3 \n", + " M 1.2 \n", + "ethnicity_6_groups Black 2.7 \n", + " Mixed 1.8 \n", + " Other 0.9 \n", + " South Asian 1.0 \n", + " Unknown 1.0 \n", + " White 0.0 \n", + "ethnicity_16_groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 3.1 \n", + " Caribbean 3.0 \n", + " Chinese 2.8 \n", + " Other 2.7 \n", + " Other Asian 0.0 \n", + " British or Mixed British 0.0 \n", + " Indian or British Indian 0.0 \n", + " Irish 0.0 \n", + " Other Black 2.9 \n", + " Other White 0.0 \n", + " Other mixed 0.0 \n", + " Pakistani or British Pakistani 2.9 \n", + " Unknown 1.2 \n", + " White + Asian 3.1 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 2.8 \n", + "imd_categories 1 Most deprived 1.7 \n", + " 2 0.8 \n", + " 3 1.6 \n", + " 4 0.8 \n", + " 5 Least deprived 1.6 \n", + " Unknown 0.0 \n", + "bmi 30+ 1.5 \n", + " under 30 1.4 \n", + "housebound no 1.2 \n", + " yes 14.3 \n", + "chronic_cardiac_disease no 1.2 \n", + " yes 0.0 \n", + "current_copd no 1.1 \n", + " yes 0.0 \n", + "dmards no 1.2 \n", + " yes 0.0 \n", + "dementia no 1.2 \n", + " yes 0.0 \n", + "psychosis_schiz_bipolar no 1.2 \n", + " yes 0.0 \n", + "LD no 1.3 \n", + " yes 0.0 \n", + "ssri no 1.3 \n", + " yes 0.0 \n", + "chemo_or_radio no 1.3 \n", + " yes 0.0 \n", + "lung_cancer no 1.3 \n", + " yes 0.0 \n", + "cancer_excl_lung_and_haem no 1.3 \n", + " yes 0.0 \n", + "haematological_cancer no 1.2 \n", + " yes 0.0 \n", + "ckd no 1.4 \n", + " yes 0.7 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 01-Apr \n", + "sex F 06-Apr \n", + " M 12-Apr \n", + "ethnicity_6_groups Black 07-Jan \n", + " Mixed 10-Feb \n", + " Other unknown \n", + " South Asian unknown \n", + " Unknown unknown \n", + " White unknown \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi 08-Jan \n", + " Caribbean 31-Dec \n", + " Chinese 26-Dec \n", + " Other 04-Jan \n", + " Other Asian unknown \n", + " British or Mixed British unknown \n", + " Indian or British Indian unknown \n", + " Irish unknown \n", + " Other Black 27-Dec \n", + " Other White unknown \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani 20-Dec \n", + " Unknown 20-Mar \n", + " White + Asian 28-Dec \n", + " White + Black African unknown \n", + " White + Black Caribbean 31-Jan \n", + "imd_categories 1 Most deprived 03-Mar \n", + " 2 unknown \n", + " 3 21-Feb \n", + " 4 unknown \n", + " 5 Least deprived 03-Mar \n", + " Unknown unknown \n", + "bmi 30+ 09-Mar \n", + " under 30 23-Mar \n", + "housebound no 15-Apr \n", + " yes 05-Nov \n", + "chronic_cardiac_disease no 15-Apr \n", + " yes unknown \n", + "current_copd no unknown \n", + " yes unknown \n", + "dmards no 15-Apr \n", + " yes unknown \n", + "dementia no 15-Apr \n", + " yes unknown \n", + "psychosis_schiz_bipolar no 15-Apr \n", + " yes unknown \n", + "LD no 01-Apr \n", + " yes unknown \n", + "ssri no 01-Apr \n", + " yes unknown \n", + "chemo_or_radio no 01-Apr \n", + " yes unknown \n", + "lung_cancer no 01-Apr \n", + " yes unknown \n", + "cancer_excl_lung_and_haem no 02-Apr \n", + " yes unknown \n", + "haematological_cancer no 15-Apr \n", + " yes unknown \n", + "ckd no 21-Mar \n", + " yes unknown " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:644: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out_csv = out_csv.drop(\"Date projected to reach 90%\",1)\n" + ] + }, + { + "data": { + "text/markdown": [ + "## " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## COVID vaccination rollout (second dose 14w ago) among **LD (aged 16-64)** population up to 2021-10-27" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- 'Date projected to reach 90%' being 'unknown' indicates projection of >6mo (likely insufficient information)\n", + "- Patient counts rounded to the nearest 7" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall97360.7160359.80.9unknown
sexF46258.479157.50.9unknown
M51162.981262.10.8unknown
ageband_5yr0733.32133.30.0unknown
0-157066.710560.06.720-Nov
16-177062.511256.26.326-Nov
18-297066.710560.06.720-Nov
30-346364.39864.30.0unknown
35-397066.710566.70.0unknown
40-444958.38458.30.0unknown
45-497058.811958.80.0unknown
50-547757.913357.90.0unknown
55-597066.710566.70.0unknown
60-645657.19857.10.0unknown
65-695657.19857.10.0unknown
70-745661.59161.50.0unknown
75-796360.010560.00.0unknown
80-845657.19857.10.0unknown
85-896360.010560.00.0unknown
90+14100.014100.00.0reached
ethnicity_6_groupsBlack16159.027359.00.0unknown
Mixed17562.528060.02.512-Jan
Other16154.829454.80.0unknown
South Asian16159.027359.00.0unknown
Unknown15468.822465.63.212-Dec
White16162.225959.52.707-Jan
\n", + "
" + ], + "text/plain": [ + " vaccinated percent total \\\n", + "category group \n", + "overall overall 973 60.7 1603 \n", + "sex F 462 58.4 791 \n", + " M 511 62.9 812 \n", + "ageband_5yr 0 7 33.3 21 \n", + " 0-15 70 66.7 105 \n", + " 16-17 70 62.5 112 \n", + " 18-29 70 66.7 105 \n", + " 30-34 63 64.3 98 \n", + " 35-39 70 66.7 105 \n", + " 40-44 49 58.3 84 \n", + " 45-49 70 58.8 119 \n", + " 50-54 77 57.9 133 \n", + " 55-59 70 66.7 105 \n", + " 60-64 56 57.1 98 \n", + " 65-69 56 57.1 98 \n", + " 70-74 56 61.5 91 \n", + " 75-79 63 60.0 105 \n", + " 80-84 56 57.1 98 \n", + " 85-89 63 60.0 105 \n", + " 90+ 14 100.0 14 \n", + "ethnicity_6_groups Black 161 59.0 273 \n", + " Mixed 175 62.5 280 \n", + " Other 161 54.8 294 \n", + " South Asian 161 59.0 273 \n", + " Unknown 154 68.8 224 \n", + " White 161 62.2 259 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.8 \n", + "sex F 57.5 \n", + " M 62.1 \n", + "ageband_5yr 0 33.3 \n", + " 0-15 60.0 \n", + " 16-17 56.2 \n", + " 18-29 60.0 \n", + " 30-34 64.3 \n", + " 35-39 66.7 \n", + " 40-44 58.3 \n", + " 45-49 58.8 \n", + " 50-54 57.9 \n", + " 55-59 66.7 \n", + " 60-64 57.1 \n", + " 65-69 57.1 \n", + " 70-74 61.5 \n", + " 75-79 60.0 \n", + " 80-84 57.1 \n", + " 85-89 60.0 \n", + " 90+ 100.0 \n", + "ethnicity_6_groups Black 59.0 \n", + " Mixed 60.0 \n", + " Other 54.8 \n", + " South Asian 59.0 \n", + " Unknown 65.6 \n", + " White 59.5 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 0.9 \n", + "sex F 0.9 \n", + " M 0.8 \n", + "ageband_5yr 0 0.0 \n", + " 0-15 6.7 \n", + " 16-17 6.3 \n", + " 18-29 6.7 \n", + " 30-34 0.0 \n", + " 35-39 0.0 \n", + " 40-44 0.0 \n", + " 45-49 0.0 \n", + " 50-54 0.0 \n", + " 55-59 0.0 \n", + " 60-64 0.0 \n", + " 65-69 0.0 \n", + " 70-74 0.0 \n", + " 75-79 0.0 \n", + " 80-84 0.0 \n", + " 85-89 0.0 \n", + " 90+ 0.0 \n", + "ethnicity_6_groups Black 0.0 \n", + " Mixed 2.5 \n", + " Other 0.0 \n", + " South Asian 0.0 \n", + " Unknown 3.2 \n", + " White 2.7 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall unknown \n", + "sex F unknown \n", + " M unknown \n", + "ageband_5yr 0 unknown \n", + " 0-15 20-Nov \n", + " 16-17 26-Nov \n", + " 18-29 20-Nov \n", + " 30-34 unknown \n", + " 35-39 unknown \n", + " 40-44 unknown \n", + " 45-49 unknown \n", + " 50-54 unknown \n", + " 55-59 unknown \n", + " 60-64 unknown \n", + " 65-69 unknown \n", + " 70-74 unknown \n", + " 75-79 unknown \n", + " 80-84 unknown \n", + " 85-89 unknown \n", + " 90+ reached \n", + "ethnicity_6_groups Black unknown \n", + " Mixed 12-Jan \n", + " Other unknown \n", + " South Asian unknown \n", + " Unknown 12-Dec \n", + " White 07-Jan " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:644: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out_csv = out_csv.drop(\"Date projected to reach 90%\",1)\n" + ] + }, + { + "data": { + "text/markdown": [ + "## " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## COVID vaccination rollout (second dose 14w ago) among **60-64** population up to 2021-10-27" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- 'Date projected to reach 90%' being 'unknown' indicates projection of >6mo (likely insufficient information)\n", + "- Patient counts rounded to the nearest 7" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall324859.6545357.91.701-Mar
sexF168059.9280758.11.821-Feb
M156859.3264657.71.610-Mar
ethnicity_6_groupsBlack58160.695958.42.228-Jan
Mixed57460.794559.31.422-Mar
Other53260.388258.71.605-Mar
South Asian54659.591758.01.518-Mar
Unknown46957.381956.40.9unknown
White54658.293856.02.205-Feb
ethnicity_16_groupsAfrican17562.528062.50.0unknown
Bangladeshi or British Bangladeshi17558.130153.54.614-Dec
Caribbean18260.530158.12.421-Jan
Chinese16855.830153.52.308-Feb
Other18962.830162.80.0unknown
Other Asian18260.530158.12.421-Jan
British or Mixed British16162.225959.52.707-Jan
Indian or British Indian16159.027356.42.618-Jan
Irish16860.028060.00.0unknown
Other Black17561.028758.52.516-Jan
Other White16159.027356.42.618-Jan
Other mixed15457.926655.32.621-Jan
Pakistani or British Pakistani18260.530158.12.421-Jan
Unknown49058.883357.11.704-Mar
White + Asian18263.428761.02.412-Jan
White + Black African18962.830162.80.0unknown
White + Black Caribbean16853.331551.12.220-Feb
imd_categories1 Most deprived57456.6101554.52.115-Feb
260958.8103656.12.715-Jan
365861.4107159.51.909-Feb
460960.8100159.41.422-Mar
5 Least deprived64460.9105759.61.301-Apr
Unknown15455.028055.00.0unknown
bmi30+96659.5162457.32.201-Feb
under 30228259.6382958.11.517-Mar
chronic_cardiac_diseaseno322059.5541157.81.701-Mar
yes2866.74266.70.0unknown
current_copdno321359.5539758.01.518-Mar
yes3562.55650.012.511-Nov
dmardsno322059.7539758.01.728-Feb
yes2850.05650.00.0unknown
dementiano319259.4537657.81.609-Mar
yes4963.67763.60.0unknown
psychosis_schiz_bipolarno321359.5540457.91.609-Mar
yes2857.14957.10.0unknown
ssrino322059.6540457.91.701-Mar
yes2857.14957.10.0unknown
chemo_or_radiono321359.5539758.01.518-Mar
yes3555.66344.411.217-Nov
lung_cancerno322059.5541157.81.701-Mar
yes2857.14957.10.0unknown
cancer_excl_lung_and_haemno321359.5539757.81.701-Mar
yes3562.55662.50.0unknown
haematological_cancerno321359.5540457.81.701-Mar
yes3571.44971.40.0unknown
ckdno261159.3440357.71.610-Mar
yes63059.6105758.31.308-Apr
\n", + "
" + ], + "text/plain": [ + " vaccinated \\\n", + "category group \n", + "overall overall 3248 \n", + "sex F 1680 \n", + " M 1568 \n", + "ethnicity_6_groups Black 581 \n", + " Mixed 574 \n", + " Other 532 \n", + " South Asian 546 \n", + " Unknown 469 \n", + " White 546 \n", + "ethnicity_16_groups African 175 \n", + " Bangladeshi or British Bangladeshi 175 \n", + " Caribbean 182 \n", + " Chinese 168 \n", + " Other 189 \n", + " Other Asian 182 \n", + " British or Mixed British 161 \n", + " Indian or British Indian 161 \n", + " Irish 168 \n", + " Other Black 175 \n", + " Other White 161 \n", + " Other mixed 154 \n", + " Pakistani or British Pakistani 182 \n", + " Unknown 490 \n", + " White + Asian 182 \n", + " White + Black African 189 \n", + " White + Black Caribbean 168 \n", + "imd_categories 1 Most deprived 574 \n", + " 2 609 \n", + " 3 658 \n", + " 4 609 \n", + " 5 Least deprived 644 \n", + " Unknown 154 \n", + "bmi 30+ 966 \n", + " under 30 2282 \n", + "chronic_cardiac_disease no 3220 \n", + " yes 28 \n", + "current_copd no 3213 \n", + " yes 35 \n", + "dmards no 3220 \n", + " yes 28 \n", + "dementia no 3192 \n", + " yes 49 \n", + "psychosis_schiz_bipolar no 3213 \n", + " yes 28 \n", + "ssri no 3220 \n", + " yes 28 \n", + "chemo_or_radio no 3213 \n", + " yes 35 \n", + "lung_cancer no 3220 \n", + " yes 28 \n", + "cancer_excl_lung_and_haem no 3213 \n", + " yes 35 \n", + "haematological_cancer no 3213 \n", + " yes 35 \n", + "ckd no 2611 \n", + " yes 630 \n", + "\n", + " percent total \\\n", + "category group \n", + "overall overall 59.6 5453 \n", + "sex F 59.9 2807 \n", + " M 59.3 2646 \n", + "ethnicity_6_groups Black 60.6 959 \n", + " Mixed 60.7 945 \n", + " Other 60.3 882 \n", + " South Asian 59.5 917 \n", + " Unknown 57.3 819 \n", + " White 58.2 938 \n", + "ethnicity_16_groups African 62.5 280 \n", + " Bangladeshi or British Bangladeshi 58.1 301 \n", + " Caribbean 60.5 301 \n", + " Chinese 55.8 301 \n", + " Other 62.8 301 \n", + " Other Asian 60.5 301 \n", + " British or Mixed British 62.2 259 \n", + " Indian or British Indian 59.0 273 \n", + " Irish 60.0 280 \n", + " Other Black 61.0 287 \n", + " Other White 59.0 273 \n", + " Other mixed 57.9 266 \n", + " Pakistani or British Pakistani 60.5 301 \n", + " Unknown 58.8 833 \n", + " White + Asian 63.4 287 \n", + " White + Black African 62.8 301 \n", + " White + Black Caribbean 53.3 315 \n", + "imd_categories 1 Most deprived 56.6 1015 \n", + " 2 58.8 1036 \n", + " 3 61.4 1071 \n", + " 4 60.8 1001 \n", + " 5 Least deprived 60.9 1057 \n", + " Unknown 55.0 280 \n", + "bmi 30+ 59.5 1624 \n", + " under 30 59.6 3829 \n", + "chronic_cardiac_disease no 59.5 5411 \n", + " yes 66.7 42 \n", + "current_copd no 59.5 5397 \n", + " yes 62.5 56 \n", + "dmards no 59.7 5397 \n", + " yes 50.0 56 \n", + "dementia no 59.4 5376 \n", + " yes 63.6 77 \n", + "psychosis_schiz_bipolar no 59.5 5404 \n", + " yes 57.1 49 \n", + "ssri no 59.6 5404 \n", + " yes 57.1 49 \n", + "chemo_or_radio no 59.5 5397 \n", + " yes 55.6 63 \n", + "lung_cancer no 59.5 5411 \n", + " yes 57.1 49 \n", + "cancer_excl_lung_and_haem no 59.5 5397 \n", + " yes 62.5 56 \n", + "haematological_cancer no 59.5 5404 \n", + " yes 71.4 49 \n", + "ckd no 59.3 4403 \n", + " yes 59.6 1057 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 57.9 \n", + "sex F 58.1 \n", + " M 57.7 \n", + "ethnicity_6_groups Black 58.4 \n", + " Mixed 59.3 \n", + " Other 58.7 \n", + " South Asian 58.0 \n", + " Unknown 56.4 \n", + " White 56.0 \n", + "ethnicity_16_groups African 62.5 \n", + " Bangladeshi or British Bangladeshi 53.5 \n", + " Caribbean 58.1 \n", + " Chinese 53.5 \n", + " Other 62.8 \n", + " Other Asian 58.1 \n", + " British or Mixed British 59.5 \n", + " Indian or British Indian 56.4 \n", + " Irish 60.0 \n", + " Other Black 58.5 \n", + " Other White 56.4 \n", + " Other mixed 55.3 \n", + " Pakistani or British Pakistani 58.1 \n", + " Unknown 57.1 \n", + " White + Asian 61.0 \n", + " White + Black African 62.8 \n", + " White + Black Caribbean 51.1 \n", + "imd_categories 1 Most deprived 54.5 \n", + " 2 56.1 \n", + " 3 59.5 \n", + " 4 59.4 \n", + " 5 Least deprived 59.6 \n", + " Unknown 55.0 \n", + "bmi 30+ 57.3 \n", + " under 30 58.1 \n", + "chronic_cardiac_disease no 57.8 \n", + " yes 66.7 \n", + "current_copd no 58.0 \n", + " yes 50.0 \n", + "dmards no 58.0 \n", + " yes 50.0 \n", + "dementia no 57.8 \n", + " yes 63.6 \n", + "psychosis_schiz_bipolar no 57.9 \n", + " yes 57.1 \n", + "ssri no 57.9 \n", + " yes 57.1 \n", + "chemo_or_radio no 58.0 \n", + " yes 44.4 \n", + "lung_cancer no 57.8 \n", + " yes 57.1 \n", + "cancer_excl_lung_and_haem no 57.8 \n", + " yes 62.5 \n", + "haematological_cancer no 57.8 \n", + " yes 71.4 \n", + "ckd no 57.7 \n", + " yes 58.3 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.7 \n", + "sex F 1.8 \n", + " M 1.6 \n", + "ethnicity_6_groups Black 2.2 \n", + " Mixed 1.4 \n", + " Other 1.6 \n", + " South Asian 1.5 \n", + " Unknown 0.9 \n", + " White 2.2 \n", + "ethnicity_16_groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 4.6 \n", + " Caribbean 2.4 \n", + " Chinese 2.3 \n", + " Other 0.0 \n", + " Other Asian 2.4 \n", + " British or Mixed British 2.7 \n", + " Indian or British Indian 2.6 \n", + " Irish 0.0 \n", + " Other Black 2.5 \n", + " Other White 2.6 \n", + " Other mixed 2.6 \n", + " Pakistani or British Pakistani 2.4 \n", + " Unknown 1.7 \n", + " White + Asian 2.4 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 2.2 \n", + "imd_categories 1 Most deprived 2.1 \n", + " 2 2.7 \n", + " 3 1.9 \n", + " 4 1.4 \n", + " 5 Least deprived 1.3 \n", + " Unknown 0.0 \n", + "bmi 30+ 2.2 \n", + " under 30 1.5 \n", + "chronic_cardiac_disease no 1.7 \n", + " yes 0.0 \n", + "current_copd no 1.5 \n", + " yes 12.5 \n", + "dmards no 1.7 \n", + " yes 0.0 \n", + "dementia no 1.6 \n", + " yes 0.0 \n", + "psychosis_schiz_bipolar no 1.6 \n", + " yes 0.0 \n", + "ssri no 1.7 \n", + " yes 0.0 \n", + "chemo_or_radio no 1.5 \n", + " yes 11.2 \n", + "lung_cancer no 1.7 \n", + " yes 0.0 \n", + "cancer_excl_lung_and_haem no 1.7 \n", + " yes 0.0 \n", + "haematological_cancer no 1.7 \n", + " yes 0.0 \n", + "ckd no 1.6 \n", + " yes 1.3 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 01-Mar \n", + "sex F 21-Feb \n", + " M 10-Mar \n", + "ethnicity_6_groups Black 28-Jan \n", + " Mixed 22-Mar \n", + " Other 05-Mar \n", + " South Asian 18-Mar \n", + " Unknown unknown \n", + " White 05-Feb \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi 14-Dec \n", + " Caribbean 21-Jan \n", + " Chinese 08-Feb \n", + " Other unknown \n", + " Other Asian 21-Jan \n", + " British or Mixed British 07-Jan \n", + " Indian or British Indian 18-Jan \n", + " Irish unknown \n", + " Other Black 16-Jan \n", + " Other White 18-Jan \n", + " Other mixed 21-Jan \n", + " Pakistani or British Pakistani 21-Jan \n", + " 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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall378060.7622359.41.302-Apr
sexF191159.6320658.11.517-Mar
M186961.9301760.81.1unknown
ethnicity_6_groupsBlack59557.4103656.11.3unknown
Mixed66562.5106461.21.324-Mar
Other65160.0108558.71.306-Apr
South Asian63061.6102260.31.328-Mar
Unknown60263.295262.50.7unknown
White63759.5107158.21.309-Apr
ethnicity_16_groupsAfrican18958.732258.70.0unknown
Bangladeshi or British Bangladeshi17558.130158.10.0unknown
Caribbean20361.732961.70.0unknown
Chinese17559.529457.12.423-Jan
Other20361.732961.70.0unknown
Other Asian18259.130859.10.0unknown
British or Mixed British19658.333658.30.0unknown
Indian or British Indian19660.932258.72.227-Jan
Irish20360.433660.40.0unknown
Other Black18955.134355.10.0unknown
Other White20358.035056.02.016-Feb
Other mixed19663.630861.42.219-Jan
Pakistani or British Pakistani22462.735762.70.0unknown
Unknown59562.595261.01.504-Mar
White + Asian21062.533660.42.126-Jan
White + Black African23863.037861.11.903-Feb
White + Black Caribbean19659.632957.42.231-Jan
imd_categories1 Most deprived74961.1122559.41.723-Feb
267959.5114157.71.822-Feb
374961.8121160.71.1unknown
471460.4118359.80.6unknown
5 Least deprived69360.7114159.51.215-Apr
Unknown19660.932258.72.227-Jan
bmi30+109960.9180659.71.214-Apr
under 30268860.9441759.41.511-Mar
chronic_cardiac_diseaseno373160.6615359.31.303-Apr
yes4963.67763.60.0unknown
current_copdno375260.8617459.41.422-Mar
yes2850.05650.00.0unknown
dmardsno373860.7616059.31.422-Mar
yes4970.07060.010.010-Nov
psychosis_schiz_bipolarno373860.6616759.31.303-Apr
yes4266.76366.70.0unknown
ssrino374560.8616059.41.422-Mar
yes3550.07050.00.0unknown
ckdno299660.6494259.31.303-Apr
yes78460.9128859.21.723-Feb
\n", + "
" + ], + "text/plain": [ + " vaccinated \\\n", + "category group \n", + "overall overall 3780 \n", + "sex F 1911 \n", + " M 1869 \n", + "ethnicity_6_groups Black 595 \n", + " Mixed 665 \n", + " Other 651 \n", + " South Asian 630 \n", + " Unknown 602 \n", + " White 637 \n", + "ethnicity_16_groups African 189 \n", + " Bangladeshi or British Bangladeshi 175 \n", + " Caribbean 203 \n", + " Chinese 175 \n", + " Other 203 \n", + " Other Asian 182 \n", + " British or Mixed British 196 \n", + " Indian or British Indian 196 \n", + " Irish 203 \n", + " Other Black 189 \n", + " Other White 203 \n", + " Other mixed 196 \n", + " Pakistani or British Pakistani 224 \n", + " Unknown 595 \n", + " White + Asian 210 \n", + " White + Black African 238 \n", + " White + Black Caribbean 196 \n", + "imd_categories 1 Most deprived 749 \n", + " 2 679 \n", + " 3 749 \n", + " 4 714 \n", + " 5 Least deprived 693 \n", + " Unknown 196 \n", + "bmi 30+ 1099 \n", + " under 30 2688 \n", + "chronic_cardiac_disease no 3731 \n", + " yes 49 \n", + "current_copd no 3752 \n", + " yes 28 \n", + "dmards no 3738 \n", + " yes 49 \n", + "psychosis_schiz_bipolar no 3738 \n", + " yes 42 \n", + "ssri no 3745 \n", + " yes 35 \n", + "ckd no 2996 \n", + " yes 784 \n", + "\n", + " percent total \\\n", + "category group \n", + "overall overall 60.7 6223 \n", + "sex F 59.6 3206 \n", + " M 61.9 3017 \n", + "ethnicity_6_groups Black 57.4 1036 \n", + " Mixed 62.5 1064 \n", + " Other 60.0 1085 \n", + " South Asian 61.6 1022 \n", + " Unknown 63.2 952 \n", + " White 59.5 1071 \n", + "ethnicity_16_groups African 58.7 322 \n", + " Bangladeshi or British Bangladeshi 58.1 301 \n", + " Caribbean 61.7 329 \n", + " Chinese 59.5 294 \n", + " Other 61.7 329 \n", + " Other Asian 59.1 308 \n", + " British or Mixed British 58.3 336 \n", + " Indian or British Indian 60.9 322 \n", + " Irish 60.4 336 \n", + " Other Black 55.1 343 \n", + " Other White 58.0 350 \n", + " Other mixed 63.6 308 \n", + " Pakistani or British Pakistani 62.7 357 \n", + " Unknown 62.5 952 \n", + " White + Asian 62.5 336 \n", + " White + Black African 63.0 378 \n", + " White + Black Caribbean 59.6 329 \n", + "imd_categories 1 Most deprived 61.1 1225 \n", + " 2 59.5 1141 \n", + " 3 61.8 1211 \n", + " 4 60.4 1183 \n", + " 5 Least deprived 60.7 1141 \n", + " Unknown 60.9 322 \n", + "bmi 30+ 60.9 1806 \n", + " under 30 60.9 4417 \n", + "chronic_cardiac_disease no 60.6 6153 \n", + " yes 63.6 77 \n", + "current_copd no 60.8 6174 \n", + " yes 50.0 56 \n", + "dmards no 60.7 6160 \n", + " yes 70.0 70 \n", + "psychosis_schiz_bipolar no 60.6 6167 \n", + " yes 66.7 63 \n", + "ssri no 60.8 6160 \n", + " yes 50.0 70 \n", + "ckd no 60.6 4942 \n", + " yes 60.9 1288 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.4 \n", + "sex F 58.1 \n", + " M 60.8 \n", + "ethnicity_6_groups Black 56.1 \n", + " Mixed 61.2 \n", + " Other 58.7 \n", + " South Asian 60.3 \n", + " Unknown 62.5 \n", + " White 58.2 \n", + "ethnicity_16_groups African 58.7 \n", + " Bangladeshi or British Bangladeshi 58.1 \n", + " Caribbean 61.7 \n", + " Chinese 57.1 \n", + " Other 61.7 \n", + " Other Asian 59.1 \n", + " British or Mixed British 58.3 \n", + " Indian or British Indian 58.7 \n", + " Irish 60.4 \n", + " Other Black 55.1 \n", + " Other White 56.0 \n", + " Other mixed 61.4 \n", + " Pakistani or British Pakistani 62.7 \n", + " Unknown 61.0 \n", + " White + Asian 60.4 \n", + " White + Black African 61.1 \n", + " White + Black Caribbean 57.4 \n", + "imd_categories 1 Most deprived 59.4 \n", + " 2 57.7 \n", + " 3 60.7 \n", + " 4 59.8 \n", + " 5 Least deprived 59.5 \n", + " Unknown 58.7 \n", + "bmi 30+ 59.7 \n", + " under 30 59.4 \n", + "chronic_cardiac_disease no 59.3 \n", + " yes 63.6 \n", + "current_copd no 59.4 \n", + " yes 50.0 \n", + "dmards no 59.3 \n", + " yes 60.0 \n", + "psychosis_schiz_bipolar no 59.3 \n", + " yes 66.7 \n", + "ssri no 59.4 \n", + " yes 50.0 \n", + "ckd no 59.3 \n", + " yes 59.2 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.3 \n", + "sex F 1.5 \n", + " M 1.1 \n", + "ethnicity_6_groups Black 1.3 \n", + " Mixed 1.3 \n", + " Other 1.3 \n", + " South Asian 1.3 \n", + " Unknown 0.7 \n", + " White 1.3 \n", + "ethnicity_16_groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 0.0 \n", + " Caribbean 0.0 \n", + " Chinese 2.4 \n", + " Other 0.0 \n", + " Other Asian 0.0 \n", + " British or Mixed British 0.0 \n", + " Indian or British Indian 2.2 \n", + " Irish 0.0 \n", + " Other Black 0.0 \n", + " Other White 2.0 \n", + " Other mixed 2.2 \n", + " Pakistani or British Pakistani 0.0 \n", + " Unknown 1.5 \n", + " White + Asian 2.1 \n", + " White + Black African 1.9 \n", + " White + Black Caribbean 2.2 \n", + "imd_categories 1 Most deprived 1.7 \n", + " 2 1.8 \n", + " 3 1.1 \n", + " 4 0.6 \n", + " 5 Least deprived 1.2 \n", + " Unknown 2.2 \n", + "bmi 30+ 1.2 \n", + " under 30 1.5 \n", + "chronic_cardiac_disease no 1.3 \n", + " yes 0.0 \n", + "current_copd no 1.4 \n", + " yes 0.0 \n", + "dmards no 1.4 \n", + " yes 10.0 \n", + "psychosis_schiz_bipolar no 1.3 \n", + " yes 0.0 \n", + "ssri no 1.4 \n", + " yes 0.0 \n", + "ckd no 1.3 \n", + " yes 1.7 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 02-Apr \n", + "sex F 17-Mar \n", + " M unknown \n", + "ethnicity_6_groups Black unknown \n", + " Mixed 24-Mar \n", + " Other 06-Apr \n", + " South Asian 28-Mar \n", + " Unknown unknown \n", + " White 09-Apr \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi unknown \n", + " Caribbean unknown \n", + " Chinese 23-Jan \n", + " Other unknown \n", + " Other Asian unknown \n", + " British or Mixed British unknown \n", + " Indian or British Indian 27-Jan \n", + " Irish unknown \n", + " Other Black unknown \n", + " Other White 16-Feb \n", + " Other mixed 19-Jan \n", + " Pakistani or British Pakistani unknown \n", + " Unknown 04-Mar \n", + " 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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall405360.2672758.61.606-Mar
sexF203059.7340258.01.728-Feb
M201660.6332558.91.725-Feb
ethnicity_6_groupsBlack72160.2119758.51.726-Feb
Mixed68658.3117656.51.827-Feb
Other65858.8112057.51.313-Apr
South Asian66561.7107859.72.003-Feb
Unknown61662.099460.61.416-Mar
White70760.8116259.01.817-Feb
ethnicity_16_groupsAfrican19653.836453.80.0unknown
Bangladeshi or British Bangladeshi20358.035056.02.016-Feb
Caribbean20358.035056.02.016-Feb
Chinese20359.234357.12.106-Feb
Other21060.035058.02.009-Feb
Other Asian23161.137859.31.816-Feb
British or Mixed British21060.035058.02.009-Feb
Indian or British Indian24562.539260.71.810-Feb
Irish20359.234357.12.106-Feb
Other Black23163.536463.50.0unknown
Other White20359.234355.14.118-Dec
Other mixed19656.035056.00.0unknown
Pakistani or British Pakistani24564.837863.01.802-Feb
Unknown63062.1101560.71.415-Mar
White + Asian20358.035056.02.016-Feb
White + Black African22464.035062.02.026-Jan
White + Black Caribbean21057.736455.81.923-Feb
imd_categories1 Most deprived72857.1127456.01.1unknown
277759.7130257.52.231-Jan
378462.6125360.32.318-Jan
477061.1126060.60.5unknown
5 Least deprived75659.7126758.01.728-Feb
Unknown23161.137859.31.816-Feb
bmi30+119060.7196058.91.817-Feb
under 30286360.1476758.41.727-Feb
chronic_cardiac_diseaseno401860.3666458.71.605-Mar
yes2844.46344.40.0unknown
current_copdno400460.2665058.61.606-Mar
yes4254.57754.50.0unknown
dmardsno401860.3666458.61.726-Feb
yes3562.55662.50.0unknown
psychosis_schiz_bipolarno400460.1665758.61.515-Mar
yes4260.07060.00.0unknown
ssrino401160.3665758.71.605-Mar
yes3555.66355.60.0unknown
ckdno324860.4537659.01.424-Mar
yes79859.1135157.02.107-Feb
\n", + "
" + ], + "text/plain": [ + " vaccinated \\\n", + "category group \n", + "overall overall 4053 \n", + "sex F 2030 \n", + " M 2016 \n", + "ethnicity_6_groups Black 721 \n", + " Mixed 686 \n", + " Other 658 \n", + " South Asian 665 \n", + " Unknown 616 \n", + " White 707 \n", + "ethnicity_16_groups African 196 \n", + " Bangladeshi or British Bangladeshi 203 \n", + " Caribbean 203 \n", + " Chinese 203 \n", + " Other 210 \n", + " Other Asian 231 \n", + " British or Mixed British 210 \n", + " Indian or British Indian 245 \n", + " Irish 203 \n", + " Other Black 231 \n", + " Other White 203 \n", + " Other mixed 196 \n", + " Pakistani or British Pakistani 245 \n", + " Unknown 630 \n", + " White + Asian 203 \n", + " White + Black African 224 \n", + " White + Black Caribbean 210 \n", + "imd_categories 1 Most deprived 728 \n", + " 2 777 \n", + " 3 784 \n", + " 4 770 \n", + " 5 Least deprived 756 \n", + " Unknown 231 \n", + "bmi 30+ 1190 \n", + " under 30 2863 \n", + "chronic_cardiac_disease no 4018 \n", + " yes 28 \n", + "current_copd no 4004 \n", + " yes 42 \n", + "dmards no 4018 \n", + " yes 35 \n", + "psychosis_schiz_bipolar no 4004 \n", + " yes 42 \n", + "ssri no 4011 \n", + " yes 35 \n", + "ckd no 3248 \n", + " yes 798 \n", + "\n", + " percent total \\\n", + "category group \n", + "overall overall 60.2 6727 \n", + "sex F 59.7 3402 \n", + " M 60.6 3325 \n", + "ethnicity_6_groups Black 60.2 1197 \n", + " Mixed 58.3 1176 \n", + " Other 58.8 1120 \n", + " South Asian 61.7 1078 \n", + " Unknown 62.0 994 \n", + " White 60.8 1162 \n", + "ethnicity_16_groups African 53.8 364 \n", + " Bangladeshi or British Bangladeshi 58.0 350 \n", + " Caribbean 58.0 350 \n", + " Chinese 59.2 343 \n", + " Other 60.0 350 \n", + " Other Asian 61.1 378 \n", + " British or Mixed British 60.0 350 \n", + " Indian or British Indian 62.5 392 \n", + " Irish 59.2 343 \n", + " Other Black 63.5 364 \n", + " Other White 59.2 343 \n", + " Other mixed 56.0 350 \n", + " Pakistani or British Pakistani 64.8 378 \n", + " Unknown 62.1 1015 \n", + " White + Asian 58.0 350 \n", + " White + Black African 64.0 350 \n", + " White + Black Caribbean 57.7 364 \n", + "imd_categories 1 Most deprived 57.1 1274 \n", + " 2 59.7 1302 \n", + " 3 62.6 1253 \n", + " 4 61.1 1260 \n", + " 5 Least deprived 59.7 1267 \n", + " Unknown 61.1 378 \n", + "bmi 30+ 60.7 1960 \n", + " under 30 60.1 4767 \n", + "chronic_cardiac_disease no 60.3 6664 \n", + " yes 44.4 63 \n", + "current_copd no 60.2 6650 \n", + " yes 54.5 77 \n", + "dmards no 60.3 6664 \n", + " yes 62.5 56 \n", + "psychosis_schiz_bipolar no 60.1 6657 \n", + " yes 60.0 70 \n", + "ssri no 60.3 6657 \n", + " yes 55.6 63 \n", + "ckd no 60.4 5376 \n", + " yes 59.1 1351 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 58.6 \n", + "sex F 58.0 \n", + " M 58.9 \n", + "ethnicity_6_groups Black 58.5 \n", + " Mixed 56.5 \n", + " Other 57.5 \n", + " South Asian 59.7 \n", + " Unknown 60.6 \n", + " White 59.0 \n", + "ethnicity_16_groups African 53.8 \n", + " Bangladeshi or British Bangladeshi 56.0 \n", + " Caribbean 56.0 \n", + " Chinese 57.1 \n", + " Other 58.0 \n", + " Other Asian 59.3 \n", + " British or Mixed British 58.0 \n", + " Indian or British Indian 60.7 \n", + " Irish 57.1 \n", + " Other Black 63.5 \n", + " Other White 55.1 \n", + " Other mixed 56.0 \n", + " Pakistani or British Pakistani 63.0 \n", + " Unknown 60.7 \n", + " White + Asian 56.0 \n", + " White + Black African 62.0 \n", + " White + Black Caribbean 55.8 \n", + "imd_categories 1 Most deprived 56.0 \n", + " 2 57.5 \n", + " 3 60.3 \n", + " 4 60.6 \n", + " 5 Least deprived 58.0 \n", + " Unknown 59.3 \n", + "bmi 30+ 58.9 \n", + " under 30 58.4 \n", + "chronic_cardiac_disease no 58.7 \n", + " yes 44.4 \n", + "current_copd no 58.6 \n", + " yes 54.5 \n", + "dmards no 58.6 \n", + " yes 62.5 \n", + "psychosis_schiz_bipolar no 58.6 \n", + " yes 60.0 \n", + "ssri no 58.7 \n", + " yes 55.6 \n", + "ckd no 59.0 \n", + " yes 57.0 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.6 \n", + "sex F 1.7 \n", + " M 1.7 \n", + "ethnicity_6_groups Black 1.7 \n", + " Mixed 1.8 \n", + " Other 1.3 \n", + " South Asian 2.0 \n", + " Unknown 1.4 \n", + " White 1.8 \n", + "ethnicity_16_groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 2.0 \n", + " Caribbean 2.0 \n", + " Chinese 2.1 \n", + " Other 2.0 \n", + " Other Asian 1.8 \n", + " British or Mixed British 2.0 \n", + " Indian or British Indian 1.8 \n", + " Irish 2.1 \n", + " Other Black 0.0 \n", + " Other White 4.1 \n", + " Other mixed 0.0 \n", + " Pakistani or British Pakistani 1.8 \n", + " Unknown 1.4 \n", + " White + Asian 2.0 \n", + " White + Black African 2.0 \n", + " White + Black Caribbean 1.9 \n", + "imd_categories 1 Most deprived 1.1 \n", + " 2 2.2 \n", + " 3 2.3 \n", + " 4 0.5 \n", + " 5 Least deprived 1.7 \n", + " Unknown 1.8 \n", + "bmi 30+ 1.8 \n", + " under 30 1.7 \n", + "chronic_cardiac_disease no 1.6 \n", + " yes 0.0 \n", + "current_copd no 1.6 \n", + " yes 0.0 \n", + "dmards no 1.7 \n", + " yes 0.0 \n", + "psychosis_schiz_bipolar no 1.5 \n", + " yes 0.0 \n", + "ssri no 1.6 \n", + " yes 0.0 \n", + "ckd no 1.4 \n", + " yes 2.1 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 06-Mar \n", + "sex F 28-Feb \n", + " M 25-Feb \n", + "ethnicity_6_groups Black 26-Feb \n", + " Mixed 27-Feb \n", + " Other 13-Apr \n", + " South Asian 03-Feb \n", + " Unknown 16-Mar \n", + " White 17-Feb \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi 16-Feb \n", + " Caribbean 16-Feb \n", + " Chinese 06-Feb \n", + " Other 09-Feb \n", + " Other Asian 16-Feb \n", + " British or Mixed British 09-Feb \n", + " Indian or British Indian 10-Feb \n", + " Irish 06-Feb \n", + " Other Black unknown \n", + " Other White 18-Dec \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani 02-Feb \n", + " Unknown 15-Mar \n", + " White + Asian 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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall748361.11225759.71.420-Mar
sexF387860.7639159.51.215-Apr
M360561.5586659.91.628-Feb
ethnicity_6_groupsBlack126760.5209359.21.303-Apr
Mixed128161.4208660.11.330-Mar
Other126761.6205860.21.418-Mar
South Asian125360.9205859.21.723-Feb
Unknown116961.6189760.51.1unknown
White124660.3206559.01.304-Apr
ethnicity_16_groupsAfrican37859.363758.21.1unknown
Bangladeshi or British Bangladeshi37157.664456.51.1unknown
Caribbean44862.771460.81.904-Feb
Chinese38560.463760.40.0unknown
Other42061.967960.81.1unknown
Other Asian37860.762359.61.1unknown
British or Mixed British40663.064462.01.0unknown
Indian or British Indian39260.964459.81.1unknown
Irish44163.669361.62.027-Jan
Other Black38557.367256.21.1unknown
Other White41360.268660.20.0unknown
Other mixed38561.163060.01.1unknown
Pakistani or British Pakistani37160.261659.11.1unknown
Unknown113462.3182060.81.505-Mar
White + Asian36461.259560.01.213-Apr
White + Black African39260.265159.11.1unknown
White + Black Caribbean40661.166558.92.226-Jan
imd_categories1 Most deprived144962.3232461.11.206-Apr
2141461.2231060.01.213-Apr
3142161.0233159.51.511-Mar
4139359.9232457.82.104-Feb
5 Least deprived144261.3235260.11.212-Apr
Unknown36459.161656.82.329-Jan
bmi30+225461.6366160.41.210-Apr
under 30522960.9858959.41.511-Mar
chronic_cardiac_diseaseno740661.11211759.71.420-Mar
yes8460.014055.05.008-Dec
current_copdno742061.11214559.71.420-Mar
yes6356.211256.20.0unknown
dmardsno740661.11211759.81.331-Mar
yes7755.014050.05.015-Dec
psychosis_schiz_bipolarno740661.01213859.61.421-Mar
yes7764.711964.70.0unknown
ssrino742761.11215959.71.420-Mar
yes5657.19857.10.0unknown
ckdno598560.9983559.51.421-Mar
yes149861.8242260.11.720-Feb
\n", + "
" + ], + "text/plain": [ + " vaccinated \\\n", + "category group \n", + "overall overall 7483 \n", + "sex F 3878 \n", + " M 3605 \n", + "ethnicity_6_groups Black 1267 \n", + " Mixed 1281 \n", + " Other 1267 \n", + " South Asian 1253 \n", + " Unknown 1169 \n", + " White 1246 \n", + "ethnicity_16_groups African 378 \n", + " Bangladeshi or British Bangladeshi 371 \n", + " Caribbean 448 \n", + " Chinese 385 \n", + " Other 420 \n", + " Other Asian 378 \n", + " British or Mixed British 406 \n", + " Indian or British Indian 392 \n", + " Irish 441 \n", + " Other Black 385 \n", + " Other White 413 \n", + " Other mixed 385 \n", + " Pakistani or British Pakistani 371 \n", + " Unknown 1134 \n", + " White + Asian 364 \n", + " White + Black African 392 \n", + " White + Black Caribbean 406 \n", + "imd_categories 1 Most deprived 1449 \n", + " 2 1414 \n", + " 3 1421 \n", + " 4 1393 \n", + " 5 Least deprived 1442 \n", + " Unknown 364 \n", + "bmi 30+ 2254 \n", + " under 30 5229 \n", + "chronic_cardiac_disease no 7406 \n", + " yes 84 \n", + "current_copd no 7420 \n", + " yes 63 \n", + "dmards no 7406 \n", + " yes 77 \n", + "psychosis_schiz_bipolar no 7406 \n", + " yes 77 \n", + "ssri no 7427 \n", + " yes 56 \n", + "ckd no 5985 \n", + " yes 1498 \n", + "\n", + " percent total \\\n", + "category group \n", + "overall overall 61.1 12257 \n", + "sex F 60.7 6391 \n", + " M 61.5 5866 \n", + "ethnicity_6_groups Black 60.5 2093 \n", + " Mixed 61.4 2086 \n", + " Other 61.6 2058 \n", + " South Asian 60.9 2058 \n", + " Unknown 61.6 1897 \n", + " White 60.3 2065 \n", + "ethnicity_16_groups African 59.3 637 \n", + " Bangladeshi or British Bangladeshi 57.6 644 \n", + " Caribbean 62.7 714 \n", + " Chinese 60.4 637 \n", + " Other 61.9 679 \n", + " Other Asian 60.7 623 \n", + " British or Mixed British 63.0 644 \n", + " Indian or British Indian 60.9 644 \n", + " Irish 63.6 693 \n", + " Other Black 57.3 672 \n", + " Other White 60.2 686 \n", + " Other mixed 61.1 630 \n", + " Pakistani or British Pakistani 60.2 616 \n", + " Unknown 62.3 1820 \n", + " White + Asian 61.2 595 \n", + " White + Black African 60.2 651 \n", + " White + Black Caribbean 61.1 665 \n", + "imd_categories 1 Most deprived 62.3 2324 \n", + " 2 61.2 2310 \n", + " 3 61.0 2331 \n", + " 4 59.9 2324 \n", + " 5 Least deprived 61.3 2352 \n", + " Unknown 59.1 616 \n", + "bmi 30+ 61.6 3661 \n", + " under 30 60.9 8589 \n", + "chronic_cardiac_disease no 61.1 12117 \n", + " yes 60.0 140 \n", + "current_copd no 61.1 12145 \n", + " yes 56.2 112 \n", + "dmards no 61.1 12117 \n", + " yes 55.0 140 \n", + "psychosis_schiz_bipolar no 61.0 12138 \n", + " yes 64.7 119 \n", + "ssri no 61.1 12159 \n", + " yes 57.1 98 \n", + "ckd no 60.9 9835 \n", + " yes 61.8 2422 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.7 \n", + "sex F 59.5 \n", + " M 59.9 \n", + "ethnicity_6_groups Black 59.2 \n", + " Mixed 60.1 \n", + " Other 60.2 \n", + " South Asian 59.2 \n", + " Unknown 60.5 \n", + " White 59.0 \n", + "ethnicity_16_groups African 58.2 \n", + " Bangladeshi or British Bangladeshi 56.5 \n", + " Caribbean 60.8 \n", + " Chinese 60.4 \n", + " Other 60.8 \n", + " Other Asian 59.6 \n", + " British or Mixed British 62.0 \n", + " Indian or British Indian 59.8 \n", + " Irish 61.6 \n", + " Other Black 56.2 \n", + " Other White 60.2 \n", + " Other mixed 60.0 \n", + " Pakistani or British Pakistani 59.1 \n", + " Unknown 60.8 \n", + " White + Asian 60.0 \n", + " White + Black African 59.1 \n", + " White + Black Caribbean 58.9 \n", + "imd_categories 1 Most deprived 61.1 \n", + " 2 60.0 \n", + " 3 59.5 \n", + " 4 57.8 \n", + " 5 Least deprived 60.1 \n", + " Unknown 56.8 \n", + "bmi 30+ 60.4 \n", + " under 30 59.4 \n", + "chronic_cardiac_disease no 59.7 \n", + " yes 55.0 \n", + "current_copd no 59.7 \n", + " yes 56.2 \n", + "dmards no 59.8 \n", + " yes 50.0 \n", + "psychosis_schiz_bipolar no 59.6 \n", + " yes 64.7 \n", + "ssri no 59.7 \n", + " yes 57.1 \n", + "ckd no 59.5 \n", + " yes 60.1 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.4 \n", + "sex F 1.2 \n", + " M 1.6 \n", + "ethnicity_6_groups Black 1.3 \n", + " Mixed 1.3 \n", + " Other 1.4 \n", + " South Asian 1.7 \n", + " Unknown 1.1 \n", + " White 1.3 \n", + "ethnicity_16_groups African 1.1 \n", + " Bangladeshi or British Bangladeshi 1.1 \n", + " Caribbean 1.9 \n", + " Chinese 0.0 \n", + " Other 1.1 \n", + " Other Asian 1.1 \n", + " British or Mixed British 1.0 \n", + " Indian or British Indian 1.1 \n", + " Irish 2.0 \n", + " Other Black 1.1 \n", + " Other White 0.0 \n", + " Other mixed 1.1 \n", + " Pakistani or British Pakistani 1.1 \n", + " Unknown 1.5 \n", + " White + Asian 1.2 \n", + " White + Black African 1.1 \n", + " White + Black Caribbean 2.2 \n", + "imd_categories 1 Most deprived 1.2 \n", + " 2 1.2 \n", + " 3 1.5 \n", + " 4 2.1 \n", + " 5 Least deprived 1.2 \n", + " Unknown 2.3 \n", + "bmi 30+ 1.2 \n", + " under 30 1.5 \n", + "chronic_cardiac_disease no 1.4 \n", + " yes 5.0 \n", + "current_copd no 1.4 \n", + " yes 0.0 \n", + "dmards no 1.3 \n", + " yes 5.0 \n", + "psychosis_schiz_bipolar no 1.4 \n", + " yes 0.0 \n", + "ssri no 1.4 \n", + " yes 0.0 \n", + "ckd no 1.4 \n", + " yes 1.7 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 20-Mar \n", + "sex F 15-Apr \n", + " M 28-Feb \n", + "ethnicity_6_groups Black 03-Apr \n", + " Mixed 30-Mar \n", + " Other 18-Mar \n", + " South Asian 23-Feb \n", + " Unknown unknown \n", + " White 04-Apr \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi unknown \n", + " Caribbean 04-Feb \n", + " Chinese unknown \n", + " Other unknown \n", + " Other Asian unknown \n", + " British or Mixed British unknown \n", + " Indian or British Indian unknown \n", + " Irish 27-Jan \n", + " Other Black unknown \n", + " Other White unknown \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani unknown 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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall785460.61295759.41.216-Apr
sexF410261.0672759.81.214-Apr
M375260.2623058.91.305-Apr
ethnicity_6_groupsBlack134460.2223358.91.305-Apr
Mixed135161.3220560.31.0unknown
Other128860.5212859.21.303-Apr
South Asian137961.2225459.61.602-Mar
Unknown117661.3191859.91.419-Mar
White132359.4222658.21.2unknown
ethnicity_16_groupsAfrican41359.070058.01.0unknown
Bangladeshi or British Bangladeshi41360.268659.21.0unknown
Caribbean40661.765860.61.1unknown
Chinese39957.070056.01.0unknown
Other43463.967962.91.0unknown
Other Asian43460.871458.82.006-Feb
British or Mixed British42759.871458.81.0unknown
Indian or British Indian41360.268659.21.0unknown
Irish40663.064460.92.125-Jan
Other Black42761.669360.61.0unknown
Other White40661.765860.61.1unknown
Other mixed42761.669359.62.003-Feb
Pakistani or British Pakistani44160.073559.01.0unknown
Unknown116260.8191159.31.512-Mar
White + Asian40658.669357.61.0unknown
White + Black African46264.172162.12.025-Jan
White + Black Caribbean39258.966557.91.0unknown
imd_categories1 Most deprived149160.3247159.21.1unknown
2149860.5247859.31.217-Apr
3149160.9245060.00.9unknown
4148460.6245058.91.725-Feb
5 Least deprived148460.9243659.51.421-Mar
Unknown41361.567260.41.1unknown
\n", + "
" + ], + "text/plain": [ + " vaccinated percent \\\n", + "category group \n", + "overall overall 7854 60.6 \n", + "sex F 4102 61.0 \n", + " M 3752 60.2 \n", + "ethnicity_6_groups Black 1344 60.2 \n", + " Mixed 1351 61.3 \n", + " Other 1288 60.5 \n", + " South Asian 1379 61.2 \n", + " Unknown 1176 61.3 \n", + " White 1323 59.4 \n", + "ethnicity_16_groups African 413 59.0 \n", + " Bangladeshi or British Bangladeshi 413 60.2 \n", + " Caribbean 406 61.7 \n", + " Chinese 399 57.0 \n", + " Other 434 63.9 \n", + " Other Asian 434 60.8 \n", + " British or Mixed British 427 59.8 \n", + " Indian or British Indian 413 60.2 \n", + " Irish 406 63.0 \n", + " Other Black 427 61.6 \n", + " Other White 406 61.7 \n", + " Other mixed 427 61.6 \n", + " Pakistani or British Pakistani 441 60.0 \n", + " Unknown 1162 60.8 \n", + " White + Asian 406 58.6 \n", + " White + Black African 462 64.1 \n", + " White + Black Caribbean 392 58.9 \n", + "imd_categories 1 Most deprived 1491 60.3 \n", + " 2 1498 60.5 \n", + " 3 1491 60.9 \n", + " 4 1484 60.6 \n", + " 5 Least deprived 1484 60.9 \n", + " Unknown 413 61.5 \n", + "\n", + " total \\\n", + "category group \n", + "overall overall 12957 \n", + "sex F 6727 \n", + " M 6230 \n", + "ethnicity_6_groups Black 2233 \n", + " Mixed 2205 \n", + " Other 2128 \n", + " South Asian 2254 \n", + " Unknown 1918 \n", + " White 2226 \n", + "ethnicity_16_groups African 700 \n", + " Bangladeshi or British Bangladeshi 686 \n", + " Caribbean 658 \n", + " Chinese 700 \n", + " Other 679 \n", + " Other Asian 714 \n", + " British or Mixed British 714 \n", + " Indian or British Indian 686 \n", + " Irish 644 \n", + " Other Black 693 \n", + " Other White 658 \n", + " Other mixed 693 \n", + " Pakistani or British Pakistani 735 \n", + " Unknown 1911 \n", + " White + Asian 693 \n", + " White + Black African 721 \n", + " White + Black Caribbean 665 \n", + "imd_categories 1 Most deprived 2471 \n", + " 2 2478 \n", + " 3 2450 \n", + " 4 2450 \n", + " 5 Least deprived 2436 \n", + " Unknown 672 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.4 \n", + "sex F 59.8 \n", + " M 58.9 \n", + "ethnicity_6_groups Black 58.9 \n", + " Mixed 60.3 \n", + " Other 59.2 \n", + " South Asian 59.6 \n", + " Unknown 59.9 \n", + " White 58.2 \n", + "ethnicity_16_groups African 58.0 \n", + " Bangladeshi or British Bangladeshi 59.2 \n", + " Caribbean 60.6 \n", + " Chinese 56.0 \n", + " Other 62.9 \n", + " Other Asian 58.8 \n", + " British or Mixed British 58.8 \n", + " Indian or British Indian 59.2 \n", + " Irish 60.9 \n", + " Other Black 60.6 \n", + " Other White 60.6 \n", + " Other mixed 59.6 \n", + " Pakistani or British Pakistani 59.0 \n", + " Unknown 59.3 \n", + " White + Asian 57.6 \n", + " White + Black African 62.1 \n", + " White + Black Caribbean 57.9 \n", + "imd_categories 1 Most deprived 59.2 \n", + " 2 59.3 \n", + " 3 60.0 \n", + " 4 58.9 \n", + " 5 Least deprived 59.5 \n", + " Unknown 60.4 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.2 \n", + "sex F 1.2 \n", + " M 1.3 \n", + "ethnicity_6_groups Black 1.3 \n", + " Mixed 1.0 \n", + " Other 1.3 \n", + " South Asian 1.6 \n", + " Unknown 1.4 \n", + " White 1.2 \n", + "ethnicity_16_groups African 1.0 \n", + " Bangladeshi or British Bangladeshi 1.0 \n", + " Caribbean 1.1 \n", + " Chinese 1.0 \n", + " Other 1.0 \n", + " Other Asian 2.0 \n", + " British or Mixed British 1.0 \n", + " Indian or British Indian 1.0 \n", + " Irish 2.1 \n", + " Other Black 1.0 \n", + " Other White 1.1 \n", + " Other mixed 2.0 \n", + " Pakistani or British Pakistani 1.0 \n", + " Unknown 1.5 \n", + " White + Asian 1.0 \n", + " White + Black African 2.0 \n", + " White + Black Caribbean 1.0 \n", + "imd_categories 1 Most deprived 1.1 \n", + " 2 1.2 \n", + " 3 0.9 \n", + " 4 1.7 \n", + " 5 Least deprived 1.4 \n", + " Unknown 1.1 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 16-Apr \n", + 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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall910060.81496659.31.512-Mar
sexF465560.6768659.11.513-Mar
M444561.0728759.41.602-Mar
ethnicity_6_groupsBlack158962.2255560.81.415-Mar
Mixed156160.6257659.01.604-Mar
Other155460.7256259.01.724-Feb
South Asian153361.0251359.61.421-Mar
Unknown136561.1223359.61.510-Mar
White149859.4252057.81.609-Mar
ethnicity_16_groupsAfrican46959.878458.90.9unknown
Bangladeshi or British Bangladeshi47659.180557.41.703-Mar
Caribbean45558.078456.21.828-Feb
Chinese51162.981261.21.715-Feb
Other47659.679857.91.701-Mar
Other Asian46258.978457.11.824-Feb
British or Mixed British46260.676359.61.0unknown
Indian or British Indian53264.482662.71.709-Feb
Irish47661.877059.12.708-Jan
Other Black49061.479859.61.815-Feb
Other White49061.979160.21.719-Feb
Other mixed49762.879161.90.9unknown
Pakistani or British Pakistani47662.476360.61.811-Feb
Unknown138660.9227559.71.214-Apr
White + Asian48358.582656.81.705-Mar
White + Black African49060.980559.11.817-Feb
White + Black Caribbean46959.379158.40.9unknown
imd_categories1 Most deprived178560.7294059.31.422-Mar
2173661.2283559.51.722-Feb
3170860.1284258.91.219-Apr
4176461.8285660.31.507-Mar
5 Least deprived165959.7277958.41.308-Apr
Unknown44862.172160.21.906-Feb
\n", + "
" + ], + "text/plain": [ + " vaccinated percent \\\n", + "category group \n", + "overall overall 9100 60.8 \n", + "sex F 4655 60.6 \n", + " M 4445 61.0 \n", + "ethnicity_6_groups Black 1589 62.2 \n", + " Mixed 1561 60.6 \n", + " Other 1554 60.7 \n", + " South Asian 1533 61.0 \n", + " Unknown 1365 61.1 \n", + " White 1498 59.4 \n", + "ethnicity_16_groups African 469 59.8 \n", + " Bangladeshi or British Bangladeshi 476 59.1 \n", + " Caribbean 455 58.0 \n", + " Chinese 511 62.9 \n", + " Other 476 59.6 \n", + " Other Asian 462 58.9 \n", + " British or Mixed British 462 60.6 \n", + " Indian or British Indian 532 64.4 \n", + " Irish 476 61.8 \n", + " Other Black 490 61.4 \n", + " Other White 490 61.9 \n", + " Other mixed 497 62.8 \n", + " Pakistani or British Pakistani 476 62.4 \n", + " Unknown 1386 60.9 \n", + " White + Asian 483 58.5 \n", + " White + Black African 490 60.9 \n", + " White + Black Caribbean 469 59.3 \n", + "imd_categories 1 Most deprived 1785 60.7 \n", + " 2 1736 61.2 \n", + " 3 1708 60.1 \n", + " 4 1764 61.8 \n", + " 5 Least deprived 1659 59.7 \n", + " Unknown 448 62.1 \n", + "\n", + " total \\\n", + "category group \n", + "overall overall 14966 \n", + "sex F 7686 \n", + " M 7287 \n", + "ethnicity_6_groups Black 2555 \n", + " Mixed 2576 \n", + " Other 2562 \n", + " South Asian 2513 \n", + " Unknown 2233 \n", + " White 2520 \n", + "ethnicity_16_groups African 784 \n", + " Bangladeshi or British Bangladeshi 805 \n", + " Caribbean 784 \n", + " Chinese 812 \n", + " Other 798 \n", + " Other Asian 784 \n", + " British or Mixed British 763 \n", + " Indian or British Indian 826 \n", + " Irish 770 \n", + " Other Black 798 \n", + " Other White 791 \n", + " Other mixed 791 \n", + " Pakistani or British Pakistani 763 \n", + " Unknown 2275 \n", + " White + Asian 826 \n", + " White + Black African 805 \n", + " White + Black Caribbean 791 \n", + "imd_categories 1 Most deprived 2940 \n", + " 2 2835 \n", + " 3 2842 \n", + " 4 2856 \n", + " 5 Least deprived 2779 \n", + " Unknown 721 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.3 \n", + "sex F 59.1 \n", + " M 59.4 \n", + "ethnicity_6_groups Black 60.8 \n", + " Mixed 59.0 \n", + " Other 59.0 \n", + " South Asian 59.6 \n", + " Unknown 59.6 \n", + " White 57.8 \n", + "ethnicity_16_groups African 58.9 \n", + " Bangladeshi or British Bangladeshi 57.4 \n", + " Caribbean 56.2 \n", + " Chinese 61.2 \n", + " Other 57.9 \n", + " Other Asian 57.1 \n", + " British or Mixed British 59.6 \n", + " Indian or British Indian 62.7 \n", + " Irish 59.1 \n", + " Other Black 59.6 \n", + " Other White 60.2 \n", + " Other mixed 61.9 \n", + " Pakistani or British Pakistani 60.6 \n", + " Unknown 59.7 \n", + " White + Asian 56.8 \n", + " White + Black African 59.1 \n", + " White + Black Caribbean 58.4 \n", + "imd_categories 1 Most deprived 59.3 \n", + " 2 59.5 \n", + " 3 58.9 \n", + " 4 60.3 \n", + " 5 Least deprived 58.4 \n", + " Unknown 60.2 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.5 \n", + "sex F 1.5 \n", + " M 1.6 \n", + "ethnicity_6_groups Black 1.4 \n", + " Mixed 1.6 \n", + " Other 1.7 \n", + " South Asian 1.4 \n", + " Unknown 1.5 \n", + " White 1.6 \n", + "ethnicity_16_groups African 0.9 \n", + " Bangladeshi or British Bangladeshi 1.7 \n", + " Caribbean 1.8 \n", + " Chinese 1.7 \n", + " Other 1.7 \n", + " Other Asian 1.8 \n", + " British or Mixed British 1.0 \n", + " Indian or British Indian 1.7 \n", + " Irish 2.7 \n", + " Other Black 1.8 \n", + " Other White 1.7 \n", + " Other mixed 0.9 \n", + " Pakistani or British Pakistani 1.8 \n", + " Unknown 1.2 \n", + " White + Asian 1.7 \n", + " White + Black African 1.8 \n", + " White + Black Caribbean 0.9 \n", + "imd_categories 1 Most deprived 1.4 \n", + " 2 1.7 \n", + " 3 1.2 \n", + " 4 1.5 \n", + " 5 Least deprived 1.3 \n", + " Unknown 1.9 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 12-Mar \n", + "sex F 13-Mar \n", + " M 02-Mar \n", + "ethnicity_6_groups Black 15-Mar \n", + " Mixed 04-Mar \n", + " Other 24-Feb \n", + " South Asian 21-Mar \n", + " Unknown 10-Mar \n", + " White 09-Mar \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi 03-Mar \n", + " Caribbean 28-Feb \n", + " Chinese 15-Feb \n", + " Other 01-Mar \n", + " Other Asian 24-Feb \n", + " British or Mixed British unknown \n", + " Indian or British Indian 09-Feb \n", + " Irish 08-Jan \n", + " Other Black 15-Feb \n", + " Other White 19-Feb \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani 11-Feb \n", + " Unknown 14-Apr \n", + " White + Asian 05-Mar \n", + " White + Black African 17-Feb \n", + " White + Black Caribbean unknown \n", + "imd_categories 1 Most deprived 22-Mar \n", + " 2 22-Feb \n", + " 3 19-Apr \n", + " 4 07-Mar \n", + " 5 Least deprived 08-Apr \n", + " Unknown 06-Feb " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:644: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out_csv = out_csv.drop(\"Date projected to reach 90%\",1)\n" + ] + } + ], + "source": [ + "\n", + "\n", + "# latest date of 200 days ago is entered as the latest_date when calculating cumulative sums below.\n", + "\n", + "# Seperately, we also ensure that second dose was dated 2 weeks after the start of the campaign, \n", + "# to be consistent with the third doses due calculated above\n", + "df_3rdDUE = df.copy()\n", + "df_3rdDUE.loc[(pd.to_datetime(df_3rdDUE[\"covid_vacc_second_dose_date\"]) <= \"2020-12-21\"), \"covid_vacc_second_dose_date\"] = 0\n", + "\n", + "df_dict_cum_3rdDUE = cumulative_sums(\n", + " df_3rdDUE, groups_of_interest=population_subgroups_third, features_dict=features_dict,\n", + " latest_date=date_3rdDUE,\n", + " reference_column_name=\"covid_vacc_second_dose_date\"\n", + " )\n", + "\n", + "summarised_data_dict_3rdDUE = summarise_data_by_group(\n", + " df_dict_cum_3rdDUE, latest_date=date_3rdDUE,\n", + " groups=population_subgroups_third.keys()\n", + " )\n", + "\n", + "create_detailed_summary_uptake(summarised_data_dict_3rdDUE, formatted_latest_date=date_3rdDUE,\n", + " groups=population_subgroups_third.keys(),\n", + " savepath=savepath, vaccine_type=f\"second_dose_{booster_delay_number}{booster_delay_unit_short}_ago\")" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:192: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out2 = out2.rename(columns={0:\"overall\"}).drop([\"level_0\"],1)\n", + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:412: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out = out.transpose().append(date_reached).transpose().drop(\"weeks_to_target\",1)\n", + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:422: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out2 = out2.loc[out2[reference_column_name]==latest_date].reset_index().set_index(reference_column_name).drop([\"index\"], 1).transpose()\n", + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:440: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out3 = out3.drop([\"Increase in uptake (%)\"],1)\n" + ] + }, + { + "data": { + "text/markdown": [ + "## " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## COVID vaccination rollout (second dose 14w ago) among **80+** population up to 2021-10-27" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- 'Date projected to reach 90%' being 'unknown' indicates projection of >6mo (likely insufficient information)\n", + "- Patient counts rounded to the nearest 7" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + 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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall252059.7422158.01.728-Feb
sexF129559.5217758.51.0unknown
M121859.6204457.91.701-Mar
ageband_5yr04970.07060.010.010-Nov
0-1514054.125954.10.0unknown
16-1715462.924562.90.0unknown
18-2915457.926655.32.621-Jan
30-3416159.027359.00.0unknown
35-3917565.826663.22.631-Dec
40-4416159.027356.42.618-Jan
45-4917562.528062.50.0unknown
50-5415459.525956.82.714-Jan
55-5917558.130158.10.0unknown
60-6414755.326655.30.0unknown
65-6917562.528060.02.512-Jan
70-7417559.529457.12.423-Jan
75-7916860.028057.52.519-Jan
80-8416159.027356.42.618-Jan
85-8916857.129457.10.0unknown
90+2160.03560.00.0unknown
ethnicity_6_groupsBlack46963.873561.91.931-Jan
Mixed40658.070055.03.009-Jan
Other44861.572859.61.909-Feb
South Asian42056.174955.11.0unknown
Unknown36459.860958.61.2unknown
White42058.871457.81.0unknown
ethnicity_16_groupsAfrican11251.621751.60.0unknown
Bangladeshi or British Bangladeshi12660.021060.00.0unknown
Caribbean13361.321758.13.228-Dec
Chinese14064.521764.50.0unknown
Other14761.823858.83.031-Dec
Other Asian13363.321060.03.322-Dec
British or Mixed British12658.121754.83.302-Jan
Indian or British Indian14062.522459.43.128-Dec
Irish14060.623157.63.003-Jan
Other Black13361.321758.13.228-Dec
Other White14058.823858.80.0unknown
Other mixed11255.220355.20.0unknown
Pakistani or British Pakistani14062.522459.43.128-Dec
Unknown41361.567259.42.130-Jan
White + Asian12656.222456.20.0unknown
White + Black African11253.321053.30.0unknown
White + Black Caribbean14758.325258.30.0unknown
imd_categories1 Most deprived49761.780559.12.611-Jan
245556.580555.70.8unknown
346960.477759.50.9unknown
447658.181957.30.8unknown
5 Least deprived49761.281259.51.722-Feb
Unknown11956.721056.70.0unknown
bmi30+77760.0129558.41.607-Mar
under 30174359.6292657.91.701-Mar
houseboundno249259.6417958.11.517-Mar
yes2866.74250.016.705-Nov
chronic_cardiac_diseaseno249259.5418658.01.518-Mar
yes2880.03580.00.0unknown
current_copdno249259.6417958.11.517-Mar
yes2857.14957.10.0unknown
dmardsno248559.6417258.11.517-Mar
yes2857.14957.10.0unknown
dementiano249259.6417958.11.517-Mar
yes2866.74266.70.0unknown
psychosis_schiz_bipolarno249259.6417958.11.517-Mar
yes2866.74266.70.0unknown
LDno245059.3413057.81.519-Mar
yes6364.39864.30.0unknown
ssrino249259.6417958.11.517-Mar
yes2857.14957.10.0unknown
chemo_or_radiono249259.5418658.01.518-Mar
yes2866.74266.70.0unknown
lung_cancerno249959.6419358.11.517-Mar
yes1440.03540.00.0unknown
cancer_excl_lung_and_haemno249959.6419358.11.517-Mar
yes2160.03560.00.0unknown
haematological_cancerno248559.5417958.01.518-Mar
yes2866.74266.70.0unknown
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+ " Date projected to reach 90% \n", + "category group \n", + "overall overall 28-Feb \n", + "sex F unknown \n", + " M 01-Mar \n", + "ageband_5yr 0 10-Nov \n", + " 0-15 unknown \n", + " 16-17 unknown \n", + " 18-29 21-Jan \n", + " 30-34 unknown \n", + " 35-39 31-Dec \n", + " 40-44 18-Jan \n", + " 45-49 unknown \n", + " 50-54 14-Jan \n", + " 55-59 unknown \n", + " 60-64 unknown \n", + " 65-69 12-Jan \n", + " 70-74 23-Jan \n", + " 75-79 19-Jan \n", + " 80-84 18-Jan \n", + " 85-89 unknown \n", + " 90+ unknown \n", + "ethnicity_6_groups Black 31-Jan \n", + " Mixed 09-Jan \n", + " Other 09-Feb \n", + " South Asian unknown \n", + " Unknown unknown \n", + " White unknown \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi unknown \n", + " Caribbean 28-Dec \n", + " Chinese unknown \n", + " Other 31-Dec \n", + " Other Asian 22-Dec \n", + " British or Mixed British 02-Jan \n", + " Indian or British Indian 28-Dec \n", + " Irish 03-Jan \n", + " Other Black 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"cancer_excl_lung_and_haem no 17-Mar \n", + " yes unknown \n", + "haematological_cancer no 18-Mar \n", + " yes unknown \n", + "ckd no unknown \n", + " yes 02-Mar " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:644: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out_csv = out_csv.drop(\"Date projected to reach 90%\",1)\n" + ] + }, + { + "data": { + "text/markdown": [ + "## " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## COVID vaccination rollout (second dose 14w ago) among **70-79** population up to 2021-10-27" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- 'Date projected to reach 90%' being 'unknown' indicates projection of >6mo (likely insufficient information)\n", + "- Patient counts rounded to the nearest 7" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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" \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", "
vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
categorygroup
overalloverall406059.2686057.81.430-Mar
sexF210059.3354257.91.429-Mar
M196059.1331857.61.520-Mar
ageband_5yr04958.38458.30.0unknown
0-1525259.042759.00.0unknown
16-1727360.045556.93.102-Jan
18-2926661.343461.30.0unknown
30-3428059.746958.21.517-Mar
35-3928762.146260.61.506-Mar
40-4425258.143456.51.615-Mar
45-4925957.844856.21.616-Mar
50-5425959.743458.11.608-Mar
55-5925255.445553.81.627-Mar
60-6427360.944859.41.511-Mar
65-6926659.444857.81.609-Mar
70-7424556.543456.50.0unknown
75-7927360.045558.51.516-Mar
80-8426660.344158.71.605-Mar
85-8925957.844856.21.616-Mar
90+4958.38458.3unknown
Other White7058.811958.8ethnicity_6_groupsBlack65857.0115555.81.2unknown
Mixed72861.2119060.01.213-Apr
Other69358.9117657.11.824-Feb
South Asian73561.0120459.91.1unknown
Unknown58857.1102955.81.3unknown
White65159.2109958.01.2unknown
ethnicity_16_groupsAfrican22462.735760.81.904-Feb
Bangladeshi or British Bangladeshi18954.035052.02.002-Mar
Caribbean21758.537156.61.920-Feb
Chinese24567.336465.41.918-Jan
Other21056.637156.60.0unknown
Other Asian21759.636457.71.916-Feb
British or Mixed British22465.334363.32.021-Jan
Indian or British Indian21758.537158.50.0unknown
Other mixed5653.310553.3Irish21057.736455.81.923-Feb
Other Black21057.736455.81.923-Feb
Other White21057.736457.70.0unknown
Other mixed20358.035056.02.016-Feb
Pakistani or British Pakistani6356.211256.219659.632959.60.0unknown
Unknown18253.134351.02.109-Jan58157.2101555.22.018-Feb
White + Asian8470.611964.75.901-Oct23861.838560.01.813-Feb
White + Black African6360.010560.00.0unknown23860.739258.91.817-Feb
White + Black Caribbean8460.014060.00.0unknown23859.639957.91.701-Mar
imd_categories1 Most deprived24558.342056.777759.7130258.11.624-Jan08-Mar
224560.340658.61.708-Jan77757.8134456.21.616-Mar
322457.139255.41.721-Jan74257.9128156.31.616-Mar
423855.742754.181261.7131660.11.605-Feb27-Feb
5 Least deprived22457.139255.41.721-Jan75659.0128158.50.5unknown
Unknown5653.310553.30.0unknown19659.632957.42.231-Jan
bmi30+32955.359554.11.2122559.3206558.31.0unknown
under 3089657.9154756.61.327-Feb283559.2478857.71.519-Mar
houseboundno121157.3211455.61.720-Jan401859.2678357.91.310-Apr
yes2175.02875.04260.07060.00.0unknown
chronic_cardiac_diseaseno121857.4212155.81.628-Jan402559.2679757.81.430-Mar
yes1466.72166.73555.66355.60.0unknown
current_copdno121857.6211456.01.627-Jan401159.2677657.71.519-Mar
yes1466.72166.74958.38458.30.0unknown
dmardsno121857.6211456.01.627-Jan401859.2679057.71.519-Mar
yes1450.02825.025.019-Sep4970.07070.00.0unknown
dementiano121857.4212155.42.031-Dec401859.3677657.91.429-Mar
yes1466.72166.74963.67763.60.0unknown
psychosis_schiz_bipolarno121857.4212155.81.628-Jan403259.4679057.91.518-Mar
yes1466.72166.73550.07050.00.0unknown
LDno121157.7210056.01.719-Jan399059.3672757.91.429-Mar
yes2150.04233.316.724-Sep7052.613352.60.0unknown
ssrino121857.2212855.61.629-Jan402559.3679057.81.519-Mar
yes750.01450.04260.07060.00.0unknown
chemo_or_radiono121857.4212155.81.628-Jan401859.2679057.81.430-Mar
yes733.32133.34260.07060.00.0unknown
lung_cancerno121157.1212155.41.721-Jan401859.2679057.71.519-Mar
yes144266.7216366.70.0unknown
cancer_excl_lung_and_haemno121857.4212155.81.628-Jan401859.2679057.71.519-Mar
yes1466.72166.74260.07060.00.0unknown
haematological_cancerno121157.1212155.41.721-Jan401859.2678357.81.430-Mar
yes1466.72166.74260.07060.00.0unknown
ckdno98757.3172255.71.629-Jan325559.4548157.91.518-Mar
yes23856.742056.70.0unknown81258.9137957.41.521-Mar
\n", @@ -41832,403 +53766,403 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1232 \n", - "sex F 651 \n", - " M 581 \n", - "ageband_5yr 0 14 \n", - " 0-15 63 \n", - " 16-17 70 \n", - " 18-29 84 \n", - " 30-34 77 \n", - " 35-39 91 \n", - " 40-44 84 \n", - " 45-49 70 \n", - " 50-54 91 \n", - " 55-59 84 \n", - " 60-64 63 \n", - " 65-69 84 \n", - " 70-74 84 \n", - " 75-79 77 \n", - " 80-84 91 \n", - " 85-89 91 \n", - " 90+ 7 \n", - "ethnicity_6_groups Black 210 \n", - " Mixed 203 \n", - " Other 175 \n", - " South Asian 224 \n", - " Unknown 189 \n", - " White 231 \n", - "ethnicity_16_groups African 63 \n", - " Bangladeshi or British Bangladeshi 56 \n", - " Caribbean 56 \n", - " Chinese 63 \n", - " Other 70 \n", - " Other Asian 63 \n", - " British or Mixed British 77 \n", - " Indian or British Indian 70 \n", - " Irish 63 \n", - " Other Black 49 \n", - " Other White 70 \n", - " Other mixed 56 \n", - " Pakistani or British Pakistani 63 \n", - " Unknown 182 \n", - " White + Asian 84 \n", - " White + Black African 63 \n", - " White + Black Caribbean 84 \n", - "imd_categories 1 Most deprived 245 \n", - " 2 245 \n", - " 3 224 \n", - " 4 238 \n", - " 5 Least deprived 224 \n", - " Unknown 56 \n", - "bmi 30+ 329 \n", - " under 30 896 \n", - "housebound no 1211 \n", - " yes 21 \n", - "chronic_cardiac_disease no 1218 \n", - " yes 14 \n", - "current_copd no 1218 \n", - " yes 14 \n", - "dmards no 1218 \n", - " yes 14 \n", - "dementia no 1218 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1218 \n", - " yes 14 \n", - "LD no 1211 \n", - " yes 21 \n", - "ssri no 1218 \n", - " yes 7 \n", - "chemo_or_radio no 1218 \n", - " yes 7 \n", - "lung_cancer no 1211 \n", - " yes 14 \n", - "cancer_excl_lung_and_haem no 1218 \n", - " yes 14 \n", - "haematological_cancer no 1211 \n", - " yes 14 \n", - "ckd no 987 \n", - " yes 238 \n", + "overall overall 4060 \n", + "sex F 2100 \n", + " M 1960 \n", + "ageband_5yr 0 49 \n", + " 0-15 252 \n", + " 16-17 273 \n", + " 18-29 266 \n", + " 30-34 280 \n", + " 35-39 287 \n", + " 40-44 252 \n", + " 45-49 259 \n", + " 50-54 259 \n", + " 55-59 252 \n", + " 60-64 273 \n", + " 65-69 266 \n", + " 70-74 245 \n", + " 75-79 273 \n", + " 80-84 266 \n", + " 85-89 259 \n", + " 90+ 49 \n", + "ethnicity_6_groups Black 658 \n", + " Mixed 728 \n", + " Other 693 \n", + " South Asian 735 \n", + " Unknown 588 \n", + " White 651 \n", + "ethnicity_16_groups African 224 \n", + " Bangladeshi or British Bangladeshi 189 \n", + " Caribbean 217 \n", + " Chinese 245 \n", + " Other 210 \n", + " Other Asian 217 \n", + " British or Mixed British 224 \n", + " Indian or British Indian 217 \n", + " Irish 210 \n", + " Other Black 210 \n", + " Other White 210 \n", + " Other mixed 203 \n", + " Pakistani or British Pakistani 196 \n", + " Unknown 581 \n", + " White + Asian 238 \n", + " White + Black African 238 \n", + " White + Black Caribbean 238 \n", + "imd_categories 1 Most deprived 777 \n", + " 2 777 \n", + " 3 742 \n", + " 4 812 \n", + " 5 Least deprived 756 \n", + " Unknown 196 \n", + "bmi 30+ 1225 \n", + " under 30 2835 \n", + "housebound no 4018 \n", + " yes 42 \n", + "chronic_cardiac_disease no 4025 \n", + " yes 35 \n", + "current_copd no 4011 \n", + " yes 49 \n", + "dmards no 4018 \n", + " yes 49 \n", + "dementia no 4018 \n", + " yes 49 \n", + "psychosis_schiz_bipolar no 4032 \n", + " yes 35 \n", + "LD no 3990 \n", + " yes 70 \n", + "ssri no 4025 \n", + " yes 42 \n", + "chemo_or_radio no 4018 \n", + " yes 42 \n", + "lung_cancer no 4018 \n", + " yes 42 \n", + "cancer_excl_lung_and_haem no 4018 \n", + " yes 42 \n", + "haematological_cancer no 4018 \n", + " yes 42 \n", + "ckd no 3255 \n", + " yes 812 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 57.5 2142 \n", - "sex F 57.8 1127 \n", - " M 57.2 1015 \n", - "ageband_5yr 0 50.0 28 \n", - " 0-15 56.2 112 \n", - " 16-17 50.0 140 \n", - " 18-29 63.2 133 \n", - " 30-34 55.0 140 \n", - " 35-39 61.9 147 \n", - " 40-44 57.1 147 \n", - " 45-49 52.6 133 \n", - " 50-54 59.1 154 \n", - " 55-59 54.5 154 \n", - " 60-64 50.0 126 \n", - " 65-69 60.0 140 \n", - " 70-74 60.0 140 \n", - " 75-79 57.9 133 \n", - " 80-84 65.0 140 \n", - " 85-89 59.1 154 \n", - " 90+ 33.3 21 \n", - "ethnicity_6_groups Black 58.8 357 \n", - " Mixed 58.0 350 \n", - " Other 52.1 336 \n", - " South Asian 61.5 364 \n", - " Unknown 55.1 343 \n", - " White 58.9 392 \n", - "ethnicity_16_groups African 60.0 105 \n", - " Bangladeshi or British Bangladeshi 47.1 119 \n", - " Caribbean 57.1 98 \n", - " Chinese 60.0 105 \n", - " Other 62.5 112 \n", - " Other Asian 56.2 112 \n", - " British or Mixed British 57.9 133 \n", - " Indian or British Indian 66.7 105 \n", - " Irish 52.9 119 \n", - " Other Black 58.3 84 \n", - " Other White 58.8 119 \n", - " Other mixed 53.3 105 \n", - " Pakistani or British Pakistani 56.2 112 \n", - " Unknown 53.1 343 \n", - " White + Asian 70.6 119 \n", - " White + Black African 60.0 105 \n", - " White + Black Caribbean 60.0 140 \n", - "imd_categories 1 Most deprived 58.3 420 \n", - " 2 60.3 406 \n", - " 3 57.1 392 \n", - " 4 55.7 427 \n", - " 5 Least deprived 57.1 392 \n", - " Unknown 53.3 105 \n", - "bmi 30+ 55.3 595 \n", - " under 30 57.9 1547 \n", - "housebound no 57.3 2114 \n", - " yes 75.0 28 \n", - "chronic_cardiac_disease no 57.4 2121 \n", - " yes 66.7 21 \n", - "current_copd no 57.6 2114 \n", - " yes 66.7 21 \n", - "dmards no 57.6 2114 \n", - " yes 50.0 28 \n", - "dementia no 57.4 2121 \n", - " yes 66.7 21 \n", - "psychosis_schiz_bipolar no 57.4 2121 \n", - " yes 66.7 21 \n", - "LD no 57.7 2100 \n", - " yes 50.0 42 \n", - "ssri no 57.2 2128 \n", - " yes 50.0 14 \n", - "chemo_or_radio no 57.4 2121 \n", - " yes 33.3 21 \n", - "lung_cancer no 57.1 2121 \n", - " yes 66.7 21 \n", - "cancer_excl_lung_and_haem no 57.4 2121 \n", - " yes 66.7 21 \n", - "haematological_cancer no 57.1 2121 \n", - " yes 66.7 21 \n", - "ckd no 57.3 1722 \n", - " yes 56.7 420 \n", + "overall overall 59.2 6860 \n", + "sex F 59.3 3542 \n", + " M 59.1 3318 \n", + "ageband_5yr 0 58.3 84 \n", + " 0-15 59.0 427 \n", + " 16-17 60.0 455 \n", + " 18-29 61.3 434 \n", + " 30-34 59.7 469 \n", + " 35-39 62.1 462 \n", + " 40-44 58.1 434 \n", + " 45-49 57.8 448 \n", + " 50-54 59.7 434 \n", + " 55-59 55.4 455 \n", + " 60-64 60.9 448 \n", + " 65-69 59.4 448 \n", + " 70-74 56.5 434 \n", + " 75-79 60.0 455 \n", + " 80-84 60.3 441 \n", + " 85-89 57.8 448 \n", + " 90+ 58.3 84 \n", + "ethnicity_6_groups Black 57.0 1155 \n", + " Mixed 61.2 1190 \n", + " Other 58.9 1176 \n", + " South Asian 61.0 1204 \n", + " Unknown 57.1 1029 \n", + " White 59.2 1099 \n", + "ethnicity_16_groups African 62.7 357 \n", + " Bangladeshi or British Bangladeshi 54.0 350 \n", + " Caribbean 58.5 371 \n", + " Chinese 67.3 364 \n", + " Other 56.6 371 \n", + " Other Asian 59.6 364 \n", + " British or Mixed British 65.3 343 \n", + " Indian or British Indian 58.5 371 \n", + " Irish 57.7 364 \n", + " Other Black 57.7 364 \n", + " Other White 57.7 364 \n", + " Other mixed 58.0 350 \n", + " Pakistani or British Pakistani 59.6 329 \n", + " Unknown 57.2 1015 \n", + " White + Asian 61.8 385 \n", + " White + Black African 60.7 392 \n", + " White + Black Caribbean 59.6 399 \n", + "imd_categories 1 Most deprived 59.7 1302 \n", + " 2 57.8 1344 \n", + " 3 57.9 1281 \n", + " 4 61.7 1316 \n", + " 5 Least deprived 59.0 1281 \n", + " Unknown 59.6 329 \n", + "bmi 30+ 59.3 2065 \n", + " under 30 59.2 4788 \n", + "housebound no 59.2 6783 \n", + " yes 60.0 70 \n", + "chronic_cardiac_disease no 59.2 6797 \n", + " yes 55.6 63 \n", + "current_copd no 59.2 6776 \n", + " yes 58.3 84 \n", + "dmards no 59.2 6790 \n", + " yes 70.0 70 \n", + "dementia no 59.3 6776 \n", + " yes 63.6 77 \n", + "psychosis_schiz_bipolar no 59.4 6790 \n", + " yes 50.0 70 \n", + "LD no 59.3 6727 \n", + " yes 52.6 133 \n", + "ssri no 59.3 6790 \n", + " yes 60.0 70 \n", + "chemo_or_radio no 59.2 6790 \n", + " yes 60.0 70 \n", + "lung_cancer no 59.2 6790 \n", + " yes 66.7 63 \n", + "cancer_excl_lung_and_haem no 59.2 6790 \n", + " yes 60.0 70 \n", + "haematological_cancer no 59.2 6783 \n", + " yes 60.0 70 \n", + "ckd no 59.4 5481 \n", + " yes 58.9 1379 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 55.9 \n", - "sex F 55.9 \n", - " M 55.9 \n", - "ageband_5yr 0 50.0 \n", - " 0-15 56.2 \n", - " 16-17 50.0 \n", - " 18-29 57.9 \n", - " 30-34 50.0 \n", - " 35-39 61.9 \n", - " 40-44 57.1 \n", - " 45-49 47.4 \n", - " 50-54 54.5 \n", - " 55-59 54.5 \n", - " 60-64 50.0 \n", - " 65-69 60.0 \n", - " 70-74 60.0 \n", - " 75-79 57.9 \n", - " 80-84 65.0 \n", - " 85-89 54.5 \n", - " 90+ 33.3 \n", - "ethnicity_6_groups Black 56.9 \n", - " Mixed 56.0 \n", - " Other 52.1 \n", - " South Asian 59.6 \n", - " Unknown 53.1 \n", - " White 58.9 \n", - "ethnicity_16_groups African 53.3 \n", - " Bangladeshi or British Bangladeshi 47.1 \n", - " Caribbean 57.1 \n", - " Chinese 60.0 \n", - " Other 56.2 \n", - " Other Asian 56.2 \n", - " British or Mixed British 52.6 \n", - " Indian or British Indian 66.7 \n", - " Irish 52.9 \n", - " Other Black 58.3 \n", - " Other White 58.8 \n", - " Other mixed 53.3 \n", - " Pakistani or British Pakistani 56.2 \n", - " Unknown 51.0 \n", - " White + Asian 64.7 \n", - " White + Black African 60.0 \n", - " White + Black Caribbean 60.0 \n", - "imd_categories 1 Most deprived 56.7 \n", - " 2 58.6 \n", - " 3 55.4 \n", - " 4 54.1 \n", - " 5 Least deprived 55.4 \n", - " Unknown 53.3 \n", - "bmi 30+ 54.1 \n", - " under 30 56.6 \n", - "housebound no 55.6 \n", - " yes 75.0 \n", - "chronic_cardiac_disease no 55.8 \n", - " yes 66.7 \n", - "current_copd no 56.0 \n", - " yes 66.7 \n", - "dmards no 56.0 \n", - " yes 25.0 \n", - "dementia no 55.4 \n", - " yes 66.7 \n", - "psychosis_schiz_bipolar no 55.8 \n", - " yes 66.7 \n", - "LD no 56.0 \n", - " yes 33.3 \n", - "ssri no 55.6 \n", + "overall overall 57.8 \n", + "sex F 57.9 \n", + " M 57.6 \n", + "ageband_5yr 0 58.3 \n", + " 0-15 59.0 \n", + " 16-17 56.9 \n", + " 18-29 61.3 \n", + " 30-34 58.2 \n", + " 35-39 60.6 \n", + " 40-44 56.5 \n", + " 45-49 56.2 \n", + " 50-54 58.1 \n", + " 55-59 53.8 \n", + " 60-64 59.4 \n", + " 65-69 57.8 \n", + " 70-74 56.5 \n", + " 75-79 58.5 \n", + " 80-84 58.7 \n", + " 85-89 56.2 \n", + " 90+ 58.3 \n", + "ethnicity_6_groups Black 55.8 \n", + " Mixed 60.0 \n", + " Other 57.1 \n", + " South Asian 59.9 \n", + " Unknown 55.8 \n", + " White 58.0 \n", + "ethnicity_16_groups African 60.8 \n", + " Bangladeshi or British Bangladeshi 52.0 \n", + " Caribbean 56.6 \n", + " Chinese 65.4 \n", + " Other 56.6 \n", + " Other Asian 57.7 \n", + " British or Mixed British 63.3 \n", + " Indian or British Indian 58.5 \n", + " Irish 55.8 \n", + " Other Black 55.8 \n", + " Other White 57.7 \n", + " Other mixed 56.0 \n", + " Pakistani or British Pakistani 59.6 \n", + " Unknown 55.2 \n", + " White + Asian 60.0 \n", + " White + Black African 58.9 \n", + " White + Black Caribbean 57.9 \n", + "imd_categories 1 Most deprived 58.1 \n", + " 2 56.2 \n", + " 3 56.3 \n", + " 4 60.1 \n", + " 5 Least deprived 58.5 \n", + " Unknown 57.4 \n", + "bmi 30+ 58.3 \n", + " under 30 57.7 \n", + "housebound no 57.9 \n", + " yes 60.0 \n", + "chronic_cardiac_disease no 57.8 \n", + " yes 55.6 \n", + "current_copd no 57.7 \n", + " yes 58.3 \n", + "dmards no 57.7 \n", + " yes 70.0 \n", + "dementia no 57.9 \n", + " yes 63.6 \n", + "psychosis_schiz_bipolar no 57.9 \n", " yes 50.0 \n", - "chemo_or_radio no 55.8 \n", - " yes 33.3 \n", - "lung_cancer no 55.4 \n", - " yes 66.7 \n", - "cancer_excl_lung_and_haem no 55.8 \n", - " yes 66.7 \n", - "haematological_cancer no 55.4 \n", + "LD no 57.9 \n", + " yes 52.6 \n", + "ssri no 57.8 \n", + " yes 60.0 \n", + "chemo_or_radio no 57.8 \n", + " yes 60.0 \n", + "lung_cancer no 57.7 \n", " yes 66.7 \n", - "ckd no 55.7 \n", - " yes 56.7 \n", + "cancer_excl_lung_and_haem no 57.7 \n", + " yes 60.0 \n", + "haematological_cancer no 57.8 \n", + " yes 60.0 \n", + "ckd no 57.9 \n", + " yes 57.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.6 \n", - "sex F 1.9 \n", - " M 1.3 \n", + "overall overall 1.4 \n", + "sex F 1.4 \n", + " M 1.5 \n", "ageband_5yr 0 0.0 \n", " 0-15 0.0 \n", - " 16-17 0.0 \n", - " 18-29 5.3 \n", - " 30-34 5.0 \n", - " 35-39 0.0 \n", - " 40-44 0.0 \n", - " 45-49 5.2 \n", - " 50-54 4.6 \n", - " 55-59 0.0 \n", - " 60-64 0.0 \n", - " 65-69 0.0 \n", + " 16-17 3.1 \n", + " 18-29 0.0 \n", + " 30-34 1.5 \n", + " 35-39 1.5 \n", + " 40-44 1.6 \n", + " 45-49 1.6 \n", + " 50-54 1.6 \n", + " 55-59 1.6 \n", + " 60-64 1.5 \n", + " 65-69 1.6 \n", " 70-74 0.0 \n", - " 75-79 0.0 \n", - " 80-84 0.0 \n", - " 85-89 4.6 \n", + " 75-79 1.5 \n", + " 80-84 1.6 \n", + " 85-89 1.6 \n", " 90+ 0.0 \n", - "ethnicity_6_groups Black 1.9 \n", - " Mixed 2.0 \n", - " Other 0.0 \n", - " South Asian 1.9 \n", - " Unknown 2.0 \n", - " White 0.0 \n", - "ethnicity_16_groups African 6.7 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", - " Chinese 0.0 \n", - " Other 6.3 \n", - " Other Asian 0.0 \n", - " British or Mixed British 5.3 \n", + "ethnicity_6_groups Black 1.2 \n", + " Mixed 1.2 \n", + " Other 1.8 \n", + " South Asian 1.1 \n", + " Unknown 1.3 \n", + " White 1.2 \n", + "ethnicity_16_groups African 1.9 \n", + " Bangladeshi or British Bangladeshi 2.0 \n", + " Caribbean 1.9 \n", + " Chinese 1.9 \n", + " Other 0.0 \n", + " Other Asian 1.9 \n", + " British or Mixed British 2.0 \n", " Indian or British Indian 0.0 \n", - " Irish 0.0 \n", - " Other Black 0.0 \n", + " Irish 1.9 \n", + " Other Black 1.9 \n", " Other White 0.0 \n", - " Other mixed 0.0 \n", + " Other mixed 2.0 \n", " Pakistani or British Pakistani 0.0 \n", - " Unknown 2.1 \n", - " White + Asian 5.9 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", + " Unknown 2.0 \n", + " White + Asian 1.8 \n", + " White + Black African 1.8 \n", + " White + Black Caribbean 1.7 \n", "imd_categories 1 Most deprived 1.6 \n", - " 2 1.7 \n", - " 3 1.7 \n", + " 2 1.6 \n", + " 3 1.6 \n", " 4 1.6 \n", - " 5 Least deprived 1.7 \n", - " Unknown 0.0 \n", - "bmi 30+ 1.2 \n", - " under 30 1.3 \n", - "housebound no 1.7 \n", + " 5 Least deprived 0.5 \n", + " Unknown 2.2 \n", + "bmi 30+ 1.0 \n", + " under 30 1.5 \n", + "housebound no 1.3 \n", " yes 0.0 \n", - "chronic_cardiac_disease no 1.6 \n", + "chronic_cardiac_disease no 1.4 \n", " yes 0.0 \n", - "current_copd no 1.6 \n", + "current_copd no 1.5 \n", " yes 0.0 \n", - "dmards no 1.6 \n", - " yes 25.0 \n", - "dementia no 2.0 \n", + "dmards no 1.5 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.6 \n", + "dementia no 1.4 \n", " yes 0.0 \n", - "LD no 1.7 \n", - " yes 16.7 \n", - "ssri no 1.6 \n", + "psychosis_schiz_bipolar no 1.5 \n", " yes 0.0 \n", - "chemo_or_radio no 1.6 \n", + "LD no 1.4 \n", " yes 0.0 \n", - "lung_cancer no 1.7 \n", + "ssri no 1.5 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.6 \n", + "chemo_or_radio no 1.4 \n", " yes 0.0 \n", - "haematological_cancer no 1.7 \n", + "lung_cancer no 1.5 \n", " yes 0.0 \n", - "ckd no 1.6 \n", + "cancer_excl_lung_and_haem no 1.5 \n", " yes 0.0 \n", + "haematological_cancer no 1.4 \n", + " yes 0.0 \n", + "ckd no 1.5 \n", + " yes 1.5 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 28-Jan \n", - "sex F 04-Jan \n", - " M unknown \n", + "overall overall 30-Mar \n", + "sex F 29-Mar \n", + " M 20-Mar \n", "ageband_5yr 0 unknown \n", " 0-15 unknown \n", - " 16-17 unknown \n", - " 18-29 13-Oct \n", - " 30-34 27-Oct \n", - " 35-39 unknown \n", - " 40-44 unknown \n", - " 45-49 28-Oct \n", - " 50-54 25-Oct \n", - " 55-59 unknown \n", - " 60-64 unknown \n", - " 65-69 unknown \n", + " 16-17 02-Jan \n", + " 18-29 unknown \n", + " 30-34 17-Mar \n", + " 35-39 06-Mar \n", + " 40-44 15-Mar \n", + " 45-49 16-Mar \n", + " 50-54 08-Mar \n", + " 55-59 27-Mar \n", + " 60-64 11-Mar \n", + " 65-69 09-Mar \n", " 70-74 unknown \n", - " 75-79 unknown \n", - " 80-84 unknown \n", - " 85-89 25-Oct \n", + " 75-79 16-Mar \n", + " 80-84 05-Mar \n", + " 85-89 16-Mar \n", " 90+ unknown \n", - "ethnicity_6_groups Black 31-Dec \n", - " Mixed 29-Dec \n", - " Other unknown \n", - " South Asian 22-Dec \n", - " Unknown 08-Jan \n", + "ethnicity_6_groups Black unknown \n", + " Mixed 13-Apr \n", + " Other 24-Feb \n", + " South Asian unknown \n", + " Unknown unknown \n", " White unknown \n", - "ethnicity_16_groups African 09-Oct \n", - " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean unknown \n", - " Chinese unknown \n", - " Other 08-Oct \n", - " Other Asian unknown \n", - " British or Mixed British 20-Oct \n", + "ethnicity_16_groups African 04-Feb \n", + " Bangladeshi or British Bangladeshi 02-Mar \n", + " Caribbean 20-Feb \n", + " Chinese 18-Jan \n", + " Other unknown \n", + " Other Asian 16-Feb \n", + " British or Mixed British 21-Jan \n", " Indian or British Indian unknown \n", - " Irish unknown \n", - " Other Black unknown \n", + " Irish 23-Feb \n", + " Other Black 23-Feb \n", " Other White unknown \n", - " Other mixed unknown \n", + " Other mixed 16-Feb \n", " Pakistani or British Pakistani unknown \n", - " Unknown 09-Jan \n", - " White + Asian 01-Oct \n", - " White + Black African unknown \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived 24-Jan \n", - " 2 08-Jan \n", - " 3 21-Jan \n", - " 4 05-Feb \n", - " 5 Least deprived 21-Jan \n", - " Unknown unknown \n", + " Unknown 18-Feb \n", + " White + Asian 13-Feb \n", + " White + Black African 17-Feb \n", + " White + Black Caribbean 01-Mar \n", + "imd_categories 1 Most deprived 08-Mar \n", + " 2 16-Mar \n", + " 3 16-Mar \n", + " 4 27-Feb \n", + " 5 Least deprived unknown \n", + " Unknown 31-Jan \n", "bmi 30+ unknown \n", - " under 30 27-Feb \n", - "housebound no 20-Jan \n", + " under 30 19-Mar \n", + "housebound no 10-Apr \n", " yes unknown \n", - "chronic_cardiac_disease no 28-Jan \n", + "chronic_cardiac_disease no 30-Mar \n", " yes unknown \n", - "current_copd no 27-Jan \n", + "current_copd no 19-Mar \n", " yes unknown \n", - "dmards no 27-Jan \n", - " yes 19-Sep \n", - "dementia no 31-Dec \n", + "dmards no 19-Mar \n", " yes unknown \n", - "psychosis_schiz_bipolar no 28-Jan \n", + "dementia no 29-Mar \n", " yes unknown \n", - "LD no 19-Jan \n", - " yes 24-Sep \n", - "ssri no 29-Jan \n", + "psychosis_schiz_bipolar no 18-Mar \n", " yes unknown \n", - "chemo_or_radio no 28-Jan \n", + "LD no 29-Mar \n", " yes unknown \n", - "lung_cancer no 21-Jan \n", + "ssri no 19-Mar \n", " yes unknown \n", - "cancer_excl_lung_and_haem no 28-Jan \n", + "chemo_or_radio no 30-Mar \n", " yes unknown \n", - "haematological_cancer no 21-Jan \n", + "lung_cancer no 19-Mar \n", " yes unknown \n", - "ckd no 29-Jan \n", - " yes unknown " + "cancer_excl_lung_and_haem no 19-Mar \n", + " yes unknown \n", + "haematological_cancer no 30-Mar \n", + " yes unknown \n", + "ckd no 18-Mar \n", + " yes 21-Mar " ] }, "metadata": {}, @@ -42257,7 +54191,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose 14weeks ago) among **70-79** population up to 2021-09-08" + "## COVID vaccination rollout (second dose 14w ago) among **care home** population up to 2021-10-27" ], "text/plain": [ "" @@ -42323,253 +54257,125 @@ " \n", " overall\n", " overall\n", - " 2016\n", - " 57.9\n", - " 3479\n", - " 56.5\n", - " 1.4\n", - " 15-Feb\n", + " 1687\n", + " 59.8\n", + " 2821\n", + " 58.3\n", + " 1.5\n", + " 16-Mar\n", " \n", " \n", " sex\n", " F\n", - " 1022\n", - " 58.2\n", - " 1757\n", - " 56.6\n", - " 1.6\n", - " 25-Jan\n", + " 847\n", + " 59.3\n", + " 1428\n", + " 57.8\n", + " 1.5\n", + " 19-Mar\n", " \n", " \n", " M\n", - " 994\n", - " 57.7\n", - " 1722\n", - " 56.5\n", - " 1.2\n", - " unknown\n", + " 833\n", + " 60.1\n", + " 1386\n", + " 58.6\n", + " 1.5\n", + " 15-Mar\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 21\n", + " 14\n", " 50.0\n", - " 42\n", + " 28\n", " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", " 0-15\n", - " 126\n", - " 60.0\n", - " 210\n", + " 105\n", " 60.0\n", - " 0.0\n", - " unknown\n", + " 175\n", + " 56.0\n", + " 4.0\n", + " 18-Dec\n", " \n", " \n", " 16-17\n", - " 140\n", - " 52.6\n", - " 266\n", - " 52.6\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 18-29\n", - " 133\n", - " 57.6\n", - " 231\n", - " 54.5\n", - " 3.1\n", - " 20-Nov\n", - " \n", - " \n", - " 30-34\n", - " 147\n", - " 56.8\n", - " 259\n", - " 54.1\n", - " 2.7\n", - " 03-Dec\n", - " \n", - " \n", - " 35-39\n", - " 126\n", - " 58.1\n", - " 217\n", - " 58.1\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 40-44\n", - " 119\n", - " 56.7\n", - " 210\n", - " 56.7\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 45-49\n", - " 147\n", - " 63.6\n", - " 231\n", - " 60.6\n", - " 3.0\n", - " 08-Nov\n", - " \n", - " \n", - " 50-54\n", - " 126\n", - " 58.1\n", - " 217\n", - " 58.1\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 55-59\n", " 119\n", - " 56.7\n", - " 210\n", - " 56.7\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 60-64\n", - " 133\n", - " 55.9\n", - " 238\n", - " 55.9\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 65-69\n", - " 140\n", - " 62.5\n", - " 224\n", - " 62.5\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 70-74\n", - " 112\n", - " 57.1\n", + " 60.7\n", " 196\n", " 57.1\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 75-79\n", - " 140\n", - " 58.8\n", - " 238\n", - " 58.8\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 80-84\n", - " 133\n", - " 55.9\n", - " 238\n", - " 52.9\n", - " 3.0\n", - " 26-Nov\n", + " 3.6\n", + " 22-Dec\n", " \n", " \n", - " 85-89\n", - " 126\n", - " 58.1\n", - " 217\n", - " 58.1\n", + " 18-29\n", + " 105\n", + " 62.5\n", + " 168\n", + " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", - " 90+\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", + " 30-34\n", + " 105\n", + " 55.6\n", + " 189\n", + " 55.6\n", " 0.0\n", " unknown\n", " \n", " \n", - " ethnicity_6_groups\n", - " Black\n", - " 350\n", - " 57.5\n", - " 609\n", - " 57.5\n", + " 35-39\n", + " 112\n", + " 59.3\n", + " 189\n", + " 59.3\n", " 0.0\n", " unknown\n", " \n", " \n", - " Mixed\n", - " 343\n", - " 55.7\n", - " 616\n", - " 54.5\n", - " 1.2\n", - " unknown\n", - " \n", - " \n", - " Other\n", - " 357\n", - " 62.2\n", - " 574\n", - " 59.8\n", - " 2.4\n", - " 28-Nov\n", - " \n", - " \n", - " South Asian\n", - " 315\n", - " 55.6\n", - " 567\n", - " 54.3\n", - " 1.3\n", - " unknown\n", + " 40-44\n", + " 105\n", + " 62.5\n", + " 168\n", + " 58.3\n", + " 4.2\n", + " 11-Dec\n", " \n", " \n", - " Unknown\n", - " 287\n", - " 56.9\n", - " 504\n", - " 56.9\n", + " 45-49\n", + " 105\n", + " 57.7\n", + " 182\n", + " 57.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " White\n", - " 357\n", - " 58.6\n", - " 609\n", - " 57.5\n", - " 1.1\n", - " unknown\n", + " 50-54\n", + " 112\n", + " 61.5\n", + " 182\n", + " 57.7\n", + " 3.8\n", + " 18-Dec\n", " \n", " \n", - " ethnicity_16_groups\n", - " African\n", + " 55-59\n", " 119\n", - " 58.6\n", - " 203\n", - " 58.6\n", + " 60.7\n", + " 196\n", + " 60.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " Bangladeshi or British Bangladeshi\n", + " 60-64\n", " 112\n", " 57.1\n", " 196\n", @@ -42578,223 +54384,123 @@ " unknown\n", " \n", " \n", - " Caribbean\n", + " 65-69\n", " 105\n", - " 60.0\n", - " 175\n", - " 60.0\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " Chinese\n", - " 84\n", - " 54.5\n", - " 154\n", - " 54.5\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " Other\n", - " 98\n", - " 58.3\n", - " 168\n", - " 54.2\n", - " 4.1\n", - " 01-Nov\n", - " \n", - " \n", - " Other Asian\n", - " 98\n", - " 53.8\n", + " 57.7\n", " 182\n", " 53.8\n", - " 0.0\n", - " unknown\n", + " 3.9\n", + " 23-Dec\n", " \n", " \n", - " British or Mixed British\n", - " 105\n", - " 55.6\n", - " 189\n", + " 70-74\n", + " 98\n", " 51.9\n", - " 3.7\n", - " 12-Nov\n", - " \n", - " \n", - " Indian or British Indian\n", - " 112\n", - " 59.3\n", - " 189\n", - " 55.6\n", - " 3.7\n", - " 05-Nov\n", - " \n", - " \n", - " Irish\n", - " 84\n", - " 50.0\n", - " 168\n", - " 50.0\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " Other Black\n", - " 112\n", - " 61.5\n", - " 182\n", - " 57.7\n", - " 3.8\n", - " 30-Oct\n", - " \n", - " \n", - " Other White\n", - " 112\n", - " 57.1\n", - " 196\n", - " 53.6\n", - " 3.5\n", - " 12-Nov\n", - " \n", - " \n", - " Other mixed\n", - " 112\n", - " 59.3\n", " 189\n", - " 59.3\n", + " 51.9\n", " 0.0\n", " unknown\n", " \n", " \n", - " Pakistani or British Pakistani\n", + " 75-79\n", " 98\n", - " 53.8\n", - " 182\n", - " 53.8\n", + " 56.0\n", + " 175\n", + " 56.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " Unknown\n", - " 329\n", - " 58.8\n", - " 560\n", - " 57.5\n", - " 1.3\n", - " 23-Feb\n", - " \n", - " \n", - " White + Asian\n", + " 80-84\n", " 119\n", - " 58.6\n", - " 203\n", - " 55.2\n", - " 3.4\n", - " 11-Nov\n", - " \n", - " \n", - " White + Black African\n", - " 112\n", - " 61.5\n", + " 65.4\n", " 182\n", - " 61.5\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " White + Black Caribbean\n", - " 105\n", - " 60.0\n", - " 175\n", - " 60.0\n", + " 65.4\n", " 0.0\n", " unknown\n", " \n", " \n", - " imd_categories\n", - " 1 Most deprived\n", - " 371\n", - " 57.6\n", - " 644\n", - " 56.5\n", - " 1.1\n", + " 85-89\n", + " 119\n", + " 68.0\n", + " 175\n", + " 68.0\n", + " 0.0\n", " unknown\n", " \n", " \n", - " 2\n", - " 385\n", - " 56.1\n", - " 686\n", - " 54.1\n", - " 2.0\n", - " 04-Jan\n", + " 90+\n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", + " 0.0\n", + " unknown\n", " \n", " \n", - " 3\n", - " 399\n", - " 58.2\n", - " 686\n", - " 56.1\n", - " 2.1\n", - " 23-Dec\n", + " ethnicity_6_groups\n", + " Black\n", + " 273\n", + " 60.9\n", + " 448\n", + " 57.8\n", + " 3.1\n", + " 31-Dec\n", " \n", " \n", - " 4\n", - " 399\n", + " Mixed\n", + " 280\n", " 60.6\n", - " 658\n", - " 59.6\n", - " 1.0\n", - " unknown\n", + " 462\n", + " 59.1\n", + " 1.5\n", + " 13-Mar\n", " \n", " \n", - " 5 Least deprived\n", - " 371\n", - " 60.2\n", - " 616\n", - " 58.0\n", - " 2.2\n", - " 11-Dec\n", + " Other\n", + " 301\n", + " 59.7\n", + " 504\n", + " 59.7\n", + " 0.0\n", + " unknown\n", " \n", " \n", - " Unknown\n", - " 105\n", - " 55.6\n", - " 189\n", - " 51.9\n", - " 3.7\n", - " 12-Nov\n", + " South Asian\n", + " 273\n", + " 58.2\n", + " 469\n", + " 56.7\n", + " 1.5\n", + " 24-Mar\n", " \n", " \n", - " bmi\n", - " 30+\n", - " 602\n", - " 55.1\n", - " 1092\n", - " 54.5\n", - " 0.6\n", - " unknown\n", + " Unknown\n", + " 273\n", + " 62.9\n", + " 434\n", + " 61.3\n", + " 1.6\n", + " 22-Feb\n", " \n", " \n", - " under 30\n", - " 1414\n", - " 59.2\n", - " 2387\n", - " 57.5\n", - " 1.7\n", - " 12-Jan\n", + " White\n", + " 287\n", + " 58.6\n", + " 490\n", + " 57.1\n", + " 1.5\n", + " 22-Mar\n", " \n", " \n", - " housebound\n", + " dementia\n", " no\n", - " 2002\n", - " 58.0\n", - " 3451\n", - " 56.6\n", - " 1.4\n", - " 15-Feb\n", + " 1673\n", + " 59.9\n", + " 2793\n", + " 58.4\n", + " 1.5\n", + " 16-Mar\n", " \n", " \n", " yes\n", @@ -42805,638 +54511,613 @@ " 0.0\n", " unknown\n", " \n", + " \n", + "\n", + "
" + ], + "text/plain": [ + " vaccinated percent total \\\n", + "category group \n", + "overall overall 1687 59.8 2821 \n", + "sex F 847 59.3 1428 \n", + " M 833 60.1 1386 \n", + "ageband_5yr 0 14 50.0 28 \n", + " 0-15 105 60.0 175 \n", + " 16-17 119 60.7 196 \n", + " 18-29 105 62.5 168 \n", + " 30-34 105 55.6 189 \n", + " 35-39 112 59.3 189 \n", + " 40-44 105 62.5 168 \n", + " 45-49 105 57.7 182 \n", + " 50-54 112 61.5 182 \n", + " 55-59 119 60.7 196 \n", + " 60-64 112 57.1 196 \n", + " 65-69 105 57.7 182 \n", + " 70-74 98 51.9 189 \n", + " 75-79 98 56.0 175 \n", + " 80-84 119 65.4 182 \n", + " 85-89 119 68.0 175 \n", + " 90+ 28 57.1 49 \n", + "ethnicity_6_groups Black 273 60.9 448 \n", + " Mixed 280 60.6 462 \n", + " Other 301 59.7 504 \n", + " South Asian 273 58.2 469 \n", + " Unknown 273 62.9 434 \n", + " White 287 58.6 490 \n", + "dementia no 1673 59.9 2793 \n", + " yes 14 50.0 28 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 58.3 \n", + "sex F 57.8 \n", + " M 58.6 \n", + "ageband_5yr 0 50.0 \n", + " 0-15 56.0 \n", + " 16-17 57.1 \n", + " 18-29 62.5 \n", + " 30-34 55.6 \n", + " 35-39 59.3 \n", + " 40-44 58.3 \n", + " 45-49 57.7 \n", + " 50-54 57.7 \n", + " 55-59 60.7 \n", + " 60-64 57.1 \n", + " 65-69 53.8 \n", + " 70-74 51.9 \n", + " 75-79 56.0 \n", + " 80-84 65.4 \n", + " 85-89 68.0 \n", + " 90+ 57.1 \n", + "ethnicity_6_groups Black 57.8 \n", + " Mixed 59.1 \n", + " Other 59.7 \n", + " South Asian 56.7 \n", + " Unknown 61.3 \n", + " White 57.1 \n", + "dementia no 58.4 \n", + " yes 50.0 \n", + "\n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.5 \n", + "sex F 1.5 \n", + " M 1.5 \n", + "ageband_5yr 0 0.0 \n", + " 0-15 4.0 \n", + " 16-17 3.6 \n", + " 18-29 0.0 \n", + " 30-34 0.0 \n", + " 35-39 0.0 \n", + " 40-44 4.2 \n", + " 45-49 0.0 \n", + " 50-54 3.8 \n", + " 55-59 0.0 \n", + " 60-64 0.0 \n", + " 65-69 3.9 \n", + " 70-74 0.0 \n", + " 75-79 0.0 \n", + " 80-84 0.0 \n", + " 85-89 0.0 \n", + " 90+ 0.0 \n", + "ethnicity_6_groups Black 3.1 \n", + " Mixed 1.5 \n", + " Other 0.0 \n", + " South Asian 1.5 \n", + " Unknown 1.6 \n", + " White 1.5 \n", + "dementia no 1.5 \n", + " yes 0.0 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 16-Mar \n", + "sex F 19-Mar \n", + " M 15-Mar \n", + "ageband_5yr 0 unknown \n", + " 0-15 18-Dec \n", + " 16-17 22-Dec \n", + " 18-29 unknown \n", + " 30-34 unknown \n", + " 35-39 unknown \n", + " 40-44 11-Dec \n", + " 45-49 unknown \n", + " 50-54 18-Dec \n", + " 55-59 unknown \n", + " 60-64 unknown \n", + " 65-69 23-Dec \n", + " 70-74 unknown \n", + " 75-79 unknown \n", + " 80-84 unknown \n", + " 85-89 unknown \n", + " 90+ unknown \n", + "ethnicity_6_groups Black 31-Dec \n", + " Mixed 13-Mar \n", + " Other unknown \n", + " South Asian 24-Mar \n", + " Unknown 22-Feb \n", + " White 22-Mar \n", + "dementia no 16-Mar \n", + " yes unknown " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/lisahopcroft/Work/Projects/COVID-VACCINE-REPORTS/covid-vaccine-preliminary-uptake-study/notebooks/../lib/report_results.py:644: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n", + " out_csv = out_csv.drop(\"Date projected to reach 90%\",1)\n" + ] + }, + { + "data": { + "text/markdown": [ + "## " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## COVID vaccination rollout (second dose 14w ago) among **shielding (aged 16-69)** population up to 2021-10-27" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- 'Date projected to reach 90%' being 'unknown' indicates projection of >6mo (likely insufficient information)\n", + "- Patient counts rounded to the nearest 7" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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vaccinatedpercenttotalvaccinated 7d previous (percent)Uptake over last 7d (percent)Date projected to reach 90%
chronic_cardiac_diseaseno199557.8345156.41.416-Febcategorygroup
yes2175.02875.00.0overalloverall54662.986862.10.8unknown
current_copdnewly_shielded_since_feb_15no200258.1344456.71.414-Feb53962.686161.80.8unknown
yes2150.04250.000.070.00.0unknown
dmardsno199557.9344456.51.415-FebsexF28764.144864.10.0unknown
yes21M25961.742060.0351.720-Feb
ageband16-296360.010560.00.0unknown
dementiano199557.9344456.51.415-Feb30-395653.310553.30.0unknown
yes2150.04250.040-497062.511262.50.0unknown
psychosis_schiz_bipolarno199557.9344456.51.415-Feb50-598466.712666.70.0unknown
yes2150.04250.060-697062.511262.50.0unknown
LDno197458.0340256.61.415-Feb70-7912662.120362.10.0unknown
yes4254.57754.580+7062.511262.50.0unknown
ssrino200258.0345156.61.415-Febethnicity_6_groupsBlack9165.014060.05.001-Dec
yes1450.02850.0Mixed9860.916160.90.0unknown
chemo_or_radiono199557.8345156.41.416-FebOther9165.014065.00.0unknown
yes2160.03560.0South Asian9161.914761.90.0unknown
lung_cancerno199557.9344456.51.415-FebUnknown7764.711964.70.0unknown
yes2160.03560.0White9860.916160.90.0unknown
imd_categories1 Most deprived11965.418265.40.0unknown
29866.714766.70.0unknown
311266.716866.70.0unknown
cancer_excl_lung_and_haemno199557.9344456.51.415-Feb49860.916156.54.412-Dec
5 Least deprived10562.516858.34.211-Dec
yesUnknown2160.03560.050.04250.00.0unknown
haematological_cancerLDno199558.0343756.61.415-Feb53963.185462.30.8unknown
yes2114100.01450.04250.00.0unknownreached
ckdno159658.2274456.91.326-Feb45563.172162.11.0unknown
yes42057.173555.21.907-Jan9866.714761.94.829-Nov
\n", "
" ], "text/plain": [ - " vaccinated \\\n", - "category group \n", - "overall overall 2016 \n", - "sex F 1022 \n", - " M 994 \n", - "ageband_5yr 0 21 \n", - " 0-15 126 \n", - " 16-17 140 \n", - " 18-29 133 \n", - " 30-34 147 \n", - " 35-39 126 \n", - " 40-44 119 \n", - " 45-49 147 \n", - " 50-54 126 \n", - " 55-59 119 \n", - " 60-64 133 \n", - " 65-69 140 \n", - " 70-74 112 \n", - " 75-79 140 \n", - " 80-84 133 \n", - " 85-89 126 \n", - " 90+ 21 \n", - "ethnicity_6_groups Black 350 \n", - " Mixed 343 \n", - " Other 357 \n", - " South Asian 315 \n", - " Unknown 287 \n", - " White 357 \n", - "ethnicity_16_groups African 119 \n", - " Bangladeshi or British Bangladeshi 112 \n", - " Caribbean 105 \n", - " Chinese 84 \n", - " Other 98 \n", - " Other Asian 98 \n", - " British or Mixed British 105 \n", - " Indian or British Indian 112 \n", - " Irish 84 \n", - " Other Black 112 \n", - " Other White 112 \n", - " Other mixed 112 \n", - " Pakistani or British Pakistani 98 \n", - " Unknown 329 \n", - " White + Asian 119 \n", - " White + Black African 112 \n", - " White + Black Caribbean 105 \n", - "imd_categories 1 Most deprived 371 \n", - " 2 385 \n", - " 3 399 \n", - " 4 399 \n", - " 5 Least deprived 371 \n", - " Unknown 105 \n", - "bmi 30+ 602 \n", - " under 30 1414 \n", - "housebound no 2002 \n", - " yes 14 \n", - "chronic_cardiac_disease no 1995 \n", - " yes 21 \n", - "current_copd no 2002 \n", - " yes 21 \n", - "dmards no 1995 \n", - " yes 21 \n", - "dementia no 1995 \n", - " yes 21 \n", - "psychosis_schiz_bipolar no 1995 \n", - " yes 21 \n", - "LD no 1974 \n", - " yes 42 \n", - "ssri no 2002 \n", - " yes 14 \n", - "chemo_or_radio no 1995 \n", - " yes 21 \n", - "lung_cancer no 1995 \n", - " yes 21 \n", - "cancer_excl_lung_and_haem no 1995 \n", - " yes 21 \n", - "haematological_cancer no 1995 \n", - " yes 21 \n", - "ckd no 1596 \n", - " yes 420 \n", - "\n", - " percent total \\\n", - "category group \n", - "overall overall 57.9 3479 \n", - "sex F 58.2 1757 \n", - " M 57.7 1722 \n", - "ageband_5yr 0 50.0 42 \n", - " 0-15 60.0 210 \n", - " 16-17 52.6 266 \n", - " 18-29 57.6 231 \n", - " 30-34 56.8 259 \n", - " 35-39 58.1 217 \n", - " 40-44 56.7 210 \n", - " 45-49 63.6 231 \n", - " 50-54 58.1 217 \n", - " 55-59 56.7 210 \n", - " 60-64 55.9 238 \n", - " 65-69 62.5 224 \n", - " 70-74 57.1 196 \n", - " 75-79 58.8 238 \n", - " 80-84 55.9 238 \n", - " 85-89 58.1 217 \n", - " 90+ 75.0 28 \n", - "ethnicity_6_groups Black 57.5 609 \n", - " Mixed 55.7 616 \n", - " Other 62.2 574 \n", - " South Asian 55.6 567 \n", - " Unknown 56.9 504 \n", - " White 58.6 609 \n", - "ethnicity_16_groups African 58.6 203 \n", - " Bangladeshi or British Bangladeshi 57.1 196 \n", - " Caribbean 60.0 175 \n", - " Chinese 54.5 154 \n", - " Other 58.3 168 \n", - " Other Asian 53.8 182 \n", - " British or Mixed British 55.6 189 \n", - " Indian or British Indian 59.3 189 \n", - " Irish 50.0 168 \n", - " Other Black 61.5 182 \n", - " Other White 57.1 196 \n", - " Other mixed 59.3 189 \n", - " Pakistani or British Pakistani 53.8 182 \n", - " Unknown 58.8 560 \n", - " White + Asian 58.6 203 \n", - " White + Black African 61.5 182 \n", - " White + Black Caribbean 60.0 175 \n", - "imd_categories 1 Most deprived 57.6 644 \n", - " 2 56.1 686 \n", - " 3 58.2 686 \n", - " 4 60.6 658 \n", - " 5 Least deprived 60.2 616 \n", - " Unknown 55.6 189 \n", - "bmi 30+ 55.1 1092 \n", - " under 30 59.2 2387 \n", - "housebound no 58.0 3451 \n", - " yes 50.0 28 \n", - "chronic_cardiac_disease no 57.8 3451 \n", - " yes 75.0 28 \n", - "current_copd no 58.1 3444 \n", - " yes 50.0 42 \n", - "dmards no 57.9 3444 \n", - " yes 60.0 35 \n", - "dementia no 57.9 3444 \n", - " yes 50.0 42 \n", - "psychosis_schiz_bipolar no 57.9 3444 \n", - " yes 50.0 42 \n", - "LD no 58.0 3402 \n", - " yes 54.5 77 \n", - "ssri no 58.0 3451 \n", - " yes 50.0 28 \n", - "chemo_or_radio no 57.8 3451 \n", - " yes 60.0 35 \n", - "lung_cancer no 57.9 3444 \n", - " yes 60.0 35 \n", - "cancer_excl_lung_and_haem no 57.9 3444 \n", - " yes 60.0 35 \n", - "haematological_cancer no 58.0 3437 \n", - " yes 50.0 42 \n", - "ckd no 58.2 2744 \n", - " yes 57.1 735 \n", + " vaccinated percent total \\\n", + "category group \n", + "overall overall 546 62.9 868 \n", + "newly_shielded_since_feb_15 no 539 62.6 861 \n", + " yes 0 0.0 7 \n", + "sex F 287 64.1 448 \n", + " M 259 61.7 420 \n", + "ageband 16-29 63 60.0 105 \n", + " 30-39 56 53.3 105 \n", + " 40-49 70 62.5 112 \n", + " 50-59 84 66.7 126 \n", + " 60-69 70 62.5 112 \n", + " 70-79 126 62.1 203 \n", + " 80+ 70 62.5 112 \n", + "ethnicity_6_groups Black 91 65.0 140 \n", + " Mixed 98 60.9 161 \n", + " Other 91 65.0 140 \n", + " South Asian 91 61.9 147 \n", + " Unknown 77 64.7 119 \n", + " White 98 60.9 161 \n", + "imd_categories 1 Most deprived 119 65.4 182 \n", + " 2 98 66.7 147 \n", + " 3 112 66.7 168 \n", + " 4 98 60.9 161 \n", + " 5 Least deprived 105 62.5 168 \n", + " Unknown 21 50.0 42 \n", + "LD no 539 63.1 854 \n", + " yes 14 100.0 14 \n", + "ckd no 455 63.1 721 \n", + " yes 98 66.7 147 \n", "\n", - " vaccinated 7d previous (percent) \\\n", - "category group \n", - "overall overall 56.5 \n", - "sex F 56.6 \n", - " M 56.5 \n", - "ageband_5yr 0 50.0 \n", - " 0-15 60.0 \n", - " 16-17 52.6 \n", - " 18-29 54.5 \n", - " 30-34 54.1 \n", - " 35-39 58.1 \n", - " 40-44 56.7 \n", - " 45-49 60.6 \n", - " 50-54 58.1 \n", - " 55-59 56.7 \n", - " 60-64 55.9 \n", - " 65-69 62.5 \n", - " 70-74 57.1 \n", - " 75-79 58.8 \n", - " 80-84 52.9 \n", - " 85-89 58.1 \n", - " 90+ 75.0 \n", - "ethnicity_6_groups Black 57.5 \n", - " Mixed 54.5 \n", - " Other 59.8 \n", - " South Asian 54.3 \n", - " Unknown 56.9 \n", - " White 57.5 \n", - "ethnicity_16_groups African 58.6 \n", - " Bangladeshi or British Bangladeshi 57.1 \n", - " Caribbean 60.0 \n", - " Chinese 54.5 \n", - " Other 54.2 \n", - " Other Asian 53.8 \n", - " British or Mixed British 51.9 \n", - " Indian or British Indian 55.6 \n", - " Irish 50.0 \n", - " Other Black 57.7 \n", - " Other White 53.6 \n", - " Other mixed 59.3 \n", - " Pakistani or British Pakistani 53.8 \n", - " Unknown 57.5 \n", - " White + Asian 55.2 \n", - " White + Black African 61.5 \n", - " White + Black Caribbean 60.0 \n", - "imd_categories 1 Most deprived 56.5 \n", - " 2 54.1 \n", - " 3 56.1 \n", - " 4 59.6 \n", - " 5 Least deprived 58.0 \n", - " Unknown 51.9 \n", - "bmi 30+ 54.5 \n", - " under 30 57.5 \n", - "housebound no 56.6 \n", - " yes 50.0 \n", - "chronic_cardiac_disease no 56.4 \n", - " yes 75.0 \n", - "current_copd no 56.7 \n", - " yes 50.0 \n", - "dmards no 56.5 \n", - " yes 60.0 \n", - "dementia no 56.5 \n", - " yes 50.0 \n", - "psychosis_schiz_bipolar no 56.5 \n", - " yes 50.0 \n", - "LD no 56.6 \n", - " yes 54.5 \n", - "ssri no 56.6 \n", - " yes 50.0 \n", - "chemo_or_radio no 56.4 \n", - " yes 60.0 \n", - "lung_cancer no 56.5 \n", - " yes 60.0 \n", - "cancer_excl_lung_and_haem no 56.5 \n", - " yes 60.0 \n", - "haematological_cancer no 56.6 \n", - " yes 50.0 \n", - "ckd no 56.9 \n", - " yes 55.2 \n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 62.1 \n", + "newly_shielded_since_feb_15 no 61.8 \n", + " yes 0.0 \n", + "sex F 64.1 \n", + " M 60.0 \n", + "ageband 16-29 60.0 \n", + " 30-39 53.3 \n", + " 40-49 62.5 \n", + " 50-59 66.7 \n", + " 60-69 62.5 \n", + " 70-79 62.1 \n", + " 80+ 62.5 \n", + "ethnicity_6_groups Black 60.0 \n", + " Mixed 60.9 \n", + " Other 65.0 \n", + " South Asian 61.9 \n", + " Unknown 64.7 \n", + " White 60.9 \n", + "imd_categories 1 Most deprived 65.4 \n", + " 2 66.7 \n", + " 3 66.7 \n", + " 4 56.5 \n", + " 5 Least deprived 58.3 \n", + " Unknown 50.0 \n", + "LD no 62.3 \n", + " yes 50.0 \n", + "ckd no 62.1 \n", + " yes 61.9 \n", "\n", - " Uptake over last 7d (percent) \\\n", - "category group \n", - "overall overall 1.4 \n", - "sex F 1.6 \n", - " M 1.2 \n", - "ageband_5yr 0 0.0 \n", - " 0-15 0.0 \n", - " 16-17 0.0 \n", - " 18-29 3.1 \n", - " 30-34 2.7 \n", - " 35-39 0.0 \n", - " 40-44 0.0 \n", - " 45-49 3.0 \n", - " 50-54 0.0 \n", - " 55-59 0.0 \n", - " 60-64 0.0 \n", - " 65-69 0.0 \n", - " 70-74 0.0 \n", - " 75-79 0.0 \n", - " 80-84 3.0 \n", - " 85-89 0.0 \n", - " 90+ 0.0 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 1.2 \n", - " Other 2.4 \n", - " South Asian 1.3 \n", - " Unknown 0.0 \n", - " White 1.1 \n", - "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", - " Chinese 0.0 \n", - " Other 4.1 \n", - " Other Asian 0.0 \n", - " British or Mixed British 3.7 \n", - " Indian or British Indian 3.7 \n", - " Irish 0.0 \n", - " Other Black 3.8 \n", - " Other White 3.5 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 1.3 \n", - " White + Asian 3.4 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 1.1 \n", - " 2 2.0 \n", - " 3 2.1 \n", - " 4 1.0 \n", - " 5 Least deprived 2.2 \n", - " Unknown 3.7 \n", - "bmi 30+ 0.6 \n", - " under 30 1.7 \n", - "housebound no 1.4 \n", - " yes 0.0 \n", - "chronic_cardiac_disease no 1.4 \n", - " yes 0.0 \n", - "current_copd no 1.4 \n", - " yes 0.0 \n", - "dmards no 1.4 \n", - " yes 0.0 \n", - "dementia no 1.4 \n", - " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.4 \n", - " yes 0.0 \n", - "LD no 1.4 \n", - " yes 0.0 \n", - "ssri no 1.4 \n", - " yes 0.0 \n", - "chemo_or_radio no 1.4 \n", - " yes 0.0 \n", - "lung_cancer no 1.4 \n", - " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.4 \n", - " yes 0.0 \n", - "haematological_cancer no 1.4 \n", - " yes 0.0 \n", - "ckd no 1.3 \n", - " yes 1.9 \n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 0.8 \n", + "newly_shielded_since_feb_15 no 0.8 \n", + " yes 0.0 \n", + "sex F 0.0 \n", + " M 1.7 \n", + "ageband 16-29 0.0 \n", + " 30-39 0.0 \n", + " 40-49 0.0 \n", + " 50-59 0.0 \n", + " 60-69 0.0 \n", + " 70-79 0.0 \n", + " 80+ 0.0 \n", + "ethnicity_6_groups Black 5.0 \n", + " Mixed 0.0 \n", + " Other 0.0 \n", + " South Asian 0.0 \n", + " Unknown 0.0 \n", + " White 0.0 \n", + "imd_categories 1 Most deprived 0.0 \n", + " 2 0.0 \n", + " 3 0.0 \n", + " 4 4.4 \n", + " 5 Least deprived 4.2 \n", + " Unknown 0.0 \n", + "LD no 0.8 \n", + " yes 50.0 \n", + "ckd no 1.0 \n", + " yes 4.8 \n", "\n", - " Date projected to reach 90% \n", - "category group \n", - "overall overall 15-Feb \n", - "sex F 25-Jan \n", - " M unknown \n", - "ageband_5yr 0 unknown \n", - " 0-15 unknown \n", - " 16-17 unknown \n", - " 18-29 20-Nov \n", - " 30-34 03-Dec \n", - " 35-39 unknown \n", - " 40-44 unknown \n", - " 45-49 08-Nov \n", - " 50-54 unknown \n", - " 55-59 unknown \n", - " 60-64 unknown \n", - " 65-69 unknown \n", - " 70-74 unknown \n", - " 75-79 unknown \n", - " 80-84 26-Nov \n", - " 85-89 unknown \n", - " 90+ unknown \n", - "ethnicity_6_groups Black unknown \n", - " Mixed unknown \n", - " Other 28-Nov \n", - " South Asian unknown \n", - " Unknown unknown \n", - " White unknown \n", - "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean unknown \n", - " Chinese unknown \n", - " Other 01-Nov \n", - " Other Asian unknown \n", - " British or Mixed British 12-Nov \n", - " Indian or British Indian 05-Nov \n", - " Irish unknown \n", - " Other Black 30-Oct \n", - " Other White 12-Nov \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani unknown \n", - " Unknown 23-Feb \n", - " White + Asian 11-Nov \n", - " White + Black African unknown \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived unknown \n", - " 2 04-Jan \n", - " 3 23-Dec \n", - " 4 unknown \n", - " 5 Least deprived 11-Dec \n", - " Unknown 12-Nov \n", - "bmi 30+ unknown \n", - " under 30 12-Jan \n", - "housebound no 15-Feb \n", - " yes unknown \n", - "chronic_cardiac_disease no 16-Feb \n", - " yes unknown \n", - "current_copd no 14-Feb \n", - " yes unknown \n", - "dmards no 15-Feb \n", - " yes unknown \n", - "dementia no 15-Feb \n", - " yes unknown \n", - "psychosis_schiz_bipolar no 15-Feb \n", - " yes unknown \n", - "LD no 15-Feb \n", - " yes unknown \n", - "ssri no 15-Feb \n", - " yes unknown \n", - "chemo_or_radio no 16-Feb \n", - " yes unknown \n", - "lung_cancer no 15-Feb \n", - " yes unknown \n", - "cancer_excl_lung_and_haem no 15-Feb \n", - " yes unknown \n", - "haematological_cancer no 15-Feb \n", - " yes unknown \n", - "ckd no 26-Feb \n", - " yes 07-Jan " + " Date projected to reach 90% \n", + "category group \n", + "overall overall unknown \n", + "newly_shielded_since_feb_15 no unknown \n", + " yes unknown \n", + "sex F unknown \n", + " M 20-Feb \n", + "ageband 16-29 unknown \n", + " 30-39 unknown \n", + " 40-49 unknown \n", + " 50-59 unknown \n", + " 60-69 unknown \n", + " 70-79 unknown \n", + " 80+ unknown \n", + "ethnicity_6_groups Black 01-Dec \n", + " Mixed unknown \n", + " Other unknown \n", + " South Asian unknown \n", + " Unknown unknown \n", + " White unknown \n", + "imd_categories 1 Most deprived unknown \n", + " 2 unknown \n", + " 3 unknown \n", + " 4 12-Dec \n", + " 5 Least deprived 11-Dec \n", + " Unknown unknown \n", + "LD no unknown \n", + " yes reached \n", + "ckd no unknown \n", + " yes 29-Nov " ] }, "metadata": {}, @@ -43465,7 +55146,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose 14weeks ago) among **care home** population up to 2021-09-08" + "## COVID vaccination rollout (second dose 14w ago) among **65-69** population up to 2021-10-27" ], "text/plain": [ "" @@ -43531,258 +55212,560 @@ " \n", " overall\n", " overall\n", - " 791\n", - " 56.8\n", - " 1393\n", - " 55.3\n", - " 1.5\n", - " 09-Feb\n", + " 2688\n", + " 60.9\n", + " 4417\n", + " 59.6\n", + " 1.3\n", + " 01-Apr\n", + " \n", + " \n", + " sex\n", + " F\n", + " 1337\n", + " 60.1\n", + " 2226\n", + " 58.8\n", + " 1.3\n", + " 06-Apr\n", + " \n", + " \n", + " M\n", + " 1344\n", + " 61.3\n", + " 2191\n", + " 60.1\n", + " 1.2\n", + " 12-Apr\n", + " \n", + " \n", + " ethnicity_6_groups\n", + " Black\n", + " 469\n", + " 62.0\n", + " 756\n", + " 59.3\n", + " 2.7\n", + " 07-Jan\n", + " \n", + " \n", + " Mixed\n", + " 483\n", + " 62.7\n", + " 770\n", + " 60.9\n", + " 1.8\n", + " 10-Feb\n", + " \n", + " \n", + " Other\n", + " 434\n", + " 57.9\n", + " 749\n", + " 57.0\n", + " 0.9\n", + " unknown\n", + " \n", + " \n", + " South Asian\n", + " 420\n", + " 59.4\n", + " 707\n", + " 58.4\n", + " 1.0\n", + " unknown\n", + " \n", + " \n", + " Unknown\n", + " 434\n", + " 62.0\n", + " 700\n", + " 61.0\n", + " 1.0\n", + " unknown\n", + " \n", + " \n", + " White\n", + " 441\n", + " 60.0\n", + " 735\n", + " 60.0\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " ethnicity_16_groups\n", + " African\n", + " 140\n", + " 62.5\n", + " 224\n", + " 62.5\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " Bangladeshi or British Bangladeshi\n", + " 133\n", + " 57.6\n", + " 231\n", + " 54.5\n", + " 3.1\n", + " 08-Jan\n", + " \n", + " \n", + " Caribbean\n", + " 147\n", + " 61.8\n", + " 238\n", + " 58.8\n", + " 3.0\n", + " 31-Dec\n", + " \n", + " \n", + " Chinese\n", + " 161\n", + " 65.7\n", + " 245\n", + " 62.9\n", + " 2.8\n", + " 26-Dec\n", + " \n", + " \n", + " Other\n", + " 168\n", + " 63.2\n", + " 266\n", + " 60.5\n", + " 2.7\n", + " 04-Jan\n", + " \n", + " \n", + " Other Asian\n", + " 126\n", + " 58.1\n", + " 217\n", + " 58.1\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " British or Mixed British\n", + " 147\n", + " 61.8\n", + " 238\n", + " 61.8\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " Indian or British Indian\n", + " 140\n", + " 57.1\n", + " 245\n", + " 57.1\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " Irish\n", + " 133\n", + " 57.6\n", + " 231\n", + " 57.6\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " Other Black\n", + " 154\n", + " 64.7\n", + " 238\n", + " 61.8\n", + " 2.9\n", + " 27-Dec\n", + " \n", + " \n", + " Other White\n", + " 147\n", + " 61.8\n", + " 238\n", + " 61.8\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " Other mixed\n", + " 133\n", + " 52.8\n", + " 252\n", + " 52.8\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " Pakistani or British Pakistani\n", + " 161\n", + " 67.6\n", + " 238\n", + " 64.7\n", + " 2.9\n", + " 20-Dec\n", + " \n", + " \n", + " Unknown\n", + " 406\n", + " 65.2\n", + " 623\n", + " 64.0\n", + " 1.2\n", + " 20-Mar\n", + " \n", + " \n", + " White + Asian\n", + " 140\n", + " 62.5\n", + " 224\n", + " 59.4\n", + " 3.1\n", + " 28-Dec\n", + " \n", + " \n", + " White + Black African\n", + " 119\n", + " 60.7\n", + " 196\n", + " 60.7\n", + " 0.0\n", + " unknown\n", + " \n", + " \n", + " White + Black Caribbean\n", + " 133\n", + " 51.4\n", + " 259\n", + " 48.6\n", + " 2.8\n", + " 31-Jan\n", " \n", " \n", - " sex\n", - " F\n", - " 413\n", + " imd_categories\n", + " 1 Most deprived\n", + " 483\n", + " 59.0\n", + " 819\n", " 57.3\n", - " 721\n", - " 56.3\n", - " 1.0\n", - " unknown\n", + " 1.7\n", + " 03-Mar\n", " \n", " \n", - " M\n", - " 378\n", - " 56.2\n", - " 672\n", - " 55.2\n", - " 1.0\n", + " 2\n", + " 511\n", + " 60.8\n", + " 840\n", + " 60.0\n", + " 0.8\n", " unknown\n", " \n", " \n", - " ageband_5yr\n", - " 0\n", - " 14\n", - " 100.0\n", - " 14\n", - " 100.0\n", - " 0.0\n", - " reached\n", + " 3\n", + " 539\n", + " 63.1\n", + " 854\n", + " 61.5\n", + " 1.6\n", + " 21-Feb\n", " \n", " \n", - " 0-15\n", - " 49\n", - " 53.8\n", - " 91\n", - " 53.8\n", - " 0.0\n", + " 4\n", + " 511\n", + " 60.8\n", + " 840\n", + " 60.0\n", + " 0.8\n", " unknown\n", " \n", " \n", - " 16-17\n", - " 63\n", - " 64.3\n", - " 98\n", - " 64.3\n", + " 5 Least deprived\n", + " 511\n", + " 60.8\n", + " 840\n", + " 59.2\n", + " 1.6\n", + " 03-Mar\n", + " \n", + " \n", + " Unknown\n", + " 133\n", + " 61.3\n", + " 217\n", + " 61.3\n", " 0.0\n", " unknown\n", " \n", " \n", - " 18-29\n", - " 49\n", - " 58.3\n", - " 84\n", - " 50.0\n", - " 8.3\n", - " 04-Oct\n", + " bmi\n", + " 30+\n", + " 840\n", + " 61.5\n", + " 1365\n", + " 60.0\n", + " 1.5\n", + " 09-Mar\n", " \n", " \n", - " 30-34\n", - " 42\n", - " 50.0\n", - " 84\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " under 30\n", + " 1848\n", + " 60.6\n", + " 3052\n", + " 59.2\n", + " 1.4\n", + " 23-Mar\n", " \n", " \n", - " 35-39\n", - " 56\n", - " 57.1\n", - " 98\n", + " housebound\n", + " no\n", + " 2653\n", + " 60.8\n", + " 4361\n", + " 59.6\n", + " 1.2\n", + " 15-Apr\n", + " \n", + " \n", + " yes\n", + " 35\n", + " 71.4\n", + " 49\n", " 57.1\n", - " 0.0\n", - " unknown\n", + " 14.3\n", + " 05-Nov\n", " \n", " \n", - " 40-44\n", - " 56\n", + " chronic_cardiac_disease\n", + " no\n", + " 2653\n", + " 60.7\n", + " 4368\n", + " 59.5\n", + " 1.2\n", + " 15-Apr\n", + " \n", + " \n", + " yes\n", + " 28\n", " 57.1\n", - " 98\n", + " 49\n", " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " 45-49\n", - " 42\n", - " 46.2\n", - " 91\n", - " 46.2\n", - " 0.0\n", + " current_copd\n", + " no\n", + " 2660\n", + " 60.8\n", + " 4375\n", + " 59.7\n", + " 1.1\n", " unknown\n", " \n", " \n", - " 50-54\n", - " 42\n", + " yes\n", + " 21\n", " 50.0\n", - " 84\n", + " 42\n", " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " 55-59\n", + " dmards\n", + " no\n", + " 2653\n", + " 60.7\n", + " 4368\n", + " 59.5\n", + " 1.2\n", + " 15-Apr\n", + " \n", + " \n", + " yes\n", + " 28\n", + " 57.1\n", " 49\n", - " 53.8\n", - " 91\n", - " 53.8\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " 60-64\n", - " 56\n", - " 61.5\n", - " 91\n", - " 61.5\n", - " 0.0\n", - " unknown\n", + " dementia\n", + " no\n", + " 2653\n", + " 60.7\n", + " 4368\n", + " 59.5\n", + " 1.2\n", + " 15-Apr\n", " \n", " \n", - " 65-69\n", - " 56\n", + " yes\n", + " 28\n", " 66.7\n", - " 84\n", + " 42\n", " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " 70-74\n", - " 63\n", - " 60.0\n", - " 105\n", - " 53.3\n", - " 6.7\n", - " 09-Oct\n", + " psychosis_schiz_bipolar\n", + " no\n", + " 2653\n", + " 60.7\n", + " 4368\n", + " 59.5\n", + " 1.2\n", + " 15-Apr\n", " \n", " \n", - " 75-79\n", + " yes\n", + " 28\n", + " 57.1\n", " 49\n", - " 53.8\n", - " 91\n", - " 53.8\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " 80-84\n", - " 42\n", - " 54.5\n", - " 77\n", - " 54.5\n", + " LD\n", + " no\n", + " 2625\n", + " 60.9\n", + " 4312\n", + " 59.6\n", + " 1.3\n", + " 01-Apr\n", + " \n", + " \n", + " yes\n", + " 63\n", + " 60.0\n", + " 105\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " 85-89\n", - " 49\n", - " 50.0\n", - " 98\n", - " 50.0\n", + " ssri\n", + " no\n", + " 2667\n", + " 61.0\n", + " 4375\n", + " 59.7\n", + " 1.3\n", + " 01-Apr\n", + " \n", + " \n", + " yes\n", + " 21\n", + " 60.0\n", + " 35\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " 90+\n", - " 7\n", + " chemo_or_radio\n", + " no\n", + " 2667\n", + " 61.0\n", + " 4375\n", + " 59.7\n", + " 1.3\n", + " 01-Apr\n", + " \n", + " \n", + " yes\n", + " 21\n", " 50.0\n", - " 14\n", + " 42\n", " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " ethnicity_6_groups\n", - " Black\n", - " 140\n", - " 62.5\n", - " 224\n", - " 59.4\n", - " 3.1\n", - " 09-Nov\n", + " lung_cancer\n", + " no\n", + " 2667\n", + " 60.9\n", + " 4382\n", + " 59.6\n", + " 1.3\n", + " 01-Apr\n", " \n", " \n", - " Mixed\n", - " 140\n", - " 55.6\n", - " 252\n", - " 52.8\n", - " 2.8\n", - " 03-Dec\n", + " yes\n", + " 21\n", + " 60.0\n", + " 35\n", + " 60.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", - " Other\n", - " 119\n", - " 56.7\n", - " 210\n", - " 53.3\n", - " 3.4\n", - " 15-Nov\n", + " cancer_excl_lung_and_haem\n", + " no\n", + " 2660\n", + " 60.8\n", + " 4375\n", + " 59.5\n", + " 1.3\n", + " 02-Apr\n", " \n", " \n", - " South Asian\n", - " 147\n", - " 55.3\n", - " 266\n", - " 55.3\n", + " yes\n", + " 28\n", + " 80.0\n", + " 35\n", + " 80.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " Unknown\n", - " 119\n", - " 56.7\n", - " 210\n", - " 53.3\n", - " 3.4\n", - " 15-Nov\n", + " haematological_cancer\n", + " no\n", + " 2653\n", + " 60.7\n", + " 4368\n", + " 59.5\n", + " 1.2\n", + " 15-Apr\n", " \n", " \n", - " White\n", - " 133\n", - " 57.6\n", - " 231\n", - " 57.6\n", + " yes\n", + " 28\n", + " 66.7\n", + " 42\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " dementia\n", + " ckd\n", " no\n", - " 784\n", - " 56.9\n", - " 1379\n", - " 55.8\n", - " 1.1\n", - " unknown\n", + " 2114\n", + " 60.9\n", + " 3472\n", + " 59.5\n", + " 1.4\n", + " 21-Mar\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 14\n", - " 0.0\n", - " 0.0\n", + " 567\n", + " 60.4\n", + " 938\n", + " 59.7\n", + " 0.7\n", " unknown\n", " \n", " \n", @@ -43790,129 +55773,320 @@ "" ], "text/plain": [ - " vaccinated percent total \\\n", - "category group \n", - "overall overall 791 56.8 1393 \n", - "sex F 413 57.3 721 \n", - " M 378 56.2 672 \n", - "ageband_5yr 0 14 100.0 14 \n", - " 0-15 49 53.8 91 \n", - " 16-17 63 64.3 98 \n", - " 18-29 49 58.3 84 \n", - " 30-34 42 50.0 84 \n", - " 35-39 56 57.1 98 \n", - " 40-44 56 57.1 98 \n", - " 45-49 42 46.2 91 \n", - " 50-54 42 50.0 84 \n", - " 55-59 49 53.8 91 \n", - " 60-64 56 61.5 91 \n", - " 65-69 56 66.7 84 \n", - " 70-74 63 60.0 105 \n", - " 75-79 49 53.8 91 \n", - " 80-84 42 54.5 77 \n", - " 85-89 49 50.0 98 \n", - " 90+ 7 50.0 14 \n", - "ethnicity_6_groups Black 140 62.5 224 \n", - " Mixed 140 55.6 252 \n", - " Other 119 56.7 210 \n", - " South Asian 147 55.3 266 \n", - " Unknown 119 56.7 210 \n", - " White 133 57.6 231 \n", - "dementia no 784 56.9 1379 \n", - " yes 0 0.0 14 \n", + " vaccinated \\\n", + "category group \n", + "overall overall 2688 \n", + "sex F 1337 \n", + " M 1344 \n", + "ethnicity_6_groups Black 469 \n", + " Mixed 483 \n", + " Other 434 \n", + " South Asian 420 \n", + " Unknown 434 \n", + " White 441 \n", + "ethnicity_16_groups African 140 \n", + " Bangladeshi or British Bangladeshi 133 \n", + " Caribbean 147 \n", + " Chinese 161 \n", + " Other 168 \n", + " Other Asian 126 \n", + " British or Mixed British 147 \n", + " Indian or British Indian 140 \n", + " Irish 133 \n", + " Other Black 154 \n", + " Other White 147 \n", + " Other mixed 133 \n", + " Pakistani or British Pakistani 161 \n", + " Unknown 406 \n", + " White + Asian 140 \n", + " White + Black African 119 \n", + " White + Black Caribbean 133 \n", + "imd_categories 1 Most deprived 483 \n", + " 2 511 \n", + " 3 539 \n", + " 4 511 \n", + " 5 Least deprived 511 \n", + " Unknown 133 \n", + "bmi 30+ 840 \n", + " under 30 1848 \n", + "housebound no 2653 \n", + " yes 35 \n", + "chronic_cardiac_disease no 2653 \n", + " yes 28 \n", + "current_copd no 2660 \n", + " yes 21 \n", + "dmards no 2653 \n", + " yes 28 \n", + "dementia no 2653 \n", + " yes 28 \n", + "psychosis_schiz_bipolar no 2653 \n", + " yes 28 \n", + "LD no 2625 \n", + " yes 63 \n", + "ssri no 2667 \n", + " yes 21 \n", + "chemo_or_radio no 2667 \n", + " yes 21 \n", + "lung_cancer no 2667 \n", + " yes 21 \n", + "cancer_excl_lung_and_haem no 2660 \n", + " yes 28 \n", + "haematological_cancer no 2653 \n", + " yes 28 \n", + "ckd no 2114 \n", + " yes 567 \n", "\n", - " vaccinated 7d previous (percent) \\\n", - "category group \n", - "overall overall 55.3 \n", - "sex F 56.3 \n", - " M 55.2 \n", - "ageband_5yr 0 100.0 \n", - " 0-15 53.8 \n", - " 16-17 64.3 \n", - " 18-29 50.0 \n", - " 30-34 50.0 \n", - " 35-39 57.1 \n", - " 40-44 57.1 \n", - " 45-49 46.2 \n", - " 50-54 50.0 \n", - " 55-59 53.8 \n", - " 60-64 61.5 \n", - " 65-69 66.7 \n", - " 70-74 53.3 \n", - " 75-79 53.8 \n", - " 80-84 54.5 \n", - " 85-89 50.0 \n", - " 90+ 50.0 \n", - "ethnicity_6_groups Black 59.4 \n", - " Mixed 52.8 \n", - " Other 53.3 \n", - " South Asian 55.3 \n", - " Unknown 53.3 \n", - " White 57.6 \n", - "dementia no 55.8 \n", - " yes 0.0 \n", + " percent total \\\n", + "category group \n", + "overall overall 60.9 4417 \n", + "sex F 60.1 2226 \n", + " M 61.3 2191 \n", + "ethnicity_6_groups Black 62.0 756 \n", + " Mixed 62.7 770 \n", + " Other 57.9 749 \n", + " South Asian 59.4 707 \n", + " Unknown 62.0 700 \n", + " White 60.0 735 \n", + "ethnicity_16_groups African 62.5 224 \n", + " Bangladeshi or British Bangladeshi 57.6 231 \n", + " Caribbean 61.8 238 \n", + " Chinese 65.7 245 \n", + " Other 63.2 266 \n", + " Other Asian 58.1 217 \n", + " British or Mixed British 61.8 238 \n", + " Indian or British Indian 57.1 245 \n", + " Irish 57.6 231 \n", + " Other Black 64.7 238 \n", + " Other White 61.8 238 \n", + " Other mixed 52.8 252 \n", + " Pakistani or British Pakistani 67.6 238 \n", + " Unknown 65.2 623 \n", + " White + Asian 62.5 224 \n", + " White + Black African 60.7 196 \n", + " White + Black Caribbean 51.4 259 \n", + "imd_categories 1 Most deprived 59.0 819 \n", + " 2 60.8 840 \n", + " 3 63.1 854 \n", + " 4 60.8 840 \n", + " 5 Least deprived 60.8 840 \n", + " Unknown 61.3 217 \n", + "bmi 30+ 61.5 1365 \n", + " under 30 60.6 3052 \n", + "housebound no 60.8 4361 \n", + " yes 71.4 49 \n", + "chronic_cardiac_disease no 60.7 4368 \n", + " yes 57.1 49 \n", + "current_copd no 60.8 4375 \n", + " yes 50.0 42 \n", + "dmards no 60.7 4368 \n", + " yes 57.1 49 \n", + "dementia no 60.7 4368 \n", + " yes 66.7 42 \n", + "psychosis_schiz_bipolar no 60.7 4368 \n", + " yes 57.1 49 \n", + "LD no 60.9 4312 \n", + " yes 60.0 105 \n", + "ssri no 61.0 4375 \n", + " yes 60.0 35 \n", + "chemo_or_radio no 61.0 4375 \n", + " yes 50.0 42 \n", + "lung_cancer no 60.9 4382 \n", + " yes 60.0 35 \n", + "cancer_excl_lung_and_haem no 60.8 4375 \n", + " yes 80.0 35 \n", + "haematological_cancer no 60.7 4368 \n", + " yes 66.7 42 \n", + "ckd no 60.9 3472 \n", + " yes 60.4 938 \n", "\n", - " Uptake over last 7d (percent) \\\n", - "category group \n", - "overall overall 1.5 \n", - "sex F 1.0 \n", - " M 1.0 \n", - "ageband_5yr 0 0.0 \n", - " 0-15 0.0 \n", - " 16-17 0.0 \n", - " 18-29 8.3 \n", - " 30-34 0.0 \n", - " 35-39 0.0 \n", - " 40-44 0.0 \n", - " 45-49 0.0 \n", - " 50-54 0.0 \n", - " 55-59 0.0 \n", - " 60-64 0.0 \n", - " 65-69 0.0 \n", - " 70-74 6.7 \n", - " 75-79 0.0 \n", - " 80-84 0.0 \n", - " 85-89 0.0 \n", - " 90+ 0.0 \n", - "ethnicity_6_groups Black 3.1 \n", - " Mixed 2.8 \n", - " Other 3.4 \n", - " South Asian 0.0 \n", - " Unknown 3.4 \n", - " White 0.0 \n", - "dementia no 1.1 \n", - " yes 0.0 \n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.6 \n", + "sex F 58.8 \n", + " M 60.1 \n", + "ethnicity_6_groups Black 59.3 \n", + " Mixed 60.9 \n", + " Other 57.0 \n", + " South Asian 58.4 \n", + " Unknown 61.0 \n", + " White 60.0 \n", + "ethnicity_16_groups African 62.5 \n", + " Bangladeshi or British Bangladeshi 54.5 \n", + " Caribbean 58.8 \n", + " Chinese 62.9 \n", + " Other 60.5 \n", + " Other Asian 58.1 \n", + " British or Mixed British 61.8 \n", + " Indian or British Indian 57.1 \n", + " Irish 57.6 \n", + " Other Black 61.8 \n", + " Other White 61.8 \n", + " Other mixed 52.8 \n", + " Pakistani or British Pakistani 64.7 \n", + " Unknown 64.0 \n", + " White + Asian 59.4 \n", + " White + Black African 60.7 \n", + " White + Black Caribbean 48.6 \n", + "imd_categories 1 Most deprived 57.3 \n", + " 2 60.0 \n", + " 3 61.5 \n", + " 4 60.0 \n", + " 5 Least deprived 59.2 \n", + " Unknown 61.3 \n", + "bmi 30+ 60.0 \n", + " under 30 59.2 \n", + "housebound no 59.6 \n", + " yes 57.1 \n", + "chronic_cardiac_disease no 59.5 \n", + " yes 57.1 \n", + "current_copd no 59.7 \n", + " yes 50.0 \n", + "dmards no 59.5 \n", + " yes 57.1 \n", + "dementia no 59.5 \n", + " yes 66.7 \n", + "psychosis_schiz_bipolar no 59.5 \n", + " yes 57.1 \n", + "LD no 59.6 \n", + " yes 60.0 \n", + "ssri no 59.7 \n", + " yes 60.0 \n", + "chemo_or_radio no 59.7 \n", + " yes 50.0 \n", + "lung_cancer no 59.6 \n", + " yes 60.0 \n", + "cancer_excl_lung_and_haem no 59.5 \n", + " yes 80.0 \n", + "haematological_cancer no 59.5 \n", + " yes 66.7 \n", + "ckd no 59.5 \n", + " yes 59.7 \n", "\n", - " Date projected to reach 90% \n", - "category group \n", - "overall overall 09-Feb \n", - "sex F unknown \n", - " M unknown \n", - "ageband_5yr 0 reached \n", - " 0-15 unknown \n", - " 16-17 unknown \n", - " 18-29 04-Oct \n", - " 30-34 unknown \n", - " 35-39 unknown \n", - " 40-44 unknown \n", - " 45-49 unknown \n", - " 50-54 unknown \n", - " 55-59 unknown \n", - " 60-64 unknown \n", - " 65-69 unknown \n", - " 70-74 09-Oct \n", - " 75-79 unknown \n", - " 80-84 unknown \n", - " 85-89 unknown \n", - " 90+ unknown \n", - "ethnicity_6_groups Black 09-Nov \n", - " Mixed 03-Dec \n", - " Other 15-Nov \n", - " South Asian unknown \n", - " Unknown 15-Nov \n", - " White unknown \n", - "dementia no unknown \n", - " yes unknown " + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.3 \n", + "sex F 1.3 \n", + " M 1.2 \n", + "ethnicity_6_groups Black 2.7 \n", + " Mixed 1.8 \n", + " Other 0.9 \n", + " South Asian 1.0 \n", + " Unknown 1.0 \n", + " White 0.0 \n", + "ethnicity_16_groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 3.1 \n", + " Caribbean 3.0 \n", + " Chinese 2.8 \n", + " Other 2.7 \n", + " Other Asian 0.0 \n", + " British or Mixed British 0.0 \n", + " Indian or British Indian 0.0 \n", + " Irish 0.0 \n", + " Other Black 2.9 \n", + " Other White 0.0 \n", + " Other mixed 0.0 \n", + " Pakistani or British Pakistani 2.9 \n", + " Unknown 1.2 \n", + " White + Asian 3.1 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 2.8 \n", + "imd_categories 1 Most deprived 1.7 \n", + " 2 0.8 \n", + " 3 1.6 \n", + " 4 0.8 \n", + " 5 Least deprived 1.6 \n", + " Unknown 0.0 \n", + "bmi 30+ 1.5 \n", + " under 30 1.4 \n", + "housebound no 1.2 \n", + " yes 14.3 \n", + "chronic_cardiac_disease no 1.2 \n", + " yes 0.0 \n", + "current_copd no 1.1 \n", + " yes 0.0 \n", + "dmards no 1.2 \n", + " yes 0.0 \n", + "dementia no 1.2 \n", + " yes 0.0 \n", + "psychosis_schiz_bipolar no 1.2 \n", + " yes 0.0 \n", + "LD no 1.3 \n", + " yes 0.0 \n", + "ssri no 1.3 \n", + " yes 0.0 \n", + "chemo_or_radio no 1.3 \n", + " yes 0.0 \n", + "lung_cancer no 1.3 \n", + " yes 0.0 \n", + "cancer_excl_lung_and_haem no 1.3 \n", + " yes 0.0 \n", + "haematological_cancer no 1.2 \n", + " yes 0.0 \n", + "ckd no 1.4 \n", + " yes 0.7 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 01-Apr \n", + "sex F 06-Apr \n", + " M 12-Apr \n", + "ethnicity_6_groups Black 07-Jan \n", + " Mixed 10-Feb \n", + " Other unknown \n", + " South Asian unknown \n", + " Unknown unknown \n", + " White unknown \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi 08-Jan \n", + " Caribbean 31-Dec \n", + " Chinese 26-Dec \n", + " Other 04-Jan \n", + " Other Asian unknown \n", + " British or Mixed British unknown \n", + " Indian or British Indian unknown \n", + " Irish unknown \n", + " Other Black 27-Dec \n", + " Other White unknown \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani 20-Dec \n", + " Unknown 20-Mar \n", + " White + Asian 28-Dec \n", + " White + Black African unknown \n", + " White + Black Caribbean 31-Jan \n", + "imd_categories 1 Most deprived 03-Mar \n", + " 2 unknown \n", + " 3 21-Feb \n", + " 4 unknown \n", + " 5 Least deprived 03-Mar \n", + " Unknown unknown \n", + "bmi 30+ 09-Mar \n", + " under 30 23-Mar \n", + "housebound no 15-Apr \n", + " yes 05-Nov \n", + "chronic_cardiac_disease no 15-Apr \n", + " yes unknown \n", + "current_copd no unknown \n", + " yes unknown \n", + "dmards no 15-Apr \n", + " yes unknown \n", + "dementia no 15-Apr \n", + " yes unknown \n", + "psychosis_schiz_bipolar no 15-Apr \n", + " yes unknown \n", + "LD no 01-Apr \n", + " yes unknown \n", + "ssri no 01-Apr \n", + " yes unknown \n", + "chemo_or_radio no 01-Apr \n", + " yes unknown \n", + "lung_cancer no 01-Apr \n", + " yes unknown \n", + "cancer_excl_lung_and_haem no 02-Apr \n", + " yes unknown \n", + "haematological_cancer no 15-Apr \n", + " yes unknown \n", + "ckd no 21-Mar \n", + " yes unknown " ] }, "metadata": {}, @@ -43941,7 +56115,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose 14weeks ago) among **shielding (aged 16-69)** population up to 2021-09-08" + "## COVID vaccination rollout (second dose 14w ago) among **LD (aged 16-64)** population up to 2021-10-27" ], "text/plain": [ "" @@ -43993,405 +56167,375 @@ " Date projected to reach 90%\n", " \n", " \n", - " category\n", - " group\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " overall\n", - " overall\n", - " 245\n", - " 58.3\n", - " 420\n", - " 56.7\n", - " 1.6\n", - " 24-Jan\n", - " \n", - " \n", - " newly_shielded_since_feb_15\n", - " no\n", - " 245\n", - " 59.3\n", - " 413\n", - " 57.6\n", - " 1.7\n", - " 12-Jan\n", + " category\n", + " group\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", + " \n", + " \n", " \n", - " yes\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", - " 0.0\n", + " overall\n", + " overall\n", + " 973\n", + " 60.7\n", + " 1603\n", + " 59.8\n", + " 0.9\n", " unknown\n", " \n", " \n", " sex\n", " F\n", - " 126\n", - " 58.1\n", - " 217\n", - " 58.1\n", - " 0.0\n", + " 462\n", + " 58.4\n", + " 791\n", + " 57.5\n", + " 0.9\n", " unknown\n", " \n", " \n", " M\n", - " 119\n", - " 58.6\n", - " 203\n", - " 55.2\n", - " 3.4\n", - " 11-Nov\n", + " 511\n", + " 62.9\n", + " 812\n", + " 62.1\n", + " 0.8\n", + " unknown\n", " \n", " \n", - " ageband\n", - " 16-29\n", - " 28\n", - " 50.0\n", - " 56\n", - " 37.5\n", - " 12.5\n", - " 30-Sep\n", + " ageband_5yr\n", + " 0\n", + " 7\n", + " 33.3\n", + " 21\n", + " 33.3\n", + " 0.0\n", + " unknown\n", " \n", " \n", - " 30-39\n", - " 35\n", - " 62.5\n", - " 56\n", - " 50.0\n", - " 12.5\n", - " 23-Sep\n", + " 0-15\n", + " 70\n", + " 66.7\n", + " 105\n", + " 60.0\n", + " 6.7\n", + " 20-Nov\n", " \n", " \n", - " 40-49\n", - " 35\n", - " 71.4\n", - " 49\n", - " 57.1\n", - " 14.3\n", - " 17-Sep\n", + " 16-17\n", + " 70\n", + " 62.5\n", + " 112\n", + " 56.2\n", + " 6.3\n", + " 26-Nov\n", " \n", " \n", - " 50-59\n", - " 42\n", - " 60.0\n", + " 18-29\n", " 70\n", + " 66.7\n", + " 105\n", " 60.0\n", - " 0.0\n", - " unknown\n", + " 6.7\n", + " 20-Nov\n", " \n", " \n", - " 60-69\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", + " 30-34\n", + " 63\n", + " 64.3\n", + " 98\n", + " 64.3\n", " 0.0\n", " unknown\n", " \n", " \n", - " 70-79\n", - " 56\n", - " 61.5\n", - " 91\n", - " 61.5\n", + " 35-39\n", + " 70\n", + " 66.7\n", + " 105\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " 80+\n", - " 28\n", - " 57.1\n", + " 40-44\n", " 49\n", - " 57.1\n", + " 58.3\n", + " 84\n", + " 58.3\n", " 0.0\n", " unknown\n", " \n", " \n", - " ethnicity_6_groups\n", - " Black\n", - " 35\n", - " 50.0\n", + " 45-49\n", " 70\n", - " 50.0\n", + " 58.8\n", + " 119\n", + " 58.8\n", " 0.0\n", " unknown\n", " \n", " \n", - " Mixed\n", - " 35\n", - " 50.0\n", - " 70\n", - " 50.0\n", + " 50-54\n", + " 77\n", + " 57.9\n", + " 133\n", + " 57.9\n", " 0.0\n", " unknown\n", " \n", " \n", - " Other\n", - " 49\n", - " 70.0\n", + " 55-59\n", " 70\n", - " 70.0\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " South Asian\n", - " 42\n", " 66.7\n", - " 63\n", + " 105\n", " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " Unknown\n", - " 35\n", - " 62.5\n", + " 60-64\n", " 56\n", - " 62.5\n", + " 57.1\n", + " 98\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " White\n", - " 42\n", - " 46.2\n", - " 91\n", - " 46.2\n", + " 65-69\n", + " 56\n", + " 57.1\n", + " 98\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " imd_categories\n", - " 1 Most deprived\n", - " 42\n", - " 50.0\n", - " 84\n", - " 50.0\n", + " 70-74\n", + " 56\n", + " 61.5\n", + " 91\n", + " 61.5\n", " 0.0\n", " unknown\n", " \n", " \n", - " 2\n", - " 42\n", + " 75-79\n", + " 63\n", + " 60.0\n", + " 105\n", " 60.0\n", - " 70\n", - " 50.0\n", - " 10.0\n", - " 29-Sep\n", - " \n", - " \n", - " 3\n", - " 49\n", - " 58.3\n", - " 84\n", - " 58.3\n", " 0.0\n", " unknown\n", " \n", " \n", - " 4\n", + " 80-84\n", " 56\n", - " 66.7\n", - " 84\n", - " 66.7\n", + " 57.1\n", + " 98\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " 5 Least deprived\n", - " 42\n", - " 54.5\n", - " 77\n", - " 54.5\n", + " 85-89\n", + " 63\n", + " 60.0\n", + " 105\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " Unknown\n", + " 90+\n", " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 100.0\n", + " 14\n", + " 100.0\n", + " 0.0\n", + " reached\n", + " \n", + " \n", + " ethnicity_6_groups\n", + " Black\n", + " 161\n", + " 59.0\n", + " 273\n", + " 59.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " LD\n", - " no\n", - " 245\n", - " 59.3\n", - " 413\n", - " 57.6\n", - " 1.7\n", + " Mixed\n", + " 175\n", + " 62.5\n", + " 280\n", + " 60.0\n", + " 2.5\n", " 12-Jan\n", " \n", " \n", - " yes\n", - " 0\n", - " 0.0\n", - " 0\n", - " NaN\n", + " Other\n", + " 161\n", + " 54.8\n", + " 294\n", + " 54.8\n", " 0.0\n", " unknown\n", " \n", " \n", - " ckd\n", - " no\n", - " 189\n", - " 58.7\n", - " 322\n", - " 58.7\n", + " South Asian\n", + " 161\n", + " 59.0\n", + " 273\n", + " 59.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " yes\n", - " 56\n", - " 57.1\n", - " 98\n", - " 50.0\n", - " 7.1\n", - " 10-Oct\n", + " Unknown\n", + " 154\n", + " 68.8\n", + " 224\n", + " 65.6\n", + " 3.2\n", + " 12-Dec\n", + " \n", + " \n", + " White\n", + " 161\n", + " 62.2\n", + " 259\n", + " 59.5\n", + " 2.7\n", + " 07-Jan\n", " \n", " \n", "\n", "" ], "text/plain": [ - " vaccinated percent total \\\n", - "category group \n", - "overall overall 245 58.3 420 \n", - "newly_shielded_since_feb_15 no 245 59.3 413 \n", - " yes 0 0.0 0 \n", - "sex F 126 58.1 217 \n", - " M 119 58.6 203 \n", - "ageband 16-29 28 50.0 56 \n", - " 30-39 35 62.5 56 \n", - " 40-49 35 71.4 49 \n", - " 50-59 42 60.0 70 \n", - " 60-69 28 57.1 49 \n", - " 70-79 56 61.5 91 \n", - " 80+ 28 57.1 49 \n", - "ethnicity_6_groups Black 35 50.0 70 \n", - " Mixed 35 50.0 70 \n", - " Other 49 70.0 70 \n", - " South Asian 42 66.7 63 \n", - " Unknown 35 62.5 56 \n", - " White 42 46.2 91 \n", - "imd_categories 1 Most deprived 42 50.0 84 \n", - " 2 42 60.0 70 \n", - " 3 49 58.3 84 \n", - " 4 56 66.7 84 \n", - " 5 Least deprived 42 54.5 77 \n", - " Unknown 14 66.7 21 \n", - "LD no 245 59.3 413 \n", - " yes 0 0.0 0 \n", - "ckd no 189 58.7 322 \n", - " yes 56 57.1 98 \n", + " vaccinated percent total \\\n", + "category group \n", + "overall overall 973 60.7 1603 \n", + "sex F 462 58.4 791 \n", + " M 511 62.9 812 \n", + "ageband_5yr 0 7 33.3 21 \n", + " 0-15 70 66.7 105 \n", + " 16-17 70 62.5 112 \n", + " 18-29 70 66.7 105 \n", + " 30-34 63 64.3 98 \n", + " 35-39 70 66.7 105 \n", + " 40-44 49 58.3 84 \n", + " 45-49 70 58.8 119 \n", + " 50-54 77 57.9 133 \n", + " 55-59 70 66.7 105 \n", + " 60-64 56 57.1 98 \n", + " 65-69 56 57.1 98 \n", + " 70-74 56 61.5 91 \n", + " 75-79 63 60.0 105 \n", + " 80-84 56 57.1 98 \n", + " 85-89 63 60.0 105 \n", + " 90+ 14 100.0 14 \n", + "ethnicity_6_groups Black 161 59.0 273 \n", + " Mixed 175 62.5 280 \n", + " Other 161 54.8 294 \n", + " South Asian 161 59.0 273 \n", + " Unknown 154 68.8 224 \n", + " White 161 62.2 259 \n", "\n", - " vaccinated 7d previous (percent) \\\n", - "category group \n", - "overall overall 56.7 \n", - "newly_shielded_since_feb_15 no 57.6 \n", - " yes NaN \n", - "sex F 58.1 \n", - " M 55.2 \n", - "ageband 16-29 37.5 \n", - " 30-39 50.0 \n", - " 40-49 57.1 \n", - " 50-59 60.0 \n", - " 60-69 57.1 \n", - " 70-79 61.5 \n", - " 80+ 57.1 \n", - "ethnicity_6_groups Black 50.0 \n", - " Mixed 50.0 \n", - " Other 70.0 \n", - " South Asian 66.7 \n", - " Unknown 62.5 \n", - " White 46.2 \n", - "imd_categories 1 Most deprived 50.0 \n", - " 2 50.0 \n", - " 3 58.3 \n", - " 4 66.7 \n", - " 5 Least deprived 54.5 \n", - " Unknown 66.7 \n", - "LD no 57.6 \n", - " yes NaN \n", - "ckd no 58.7 \n", - " yes 50.0 \n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.8 \n", + "sex F 57.5 \n", + " M 62.1 \n", + "ageband_5yr 0 33.3 \n", + " 0-15 60.0 \n", + " 16-17 56.2 \n", + " 18-29 60.0 \n", + " 30-34 64.3 \n", + " 35-39 66.7 \n", + " 40-44 58.3 \n", + " 45-49 58.8 \n", + " 50-54 57.9 \n", + " 55-59 66.7 \n", + " 60-64 57.1 \n", + " 65-69 57.1 \n", + " 70-74 61.5 \n", + " 75-79 60.0 \n", + " 80-84 57.1 \n", + " 85-89 60.0 \n", + " 90+ 100.0 \n", + "ethnicity_6_groups Black 59.0 \n", + " Mixed 60.0 \n", + " Other 54.8 \n", + " South Asian 59.0 \n", + " Unknown 65.6 \n", + " White 59.5 \n", "\n", - " Uptake over last 7d (percent) \\\n", - "category group \n", - "overall overall 1.6 \n", - "newly_shielded_since_feb_15 no 1.7 \n", - " yes 0.0 \n", - "sex F 0.0 \n", - " M 3.4 \n", - "ageband 16-29 12.5 \n", - " 30-39 12.5 \n", - " 40-49 14.3 \n", - " 50-59 0.0 \n", - " 60-69 0.0 \n", - " 70-79 0.0 \n", - " 80+ 0.0 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 0.0 \n", - " Other 0.0 \n", - " South Asian 0.0 \n", - " Unknown 0.0 \n", - " White 0.0 \n", - "imd_categories 1 Most deprived 0.0 \n", - " 2 10.0 \n", - " 3 0.0 \n", - " 4 0.0 \n", - " 5 Least deprived 0.0 \n", - " Unknown 0.0 \n", - "LD no 1.7 \n", - " yes 0.0 \n", - "ckd no 0.0 \n", - " yes 7.1 \n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 0.9 \n", + "sex F 0.9 \n", + " M 0.8 \n", + "ageband_5yr 0 0.0 \n", + " 0-15 6.7 \n", + " 16-17 6.3 \n", + " 18-29 6.7 \n", + " 30-34 0.0 \n", + " 35-39 0.0 \n", + " 40-44 0.0 \n", + " 45-49 0.0 \n", + " 50-54 0.0 \n", + " 55-59 0.0 \n", + " 60-64 0.0 \n", + " 65-69 0.0 \n", + " 70-74 0.0 \n", + " 75-79 0.0 \n", + " 80-84 0.0 \n", + " 85-89 0.0 \n", + " 90+ 0.0 \n", + "ethnicity_6_groups Black 0.0 \n", + " Mixed 2.5 \n", + " Other 0.0 \n", + " South Asian 0.0 \n", + " Unknown 3.2 \n", + " White 2.7 \n", "\n", - " Date projected to reach 90% \n", - "category group \n", - "overall overall 24-Jan \n", - "newly_shielded_since_feb_15 no 12-Jan \n", - " yes unknown \n", - "sex F unknown \n", - " M 11-Nov \n", - "ageband 16-29 30-Sep \n", - " 30-39 23-Sep \n", - " 40-49 17-Sep \n", - " 50-59 unknown \n", - " 60-69 unknown \n", - " 70-79 unknown \n", - " 80+ unknown \n", - "ethnicity_6_groups Black unknown \n", - " Mixed unknown \n", - " Other unknown \n", - " South Asian unknown \n", - " Unknown unknown \n", - " White unknown \n", - "imd_categories 1 Most deprived unknown \n", - " 2 29-Sep \n", - " 3 unknown \n", - " 4 unknown \n", - " 5 Least deprived unknown \n", - " Unknown unknown \n", - "LD no 12-Jan \n", - " yes unknown \n", - "ckd no unknown \n", - " yes 10-Oct " + " Date projected to reach 90% \n", + "category group \n", + "overall overall unknown \n", + "sex F unknown \n", + " M unknown \n", + "ageband_5yr 0 unknown \n", + " 0-15 20-Nov \n", + " 16-17 26-Nov \n", + " 18-29 20-Nov \n", + " 30-34 unknown \n", + " 35-39 unknown \n", + " 40-44 unknown \n", + " 45-49 unknown \n", + " 50-54 unknown \n", + " 55-59 unknown \n", + " 60-64 unknown \n", + " 65-69 unknown \n", + " 70-74 unknown \n", + " 75-79 unknown \n", + " 80-84 unknown \n", + " 85-89 unknown \n", + " 90+ reached \n", + "ethnicity_6_groups Black unknown \n", + " Mixed 12-Jan \n", + " Other unknown \n", + " South Asian unknown \n", + " Unknown 12-Dec \n", + " White 07-Jan " ] }, "metadata": {}, @@ -44420,7 +56564,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose 14weeks ago) among **65-69** population up to 2021-09-08" + "## COVID vaccination rollout (second dose 14w ago) among **60-64** population up to 2021-10-27" ], "text/plain": [ "" @@ -44486,561 +56630,523 @@ " \n", " overall\n", " overall\n", - " 1267\n", - " 58.4\n", - " 2170\n", - " 56.5\n", - " 1.9\n", - " 02-Jan\n", + " 3248\n", + " 59.6\n", + " 5453\n", + " 57.9\n", + " 1.7\n", + " 01-Mar\n", " \n", " \n", " sex\n", " F\n", - " 644\n", - " 60.1\n", - " 1071\n", - " 58.8\n", - " 1.3\n", - " 16-Feb\n", + " 1680\n", + " 59.9\n", + " 2807\n", + " 58.1\n", + " 1.8\n", + " 21-Feb\n", " \n", " \n", " M\n", - " 623\n", - " 56.7\n", - " 1099\n", - " 54.1\n", - " 2.6\n", - " 06-Dec\n", + " 1568\n", + " 59.3\n", + " 2646\n", + " 57.7\n", + " 1.6\n", + " 10-Mar\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 231\n", - " 62.3\n", - " 371\n", - " 60.4\n", - " 1.9\n", - " 19-Dec\n", + " 581\n", + " 60.6\n", + " 959\n", + " 58.4\n", + " 2.2\n", + " 28-Jan\n", " \n", " \n", " Mixed\n", - " 189\n", - " 54.0\n", - " 350\n", - " 52.0\n", - " 2.0\n", - " 12-Jan\n", + " 574\n", + " 60.7\n", + " 945\n", + " 59.3\n", + " 1.4\n", + " 22-Mar\n", " \n", " \n", " Other\n", - " 196\n", - " 56.0\n", - " 350\n", - " 54.0\n", - " 2.0\n", - " 05-Jan\n", + " 532\n", + " 60.3\n", + " 882\n", + " 58.7\n", + " 1.6\n", + " 05-Mar\n", " \n", " \n", " South Asian\n", - " 252\n", - " 63.2\n", - " 399\n", - " 61.4\n", - " 1.8\n", - " 21-Dec\n", + " 546\n", + " 59.5\n", + " 917\n", + " 58.0\n", + " 1.5\n", + " 18-Mar\n", " \n", " \n", " Unknown\n", - " 196\n", - " 58.3\n", - " 336\n", - " 56.2\n", - " 2.1\n", - " 22-Dec\n", + " 469\n", + " 57.3\n", + " 819\n", + " 56.4\n", + " 0.9\n", + " unknown\n", " \n", " \n", " White\n", - " 210\n", - " 57.7\n", - " 364\n", - " 55.8\n", - " 1.9\n", - " 05-Jan\n", + " 546\n", + " 58.2\n", + " 938\n", + " 56.0\n", + " 2.2\n", + " 05-Feb\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 70\n", + " 175\n", " 62.5\n", - " 112\n", + " 280\n", " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 70\n", - " 55.6\n", - " 126\n", - " 55.6\n", - " 0.0\n", - " unknown\n", + " 175\n", + " 58.1\n", + " 301\n", + " 53.5\n", + " 4.6\n", + " 14-Dec\n", " \n", " \n", " Caribbean\n", - " 49\n", - " 46.7\n", - " 105\n", - " 46.7\n", - " 0.0\n", - " unknown\n", + " 182\n", + " 60.5\n", + " 301\n", + " 58.1\n", + " 2.4\n", + " 21-Jan\n", " \n", " \n", " Chinese\n", - " 70\n", - " 62.5\n", - " 112\n", - " 56.2\n", - " 6.3\n", - " 08-Oct\n", + " 168\n", + " 55.8\n", + " 301\n", + " 53.5\n", + " 2.3\n", + " 08-Feb\n", " \n", " \n", " Other\n", - " 77\n", - " 57.9\n", - " 133\n", - " 57.9\n", + " 189\n", + " 62.8\n", + " 301\n", + " 62.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 77\n", - " 61.1\n", - " 126\n", - " 61.1\n", - " 0.0\n", - " unknown\n", + " 182\n", + " 60.5\n", + " 301\n", + " 58.1\n", + " 2.4\n", + " 21-Jan\n", " \n", " \n", " British or Mixed British\n", - " 77\n", - " 68.8\n", - " 112\n", - " 62.5\n", - " 6.3\n", - " 01-Oct\n", + " 161\n", + " 62.2\n", + " 259\n", + " 59.5\n", + " 2.7\n", + " 07-Jan\n", " \n", " \n", " Indian or British Indian\n", - " 63\n", - " 60.0\n", - " 105\n", - " 53.3\n", - " 6.7\n", - " 09-Oct\n", + " 161\n", + " 59.0\n", + " 273\n", + " 56.4\n", + " 2.6\n", + " 18-Jan\n", " \n", " \n", " Irish\n", - " 70\n", - " 62.5\n", - " 112\n", - " 62.5\n", + " 168\n", + " 60.0\n", + " 280\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 70\n", - " 62.5\n", - " 112\n", - " 56.2\n", - " 6.3\n", - " 08-Oct\n", + " 175\n", + " 61.0\n", + " 287\n", + " 58.5\n", + " 2.5\n", + " 16-Jan\n", " \n", " \n", " Other White\n", - " 70\n", - " 62.5\n", - " 112\n", - " 62.5\n", - " 0.0\n", - " unknown\n", + " 161\n", + " 59.0\n", + " 273\n", + " 56.4\n", + " 2.6\n", + " 18-Jan\n", " \n", " \n", " Other mixed\n", - " 42\n", - " 46.2\n", - " 91\n", - " 46.2\n", - " 0.0\n", - " unknown\n", + " 154\n", + " 57.9\n", + " 266\n", + " 55.3\n", + " 2.6\n", + " 21-Jan\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 77\n", - " 57.9\n", - " 133\n", - " 52.6\n", - " 5.3\n", - " 20-Oct\n", + " 182\n", + " 60.5\n", + " 301\n", + " 58.1\n", + " 2.4\n", + " 21-Jan\n", " \n", " \n", " Unknown\n", - " 182\n", - " 55.3\n", - " 329\n", - " 53.2\n", - " 2.1\n", - " 01-Jan\n", + " 490\n", + " 58.8\n", + " 833\n", + " 57.1\n", + " 1.7\n", + " 04-Mar\n", " \n", " \n", " White + Asian\n", - " 70\n", - " 62.5\n", - " 112\n", - " 62.5\n", - " 0.0\n", - " unknown\n", + " 182\n", + " 63.4\n", + " 287\n", + " 61.0\n", + " 2.4\n", + " 12-Jan\n", " \n", " \n", " White + Black African\n", - " 70\n", - " 58.8\n", - " 119\n", - " 52.9\n", - " 5.9\n", - " 15-Oct\n", + " 189\n", + " 62.8\n", + " 301\n", + " 62.8\n", + " 0.0\n", + " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 70\n", - " 55.6\n", - " 126\n", - " 55.6\n", - " 0.0\n", - " unknown\n", + " 168\n", + " 53.3\n", + " 315\n", + " 51.1\n", + " 2.2\n", + " 20-Feb\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 217\n", - " 55.4\n", - " 392\n", - " 55.4\n", - " 0.0\n", - " unknown\n", + " 574\n", + " 56.6\n", + " 1015\n", + " 54.5\n", + " 2.1\n", + " 15-Feb\n", " \n", " \n", " 2\n", - " 252\n", - " 56.2\n", - " 448\n", - " 54.7\n", - " 1.5\n", - " 12-Feb\n", + " 609\n", + " 58.8\n", + " 1036\n", + " 56.1\n", + " 2.7\n", + " 15-Jan\n", " \n", " \n", " 3\n", - " 245\n", - " 59.3\n", - " 413\n", - " 57.6\n", - " 1.7\n", - " 12-Jan\n", + " 658\n", + " 61.4\n", + " 1071\n", + " 59.5\n", + " 1.9\n", + " 09-Feb\n", " \n", " \n", " 4\n", - " 252\n", - " 62.1\n", - " 406\n", - " 60.3\n", - " 1.8\n", - " 25-Dec\n", + " 609\n", + " 60.8\n", + " 1001\n", + " 59.4\n", + " 1.4\n", + " 22-Mar\n", " \n", " \n", " 5 Least deprived\n", - " 238\n", - " 58.6\n", - " 406\n", - " 55.2\n", - " 3.4\n", - " 11-Nov\n", + " 644\n", + " 60.9\n", + " 1057\n", + " 59.6\n", + " 1.3\n", + " 01-Apr\n", " \n", " \n", " Unknown\n", - " 63\n", - " 60.0\n", - " 105\n", - " 53.3\n", - " 6.7\n", - " 09-Oct\n", + " 154\n", + " 55.0\n", + " 280\n", + " 55.0\n", + " 0.0\n", + " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 350\n", - " 56.8\n", - " 616\n", - " 55.7\n", - " 1.1\n", - " unknown\n", - " \n", - " \n", - " under 30\n", - " 917\n", - " 59.0\n", - " 1554\n", - " 56.8\n", + " 966\n", + " 59.5\n", + " 1624\n", + " 57.3\n", " 2.2\n", - " 15-Dec\n", - " \n", - " \n", - " housebound\n", - " no\n", - " 1260\n", - " 58.4\n", - " 2156\n", - " 56.5\n", - " 1.9\n", - " 02-Jan\n", + " 01-Feb\n", " \n", " \n", - " yes\n", - " 7\n", - " 50.0\n", - " 14\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " under 30\n", + " 2282\n", + " 59.6\n", + " 3829\n", + " 58.1\n", + " 1.5\n", + " 17-Mar\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1246\n", - " 58.4\n", - " 2135\n", - " 56.7\n", + " 3220\n", + " 59.5\n", + " 5411\n", + " 57.8\n", " 1.7\n", - " 16-Jan\n", - " \n", - " \n", - " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 40.0\n", - " 20.0\n", - " 18-Sep\n", - " \n", - " \n", - " current_copd\n", - " no\n", - " 1253\n", - " 58.3\n", - " 2149\n", - " 56.4\n", - " 1.9\n", - " 02-Jan\n", + " 01-Mar\n", " \n", " \n", " yes\n", - " 14\n", + " 28\n", " 66.7\n", - " 21\n", + " 42\n", " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " dmards\n", + " current_copd\n", " no\n", - " 1260\n", - " 58.6\n", - " 2149\n", - " 56.7\n", - " 1.9\n", - " 01-Jan\n", + " 3213\n", + " 59.5\n", + " 5397\n", + " 58.0\n", + " 1.5\n", + " 18-Mar\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", - " 0.0\n", - " unknown\n", + " 35\n", + " 62.5\n", + " 56\n", + " 50.0\n", + " 12.5\n", + " 11-Nov\n", " \n", " \n", - " dementia\n", + " dmards\n", " no\n", - " 1260\n", - " 58.6\n", - " 2149\n", - " 56.7\n", - " 1.9\n", - " 01-Jan\n", + " 3220\n", + " 59.7\n", + " 5397\n", + " 58.0\n", + " 1.7\n", + " 28-Feb\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 28\n", + " 50.0\n", + " 56\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " psychosis_schiz_bipolar\n", + " dementia\n", " no\n", - " 1253\n", - " 58.3\n", - " 2149\n", - " 56.4\n", - " 1.9\n", - " 02-Jan\n", + " 3192\n", + " 59.4\n", + " 5376\n", + " 57.8\n", + " 1.6\n", + " 09-Mar\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 49\n", + " 63.6\n", + " 77\n", + " 63.6\n", " 0.0\n", " unknown\n", " \n", " \n", - " LD\n", + " psychosis_schiz_bipolar\n", " no\n", - " 1239\n", - " 58.2\n", - " 2128\n", - " 56.2\n", - " 2.0\n", - " 28-Dec\n", + " 3213\n", + " 59.5\n", + " 5404\n", + " 57.9\n", + " 1.6\n", + " 09-Mar\n", " \n", " \n", " yes\n", " 28\n", - " 66.7\n", - " 42\n", - " 66.7\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1253\n", - " 58.3\n", - " 2149\n", - " 56.7\n", - " 1.6\n", - " 24-Jan\n", + " 3220\n", + " 59.6\n", + " 5404\n", + " 57.9\n", + " 1.7\n", + " 01-Mar\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 1253\n", - " 58.3\n", - " 2149\n", - " 56.4\n", - " 1.9\n", - " 02-Jan\n", + " 3213\n", + " 59.5\n", + " 5397\n", + " 58.0\n", + " 1.5\n", + " 18-Mar\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 35\n", + " 55.6\n", + " 63\n", + " 44.4\n", + " 11.2\n", + " 17-Nov\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1253\n", - " 58.3\n", - " 2149\n", - " 56.4\n", - " 1.9\n", - " 02-Jan\n", + " 3220\n", + " 59.5\n", + " 5411\n", + " 57.8\n", + " 1.7\n", + " 01-Mar\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 28\n", + " 57.1\n", + " 49\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1260\n", - " 58.6\n", - " 2149\n", - " 56.7\n", - " 1.9\n", - " 01-Jan\n", + " 3213\n", + " 59.5\n", + " 5397\n", + " 57.8\n", + " 1.7\n", + " 01-Mar\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 35\n", + " 62.5\n", + " 56\n", + " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1253\n", - " 58.3\n", - " 2149\n", - " 56.7\n", - " 1.6\n", - " 24-Jan\n", + " 3213\n", + " 59.5\n", + " 5404\n", + " 57.8\n", + " 1.7\n", + " 01-Mar\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 35\n", + " 71.4\n", + " 49\n", + " 71.4\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1015\n", - " 58.5\n", - " 1736\n", - " 56.5\n", - " 2.0\n", - " 27-Dec\n", + " 2611\n", + " 59.3\n", + " 4403\n", + " 57.7\n", + " 1.6\n", + " 10-Mar\n", " \n", " \n", " yes\n", - " 252\n", - " 58.1\n", - " 434\n", - " 56.5\n", - " 1.6\n", - " 25-Jan\n", + " 630\n", + " 59.6\n", + " 1057\n", + " 58.3\n", + " 1.3\n", + " 08-Apr\n", " \n", " \n", "\n", @@ -45049,318 +57155,298 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1267 \n", - "sex F 644 \n", - " M 623 \n", - "ethnicity_6_groups Black 231 \n", - " Mixed 189 \n", - " Other 196 \n", - " South Asian 252 \n", - " Unknown 196 \n", - " White 210 \n", - "ethnicity_16_groups African 70 \n", - " Bangladeshi or British Bangladeshi 70 \n", - " Caribbean 49 \n", - " Chinese 70 \n", - " Other 77 \n", - " Other Asian 77 \n", - " British or Mixed British 77 \n", - " Indian or British Indian 63 \n", - " Irish 70 \n", - " Other Black 70 \n", - " Other White 70 \n", - " Other mixed 42 \n", - " Pakistani or British Pakistani 77 \n", - " Unknown 182 \n", - " White + Asian 70 \n", - " White + Black African 70 \n", - " White + Black Caribbean 70 \n", - "imd_categories 1 Most deprived 217 \n", - " 2 252 \n", - " 3 245 \n", - " 4 252 \n", - " 5 Least deprived 238 \n", - " Unknown 63 \n", - "bmi 30+ 350 \n", - " under 30 917 \n", - "housebound no 1260 \n", - " yes 7 \n", - "chronic_cardiac_disease no 1246 \n", - " yes 21 \n", - "current_copd no 1253 \n", - " yes 14 \n", - "dmards no 1260 \n", - " yes 7 \n", - "dementia no 1260 \n", - " yes 7 \n", - "psychosis_schiz_bipolar no 1253 \n", - " yes 14 \n", - "LD no 1239 \n", + "overall overall 3248 \n", + "sex F 1680 \n", + " M 1568 \n", + "ethnicity_6_groups Black 581 \n", + " Mixed 574 \n", + " Other 532 \n", + " South Asian 546 \n", + " Unknown 469 \n", + " White 546 \n", + "ethnicity_16_groups African 175 \n", + " Bangladeshi or British Bangladeshi 175 \n", + " Caribbean 182 \n", + " Chinese 168 \n", + " Other 189 \n", + " Other Asian 182 \n", + " British or Mixed British 161 \n", + " Indian or British Indian 161 \n", + " Irish 168 \n", + " Other Black 175 \n", + " Other White 161 \n", + " Other mixed 154 \n", + " Pakistani or British Pakistani 182 \n", + " Unknown 490 \n", + " White + Asian 182 \n", + " White + Black African 189 \n", + " White + Black Caribbean 168 \n", + "imd_categories 1 Most deprived 574 \n", + " 2 609 \n", + " 3 658 \n", + " 4 609 \n", + " 5 Least deprived 644 \n", + " Unknown 154 \n", + "bmi 30+ 966 \n", + " under 30 2282 \n", + "chronic_cardiac_disease no 3220 \n", " yes 28 \n", - "ssri no 1253 \n", - " yes 14 \n", - "chemo_or_radio no 1253 \n", - " yes 14 \n", - "lung_cancer no 1253 \n", - " yes 14 \n", - "cancer_excl_lung_and_haem no 1260 \n", - " yes 7 \n", - "haematological_cancer no 1253 \n", - " yes 14 \n", - "ckd no 1015 \n", - " yes 252 \n", - "\n", - " percent total \\\n", - "category group \n", - "overall overall 58.4 2170 \n", - "sex F 60.1 1071 \n", - " M 56.7 1099 \n", - "ethnicity_6_groups Black 62.3 371 \n", - " Mixed 54.0 350 \n", - " Other 56.0 350 \n", - " South Asian 63.2 399 \n", - " Unknown 58.3 336 \n", - " White 57.7 364 \n", - "ethnicity_16_groups African 62.5 112 \n", - " Bangladeshi or British Bangladeshi 55.6 126 \n", - " Caribbean 46.7 105 \n", - " Chinese 62.5 112 \n", - " Other 57.9 133 \n", - " Other Asian 61.1 126 \n", - " British or Mixed British 68.8 112 \n", - " Indian or British Indian 60.0 105 \n", - " Irish 62.5 112 \n", - " Other Black 62.5 112 \n", - " Other White 62.5 112 \n", - " Other mixed 46.2 91 \n", - " Pakistani or British Pakistani 57.9 133 \n", - " Unknown 55.3 329 \n", - " White + Asian 62.5 112 \n", - " White + Black African 58.8 119 \n", - " White + Black Caribbean 55.6 126 \n", - "imd_categories 1 Most deprived 55.4 392 \n", - " 2 56.2 448 \n", - " 3 59.3 413 \n", - " 4 62.1 406 \n", - " 5 Least deprived 58.6 406 \n", - " Unknown 60.0 105 \n", - "bmi 30+ 56.8 616 \n", - " under 30 59.0 1554 \n", - "housebound no 58.4 2156 \n", - " yes 50.0 14 \n", - "chronic_cardiac_disease no 58.4 2135 \n", - " yes 60.0 35 \n", - "current_copd no 58.3 2149 \n", - " yes 66.7 21 \n", - "dmards no 58.6 2149 \n", - " yes 33.3 21 \n", - "dementia no 58.6 2149 \n", - " yes 33.3 21 \n", - "psychosis_schiz_bipolar no 58.3 2149 \n", - " yes 66.7 21 \n", - "LD no 58.2 2128 \n", - " yes 66.7 42 \n", - "ssri no 58.3 2149 \n", - " yes 66.7 21 \n", - "chemo_or_radio no 58.3 2149 \n", - " yes 66.7 21 \n", - "lung_cancer no 58.3 2149 \n", - " yes 66.7 21 \n", - "cancer_excl_lung_and_haem no 58.6 2149 \n", - " yes 33.3 21 \n", - "haematological_cancer no 58.3 2149 \n", - " yes 66.7 21 \n", - "ckd no 58.5 1736 \n", - " yes 58.1 434 \n", - "\n", - " vaccinated 7d previous (percent) \\\n", - "category group \n", - "overall overall 56.5 \n", - "sex F 58.8 \n", - " M 54.1 \n", - "ethnicity_6_groups Black 60.4 \n", - " Mixed 52.0 \n", - " Other 54.0 \n", - " South Asian 61.4 \n", - " Unknown 56.2 \n", - " White 55.8 \n", - "ethnicity_16_groups African 62.5 \n", - " Bangladeshi or British Bangladeshi 55.6 \n", - " Caribbean 46.7 \n", - " Chinese 56.2 \n", - " Other 57.9 \n", - " Other Asian 61.1 \n", - " British or Mixed British 62.5 \n", - " Indian or British Indian 53.3 \n", - " Irish 62.5 \n", - " Other Black 56.2 \n", - " Other White 62.5 \n", - " Other mixed 46.2 \n", - " Pakistani or British Pakistani 52.6 \n", - " Unknown 53.2 \n", - " White + Asian 62.5 \n", - " White + Black African 52.9 \n", - " White + Black Caribbean 55.6 \n", - "imd_categories 1 Most deprived 55.4 \n", - " 2 54.7 \n", - " 3 57.6 \n", - " 4 60.3 \n", - " 5 Least deprived 55.2 \n", - " Unknown 53.3 \n", - "bmi 30+ 55.7 \n", - " under 30 56.8 \n", - "housebound no 56.5 \n", - " yes 50.0 \n", - "chronic_cardiac_disease no 56.7 \n", - " yes 40.0 \n", - "current_copd no 56.4 \n", - " yes 66.7 \n", - "dmards no 56.7 \n", - " yes 33.3 \n", - "dementia no 56.7 \n", - " yes 33.3 \n", - "psychosis_schiz_bipolar no 56.4 \n", - " yes 66.7 \n", - "LD no 56.2 \n", - " yes 66.7 \n", - "ssri no 56.7 \n", - " yes 66.7 \n", - "chemo_or_radio no 56.4 \n", - " yes 66.7 \n", - "lung_cancer no 56.4 \n", - " yes 66.7 \n", - "cancer_excl_lung_and_haem no 56.7 \n", - " yes 33.3 \n", - "haematological_cancer no 56.7 \n", + "current_copd no 3213 \n", + " yes 35 \n", + "dmards no 3220 \n", + " yes 28 \n", + "dementia no 3192 \n", + " yes 49 \n", + "psychosis_schiz_bipolar no 3213 \n", + " yes 28 \n", + "ssri no 3220 \n", + " yes 28 \n", + "chemo_or_radio no 3213 \n", + " yes 35 \n", + "lung_cancer no 3220 \n", + " yes 28 \n", + "cancer_excl_lung_and_haem no 3213 \n", + " yes 35 \n", + "haematological_cancer no 3213 \n", + " yes 35 \n", + "ckd no 2611 \n", + " yes 630 \n", + "\n", + " percent total \\\n", + "category group \n", + "overall overall 59.6 5453 \n", + "sex F 59.9 2807 \n", + " M 59.3 2646 \n", + "ethnicity_6_groups Black 60.6 959 \n", + " Mixed 60.7 945 \n", + " Other 60.3 882 \n", + " South Asian 59.5 917 \n", + " Unknown 57.3 819 \n", + " White 58.2 938 \n", + "ethnicity_16_groups African 62.5 280 \n", + " Bangladeshi or British Bangladeshi 58.1 301 \n", + " Caribbean 60.5 301 \n", + " Chinese 55.8 301 \n", + " Other 62.8 301 \n", + " Other Asian 60.5 301 \n", + " British or Mixed British 62.2 259 \n", + " Indian or British Indian 59.0 273 \n", + " Irish 60.0 280 \n", + " Other Black 61.0 287 \n", + " Other White 59.0 273 \n", + " Other mixed 57.9 266 \n", + " Pakistani or British Pakistani 60.5 301 \n", + " Unknown 58.8 833 \n", + " White + Asian 63.4 287 \n", + " White + Black African 62.8 301 \n", + " White + Black Caribbean 53.3 315 \n", + "imd_categories 1 Most deprived 56.6 1015 \n", + " 2 58.8 1036 \n", + " 3 61.4 1071 \n", + " 4 60.8 1001 \n", + " 5 Least deprived 60.9 1057 \n", + " Unknown 55.0 280 \n", + "bmi 30+ 59.5 1624 \n", + " under 30 59.6 3829 \n", + "chronic_cardiac_disease no 59.5 5411 \n", + " yes 66.7 42 \n", + "current_copd no 59.5 5397 \n", + " yes 62.5 56 \n", + "dmards no 59.7 5397 \n", + " yes 50.0 56 \n", + "dementia no 59.4 5376 \n", + " yes 63.6 77 \n", + "psychosis_schiz_bipolar no 59.5 5404 \n", + " yes 57.1 49 \n", + "ssri no 59.6 5404 \n", + " yes 57.1 49 \n", + "chemo_or_radio no 59.5 5397 \n", + " yes 55.6 63 \n", + "lung_cancer no 59.5 5411 \n", + " yes 57.1 49 \n", + "cancer_excl_lung_and_haem no 59.5 5397 \n", + " yes 62.5 56 \n", + "haematological_cancer no 59.5 5404 \n", + " yes 71.4 49 \n", + "ckd no 59.3 4403 \n", + " yes 59.6 1057 \n", + "\n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 57.9 \n", + "sex F 58.1 \n", + " M 57.7 \n", + "ethnicity_6_groups Black 58.4 \n", + " Mixed 59.3 \n", + " Other 58.7 \n", + " South Asian 58.0 \n", + " Unknown 56.4 \n", + " White 56.0 \n", + "ethnicity_16_groups African 62.5 \n", + " Bangladeshi or British Bangladeshi 53.5 \n", + " Caribbean 58.1 \n", + " Chinese 53.5 \n", + " Other 62.8 \n", + " Other Asian 58.1 \n", + " British or Mixed British 59.5 \n", + " Indian or British Indian 56.4 \n", + " Irish 60.0 \n", + " Other Black 58.5 \n", + " Other White 56.4 \n", + " Other mixed 55.3 \n", + " Pakistani or British Pakistani 58.1 \n", + " Unknown 57.1 \n", + " White + Asian 61.0 \n", + " White + Black African 62.8 \n", + " White + Black Caribbean 51.1 \n", + "imd_categories 1 Most deprived 54.5 \n", + " 2 56.1 \n", + " 3 59.5 \n", + " 4 59.4 \n", + " 5 Least deprived 59.6 \n", + " Unknown 55.0 \n", + "bmi 30+ 57.3 \n", + " under 30 58.1 \n", + "chronic_cardiac_disease no 57.8 \n", " yes 66.7 \n", - "ckd no 56.5 \n", - " yes 56.5 \n", + "current_copd no 58.0 \n", + " yes 50.0 \n", + "dmards no 58.0 \n", + " yes 50.0 \n", + "dementia no 57.8 \n", + " yes 63.6 \n", + "psychosis_schiz_bipolar no 57.9 \n", + " yes 57.1 \n", + "ssri no 57.9 \n", + " yes 57.1 \n", + "chemo_or_radio no 58.0 \n", + " yes 44.4 \n", + "lung_cancer no 57.8 \n", + " yes 57.1 \n", + "cancer_excl_lung_and_haem no 57.8 \n", + " yes 62.5 \n", + "haematological_cancer no 57.8 \n", + " yes 71.4 \n", + "ckd no 57.7 \n", + " yes 58.3 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.9 \n", - "sex F 1.3 \n", - " M 2.6 \n", - "ethnicity_6_groups Black 1.9 \n", - " Mixed 2.0 \n", - " Other 2.0 \n", - " South Asian 1.8 \n", - " Unknown 2.1 \n", - " White 1.9 \n", + "overall overall 1.7 \n", + "sex F 1.8 \n", + " M 1.6 \n", + "ethnicity_6_groups Black 2.2 \n", + " Mixed 1.4 \n", + " Other 1.6 \n", + " South Asian 1.5 \n", + " Unknown 0.9 \n", + " White 2.2 \n", "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", - " Chinese 6.3 \n", + " Bangladeshi or British Bangladeshi 4.6 \n", + " Caribbean 2.4 \n", + " Chinese 2.3 \n", " Other 0.0 \n", - " Other Asian 0.0 \n", - " British or Mixed British 6.3 \n", - " Indian or British Indian 6.7 \n", + " Other Asian 2.4 \n", + " British or Mixed British 2.7 \n", + " Indian or British Indian 2.6 \n", " Irish 0.0 \n", - " Other Black 6.3 \n", - " Other White 0.0 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 5.3 \n", - " Unknown 2.1 \n", - " White + Asian 0.0 \n", - " White + Black African 5.9 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 0.0 \n", - " 2 1.5 \n", - " 3 1.7 \n", - " 4 1.8 \n", - " 5 Least deprived 3.4 \n", - " Unknown 6.7 \n", - "bmi 30+ 1.1 \n", - " under 30 2.2 \n", - "housebound no 1.9 \n", - " yes 0.0 \n", + " Other Black 2.5 \n", + " Other White 2.6 \n", + " Other mixed 2.6 \n", + " Pakistani or British Pakistani 2.4 \n", + " Unknown 1.7 \n", + " White + Asian 2.4 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 2.2 \n", + "imd_categories 1 Most deprived 2.1 \n", + " 2 2.7 \n", + " 3 1.9 \n", + " 4 1.4 \n", + " 5 Least deprived 1.3 \n", + " Unknown 0.0 \n", + "bmi 30+ 2.2 \n", + " under 30 1.5 \n", "chronic_cardiac_disease no 1.7 \n", - " yes 20.0 \n", - "current_copd no 1.9 \n", - " yes 0.0 \n", - "dmards no 1.9 \n", " yes 0.0 \n", - "dementia no 1.9 \n", + "current_copd no 1.5 \n", + " yes 12.5 \n", + "dmards no 1.7 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.9 \n", - " yes 0.0 \n", - "LD no 2.0 \n", + "dementia no 1.6 \n", " yes 0.0 \n", - "ssri no 1.6 \n", + "psychosis_schiz_bipolar no 1.6 \n", " yes 0.0 \n", - "chemo_or_radio no 1.9 \n", + "ssri no 1.7 \n", " yes 0.0 \n", - "lung_cancer no 1.9 \n", + "chemo_or_radio no 1.5 \n", + " yes 11.2 \n", + "lung_cancer no 1.7 \n", " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.9 \n", + "cancer_excl_lung_and_haem no 1.7 \n", " yes 0.0 \n", - "haematological_cancer no 1.6 \n", + "haematological_cancer no 1.7 \n", " yes 0.0 \n", - "ckd no 2.0 \n", - " yes 1.6 \n", + "ckd no 1.6 \n", + " yes 1.3 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 02-Jan \n", - "sex F 16-Feb \n", - " M 06-Dec \n", - "ethnicity_6_groups Black 19-Dec \n", - " Mixed 12-Jan \n", - " Other 05-Jan \n", - " South Asian 21-Dec \n", - " Unknown 22-Dec \n", - " White 05-Jan \n", + "overall overall 01-Mar \n", + "sex F 21-Feb \n", + " M 10-Mar \n", + "ethnicity_6_groups Black 28-Jan \n", + " Mixed 22-Mar \n", + " Other 05-Mar \n", + " South Asian 18-Mar \n", + " Unknown unknown \n", + " White 05-Feb \n", "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean unknown \n", - " Chinese 08-Oct \n", + " Bangladeshi or British Bangladeshi 14-Dec \n", + " Caribbean 21-Jan \n", + " Chinese 08-Feb \n", " Other unknown \n", - " Other Asian unknown \n", - " British or Mixed British 01-Oct \n", - " Indian or British Indian 09-Oct \n", + " Other Asian 21-Jan \n", + " British or Mixed British 07-Jan \n", + " Indian or British Indian 18-Jan \n", " Irish unknown \n", - " Other Black 08-Oct \n", - " Other White unknown \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani 20-Oct \n", - " Unknown 01-Jan \n", - " White + Asian unknown \n", - " White + Black African 15-Oct \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived unknown \n", - " 2 12-Feb \n", - " 3 12-Jan \n", - " 4 25-Dec \n", - " 5 Least deprived 11-Nov \n", - " Unknown 09-Oct \n", - "bmi 30+ unknown \n", - " under 30 15-Dec \n", - "housebound no 02-Jan \n", - " yes unknown \n", - "chronic_cardiac_disease no 16-Jan \n", - " yes 18-Sep \n", - "current_copd no 02-Jan \n", - " yes unknown \n", - "dmards no 01-Jan \n", - " yes unknown \n", - "dementia no 01-Jan \n", + " Other Black 16-Jan \n", + " Other White 18-Jan \n", + " Other mixed 21-Jan \n", + " Pakistani or British Pakistani 21-Jan \n", + " Unknown 04-Mar \n", + " White + Asian 12-Jan \n", + " White + Black African unknown \n", + " White + Black Caribbean 20-Feb \n", + "imd_categories 1 Most deprived 15-Feb \n", + " 2 15-Jan \n", + " 3 09-Feb \n", + " 4 22-Mar \n", + " 5 Least deprived 01-Apr \n", + " Unknown unknown \n", + "bmi 30+ 01-Feb \n", + " under 30 17-Mar \n", + "chronic_cardiac_disease no 01-Mar \n", " yes unknown \n", - "psychosis_schiz_bipolar no 02-Jan \n", + "current_copd no 18-Mar \n", + " yes 11-Nov \n", + "dmards no 28-Feb \n", " yes unknown \n", - "LD no 28-Dec \n", + "dementia no 09-Mar \n", " yes unknown \n", - "ssri no 24-Jan \n", + "psychosis_schiz_bipolar no 09-Mar \n", " yes unknown \n", - "chemo_or_radio no 02-Jan \n", + "ssri no 01-Mar \n", " yes unknown \n", - "lung_cancer no 02-Jan \n", + "chemo_or_radio no 18-Mar \n", + " yes 17-Nov \n", + "lung_cancer no 01-Mar \n", " yes unknown \n", - "cancer_excl_lung_and_haem no 01-Jan \n", + "cancer_excl_lung_and_haem no 01-Mar \n", " yes unknown \n", - "haematological_cancer no 24-Jan \n", + "haematological_cancer no 01-Mar \n", " yes unknown \n", - "ckd no 27-Dec \n", - " yes 25-Jan " + "ckd no 10-Mar \n", + " yes 08-Apr " ] }, "metadata": {}, @@ -45389,7 +57475,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose 14weeks ago) among **LD (aged 16-64)** population up to 2021-09-08" + "## COVID vaccination rollout (second dose 14w ago) among **55-59** population up to 2021-10-27" ], "text/plain": [ "" @@ -45455,361 +57541,678 @@ " \n", " overall\n", " overall\n", - " 462\n", - " 57.4\n", - " 805\n", - " 55.7\n", - " 1.7\n", - " 20-Jan\n", + " 3780\n", + " 60.7\n", + " 6223\n", + " 59.4\n", + " 1.3\n", + " 02-Apr\n", " \n", " \n", " sex\n", " F\n", - " 238\n", - " 57.6\n", - " 413\n", - " 55.9\n", - " 1.7\n", - " 19-Jan\n", + " 1911\n", + " 59.6\n", + " 3206\n", + " 58.1\n", + " 1.5\n", + " 17-Mar\n", " \n", " \n", " M\n", - " 224\n", - " 57.1\n", - " 392\n", - " 55.4\n", - " 1.7\n", - " 21-Jan\n", + " 1869\n", + " 61.9\n", + " 3017\n", + " 60.8\n", + " 1.1\n", + " unknown\n", " \n", " \n", - " ageband_5yr\n", - " 0\n", - " 7\n", - " 100.0\n", - " 7\n", - " 100.0\n", - " 0.0\n", - " reached\n", + " ethnicity_6_groups\n", + " Black\n", + " 595\n", + " 57.4\n", + " 1036\n", + " 56.1\n", + " 1.3\n", + " unknown\n", " \n", " \n", - " 0-15\n", - " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", - " 0.0\n", - " unknown\n", + " Mixed\n", + " 665\n", + " 62.5\n", + " 1064\n", + " 61.2\n", + " 1.3\n", + " 24-Mar\n", " \n", " \n", - " 16-17\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", - " 0.0\n", - " unknown\n", + " Other\n", + " 651\n", + " 60.0\n", + " 1085\n", + " 58.7\n", + " 1.3\n", + " 06-Apr\n", " \n", " \n", - " 18-29\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", - " 0.0\n", - " unknown\n", + " South Asian\n", + " 630\n", + " 61.6\n", + " 1022\n", + " 60.3\n", + " 1.3\n", + " 28-Mar\n", " \n", " \n", - " 30-34\n", - " 21\n", - " 50.0\n", - " 42\n", - " 50.0\n", - " 0.0\n", + " Unknown\n", + " 602\n", + " 63.2\n", + " 952\n", + " 62.5\n", + " 0.7\n", " unknown\n", " \n", " \n", - " 35-39\n", - " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", - " 0.0\n", - " unknown\n", + " White\n", + " 637\n", + " 59.5\n", + " 1071\n", + " 58.2\n", + " 1.3\n", + " 09-Apr\n", " \n", " \n", - " 40-44\n", - " 35\n", - " 71.4\n", - " 49\n", - " 71.4\n", + " ethnicity_16_groups\n", + " African\n", + " 189\n", + " 58.7\n", + " 322\n", + " 58.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " 45-49\n", - " 35\n", - " 62.5\n", - " 56\n", - " 62.5\n", + " Bangladeshi or British Bangladeshi\n", + " 175\n", + " 58.1\n", + " 301\n", + " 58.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " 50-54\n", - " 28\n", - " 50.0\n", - " 56\n", - " 50.0\n", + " Caribbean\n", + " 203\n", + " 61.7\n", + " 329\n", + " 61.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " 55-59\n", - " 28\n", - " 57.1\n", - " 49\n", + " Chinese\n", + " 175\n", + " 59.5\n", + " 294\n", " 57.1\n", + " 2.4\n", + " 23-Jan\n", + " \n", + " \n", + " Other\n", + " 203\n", + " 61.7\n", + " 329\n", + " 61.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " 60-64\n", - " 28\n", - " 50.0\n", - " 56\n", - " 50.0\n", + " Other Asian\n", + " 182\n", + " 59.1\n", + " 308\n", + " 59.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " 65-69\n", - " 42\n", - " 66.7\n", - " 63\n", - " 66.7\n", + " British or Mixed British\n", + " 196\n", + " 58.3\n", + " 336\n", + " 58.3\n", " 0.0\n", " unknown\n", " \n", " \n", - " 70-74\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", + " Indian or British Indian\n", + " 196\n", + " 60.9\n", + " 322\n", + " 58.7\n", + " 2.2\n", + " 27-Jan\n", + " \n", + " \n", + " Irish\n", + " 203\n", + " 60.4\n", + " 336\n", + " 60.4\n", " 0.0\n", " unknown\n", " \n", " \n", - " 75-79\n", - " 35\n", - " 55.6\n", - " 63\n", - " 55.6\n", + " Other Black\n", + " 189\n", + " 55.1\n", + " 343\n", + " 55.1\n", " 0.0\n", " unknown\n", " \n", " \n", - " 80-84\n", - " 35\n", - " 71.4\n", - " 49\n", - " 71.4\n", + " Other White\n", + " 203\n", + " 58.0\n", + " 350\n", + " 56.0\n", + " 2.0\n", + " 16-Feb\n", + " \n", + " \n", + " Other mixed\n", + " 196\n", + " 63.6\n", + " 308\n", + " 61.4\n", + " 2.2\n", + " 19-Jan\n", + " \n", + " \n", + " Pakistani or British Pakistani\n", + " 224\n", + " 62.7\n", + " 357\n", + " 62.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " 85-89\n", - " 28\n", - " 57.1\n", - " 49\n", - " 57.1\n", - " 0.0\n", + " Unknown\n", + " 595\n", + " 62.5\n", + " 952\n", + " 61.0\n", + " 1.5\n", + " 04-Mar\n", + " \n", + " \n", + " White + Asian\n", + " 210\n", + " 62.5\n", + " 336\n", + " 60.4\n", + " 2.1\n", + " 26-Jan\n", + " \n", + " \n", + " White + Black African\n", + " 238\n", + " 63.0\n", + " 378\n", + " 61.1\n", + " 1.9\n", + " 03-Feb\n", + " \n", + " \n", + " White + Black Caribbean\n", + " 196\n", + " 59.6\n", + " 329\n", + " 57.4\n", + " 2.2\n", + " 31-Jan\n", + " \n", + " \n", + " imd_categories\n", + " 1 Most deprived\n", + " 749\n", + " 61.1\n", + " 1225\n", + " 59.4\n", + " 1.7\n", + " 23-Feb\n", + " \n", + " \n", + " 2\n", + " 679\n", + " 59.5\n", + " 1141\n", + " 57.7\n", + " 1.8\n", + " 22-Feb\n", + " \n", + " \n", + " 3\n", + " 749\n", + " 61.8\n", + " 1211\n", + " 60.7\n", + " 1.1\n", " unknown\n", " \n", " \n", - " 90+\n", - " 0\n", - " 0.0\n", - " 7\n", - " 0.0\n", - " 0.0\n", + " 4\n", + " 714\n", + " 60.4\n", + " 1183\n", + " 59.8\n", + " 0.6\n", " unknown\n", " \n", " \n", - " ethnicity_6_groups\n", - " Black\n", + " 5 Least deprived\n", + " 693\n", + " 60.7\n", + " 1141\n", + " 59.5\n", + " 1.2\n", + " 15-Apr\n", + " \n", + " \n", + " Unknown\n", + " 196\n", + " 60.9\n", + " 322\n", + " 58.7\n", + " 2.2\n", + " 27-Jan\n", + " \n", + " \n", + " bmi\n", + " 30+\n", + " 1099\n", + " 60.9\n", + " 1806\n", + " 59.7\n", + " 1.2\n", + " 14-Apr\n", + " \n", + " \n", + " under 30\n", + " 2688\n", + " 60.9\n", + " 4417\n", + " 59.4\n", + " 1.5\n", + " 11-Mar\n", + " \n", + " \n", + " chronic_cardiac_disease\n", + " no\n", + " 3731\n", + " 60.6\n", + " 6153\n", + " 59.3\n", + " 1.3\n", + " 03-Apr\n", + " \n", + " \n", + " yes\n", + " 49\n", + " 63.6\n", " 77\n", - " 61.1\n", - " 126\n", - " 61.1\n", + " 63.6\n", " 0.0\n", " unknown\n", " \n", " \n", - " Mixed\n", - " 91\n", - " 56.5\n", - " 161\n", - " 52.2\n", - " 4.3\n", - " 01-Nov\n", + " current_copd\n", + " no\n", + " 3752\n", + " 60.8\n", + " 6174\n", + " 59.4\n", + " 1.4\n", + " 22-Mar\n", " \n", " \n", - " Other\n", - " 70\n", - " 52.6\n", - " 133\n", - " 52.6\n", + " yes\n", + " 28\n", + " 50.0\n", + " 56\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " South Asian\n", + " dmards\n", + " no\n", + " 3738\n", + " 60.7\n", + " 6160\n", + " 59.3\n", + " 1.4\n", + " 22-Mar\n", + " \n", + " \n", + " yes\n", + " 49\n", + " 70.0\n", " 70\n", - " 52.6\n", - " 133\n", - " 52.6\n", + " 60.0\n", + " 10.0\n", + " 10-Nov\n", + " \n", + " \n", + " psychosis_schiz_bipolar\n", + " no\n", + " 3738\n", + " 60.6\n", + " 6167\n", + " 59.3\n", + " 1.3\n", + " 03-Apr\n", + " \n", + " \n", + " yes\n", + " 42\n", + " 66.7\n", + " 63\n", + " 66.7\n", " 0.0\n", " unknown\n", " \n", " \n", - " Unknown\n", - " 77\n", - " 61.1\n", - " 126\n", - " 55.6\n", - " 5.5\n", - " 14-Oct\n", + " ssri\n", + " no\n", + " 3745\n", + " 60.8\n", + " 6160\n", + " 59.4\n", + " 1.4\n", + " 22-Mar\n", " \n", " \n", - " White\n", - " 77\n", - " 61.1\n", - " 126\n", - " 61.1\n", + " yes\n", + " 35\n", + " 50.0\n", + " 70\n", + " 50.0\n", " 0.0\n", " unknown\n", " \n", + " \n", + " ckd\n", + " no\n", + " 2996\n", + " 60.6\n", + " 4942\n", + " 59.3\n", + " 1.3\n", + " 03-Apr\n", + " \n", + " \n", + " yes\n", + " 784\n", + " 60.9\n", + " 1288\n", + " 59.2\n", + " 1.7\n", + " 23-Feb\n", + " \n", " \n", "\n", "" ], "text/plain": [ - " vaccinated percent total \\\n", - "category group \n", - "overall overall 462 57.4 805 \n", - "sex F 238 57.6 413 \n", - " M 224 57.1 392 \n", - "ageband_5yr 0 7 100.0 7 \n", - " 0-15 21 42.9 49 \n", - " 16-17 28 57.1 49 \n", - " 18-29 28 57.1 49 \n", - " 30-34 21 50.0 42 \n", - " 35-39 21 42.9 49 \n", - " 40-44 35 71.4 49 \n", - " 45-49 35 62.5 56 \n", - " 50-54 28 50.0 56 \n", - " 55-59 28 57.1 49 \n", - " 60-64 28 50.0 56 \n", - " 65-69 42 66.7 63 \n", - " 70-74 28 57.1 49 \n", - " 75-79 35 55.6 63 \n", - " 80-84 35 71.4 49 \n", - " 85-89 28 57.1 49 \n", - " 90+ 0 0.0 7 \n", - "ethnicity_6_groups Black 77 61.1 126 \n", - " Mixed 91 56.5 161 \n", - " Other 70 52.6 133 \n", - " South Asian 70 52.6 133 \n", - " Unknown 77 61.1 126 \n", - " White 77 61.1 126 \n", + " vaccinated \\\n", + "category group \n", + "overall overall 3780 \n", + "sex F 1911 \n", + " M 1869 \n", + "ethnicity_6_groups Black 595 \n", + " Mixed 665 \n", + " Other 651 \n", + " South Asian 630 \n", + " Unknown 602 \n", + " White 637 \n", + "ethnicity_16_groups African 189 \n", + " Bangladeshi or British Bangladeshi 175 \n", + " Caribbean 203 \n", + " Chinese 175 \n", + " Other 203 \n", + " Other Asian 182 \n", + " British or Mixed British 196 \n", + " Indian or British Indian 196 \n", + " Irish 203 \n", + " Other Black 189 \n", + " Other White 203 \n", + " Other mixed 196 \n", + " Pakistani or British Pakistani 224 \n", + " Unknown 595 \n", + " White + Asian 210 \n", + " White + Black African 238 \n", + " White + Black Caribbean 196 \n", + "imd_categories 1 Most deprived 749 \n", + " 2 679 \n", + " 3 749 \n", + " 4 714 \n", + " 5 Least deprived 693 \n", + " Unknown 196 \n", + "bmi 30+ 1099 \n", + " under 30 2688 \n", + "chronic_cardiac_disease no 3731 \n", + " yes 49 \n", + "current_copd no 3752 \n", + " yes 28 \n", + "dmards no 3738 \n", + " yes 49 \n", + "psychosis_schiz_bipolar no 3738 \n", + " yes 42 \n", + "ssri no 3745 \n", + " yes 35 \n", + "ckd no 2996 \n", + " yes 784 \n", "\n", - " vaccinated 7d previous (percent) \\\n", - "category group \n", - "overall overall 55.7 \n", - "sex F 55.9 \n", - " M 55.4 \n", - "ageband_5yr 0 100.0 \n", - " 0-15 42.9 \n", - " 16-17 57.1 \n", - " 18-29 57.1 \n", - " 30-34 50.0 \n", - " 35-39 42.9 \n", - " 40-44 71.4 \n", - " 45-49 62.5 \n", - " 50-54 50.0 \n", - " 55-59 57.1 \n", - " 60-64 50.0 \n", - " 65-69 66.7 \n", - " 70-74 57.1 \n", - " 75-79 55.6 \n", - " 80-84 71.4 \n", - " 85-89 57.1 \n", - " 90+ 0.0 \n", - "ethnicity_6_groups Black 61.1 \n", - " Mixed 52.2 \n", - " Other 52.6 \n", - " South Asian 52.6 \n", - " Unknown 55.6 \n", - " White 61.1 \n", + " percent total \\\n", + "category group \n", + "overall overall 60.7 6223 \n", + "sex F 59.6 3206 \n", + " M 61.9 3017 \n", + "ethnicity_6_groups Black 57.4 1036 \n", + " Mixed 62.5 1064 \n", + " Other 60.0 1085 \n", + " South Asian 61.6 1022 \n", + " Unknown 63.2 952 \n", + " White 59.5 1071 \n", + "ethnicity_16_groups African 58.7 322 \n", + " Bangladeshi or British Bangladeshi 58.1 301 \n", + " Caribbean 61.7 329 \n", + " Chinese 59.5 294 \n", + " Other 61.7 329 \n", + " Other Asian 59.1 308 \n", + " British or Mixed British 58.3 336 \n", + " Indian or British Indian 60.9 322 \n", + " Irish 60.4 336 \n", + " Other Black 55.1 343 \n", + " Other White 58.0 350 \n", + " Other mixed 63.6 308 \n", + " Pakistani or British Pakistani 62.7 357 \n", + " Unknown 62.5 952 \n", + " White + Asian 62.5 336 \n", + " White + Black African 63.0 378 \n", + " White + Black Caribbean 59.6 329 \n", + "imd_categories 1 Most deprived 61.1 1225 \n", + " 2 59.5 1141 \n", + " 3 61.8 1211 \n", + " 4 60.4 1183 \n", + " 5 Least deprived 60.7 1141 \n", + " Unknown 60.9 322 \n", + "bmi 30+ 60.9 1806 \n", + " under 30 60.9 4417 \n", + "chronic_cardiac_disease no 60.6 6153 \n", + " yes 63.6 77 \n", + "current_copd no 60.8 6174 \n", + " yes 50.0 56 \n", + "dmards no 60.7 6160 \n", + " yes 70.0 70 \n", + "psychosis_schiz_bipolar no 60.6 6167 \n", + " yes 66.7 63 \n", + "ssri no 60.8 6160 \n", + " yes 50.0 70 \n", + "ckd no 60.6 4942 \n", + " yes 60.9 1288 \n", "\n", - " Uptake over last 7d (percent) \\\n", - "category group \n", - "overall overall 1.7 \n", - "sex F 1.7 \n", - " M 1.7 \n", - "ageband_5yr 0 0.0 \n", - " 0-15 0.0 \n", - " 16-17 0.0 \n", - " 18-29 0.0 \n", - " 30-34 0.0 \n", - " 35-39 0.0 \n", - " 40-44 0.0 \n", - " 45-49 0.0 \n", - " 50-54 0.0 \n", - " 55-59 0.0 \n", - " 60-64 0.0 \n", - " 65-69 0.0 \n", - " 70-74 0.0 \n", - " 75-79 0.0 \n", - " 80-84 0.0 \n", - " 85-89 0.0 \n", - " 90+ 0.0 \n", - "ethnicity_6_groups Black 0.0 \n", - " Mixed 4.3 \n", - " Other 0.0 \n", - " South Asian 0.0 \n", - " Unknown 5.5 \n", - " White 0.0 \n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.4 \n", + "sex F 58.1 \n", + " M 60.8 \n", + "ethnicity_6_groups Black 56.1 \n", + " Mixed 61.2 \n", + " Other 58.7 \n", + " South Asian 60.3 \n", + " Unknown 62.5 \n", + " White 58.2 \n", + "ethnicity_16_groups African 58.7 \n", + " Bangladeshi or British Bangladeshi 58.1 \n", + " Caribbean 61.7 \n", + " Chinese 57.1 \n", + " Other 61.7 \n", + " Other Asian 59.1 \n", + " British or Mixed British 58.3 \n", + " Indian or British Indian 58.7 \n", + " Irish 60.4 \n", + " Other Black 55.1 \n", + " Other White 56.0 \n", + " Other mixed 61.4 \n", + " Pakistani or British Pakistani 62.7 \n", + " Unknown 61.0 \n", + " White + Asian 60.4 \n", + " White + Black African 61.1 \n", + " White + Black Caribbean 57.4 \n", + "imd_categories 1 Most deprived 59.4 \n", + " 2 57.7 \n", + " 3 60.7 \n", + " 4 59.8 \n", + " 5 Least deprived 59.5 \n", + " Unknown 58.7 \n", + "bmi 30+ 59.7 \n", + " under 30 59.4 \n", + "chronic_cardiac_disease no 59.3 \n", + " yes 63.6 \n", + "current_copd no 59.4 \n", + " yes 50.0 \n", + "dmards no 59.3 \n", + " yes 60.0 \n", + "psychosis_schiz_bipolar no 59.3 \n", + " yes 66.7 \n", + "ssri no 59.4 \n", + " yes 50.0 \n", + "ckd no 59.3 \n", + " yes 59.2 \n", "\n", - " Date projected to reach 90% \n", - "category group \n", - "overall overall 20-Jan \n", - "sex F 19-Jan \n", - " M 21-Jan \n", - "ageband_5yr 0 reached \n", - " 0-15 unknown \n", - " 16-17 unknown \n", - " 18-29 unknown \n", - " 30-34 unknown \n", - " 35-39 unknown \n", - " 40-44 unknown \n", - " 45-49 unknown \n", - " 50-54 unknown \n", - " 55-59 unknown \n", - " 60-64 unknown \n", - " 65-69 unknown \n", - " 70-74 unknown \n", - " 75-79 unknown \n", - " 80-84 unknown \n", - " 85-89 unknown \n", - " 90+ unknown \n", - "ethnicity_6_groups Black unknown \n", - " Mixed 01-Nov \n", - " Other unknown \n", - " South Asian unknown \n", - " Unknown 14-Oct \n", - " White unknown " + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.3 \n", + "sex F 1.5 \n", + " M 1.1 \n", + "ethnicity_6_groups Black 1.3 \n", + " Mixed 1.3 \n", + " Other 1.3 \n", + " South Asian 1.3 \n", + " Unknown 0.7 \n", + " White 1.3 \n", + "ethnicity_16_groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 0.0 \n", + " Caribbean 0.0 \n", + " Chinese 2.4 \n", + " Other 0.0 \n", + " Other Asian 0.0 \n", + " British or Mixed British 0.0 \n", + " Indian or British Indian 2.2 \n", + " Irish 0.0 \n", + " Other Black 0.0 \n", + " Other White 2.0 \n", + " Other mixed 2.2 \n", + " Pakistani or British Pakistani 0.0 \n", + " Unknown 1.5 \n", + " White + Asian 2.1 \n", + " White + Black African 1.9 \n", + " White + Black Caribbean 2.2 \n", + "imd_categories 1 Most deprived 1.7 \n", + " 2 1.8 \n", + " 3 1.1 \n", + " 4 0.6 \n", + " 5 Least deprived 1.2 \n", + " Unknown 2.2 \n", + "bmi 30+ 1.2 \n", + " under 30 1.5 \n", + "chronic_cardiac_disease no 1.3 \n", + " yes 0.0 \n", + "current_copd no 1.4 \n", + " yes 0.0 \n", + "dmards no 1.4 \n", + " yes 10.0 \n", + "psychosis_schiz_bipolar no 1.3 \n", + " yes 0.0 \n", + "ssri no 1.4 \n", + " yes 0.0 \n", + "ckd no 1.3 \n", + " yes 1.7 \n", + "\n", + " Date projected to reach 90% \n", + "category group \n", + "overall overall 02-Apr \n", + "sex F 17-Mar \n", + " M unknown \n", + "ethnicity_6_groups Black unknown \n", + " Mixed 24-Mar \n", + " Other 06-Apr \n", + " South Asian 28-Mar \n", + " Unknown unknown \n", + " White 09-Apr \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi unknown \n", + " Caribbean unknown \n", + " Chinese 23-Jan \n", + " Other unknown \n", + " Other Asian unknown \n", + " British or Mixed British unknown \n", + " Indian or British Indian 27-Jan \n", + " Irish unknown \n", + " Other Black unknown \n", + " Other White 16-Feb \n", + " Other mixed 19-Jan \n", + " Pakistani or British Pakistani unknown \n", + " Unknown 04-Mar \n", + " White + Asian 26-Jan \n", + " White + Black African 03-Feb \n", + " White + Black Caribbean 31-Jan \n", + "imd_categories 1 Most deprived 23-Feb \n", + " 2 22-Feb \n", + " 3 unknown \n", + " 4 unknown \n", + " 5 Least deprived 15-Apr \n", + " Unknown 27-Jan \n", + "bmi 30+ 14-Apr \n", + " under 30 11-Mar \n", + "chronic_cardiac_disease no 03-Apr \n", + " yes unknown \n", + "current_copd no 22-Mar \n", + " yes unknown \n", + "dmards no 22-Mar \n", + " yes 10-Nov \n", + "psychosis_schiz_bipolar no 03-Apr \n", + " yes unknown \n", + "ssri no 22-Mar \n", + " yes unknown \n", + "ckd no 03-Apr \n", + " yes 23-Feb " ] }, "metadata": {}, @@ -45838,7 +58241,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose 14weeks ago) among **60-64** population up to 2021-09-08" + "## COVID vaccination rollout (second dose 14w ago) among **50-54** population up to 2021-10-27" ], "text/plain": [ "" @@ -45904,823 +58307,678 @@ " \n", " overall\n", " overall\n", - " 1512\n", - " 56.5\n", - " 2674\n", - " 55.2\n", - " 1.3\n", - " unknown\n", + " 4053\n", + " 60.2\n", + " 6727\n", + " 58.6\n", + " 1.6\n", + " 06-Mar\n", " \n", " \n", " sex\n", " F\n", - " 756\n", - " 56.8\n", - " 1330\n", - " 54.7\n", - " 2.1\n", - " 27-Dec\n", + " 2030\n", + " 59.7\n", + " 3402\n", + " 58.0\n", + " 1.7\n", + " 28-Feb\n", " \n", " \n", " M\n", - " 756\n", - " 56.2\n", - " 1344\n", - " 55.2\n", - " 1.0\n", - " unknown\n", + " 2016\n", + " 60.6\n", + " 3325\n", + " 58.9\n", + " 1.7\n", + " 25-Feb\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 266\n", - " 56.7\n", - " 469\n", - " 55.2\n", - " 1.5\n", - " 10-Feb\n", + " 721\n", + " 60.2\n", + " 1197\n", + " 58.5\n", + " 1.7\n", + " 26-Feb\n", " \n", " \n", " Mixed\n", - " 252\n", - " 54.5\n", - " 462\n", - " 53.0\n", - " 1.5\n", - " 20-Feb\n", + " 686\n", + " 58.3\n", + " 1176\n", + " 56.5\n", + " 1.8\n", + " 27-Feb\n", " \n", " \n", " Other\n", - " 266\n", - " 59.4\n", - " 448\n", - " 59.4\n", - " 0.0\n", - " unknown\n", + " 658\n", + " 58.8\n", + " 1120\n", + " 57.5\n", + " 1.3\n", + " 13-Apr\n", " \n", " \n", " South Asian\n", - " 245\n", - " 53.8\n", - " 455\n", - " 52.3\n", - " 1.5\n", - " 23-Feb\n", + " 665\n", + " 61.7\n", + " 1078\n", + " 59.7\n", + " 2.0\n", + " 03-Feb\n", " \n", " \n", " Unknown\n", - " 210\n", - " 57.7\n", - " 364\n", - " 55.8\n", - " 1.9\n", - " 05-Jan\n", + " 616\n", + " 62.0\n", + " 994\n", + " 60.6\n", + " 1.4\n", + " 16-Mar\n", " \n", " \n", " White\n", - " 273\n", - " 58.2\n", - " 469\n", - " 56.7\n", - " 1.5\n", - " 03-Feb\n", + " 707\n", + " 60.8\n", + " 1162\n", + " 59.0\n", + " 1.8\n", + " 17-Feb\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 56\n", - " 47.1\n", - " 119\n", - " 47.1\n", + " 196\n", + " 53.8\n", + " 364\n", + " 53.8\n", " 0.0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 84\n", - " 54.5\n", - " 154\n", - " 50.0\n", - " 4.5\n", - " 02-Nov\n", + " 203\n", + " 58.0\n", + " 350\n", + " 56.0\n", + " 2.0\n", + " 16-Feb\n", " \n", " \n", " Caribbean\n", - " 63\n", - " 42.9\n", - " 147\n", - " 42.9\n", - " 0.0\n", - " unknown\n", + " 203\n", + " 58.0\n", + " 350\n", + " 56.0\n", + " 2.0\n", + " 16-Feb\n", " \n", " \n", " Chinese\n", - " 84\n", - " 54.5\n", - " 154\n", - " 54.5\n", - " 0.0\n", - " unknown\n", + " 203\n", + " 59.2\n", + " 343\n", + " 57.1\n", + " 2.1\n", + " 06-Feb\n", " \n", " \n", " Other\n", - " 91\n", - " 59.1\n", - " 154\n", - " 54.5\n", - " 4.6\n", - " 25-Oct\n", + " 210\n", + " 60.0\n", + " 350\n", + " 58.0\n", + " 2.0\n", + " 09-Feb\n", " \n", " \n", " Other Asian\n", - " 77\n", - " 61.1\n", - " 126\n", + " 231\n", " 61.1\n", - " 0.0\n", - " unknown\n", + " 378\n", + " 59.3\n", + " 1.8\n", + " 16-Feb\n", " \n", " \n", " British or Mixed British\n", - " 77\n", - " 52.4\n", - " 147\n", - " 52.4\n", - " 0.0\n", - " unknown\n", + " 210\n", + " 60.0\n", + " 350\n", + " 58.0\n", + " 2.0\n", + " 09-Feb\n", " \n", " \n", " Indian or British Indian\n", - " 77\n", - " 57.9\n", - " 133\n", - " 52.6\n", - " 5.3\n", - " 20-Oct\n", + " 245\n", + " 62.5\n", + " 392\n", + " 60.7\n", + " 1.8\n", + " 10-Feb\n", " \n", " \n", " Irish\n", - " 98\n", - " 63.6\n", - " 154\n", - " 59.1\n", - " 4.5\n", - " 19-Oct\n", + " 203\n", + " 59.2\n", + " 343\n", + " 57.1\n", + " 2.1\n", + " 06-Feb\n", " \n", " \n", " Other Black\n", - " 77\n", - " 61.1\n", - " 126\n", - " 61.1\n", + " 231\n", + " 63.5\n", + " 364\n", + " 63.5\n", " 0.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 105\n", - " 65.2\n", - " 161\n", - " 65.2\n", - " 0.0\n", - " unknown\n", + " 203\n", + " 59.2\n", + " 343\n", + " 55.1\n", + " 4.1\n", + " 18-Dec\n", " \n", " \n", " Other mixed\n", - " 98\n", - " 66.7\n", - " 147\n", - " 66.7\n", + " 196\n", + " 56.0\n", + " 350\n", + " 56.0\n", " 0.0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 84\n", - " 57.1\n", - " 147\n", - " 57.1\n", - " 0.0\n", - " unknown\n", + " 245\n", + " 64.8\n", + " 378\n", + " 63.0\n", + " 1.8\n", + " 02-Feb\n", " \n", " \n", " Unknown\n", - " 231\n", - " 56.9\n", - " 406\n", - " 55.2\n", - " 1.7\n", - " 22-Jan\n", + " 630\n", + " 62.1\n", + " 1015\n", + " 60.7\n", + " 1.4\n", + " 15-Mar\n", " \n", " \n", " White + Asian\n", - " 77\n", - " 57.9\n", - " 133\n", - " 57.9\n", - " 0.0\n", - " unknown\n", + " 203\n", + " 58.0\n", + " 350\n", + " 56.0\n", + " 2.0\n", + " 16-Feb\n", " \n", " \n", " White + Black African\n", - " 70\n", - " 52.6\n", - " 133\n", - " 52.6\n", - " 0.0\n", - " unknown\n", + " 224\n", + " 64.0\n", + " 350\n", + " 62.0\n", + " 2.0\n", + " 26-Jan\n", " \n", " \n", " White + Black Caribbean\n", - " 63\n", - " 50.0\n", - " 126\n", - " 50.0\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " imd_categories\n", - " 1 Most deprived\n", - " 280\n", - " 55.6\n", - " 504\n", - " 55.6\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 2\n", - " 315\n", - " 57.7\n", - " 546\n", - " 56.4\n", - " 1.3\n", - " 28-Feb\n", - " \n", - " \n", - " 3\n", - " 280\n", - " 55.6\n", - " 504\n", - " 55.6\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " 4\n", - " 273\n", - " 56.5\n", - " 483\n", - " 55.1\n", - " 1.4\n", - " 22-Feb\n", - " \n", - " \n", - " 5 Least deprived\n", - " 280\n", - " 55.6\n", - " 504\n", - " 54.2\n", - " 1.4\n", - " 27-Feb\n", - " \n", - " \n", - " Unknown\n", - " 77\n", - " 57.9\n", - " 133\n", - " 52.6\n", - " 5.3\n", - " 20-Oct\n", - " \n", - " \n", - " bmi\n", - " 30+\n", - " 476\n", - " 57.6\n", - " 826\n", - " 56.8\n", - " 0.8\n", - " unknown\n", - " \n", - " \n", - " under 30\n", - " 1036\n", - " 56.1\n", - " 1848\n", - " 54.5\n", - " 1.6\n", - " 03-Feb\n", - " \n", - " \n", - " chronic_cardiac_disease\n", - " no\n", - " 1491\n", - " 56.5\n", - " 2639\n", - " 55.2\n", - " 1.3\n", - " unknown\n", - " \n", - " \n", - " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", - " 0.0\n", - " unknown\n", + " 210\n", + " 57.7\n", + " 364\n", + " 55.8\n", + " 1.9\n", + " 23-Feb\n", " \n", " \n", - " current_copd\n", - " no\n", - " 1505\n", - " 56.7\n", - " 2653\n", - " 55.4\n", - " 1.3\n", + " imd_categories\n", + " 1 Most deprived\n", + " 728\n", + " 57.1\n", + " 1274\n", + " 56.0\n", + " 1.1\n", " unknown\n", " \n", " \n", - " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", - " 0.0\n", - " unknown\n", + " 2\n", + " 777\n", + " 59.7\n", + " 1302\n", + " 57.5\n", + " 2.2\n", + " 31-Jan\n", " \n", " \n", - " dmards\n", - " no\n", - " 1498\n", - " 56.5\n", - " 2653\n", - " 55.1\n", - " 1.4\n", - " 22-Feb\n", + " 3\n", + " 784\n", + " 62.6\n", + " 1253\n", + " 60.3\n", + " 2.3\n", + " 18-Jan\n", " \n", " \n", - " yes\n", - " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", - " 0.0\n", + " 4\n", + " 770\n", + " 61.1\n", + " 1260\n", + " 60.6\n", + " 0.5\n", " unknown\n", " \n", " \n", - " dementia\n", - " no\n", - " 1498\n", - " 56.6\n", - " 2646\n", - " 55.0\n", - " 1.6\n", - " 01-Feb\n", + " 5 Least deprived\n", + " 756\n", + " 59.7\n", + " 1267\n", + " 58.0\n", + " 1.7\n", + " 28-Feb\n", " \n", " \n", - " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " Unknown\n", + " 231\n", + " 61.1\n", + " 378\n", + " 59.3\n", + " 1.8\n", + " 16-Feb\n", " \n", " \n", - " psychosis_schiz_bipolar\n", - " no\n", - " 1498\n", - " 56.6\n", - " 2646\n", - " 55.3\n", - " 1.3\n", - " unknown\n", + " bmi\n", + " 30+\n", + " 1190\n", + " 60.7\n", + " 1960\n", + " 58.9\n", + " 1.8\n", + " 17-Feb\n", " \n", " \n", - " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " under 30\n", + " 2863\n", + " 60.1\n", + " 4767\n", + " 58.4\n", + " 1.7\n", + " 27-Feb\n", " \n", " \n", - " ssri\n", + " chronic_cardiac_disease\n", " no\n", - " 1498\n", - " 56.6\n", - " 2646\n", - " 55.0\n", + " 4018\n", + " 60.3\n", + " 6664\n", + " 58.7\n", " 1.6\n", - " 01-Feb\n", + " 05-Mar\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", " 28\n", - " 50.0\n", + " 44.4\n", + " 63\n", + " 44.4\n", " 0.0\n", " unknown\n", " \n", " \n", - " chemo_or_radio\n", + " current_copd\n", " no\n", - " 1498\n", - " 56.6\n", - " 2646\n", - " 55.0\n", + " 4004\n", + " 60.2\n", + " 6650\n", + " 58.6\n", " 1.6\n", - " 01-Feb\n", + " 06-Mar\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 42\n", + " 54.5\n", + " 77\n", + " 54.5\n", " 0.0\n", " unknown\n", " \n", " \n", - " lung_cancer\n", + " dmards\n", " no\n", - " 1505\n", - " 56.7\n", - " 2653\n", - " 55.1\n", - " 1.6\n", - " 31-Jan\n", + " 4018\n", + " 60.3\n", + " 6664\n", + " 58.6\n", + " 1.7\n", + " 26-Feb\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 35\n", + " 62.5\n", + " 56\n", + " 62.5\n", " 0.0\n", " unknown\n", " \n", " \n", - " cancer_excl_lung_and_haem\n", + " psychosis_schiz_bipolar\n", " no\n", - " 1505\n", - " 56.7\n", - " 2653\n", - " 55.1\n", - " 1.6\n", - " 31-Jan\n", + " 4004\n", + " 60.1\n", + " 6657\n", + " 58.6\n", + " 1.5\n", + " 15-Mar\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 42\n", + " 60.0\n", + " 70\n", + " 60.0\n", " 0.0\n", " unknown\n", " \n", " \n", - " haematological_cancer\n", + " ssri\n", " no\n", - " 1498\n", - " 56.6\n", - " 2646\n", - " 55.3\n", - " 1.3\n", - " unknown\n", + " 4011\n", + " 60.3\n", + " 6657\n", + " 58.7\n", + " 1.6\n", + " 05-Mar\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", " 35\n", - " 40.0\n", + " 55.6\n", + " 63\n", + " 55.6\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1197\n", - " 56.6\n", - " 2114\n", - " 55.0\n", - " 1.6\n", - " 01-Feb\n", + " 3248\n", + " 60.4\n", + " 5376\n", + " 59.0\n", + " 1.4\n", + " 24-Mar\n", " \n", " \n", " yes\n", - " 315\n", - " 56.2\n", - " 560\n", - " 55.0\n", - " 1.2\n", - " unknown\n", + " 798\n", + " 59.1\n", + " 1351\n", + " 57.0\n", + " 2.1\n", + " 07-Feb\n", " \n", " \n", "\n", "" ], "text/plain": [ - " vaccinated \\\n", - "category group \n", - "overall overall 1512 \n", - "sex F 756 \n", - " M 756 \n", - "ethnicity_6_groups Black 266 \n", - " Mixed 252 \n", - " Other 266 \n", - " South Asian 245 \n", - " Unknown 210 \n", - " White 273 \n", - "ethnicity_16_groups African 56 \n", - " Bangladeshi or British Bangladeshi 84 \n", - " Caribbean 63 \n", - " Chinese 84 \n", - " Other 91 \n", - " Other Asian 77 \n", - " British or Mixed British 77 \n", - " Indian or British Indian 77 \n", - " Irish 98 \n", - " Other Black 77 \n", - " Other White 105 \n", - " Other mixed 98 \n", - " Pakistani or British Pakistani 84 \n", - " Unknown 231 \n", - " White + Asian 77 \n", - " White + Black African 70 \n", - " White + Black Caribbean 63 \n", - "imd_categories 1 Most deprived 280 \n", - " 2 315 \n", - " 3 280 \n", - " 4 273 \n", - " 5 Least deprived 280 \n", - " Unknown 77 \n", - "bmi 30+ 476 \n", - " under 30 1036 \n", - "chronic_cardiac_disease no 1491 \n", - " yes 21 \n", - "current_copd no 1505 \n", - " yes 7 \n", - "dmards no 1498 \n", - " yes 14 \n", - "dementia no 1498 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1498 \n", - " yes 14 \n", - "ssri no 1498 \n", - " yes 14 \n", - "chemo_or_radio no 1498 \n", - " yes 14 \n", - "lung_cancer no 1505 \n", - " yes 7 \n", - "cancer_excl_lung_and_haem no 1505 \n", - " yes 7 \n", - "haematological_cancer no 1498 \n", - " yes 14 \n", - "ckd no 1197 \n", - " yes 315 \n", + " vaccinated \\\n", + "category group \n", + "overall overall 4053 \n", + "sex F 2030 \n", + " M 2016 \n", + "ethnicity_6_groups Black 721 \n", + " Mixed 686 \n", + " Other 658 \n", + " South Asian 665 \n", + " Unknown 616 \n", + " White 707 \n", + "ethnicity_16_groups African 196 \n", + " Bangladeshi or British Bangladeshi 203 \n", + " Caribbean 203 \n", + " Chinese 203 \n", + " Other 210 \n", + " Other Asian 231 \n", + " British or Mixed British 210 \n", + " Indian or British Indian 245 \n", + " Irish 203 \n", + " Other Black 231 \n", + " Other White 203 \n", + " Other mixed 196 \n", + " Pakistani or British Pakistani 245 \n", + " Unknown 630 \n", + " White + Asian 203 \n", + " White + Black African 224 \n", + " White + Black Caribbean 210 \n", + "imd_categories 1 Most deprived 728 \n", + " 2 777 \n", + " 3 784 \n", + " 4 770 \n", + " 5 Least deprived 756 \n", + " Unknown 231 \n", + "bmi 30+ 1190 \n", + " under 30 2863 \n", + "chronic_cardiac_disease no 4018 \n", + " yes 28 \n", + "current_copd no 4004 \n", + " yes 42 \n", + "dmards no 4018 \n", + " yes 35 \n", + "psychosis_schiz_bipolar no 4004 \n", + " yes 42 \n", + "ssri no 4011 \n", + " yes 35 \n", + "ckd no 3248 \n", + " yes 798 \n", "\n", - " percent total \\\n", - "category group \n", - "overall overall 56.5 2674 \n", - "sex F 56.8 1330 \n", - " M 56.2 1344 \n", - "ethnicity_6_groups Black 56.7 469 \n", - " Mixed 54.5 462 \n", - " Other 59.4 448 \n", - " South Asian 53.8 455 \n", - " Unknown 57.7 364 \n", - " White 58.2 469 \n", - "ethnicity_16_groups African 47.1 119 \n", - " Bangladeshi or British Bangladeshi 54.5 154 \n", - " Caribbean 42.9 147 \n", - " Chinese 54.5 154 \n", - " Other 59.1 154 \n", - " Other Asian 61.1 126 \n", - " British or Mixed British 52.4 147 \n", - " Indian or British Indian 57.9 133 \n", - " Irish 63.6 154 \n", - " Other Black 61.1 126 \n", - " Other White 65.2 161 \n", - " Other mixed 66.7 147 \n", - " Pakistani or British Pakistani 57.1 147 \n", - " Unknown 56.9 406 \n", - " White + Asian 57.9 133 \n", - " White + Black African 52.6 133 \n", - " White + Black Caribbean 50.0 126 \n", - "imd_categories 1 Most deprived 55.6 504 \n", - " 2 57.7 546 \n", - " 3 55.6 504 \n", - " 4 56.5 483 \n", - " 5 Least deprived 55.6 504 \n", - " Unknown 57.9 133 \n", - "bmi 30+ 57.6 826 \n", - " under 30 56.1 1848 \n", - "chronic_cardiac_disease no 56.5 2639 \n", - " yes 60.0 35 \n", - "current_copd no 56.7 2653 \n", - " yes 33.3 21 \n", - "dmards no 56.5 2653 \n", - " yes 66.7 21 \n", - "dementia no 56.6 2646 \n", - " yes 50.0 28 \n", - "psychosis_schiz_bipolar no 56.6 2646 \n", - " yes 50.0 28 \n", - "ssri no 56.6 2646 \n", - " yes 50.0 28 \n", - "chemo_or_radio no 56.6 2646 \n", - " yes 40.0 35 \n", - "lung_cancer no 56.7 2653 \n", - " yes 33.3 21 \n", - "cancer_excl_lung_and_haem no 56.7 2653 \n", - " yes 33.3 21 \n", - "haematological_cancer no 56.6 2646 \n", - " yes 40.0 35 \n", - "ckd no 56.6 2114 \n", - " yes 56.2 560 \n", + " percent total \\\n", + "category group \n", + "overall overall 60.2 6727 \n", + "sex F 59.7 3402 \n", + " M 60.6 3325 \n", + "ethnicity_6_groups Black 60.2 1197 \n", + " Mixed 58.3 1176 \n", + " Other 58.8 1120 \n", + " South Asian 61.7 1078 \n", + " Unknown 62.0 994 \n", + " White 60.8 1162 \n", + "ethnicity_16_groups African 53.8 364 \n", + " Bangladeshi or British Bangladeshi 58.0 350 \n", + " Caribbean 58.0 350 \n", + " Chinese 59.2 343 \n", + " Other 60.0 350 \n", + " Other Asian 61.1 378 \n", + " British or Mixed British 60.0 350 \n", + " Indian or British Indian 62.5 392 \n", + " Irish 59.2 343 \n", + " Other Black 63.5 364 \n", + " Other White 59.2 343 \n", + " Other mixed 56.0 350 \n", + " Pakistani or British Pakistani 64.8 378 \n", + " Unknown 62.1 1015 \n", + " White + Asian 58.0 350 \n", + " White + Black African 64.0 350 \n", + " White + Black Caribbean 57.7 364 \n", + "imd_categories 1 Most deprived 57.1 1274 \n", + " 2 59.7 1302 \n", + " 3 62.6 1253 \n", + " 4 61.1 1260 \n", + " 5 Least deprived 59.7 1267 \n", + " Unknown 61.1 378 \n", + "bmi 30+ 60.7 1960 \n", + " under 30 60.1 4767 \n", + "chronic_cardiac_disease no 60.3 6664 \n", + " yes 44.4 63 \n", + "current_copd no 60.2 6650 \n", + " yes 54.5 77 \n", + "dmards no 60.3 6664 \n", + " yes 62.5 56 \n", + "psychosis_schiz_bipolar no 60.1 6657 \n", + " yes 60.0 70 \n", + "ssri no 60.3 6657 \n", + " yes 55.6 63 \n", + "ckd no 60.4 5376 \n", + " yes 59.1 1351 \n", "\n", - " vaccinated 7d previous (percent) \\\n", - "category group \n", - "overall overall 55.2 \n", - "sex F 54.7 \n", - " M 55.2 \n", - "ethnicity_6_groups Black 55.2 \n", - " Mixed 53.0 \n", - " Other 59.4 \n", - " South Asian 52.3 \n", - " Unknown 55.8 \n", - " White 56.7 \n", - "ethnicity_16_groups African 47.1 \n", - " Bangladeshi or British Bangladeshi 50.0 \n", - " Caribbean 42.9 \n", - " Chinese 54.5 \n", - " Other 54.5 \n", - " Other Asian 61.1 \n", - " British or Mixed British 52.4 \n", - " Indian or British Indian 52.6 \n", - " Irish 59.1 \n", - " Other Black 61.1 \n", - " Other White 65.2 \n", - " Other mixed 66.7 \n", - " Pakistani or British Pakistani 57.1 \n", - " Unknown 55.2 \n", - " White + Asian 57.9 \n", - " White + Black African 52.6 \n", - " White + Black Caribbean 50.0 \n", - "imd_categories 1 Most deprived 55.6 \n", - " 2 56.4 \n", - " 3 55.6 \n", - " 4 55.1 \n", - " 5 Least deprived 54.2 \n", - " Unknown 52.6 \n", - "bmi 30+ 56.8 \n", - " under 30 54.5 \n", - "chronic_cardiac_disease no 55.2 \n", - " yes 60.0 \n", - "current_copd no 55.4 \n", - " yes 33.3 \n", - "dmards no 55.1 \n", - " yes 66.7 \n", - "dementia no 55.0 \n", - " yes 50.0 \n", - "psychosis_schiz_bipolar no 55.3 \n", - " yes 50.0 \n", - "ssri no 55.0 \n", - " yes 50.0 \n", - "chemo_or_radio no 55.0 \n", - " yes 40.0 \n", - "lung_cancer no 55.1 \n", - " yes 33.3 \n", - "cancer_excl_lung_and_haem no 55.1 \n", - " yes 33.3 \n", - "haematological_cancer no 55.3 \n", - " yes 40.0 \n", - "ckd no 55.0 \n", - " yes 55.0 \n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 58.6 \n", + "sex F 58.0 \n", + " M 58.9 \n", + "ethnicity_6_groups Black 58.5 \n", + " Mixed 56.5 \n", + " Other 57.5 \n", + " South Asian 59.7 \n", + " Unknown 60.6 \n", + " White 59.0 \n", + "ethnicity_16_groups African 53.8 \n", + " Bangladeshi or British Bangladeshi 56.0 \n", + " Caribbean 56.0 \n", + " Chinese 57.1 \n", + " Other 58.0 \n", + " Other Asian 59.3 \n", + " British or Mixed British 58.0 \n", + " Indian or British Indian 60.7 \n", + " Irish 57.1 \n", + " Other Black 63.5 \n", + " Other White 55.1 \n", + " Other mixed 56.0 \n", + " Pakistani or British Pakistani 63.0 \n", + " Unknown 60.7 \n", + " White + Asian 56.0 \n", + " White + Black African 62.0 \n", + " White + Black Caribbean 55.8 \n", + "imd_categories 1 Most deprived 56.0 \n", + " 2 57.5 \n", + " 3 60.3 \n", + " 4 60.6 \n", + " 5 Least deprived 58.0 \n", + " Unknown 59.3 \n", + "bmi 30+ 58.9 \n", + " under 30 58.4 \n", + "chronic_cardiac_disease no 58.7 \n", + " yes 44.4 \n", + "current_copd no 58.6 \n", + " yes 54.5 \n", + "dmards no 58.6 \n", + " yes 62.5 \n", + "psychosis_schiz_bipolar no 58.6 \n", + " yes 60.0 \n", + "ssri no 58.7 \n", + " yes 55.6 \n", + "ckd no 59.0 \n", + " yes 57.0 \n", "\n", - " Uptake over last 7d (percent) \\\n", - "category group \n", - "overall overall 1.3 \n", - "sex F 2.1 \n", - " M 1.0 \n", - "ethnicity_6_groups Black 1.5 \n", - " Mixed 1.5 \n", - " Other 0.0 \n", - " South Asian 1.5 \n", - " Unknown 1.9 \n", - " White 1.5 \n", - "ethnicity_16_groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 4.5 \n", - " Caribbean 0.0 \n", - " Chinese 0.0 \n", - " Other 4.6 \n", - " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 5.3 \n", - " Irish 4.5 \n", - " Other Black 0.0 \n", - " Other White 0.0 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 1.7 \n", - " White + Asian 0.0 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 0.0 \n", - " 2 1.3 \n", - " 3 0.0 \n", - " 4 1.4 \n", - " 5 Least deprived 1.4 \n", - " Unknown 5.3 \n", - "bmi 30+ 0.8 \n", - " under 30 1.6 \n", - "chronic_cardiac_disease no 1.3 \n", - " yes 0.0 \n", - "current_copd no 1.3 \n", - " yes 0.0 \n", - "dmards no 1.4 \n", - " yes 0.0 \n", - "dementia no 1.6 \n", - " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.3 \n", - " yes 0.0 \n", - "ssri no 1.6 \n", - " yes 0.0 \n", - "chemo_or_radio no 1.6 \n", - " yes 0.0 \n", - "lung_cancer no 1.6 \n", - " yes 0.0 \n", - "cancer_excl_lung_and_haem no 1.6 \n", - " yes 0.0 \n", - "haematological_cancer no 1.3 \n", - " yes 0.0 \n", - "ckd no 1.6 \n", - " yes 1.2 \n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.6 \n", + "sex F 1.7 \n", + " M 1.7 \n", + "ethnicity_6_groups Black 1.7 \n", + " Mixed 1.8 \n", + " Other 1.3 \n", + " South Asian 2.0 \n", + " Unknown 1.4 \n", + " White 1.8 \n", + "ethnicity_16_groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 2.0 \n", + " Caribbean 2.0 \n", + " Chinese 2.1 \n", + " Other 2.0 \n", + " Other Asian 1.8 \n", + " British or Mixed British 2.0 \n", + " Indian or British Indian 1.8 \n", + " Irish 2.1 \n", + " Other Black 0.0 \n", + " Other White 4.1 \n", + " Other mixed 0.0 \n", + " Pakistani or British Pakistani 1.8 \n", + " Unknown 1.4 \n", + " White + Asian 2.0 \n", + " White + Black African 2.0 \n", + " White + Black Caribbean 1.9 \n", + "imd_categories 1 Most deprived 1.1 \n", + " 2 2.2 \n", + " 3 2.3 \n", + " 4 0.5 \n", + " 5 Least deprived 1.7 \n", + " Unknown 1.8 \n", + "bmi 30+ 1.8 \n", + " under 30 1.7 \n", + "chronic_cardiac_disease no 1.6 \n", + " yes 0.0 \n", + "current_copd no 1.6 \n", + " yes 0.0 \n", + "dmards no 1.7 \n", + " yes 0.0 \n", + "psychosis_schiz_bipolar no 1.5 \n", + " yes 0.0 \n", + "ssri no 1.6 \n", + " yes 0.0 \n", + "ckd no 1.4 \n", + " yes 2.1 \n", "\n", - " Date projected to reach 90% \n", - "category group \n", - "overall overall unknown \n", - "sex F 27-Dec \n", - " M unknown \n", - "ethnicity_6_groups Black 10-Feb \n", - " Mixed 20-Feb \n", - " Other unknown \n", - " South Asian 23-Feb \n", - " Unknown 05-Jan \n", - " White 03-Feb \n", - "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi 02-Nov \n", - " Caribbean unknown \n", - " Chinese unknown \n", - " Other 25-Oct \n", - " Other Asian unknown \n", - " British or Mixed British unknown \n", - " Indian or British Indian 20-Oct \n", - " Irish 19-Oct \n", - " Other Black unknown \n", - " Other White unknown \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani unknown \n", - " Unknown 22-Jan \n", - " White + Asian unknown \n", - " White + Black African unknown \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived unknown \n", - " 2 28-Feb \n", - " 3 unknown \n", - " 4 22-Feb \n", - " 5 Least deprived 27-Feb \n", - " Unknown 20-Oct \n", - "bmi 30+ unknown \n", - " under 30 03-Feb \n", - "chronic_cardiac_disease no unknown \n", - " yes unknown \n", - "current_copd no unknown \n", - " yes unknown \n", - "dmards no 22-Feb \n", - " yes unknown \n", - "dementia no 01-Feb \n", - " yes unknown \n", - "psychosis_schiz_bipolar no unknown \n", - " yes unknown \n", - "ssri no 01-Feb \n", - " yes unknown \n", - "chemo_or_radio no 01-Feb \n", - " yes unknown \n", - "lung_cancer no 31-Jan \n", - " yes unknown \n", - "cancer_excl_lung_and_haem no 31-Jan \n", - " yes unknown \n", - "haematological_cancer no unknown \n", - " yes unknown \n", - "ckd no 01-Feb \n", - " yes unknown " + " Date projected to reach 90% \n", + "category group \n", + "overall overall 06-Mar \n", + "sex F 28-Feb \n", + " M 25-Feb \n", + "ethnicity_6_groups Black 26-Feb \n", + " Mixed 27-Feb \n", + " Other 13-Apr \n", + " South Asian 03-Feb \n", + " Unknown 16-Mar \n", + " White 17-Feb \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi 16-Feb \n", + " Caribbean 16-Feb \n", + " Chinese 06-Feb \n", + " Other 09-Feb \n", + " Other Asian 16-Feb \n", + " British or Mixed British 09-Feb \n", + " Indian or British Indian 10-Feb \n", + " Irish 06-Feb \n", + " Other Black unknown \n", + " Other White 18-Dec \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani 02-Feb \n", + " Unknown 15-Mar \n", + " White + Asian 16-Feb \n", + " White + Black African 26-Jan \n", + " White + Black Caribbean 23-Feb \n", + "imd_categories 1 Most deprived unknown \n", + " 2 31-Jan \n", + " 3 18-Jan \n", + " 4 unknown \n", + " 5 Least deprived 28-Feb \n", + " Unknown 16-Feb \n", + "bmi 30+ 17-Feb \n", + " under 30 27-Feb \n", + "chronic_cardiac_disease no 05-Mar \n", + " yes unknown \n", + "current_copd no 06-Mar \n", + " yes unknown \n", + "dmards no 26-Feb \n", + " yes unknown \n", + "psychosis_schiz_bipolar no 15-Mar \n", + " yes unknown \n", + "ssri no 05-Mar \n", + " yes unknown \n", + "ckd no 24-Mar \n", + " yes 07-Feb " ] }, "metadata": {}, @@ -46749,7 +59007,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose 14weeks ago) among **55-59** population up to 2021-09-08" + "## COVID vaccination rollout (second dose 14w ago) among **40-49** population up to 2021-10-27" ], "text/plain": [ "" @@ -46815,428 +59073,428 @@ " \n", " overall\n", " overall\n", - " 1799\n", - " 56.5\n", - " 3185\n", - " 54.9\n", - " 1.6\n", - " 01-Feb\n", + " 7483\n", + " 61.1\n", + " 12257\n", + " 59.7\n", + " 1.4\n", + " 20-Mar\n", " \n", " \n", " sex\n", " F\n", - " 938\n", - " 57.8\n", - " 1624\n", - " 56.0\n", - " 1.8\n", - " 11-Jan\n", + " 3878\n", + " 60.7\n", + " 6391\n", + " 59.5\n", + " 1.2\n", + " 15-Apr\n", " \n", " \n", " M\n", - " 861\n", - " 55.2\n", - " 1561\n", - " 53.8\n", - " 1.4\n", - " 01-Mar\n", + " 3605\n", + " 61.5\n", + " 5866\n", + " 59.9\n", + " 1.6\n", + " 28-Feb\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 315\n", - " 54.9\n", - " 574\n", - " 52.4\n", - " 2.5\n", - " 15-Dec\n", + " 1267\n", + " 60.5\n", + " 2093\n", + " 59.2\n", + " 1.3\n", + " 03-Apr\n", " \n", " \n", " Mixed\n", - " 322\n", - " 56.1\n", - " 574\n", - " 54.9\n", - " 1.2\n", - " unknown\n", + " 1281\n", + " 61.4\n", + " 2086\n", + " 60.1\n", + " 1.3\n", + " 30-Mar\n", " \n", " \n", " Other\n", - " 301\n", - " 58.1\n", - " 518\n", - " 56.8\n", - " 1.3\n", - " 26-Feb\n", + " 1267\n", + " 61.6\n", + " 2058\n", + " 60.2\n", + " 1.4\n", + " 18-Mar\n", " \n", " \n", " South Asian\n", - " 301\n", - " 55.8\n", - " 539\n", - " 54.5\n", - " 1.3\n", - " unknown\n", + " 1253\n", + " 60.9\n", + " 2058\n", + " 59.2\n", + " 1.7\n", + " 23-Feb\n", " \n", " \n", " Unknown\n", - " 231\n", - " 55.0\n", - " 420\n", - " 55.0\n", - " 0.0\n", + " 1169\n", + " 61.6\n", + " 1897\n", + " 60.5\n", + " 1.1\n", " unknown\n", " \n", " \n", " White\n", - " 322\n", - " 58.2\n", - " 553\n", - " 57.0\n", - " 1.2\n", - " unknown\n", + " 1246\n", + " 60.3\n", + " 2065\n", + " 59.0\n", + " 1.3\n", + " 04-Apr\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 105\n", - " 60.0\n", - " 175\n", - " 56.0\n", - " 4.0\n", - " 30-Oct\n", + " 378\n", + " 59.3\n", + " 637\n", + " 58.2\n", + " 1.1\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 98\n", - " 58.3\n", - " 168\n", - " 58.3\n", - " 0.0\n", + " 371\n", + " 57.6\n", + " 644\n", + " 56.5\n", + " 1.1\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 91\n", - " 56.5\n", - " 161\n", - " 52.2\n", - " 4.3\n", - " 01-Nov\n", + " 448\n", + " 62.7\n", + " 714\n", + " 60.8\n", + " 1.9\n", + " 04-Feb\n", " \n", " \n", " Chinese\n", - " 105\n", - " 57.7\n", - " 182\n", - " 53.8\n", - " 3.9\n", - " 04-Nov\n", + " 385\n", + " 60.4\n", + " 637\n", + " 60.4\n", + " 0.0\n", + " unknown\n", " \n", " \n", " Other\n", - " 84\n", - " 57.1\n", - " 147\n", - " 57.1\n", - " 0.0\n", + " 420\n", + " 61.9\n", + " 679\n", + " 60.8\n", + " 1.1\n", " unknown\n", " \n", " \n", " Other Asian\n", - " 84\n", - " 52.2\n", - " 161\n", - " 52.2\n", - " 0.0\n", + " 378\n", + " 60.7\n", + " 623\n", + " 59.6\n", + " 1.1\n", " unknown\n", " \n", " \n", " British or Mixed British\n", - " 91\n", - " 56.5\n", - " 161\n", - " 56.5\n", - " 0.0\n", + " 406\n", + " 63.0\n", + " 644\n", + " 62.0\n", + " 1.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 91\n", - " 54.2\n", - " 168\n", - " 50.0\n", - " 4.2\n", - " 06-Nov\n", + " 392\n", + " 60.9\n", + " 644\n", + " 59.8\n", + " 1.1\n", + " unknown\n", " \n", " \n", " Irish\n", - " 98\n", - " 56.0\n", - " 175\n", - " 56.0\n", - " 0.0\n", - " unknown\n", + " 441\n", + " 63.6\n", + " 693\n", + " 61.6\n", + " 2.0\n", + " 27-Jan\n", " \n", " \n", " Other Black\n", - " 91\n", - " 59.1\n", - " 154\n", - " 59.1\n", - " 0.0\n", + " 385\n", + " 57.3\n", + " 672\n", + " 56.2\n", + " 1.1\n", " unknown\n", " \n", " \n", " Other White\n", - " 91\n", - " 59.1\n", - " 154\n", - " 59.1\n", + " 413\n", + " 60.2\n", + " 686\n", + " 60.2\n", " 0.0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 84\n", - " 46.2\n", - " 182\n", - " 46.2\n", - " 0.0\n", + " 385\n", + " 61.1\n", + " 630\n", + " 60.0\n", + " 1.1\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 112\n", - " 59.3\n", - " 189\n", - " 55.6\n", - " 3.7\n", - " 05-Nov\n", + " 371\n", + " 60.2\n", + " 616\n", + " 59.1\n", + " 1.1\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 287\n", - " 59.4\n", - " 483\n", - " 58.0\n", - " 1.4\n", - " 08-Feb\n", + " 1134\n", + " 62.3\n", + " 1820\n", + " 60.8\n", + " 1.5\n", + " 05-Mar\n", " \n", " \n", " White + Asian\n", - " 105\n", - " 62.5\n", - " 168\n", - " 62.5\n", - " 0.0\n", - " unknown\n", + " 364\n", + " 61.2\n", + " 595\n", + " 60.0\n", + " 1.2\n", + " 13-Apr\n", " \n", " \n", " White + Black African\n", - " 91\n", - " 56.5\n", - " 161\n", - " 56.5\n", - " 0.0\n", + " 392\n", + " 60.2\n", + " 651\n", + " 59.1\n", + " 1.1\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 91\n", - " 50.0\n", - " 182\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 406\n", + " 61.1\n", + " 665\n", + " 58.9\n", + " 2.2\n", + " 26-Jan\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 364\n", - " 59.8\n", - " 609\n", - " 58.6\n", + " 1449\n", + " 62.3\n", + " 2324\n", + " 61.1\n", " 1.2\n", - " unknown\n", + " 06-Apr\n", " \n", " \n", " 2\n", - " 336\n", - " 52.2\n", - " 644\n", - " 51.1\n", - " 1.1\n", - " unknown\n", + " 1414\n", + " 61.2\n", + " 2310\n", + " 60.0\n", + " 1.2\n", + " 13-Apr\n", " \n", " \n", " 3\n", - " 336\n", - " 57.1\n", - " 588\n", - " 54.8\n", - " 2.3\n", - " 17-Dec\n", + " 1421\n", + " 61.0\n", + " 2331\n", + " 59.5\n", + " 1.5\n", + " 11-Mar\n", " \n", " \n", " 4\n", - " 329\n", - " 54.7\n", - " 602\n", - " 52.3\n", - " 2.4\n", - " 19-Dec\n", + " 1393\n", + " 59.9\n", + " 2324\n", + " 57.8\n", + " 2.1\n", + " 04-Feb\n", " \n", " \n", " 5 Least deprived\n", - " 336\n", - " 59.3\n", - " 567\n", - " 58.0\n", - " 1.3\n", - " 20-Feb\n", + " 1442\n", + " 61.3\n", + " 2352\n", + " 60.1\n", + " 1.2\n", + " 12-Apr\n", " \n", " \n", " Unknown\n", - " 105\n", - " 60.0\n", - " 175\n", - " 56.0\n", - " 4.0\n", - " 30-Oct\n", + " 364\n", + " 59.1\n", + " 616\n", + " 56.8\n", + " 2.3\n", + " 29-Jan\n", " \n", " \n", " bmi\n", " 30+\n", - " 546\n", - " 56.9\n", - " 959\n", - " 55.5\n", - " 1.4\n", - " 20-Feb\n", + " 2254\n", + " 61.6\n", + " 3661\n", + " 60.4\n", + " 1.2\n", + " 10-Apr\n", " \n", " \n", " under 30\n", - " 1253\n", - " 56.3\n", - " 2226\n", - " 54.7\n", - " 1.6\n", - " 02-Feb\n", + " 5229\n", + " 60.9\n", + " 8589\n", + " 59.4\n", + " 1.5\n", + " 11-Mar\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1771\n", - " 56.3\n", - " 3143\n", - " 54.8\n", - " 1.5\n", - " 12-Feb\n", + " 7406\n", + " 61.1\n", + " 12117\n", + " 59.7\n", + " 1.4\n", + " 20-Mar\n", " \n", " \n", " yes\n", - " 28\n", - " 66.7\n", - " 42\n", - " 66.7\n", - " 0.0\n", - " unknown\n", + " 84\n", + " 60.0\n", + " 140\n", + " 55.0\n", + " 5.0\n", + " 08-Dec\n", " \n", " \n", " current_copd\n", " no\n", - " 1778\n", - " 56.4\n", - " 3150\n", - " 54.9\n", - " 1.5\n", - " 11-Feb\n", + " 7420\n", + " 61.1\n", + " 12145\n", + " 59.7\n", + " 1.4\n", + " 20-Mar\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 63\n", + " 56.2\n", + " 112\n", + " 56.2\n", " 0.0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1785\n", - " 56.7\n", - " 3150\n", - " 55.1\n", - " 1.6\n", - " 31-Jan\n", + " 7406\n", + " 61.1\n", + " 12117\n", + " 59.8\n", + " 1.3\n", + " 31-Mar\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", - " 0.0\n", - " unknown\n", + " 77\n", + " 55.0\n", + " 140\n", + " 50.0\n", + " 5.0\n", + " 15-Dec\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1778\n", - " 56.4\n", - " 3150\n", - " 55.1\n", - " 1.3\n", - " unknown\n", + " 7406\n", + " 61.0\n", + " 12138\n", + " 59.6\n", + " 1.4\n", + " 21-Mar\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 77\n", + " 64.7\n", + " 119\n", + " 64.7\n", " 0.0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1778\n", - " 56.6\n", - " 3143\n", - " 55.0\n", - " 1.6\n", - " 01-Feb\n", + " 7427\n", + " 61.1\n", + " 12159\n", + " 59.7\n", + " 1.4\n", + " 20-Mar\n", " \n", " \n", " yes\n", - " 21\n", - " 50.0\n", - " 42\n", - " 50.0\n", + " 56\n", + " 57.1\n", + " 98\n", + " 57.1\n", " 0.0\n", " unknown\n", " \n", " \n", " ckd\n", " no\n", - " 1456\n", - " 56.1\n", - " 2597\n", - " 54.4\n", - " 1.7\n", - " 25-Jan\n", + " 5985\n", + " 60.9\n", + " 9835\n", + " 59.5\n", + " 1.4\n", + " 21-Mar\n", " \n", " \n", " yes\n", - " 343\n", - " 58.3\n", - " 588\n", - " 57.1\n", - " 1.2\n", - " unknown\n", + " 1498\n", + " 61.8\n", + " 2422\n", + " 60.1\n", + " 1.7\n", + " 20-Feb\n", " \n", " \n", "\n", @@ -47245,248 +59503,248 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1799 \n", - "sex F 938 \n", - " M 861 \n", - "ethnicity_6_groups Black 315 \n", - " Mixed 322 \n", - " Other 301 \n", - " South Asian 301 \n", - " Unknown 231 \n", - " White 322 \n", - "ethnicity_16_groups African 105 \n", - " Bangladeshi or British Bangladeshi 98 \n", - " Caribbean 91 \n", - " Chinese 105 \n", - " Other 84 \n", - " Other Asian 84 \n", - " British or Mixed British 91 \n", - " Indian or British Indian 91 \n", - " Irish 98 \n", - " Other Black 91 \n", - " Other White 91 \n", - " Other mixed 84 \n", - " Pakistani or British Pakistani 112 \n", - " Unknown 287 \n", - " White + Asian 105 \n", - " White + Black African 91 \n", - " White + Black Caribbean 91 \n", - "imd_categories 1 Most deprived 364 \n", - " 2 336 \n", - " 3 336 \n", - " 4 329 \n", - " 5 Least deprived 336 \n", - " Unknown 105 \n", - "bmi 30+ 546 \n", - " under 30 1253 \n", - "chronic_cardiac_disease no 1771 \n", - " yes 28 \n", - "current_copd no 1778 \n", - " yes 21 \n", - "dmards no 1785 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1778 \n", - " yes 21 \n", - "ssri no 1778 \n", - " yes 21 \n", - "ckd no 1456 \n", - " yes 343 \n", + "overall overall 7483 \n", + "sex F 3878 \n", + " M 3605 \n", + "ethnicity_6_groups Black 1267 \n", + " Mixed 1281 \n", + " Other 1267 \n", + " South Asian 1253 \n", + " Unknown 1169 \n", + " White 1246 \n", + "ethnicity_16_groups African 378 \n", + " Bangladeshi or British Bangladeshi 371 \n", + " Caribbean 448 \n", + " Chinese 385 \n", + " Other 420 \n", + " Other Asian 378 \n", + " British or Mixed British 406 \n", + " Indian or British Indian 392 \n", + " Irish 441 \n", + " Other Black 385 \n", + " Other White 413 \n", + " Other mixed 385 \n", + " Pakistani or British Pakistani 371 \n", + " Unknown 1134 \n", + " White + Asian 364 \n", + " White + Black African 392 \n", + " White + Black Caribbean 406 \n", + "imd_categories 1 Most deprived 1449 \n", + " 2 1414 \n", + " 3 1421 \n", + " 4 1393 \n", + " 5 Least deprived 1442 \n", + " Unknown 364 \n", + "bmi 30+ 2254 \n", + " under 30 5229 \n", + "chronic_cardiac_disease no 7406 \n", + " yes 84 \n", + "current_copd no 7420 \n", + " yes 63 \n", + "dmards no 7406 \n", + " yes 77 \n", + "psychosis_schiz_bipolar no 7406 \n", + " yes 77 \n", + "ssri no 7427 \n", + " yes 56 \n", + "ckd no 5985 \n", + " yes 1498 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 56.5 3185 \n", - "sex F 57.8 1624 \n", - " M 55.2 1561 \n", - "ethnicity_6_groups Black 54.9 574 \n", - " Mixed 56.1 574 \n", - " Other 58.1 518 \n", - " South Asian 55.8 539 \n", - " Unknown 55.0 420 \n", - " White 58.2 553 \n", - "ethnicity_16_groups African 60.0 175 \n", - " Bangladeshi or British Bangladeshi 58.3 168 \n", - " Caribbean 56.5 161 \n", - " Chinese 57.7 182 \n", - " Other 57.1 147 \n", - " Other Asian 52.2 161 \n", - " British or Mixed British 56.5 161 \n", - " Indian or British Indian 54.2 168 \n", - " Irish 56.0 175 \n", - " Other Black 59.1 154 \n", - " Other White 59.1 154 \n", - " Other mixed 46.2 182 \n", - " Pakistani or British Pakistani 59.3 189 \n", - " Unknown 59.4 483 \n", - " White + Asian 62.5 168 \n", - " White + Black African 56.5 161 \n", - " White + Black Caribbean 50.0 182 \n", - "imd_categories 1 Most deprived 59.8 609 \n", - " 2 52.2 644 \n", - " 3 57.1 588 \n", - " 4 54.7 602 \n", - " 5 Least deprived 59.3 567 \n", - " Unknown 60.0 175 \n", - "bmi 30+ 56.9 959 \n", - " under 30 56.3 2226 \n", - "chronic_cardiac_disease no 56.3 3143 \n", - " yes 66.7 42 \n", - "current_copd no 56.4 3150 \n", - " yes 60.0 35 \n", - "dmards no 56.7 3150 \n", - " yes 40.0 35 \n", - "psychosis_schiz_bipolar no 56.4 3150 \n", - " yes 60.0 35 \n", - "ssri no 56.6 3143 \n", - " yes 50.0 42 \n", - "ckd no 56.1 2597 \n", - " yes 58.3 588 \n", + "overall overall 61.1 12257 \n", + "sex F 60.7 6391 \n", + " M 61.5 5866 \n", + "ethnicity_6_groups Black 60.5 2093 \n", + " Mixed 61.4 2086 \n", + " Other 61.6 2058 \n", + " South Asian 60.9 2058 \n", + " Unknown 61.6 1897 \n", + " White 60.3 2065 \n", + "ethnicity_16_groups African 59.3 637 \n", + " Bangladeshi or British Bangladeshi 57.6 644 \n", + " Caribbean 62.7 714 \n", + " Chinese 60.4 637 \n", + " Other 61.9 679 \n", + " Other Asian 60.7 623 \n", + " British or Mixed British 63.0 644 \n", + " Indian or British Indian 60.9 644 \n", + " Irish 63.6 693 \n", + " Other Black 57.3 672 \n", + " Other White 60.2 686 \n", + " Other mixed 61.1 630 \n", + " Pakistani or British Pakistani 60.2 616 \n", + " Unknown 62.3 1820 \n", + " White + Asian 61.2 595 \n", + " White + Black African 60.2 651 \n", + " White + Black Caribbean 61.1 665 \n", + "imd_categories 1 Most deprived 62.3 2324 \n", + " 2 61.2 2310 \n", + " 3 61.0 2331 \n", + " 4 59.9 2324 \n", + " 5 Least deprived 61.3 2352 \n", + " Unknown 59.1 616 \n", + "bmi 30+ 61.6 3661 \n", + " under 30 60.9 8589 \n", + "chronic_cardiac_disease no 61.1 12117 \n", + " yes 60.0 140 \n", + "current_copd no 61.1 12145 \n", + " yes 56.2 112 \n", + "dmards no 61.1 12117 \n", + " yes 55.0 140 \n", + "psychosis_schiz_bipolar no 61.0 12138 \n", + " yes 64.7 119 \n", + "ssri no 61.1 12159 \n", + " yes 57.1 98 \n", + "ckd no 60.9 9835 \n", + " yes 61.8 2422 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 54.9 \n", - "sex F 56.0 \n", - " M 53.8 \n", - "ethnicity_6_groups Black 52.4 \n", - " Mixed 54.9 \n", - " Other 56.8 \n", - " South Asian 54.5 \n", - " Unknown 55.0 \n", - " White 57.0 \n", - "ethnicity_16_groups African 56.0 \n", - " Bangladeshi or British Bangladeshi 58.3 \n", - " Caribbean 52.2 \n", - " Chinese 53.8 \n", - " Other 57.1 \n", - " Other Asian 52.2 \n", - " British or Mixed British 56.5 \n", - " Indian or British Indian 50.0 \n", - " Irish 56.0 \n", - " Other Black 59.1 \n", - " Other White 59.1 \n", - " Other mixed 46.2 \n", - " Pakistani or British Pakistani 55.6 \n", - " Unknown 58.0 \n", - " White + Asian 62.5 \n", - " White + Black African 56.5 \n", - " White + Black Caribbean 50.0 \n", - "imd_categories 1 Most deprived 58.6 \n", - " 2 51.1 \n", - " 3 54.8 \n", - " 4 52.3 \n", - " 5 Least deprived 58.0 \n", - " Unknown 56.0 \n", - "bmi 30+ 55.5 \n", - " under 30 54.7 \n", - "chronic_cardiac_disease no 54.8 \n", - " yes 66.7 \n", - "current_copd no 54.9 \n", - " yes 60.0 \n", - "dmards no 55.1 \n", - " yes 40.0 \n", - "psychosis_schiz_bipolar no 55.1 \n", - " yes 60.0 \n", - "ssri no 55.0 \n", + "overall overall 59.7 \n", + "sex F 59.5 \n", + " M 59.9 \n", + "ethnicity_6_groups Black 59.2 \n", + " Mixed 60.1 \n", + " Other 60.2 \n", + " South Asian 59.2 \n", + " Unknown 60.5 \n", + " White 59.0 \n", + "ethnicity_16_groups African 58.2 \n", + " Bangladeshi or British Bangladeshi 56.5 \n", + " Caribbean 60.8 \n", + " Chinese 60.4 \n", + " Other 60.8 \n", + " Other Asian 59.6 \n", + " British or Mixed British 62.0 \n", + " Indian or British Indian 59.8 \n", + " Irish 61.6 \n", + " Other Black 56.2 \n", + " Other White 60.2 \n", + " Other mixed 60.0 \n", + " Pakistani or British Pakistani 59.1 \n", + " Unknown 60.8 \n", + " White + Asian 60.0 \n", + " White + Black African 59.1 \n", + " White + Black Caribbean 58.9 \n", + "imd_categories 1 Most deprived 61.1 \n", + " 2 60.0 \n", + " 3 59.5 \n", + " 4 57.8 \n", + " 5 Least deprived 60.1 \n", + " Unknown 56.8 \n", + "bmi 30+ 60.4 \n", + " under 30 59.4 \n", + "chronic_cardiac_disease no 59.7 \n", + " yes 55.0 \n", + "current_copd no 59.7 \n", + " yes 56.2 \n", + "dmards no 59.8 \n", " yes 50.0 \n", - "ckd no 54.4 \n", + "psychosis_schiz_bipolar no 59.6 \n", + " yes 64.7 \n", + "ssri no 59.7 \n", " yes 57.1 \n", + "ckd no 59.5 \n", + " yes 60.1 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 1.6 \n", - "sex F 1.8 \n", - " M 1.4 \n", - "ethnicity_6_groups Black 2.5 \n", - " Mixed 1.2 \n", - " Other 1.3 \n", - " South Asian 1.3 \n", - " Unknown 0.0 \n", - " White 1.2 \n", - "ethnicity_16_groups African 4.0 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 4.3 \n", - " Chinese 3.9 \n", - " Other 0.0 \n", - " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 4.2 \n", - " Irish 0.0 \n", - " Other Black 0.0 \n", + "overall overall 1.4 \n", + "sex F 1.2 \n", + " M 1.6 \n", + "ethnicity_6_groups Black 1.3 \n", + " Mixed 1.3 \n", + " Other 1.4 \n", + " South Asian 1.7 \n", + " Unknown 1.1 \n", + " White 1.3 \n", + "ethnicity_16_groups African 1.1 \n", + " Bangladeshi or British Bangladeshi 1.1 \n", + " Caribbean 1.9 \n", + " Chinese 0.0 \n", + " Other 1.1 \n", + " Other Asian 1.1 \n", + " British or Mixed British 1.0 \n", + " Indian or British Indian 1.1 \n", + " Irish 2.0 \n", + " Other Black 1.1 \n", " Other White 0.0 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 3.7 \n", - " Unknown 1.4 \n", - " White + Asian 0.0 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", + " Other mixed 1.1 \n", + " Pakistani or British Pakistani 1.1 \n", + " Unknown 1.5 \n", + " White + Asian 1.2 \n", + " White + Black African 1.1 \n", + " White + Black Caribbean 2.2 \n", "imd_categories 1 Most deprived 1.2 \n", - " 2 1.1 \n", - " 3 2.3 \n", - " 4 2.4 \n", - " 5 Least deprived 1.3 \n", - " Unknown 4.0 \n", - "bmi 30+ 1.4 \n", - " under 30 1.6 \n", - "chronic_cardiac_disease no 1.5 \n", - " yes 0.0 \n", - "current_copd no 1.5 \n", - " yes 0.0 \n", - "dmards no 1.6 \n", + " 2 1.2 \n", + " 3 1.5 \n", + " 4 2.1 \n", + " 5 Least deprived 1.2 \n", + " Unknown 2.3 \n", + "bmi 30+ 1.2 \n", + " under 30 1.5 \n", + "chronic_cardiac_disease no 1.4 \n", + " yes 5.0 \n", + "current_copd no 1.4 \n", " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.3 \n", + "dmards no 1.3 \n", + " yes 5.0 \n", + "psychosis_schiz_bipolar no 1.4 \n", " yes 0.0 \n", - "ssri no 1.6 \n", + "ssri no 1.4 \n", " yes 0.0 \n", - "ckd no 1.7 \n", - " yes 1.2 \n", + "ckd no 1.4 \n", + " yes 1.7 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 01-Feb \n", - "sex F 11-Jan \n", - " M 01-Mar \n", - "ethnicity_6_groups Black 15-Dec \n", - " Mixed unknown \n", - " Other 26-Feb \n", - " South Asian unknown \n", + "overall overall 20-Mar \n", + "sex F 15-Apr \n", + " M 28-Feb \n", + "ethnicity_6_groups Black 03-Apr \n", + " Mixed 30-Mar \n", + " Other 18-Mar \n", + " South Asian 23-Feb \n", " Unknown unknown \n", - " White unknown \n", - "ethnicity_16_groups African 30-Oct \n", + " White 04-Apr \n", + "ethnicity_16_groups African unknown \n", " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean 01-Nov \n", - " Chinese 04-Nov \n", + " Caribbean 04-Feb \n", + " Chinese unknown \n", " Other unknown \n", " Other Asian unknown \n", " British or Mixed British unknown \n", - " Indian or British Indian 06-Nov \n", - " Irish unknown \n", + " Indian or British Indian unknown \n", + " Irish 27-Jan \n", " Other Black unknown \n", " Other White unknown \n", " Other mixed unknown \n", - " Pakistani or British Pakistani 05-Nov \n", - " Unknown 08-Feb \n", - " White + Asian unknown \n", + " Pakistani or British Pakistani unknown \n", + " Unknown 05-Mar \n", + " White + Asian 13-Apr \n", " White + Black African unknown \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived unknown \n", - " 2 unknown \n", - " 3 17-Dec \n", - " 4 19-Dec \n", - " 5 Least deprived 20-Feb \n", - " Unknown 30-Oct \n", - "bmi 30+ 20-Feb \n", - " under 30 02-Feb \n", - "chronic_cardiac_disease no 12-Feb \n", - " yes unknown \n", - "current_copd no 11-Feb \n", - " yes unknown \n", - "dmards no 31-Jan \n", + " White + Black Caribbean 26-Jan \n", + "imd_categories 1 Most deprived 06-Apr \n", + " 2 13-Apr \n", + " 3 11-Mar \n", + " 4 04-Feb \n", + " 5 Least deprived 12-Apr \n", + " Unknown 29-Jan \n", + "bmi 30+ 10-Apr \n", + " under 30 11-Mar \n", + "chronic_cardiac_disease no 20-Mar \n", + " yes 08-Dec \n", + "current_copd no 20-Mar \n", " yes unknown \n", - "psychosis_schiz_bipolar no unknown \n", + "dmards no 31-Mar \n", + " yes 15-Dec \n", + "psychosis_schiz_bipolar no 21-Mar \n", " yes unknown \n", - "ssri no 01-Feb \n", + "ssri no 20-Mar \n", " yes unknown \n", - "ckd no 25-Jan \n", - " yes unknown " + "ckd no 21-Mar \n", + " yes 20-Feb " ] }, "metadata": {}, @@ -47515,7 +59773,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose 14weeks ago) among **50-54** population up to 2021-09-08" + "## COVID vaccination rollout (second dose 14w ago) among **30-39** population up to 2021-10-27" ], "text/plain": [ "" @@ -47581,426 +59839,293 @@ " \n", " overall\n", " overall\n", - " 1995\n", - " 57.7\n", - " 3458\n", - " 55.9\n", - " 1.8\n", - " 11-Jan\n", + " 7854\n", + " 60.6\n", + " 12957\n", + " 59.4\n", + " 1.2\n", + " 16-Apr\n", " \n", " \n", " sex\n", " F\n", - " 1050\n", - " 59.3\n", - " 1771\n", - " 57.3\n", - " 2.0\n", - " 24-Dec\n", + " 4102\n", + " 61.0\n", + " 6727\n", + " 59.8\n", + " 1.2\n", + " 14-Apr\n", " \n", " \n", " M\n", - " 945\n", - " 56.0\n", - " 1687\n", - " 54.4\n", - " 1.6\n", - " 03-Feb\n", + " 3752\n", + " 60.2\n", + " 6230\n", + " 58.9\n", + " 1.3\n", + " 05-Apr\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 350\n", - " 58.8\n", - " 595\n", - " 56.5\n", - " 2.3\n", - " 11-Dec\n", + " 1344\n", + " 60.2\n", + " 2233\n", + " 58.9\n", + " 1.3\n", + " 05-Apr\n", " \n", " \n", " Mixed\n", - " 315\n", - " 53.6\n", - " 588\n", - " 51.2\n", - " 2.4\n", - " 23-Dec\n", + " 1351\n", + " 61.3\n", + " 2205\n", + " 60.3\n", + " 1.0\n", + " unknown\n", " \n", " \n", " Other\n", - " 364\n", - " 59.1\n", - " 616\n", - " 58.0\n", - " 1.1\n", - " unknown\n", + " 1288\n", + " 60.5\n", + " 2128\n", + " 59.2\n", + " 1.3\n", + " 03-Apr\n", " \n", " \n", " South Asian\n", - " 343\n", - " 61.3\n", - " 560\n", - " 58.8\n", - " 2.5\n", - " 27-Nov\n", - " \n", - " \n", - " Unknown\n", - " 287\n", - " 54.7\n", - " 525\n", - " 53.3\n", + " 1379\n", + " 61.2\n", + " 2254\n", + " 59.6\n", + " 1.6\n", + " 02-Mar\n", + " \n", + " \n", + " Unknown\n", + " 1176\n", + " 61.3\n", + " 1918\n", + " 59.9\n", " 1.4\n", - " unknown\n", + " 19-Mar\n", " \n", " \n", " White\n", - " 336\n", - " 58.5\n", - " 574\n", - " 57.3\n", + " 1323\n", + " 59.4\n", + " 2226\n", + " 58.2\n", " 1.2\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 112\n", - " 55.2\n", - " 203\n", - " 51.7\n", - " 3.5\n", - " 16-Nov\n", + " 413\n", + " 59.0\n", + " 700\n", + " 58.0\n", + " 1.0\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 84\n", - " 50.0\n", - " 168\n", - " 50.0\n", - " 0.0\n", + " 413\n", + " 60.2\n", + " 686\n", + " 59.2\n", + " 1.0\n", " unknown\n", " \n", " \n", " Caribbean\n", - " 105\n", - " 55.6\n", - " 189\n", - " 55.6\n", - " 0.0\n", + " 406\n", + " 61.7\n", + " 658\n", + " 60.6\n", + " 1.1\n", " unknown\n", " \n", " \n", " Chinese\n", - " 98\n", - " 53.8\n", - " 182\n", - " 53.8\n", - " 0.0\n", + " 399\n", + " 57.0\n", + " 700\n", + " 56.0\n", + " 1.0\n", " unknown\n", " \n", " \n", " Other\n", - " 112\n", - " 59.3\n", - " 189\n", - " 55.6\n", - " 3.7\n", - " 05-Nov\n", + " 434\n", + " 63.9\n", + " 679\n", + " 62.9\n", + " 1.0\n", + " unknown\n", " \n", " \n", " Other Asian\n", - " 105\n", - " 57.7\n", - " 182\n", - " 53.8\n", - " 3.9\n", - " 04-Nov\n", + " 434\n", + " 60.8\n", + " 714\n", + " 58.8\n", + " 2.0\n", + " 06-Feb\n", " \n", " \n", " British or Mixed British\n", - " 105\n", - " 53.6\n", - " 196\n", - " 53.6\n", - " 0.0\n", + " 427\n", + " 59.8\n", + " 714\n", + " 58.8\n", + " 1.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 119\n", - " 65.4\n", - " 182\n", - " 61.5\n", - " 3.9\n", - " 22-Oct\n", + " 413\n", + " 60.2\n", + " 686\n", + " 59.2\n", + " 1.0\n", + " unknown\n", " \n", " \n", " Irish\n", - " 105\n", - " 57.7\n", - " 182\n", - " 53.8\n", - " 3.9\n", - " 04-Nov\n", + " 406\n", + " 63.0\n", + " 644\n", + " 60.9\n", + " 2.1\n", + " 25-Jan\n", " \n", " \n", " Other Black\n", - " 98\n", - " 56.0\n", - " 175\n", - " 56.0\n", - " 0.0\n", + " 427\n", + " 61.6\n", + " 693\n", + " 60.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " Other White\n", - " 98\n", - " 56.0\n", - " 175\n", - " 56.0\n", - " 0.0\n", + " 406\n", + " 61.7\n", + " 658\n", + " 60.6\n", + " 1.1\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 105\n", - " 62.5\n", - " 168\n", - " 58.3\n", - " 4.2\n", - " 23-Oct\n", + " 427\n", + " 61.6\n", + " 693\n", + " 59.6\n", + " 2.0\n", + " 03-Feb\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 105\n", - " 57.7\n", - " 182\n", - " 57.7\n", - " 0.0\n", + " 441\n", + " 60.0\n", + " 735\n", + " 59.0\n", + " 1.0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 294\n", - " 59.2\n", - " 497\n", - " 57.7\n", + " 1162\n", + " 60.8\n", + " 1911\n", + " 59.3\n", " 1.5\n", - " 29-Jan\n", + " 12-Mar\n", " \n", " \n", " White + Asian\n", - " 105\n", - " 55.6\n", - " 189\n", - " 55.6\n", - " 0.0\n", + " 406\n", + " 58.6\n", + " 693\n", + " 57.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " White + Black African\n", - " 140\n", - " 64.5\n", - " 217\n", - " 58.1\n", - " 6.4\n", - " 05-Oct\n", + " 462\n", + " 64.1\n", + " 721\n", + " 62.1\n", + " 2.0\n", + " 25-Jan\n", " \n", " \n", " White + Black Caribbean\n", - " 98\n", - " 58.3\n", - " 168\n", - " 58.3\n", - " 0.0\n", + " 392\n", + " 58.9\n", + " 665\n", + " 57.9\n", + " 1.0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 392\n", - " 57.1\n", - " 686\n", - " 54.1\n", - " 3.0\n", - " 23-Nov\n", - " \n", - " \n", - " 2\n", - " 371\n", - " 55.8\n", - " 665\n", - " 53.7\n", - " 2.1\n", - " 31-Dec\n", - " \n", - " \n", - " 3\n", - " 378\n", - " 59.3\n", - " 637\n", - " 57.1\n", - " 2.2\n", - " 14-Dec\n", - " \n", - " \n", - " 4\n", - " 392\n", - " 60.2\n", - " 651\n", - " 59.1\n", + " 1491\n", + " 60.3\n", + " 2471\n", + " 59.2\n", " 1.1\n", " unknown\n", " \n", " \n", - " 5 Least deprived\n", - " 364\n", - " 57.1\n", - " 637\n", - " 54.9\n", - " 2.2\n", - " 21-Dec\n", + " 2\n", + " 1498\n", + " 60.5\n", + " 2478\n", + " 59.3\n", + " 1.2\n", + " 17-Apr\n", " \n", " \n", - " Unknown\n", - " 105\n", + " 3\n", + " 1491\n", + " 60.9\n", + " 2450\n", " 60.0\n", - " 175\n", - " 56.0\n", - " 4.0\n", - " 30-Oct\n", - " \n", - " \n", - " bmi\n", - " 30+\n", - " 581\n", - " 58.0\n", - " 1001\n", - " 55.9\n", - " 2.1\n", - " 23-Dec\n", - " \n", - " \n", - " under 30\n", - " 1414\n", - " 57.5\n", - " 2457\n", - " 56.1\n", - " 1.4\n", - " 17-Feb\n", - " \n", - " \n", - " chronic_cardiac_disease\n", - " no\n", - " 1981\n", - " 57.8\n", - " 3430\n", - " 55.9\n", - " 1.9\n", - " 04-Jan\n", - " \n", - " \n", - " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " current_copd\n", - " no\n", - " 1981\n", - " 57.9\n", - " 3423\n", - " 56.0\n", - " 1.9\n", - " 04-Jan\n", - " \n", - " \n", - " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", - " 0.0\n", + " 0.9\n", " unknown\n", " \n", " \n", - " dmards\n", - " no\n", - " 1974\n", - " 57.6\n", - " 3430\n", - " 55.9\n", + " 4\n", + " 1484\n", + " 60.6\n", + " 2450\n", + " 58.9\n", " 1.7\n", - " 19-Jan\n", - " \n", - " \n", - " yes\n", - " 21\n", - " 75.0\n", - " 28\n", - " 75.0\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " psychosis_schiz_bipolar\n", - " no\n", - " 1974\n", - " 57.7\n", - " 3423\n", - " 55.8\n", - " 1.9\n", - " 05-Jan\n", - " \n", - " \n", - " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " ssri\n", - " no\n", - " 1974\n", - " 57.8\n", - " 3416\n", - " 55.9\n", - " 1.9\n", - " 04-Jan\n", - " \n", - " \n", - " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", - " 0.0\n", - " unknown\n", + " 25-Feb\n", " \n", " \n", - " ckd\n", - " no\n", - " 1596\n", - " 57.3\n", - " 2786\n", - " 55.5\n", - " 1.8\n", - " 13-Jan\n", + " 5 Least deprived\n", + " 1484\n", + " 60.9\n", + " 2436\n", + " 59.5\n", + " 1.4\n", + " 21-Mar\n", " \n", " \n", - " yes\n", - " 399\n", - " 59.4\n", + " Unknown\n", + " 413\n", + " 61.5\n", " 672\n", - " 58.3\n", + " 60.4\n", " 1.1\n", " unknown\n", " \n", @@ -48009,250 +60134,180 @@ "" ], "text/plain": [ - " vaccinated \\\n", - "category group \n", - "overall overall 1995 \n", - "sex F 1050 \n", - " M 945 \n", - "ethnicity_6_groups Black 350 \n", - " Mixed 315 \n", - " Other 364 \n", - " South Asian 343 \n", - " Unknown 287 \n", - " White 336 \n", - "ethnicity_16_groups African 112 \n", - " Bangladeshi or British Bangladeshi 84 \n", - " Caribbean 105 \n", - " Chinese 98 \n", - " Other 112 \n", - " Other Asian 105 \n", - " British or Mixed British 105 \n", - " Indian or British Indian 119 \n", - " Irish 105 \n", - " Other Black 98 \n", - " Other White 98 \n", - " Other mixed 105 \n", - " Pakistani or British Pakistani 105 \n", - " Unknown 294 \n", - " White + Asian 105 \n", - " White + Black African 140 \n", - " White + Black Caribbean 98 \n", - "imd_categories 1 Most deprived 392 \n", - " 2 371 \n", - " 3 378 \n", - " 4 392 \n", - " 5 Least deprived 364 \n", - " Unknown 105 \n", - "bmi 30+ 581 \n", - " under 30 1414 \n", - "chronic_cardiac_disease no 1981 \n", - " yes 14 \n", - "current_copd no 1981 \n", - " yes 14 \n", - "dmards no 1974 \n", - " yes 21 \n", - "psychosis_schiz_bipolar no 1974 \n", - " yes 21 \n", - "ssri no 1974 \n", - " yes 21 \n", - "ckd no 1596 \n", - " yes 399 \n", + " vaccinated percent \\\n", + "category group \n", + "overall overall 7854 60.6 \n", + "sex F 4102 61.0 \n", + " M 3752 60.2 \n", + "ethnicity_6_groups Black 1344 60.2 \n", + " Mixed 1351 61.3 \n", + " Other 1288 60.5 \n", + " South Asian 1379 61.2 \n", + " Unknown 1176 61.3 \n", + " White 1323 59.4 \n", + "ethnicity_16_groups African 413 59.0 \n", + " Bangladeshi or British Bangladeshi 413 60.2 \n", + " Caribbean 406 61.7 \n", + " Chinese 399 57.0 \n", + " Other 434 63.9 \n", + " Other Asian 434 60.8 \n", + " British or Mixed British 427 59.8 \n", + " Indian or British Indian 413 60.2 \n", + " Irish 406 63.0 \n", + " Other Black 427 61.6 \n", + " Other White 406 61.7 \n", + " Other mixed 427 61.6 \n", + " Pakistani or British Pakistani 441 60.0 \n", + " Unknown 1162 60.8 \n", + " White + Asian 406 58.6 \n", + " White + Black African 462 64.1 \n", + " White + Black Caribbean 392 58.9 \n", + "imd_categories 1 Most deprived 1491 60.3 \n", + " 2 1498 60.5 \n", + " 3 1491 60.9 \n", + " 4 1484 60.6 \n", + " 5 Least deprived 1484 60.9 \n", + " Unknown 413 61.5 \n", "\n", - " percent total \\\n", - "category group \n", - "overall overall 57.7 3458 \n", - "sex F 59.3 1771 \n", - " M 56.0 1687 \n", - "ethnicity_6_groups Black 58.8 595 \n", - " Mixed 53.6 588 \n", - " Other 59.1 616 \n", - " South Asian 61.3 560 \n", - " Unknown 54.7 525 \n", - " White 58.5 574 \n", - "ethnicity_16_groups African 55.2 203 \n", - " Bangladeshi or British Bangladeshi 50.0 168 \n", - " Caribbean 55.6 189 \n", - " Chinese 53.8 182 \n", - " Other 59.3 189 \n", - " Other Asian 57.7 182 \n", - " British or Mixed British 53.6 196 \n", - " Indian or British Indian 65.4 182 \n", - " Irish 57.7 182 \n", - " Other Black 56.0 175 \n", - " Other White 56.0 175 \n", - " Other mixed 62.5 168 \n", - " Pakistani or British Pakistani 57.7 182 \n", - " Unknown 59.2 497 \n", - " White + Asian 55.6 189 \n", - " White + Black African 64.5 217 \n", - " White + Black Caribbean 58.3 168 \n", - "imd_categories 1 Most deprived 57.1 686 \n", - " 2 55.8 665 \n", - " 3 59.3 637 \n", - " 4 60.2 651 \n", - " 5 Least deprived 57.1 637 \n", - " Unknown 60.0 175 \n", - "bmi 30+ 58.0 1001 \n", - " under 30 57.5 2457 \n", - "chronic_cardiac_disease no 57.8 3430 \n", - " yes 50.0 28 \n", - "current_copd no 57.9 3423 \n", - " yes 40.0 35 \n", - "dmards no 57.6 3430 \n", - " yes 75.0 28 \n", - "psychosis_schiz_bipolar no 57.7 3423 \n", - " yes 60.0 35 \n", - "ssri no 57.8 3416 \n", - " yes 60.0 35 \n", - "ckd no 57.3 2786 \n", - " yes 59.4 672 \n", + " total \\\n", + "category group \n", + "overall overall 12957 \n", + "sex F 6727 \n", + " M 6230 \n", + "ethnicity_6_groups Black 2233 \n", + " Mixed 2205 \n", + " Other 2128 \n", + " South Asian 2254 \n", + " Unknown 1918 \n", + " White 2226 \n", + "ethnicity_16_groups African 700 \n", + " Bangladeshi or British Bangladeshi 686 \n", + " Caribbean 658 \n", + " Chinese 700 \n", + " Other 679 \n", + " Other Asian 714 \n", + " British or Mixed British 714 \n", + " Indian or British Indian 686 \n", + " Irish 644 \n", + " Other Black 693 \n", + " Other White 658 \n", + " Other mixed 693 \n", + " Pakistani or British Pakistani 735 \n", + " Unknown 1911 \n", + " White + Asian 693 \n", + " White + Black African 721 \n", + " White + Black Caribbean 665 \n", + "imd_categories 1 Most deprived 2471 \n", + " 2 2478 \n", + " 3 2450 \n", + " 4 2450 \n", + " 5 Least deprived 2436 \n", + " Unknown 672 \n", "\n", - " vaccinated 7d previous (percent) \\\n", - "category group \n", - "overall overall 55.9 \n", - "sex F 57.3 \n", - " M 54.4 \n", - "ethnicity_6_groups Black 56.5 \n", - " Mixed 51.2 \n", - " Other 58.0 \n", - " South Asian 58.8 \n", - " Unknown 53.3 \n", - " White 57.3 \n", - "ethnicity_16_groups African 51.7 \n", - " Bangladeshi or British Bangladeshi 50.0 \n", - " Caribbean 55.6 \n", - " Chinese 53.8 \n", - " Other 55.6 \n", - " Other Asian 53.8 \n", - " British or Mixed British 53.6 \n", - " Indian or British Indian 61.5 \n", - " Irish 53.8 \n", - " Other Black 56.0 \n", - " Other White 56.0 \n", - " Other mixed 58.3 \n", - " Pakistani or British Pakistani 57.7 \n", - " Unknown 57.7 \n", - " White + Asian 55.6 \n", - " White + Black African 58.1 \n", - " White + Black Caribbean 58.3 \n", - "imd_categories 1 Most deprived 54.1 \n", - " 2 53.7 \n", - " 3 57.1 \n", - " 4 59.1 \n", - " 5 Least deprived 54.9 \n", - " Unknown 56.0 \n", - "bmi 30+ 55.9 \n", - " under 30 56.1 \n", - "chronic_cardiac_disease no 55.9 \n", - " yes 50.0 \n", - "current_copd no 56.0 \n", - " yes 40.0 \n", - "dmards no 55.9 \n", - " yes 75.0 \n", - "psychosis_schiz_bipolar no 55.8 \n", - " yes 60.0 \n", - "ssri no 55.9 \n", - " yes 60.0 \n", - "ckd no 55.5 \n", - " yes 58.3 \n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.4 \n", + "sex F 59.8 \n", + " M 58.9 \n", + "ethnicity_6_groups Black 58.9 \n", + " Mixed 60.3 \n", + " Other 59.2 \n", + " South Asian 59.6 \n", + " Unknown 59.9 \n", + " White 58.2 \n", + "ethnicity_16_groups African 58.0 \n", + " Bangladeshi or British Bangladeshi 59.2 \n", + " Caribbean 60.6 \n", + " Chinese 56.0 \n", + " Other 62.9 \n", + " Other Asian 58.8 \n", + " British or Mixed British 58.8 \n", + " Indian or British Indian 59.2 \n", + " Irish 60.9 \n", + " Other Black 60.6 \n", + " Other White 60.6 \n", + " Other mixed 59.6 \n", + " Pakistani or British Pakistani 59.0 \n", + " Unknown 59.3 \n", + " White + Asian 57.6 \n", + " White + Black African 62.1 \n", + " White + Black Caribbean 57.9 \n", + "imd_categories 1 Most deprived 59.2 \n", + " 2 59.3 \n", + " 3 60.0 \n", + " 4 58.9 \n", + " 5 Least deprived 59.5 \n", + " Unknown 60.4 \n", "\n", - " Uptake over last 7d (percent) \\\n", - "category group \n", - "overall overall 1.8 \n", - "sex F 2.0 \n", - " M 1.6 \n", - "ethnicity_6_groups Black 2.3 \n", - " Mixed 2.4 \n", - " Other 1.1 \n", - " South Asian 2.5 \n", - " Unknown 1.4 \n", - " White 1.2 \n", - "ethnicity_16_groups African 3.5 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", - " Chinese 0.0 \n", - " Other 3.7 \n", - " Other Asian 3.9 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 3.9 \n", - " Irish 3.9 \n", - " Other Black 0.0 \n", - " Other White 0.0 \n", - " Other mixed 4.2 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 1.5 \n", - " White + Asian 0.0 \n", - " White + Black African 6.4 \n", - " White + Black Caribbean 0.0 \n", - "imd_categories 1 Most deprived 3.0 \n", - " 2 2.1 \n", - " 3 2.2 \n", - " 4 1.1 \n", - " 5 Least deprived 2.2 \n", - " Unknown 4.0 \n", - "bmi 30+ 2.1 \n", - " under 30 1.4 \n", - "chronic_cardiac_disease no 1.9 \n", - " yes 0.0 \n", - "current_copd no 1.9 \n", - " yes 0.0 \n", - "dmards no 1.7 \n", - " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.9 \n", - " yes 0.0 \n", - "ssri no 1.9 \n", - " yes 0.0 \n", - "ckd no 1.8 \n", - " yes 1.1 \n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.2 \n", + "sex F 1.2 \n", + " M 1.3 \n", + "ethnicity_6_groups Black 1.3 \n", + " Mixed 1.0 \n", + " Other 1.3 \n", + " South Asian 1.6 \n", + " Unknown 1.4 \n", + " White 1.2 \n", + "ethnicity_16_groups African 1.0 \n", + " Bangladeshi or British Bangladeshi 1.0 \n", + " Caribbean 1.1 \n", + " Chinese 1.0 \n", + " Other 1.0 \n", + " Other Asian 2.0 \n", + " British or Mixed British 1.0 \n", + " Indian or British Indian 1.0 \n", + " Irish 2.1 \n", + " Other Black 1.0 \n", + " Other White 1.1 \n", + " Other mixed 2.0 \n", + " Pakistani or British Pakistani 1.0 \n", + " Unknown 1.5 \n", + " White + Asian 1.0 \n", + " White + Black African 2.0 \n", + " White + Black Caribbean 1.0 \n", + "imd_categories 1 Most deprived 1.1 \n", + " 2 1.2 \n", + " 3 0.9 \n", + " 4 1.7 \n", + " 5 Least deprived 1.4 \n", + " Unknown 1.1 \n", "\n", - " Date projected to reach 90% \n", - "category group \n", - "overall overall 11-Jan \n", - "sex F 24-Dec \n", - " M 03-Feb \n", - "ethnicity_6_groups Black 11-Dec \n", - " Mixed 23-Dec \n", - " Other unknown \n", - " South Asian 27-Nov \n", - " Unknown unknown \n", - " White unknown \n", - "ethnicity_16_groups African 16-Nov \n", - " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean unknown \n", - " Chinese unknown \n", - " Other 05-Nov \n", - " Other Asian 04-Nov \n", - " British or Mixed British unknown \n", - " Indian or British Indian 22-Oct \n", - " Irish 04-Nov \n", - " Other Black unknown \n", - " Other White unknown \n", - " Other mixed 23-Oct \n", - " Pakistani or British Pakistani unknown \n", - " Unknown 29-Jan \n", - " White + Asian unknown \n", - " White + Black African 05-Oct \n", - " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived 23-Nov \n", - " 2 31-Dec \n", - " 3 14-Dec \n", - " 4 unknown \n", - " 5 Least deprived 21-Dec \n", - " Unknown 30-Oct \n", - "bmi 30+ 23-Dec \n", - " under 30 17-Feb \n", - "chronic_cardiac_disease no 04-Jan \n", - " yes unknown \n", - "current_copd no 04-Jan \n", - " yes unknown \n", - "dmards no 19-Jan \n", - " yes unknown \n", - "psychosis_schiz_bipolar no 05-Jan \n", - " yes unknown \n", - "ssri no 04-Jan \n", - " yes unknown \n", - "ckd no 13-Jan \n", - " yes unknown " + " Date projected to reach 90% \n", + "category group \n", + "overall overall 16-Apr \n", + "sex F 14-Apr \n", + " M 05-Apr \n", + "ethnicity_6_groups Black 05-Apr \n", + " Mixed unknown \n", + " Other 03-Apr \n", + " South Asian 02-Mar \n", + " Unknown 19-Mar \n", + " White unknown \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi unknown \n", + " Caribbean unknown \n", + " Chinese unknown \n", + " Other unknown \n", + " Other Asian 06-Feb \n", + " British or Mixed British unknown \n", + " Indian or British Indian unknown \n", + " Irish 25-Jan \n", + " Other Black unknown \n", + " Other White unknown \n", + " Other mixed 03-Feb \n", + " Pakistani or British Pakistani unknown \n", + " Unknown 12-Mar \n", + " White + Asian unknown \n", + " White + Black African 25-Jan \n", + " White + Black Caribbean unknown \n", + "imd_categories 1 Most deprived unknown \n", + " 2 17-Apr \n", + " 3 unknown \n", + " 4 25-Feb \n", + " 5 Least deprived 21-Mar \n", + " Unknown unknown " ] }, "metadata": {}, @@ -48281,7 +60336,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout (second dose 14weeks ago) among **40-49** population up to 2021-09-08" + "## COVID vaccination rollout (second dose 14w ago) among **18-29** population up to 2021-10-27" ], "text/plain": [ "" @@ -48347,678 +60402,475 @@ " \n", " overall\n", " overall\n", - " 3584\n", - " 58.4\n", - " 6139\n", - " 56.4\n", - " 2.0\n", - " 27-Dec\n", + " 9100\n", + " 60.8\n", + " 14966\n", + " 59.3\n", + " 1.5\n", + " 12-Mar\n", " \n", " \n", " sex\n", " F\n", - " 1820\n", - " 57.5\n", - " 3164\n", - " 55.3\n", - " 2.2\n", - " 20-Dec\n", + " 4655\n", + " 60.6\n", + " 7686\n", + " 59.1\n", + " 1.5\n", + " 13-Mar\n", " \n", " \n", " M\n", - " 1764\n", - " 59.3\n", - " 2975\n", - " 57.6\n", - " 1.7\n", - " 12-Jan\n", + " 4445\n", + " 61.0\n", + " 7287\n", + " 59.4\n", + " 1.6\n", + " 02-Mar\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 574\n", - " 56.9\n", - " 1008\n", - " 54.9\n", - " 2.0\n", - " 01-Jan\n", + " 1589\n", + " 62.2\n", + " 2555\n", + " 60.8\n", + " 1.4\n", + " 15-Mar\n", " \n", " \n", - " Mixed\n", - " 637\n", - " 60.3\n", - " 1057\n", - " 58.3\n", - " 2.0\n", - " 20-Dec\n", + " Mixed\n", + " 1561\n", + " 60.6\n", + " 2576\n", + " 59.0\n", + " 1.6\n", + " 04-Mar\n", " \n", " \n", " Other\n", - " 602\n", - " 58.9\n", - " 1022\n", - " 57.5\n", - " 1.4\n", - " 10-Feb\n", + " 1554\n", + " 60.7\n", + " 2562\n", + " 59.0\n", + " 1.7\n", + " 24-Feb\n", " \n", " \n", " South Asian\n", - " 616\n", - " 58.3\n", - " 1057\n", - " 56.3\n", - " 2.0\n", - " 27-Dec\n", + " 1533\n", + " 61.0\n", + " 2513\n", + " 59.6\n", + " 1.4\n", + " 21-Mar\n", " \n", " \n", " Unknown\n", - " 511\n", - " 56.6\n", - " 903\n", - " 53.5\n", - " 3.1\n", - " 22-Nov\n", + " 1365\n", + " 61.1\n", + " 2233\n", + " 59.6\n", + " 1.5\n", + " 10-Mar\n", " \n", " \n", " White\n", - " 644\n", - " 59.0\n", - " 1092\n", - " 57.7\n", - " 1.3\n", - " 21-Feb\n", + " 1498\n", + " 59.4\n", + " 2520\n", + " 57.8\n", + " 1.6\n", + " 09-Mar\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 182\n", - " 56.5\n", - " 322\n", - " 54.3\n", - " 2.2\n", - " 23-Dec\n", + " 469\n", + " 59.8\n", + " 784\n", + " 58.9\n", + " 0.9\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 196\n", - " 63.6\n", - " 308\n", - " 61.4\n", - " 2.2\n", - " 01-Dec\n", + " 476\n", + " 59.1\n", + " 805\n", + " 57.4\n", + " 1.7\n", + " 03-Mar\n", " \n", " \n", " Caribbean\n", - " 182\n", - " 56.5\n", - " 322\n", - " 54.3\n", - " 2.2\n", - " 23-Dec\n", + " 455\n", + " 58.0\n", + " 784\n", + " 56.2\n", + " 1.8\n", + " 28-Feb\n", " \n", " \n", " Chinese\n", - " 196\n", - " 57.1\n", - " 343\n", - " 55.1\n", - " 2.0\n", - " 01-Jan\n", + " 511\n", + " 62.9\n", + " 812\n", + " 61.2\n", + " 1.7\n", + " 15-Feb\n", " \n", " \n", " Other\n", - " 203\n", - " 58.0\n", - " 350\n", - " 56.0\n", - " 2.0\n", - " 29-Dec\n", + " 476\n", + " 59.6\n", + " 798\n", + " 57.9\n", + " 1.7\n", + " 01-Mar\n", " \n", " \n", " Other Asian\n", - " 196\n", - " 59.6\n", - " 329\n", - " 57.4\n", - " 2.2\n", - " 13-Dec\n", + " 462\n", + " 58.9\n", + " 784\n", + " 57.1\n", + " 1.8\n", + " 24-Feb\n", " \n", " \n", " British or Mixed British\n", - " 182\n", - " 53.1\n", - " 343\n", - " 53.1\n", - " 0.0\n", + " 462\n", + " 60.6\n", + " 763\n", + " 59.6\n", + " 1.0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 161\n", - " 54.8\n", - " 294\n", - " 52.4\n", - " 2.4\n", - " 19-Dec\n", + " 532\n", + " 64.4\n", + " 826\n", + " 62.7\n", + " 1.7\n", + " 09-Feb\n", " \n", " \n", " Irish\n", - " 175\n", - " 51.0\n", - " 343\n", - " 46.9\n", - " 4.1\n", - " 13-Nov\n", + " 476\n", + " 61.8\n", + " 770\n", + " 59.1\n", + " 2.7\n", + " 08-Jan\n", " \n", " \n", " Other Black\n", - " 210\n", - " 63.8\n", - " 329\n", - " 63.8\n", - " 0.0\n", - " unknown\n", + " 490\n", + " 61.4\n", + " 798\n", + " 59.6\n", + " 1.8\n", + " 15-Feb\n", " \n", " \n", " Other White\n", - " 203\n", - " 64.4\n", - " 315\n", - " 62.2\n", - " 2.2\n", - " 28-Nov\n", + " 490\n", + " 61.9\n", + " 791\n", + " 60.2\n", + " 1.7\n", + " 19-Feb\n", " \n", " \n", " Other mixed\n", - " 182\n", - " 59.1\n", - " 308\n", - " 56.8\n", - " 2.3\n", - " 11-Dec\n", + " 497\n", + " 62.8\n", + " 791\n", + " 61.9\n", + " 0.9\n", + " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 182\n", - " 56.5\n", - " 322\n", - " 56.5\n", - " 0.0\n", - " unknown\n", + " 476\n", + " 62.4\n", + " 763\n", + " 60.6\n", + " 1.8\n", + " 11-Feb\n", " \n", " \n", " Unknown\n", - " 539\n", - " 57.5\n", - " 938\n", - " 55.2\n", - " 2.3\n", - " 15-Dec\n", + " 1386\n", + " 60.9\n", + " 2275\n", + " 59.7\n", + " 1.2\n", + " 14-Apr\n", " \n", " \n", " White + Asian\n", - " 182\n", - " 56.5\n", - " 322\n", - " 54.3\n", - " 2.2\n", - " 23-Dec\n", + " 483\n", + " 58.5\n", + " 826\n", + " 56.8\n", + " 1.7\n", + " 05-Mar\n", " \n", " \n", " White + Black African\n", - " 196\n", + " 490\n", " 60.9\n", - " 322\n", - " 58.7\n", - " 2.2\n", - " 09-Dec\n", + " 805\n", + " 59.1\n", + " 1.8\n", + " 17-Feb\n", " \n", " \n", " White + Black Caribbean\n", - " 210\n", - " 63.8\n", - " 329\n", - " 61.7\n", - " 2.1\n", - " 04-Dec\n", + " 469\n", + " 59.3\n", + " 791\n", + " 58.4\n", + " 0.9\n", + " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 644\n", - " 55.1\n", - " 1169\n", - " 53.3\n", - " 1.8\n", - " 21-Jan\n", + " 1785\n", + " 60.7\n", + " 2940\n", + " 59.3\n", + " 1.4\n", + " 22-Mar\n", " \n", " \n", " 2\n", - " 672\n", - " 58.5\n", - " 1148\n", - " 56.1\n", - " 2.4\n", - " 08-Dec\n", + " 1736\n", + " 61.2\n", + " 2835\n", + " 59.5\n", + " 1.7\n", + " 22-Feb\n", " \n", " \n", " 3\n", - " 700\n", - " 60.2\n", - " 1162\n", - " 59.0\n", + " 1708\n", + " 60.1\n", + " 2842\n", + " 58.9\n", " 1.2\n", - " 28-Feb\n", + " 19-Apr\n", " \n", " \n", " 4\n", - " 672\n", - " 58.2\n", - " 1155\n", - " 56.4\n", - " 1.8\n", - " 09-Jan\n", - " \n", - " \n", - " 5 Least deprived\n", - " 707\n", - " 59.1\n", - " 1197\n", - " 56.1\n", - " 3.0\n", - " 19-Nov\n", - " \n", - " \n", - " Unknown\n", - " 189\n", - " 62.8\n", - " 301\n", - " 60.5\n", - " 2.3\n", - " 29-Nov\n", - " \n", - " \n", - " bmi\n", - " 30+\n", - " 1092\n", - " 57.6\n", - " 1897\n", - " 56.1\n", + " 1764\n", + " 61.8\n", + " 2856\n", + " 60.3\n", " 1.5\n", - " 06-Feb\n", - " \n", - " \n", - " under 30\n", - " 2492\n", - " 58.7\n", - " 4242\n", - " 56.6\n", - " 2.1\n", - " 21-Dec\n", - " \n", - " \n", - " chronic_cardiac_disease\n", - " no\n", - " 3549\n", - " 58.4\n", - " 6076\n", - " 56.5\n", - " 1.9\n", - " 02-Jan\n", - " \n", - " \n", - " yes\n", - " 35\n", - " 55.6\n", - " 63\n", - " 55.6\n", - " 0.0\n", - " unknown\n", - " \n", - " \n", - " current_copd\n", - " no\n", - " 3549\n", - " 58.4\n", - " 6076\n", - " 56.5\n", - " 1.9\n", - " 02-Jan\n", - " \n", - " \n", - " yes\n", - " 35\n", - " 62.5\n", - " 56\n", - " 50.0\n", - " 12.5\n", - " 23-Sep\n", - " \n", - " \n", - " dmards\n", - " no\n", - " 3549\n", - " 58.5\n", - " 6069\n", - " 56.5\n", - " 2.0\n", - " 27-Dec\n", - " \n", - " \n", - " yes\n", - " 35\n", - " 50.0\n", - " 70\n", - " 50.0\n", - " 0.0\n", - " unknown\n", + " 07-Mar\n", " \n", " \n", - " psychosis_schiz_bipolar\n", - " no\n", - " 3549\n", + " 5 Least deprived\n", + " 1659\n", + " 59.7\n", + " 2779\n", " 58.4\n", - " 6076\n", - " 56.5\n", - " 1.9\n", - " 02-Jan\n", - " \n", - " \n", - " yes\n", - " 35\n", - " 62.5\n", - " 56\n", - " 62.5\n", - " 0.0\n", - " unknown\n", + " 1.3\n", + " 08-Apr\n", " \n", " \n", - " ssri\n", - " no\n", - " 3563\n", - " 58.5\n", - " 6090\n", - " 56.6\n", + " Unknown\n", + " 448\n", + " 62.1\n", + " 721\n", + " 60.2\n", " 1.9\n", - " 02-Jan\n", - " \n", - " \n", - " yes\n", - " 21\n", - " 42.9\n", - " 49\n", - " 28.6\n", - " 14.3\n", - " 01-Oct\n", - " \n", - " \n", - " ckd\n", - " no\n", - " 2842\n", - " 58.2\n", - " 4879\n", - " 56.2\n", - " 2.0\n", - " 28-Dec\n", - " \n", - " \n", - " yes\n", - " 742\n", - " 58.9\n", - " 1260\n", - " 57.2\n", - " 1.7\n", - " 14-Jan\n", + " 06-Feb\n", " \n", " \n", "\n", "" ], "text/plain": [ - " vaccinated \\\n", - "category group \n", - "overall overall 3584 \n", - "sex F 1820 \n", - " M 1764 \n", - "ethnicity_6_groups Black 574 \n", - " Mixed 637 \n", - " Other 602 \n", - " South Asian 616 \n", - " Unknown 511 \n", - " White 644 \n", - "ethnicity_16_groups African 182 \n", - " Bangladeshi or British Bangladeshi 196 \n", - " Caribbean 182 \n", - " Chinese 196 \n", - " Other 203 \n", - " Other Asian 196 \n", - " British or Mixed British 182 \n", - " Indian or British Indian 161 \n", - " Irish 175 \n", - " Other Black 210 \n", - " Other White 203 \n", - " Other mixed 182 \n", - " Pakistani or British Pakistani 182 \n", - " Unknown 539 \n", - " White + Asian 182 \n", - " White + Black African 196 \n", - " White + Black Caribbean 210 \n", - "imd_categories 1 Most deprived 644 \n", - " 2 672 \n", - " 3 700 \n", - " 4 672 \n", - " 5 Least deprived 707 \n", - " Unknown 189 \n", - "bmi 30+ 1092 \n", - " under 30 2492 \n", - "chronic_cardiac_disease no 3549 \n", - " yes 35 \n", - "current_copd no 3549 \n", - " yes 35 \n", - "dmards no 3549 \n", - " yes 35 \n", - "psychosis_schiz_bipolar no 3549 \n", - " yes 35 \n", - "ssri no 3563 \n", - " yes 21 \n", - "ckd no 2842 \n", - " yes 742 \n", + " vaccinated percent \\\n", + "category group \n", + "overall overall 9100 60.8 \n", + "sex F 4655 60.6 \n", + " M 4445 61.0 \n", + "ethnicity_6_groups Black 1589 62.2 \n", + " Mixed 1561 60.6 \n", + " Other 1554 60.7 \n", + " South Asian 1533 61.0 \n", + " Unknown 1365 61.1 \n", + " White 1498 59.4 \n", + "ethnicity_16_groups African 469 59.8 \n", + " Bangladeshi or British Bangladeshi 476 59.1 \n", + " Caribbean 455 58.0 \n", + " Chinese 511 62.9 \n", + " Other 476 59.6 \n", + " Other Asian 462 58.9 \n", + " British or Mixed British 462 60.6 \n", + " Indian or British Indian 532 64.4 \n", + " Irish 476 61.8 \n", + " Other Black 490 61.4 \n", + " Other White 490 61.9 \n", + " Other mixed 497 62.8 \n", + " Pakistani or British Pakistani 476 62.4 \n", + " Unknown 1386 60.9 \n", + " White + Asian 483 58.5 \n", + " White + Black African 490 60.9 \n", + " White + Black Caribbean 469 59.3 \n", + "imd_categories 1 Most deprived 1785 60.7 \n", + " 2 1736 61.2 \n", + " 3 1708 60.1 \n", + " 4 1764 61.8 \n", + " 5 Least deprived 1659 59.7 \n", + " Unknown 448 62.1 \n", "\n", - " percent total \\\n", - "category group \n", - "overall overall 58.4 6139 \n", - "sex F 57.5 3164 \n", - " M 59.3 2975 \n", - "ethnicity_6_groups Black 56.9 1008 \n", - " Mixed 60.3 1057 \n", - " Other 58.9 1022 \n", - " South Asian 58.3 1057 \n", - " Unknown 56.6 903 \n", - " White 59.0 1092 \n", - "ethnicity_16_groups African 56.5 322 \n", - " Bangladeshi or British Bangladeshi 63.6 308 \n", - " Caribbean 56.5 322 \n", - " Chinese 57.1 343 \n", - " Other 58.0 350 \n", - " Other Asian 59.6 329 \n", - " British or Mixed British 53.1 343 \n", - " Indian or British Indian 54.8 294 \n", - " Irish 51.0 343 \n", - " Other Black 63.8 329 \n", - " Other White 64.4 315 \n", - " Other mixed 59.1 308 \n", - " Pakistani or British Pakistani 56.5 322 \n", - " Unknown 57.5 938 \n", - " White + Asian 56.5 322 \n", - " White + Black African 60.9 322 \n", - " White + Black Caribbean 63.8 329 \n", - "imd_categories 1 Most deprived 55.1 1169 \n", - " 2 58.5 1148 \n", - " 3 60.2 1162 \n", - " 4 58.2 1155 \n", - " 5 Least deprived 59.1 1197 \n", - " Unknown 62.8 301 \n", - "bmi 30+ 57.6 1897 \n", - " under 30 58.7 4242 \n", - "chronic_cardiac_disease no 58.4 6076 \n", - " yes 55.6 63 \n", - "current_copd no 58.4 6076 \n", - " yes 62.5 56 \n", - "dmards no 58.5 6069 \n", - " yes 50.0 70 \n", - "psychosis_schiz_bipolar no 58.4 6076 \n", - " yes 62.5 56 \n", - "ssri no 58.5 6090 \n", - " yes 42.9 49 \n", - "ckd no 58.2 4879 \n", - " yes 58.9 1260 \n", + " total \\\n", + "category group \n", + "overall overall 14966 \n", + "sex F 7686 \n", + " M 7287 \n", + "ethnicity_6_groups Black 2555 \n", + " Mixed 2576 \n", + " Other 2562 \n", + " South Asian 2513 \n", + " Unknown 2233 \n", + " White 2520 \n", + "ethnicity_16_groups African 784 \n", + " Bangladeshi or British Bangladeshi 805 \n", + " Caribbean 784 \n", + " Chinese 812 \n", + " Other 798 \n", + " Other Asian 784 \n", + " British or Mixed British 763 \n", + " Indian or British Indian 826 \n", + " Irish 770 \n", + " Other Black 798 \n", + " Other White 791 \n", + " Other mixed 791 \n", + " Pakistani or British Pakistani 763 \n", + " Unknown 2275 \n", + " White + Asian 826 \n", + " White + Black African 805 \n", + " White + Black Caribbean 791 \n", + "imd_categories 1 Most deprived 2940 \n", + " 2 2835 \n", + " 3 2842 \n", + " 4 2856 \n", + " 5 Least deprived 2779 \n", + " Unknown 721 \n", "\n", - " vaccinated 7d previous (percent) \\\n", - "category group \n", - "overall overall 56.4 \n", - "sex F 55.3 \n", - " M 57.6 \n", - "ethnicity_6_groups Black 54.9 \n", - " Mixed 58.3 \n", - " Other 57.5 \n", - " South Asian 56.3 \n", - " Unknown 53.5 \n", - " White 57.7 \n", - "ethnicity_16_groups African 54.3 \n", - " Bangladeshi or British Bangladeshi 61.4 \n", - " Caribbean 54.3 \n", - " Chinese 55.1 \n", - " Other 56.0 \n", - " Other Asian 57.4 \n", - " British or Mixed British 53.1 \n", - " Indian or British Indian 52.4 \n", - " Irish 46.9 \n", - " Other Black 63.8 \n", - " Other White 62.2 \n", - " Other mixed 56.8 \n", - " Pakistani or British Pakistani 56.5 \n", - " Unknown 55.2 \n", - " White + Asian 54.3 \n", - " White + Black African 58.7 \n", - " White + Black Caribbean 61.7 \n", - "imd_categories 1 Most deprived 53.3 \n", - " 2 56.1 \n", - " 3 59.0 \n", - " 4 56.4 \n", - " 5 Least deprived 56.1 \n", - " Unknown 60.5 \n", - "bmi 30+ 56.1 \n", - " under 30 56.6 \n", - "chronic_cardiac_disease no 56.5 \n", - " yes 55.6 \n", - "current_copd no 56.5 \n", - " yes 50.0 \n", - "dmards no 56.5 \n", - " yes 50.0 \n", - "psychosis_schiz_bipolar no 56.5 \n", - " yes 62.5 \n", - "ssri no 56.6 \n", - " yes 28.6 \n", - "ckd no 56.2 \n", - " yes 57.2 \n", + " vaccinated 7d previous (percent) \\\n", + "category group \n", + "overall overall 59.3 \n", + "sex F 59.1 \n", + " M 59.4 \n", + "ethnicity_6_groups Black 60.8 \n", + " Mixed 59.0 \n", + " Other 59.0 \n", + " South Asian 59.6 \n", + " Unknown 59.6 \n", + " White 57.8 \n", + "ethnicity_16_groups African 58.9 \n", + " Bangladeshi or British Bangladeshi 57.4 \n", + " Caribbean 56.2 \n", + " Chinese 61.2 \n", + " Other 57.9 \n", + " Other Asian 57.1 \n", + " British or Mixed British 59.6 \n", + " Indian or British Indian 62.7 \n", + " Irish 59.1 \n", + " Other Black 59.6 \n", + " Other White 60.2 \n", + " Other mixed 61.9 \n", + " Pakistani or British Pakistani 60.6 \n", + " Unknown 59.7 \n", + " White + Asian 56.8 \n", + " White + Black African 59.1 \n", + " White + Black Caribbean 58.4 \n", + "imd_categories 1 Most deprived 59.3 \n", + " 2 59.5 \n", + " 3 58.9 \n", + " 4 60.3 \n", + " 5 Least deprived 58.4 \n", + " Unknown 60.2 \n", "\n", - " Uptake over last 7d (percent) \\\n", - "category group \n", - "overall overall 2.0 \n", - "sex F 2.2 \n", - " M 1.7 \n", - "ethnicity_6_groups Black 2.0 \n", - " Mixed 2.0 \n", - " Other 1.4 \n", - " South Asian 2.0 \n", - " Unknown 3.1 \n", - " White 1.3 \n", - "ethnicity_16_groups African 2.2 \n", - " Bangladeshi or British Bangladeshi 2.2 \n", - " Caribbean 2.2 \n", - " Chinese 2.0 \n", - " Other 2.0 \n", - " Other Asian 2.2 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 2.4 \n", - " Irish 4.1 \n", - " Other Black 0.0 \n", - " Other White 2.2 \n", - " Other mixed 2.3 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 2.3 \n", - " White + Asian 2.2 \n", - " White + Black African 2.2 \n", - " White + Black Caribbean 2.1 \n", - "imd_categories 1 Most deprived 1.8 \n", - " 2 2.4 \n", - " 3 1.2 \n", - " 4 1.8 \n", - " 5 Least deprived 3.0 \n", - " Unknown 2.3 \n", - "bmi 30+ 1.5 \n", - " under 30 2.1 \n", - "chronic_cardiac_disease no 1.9 \n", - " yes 0.0 \n", - "current_copd no 1.9 \n", - " yes 12.5 \n", - "dmards no 2.0 \n", - " yes 0.0 \n", - "psychosis_schiz_bipolar no 1.9 \n", - " yes 0.0 \n", - "ssri no 1.9 \n", - " yes 14.3 \n", - "ckd no 2.0 \n", - " yes 1.7 \n", + " Uptake over last 7d (percent) \\\n", + "category group \n", + "overall overall 1.5 \n", + "sex F 1.5 \n", + " M 1.6 \n", + "ethnicity_6_groups Black 1.4 \n", + " Mixed 1.6 \n", + " Other 1.7 \n", + " South Asian 1.4 \n", + " Unknown 1.5 \n", + " White 1.6 \n", + "ethnicity_16_groups African 0.9 \n", + " Bangladeshi or British Bangladeshi 1.7 \n", + " Caribbean 1.8 \n", + " Chinese 1.7 \n", + " Other 1.7 \n", + " Other Asian 1.8 \n", + " British or Mixed British 1.0 \n", + " Indian or British Indian 1.7 \n", + " Irish 2.7 \n", + " Other Black 1.8 \n", + " Other White 1.7 \n", + " Other mixed 0.9 \n", + " Pakistani or British Pakistani 1.8 \n", + " Unknown 1.2 \n", + " White + Asian 1.7 \n", + " White + Black African 1.8 \n", + " White + Black Caribbean 0.9 \n", + "imd_categories 1 Most deprived 1.4 \n", + " 2 1.7 \n", + " 3 1.2 \n", + " 4 1.5 \n", + " 5 Least deprived 1.3 \n", + " Unknown 1.9 \n", "\n", - " Date projected to reach 90% \n", - "category group \n", - "overall overall 27-Dec \n", - "sex F 20-Dec \n", - " M 12-Jan \n", - "ethnicity_6_groups Black 01-Jan \n", - " Mixed 20-Dec \n", - " Other 10-Feb \n", - " South Asian 27-Dec \n", - " Unknown 22-Nov \n", - " White 21-Feb \n", - "ethnicity_16_groups African 23-Dec \n", - " Bangladeshi or British Bangladeshi 01-Dec \n", - " Caribbean 23-Dec \n", - " Chinese 01-Jan \n", - " Other 29-Dec \n", - " Other Asian 13-Dec \n", - " British or Mixed British unknown \n", - " Indian or British Indian 19-Dec \n", - " Irish 13-Nov \n", - " Other Black unknown \n", - " Other White 28-Nov \n", - " Other mixed 11-Dec \n", - " Pakistani or British Pakistani unknown \n", - " Unknown 15-Dec \n", - " White + Asian 23-Dec \n", - " White + Black African 09-Dec \n", - " White + Black Caribbean 04-Dec \n", - "imd_categories 1 Most deprived 21-Jan \n", - " 2 08-Dec \n", - " 3 28-Feb \n", - " 4 09-Jan \n", - " 5 Least deprived 19-Nov \n", - " Unknown 29-Nov \n", - "bmi 30+ 06-Feb \n", - " under 30 21-Dec \n", - "chronic_cardiac_disease no 02-Jan \n", - " yes unknown \n", - "current_copd no 02-Jan \n", - " yes 23-Sep \n", - "dmards no 27-Dec \n", - " yes unknown \n", - "psychosis_schiz_bipolar no 02-Jan \n", - " yes unknown \n", - "ssri no 02-Jan \n", - " yes 01-Oct \n", - "ckd no 28-Dec \n", - " yes 14-Jan " + " Date projected to reach 90% \n", + "category group \n", + "overall overall 12-Mar \n", + "sex F 13-Mar \n", + " M 02-Mar \n", + "ethnicity_6_groups Black 15-Mar \n", + " Mixed 04-Mar \n", + " Other 24-Feb \n", + " South Asian 21-Mar \n", + " Unknown 10-Mar \n", + " White 09-Mar \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi 03-Mar \n", + " Caribbean 28-Feb \n", + " Chinese 15-Feb \n", + " Other 01-Mar \n", + " Other Asian 24-Feb \n", + " British or Mixed British unknown \n", + " Indian or British Indian 09-Feb \n", + " Irish 08-Jan \n", + " Other Black 15-Feb \n", + " Other White 19-Feb \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani 11-Feb \n", + " Unknown 14-Apr \n", + " White + Asian 05-Mar \n", + " White + Black African 17-Feb \n", + " White + Black Caribbean unknown \n", + "imd_categories 1 Most deprived 22-Mar \n", + " 2 22-Feb \n", + " 3 19-Apr \n", + " 4 07-Mar \n", + " 5 Least deprived 08-Apr \n", + " Unknown 06-Feb " ] }, "metadata": {}, @@ -49034,12 +60886,7 @@ } ], "source": [ - "# latest date of 200 days ago is entered as the latest_date when calculating cumulative sums below.\n", "\n", - "# Seperately, we also ensure that second dose was dated 2 weeks after the start of the campaign, \n", - "# to be consistent with the third doses due calculated above\n", - "df_3rdDUE = df.copy()\n", - "df_3rdDUE.loc[(pd.to_datetime(df_3rdDUE[\"covid_vacc_second_dose_date\"]) <= \"2020-12-21\"), \"covid_vacc_second_dose_date\"] = 0\n", "\n", "df_dict_cum_3rdDUE = cumulative_sums(\n", " df_3rdDUE, groups_of_interest=population_subgroups_third, features_dict=features_dict,\n", @@ -49054,7 +60901,7 @@ "\n", "create_detailed_summary_uptake(summarised_data_dict_3rdDUE, formatted_latest_date=date_3rdDUE,\n", " groups=population_subgroups_third.keys(),\n", - " savepath=savepath, vaccine_type=f\"second_dose_{booster_delay_number}{booster_delay_unit_short}_ago\")\n" + " savepath=savepath, vaccine_type=f\"second_dose_{booster_delay_number}{booster_delay_unit_short}_ago\")" ] } ], diff --git a/notebooks/second_doses.ipynb b/notebooks/second_doses.ipynb index 8ae768e..d05efed 100644 --- a/notebooks/second_doses.ipynb +++ b/notebooks/second_doses.ipynb @@ -13,7 +13,7 @@ "source": [ "OpenSAFELY is a new secure analytics platform for electronic patient records built on behalf of NHS England to deliver urgent academic and operational research during the pandemic. \n", "\n", - "This is an extension of our [regular weekly report](https://reports.opensafely.org/reports/vaccine-coverage/) on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our paper available [here](https://doi.org/10.3399/BJGP.2021.0376).** \n", + "This is an extension of our [regular weekly report](https://reports.opensafely.org/reports/vaccine-coverage/) on COVID-19 vaccination coverage in England using data from 40% of general practices that use TPP electronic health record software. **The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussion of our earlier results (as of 17 March 2021) in our [peer-reviewed publication in the British Journal of General Practice](https://doi.org/10.3399/BJGP.2021.0376).** \n", "\n", "The full analytical methods behind the latest results in this report are available [here](https://github.com/opensafely/nhs-covid-vaccination-uptake).\n", "\n",