diff --git a/analysis/codelists.py b/analysis/codelists.py index 541ee58..1be3cca 100644 --- a/analysis/codelists.py +++ b/analysis/codelists.py @@ -166,3 +166,7 @@ wider_ld_codes = codelist_from_csv( "codelists/primis-covid19-vacc-uptake-learndis.csv", system="snomed", column="code" ) + +covid_vacc_declined = codelist_from_csv( + "codelists/primis-covid19-vacc-uptake-cov1decl.csv", system="snomed", column="code" +) diff --git a/analysis/study_definition_delivery.py b/analysis/study_definition_delivery.py index ac3e664..59fa132 100644 --- a/analysis/study_definition_delivery.py +++ b/analysis/study_definition_delivery.py @@ -166,30 +166,30 @@ returning="binary_flag", return_expectations={"incidence": 0.01,}, ), - cystic_fibrosis=patients.with_these_clinical_events( - cystic_fibrosis_codes, - on_or_before=index_date, - returning="binary_flag", - return_expectations={"incidence": 0.01,}, - ), - sickle_cell_disease=patients.with_these_clinical_events( - sickle_cell_disease_codes, - on_or_before=index_date, - returning="binary_flag", - return_expectations={"incidence": 0.01,}, - ), - permanant_immunosuppression=patients.with_these_clinical_events( - permanent_immunosuppression_codes, - on_or_before=index_date, - returning="binary_flag", - return_expectations={"incidence": 0.01,}, - ), - temporary_immunosuppression=patients.with_these_clinical_events( - temporary_immunosuppression_codes, - on_or_before=index_date, - returning="binary_flag", - return_expectations={"incidence": 0.01,}, - ), + # cystic_fibrosis=patients.with_these_clinical_events( + # cystic_fibrosis_codes, + # on_or_before=index_date, + # returning="binary_flag", + # return_expectations={"incidence": 0.01,}, + # ), + # sickle_cell_disease=patients.with_these_clinical_events( + # sickle_cell_disease_codes, + # on_or_before=index_date, + # returning="binary_flag", + # return_expectations={"incidence": 0.01,}, + # ), + # permanant_immunosuppression=patients.with_these_clinical_events( + # permanent_immunosuppression_codes, + # on_or_before=index_date, + # returning="binary_flag", + # return_expectations={"incidence": 0.01,}, + # ), + # temporary_immunosuppression=patients.with_these_clinical_events( + # temporary_immunosuppression_codes, + # on_or_before=index_date, + # returning="binary_flag", + # return_expectations={"incidence": 0.01,}, + # ), # psychosis_schiz_bipolar=patients.with_these_clinical_events( psychosis_schizophrenia_bipolar_affective_disease_codes, @@ -199,12 +199,12 @@ ), # https://github.com/opensafely/codelist-development/issues/4 - asplenia=patients.with_these_clinical_events( - asplenia_codes, - on_or_before=index_date, - returning="binary_flag", - return_expectations={"incidence": 0.01,}, - ), + # asplenia=patients.with_these_clinical_events( + # asplenia_codes, + # on_or_before=index_date, + # returning="binary_flag", + # return_expectations={"incidence": 0.01,}, + # ), ############################################################################### # COVID VACCINATION diff --git a/analysis/study_definition_delivery_common.py b/analysis/study_definition_delivery_common.py index 341281a..493c5b0 100644 --- a/analysis/study_definition_delivery_common.py +++ b/analysis/study_definition_delivery_common.py @@ -30,11 +30,16 @@ OR shielded OR - (care_home) - OR (LD) ) - """ + """, + registered=patients.registered_as_of( + index_date, + ), + has_died=patients.died_from_any_cause( + on_or_before=index_date, + returning="binary_flag", + ), ), has_follow_up=patients.registered_with_one_practice_between( @@ -42,15 +47,7 @@ end_date=index_date, return_expectations={"incidence": 0.90}, ), - registered=patients.registered_as_of( - index_date, - return_expectations={"incidence": 0.98}, - ), - has_died=patients.died_from_any_cause( - on_or_before=index_date, - returning="binary_flag", - return_expectations={"incidence": 0.05}, - ), + ### PRIMIS care home flag @@ -94,37 +91,6 @@ }, }, ), - # age bands for patients not in care homes (ie living in the community) - # this is used to define eligible groups not defined by clinical criteria - ageband_community=patients.categorised_as( - { - "care home" : "DEFAULT", - "16-29": """ age >= 16 AND age < 30 AND NOT care_home""", - "30-39": """ age >= 30 AND age < 40 AND NOT care_home""", - "40-49": """ age >= 40 AND age < 50 AND NOT care_home""", - "50-59": """ age >= 50 AND age < 60 AND NOT care_home""", - "60-64": """ age >= 60 AND age < 65 AND NOT care_home""", - "65-69": """ age >= 65 AND age < 70 AND NOT care_home""", - "70-79": """ age >= 70 AND age < 80 AND NOT care_home""", - "80+": """ age >= 80 AND age < 120 AND NOT care_home""", - }, - return_expectations={ - "rate": "universal", - "category": { - "ratios": { - "care home":0.125, - "16-29": 0.125, - "30-39": 0.125, - "40-49": 0.125, - "50-59": 0.125, - "60-64": 0.0625, - "65-69": 0.0625, - "70-79": 0.125, - "80+": 0.125, - } - }, - }, - ), # 5 year age bands ageband_5yr=patients.categorised_as( @@ -300,17 +266,7 @@ returning="binary_flag", return_expectations={"incidence": 0.01,}, ), - adrenaline_pen=patients.with_these_medications( - adrenaline_pen, - on_or_after="index_date - 24 months", # look for last two years - returning="binary_flag", - return_last_date_in_period=False, - include_month=False, - return_expectations={ - "date": {"earliest": "2018-12-01", "latest": index_date}, - "incidence": 0.001, - }, - ), + ### PRIMIS overall flag for shielded group @@ -387,5 +343,20 @@ wider_ld_codes, return_expectations={"incidence": 0.02,}, ), + + # declined vaccination / vaccination course / first dose (not including declined second dose) + covid_vacc_declined_date = patients.with_these_clinical_events( + covid_vacc_declined, + returning="date", + find_first_match_in_period=True, + date_format = "YYYY-MM-DD", + return_expectations={ + "date": { + "earliest": "2020-12-08", # first vaccine administered on the 8/12 + "latest": index_date, + }, + "incidence":0.04 + }, + ), ) diff --git a/codelists/codelists.json b/codelists/codelists.json index 635098f..9497135 100644 --- a/codelists/codelists.json +++ b/codelists/codelists.json @@ -174,17 +174,17 @@ "downloaded_at": "2021-02-10 14:28:12.124536Z", "sha": "99f6c0787e17e16430549a4cfb5084612faba2ac" }, - "user-peter-inglesby-eth2001.csv": { - "id": "user/peter-inglesby/eth2001/0f56fa3b", - "url": "https://codelists.opensafely.org/codelist/user/peter-inglesby/eth2001/0f56fa3b/", - "downloaded_at": "2021-02-10 14:28:12.230527Z", - "sha": "708774541b925cf190016e2e160eec31b02d2512" - }, "primis-covid19-vacc-uptake-learndis.csv": { "id": "primis-covid19-vacc-uptake/learndis/v1", "url": "https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/learndis/v1/", "downloaded_at": "2021-03-09 11:58:49.613669Z", "sha": "41f81fcb9fadb082a77cadd6cf60614d7c8d860f" + }, + "primis-covid19-vacc-uptake-cov1decl.csv": { + "id": "primis-covid19-vacc-uptake/cov1decl/v1.1", + "url": "https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/cov1decl/v1.1/", + "downloaded_at": "2021-04-19 13:00:27.222055Z", + "sha": "c8f6ef075bb2f267ee8524453967ba927703fe9d" } } } \ No newline at end of file diff --git a/codelists/codelists.txt b/codelists/codelists.txt index 6d69090..ef1063c 100644 --- a/codelists/codelists.txt +++ b/codelists/codelists.txt @@ -27,5 +27,5 @@ opensafely/sickle-cell-disease/2020-04-14 opensafely/solid-organ-transplantation/2020-04-10 opensafely/permanent-immunosuppression/2020-06-02 opensafely/temporary-immunosuppression/2020-04-24 -user/peter-inglesby/eth2001/0f56fa3b primis-covid19-vacc-uptake/learndis/v1 +primis-covid19-vacc-uptake/cov1decl/v1.1 diff --git a/codelists/primis-covid19-vacc-uptake-cov1decl.csv b/codelists/primis-covid19-vacc-uptake-cov1decl.csv new file mode 100644 index 0000000..f515df1 --- /dev/null +++ b/codelists/primis-covid19-vacc-uptake-cov1decl.csv @@ -0,0 +1,4 @@ +code,term +1324721000000108,Severe acute respiratory syndrome coronavirus 2 vaccination dose declined +1324741000000101,Severe acute respiratory syndrome coronavirus 2 vaccination first dose declined +1324811000000107,Severe acute respiratory syndrome coronavirus 2 immunisation course declined diff --git a/codelists/user-peter-inglesby-eth2001.csv b/codelists/user-peter-inglesby-eth2001.csv deleted file mode 100644 index 48c3123..0000000 --- a/codelists/user-peter-inglesby-eth2001.csv +++ /dev/null @@ -1,83 +0,0 @@ -code,term,grouping_16_label,category_16_id,grouping_6_label,category_6_id -110761000000106,English - ethnic category 2001 census,eth2001_whibrit,1,White,1 -494131000000105,White British - ethnic category 2001 census,eth2001_whibrit,1,White,1 -92391000000108,British or mixed British - ethnic category 2001 census,eth2001_whibrit,1,White,1 -92541000000108,Scottish - ethnic category 2001 census,eth2001_whibrit,1,White,1 -92551000000106,Welsh - ethnic category 2001 census,eth2001_whibrit,1,White,1 -92561000000109,Northern Irish - ethnic category 2001 census,eth2001_whibrit,1,White,1 -92571000000102,Cornish - ethnic category 2001 census,eth2001_whibrit,1,White,1 -93921000000101,Ulster Scots - ethnic category 2001 census,eth2001_whibrit,1,White,1 -494161000000100,White Irish - ethnic category 2001 census,eth2001_whiirish,2,White,1 -92401000000106,Irish - ethnic category 2001 census,eth2001_whiirish,2,White,1 -110401000000103,Turkish - ethnic category 2001 census,eth2001_whiother,3,White,1 -88911000000101,Irish Traveller - ethnic category 2001 census,eth2001_whiother,3,White,1 -88921000000107,Traveller - ethnic category 2001 census,eth2001_whiother,3,White,1 -88931000000109,Gypsy/Romany - ethnic category 2001 census,eth2001_whiother,3,White,1 -88941000000100,Polish - ethnic category 2001 census,eth2001_whiother,3,White,1 -88951000000102,Baltic States (Estonian or Latvian or Lithuanian) - ethnic category 2001 census,eth2001_whiother,3,White,1 -88961000000104,Commonwealth of (Russian) Independent States - ethnic category 2001 census,eth2001_whiother,3,White,1 -88971000000106,Albanian - ethnic category 2001 census,eth2001_whiother,3,White,1 -88981000000108,Serbian - ethnic category 2001 census,eth2001_whiother,3,White,1 -92411000000108,Other White background - ethnic category 2001 census,eth2001_whiother,3,White,1 -92791000000109,Cypriot (part not stated) - ethnic category 2001 census,eth2001_whiother,3,White,1 -93931000000104,Greek - ethnic category 2001 census,eth2001_whiother,3,White,1 -93941000000108,Greek Cypriot - ethnic category 2001 census,eth2001_whiother,3,White,1 -93951000000106,Turkish Cypriot - ethnic category 2001 census,eth2001_whiother,3,White,1 -93961000000109,Italian - ethnic category 2001 census,eth2001_whiother,3,White,1 -93981000000100,Kosovan - ethnic category 2001 census,eth2001_whiother,3,White,1 -93991000000103,Bosnian - ethnic category 2001 census,eth2001_whiother,3,White,1 -94001000000108,Croatian - ethnic category 2001 census,eth2001_whiother,3,White,1 -94011000000105,Other republics which made up the former Yugoslavia - ethnic category 2001 census,eth2001_whiother,3,White,1 -94021000000104,Mixed Irish and other White - ethnic category 2001 census,eth2001_whiother,3,White,1 -94031000000102,Other mixed White - ethnic category 2001 census,eth2001_whiother,3,White,1 -94041000000106,Other White European or European unspecified or Mixed European - ethnic category 2001 census,eth2001_whiother,3,White,1 -94051000000109,Other White or White unspecified - ethnic category 2001 census,eth2001_whiother,3,White,1 -92421000000102,White and Black Caribbean - ethnic category 2001 census,eth2001_mxdwhiblkcar,4,Mixed,2 -92431000000100,White and Black African - ethnic category 2001 census,eth2001_mxdwhiblkafr,5,Mixed,2 -92441000000109,White and Asian - ethnic category 2001 census,eth2001_mxdwhiasn,6,Mixed,2 -110771000000104,Black and White - ethnic category 2001 census,eth2001_mxdother,7,Mixed,2 -92451000000107,Other Mixed background - ethnic category 2001 census,eth2001_mxdother,7,Mixed,2 -92581000000100,Black and Asian - ethnic category 2001 census,eth2001_mxdother,7,Mixed,2 -92591000000103,Black and Chinese - ethnic category 2001 census,eth2001_mxdother,7,Mixed,2 -92601000000109,Chinese and White - ethnic category 2001 census,eth2001_mxdother,7,Mixed,2 -92611000000106,Asian and Chinese - ethnic category 2001 census,eth2001_mxdother,7,Mixed,2 -92621000000100,Other Mixed or Mixed unspecified - ethnic category 2001 census,eth2001_mxdother,7,Mixed,2 -92631000000103,Mixed Asian - ethnic category 2001 census,eth2001_mxdother,7,Mixed,2 -92721000000106,Mixed Black - ethnic category 2001 census,eth2001_mxdother,7,Mixed,2 -110751000000108,Indian or British Indian - ethnic category 2001 census,eth2001_asnindian,8,South Asian,3 -92461000000105,Pakistani or British Pakistani - ethnic category 2001 census,eth2001_asnpak,9,South Asian,3 -92471000000103,Bangladeshi or British Bangladeshi - ethnic category 2001 census,eth2001_asnbang,10,South Asian,3 -110781000000102,Sinhalese - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -86461000000107,Sri Lankan - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92481000000101,Other Asian background - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92641000000107,Punjabi - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92651000000105,Kashmiri - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92661000000108,East African Asian - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92671000000101,Tamil - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92681000000104,British Asian - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92691000000102,Caribbean Asian - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92701000000102,Other Asian or Asian unspecified - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92751000000101,Vietnamese - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92761000000103,Japanese - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92771000000105,Filipino - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -92781000000107,Malaysian - ethnic category 2001 census,eth2001_asnother,11,South Asian,3 -107691000000105,Caribbean - ethnic category 2001 census,eth2001_blkcarib,12,Black,4 -92491000000104,African - ethnic category 2001 census,eth2001_blkafric,13,Black,4 -92711000000100,Somali - ethnic category 2001 census,eth2001_blkafric,13,Black,4 -92731000000108,Nigerian - ethnic category 2001 census,eth2001_blkafric,13,Black,4 -110791000000100,Black British - ethnic category 2001 census,eth2001_blkoth,14,Black,4 -92501000000105,Other Black background - ethnic category 2001 census,eth2001_blkoth,14,Black,4 -92741000000104,Other Black or Black unspecified - ethnic category 2001 census,eth2001_blkoth,14,Black,4 -92511000000107,Chinese - ethnic category 2001 census,eth2001_chinese,15,Other,5 -89001000000105,Arab - ethnic category 2001 census,eth2001_other,16,Other,5 -89011000000107,Iranian - ethnic category 2001 census,eth2001_other,16,Other,5 -89021000000101,South and Central American - ethnic category 2001 census,eth2001_other,16,Other,5 -92521000000101,Other - ethnic category 2001 census,eth2001_other,16,Other,5 -94061000000107,North African - ethnic category 2001 census,eth2001_other,16,Other,5 -94071000000100,"Middle Eastern (excluding Israeli, Iranian and Arab) - ethnic category 2001 census",eth2001_other,16,Other,5 -94081000000103,Israeli - ethnic category 2001 census,eth2001_other,16,Other,5 -94091000000101,Kurdish - ethnic category 2001 census,eth2001_other,16,Other,5 -94101000000109,Moroccan - ethnic category 2001 census,eth2001_other,16,Other,5 -94111000000106,Latin American - ethnic category 2001 census,eth2001_other,16,Other,5 -94121000000100,Multi-ethnic islands: Mauritian or Seychellois or Maldivian or St Helena - ethnic category 2001 census,eth2001_other,16,Other,5 -94151000000105,Any other group - ethnic category 2001 census,eth2001_other,16,Other,5 diff --git a/lib/data_processing.py b/lib/data_processing.py index f6be805..2cca970 100644 --- a/lib/data_processing.py +++ b/lib/data_processing.py @@ -10,7 +10,7 @@ -def load_data(input_file='input_delivery.csv', input_path="output"): +def load_data(input_file='input_delivery.csv.gz', input_path="output"): """ This reads in a csv that must be in output/ directory and cleans the data ready for use in the graphs and tables @@ -33,7 +33,7 @@ def load_data(input_file='input_delivery.csv', input_path="output"): """ # import data and fill nulls with 0 - df = pd.read_csv(os.path.join("..",input_path, input_file)).fillna(0) + df = pd.read_csv(os.path.join("..",input_path, input_file), compression='gzip').fillna(0) # fill unknown ethnicity from GP records with ethnicity from SUS (secondary care) df.loc[df["ethnicity"]==0, "ethnicity"] = df["ethnicity_6_sus"] @@ -62,6 +62,9 @@ def load_data(input_file='input_delivery.csv', input_path="output"): covid_vacc_2nd = np.where(df["covid_vacc_second_dose_date"]!=0, 1, 0), covid_vacc_bin = np.where(df["covid_vacc_date"]!=0, 1, 0)) + # declined - suppress if vaccine has been received + df["covid_vacc_declined_date"] = np.where(df["covid_vacc_date"]==0, df["covid_vacc_declined_date"], 0) + # create an additional field for 2nd dose to use as a flag for each eligible group df["2nd_dose"] = df["covid_vacc_2nd"] @@ -84,7 +87,7 @@ def load_data(input_file='input_delivery.csv', input_path="output"): # drop unnecssary columns or columns created for processing df = df.drop(["imd","ethnicity_16", "ethnicity", 'ethnicity_6_sus', - 'ethnicity_16_sus', "adrenaline_pen", "has_died", "has_follow_up"], 1) + 'ethnicity_16_sus', "has_follow_up"], 1) # categorise into priority groups (similar to the national groups but not exactly the same) conditions = [ @@ -111,9 +114,7 @@ def load_data(input_file='input_delivery.csv', input_path="output"): for c in ["2nd_dose", "LD", "newly_shielded_since_feb_15", "dementia", "chronic_cardiac_disease", "current_copd", "dialysis", "dmards","psychosis_schiz_bipolar", "solid_organ_transplantation", "chemo_or_radio", "intel_dis_incl_downs_syndrome","ssri", - "lung_cancer", "cancer_excl_lung_and_haem", "haematological_cancer", "bone_marrow_transplant", - "cystic_fibrosis", "sickle_cell_disease", "permanant_immunosuppression", - "temporary_immunosuppression", "asplenia"]: + "lung_cancer", "cancer_excl_lung_and_haem", "haematological_cancer"]: df[c] = np.where(df[c]==1, "yes", "no") @@ -122,7 +123,7 @@ def load_data(input_file='input_delivery.csv', input_path="output"): df = df.merge(stps, left_on="stp", right_on="stp_id", how="left").rename(columns={"name":"stp_name"}) # drop additional columns - df = df.drop(['registered', 'care_home', 'age',"stp_id", "ageband_community"], 1) + df = df.drop(['care_home', 'age',"stp_id"], 1) return df diff --git a/lib/report_results.py b/lib/report_results.py index 7cb9477..dae2433 100644 --- a/lib/report_results.py +++ b/lib/report_results.py @@ -234,7 +234,7 @@ def filtered_cumulative_sum(df, columns, latest_date, reference_column_name="cov return df_dict_temp -def make_vaccine_graphs(df, latest_date, savepath, savepath_figure_csvs, suffix=""): +def make_vaccine_graphs(df, latest_date, savepath, savepath_figure_csvs, vaccine_type="first_dose", suffix=""): ''' Cumulative chart by day of total vaccines given across key eligible groups @@ -243,16 +243,25 @@ def make_vaccine_graphs(df, latest_date, savepath, savepath_figure_csvs, suffix= latest_date (str): latest date across dataset in YYYY-MM-DD format savepath (dict): path to save figure as svg (savepath["figures"]) savepath_figure_csvs (str): path to save machine readable csv for recreating the chart - groups_of_interest (dict): population subgroups + vaccine_type (str): used in output strings to describe type of vaccine received e.g. "first_dose", "moderna". + Also appended to filename of output. + suffix (str) ''' - dfp = df.copy().loc[(df["covid_vacc_date"]!=0)] + if vaccine_type=="first_dose": + reference_column_name="covid_vacc_date" + title=f"Cumulative vaccination figures" + else: + reference_column_name=f"covid_vacc_{vaccine_type}_date" + title=f"Cumulative {vaccine_type.replace('_',' ')} vaccination figures" + + dfp = df.copy().loc[(df[reference_column_name]!=0)] - dfp = dfp.groupby(["covid_vacc_date","group_name"])[["patient_id"]].count() + dfp = dfp.groupby([reference_column_name,"group_name"])[["patient_id"]].count() dfp = dfp.unstack().fillna(0).cumsum().reset_index().replace([0,1,2,3,4,5,6],0) - dfp["covid_vacc_date"] = pd.to_datetime(dfp["covid_vacc_date"]).dt.strftime("%d %b") - dfp = dfp.set_index("covid_vacc_date") + dfp[reference_column_name] = pd.to_datetime(dfp[reference_column_name]).dt.strftime("%d %b") + dfp = dfp.set_index(reference_column_name) dfp = round7(dfp) dfp.columns = dfp.columns.droplevel() @@ -263,14 +272,18 @@ def make_vaccine_graphs(df, latest_date, savepath, savepath_figure_csvs, suffix= dfp = dfp.sort_values(by=dfp.last_valid_index(), axis=1, ascending=False) - # export data to csv out = dfp.copy() if savepath_figure_csvs: - out.to_csv(os.path.join(savepath_figure_csvs, f"Cumulative vaccination figures among each eligible group{suffix}.csv"), index=True) + out.to_csv(os.path.join(savepath_figure_csvs, f"{title} among each eligible group{suffix}.csv"), index=True) - # divide numbers into millions - dfp = dfp/1e6 + # divide numbers into millions if exceeding 10m, otherwise thousands + if dfp["total"].max() >= 1e7: + dfp = dfp/1e6 + ylabel = "number of patients (millions)" + else: + dfp = dfp/1000 + ylabel = "number of patients (thousands)" # plot chart dfp.plot(legend=True, ds='steps-post') @@ -278,12 +291,12 @@ def make_vaccine_graphs(df, latest_date, savepath, savepath_figure_csvs, suffix= # set chart labels and other options plt.xlabel("date", fontweight='bold') plt.xticks(rotation=90) - plt.ylabel("number of patients vaccinated (millions)", fontweight='bold') - plt.title(f"Cumulative vaccination figures to {latest_date}", fontsize=16) + plt.ylabel(ylabel, fontweight='bold') + plt.title(f"{title} to {latest_date}", fontsize=16) plt.legend(bbox_to_anchor=(1.04,1), loc="upper left") # export figure to file and display it - plt.savefig(os.path.join(savepath["figures"], f"Cumulative vaccination figures.svg"), dpi=300, bbox_inches='tight') + plt.savefig(os.path.join(savepath["figures"], f"{title}.svg"), dpi=300, bbox_inches='tight') plt.show() @@ -469,8 +482,8 @@ def create_summary_stats(df, summarised_data_dict, formatted_latest_date, savep # get the total vaccinated and round to the nearest 7 if vaccine_type=="first_dose": reference_column_name="covid_vacc_date" - elif vaccine_type=="second_dose": - reference_column_name="covid_vacc_second_dose_date" + else: + reference_column_name=f"covid_vacc_{vaccine_type}_date" vaccinated_total = round7( df.loc[df[reference_column_name]!=0]["patient_id"].nunique() ) # add the results fo the summary_stats dict @@ -560,6 +573,7 @@ def plot_dem_charts(summary_stats_results, cumulative_data_dict, formatted_lates If org_name is supplied this dict should map filetypes to orgs to filepaths. pop_subgroups (list): population subgroups for which to create charts, default ["80+", "70-79"] groups_dict (dict): dictionary mapping population subgroups to a list of demographic/clinical factors to include for that group + groups_to_exclude (list): savepath_figure_csvs (dict): Optionally supply if exporting numbers presented in charts to csv include_overall (bool): Option to include "overall" chart ie. chart with a single line, not broken down into any groups org_name (str): name of organisation for which data is to be presented (e.g. an STP or region) @@ -593,19 +607,22 @@ def plot_dem_charts(summary_stats_results, cumulative_data_dict, formatted_lates display(Markdown(f"## \n ## COVID vaccination rollout among **{k}** population up to {formatted_latest_date}{org_string}")) # get the overall vaccination rate among relevant group and strip out the text to get the number (should be within 0 - 100) - overall_rate = float(summary_stats_results[f"{k}"][0:4]) + overall_rate = float(summary_stats_results[f"{k}"][0:4].replace("%","")) out=cumulative_data_dict[k] for c in groups: out=cumulative_data_dict[k][c] - # suppress low numbers + + # get index name (== "covid_vacc_date" for first doses) + reference_column_name = out.index.name + vaccine_type = reference_column_name.replace("covid_vacc_","").replace("date"," ").replace("_"," ").title() # export csv to file - numerator and denominator rather than percentages if savepath_figure_csvs: cols = [c for c in out.columns if '_percent' not in c] out_csv = out.copy()[cols] - out_csv.to_csv(os.path.join(savepath_figure_csvs, f"Cumulative vaccination percent among {k} population by {c.replace('_',' ')}{suffix}.csv"), index=True) + out_csv.to_csv(os.path.join(savepath_figure_csvs, f"Cumulative {vaccine_type}vaccination percent among {k} population by {c.replace('_',' ')}{suffix}.csv"), index=True) # for plotting, drop vaccinated and total column but keep percentage cols = [c for c in out.columns if ('_percent' not in c) & ('_total' not in c)] @@ -614,15 +631,16 @@ def plot_dem_charts(summary_stats_results, cumulative_data_dict, formatted_lates out = out.rename(columns={f"{c2}_percent":c2}) # display title and caveats for individual chart - display(Markdown(f"### COVID vaccinations among **{k}** population by **{c.replace('_',' ')}**")) + display(Markdown(f"### {vaccine_type}COVID vaccinations among **{k}** population by **{c.replace('_',' ')}**")) if len(org_name)>0: display(Markdown(f"#### {org_string}")) if ~(c in ["overall","sex","imd_categories"]): display(Markdown(f"Zero percentages may represent suppressed low numbers; raw numbers were rounded to nearest 7")) + out = out.reset_index() - out["covid_vacc_date"] = pd.to_datetime(out["covid_vacc_date"]).dt.strftime("%d %b") - out = out.set_index("covid_vacc_date") + out[reference_column_name] = pd.to_datetime(out[reference_column_name]).dt.strftime("%d %b") + out = out.set_index(reference_column_name) # plot trend chart and set chart options @@ -630,8 +648,8 @@ def plot_dem_charts(summary_stats_results, cumulative_data_dict, formatted_lates plt.axhline(overall_rate, color="k", linestyle="--", alpha=0.5) plt.text(0, overall_rate*1.02, "latest overall cohort rate") plt.ylim(top=1.1*max(overall_rate, out.max().max())) - plt.ylabel("Percent vaccinated (cumulative)") - plt.xlabel("Date vaccinated") + plt.ylabel("Percent (cumulative)") + plt.xlabel("Date") plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left') # export figures to file @@ -639,6 +657,6 @@ def plot_dem_charts(summary_stats_results, cumulative_data_dict, formatted_lates figure_savepath = savepath["figures"][org_name] else: figure_savepath = savepath["figures"] - plt.savefig(os.path.join(figure_savepath, f"COVID vaccinations among {k} population by {c.replace('_',' ')}.svg"), dpi=300, bbox_inches='tight') + plt.savefig(os.path.join(figure_savepath, f"{vaccine_type}COVID vaccinations among {k} population by {c.replace('_',' ')}.svg"), dpi=300, bbox_inches='tight') plt.show() \ No newline at end of file diff --git a/notebooks/opensafely_vaccine_report_overall.ipynb b/notebooks/opensafely_vaccine_report_overall.ipynb index 8263307..a6c8d91 100644 --- a/notebooks/opensafely_vaccine_report_overall.ipynb +++ b/notebooks/opensafely_vaccine_report_overall.ipynb @@ -26,7 +26,7 @@ { "data": { "text/markdown": [ - "### Report last updated **12 Apr 2021**" + "### Report last updated **19 Apr 2021**" ], "text/plain": [ "" @@ -38,7 +38,7 @@ { "data": { "text/markdown": [ - "### Vaccinations included up to **30 Mar 2021** inclusive" + "### Vaccinations included up to **16 Apr 2021** inclusive" ], "text/plain": [ "" @@ -79,6 +79,7 @@ " - 65-69 population\n", " - 60-64 population\n", " - 55-59 population\n", + " - 50-54 population\n", "- **Current vaccination coverage of each eligible population group, according to demographic/clinical features**
\n", " - Includes each of the groups above, plus care home (65+) and LD (aged 16-64) populations.\n", "- Appendix: Proportion of each population group for whom ethnicity is known" @@ -118,8 +119,8 @@ " \n", " \n", " \n", - " first dose as at 30 Mar 2021\n", - " second dose as at 30 Mar 2021\n", + " first dose as at 16 Apr 2021\n", + " second dose as at 16 Apr 2021\n", " \n", " \n", " Group\n", @@ -135,86 +136,86 @@ " \n", " \n", " 80+\n", - " 40.1% (854 of 2,121)\n", - " 10.1% (217 of 2,121)\n", + " 40.7% (833 of 2,044)\n", + " 10.4% (210 of 2,044)\n", " \n", " \n", " 70-79\n", - " 39.5% (1,414 of 3,570)\n", - " 9.6% (343 of 3,570)\n", + " 39.4% (1,351 of 3,437)\n", + " 9.0% (308 of 3,437)\n", " \n", " \n", " care home\n", - " 40.0% (546 of 1,372)\n", - " 10.6% (147 of 1,372)\n", + " 40.0% (553 of 1,386)\n", + " 10.2% (140 of 1,386)\n", " \n", " \n", " shielding (aged 16-69)\n", - " 37.0% (154 of 413)\n", - " 10.2% (42 of 413)\n", + " 41.5% (182 of 434)\n", + " 9.9% (42 of 434)\n", " \n", " \n", " 65-69\n", - " 41.1% (903 of 2,191)\n", - " 9.6% (210 of 2,191)\n", + " 39.3% (861 of 2,184)\n", + " 9.5% (210 of 2,184)\n", " \n", " \n", " LD (aged 16-64)\n", - " 41.3% (322 of 784)\n", - " 10.3% (84 of 784)\n", + " 41.6% (343 of 826)\n", + " 7.9% (63 of 826)\n", " \n", " \n", " 60-64\n", - " 39.7% (1,043 of 2,632)\n", - " 11.2% (294 of 2,632)\n", + " 39.7% (1,078 of 2,716)\n", + " 9.5% (259 of 2,716)\n", " \n", " \n", " 55-59\n", - " 41.5% (1,302 of 3,136)\n", - " 10.0% (315 of 3,136)\n", + " 39.8% (1,267 of 3,192)\n", + " 9.8% (315 of 3,192)\n", " \n", " \n", " 50-54\n", - " 38.3% (1,309 of 3,409)\n", - " 9.7% (329 of 3,409)\n", + " 40.5% (1,379 of 3,402)\n", + " 10.9% (371 of 3,402)\n", " \n", " \n", " 16-49, not in other eligible groups shown\n", - " 12,159\n", - " 3,024\n", + " 12,152\n", + " 3,080\n", " \n", " \n", "\n", "" ], "text/plain": [ - " first dose as at 30 Mar 2021 \\\n", + " first dose as at 16 Apr 2021 \\\n", "Group \n", "Total vaccinated in TPP 19,999 \n", - "80+ 40.1% (854 of 2,121) \n", - "70-79 39.5% (1,414 of 3,570) \n", - "care home 40.0% (546 of 1,372) \n", - "shielding (aged 16-69) 37.0% (154 of 413) \n", - "65-69 41.1% (903 of 2,191) \n", - "LD (aged 16-64) 41.3% (322 of 784) \n", - "60-64 39.7% (1,043 of 2,632) \n", - "55-59 41.5% (1,302 of 3,136) \n", - "50-54 38.3% (1,309 of 3,409) \n", - "16-49, not in other eligible groups shown 12,159 \n", + "80+ 40.7% (833 of 2,044) \n", + "70-79 39.4% (1,351 of 3,437) \n", + "care home 40.0% (553 of 1,386) \n", + "shielding (aged 16-69) 41.5% (182 of 434) \n", + "65-69 39.3% (861 of 2,184) \n", + "LD (aged 16-64) 41.6% (343 of 826) \n", + "60-64 39.7% (1,078 of 2,716) \n", + "55-59 39.8% (1,267 of 3,192) \n", + "50-54 40.5% (1,379 of 3,402) \n", + "16-49, not in other eligible groups shown 12,152 \n", "\n", - " second dose as at 30 Mar 2021 \n", + " second dose as at 16 Apr 2021 \n", "Group \n", "Total vaccinated in TPP 4,998 \n", - "80+ 10.1% (217 of 2,121) \n", - "70-79 9.6% (343 of 3,570) \n", - "care home 10.6% (147 of 1,372) \n", - "shielding (aged 16-69) 10.2% (42 of 413) \n", - "65-69 9.6% (210 of 2,191) \n", - "LD (aged 16-64) 10.3% (84 of 784) \n", - "60-64 11.2% (294 of 2,632) \n", - "55-59 10.0% (315 of 3,136) \n", - "50-54 9.7% (329 of 3,409) \n", - "16-49, not in other eligible groups shown 3,024 " + "80+ 10.4% (210 of 2,044) \n", + "70-79 9.0% (308 of 3,437) \n", + "care home 10.2% (140 of 1,386) \n", + "shielding (aged 16-69) 9.9% (42 of 434) \n", + "65-69 9.5% (210 of 2,184) \n", + "LD (aged 16-64) 7.9% (63 of 826) \n", + "60-64 9.5% (259 of 2,716) \n", + "55-59 9.8% (315 of 3,192) \n", + "50-54 10.9% (371 of 3,402) \n", + "16-49, not in other eligible groups shown 3,080 " ] }, "metadata": {}, @@ -270,12 +271,24 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/markdown": [ + "Moderna vaccines (% of all first doses): **0.0%** (7)\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "data": { "text/markdown": [ "##### \n", "### Group definitions \n", - " - The **care home** group is defined based on patients having one of [these codes](https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/longres/v1/).\n", + " - The **care home** group is defined based on patients (aged 65+) having one of [these codes](https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/longres/v1/).\n", "\n", "- The **shielding** group is defined based on patients having one of [these codes](https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/shield/v1/) provided it was not superceded by one of [these codes](https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/nonshield/v1/).\n", "\n", @@ -307,15 +320,14 @@ "\n", "display(Markdown(f\"### Vaccine types and second doses\" ))\n", "\n", - "for x in additional_stats.index:\n", - " if \"Moderna\" not in x: \n", - " display(Markdown(f\"{x}: {additional_stats.loc[x][0]}\\n\"))\n", + "for x in additional_stats.index: \n", + " display(Markdown(f\"{x}: {additional_stats.loc[x][0]}\\n\"))\n", " \n", " \n", "\n", "\n", "display(Markdown(f\"##### \\n\"\n", - " \"### Group definitions \\n - The **care home** group is defined based on patients having one of [these codes](https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/longres/v1/).\\n\"\n", + " \"### Group definitions \\n - The **care home** group is defined based on patients (aged 65+) having one of [these codes](https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/longres/v1/).\\n\"\n", " \"\\n- The **shielding** group is defined based on patients having one of [these codes](https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/shield/v1/) \\\n", " provided it was not superceded by one of [these codes](https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/nonshield/v1/).\\n\" \n", " \"\\n- The **LD** (learning disability) group is defined based on [this](https://codelists.opensafely.org/codelist/primis-covid19-vacc-uptake/learndis/v1/)\\\n", @@ -341,7 +353,7 @@ { "data": { "image/svg+xml": [ - "\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", @@ -375,7 +387,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -388,7 +400,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -396,7 +408,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -409,7 +421,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -421,7 +433,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -434,7 +446,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -444,7 +456,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -457,12 +469,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -475,7 +487,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -484,7 +496,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -494,7 +506,29 @@ " \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", @@ -502,7 +536,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -512,178 +546,156 @@ " \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", - " \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", + " \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", @@ -696,13 +708,11 @@ " \n", " \n", " \n", - " \n", - " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -722,77 +732,67 @@ " \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", @@ -806,9 +806,10 @@ " \n", " \n", " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -849,23 +850,23 @@ " \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", @@ -873,21 +874,18 @@ " \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", @@ -931,27 +929,13 @@ " \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", @@ -959,13 +943,27 @@ " \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", @@ -973,13 +971,13 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -987,13 +985,13 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1001,28 +999,28 @@ " \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", @@ -1034,11 +1032,11 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -1046,7 +1044,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1064,13 +1062,13 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1099,8 +1097,8 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "" @@ -1126,7 +1124,7 @@ "metadata": {}, "source": [ "## Trends in vaccination rates of 80+ population according to demographic/clinical features, cumulatively by day. \n", - "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**\n" + "**\\*_Latest overall cohort rate_ calculated as at latest date for vaccinations recorded across all TPP practices.**\n" ] }, { @@ -1149,7 +1147,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", + "### COVID vaccinations among 80+ population\n", " ### by Sex" ], "text/plain": [ @@ -1180,10 +1178,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1209,7 +1207,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1217,7 +1215,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1230,7 +1228,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1242,7 +1240,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1255,7 +1253,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1265,7 +1263,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1278,12 +1276,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1296,7 +1294,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1305,7 +1303,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1315,123 +1313,133 @@ " \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", " \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", @@ -1440,40 +1448,29 @@ " \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", @@ -1487,14 +1484,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1527,21 +1524,21 @@ " \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", @@ -1551,7 +1548,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1567,8 +1564,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by Ethnicity (broad categories)" + "### DateCOVID vaccinations among 80+ population\n", + " ### by Sex" ], "text/plain": [ "" @@ -1580,7 +1577,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1598,10 +1595,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1627,7 +1624,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1635,7 +1632,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1648,7 +1645,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1660,7 +1657,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1673,7 +1670,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1683,7 +1680,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1696,12 +1693,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1714,7 +1711,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1723,7 +1720,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1733,123 +1730,133 @@ " \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", " \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", @@ -1858,52 +1865,29 @@ " \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", @@ -1917,14 +1901,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -1955,126 +1939,33 @@ " \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", - " \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", @@ -2090,8 +1981,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by Index of Multiple Deprivation (quintiles)" + "### COVID vaccinations among 80+ population\n", + " ### by Ethnicity (broad categories)" ], "text/plain": [ "" @@ -2103,7 +1994,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2121,10 +2012,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2150,7 +2041,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2158,7 +2049,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2171,7 +2062,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2183,7 +2074,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2196,7 +2087,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2206,7 +2097,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2219,12 +2110,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2237,7 +2128,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2246,7 +2137,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2256,44 +2147,52 @@ " \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", @@ -2301,78 +2200,80 @@ " \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", @@ -2381,52 +2282,41 @@ " \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", @@ -2440,14 +2330,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2478,106 +2368,95 @@ " \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", + " \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", @@ -2587,11 +2466,28 @@ " \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", @@ -2607,8 +2503,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by BMI" + "### DateCOVID vaccinations among 80+ population\n", + " ### by Ethnicity (broad categories)" ], "text/plain": [ "" @@ -2620,7 +2516,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2638,10 +2534,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2667,7 +2563,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2675,7 +2571,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2688,7 +2584,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2700,7 +2596,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2713,7 +2609,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2723,7 +2619,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2736,12 +2632,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2754,7 +2650,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2763,7 +2659,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2773,44 +2669,52 @@ " \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", @@ -2818,78 +2722,80 @@ " \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", @@ -2898,40 +2804,41 @@ " \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", @@ -2945,14 +2852,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -2983,45 +2890,126 @@ " \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", + " \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", @@ -3037,8 +3025,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by Chronic cardiac disease" + "### COVID vaccinations among 80+ population\n", + " ### by Index of Multiple Deprivation (quintiles)" ], "text/plain": [ "" @@ -3050,7 +3038,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3068,10 +3056,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3097,7 +3085,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3105,7 +3093,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3118,7 +3106,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3130,7 +3118,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3143,7 +3131,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3153,7 +3141,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3166,12 +3154,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3184,7 +3172,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3193,7 +3181,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3203,44 +3191,52 @@ " \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", @@ -3248,78 +3244,80 @@ " \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", @@ -3328,40 +3326,41 @@ " \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", @@ -3375,14 +3374,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3413,39 +3412,120 @@ " \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", + " \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", @@ -3461,8 +3541,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by Current COPD" + "### DateCOVID vaccinations among 80+ population\n", + " ### by Index of Multiple Deprivation (quintiles)" ], "text/plain": [ "" @@ -3474,7 +3554,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3492,10 +3572,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3521,7 +3601,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3529,7 +3609,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3542,7 +3622,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3554,7 +3634,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3567,7 +3647,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3577,7 +3657,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3590,12 +3670,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3608,7 +3688,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3617,7 +3697,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3627,44 +3707,52 @@ " \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", @@ -3672,78 +3760,80 @@ " \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", @@ -3752,40 +3842,41 @@ " \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", @@ -3799,14 +3890,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3837,39 +3928,120 @@ " \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", + " \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", @@ -3885,8 +4057,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by Dialysis" + "### COVID vaccinations among 80+ population\n", + " ### by BMI" ], "text/plain": [ "" @@ -3898,7 +4070,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3916,10 +4088,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3945,7 +4117,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3953,7 +4125,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3966,7 +4138,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3978,7 +4150,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -3991,7 +4163,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4001,7 +4173,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4014,12 +4186,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4032,7 +4204,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4041,7 +4213,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4051,123 +4223,133 @@ " \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", " \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", @@ -4176,40 +4358,29 @@ " \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", @@ -4223,14 +4394,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4261,39 +4432,48 @@ " \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", @@ -4309,8 +4489,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by Dementia" + "### DateCOVID vaccinations among 80+ population\n", + " ### by BMI" ], "text/plain": [ "" @@ -4322,7 +4502,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4340,10 +4520,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4369,7 +4549,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4377,7 +4557,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4390,7 +4570,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4402,7 +4582,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4415,7 +4595,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4425,7 +4605,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4438,12 +4618,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4456,7 +4636,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4465,7 +4645,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4475,44 +4655,52 @@ " \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", @@ -4520,78 +4708,80 @@ " \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", @@ -4600,40 +4790,29 @@ " \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", @@ -4647,14 +4826,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4685,39 +4864,48 @@ " \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", @@ -4733,8 +4921,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by Learning disability" + "### COVID vaccinations among 80+ population\n", + " ### by Chronic cardiac disease" ], "text/plain": [ "" @@ -4764,10 +4952,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4793,7 +4981,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4801,7 +4989,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4814,7 +5002,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4826,7 +5014,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4839,7 +5027,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4849,7 +5037,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4862,12 +5050,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4880,7 +5068,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4889,7 +5077,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4899,140 +5087,133 @@ " \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", " \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", @@ -5041,40 +5222,29 @@ " \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", @@ -5095,7 +5265,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5158,7 +5328,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5174,8 +5344,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by Psychosis, schizophrenia, or bipolar" + "### DateCOVID vaccinations among 80+ population\n", + " ### by Chronic cardiac disease" ], "text/plain": [ "" @@ -5205,10 +5375,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5234,7 +5404,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5242,7 +5412,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5255,7 +5425,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5267,7 +5437,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5280,7 +5450,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5290,7 +5460,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5303,12 +5473,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5321,7 +5491,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5330,7 +5500,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5340,123 +5510,133 @@ " \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", " \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", @@ -5465,40 +5645,29 @@ " \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", @@ -5512,14 +5681,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5552,22 +5721,22 @@ " \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", @@ -5582,7 +5751,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5598,8 +5767,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by SSRI (last 12 months)" + "### COVID vaccinations among 80+ population\n", + " ### by Current COPD" ], "text/plain": [ "" @@ -5629,10 +5798,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5658,7 +5827,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5666,7 +5835,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5679,7 +5848,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5691,7 +5860,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5704,7 +5873,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5714,7 +5883,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5727,12 +5896,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5745,7 +5914,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5754,7 +5923,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5764,123 +5933,133 @@ " \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", " \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", @@ -5889,40 +6068,29 @@ " \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", @@ -5936,14 +6104,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -5976,22 +6144,22 @@ " \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", @@ -6006,7 +6174,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6022,8 +6190,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by 2nd dose" + "### DateCOVID vaccinations among 80+ population\n", + " ### by Current COPD" ], "text/plain": [ "" @@ -6053,10 +6221,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6082,7 +6250,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6090,7 +6258,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6103,7 +6271,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6115,7 +6283,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6128,7 +6296,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6138,7 +6306,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6151,12 +6319,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6169,7 +6337,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6178,7 +6346,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6188,123 +6356,133 @@ " \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", " \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", @@ -6313,40 +6491,29 @@ " \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", @@ -6360,14 +6527,14 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6383,42 +6550,39 @@ " \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", @@ -6433,7 +6597,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6449,8 +6613,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 80+ population\n", - " ### by Age band" + "### COVID vaccinations among 80+ population\n", + " ### by Dialysis" ], "text/plain": [ "" @@ -6462,7 +6626,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6480,10 +6644,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6509,7 +6673,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6517,7 +6681,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6530,7 +6694,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6542,7 +6706,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6555,7 +6719,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6565,7 +6729,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6578,12 +6742,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6596,7 +6760,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6605,7 +6769,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6615,140 +6779,133 @@ " \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", " \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", @@ -6757,82 +6914,29 @@ " \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", @@ -6853,7 +6957,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -6884,239 +6988,39 @@ " \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", - " \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", - " \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", @@ -7128,47 +7032,12 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - "chartlist = find_and_sort_filenames(foldername=\"figures\",\n", - " files_to_exclude=[\"Cumulative vaccination figures.svg\"])\n", - " \n", - "display(Markdown(\"## 80+ population\"))\n", - "for item in chartlist:\n", - " show_chart(item)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Trends in vaccination rates of 70-79 population according to demographic/clinical features, cumulatively by day. \n", - "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "## 70-79 population" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" }, { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by Sex" + "### DateCOVID vaccinations among 80+ population\n", + " ### by Dialysis" ], "text/plain": [ "" @@ -7180,7 +7049,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7198,10 +7067,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7227,7 +7096,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7235,7 +7104,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7248,7 +7117,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7260,7 +7129,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7273,7 +7142,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7283,7 +7152,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7296,12 +7165,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7314,7 +7183,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7323,7 +7192,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7333,123 +7202,133 @@ " \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", " \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", @@ -7458,40 +7337,29 @@ " \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", @@ -7505,14 +7373,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7543,33 +7411,39 @@ " \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", @@ -7585,8 +7459,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by Ethnicity (broad categories)" + "### COVID vaccinations among 80+ population\n", + " ### by Dementia" ], "text/plain": [ "" @@ -7598,7 +7472,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7616,10 +7490,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7632,7 +7506,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7645,7 +7519,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7653,7 +7527,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7666,7 +7540,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7678,7 +7552,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7691,7 +7565,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7701,7 +7575,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7714,12 +7588,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7732,7 +7606,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7741,7 +7615,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7751,123 +7625,133 @@ " \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", " \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", @@ -7876,52 +7760,29 @@ " \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", @@ -7935,14 +7796,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -7973,126 +7834,39 @@ " \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", - " \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", @@ -8108,8 +7882,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by Index of Multiple Deprivation (quintiles)" + "### DateCOVID vaccinations among 80+ population\n", + " ### by Dementia" ], "text/plain": [ "" @@ -8121,7 +7895,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8139,10 +7913,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8168,7 +7942,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8176,7 +7950,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8189,7 +7963,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8201,7 +7975,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8214,7 +7988,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8224,7 +7998,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8237,12 +8011,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8255,7 +8029,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8264,7 +8038,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8274,123 +8048,133 @@ " \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", " \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", @@ -8399,52 +8183,29 @@ " \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", @@ -8458,14 +8219,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8496,120 +8257,39 @@ " \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", + " \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", @@ -8625,8 +8305,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by BMI" + "### COVID vaccinations among 80+ population\n", + " ### by Learning disability" ], "text/plain": [ "" @@ -8638,7 +8318,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8656,10 +8336,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8685,7 +8365,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8693,7 +8373,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8706,7 +8386,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8718,7 +8398,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8731,7 +8411,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8741,7 +8421,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8754,12 +8434,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8772,7 +8452,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8781,7 +8461,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -8791,123 +8471,150 @@ " \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", " \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", @@ -8916,40 +8623,29 @@ " \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", @@ -8963,14 +8659,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9001,45 +8697,39 @@ " \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", @@ -9055,8 +8745,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by Chronic cardiac disease" + "### DateCOVID vaccinations among 80+ population\n", + " ### by Learning disability" ], "text/plain": [ "" @@ -9086,10 +8776,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9115,7 +8805,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9123,7 +8813,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9136,7 +8826,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9148,7 +8838,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9161,7 +8851,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9171,7 +8861,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9184,12 +8874,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9202,7 +8892,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9211,7 +8901,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9221,44 +8911,52 @@ " \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", @@ -9266,78 +8964,97 @@ " \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", - " \n", + " \n", " \n", " \n", " \n", @@ -9346,40 +9063,29 @@ " \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", @@ -9393,14 +9099,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9433,22 +9139,22 @@ " \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", @@ -9463,7 +9169,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9479,8 +9185,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by Current COPD" + "### COVID vaccinations among 80+ population\n", + " ### by Psychosis, schizophrenia, or bipolar" ], "text/plain": [ "" @@ -9510,10 +9216,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9539,7 +9245,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9547,7 +9253,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9560,7 +9266,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9572,7 +9278,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9585,7 +9291,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9595,7 +9301,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9608,12 +9314,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9626,7 +9332,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9635,7 +9341,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9645,157 +9351,133 @@ " \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", " \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", @@ -9804,40 +9486,29 @@ " \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", @@ -9851,14 +9522,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9891,22 +9562,22 @@ " \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", @@ -9921,7 +9592,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9937,8 +9608,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by Dialysis" + "### DateCOVID vaccinations among 80+ population\n", + " ### by Psychosis, schizophrenia, or bipolar" ], "text/plain": [ "" @@ -9968,10 +9639,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -9997,7 +9668,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10005,7 +9676,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10018,7 +9689,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10030,7 +9701,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10043,7 +9714,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10053,7 +9724,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10066,12 +9737,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10084,7 +9755,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10093,7 +9764,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10103,171 +9774,133 @@ " \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", " \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", @@ -10276,40 +9909,29 @@ " \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", @@ -10323,14 +9945,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10363,22 +9985,22 @@ " \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", @@ -10393,7 +10015,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10409,8 +10031,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by Dementia" + "### COVID vaccinations among 80+ population\n", + " ### by SSRI (last 12 months)" ], "text/plain": [ "" @@ -10440,10 +10062,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10469,7 +10091,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10477,7 +10099,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10490,7 +10112,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10502,7 +10124,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10515,7 +10137,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10525,7 +10147,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10538,12 +10160,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10556,7 +10178,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10565,7 +10187,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10575,44 +10197,52 @@ " \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", @@ -10620,12 +10250,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10634,12 +10264,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10648,12 +10278,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10665,12 +10295,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10682,12 +10312,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10698,17 +10328,19 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", + " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10717,40 +10349,29 @@ " \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", @@ -10764,14 +10385,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10804,22 +10425,22 @@ " \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", @@ -10834,7 +10455,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10850,8 +10471,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by Learning disability" + "### DateCOVID vaccinations among 80+ population\n", + " ### by SSRI (last 12 months)" ], "text/plain": [ "" @@ -10881,10 +10502,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10910,7 +10531,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10918,7 +10539,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10931,7 +10552,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10943,7 +10564,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10956,7 +10577,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10966,7 +10587,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10979,12 +10600,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -10997,7 +10618,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11006,7 +10627,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11016,44 +10637,52 @@ " \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", @@ -11061,78 +10690,97 @@ " \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", - " \n", + " \n", " \n", " \n", " \n", @@ -11141,40 +10789,29 @@ " \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", @@ -11188,14 +10825,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11228,22 +10865,22 @@ " \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", @@ -11258,7 +10895,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11274,8 +10911,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by Psychosis, schizophrenia, or bipolar" + "### COVID vaccinations among 80+ population\n", + " ### by Age band" ], "text/plain": [ "" @@ -11287,7 +10924,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11305,10 +10942,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11334,7 +10971,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11342,7 +10979,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11355,7 +10992,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11367,7 +11004,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11380,7 +11017,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11390,7 +11027,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11403,12 +11040,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11421,7 +11058,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11430,7 +11067,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11440,44 +11077,52 @@ " \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", @@ -11485,78 +11130,97 @@ " \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", - " \n", + " \n", " \n", " \n", " \n", @@ -11565,40 +11229,71 @@ " \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", @@ -11612,14 +11307,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11650,39 +11345,239 @@ " \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", + " \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", + " \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", @@ -11698,8 +11593,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by SSRI (last 12 months)" + "### DateCOVID vaccinations among 80+ population\n", + " ### by Age band" ], "text/plain": [ "" @@ -11711,7 +11606,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11729,10 +11624,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11758,7 +11653,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11766,7 +11661,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11779,7 +11674,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11791,7 +11686,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11804,7 +11699,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11814,7 +11709,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11827,12 +11722,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11845,7 +11740,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11854,7 +11749,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -11864,44 +11759,52 @@ " \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", @@ -11909,78 +11812,97 @@ " \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", - " \n", + " \n", " \n", " \n", " \n", @@ -11989,40 +11911,71 @@ " \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", @@ -12036,14 +11989,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12074,89 +12027,324 @@ " \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", - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by 2nd dose" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/svg+xml": [ - "\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", + " \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", + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "chartlist = find_and_sort_filenames(foldername=\"figures\",\n", + " files_to_exclude=[\"Cumulative vaccination figures.svg\"])\n", + " \n", + "display(Markdown(\"## 80+ population\"))\n", + "for item in chartlist:\n", + " show_chart(item)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Trends in vaccination rates of 70-79 population according to demographic/clinical features, cumulatively by day. \n", + "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "## 70-79 population" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "### COVID vaccinations among 70-79 population\n", + " ### by Sex" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/svg+xml": [ + "\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", @@ -12182,7 +12370,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12190,7 +12378,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12203,7 +12391,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12215,7 +12403,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12228,7 +12416,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12238,7 +12426,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12251,12 +12439,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12269,7 +12457,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12278,7 +12466,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12288,123 +12476,133 @@ " \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", " \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", @@ -12413,40 +12611,29 @@ " \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", @@ -12460,14 +12647,14 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12483,57 +12670,48 @@ " \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", @@ -12549,8 +12727,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 70-79 population\n", - " ### by Age band" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by Sex" ], "text/plain": [ "" @@ -12562,7 +12740,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12580,10 +12758,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12609,7 +12787,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12617,7 +12795,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12630,7 +12808,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12642,7 +12820,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12655,7 +12833,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12665,7 +12843,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12678,12 +12856,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12696,7 +12874,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12705,7 +12883,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12715,44 +12893,52 @@ " \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", @@ -12760,78 +12946,80 @@ " \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", @@ -12840,82 +13028,29 @@ " \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", @@ -12929,14 +13064,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -12967,240 +13102,33 @@ " \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", - " \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", - " \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", @@ -13212,49 +13140,12 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - " \n", - "display(Markdown(\"## 70-79 population\"))\n", - "chartlist2 = find_and_sort_filenames(foldername=\"figures\", population_subset=\"70-79\",\n", - " files_to_exclude=[\"Cumulative vaccination figures.svg\"])\n", - " \n", - "for item in chartlist2:\n", - " show_chart(item) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## \n", - "## Trends in vaccination rates of **shielding** population according to demographic/clinical features, cumulatively by day. \n", - "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "## Shielding population (aged 16-69)" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" }, { "data": { "text/markdown": [ - "### COVID vaccinations among shielding (aged 16-69) population\n", - " ### by newly shielded since feb 15" + "### COVID vaccinations among 70-79 population\n", + " ### by Ethnicity (broad categories)" ], "text/plain": [ "" @@ -13266,7 +13157,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -13284,10 +13175,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -13300,7 +13191,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -13313,20 +13204,42 @@ " \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", @@ -13334,22 +13247,22 @@ " \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", @@ -13357,17 +13270,17 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -13375,22 +13288,21 @@ " \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", @@ -13398,44 +13310,52 @@ " \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", @@ -13443,136 +13363,80 @@ " \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", - " \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", @@ -13581,40 +13445,41 @@ " \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", @@ -13628,14 +13493,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -13666,39 +13531,126 @@ " \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", + " \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", @@ -13714,8 +13666,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among shielding (aged 16-69) population\n", - " ### by Age band" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by Ethnicity (broad categories)" ], "text/plain": [ "" @@ -13727,7 +13679,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -13745,10 +13697,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -13761,7 +13713,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -13774,43 +13726,65 @@ " \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", @@ -13818,17 +13792,17 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -13836,22 +13810,21 @@ " \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", @@ -13859,44 +13832,52 @@ " \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", @@ -13904,95 +13885,80 @@ " \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", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -14001,55 +13967,41 @@ " \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", @@ -14063,14 +14015,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -14101,119 +14053,126 @@ " \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", + " \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", @@ -14229,8 +14188,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among shielding (aged 16-69) population\n", - " ### by Sex" + "### COVID vaccinations among 70-79 population\n", + " ### by Index of Multiple Deprivation (quintiles)" ], "text/plain": [ "" @@ -14242,7 +14201,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -14260,10 +14219,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -14289,20 +14248,42 @@ " \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", @@ -14310,22 +14291,22 @@ " \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", @@ -14333,17 +14314,17 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -14351,22 +14332,21 @@ " \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", @@ -14374,44 +14354,52 @@ " \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", @@ -14419,136 +14407,80 @@ " \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", - " \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", @@ -14557,40 +14489,41 @@ " \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", @@ -14604,14 +14537,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -14642,83 +14575,170 @@ " \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", - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/markdown": [ - "### COVID vaccinations among shielding (aged 16-69) population\n", - " ### by Ethnicity (broad categories)" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/svg+xml": [ - "\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", + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "### DateCOVID vaccinations among 70-79 population\n", + " ### by Index of Multiple Deprivation (quintiles)" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/svg+xml": [ + "\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", @@ -14731,7 +14751,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -14744,20 +14764,42 @@ " \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", @@ -14765,22 +14807,22 @@ " \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", @@ -14788,17 +14830,17 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -14806,22 +14848,21 @@ " \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", @@ -14829,140 +14870,133 @@ " \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", " \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", @@ -14971,73 +15005,62 @@ " \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", @@ -15068,95 +15091,106 @@ " \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", + " \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", @@ -15166,29 +15200,12 @@ " \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", "" @@ -15203,8 +15220,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among shielding (aged 16-69) population\n", - " ### by Index of Multiple Deprivation (quintiles)" + "### COVID vaccinations among 70-79 population\n", + " ### by BMI" ], "text/plain": [ "" @@ -15216,7 +15233,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -15234,10 +15251,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -15263,20 +15280,42 @@ " \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", @@ -15284,22 +15323,22 @@ " \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", @@ -15307,17 +15346,17 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -15325,22 +15364,21 @@ " \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", @@ -15348,44 +15386,52 @@ " \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", @@ -15393,78 +15439,80 @@ " \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", @@ -15473,52 +15521,29 @@ " \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", @@ -15532,14 +15557,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -15570,120 +15595,48 @@ " \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", - " \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", @@ -15699,8 +15652,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among shielding (aged 16-69) population\n", - " ### by Learning disability" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by BMI" ], "text/plain": [ "" @@ -15712,7 +15665,7 @@ { "data": { "image/svg+xml": [ - "\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", @@ -15746,7 +15699,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -15759,20 +15712,42 @@ " \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", @@ -15780,22 +15755,22 @@ " \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", @@ -15803,17 +15778,17 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -15821,22 +15796,21 @@ " \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", @@ -15844,181 +15818,133 @@ " \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", " \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", " \n", " \n", " \n", + " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16027,61 +15953,50 @@ " \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", @@ -16112,40 +16027,49 @@ " \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", "" @@ -16156,49 +16080,12 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - " \n", - "display(Markdown(\"## Shielding population (aged 16-69)\"))\n", - "chartlist2 = find_and_sort_filenames(foldername=\"figures\", population_subset=\"shielding (aged 16-69)\",\n", - " files_to_exclude=[\"Cumulative vaccination figures.svg\"])\n", - " \n", - "for item in chartlist2:\n", - " show_chart(item) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## \n", - "## Trends in vaccination rates of 65-69 population according to demographic/clinical features, cumulatively by day. \n", - "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "## 65-69 population" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" }, { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", - " ### by Sex" + "### COVID vaccinations among 70-79 population\n", + " ### by Chronic cardiac disease" ], "text/plain": [ "" @@ -16210,7 +16097,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16228,10 +16115,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16257,7 +16144,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16265,7 +16152,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16278,7 +16165,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16290,7 +16177,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16303,7 +16190,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16313,7 +16200,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16326,12 +16213,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16344,7 +16231,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16353,7 +16240,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16363,44 +16250,52 @@ " \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", @@ -16408,78 +16303,97 @@ " \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", - " \n", + " \n", " \n", " \n", " \n", @@ -16488,40 +16402,29 @@ " \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", @@ -16535,14 +16438,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16573,33 +16476,39 @@ " \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", @@ -16615,8 +16524,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", - " ### by Ethnicity (broad categories)" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by Chronic cardiac disease" ], "text/plain": [ "" @@ -16628,7 +16537,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16646,10 +16555,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16675,7 +16584,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16683,7 +16592,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16696,7 +16605,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16708,7 +16617,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16721,7 +16630,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16731,7 +16640,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16744,12 +16653,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16762,7 +16671,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16771,7 +16680,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -16781,44 +16690,52 @@ " \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", @@ -16826,78 +16743,97 @@ " \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", - " \n", + " \n", " \n", " \n", " \n", @@ -16906,52 +16842,29 @@ " \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", @@ -16965,14 +16878,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17003,126 +16916,39 @@ " \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", - " \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", @@ -17138,8 +16964,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", - " ### by Index of Multiple Deprivation (quintiles)" + "### COVID vaccinations among 70-79 population\n", + " ### by Current COPD" ], "text/plain": [ "" @@ -17151,7 +16977,7 @@ { "data": { "image/svg+xml": [ - "\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", @@ -17185,7 +17011,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17198,7 +17024,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17206,7 +17032,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17219,7 +17045,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17231,7 +17057,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17244,7 +17070,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17254,7 +17080,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17267,12 +17093,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17285,7 +17111,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17294,7 +17120,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17304,140 +17130,133 @@ " \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", " \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", @@ -17446,64 +17265,41 @@ " \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", @@ -17512,7 +17308,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17543,120 +17339,40 @@ " \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", - " \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", "" @@ -17671,8 +17387,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", - " ### by BMI" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by Current COPD" ], "text/plain": [ "" @@ -17684,7 +17400,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17702,10 +17418,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17731,7 +17447,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17739,7 +17455,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17752,7 +17468,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17764,7 +17480,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17777,7 +17493,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17787,7 +17503,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17800,12 +17516,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17818,7 +17534,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17827,7 +17543,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -17837,44 +17553,52 @@ " \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", @@ -17882,78 +17606,80 @@ " \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", @@ -17962,40 +17688,29 @@ " \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", @@ -18009,14 +17724,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18047,45 +17762,39 @@ " \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", @@ -18101,8 +17810,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", - " ### by Chronic cardiac disease" + "### COVID vaccinations among 70-79 population\n", + " ### by Dialysis" ], "text/plain": [ "" @@ -18132,10 +17841,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18161,7 +17870,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18169,7 +17878,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18182,7 +17891,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18194,7 +17903,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18207,7 +17916,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18217,7 +17926,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18230,12 +17939,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18248,7 +17957,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18257,7 +17966,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18267,44 +17976,52 @@ " \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", @@ -18312,126 +18029,80 @@ " \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", - " \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", @@ -18440,40 +18111,29 @@ " \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", @@ -18487,14 +18147,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18527,22 +18187,22 @@ " \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", @@ -18557,7 +18217,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18573,8 +18233,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", - " ### by Current COPD" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by Dialysis" ], "text/plain": [ "" @@ -18604,10 +18264,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18620,7 +18280,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18633,7 +18293,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18641,7 +18301,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18654,7 +18314,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18666,7 +18326,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18679,7 +18339,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18689,7 +18349,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18702,12 +18362,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18720,7 +18380,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18729,7 +18389,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18739,44 +18399,52 @@ " \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", @@ -18784,78 +18452,80 @@ " \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", @@ -18864,40 +18534,29 @@ " \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", @@ -18911,14 +18570,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18951,27 +18610,27 @@ " \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", @@ -18981,7 +18640,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -18997,7 +18656,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", + "### COVID vaccinations among 70-79 population\n", " ### by Dementia" ], "text/plain": [ @@ -19028,10 +18687,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19044,7 +18703,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19057,7 +18716,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19065,7 +18724,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19078,7 +18737,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19090,7 +18749,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19103,7 +18762,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19113,7 +18772,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19126,12 +18785,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19144,7 +18803,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19153,7 +18812,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19163,44 +18822,52 @@ " \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", @@ -19208,78 +18875,97 @@ " \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", - " \n", + " \n", " \n", " \n", " \n", @@ -19288,40 +18974,29 @@ " \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", @@ -19335,14 +19010,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19375,27 +19050,27 @@ " \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", @@ -19405,7 +19080,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19421,8 +19096,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", - " ### by Learning disability" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by Dementia" ], "text/plain": [ "" @@ -19452,10 +19127,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19481,7 +19156,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19489,7 +19164,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19502,7 +19177,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19514,7 +19189,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19527,7 +19202,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19537,7 +19212,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19550,12 +19225,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19568,7 +19243,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19577,7 +19252,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19587,44 +19262,52 @@ " \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", @@ -19632,78 +19315,97 @@ " \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", - " \n", + " \n", " \n", " \n", " \n", @@ -19712,40 +19414,29 @@ " \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", @@ -19759,14 +19450,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19799,22 +19490,22 @@ " \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", @@ -19829,7 +19520,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19845,8 +19536,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", - " ### by Psychosis, schizophrenia, or bipolar" + "### COVID vaccinations among 70-79 population\n", + " ### by Learning disability" ], "text/plain": [ "" @@ -19858,7 +19549,7 @@ { "data": { "image/svg+xml": [ - "\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", @@ -19892,7 +19583,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19905,7 +19596,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19913,7 +19604,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19926,7 +19617,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19938,7 +19629,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19951,7 +19642,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19961,7 +19652,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19974,12 +19665,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -19992,7 +19683,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20001,7 +19692,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20011,123 +19702,167 @@ " \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", " \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", @@ -20136,61 +19871,50 @@ " \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", @@ -20221,29 +19945,29 @@ " \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", @@ -20253,8 +19977,8 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "" @@ -20269,8 +19993,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", - " ### by SSRI (last 12 months)" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by Learning disability" ], "text/plain": [ "" @@ -20282,7 +20006,7 @@ { "data": { "image/svg+xml": [ - "\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", @@ -20316,7 +20040,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20329,7 +20053,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20337,7 +20061,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20350,7 +20074,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20362,7 +20086,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20375,7 +20099,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20385,7 +20109,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20398,12 +20122,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20416,7 +20140,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20425,7 +20149,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20435,171 +20159,167 @@ " \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", " \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", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20608,52 +20328,41 @@ " \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", @@ -20662,7 +20371,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20693,21 +20402,21 @@ " \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", @@ -20715,7 +20424,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20725,8 +20434,8 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "" @@ -20741,8 +20450,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 65-69 population\n", - " ### by 2nd dose" + "### COVID vaccinations among 70-79 population\n", + " ### by Psychosis, schizophrenia, or bipolar" ], "text/plain": [ "" @@ -20772,10 +20481,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20801,7 +20510,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20809,7 +20518,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20822,7 +20531,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20834,7 +20543,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20847,7 +20556,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20857,7 +20566,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20870,12 +20579,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20888,7 +20597,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20897,7 +20606,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -20907,44 +20616,52 @@ " \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", @@ -20952,78 +20669,80 @@ " \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", @@ -21032,40 +20751,29 @@ " \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", @@ -21079,14 +20787,14 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21102,42 +20810,39 @@ " \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", @@ -21152,7 +20857,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21164,49 +20869,12 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - " \n", - "display(Markdown(\"## 65-69 population\"))\n", - "chartlist2 = find_and_sort_filenames(foldername=\"figures\", population_subset=\"65-69\",\n", - " files_to_exclude=[\"Cumulative vaccination figures.svg\"])\n", - " \n", - "for item in chartlist2:\n", - " show_chart(item) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## \n", - "## Trends in vaccination rates of 60-64 population according to demographic/clinical features, cumulatively by day. \n", - "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "## 60-64 population" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" }, { "data": { "text/markdown": [ - "### COVID vaccinations among 60-64 population\n", - " ### by Sex" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by Psychosis, schizophrenia, or bipolar" ], "text/plain": [ "" @@ -21218,7 +20886,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21236,10 +20904,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21265,7 +20933,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21273,7 +20941,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21286,7 +20954,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21298,7 +20966,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21311,7 +20979,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21321,7 +20989,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21334,12 +21002,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21352,7 +21020,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21361,7 +21029,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21371,44 +21039,52 @@ " \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", @@ -21416,78 +21092,80 @@ " \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", @@ -21496,40 +21174,29 @@ " \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", @@ -21543,14 +21210,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21581,33 +21248,39 @@ " \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", @@ -21623,8 +21296,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 60-64 population\n", - " ### by Ethnicity (broad categories)" + "### COVID vaccinations among 70-79 population\n", + " ### by SSRI (last 12 months)" ], "text/plain": [ "" @@ -21636,7 +21309,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21654,10 +21327,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21683,7 +21356,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21691,7 +21364,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21704,7 +21377,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21716,7 +21389,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21729,7 +21402,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21739,7 +21412,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21752,12 +21425,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21770,7 +21443,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21779,7 +21452,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -21789,44 +21462,52 @@ " \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", @@ -21834,78 +21515,80 @@ " \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", @@ -21914,52 +21597,29 @@ " \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", @@ -21973,14 +21633,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22011,126 +21671,39 @@ " \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", - " \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", @@ -22146,8 +21719,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 60-64 population\n", - " ### by Index of Multiple Deprivation (quintiles)" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by SSRI (last 12 months)" ], "text/plain": [ "" @@ -22159,7 +21732,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22177,10 +21750,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22206,7 +21779,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22214,7 +21787,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22227,7 +21800,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22239,7 +21812,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22252,7 +21825,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22262,7 +21835,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22275,12 +21848,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22293,7 +21866,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22302,7 +21875,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22312,44 +21885,52 @@ " \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", @@ -22357,78 +21938,80 @@ " \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", @@ -22437,52 +22020,29 @@ " \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", @@ -22496,14 +22056,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22534,120 +22094,39 @@ " \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", + " \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", @@ -22663,8 +22142,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 60-64 population\n", - " ### by BMI" + "### COVID vaccinations among 70-79 population\n", + " ### by Age band" ], "text/plain": [ "" @@ -22676,7 +22155,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22694,10 +22173,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22723,7 +22202,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22731,7 +22210,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22744,7 +22223,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22756,7 +22235,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22769,7 +22248,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22779,7 +22258,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22792,12 +22271,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22810,7 +22289,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22819,7 +22298,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -22829,44 +22308,52 @@ " \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", @@ -22874,78 +22361,80 @@ " \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", @@ -22954,40 +22443,71 @@ " \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", @@ -23001,14 +22521,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23039,45 +22559,240 @@ " \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", + " \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", + " \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", @@ -23093,8 +22808,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 60-64 population\n", - " ### by Chronic cardiac disease" + "### DateCOVID vaccinations among 70-79 population\n", + " ### by Age band" ], "text/plain": [ "" @@ -23106,7 +22821,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23124,10 +22839,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23153,7 +22868,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23161,7 +22876,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23174,7 +22889,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23186,7 +22901,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23199,7 +22914,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23209,7 +22924,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23222,12 +22937,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23240,7 +22955,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23249,7 +22964,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23259,44 +22974,52 @@ " \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", @@ -23304,126 +23027,80 @@ " \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", - " \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", @@ -23432,40 +23109,71 @@ " \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", @@ -23479,14 +23187,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23517,39 +23225,240 @@ " \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", + " \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", + " \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", @@ -23561,12 +23470,49 @@ }, "metadata": {}, "output_type": "display_data" + } + ], + "source": [ + " \n", + "display(Markdown(\"## 70-79 population\"))\n", + "chartlist2 = find_and_sort_filenames(foldername=\"figures\", population_subset=\"70-79\",\n", + " files_to_exclude=[\"Cumulative vaccination figures.svg\"])\n", + " \n", + "for item in chartlist2:\n", + " show_chart(item) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## \n", + "## Trends in vaccination rates of **shielding** population according to demographic/clinical features, cumulatively by day. \n", + "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "## Shielding population (aged 16-69)" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" }, { "data": { "text/markdown": [ - "### COVID vaccinations among 60-64 population\n", - " ### by Current COPD" + "### COVID vaccinations among shielding (aged 16-69) population\n", + " ### by newly shielded since feb 15" ], "text/plain": [ "" @@ -23596,25 +23542,25 @@ " \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", @@ -23625,42 +23571,41 @@ " \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", @@ -23671,19 +23616,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -23694,67 +23638,58 @@ " \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", @@ -23762,15 +23697,15 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23778,12 +23713,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23792,12 +23727,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23806,7 +23741,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23814,7 +23749,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23823,7 +23758,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23831,23 +23766,25 @@ " \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", @@ -23856,40 +23793,29 @@ " \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", @@ -23910,7 +23836,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23973,7 +23899,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -23989,8 +23915,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 60-64 population\n", - " ### by Dementia" + "### DateCOVID vaccinations among shielding (aged 16-69) population\n", + " ### by newly shielded since feb 15" ], "text/plain": [ "" @@ -24020,25 +23946,25 @@ " \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", @@ -24049,42 +23975,41 @@ " \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", @@ -24095,19 +24020,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -24118,67 +24042,58 @@ " \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", @@ -24186,15 +24101,15 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24202,12 +24117,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24216,12 +24131,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24230,7 +24145,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24238,7 +24153,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24247,7 +24162,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24255,40 +24170,25 @@ " \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", @@ -24297,40 +24197,29 @@ " \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", @@ -24344,14 +24233,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24384,22 +24273,22 @@ " \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", @@ -24414,7 +24303,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24430,8 +24319,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 60-64 population\n", - " ### by Psychosis, schizophrenia, or bipolar" + "### COVID vaccinations among shielding (aged 16-69) population\n", + " ### by Age band" ], "text/plain": [ "" @@ -24443,7 +24332,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24461,25 +24350,25 @@ " \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", @@ -24490,42 +24379,41 @@ " \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", @@ -24536,19 +24424,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -24559,67 +24446,58 @@ " \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", @@ -24627,10 +24505,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24643,12 +24521,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24657,12 +24535,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24671,7 +24549,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24679,7 +24557,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24688,7 +24566,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24696,23 +24574,56 @@ " \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", @@ -24721,40 +24632,44 @@ " \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", @@ -24768,14 +24683,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24806,39 +24721,117 @@ " \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", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24854,8 +24847,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 60-64 population\n", - " ### by SSRI (last 12 months)" + "### DateCOVID vaccinations among shielding (aged 16-69) population\n", + " ### by Age band" ], "text/plain": [ "" @@ -24867,7 +24860,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24885,25 +24878,25 @@ " \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", @@ -24914,42 +24907,41 @@ " \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", @@ -24960,19 +24952,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -24983,67 +24974,58 @@ " \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", @@ -25051,10 +25033,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25067,12 +25049,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25081,12 +25063,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25095,7 +25077,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25103,7 +25085,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25112,7 +25094,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25120,23 +25102,56 @@ " \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", @@ -25145,40 +25160,44 @@ " \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", @@ -25192,14 +25211,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25230,39 +25249,117 @@ " \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", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25278,8 +25375,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 60-64 population\n", - " ### by 2nd dose" + "### COVID vaccinations among shielding (aged 16-69) population\n", + " ### by Sex" ], "text/plain": [ "" @@ -25291,7 +25388,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25309,25 +25406,25 @@ " \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", @@ -25338,42 +25435,41 @@ " \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", @@ -25384,19 +25480,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -25407,67 +25502,58 @@ " \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", @@ -25475,10 +25561,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25491,12 +25577,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25505,12 +25591,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25519,7 +25605,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25527,7 +25613,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25536,7 +25622,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25544,23 +25630,25 @@ " \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", @@ -25569,40 +25657,29 @@ " \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", @@ -25617,13 +25694,13 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25639,35 +25716,31 @@ " \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", @@ -25675,21 +25748,16 @@ " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", " \n", - " \n", - " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25701,52 +25769,11 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - "display(Markdown(\"## 60-64 population\"))\n", - "chartlist2 = find_and_sort_filenames(foldername=\"figures\", population_subset=\"60-64\",\n", - " files_to_exclude=[\"Cumulative vaccination figures.svg\"])\n", - " \n", - "for item in chartlist2:\n", - " show_chart(item) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## \n", - "## Trends in vaccination rates of 55-59 population according to demographic/clinical features, cumulatively by day. \n", - "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - } - }, - "outputs": [ - { - "data": { - "text/markdown": [ - "## 55-59 population" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" }, { "data": { "text/markdown": [ - "### COVID vaccinations among 55-59 population\n", + "### DateCOVID vaccinations among shielding (aged 16-69) population\n", " ### by Sex" ], "text/plain": [ @@ -25777,25 +25804,25 @@ " \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", @@ -25806,42 +25833,41 @@ " \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", @@ -25852,19 +25878,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -25875,67 +25900,58 @@ " \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", @@ -25943,10 +25959,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25959,12 +25975,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25973,12 +25989,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25987,7 +26003,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25995,7 +26011,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26004,7 +26020,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26012,23 +26028,25 @@ " \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", @@ -26037,40 +26055,29 @@ " \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", @@ -26091,7 +26098,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26148,7 +26155,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26164,7 +26171,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 55-59 population\n", + "### COVID vaccinations among shielding (aged 16-69) population\n", " ### by Ethnicity (broad categories)" ], "text/plain": [ @@ -26195,25 +26202,25 @@ " \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", @@ -26224,42 +26231,41 @@ " \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", @@ -26270,19 +26276,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -26293,67 +26298,58 @@ " \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", @@ -26361,10 +26357,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26377,12 +26373,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26391,12 +26387,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26405,7 +26401,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26413,7 +26409,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26422,7 +26418,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26430,23 +26426,42 @@ " \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", @@ -26455,52 +26470,41 @@ " \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", @@ -26514,14 +26518,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26554,11 +26558,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -26572,14 +26576,15 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", + " \n", " \n", " \n", " \n", @@ -26589,11 +26594,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -26606,15 +26611,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", " \n", " \n", " \n", @@ -26630,11 +26634,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -26650,11 +26654,11 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -26671,7 +26675,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26687,8 +26691,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 55-59 population\n", - " ### by Index of Multiple Deprivation (quintiles)" + "### DateCOVID vaccinations among shielding (aged 16-69) population\n", + " ### by Ethnicity (broad categories)" ], "text/plain": [ "" @@ -26700,7 +26704,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26718,25 +26722,25 @@ " \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", @@ -26747,42 +26751,41 @@ " \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", @@ -26793,19 +26796,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -26816,67 +26818,58 @@ " \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", @@ -26884,10 +26877,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26900,12 +26893,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26914,12 +26907,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26928,7 +26921,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26936,7 +26929,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26945,7 +26938,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -26953,23 +26946,42 @@ " \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", @@ -26978,52 +26990,41 @@ " \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", @@ -27037,14 +27038,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27075,106 +27076,95 @@ " \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", + " \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", @@ -27184,11 +27174,28 @@ " \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", @@ -27204,8 +27211,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 55-59 population\n", - " ### by BMI" + "### COVID vaccinations among shielding (aged 16-69) population\n", + " ### by Index of Multiple Deprivation (quintiles)" ], "text/plain": [ "" @@ -27217,7 +27224,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27235,25 +27242,25 @@ " \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", @@ -27264,42 +27271,41 @@ " \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", @@ -27310,19 +27316,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -27333,67 +27338,58 @@ " \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", @@ -27401,15 +27397,15 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27417,12 +27413,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27431,12 +27427,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27445,7 +27441,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27453,7 +27449,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27462,7 +27458,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27470,23 +27466,42 @@ " \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", @@ -27495,40 +27510,41 @@ " \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", @@ -27542,14 +27558,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27580,45 +27596,119 @@ " \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", + " \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", @@ -27634,8 +27724,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 55-59 population\n", - " ### by Chronic cardiac disease" + "### DateCOVID vaccinations among shielding (aged 16-69) population\n", + " ### by Index of Multiple Deprivation (quintiles)" ], "text/plain": [ "" @@ -27647,7 +27737,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27665,25 +27755,25 @@ " \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", @@ -27694,42 +27784,41 @@ " \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", @@ -27740,19 +27829,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -27763,67 +27851,58 @@ " \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", @@ -27831,15 +27910,15 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27847,12 +27926,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27861,12 +27940,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27875,7 +27954,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27883,7 +27962,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27892,7 +27971,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -27900,23 +27979,42 @@ " \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", @@ -27925,40 +28023,41 @@ " \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", @@ -27972,14 +28071,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28010,39 +28109,119 @@ " \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", + " \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", @@ -28058,8 +28237,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 55-59 population\n", - " ### by Current COPD" + "### COVID vaccinations among shielding (aged 16-69) population\n", + " ### by Learning disability" ], "text/plain": [ "" @@ -28089,25 +28268,25 @@ " \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", @@ -28118,42 +28297,41 @@ " \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", @@ -28164,19 +28342,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -28187,67 +28364,58 @@ " \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", @@ -28255,10 +28423,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28271,12 +28439,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28285,12 +28453,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28299,7 +28467,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28307,7 +28475,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28316,7 +28484,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28324,23 +28492,25 @@ " \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", @@ -28349,40 +28519,29 @@ " \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", @@ -28403,7 +28562,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28466,7 +28625,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28482,8 +28641,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 55-59 population\n", - " ### by Psychosis, schizophrenia, or bipolar" + "### DateCOVID vaccinations among shielding (aged 16-69) population\n", + " ### by Learning disability" ], "text/plain": [ "" @@ -28513,25 +28672,25 @@ " \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", @@ -28542,42 +28701,41 @@ " \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", @@ -28588,19 +28746,18 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -28611,67 +28768,58 @@ " \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", @@ -28679,10 +28827,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28695,12 +28843,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28709,12 +28857,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28723,7 +28871,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28731,7 +28879,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28740,7 +28888,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28748,40 +28896,25 @@ " \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", @@ -28790,40 +28923,29 @@ " \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", @@ -28837,14 +28959,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28877,22 +28999,22 @@ " \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", @@ -28907,7 +29029,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28919,12 +29041,49 @@ }, "metadata": {}, "output_type": "display_data" + } + ], + "source": [ + " \n", + "display(Markdown(\"## Shielding population (aged 16-69)\"))\n", + "chartlist2 = find_and_sort_filenames(foldername=\"figures\", population_subset=\"shielding (aged 16-69)\",\n", + " files_to_exclude=[\"Cumulative vaccination figures.svg\"])\n", + " \n", + "for item in chartlist2:\n", + " show_chart(item) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## \n", + "## Trends in vaccination rates of 65-69 population according to demographic/clinical features, cumulatively by day. \n", + "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "## 65-69 population" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" }, { "data": { "text/markdown": [ - "### COVID vaccinations among 55-59 population\n", - " ### by SSRI (last 12 months)" + "### COVID vaccinations among 65-69 population\n", + " ### by Sex" ], "text/plain": [ "" @@ -28936,7 +29095,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28954,10 +29113,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28983,7 +29142,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -28991,7 +29150,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29004,7 +29163,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29016,7 +29175,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29029,7 +29188,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29039,7 +29198,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29052,12 +29211,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29070,7 +29229,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29079,7 +29238,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29089,44 +29248,52 @@ " \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", @@ -29134,95 +29301,80 @@ " \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", + " \n", " \n", " \n", " \n", @@ -29231,40 +29383,29 @@ " \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", @@ -29285,7 +29426,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29316,17 +29457,16 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", - " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29334,21 +29474,16 @@ " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", + " \n", " \n", - " \n", - " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29360,47 +29495,11 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - "display(Markdown(\"## 55-59 population\"))\n", - "chartlist2 = find_and_sort_filenames(foldername=\"figures\", population_subset=\"55-59\",\n", - " files_to_exclude=[\"Cumulative vaccination figures.svg\"])\n", - " \n", - "for item in chartlist2:\n", - " show_chart(item) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## \n", - "## Trends in vaccination rates of 50-54 population according to demographic/clinical features, cumulatively by day. \n", - "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "## 50-54 population" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" }, { "data": { "text/markdown": [ - "### COVID vaccinations among 50-54 population\n", + "### DateCOVID vaccinations among 65-69 population\n", " ### by Sex" ], "text/plain": [ @@ -29431,10 +29530,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29460,7 +29559,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29468,7 +29567,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29481,7 +29580,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29493,7 +29592,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29506,7 +29605,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29516,7 +29615,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29529,12 +29628,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29547,7 +29646,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29556,7 +29655,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29566,44 +29665,52 @@ " \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", @@ -29611,136 +29718,80 @@ " \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", - " \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", @@ -29749,40 +29800,29 @@ " \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", @@ -29796,14 +29836,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29836,21 +29876,21 @@ " \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", @@ -29860,7 +29900,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29876,7 +29916,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 50-54 population\n", + "### COVID vaccinations among 65-69 population\n", " ### by Ethnicity (broad categories)" ], "text/plain": [ @@ -29907,10 +29947,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29923,7 +29963,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29936,7 +29976,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29944,7 +29984,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29957,7 +29997,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29969,7 +30009,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29982,7 +30022,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -29992,7 +30032,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30005,12 +30045,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30023,7 +30063,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30032,7 +30072,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30042,44 +30082,52 @@ " \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", @@ -30087,78 +30135,80 @@ " \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", @@ -30167,52 +30217,41 @@ " \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", @@ -30226,14 +30265,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30266,17 +30305,17 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30284,16 +30323,17 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30301,16 +30341,16 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30318,17 +30358,16 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30342,17 +30381,17 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30362,16 +30401,16 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30383,7 +30422,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30399,8 +30438,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 50-54 population\n", - " ### by Index of Multiple Deprivation (quintiles)" + "### DateCOVID vaccinations among 65-69 population\n", + " ### by Ethnicity (broad categories)" ], "text/plain": [ "" @@ -30412,7 +30451,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30430,10 +30469,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30446,7 +30485,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30459,7 +30498,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30467,7 +30506,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30480,7 +30519,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30492,7 +30531,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30505,7 +30544,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30515,7 +30554,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30528,12 +30567,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30546,7 +30585,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30555,7 +30594,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30565,44 +30604,52 @@ " \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", @@ -30610,78 +30657,80 @@ " \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", @@ -30690,52 +30739,41 @@ " \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", @@ -30749,14 +30787,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30787,106 +30825,95 @@ " \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", - " \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", @@ -30896,11 +30923,28 @@ " \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", @@ -30916,8 +30960,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 50-54 population\n", - " ### by BMI" + "### COVID vaccinations among 65-69 population\n", + " ### by Index of Multiple Deprivation (quintiles)" ], "text/plain": [ "" @@ -30929,7 +30973,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30947,10 +30991,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30976,7 +31020,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30984,7 +31028,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -30997,7 +31041,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31009,7 +31053,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31022,7 +31066,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31032,7 +31076,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31045,12 +31089,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31063,7 +31107,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31072,7 +31116,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31082,44 +31126,52 @@ " \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", @@ -31127,136 +31179,80 @@ " \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", - " \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", @@ -31265,40 +31261,41 @@ " \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", @@ -31312,14 +31309,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31350,45 +31347,120 @@ " \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", + " \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", @@ -31404,8 +31476,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 50-54 population\n", - " ### by Chronic cardiac disease" + "### DateCOVID vaccinations among 65-69 population\n", + " ### by Index of Multiple Deprivation (quintiles)" ], "text/plain": [ "" @@ -31417,7 +31489,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31435,10 +31507,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31464,7 +31536,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31472,7 +31544,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31485,7 +31557,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31497,7 +31569,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31510,7 +31582,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31520,7 +31592,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31533,12 +31605,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31551,7 +31623,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31560,7 +31632,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31570,44 +31642,52 @@ " \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", @@ -31615,78 +31695,80 @@ " \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", @@ -31695,40 +31777,41 @@ " \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", @@ -31742,14 +31825,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31780,39 +31863,120 @@ " \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", + " \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", @@ -31828,8 +31992,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 50-54 population\n", - " ### by Current COPD" + "### COVID vaccinations among 65-69 population\n", + " ### by BMI" ], "text/plain": [ "" @@ -31841,7 +32005,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31859,10 +32023,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31888,7 +32052,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31896,7 +32060,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31909,7 +32073,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31921,7 +32085,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31934,7 +32098,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31944,7 +32108,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31957,12 +32121,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31975,7 +32139,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31984,7 +32148,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -31994,44 +32158,52 @@ " \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", @@ -32039,136 +32211,80 @@ " \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", - " \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", @@ -32177,40 +32293,29 @@ " \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", @@ -32224,14 +32329,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32262,39 +32367,48 @@ " \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", @@ -32310,8 +32424,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 50-54 population\n", - " ### by Psychosis, schizophrenia, or bipolar" + "### DateCOVID vaccinations among 65-69 population\n", + " ### by BMI" ], "text/plain": [ "" @@ -32323,7 +32437,7 @@ { "data": { "image/svg+xml": [ - "\n", + "\n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32341,10 +32455,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32370,7 +32484,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32378,7 +32492,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32391,7 +32505,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32403,7 +32517,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32416,7 +32530,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32426,7 +32540,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32439,12 +32553,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32457,7 +32571,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32466,7 +32580,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32476,44 +32590,52 @@ " \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", @@ -32521,78 +32643,80 @@ " \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", @@ -32601,40 +32725,29 @@ " \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", @@ -32648,14 +32761,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32686,39 +32799,48 @@ " \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", @@ -32734,8 +32856,8 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among 50-54 population\n", - " ### by SSRI (last 12 months)" + "### COVID vaccinations among 65-69 population\n", + " ### by Chronic cardiac disease" ], "text/plain": [ "" @@ -32765,10 +32887,10 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32794,7 +32916,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32802,7 +32924,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32815,7 +32937,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32827,7 +32949,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32840,7 +32962,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32850,7 +32972,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32863,12 +32985,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32881,7 +33003,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32890,7 +33012,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -32900,44 +33022,52 @@ " \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", @@ -32945,136 +33075,80 @@ " \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", - " \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", @@ -33083,40 +33157,29 @@ " \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", @@ -33130,14 +33193,14 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -33170,22 +33233,22 @@ " \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", @@ -33200,7 +33263,7 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -33212,36 +33275,12 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - "display(Markdown(\"## 50-54 population\"))\n", - "chartlist2 = find_and_sort_filenames(foldername=\"figures\", population_subset=\"50-54\",\n", - " files_to_exclude=[\"Cumulative vaccination figures.svg\"])\n", - " \n", - "for item in chartlist2:\n", - " show_chart(item) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# \n", - "## Vaccination rates of each eligible population group, according to demographic/clinical features " - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ + }, { "data": { "text/markdown": [ - "## \n", - " ## Cumulative vaccination figures among 80+ population \n", - " Please refer to footnotes below table for information." + "### DateCOVID vaccinations among 65-69 population\n", + " ### by Chronic cardiac disease" ], "text/plain": [ "" @@ -33252,1043 +33291,26556 @@ }, { "data": { - "text/html": [ - "
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Vaccinated at 30 Mar (n)Vaccinated at 30 Mar (%)Total eligiblePrevious week's vaccination coverage (%)Vaccinated over last 7d (%)
CategoryGroup
overalloverall85140.1212137.42.7
SexF45541.1110638.62.5
M39939.3101536.62.7
Age band05644.412638.95.5
0-155638.114733.34.8
16-295640.014040.00.0
30-344936.813336.80.0
35-393527.812627.80.0
40-444235.311929.45.9
45-495644.412644.40.0
50-545642.113342.10.0
55-594938.912633.35.6
60-644935.014035.00.0
65-697052.613347.45.2
70-746342.914738.14.8
75-795640.014035.05.0
80-845647.111941.25.9
85-894938.912638.90.0
90+6345.014040.05.0
Ethnicity (broad categories)Black14036.438534.51.9
Mixed14040.035036.04.0
Other14039.235737.31.9
South Asian16141.838540.01.8
Unknown11938.630836.42.2
White14743.833641.72.1
ethnicity 16 groupsAfrican5644.412638.95.5
Bangladeshi or British Bangladeshi4242.99842.90.0
Caribbean4242.99835.77.2
Chinese4237.511237.50.0
Other4941.211935.35.9
Other Asian4941.211935.35.9
British or Mixed British4941.211935.35.9
Indian or British Indian4936.813336.80.0
Irish3533.310533.30.0
Other Black5650.011243.86.2
Other White5642.113336.85.3
Other mixed4240.010540.00.0
Pakistani or British Pakistani3535.79828.67.1
Unknown11940.529435.74.8
White + Asian4237.511237.50.0
White + Black African5644.412644.40.0
White + Black Caribbean4240.010540.00.0
Index of Multiple Deprivation (quintiles)1 Most deprived16839.342736.13.2
216842.139940.41.7
317543.140639.73.4
416842.139938.63.5
5 Least deprived14738.238534.53.7
Unknown2826.710526.70.0
BMI30+25938.966536.82.1
under 3059540.9145637.53.4
Chronic cardiac diseaseno84040.1209337.52.6
yes725.02825.00.0
Current COPDno84740.2210737.52.7
yes00.0140.00.0
Dialysisno84040.0210037.32.7
yes733.32133.30.0
DMARDsno84740.3210037.72.6
yes00.0210.00.0
Dementiano84740.3210037.72.6
yes00.0210.00.0
Psychosis, schizophrenia, or bipolarno84740.2210737.52.7
yes00.0140.00.0
Learning disabilityno82639.7207937.02.7
yes2150.04250.00.0
SSRI (last 12 months)no84040.0210037.32.7
yes733.32133.30.0
Chemo or radiotherapyno84740.2210737.52.7
yes00.0140.00.0
Cancer (lung)no84740.3210037.72.6
yes00.0210.00.0
Cancer (excluding lung/haem)no84040.1209337.52.6
yes725.02825.00.0
Cancer (haematological)no84740.3210037.72.6
yes00.0210.00.0
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vaccination figures.svg\"])\n", + " \n", + "for item in chartlist2:\n", + " show_chart(item) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## \n", + "## Trends in vaccination rates of 55-59 population according to demographic/clinical features, cumulatively by day. \n", + "**\\*National rate calculated as at latest date for vaccinations recorded across all TPP practices.**" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "## 55-59 population" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "### COVID vaccinations among 55-59 population\n", + " ### by Sex" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/svg+xml": [ + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " 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" 70-74 63 \n", - " 75-79 56 \n", - " 80-84 56 \n", - " 85-89 49 \n", - " 90+ 63 \n", - "Ethnicity (broad categories) Black 140 \n", - " Mixed 140 \n", - " Other 140 \n", - " South Asian 161 \n", - " Unknown 119 \n", - " White 147 \n", - "ethnicity 16 groups African 56 \n", - " Bangladeshi or British Bangladeshi 42 \n", - " Caribbean 42 \n", - " Chinese 42 \n", - " Other 49 \n", - " Other Asian 49 \n", - " British or Mixed British 49 \n", - " Indian or British Indian 49 \n", - " Irish 35 \n", - " Other Black 56 \n", - " Other White 56 \n", - " Other mixed 42 \n", - " Pakistani or British Pakistani 35 \n", - " Unknown 119 \n", - " White + Asian 42 \n", - " White + Black African 56 \n", - " White + Black Caribbean 42 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 168 \n", - " 2 168 \n", - " 3 175 \n", - " 4 168 \n", - " 5 Least deprived 147 \n", - " Unknown 28 \n", - "BMI 30+ 259 \n", - " under 30 595 \n", - "Chronic cardiac disease no 840 \n", - " yes 7 \n", - "Current COPD no 847 \n", - " yes 0 \n", - "Dialysis no 840 \n", - " yes 7 \n", - "DMARDs no 847 \n", - " yes 0 \n", - "Dementia no 847 \n", - " yes 0 \n", - "Psychosis, schizophrenia, or bipolar no 847 \n", - " yes 0 \n", - "Learning disability no 826 \n", - " yes 21 \n", - "SSRI (last 12 months) no 840 \n", - " yes 7 \n", - "Chemo or radiotherapy no 847 \n", - " yes 0 \n", - "Cancer (lung) no 847 \n", - " yes 0 \n", - "Cancer (excluding lung/haem) no 840 \n", - " yes 7 \n", - "Cancer (haematological) no 847 \n", - " yes 0 \n", - "\n", - " Vaccinated at 30 Mar (%) \\\n", - "Category Group \n", - "overall overall 40.1 \n", - "Sex F 41.1 \n", - " M 39.3 \n", - "Age band 0 44.4 \n", - " 0-15 38.1 \n", - " 16-29 40.0 \n", - " 30-34 36.8 \n", - " 35-39 27.8 \n", - " 40-44 35.3 \n", - " 45-49 44.4 \n", - " 50-54 42.1 \n", - " 55-59 38.9 \n", - " 60-64 35.0 \n", - " 65-69 52.6 \n", - " 70-74 42.9 \n", - " 75-79 40.0 \n", - " 80-84 47.1 \n", - " 85-89 38.9 \n", - " 90+ 45.0 \n", - "Ethnicity (broad categories) Black 36.4 \n", - " Mixed 40.0 \n", - " Other 39.2 \n", - " South Asian 41.8 \n", - " Unknown 38.6 \n", - " White 43.8 \n", - "ethnicity 16 groups African 44.4 \n", - " Bangladeshi or British Bangladeshi 42.9 \n", - " Caribbean 42.9 \n", - " Chinese 37.5 \n", - " Other 41.2 \n", - " Other Asian 41.2 \n", - " British or Mixed British 41.2 \n", - " Indian or British Indian 36.8 \n", - " Irish 33.3 \n", - " Other Black 50.0 \n", - " Other White 42.1 \n", - " Other mixed 40.0 \n", - " Pakistani or British Pakistani 35.7 \n", - " Unknown 40.5 \n", - " White + Asian 37.5 \n", - " White + Black African 44.4 \n", - " White + Black Caribbean 40.0 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 39.3 \n", - " 2 42.1 \n", - " 3 43.1 \n", - " 4 42.1 \n", - " 5 Least deprived 38.2 \n", - " Unknown 26.7 \n", - "BMI 30+ 38.9 \n", - " under 30 40.9 \n", - "Chronic cardiac disease no 40.1 \n", - " yes 25.0 \n", - "Current COPD no 40.2 \n", - " yes 0.0 \n", - "Dialysis no 40.0 \n", - " yes 33.3 \n", - "DMARDs no 40.3 \n", - " yes 0.0 \n", - "Dementia no 40.3 \n", - " yes 0.0 \n", - "Psychosis, schizophrenia, or bipolar no 40.2 \n", - " yes 0.0 \n", - "Learning disability no 39.7 \n", - " yes 50.0 \n", - "SSRI (last 12 months) no 40.0 \n", - " yes 33.3 \n", - "Chemo or radiotherapy no 40.2 \n", - " yes 0.0 \n", - "Cancer (lung) no 40.3 \n", - " yes 0.0 \n", - "Cancer (excluding lung/haem) no 40.1 \n", - " yes 25.0 \n", - "Cancer (haematological) no 40.3 \n", - " yes 0.0 \n", - "\n", - " Total eligible \\\n", - "Category Group \n", - "overall overall 2121 \n", - "Sex F 1106 \n", - " M 1015 \n", - "Age band 0 126 \n", - " 0-15 147 \n", - " 16-29 140 \n", - " 30-34 133 \n", - " 35-39 126 \n", - " 40-44 119 \n", - " 45-49 126 \n", - " 50-54 133 \n", - " 55-59 126 \n", - " 60-64 140 \n", - " 65-69 133 \n", - " 70-74 147 \n", - " 75-79 140 \n", - " 80-84 119 \n", - " 85-89 126 \n", - " 90+ 140 \n", - "Ethnicity (broad categories) Black 385 \n", - " Mixed 350 \n", - " Other 357 \n", - " South Asian 385 \n", - " Unknown 308 \n", - " White 336 \n", - "ethnicity 16 groups African 126 \n", - " Bangladeshi or British Bangladeshi 98 \n", - " Caribbean 98 \n", - " Chinese 112 \n", - " Other 119 \n", - " Other Asian 119 \n", - " British or Mixed British 119 \n", - " Indian or British Indian 133 \n", - " Irish 105 \n", - " Other Black 112 \n", - " Other White 133 \n", - " Other mixed 105 \n", - " Pakistani or British Pakistani 98 \n", - " Unknown 294 \n", - " White + Asian 112 \n", - " White + Black African 126 \n", - " White + Black Caribbean 105 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 427 \n", - " 2 399 \n", - " 3 406 \n", - " 4 399 \n", - " 5 Least deprived 385 \n", - " Unknown 105 \n", - "BMI 30+ 665 \n", - " under 30 1456 \n", - "Chronic cardiac disease no 2093 \n", - " yes 28 \n", - "Current COPD no 2107 \n", - " yes 14 \n", - "Dialysis no 2100 \n", - " yes 21 \n", - "DMARDs no 2100 \n", - " yes 21 \n", - "Dementia no 2100 \n", - " yes 21 \n", - "Psychosis, schizophrenia, or bipolar no 2107 \n", - " yes 14 \n", - "Learning disability no 2079 \n", - " yes 42 \n", - "SSRI (last 12 months) no 2100 \n", - " yes 21 \n", - "Chemo or radiotherapy no 2107 \n", - " yes 14 \n", - "Cancer (lung) no 2100 \n", - " yes 21 \n", - "Cancer (excluding lung/haem) no 2093 \n", - " yes 28 \n", - "Cancer (haematological) no 2100 \n", - " yes 21 \n", - "\n", - " Previous week's vaccination coverage (%) \\\n", - "Category Group \n", - "overall overall 37.4 \n", - "Sex F 38.6 \n", - " M 36.6 \n", - "Age band 0 38.9 \n", - " 0-15 33.3 \n", - " 16-29 40.0 \n", - " 30-34 36.8 \n", - " 35-39 27.8 \n", - " 40-44 29.4 \n", - " 45-49 44.4 \n", - " 50-54 42.1 \n", - " 55-59 33.3 \n", - " 60-64 35.0 \n", - " 65-69 47.4 \n", - " 70-74 38.1 \n", - " 75-79 35.0 \n", - " 80-84 41.2 \n", - " 85-89 38.9 \n", - " 90+ 40.0 \n", - "Ethnicity (broad categories) Black 34.5 \n", - " Mixed 36.0 \n", - " Other 37.3 \n", - " South Asian 40.0 \n", - " Unknown 36.4 \n", - " White 41.7 \n", - "ethnicity 16 groups African 38.9 \n", - " Bangladeshi or British Bangladeshi 42.9 \n", - " Caribbean 35.7 \n", - " Chinese 37.5 \n", - " Other 35.3 \n", - " Other Asian 35.3 \n", - " British or Mixed British 35.3 \n", - " Indian or British Indian 36.8 \n", - " Irish 33.3 \n", - " Other Black 43.8 \n", - " Other White 36.8 \n", - " Other mixed 40.0 \n", - " Pakistani or British Pakistani 28.6 \n", - " Unknown 35.7 \n", - " White + Asian 37.5 \n", - " White + Black African 44.4 \n", - " White + Black Caribbean 40.0 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 36.1 \n", - " 2 40.4 \n", - " 3 39.7 \n", - " 4 38.6 \n", - " 5 Least deprived 34.5 \n", - " Unknown 26.7 \n", - "BMI 30+ 36.8 \n", - " under 30 37.5 \n", - "Chronic cardiac disease no 37.5 \n", - " yes 25.0 \n", - "Current COPD no 37.5 \n", - " yes 0.0 \n", - "Dialysis no 37.3 \n", - " yes 33.3 \n", - "DMARDs no 37.7 \n", - " yes 0.0 \n", - "Dementia no 37.7 \n", - " yes 0.0 \n", - "Psychosis, schizophrenia, or bipolar no 37.5 \n", - " yes 0.0 \n", - "Learning disability no 37.0 \n", - " yes 50.0 \n", - "SSRI (last 12 months) no 37.3 \n", - " yes 33.3 \n", - "Chemo or radiotherapy no 37.5 \n", - " yes 0.0 \n", - "Cancer (lung) no 37.7 \n", - " yes 0.0 \n", - "Cancer (excluding lung/haem) no 37.5 \n", - " yes 25.0 \n", - "Cancer (haematological) no 37.7 \n", - " yes 0.0 \n", - "\n", - " Vaccinated over last 7d (%) \n", - "Category Group \n", - "overall overall 2.7 \n", - "Sex F 2.5 \n", - " M 2.7 \n", - "Age band 0 5.5 \n", - " 0-15 4.8 \n", - " 16-29 0.0 \n", - " 30-34 0.0 \n", - " 35-39 0.0 \n", - " 40-44 5.9 \n", - " 45-49 0.0 \n", - " 50-54 0.0 \n", - " 55-59 5.6 \n", - " 60-64 0.0 \n", - " 65-69 5.2 \n", - " 70-74 4.8 \n", - " 75-79 5.0 \n", - " 80-84 5.9 \n", - " 85-89 0.0 \n", - " 90+ 5.0 \n", - "Ethnicity (broad categories) Black 1.9 \n", - " Mixed 4.0 \n", - " Other 1.9 \n", - " South Asian 1.8 \n", - " Unknown 2.2 \n", - " White 2.1 \n", - "ethnicity 16 groups African 5.5 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 7.2 \n", - " Chinese 0.0 \n", - " Other 5.9 \n", - " Other Asian 5.9 \n", - " British or Mixed British 5.9 \n", - " Indian or British Indian 0.0 \n", - " Irish 0.0 \n", - " Other Black 6.2 \n", - " Other White 5.3 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 7.1 \n", - " Unknown 4.8 \n", - " White + Asian 0.0 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 3.2 \n", - " 2 1.7 \n", - " 3 3.4 \n", - " 4 3.5 \n", - " 5 Least deprived 3.7 \n", - " Unknown 0.0 \n", - "BMI 30+ 2.1 \n", - " under 30 3.4 \n", - "Chronic cardiac disease no 2.6 \n", - " yes 0.0 \n", - "Current COPD no 2.7 \n", - " yes 0.0 \n", - "Dialysis no 2.7 \n", - " yes 0.0 \n", - "DMARDs no 2.6 \n", - " yes 0.0 \n", - "Dementia no 2.6 \n", - " yes 0.0 \n", - "Psychosis, schizophrenia, or bipolar no 2.7 \n", - " yes 0.0 \n", - "Learning disability no 2.7 \n", - " yes 0.0 \n", - "SSRI (last 12 months) no 2.7 \n", - " yes 0.0 \n", - "Chemo or radiotherapy no 2.7 \n", - " yes 0.0 \n", - "Cancer (lung) no 2.6 \n", - " yes 0.0 \n", - "Cancer (excluding lung/haem) no 2.6 \n", - " yes 0.0 \n", - "Cancer (haematological) no 2.6 \n", - " yes 0.0 " + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "### DateCOVID vaccinations among 50-54 population\n", + " ### by Psychosis, schizophrenia, or bipolar" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/svg+xml": [ + "\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", 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{ + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# \n", + "## Vaccination rates of each eligible population group, according to demographic/clinical features " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ { "data": { "text/markdown": [ "## \n", - " ## Cumulative vaccination figures among 70-79 population \n", + " ## Cumulative vaccination figures among 80+ population \n", " Please refer to footnotes below table for information." ], "text/plain": [ @@ -34367,8 +60751,8 @@ " \n", " \n", " \n", - " Vaccinated at 30 Mar (n)\n", - " Vaccinated at 30 Mar (%)\n", + " Vaccinated at 16 Apr (n)\n", + " Vaccinated at 16 Apr (%)\n", " Total eligible\n", " Previous week's vaccination coverage (%)\n", " Vaccinated over last 7d (%)\n", @@ -34387,612 +60771,612 @@ " \n", " overall\n", " overall\n", - " 1411\n", - " 39.5\n", - " 3570\n", - " 37.3\n", - " 2.2\n", + " 831\n", + " 40.7\n", + " 2044\n", + " 38.8\n", + " 1.9\n", " \n", " \n", " Sex\n", " F\n", - " 714\n", - " 40.0\n", - " 1785\n", - " 37.6\n", - " 2.4\n", + " 406\n", + " 40.6\n", + " 1001\n", + " 38.5\n", + " 2.1\n", " \n", " \n", " M\n", - " 693\n", - " 39.0\n", - " 1778\n", - " 37.0\n", + " 427\n", + " 40.7\n", + " 1050\n", + " 38.7\n", " 2.0\n", " \n", " \n", " Age band\n", " 0\n", - " 84\n", - " 37.5\n", - " 224\n", - " 34.4\n", - " 3.1\n", + " 49\n", + " 36.8\n", + " 133\n", + " 36.8\n", + " 0.0\n", " \n", " \n", " 0-15\n", - " 91\n", - " 37.1\n", - " 245\n", - " 37.1\n", + " 49\n", + " 38.9\n", + " 126\n", + " 38.9\n", " 0.0\n", " \n", " \n", " 16-29\n", - " 77\n", - " 36.7\n", - " 210\n", - " 33.3\n", - " 3.4\n", + " 56\n", + " 47.1\n", + " 119\n", + " 47.1\n", + " 0.0\n", " \n", " \n", " 30-34\n", - " 91\n", - " 37.1\n", - " 245\n", - " 37.1\n", - " 0.0\n", + " 56\n", + " 44.4\n", + " 126\n", + " 38.9\n", + " 5.5\n", " \n", " \n", " 35-39\n", - " 84\n", - " 36.4\n", - " 231\n", + " 42\n", " 33.3\n", - " 3.1\n", + " 126\n", + " 33.3\n", + " 0.0\n", " \n", " \n", " 40-44\n", - " 105\n", - " 44.1\n", - " 238\n", - " 44.1\n", - " 0.0\n", + " 63\n", + " 47.4\n", + " 133\n", + " 42.1\n", + " 5.3\n", " \n", " \n", " 45-49\n", - " 70\n", - " 35.7\n", - " 196\n", - " 32.1\n", - " 3.6\n", + " 56\n", + " 42.1\n", + " 133\n", + " 42.1\n", + " 0.0\n", " \n", " \n", " 50-54\n", - " 98\n", - " 45.2\n", - " 217\n", - " 41.9\n", - " 3.3\n", + " 42\n", + " 35.3\n", + " 119\n", + " 35.3\n", + " 0.0\n", " \n", " \n", " 55-59\n", - " 84\n", - " 41.4\n", - " 203\n", - " 41.4\n", + " 49\n", + " 41.2\n", + " 119\n", + " 41.2\n", " 0.0\n", " \n", " \n", " 60-64\n", - " 91\n", - " 40.6\n", - " 224\n", - " 40.6\n", - " 0.0\n", + " 56\n", + " 42.1\n", + " 133\n", + " 36.8\n", + " 5.3\n", " \n", " \n", " 65-69\n", - " 91\n", - " 39.4\n", - " 231\n", - " 39.4\n", + " 42\n", + " 35.3\n", + " 119\n", + " 35.3\n", " 0.0\n", " \n", " \n", " 70-74\n", - " 84\n", - " 37.5\n", - " 224\n", - " 34.4\n", - " 3.1\n", + " 63\n", + " 42.9\n", + " 147\n", + " 38.1\n", + " 4.8\n", " \n", " \n", " 75-79\n", - " 91\n", - " 41.9\n", - " 217\n", - " 38.7\n", - " 3.2\n", + " 49\n", + " 38.9\n", + " 126\n", + " 33.3\n", + " 5.6\n", " \n", " \n", " 80-84\n", - " 84\n", - " 40.0\n", - " 210\n", - " 36.7\n", - " 3.3\n", + " 56\n", + " 42.1\n", + " 133\n", + " 36.8\n", + " 5.3\n", " \n", " \n", " 85-89\n", - " 98\n", - " 42.4\n", - " 231\n", - " 39.4\n", - " 3.0\n", + " 56\n", + " 40.0\n", + " 140\n", + " 40.0\n", + " 0.0\n", " \n", " \n", " 90+\n", - " 77\n", - " 35.5\n", - " 217\n", - " 35.5\n", + " 42\n", + " 35.3\n", + " 119\n", + " 35.3\n", " 0.0\n", " \n", - " \n", - " Ethnicity (broad categories)\n", - " Black\n", - " 224\n", - " 39.0\n", - " 574\n", - " 37.8\n", - " 1.2\n", + " \n", + " Ethnicity (broad categories)\n", + " Black\n", + " 154\n", + " 40.7\n", + " 378\n", + " 38.9\n", + " 1.8\n", " \n", " \n", " Mixed\n", - " 231\n", - " 36.3\n", - " 637\n", - " 34.1\n", - " 2.2\n", + " 147\n", + " 42.9\n", + " 343\n", + " 40.8\n", + " 2.1\n", " \n", " \n", " Other\n", - " 245\n", - " 40.2\n", - " 609\n", - " 39.1\n", - " 1.1\n", + " 133\n", + " 36.5\n", + " 364\n", + " 34.6\n", + " 1.9\n", " \n", " \n", " South Asian\n", - " 252\n", - " 40.4\n", - " 623\n", - " 37.1\n", - " 3.3\n", + " 126\n", + " 39.1\n", + " 322\n", + " 37.0\n", + " 2.1\n", " \n", " \n", " Unknown\n", - " 217\n", - " 39.7\n", - " 546\n", - " 38.5\n", - " 1.2\n", + " 133\n", + " 43.2\n", + " 308\n", + " 40.9\n", + " 2.3\n", " \n", " \n", " White\n", - " 245\n", - " 42.2\n", - " 581\n", - " 38.6\n", - " 3.6\n", + " 147\n", + " 43.8\n", + " 336\n", + " 41.7\n", + " 2.1\n", " \n", " \n", " ethnicity 16 groups\n", " African\n", - " 63\n", - " 34.6\n", - " 182\n", - " 34.6\n", + " 49\n", + " 41.2\n", + " 119\n", + " 41.2\n", " 0.0\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 70\n", - " 41.7\n", - " 168\n", - " 37.5\n", - " 4.2\n", + " 56\n", + " 53.3\n", + " 105\n", + " 46.7\n", + " 6.6\n", " \n", " \n", " Caribbean\n", - " 77\n", - " 42.3\n", - " 182\n", - " 38.5\n", - " 3.8\n", + " 49\n", + " 43.8\n", + " 112\n", + " 43.8\n", + " 0.0\n", " \n", " \n", " Chinese\n", - " 70\n", - " 40.0\n", - " 175\n", - " 36.0\n", - " 4.0\n", + " 35\n", + " 38.5\n", + " 91\n", + " 38.5\n", + " 0.0\n", " \n", " \n", " Other\n", - " 77\n", - " 44.0\n", - " 175\n", + " 42\n", " 40.0\n", - " 4.0\n", + " 105\n", + " 40.0\n", + " 0.0\n", " \n", " \n", " Other Asian\n", - " 77\n", - " 40.7\n", - " 189\n", - " 37.0\n", - " 3.7\n", + " 49\n", + " 43.8\n", + " 112\n", + " 37.5\n", + " 6.3\n", " \n", " \n", " British or Mixed British\n", - " 91\n", - " 46.4\n", - " 196\n", - " 42.9\n", - " 3.5\n", + " 42\n", + " 40.0\n", + " 105\n", + " 40.0\n", + " 0.0\n", " \n", " \n", " Indian or British Indian\n", - " 84\n", - " 41.4\n", - " 203\n", - " 41.4\n", + " 42\n", + " 40.0\n", + " 105\n", + " 40.0\n", " 0.0\n", " \n", " \n", " Irish\n", - " 70\n", - " 38.5\n", - " 182\n", - " 38.5\n", + " 35\n", + " 35.7\n", + " 98\n", + " 35.7\n", " 0.0\n", " \n", " \n", " Other Black\n", - " 63\n", - " 34.6\n", - " 182\n", - " 30.8\n", - " 3.8\n", + " 42\n", + " 50.0\n", + " 84\n", + " 50.0\n", + " 0.0\n", " \n", " \n", " Other White\n", - " 84\n", - " 41.4\n", - " 203\n", - " 37.9\n", - " 3.5\n", + " 42\n", + " 40.0\n", + " 105\n", + " 40.0\n", + " 0.0\n", " \n", " \n", " Other mixed\n", - " 70\n", - " 37.0\n", - " 189\n", - " 37.0\n", - " 0.0\n", + " 42\n", + " 40.0\n", + " 105\n", + " 33.3\n", + " 6.7\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 77\n", - " 39.3\n", - " 196\n", - " 35.7\n", - " 3.6\n", + " 49\n", + " 41.2\n", + " 119\n", + " 41.2\n", + " 0.0\n", " \n", " \n", " Unknown\n", - " 210\n", - " 38.5\n", - " 546\n", - " 35.9\n", - " 2.6\n", + " 119\n", + " 36.2\n", + " 329\n", + " 34.0\n", + " 2.2\n", " \n", " \n", " White + Asian\n", - " 84\n", - " 44.4\n", - " 189\n", - " 44.4\n", + " 35\n", + " 31.2\n", + " 112\n", + " 31.2\n", " 0.0\n", " \n", " \n", " White + Black African\n", - " 70\n", - " 34.5\n", - " 203\n", - " 31.0\n", - " 3.5\n", + " 42\n", + " 37.5\n", + " 112\n", + " 37.5\n", + " 0.0\n", " \n", " \n", " White + Black Caribbean\n", - " 84\n", - " 41.4\n", - " 203\n", - " 37.9\n", - " 3.5\n", + " 49\n", + " 38.9\n", + " 126\n", + " 38.9\n", + " 0.0\n", " \n", " \n", " Index of Multiple Deprivation (quintiles)\n", " 1 Most deprived\n", - " 259\n", - " 37.4\n", - " 693\n", - " 35.4\n", - " 2.0\n", + " 175\n", + " 42.4\n", + " 413\n", + " 40.7\n", + " 1.7\n", " \n", " \n", " 2\n", - " 245\n", - " 38.0\n", - " 644\n", - " 35.9\n", - " 2.1\n", + " 140\n", + " 40.8\n", + " 343\n", + " 38.8\n", + " 2.0\n", " \n", " \n", " 3\n", - " 266\n", - " 40.9\n", - " 651\n", - " 37.6\n", - " 3.3\n", + " 154\n", + " 39.3\n", + " 392\n", + " 37.5\n", + " 1.8\n", " \n", " \n", " 4\n", - " 287\n", - " 40.2\n", - " 714\n", - " 37.3\n", - " 2.9\n", + " 168\n", + " 42.1\n", + " 399\n", + " 40.4\n", + " 1.7\n", " \n", " \n", " 5 Least deprived\n", - " 280\n", - " 41.2\n", - " 679\n", - " 39.2\n", - " 2.0\n", + " 154\n", + " 39.3\n", + " 392\n", + " 37.5\n", + " 1.8\n", " \n", " \n", " Unknown\n", - " 77\n", - " 40.7\n", - " 189\n", - " 40.7\n", + " 42\n", + " 42.9\n", + " 98\n", + " 42.9\n", " 0.0\n", " \n", " \n", " BMI\n", " 30+\n", - " 434\n", - " 39.5\n", - " 1099\n", - " 37.6\n", - " 1.9\n", + " 231\n", + " 38.4\n", + " 602\n", + " 37.2\n", + " 1.2\n", " \n", " \n", " under 30\n", - " 973\n", - " 39.5\n", - " 2464\n", - " 37.2\n", - " 2.3\n", + " 602\n", + " 41.7\n", + " 1442\n", + " 39.8\n", + " 1.9\n", " \n", " \n", " Chronic cardiac disease\n", " no\n", - " 1393\n", - " 39.4\n", - " 3535\n", - " 37.2\n", - " 2.2\n", + " 819\n", + " 40.5\n", + " 2023\n", + " 38.8\n", + " 1.7\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 7\n", + " 25.0\n", + " 28\n", + " 25.0\n", " 0.0\n", " \n", " \n", " Current COPD\n", " no\n", - " 1393\n", - " 39.5\n", - " 3528\n", - " 37.3\n", - " 2.2\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 39.0\n", + " 1.7\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", - " 35\n", - " 60.0\n", + " 0\n", + " 0.0\n", + " 14\n", + " 0.0\n", " 0.0\n", " \n", " \n", " Dialysis\n", " no\n", - " 1400\n", - " 39.5\n", - " 3542\n", - " 37.4\n", - " 2.1\n", + " 819\n", + " 40.5\n", + " 2023\n", + " 38.8\n", + " 1.7\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", + " 7\n", + " 33.3\n", " 21\n", - " 66.7\n", + " 33.3\n", " 0.0\n", " \n", " \n", " DMARDs\n", " no\n", - " 1393\n", - " 39.5\n", - " 3528\n", - " 37.3\n", - " 2.2\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 39.0\n", + " 1.7\n", " \n", " \n", " yes\n", + " 0\n", + " 0.0\n", " 14\n", - " 33.3\n", - " 42\n", - " 33.3\n", + " 0.0\n", " 0.0\n", " \n", " \n", " Dementia\n", " no\n", - " 1400\n", - " 39.6\n", - " 3535\n", - " 37.2\n", - " 2.4\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 39.0\n", + " 1.7\n", " \n", " \n", " yes\n", + " 0\n", + " 0.0\n", " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 0.0\n", " 0.0\n", " \n", " \n", " Psychosis, schizophrenia, or bipolar\n", " no\n", - " 1400\n", - " 39.6\n", - " 3535\n", - " 37.4\n", - " 2.2\n", + " 826\n", + " 40.5\n", + " 2037\n", + " 38.8\n", + " 1.7\n", " \n", " \n", " yes\n", + " 0\n", + " 0.0\n", " 7\n", - " 20.0\n", - " 35\n", - " 20.0\n", + " 0.0\n", " 0.0\n", " \n", " \n", " Learning disability\n", " no\n", - " 1379\n", - " 39.6\n", - " 3486\n", - " 37.3\n", - " 2.3\n", + " 812\n", + " 40.6\n", + " 2002\n", + " 38.5\n", + " 2.1\n", " \n", " \n", " yes\n", - " 35\n", - " 41.7\n", - " 84\n", - " 33.3\n", - " 8.4\n", + " 21\n", + " 50.0\n", + " 42\n", + " 50.0\n", + " 0.0\n", " \n", " \n", " SSRI (last 12 months)\n", " no\n", - " 1400\n", - " 39.6\n", - " 3535\n", - " 37.4\n", - " 2.2\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 38.6\n", + " 2.1\n", " \n", " \n", " yes\n", + " 7\n", + " 50.0\n", " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 50.0\n", " 0.0\n", " \n", " \n", " Chemo or radiotherapy\n", " no\n", - " 1393\n", - " 39.6\n", - " 3521\n", - " 37.4\n", - " 2.2\n", + " 826\n", + " 40.8\n", + " 2023\n", + " 38.8\n", + " 2.0\n", " \n", " \n", " yes\n", - " 14\n", - " 28.6\n", - " 49\n", - " 28.6\n", + " 7\n", + " 33.3\n", + " 21\n", " 0.0\n", + " 33.3\n", " \n", " \n", " Cancer (lung)\n", " no\n", - " 1400\n", - " 39.6\n", - " 3535\n", - " 37.4\n", - " 2.2\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 38.6\n", + " 2.1\n", " \n", " \n", " yes\n", + " 0\n", + " 0.0\n", " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 0.0\n", " 0.0\n", " \n", " \n", " Cancer (excluding lung/haem)\n", " no\n", - " 1400\n", - " 39.6\n", - " 3535\n", - " 37.4\n", - " 2.2\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 39.0\n", + " 1.7\n", " \n", " \n", " yes\n", + " 0\n", + " 0.0\n", " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 0.0\n", " 0.0\n", " \n", " \n", " Cancer (haematological)\n", " no\n", - " 1400\n", - " 39.7\n", - " 3528\n", - " 37.5\n", - " 2.2\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 38.6\n", + " 2.1\n", " \n", " \n", " yes\n", + " 0\n", + " 0.0\n", " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 0.0\n", " 0.0\n", " \n", " \n", @@ -35000,389 +61384,389 @@ "" ], "text/plain": [ - " Vaccinated at 30 Mar (n) \\\n", + " Vaccinated at 16 Apr (n) \\\n", "Category Group \n", - "overall overall 1411 \n", - "Sex F 714 \n", - " M 693 \n", - "Age band 0 84 \n", - " 0-15 91 \n", - " 16-29 77 \n", - " 30-34 91 \n", - " 35-39 84 \n", - " 40-44 105 \n", - " 45-49 70 \n", - " 50-54 98 \n", - " 55-59 84 \n", - " 60-64 91 \n", - " 65-69 91 \n", - " 70-74 84 \n", - " 75-79 91 \n", - " 80-84 84 \n", - " 85-89 98 \n", - " 90+ 77 \n", - "Ethnicity (broad categories) Black 224 \n", - " Mixed 231 \n", - " Other 245 \n", - " South Asian 252 \n", - " Unknown 217 \n", - " White 245 \n", - "ethnicity 16 groups African 63 \n", - " Bangladeshi or British Bangladeshi 70 \n", - " Caribbean 77 \n", - " Chinese 70 \n", - " Other 77 \n", - " Other Asian 77 \n", - " British or Mixed British 91 \n", - " Indian or British Indian 84 \n", - " Irish 70 \n", - " Other Black 63 \n", - " Other White 84 \n", - " Other mixed 70 \n", - " Pakistani or British Pakistani 77 \n", - " Unknown 210 \n", - " White + Asian 84 \n", - " White + Black African 70 \n", - " White + Black Caribbean 84 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 259 \n", - " 2 245 \n", - " 3 266 \n", - " 4 287 \n", - " 5 Least deprived 280 \n", - " Unknown 77 \n", - "BMI 30+ 434 \n", - " under 30 973 \n", - "Chronic cardiac disease no 1393 \n", - " yes 14 \n", - "Current COPD no 1393 \n", + "overall overall 831 \n", + "Sex F 406 \n", + " M 427 \n", + "Age band 0 49 \n", + " 0-15 49 \n", + " 16-29 56 \n", + " 30-34 56 \n", + " 35-39 42 \n", + " 40-44 63 \n", + " 45-49 56 \n", + " 50-54 42 \n", + " 55-59 49 \n", + " 60-64 56 \n", + " 65-69 42 \n", + " 70-74 63 \n", + " 75-79 49 \n", + " 80-84 56 \n", + " 85-89 56 \n", + " 90+ 42 \n", + "Ethnicity (broad categories) Black 154 \n", + " Mixed 147 \n", + " Other 133 \n", + " South Asian 126 \n", + " Unknown 133 \n", + " White 147 \n", + "ethnicity 16 groups African 49 \n", + " Bangladeshi or British Bangladeshi 56 \n", + " Caribbean 49 \n", + " Chinese 35 \n", + " Other 42 \n", + " Other Asian 49 \n", + " British or Mixed British 42 \n", + " Indian or British Indian 42 \n", + " Irish 35 \n", + " Other Black 42 \n", + " Other White 42 \n", + " Other mixed 42 \n", + " Pakistani or British Pakistani 49 \n", + " Unknown 119 \n", + " White + Asian 35 \n", + " White + Black African 42 \n", + " White + Black Caribbean 49 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 175 \n", + " 2 140 \n", + " 3 154 \n", + " 4 168 \n", + " 5 Least deprived 154 \n", + " Unknown 42 \n", + "BMI 30+ 231 \n", + " under 30 602 \n", + "Chronic cardiac disease no 819 \n", + " yes 7 \n", + "Current COPD no 826 \n", + " yes 0 \n", + "Dialysis no 819 \n", + " yes 7 \n", + "DMARDs no 826 \n", + " yes 0 \n", + "Dementia no 826 \n", + " yes 0 \n", + "Psychosis, schizophrenia, or bipolar no 826 \n", + " yes 0 \n", + "Learning disability no 812 \n", " yes 21 \n", - "Dialysis no 1400 \n", - " yes 14 \n", - "DMARDs no 1393 \n", - " yes 14 \n", - "Dementia no 1400 \n", - " yes 14 \n", - "Psychosis, schizophrenia, or bipolar no 1400 \n", + "SSRI (last 12 months) no 826 \n", " yes 7 \n", - "Learning disability no 1379 \n", - " yes 35 \n", - "SSRI (last 12 months) no 1400 \n", - " yes 14 \n", - "Chemo or radiotherapy no 1393 \n", - " yes 14 \n", - "Cancer (lung) no 1400 \n", - " yes 14 \n", - "Cancer (excluding lung/haem) no 1400 \n", - " yes 14 \n", - "Cancer (haematological) no 1400 \n", - " yes 14 \n", + "Chemo or radiotherapy no 826 \n", + " yes 7 \n", + "Cancer (lung) no 826 \n", + " yes 0 \n", + "Cancer (excluding lung/haem) no 826 \n", + " yes 0 \n", + "Cancer (haematological) no 826 \n", + " yes 0 \n", "\n", - " Vaccinated at 30 Mar (%) \\\n", - "Category Group \n", - "overall overall 39.5 \n", - "Sex F 40.0 \n", - " M 39.0 \n", - "Age band 0 37.5 \n", - " 0-15 37.1 \n", - " 16-29 36.7 \n", - " 30-34 37.1 \n", - " 35-39 36.4 \n", - " 40-44 44.1 \n", - " 45-49 35.7 \n", - " 50-54 45.2 \n", - " 55-59 41.4 \n", - " 60-64 40.6 \n", - " 65-69 39.4 \n", - " 70-74 37.5 \n", - " 75-79 41.9 \n", - " 80-84 40.0 \n", - " 85-89 42.4 \n", - " 90+ 35.5 \n", - "Ethnicity (broad categories) Black 39.0 \n", - " Mixed 36.3 \n", - " Other 40.2 \n", - " South Asian 40.4 \n", - " Unknown 39.7 \n", - " White 42.2 \n", - "ethnicity 16 groups African 34.6 \n", - " Bangladeshi or British Bangladeshi 41.7 \n", - " Caribbean 42.3 \n", - " Chinese 40.0 \n", - " Other 44.0 \n", - " Other Asian 40.7 \n", - " British or Mixed British 46.4 \n", - " Indian or British Indian 41.4 \n", - " Irish 38.5 \n", - " Other Black 34.6 \n", - " Other White 41.4 \n", - " Other mixed 37.0 \n", - " Pakistani or British Pakistani 39.3 \n", - " Unknown 38.5 \n", - " White + Asian 44.4 \n", - " White + Black African 34.5 \n", - " White + Black Caribbean 41.4 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 37.4 \n", - " 2 38.0 \n", - " 3 40.9 \n", - " 4 40.2 \n", - " 5 Least deprived 41.2 \n", - " Unknown 40.7 \n", - "BMI 30+ 39.5 \n", - " under 30 39.5 \n", - "Chronic cardiac disease no 39.4 \n", - " yes 40.0 \n", - "Current COPD no 39.5 \n", - " yes 60.0 \n", - "Dialysis no 39.5 \n", - " yes 66.7 \n", - "DMARDs no 39.5 \n", + " Vaccinated at 16 Apr (%) \\\n", + "Category Group \n", + "overall overall 40.7 \n", + "Sex F 40.6 \n", + " M 40.7 \n", + "Age band 0 36.8 \n", + " 0-15 38.9 \n", + " 16-29 47.1 \n", + " 30-34 44.4 \n", + " 35-39 33.3 \n", + " 40-44 47.4 \n", + " 45-49 42.1 \n", + " 50-54 35.3 \n", + " 55-59 41.2 \n", + " 60-64 42.1 \n", + " 65-69 35.3 \n", + " 70-74 42.9 \n", + " 75-79 38.9 \n", + " 80-84 42.1 \n", + " 85-89 40.0 \n", + " 90+ 35.3 \n", + "Ethnicity (broad categories) Black 40.7 \n", + " Mixed 42.9 \n", + " Other 36.5 \n", + " South Asian 39.1 \n", + " Unknown 43.2 \n", + " White 43.8 \n", + "ethnicity 16 groups African 41.2 \n", + " Bangladeshi or British Bangladeshi 53.3 \n", + " Caribbean 43.8 \n", + " Chinese 38.5 \n", + " Other 40.0 \n", + " Other Asian 43.8 \n", + " British or Mixed British 40.0 \n", + " Indian or British Indian 40.0 \n", + " Irish 35.7 \n", + " Other Black 50.0 \n", + " Other White 40.0 \n", + " Other mixed 40.0 \n", + " Pakistani or British Pakistani 41.2 \n", + " Unknown 36.2 \n", + " White + Asian 31.2 \n", + " White + Black African 37.5 \n", + " White + Black Caribbean 38.9 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 42.4 \n", + " 2 40.8 \n", + " 3 39.3 \n", + " 4 42.1 \n", + " 5 Least deprived 39.3 \n", + " Unknown 42.9 \n", + "BMI 30+ 38.4 \n", + " under 30 41.7 \n", + "Chronic cardiac disease no 40.5 \n", + " yes 25.0 \n", + "Current COPD no 40.7 \n", + " yes 0.0 \n", + "Dialysis no 40.5 \n", " yes 33.3 \n", - "Dementia no 39.6 \n", + "DMARDs no 40.7 \n", + " yes 0.0 \n", + "Dementia no 40.7 \n", + " yes 0.0 \n", + "Psychosis, schizophrenia, or bipolar no 40.5 \n", + " yes 0.0 \n", + "Learning disability no 40.6 \n", " yes 50.0 \n", - "Psychosis, schizophrenia, or bipolar no 39.6 \n", - " yes 20.0 \n", - "Learning disability no 39.6 \n", - " yes 41.7 \n", - "SSRI (last 12 months) no 39.6 \n", - " yes 40.0 \n", - "Chemo or radiotherapy no 39.6 \n", - " yes 28.6 \n", - "Cancer (lung) no 39.6 \n", + "SSRI (last 12 months) no 40.7 \n", " yes 50.0 \n", - "Cancer (excluding lung/haem) no 39.6 \n", - " yes 40.0 \n", - "Cancer (haematological) no 39.7 \n", - " yes 40.0 \n", + "Chemo or radiotherapy no 40.8 \n", + " yes 33.3 \n", + "Cancer (lung) no 40.7 \n", + " yes 0.0 \n", + "Cancer (excluding lung/haem) no 40.7 \n", + " yes 0.0 \n", + "Cancer (haematological) no 40.7 \n", + " yes 0.0 \n", "\n", " Total eligible \\\n", "Category Group \n", - "overall overall 3570 \n", - "Sex F 1785 \n", - " M 1778 \n", - "Age band 0 224 \n", - " 0-15 245 \n", - " 16-29 210 \n", - " 30-34 245 \n", - " 35-39 231 \n", - " 40-44 238 \n", - " 45-49 196 \n", - " 50-54 217 \n", - " 55-59 203 \n", - " 60-64 224 \n", - " 65-69 231 \n", - " 70-74 224 \n", - " 75-79 217 \n", - " 80-84 210 \n", - " 85-89 231 \n", - " 90+ 217 \n", - "Ethnicity (broad categories) Black 574 \n", - " Mixed 637 \n", - " Other 609 \n", - " South Asian 623 \n", - " Unknown 546 \n", - " White 581 \n", - "ethnicity 16 groups African 182 \n", - " Bangladeshi or British Bangladeshi 168 \n", - " Caribbean 182 \n", - " Chinese 175 \n", - " Other 175 \n", - " Other Asian 189 \n", - " British or Mixed British 196 \n", - " Indian or British Indian 203 \n", - " Irish 182 \n", - " Other Black 182 \n", - " Other White 203 \n", - " Other mixed 189 \n", - " Pakistani or British Pakistani 196 \n", - " Unknown 546 \n", - " White + Asian 189 \n", - " White + Black African 203 \n", - " White + Black Caribbean 203 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 693 \n", - " 2 644 \n", - " 3 651 \n", - " 4 714 \n", - " 5 Least deprived 679 \n", - " Unknown 189 \n", - "BMI 30+ 1099 \n", - " under 30 2464 \n", - "Chronic cardiac disease no 3535 \n", - " yes 35 \n", - "Current COPD no 3528 \n", - " yes 35 \n", - "Dialysis no 3542 \n", + "overall overall 2044 \n", + "Sex F 1001 \n", + " M 1050 \n", + "Age band 0 133 \n", + " 0-15 126 \n", + " 16-29 119 \n", + " 30-34 126 \n", + " 35-39 126 \n", + " 40-44 133 \n", + " 45-49 133 \n", + " 50-54 119 \n", + " 55-59 119 \n", + " 60-64 133 \n", + " 65-69 119 \n", + " 70-74 147 \n", + " 75-79 126 \n", + " 80-84 133 \n", + " 85-89 140 \n", + " 90+ 119 \n", + "Ethnicity (broad categories) Black 378 \n", + " Mixed 343 \n", + " Other 364 \n", + " South Asian 322 \n", + " Unknown 308 \n", + " White 336 \n", + "ethnicity 16 groups African 119 \n", + " Bangladeshi or British Bangladeshi 105 \n", + " Caribbean 112 \n", + " Chinese 91 \n", + " Other 105 \n", + " Other Asian 112 \n", + " British or Mixed British 105 \n", + " Indian or British Indian 105 \n", + " Irish 98 \n", + " Other Black 84 \n", + " Other White 105 \n", + " Other mixed 105 \n", + " Pakistani or British Pakistani 119 \n", + " Unknown 329 \n", + " White + Asian 112 \n", + " White + Black African 112 \n", + " White + Black Caribbean 126 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 413 \n", + " 2 343 \n", + " 3 392 \n", + " 4 399 \n", + " 5 Least deprived 392 \n", + " Unknown 98 \n", + "BMI 30+ 602 \n", + " under 30 1442 \n", + "Chronic cardiac disease no 2023 \n", + " yes 28 \n", + "Current COPD no 2030 \n", + " yes 14 \n", + "Dialysis no 2023 \n", " yes 21 \n", - "DMARDs no 3528 \n", + "DMARDs no 2030 \n", + " yes 14 \n", + "Dementia no 2030 \n", + " yes 14 \n", + "Psychosis, schizophrenia, or bipolar no 2037 \n", + " yes 7 \n", + "Learning disability no 2002 \n", " yes 42 \n", - "Dementia no 3535 \n", - " yes 28 \n", - "Psychosis, schizophrenia, or bipolar no 3535 \n", - " yes 35 \n", - "Learning disability no 3486 \n", - " yes 84 \n", - "SSRI (last 12 months) no 3535 \n", - " yes 35 \n", - "Chemo or radiotherapy no 3521 \n", - " yes 49 \n", - "Cancer (lung) no 3535 \n", - " yes 28 \n", - "Cancer (excluding lung/haem) no 3535 \n", - " yes 35 \n", - "Cancer (haematological) no 3528 \n", - " yes 35 \n", + "SSRI (last 12 months) no 2030 \n", + " yes 14 \n", + "Chemo or radiotherapy no 2023 \n", + " yes 21 \n", + "Cancer (lung) no 2030 \n", + " yes 14 \n", + "Cancer (excluding lung/haem) no 2030 \n", + " yes 14 \n", + "Cancer (haematological) no 2030 \n", + " yes 14 \n", "\n", " Previous week's vaccination coverage (%) \\\n", "Category Group \n", - "overall overall 37.3 \n", - "Sex F 37.6 \n", - " M 37.0 \n", - "Age band 0 34.4 \n", - " 0-15 37.1 \n", - " 16-29 33.3 \n", - " 30-34 37.1 \n", + "overall overall 38.8 \n", + "Sex F 38.5 \n", + " M 38.7 \n", + "Age band 0 36.8 \n", + " 0-15 38.9 \n", + " 16-29 47.1 \n", + " 30-34 38.9 \n", " 35-39 33.3 \n", - " 40-44 44.1 \n", - " 45-49 32.1 \n", - " 50-54 41.9 \n", - " 55-59 41.4 \n", - " 60-64 40.6 \n", - " 65-69 39.4 \n", - " 70-74 34.4 \n", - " 75-79 38.7 \n", - " 80-84 36.7 \n", - " 85-89 39.4 \n", - " 90+ 35.5 \n", - "Ethnicity (broad categories) Black 37.8 \n", - " Mixed 34.1 \n", - " Other 39.1 \n", - " South Asian 37.1 \n", - " Unknown 38.5 \n", - " White 38.6 \n", - "ethnicity 16 groups African 34.6 \n", - " Bangladeshi or British Bangladeshi 37.5 \n", - " Caribbean 38.5 \n", - " Chinese 36.0 \n", + " 40-44 42.1 \n", + " 45-49 42.1 \n", + " 50-54 35.3 \n", + " 55-59 41.2 \n", + " 60-64 36.8 \n", + " 65-69 35.3 \n", + " 70-74 38.1 \n", + " 75-79 33.3 \n", + " 80-84 36.8 \n", + " 85-89 40.0 \n", + " 90+ 35.3 \n", + "Ethnicity (broad categories) Black 38.9 \n", + " Mixed 40.8 \n", + " Other 34.6 \n", + " South Asian 37.0 \n", + " Unknown 40.9 \n", + " White 41.7 \n", + "ethnicity 16 groups African 41.2 \n", + " Bangladeshi or British Bangladeshi 46.7 \n", + " Caribbean 43.8 \n", + " Chinese 38.5 \n", " Other 40.0 \n", - " Other Asian 37.0 \n", - " British or Mixed British 42.9 \n", - " Indian or British Indian 41.4 \n", - " Irish 38.5 \n", - " Other Black 30.8 \n", - " Other White 37.9 \n", - " Other mixed 37.0 \n", - " Pakistani or British Pakistani 35.7 \n", - " Unknown 35.9 \n", - " White + Asian 44.4 \n", - " White + Black African 31.0 \n", - " White + Black Caribbean 37.9 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 35.4 \n", - " 2 35.9 \n", - " 3 37.6 \n", - " 4 37.3 \n", - " 5 Least deprived 39.2 \n", - " Unknown 40.7 \n", - "BMI 30+ 37.6 \n", - " under 30 37.2 \n", - "Chronic cardiac disease no 37.2 \n", - " yes 40.0 \n", - "Current COPD no 37.3 \n", - " yes 60.0 \n", - "Dialysis no 37.4 \n", - " yes 66.7 \n", - "DMARDs no 37.3 \n", + " Other Asian 37.5 \n", + " British or Mixed British 40.0 \n", + " Indian or British Indian 40.0 \n", + " Irish 35.7 \n", + " Other Black 50.0 \n", + " Other White 40.0 \n", + " Other mixed 33.3 \n", + " Pakistani or British Pakistani 41.2 \n", + " Unknown 34.0 \n", + " White + Asian 31.2 \n", + " White + Black African 37.5 \n", + " White + Black Caribbean 38.9 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 40.7 \n", + " 2 38.8 \n", + " 3 37.5 \n", + " 4 40.4 \n", + " 5 Least deprived 37.5 \n", + " Unknown 42.9 \n", + "BMI 30+ 37.2 \n", + " under 30 39.8 \n", + "Chronic cardiac disease no 38.8 \n", + " yes 25.0 \n", + "Current COPD no 39.0 \n", + " yes 0.0 \n", + "Dialysis no 38.8 \n", " yes 33.3 \n", - "Dementia no 37.2 \n", + "DMARDs no 39.0 \n", + " yes 0.0 \n", + "Dementia no 39.0 \n", + " yes 0.0 \n", + "Psychosis, schizophrenia, or bipolar no 38.8 \n", + " yes 0.0 \n", + "Learning disability no 38.5 \n", " yes 50.0 \n", - "Psychosis, schizophrenia, or bipolar no 37.4 \n", - " yes 20.0 \n", - "Learning disability no 37.3 \n", - " yes 33.3 \n", - "SSRI (last 12 months) no 37.4 \n", - " yes 40.0 \n", - "Chemo or radiotherapy no 37.4 \n", - " yes 28.6 \n", - "Cancer (lung) no 37.4 \n", + "SSRI (last 12 months) no 38.6 \n", " yes 50.0 \n", - "Cancer (excluding lung/haem) no 37.4 \n", - " yes 40.0 \n", - "Cancer (haematological) no 37.5 \n", - " yes 40.0 \n", + "Chemo or radiotherapy no 38.8 \n", + " yes 0.0 \n", + "Cancer (lung) no 38.6 \n", + " yes 0.0 \n", + "Cancer (excluding lung/haem) no 39.0 \n", + " yes 0.0 \n", + "Cancer (haematological) no 38.6 \n", + " yes 0.0 \n", "\n", " Vaccinated over last 7d (%) \n", "Category Group \n", - "overall overall 2.2 \n", - "Sex F 2.4 \n", + "overall overall 1.9 \n", + "Sex F 2.1 \n", " M 2.0 \n", - "Age band 0 3.1 \n", + "Age band 0 0.0 \n", " 0-15 0.0 \n", - " 16-29 3.4 \n", - " 30-34 0.0 \n", - " 35-39 3.1 \n", - " 40-44 0.0 \n", - " 45-49 3.6 \n", - " 50-54 3.3 \n", + " 16-29 0.0 \n", + " 30-34 5.5 \n", + " 35-39 0.0 \n", + " 40-44 5.3 \n", + " 45-49 0.0 \n", + " 50-54 0.0 \n", " 55-59 0.0 \n", - " 60-64 0.0 \n", + " 60-64 5.3 \n", " 65-69 0.0 \n", - " 70-74 3.1 \n", - " 75-79 3.2 \n", - " 80-84 3.3 \n", - " 85-89 3.0 \n", + " 70-74 4.8 \n", + " 75-79 5.6 \n", + " 80-84 5.3 \n", + " 85-89 0.0 \n", " 90+ 0.0 \n", - "Ethnicity (broad categories) Black 1.2 \n", - " Mixed 2.2 \n", - " Other 1.1 \n", - " South Asian 3.3 \n", - " Unknown 1.2 \n", - " White 3.6 \n", + "Ethnicity (broad categories) Black 1.8 \n", + " Mixed 2.1 \n", + " Other 1.9 \n", + " South Asian 2.1 \n", + " Unknown 2.3 \n", + " White 2.1 \n", "ethnicity 16 groups African 0.0 \n", - " Bangladeshi or British Bangladeshi 4.2 \n", - " Caribbean 3.8 \n", - " Chinese 4.0 \n", - " Other 4.0 \n", - " Other Asian 3.7 \n", - " British or Mixed British 3.5 \n", + " Bangladeshi or British Bangladeshi 6.6 \n", + " Caribbean 0.0 \n", + " Chinese 0.0 \n", + " Other 0.0 \n", + " Other Asian 6.3 \n", + " British or Mixed British 0.0 \n", " Indian or British Indian 0.0 \n", " Irish 0.0 \n", - " Other Black 3.8 \n", - " Other White 3.5 \n", - " Other mixed 0.0 \n", - " Pakistani or British Pakistani 3.6 \n", - " Unknown 2.6 \n", + " Other Black 0.0 \n", + " Other White 0.0 \n", + " Other mixed 6.7 \n", + " Pakistani or British Pakistani 0.0 \n", + " Unknown 2.2 \n", " White + Asian 0.0 \n", - " White + Black African 3.5 \n", - " White + Black Caribbean 3.5 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 2.0 \n", - " 2 2.1 \n", - " 3 3.3 \n", - " 4 2.9 \n", - " 5 Least deprived 2.0 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 0.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 1.7 \n", + " 2 2.0 \n", + " 3 1.8 \n", + " 4 1.7 \n", + " 5 Least deprived 1.8 \n", " Unknown 0.0 \n", - "BMI 30+ 1.9 \n", - " under 30 2.3 \n", - "Chronic cardiac disease no 2.2 \n", + "BMI 30+ 1.2 \n", + " under 30 1.9 \n", + "Chronic cardiac disease no 1.7 \n", " yes 0.0 \n", - "Current COPD no 2.2 \n", + "Current COPD no 1.7 \n", " yes 0.0 \n", - "Dialysis no 2.1 \n", + "Dialysis no 1.7 \n", " yes 0.0 \n", - "DMARDs no 2.2 \n", + "DMARDs no 1.7 \n", " yes 0.0 \n", - "Dementia no 2.4 \n", + "Dementia no 1.7 \n", " yes 0.0 \n", - "Psychosis, schizophrenia, or bipolar no 2.2 \n", + "Psychosis, schizophrenia, or bipolar no 1.7 \n", " yes 0.0 \n", - "Learning disability no 2.3 \n", - " yes 8.4 \n", - "SSRI (last 12 months) no 2.2 \n", + "Learning disability no 2.1 \n", " yes 0.0 \n", - "Chemo or radiotherapy no 2.2 \n", + "SSRI (last 12 months) no 2.1 \n", " yes 0.0 \n", - "Cancer (lung) no 2.2 \n", + "Chemo or radiotherapy no 2.0 \n", + " yes 33.3 \n", + "Cancer (lung) no 2.1 \n", " yes 0.0 \n", - "Cancer (excluding lung/haem) no 2.2 \n", + "Cancer (excluding lung/haem) no 1.7 \n", " yes 0.0 \n", - "Cancer (haematological) no 2.2 \n", + "Cancer (haematological) no 2.1 \n", " yes 0.0 " ] }, @@ -35430,7 +61814,7 @@ "data": { "text/markdown": [ "## \n", - " ## Cumulative vaccination figures among care home population \n", + " ## Cumulative vaccination figures among 70-79 population \n", " Please refer to footnotes below table for information." ], "text/plain": [ @@ -35462,8 +61846,8 @@ " \n", " \n", " \n", - " Vaccinated at 30 Mar (n)\n", - " Vaccinated at 30 Mar (%)\n", + " Vaccinated at 16 Apr (n)\n", + " Vaccinated at 16 Apr (%)\n", " Total eligible\n", " Previous week's vaccination coverage (%)\n", " Vaccinated over last 7d (%)\n", @@ -35482,674 +61866,612 @@ " \n", " overall\n", " overall\n", - " 549\n", - " 40.0\n", - " 1372\n", - " 37.8\n", - " 2.2\n", + " 1354\n", + " 39.4\n", + " 3437\n", + " 37.3\n", + " 2.1\n", " \n", " \n", " Sex\n", " F\n", - " 266\n", - " 37.6\n", - " 707\n", - " 35.6\n", + " 693\n", + " 39.9\n", + " 1736\n", + " 37.9\n", " 2.0\n", " \n", " \n", " M\n", - " 280\n", - " 42.1\n", - " 665\n", - " 40.0\n", + " 658\n", + " 38.7\n", + " 1701\n", + " 36.6\n", " 2.1\n", " \n", " \n", " Age band\n", " 0\n", - " 42\n", - " 46.2\n", - " 91\n", - " 46.2\n", + " 84\n", + " 37.5\n", + " 224\n", + " 37.5\n", " 0.0\n", " \n", " \n", " 0-15\n", - " 28\n", - " 36.4\n", - " 77\n", - " 36.4\n", + " 70\n", + " 40.0\n", + " 175\n", + " 40.0\n", " 0.0\n", " \n", " \n", " 16-29\n", - " 42\n", - " 50.0\n", " 84\n", - " 41.7\n", - " 8.3\n", + " 36.4\n", + " 231\n", + " 33.3\n", + " 3.1\n", " \n", " \n", " 30-34\n", - " 28\n", - " 36.4\n", - " 77\n", - " 36.4\n", - " 0.0\n", + " 91\n", + " 43.3\n", + " 210\n", + " 40.0\n", + " 3.3\n", " \n", " \n", " 35-39\n", - " 42\n", - " 42.9\n", " 98\n", - " 42.9\n", - " 0.0\n", + " 42.4\n", + " 231\n", + " 39.4\n", + " 3.0\n", " \n", " \n", " 40-44\n", - " 21\n", - " 27.3\n", - " 77\n", - " 27.3\n", + " 91\n", + " 39.4\n", + " 231\n", + " 39.4\n", " 0.0\n", " \n", " \n", " 45-49\n", - " 35\n", - " 41.7\n", - " 84\n", - " 33.3\n", - " 8.4\n", + " 98\n", + " 42.4\n", + " 231\n", + " 39.4\n", + " 3.0\n", " \n", " \n", " 50-54\n", - " 35\n", - " 41.7\n", - " 84\n", - " 41.7\n", + " 70\n", + " 38.5\n", + " 182\n", + " 38.5\n", " 0.0\n", " \n", " \n", " 55-59\n", - " 42\n", - " 46.2\n", - " 91\n", - " 46.2\n", - " 0.0\n", + " 84\n", + " 38.7\n", + " 217\n", + " 35.5\n", + " 3.2\n", " \n", " \n", " 60-64\n", - " 49\n", - " 50.0\n", - " 98\n", - " 50.0\n", + " 77\n", + " 36.7\n", + " 210\n", + " 36.7\n", " 0.0\n", " \n", " \n", " 65-69\n", - " 21\n", - " 25.0\n", " 84\n", - " 25.0\n", - " 0.0\n", + " 40.0\n", + " 210\n", + " 36.7\n", + " 3.3\n", " \n", " \n", " 70-74\n", - " 28\n", - " 30.8\n", " 91\n", - " 23.1\n", - " 7.7\n", + " 38.2\n", + " 238\n", + " 35.3\n", + " 2.9\n", " \n", " \n", " 75-79\n", - " 42\n", - " 46.2\n", - " 91\n", - " 38.5\n", - " 7.7\n", + " 84\n", + " 41.4\n", + " 203\n", + " 37.9\n", + " 3.5\n", " \n", " \n", " 80-84\n", - " 35\n", - " 41.7\n", - " 84\n", - " 41.7\n", + " 77\n", + " 39.3\n", + " 196\n", + " 39.3\n", " 0.0\n", " \n", " \n", " 85-89\n", - " 21\n", - " 27.3\n", - " 77\n", - " 27.3\n", - " 0.0\n", + " 84\n", + " 36.4\n", + " 231\n", + " 33.3\n", + " 3.1\n", " \n", " \n", " 90+\n", - " 35\n", - " 41.7\n", - " 84\n", - " 41.7\n", - " 0.0\n", + " 91\n", + " 41.9\n", + " 217\n", + " 38.7\n", + " 3.2\n", " \n", " \n", " Ethnicity (broad categories)\n", " Black\n", - " 91\n", - " 38.2\n", - " 238\n", - " 35.3\n", - " 2.9\n", + " 231\n", + " 37.5\n", + " 616\n", + " 35.2\n", + " 2.3\n", " \n", " \n", " Mixed\n", - " 98\n", - " 38.9\n", - " 252\n", - " 36.1\n", - " 2.8\n", + " 217\n", + " 38.8\n", + " 560\n", + " 37.5\n", + " 1.3\n", " \n", " \n", " Other\n", - " 84\n", - " 38.7\n", " 217\n", - " 38.7\n", - " 0.0\n", + " 39.7\n", + " 546\n", + " 38.5\n", + " 1.2\n", " \n", " \n", " South Asian\n", - " 91\n", - " 40.6\n", - " 224\n", - " 37.5\n", - " 3.1\n", + " 245\n", + " 42.2\n", + " 581\n", + " 39.8\n", + " 2.4\n", " \n", " \n", " Unknown\n", - " 84\n", - " 40.0\n", - " 210\n", - " 36.7\n", - " 3.3\n", + " 203\n", + " 38.7\n", + " 525\n", + " 36.0\n", + " 2.7\n", " \n", " \n", " White\n", - " 98\n", - " 42.4\n", - " 231\n", - " 39.4\n", - " 3.0\n", - " \n", - " \n", - " Dementia\n", - " no\n", - " 539\n", - " 39.9\n", - " 1351\n", - " 37.8\n", - " 2.1\n", + " 238\n", + " 39.5\n", + " 602\n", + " 37.2\n", + " 2.3\n", " \n", " \n", - " yes\n", - " 7\n", + " ethnicity 16 groups\n", + " African\n", + " 63\n", " 33.3\n", - " 21\n", - " 0.0\n", + " 189\n", " 33.3\n", + " 0.0\n", " \n", - " \n", - "\n", - "" - ], - "text/plain": [ - " Vaccinated at 30 Mar (n) \\\n", - "Category Group \n", - "overall overall 549 \n", - "Sex F 266 \n", - " M 280 \n", - "Age band 0 42 \n", - " 0-15 28 \n", - " 16-29 42 \n", - " 30-34 28 \n", - " 35-39 42 \n", - " 40-44 21 \n", - " 45-49 35 \n", - " 50-54 35 \n", - " 55-59 42 \n", - " 60-64 49 \n", - " 65-69 21 \n", - " 70-74 28 \n", - " 75-79 42 \n", - " 80-84 35 \n", - " 85-89 21 \n", - " 90+ 35 \n", - "Ethnicity (broad categories) Black 91 \n", - " Mixed 98 \n", - " Other 84 \n", - " South Asian 91 \n", - " Unknown 84 \n", - " White 98 \n", - "Dementia no 539 \n", - " yes 7 \n", - "\n", - " Vaccinated at 30 Mar (%) \\\n", - "Category Group \n", - "overall overall 40.0 \n", - "Sex F 37.6 \n", - " M 42.1 \n", - "Age band 0 46.2 \n", - " 0-15 36.4 \n", - " 16-29 50.0 \n", - " 30-34 36.4 \n", - " 35-39 42.9 \n", - " 40-44 27.3 \n", - " 45-49 41.7 \n", - " 50-54 41.7 \n", - " 55-59 46.2 \n", - " 60-64 50.0 \n", - " 65-69 25.0 \n", - " 70-74 30.8 \n", - " 75-79 46.2 \n", - " 80-84 41.7 \n", - " 85-89 27.3 \n", - " 90+ 41.7 \n", - "Ethnicity (broad categories) Black 38.2 \n", - " Mixed 38.9 \n", - " Other 38.7 \n", - " South Asian 40.6 \n", - " Unknown 40.0 \n", - " White 42.4 \n", - "Dementia no 39.9 \n", - " yes 33.3 \n", - "\n", - " Total eligible \\\n", - "Category Group \n", - "overall overall 1372 \n", - "Sex F 707 \n", - " M 665 \n", - "Age band 0 91 \n", - " 0-15 77 \n", - " 16-29 84 \n", - " 30-34 77 \n", - " 35-39 98 \n", - " 40-44 77 \n", - " 45-49 84 \n", - " 50-54 84 \n", - " 55-59 91 \n", - " 60-64 98 \n", - " 65-69 84 \n", - " 70-74 91 \n", - " 75-79 91 \n", - " 80-84 84 \n", - " 85-89 77 \n", - " 90+ 84 \n", - "Ethnicity (broad categories) Black 238 \n", - " Mixed 252 \n", - " Other 217 \n", - " South Asian 224 \n", - " Unknown 210 \n", - " White 231 \n", - "Dementia no 1351 \n", - " yes 21 \n", - "\n", - " Previous week's vaccination coverage (%) \\\n", - "Category Group \n", - "overall overall 37.8 \n", - "Sex F 35.6 \n", - " M 40.0 \n", - "Age band 0 46.2 \n", - " 0-15 36.4 \n", - " 16-29 41.7 \n", - " 30-34 36.4 \n", - " 35-39 42.9 \n", - " 40-44 27.3 \n", - " 45-49 33.3 \n", - " 50-54 41.7 \n", - " 55-59 46.2 \n", - " 60-64 50.0 \n", - " 65-69 25.0 \n", - " 70-74 23.1 \n", - " 75-79 38.5 \n", - " 80-84 41.7 \n", - " 85-89 27.3 \n", - " 90+ 41.7 \n", - "Ethnicity (broad categories) Black 35.3 \n", - " Mixed 36.1 \n", - " Other 38.7 \n", - " South Asian 37.5 \n", - " Unknown 36.7 \n", - " White 39.4 \n", - "Dementia no 37.8 \n", - " yes 0.0 \n", - "\n", - " Vaccinated over last 7d (%) \n", - "Category Group \n", - "overall overall 2.2 \n", - "Sex F 2.0 \n", - " M 2.1 \n", - "Age band 0 0.0 \n", - " 0-15 0.0 \n", - " 16-29 8.3 \n", - " 30-34 0.0 \n", - " 35-39 0.0 \n", - " 40-44 0.0 \n", - " 45-49 8.4 \n", - " 50-54 0.0 \n", - " 55-59 0.0 \n", - " 60-64 0.0 \n", - " 65-69 0.0 \n", - " 70-74 7.7 \n", - " 75-79 7.7 \n", - " 80-84 0.0 \n", - " 85-89 0.0 \n", - " 90+ 0.0 \n", - "Ethnicity (broad categories) Black 2.9 \n", - " Mixed 2.8 \n", - " Other 0.0 \n", - " South Asian 3.1 \n", - " Unknown 3.3 \n", - " White 3.0 \n", - "Dementia no 2.1 \n", - " yes 33.3 " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/markdown": [ - "**Footnotes:**\n", - "- Patient counts rounded to the nearest 7" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/markdown": [ - "- Population includes those known to live in an elderly care home, based upon clinical coding." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/markdown": [ - "## \n", - " ## Cumulative vaccination figures among shielding (aged 16-69) population \n", - " Please refer to footnotes below table for information." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
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" 2 28 \n", - " 3 28 \n", - " 4 35 \n", - " 5 Least deprived 28 \n", - " Unknown 7 \n", - "Learning disability no 147 \n", - " yes 0 \n", - "\n", - " Vaccinated at 30 Mar (%) \\\n", - "Category Group \n", - "overall overall 37.0 \n", - "newly shielded since feb 15 no 37.9 \n", - " yes NaN \n", - "Sex F 36.7 \n", - " M 37.9 \n", - "Age band 16-29 37.5 \n", - " 30-39 50.0 \n", - " 40-49 37.5 \n", - " 50-59 28.6 \n", - " 60-69 42.9 \n", - " 70-79 35.7 \n", - " 80+ 37.5 \n", - "Ethnicity (broad categories) Black 33.3 \n", - " Mixed 45.5 \n", - " Other 36.4 \n", - " South Asian 44.4 \n", - " Unknown 33.3 \n", - " White 33.3 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 40.0 \n", - " 2 30.8 \n", - " 3 33.3 \n", - " 4 41.7 \n", - " 5 Least deprived 44.4 \n", - " Unknown 33.3 \n", - "Learning disability no 36.2 \n", - " yes 0.0 \n", + " Vaccinated at 16 Apr (n) \\\n", + "Category Group \n", + "overall overall 1354 \n", + "Sex F 693 \n", + " M 658 \n", + "Age band 0 84 \n", + " 0-15 70 \n", + " 16-29 84 \n", + " 30-34 91 \n", + " 35-39 98 \n", + " 40-44 91 \n", + " 45-49 98 \n", + " 50-54 70 \n", + " 55-59 84 \n", + " 60-64 77 \n", + " 65-69 84 \n", + " 70-74 91 \n", + " 75-79 84 \n", + " 80-84 77 \n", + " 85-89 84 \n", + " 90+ 91 \n", + "Ethnicity (broad categories) Black 231 \n", + " Mixed 217 \n", + " Other 217 \n", + " South Asian 245 \n", + " Unknown 203 \n", + " White 238 \n", + "ethnicity 16 groups African 63 \n", + " Bangladeshi or British Bangladeshi 77 \n", + " Caribbean 84 \n", + " Chinese 70 \n", + " Other 84 \n", + " Other Asian 70 \n", + " British or Mixed British 63 \n", + " Indian or British Indian 77 \n", + " Irish 77 \n", + " Other Black 56 \n", + " Other White 56 \n", + " Other mixed 63 \n", + " Pakistani or British Pakistani 77 \n", + " Unknown 217 \n", + " White + Asian 77 \n", + " White + Black African 77 \n", + " White + Black Caribbean 56 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 252 \n", + " 2 259 \n", + " 3 259 \n", + " 4 259 \n", + " 5 Least deprived 245 \n", + " Unknown 77 \n", + "BMI 30+ 427 \n", + " under 30 924 \n", + "Chronic cardiac disease no 1344 \n", + " yes 14 \n", + "Current COPD no 1344 \n", + " yes 14 \n", + "Dialysis no 1344 \n", + " yes 14 \n", + "DMARDs no 1344 \n", + " yes 14 \n", + "Dementia no 1344 \n", + " yes 14 \n", + "Psychosis, schizophrenia, or bipolar no 1351 \n", + " yes 0 \n", + "Learning disability no 1323 \n", + " yes 35 \n", + "SSRI (last 12 months) no 1337 \n", + " yes 14 \n", + "Chemo or radiotherapy no 1344 \n", + " yes 14 \n", + "Cancer (lung) no 1344 \n", + " yes 14 \n", + "Cancer (excluding lung/haem) no 1337 \n", + " yes 14 \n", + "Cancer (haematological) no 1337 \n", + " yes 14 \n", "\n", - " Total eligible \\\n", - "Category Group \n", - "overall overall 413 \n", - "newly shielded since feb 15 no 406 \n", - " yes 0 \n", - "Sex F 210 \n", - " M 203 \n", - "Age band 16-29 56 \n", - " 30-39 42 \n", - " 40-49 56 \n", - " 50-59 49 \n", - " 60-69 49 \n", - " 70-79 98 \n", - " 80+ 56 \n", - "Ethnicity (broad categories) Black 63 \n", - " Mixed 77 \n", - " Other 77 \n", - " South Asian 63 \n", - " Unknown 63 \n", - " White 63 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 70 \n", - " 2 91 \n", - " 3 84 \n", - " 4 84 \n", - " 5 Least deprived 63 \n", - " Unknown 21 \n", - "Learning disability no 406 \n", - " yes 7 \n", + " Vaccinated at 16 Apr (%) \\\n", + "Category Group \n", + "overall overall 39.4 \n", + "Sex F 39.9 \n", + " M 38.7 \n", + "Age band 0 37.5 \n", + " 0-15 40.0 \n", + " 16-29 36.4 \n", + " 30-34 43.3 \n", + " 35-39 42.4 \n", + " 40-44 39.4 \n", + " 45-49 42.4 \n", + " 50-54 38.5 \n", + " 55-59 38.7 \n", + " 60-64 36.7 \n", + " 65-69 40.0 \n", + " 70-74 38.2 \n", + " 75-79 41.4 \n", + " 80-84 39.3 \n", + " 85-89 36.4 \n", + " 90+ 41.9 \n", + "Ethnicity (broad categories) Black 37.5 \n", + " Mixed 38.8 \n", + " Other 39.7 \n", + " South Asian 42.2 \n", + " Unknown 38.7 \n", + " White 39.5 \n", + "ethnicity 16 groups African 33.3 \n", + " Bangladeshi or British Bangladeshi 37.9 \n", + " Caribbean 44.4 \n", + " Chinese 37.0 \n", + " Other 44.4 \n", + " Other Asian 40.0 \n", + " British or Mixed British 36.0 \n", + " Indian or British Indian 44.0 \n", + " Irish 39.3 \n", + " Other Black 32.0 \n", + " Other White 36.4 \n", + " Other mixed 36.0 \n", + " Pakistani or British Pakistani 42.3 \n", + " Unknown 40.8 \n", + " White + Asian 40.7 \n", + " White + Black African 44.0 \n", + " White + Black Caribbean 34.8 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 40.0 \n", + " 2 37.8 \n", + " 3 38.1 \n", + " 4 40.7 \n", + " 5 Least deprived 39.3 \n", + " Unknown 44.0 \n", + "BMI 30+ 41.5 \n", + " under 30 38.4 \n", + "Chronic cardiac disease no 39.5 \n", + " yes 50.0 \n", + "Current COPD no 39.5 \n", + " yes 40.0 \n", + "Dialysis no 39.5 \n", + " yes 40.0 \n", + "DMARDs no 39.6 \n", + " yes 33.3 \n", + "Dementia no 39.4 \n", + " yes 50.0 \n", + "Psychosis, schizophrenia, or bipolar no 39.6 \n", + " yes 0.0 \n", + "Learning disability no 39.3 \n", + " yes 55.6 \n", + "SSRI (last 12 months) no 39.3 \n", + " yes 40.0 \n", + "Chemo or radiotherapy no 39.5 \n", + " yes 50.0 \n", + "Cancer (lung) no 39.5 \n", + " yes 40.0 \n", + "Cancer (excluding lung/haem) no 39.3 \n", + " yes 50.0 \n", + "Cancer (haematological) no 39.3 \n", + " yes 50.0 \n", "\n", - " Previous week's vaccination coverage (%) \\\n", - "Category Group \n", - "overall overall 35.4 \n", - "newly shielded since feb 15 no 36.2 \n", - " yes NaN \n", - "Sex F 33.3 \n", - " M 34.5 \n", - "Age band 16-29 37.5 \n", - " 30-39 50.0 \n", - " 40-49 37.5 \n", - " 50-59 28.6 \n", - " 60-69 42.9 \n", - " 70-79 35.7 \n", - " 80+ 37.5 \n", - "Ethnicity (broad categories) Black 33.3 \n", - " Mixed 45.5 \n", - " Other 36.4 \n", - " South Asian 44.4 \n", - " Unknown 33.3 \n", - " White 33.3 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 40.0 \n", - " 2 30.8 \n", - " 3 33.3 \n", - " 4 33.3 \n", - " 5 Least deprived 44.4 \n", - " Unknown 33.3 \n", - "Learning disability no 34.5 \n", - " yes 0.0 \n", + " Total eligible \\\n", + "Category Group \n", + "overall overall 3437 \n", + "Sex F 1736 \n", + " M 1701 \n", + "Age band 0 224 \n", + " 0-15 175 \n", + " 16-29 231 \n", + " 30-34 210 \n", + " 35-39 231 \n", + " 40-44 231 \n", + " 45-49 231 \n", + " 50-54 182 \n", + " 55-59 217 \n", + " 60-64 210 \n", + " 65-69 210 \n", + " 70-74 238 \n", + " 75-79 203 \n", + " 80-84 196 \n", + " 85-89 231 \n", + " 90+ 217 \n", + "Ethnicity (broad categories) Black 616 \n", + " Mixed 560 \n", + " Other 546 \n", + " South Asian 581 \n", + " Unknown 525 \n", + " White 602 \n", + "ethnicity 16 groups African 189 \n", + " Bangladeshi or British Bangladeshi 203 \n", + " Caribbean 189 \n", + " Chinese 189 \n", + " Other 189 \n", + " Other Asian 175 \n", + " British or Mixed British 175 \n", + " Indian or British Indian 175 \n", + " Irish 196 \n", + " Other Black 175 \n", + " Other White 154 \n", + " Other mixed 175 \n", + " Pakistani or British Pakistani 182 \n", + " Unknown 532 \n", + " White + Asian 189 \n", + " White + Black African 175 \n", + " White + Black Caribbean 161 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 630 \n", + " 2 686 \n", + " 3 679 \n", + " 4 637 \n", + " 5 Least deprived 623 \n", + " Unknown 175 \n", + "BMI 30+ 1029 \n", + " under 30 2408 \n", + "Chronic cardiac disease no 3402 \n", + " yes 28 \n", + "Current COPD no 3402 \n", + " yes 35 \n", + "Dialysis no 3402 \n", + " yes 35 \n", + "DMARDs no 3395 \n", + " yes 42 \n", + "Dementia no 3409 \n", + " yes 28 \n", + "Psychosis, schizophrenia, or bipolar no 3409 \n", + " yes 21 \n", + "Learning disability no 3367 \n", + " yes 63 \n", + "SSRI (last 12 months) no 3402 \n", + " yes 35 \n", + "Chemo or radiotherapy no 3402 \n", + " yes 28 \n", + "Cancer (lung) no 3402 \n", + " yes 35 \n", + "Cancer (excluding lung/haem) no 3402 \n", + " yes 28 \n", + "Cancer (haematological) no 3402 \n", + " yes 28 \n", "\n", - " Vaccinated over last 7d (%) \n", - "Category Group \n", - "overall overall 1.6 \n", - "newly shielded since feb 15 no 1.7 \n", - " yes 0.0 \n", - "Sex F 3.4 \n", - " M 3.4 \n", - "Age band 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 (broad categories) 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", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 0.0 \n", - " 2 0.0 \n", - " 3 0.0 \n", - " 4 8.4 \n", - " 5 Least deprived 0.0 \n", - " Unknown 0.0 \n", - "Learning disability no 1.7 \n", - " yes 0.0 " + " Previous week's vaccination coverage (%) \\\n", + "Category Group \n", + "overall overall 37.3 \n", + "Sex F 37.9 \n", + " M 36.6 \n", + "Age band 0 37.5 \n", + " 0-15 40.0 \n", + " 16-29 33.3 \n", + " 30-34 40.0 \n", + " 35-39 39.4 \n", + " 40-44 39.4 \n", + " 45-49 39.4 \n", + " 50-54 38.5 \n", + " 55-59 35.5 \n", + " 60-64 36.7 \n", + " 65-69 36.7 \n", + " 70-74 35.3 \n", + " 75-79 37.9 \n", + " 80-84 39.3 \n", + " 85-89 33.3 \n", + " 90+ 38.7 \n", + "Ethnicity (broad categories) Black 35.2 \n", + " Mixed 37.5 \n", + " Other 38.5 \n", + " South Asian 39.8 \n", + " Unknown 36.0 \n", + " White 37.2 \n", + "ethnicity 16 groups African 33.3 \n", + " Bangladeshi or British Bangladeshi 34.5 \n", + " Caribbean 40.7 \n", + " Chinese 33.3 \n", + " Other 40.7 \n", + " Other Asian 40.0 \n", + " British or Mixed British 32.0 \n", + " Indian or British Indian 40.0 \n", + " Irish 39.3 \n", + " Other Black 32.0 \n", + " Other White 31.8 \n", + " Other mixed 36.0 \n", + " Pakistani or British Pakistani 42.3 \n", + " Unknown 39.5 \n", + " White + Asian 37.0 \n", + " White + Black African 44.0 \n", + " White + Black Caribbean 34.8 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 37.8 \n", + " 2 35.7 \n", + " 3 36.1 \n", + " 4 38.5 \n", + " 5 Least deprived 37.1 \n", + " Unknown 44.0 \n", + "BMI 30+ 38.8 \n", + " under 30 36.6 \n", + "Chronic cardiac disease no 37.4 \n", + " yes 50.0 \n", + "Current COPD no 37.4 \n", + " yes 20.0 \n", + "Dialysis no 37.2 \n", + " yes 40.0 \n", + "DMARDs no 37.5 \n", + " yes 16.7 \n", + "Dementia no 37.4 \n", + " yes 25.0 \n", + "Psychosis, schizophrenia, or bipolar no 37.4 \n", + " yes 0.0 \n", + "Learning disability no 37.2 \n", + " yes 44.4 \n", + "SSRI (last 12 months) no 37.2 \n", + " yes 40.0 \n", + "Chemo or radiotherapy no 37.4 \n", + " yes 50.0 \n", + "Cancer (lung) no 37.4 \n", + " yes 40.0 \n", + "Cancer (excluding lung/haem) no 37.2 \n", + " yes 50.0 \n", + "Cancer (haematological) no 37.2 \n", + " yes 50.0 \n", + "\n", + " Vaccinated over last 7d (%) \n", + "Category Group \n", + "overall overall 2.1 \n", + "Sex F 2.0 \n", + " M 2.1 \n", + "Age band 0 0.0 \n", + " 0-15 0.0 \n", + " 16-29 3.1 \n", + " 30-34 3.3 \n", + " 35-39 3.0 \n", + " 40-44 0.0 \n", + " 45-49 3.0 \n", + " 50-54 0.0 \n", + " 55-59 3.2 \n", + " 60-64 0.0 \n", + " 65-69 3.3 \n", + " 70-74 2.9 \n", + " 75-79 3.5 \n", + " 80-84 0.0 \n", + " 85-89 3.1 \n", + " 90+ 3.2 \n", + "Ethnicity (broad categories) Black 2.3 \n", + " Mixed 1.3 \n", + " Other 1.2 \n", + " South Asian 2.4 \n", + " Unknown 2.7 \n", + " White 2.3 \n", + "ethnicity 16 groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 3.4 \n", + " Caribbean 3.7 \n", + " Chinese 3.7 \n", + " Other 3.7 \n", + " Other Asian 0.0 \n", + " British or Mixed British 4.0 \n", + " Indian or British Indian 4.0 \n", + " Irish 0.0 \n", + " Other Black 0.0 \n", + " Other White 4.6 \n", + " Other mixed 0.0 \n", + " Pakistani or British Pakistani 0.0 \n", + " Unknown 1.3 \n", + " White + Asian 3.7 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 0.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 2.2 \n", + " 2 2.1 \n", + " 3 2.0 \n", + " 4 2.2 \n", + " 5 Least deprived 2.2 \n", + " Unknown 0.0 \n", + "BMI 30+ 2.7 \n", + " under 30 1.8 \n", + "Chronic cardiac disease no 2.1 \n", + " yes 0.0 \n", + "Current COPD no 2.1 \n", + " yes 20.0 \n", + "Dialysis no 2.3 \n", + " yes 0.0 \n", + "DMARDs no 2.1 \n", + " yes 16.6 \n", + "Dementia no 2.0 \n", + " yes 25.0 \n", + "Psychosis, schizophrenia, or bipolar no 2.2 \n", + " yes 0.0 \n", + "Learning disability no 2.1 \n", + " yes 11.2 \n", + "SSRI (last 12 months) no 2.1 \n", + " yes 0.0 \n", + "Chemo or radiotherapy no 2.1 \n", + " yes 0.0 \n", + "Cancer (lung) no 2.1 \n", + " yes 0.0 \n", + "Cancer (excluding lung/haem) no 2.1 \n", + " yes 0.0 \n", + "Cancer (haematological) no 2.1 \n", + " yes 0.0 " ] }, "metadata": {}, @@ -36322,7 +62884,19 @@ { "data": { "text/markdown": [ - "- Population excludes those over 65 known to live in an elderly care home, based upon clinical coding." + "- Population excludes those known to live in an elderly care home, based upon clinical coding." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- SSRIs group excludes individuals with Psychosis/ schizophrenia/bipolar, LD, or Dementia." ], "text/plain": [ "" @@ -36335,7 +62909,7 @@ "data": { "text/markdown": [ "## \n", - " ## Cumulative vaccination figures among 65-69 population \n", + " ## Cumulative vaccination figures among care home population \n", " Please refer to footnotes below table for information." ], "text/plain": [ @@ -36367,8 +62941,8 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -36387,250 +62961,473 @@ " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - 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Vaccinated at 30 Mar (n)Vaccinated at 30 Mar (%)Total eligiblePrevious week's vaccination coverage (%)Vaccinated over last 7d (%)
Bangladeshi or British Bangladeshi7737.920334.53.4
Caribbean8444.418940.73.7
Chinese7037.018933.33.7
CategoryGroupOther8444.418940.73.7
overalloverall15337.041335.41.6Other Asian7040.017540.00.0
newly shielded since feb 15noBritish or Mixed British6336.017532.04.0
Indian or British Indian7744.017540.04.0
Irish7739.319639.30.0
Other Black5632.017532.00.0
Other White5636.415437.940636.21.731.84.6
yes0NaN0NaNOther mixed6336.017536.00.0
SexFPakistani or British Pakistani7736.721033.33.442.318242.30.0
MUnknown21740.853239.51.3
White + Asian7737.920334.53.440.718937.03.7
Age band16-292137.5White + Black African7744.017544.00.0
White + Black Caribbean5637.534.816134.80.0
30-3921Index of Multiple Deprivation (quintiles)1 Most deprived25240.063037.82.2
225937.868635.72.1
325938.167936.12.0
425940.763738.52.2
5 Least deprived24539.362337.12.2
Unknown7744.017544.00.0
BMI30+42741.5102938.82.7
under 3092438.4240836.61.8
Chronic cardiac diseaseno134439.5340237.42.1
yes1450.0422850.00.0
40-492137.55637.50.0Current COPDno134439.5340237.42.1
50-59yes1428.64928.60.040.03520.020.0
60-692142.94942.90.0Dialysisno134439.5340237.22.3
70-79yes1440.03535.79835.740.00.0
80+2137.556DMARDsno134439.6339537.50.02.1
Ethnicity (broad categories)Black2133.363yes1433.30.04216.716.6
Mixed3545.57745.50.0Dementiano134439.4340937.42.0
Otheryes1450.02836.47736.40.025.025.0
South Asian2844.46344.40.0Psychosis, schizophrenia, or bipolarno135139.6340937.42.2
Unknownyes00.02133.36333.30.00.0
White2133.3Learning disabilityno132339.3336737.22.1
yes3555.66333.30.044.411.2
Index of Multiple Deprivation (quintiles)1 Most deprived28SSRI (last 12 months)no133739.3340237.22.1
yes1440.0703540.00.0
22830.89130.80.0Chemo or radiotherapyno134439.5340237.42.1
3yes1450.02833.38433.350.00.0
43541.78433.38.4Cancer (lung)no134439.5340237.42.1
5 Least deprived2844.46344.4yes1440.03540.00.0
Unknown733.32133.3Cancer (excluding lung/haem)no133739.3340237.22.1
yes1450.02850.00.0
Learning disabilityCancer (haematological)no14736.240634.51.7133739.3340237.22.1
yes00.070.01450.02850.00.0
Vaccinated at 30 Mar (n)Vaccinated at 30 Mar (%)Vaccinated at 16 Apr (n)Vaccinated at 16 Apr (%)Total eligiblePrevious week's vaccination coverage (%)Vaccinated over last 7d (%)
overalloverall90041.1219138.42.755540.0138638.31.7
SexF47641.2115538.82.428038.572836.52.0
M42741.2103637.83.428042.665840.42.2
Ethnicity (broad categories)Black15440.737838.91.8Age band05650.011243.86.2
Mixed15440.737838.91.80-153545.57745.50.0
Other14016-293538.536434.63.99138.50.0
South Asian14739.637139.630-343541.78441.70.0
Unknown12640.930838.62.335-393535.79835.70.0
White16844.437842.61.840-443541.78441.70.0
ethnicity 16 groupsAfrican4240.010533.36.745-493538.59130.87.7
Bangladeshi or British Bangladeshi4946.710546.750-543541.78441.70.0
Caribbean4235.311935.355-592133.36333.30.0
Chinese4938.912660-642833.35.68433.30.0
Other4237.511237.565-693538.59138.50.0
Other Asian4946.710546.770-743541.78441.70.0
British or Mixed British75-794237.511237.50.046.29138.57.7
Indian or British Indian4941.211941.280-842833.38433.30.0
Irish5644.412638.95.585-893545.57745.50.0
Other Black5644.412638.95.590+3545.57745.50.0
Other White5644.412638.95.5Ethnicity (broad categories)Black8434.324534.30.0
Other mixed4237.511231.26.3Mixed9841.223838.23.0
Pakistani or British Pakistani4237.511237.5Other9139.423139.40.0
Unknown14042.632938.34.3
White + Asian6347.413342.15.3South Asian9843.822440.63.2
White + Black African42Unknown8440.010521040.00.0
White + Black Caribbean4237.511237.5White9138.223838.20.0
Index of Multiple Deprivation (quintiles)1 Most deprived18239.446236.43.0Dementiano55340.5136538.52.0
216139.740637.91.8yes00.0140.00.0
\n", + "
" + ], + "text/plain": [ + " Vaccinated at 16 Apr (n) \\\n", + "Category Group \n", + "overall overall 555 \n", + "Sex F 280 \n", + " M 280 \n", + "Age band 0 56 \n", + " 0-15 35 \n", + " 16-29 35 \n", + " 30-34 35 \n", + " 35-39 35 \n", + " 40-44 35 \n", + " 45-49 35 \n", + " 50-54 35 \n", + " 55-59 21 \n", + " 60-64 28 \n", + " 65-69 35 \n", + " 70-74 35 \n", + " 75-79 42 \n", + " 80-84 28 \n", + " 85-89 35 \n", + " 90+ 35 \n", + "Ethnicity (broad categories) Black 84 \n", + " Mixed 98 \n", + " Other 91 \n", + " South Asian 98 \n", + " Unknown 84 \n", + " White 91 \n", + "Dementia no 553 \n", + " yes 0 \n", + "\n", + " Vaccinated at 16 Apr (%) \\\n", + "Category Group \n", + "overall overall 40.0 \n", + "Sex F 38.5 \n", + " M 42.6 \n", + "Age band 0 50.0 \n", + " 0-15 45.5 \n", + " 16-29 38.5 \n", + " 30-34 41.7 \n", + " 35-39 35.7 \n", + " 40-44 41.7 \n", + " 45-49 38.5 \n", + " 50-54 41.7 \n", + " 55-59 33.3 \n", + " 60-64 33.3 \n", + " 65-69 38.5 \n", + " 70-74 41.7 \n", + " 75-79 46.2 \n", + " 80-84 33.3 \n", + " 85-89 45.5 \n", + " 90+ 45.5 \n", + "Ethnicity (broad categories) Black 34.3 \n", + " Mixed 41.2 \n", + " Other 39.4 \n", + " South Asian 43.8 \n", + " Unknown 40.0 \n", + " White 38.2 \n", + "Dementia no 40.5 \n", + " yes 0.0 \n", + "\n", + " Total eligible \\\n", + "Category Group \n", + "overall overall 1386 \n", + "Sex F 728 \n", + " M 658 \n", + "Age band 0 112 \n", + " 0-15 77 \n", + " 16-29 91 \n", + " 30-34 84 \n", + " 35-39 98 \n", + " 40-44 84 \n", + " 45-49 91 \n", + " 50-54 84 \n", + " 55-59 63 \n", + " 60-64 84 \n", + " 65-69 91 \n", + " 70-74 84 \n", + " 75-79 91 \n", + " 80-84 84 \n", + " 85-89 77 \n", + " 90+ 77 \n", + "Ethnicity (broad categories) Black 245 \n", + " Mixed 238 \n", + " Other 231 \n", + " South Asian 224 \n", + " Unknown 210 \n", + " White 238 \n", + "Dementia no 1365 \n", + " yes 14 \n", + "\n", + " Previous week's vaccination coverage (%) \\\n", + "Category Group \n", + "overall overall 38.3 \n", + "Sex F 36.5 \n", + " M 40.4 \n", + "Age band 0 43.8 \n", + " 0-15 45.5 \n", + " 16-29 38.5 \n", + " 30-34 41.7 \n", + " 35-39 35.7 \n", + " 40-44 41.7 \n", + " 45-49 30.8 \n", + " 50-54 41.7 \n", + " 55-59 33.3 \n", + " 60-64 33.3 \n", + " 65-69 38.5 \n", + " 70-74 41.7 \n", + " 75-79 38.5 \n", + " 80-84 33.3 \n", + " 85-89 45.5 \n", + " 90+ 45.5 \n", + "Ethnicity (broad categories) Black 34.3 \n", + " Mixed 38.2 \n", + " Other 39.4 \n", + " South Asian 40.6 \n", + " Unknown 40.0 \n", + " White 38.2 \n", + "Dementia no 38.5 \n", + " yes 0.0 \n", + "\n", + " Vaccinated over last 7d (%) \n", + "Category Group \n", + "overall overall 1.7 \n", + "Sex F 2.0 \n", + " M 2.2 \n", + "Age band 0 6.2 \n", + " 0-15 0.0 \n", + " 16-29 0.0 \n", + " 30-34 0.0 \n", + " 35-39 0.0 \n", + " 40-44 0.0 \n", + " 45-49 7.7 \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 7.7 \n", + " 80-84 0.0 \n", + " 85-89 0.0 \n", + " 90+ 0.0 \n", + "Ethnicity (broad categories) Black 0.0 \n", + " Mixed 3.0 \n", + " Other 0.0 \n", + " South Asian 3.2 \n", + " Unknown 0.0 \n", + " White 0.0 \n", + "Dementia no 2.0 \n", + " yes 0.0 " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "**Footnotes:**\n", + "- Patient counts rounded to the nearest 7" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "- Population includes those known to live in an elderly care home, based upon clinical coding." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "## \n", + " ## Cumulative vaccination figures among shielding (aged 16-69) population \n", + " Please refer to footnotes below table for information." + ], + "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", - " \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", @@ -36854,300 +63636,150 @@ "" ], "text/plain": [ - " Vaccinated at 30 Mar (n) \\\n", - "Category Group \n", - "overall overall 900 \n", - "Sex F 476 \n", - " M 427 \n", - "Ethnicity (broad categories) Black 154 \n", - " Mixed 154 \n", - " Other 140 \n", - " South Asian 147 \n", - " Unknown 126 \n", - " White 168 \n", - "ethnicity 16 groups African 42 \n", - " Bangladeshi or British Bangladeshi 49 \n", - " Caribbean 42 \n", - " Chinese 49 \n", - " Other 42 \n", - " Other Asian 49 \n", - " British or Mixed British 42 \n", - " Indian or British Indian 49 \n", - " Irish 56 \n", - " Other Black 56 \n", - " Other White 56 \n", - " Other mixed 42 \n", - " Pakistani or British Pakistani 42 \n", - " Unknown 140 \n", - " White + Asian 63 \n", - " White + Black African 42 \n", - " White + Black Caribbean 42 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 182 \n", - " 2 161 \n", - " 3 168 \n", - " 4 175 \n", - " 5 Least deprived 175 \n", - " Unknown 42 \n", - "BMI 30+ 280 \n", - " under 30 623 \n", - "Chronic cardiac disease no 889 \n", - " yes 14 \n", - "Current COPD no 889 \n", - " yes 7 \n", - "DMARDs no 889 \n", - " yes 7 \n", - "Dementia no 889 \n", - " yes 7 \n", - "Psychosis, schizophrenia, or bipolar no 889 \n", - " yes 7 \n", - "Learning disability no 882 \n", - " yes 21 \n", - "SSRI (last 12 months) no 889 \n", - " yes 14 \n", - "Chemo or radiotherapy no 896 \n", - " yes 7 \n", - "Cancer (lung) no 889 \n", - " yes 14 \n", - "Cancer (excluding lung/haem) no 889 \n", - " yes 14 \n", - "Cancer (haematological) no 889 \n", - " yes 14 \n", + " Vaccinated at 16 Apr (n) \\\n", + "Category Group \n", + "overall overall 180 \n", + "newly shielded since feb 15 no 175 \n", + " yes 0 \n", + "Sex F 98 \n", + " M 84 \n", + "Age band 16-29 14 \n", + " 30-39 21 \n", + " 40-49 28 \n", + " 50-59 28 \n", + " 60-69 21 \n", + " 70-79 42 \n", + " 80+ 21 \n", + "Ethnicity (broad categories) Black 28 \n", + " Mixed 35 \n", + " Other 35 \n", + " South Asian 21 \n", + " Unknown 28 \n", + " White 35 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 42 \n", + " 2 42 \n", + " 3 28 \n", + " 4 28 \n", + " 5 Least deprived 28 \n", + " Unknown 14 \n", + "Learning disability no 175 \n", + " yes 0 \n", "\n", - " Vaccinated at 30 Mar (%) \\\n", - "Category Group \n", - "overall overall 41.1 \n", - "Sex F 41.2 \n", - " M 41.2 \n", - "Ethnicity (broad categories) Black 40.7 \n", - " Mixed 40.7 \n", - " Other 38.5 \n", - " South Asian 39.6 \n", - " Unknown 40.9 \n", - " White 44.4 \n", - "ethnicity 16 groups African 40.0 \n", - " Bangladeshi or British Bangladeshi 46.7 \n", - " Caribbean 35.3 \n", - " Chinese 38.9 \n", - " Other 37.5 \n", - " Other Asian 46.7 \n", - " British or Mixed British 37.5 \n", - " Indian or British Indian 41.2 \n", - " Irish 44.4 \n", - " Other Black 44.4 \n", - " Other White 44.4 \n", - " Other mixed 37.5 \n", - " Pakistani or British Pakistani 37.5 \n", - " Unknown 42.6 \n", - " White + Asian 47.4 \n", - " White + Black African 40.0 \n", - " White + Black Caribbean 37.5 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 39.4 \n", - " 2 39.7 \n", - " 3 42.1 \n", - " 4 42.4 \n", - " 5 Least deprived 41.0 \n", - " Unknown 46.2 \n", - "BMI 30+ 41.7 \n", - " under 30 41.2 \n", - "Chronic cardiac disease no 41.0 \n", - " yes 66.7 \n", - "Current COPD no 41.1 \n", - " yes 25.0 \n", - "DMARDs no 41.0 \n", - " yes 33.3 \n", - "Dementia no 41.1 \n", - " yes 33.3 \n", - "Psychosis, schizophrenia, or bipolar no 41.1 \n", - " yes 33.3 \n", - "Learning disability no 41.3 \n", - " yes 37.5 \n", - "SSRI (last 12 months) no 41.0 \n", - " yes 66.7 \n", - "Chemo or radiotherapy no 41.3 \n", - " yes 33.3 \n", - "Cancer (lung) no 41.2 \n", - " yes 40.0 \n", - "Cancer (excluding lung/haem) no 41.1 \n", - " yes 50.0 \n", - "Cancer (haematological) no 41.0 \n", - " yes 66.7 \n", + " Vaccinated at 16 Apr (%) \\\n", + "Category Group \n", + "overall overall 41.5 \n", + "newly shielded since feb 15 no 41.0 \n", + " yes NaN \n", + "Sex F 45.2 \n", + " M 38.7 \n", + "Age band 16-29 28.6 \n", + " 30-39 37.5 \n", + " 40-49 57.1 \n", + " 50-59 57.1 \n", + " 60-69 33.3 \n", + " 70-79 35.3 \n", + " 80+ 37.5 \n", + "Ethnicity (broad categories) Black 40.0 \n", + " Mixed 45.5 \n", + " Other 45.5 \n", + " South Asian 33.3 \n", + " Unknown 40.0 \n", + " White 50.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 42.9 \n", + " 2 46.2 \n", + " 3 36.4 \n", + " 4 40.0 \n", + " 5 Least deprived 40.0 \n", + " Unknown 50.0 \n", + "Learning disability no 41.7 \n", + " yes 0.0 \n", "\n", - " Total eligible \\\n", - "Category Group \n", - "overall overall 2191 \n", - "Sex F 1155 \n", - " M 1036 \n", - "Ethnicity (broad categories) Black 378 \n", - " Mixed 378 \n", - " Other 364 \n", - " South Asian 371 \n", - " Unknown 308 \n", - " White 378 \n", - "ethnicity 16 groups African 105 \n", - " Bangladeshi or British Bangladeshi 105 \n", - " Caribbean 119 \n", - " Chinese 126 \n", - " Other 112 \n", - " Other Asian 105 \n", - " British or Mixed British 112 \n", - " Indian or British Indian 119 \n", - " Irish 126 \n", - " Other Black 126 \n", - " Other White 126 \n", - " Other mixed 112 \n", - " Pakistani or British Pakistani 112 \n", - " Unknown 329 \n", - " White + Asian 133 \n", - " White + Black African 105 \n", - " White + Black Caribbean 112 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 462 \n", - " 2 406 \n", - " 3 399 \n", - " 4 413 \n", - " 5 Least deprived 427 \n", - " Unknown 91 \n", - "BMI 30+ 672 \n", - " under 30 1512 \n", - "Chronic cardiac disease no 2170 \n", - " yes 21 \n", - "Current COPD no 2163 \n", - " yes 28 \n", - "DMARDs no 2170 \n", - " yes 21 \n", - "Dementia no 2163 \n", - " yes 21 \n", - "Psychosis, schizophrenia, or bipolar no 2163 \n", - " yes 21 \n", - "Learning disability no 2135 \n", - " yes 56 \n", - "SSRI (last 12 months) no 2170 \n", - " yes 21 \n", - "Chemo or radiotherapy no 2170 \n", - " yes 21 \n", - "Cancer (lung) no 2156 \n", - " yes 35 \n", - "Cancer (excluding lung/haem) no 2163 \n", - " yes 28 \n", - "Cancer (haematological) no 2170 \n", - " yes 21 \n", + " Total eligible \\\n", + "Category Group \n", + "overall overall 434 \n", + "newly shielded since feb 15 no 427 \n", + " yes 0 \n", + "Sex F 217 \n", + " M 217 \n", + "Age band 16-29 49 \n", + " 30-39 56 \n", + " 40-49 49 \n", + " 50-59 49 \n", + " 60-69 63 \n", + " 70-79 119 \n", + " 80+ 56 \n", + "Ethnicity (broad categories) Black 70 \n", + " Mixed 77 \n", + " Other 77 \n", + " South Asian 63 \n", + " Unknown 70 \n", + " White 70 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 98 \n", + " 2 91 \n", + " 3 77 \n", + " 4 70 \n", + " 5 Least deprived 70 \n", + " Unknown 28 \n", + "Learning disability no 420 \n", + " yes 14 \n", "\n", - " Previous week's vaccination coverage (%) \\\n", - "Category Group \n", - "overall overall 38.4 \n", - "Sex F 38.8 \n", - " M 37.8 \n", - "Ethnicity (broad categories) Black 38.9 \n", - " Mixed 38.9 \n", - " Other 34.6 \n", - " South Asian 39.6 \n", - " Unknown 38.6 \n", - " White 42.6 \n", - "ethnicity 16 groups African 33.3 \n", - " Bangladeshi or British Bangladeshi 46.7 \n", - " Caribbean 35.3 \n", - " Chinese 33.3 \n", - " Other 37.5 \n", - " Other Asian 46.7 \n", - " British or Mixed British 37.5 \n", - " Indian or British Indian 41.2 \n", - " Irish 38.9 \n", - " Other Black 38.9 \n", - " Other White 38.9 \n", - " Other mixed 31.2 \n", - " Pakistani or British Pakistani 37.5 \n", - " Unknown 38.3 \n", - " White + Asian 42.1 \n", - " White + Black African 40.0 \n", - " White + Black Caribbean 37.5 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 36.4 \n", - " 2 37.9 \n", - " 3 38.6 \n", - " 4 39.0 \n", - " 5 Least deprived 37.7 \n", - " Unknown 38.5 \n", - "BMI 30+ 39.6 \n", - " under 30 38.0 \n", - "Chronic cardiac disease no 38.4 \n", - " yes 66.7 \n", - "Current COPD no 38.5 \n", - " yes 25.0 \n", - "DMARDs no 38.4 \n", - " yes 33.3 \n", - "Dementia no 38.5 \n", - " yes 33.3 \n", - "Psychosis, schizophrenia, or bipolar no 38.5 \n", - " yes 33.3 \n", - "Learning disability no 38.4 \n", - " yes 37.5 \n", - "SSRI (last 12 months) no 38.1 \n", - " yes 66.7 \n", - "Chemo or radiotherapy no 38.4 \n", - " yes 0.0 \n", - "Cancer (lung) no 38.6 \n", - " yes 40.0 \n", - "Cancer (excluding lung/haem) no 38.2 \n", - " yes 50.0 \n", - "Cancer (haematological) no 38.1 \n", - " yes 66.7 \n", + " Previous week's vaccination coverage (%) \\\n", + "Category Group \n", + "overall overall 38.2 \n", + "newly shielded since feb 15 no 37.7 \n", + " yes NaN \n", + "Sex F 41.9 \n", + " M 35.5 \n", + "Age band 16-29 28.6 \n", + " 30-39 37.5 \n", + " 40-49 42.9 \n", + " 50-59 57.1 \n", + " 60-69 33.3 \n", + " 70-79 29.4 \n", + " 80+ 37.5 \n", + "Ethnicity (broad categories) Black 30.0 \n", + " Mixed 36.4 \n", + " Other 45.5 \n", + " South Asian 33.3 \n", + " Unknown 40.0 \n", + " White 40.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 42.9 \n", + " 2 38.5 \n", + " 3 36.4 \n", + " 4 30.0 \n", + " 5 Least deprived 40.0 \n", + " Unknown 25.0 \n", + "Learning disability no 40.0 \n", + " yes 0.0 \n", "\n", - " Vaccinated over last 7d (%) \n", - "Category Group \n", - "overall overall 2.7 \n", - "Sex F 2.4 \n", - " M 3.4 \n", - "Ethnicity (broad categories) Black 1.8 \n", - " Mixed 1.8 \n", - " Other 3.9 \n", - " South Asian 0.0 \n", - " Unknown 2.3 \n", - " White 1.8 \n", - "ethnicity 16 groups African 6.7 \n", - " Bangladeshi or British Bangladeshi 0.0 \n", - " Caribbean 0.0 \n", - " Chinese 5.6 \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 5.5 \n", - " Other Black 5.5 \n", - " Other White 5.5 \n", - " Other mixed 6.3 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 4.3 \n", - " White + Asian 5.3 \n", - " White + Black African 0.0 \n", - " White + Black Caribbean 0.0 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 3.0 \n", - " 2 1.8 \n", - " 3 3.5 \n", - " 4 3.4 \n", - " 5 Least deprived 3.3 \n", - " Unknown 7.7 \n", - "BMI 30+ 2.1 \n", - " under 30 3.2 \n", - "Chronic cardiac disease no 2.6 \n", - " yes 0.0 \n", - "Current COPD no 2.6 \n", - " yes 0.0 \n", - "DMARDs no 2.6 \n", - " yes 0.0 \n", - "Dementia no 2.6 \n", - " yes 0.0 \n", - "Psychosis, schizophrenia, or bipolar no 2.6 \n", - " yes 0.0 \n", - "Learning disability no 2.9 \n", - " yes 0.0 \n", - "SSRI (last 12 months) no 2.9 \n", - " yes 0.0 \n", - "Chemo or radiotherapy no 2.9 \n", - " yes 33.3 \n", - "Cancer (lung) no 2.6 \n", - " yes 0.0 \n", - "Cancer (excluding lung/haem) no 2.9 \n", - " yes 0.0 \n", - "Cancer (haematological) no 2.9 \n", - " yes 0.0 " + " Vaccinated over last 7d (%) \n", + "Category Group \n", + "overall overall 3.3 \n", + "newly shielded since feb 15 no 3.3 \n", + " yes 0.0 \n", + "Sex F 3.3 \n", + " M 3.2 \n", + "Age band 16-29 0.0 \n", + " 30-39 0.0 \n", + " 40-49 14.2 \n", + " 50-59 0.0 \n", + " 60-69 0.0 \n", + " 70-79 5.9 \n", + " 80+ 0.0 \n", + "Ethnicity (broad categories) Black 10.0 \n", + " Mixed 9.1 \n", + " Other 0.0 \n", + " South Asian 0.0 \n", + " Unknown 0.0 \n", + " White 10.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 0.0 \n", + " 2 7.7 \n", + " 3 0.0 \n", + " 4 10.0 \n", + " 5 Least deprived 0.0 \n", + " Unknown 25.0 \n", + "Learning disability no 1.7 \n", + " yes 0.0 " ] }, "metadata": {}, @@ -37169,31 +63801,7 @@ { "data": { "text/markdown": [ - "- Population excludes those known to live in an elderly care home, based upon clinical coding." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/markdown": [ - "- Population excludes those who are currently shielding." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/markdown": [ - "- SSRIs group excludes individuals with Psychosis/ schizophrenia/bipolar, LD, or Dementia." + "- Population excludes those over 65 known to live in an elderly care home, based upon clinical coding." ], "text/plain": [ "" @@ -37206,7 +63814,7 @@ "data": { "text/markdown": [ "## \n", - " ## Cumulative vaccination figures among LD (aged 16-64) population \n", + " ## Cumulative vaccination figures among 65-69 population \n", " Please refer to footnotes below table for information." ], "text/plain": [ @@ -37238,371 +63846,787 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", - 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Vaccinated at 16 Apr (n)Vaccinated at 16 Apr (%)Total eligiblePrevious week's vaccination coverage (%)Vaccinated over last 7d (%)
316842.139938.63.5CategoryGroup
417542.441339.03.4overalloverall18041.543438.23.3
5 Least deprivednewly shielded since feb 15no17541.04273.3
Unknown4246.29138.57.7yes0NaN0NaN0.0
BMI30+28041.767239.62.1SexF9845.221741.93.3
under 3062341.2151238.0M8438.721735.53.2
Chronic cardiac diseaseno88941.0217038.42.6Age band16-291428.64928.60.0
yes1466.730-392166.737.55637.50.0
Current COPDno88941.1216338.52.640-492857.14942.914.2
yes725.050-592825.057.14957.10.0
DMARDsno88941.0217038.42.6
yes733.360-692133.36333.30.0
Dementiano88941.1216338.52.670-794235.311929.45.9
yes733.380+2133.337.55637.50.0
Psychosis, schizophrenia, or bipolarno88941.1216338.52.6Ethnicity (broad categories)Black2840.07030.010.0
yes733.32133.30.0Mixed3545.57736.49.1
Learning disabilityno88241.3213538.42.9Other3545.57745.50.0
yesSouth Asian2137.55637.533.36333.30.0
SSRI (last 12 months)no88941.0217038.12.9Unknown2840.07040.00.0
yes1466.72166.7White3550.07040.010.0
Index of Multiple Deprivation (quintiles)1 Most deprived4242.99842.90.0
Chemo or radiotherapyno89641.3217038.42.924246.29138.57.7
yes733.32132836.47736.40.033.3
Cancer (lung)no88941.2215638.62.642840.07030.010.0
yes145 Least deprived2840.0357040.00.0
Cancer (excluding lung/haem)no88941.1216338.22.9
yesUnknown1450.02850.00.025.025.0
Cancer (haematological)Learning disabilityno88941.0217038.12.917541.742040.01.7
yes00.01466.72166.70.00.0
Vaccinated at 30 Mar (n)Vaccinated at 30 Mar (%)Vaccinated at 16 Apr (n)Vaccinated at 16 Apr (%)Total eligiblePrevious week's vaccination coverage (%)Vaccinated over last 7d (%)
CategoryGroupCategoryGroup
overalloverall85939.3218437.12.2
SexF43439.0111337.11.9
M42739.9107137.32.6
Ethnicity (broad categories)Black14038.536436.52.0
Mixed14039.235737.31.9
overalloverall32441.378438.13.2Other15441.537139.61.9
SexFSouth Asian15439.339235.73.637.51.8
M16842.139940.41.7Unknown14040.834336.74.1
Age band021White12636.734334.72.0
ethnicity 16 groupsAfrican4235.311935.30.0
Bangladeshi or British Bangladeshi4237.511237.50.0
Caribbean4242.9499842.90.0
0-1514Chinese3535.79828.67.1
Other4938.912633.35.6
Other Asian4237.511237.50.0
British or Mixed British4233.312633.30.0
16-292137.5Indian or British Indian4941.211935.35.9
Irish5625.012.544.412638.95.5
30-342150.0Other Black4240.010533.316.76.7
35-392150.04250.0Other White4943.811237.56.3
Other mixed5640.014035.05.0
Pakistani or British Pakistani4938.912638.90.0
40-442142.9Unknown12639.132237.02.1
White + Asian4942.941.211935.35.9
White + Black African4233.312633.30.0
45-492142.9White + Black Caribbean4928.614.346.710546.70.0
50-5421Index of Multiple Deprivation (quintiles)1 Most deprived15439.339237.51.8
218238.846937.31.5
316139.740636.23.5
414736.839933.33.5
5 Least deprived15439.339239.30.0
Unknown5637.544.412644.40.0
55-59BMI30+25239.663737.42.2
under 3060939.5154036.82.7
Chronic cardiac diseaseno85439.5216337.22.3
yes00.01428.64928.60.00.0
60-642142.94928.614.3Current COPDno85439.5216337.22.3
65-6914yes733.3422133.30.0
70-74DMARDsno85439.5216337.22.3
yes733.32142.94942.933.30.0
75-792142.94942.9Dementiano85439.4217037.12.3
yes00.0140.00.0
80-84Psychosis, schizophrenia, or bipolarno85439.5216337.22.3
yes733.32142.94942.90.033.3
85-892844.46344.40.0Learning disabilityno84739.4214937.12.3
90+yes1450.02844.46333.311.150.00.0
Ethnicity (broad categories)Black4936.813331.65.2SSRI (last 12 months)no84739.3215637.02.3
Mixed3527.812627.8yes1466.72166.70.0
Other6347.413347.4Chemo or radiotherapyno84739.3215637.32.0
yes733.32133.30.0
South Asian6347.413342.15.3Cancer (lung)no84739.3215637.02.3
Unknown4946.710540.06.7yes1466.72133.333.4
White7045.515440.94.6Cancer (excluding lung/haem)no84739.3215637.02.3
yes733.32133.30.0
Cancer (haematological)no84739.3215637.02.3
yes733.32133.30.0
\n", "
" ], "text/plain": [ - " Vaccinated at 30 Mar (n) \\\n", - "Category Group \n", - "overall overall 324 \n", - "Sex F 154 \n", - " M 168 \n", - "Age band 0 21 \n", - " 0-15 14 \n", - " 16-29 21 \n", - " 30-34 21 \n", - " 35-39 21 \n", - " 40-44 21 \n", - " 45-49 21 \n", - " 50-54 21 \n", - " 55-59 14 \n", - " 60-64 21 \n", - " 65-69 14 \n", - " 70-74 21 \n", - " 75-79 21 \n", - " 80-84 21 \n", - " 85-89 28 \n", - " 90+ 28 \n", - "Ethnicity (broad categories) Black 49 \n", - " Mixed 35 \n", - " Other 63 \n", - " South Asian 63 \n", - " Unknown 49 \n", - " White 70 \n", + " Vaccinated at 16 Apr (n) \\\n", + "Category Group \n", + "overall overall 859 \n", + "Sex F 434 \n", + " M 427 \n", + "Ethnicity (broad categories) Black 140 \n", + " Mixed 140 \n", + " Other 154 \n", + " South Asian 154 \n", + " Unknown 140 \n", + " White 126 \n", + "ethnicity 16 groups African 42 \n", + " Bangladeshi or British Bangladeshi 42 \n", + " Caribbean 42 \n", + " Chinese 35 \n", + " Other 49 \n", + " Other Asian 42 \n", + " British or Mixed British 42 \n", + " Indian or British Indian 49 \n", + " Irish 56 \n", + " Other Black 42 \n", + " Other White 49 \n", + " Other mixed 56 \n", + " Pakistani or British Pakistani 49 \n", + " Unknown 126 \n", + " White + Asian 49 \n", + " White + Black African 42 \n", + " White + Black Caribbean 49 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 154 \n", + " 2 182 \n", + " 3 161 \n", + " 4 147 \n", + " 5 Least deprived 154 \n", + " Unknown 56 \n", + "BMI 30+ 252 \n", + " under 30 609 \n", + "Chronic cardiac disease no 854 \n", + " yes 0 \n", + "Current COPD no 854 \n", + " yes 7 \n", + "DMARDs no 854 \n", + " yes 7 \n", + "Dementia no 854 \n", + " yes 0 \n", + "Psychosis, schizophrenia, or bipolar no 854 \n", + " yes 7 \n", + "Learning disability no 847 \n", + " yes 14 \n", + "SSRI (last 12 months) no 847 \n", + " yes 14 \n", + "Chemo or radiotherapy no 847 \n", + " yes 7 \n", + "Cancer (lung) no 847 \n", + " yes 14 \n", + "Cancer (excluding lung/haem) no 847 \n", + " yes 7 \n", + "Cancer (haematological) no 847 \n", + " yes 7 \n", "\n", - " Vaccinated at 30 Mar (%) \\\n", - "Category Group \n", - "overall overall 41.3 \n", - "Sex F 39.3 \n", - " M 42.1 \n", - "Age band 0 42.9 \n", - " 0-15 33.3 \n", - " 16-29 37.5 \n", - " 30-34 50.0 \n", - " 35-39 50.0 \n", - " 40-44 42.9 \n", - " 45-49 42.9 \n", - " 50-54 37.5 \n", - " 55-59 28.6 \n", - " 60-64 42.9 \n", - " 65-69 33.3 \n", - " 70-74 42.9 \n", - " 75-79 42.9 \n", - " 80-84 42.9 \n", - " 85-89 44.4 \n", - " 90+ 44.4 \n", - "Ethnicity (broad categories) Black 36.8 \n", - " Mixed 27.8 \n", - " Other 47.4 \n", - " South Asian 47.4 \n", - " Unknown 46.7 \n", - " White 45.5 \n", + " Vaccinated at 16 Apr (%) \\\n", + "Category Group \n", + "overall overall 39.3 \n", + "Sex F 39.0 \n", + " M 39.9 \n", + "Ethnicity (broad categories) Black 38.5 \n", + " Mixed 39.2 \n", + " Other 41.5 \n", + " South Asian 39.3 \n", + " Unknown 40.8 \n", + " White 36.7 \n", + "ethnicity 16 groups African 35.3 \n", + " Bangladeshi or British Bangladeshi 37.5 \n", + " Caribbean 42.9 \n", + " Chinese 35.7 \n", + " Other 38.9 \n", + " Other Asian 37.5 \n", + " British or Mixed British 33.3 \n", + " Indian or British Indian 41.2 \n", + " Irish 44.4 \n", + " Other Black 40.0 \n", + " Other White 43.8 \n", + " Other mixed 40.0 \n", + " Pakistani or British Pakistani 38.9 \n", + " Unknown 39.1 \n", + " White + Asian 41.2 \n", + " White + Black African 33.3 \n", + " White + Black Caribbean 46.7 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 39.3 \n", + " 2 38.8 \n", + " 3 39.7 \n", + " 4 36.8 \n", + " 5 Least deprived 39.3 \n", + " Unknown 44.4 \n", + "BMI 30+ 39.6 \n", + " under 30 39.5 \n", + "Chronic cardiac disease no 39.5 \n", + " yes 0.0 \n", + "Current COPD no 39.5 \n", + " yes 33.3 \n", + "DMARDs no 39.5 \n", + " yes 33.3 \n", + "Dementia no 39.4 \n", + " yes 0.0 \n", + "Psychosis, schizophrenia, or bipolar no 39.5 \n", + " yes 33.3 \n", + "Learning disability no 39.4 \n", + " yes 50.0 \n", + "SSRI (last 12 months) no 39.3 \n", + " yes 66.7 \n", + "Chemo or radiotherapy no 39.3 \n", + " yes 33.3 \n", + "Cancer (lung) no 39.3 \n", + " yes 66.7 \n", + "Cancer (excluding lung/haem) no 39.3 \n", + " yes 33.3 \n", + "Cancer (haematological) no 39.3 \n", + " yes 33.3 \n", "\n", - " Total eligible \\\n", - "Category Group \n", - "overall overall 784 \n", - "Sex F 392 \n", - " M 399 \n", - "Age band 0 49 \n", - " 0-15 42 \n", - " 16-29 56 \n", - " 30-34 42 \n", - " 35-39 42 \n", - " 40-44 49 \n", - " 45-49 49 \n", - " 50-54 56 \n", - " 55-59 49 \n", - " 60-64 49 \n", - " 65-69 42 \n", - " 70-74 49 \n", - " 75-79 49 \n", - " 80-84 49 \n", - " 85-89 63 \n", - " 90+ 63 \n", - "Ethnicity (broad categories) Black 133 \n", - " Mixed 126 \n", - " Other 133 \n", - " South Asian 133 \n", - " Unknown 105 \n", - " White 154 \n", + " Total eligible \\\n", + "Category Group \n", + "overall overall 2184 \n", + "Sex F 1113 \n", + " M 1071 \n", + "Ethnicity (broad categories) Black 364 \n", + " Mixed 357 \n", + " Other 371 \n", + " South Asian 392 \n", + " Unknown 343 \n", + " White 343 \n", + "ethnicity 16 groups African 119 \n", + " Bangladeshi or British Bangladeshi 112 \n", + " Caribbean 98 \n", + " Chinese 98 \n", + " Other 126 \n", + " Other Asian 112 \n", + " British or Mixed British 126 \n", + " Indian or British Indian 119 \n", + " Irish 126 \n", + " Other Black 105 \n", + " Other White 112 \n", + " Other mixed 140 \n", + " Pakistani or British Pakistani 126 \n", + " Unknown 322 \n", + " White + Asian 119 \n", + " White + Black African 126 \n", + " White + Black Caribbean 105 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 392 \n", + " 2 469 \n", + " 3 406 \n", + " 4 399 \n", + " 5 Least deprived 392 \n", + " Unknown 126 \n", + "BMI 30+ 637 \n", + " under 30 1540 \n", + "Chronic cardiac disease no 2163 \n", + " yes 14 \n", + "Current COPD no 2163 \n", + " yes 21 \n", + "DMARDs no 2163 \n", + " yes 21 \n", + "Dementia no 2170 \n", + " yes 14 \n", + "Psychosis, schizophrenia, or bipolar no 2163 \n", + " yes 21 \n", + "Learning disability no 2149 \n", + " yes 28 \n", + "SSRI (last 12 months) no 2156 \n", + " yes 21 \n", + "Chemo or radiotherapy no 2156 \n", + " yes 21 \n", + "Cancer (lung) no 2156 \n", + " yes 21 \n", + "Cancer (excluding lung/haem) no 2156 \n", + " yes 21 \n", + "Cancer (haematological) no 2156 \n", + " yes 21 \n", "\n", - " Previous week's vaccination coverage (%) \\\n", - "Category Group \n", - "overall overall 38.1 \n", - "Sex F 35.7 \n", - " M 40.4 \n", - "Age band 0 42.9 \n", - " 0-15 33.3 \n", - " 16-29 25.0 \n", - " 30-34 33.3 \n", - " 35-39 50.0 \n", - " 40-44 42.9 \n", - " 45-49 28.6 \n", - " 50-54 37.5 \n", - " 55-59 28.6 \n", - " 60-64 28.6 \n", - " 65-69 33.3 \n", - " 70-74 42.9 \n", - " 75-79 42.9 \n", - " 80-84 42.9 \n", - " 85-89 44.4 \n", - " 90+ 33.3 \n", - "Ethnicity (broad categories) Black 31.6 \n", - " Mixed 27.8 \n", - " Other 47.4 \n", - " South Asian 42.1 \n", - " Unknown 40.0 \n", - " White 40.9 \n", + " Previous week's vaccination coverage (%) \\\n", + "Category Group \n", + "overall overall 37.1 \n", + "Sex F 37.1 \n", + " M 37.3 \n", + "Ethnicity (broad categories) Black 36.5 \n", + " Mixed 37.3 \n", + " Other 39.6 \n", + " South Asian 37.5 \n", + " Unknown 36.7 \n", + " White 34.7 \n", + "ethnicity 16 groups African 35.3 \n", + " Bangladeshi or British Bangladeshi 37.5 \n", + " Caribbean 42.9 \n", + " Chinese 28.6 \n", + " Other 33.3 \n", + " Other Asian 37.5 \n", + " British or Mixed British 33.3 \n", + " Indian or British Indian 35.3 \n", + " Irish 38.9 \n", + " Other Black 33.3 \n", + " Other White 37.5 \n", + " Other mixed 35.0 \n", + " Pakistani or British Pakistani 38.9 \n", + " Unknown 37.0 \n", + " White + Asian 35.3 \n", + " White + Black African 33.3 \n", + " White + Black Caribbean 46.7 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 37.5 \n", + " 2 37.3 \n", + " 3 36.2 \n", + " 4 33.3 \n", + " 5 Least deprived 39.3 \n", + " Unknown 44.4 \n", + "BMI 30+ 37.4 \n", + " under 30 36.8 \n", + "Chronic cardiac disease no 37.2 \n", + " yes 0.0 \n", + "Current COPD no 37.2 \n", + " yes 33.3 \n", + "DMARDs no 37.2 \n", + " yes 33.3 \n", + "Dementia no 37.1 \n", + " yes 0.0 \n", + "Psychosis, schizophrenia, or bipolar no 37.2 \n", + " yes 0.0 \n", + "Learning disability no 37.1 \n", + " yes 50.0 \n", + "SSRI (last 12 months) no 37.0 \n", + " yes 66.7 \n", + "Chemo or radiotherapy no 37.3 \n", + " yes 33.3 \n", + "Cancer (lung) no 37.0 \n", + " yes 33.3 \n", + "Cancer (excluding lung/haem) no 37.0 \n", + " yes 33.3 \n", + "Cancer (haematological) no 37.0 \n", + " yes 33.3 \n", "\n", - " Vaccinated over last 7d (%) \n", - "Category Group \n", - "overall overall 3.2 \n", - "Sex F 3.6 \n", - " M 1.7 \n", - "Age band 0 0.0 \n", - " 0-15 0.0 \n", - " 16-29 12.5 \n", - " 30-34 16.7 \n", - " 35-39 0.0 \n", - " 40-44 0.0 \n", - " 45-49 14.3 \n", - " 50-54 0.0 \n", - " 55-59 0.0 \n", - " 60-64 14.3 \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+ 11.1 \n", - "Ethnicity (broad categories) Black 5.2 \n", - " Mixed 0.0 \n", - " Other 0.0 \n", - " South Asian 5.3 \n", - " Unknown 6.7 \n", - " White 4.6 " + " Vaccinated over last 7d (%) \n", + "Category Group \n", + "overall overall 2.2 \n", + "Sex F 1.9 \n", + " M 2.6 \n", + "Ethnicity (broad categories) Black 2.0 \n", + " Mixed 1.9 \n", + " Other 1.9 \n", + " South Asian 1.8 \n", + " Unknown 4.1 \n", + " White 2.0 \n", + "ethnicity 16 groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 0.0 \n", + " Caribbean 0.0 \n", + " Chinese 7.1 \n", + " Other 5.6 \n", + " Other Asian 0.0 \n", + " British or Mixed British 0.0 \n", + " Indian or British Indian 5.9 \n", + " Irish 5.5 \n", + " Other Black 6.7 \n", + " Other White 6.3 \n", + " Other mixed 5.0 \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", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 1.8 \n", + " 2 1.5 \n", + " 3 3.5 \n", + " 4 3.5 \n", + " 5 Least deprived 0.0 \n", + " Unknown 0.0 \n", + "BMI 30+ 2.2 \n", + " under 30 2.7 \n", + "Chronic cardiac disease no 2.3 \n", + " yes 0.0 \n", + "Current COPD no 2.3 \n", + " yes 0.0 \n", + "DMARDs no 2.3 \n", + " yes 0.0 \n", + "Dementia no 2.3 \n", + " yes 0.0 \n", + "Psychosis, schizophrenia, or bipolar no 2.3 \n", + " yes 33.3 \n", + "Learning disability no 2.3 \n", + " yes 0.0 \n", + "SSRI (last 12 months) no 2.3 \n", + " yes 0.0 \n", + "Chemo or radiotherapy no 2.0 \n", + " yes 0.0 \n", + "Cancer (lung) no 2.3 \n", + " yes 33.4 \n", + "Cancer (excluding lung/haem) no 2.3 \n", + " yes 0.0 \n", + "Cancer (haematological) no 2.3 \n", + " yes 0.0 " ] }, "metadata": {}, @@ -37621,6 +64645,18 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/markdown": [ + "- Population excludes those known to live in an elderly care home, based upon clinical coding." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "data": { "text/markdown": [ @@ -37633,11 +64669,23 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/markdown": [ + "- SSRIs group excludes individuals with Psychosis/ schizophrenia/bipolar, LD, or Dementia." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "data": { "text/markdown": [ "## \n", - " ## Cumulative vaccination figures among 60-64 population \n", + " ## Cumulative vaccination figures among LD (aged 16-64) population \n", " Please refer to footnotes below table for information." ], "text/plain": [ @@ -37669,8 +64717,8 @@ " \n", " \n", " \n", - " Vaccinated at 30 Mar (n)\n", - " Vaccinated at 30 Mar (%)\n", + " Vaccinated at 16 Apr (n)\n", + " Vaccinated at 16 Apr (%)\n", " Total eligible\n", " Previous week's vaccination coverage (%)\n", " Vaccinated over last 7d (%)\n", @@ -37689,740 +64737,351 @@ " \n", " overall\n", " overall\n", - " 1044\n", - " 39.7\n", - " 2632\n", - " 37.5\n", - " 2.2\n", + " 344\n", + " 41.6\n", + " 826\n", + " 39.6\n", + " 2.0\n", " \n", " \n", " Sex\n", " F\n", - " 532\n", - " 39.2\n", - " 1358\n", - " 37.6\n", - " 1.6\n", - " \n", - " \n", - " M\n", - " 511\n", - " 40.1\n", - " 1274\n", - " 37.9\n", - " 2.2\n", - " \n", - " \n", - " Ethnicity (broad categories)\n", - " Black\n", - " 175\n", - " 39.7\n", - " 441\n", - " 34.9\n", - " 4.8\n", - " \n", - " \n", - " Mixed\n", - " 154\n", - " 37.9\n", - " 406\n", - " 36.2\n", - " 1.7\n", - " \n", - " \n", - " Other\n", - " 175\n", - " 37.3\n", - " 469\n", - " 34.3\n", - " 3.0\n", - " \n", - " \n", - " South Asian\n", - " 196\n", + " 182\n", " 40.6\n", - " 483\n", - " 37.7\n", - " 2.9\n", + " 448\n", + " 39.1\n", + " 1.5\n", " \n", " \n", - " Unknown\n", + " M\n", " 161\n", - " 41.1\n", - " 392\n", - " 39.3\n", - " 1.8\n", - " \n", - " \n", - " White\n", - " 189\n", - " 42.9\n", - " 441\n", - " 41.3\n", - " 1.6\n", - " \n", - " \n", - " ethnicity 16 groups\n", - " African\n", - " 42\n", - " 35.3\n", - " 119\n", - " 29.4\n", - " 5.9\n", - " \n", - " \n", - " Bangladeshi or British Bangladeshi\n", - " 56\n", - " 40.0\n", - " 140\n", - " 35.0\n", - " 5.0\n", + " 42.6\n", + " 378\n", + " 40.7\n", + " 1.9\n", " \n", " \n", - " Caribbean\n", - " 56\n", + " Age band\n", + " 0\n", + " 14\n", " 40.0\n", - " 140\n", + " 35\n", " 40.0\n", " 0.0\n", " \n", " \n", - " Chinese\n", - " 56\n", - " 47.1\n", - " 119\n", - " 41.2\n", - " 5.9\n", - " \n", - " \n", - " Other\n", - " 56\n", - " 42.1\n", - " 133\n", - " 36.8\n", - " 5.3\n", - " \n", - " \n", - " Other Asian\n", - " 63\n", - " 45.0\n", - " 140\n", - " 40.0\n", - " 5.0\n", - " \n", - " \n", - " British or Mixed British\n", + " 0-15\n", + " 28\n", + " 50.0\n", " 56\n", - " 42.1\n", - " 133\n", - " 42.1\n", - " 0.0\n", + " 37.5\n", + " 12.5\n", " \n", " \n", - " Indian or British Indian\n", + " 16-29\n", + " 21\n", + " 37.5\n", " 56\n", - " 44.4\n", - " 126\n", - " 44.4\n", - " 0.0\n", + " 25.0\n", + " 12.5\n", " \n", " \n", - " Irish\n", + " 30-34\n", + " 21\n", + " 42.9\n", " 49\n", - " 36.8\n", - " 133\n", - " 36.8\n", + " 42.9\n", " 0.0\n", " \n", " \n", - " Other Black\n", + " 35-39\n", + " 35\n", + " 55.6\n", " 63\n", - " 37.5\n", - " 168\n", - " 33.3\n", - " 4.2\n", - " \n", - " \n", - " Other White\n", - " 56\n", - " 44.4\n", - " 126\n", " 44.4\n", - " 0.0\n", - " \n", - " \n", - " Other mixed\n", - " 70\n", - " 47.6\n", - " 147\n", - " 42.9\n", - " 4.7\n", + " 11.2\n", " \n", " \n", - " Pakistani or British Pakistani\n", + " 40-44\n", + " 21\n", + " 37.5\n", " 56\n", - " 42.1\n", - " 133\n", - " 42.1\n", + " 37.5\n", " 0.0\n", " \n", " \n", - " Unknown\n", - " 140\n", - " 34.5\n", - " 406\n", - " 32.8\n", - " 1.7\n", - " \n", - " \n", - " White + Asian\n", - " 63\n", - " 40.9\n", - " 154\n", - " 36.4\n", - " 4.5\n", - " \n", - " \n", - " White + Black African\n", - " 56\n", - " 38.1\n", - " 147\n", - " 33.3\n", - " 4.8\n", - " \n", - " \n", - " White + Black Caribbean\n", - " 63\n", - " 39.1\n", - " 161\n", - " 34.8\n", - " 4.3\n", - " \n", - " \n", - " Index of Multiple Deprivation (quintiles)\n", - " 1 Most deprived\n", - " 203\n", - " 43.3\n", - " 469\n", - " 40.3\n", - " 3.0\n", - " \n", - " \n", - " 2\n", - " 196\n", - " 39.4\n", - " 497\n", - " 36.6\n", - " 2.8\n", - " \n", - " \n", - " 3\n", - " 189\n", - " 38.0\n", - " 497\n", - " 35.2\n", - " 2.8\n", - " \n", - " \n", - " 4\n", - " 189\n", - " 38.0\n", - " 497\n", - " 36.6\n", - " 1.4\n", - " \n", - " \n", - " 5 Least deprived\n", - " 203\n", - " 39.2\n", - " 518\n", - " 37.8\n", - " 1.4\n", + " 45-49\n", + " 21\n", + " 42.9\n", + " 49\n", + " 28.6\n", + " 14.3\n", " \n", " \n", - " Unknown\n", - " 63\n", + " 50-54\n", + " 21\n", " 42.9\n", - " 147\n", + " 49\n", " 42.9\n", " 0.0\n", " \n", " \n", - " BMI\n", - " 30+\n", - " 350\n", - " 42.0\n", - " 833\n", - " 39.5\n", - " 2.5\n", - " \n", - " \n", - " under 30\n", - " 693\n", - " 38.5\n", - " 1799\n", - " 36.6\n", - " 1.9\n", - " \n", - " \n", - " Chronic cardiac disease\n", - " no\n", - " 1029\n", - " 39.5\n", - " 2604\n", - " 37.4\n", - " 2.1\n", - " \n", - " \n", - " yes\n", - " 14\n", - " 66.7\n", + " 55-59\n", " 21\n", - " 66.7\n", - " 0.0\n", - " \n", - " \n", - " Current COPD\n", - " no\n", - " 1043\n", - " 39.9\n", - " 2611\n", - " 37.8\n", - " 2.1\n", + " 42.9\n", + " 49\n", + " 28.6\n", + " 14.3\n", " \n", " \n", - " yes\n", - " 0\n", - " 0.0\n", + " 60-64\n", " 21\n", + " 37.5\n", + " 56\n", + " 37.5\n", " 0.0\n", - " 0.0\n", - " \n", - " \n", - " DMARDs\n", - " no\n", - " 1036\n", - " 39.9\n", - " 2597\n", - " 37.7\n", - " 2.2\n", - " \n", - " \n", - " yes\n", - " 7\n", - " 25.0\n", - " 28\n", - " 25.0\n", - " 0.0\n", - " \n", - " \n", - " Dementia\n", - " no\n", - " 1029\n", - " 39.5\n", - " 2604\n", - " 37.4\n", - " 2.1\n", " \n", " \n", - " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", + " 65-69\n", + " 21\n", + " 42.9\n", + " 49\n", + " 42.9\n", " 0.0\n", " \n", " \n", - " Psychosis, schizophrenia, or bipolar\n", - " no\n", - " 1036\n", - " 39.8\n", - " 2604\n", - " 37.6\n", - " 2.2\n", - " \n", - " \n", - " yes\n", - " 0\n", - " 0.0\n", + " 70-74\n", " 21\n", + " 42.9\n", + " 49\n", + " 42.9\n", " 0.0\n", + " \n", + " \n", + " 75-79\n", + " 21\n", + " 50.0\n", + " 42\n", + " 50.0\n", " 0.0\n", " \n", " \n", - " SSRI (last 12 months)\n", - " no\n", - " 1036\n", - " 39.9\n", - " 2597\n", - " 37.7\n", - " 2.2\n", - " \n", - " \n", - " yes\n", - " 7\n", - " 25.0\n", - " 28\n", - " 25.0\n", - " 0.0\n", - " \n", - " \n", - " Chemo or radiotherapy\n", - " no\n", - " 1036\n", - " 39.8\n", - " 2604\n", - " 37.6\n", - " 2.2\n", + " 80-84\n", + " 21\n", + " 42.9\n", + " 49\n", + " 42.9\n", + " 0.0\n", " \n", " \n", - " yes\n", - " 7\n", - " 25.0\n", + " 85-89\n", " 28\n", - " 25.0\n", + " 50.0\n", + " 56\n", + " 50.0\n", " 0.0\n", " \n", " \n", - " Cancer (lung)\n", - " no\n", - " 1029\n", - " 39.7\n", - " 2590\n", - " 37.6\n", - " 2.1\n", + " 90+\n", + " 21\n", + " 37.5\n", + " 56\n", + " 37.5\n", + " 0.0\n", " \n", " \n", - " yes\n", - " 14\n", - " 40.0\n", - " 35\n", + " Ethnicity (broad categories)\n", + " Black\n", + " 56\n", " 40.0\n", + " 140\n", + " 35.0\n", + " 5.0\n", + " \n", + " \n", + " Mixed\n", + " 63\n", + " 47.4\n", + " 133\n", + " 47.4\n", " 0.0\n", " \n", " \n", - " Cancer (excluding lung/haem)\n", - " no\n", - " 1036\n", - " 39.9\n", - " 2597\n", - " 37.7\n", - " 2.2\n", + " Other\n", + " 56\n", + " 40.0\n", + " 140\n", + " 35.0\n", + " 5.0\n", " \n", " \n", - " yes\n", - " 7\n", - " 25.0\n", - " 28\n", - " 25.0\n", + " South Asian\n", + " 63\n", + " 45.0\n", + " 140\n", + " 45.0\n", " 0.0\n", " \n", " \n", - " Cancer (haematological)\n", - " no\n", - " 1029\n", - " 39.5\n", - " 2604\n", - " 37.4\n", - " 2.1\n", + " Unknown\n", + " 49\n", + " 38.9\n", + " 126\n", + " 33.3\n", + " 5.6\n", " \n", " \n", - " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50.0\n", - " 0.0\n", + " White\n", + " 63\n", + " 40.9\n", + " 154\n", + " 36.4\n", + " 4.5\n", " \n", " \n", "\n", "" ], "text/plain": [ - " Vaccinated at 30 Mar (n) \\\n", - "Category Group \n", - "overall overall 1044 \n", - "Sex F 532 \n", - " M 511 \n", - "Ethnicity (broad categories) Black 175 \n", - " Mixed 154 \n", - " Other 175 \n", - " South Asian 196 \n", - " Unknown 161 \n", - " White 189 \n", - "ethnicity 16 groups African 42 \n", - " Bangladeshi or British Bangladeshi 56 \n", - " Caribbean 56 \n", - " Chinese 56 \n", - " Other 56 \n", - " Other Asian 63 \n", - " British or Mixed British 56 \n", - " Indian or British Indian 56 \n", - " Irish 49 \n", - " Other Black 63 \n", - " Other White 56 \n", - " Other mixed 70 \n", - " Pakistani or British Pakistani 56 \n", - " Unknown 140 \n", - " White + Asian 63 \n", - " White + Black African 56 \n", - " White + Black Caribbean 63 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 203 \n", - " 2 196 \n", - " 3 189 \n", - " 4 189 \n", - " 5 Least deprived 203 \n", - " Unknown 63 \n", - "BMI 30+ 350 \n", - " under 30 693 \n", - "Chronic cardiac disease no 1029 \n", - " yes 14 \n", - "Current COPD no 1043 \n", - " yes 0 \n", - "DMARDs no 1036 \n", - " yes 7 \n", - "Dementia no 1029 \n", - " yes 14 \n", - "Psychosis, schizophrenia, or bipolar no 1036 \n", - " yes 0 \n", - "SSRI (last 12 months) no 1036 \n", - " yes 7 \n", - "Chemo or radiotherapy no 1036 \n", - " yes 7 \n", - "Cancer (lung) no 1029 \n", - " yes 14 \n", - "Cancer (excluding lung/haem) no 1036 \n", - " yes 7 \n", - "Cancer (haematological) no 1029 \n", - " yes 14 \n", + " Vaccinated at 16 Apr (n) \\\n", + "Category Group \n", + "overall overall 344 \n", + "Sex F 182 \n", + " M 161 \n", + "Age band 0 14 \n", + " 0-15 28 \n", + " 16-29 21 \n", + " 30-34 21 \n", + " 35-39 35 \n", + " 40-44 21 \n", + " 45-49 21 \n", + " 50-54 21 \n", + " 55-59 21 \n", + " 60-64 21 \n", + " 65-69 21 \n", + " 70-74 21 \n", + " 75-79 21 \n", + " 80-84 21 \n", + " 85-89 28 \n", + " 90+ 21 \n", + "Ethnicity (broad categories) Black 56 \n", + " Mixed 63 \n", + " Other 56 \n", + " South Asian 63 \n", + " Unknown 49 \n", + " White 63 \n", "\n", - " Vaccinated at 30 Mar (%) \\\n", - "Category Group \n", - "overall overall 39.7 \n", - "Sex F 39.2 \n", - " M 40.1 \n", - "Ethnicity (broad categories) Black 39.7 \n", - " Mixed 37.9 \n", - " Other 37.3 \n", - " South Asian 40.6 \n", - " Unknown 41.1 \n", - " White 42.9 \n", - "ethnicity 16 groups African 35.3 \n", - " Bangladeshi or British Bangladeshi 40.0 \n", - " Caribbean 40.0 \n", - " Chinese 47.1 \n", - " Other 42.1 \n", - " Other Asian 45.0 \n", - " British or Mixed British 42.1 \n", - " Indian or British Indian 44.4 \n", - " Irish 36.8 \n", - " Other Black 37.5 \n", - " Other White 44.4 \n", - " Other mixed 47.6 \n", - " Pakistani or British Pakistani 42.1 \n", - " Unknown 34.5 \n", - " White + Asian 40.9 \n", - " White + Black African 38.1 \n", - " White + Black Caribbean 39.1 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 43.3 \n", - " 2 39.4 \n", - " 3 38.0 \n", - " 4 38.0 \n", - " 5 Least deprived 39.2 \n", - " Unknown 42.9 \n", - "BMI 30+ 42.0 \n", - " under 30 38.5 \n", - "Chronic cardiac disease no 39.5 \n", - " yes 66.7 \n", - "Current COPD no 39.9 \n", - " yes 0.0 \n", - "DMARDs no 39.9 \n", - " yes 25.0 \n", - "Dementia no 39.5 \n", - " yes 50.0 \n", - "Psychosis, schizophrenia, or bipolar no 39.8 \n", - " yes 0.0 \n", - "SSRI (last 12 months) no 39.9 \n", - " yes 25.0 \n", - "Chemo or radiotherapy no 39.8 \n", - " yes 25.0 \n", - "Cancer (lung) no 39.7 \n", - " yes 40.0 \n", - "Cancer (excluding lung/haem) no 39.9 \n", - " yes 25.0 \n", - "Cancer (haematological) no 39.5 \n", - " yes 50.0 \n", + " Vaccinated at 16 Apr (%) \\\n", + "Category Group \n", + "overall overall 41.6 \n", + "Sex F 40.6 \n", + " M 42.6 \n", + "Age band 0 40.0 \n", + " 0-15 50.0 \n", + " 16-29 37.5 \n", + " 30-34 42.9 \n", + " 35-39 55.6 \n", + " 40-44 37.5 \n", + " 45-49 42.9 \n", + " 50-54 42.9 \n", + " 55-59 42.9 \n", + " 60-64 37.5 \n", + " 65-69 42.9 \n", + " 70-74 42.9 \n", + " 75-79 50.0 \n", + " 80-84 42.9 \n", + " 85-89 50.0 \n", + " 90+ 37.5 \n", + "Ethnicity (broad categories) Black 40.0 \n", + " Mixed 47.4 \n", + " Other 40.0 \n", + " South Asian 45.0 \n", + " Unknown 38.9 \n", + " White 40.9 \n", "\n", - " Total eligible \\\n", - "Category Group \n", - "overall overall 2632 \n", - "Sex F 1358 \n", - " M 1274 \n", - "Ethnicity (broad categories) Black 441 \n", - " Mixed 406 \n", - " Other 469 \n", - " South Asian 483 \n", - " Unknown 392 \n", - " White 441 \n", - "ethnicity 16 groups African 119 \n", - " Bangladeshi or British Bangladeshi 140 \n", - " Caribbean 140 \n", - " Chinese 119 \n", - " Other 133 \n", - " Other Asian 140 \n", - " British or Mixed British 133 \n", - " Indian or British Indian 126 \n", - " Irish 133 \n", - " Other Black 168 \n", - " Other White 126 \n", - " Other mixed 147 \n", - " Pakistani or British Pakistani 133 \n", - " Unknown 406 \n", - " White + Asian 154 \n", - " White + Black African 147 \n", - " White + Black Caribbean 161 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 469 \n", - " 2 497 \n", - " 3 497 \n", - " 4 497 \n", - " 5 Least deprived 518 \n", - " Unknown 147 \n", - "BMI 30+ 833 \n", - " under 30 1799 \n", - "Chronic cardiac disease no 2604 \n", - " yes 21 \n", - "Current COPD no 2611 \n", - " yes 21 \n", - "DMARDs no 2597 \n", - " yes 28 \n", - "Dementia no 2604 \n", - " yes 28 \n", - "Psychosis, schizophrenia, or bipolar no 2604 \n", - " yes 21 \n", - "SSRI (last 12 months) no 2597 \n", - " yes 28 \n", - "Chemo or radiotherapy no 2604 \n", - " yes 28 \n", - "Cancer (lung) no 2590 \n", - " yes 35 \n", - "Cancer (excluding lung/haem) no 2597 \n", - " yes 28 \n", - "Cancer (haematological) no 2604 \n", - " yes 28 \n", + " Total eligible \\\n", + "Category Group \n", + "overall overall 826 \n", + "Sex F 448 \n", + " M 378 \n", + "Age band 0 35 \n", + " 0-15 56 \n", + " 16-29 56 \n", + " 30-34 49 \n", + " 35-39 63 \n", + " 40-44 56 \n", + " 45-49 49 \n", + " 50-54 49 \n", + " 55-59 49 \n", + " 60-64 56 \n", + " 65-69 49 \n", + " 70-74 49 \n", + " 75-79 42 \n", + " 80-84 49 \n", + " 85-89 56 \n", + " 90+ 56 \n", + "Ethnicity (broad categories) Black 140 \n", + " Mixed 133 \n", + " Other 140 \n", + " South Asian 140 \n", + " Unknown 126 \n", + " White 154 \n", "\n", - " Previous week's vaccination coverage (%) \\\n", - "Category Group \n", - "overall overall 37.5 \n", - "Sex F 37.6 \n", - " M 37.9 \n", - "Ethnicity (broad categories) Black 34.9 \n", - " Mixed 36.2 \n", - " Other 34.3 \n", - " South Asian 37.7 \n", - " Unknown 39.3 \n", - " White 41.3 \n", - "ethnicity 16 groups African 29.4 \n", - " Bangladeshi or British Bangladeshi 35.0 \n", - " Caribbean 40.0 \n", - " Chinese 41.2 \n", - " Other 36.8 \n", - " Other Asian 40.0 \n", - " British or Mixed British 42.1 \n", - " Indian or British Indian 44.4 \n", - " Irish 36.8 \n", - " Other Black 33.3 \n", - " Other White 44.4 \n", - " Other mixed 42.9 \n", - " Pakistani or British Pakistani 42.1 \n", - " Unknown 32.8 \n", - " White + Asian 36.4 \n", - " White + Black African 33.3 \n", - " White + Black Caribbean 34.8 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 40.3 \n", - " 2 36.6 \n", - " 3 35.2 \n", - " 4 36.6 \n", - " 5 Least deprived 37.8 \n", - " Unknown 42.9 \n", - "BMI 30+ 39.5 \n", - " under 30 36.6 \n", - "Chronic cardiac disease no 37.4 \n", - " yes 66.7 \n", - "Current COPD no 37.8 \n", - " yes 0.0 \n", - "DMARDs no 37.7 \n", - " yes 25.0 \n", - "Dementia no 37.4 \n", - " yes 50.0 \n", - "Psychosis, schizophrenia, or bipolar no 37.6 \n", - " yes 0.0 \n", - "SSRI (last 12 months) no 37.7 \n", - " yes 25.0 \n", - "Chemo or radiotherapy no 37.6 \n", - " yes 25.0 \n", - "Cancer (lung) no 37.6 \n", - " yes 40.0 \n", - "Cancer (excluding lung/haem) no 37.7 \n", - " yes 25.0 \n", - "Cancer (haematological) no 37.4 \n", - " yes 50.0 \n", + " Previous week's vaccination coverage (%) \\\n", + "Category Group \n", + "overall overall 39.6 \n", + "Sex F 39.1 \n", + " M 40.7 \n", + "Age band 0 40.0 \n", + " 0-15 37.5 \n", + " 16-29 25.0 \n", + " 30-34 42.9 \n", + " 35-39 44.4 \n", + " 40-44 37.5 \n", + " 45-49 28.6 \n", + " 50-54 42.9 \n", + " 55-59 28.6 \n", + " 60-64 37.5 \n", + " 65-69 42.9 \n", + " 70-74 42.9 \n", + " 75-79 50.0 \n", + " 80-84 42.9 \n", + " 85-89 50.0 \n", + " 90+ 37.5 \n", + "Ethnicity (broad categories) Black 35.0 \n", + " Mixed 47.4 \n", + " Other 35.0 \n", + " South Asian 45.0 \n", + " Unknown 33.3 \n", + " White 36.4 \n", "\n", - " Vaccinated over last 7d (%) \n", - "Category Group \n", - "overall overall 2.2 \n", - "Sex F 1.6 \n", - " M 2.2 \n", - "Ethnicity (broad categories) Black 4.8 \n", - " Mixed 1.7 \n", - " Other 3.0 \n", - " South Asian 2.9 \n", - " Unknown 1.8 \n", - " White 1.6 \n", - "ethnicity 16 groups African 5.9 \n", - " Bangladeshi or British Bangladeshi 5.0 \n", - " Caribbean 0.0 \n", - " Chinese 5.9 \n", - " Other 5.3 \n", - " Other Asian 5.0 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 0.0 \n", - " Irish 0.0 \n", - " Other Black 4.2 \n", - " Other White 0.0 \n", - " Other mixed 4.7 \n", - " Pakistani or British Pakistani 0.0 \n", - " Unknown 1.7 \n", - " White + Asian 4.5 \n", - " White + Black African 4.8 \n", - " White + Black Caribbean 4.3 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 3.0 \n", - " 2 2.8 \n", - " 3 2.8 \n", - " 4 1.4 \n", - " 5 Least deprived 1.4 \n", - " Unknown 0.0 \n", - "BMI 30+ 2.5 \n", - " under 30 1.9 \n", - "Chronic cardiac disease no 2.1 \n", - " yes 0.0 \n", - "Current COPD no 2.1 \n", - " yes 0.0 \n", - "DMARDs no 2.2 \n", - " yes 0.0 \n", - "Dementia no 2.1 \n", - " yes 0.0 \n", - "Psychosis, schizophrenia, or bipolar no 2.2 \n", - " yes 0.0 \n", - "SSRI (last 12 months) no 2.2 \n", - " yes 0.0 \n", - "Chemo or radiotherapy no 2.2 \n", - " yes 0.0 \n", - "Cancer (lung) no 2.1 \n", - " yes 0.0 \n", - "Cancer (excluding lung/haem) no 2.2 \n", - " yes 0.0 \n", - "Cancer (haematological) no 2.1 \n", - " yes 0.0 " + " Vaccinated over last 7d (%) \n", + "Category Group \n", + "overall overall 2.0 \n", + "Sex F 1.5 \n", + " M 1.9 \n", + "Age band 0 0.0 \n", + " 0-15 12.5 \n", + " 16-29 12.5 \n", + " 30-34 0.0 \n", + " 35-39 11.2 \n", + " 40-44 0.0 \n", + " 45-49 14.3 \n", + " 50-54 0.0 \n", + " 55-59 14.3 \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 (broad categories) Black 5.0 \n", + " Mixed 0.0 \n", + " Other 5.0 \n", + " South Asian 0.0 \n", + " Unknown 5.6 \n", + " White 4.5 " ] }, "metadata": {}, @@ -38453,23 +65112,11 @@ "metadata": {}, "output_type": "display_data" }, - { - "data": { - "text/markdown": [ - "- SSRIs group excludes individuals with Psychosis/ schizophrenia/bipolar, LD, or Dementia." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, { "data": { "text/markdown": [ "## \n", - " ## Cumulative vaccination figures among 55-59 population \n", + " ## Cumulative vaccination figures among 60-64 population \n", " Please refer to footnotes below table for information." ], "text/plain": [ @@ -38501,8 +65148,8 @@ " \n", " \n", " \n", - " Vaccinated at 30 Mar (n)\n", - " Vaccinated at 30 Mar (%)\n", + " Vaccinated at 16 Apr (n)\n", + " Vaccinated at 16 Apr (%)\n", " Total eligible\n", " Previous week's vaccination coverage (%)\n", " Vaccinated over last 7d (%)\n", @@ -38521,201 +65168,193 @@ " \n", " overall\n", " overall\n", - " 1300\n", - " 41.5\n", - " 3136\n", - " 38.8\n", - " 2.7\n", + " 1079\n", + " 39.7\n", + " 2716\n", + " 37.6\n", + " 2.1\n", " \n", " \n", " Sex\n", " F\n", - " 707\n", - " 43.0\n", - " 1645\n", - " 39.1\n", - " 3.9\n", + " 546\n", + " 38.6\n", + " 1414\n", + " 36.6\n", + " 2.0\n", " \n", " \n", " M\n", - " 595\n", - " 39.9\n", - " 1491\n", - " 38.5\n", - " 1.4\n", + " 532\n", + " 40.9\n", + " 1302\n", + " 38.7\n", + " 2.2\n", " \n", " \n", " Ethnicity (broad categories)\n", " Black\n", - " 217\n", - " 40.8\n", - " 532\n", - " 38.2\n", - " 2.6\n", + " 175\n", + " 38.5\n", + " 455\n", + " 36.9\n", + " 1.6\n", " \n", " \n", " Mixed\n", - " 210\n", - " 41.1\n", - " 511\n", - " 38.4\n", - " 2.7\n", + " 175\n", + " 39.1\n", + " 448\n", + " 37.5\n", + " 1.6\n", " \n", " \n", " Other\n", - " 231\n", - " 43.4\n", - " 532\n", - " 40.8\n", - " 2.6\n", + " 175\n", + " 37.9\n", + " 462\n", + " 36.4\n", + " 1.5\n", " \n", " \n", " South Asian\n", - " 252\n", - " 42.4\n", - " 595\n", + " 182\n", " 40.0\n", - " 2.4\n", + " 455\n", + " 36.9\n", + " 3.1\n", " \n", " \n", " Unknown\n", - " 189\n", - " 41.5\n", - " 455\n", - " 38.5\n", - " 3.0\n", + " 168\n", + " 42.1\n", + " 399\n", + " 38.6\n", + " 3.5\n", " \n", " \n", " White\n", - " 203\n", - " 40.3\n", + " 210\n", + " 41.7\n", " 504\n", - " 37.5\n", + " 38.9\n", " 2.8\n", " \n", " \n", " ethnicity 16 groups\n", " African\n", " 63\n", - " 36.0\n", - " 175\n", - " 32.0\n", - " 4.0\n", + " 42.9\n", + " 147\n", + " 38.1\n", + " 4.8\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 56\n", - " 34.8\n", - " 161\n", - " 30.4\n", - " 4.4\n", + " 63\n", + " 40.9\n", + " 154\n", + " 36.4\n", + " 4.5\n", " \n", " \n", " Caribbean\n", - " 77\n", - " 44.0\n", - " 175\n", - " 44.0\n", - " 0.0\n", + " 84\n", + " 52.2\n", + " 161\n", + " 47.8\n", + " 4.4\n", " \n", " \n", " Chinese\n", - " 77\n", - " 44.0\n", - " 175\n", - " 40.0\n", - " 4.0\n", + " 49\n", + " 35.0\n", + " 140\n", + " 35.0\n", + " 0.0\n", " \n", " \n", " Other\n", - " 77\n", - " 45.8\n", - " 168\n", - " 41.7\n", - " 4.1\n", + " 49\n", + " 38.9\n", + " 126\n", + " 38.9\n", + " 0.0\n", " \n", " \n", " Other Asian\n", " 77\n", - " 45.8\n", - " 168\n", - " 41.7\n", - " 4.1\n", + " 47.8\n", + " 161\n", + " 43.5\n", + " 4.3\n", " \n", " \n", " British or Mixed British\n", - " 56\n", - " 34.8\n", - " 161\n", - " 30.4\n", - " 4.4\n", + " 42\n", + " 28.6\n", + " 147\n", + " 28.6\n", + " 0.0\n", " \n", " \n", " Indian or British Indian\n", - " 84\n", - " 48.0\n", - " 175\n", - " 48.0\n", + " 49\n", + " 35.0\n", + " 140\n", + " 35.0\n", " 0.0\n", " \n", " \n", " Irish\n", - " 84\n", - " 46.2\n", - " 182\n", - " 42.3\n", - " 3.9\n", + " 56\n", + " 34.8\n", + " 161\n", + " 30.4\n", + " 4.4\n", " \n", " \n", " Other Black\n", - " 70\n", - " 41.7\n", - " 168\n", - " 37.5\n", - " 4.2\n", + " 77\n", + " 50.0\n", + " 154\n", + " 45.5\n", + " 4.5\n", " \n", " \n", " Other White\n", - " 84\n", - " 44.4\n", - " 189\n", - " 40.7\n", - " 3.7\n", + " 63\n", + " 40.9\n", + " 154\n", + " 36.4\n", + " 4.5\n", " \n", " \n", " Other mixed\n", - " 56\n", - " 40.0\n", - " 140\n", - " 35.0\n", - " 5.0\n", + " 49\n", + " 36.8\n", + " 133\n", + " 36.8\n", + " 0.0\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 63\n", - " 40.9\n", + " 70\n", + " 45.5\n", " 154\n", - " 36.4\n", - " 4.5\n", + " 40.9\n", + " 4.6\n", " \n", " \n", " Unknown\n", - " 182\n", - " 37.7\n", - " 483\n", - " 36.2\n", - " 1.5\n", + " 133\n", + " 34.5\n", + " 385\n", + " 32.7\n", + " 1.8\n", " \n", " \n", " White + Asian\n", - " 77\n", - " 45.8\n", - " 168\n", - " 41.7\n", - " 4.1\n", - " \n", - " \n", - " White + Black African\n", " 56\n", " 42.1\n", " 133\n", @@ -38723,121 +65362,129 @@ " 5.3\n", " \n", " \n", + " White + Black African\n", + " 56\n", + " 44.4\n", + " 126\n", + " 44.4\n", + " 0.0\n", + " \n", + " \n", " White + Black Caribbean\n", - " 77\n", - " 47.8\n", - " 161\n", - " 43.5\n", - " 4.3\n", + " 49\n", + " 35.0\n", + " 140\n", + " 30.0\n", + " 5.0\n", " \n", " \n", - " Index of Multiple Deprivation (quintiles)\n", - " 1 Most deprived\n", - " 238\n", - " 40.0\n", - " 595\n", - " 37.6\n", - " 2.4\n", + " Index of Multiple Deprivation (quintiles)\n", + " 1 Most deprived\n", + " 210\n", + " 39.5\n", + " 532\n", + " 38.2\n", + " 1.3\n", " \n", " \n", " 2\n", - " 252\n", - " 41.9\n", - " 602\n", + " 210\n", " 39.5\n", - " 2.4\n", + " 532\n", + " 38.2\n", + " 1.3\n", " \n", " \n", " 3\n", - " 252\n", - " 43.4\n", - " 581\n", - " 39.8\n", - " 3.6\n", + " 210\n", + " 41.7\n", + " 504\n", + " 38.9\n", + " 2.8\n", " \n", " \n", " 4\n", - " 245\n", - " 38.5\n", - " 637\n", - " 36.3\n", - " 2.2\n", + " 189\n", + " 37.5\n", + " 504\n", + " 34.7\n", + " 2.8\n", " \n", " \n", " 5 Least deprived\n", - " 238\n", - " 44.7\n", - " 532\n", - " 42.1\n", - " 2.6\n", + " 217\n", + " 41.9\n", + " 518\n", + " 40.5\n", + " 1.4\n", " \n", " \n", " Unknown\n", - " 77\n", - " 42.3\n", - " 182\n", - " 38.5\n", - " 3.8\n", + " 42\n", + " 31.6\n", + " 133\n", + " 31.6\n", + " 0.0\n", " \n", " \n", " BMI\n", " 30+\n", - " 392\n", - " 41.2\n", - " 952\n", - " 39.0\n", - " 2.2\n", + " 329\n", + " 40.5\n", + " 812\n", + " 37.9\n", + " 2.6\n", " \n", " \n", " under 30\n", - " 910\n", - " 41.7\n", - " 2184\n", - " 38.8\n", - " 2.9\n", + " 749\n", + " 39.3\n", + " 1904\n", + " 37.5\n", + " 1.8\n", " \n", " \n", " Chronic cardiac disease\n", " no\n", - " 1288\n", - " 41.4\n", - " 3108\n", - " 38.7\n", - " 2.7\n", + " 1064\n", + " 39.6\n", + " 2688\n", + " 37.5\n", + " 2.1\n", " \n", " \n", " yes\n", - " 7\n", - " 25.0\n", + " 14\n", + " 50.0\n", " 28\n", - " 25.0\n", + " 50.0\n", " 0.0\n", " \n", " \n", " Current COPD\n", " no\n", - " 1288\n", - " 41.5\n", - " 3101\n", - " 38.8\n", - " 2.7\n", + " 1071\n", + " 39.8\n", + " 2688\n", + " 37.8\n", + " 2.0\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", + " 7\n", + " 25.0\n", + " 28\n", + " 25.0\n", " 0.0\n", " \n", " \n", " DMARDs\n", " no\n", - " 1288\n", - " 41.4\n", - " 3108\n", - " 38.7\n", - " 2.7\n", + " 1071\n", + " 39.7\n", + " 2695\n", + " 37.7\n", + " 2.0\n", " \n", " \n", " yes\n", @@ -38848,30 +65495,98 @@ " 0.0\n", " \n", " \n", + " Dementia\n", + " no\n", + " 1057\n", + " 39.4\n", + " 2681\n", + " 37.3\n", + " 2.1\n", + " \n", + " \n", + " yes\n", + " 21\n", + " 60.0\n", + " 35\n", + " 60.0\n", + " 0.0\n", + " \n", + " \n", " Psychosis, schizophrenia, or bipolar\n", " no\n", - " 1281\n", - " 41.2\n", - " 3108\n", - " 38.7\n", - " 2.5\n", + " 1071\n", + " 39.8\n", + " 2688\n", + " 37.8\n", + " 2.0\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", + " 7\n", + " 25.0\n", " 28\n", - " 50.0\n", + " 25.0\n", " 0.0\n", " \n", " \n", " SSRI (last 12 months)\n", " no\n", - " 1288\n", - " 41.4\n", - " 3108\n", - " 38.7\n", - " 2.7\n", + " 1064\n", + " 39.7\n", + " 2681\n", + " 37.6\n", + " 2.1\n", + " \n", + " \n", + " yes\n", + " 14\n", + " 40.0\n", + " 35\n", + " 40.0\n", + " 0.0\n", + " \n", + " \n", + " Chemo or radiotherapy\n", + " no\n", + " 1064\n", + " 39.7\n", + " 2681\n", + " 37.6\n", + " 2.1\n", + " \n", + " \n", + " yes\n", + " 14\n", + " 40.0\n", + " 35\n", + " 40.0\n", + " 0.0\n", + " \n", + " \n", + " Cancer (lung)\n", + " no\n", + " 1064\n", + " 39.7\n", + " 2681\n", + " 37.6\n", + " 2.1\n", + " \n", + " \n", + " yes\n", + " 14\n", + " 40.0\n", + " 35\n", + " 40.0\n", + " 0.0\n", + " \n", + " \n", + " Cancer (excluding lung/haem)\n", + " no\n", + " 1064\n", + " 39.6\n", + " 2688\n", + " 37.5\n", + " 2.1\n", " \n", " \n", " yes\n", @@ -38881,244 +65596,311 @@ " 50.0\n", " 0.0\n", " \n", + " \n", + " Cancer (haematological)\n", + " no\n", + " 1071\n", + " 39.7\n", + " 2695\n", + " 37.7\n", + " 2.0\n", + " \n", + " \n", + " yes\n", + " 7\n", + " 33.3\n", + " 21\n", + " 33.3\n", + " 0.0\n", + " \n", " \n", "\n", "" ], "text/plain": [ - " Vaccinated at 30 Mar (n) \\\n", + " Vaccinated at 16 Apr (n) \\\n", "Category Group \n", - "overall overall 1300 \n", - "Sex F 707 \n", - " M 595 \n", - "Ethnicity (broad categories) Black 217 \n", - " Mixed 210 \n", - " Other 231 \n", - " South Asian 252 \n", - " Unknown 189 \n", - " White 203 \n", + "overall overall 1079 \n", + "Sex F 546 \n", + " M 532 \n", + "Ethnicity (broad categories) Black 175 \n", + " Mixed 175 \n", + " Other 175 \n", + " South Asian 182 \n", + " Unknown 168 \n", + " White 210 \n", "ethnicity 16 groups African 63 \n", - " Bangladeshi or British Bangladeshi 56 \n", - " Caribbean 77 \n", - " Chinese 77 \n", - " Other 77 \n", + " Bangladeshi or British Bangladeshi 63 \n", + " Caribbean 84 \n", + " Chinese 49 \n", + " Other 49 \n", " Other Asian 77 \n", - " British or Mixed British 56 \n", - " Indian or British Indian 84 \n", - " Irish 84 \n", - " Other Black 70 \n", - " Other White 84 \n", - " Other mixed 56 \n", - " Pakistani or British Pakistani 63 \n", - " Unknown 182 \n", - " White + Asian 77 \n", + " British or Mixed British 42 \n", + " Indian or British Indian 49 \n", + " Irish 56 \n", + " Other Black 77 \n", + " Other White 63 \n", + " Other mixed 49 \n", + " Pakistani or British Pakistani 70 \n", + " Unknown 133 \n", + " White + Asian 56 \n", " White + Black African 56 \n", - " White + Black Caribbean 77 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 238 \n", - " 2 252 \n", - " 3 252 \n", - " 4 245 \n", - " 5 Least deprived 238 \n", - " Unknown 77 \n", - "BMI 30+ 392 \n", - " under 30 910 \n", - "Chronic cardiac disease no 1288 \n", - " yes 7 \n", - "Current COPD no 1288 \n", + " White + Black Caribbean 49 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 210 \n", + " 2 210 \n", + " 3 210 \n", + " 4 189 \n", + " 5 Least deprived 217 \n", + " Unknown 42 \n", + "BMI 30+ 329 \n", + " under 30 749 \n", + "Chronic cardiac disease no 1064 \n", " yes 14 \n", - "DMARDs no 1288 \n", + "Current COPD no 1071 \n", + " yes 7 \n", + "DMARDs no 1071 \n", " yes 7 \n", - "Psychosis, schizophrenia, or bipolar no 1281 \n", + "Dementia no 1057 \n", + " yes 21 \n", + "Psychosis, schizophrenia, or bipolar no 1071 \n", + " yes 7 \n", + "SSRI (last 12 months) no 1064 \n", + " yes 14 \n", + "Chemo or radiotherapy no 1064 \n", + " yes 14 \n", + "Cancer (lung) no 1064 \n", " yes 14 \n", - "SSRI (last 12 months) no 1288 \n", + "Cancer (excluding lung/haem) no 1064 \n", " yes 14 \n", + "Cancer (haematological) no 1071 \n", + " yes 7 \n", "\n", - " Vaccinated at 30 Mar (%) \\\n", + " Vaccinated at 16 Apr (%) \\\n", "Category Group \n", - "overall overall 41.5 \n", - "Sex F 43.0 \n", - " M 39.9 \n", - "Ethnicity (broad categories) Black 40.8 \n", - " Mixed 41.1 \n", - " Other 43.4 \n", - " South Asian 42.4 \n", - " Unknown 41.5 \n", - " White 40.3 \n", - "ethnicity 16 groups African 36.0 \n", - " Bangladeshi or British Bangladeshi 34.8 \n", - " Caribbean 44.0 \n", - " Chinese 44.0 \n", - " Other 45.8 \n", - " Other Asian 45.8 \n", - " British or Mixed British 34.8 \n", - " Indian or British Indian 48.0 \n", - " Irish 46.2 \n", - " Other Black 41.7 \n", - " Other White 44.4 \n", - " Other mixed 40.0 \n", - " Pakistani or British Pakistani 40.9 \n", - " Unknown 37.7 \n", - " White + Asian 45.8 \n", - " White + Black African 42.1 \n", - " White + Black Caribbean 47.8 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 40.0 \n", - " 2 41.9 \n", - " 3 43.4 \n", - " 4 38.5 \n", - " 5 Least deprived 44.7 \n", - " Unknown 42.3 \n", - "BMI 30+ 41.2 \n", - " under 30 41.7 \n", - "Chronic cardiac disease no 41.4 \n", + "overall overall 39.7 \n", + "Sex F 38.6 \n", + " M 40.9 \n", + "Ethnicity (broad categories) Black 38.5 \n", + " Mixed 39.1 \n", + " Other 37.9 \n", + " South Asian 40.0 \n", + " Unknown 42.1 \n", + " White 41.7 \n", + "ethnicity 16 groups African 42.9 \n", + " Bangladeshi or British Bangladeshi 40.9 \n", + " Caribbean 52.2 \n", + " Chinese 35.0 \n", + " Other 38.9 \n", + " Other Asian 47.8 \n", + " British or Mixed British 28.6 \n", + " Indian or British Indian 35.0 \n", + " Irish 34.8 \n", + " Other Black 50.0 \n", + " Other White 40.9 \n", + " Other mixed 36.8 \n", + " Pakistani or British Pakistani 45.5 \n", + " Unknown 34.5 \n", + " White + Asian 42.1 \n", + " White + Black African 44.4 \n", + " White + Black Caribbean 35.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 39.5 \n", + " 2 39.5 \n", + " 3 41.7 \n", + " 4 37.5 \n", + " 5 Least deprived 41.9 \n", + " Unknown 31.6 \n", + "BMI 30+ 40.5 \n", + " under 30 39.3 \n", + "Chronic cardiac disease no 39.6 \n", + " yes 50.0 \n", + "Current COPD no 39.8 \n", " yes 25.0 \n", - "Current COPD no 41.5 \n", - " yes 40.0 \n", - "DMARDs no 41.4 \n", + "DMARDs no 39.7 \n", " yes 25.0 \n", - "Psychosis, schizophrenia, or bipolar no 41.2 \n", - " yes 50.0 \n", - "SSRI (last 12 months) no 41.4 \n", + "Dementia no 39.4 \n", + " yes 60.0 \n", + "Psychosis, schizophrenia, or bipolar no 39.8 \n", + " yes 25.0 \n", + "SSRI (last 12 months) no 39.7 \n", + " yes 40.0 \n", + "Chemo or radiotherapy no 39.7 \n", + " yes 40.0 \n", + "Cancer (lung) no 39.7 \n", + " yes 40.0 \n", + "Cancer (excluding lung/haem) no 39.6 \n", " yes 50.0 \n", + "Cancer (haematological) no 39.7 \n", + " yes 33.3 \n", "\n", " Total eligible \\\n", "Category Group \n", - "overall overall 3136 \n", - "Sex F 1645 \n", - " M 1491 \n", - "Ethnicity (broad categories) Black 532 \n", - " Mixed 511 \n", - " Other 532 \n", - " South Asian 595 \n", - " Unknown 455 \n", + "overall overall 2716 \n", + "Sex F 1414 \n", + " M 1302 \n", + "Ethnicity (broad categories) Black 455 \n", + " Mixed 448 \n", + " Other 462 \n", + " South Asian 455 \n", + " Unknown 399 \n", " White 504 \n", - "ethnicity 16 groups African 175 \n", - " Bangladeshi or British Bangladeshi 161 \n", - " Caribbean 175 \n", - " Chinese 175 \n", - " Other 168 \n", - " Other Asian 168 \n", - " British or Mixed British 161 \n", - " Indian or British Indian 175 \n", - " Irish 182 \n", - " Other Black 168 \n", - " Other White 189 \n", - " Other mixed 140 \n", + "ethnicity 16 groups African 147 \n", + " Bangladeshi or British Bangladeshi 154 \n", + " Caribbean 161 \n", + " Chinese 140 \n", + " Other 126 \n", + " Other Asian 161 \n", + " British or Mixed British 147 \n", + " Indian or British Indian 140 \n", + " Irish 161 \n", + " Other Black 154 \n", + " Other White 154 \n", + " Other mixed 133 \n", " Pakistani or British Pakistani 154 \n", - " Unknown 483 \n", - " White + Asian 168 \n", - " White + Black African 133 \n", - " White + Black Caribbean 161 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 595 \n", - " 2 602 \n", - " 3 581 \n", - " 4 637 \n", - " 5 Least deprived 532 \n", - " Unknown 182 \n", - "BMI 30+ 952 \n", - " under 30 2184 \n", - "Chronic cardiac disease no 3108 \n", + " Unknown 385 \n", + " White + Asian 133 \n", + " White + Black African 126 \n", + " White + Black Caribbean 140 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 532 \n", + " 2 532 \n", + " 3 504 \n", + " 4 504 \n", + " 5 Least deprived 518 \n", + " Unknown 133 \n", + "BMI 30+ 812 \n", + " under 30 1904 \n", + "Chronic cardiac disease no 2688 \n", " yes 28 \n", - "Current COPD no 3101 \n", - " yes 35 \n", - "DMARDs no 3108 \n", + "Current COPD no 2688 \n", + " yes 28 \n", + "DMARDs no 2695 \n", " yes 28 \n", - "Psychosis, schizophrenia, or bipolar no 3108 \n", + "Dementia no 2681 \n", + " yes 35 \n", + "Psychosis, schizophrenia, or bipolar no 2688 \n", " yes 28 \n", - "SSRI (last 12 months) no 3108 \n", + "SSRI (last 12 months) no 2681 \n", + " yes 35 \n", + "Chemo or radiotherapy no 2681 \n", + " yes 35 \n", + "Cancer (lung) no 2681 \n", + " yes 35 \n", + "Cancer (excluding lung/haem) no 2688 \n", " yes 28 \n", + "Cancer (haematological) no 2695 \n", + " yes 21 \n", "\n", " Previous week's vaccination coverage (%) \\\n", "Category Group \n", - "overall overall 38.8 \n", - "Sex F 39.1 \n", - " M 38.5 \n", - "Ethnicity (broad categories) Black 38.2 \n", - " Mixed 38.4 \n", - " Other 40.8 \n", - " South Asian 40.0 \n", - " Unknown 38.5 \n", - " White 37.5 \n", - "ethnicity 16 groups African 32.0 \n", - " Bangladeshi or British Bangladeshi 30.4 \n", - " Caribbean 44.0 \n", - " Chinese 40.0 \n", - " Other 41.7 \n", - " Other Asian 41.7 \n", - " British or Mixed British 30.4 \n", - " Indian or British Indian 48.0 \n", - " Irish 42.3 \n", - " Other Black 37.5 \n", - " Other White 40.7 \n", - " Other mixed 35.0 \n", - " Pakistani or British Pakistani 36.4 \n", - " Unknown 36.2 \n", - " White + Asian 41.7 \n", - " White + Black African 36.8 \n", - " White + Black Caribbean 43.5 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 37.6 \n", - " 2 39.5 \n", - " 3 39.8 \n", - " 4 36.3 \n", - " 5 Least deprived 42.1 \n", - " Unknown 38.5 \n", - "BMI 30+ 39.0 \n", - " under 30 38.8 \n", - "Chronic cardiac disease no 38.7 \n", + "overall overall 37.6 \n", + "Sex F 36.6 \n", + " M 38.7 \n", + "Ethnicity (broad categories) Black 36.9 \n", + " Mixed 37.5 \n", + " Other 36.4 \n", + " South Asian 36.9 \n", + " Unknown 38.6 \n", + " White 38.9 \n", + "ethnicity 16 groups African 38.1 \n", + " Bangladeshi or British Bangladeshi 36.4 \n", + " Caribbean 47.8 \n", + " Chinese 35.0 \n", + " Other 38.9 \n", + " Other Asian 43.5 \n", + " British or Mixed British 28.6 \n", + " Indian or British Indian 35.0 \n", + " Irish 30.4 \n", + " Other Black 45.5 \n", + " Other White 36.4 \n", + " Other mixed 36.8 \n", + " Pakistani or British Pakistani 40.9 \n", + " Unknown 32.7 \n", + " White + Asian 36.8 \n", + " White + Black African 44.4 \n", + " White + Black Caribbean 30.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 38.2 \n", + " 2 38.2 \n", + " 3 38.9 \n", + " 4 34.7 \n", + " 5 Least deprived 40.5 \n", + " Unknown 31.6 \n", + "BMI 30+ 37.9 \n", + " under 30 37.5 \n", + "Chronic cardiac disease no 37.5 \n", + " yes 50.0 \n", + "Current COPD no 37.8 \n", " yes 25.0 \n", - "Current COPD no 38.8 \n", - " yes 40.0 \n", - "DMARDs no 38.7 \n", + "DMARDs no 37.7 \n", " yes 25.0 \n", - "Psychosis, schizophrenia, or bipolar no 38.7 \n", - " yes 50.0 \n", - "SSRI (last 12 months) no 38.7 \n", + "Dementia no 37.3 \n", + " yes 60.0 \n", + "Psychosis, schizophrenia, or bipolar no 37.8 \n", + " yes 25.0 \n", + "SSRI (last 12 months) no 37.6 \n", + " yes 40.0 \n", + "Chemo or radiotherapy no 37.6 \n", + " yes 40.0 \n", + "Cancer (lung) no 37.6 \n", + " yes 40.0 \n", + "Cancer (excluding lung/haem) no 37.5 \n", " yes 50.0 \n", + "Cancer (haematological) no 37.7 \n", + " yes 33.3 \n", "\n", " Vaccinated over last 7d (%) \n", "Category Group \n", - "overall overall 2.7 \n", - "Sex F 3.9 \n", - " M 1.4 \n", - "Ethnicity (broad categories) Black 2.6 \n", - " Mixed 2.7 \n", - " Other 2.6 \n", - " South Asian 2.4 \n", - " Unknown 3.0 \n", + "overall overall 2.1 \n", + "Sex F 2.0 \n", + " M 2.2 \n", + "Ethnicity (broad categories) Black 1.6 \n", + " Mixed 1.6 \n", + " Other 1.5 \n", + " South Asian 3.1 \n", + " Unknown 3.5 \n", " White 2.8 \n", - "ethnicity 16 groups African 4.0 \n", - " Bangladeshi or British Bangladeshi 4.4 \n", - " Caribbean 0.0 \n", - " Chinese 4.0 \n", - " Other 4.1 \n", - " Other Asian 4.1 \n", - " British or Mixed British 4.4 \n", + "ethnicity 16 groups African 4.8 \n", + " Bangladeshi or British Bangladeshi 4.5 \n", + " Caribbean 4.4 \n", + " Chinese 0.0 \n", + " Other 0.0 \n", + " Other Asian 4.3 \n", + " British or Mixed British 0.0 \n", " Indian or British Indian 0.0 \n", - " Irish 3.9 \n", - " Other Black 4.2 \n", - " Other White 3.7 \n", - " Other mixed 5.0 \n", - " Pakistani or British Pakistani 4.5 \n", - " Unknown 1.5 \n", - " White + Asian 4.1 \n", - " White + Black African 5.3 \n", - " White + Black Caribbean 4.3 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 2.4 \n", - " 2 2.4 \n", - " 3 3.6 \n", - " 4 2.2 \n", - " 5 Least deprived 2.6 \n", - " Unknown 3.8 \n", - "BMI 30+ 2.2 \n", - " under 30 2.9 \n", - "Chronic cardiac disease no 2.7 \n", + " Irish 4.4 \n", + " Other Black 4.5 \n", + " Other White 4.5 \n", + " Other mixed 0.0 \n", + " Pakistani or British Pakistani 4.6 \n", + " Unknown 1.8 \n", + " White + Asian 5.3 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 5.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 1.3 \n", + " 2 1.3 \n", + " 3 2.8 \n", + " 4 2.8 \n", + " 5 Least deprived 1.4 \n", + " Unknown 0.0 \n", + "BMI 30+ 2.6 \n", + " under 30 1.8 \n", + "Chronic cardiac disease no 2.1 \n", " yes 0.0 \n", - "Current COPD no 2.7 \n", + "Current COPD no 2.0 \n", " yes 0.0 \n", - "DMARDs no 2.7 \n", + "DMARDs no 2.0 \n", " yes 0.0 \n", - "Psychosis, schizophrenia, or bipolar no 2.5 \n", + "Dementia no 2.1 \n", + " yes 0.0 \n", + "Psychosis, schizophrenia, or bipolar no 2.0 \n", + " yes 0.0 \n", + "SSRI (last 12 months) no 2.1 \n", " yes 0.0 \n", - "SSRI (last 12 months) no 2.7 \n", + "Chemo or radiotherapy no 2.1 \n", + " yes 0.0 \n", + "Cancer (lung) no 2.1 \n", + " yes 0.0 \n", + "Cancer (excluding lung/haem) no 2.1 \n", + " yes 0.0 \n", + "Cancer (haematological) no 2.0 \n", " yes 0.0 " ] }, @@ -39166,7 +65948,7 @@ "data": { "text/markdown": [ "## \n", - " ## Cumulative vaccination figures among 50-54 population \n", + " ## Cumulative vaccination figures among 55-59 population \n", " Please refer to footnotes below table for information." ], "text/plain": [ @@ -39198,8 +65980,8 @@ " \n", " \n", " \n", - " Vaccinated at 30 Mar (n)\n", - " Vaccinated at 30 Mar (%)\n", + " Vaccinated at 16 Apr (n)\n", + " Vaccinated at 16 Apr (%)\n", " Total eligible\n", " Previous week's vaccination coverage (%)\n", " Vaccinated over last 7d (%)\n", @@ -39218,255 +66000,255 @@ " \n", " overall\n", " overall\n", - " 1306\n", - " 38.3\n", - " 3409\n", - " 35.7\n", - " 2.6\n", + " 1270\n", + " 39.8\n", + " 3192\n", + " 37.5\n", + " 2.3\n", " \n", " \n", " Sex\n", " F\n", - " 658\n", - " 37.9\n", - " 1736\n", - " 35.5\n", - " 2.4\n", + " 637\n", + " 38.7\n", + " 1645\n", + " 36.2\n", + " 2.5\n", " \n", " \n", " M\n", - " 644\n", - " 38.5\n", - " 1673\n", - " 36.0\n", - " 2.5\n", + " 630\n", + " 40.7\n", + " 1547\n", + " 38.9\n", + " 1.8\n", " \n", " \n", " Ethnicity (broad categories)\n", " Black\n", - " 231\n", - " 39.8\n", - " 581\n", - " 37.3\n", + " 224\n", + " 41.0\n", + " 546\n", + " 38.5\n", " 2.5\n", " \n", " \n", " Mixed\n", - " 217\n", - " 40.3\n", - " 539\n", - " 39.0\n", - " 1.3\n", + " 210\n", + " 38.5\n", + " 546\n", + " 35.9\n", + " 2.6\n", " \n", " \n", " Other\n", - " 217\n", + " 203\n", + " 39.2\n", + " 518\n", " 37.8\n", - " 574\n", - " 35.4\n", - " 2.4\n", + " 1.4\n", " \n", " \n", " South Asian\n", - " 252\n", - " 39.1\n", - " 644\n", - " 37.0\n", - " 2.1\n", + " 196\n", + " 37.3\n", + " 525\n", + " 36.0\n", + " 1.3\n", " \n", " \n", " Unknown\n", - " 168\n", - " 34.8\n", - " 483\n", - " 31.9\n", - " 2.9\n", + " 217\n", + " 43.1\n", + " 504\n", + " 40.3\n", + " 2.8\n", " \n", " \n", " White\n", " 224\n", - " 38.1\n", - " 588\n", - " 34.5\n", - " 3.6\n", + " 40.5\n", + " 553\n", + " 38.0\n", + " 2.5\n", " \n", " \n", " ethnicity 16 groups\n", " African\n", - " 77\n", - " 39.3\n", - " 196\n", - " 35.7\n", - " 3.6\n", + " 70\n", + " 40.0\n", + " 175\n", + " 40.0\n", + " 0.0\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 63\n", - " 36.0\n", - " 175\n", - " 32.0\n", - " 4.0\n", + " 56\n", + " 38.1\n", + " 147\n", + " 33.3\n", + " 4.8\n", " \n", " \n", " Caribbean\n", - " 56\n", - " 32.0\n", + " 70\n", + " 40.0\n", " 175\n", - " 32.0\n", + " 40.0\n", " 0.0\n", " \n", " \n", " Chinese\n", - " 63\n", - " 36.0\n", - " 175\n", - " 32.0\n", - " 4.0\n", + " 77\n", + " 39.3\n", + " 196\n", + " 35.7\n", + " 3.6\n", " \n", " \n", " Other\n", - " 63\n", - " 37.5\n", - " 168\n", - " 37.5\n", + " 77\n", + " 37.9\n", + " 203\n", + " 37.9\n", " 0.0\n", " \n", " \n", " Other Asian\n", " 70\n", - " 41.7\n", - " 168\n", - " 41.7\n", - " 0.0\n", + " 38.5\n", + " 182\n", + " 34.6\n", + " 3.9\n", " \n", " \n", " British or Mixed British\n", " 70\n", - " 35.7\n", - " 196\n", - " 35.7\n", - " 0.0\n", + " 41.7\n", + " 168\n", + " 37.5\n", + " 4.2\n", " \n", " \n", " Indian or British Indian\n", - " 70\n", - " 37.0\n", - " 189\n", - " 33.3\n", - " 3.7\n", + " 63\n", + " 40.9\n", + " 154\n", + " 40.9\n", + " 0.0\n", " \n", " \n", " Irish\n", - " 91\n", - " 46.4\n", - " 196\n", - " 42.9\n", - " 3.5\n", + " 63\n", + " 40.9\n", + " 154\n", + " 36.4\n", + " 4.5\n", " \n", " \n", " Other Black\n", - " 70\n", - " 40.0\n", - " 175\n", - " 36.0\n", - " 4.0\n", + " 63\n", + " 39.1\n", + " 161\n", + " 34.8\n", + " 4.3\n", " \n", " \n", " Other White\n", - " 63\n", - " 34.6\n", + " 77\n", + " 42.3\n", " 182\n", - " 34.6\n", - " 0.0\n", + " 38.5\n", + " 3.8\n", " \n", " \n", " Other mixed\n", - " 49\n", - " 28.0\n", - " 175\n", - " 28.0\n", + " 63\n", + " 37.5\n", + " 168\n", + " 37.5\n", " 0.0\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 77\n", - " 37.9\n", - " 203\n", - " 34.5\n", - " 3.4\n", + " 63\n", + " 37.5\n", + " 168\n", + " 37.5\n", + " 0.0\n", " \n", " \n", - " Unknown\n", - " 210\n", - " 41.1\n", - " 511\n", - " 38.4\n", - " 2.7\n", + " Unknown\n", + " 196\n", + " 40.6\n", + " 483\n", + " 37.7\n", + " 2.9\n", " \n", " \n", " White + Asian\n", - " 77\n", - " 39.3\n", - " 196\n", - " 39.3\n", + " 63\n", + " 39.1\n", + " 161\n", + " 39.1\n", " 0.0\n", " \n", " \n", " White + Black African\n", - " 70\n", - " 41.7\n", - " 168\n", - " 37.5\n", - " 4.2\n", + " 56\n", + " 34.8\n", + " 161\n", + " 30.4\n", + " 4.4\n", " \n", " \n", " White + Black Caribbean\n", - " 63\n", - " 39.1\n", - " 161\n", - " 34.8\n", - " 4.3\n", + " 56\n", + " 38.1\n", + " 147\n", + " 38.1\n", + " 0.0\n", " \n", " \n", " Index of Multiple Deprivation (quintiles)\n", " 1 Most deprived\n", - " 245\n", - " 36.5\n", - " 672\n", - " 34.4\n", - " 2.1\n", + " 252\n", + " 42.4\n", + " 595\n", + " 38.8\n", + " 3.6\n", " \n", " \n", " 2\n", - " 245\n", - " 37.6\n", - " 651\n", - " 36.6\n", - " 1.0\n", + " 238\n", + " 39.5\n", + " 602\n", + " 37.2\n", + " 2.3\n", " \n", " \n", " 3\n", - " 238\n", - " 38.2\n", - " 623\n", - " 36.0\n", - " 2.2\n", + " 245\n", + " 40.7\n", + " 602\n", + " 37.2\n", + " 3.5\n", " \n", " \n", " 4\n", - " 238\n", - " 38.2\n", - " 623\n", - " 36.0\n", - " 2.2\n", + " 231\n", + " 37.5\n", + " 616\n", + " 35.2\n", + " 2.3\n", " \n", " \n", " 5 Least deprived\n", - " 273\n", - " 40.6\n", - " 672\n", - " 37.5\n", - " 3.1\n", + " 252\n", + " 41.4\n", + " 609\n", + " 39.1\n", + " 2.3\n", " \n", " \n", " Unknown\n", @@ -39479,62 +66261,62 @@ " \n", " BMI\n", " 30+\n", - " 392\n", - " 37.8\n", - " 1036\n", - " 35.1\n", - " 2.7\n", + " 371\n", + " 40.2\n", + " 924\n", + " 37.9\n", + " 2.3\n", " \n", " \n", " under 30\n", - " 910\n", - " 38.3\n", - " 2373\n", - " 36.0\n", - " 2.3\n", + " 896\n", + " 39.5\n", + " 2268\n", + " 37.3\n", + " 2.2\n", " \n", " \n", " Chronic cardiac disease\n", " no\n", - " 1295\n", - " 38.4\n", - " 3374\n", - " 35.7\n", - " 2.7\n", + " 1260\n", + " 39.8\n", + " 3164\n", + " 37.6\n", + " 2.2\n", " \n", " \n", " yes\n", " 14\n", - " 40.0\n", - " 35\n", - " 40.0\n", - " 0.0\n", + " 50.0\n", + " 28\n", + " 25.0\n", + " 25.0\n", " \n", " \n", " Current COPD\n", " no\n", - " 1295\n", - " 38.3\n", - " 3381\n", - " 35.8\n", - " 2.5\n", + " 1253\n", + " 39.6\n", + " 3164\n", + " 37.4\n", + " 2.2\n", " \n", " \n", " yes\n", - " 7\n", - " 25.0\n", - " 28\n", - " 25.0\n", + " 14\n", + " 40.0\n", + " 35\n", + " 40.0\n", " 0.0\n", " \n", " \n", " DMARDs\n", " no\n", - " 1295\n", - " 38.3\n", - " 3381\n", - " 35.6\n", - " 2.7\n", + " 1260\n", + " 39.8\n", + " 3164\n", + " 37.4\n", + " 2.4\n", " \n", " \n", " yes\n", @@ -39547,35 +66329,35 @@ " \n", " Psychosis, schizophrenia, or bipolar\n", " no\n", - " 1295\n", - " 38.4\n", - " 3374\n", - " 35.7\n", - " 2.7\n", + " 1260\n", + " 39.9\n", + " 3157\n", + " 37.7\n", + " 2.2\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", + " 7\n", + " 20.0\n", " 35\n", - " 40.0\n", + " 20.0\n", " 0.0\n", " \n", " \n", " SSRI (last 12 months)\n", " no\n", - " 1295\n", - " 38.4\n", - " 3374\n", - " 35.9\n", - " 2.5\n", + " 1253\n", + " 39.7\n", + " 3157\n", + " 37.5\n", + " 2.2\n", " \n", " \n", " yes\n", - " 7\n", - " 20.0\n", + " 14\n", + " 40.0\n", " 35\n", - " 20.0\n", + " 40.0\n", " 0.0\n", " \n", " \n", @@ -39583,239 +66365,239 @@ "" ], "text/plain": [ - " Vaccinated at 30 Mar (n) \\\n", + " Vaccinated at 16 Apr (n) \\\n", "Category Group \n", - "overall overall 1306 \n", - "Sex F 658 \n", - " M 644 \n", - "Ethnicity (broad categories) Black 231 \n", - " Mixed 217 \n", - " Other 217 \n", - " South Asian 252 \n", - " Unknown 168 \n", + "overall overall 1270 \n", + "Sex F 637 \n", + " M 630 \n", + "Ethnicity (broad categories) Black 224 \n", + " Mixed 210 \n", + " Other 203 \n", + " South Asian 196 \n", + " Unknown 217 \n", " White 224 \n", - "ethnicity 16 groups African 77 \n", - " Bangladeshi or British Bangladeshi 63 \n", - " Caribbean 56 \n", - " Chinese 63 \n", - " Other 63 \n", + "ethnicity 16 groups African 70 \n", + " Bangladeshi or British Bangladeshi 56 \n", + " Caribbean 70 \n", + " Chinese 77 \n", + " Other 77 \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 63 \n", - " Other mixed 49 \n", - " Pakistani or British Pakistani 77 \n", - " Unknown 210 \n", - " White + Asian 77 \n", - " White + Black African 70 \n", - " White + Black Caribbean 63 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 245 \n", - " 2 245 \n", - " 3 238 \n", - " 4 238 \n", - " 5 Least deprived 273 \n", + " Indian or British Indian 63 \n", + " Irish 63 \n", + " Other Black 63 \n", + " Other White 77 \n", + " Other mixed 63 \n", + " Pakistani or British Pakistani 63 \n", + " Unknown 196 \n", + " White + Asian 63 \n", + " White + Black African 56 \n", + " White + Black Caribbean 56 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 252 \n", + " 2 238 \n", + " 3 245 \n", + " 4 231 \n", + " 5 Least deprived 252 \n", " Unknown 63 \n", - "BMI 30+ 392 \n", - " under 30 910 \n", - "Chronic cardiac disease no 1295 \n", + "BMI 30+ 371 \n", + " under 30 896 \n", + "Chronic cardiac disease no 1260 \n", " yes 14 \n", - "Current COPD no 1295 \n", - " yes 7 \n", - "DMARDs no 1295 \n", + "Current COPD no 1253 \n", " yes 14 \n", - "Psychosis, schizophrenia, or bipolar no 1295 \n", + "DMARDs no 1260 \n", " yes 14 \n", - "SSRI (last 12 months) no 1295 \n", + "Psychosis, schizophrenia, or bipolar no 1260 \n", " yes 7 \n", + "SSRI (last 12 months) no 1253 \n", + " yes 14 \n", "\n", - " Vaccinated at 30 Mar (%) \\\n", + " Vaccinated at 16 Apr (%) \\\n", "Category Group \n", - "overall overall 38.3 \n", - "Sex F 37.9 \n", - " M 38.5 \n", - "Ethnicity (broad categories) Black 39.8 \n", - " Mixed 40.3 \n", - " Other 37.8 \n", - " South Asian 39.1 \n", - " Unknown 34.8 \n", - " White 38.1 \n", - "ethnicity 16 groups African 39.3 \n", - " Bangladeshi or British Bangladeshi 36.0 \n", - " Caribbean 32.0 \n", - " Chinese 36.0 \n", - " Other 37.5 \n", - " Other Asian 41.7 \n", - " British or Mixed British 35.7 \n", - " Indian or British Indian 37.0 \n", - " Irish 46.4 \n", - " Other Black 40.0 \n", - " Other White 34.6 \n", - " Other mixed 28.0 \n", - " Pakistani or British Pakistani 37.9 \n", - " Unknown 41.1 \n", - " White + Asian 39.3 \n", - " White + Black African 41.7 \n", - " White + Black Caribbean 39.1 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 36.5 \n", - " 2 37.6 \n", - " 3 38.2 \n", - " 4 38.2 \n", - " 5 Least deprived 40.6 \n", + "overall overall 39.8 \n", + "Sex F 38.7 \n", + " M 40.7 \n", + "Ethnicity (broad categories) Black 41.0 \n", + " Mixed 38.5 \n", + " Other 39.2 \n", + " South Asian 37.3 \n", + " Unknown 43.1 \n", + " White 40.5 \n", + "ethnicity 16 groups African 40.0 \n", + " Bangladeshi or British Bangladeshi 38.1 \n", + " Caribbean 40.0 \n", + " Chinese 39.3 \n", + " Other 37.9 \n", + " Other Asian 38.5 \n", + " British or Mixed British 41.7 \n", + " Indian or British Indian 40.9 \n", + " Irish 40.9 \n", + " Other Black 39.1 \n", + " Other White 42.3 \n", + " Other mixed 37.5 \n", + " Pakistani or British Pakistani 37.5 \n", + " Unknown 40.6 \n", + " White + Asian 39.1 \n", + " White + Black African 34.8 \n", + " White + Black Caribbean 38.1 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 42.4 \n", + " 2 39.5 \n", + " 3 40.7 \n", + " 4 37.5 \n", + " 5 Least deprived 41.4 \n", " Unknown 37.5 \n", - "BMI 30+ 37.8 \n", - " under 30 38.3 \n", - "Chronic cardiac disease no 38.4 \n", - " yes 40.0 \n", - "Current COPD no 38.3 \n", - " yes 25.0 \n", - "DMARDs no 38.3 \n", + "BMI 30+ 40.2 \n", + " under 30 39.5 \n", + "Chronic cardiac disease no 39.8 \n", " yes 50.0 \n", - "Psychosis, schizophrenia, or bipolar no 38.4 \n", + "Current COPD no 39.6 \n", " yes 40.0 \n", - "SSRI (last 12 months) no 38.4 \n", + "DMARDs no 39.8 \n", + " yes 50.0 \n", + "Psychosis, schizophrenia, or bipolar no 39.9 \n", " yes 20.0 \n", + "SSRI (last 12 months) no 39.7 \n", + " yes 40.0 \n", "\n", " Total eligible \\\n", "Category Group \n", - "overall overall 3409 \n", - "Sex F 1736 \n", - " M 1673 \n", - "Ethnicity (broad categories) Black 581 \n", - " Mixed 539 \n", - " Other 574 \n", - " South Asian 644 \n", - " Unknown 483 \n", - " White 588 \n", - "ethnicity 16 groups African 196 \n", - " Bangladeshi or British Bangladeshi 175 \n", + "overall overall 3192 \n", + "Sex F 1645 \n", + " M 1547 \n", + "Ethnicity (broad categories) Black 546 \n", + " Mixed 546 \n", + " Other 518 \n", + " South Asian 525 \n", + " Unknown 504 \n", + " White 553 \n", + "ethnicity 16 groups African 175 \n", + " Bangladeshi or British Bangladeshi 147 \n", " Caribbean 175 \n", - " Chinese 175 \n", - " Other 168 \n", - " Other Asian 168 \n", - " British or Mixed British 196 \n", - " Indian or British Indian 189 \n", - " Irish 196 \n", - " Other Black 175 \n", + " Chinese 196 \n", + " Other 203 \n", + " Other Asian 182 \n", + " British or Mixed British 168 \n", + " Indian or British Indian 154 \n", + " Irish 154 \n", + " Other Black 161 \n", " Other White 182 \n", - " Other mixed 175 \n", - " Pakistani or British Pakistani 203 \n", - " Unknown 511 \n", - " White + Asian 196 \n", - " White + Black African 168 \n", - " White + Black Caribbean 161 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 672 \n", - " 2 651 \n", - " 3 623 \n", - " 4 623 \n", - " 5 Least deprived 672 \n", + " Other mixed 168 \n", + " Pakistani or British Pakistani 168 \n", + " Unknown 483 \n", + " White + Asian 161 \n", + " White + Black African 161 \n", + " White + Black Caribbean 147 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 595 \n", + " 2 602 \n", + " 3 602 \n", + " 4 616 \n", + " 5 Least deprived 609 \n", " Unknown 168 \n", - "BMI 30+ 1036 \n", - " under 30 2373 \n", - "Chronic cardiac disease no 3374 \n", - " yes 35 \n", - "Current COPD no 3381 \n", + "BMI 30+ 924 \n", + " under 30 2268 \n", + "Chronic cardiac disease no 3164 \n", " yes 28 \n", - "DMARDs no 3381 \n", + "Current COPD no 3164 \n", + " yes 35 \n", + "DMARDs no 3164 \n", " yes 28 \n", - "Psychosis, schizophrenia, or bipolar no 3374 \n", + "Psychosis, schizophrenia, or bipolar no 3157 \n", " yes 35 \n", - "SSRI (last 12 months) no 3374 \n", + "SSRI (last 12 months) no 3157 \n", " yes 35 \n", "\n", " Previous week's vaccination coverage (%) \\\n", "Category Group \n", - "overall overall 35.7 \n", - "Sex F 35.5 \n", - " M 36.0 \n", - "Ethnicity (broad categories) Black 37.3 \n", - " Mixed 39.0 \n", - " Other 35.4 \n", - " South Asian 37.0 \n", - " Unknown 31.9 \n", - " White 34.5 \n", - "ethnicity 16 groups African 35.7 \n", - " Bangladeshi or British Bangladeshi 32.0 \n", - " Caribbean 32.0 \n", - " Chinese 32.0 \n", - " Other 37.5 \n", - " Other Asian 41.7 \n", - " British or Mixed British 35.7 \n", - " Indian or British Indian 33.3 \n", - " Irish 42.9 \n", - " Other Black 36.0 \n", - " Other White 34.6 \n", - " Other mixed 28.0 \n", - " Pakistani or British Pakistani 34.5 \n", - " Unknown 38.4 \n", - " White + Asian 39.3 \n", - " White + Black African 37.5 \n", - " White + Black Caribbean 34.8 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 34.4 \n", - " 2 36.6 \n", - " 3 36.0 \n", - " 4 36.0 \n", - " 5 Least deprived 37.5 \n", + "overall overall 37.5 \n", + "Sex F 36.2 \n", + " M 38.9 \n", + "Ethnicity (broad categories) Black 38.5 \n", + " Mixed 35.9 \n", + " Other 37.8 \n", + " South Asian 36.0 \n", + " Unknown 40.3 \n", + " White 38.0 \n", + "ethnicity 16 groups African 40.0 \n", + " Bangladeshi or British Bangladeshi 33.3 \n", + " Caribbean 40.0 \n", + " Chinese 35.7 \n", + " Other 37.9 \n", + " Other Asian 34.6 \n", + " British or Mixed British 37.5 \n", + " Indian or British Indian 40.9 \n", + " Irish 36.4 \n", + " Other Black 34.8 \n", + " Other White 38.5 \n", + " Other mixed 37.5 \n", + " Pakistani or British Pakistani 37.5 \n", + " Unknown 37.7 \n", + " White + Asian 39.1 \n", + " White + Black African 30.4 \n", + " White + Black Caribbean 38.1 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 38.8 \n", + " 2 37.2 \n", + " 3 37.2 \n", + " 4 35.2 \n", + " 5 Least deprived 39.1 \n", " Unknown 33.3 \n", - "BMI 30+ 35.1 \n", - " under 30 36.0 \n", - "Chronic cardiac disease no 35.7 \n", - " yes 40.0 \n", - "Current COPD no 35.8 \n", + "BMI 30+ 37.9 \n", + " under 30 37.3 \n", + "Chronic cardiac disease no 37.6 \n", " yes 25.0 \n", - "DMARDs no 35.6 \n", - " yes 50.0 \n", - "Psychosis, schizophrenia, or bipolar no 35.7 \n", + "Current COPD no 37.4 \n", " yes 40.0 \n", - "SSRI (last 12 months) no 35.9 \n", + "DMARDs no 37.4 \n", + " yes 50.0 \n", + "Psychosis, schizophrenia, or bipolar no 37.7 \n", " yes 20.0 \n", + "SSRI (last 12 months) no 37.5 \n", + " yes 40.0 \n", "\n", " Vaccinated over last 7d (%) \n", "Category Group \n", - "overall overall 2.6 \n", - "Sex F 2.4 \n", - " M 2.5 \n", + "overall overall 2.3 \n", + "Sex F 2.5 \n", + " M 1.8 \n", "Ethnicity (broad categories) Black 2.5 \n", - " Mixed 1.3 \n", - " Other 2.4 \n", - " South Asian 2.1 \n", - " Unknown 2.9 \n", - " White 3.6 \n", - "ethnicity 16 groups African 3.6 \n", - " Bangladeshi or British Bangladeshi 4.0 \n", + " Mixed 2.6 \n", + " Other 1.4 \n", + " South Asian 1.3 \n", + " Unknown 2.8 \n", + " White 2.5 \n", + "ethnicity 16 groups African 0.0 \n", + " Bangladeshi or British Bangladeshi 4.8 \n", " Caribbean 0.0 \n", - " Chinese 4.0 \n", + " Chinese 3.6 \n", " Other 0.0 \n", - " Other Asian 0.0 \n", - " British or Mixed British 0.0 \n", - " Indian or British Indian 3.7 \n", - " Irish 3.5 \n", - " Other Black 4.0 \n", - " Other White 0.0 \n", + " Other Asian 3.9 \n", + " British or Mixed British 4.2 \n", + " Indian or British Indian 0.0 \n", + " Irish 4.5 \n", + " Other Black 4.3 \n", + " Other White 3.8 \n", " Other mixed 0.0 \n", - " Pakistani or British Pakistani 3.4 \n", - " Unknown 2.7 \n", + " Pakistani or British Pakistani 0.0 \n", + " Unknown 2.9 \n", " White + Asian 0.0 \n", - " White + Black African 4.2 \n", - " White + Black Caribbean 4.3 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 2.1 \n", - " 2 1.0 \n", - " 3 2.2 \n", - " 4 2.2 \n", - " 5 Least deprived 3.1 \n", + " White + Black African 4.4 \n", + " White + Black Caribbean 0.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 3.6 \n", + " 2 2.3 \n", + " 3 3.5 \n", + " 4 2.3 \n", + " 5 Least deprived 2.3 \n", " Unknown 4.2 \n", - "BMI 30+ 2.7 \n", - " under 30 2.3 \n", - "Chronic cardiac disease no 2.7 \n", - " yes 0.0 \n", - "Current COPD no 2.5 \n", + "BMI 30+ 2.3 \n", + " under 30 2.2 \n", + "Chronic cardiac disease no 2.2 \n", + " yes 25.0 \n", + "Current COPD no 2.2 \n", " yes 0.0 \n", - "DMARDs no 2.7 \n", + "DMARDs no 2.4 \n", " yes 0.0 \n", - "Psychosis, schizophrenia, or bipolar no 2.7 \n", + "Psychosis, schizophrenia, or bipolar no 2.2 \n", " yes 0.0 \n", - "SSRI (last 12 months) no 2.5 \n", + "SSRI (last 12 months) no 2.2 \n", " yes 0.0 " ] }, @@ -39863,7 +66645,7 @@ "data": { "text/markdown": [ "## \n", - " ## Cumulative vaccination figures among 16-49, not in other eligible groups shown population \n", + " ## Cumulative vaccination figures among 50-54 population \n", " Please refer to footnotes below table for information." ], "text/plain": [ @@ -39895,10 +66677,11 @@ " \n", " \n", " \n", - " Vaccinated at 30 Mar (n)\n", - " Previous week's vaccination figure (n)\n", - " Vaccinated over last 7d (n)\n", - " Increase in coverage over last 7d (%)\n", + " Vaccinated at 16 Apr (n)\n", + " Vaccinated at 16 Apr (%)\n", + " Total eligible\n", + " Previous week's vaccination coverage (%)\n", + " Vaccinated over last 7d (%)\n", " \n", " \n", " Category\n", @@ -39907,575 +66690,612 @@ " \n", " \n", " \n", + " \n", " \n", " \n", " \n", " \n", " overall\n", " overall\n", - " 12162\n", - " 11440.0\n", - " 722.0\n", - " 6.3\n", + " 1378\n", + " 40.5\n", + " 3402\n", + " 38.0\n", + " 2.5\n", " \n", " \n", " Sex\n", " F\n", - " 6202\n", - " 5845.0\n", - " 357.0\n", - " 6.1\n", + " 665\n", + " 38.8\n", + " 1715\n", + " 36.7\n", + " 2.1\n", " \n", " \n", " M\n", - " 5964\n", - " 5593.0\n", - " 371.0\n", - " 6.6\n", - " \n", - " \n", - " Age band\n", - " 16-29\n", - " 1498\n", - " 1407.0\n", - " 91.0\n", - " 6.5\n", - " \n", - " \n", - " 30-39\n", - " 1519\n", - " 1421.0\n", - " 98.0\n", - " 6.9\n", - " \n", - " \n", - " 40-49\n", - " 1505\n", - " 1421.0\n", - " 84.0\n", - " 5.9\n", - " \n", - " \n", - " 50-59\n", - " 1575\n", - " 1491.0\n", - " 84.0\n", - " 5.6\n", - " \n", - " \n", - " 60-69\n", - " 1547\n", - " 1463.0\n", - " 84.0\n", - " 5.7\n", - " \n", - " \n", - " 70-79\n", - " 3080\n", - " 2877.0\n", - " 203.0\n", - " 7.1\n", - " \n", - " \n", - " 80+\n", - " 1442\n", - " 1351.0\n", - " 91.0\n", - " 6.7\n", + " 707\n", + " 41.9\n", + " 1687\n", + " 39.4\n", + " 2.5\n", " \n", " \n", " Ethnicity (broad categories)\n", " Black\n", - " 2079\n", - " 1939.0\n", - " 140.0\n", - " 7.2\n", + " 245\n", + " 41.7\n", + " 588\n", + " 39.3\n", + " 2.4\n", " \n", " \n", " Mixed\n", - " 2072\n", - " 1967.0\n", - " 105.0\n", - " 5.3\n", + " 245\n", + " 40.2\n", + " 609\n", + " 37.9\n", + " 2.3\n", " \n", " \n", " Other\n", - " 2051\n", - " 1939.0\n", - " 112.0\n", - " 5.8\n", + " 245\n", + " 40.7\n", + " 602\n", + " 38.4\n", + " 2.3\n", " \n", " \n", " South Asian\n", - " 2093\n", - " 1974.0\n", - " 119.0\n", - " 6.0\n", + " 238\n", + " 41.5\n", + " 574\n", + " 40.2\n", + " 1.3\n", " \n", " \n", " Unknown\n", - " 1827\n", - " 1701.0\n", - " 126.0\n", - " 7.4\n", + " 189\n", + " 39.7\n", + " 476\n", + " 36.8\n", + " 2.9\n", " \n", " \n", " White\n", - " 2030\n", - " 1925.0\n", - " 105.0\n", - " 5.5\n", + " 210\n", + " 38.0\n", + " 553\n", + " 35.4\n", + " 2.6\n", " \n", " \n", " ethnicity 16 groups\n", " African\n", - " 637\n", - " 602.0\n", - " 35.0\n", - " 5.8\n", + " 77\n", + " 44.0\n", + " 175\n", + " 40.0\n", + " 4.0\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 616\n", - " 574.0\n", - " 42.0\n", - " 7.3\n", + " 70\n", + " 40.0\n", + " 175\n", + " 36.0\n", + " 4.0\n", " \n", " \n", " Caribbean\n", - " 637\n", - " 602.0\n", - " 35.0\n", - " 5.8\n", + " 70\n", + " 38.5\n", + " 182\n", + " 38.5\n", + " 0.0\n", " \n", " \n", " Chinese\n", - " 637\n", - " 609.0\n", - " 28.0\n", - " 4.6\n", + " 63\n", + " 39.1\n", + " 161\n", + " 34.8\n", + " 4.3\n", " \n", " \n", " Other\n", - " 665\n", - " 630.0\n", - " 35.0\n", - " 5.6\n", + " 77\n", + " 40.7\n", + " 189\n", + " 40.7\n", + " 0.0\n", " \n", " \n", " Other Asian\n", - " 630\n", - " 588.0\n", - " 42.0\n", - " 7.1\n", + " 77\n", + " 42.3\n", + " 182\n", + " 42.3\n", + " 0.0\n", " \n", " \n", " British or Mixed British\n", - " 630\n", - " 588.0\n", - " 42.0\n", - " 7.1\n", + " 70\n", + " 33.3\n", + " 210\n", + " 33.3\n", + " 0.0\n", " \n", " \n", " Indian or British Indian\n", - " 637\n", - " 595.0\n", - " 42.0\n", - " 7.1\n", + " 70\n", + " 40.0\n", + " 175\n", + " 40.0\n", + " 0.0\n", " \n", " \n", " Irish\n", - " 679\n", - " 644.0\n", - " 35.0\n", - " 5.4\n", + " 77\n", + " 39.3\n", + " 196\n", + " 35.7\n", + " 3.6\n", " \n", " \n", " Other Black\n", - " 665\n", - " 630.0\n", - " 35.0\n", - " 5.6\n", + " 77\n", + " 44.0\n", + " 175\n", + " 40.0\n", + " 4.0\n", " \n", " \n", " Other White\n", - " 651\n", - " 616.0\n", - " 35.0\n", - " 5.7\n", + " 77\n", + " 44.0\n", + " 175\n", + " 44.0\n", + " 0.0\n", " \n", " \n", " Other mixed\n", - " 630\n", - " 595.0\n", - " 35.0\n", - " 5.9\n", + " 70\n", + " 40.0\n", + " 175\n", + " 36.0\n", + " 4.0\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 693\n", - " 651.0\n", - " 42.0\n", - " 6.5\n", + " 70\n", + " 41.7\n", + " 168\n", + " 41.7\n", + " 0.0\n", " \n", " \n", " Unknown\n", - " 1862\n", - " 1736.0\n", - " 126.0\n", - " 7.3\n", + " 217\n", + " 40.8\n", + " 532\n", + " 38.2\n", + " 2.6\n", " \n", " \n", " White + Asian\n", - " 637\n", - " 602.0\n", - " 35.0\n", - " 5.8\n", + " 63\n", + " 37.5\n", + " 168\n", + " 33.3\n", + " 4.2\n", " \n", " \n", " White + Black African\n", - " 644\n", - " 609.0\n", - " 35.0\n", - " 5.7\n", + " 84\n", + " 48.0\n", + " 175\n", + " 48.0\n", + " 0.0\n", " \n", " \n", " White + Black Caribbean\n", - " 602\n", - " 567.0\n", - " 35.0\n", - " 6.2\n", + " 77\n", + " 42.3\n", + " 182\n", + " 38.5\n", + " 3.8\n", " \n", " \n", " Index of Multiple Deprivation (quintiles)\n", " 1 Most deprived\n", - " 2275\n", - " 2149.0\n", - " 126.0\n", - " 5.9\n", + " 259\n", + " 39.8\n", + " 651\n", + " 37.6\n", + " 2.2\n", " \n", " \n", " 2\n", - " 2366\n", - " 2219.0\n", - " 147.0\n", - " 6.6\n", + " 238\n", + " 39.1\n", + " 609\n", + " 35.6\n", + " 3.5\n", " \n", " \n", " 3\n", - " 2268\n", - " 2135.0\n", - " 133.0\n", - " 6.2\n", + " 245\n", + " 37.6\n", + " 651\n", + " 34.4\n", + " 3.2\n", " \n", " \n", " 4\n", - " 2387\n", - " 2247.0\n", - " 140.0\n", - " 6.2\n", + " 280\n", + " 41.2\n", + " 679\n", + " 39.2\n", + " 2.0\n", " \n", " \n", " 5 Least deprived\n", - " 2289\n", - " 2142.0\n", - " 147.0\n", - " 6.9\n", + " 280\n", + " 44.0\n", + " 637\n", + " 40.7\n", + " 3.3\n", " \n", " \n", " Unknown\n", - " 588\n", - " 553.0\n", - " 35.0\n", - " 6.3\n", + " 77\n", + " 42.3\n", + " 182\n", + " 38.5\n", + " 3.8\n", " \n", " \n", " BMI\n", " 30+\n", - " 3654\n", - " 3437.0\n", - " 217.0\n", - " 6.3\n", + " 399\n", + " 39.3\n", + " 1015\n", + " 36.6\n", + " 2.7\n", " \n", " \n", " under 30\n", - " 8505\n", - " 8001.0\n", - " 504.0\n", - " 6.3\n", + " 980\n", + " 41.1\n", + " 2387\n", + " 38.7\n", + " 2.4\n", " \n", " \n", " Chronic cardiac disease\n", " no\n", - " 12040\n", - " 11319.0\n", - " 721.0\n", - " 6.4\n", + " 1365\n", + " 40.6\n", + " 3360\n", + " 38.1\n", + " 2.5\n", " \n", " \n", " yes\n", - " 126\n", - " 119.0\n", - " 7.0\n", - " 5.9\n", + " 14\n", + " 33.3\n", + " 42\n", + " 33.3\n", + " 0.0\n", " \n", " \n", " Current COPD\n", " no\n", - " 12026\n", - " 11319.0\n", - " 707.0\n", - " 6.2\n", + " 1372\n", + " 40.7\n", + " 3374\n", + " 38.2\n", + " 2.5\n", " \n", " \n", " yes\n", - " 133\n", - " 119.0\n", - " 14.0\n", - " 11.8\n", + " 7\n", + " 25.0\n", + " 28\n", + " 25.0\n", + " 0.0\n", " \n", " \n", " DMARDs\n", " no\n", - " 12033\n", - " 11319.0\n", - " 714.0\n", - " 6.3\n", + " 1365\n", + " 40.6\n", + " 3360\n", + " 38.1\n", + " 2.5\n", " \n", " \n", " yes\n", - " 126\n", - " 119.0\n", - " 7.0\n", - " 5.9\n", + " 14\n", + " 33.3\n", + " 42\n", + " 33.3\n", + " 0.0\n", + " \n", + " \n", + " Psychosis, schizophrenia, or bipolar\n", + " no\n", + " 1358\n", + " 40.3\n", + " 3367\n", + " 37.8\n", + " 2.5\n", + " \n", + " \n", + " yes\n", + " 21\n", + " 60.0\n", + " 35\n", + " 60.0\n", + " 0.0\n", " \n", " \n", " SSRI (last 12 months)\n", " no\n", - " 12040\n", - " 11326.0\n", - " 714.0\n", - " 6.3\n", + " 1365\n", + " 40.6\n", + " 3360\n", + " 38.1\n", + " 2.5\n", " \n", " \n", " yes\n", - " 119\n", - " 112.0\n", - " 7.0\n", - " 6.2\n", + " 14\n", + " 33.3\n", + " 42\n", + " 33.3\n", + " 0.0\n", " \n", " \n", "\n", "" ], "text/plain": [ - " Vaccinated at 30 Mar (n) \\\n", + " Vaccinated at 16 Apr (n) \\\n", "Category Group \n", - "overall overall 12162 \n", - "Sex F 6202 \n", - " M 5964 \n", - "Age band 16-29 1498 \n", - " 30-39 1519 \n", - " 40-49 1505 \n", - " 50-59 1575 \n", - " 60-69 1547 \n", - " 70-79 3080 \n", - " 80+ 1442 \n", - "Ethnicity (broad categories) Black 2079 \n", - " Mixed 2072 \n", - " Other 2051 \n", - " South Asian 2093 \n", - " Unknown 1827 \n", - " White 2030 \n", - "ethnicity 16 groups African 637 \n", - " Bangladeshi or British Bangladeshi 616 \n", - " Caribbean 637 \n", - " Chinese 637 \n", - " Other 665 \n", - " Other Asian 630 \n", - " British or Mixed British 630 \n", - " Indian or British Indian 637 \n", - " Irish 679 \n", - " Other Black 665 \n", - " Other White 651 \n", - " Other mixed 630 \n", - " Pakistani or British Pakistani 693 \n", - " Unknown 1862 \n", - " White + Asian 637 \n", - " White + Black African 644 \n", - " White + Black Caribbean 602 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 2275 \n", - " 2 2366 \n", - " 3 2268 \n", - " 4 2387 \n", - " 5 Least deprived 2289 \n", - " Unknown 588 \n", - "BMI 30+ 3654 \n", - " under 30 8505 \n", - "Chronic cardiac disease no 12040 \n", - " yes 126 \n", - "Current COPD no 12026 \n", - " yes 133 \n", - "DMARDs no 12033 \n", - " yes 126 \n", - "SSRI (last 12 months) no 12040 \n", - " yes 119 \n", + "overall overall 1378 \n", + "Sex F 665 \n", + " M 707 \n", + "Ethnicity (broad categories) Black 245 \n", + " Mixed 245 \n", + " Other 245 \n", + " South Asian 238 \n", + " Unknown 189 \n", + " White 210 \n", + "ethnicity 16 groups African 77 \n", + " Bangladeshi or British Bangladeshi 70 \n", + " Caribbean 70 \n", + " Chinese 63 \n", + " Other 77 \n", + " Other Asian 77 \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 70 \n", + " Pakistani or British Pakistani 70 \n", + " Unknown 217 \n", + " White + Asian 63 \n", + " White + Black African 84 \n", + " White + Black Caribbean 77 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 259 \n", + " 2 238 \n", + " 3 245 \n", + " 4 280 \n", + " 5 Least deprived 280 \n", + " Unknown 77 \n", + "BMI 30+ 399 \n", + " under 30 980 \n", + "Chronic cardiac disease no 1365 \n", + " yes 14 \n", + "Current COPD no 1372 \n", + " yes 7 \n", + "DMARDs no 1365 \n", + " yes 14 \n", + "Psychosis, schizophrenia, or bipolar no 1358 \n", + " yes 21 \n", + "SSRI (last 12 months) no 1365 \n", + " yes 14 \n", "\n", - " Previous week's vaccination figure (n) \\\n", - "Category Group \n", - "overall overall 11440.0 \n", - "Sex F 5845.0 \n", - " M 5593.0 \n", - "Age band 16-29 1407.0 \n", - " 30-39 1421.0 \n", - " 40-49 1421.0 \n", - " 50-59 1491.0 \n", - " 60-69 1463.0 \n", - " 70-79 2877.0 \n", - " 80+ 1351.0 \n", - "Ethnicity (broad categories) Black 1939.0 \n", - " Mixed 1967.0 \n", - " Other 1939.0 \n", - " South Asian 1974.0 \n", - " Unknown 1701.0 \n", - " White 1925.0 \n", - "ethnicity 16 groups African 602.0 \n", - " Bangladeshi or British Bangladeshi 574.0 \n", - " Caribbean 602.0 \n", - " Chinese 609.0 \n", - " Other 630.0 \n", - " Other Asian 588.0 \n", - " British or Mixed British 588.0 \n", - " Indian or British Indian 595.0 \n", - " Irish 644.0 \n", - " Other Black 630.0 \n", - " Other White 616.0 \n", - " Other mixed 595.0 \n", - " Pakistani or British Pakistani 651.0 \n", - " Unknown 1736.0 \n", - " White + Asian 602.0 \n", - " White + Black African 609.0 \n", - " White + Black Caribbean 567.0 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 2149.0 \n", - " 2 2219.0 \n", - " 3 2135.0 \n", - " 4 2247.0 \n", - " 5 Least deprived 2142.0 \n", - " Unknown 553.0 \n", - "BMI 30+ 3437.0 \n", - " under 30 8001.0 \n", - "Chronic cardiac disease no 11319.0 \n", - " yes 119.0 \n", - "Current COPD no 11319.0 \n", - " yes 119.0 \n", - "DMARDs no 11319.0 \n", - " yes 119.0 \n", - "SSRI (last 12 months) no 11326.0 \n", - " yes 112.0 \n", + " Vaccinated at 16 Apr (%) \\\n", + "Category Group \n", + "overall overall 40.5 \n", + "Sex F 38.8 \n", + " M 41.9 \n", + "Ethnicity (broad categories) Black 41.7 \n", + " Mixed 40.2 \n", + " Other 40.7 \n", + " South Asian 41.5 \n", + " Unknown 39.7 \n", + " White 38.0 \n", + "ethnicity 16 groups African 44.0 \n", + " Bangladeshi or British Bangladeshi 40.0 \n", + " Caribbean 38.5 \n", + " Chinese 39.1 \n", + " Other 40.7 \n", + " Other Asian 42.3 \n", + " British or Mixed British 33.3 \n", + " Indian or British Indian 40.0 \n", + " Irish 39.3 \n", + " Other Black 44.0 \n", + " Other White 44.0 \n", + " Other mixed 40.0 \n", + " Pakistani or British Pakistani 41.7 \n", + " Unknown 40.8 \n", + " White + Asian 37.5 \n", + " White + Black African 48.0 \n", + " White + Black Caribbean 42.3 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 39.8 \n", + " 2 39.1 \n", + " 3 37.6 \n", + " 4 41.2 \n", + " 5 Least deprived 44.0 \n", + " Unknown 42.3 \n", + "BMI 30+ 39.3 \n", + " under 30 41.1 \n", + "Chronic cardiac disease no 40.6 \n", + " yes 33.3 \n", + "Current COPD no 40.7 \n", + " yes 25.0 \n", + "DMARDs no 40.6 \n", + " yes 33.3 \n", + "Psychosis, schizophrenia, or bipolar no 40.3 \n", + " yes 60.0 \n", + "SSRI (last 12 months) no 40.6 \n", + " yes 33.3 \n", "\n", - " Vaccinated over last 7d (n) \\\n", - "Category Group \n", - "overall overall 722.0 \n", - "Sex F 357.0 \n", - " M 371.0 \n", - "Age band 16-29 91.0 \n", - " 30-39 98.0 \n", - " 40-49 84.0 \n", - " 50-59 84.0 \n", - " 60-69 84.0 \n", - " 70-79 203.0 \n", - " 80+ 91.0 \n", - "Ethnicity (broad categories) Black 140.0 \n", - " Mixed 105.0 \n", - " Other 112.0 \n", - " South Asian 119.0 \n", - " Unknown 126.0 \n", - " White 105.0 \n", - "ethnicity 16 groups African 35.0 \n", - " Bangladeshi or British Bangladeshi 42.0 \n", - " Caribbean 35.0 \n", - " Chinese 28.0 \n", - " Other 35.0 \n", - " Other Asian 42.0 \n", - " British or Mixed British 42.0 \n", - " Indian or British Indian 42.0 \n", - " Irish 35.0 \n", - " Other Black 35.0 \n", - " Other White 35.0 \n", - " Other mixed 35.0 \n", - " Pakistani or British Pakistani 42.0 \n", - " Unknown 126.0 \n", - " White + Asian 35.0 \n", - " White + Black African 35.0 \n", - " White + Black Caribbean 35.0 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 126.0 \n", - " 2 147.0 \n", - " 3 133.0 \n", - " 4 140.0 \n", - " 5 Least deprived 147.0 \n", - " Unknown 35.0 \n", - "BMI 30+ 217.0 \n", - " under 30 504.0 \n", - "Chronic cardiac disease no 721.0 \n", - " yes 7.0 \n", - "Current COPD no 707.0 \n", - " yes 14.0 \n", - "DMARDs no 714.0 \n", - " yes 7.0 \n", - "SSRI (last 12 months) no 714.0 \n", - " yes 7.0 \n", + " Total eligible \\\n", + "Category Group \n", + "overall overall 3402 \n", + "Sex F 1715 \n", + " M 1687 \n", + "Ethnicity (broad categories) Black 588 \n", + " Mixed 609 \n", + " Other 602 \n", + " South Asian 574 \n", + " Unknown 476 \n", + " White 553 \n", + "ethnicity 16 groups African 175 \n", + " Bangladeshi or British Bangladeshi 175 \n", + " Caribbean 182 \n", + " Chinese 161 \n", + " Other 189 \n", + " Other Asian 182 \n", + " British or Mixed British 210 \n", + " Indian or British Indian 175 \n", + " Irish 196 \n", + " Other Black 175 \n", + " Other White 175 \n", + " Other mixed 175 \n", + " Pakistani or British Pakistani 168 \n", + " Unknown 532 \n", + " White + Asian 168 \n", + " White + Black African 175 \n", + " White + Black Caribbean 182 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 651 \n", + " 2 609 \n", + " 3 651 \n", + " 4 679 \n", + " 5 Least deprived 637 \n", + " Unknown 182 \n", + "BMI 30+ 1015 \n", + " under 30 2387 \n", + "Chronic cardiac disease no 3360 \n", + " yes 42 \n", + "Current COPD no 3374 \n", + " yes 28 \n", + "DMARDs no 3360 \n", + " yes 42 \n", + "Psychosis, schizophrenia, or bipolar no 3367 \n", + " yes 35 \n", + "SSRI (last 12 months) no 3360 \n", + " yes 42 \n", "\n", - " Increase in coverage over last 7d (%) \n", - "Category Group \n", - "overall overall 6.3 \n", - "Sex F 6.1 \n", - " M 6.6 \n", - "Age band 16-29 6.5 \n", - " 30-39 6.9 \n", - " 40-49 5.9 \n", - " 50-59 5.6 \n", - " 60-69 5.7 \n", - " 70-79 7.1 \n", - " 80+ 6.7 \n", - "Ethnicity (broad categories) Black 7.2 \n", - " Mixed 5.3 \n", - " Other 5.8 \n", - " South Asian 6.0 \n", - " Unknown 7.4 \n", - " White 5.5 \n", - "ethnicity 16 groups African 5.8 \n", - " Bangladeshi or British Bangladeshi 7.3 \n", - " Caribbean 5.8 \n", - " Chinese 4.6 \n", - " Other 5.6 \n", - " Other Asian 7.1 \n", - " British or Mixed British 7.1 \n", - " Indian or British Indian 7.1 \n", - " Irish 5.4 \n", - " Other Black 5.6 \n", - " Other White 5.7 \n", - " Other mixed 5.9 \n", - " Pakistani or British Pakistani 6.5 \n", - " Unknown 7.3 \n", - " White + Asian 5.8 \n", - " White + Black African 5.7 \n", - " White + Black Caribbean 6.2 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 5.9 \n", - " 2 6.6 \n", - " 3 6.2 \n", - " 4 6.2 \n", - " 5 Least deprived 6.9 \n", - " Unknown 6.3 \n", - "BMI 30+ 6.3 \n", - " under 30 6.3 \n", - "Chronic cardiac disease no 6.4 \n", - " yes 5.9 \n", - "Current COPD no 6.2 \n", - " yes 11.8 \n", - "DMARDs no 6.3 \n", - " yes 5.9 \n", - "SSRI (last 12 months) no 6.3 \n", - " yes 6.2 " + " Previous week's vaccination coverage (%) \\\n", + "Category Group \n", + "overall overall 38.0 \n", + "Sex F 36.7 \n", + " M 39.4 \n", + "Ethnicity (broad categories) Black 39.3 \n", + " Mixed 37.9 \n", + " Other 38.4 \n", + " South Asian 40.2 \n", + " Unknown 36.8 \n", + " White 35.4 \n", + "ethnicity 16 groups African 40.0 \n", + " Bangladeshi or British Bangladeshi 36.0 \n", + " Caribbean 38.5 \n", + " Chinese 34.8 \n", + " Other 40.7 \n", + " Other Asian 42.3 \n", + " British or Mixed British 33.3 \n", + " Indian or British Indian 40.0 \n", + " Irish 35.7 \n", + " Other Black 40.0 \n", + " Other White 44.0 \n", + " Other mixed 36.0 \n", + " Pakistani or British Pakistani 41.7 \n", + " Unknown 38.2 \n", + " White + Asian 33.3 \n", + " White + Black African 48.0 \n", + " White + Black Caribbean 38.5 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 37.6 \n", + " 2 35.6 \n", + " 3 34.4 \n", + " 4 39.2 \n", + " 5 Least deprived 40.7 \n", + " Unknown 38.5 \n", + "BMI 30+ 36.6 \n", + " under 30 38.7 \n", + "Chronic cardiac disease no 38.1 \n", + " yes 33.3 \n", + "Current COPD no 38.2 \n", + " yes 25.0 \n", + "DMARDs no 38.1 \n", + " yes 33.3 \n", + "Psychosis, schizophrenia, or bipolar no 37.8 \n", + " yes 60.0 \n", + "SSRI (last 12 months) no 38.1 \n", + " yes 33.3 \n", + "\n", + " Vaccinated over last 7d (%) \n", + "Category Group \n", + "overall overall 2.5 \n", + "Sex F 2.1 \n", + " M 2.5 \n", + "Ethnicity (broad categories) Black 2.4 \n", + " Mixed 2.3 \n", + " Other 2.3 \n", + " South Asian 1.3 \n", + " Unknown 2.9 \n", + " White 2.6 \n", + "ethnicity 16 groups African 4.0 \n", + " Bangladeshi or British Bangladeshi 4.0 \n", + " Caribbean 0.0 \n", + " Chinese 4.3 \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 3.6 \n", + " Other Black 4.0 \n", + " Other White 0.0 \n", + " Other mixed 4.0 \n", + " Pakistani or British Pakistani 0.0 \n", + " Unknown 2.6 \n", + " White + Asian 4.2 \n", + " White + Black African 0.0 \n", + " White + Black Caribbean 3.8 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 2.2 \n", + " 2 3.5 \n", + " 3 3.2 \n", + " 4 2.0 \n", + " 5 Least deprived 3.3 \n", + " Unknown 3.8 \n", + "BMI 30+ 2.7 \n", + " under 30 2.4 \n", + "Chronic cardiac disease no 2.5 \n", + " yes 0.0 \n", + "Current COPD no 2.5 \n", + " yes 0.0 \n", + "DMARDs no 2.5 \n", + " yes 0.0 \n", + "Psychosis, schizophrenia, or bipolar no 2.5 \n", + " yes 0.0 \n", + "SSRI (last 12 months) no 2.5 \n", + " yes 0.0 " ] }, "metadata": {}, @@ -40494,6 +67314,18 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/markdown": [ + "- Population excludes those who are currently shielding." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "data": { "text/markdown": [ @@ -40510,7 +67342,7 @@ "data": { "text/markdown": [ "## \n", - " ## Cumulative vaccination figures among under 55s, not in other eligible groups shown population \n", + " ## Cumulative vaccination figures among 16-49, not in other eligible groups shown population \n", " Please refer to footnotes below table for information." ], "text/plain": [ @@ -40542,7 +67374,7 @@ " \n", " \n", " \n", - " Vaccinated at 30 Mar (n)\n", + " Vaccinated at 16 Apr (n)\n", " Previous week's vaccination figure (n)\n", " Vaccinated over last 7d (n)\n", " Increase in coverage over last 7d (%)\n", @@ -40560,569 +67392,569 @@ " \n", " overall\n", " overall\n", - " 13468\n", - " 12658.0\n", - " 810.0\n", - " 6.4\n", + " 12150\n", + " 11496.0\n", + " 654.0\n", + " 5.7\n", " \n", " \n", " Sex\n", " F\n", - " 6860\n", - " 6461.0\n", - " 399.0\n", - " 6.2\n", + " 6223\n", + " 5887.0\n", + " 336.0\n", + " 5.7\n", " \n", " \n", " M\n", - " 6608\n", - " 6195.0\n", - " 413.0\n", - " 6.7\n", + " 5929\n", + " 5607.0\n", + " 322.0\n", + " 5.7\n", " \n", " \n", " Age band\n", " 16-29\n", - " 1645\n", - " 1540.0\n", - " 105.0\n", - " 6.8\n", + " 1512\n", + " 1428.0\n", + " 84.0\n", + " 5.9\n", " \n", " \n", " 30-39\n", - " 1687\n", - " 1575.0\n", - " 112.0\n", - " 7.1\n", + " 1512\n", + " 1435.0\n", + " 77.0\n", + " 5.4\n", " \n", " \n", " 40-49\n", - " 1687\n", - " 1596.0\n", - " 91.0\n", - " 5.7\n", + " 1512\n", + " 1435.0\n", + " 77.0\n", + " 5.4\n", " \n", " \n", " 50-59\n", - " 1750\n", - " 1652.0\n", - " 98.0\n", - " 5.9\n", + " 1589\n", + " 1498.0\n", + " 91.0\n", + " 6.1\n", " \n", " \n", " 60-69\n", - " 1722\n", - " 1631.0\n", - " 91.0\n", - " 5.6\n", + " 1505\n", + " 1421.0\n", + " 84.0\n", + " 5.9\n", " \n", " \n", " 70-79\n", - " 3402\n", - " 3178.0\n", - " 224.0\n", - " 7.0\n", + " 2982\n", + " 2828.0\n", + " 154.0\n", + " 5.4\n", " \n", " \n", " 80+\n", - " 1582\n", - " 1484.0\n", - " 98.0\n", - " 6.6\n", + " 1540\n", + " 1449.0\n", + " 91.0\n", + " 6.3\n", " \n", " \n", " Ethnicity (broad categories)\n", " Black\n", - " 2310\n", - " 2156.0\n", - " 154.0\n", - " 7.1\n", + " 1995\n", + " 1883.0\n", + " 112.0\n", + " 5.9\n", " \n", " \n", " Mixed\n", - " 2289\n", - " 2170.0\n", - " 119.0\n", - " 5.5\n", + " 2107\n", + " 1995.0\n", + " 112.0\n", + " 5.6\n", " \n", " \n", " Other\n", - " 2268\n", - " 2142.0\n", - " 126.0\n", - " 5.9\n", + " 2121\n", + " 1981.0\n", + " 140.0\n", + " 7.1\n", " \n", " \n", " South Asian\n", - " 2345\n", - " 2205.0\n", - " 140.0\n", - " 6.3\n", + " 2135\n", + " 2037.0\n", + " 98.0\n", + " 4.8\n", " \n", " \n", " Unknown\n", - " 1995\n", - " 1855.0\n", - " 140.0\n", - " 7.5\n", + " 1792\n", + " 1694.0\n", + " 98.0\n", + " 5.8\n", " \n", " \n", " White\n", - " 2254\n", - " 2121.0\n", - " 133.0\n", - " 6.3\n", + " 2002\n", + " 1897.0\n", + " 105.0\n", + " 5.5\n", " \n", " \n", " ethnicity 16 groups\n", " African\n", - " 707\n", - " 672.0\n", + " 637\n", + " 602.0\n", " 35.0\n", - " 5.2\n", + " 5.8\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 679\n", + " 651\n", " 630.0\n", - " 49.0\n", - " 7.8\n", + " 21.0\n", + " 3.3\n", " \n", " \n", " Caribbean\n", - " 693\n", - " 651.0\n", - " 42.0\n", - " 6.5\n", + " 672\n", + " 637.0\n", + " 35.0\n", + " 5.5\n", " \n", " \n", " Chinese\n", - " 700\n", - " 665.0\n", - " 35.0\n", - " 5.3\n", + " 672\n", + " 644.0\n", + " 28.0\n", + " 4.3\n", " \n", " \n", " Other\n", - " 735\n", - " 693.0\n", - " 42.0\n", - " 6.1\n", + " 658\n", + " 623.0\n", + " 35.0\n", + " 5.6\n", " \n", " \n", " Other Asian\n", - " 700\n", - " 658.0\n", + " 630\n", + " 588.0\n", " 42.0\n", - " 6.4\n", + " 7.1\n", " \n", " \n", " British or Mixed British\n", - " 700\n", - " 658.0\n", + " 637\n", + " 595.0\n", " 42.0\n", - " 6.4\n", + " 7.1\n", " \n", " \n", " Indian or British Indian\n", - " 707\n", - " 658.0\n", - " 49.0\n", - " 7.4\n", + " 672\n", + " 637.0\n", + " 35.0\n", + " 5.5\n", " \n", " \n", " Irish\n", - " 770\n", - " 728.0\n", - " 42.0\n", - " 5.8\n", + " 665\n", + " 616.0\n", + " 49.0\n", + " 8.0\n", " \n", " \n", " Other Black\n", - " 735\n", - " 693.0\n", - " 42.0\n", - " 6.1\n", + " 651\n", + " 623.0\n", + " 28.0\n", + " 4.5\n", " \n", " \n", " Other White\n", - " 721\n", - " 672.0\n", - " 49.0\n", - " 7.3\n", + " 602\n", + " 567.0\n", + " 35.0\n", + " 6.2\n", " \n", " \n", " Other mixed\n", - " 686\n", - " 644.0\n", - " 42.0\n", - " 6.5\n", + " 616\n", + " 602.0\n", + " 14.0\n", + " 2.3\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 777\n", - " 721.0\n", - " 56.0\n", - " 7.8\n", + " 616\n", + " 581.0\n", + " 35.0\n", + " 6.0\n", " \n", " \n", " Unknown\n", - " 2072\n", - " 1932.0\n", - " 140.0\n", - " 7.2\n", + " 1813\n", + " 1722.0\n", + " 91.0\n", + " 5.3\n", " \n", " \n", " White + Asian\n", - " 714\n", - " 679.0\n", - " 35.0\n", - " 5.2\n", + " 672\n", + " 630.0\n", + " 42.0\n", + " 6.7\n", " \n", " \n", " White + Black African\n", - " 714\n", - " 672.0\n", - " 42.0\n", - " 6.2\n", + " 658\n", + " 623.0\n", + " 35.0\n", + " 5.6\n", " \n", " \n", " White + Black Caribbean\n", - " 665\n", - " 623.0\n", - " 42.0\n", - " 6.7\n", + " 623\n", + " 588.0\n", + " 35.0\n", + " 6.0\n", " \n", " \n", " Index of Multiple Deprivation (quintiles)\n", " 1 Most deprived\n", - " 2520\n", - " 2373.0\n", - " 147.0\n", - " 6.2\n", + " 2296\n", + " 2170.0\n", + " 126.0\n", + " 5.8\n", " \n", " \n", " 2\n", - " 2611\n", - " 2450.0\n", - " 161.0\n", - " 6.6\n", + " 2345\n", + " 2205.0\n", + " 140.0\n", + " 6.3\n", " \n", " \n", " 3\n", - " 2506\n", - " 2352.0\n", - " 154.0\n", - " 6.5\n", + " 2296\n", + " 2184.0\n", + " 112.0\n", + " 5.1\n", " \n", " \n", " 4\n", - " 2625\n", - " 2464.0\n", - " 161.0\n", - " 6.5\n", + " 2254\n", + " 2128.0\n", + " 126.0\n", + " 5.9\n", " \n", " \n", " 5 Least deprived\n", - " 2555\n", - " 2401.0\n", - " 154.0\n", - " 6.4\n", + " 2331\n", + " 2212.0\n", + " 119.0\n", + " 5.4\n", " \n", " \n", " Unknown\n", - " 651\n", - " 609.0\n", - " 42.0\n", - " 6.9\n", + " 623\n", + " 595.0\n", + " 28.0\n", + " 4.7\n", " \n", " \n", " BMI\n", " 30+\n", - " 4046\n", - " 3808.0\n", - " 238.0\n", - " 6.2\n", + " 3647\n", + " 3465.0\n", + " 182.0\n", + " 5.3\n", " \n", " \n", " under 30\n", - " 9422\n", - " 8855.0\n", - " 567.0\n", - " 6.4\n", + " 8505\n", + " 8029.0\n", + " 476.0\n", + " 5.9\n", " \n", " \n", " Chronic cardiac disease\n", " no\n", - " 13328\n", - " 12523.0\n", - " 805.0\n", - " 6.4\n", + " 12019\n", + " 11375.0\n", + " 644.0\n", + " 5.7\n", " \n", " \n", " yes\n", - " 140\n", - " 133.0\n", + " 126\n", + " 119.0\n", " 7.0\n", - " 5.3\n", + " 5.9\n", " \n", " \n", " Current COPD\n", " no\n", - " 13328\n", - " 12530.0\n", - " 798.0\n", - " 6.4\n", + " 12019\n", + " 11375.0\n", + " 644.0\n", + " 5.7\n", " \n", " \n", " yes\n", - " 140\n", - " 126.0\n", - " 14.0\n", - " 11.1\n", + " 126\n", + " 119.0\n", + " 7.0\n", + " 5.9\n", " \n", " \n", " DMARDs\n", " no\n", - " 13328\n", - " 12530.0\n", - " 798.0\n", - " 6.4\n", + " 12033\n", + " 11382.0\n", + " 651.0\n", + " 5.7\n", " \n", " \n", " yes\n", - " 140\n", - " 133.0\n", + " 119\n", + " 112.0\n", " 7.0\n", - " 5.3\n", + " 6.2\n", " \n", " \n", " SSRI (last 12 months)\n", " no\n", - " 13335\n", - " 12537.0\n", - " 798.0\n", - " 6.4\n", + " 12033\n", + " 11382.0\n", + " 651.0\n", + " 5.7\n", " \n", " \n", " yes\n", - " 133\n", - " 126.0\n", + " 119\n", + " 112.0\n", " 7.0\n", - " 5.6\n", + " 6.2\n", " \n", " \n", "\n", "" ], "text/plain": [ - " Vaccinated at 30 Mar (n) \\\n", + " Vaccinated at 16 Apr (n) \\\n", "Category Group \n", - "overall overall 13468 \n", - "Sex F 6860 \n", - " M 6608 \n", - "Age band 16-29 1645 \n", - " 30-39 1687 \n", - " 40-49 1687 \n", - " 50-59 1750 \n", - " 60-69 1722 \n", - " 70-79 3402 \n", - " 80+ 1582 \n", - "Ethnicity (broad categories) Black 2310 \n", - " Mixed 2289 \n", - " Other 2268 \n", - " South Asian 2345 \n", - " Unknown 1995 \n", - " White 2254 \n", - "ethnicity 16 groups African 707 \n", - " Bangladeshi or British Bangladeshi 679 \n", - " Caribbean 693 \n", - " Chinese 700 \n", - " Other 735 \n", - " Other Asian 700 \n", - " British or Mixed British 700 \n", - " Indian or British Indian 707 \n", - " Irish 770 \n", - " Other Black 735 \n", - " Other White 721 \n", - " Other mixed 686 \n", - " Pakistani or British Pakistani 777 \n", - " Unknown 2072 \n", - " White + Asian 714 \n", - " White + Black African 714 \n", - " White + Black Caribbean 665 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 2520 \n", - " 2 2611 \n", - " 3 2506 \n", - " 4 2625 \n", - " 5 Least deprived 2555 \n", - " Unknown 651 \n", - "BMI 30+ 4046 \n", - " under 30 9422 \n", - "Chronic cardiac disease no 13328 \n", - " yes 140 \n", - "Current COPD no 13328 \n", - " yes 140 \n", - "DMARDs no 13328 \n", - " yes 140 \n", - "SSRI (last 12 months) no 13335 \n", - " yes 133 \n", + "overall overall 12150 \n", + "Sex F 6223 \n", + " M 5929 \n", + "Age band 16-29 1512 \n", + " 30-39 1512 \n", + " 40-49 1512 \n", + " 50-59 1589 \n", + " 60-69 1505 \n", + " 70-79 2982 \n", + " 80+ 1540 \n", + "Ethnicity (broad categories) Black 1995 \n", + " Mixed 2107 \n", + " Other 2121 \n", + " South Asian 2135 \n", + " Unknown 1792 \n", + " White 2002 \n", + "ethnicity 16 groups African 637 \n", + " Bangladeshi or British Bangladeshi 651 \n", + " Caribbean 672 \n", + " Chinese 672 \n", + " Other 658 \n", + " Other Asian 630 \n", + " British or Mixed British 637 \n", + " Indian or British Indian 672 \n", + " Irish 665 \n", + " Other Black 651 \n", + " Other White 602 \n", + " Other mixed 616 \n", + " Pakistani or British Pakistani 616 \n", + " Unknown 1813 \n", + " White + Asian 672 \n", + " White + Black African 658 \n", + " White + Black Caribbean 623 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 2296 \n", + " 2 2345 \n", + " 3 2296 \n", + " 4 2254 \n", + " 5 Least deprived 2331 \n", + " Unknown 623 \n", + "BMI 30+ 3647 \n", + " under 30 8505 \n", + "Chronic cardiac disease no 12019 \n", + " yes 126 \n", + "Current COPD no 12019 \n", + " yes 126 \n", + "DMARDs no 12033 \n", + " yes 119 \n", + "SSRI (last 12 months) no 12033 \n", + " yes 119 \n", "\n", " Previous week's vaccination figure (n) \\\n", "Category Group \n", - "overall overall 12658.0 \n", - "Sex F 6461.0 \n", - " M 6195.0 \n", - "Age band 16-29 1540.0 \n", - " 30-39 1575.0 \n", - " 40-49 1596.0 \n", - " 50-59 1652.0 \n", - " 60-69 1631.0 \n", - " 70-79 3178.0 \n", - " 80+ 1484.0 \n", - "Ethnicity (broad categories) Black 2156.0 \n", - " Mixed 2170.0 \n", - " Other 2142.0 \n", - " South Asian 2205.0 \n", - " Unknown 1855.0 \n", - " White 2121.0 \n", - "ethnicity 16 groups African 672.0 \n", + "overall overall 11496.0 \n", + "Sex F 5887.0 \n", + " M 5607.0 \n", + "Age band 16-29 1428.0 \n", + " 30-39 1435.0 \n", + " 40-49 1435.0 \n", + " 50-59 1498.0 \n", + " 60-69 1421.0 \n", + " 70-79 2828.0 \n", + " 80+ 1449.0 \n", + "Ethnicity (broad categories) Black 1883.0 \n", + " Mixed 1995.0 \n", + " Other 1981.0 \n", + " South Asian 2037.0 \n", + " Unknown 1694.0 \n", + " White 1897.0 \n", + "ethnicity 16 groups African 602.0 \n", " Bangladeshi or British Bangladeshi 630.0 \n", - " Caribbean 651.0 \n", - " Chinese 665.0 \n", - " Other 693.0 \n", - " Other Asian 658.0 \n", - " British or Mixed British 658.0 \n", - " Indian or British Indian 658.0 \n", - " Irish 728.0 \n", - " Other Black 693.0 \n", - " Other White 672.0 \n", - " Other mixed 644.0 \n", - " Pakistani or British Pakistani 721.0 \n", - " Unknown 1932.0 \n", - " White + Asian 679.0 \n", - " White + Black African 672.0 \n", - " White + Black Caribbean 623.0 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 2373.0 \n", - " 2 2450.0 \n", - " 3 2352.0 \n", - " 4 2464.0 \n", - " 5 Least deprived 2401.0 \n", - " Unknown 609.0 \n", - "BMI 30+ 3808.0 \n", - " under 30 8855.0 \n", - "Chronic cardiac disease no 12523.0 \n", - " yes 133.0 \n", - "Current COPD no 12530.0 \n", - " yes 126.0 \n", - "DMARDs no 12530.0 \n", - " yes 133.0 \n", - "SSRI (last 12 months) no 12537.0 \n", - " yes 126.0 \n", + " Caribbean 637.0 \n", + " Chinese 644.0 \n", + " Other 623.0 \n", + " Other Asian 588.0 \n", + " British or Mixed British 595.0 \n", + " Indian or British Indian 637.0 \n", + " Irish 616.0 \n", + " Other Black 623.0 \n", + " Other White 567.0 \n", + " Other mixed 602.0 \n", + " Pakistani or British Pakistani 581.0 \n", + " Unknown 1722.0 \n", + " White + Asian 630.0 \n", + " White + Black African 623.0 \n", + " White + Black Caribbean 588.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 2170.0 \n", + " 2 2205.0 \n", + " 3 2184.0 \n", + " 4 2128.0 \n", + " 5 Least deprived 2212.0 \n", + " Unknown 595.0 \n", + "BMI 30+ 3465.0 \n", + " under 30 8029.0 \n", + "Chronic cardiac disease no 11375.0 \n", + " yes 119.0 \n", + "Current COPD no 11375.0 \n", + " yes 119.0 \n", + "DMARDs no 11382.0 \n", + " yes 112.0 \n", + "SSRI (last 12 months) no 11382.0 \n", + " yes 112.0 \n", "\n", " Vaccinated over last 7d (n) \\\n", "Category Group \n", - "overall overall 810.0 \n", - "Sex F 399.0 \n", - " M 413.0 \n", - "Age band 16-29 105.0 \n", - " 30-39 112.0 \n", - " 40-49 91.0 \n", - " 50-59 98.0 \n", - " 60-69 91.0 \n", - " 70-79 224.0 \n", - " 80+ 98.0 \n", - "Ethnicity (broad categories) Black 154.0 \n", - " Mixed 119.0 \n", - " Other 126.0 \n", - " South Asian 140.0 \n", - " Unknown 140.0 \n", - " White 133.0 \n", + "overall overall 654.0 \n", + "Sex F 336.0 \n", + " M 322.0 \n", + "Age band 16-29 84.0 \n", + " 30-39 77.0 \n", + " 40-49 77.0 \n", + " 50-59 91.0 \n", + " 60-69 84.0 \n", + " 70-79 154.0 \n", + " 80+ 91.0 \n", + "Ethnicity (broad categories) Black 112.0 \n", + " Mixed 112.0 \n", + " Other 140.0 \n", + " South Asian 98.0 \n", + " Unknown 98.0 \n", + " White 105.0 \n", "ethnicity 16 groups African 35.0 \n", - " Bangladeshi or British Bangladeshi 49.0 \n", - " Caribbean 42.0 \n", - " Chinese 35.0 \n", - " Other 42.0 \n", + " Bangladeshi or British Bangladeshi 21.0 \n", + " Caribbean 35.0 \n", + " Chinese 28.0 \n", + " Other 35.0 \n", " Other Asian 42.0 \n", " British or Mixed British 42.0 \n", - " Indian or British Indian 49.0 \n", - " Irish 42.0 \n", - " Other Black 42.0 \n", - " Other White 49.0 \n", - " Other mixed 42.0 \n", - " Pakistani or British Pakistani 56.0 \n", - " Unknown 140.0 \n", - " White + Asian 35.0 \n", - " White + Black African 42.0 \n", - " White + Black Caribbean 42.0 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 147.0 \n", - " 2 161.0 \n", - " 3 154.0 \n", - " 4 161.0 \n", - " 5 Least deprived 154.0 \n", - " Unknown 42.0 \n", - "BMI 30+ 238.0 \n", - " under 30 567.0 \n", - "Chronic cardiac disease no 805.0 \n", + " Indian or British Indian 35.0 \n", + " Irish 49.0 \n", + " Other Black 28.0 \n", + " Other White 35.0 \n", + " Other mixed 14.0 \n", + " Pakistani or British Pakistani 35.0 \n", + " Unknown 91.0 \n", + " White + Asian 42.0 \n", + " White + Black African 35.0 \n", + " White + Black Caribbean 35.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 126.0 \n", + " 2 140.0 \n", + " 3 112.0 \n", + " 4 126.0 \n", + " 5 Least deprived 119.0 \n", + " Unknown 28.0 \n", + "BMI 30+ 182.0 \n", + " under 30 476.0 \n", + "Chronic cardiac disease no 644.0 \n", + " yes 7.0 \n", + "Current COPD no 644.0 \n", " yes 7.0 \n", - "Current COPD no 798.0 \n", - " yes 14.0 \n", - "DMARDs no 798.0 \n", + "DMARDs no 651.0 \n", " yes 7.0 \n", - "SSRI (last 12 months) no 798.0 \n", + "SSRI (last 12 months) no 651.0 \n", " yes 7.0 \n", "\n", " Increase in coverage over last 7d (%) \n", "Category Group \n", - "overall overall 6.4 \n", - "Sex F 6.2 \n", - " M 6.7 \n", - "Age band 16-29 6.8 \n", - " 30-39 7.1 \n", - " 40-49 5.7 \n", - " 50-59 5.9 \n", - " 60-69 5.6 \n", - " 70-79 7.0 \n", - " 80+ 6.6 \n", - "Ethnicity (broad categories) Black 7.1 \n", - " Mixed 5.5 \n", - " Other 5.9 \n", - " South Asian 6.3 \n", - " Unknown 7.5 \n", - " White 6.3 \n", - "ethnicity 16 groups African 5.2 \n", - " Bangladeshi or British Bangladeshi 7.8 \n", - " Caribbean 6.5 \n", - " Chinese 5.3 \n", - " Other 6.1 \n", - " Other Asian 6.4 \n", - " British or Mixed British 6.4 \n", - " Indian or British Indian 7.4 \n", - " Irish 5.8 \n", - " Other Black 6.1 \n", - " Other White 7.3 \n", - " Other mixed 6.5 \n", - " Pakistani or British Pakistani 7.8 \n", - " Unknown 7.2 \n", - " White + Asian 5.2 \n", - " White + Black African 6.2 \n", - " White + Black Caribbean 6.7 \n", - "Index of Multiple Deprivation (quintiles) 1 Most deprived 6.2 \n", - " 2 6.6 \n", - " 3 6.5 \n", - " 4 6.5 \n", - " 5 Least deprived 6.4 \n", - " Unknown 6.9 \n", - "BMI 30+ 6.2 \n", - " under 30 6.4 \n", - "Chronic cardiac disease no 6.4 \n", - " yes 5.3 \n", - "Current COPD no 6.4 \n", - " yes 11.1 \n", - "DMARDs no 6.4 \n", - " yes 5.3 \n", - "SSRI (last 12 months) no 6.4 \n", - " yes 5.6 " + "overall overall 5.7 \n", + "Sex F 5.7 \n", + " M 5.7 \n", + "Age band 16-29 5.9 \n", + " 30-39 5.4 \n", + " 40-49 5.4 \n", + " 50-59 6.1 \n", + " 60-69 5.9 \n", + " 70-79 5.4 \n", + " 80+ 6.3 \n", + "Ethnicity (broad categories) Black 5.9 \n", + " Mixed 5.6 \n", + " Other 7.1 \n", + " South Asian 4.8 \n", + " Unknown 5.8 \n", + " White 5.5 \n", + "ethnicity 16 groups African 5.8 \n", + " Bangladeshi or British Bangladeshi 3.3 \n", + " Caribbean 5.5 \n", + " Chinese 4.3 \n", + " Other 5.6 \n", + " Other Asian 7.1 \n", + " British or Mixed British 7.1 \n", + " Indian or British Indian 5.5 \n", + " Irish 8.0 \n", + " Other Black 4.5 \n", + " Other White 6.2 \n", + " Other mixed 2.3 \n", + " Pakistani or British Pakistani 6.0 \n", + " Unknown 5.3 \n", + " White + Asian 6.7 \n", + " White + Black African 5.6 \n", + " White + Black Caribbean 6.0 \n", + "Index of Multiple Deprivation (quintiles) 1 Most deprived 5.8 \n", + " 2 6.3 \n", + " 3 5.1 \n", + " 4 5.9 \n", + " 5 Least deprived 5.4 \n", + " Unknown 4.7 \n", + "BMI 30+ 5.3 \n", + " under 30 5.9 \n", + "Chronic cardiac disease no 5.7 \n", + " yes 5.9 \n", + "Current COPD no 5.7 \n", + " yes 5.9 \n", + "DMARDs no 5.7 \n", + " yes 6.2 \n", + "SSRI (last 12 months) no 5.7 \n", + " yes 6.2 " ] }, "metadata": {}, @@ -41175,7 +68007,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -41227,48 +68059,48 @@ " \n", " \n", " 80+\n", - " 2121\n", - " 85.5\n", + " 2044\n", + " 85.3\n", " \n", " \n", " 70-79\n", - " 3570\n", + " 3437\n", " 84.5\n", " \n", " \n", " care home\n", - " 1372\n", - " 84.2\n", + " 1386\n", + " 84.8\n", " \n", " \n", " shielding (aged 16-69)\n", - " 413\n", - " 83.1\n", + " 434\n", + " 82.3\n", " \n", " \n", " 65-69\n", - " 2191\n", - " 85.6\n", + " 2184\n", + " 84.0\n", " \n", " \n", " LD (aged 16-64)\n", - " 784\n", - " 86.6\n", + " 826\n", + " 85.6\n", " \n", " \n", " 60-64\n", - " 2632\n", - " 85.1\n", + " 2716\n", + " 85.3\n", " \n", " \n", " 55-59\n", - " 3136\n", - " 85.5\n", + " 3192\n", + " 84.2\n", " \n", " \n", " 50-54\n", - " 3409\n", - " 85.8\n", + " 3402\n", + " 86.0\n", " \n", " \n", "\n", @@ -41277,18 +68109,18 @@ "text/plain": [ " total population (n) ethnicity coverage (%)\n", "group \n", - "80+ 2121 85.5\n", - "70-79 3570 84.5\n", - "care home 1372 84.2\n", - "shielding (aged 16-69) 413 83.1\n", - "65-69 2191 85.6\n", - "LD (aged 16-64) 784 86.6\n", - "60-64 2632 85.1\n", - "55-59 3136 85.5\n", - "50-54 3409 85.8" - ] - }, - "execution_count": 15, + "80+ 2044 85.3\n", + "70-79 3437 84.5\n", + "care home 1386 84.8\n", + "shielding (aged 16-69) 434 82.3\n", + "65-69 2184 84.0\n", + "LD (aged 16-64) 826 85.6\n", + "60-64 2716 85.3\n", + "55-59 3192 84.2\n", + "50-54 3402 86.0" + ] + }, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } diff --git a/notebooks/population_characteristics.ipynb b/notebooks/population_characteristics.ipynb index 9398e55..62bec42 100644 --- a/notebooks/population_characteristics.ipynb +++ b/notebooks/population_characteristics.ipynb @@ -118,7 +118,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Latest Date: 30 Mar 2021\n" + "Latest Date: 16 Apr 2021\n" ] } ], @@ -251,7 +251,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -363,8 +363,8 @@ " \n", " \n", " \n", - " first dose as at 30 Mar 2021\n", - " second dose as at 30 Mar 2021\n", + " first dose as at 16 Apr 2021\n", + " second dose as at 16 Apr 2021\n", " \n", " \n", " \n", @@ -375,84 +375,84 @@ " \n", " \n", " 80+\n", - " 40.1% (854 of 2,121)\n", - " 10.1% (217 of 2,121)\n", + " 40.7% (833 of 2,044)\n", + " 10.4% (210 of 2,044)\n", " \n", " \n", " 70-79\n", - " 39.5% (1,414 of 3,570)\n", - " 9.6% (343 of 3,570)\n", + " 39.4% (1,351 of 3,437)\n", + " 9.0% (308 of 3,437)\n", " \n", " \n", " care home\n", - " 40.0% (546 of 1,372)\n", - " 10.6% (147 of 1,372)\n", + " 40.0% (553 of 1,386)\n", + " 10.2% (140 of 1,386)\n", " \n", " \n", " shielding (aged 16-69)\n", - " 37.0% (154 of 413)\n", - " 10.2% (42 of 413)\n", + " 41.5% (182 of 434)\n", + " 9.9% (42 of 434)\n", " \n", " \n", " 65-69\n", - " 41.1% (903 of 2,191)\n", - " 9.6% (210 of 2,191)\n", + " 39.3% (861 of 2,184)\n", + " 9.5% (210 of 2,184)\n", " \n", " \n", " LD (aged 16-64)\n", - " 41.3% (322 of 784)\n", - " 10.3% (84 of 784)\n", + " 41.6% (343 of 826)\n", + " 7.9% (63 of 826)\n", " \n", " \n", " 60-64\n", - " 39.7% (1,043 of 2,632)\n", - " 11.2% (294 of 2,632)\n", + " 39.7% (1,078 of 2,716)\n", + " 9.5% (259 of 2,716)\n", " \n", " \n", " 55-59\n", - " 41.5% (1,302 of 3,136)\n", - " 10.0% (315 of 3,136)\n", + " 39.8% (1,267 of 3,192)\n", + " 9.8% (315 of 3,192)\n", " \n", " \n", " 50-54\n", - " 38.3% (1,309 of 3,409)\n", - " 9.7% (329 of 3,409)\n", + " 40.5% (1,379 of 3,402)\n", + " 10.9% (371 of 3,402)\n", " \n", " \n", " 16-49, not in other eligible groups shown\n", - " 12,159\n", - " 3,024\n", + " 12,152\n", + " 3,080\n", " \n", " \n", "\n", "" ], "text/plain": [ - " first dose as at 30 Mar 2021 \\\n", + " first dose as at 16 Apr 2021 \\\n", "Total vaccinated in TPP 19,999 \n", - "80+ 40.1% (854 of 2,121) \n", - "70-79 39.5% (1,414 of 3,570) \n", - "care home 40.0% (546 of 1,372) \n", - "shielding (aged 16-69) 37.0% (154 of 413) \n", - "65-69 41.1% (903 of 2,191) \n", - "LD (aged 16-64) 41.3% (322 of 784) \n", - "60-64 39.7% (1,043 of 2,632) \n", - "55-59 41.5% (1,302 of 3,136) \n", - "50-54 38.3% (1,309 of 3,409) \n", - "16-49, not in other eligible groups shown 12,159 \n", + "80+ 40.7% (833 of 2,044) \n", + "70-79 39.4% (1,351 of 3,437) \n", + "care home 40.0% (553 of 1,386) \n", + "shielding (aged 16-69) 41.5% (182 of 434) \n", + "65-69 39.3% (861 of 2,184) \n", + "LD (aged 16-64) 41.6% (343 of 826) \n", + "60-64 39.7% (1,078 of 2,716) \n", + "55-59 39.8% (1,267 of 3,192) \n", + "50-54 40.5% (1,379 of 3,402) \n", + "16-49, not in other eligible groups shown 12,152 \n", "\n", - " second dose as at 30 Mar 2021 \n", + " second dose as at 16 Apr 2021 \n", "Total vaccinated in TPP 4,998 \n", - "80+ 10.1% (217 of 2,121) \n", - "70-79 9.6% (343 of 3,570) \n", - "care home 10.6% (147 of 1,372) \n", - "shielding (aged 16-69) 10.2% (42 of 413) \n", - "65-69 9.6% (210 of 2,191) \n", - "LD (aged 16-64) 10.3% (84 of 784) \n", - "60-64 11.2% (294 of 2,632) \n", - "55-59 10.0% (315 of 3,136) \n", - "50-54 9.7% (329 of 3,409) \n", - "16-49, not in other eligible groups shown 3,024 " + "80+ 10.4% (210 of 2,044) \n", + "70-79 9.0% (308 of 3,437) \n", + "care home 10.2% (140 of 1,386) \n", + "shielding (aged 16-69) 9.9% (42 of 434) \n", + "65-69 9.5% (210 of 2,184) \n", + "LD (aged 16-64) 7.9% (63 of 826) \n", + "60-64 9.5% (259 of 2,716) \n", + "55-59 9.8% (315 of 3,192) \n", + "50-54 10.9% (371 of 3,402) \n", + "16-49, not in other eligible groups shown 3,080 " ] }, "metadata": {}, @@ -569,7 +569,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout among **80+** population up to 30 Mar 2021" + "## COVID vaccination rollout among **80+** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -635,131 +635,131 @@ " \n", " overall\n", " overall\n", - " 851\n", - " 40.1\n", - " 2121\n", - " 37.4\n", - " 2.7\n", - " 06-Aug\n", + " 831\n", + " 40.7\n", + " 2044\n", + " 38.8\n", + " 1.9\n", + " unknown\n", " \n", " \n", " sex\n", " F\n", - " 455\n", - " 41.1\n", - " 1106\n", - " 38.6\n", - " 2.5\n", - " 13-Aug\n", + " 406\n", + " 40.6\n", + " 1001\n", + " 38.5\n", + " 2.1\n", + " 27-Sep\n", " \n", " \n", " M\n", - " 399\n", - " 39.3\n", - " 1015\n", - " 36.6\n", - " 2.7\n", - " 08-Aug\n", + " 427\n", + " 40.7\n", + " 1050\n", + " 38.7\n", + " 2\n", + " 05-Oct\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 56\n", - " 44.4\n", - " 126\n", - " 38.9\n", - " 5.5\n", - " 27-May\n", + " 49\n", + " 36.8\n", + " 133\n", + " 36.8\n", + " 0\n", + " unknown\n", " \n", " \n", " 0-15\n", - " 56\n", - " 38.1\n", - " 147\n", - " 33.3\n", - " 4.8\n", - " 13-Jun\n", + " 49\n", + " 38.9\n", + " 126\n", + " 38.9\n", + " 0\n", + " unknown\n", " \n", " \n", " 16-29\n", " 56\n", - " 40.0\n", - " 140\n", - " 40\n", + " 47.1\n", + " 119\n", + " 47.1\n", " 0\n", " unknown\n", " \n", " \n", " 30-34\n", - " 49\n", - " 36.8\n", - " 133\n", - " 36.8\n", - " 0\n", - " unknown\n", + " 56\n", + " 44.4\n", + " 126\n", + " 38.9\n", + " 5.5\n", + " 13-Jun\n", " \n", " \n", " 35-39\n", - " 35\n", - " 27.8\n", + " 42\n", + " 33.3\n", " 126\n", - " 27.8\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " 40-44\n", - " 42\n", - " 35.3\n", - " 119\n", - " 29.4\n", - " 5.9\n", - " 02-Jun\n", + " 63\n", + " 47.4\n", + " 133\n", + " 42.1\n", + " 5.3\n", + " 11-Jun\n", " \n", " \n", " 45-49\n", " 56\n", - " 44.4\n", - " 126\n", - " 44.4\n", + " 42.1\n", + " 133\n", + " 42.1\n", " 0\n", " unknown\n", " \n", " \n", " 50-54\n", - " 56\n", - " 42.1\n", - " 133\n", - " 42.1\n", + " 42\n", + " 35.3\n", + " 119\n", + " 35.3\n", " 0\n", " unknown\n", " \n", " \n", " 55-59\n", " 49\n", - " 38.9\n", - " 126\n", - " 33.3\n", - " 5.6\n", - " 01-Jun\n", + " 41.2\n", + " 119\n", + " 41.2\n", + " 0\n", + " unknown\n", " \n", " \n", " 60-64\n", - " 49\n", - " 35.0\n", - " 140\n", - " 35\n", - " 0\n", - " unknown\n", + " 56\n", + " 42.1\n", + " 133\n", + " 36.8\n", + " 5.3\n", + " 18-Jun\n", " \n", " \n", " 65-69\n", - " 70\n", - " 52.6\n", - " 133\n", - " 47.4\n", - " 5.2\n", - " 19-May\n", + " 42\n", + " 35.3\n", + " 119\n", + " 35.3\n", + " 0\n", + " unknown\n", " \n", " \n", " 70-74\n", @@ -768,89 +768,89 @@ " 147\n", " 38.1\n", " 4.8\n", - " 06-Jun\n", + " 23-Jun\n", " \n", " \n", " 75-79\n", - " 56\n", - " 40.0\n", - " 140\n", - " 35\n", - " 5\n", - " 08-Jun\n", + " 49\n", + " 38.9\n", + " 126\n", + " 33.3\n", + " 5.6\n", + " 18-Jun\n", " \n", " \n", " 80-84\n", " 56\n", - " 47.1\n", - " 119\n", - " 41.2\n", - " 5.9\n", - " 19-May\n", + " 42.1\n", + " 133\n", + " 36.8\n", + " 5.3\n", + " 18-Jun\n", " \n", " \n", " 85-89\n", - " 49\n", - " 38.9\n", - " 126\n", - " 38.9\n", + " 56\n", + " 40.0\n", + " 140\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " 90+\n", - " 63\n", - " 45.0\n", - " 140\n", - " 40\n", - " 5\n", - " 01-Jun\n", + " 42\n", + " 35.3\n", + " 119\n", + " 35.3\n", + " 0\n", + " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 140\n", - " 36.4\n", - " 385\n", - " 34.5\n", - " 1.9\n", + " 154\n", + " 40.7\n", + " 378\n", + " 38.9\n", + " 1.8\n", " unknown\n", " \n", " \n", " Mixed\n", - " 140\n", - " 40.0\n", - " 350\n", - " 36\n", - " 4\n", - " 25-Jun\n", + " 147\n", + " 42.9\n", + " 343\n", + " 40.8\n", + " 2.1\n", + " 20-Sep\n", " \n", " \n", " Other\n", - " 140\n", - " 39.2\n", - " 357\n", - " 37.3\n", + " 133\n", + " 36.5\n", + " 364\n", + " 34.6\n", " 1.9\n", " unknown\n", " \n", " \n", " South Asian\n", - " 161\n", - " 41.8\n", - " 385\n", - " 40\n", - " 1.8\n", - " unknown\n", + " 126\n", + " 39.1\n", + " 322\n", + " 37\n", + " 2.1\n", + " 02-Oct\n", " \n", " \n", " Unknown\n", - " 119\n", - " 38.6\n", + " 133\n", + " 43.2\n", " 308\n", - " 36.4\n", - " 2.2\n", - " 09-Sep\n", + " 40.9\n", + " 2.3\n", + " 05-Sep\n", " \n", " \n", " White\n", @@ -859,110 +859,101 @@ " 336\n", " 41.7\n", " 2.1\n", - " 31-Aug\n", + " 17-Sep\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 56\n", - " 44.4\n", - " 126\n", - " 38.9\n", - " 5.5\n", - " 27-May\n", + " 49\n", + " 41.2\n", + " 119\n", + " 41.2\n", + " 0\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 42\n", - " 42.9\n", - " 98\n", - " 42.9\n", - " 0\n", - " unknown\n", + " 56\n", + " 53.3\n", + " 105\n", + " 46.7\n", + " 6.6\n", + " 24-May\n", " \n", " \n", " Caribbean\n", - " 42\n", - " 42.9\n", - " 98\n", - " 35.7\n", - " 7.2\n", - " 14-May\n", + " 49\n", + " 43.8\n", + " 112\n", + " 43.8\n", + " 0\n", + " unknown\n", " \n", " \n", " Chinese\n", - " 42\n", - " 37.5\n", - " 112\n", - " 37.5\n", + " 35\n", + " 38.5\n", + " 91\n", + " 38.5\n", " 0\n", " unknown\n", " \n", " \n", " Other\n", - " 49\n", - " 41.2\n", - " 119\n", - " 35.3\n", - " 5.9\n", - " 26-May\n", + " 42\n", + " 40.0\n", + " 105\n", + " 40\n", + " 0\n", + " unknown\n", " \n", " \n", " Other Asian\n", " 49\n", - " 41.2\n", - " 119\n", - " 35.3\n", - " 5.9\n", - " 26-May\n", + " 43.8\n", + " 112\n", + " 37.5\n", + " 6.3\n", + " 06-Jun\n", " \n", " \n", " British or Mixed British\n", - " 49\n", - " 41.2\n", - " 119\n", - " 35.3\n", - " 5.9\n", - " 26-May\n", + " 42\n", + " 40.0\n", + " 105\n", + " 40\n", + " 0\n", + " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 49\n", - " 36.8\n", - " 133\n", - " 36.8\n", + " 42\n", + " 40.0\n", + " 105\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " Irish\n", " 35\n", - " 33.3\n", - " 105\n", - " 33.3\n", + " 35.7\n", + " 98\n", + " 35.7\n", " 0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 56\n", + " 42\n", " 50.0\n", - " 112\n", - " 43.8\n", - " 6.2\n", - " 14-May\n", + " 84\n", + " 50\n", + " 0\n", + " unknown\n", " \n", " \n", " Other White\n", - " 56\n", - " 42.1\n", - " 133\n", - " 36.8\n", - " 5.3\n", - " 01-Jun\n", - " \n", - " \n", - " Other mixed\n", " 42\n", " 40.0\n", " 105\n", @@ -971,133 +962,142 @@ " unknown\n", " \n", " \n", + " Other mixed\n", + " 42\n", + " 40.0\n", + " 105\n", + " 33.3\n", + " 6.7\n", + " 07-Jun\n", + " \n", + " \n", " Pakistani or British Pakistani\n", - " 35\n", - " 35.7\n", - " 98\n", - " 28.6\n", - " 7.1\n", - " 22-May\n", + " 49\n", + " 41.2\n", + " 119\n", + " 41.2\n", + " 0\n", + " unknown\n", " \n", " \n", " Unknown\n", " 119\n", - " 40.5\n", - " 294\n", - " 35.7\n", - " 4.8\n", - " 10-Jun\n", + " 36.2\n", + " 329\n", + " 34\n", + " 2.2\n", + " 04-Oct\n", " \n", " \n", " White + Asian\n", - " 42\n", - " 37.5\n", + " 35\n", + " 31.2\n", " 112\n", - " 37.5\n", + " 31.2\n", " 0\n", " unknown\n", " \n", " \n", " White + Black African\n", - " 56\n", - " 44.4\n", - " 126\n", - " 44.4\n", + " 42\n", + " 37.5\n", + " 112\n", + " 37.5\n", " 0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 42\n", - " 40.0\n", - " 105\n", - " 40\n", + " 49\n", + " 38.9\n", + " 126\n", + " 38.9\n", " 0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 168\n", - " 39.3\n", - " 427\n", - " 36.1\n", - " 3.2\n", - " 18-Jul\n", + " 175\n", + " 42.4\n", + " 413\n", + " 40.7\n", + " 1.7\n", + " unknown\n", " \n", " \n", " 2\n", - " 168\n", - " 42.1\n", - " 399\n", - " 40.4\n", - " 1.7\n", - " unknown\n", + " 140\n", + " 40.8\n", + " 343\n", + " 38.8\n", + " 2\n", + " 05-Oct\n", " \n", " \n", " 3\n", - " 175\n", - " 43.1\n", - " 406\n", - " 39.7\n", - " 3.4\n", - " 04-Jul\n", + " 154\n", + " 39.3\n", + " 392\n", + " 37.5\n", + " 1.8\n", + " unknown\n", " \n", " \n", " 4\n", " 168\n", " 42.1\n", " 399\n", - " 38.6\n", - " 3.5\n", - " 03-Jul\n", + " 40.4\n", + " 1.7\n", + " unknown\n", " \n", " \n", " 5 Least deprived\n", - " 147\n", - " 38.2\n", - " 385\n", - " 34.5\n", - " 3.7\n", - " 06-Jul\n", + " 154\n", + " 39.3\n", + " 392\n", + " 37.5\n", + " 1.8\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 28\n", - " 26.7\n", - " 105\n", - " 26.7\n", + " 42\n", + " 42.9\n", + " 98\n", + " 42.9\n", " 0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 259\n", - " 38.9\n", - " 665\n", - " 36.8\n", - " 2.1\n", - " 16-Sep\n", + " 231\n", + " 38.4\n", + " 602\n", + " 37.2\n", + " 1.2\n", + " unknown\n", " \n", " \n", " under 30\n", - " 595\n", - " 40.9\n", - " 1456\n", - " 37.5\n", - " 3.4\n", - " 09-Jul\n", + " 602\n", + " 41.7\n", + " 1442\n", + " 39.8\n", + " 1.9\n", + " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 840\n", - " 40.1\n", - " 2093\n", - " 37.5\n", - " 2.6\n", - " 11-Aug\n", + " 819\n", + " 40.5\n", + " 2023\n", + " 38.8\n", + " 1.7\n", + " unknown\n", " \n", " \n", " yes\n", @@ -1111,12 +1111,12 @@ " \n", " current_copd\n", " no\n", - " 847\n", - " 40.2\n", - " 2107\n", - " 37.5\n", - " 2.7\n", - " 06-Aug\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 39\n", + " 1.7\n", + " unknown\n", " \n", " \n", " yes\n", @@ -1130,12 +1130,12 @@ " \n", " dialysis\n", " no\n", - " 840\n", - " 40.0\n", - " 2100\n", - " 37.3\n", - " 2.7\n", - " 06-Aug\n", + " 819\n", + " 40.5\n", + " 2023\n", + " 38.8\n", + " 1.7\n", + " unknown\n", " \n", " \n", " yes\n", @@ -1149,18 +1149,18 @@ " \n", " dmards\n", " no\n", - " 847\n", - " 40.3\n", - " 2100\n", - " 37.7\n", - " 2.6\n", - " 10-Aug\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 39\n", + " 1.7\n", + " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 14\n", " 0\n", " 0\n", " unknown\n", @@ -1168,18 +1168,18 @@ " \n", " dementia\n", " no\n", - " 847\n", - " 40.3\n", - " 2100\n", - " 37.7\n", - " 2.6\n", - " 10-Aug\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 39\n", + " 1.7\n", + " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 14\n", " 0\n", " 0\n", " unknown\n", @@ -1187,18 +1187,18 @@ " \n", " psychosis_schiz_bipolar\n", " no\n", - " 847\n", - " 40.2\n", - " 2107\n", - " 37.5\n", - " 2.7\n", - " 06-Aug\n", + " 826\n", + " 40.5\n", + " 2037\n", + " 38.8\n", + " 1.7\n", + " unknown\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 14\n", + " 7\n", " 0\n", " 0\n", " unknown\n", @@ -1206,12 +1206,12 @@ " \n", " LD\n", " no\n", - " 826\n", - " 39.7\n", - " 2079\n", - " 37\n", - " 2.7\n", - " 07-Aug\n", + " 812\n", + " 40.6\n", + " 2002\n", + " 38.5\n", + " 2.1\n", + " 27-Sep\n", " \n", " \n", " yes\n", @@ -1225,56 +1225,56 @@ " \n", " ssri\n", " no\n", - " 840\n", - " 40.0\n", - " 2100\n", - " 37.3\n", - " 2.7\n", - " 06-Aug\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 38.6\n", + " 2.1\n", + " 27-Sep\n", " \n", " \n", " yes\n", " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 50.0\n", + " 14\n", + " 50\n", " 0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 847\n", - " 40.2\n", - " 2107\n", - " 37.5\n", - " 2.7\n", - " 06-Aug\n", + " 826\n", + " 40.8\n", + " 2023\n", + " 38.8\n", + " 2\n", + " 05-Oct\n", " \n", " \n", " yes\n", + " 7\n", + " 33.3\n", + " 21\n", " 0\n", - " 0.0\n", - " 14\n", - " 0\n", - " 0\n", - " unknown\n", + " 33.3\n", + " 27-Apr\n", " \n", " \n", " lung_cancer\n", " no\n", - " 847\n", - " 40.3\n", - " 2100\n", - " 37.7\n", - " 2.6\n", - " 10-Aug\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 38.6\n", + " 2.1\n", + " 27-Sep\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 14\n", " 0\n", " 0\n", " unknown\n", @@ -1282,37 +1282,37 @@ " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 840\n", - " 40.1\n", - " 2093\n", - " 37.5\n", - " 2.6\n", - " 11-Aug\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 39\n", + " 1.7\n", + " unknown\n", " \n", " \n", " yes\n", - " 7\n", - " 25.0\n", - " 28\n", - " 25\n", + " 0\n", + " 0.0\n", + " 14\n", + " 0\n", " 0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 847\n", - " 40.3\n", - " 2100\n", - " 37.7\n", - " 2.6\n", - " 10-Aug\n", + " 826\n", + " 40.7\n", + " 2030\n", + " 38.6\n", + " 2.1\n", + " 27-Sep\n", " \n", " \n", " yes\n", " 0\n", " 0.0\n", - " 21\n", + " 14\n", " 0\n", " 0\n", " unknown\n", @@ -1324,387 +1324,387 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 851 \n", - "sex F 455 \n", - " M 399 \n", - "ageband_5yr 0 56 \n", - " 0-15 56 \n", + "overall overall 831 \n", + "sex F 406 \n", + " M 427 \n", + "ageband_5yr 0 49 \n", + " 0-15 49 \n", " 16-29 56 \n", - " 30-34 49 \n", - " 35-39 35 \n", - " 40-44 42 \n", + " 30-34 56 \n", + " 35-39 42 \n", + " 40-44 63 \n", " 45-49 56 \n", - " 50-54 56 \n", + " 50-54 42 \n", " 55-59 49 \n", - " 60-64 49 \n", - " 65-69 70 \n", + " 60-64 56 \n", + " 65-69 42 \n", " 70-74 63 \n", - " 75-79 56 \n", + " 75-79 49 \n", " 80-84 56 \n", - " 85-89 49 \n", - " 90+ 63 \n", - "ethnicity_6_groups Black 140 \n", - " Mixed 140 \n", - " Other 140 \n", - " South Asian 161 \n", - " Unknown 119 \n", + " 85-89 56 \n", + " 90+ 42 \n", + "ethnicity_6_groups Black 154 \n", + " Mixed 147 \n", + " Other 133 \n", + " South Asian 126 \n", + " Unknown 133 \n", " White 147 \n", - "ethnicity_16_groups African 56 \n", - " Bangladeshi or British Bangladeshi 42 \n", - " Caribbean 42 \n", - " Chinese 42 \n", - " Other 49 \n", + "ethnicity_16_groups African 49 \n", + " Bangladeshi or British Bangladeshi 56 \n", + " Caribbean 49 \n", + " Chinese 35 \n", + " Other 42 \n", " Other Asian 49 \n", - " British or Mixed British 49 \n", - " Indian or British Indian 49 \n", + " British or Mixed British 42 \n", + " Indian or British Indian 42 \n", " Irish 35 \n", - " Other Black 56 \n", - " Other White 56 \n", + " Other Black 42 \n", + " Other White 42 \n", " Other mixed 42 \n", - " Pakistani or British Pakistani 35 \n", + " Pakistani or British Pakistani 49 \n", " Unknown 119 \n", - " White + Asian 42 \n", - " White + Black African 56 \n", - " White + Black Caribbean 42 \n", - "imd_categories 1 Most deprived 168 \n", - " 2 168 \n", - " 3 175 \n", + " White + Asian 35 \n", + " White + Black African 42 \n", + " White + Black Caribbean 49 \n", + "imd_categories 1 Most deprived 175 \n", + " 2 140 \n", + " 3 154 \n", " 4 168 \n", - " 5 Least deprived 147 \n", - " Unknown 28 \n", - "bmi 30+ 259 \n", - " under 30 595 \n", - "chronic_cardiac_disease no 840 \n", + " 5 Least deprived 154 \n", + " Unknown 42 \n", + "bmi 30+ 231 \n", + " under 30 602 \n", + "chronic_cardiac_disease no 819 \n", " yes 7 \n", - "current_copd no 847 \n", + "current_copd no 826 \n", " yes 0 \n", - "dialysis no 840 \n", + "dialysis no 819 \n", " yes 7 \n", - "dmards no 847 \n", + "dmards no 826 \n", " yes 0 \n", - "dementia no 847 \n", + "dementia no 826 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 847 \n", + "psychosis_schiz_bipolar no 826 \n", " yes 0 \n", - "LD no 826 \n", + "LD no 812 \n", " yes 21 \n", - "ssri no 840 \n", + "ssri no 826 \n", " yes 7 \n", - "chemo_or_radio no 847 \n", + "chemo_or_radio no 826 \n", + " yes 7 \n", + "lung_cancer no 826 \n", " yes 0 \n", - "lung_cancer no 847 \n", + "cancer_excl_lung_and_haem no 826 \n", " yes 0 \n", - "cancer_excl_lung_and_haem no 840 \n", - " yes 7 \n", - "haematological_cancer no 847 \n", + "haematological_cancer no 826 \n", " yes 0 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 40.1 2121 \n", - "sex F 41.1 1106 \n", - " M 39.3 1015 \n", - "ageband_5yr 0 44.4 126 \n", - " 0-15 38.1 147 \n", - " 16-29 40.0 140 \n", - " 30-34 36.8 133 \n", - " 35-39 27.8 126 \n", - " 40-44 35.3 119 \n", - " 45-49 44.4 126 \n", - " 50-54 42.1 133 \n", - " 55-59 38.9 126 \n", - " 60-64 35.0 140 \n", - " 65-69 52.6 133 \n", + "overall overall 40.7 2044 \n", + "sex F 40.6 1001 \n", + " M 40.7 1050 \n", + "ageband_5yr 0 36.8 133 \n", + " 0-15 38.9 126 \n", + " 16-29 47.1 119 \n", + " 30-34 44.4 126 \n", + " 35-39 33.3 126 \n", + " 40-44 47.4 133 \n", + " 45-49 42.1 133 \n", + " 50-54 35.3 119 \n", + " 55-59 41.2 119 \n", + " 60-64 42.1 133 \n", + " 65-69 35.3 119 \n", " 70-74 42.9 147 \n", - " 75-79 40.0 140 \n", - " 80-84 47.1 119 \n", - " 85-89 38.9 126 \n", - " 90+ 45.0 140 \n", - "ethnicity_6_groups Black 36.4 385 \n", - " Mixed 40.0 350 \n", - " Other 39.2 357 \n", - " South Asian 41.8 385 \n", - " Unknown 38.6 308 \n", + " 75-79 38.9 126 \n", + " 80-84 42.1 133 \n", + " 85-89 40.0 140 \n", + " 90+ 35.3 119 \n", + "ethnicity_6_groups Black 40.7 378 \n", + " Mixed 42.9 343 \n", + " Other 36.5 364 \n", + " South Asian 39.1 322 \n", + " Unknown 43.2 308 \n", " White 43.8 336 \n", - "ethnicity_16_groups African 44.4 126 \n", - " Bangladeshi or British Bangladeshi 42.9 98 \n", - " Caribbean 42.9 98 \n", - " Chinese 37.5 112 \n", - " Other 41.2 119 \n", - " Other Asian 41.2 119 \n", - " British or Mixed British 41.2 119 \n", - " Indian or British Indian 36.8 133 \n", - " Irish 33.3 105 \n", - " Other Black 50.0 112 \n", - " Other White 42.1 133 \n", + "ethnicity_16_groups African 41.2 119 \n", + " Bangladeshi or British Bangladeshi 53.3 105 \n", + " Caribbean 43.8 112 \n", + " Chinese 38.5 91 \n", + " Other 40.0 105 \n", + " Other Asian 43.8 112 \n", + " British or Mixed British 40.0 105 \n", + " Indian or British Indian 40.0 105 \n", + " Irish 35.7 98 \n", + " Other Black 50.0 84 \n", + " Other White 40.0 105 \n", " Other mixed 40.0 105 \n", - " Pakistani or British Pakistani 35.7 98 \n", - " Unknown 40.5 294 \n", - " White + Asian 37.5 112 \n", - " White + Black African 44.4 126 \n", - " White + Black Caribbean 40.0 105 \n", - "imd_categories 1 Most deprived 39.3 427 \n", - " 2 42.1 399 \n", - " 3 43.1 406 \n", + " Pakistani or British Pakistani 41.2 119 \n", + " Unknown 36.2 329 \n", + " White + Asian 31.2 112 \n", + " White + Black African 37.5 112 \n", + " White + Black Caribbean 38.9 126 \n", + "imd_categories 1 Most deprived 42.4 413 \n", + " 2 40.8 343 \n", + " 3 39.3 392 \n", " 4 42.1 399 \n", - " 5 Least deprived 38.2 385 \n", - " Unknown 26.7 105 \n", - "bmi 30+ 38.9 665 \n", - " under 30 40.9 1456 \n", - "chronic_cardiac_disease no 40.1 2093 \n", + " 5 Least deprived 39.3 392 \n", + " Unknown 42.9 98 \n", + "bmi 30+ 38.4 602 \n", + " under 30 41.7 1442 \n", + "chronic_cardiac_disease no 40.5 2023 \n", " yes 25.0 28 \n", - "current_copd no 40.2 2107 \n", + "current_copd no 40.7 2030 \n", " yes 0.0 14 \n", - "dialysis no 40.0 2100 \n", + "dialysis no 40.5 2023 \n", " yes 33.3 21 \n", - "dmards no 40.3 2100 \n", - " yes 0.0 21 \n", - "dementia no 40.3 2100 \n", - " yes 0.0 21 \n", - "psychosis_schiz_bipolar no 40.2 2107 \n", + "dmards no 40.7 2030 \n", + " yes 0.0 14 \n", + "dementia no 40.7 2030 \n", " yes 0.0 14 \n", - "LD no 39.7 2079 \n", + "psychosis_schiz_bipolar no 40.5 2037 \n", + " yes 0.0 7 \n", + "LD no 40.6 2002 \n", " yes 50.0 42 \n", - "ssri no 40.0 2100 \n", + "ssri no 40.7 2030 \n", + " yes 50.0 14 \n", + "chemo_or_radio no 40.8 2023 \n", " yes 33.3 21 \n", - "chemo_or_radio no 40.2 2107 \n", + "lung_cancer no 40.7 2030 \n", + " yes 0.0 14 \n", + "cancer_excl_lung_and_haem no 40.7 2030 \n", + " yes 0.0 14 \n", + "haematological_cancer no 40.7 2030 \n", " yes 0.0 14 \n", - "lung_cancer no 40.3 2100 \n", - " yes 0.0 21 \n", - "cancer_excl_lung_and_haem no 40.1 2093 \n", - " yes 25.0 28 \n", - "haematological_cancer no 40.3 2100 \n", - " yes 0.0 21 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 37.4 \n", - "sex F 38.6 \n", - " M 36.6 \n", - "ageband_5yr 0 38.9 \n", - " 0-15 33.3 \n", - " 16-29 40 \n", - " 30-34 36.8 \n", - " 35-39 27.8 \n", - " 40-44 29.4 \n", - " 45-49 44.4 \n", - " 50-54 42.1 \n", - " 55-59 33.3 \n", - " 60-64 35 \n", - " 65-69 47.4 \n", + "overall overall 38.8 \n", + "sex F 38.5 \n", + " M 38.7 \n", + "ageband_5yr 0 36.8 \n", + " 0-15 38.9 \n", + " 16-29 47.1 \n", + " 30-34 38.9 \n", + " 35-39 33.3 \n", + " 40-44 42.1 \n", + " 45-49 42.1 \n", + " 50-54 35.3 \n", + " 55-59 41.2 \n", + " 60-64 36.8 \n", + " 65-69 35.3 \n", " 70-74 38.1 \n", - " 75-79 35 \n", - " 80-84 41.2 \n", - " 85-89 38.9 \n", - " 90+ 40 \n", - "ethnicity_6_groups Black 34.5 \n", - " Mixed 36 \n", - " Other 37.3 \n", - " South Asian 40 \n", - " Unknown 36.4 \n", + " 75-79 33.3 \n", + " 80-84 36.8 \n", + " 85-89 40 \n", + " 90+ 35.3 \n", + "ethnicity_6_groups Black 38.9 \n", + " Mixed 40.8 \n", + " Other 34.6 \n", + " South Asian 37 \n", + " Unknown 40.9 \n", " White 41.7 \n", - "ethnicity_16_groups African 38.9 \n", - " Bangladeshi or British Bangladeshi 42.9 \n", - " Caribbean 35.7 \n", - " Chinese 37.5 \n", - " Other 35.3 \n", - " Other Asian 35.3 \n", - " British or Mixed British 35.3 \n", - " Indian or British Indian 36.8 \n", - " Irish 33.3 \n", - " Other Black 43.8 \n", - " Other White 36.8 \n", - " Other mixed 40 \n", - " Pakistani or British Pakistani 28.6 \n", - " Unknown 35.7 \n", - " White + Asian 37.5 \n", - " White + Black African 44.4 \n", - " White + Black Caribbean 40 \n", - "imd_categories 1 Most deprived 36.1 \n", - " 2 40.4 \n", - " 3 39.7 \n", - " 4 38.6 \n", - " 5 Least deprived 34.5 \n", - " Unknown 26.7 \n", - "bmi 30+ 36.8 \n", - " under 30 37.5 \n", - "chronic_cardiac_disease no 37.5 \n", + "ethnicity_16_groups African 41.2 \n", + " Bangladeshi or British Bangladeshi 46.7 \n", + " Caribbean 43.8 \n", + " Chinese 38.5 \n", + " Other 40 \n", + " Other Asian 37.5 \n", + " British or Mixed British 40 \n", + " Indian or British Indian 40 \n", + " Irish 35.7 \n", + " Other Black 50 \n", + " Other White 40 \n", + " Other mixed 33.3 \n", + " Pakistani or British Pakistani 41.2 \n", + " Unknown 34 \n", + " White + Asian 31.2 \n", + " White + Black African 37.5 \n", + " White + Black Caribbean 38.9 \n", + "imd_categories 1 Most deprived 40.7 \n", + " 2 38.8 \n", + " 3 37.5 \n", + " 4 40.4 \n", + " 5 Least deprived 37.5 \n", + " Unknown 42.9 \n", + "bmi 30+ 37.2 \n", + " under 30 39.8 \n", + "chronic_cardiac_disease no 38.8 \n", " yes 25 \n", - "current_copd no 37.5 \n", + "current_copd no 39 \n", " yes 0 \n", - "dialysis no 37.3 \n", + "dialysis no 38.8 \n", " yes 33.3 \n", - "dmards no 37.7 \n", + "dmards no 39 \n", " yes 0 \n", - "dementia no 37.7 \n", + "dementia no 39 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 37.5 \n", + "psychosis_schiz_bipolar no 38.8 \n", " yes 0 \n", - "LD no 37 \n", + "LD no 38.5 \n", " yes 50 \n", - "ssri no 37.3 \n", - " yes 33.3 \n", - "chemo_or_radio no 37.5 \n", + "ssri no 38.6 \n", + " yes 50 \n", + "chemo_or_radio no 38.8 \n", " yes 0 \n", - "lung_cancer no 37.7 \n", + "lung_cancer no 38.6 \n", " yes 0 \n", - "cancer_excl_lung_and_haem no 37.5 \n", - " yes 25 \n", - "haematological_cancer no 37.7 \n", + "cancer_excl_lung_and_haem no 39 \n", + " yes 0 \n", + "haematological_cancer no 38.6 \n", " yes 0 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 2.7 \n", - "sex F 2.5 \n", - " M 2.7 \n", - "ageband_5yr 0 5.5 \n", - " 0-15 4.8 \n", + "overall overall 1.9 \n", + "sex F 2.1 \n", + " M 2 \n", + "ageband_5yr 0 0 \n", + " 0-15 0 \n", " 16-29 0 \n", - " 30-34 0 \n", + " 30-34 5.5 \n", " 35-39 0 \n", - " 40-44 5.9 \n", + " 40-44 5.3 \n", " 45-49 0 \n", " 50-54 0 \n", - " 55-59 5.6 \n", - " 60-64 0 \n", - " 65-69 5.2 \n", + " 55-59 0 \n", + " 60-64 5.3 \n", + " 65-69 0 \n", " 70-74 4.8 \n", - " 75-79 5 \n", - " 80-84 5.9 \n", + " 75-79 5.6 \n", + " 80-84 5.3 \n", " 85-89 0 \n", - " 90+ 5 \n", - "ethnicity_6_groups Black 1.9 \n", - " Mixed 4 \n", + " 90+ 0 \n", + "ethnicity_6_groups Black 1.8 \n", + " Mixed 2.1 \n", " Other 1.9 \n", - " South Asian 1.8 \n", - " Unknown 2.2 \n", + " South Asian 2.1 \n", + " Unknown 2.3 \n", " White 2.1 \n", - "ethnicity_16_groups African 5.5 \n", - " Bangladeshi or British Bangladeshi 0 \n", - " Caribbean 7.2 \n", + "ethnicity_16_groups African 0 \n", + " Bangladeshi or British Bangladeshi 6.6 \n", + " Caribbean 0 \n", " Chinese 0 \n", - " Other 5.9 \n", - " Other Asian 5.9 \n", - " British or Mixed British 5.9 \n", + " Other 0 \n", + " Other Asian 6.3 \n", + " British or Mixed British 0 \n", " Indian or British Indian 0 \n", " Irish 0 \n", - " Other Black 6.2 \n", - " Other White 5.3 \n", - " Other mixed 0 \n", - " Pakistani or British Pakistani 7.1 \n", - " Unknown 4.8 \n", + " Other Black 0 \n", + " Other White 0 \n", + " Other mixed 6.7 \n", + " Pakistani or British Pakistani 0 \n", + " Unknown 2.2 \n", " White + Asian 0 \n", " White + Black African 0 \n", " White + Black Caribbean 0 \n", - "imd_categories 1 Most deprived 3.2 \n", - " 2 1.7 \n", - " 3 3.4 \n", - " 4 3.5 \n", - " 5 Least deprived 3.7 \n", + "imd_categories 1 Most deprived 1.7 \n", + " 2 2 \n", + " 3 1.8 \n", + " 4 1.7 \n", + " 5 Least deprived 1.8 \n", " Unknown 0 \n", - "bmi 30+ 2.1 \n", - " under 30 3.4 \n", - "chronic_cardiac_disease no 2.6 \n", - " yes 0 \n", - "current_copd no 2.7 \n", + "bmi 30+ 1.2 \n", + " under 30 1.9 \n", + "chronic_cardiac_disease no 1.7 \n", " yes 0 \n", - "dialysis no 2.7 \n", + "current_copd no 1.7 \n", " yes 0 \n", - "dmards no 2.6 \n", + "dialysis no 1.7 \n", " yes 0 \n", - "dementia no 2.6 \n", + "dmards no 1.7 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 2.7 \n", + "dementia no 1.7 \n", " yes 0 \n", - "LD no 2.7 \n", + "psychosis_schiz_bipolar no 1.7 \n", " yes 0 \n", - "ssri no 2.7 \n", + "LD no 2.1 \n", " yes 0 \n", - "chemo_or_radio no 2.7 \n", + "ssri no 2.1 \n", " yes 0 \n", - "lung_cancer no 2.6 \n", + "chemo_or_radio no 2 \n", + " yes 33.3 \n", + "lung_cancer no 2.1 \n", " yes 0 \n", - "cancer_excl_lung_and_haem no 2.6 \n", + "cancer_excl_lung_and_haem no 1.7 \n", " yes 0 \n", - "haematological_cancer no 2.6 \n", + "haematological_cancer no 2.1 \n", " yes 0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 06-Aug \n", - "sex F 13-Aug \n", - " M 08-Aug \n", - "ageband_5yr 0 27-May \n", - " 0-15 13-Jun \n", + "overall overall unknown \n", + "sex F 27-Sep \n", + " M 05-Oct \n", + "ageband_5yr 0 unknown \n", + " 0-15 unknown \n", " 16-29 unknown \n", - " 30-34 unknown \n", + " 30-34 13-Jun \n", " 35-39 unknown \n", - " 40-44 02-Jun \n", + " 40-44 11-Jun \n", " 45-49 unknown \n", " 50-54 unknown \n", - " 55-59 01-Jun \n", - " 60-64 unknown \n", - " 65-69 19-May \n", - " 70-74 06-Jun \n", - " 75-79 08-Jun \n", - " 80-84 19-May \n", + " 55-59 unknown \n", + " 60-64 18-Jun \n", + " 65-69 unknown \n", + " 70-74 23-Jun \n", + " 75-79 18-Jun \n", + " 80-84 18-Jun \n", " 85-89 unknown \n", - " 90+ 01-Jun \n", + " 90+ unknown \n", "ethnicity_6_groups Black unknown \n", - " Mixed 25-Jun \n", + " Mixed 20-Sep \n", " Other unknown \n", - " South Asian unknown \n", - " Unknown 09-Sep \n", - " White 31-Aug \n", - "ethnicity_16_groups African 27-May \n", - " Bangladeshi or British Bangladeshi unknown \n", - " Caribbean 14-May \n", + " South Asian 02-Oct \n", + " Unknown 05-Sep \n", + " White 17-Sep \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi 24-May \n", + " Caribbean unknown \n", " Chinese unknown \n", - " Other 26-May \n", - " Other Asian 26-May \n", - " British or Mixed British 26-May \n", + " Other unknown \n", + " Other Asian 06-Jun \n", + " British or Mixed British unknown \n", " Indian or British Indian unknown \n", " Irish unknown \n", - " Other Black 14-May \n", - " Other White 01-Jun \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani 22-May \n", - " Unknown 10-Jun \n", + " Other Black unknown \n", + " Other White unknown \n", + " Other mixed 07-Jun \n", + " Pakistani or British Pakistani unknown \n", + " Unknown 04-Oct \n", " White + Asian unknown \n", " White + Black African unknown \n", " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived 18-Jul \n", - " 2 unknown \n", - " 3 04-Jul \n", - " 4 03-Jul \n", - " 5 Least deprived 06-Jul \n", + "imd_categories 1 Most deprived unknown \n", + " 2 05-Oct \n", + " 3 unknown \n", + " 4 unknown \n", + " 5 Least deprived unknown \n", " Unknown unknown \n", - "bmi 30+ 16-Sep \n", - " under 30 09-Jul \n", - "chronic_cardiac_disease no 11-Aug \n", - " yes unknown \n", - "current_copd no 06-Aug \n", + "bmi 30+ unknown \n", + " under 30 unknown \n", + "chronic_cardiac_disease no unknown \n", " yes unknown \n", - "dialysis no 06-Aug \n", + "current_copd no unknown \n", " yes unknown \n", - "dmards no 10-Aug \n", + "dialysis no unknown \n", " yes unknown \n", - "dementia no 10-Aug \n", + "dmards no unknown \n", " yes unknown \n", - "psychosis_schiz_bipolar no 06-Aug \n", + "dementia no unknown \n", " yes unknown \n", - "LD no 07-Aug \n", + "psychosis_schiz_bipolar no unknown \n", " yes unknown \n", - "ssri no 06-Aug \n", + "LD no 27-Sep \n", " yes unknown \n", - "chemo_or_radio no 06-Aug \n", + "ssri no 27-Sep \n", " yes unknown \n", - "lung_cancer no 10-Aug \n", + "chemo_or_radio no 05-Oct \n", + " yes 27-Apr \n", + "lung_cancer no 27-Sep \n", " yes unknown \n", - "cancer_excl_lung_and_haem no 11-Aug \n", + "cancer_excl_lung_and_haem no unknown \n", " yes unknown \n", - "haematological_cancer no 10-Aug \n", + "haematological_cancer no 27-Sep \n", " yes unknown " ] }, @@ -1726,7 +1726,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout among **70-79** population up to 30 Mar 2021" + "## COVID vaccination rollout among **70-79** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -1792,216 +1792,198 @@ " \n", " overall\n", " overall\n", - " 1411\n", - " 39.5\n", - " 3570\n", + " 1354\n", + " 39.4\n", + " 3437\n", " 37.3\n", - " 2.2\n", - " 06-Sep\n", + " 2.1\n", + " 01-Oct\n", " \n", " \n", " sex\n", " F\n", - " 714\n", - " 40.0\n", - " 1785\n", - " 37.6\n", - " 2.4\n", - " 22-Aug\n", - " \n", - " \n", - " M\n", " 693\n", - " 39.0\n", - " 1778\n", - " 37\n", + " 39.9\n", + " 1736\n", + " 37.9\n", " 2\n", " unknown\n", " \n", " \n", + " M\n", + " 658\n", + " 38.7\n", + " 1701\n", + " 36.6\n", + " 2.1\n", + " 04-Oct\n", + " \n", + " \n", " ageband_5yr\n", " 0\n", " 84\n", " 37.5\n", " 224\n", - " 34.4\n", - " 3.1\n", - " 26-Jul\n", + " 37.5\n", + " 0\n", + " unknown\n", " \n", " \n", " 0-15\n", - " 91\n", - " 37.1\n", - " 245\n", - " 37.1\n", + " 70\n", + " 40.0\n", + " 175\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " 16-29\n", - " 77\n", - " 36.7\n", - " 210\n", + " 84\n", + " 36.4\n", + " 231\n", " 33.3\n", - " 3.4\n", - " 17-Jul\n", + " 3.1\n", + " 15-Aug\n", " \n", " \n", " 30-34\n", " 91\n", - " 37.1\n", - " 245\n", - " 37.1\n", - " 0\n", - " unknown\n", + " 43.3\n", + " 210\n", + " 40\n", + " 3.3\n", + " 24-Jul\n", " \n", " \n", " 35-39\n", - " 84\n", - " 36.4\n", + " 98\n", + " 42.4\n", " 231\n", - " 33.3\n", - " 3.1\n", - " 29-Jul\n", + " 39.4\n", + " 3\n", + " 05-Aug\n", " \n", " \n", " 40-44\n", - " 105\n", - " 44.1\n", - " 238\n", - " 44.1\n", + " 91\n", + " 39.4\n", + " 231\n", + " 39.4\n", " 0\n", " unknown\n", " \n", " \n", " 45-49\n", - " 70\n", - " 35.7\n", - " 196\n", - " 32.1\n", - " 3.6\n", - " 13-Jul\n", - " \n", - " \n", - " 50-54\n", " 98\n", - " 45.2\n", - " 217\n", - " 41.9\n", - " 3.3\n", - " 03-Jul\n", + " 42.4\n", + " 231\n", + " 39.4\n", + " 3\n", + " 05-Aug\n", " \n", " \n", - " 55-59\n", - " 84\n", - " 41.4\n", - " 203\n", - " 41.4\n", + " 50-54\n", + " 70\n", + " 38.5\n", + " 182\n", + " 38.5\n", " 0\n", " unknown\n", " \n", " \n", + " 55-59\n", + " 84\n", + " 38.7\n", + " 217\n", + " 35.5\n", + " 3.2\n", + " 06-Aug\n", + " \n", + " \n", " 60-64\n", - " 91\n", - " 40.6\n", - " 224\n", - " 40.6\n", + " 77\n", + " 36.7\n", + " 210\n", + " 36.7\n", " 0\n", " unknown\n", " \n", " \n", " 65-69\n", - " 91\n", - " 39.4\n", - " 231\n", - " 39.4\n", - " 0\n", - " unknown\n", + " 84\n", + " 40.0\n", + " 210\n", + " 36.7\n", + " 3.3\n", + " 31-Jul\n", " \n", " \n", " 70-74\n", - " 84\n", - " 37.5\n", - " 224\n", - " 34.4\n", - " 3.1\n", - " 26-Jul\n", + " 91\n", + " 38.2\n", + " 238\n", + " 35.3\n", + " 2.9\n", + " 19-Aug\n", " \n", " \n", " 75-79\n", - " 91\n", - " 41.9\n", - " 217\n", - " 38.7\n", - " 3.2\n", - " 13-Jul\n", + " 84\n", + " 41.4\n", + " 203\n", + " 37.9\n", + " 3.5\n", + " 22-Jul\n", " \n", " \n", " 80-84\n", - " 84\n", - " 40.0\n", - " 210\n", - " 36.7\n", - " 3.3\n", - " 14-Jul\n", + " 77\n", + " 39.3\n", + " 196\n", + " 39.3\n", + " 0\n", + " unknown\n", " \n", " \n", " 85-89\n", - " 98\n", - " 42.4\n", + " 84\n", + " 36.4\n", " 231\n", - " 39.4\n", - " 3\n", - " 19-Jul\n", + " 33.3\n", + " 3.1\n", + " 15-Aug\n", " \n", " \n", " 90+\n", - " 77\n", - " 35.5\n", + " 91\n", + " 41.9\n", " 217\n", - " 35.5\n", - " 0\n", - " unknown\n", + " 38.7\n", + " 3.2\n", + " 30-Jul\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 224\n", - " 39.0\n", - " 574\n", - " 37.8\n", - " 1.2\n", - " unknown\n", - " \n", - " \n", - " Mixed\n", " 231\n", - " 36.3\n", - " 637\n", - " 34.1\n", - " 2.2\n", - " 16-Sep\n", + " 37.5\n", + " 616\n", + " 35.2\n", + " 2.3\n", + " 22-Sep\n", " \n", " \n", - " Other\n", - " 245\n", - " 40.2\n", - " 609\n", - " 39.1\n", - " 1.1\n", + " Mixed\n", + " 217\n", + " 38.8\n", + " 560\n", + " 37.5\n", + " 1.3\n", " unknown\n", " \n", " \n", - " South Asian\n", - " 252\n", - " 40.4\n", - " 623\n", - " 37.1\n", - " 3.3\n", - " 13-Jul\n", - " \n", - " \n", - " Unknown\n", + " Other\n", " 217\n", " 39.7\n", " 546\n", @@ -2010,384 +1992,402 @@ " unknown\n", " \n", " \n", - " White\n", + " South Asian\n", " 245\n", " 42.2\n", " 581\n", - " 38.6\n", - " 3.6\n", - " 30-Jun\n", + " 39.8\n", + " 2.4\n", + " 02-Sep\n", + " \n", + " \n", + " Unknown\n", + " 203\n", + " 38.7\n", + " 525\n", + " 36\n", + " 2.7\n", + " 27-Aug\n", + " \n", + " \n", + " White\n", + " 238\n", + " 39.5\n", + " 602\n", + " 37.2\n", + " 2.3\n", + " 16-Sep\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", " 63\n", - " 34.6\n", - " 182\n", - " 34.6\n", + " 33.3\n", + " 189\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 70\n", - " 41.7\n", - " 168\n", - " 37.5\n", - " 4.2\n", - " 18-Jun\n", + " 77\n", + " 37.9\n", + " 203\n", + " 34.5\n", + " 3.4\n", + " 01-Aug\n", " \n", " \n", " Caribbean\n", - " 77\n", - " 42.3\n", - " 182\n", - " 38.5\n", - " 3.8\n", - " 25-Jun\n", + " 84\n", + " 44.4\n", + " 189\n", + " 40.7\n", + " 3.7\n", + " 11-Jul\n", " \n", " \n", " Chinese\n", " 70\n", - " 40.0\n", - " 175\n", - " 36\n", - " 4\n", - " 25-Jun\n", + " 37.0\n", + " 189\n", + " 33.3\n", + " 3.7\n", + " 25-Jul\n", " \n", " \n", " Other\n", - " 77\n", - " 44.0\n", - " 175\n", - " 40\n", - " 4\n", - " 18-Jun\n", + " 84\n", + " 44.4\n", + " 189\n", + " 40.7\n", + " 3.7\n", + " 11-Jul\n", " \n", " \n", " Other Asian\n", - " 77\n", - " 40.7\n", - " 189\n", - " 37\n", - " 3.7\n", - " 01-Jul\n", + " 70\n", + " 40.0\n", + " 175\n", + " 40\n", + " 0\n", + " unknown\n", " \n", " \n", " British or Mixed British\n", - " 91\n", - " 46.4\n", - " 196\n", - " 42.9\n", - " 3.5\n", - " 25-Jun\n", + " 63\n", + " 36.0\n", + " 175\n", + " 32\n", + " 4\n", + " 19-Jul\n", " \n", " \n", " Indian or British Indian\n", - " 84\n", - " 41.4\n", - " 203\n", - " 41.4\n", - " 0\n", - " unknown\n", + " 77\n", + " 44.0\n", + " 175\n", + " 40\n", + " 4\n", + " 05-Jul\n", " \n", " \n", " Irish\n", - " 70\n", - " 38.5\n", - " 182\n", - " 38.5\n", + " 77\n", + " 39.3\n", + " 196\n", + " 39.3\n", " 0\n", " unknown\n", " \n", " \n", " Other Black\n", - " 63\n", - " 34.6\n", - " 182\n", - " 30.8\n", - " 3.8\n", - " 10-Jul\n", + " 56\n", + " 32.0\n", + " 175\n", + " 32\n", + " 0\n", + " unknown\n", " \n", " \n", " Other White\n", - " 84\n", - " 41.4\n", - " 203\n", - " 37.9\n", - " 3.5\n", - " 05-Jul\n", + " 56\n", + " 36.4\n", + " 154\n", + " 31.8\n", + " 4.6\n", + " 06-Jul\n", " \n", " \n", " Other mixed\n", - " 70\n", - " 37.0\n", - " 189\n", - " 37\n", + " 63\n", + " 36.0\n", + " 175\n", + " 36\n", " 0\n", " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", " 77\n", - " 39.3\n", - " 196\n", - " 35.7\n", - " 3.6\n", - " 06-Jul\n", + " 42.3\n", + " 182\n", + " 42.3\n", + " 0\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 210\n", - " 38.5\n", - " 546\n", - " 35.9\n", - " 2.6\n", - " 15-Aug\n", + " 217\n", + " 40.8\n", + " 532\n", + " 39.5\n", + " 1.3\n", + " unknown\n", " \n", " \n", " White + Asian\n", - " 84\n", - " 44.4\n", + " 77\n", + " 40.7\n", " 189\n", - " 44.4\n", - " 0\n", - " unknown\n", + " 37\n", + " 3.7\n", + " 18-Jul\n", " \n", " \n", " White + Black African\n", - " 70\n", - " 34.5\n", - " 203\n", - " 31\n", - " 3.5\n", - " 19-Jul\n", + " 77\n", + " 44.0\n", + " 175\n", + " 44\n", + " 0\n", + " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 84\n", - " 41.4\n", - " 203\n", - " 37.9\n", - " 3.5\n", - " 05-Jul\n", + " 56\n", + " 34.8\n", + " 161\n", + " 34.8\n", + " 0\n", + " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 259\n", - " 37.4\n", - " 693\n", - " 35.4\n", - " 2\n", - " unknown\n", + " 252\n", + " 40.0\n", + " 630\n", + " 37.8\n", + " 2.2\n", + " 22-Sep\n", " \n", " \n", " 2\n", - " 245\n", - " 38.0\n", - " 644\n", - " 35.9\n", + " 259\n", + " 37.8\n", + " 686\n", + " 35.7\n", " 2.1\n", - " 19-Sep\n", + " 07-Oct\n", " \n", " \n", " 3\n", - " 266\n", - " 40.9\n", - " 651\n", - " 37.6\n", - " 3.3\n", - " 12-Jul\n", + " 259\n", + " 38.1\n", + " 679\n", + " 36.1\n", + " 2\n", + " unknown\n", " \n", " \n", " 4\n", - " 287\n", - " 40.2\n", - " 714\n", - " 37.3\n", - " 2.9\n", - " 28-Jul\n", + " 259\n", + " 40.7\n", + " 637\n", + " 38.5\n", + " 2.2\n", + " 19-Sep\n", " \n", " \n", " 5 Least deprived\n", - " 280\n", - " 41.2\n", - " 679\n", - " 39.2\n", - " 2\n", - " 16-Sep\n", + " 245\n", + " 39.3\n", + " 623\n", + " 37.1\n", + " 2.2\n", + " 24-Sep\n", " \n", " \n", " Unknown\n", " 77\n", - " 40.7\n", - " 189\n", - " 40.7\n", + " 44.0\n", + " 175\n", + " 44\n", " 0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 434\n", - " 39.5\n", - " 1099\n", - " 37.6\n", - " 1.9\n", - " unknown\n", + " 427\n", + " 41.5\n", + " 1029\n", + " 38.8\n", + " 2.7\n", + " 19-Aug\n", " \n", " \n", " under 30\n", - " 973\n", - " 39.5\n", - " 2464\n", - " 37.2\n", - " 2.3\n", - " 30-Aug\n", + " 924\n", + " 38.4\n", + " 2408\n", + " 36.6\n", + " 1.8\n", + " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1393\n", - " 39.4\n", - " 3535\n", - " 37.2\n", - " 2.2\n", - " 07-Sep\n", + " 1344\n", + " 39.5\n", + " 3402\n", + " 37.4\n", + " 2.1\n", + " 01-Oct\n", " \n", " \n", " yes\n", " 14\n", - " 40.0\n", - " 35\n", - " 40\n", + " 50.0\n", + " 28\n", + " 50\n", " 0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1393\n", + " 1344\n", " 39.5\n", - " 3528\n", - " 37.3\n", - " 2.2\n", - " 06-Sep\n", + " 3402\n", + " 37.4\n", + " 2.1\n", + " 01-Oct\n", " \n", " \n", " yes\n", - " 21\n", - " 60.0\n", + " 14\n", + " 40.0\n", " 35\n", - " 60\n", - " 0\n", - " unknown\n", + " 20\n", + " 20\n", + " 03-May\n", " \n", " \n", " dialysis\n", " no\n", - " 1400\n", + " 1344\n", " 39.5\n", - " 3542\n", - " 37.4\n", - " 2.1\n", - " 14-Sep\n", + " 3402\n", + " 37.2\n", + " 2.3\n", + " 16-Sep\n", " \n", " \n", " yes\n", " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 40.0\n", + " 35\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1393\n", - " 39.5\n", - " 3528\n", - " 37.3\n", - " 2.2\n", - " 06-Sep\n", + " 1344\n", + " 39.6\n", + " 3395\n", + " 37.5\n", + " 2.1\n", + " 01-Oct\n", " \n", " \n", " yes\n", " 14\n", " 33.3\n", " 42\n", - " 33.3\n", - " 0\n", - " unknown\n", + " 16.7\n", + " 16.6\n", + " 09-May\n", " \n", " \n", " dementia\n", " no\n", - " 1400\n", - " 39.6\n", - " 3535\n", - " 37.2\n", - " 2.4\n", - " 24-Aug\n", + " 1344\n", + " 39.4\n", + " 3409\n", + " 37.4\n", + " 2\n", + " unknown\n", " \n", " \n", " yes\n", " 14\n", " 50.0\n", " 28\n", - " 50\n", - " 0\n", - " unknown\n", + " 25\n", + " 25\n", + " 27-Apr\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1400\n", + " 1351\n", " 39.6\n", - " 3535\n", + " 3409\n", " 37.4\n", " 2.2\n", - " 06-Sep\n", + " 23-Sep\n", " \n", " \n", " yes\n", - " 7\n", - " 20.0\n", - " 35\n", - " 20\n", + " 0\n", + " 0.0\n", + " 21\n", + " 0\n", " 0\n", " unknown\n", " \n", " \n", " LD\n", " no\n", - " 1379\n", - " 39.6\n", - " 3486\n", - " 37.3\n", - " 2.3\n", - " 30-Aug\n", + " 1323\n", + " 39.3\n", + " 3367\n", + " 37.2\n", + " 2.1\n", + " 02-Oct\n", " \n", " \n", " yes\n", " 35\n", - " 41.7\n", - " 84\n", - " 33.3\n", - " 8.4\n", - " 09-May\n", + " 55.6\n", + " 63\n", + " 44.4\n", + " 11.2\n", + " 07-May\n", " \n", " \n", " ssri\n", " no\n", - " 1400\n", - " 39.6\n", - " 3535\n", - " 37.4\n", - " 2.2\n", - " 06-Sep\n", + " 1337\n", + " 39.3\n", + " 3402\n", + " 37.2\n", + " 2.1\n", + " 02-Oct\n", " \n", " \n", " yes\n", @@ -2401,76 +2401,76 @@ " \n", " chemo_or_radio\n", " no\n", - " 1393\n", - " 39.6\n", - " 3521\n", + " 1344\n", + " 39.5\n", + " 3402\n", " 37.4\n", - " 2.2\n", - " 06-Sep\n", + " 2.1\n", + " 01-Oct\n", " \n", " \n", " yes\n", " 14\n", - " 28.6\n", - " 49\n", - " 28.6\n", + " 50.0\n", + " 28\n", + " 50\n", " 0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1400\n", - " 39.6\n", - " 3535\n", + " 1344\n", + " 39.5\n", + " 3402\n", " 37.4\n", - " 2.2\n", - " 06-Sep\n", + " 2.1\n", + " 01-Oct\n", " \n", " \n", " yes\n", " 14\n", - " 50.0\n", - " 28\n", - " 50\n", + " 40.0\n", + " 35\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1400\n", - " 39.6\n", - " 3535\n", - " 37.4\n", - " 2.2\n", - " 06-Sep\n", + " 1337\n", + " 39.3\n", + " 3402\n", + " 37.2\n", + " 2.1\n", + " 02-Oct\n", " \n", " \n", " yes\n", " 14\n", - " 40.0\n", - " 35\n", - " 40\n", + " 50.0\n", + " 28\n", + " 50\n", " 0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1400\n", - " 39.7\n", - " 3528\n", - " 37.5\n", - " 2.2\n", - " 06-Sep\n", + " 1337\n", + " 39.3\n", + " 3402\n", + " 37.2\n", + " 2.1\n", + " 02-Oct\n", " \n", " \n", " yes\n", " 14\n", - " 40.0\n", - " 35\n", - " 40\n", + " 50.0\n", + " 28\n", + " 50\n", " 0\n", " unknown\n", " \n", @@ -2481,387 +2481,387 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1411 \n", - "sex F 714 \n", - " M 693 \n", + "overall overall 1354 \n", + "sex F 693 \n", + " M 658 \n", "ageband_5yr 0 84 \n", - " 0-15 91 \n", - " 16-29 77 \n", + " 0-15 70 \n", + " 16-29 84 \n", " 30-34 91 \n", - " 35-39 84 \n", - " 40-44 105 \n", - " 45-49 70 \n", - " 50-54 98 \n", + " 35-39 98 \n", + " 40-44 91 \n", + " 45-49 98 \n", + " 50-54 70 \n", " 55-59 84 \n", - " 60-64 91 \n", - " 65-69 91 \n", - " 70-74 84 \n", - " 75-79 91 \n", - " 80-84 84 \n", - " 85-89 98 \n", - " 90+ 77 \n", - "ethnicity_6_groups Black 224 \n", - " Mixed 231 \n", - " Other 245 \n", - " South Asian 252 \n", - " Unknown 217 \n", - " White 245 \n", + " 60-64 77 \n", + " 65-69 84 \n", + " 70-74 91 \n", + " 75-79 84 \n", + " 80-84 77 \n", + " 85-89 84 \n", + " 90+ 91 \n", + "ethnicity_6_groups Black 231 \n", + " Mixed 217 \n", + " Other 217 \n", + " South Asian 245 \n", + " Unknown 203 \n", + " White 238 \n", "ethnicity_16_groups African 63 \n", - " Bangladeshi or British Bangladeshi 70 \n", - " Caribbean 77 \n", + " Bangladeshi or British Bangladeshi 77 \n", + " Caribbean 84 \n", " Chinese 70 \n", - " Other 77 \n", - " Other Asian 77 \n", - " British or Mixed British 91 \n", - " Indian or British Indian 84 \n", - " Irish 70 \n", - " Other Black 63 \n", - " Other White 84 \n", - " Other mixed 70 \n", + " Other 84 \n", + " Other Asian 70 \n", + " British or Mixed British 63 \n", + " Indian or British Indian 77 \n", + " Irish 77 \n", + " Other Black 56 \n", + " Other White 56 \n", + " Other mixed 63 \n", " Pakistani or British Pakistani 77 \n", - " Unknown 210 \n", - " White + Asian 84 \n", - " White + Black African 70 \n", - " White + Black Caribbean 84 \n", - "imd_categories 1 Most deprived 259 \n", - " 2 245 \n", - " 3 266 \n", - " 4 287 \n", - " 5 Least deprived 280 \n", + " Unknown 217 \n", + " White + Asian 77 \n", + " White + Black African 77 \n", + " White + Black Caribbean 56 \n", + "imd_categories 1 Most deprived 252 \n", + " 2 259 \n", + " 3 259 \n", + " 4 259 \n", + " 5 Least deprived 245 \n", " Unknown 77 \n", - "bmi 30+ 434 \n", - " under 30 973 \n", - "chronic_cardiac_disease no 1393 \n", + "bmi 30+ 427 \n", + " under 30 924 \n", + "chronic_cardiac_disease no 1344 \n", " yes 14 \n", - "current_copd no 1393 \n", - " yes 21 \n", - "dialysis no 1400 \n", + "current_copd no 1344 \n", " yes 14 \n", - "dmards no 1393 \n", + "dialysis no 1344 \n", " yes 14 \n", - "dementia no 1400 \n", + "dmards no 1344 \n", " yes 14 \n", - "psychosis_schiz_bipolar no 1400 \n", - " yes 7 \n", - "LD no 1379 \n", + "dementia no 1344 \n", + " yes 14 \n", + "psychosis_schiz_bipolar no 1351 \n", + " yes 0 \n", + "LD no 1323 \n", " yes 35 \n", - "ssri no 1400 \n", + "ssri no 1337 \n", " yes 14 \n", - "chemo_or_radio no 1393 \n", + "chemo_or_radio no 1344 \n", " yes 14 \n", - "lung_cancer no 1400 \n", + "lung_cancer no 1344 \n", " yes 14 \n", - "cancer_excl_lung_and_haem no 1400 \n", + "cancer_excl_lung_and_haem no 1337 \n", " yes 14 \n", - "haematological_cancer no 1400 \n", + "haematological_cancer no 1337 \n", " yes 14 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 39.5 3570 \n", - "sex F 40.0 1785 \n", - " M 39.0 1778 \n", + "overall overall 39.4 3437 \n", + "sex F 39.9 1736 \n", + " M 38.7 1701 \n", "ageband_5yr 0 37.5 224 \n", - " 0-15 37.1 245 \n", - " 16-29 36.7 210 \n", - " 30-34 37.1 245 \n", - " 35-39 36.4 231 \n", - " 40-44 44.1 238 \n", - " 45-49 35.7 196 \n", - " 50-54 45.2 217 \n", - " 55-59 41.4 203 \n", - " 60-64 40.6 224 \n", - " 65-69 39.4 231 \n", - " 70-74 37.5 224 \n", - " 75-79 41.9 217 \n", - " 80-84 40.0 210 \n", - " 85-89 42.4 231 \n", - " 90+ 35.5 217 \n", - "ethnicity_6_groups Black 39.0 574 \n", - " Mixed 36.3 637 \n", - " Other 40.2 609 \n", - " South Asian 40.4 623 \n", - " Unknown 39.7 546 \n", - " White 42.2 581 \n", - "ethnicity_16_groups African 34.6 182 \n", - " Bangladeshi or British Bangladeshi 41.7 168 \n", - " Caribbean 42.3 182 \n", - " Chinese 40.0 175 \n", - " Other 44.0 175 \n", - " Other Asian 40.7 189 \n", - " British or Mixed British 46.4 196 \n", - " Indian or British Indian 41.4 203 \n", - " Irish 38.5 182 \n", - " Other Black 34.6 182 \n", - " Other White 41.4 203 \n", - " Other mixed 37.0 189 \n", - " Pakistani or British Pakistani 39.3 196 \n", - " Unknown 38.5 546 \n", - " White + Asian 44.4 189 \n", - " White + Black African 34.5 203 \n", - " White + Black Caribbean 41.4 203 \n", - "imd_categories 1 Most deprived 37.4 693 \n", - " 2 38.0 644 \n", - " 3 40.9 651 \n", - " 4 40.2 714 \n", - " 5 Least deprived 41.2 679 \n", - " Unknown 40.7 189 \n", - "bmi 30+ 39.5 1099 \n", - " under 30 39.5 2464 \n", - "chronic_cardiac_disease no 39.4 3535 \n", + " 0-15 40.0 175 \n", + " 16-29 36.4 231 \n", + " 30-34 43.3 210 \n", + " 35-39 42.4 231 \n", + " 40-44 39.4 231 \n", + " 45-49 42.4 231 \n", + " 50-54 38.5 182 \n", + " 55-59 38.7 217 \n", + " 60-64 36.7 210 \n", + " 65-69 40.0 210 \n", + " 70-74 38.2 238 \n", + " 75-79 41.4 203 \n", + " 80-84 39.3 196 \n", + " 85-89 36.4 231 \n", + " 90+ 41.9 217 \n", + "ethnicity_6_groups Black 37.5 616 \n", + " Mixed 38.8 560 \n", + " Other 39.7 546 \n", + " South Asian 42.2 581 \n", + " Unknown 38.7 525 \n", + " White 39.5 602 \n", + "ethnicity_16_groups African 33.3 189 \n", + " Bangladeshi or British Bangladeshi 37.9 203 \n", + " Caribbean 44.4 189 \n", + " Chinese 37.0 189 \n", + " Other 44.4 189 \n", + " Other Asian 40.0 175 \n", + " British or Mixed British 36.0 175 \n", + " Indian or British Indian 44.0 175 \n", + " Irish 39.3 196 \n", + " Other Black 32.0 175 \n", + " Other White 36.4 154 \n", + " Other mixed 36.0 175 \n", + " Pakistani or British Pakistani 42.3 182 \n", + " Unknown 40.8 532 \n", + " White + Asian 40.7 189 \n", + " White + Black African 44.0 175 \n", + " White + Black Caribbean 34.8 161 \n", + "imd_categories 1 Most deprived 40.0 630 \n", + " 2 37.8 686 \n", + " 3 38.1 679 \n", + " 4 40.7 637 \n", + " 5 Least deprived 39.3 623 \n", + " Unknown 44.0 175 \n", + "bmi 30+ 41.5 1029 \n", + " under 30 38.4 2408 \n", + "chronic_cardiac_disease no 39.5 3402 \n", + " yes 50.0 28 \n", + "current_copd no 39.5 3402 \n", " yes 40.0 35 \n", - "current_copd no 39.5 3528 \n", - " yes 60.0 35 \n", - "dialysis no 39.5 3542 \n", - " yes 66.7 21 \n", - "dmards no 39.5 3528 \n", + "dialysis no 39.5 3402 \n", + " yes 40.0 35 \n", + "dmards no 39.6 3395 \n", " yes 33.3 42 \n", - "dementia no 39.6 3535 \n", + "dementia no 39.4 3409 \n", " yes 50.0 28 \n", - "psychosis_schiz_bipolar no 39.6 3535 \n", - " yes 20.0 35 \n", - "LD no 39.6 3486 \n", - " yes 41.7 84 \n", - "ssri no 39.6 3535 \n", + "psychosis_schiz_bipolar no 39.6 3409 \n", + " yes 0.0 21 \n", + "LD no 39.3 3367 \n", + " yes 55.6 63 \n", + "ssri no 39.3 3402 \n", " yes 40.0 35 \n", - "chemo_or_radio no 39.6 3521 \n", - " yes 28.6 49 \n", - "lung_cancer no 39.6 3535 \n", + "chemo_or_radio no 39.5 3402 \n", " yes 50.0 28 \n", - "cancer_excl_lung_and_haem no 39.6 3535 \n", - " yes 40.0 35 \n", - "haematological_cancer no 39.7 3528 \n", + "lung_cancer no 39.5 3402 \n", " yes 40.0 35 \n", + "cancer_excl_lung_and_haem no 39.3 3402 \n", + " yes 50.0 28 \n", + "haematological_cancer no 39.3 3402 \n", + " yes 50.0 28 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", "overall overall 37.3 \n", - "sex F 37.6 \n", - " M 37 \n", - "ageband_5yr 0 34.4 \n", - " 0-15 37.1 \n", + "sex F 37.9 \n", + " M 36.6 \n", + "ageband_5yr 0 37.5 \n", + " 0-15 40 \n", " 16-29 33.3 \n", - " 30-34 37.1 \n", - " 35-39 33.3 \n", - " 40-44 44.1 \n", - " 45-49 32.1 \n", - " 50-54 41.9 \n", - " 55-59 41.4 \n", - " 60-64 40.6 \n", - " 65-69 39.4 \n", - " 70-74 34.4 \n", - " 75-79 38.7 \n", - " 80-84 36.7 \n", - " 85-89 39.4 \n", - " 90+ 35.5 \n", - "ethnicity_6_groups Black 37.8 \n", - " Mixed 34.1 \n", - " Other 39.1 \n", - " South Asian 37.1 \n", - " Unknown 38.5 \n", - " White 38.6 \n", - "ethnicity_16_groups African 34.6 \n", - " Bangladeshi or British Bangladeshi 37.5 \n", - " Caribbean 38.5 \n", - " Chinese 36 \n", - " Other 40 \n", - " Other Asian 37 \n", - " British or Mixed British 42.9 \n", - " Indian or British Indian 41.4 \n", - " Irish 38.5 \n", - " Other Black 30.8 \n", - " Other White 37.9 \n", - " Other mixed 37 \n", - " Pakistani or British Pakistani 35.7 \n", - " Unknown 35.9 \n", - " White + Asian 44.4 \n", - " White + Black African 31 \n", - " White + Black Caribbean 37.9 \n", - "imd_categories 1 Most deprived 35.4 \n", - " 2 35.9 \n", - " 3 37.6 \n", - " 4 37.3 \n", - " 5 Least deprived 39.2 \n", - " Unknown 40.7 \n", - "bmi 30+ 37.6 \n", - " under 30 37.2 \n", - "chronic_cardiac_disease no 37.2 \n", - " yes 40 \n", - "current_copd no 37.3 \n", - " yes 60 \n", - "dialysis no 37.4 \n", - " yes 66.7 \n", - "dmards no 37.3 \n", - " yes 33.3 \n", - "dementia no 37.2 \n", + " 30-34 40 \n", + " 35-39 39.4 \n", + " 40-44 39.4 \n", + " 45-49 39.4 \n", + " 50-54 38.5 \n", + " 55-59 35.5 \n", + " 60-64 36.7 \n", + " 65-69 36.7 \n", + " 70-74 35.3 \n", + " 75-79 37.9 \n", + " 80-84 39.3 \n", + " 85-89 33.3 \n", + " 90+ 38.7 \n", + "ethnicity_6_groups Black 35.2 \n", + " Mixed 37.5 \n", + " Other 38.5 \n", + " South Asian 39.8 \n", + " Unknown 36 \n", + " White 37.2 \n", + "ethnicity_16_groups African 33.3 \n", + " Bangladeshi or British Bangladeshi 34.5 \n", + " Caribbean 40.7 \n", + " Chinese 33.3 \n", + " Other 40.7 \n", + " Other Asian 40 \n", + " British or Mixed British 32 \n", + " Indian or British Indian 40 \n", + " Irish 39.3 \n", + " Other Black 32 \n", + " Other White 31.8 \n", + " Other mixed 36 \n", + " Pakistani or British Pakistani 42.3 \n", + " Unknown 39.5 \n", + " White + Asian 37 \n", + " White + Black African 44 \n", + " White + Black Caribbean 34.8 \n", + "imd_categories 1 Most deprived 37.8 \n", + " 2 35.7 \n", + " 3 36.1 \n", + " 4 38.5 \n", + " 5 Least deprived 37.1 \n", + " Unknown 44 \n", + "bmi 30+ 38.8 \n", + " under 30 36.6 \n", + "chronic_cardiac_disease no 37.4 \n", " yes 50 \n", - "psychosis_schiz_bipolar no 37.4 \n", + "current_copd no 37.4 \n", " yes 20 \n", - "LD no 37.3 \n", - " yes 33.3 \n", - "ssri no 37.4 \n", + "dialysis no 37.2 \n", + " yes 40 \n", + "dmards no 37.5 \n", + " yes 16.7 \n", + "dementia no 37.4 \n", + " yes 25 \n", + "psychosis_schiz_bipolar no 37.4 \n", + " yes 0 \n", + "LD no 37.2 \n", + " yes 44.4 \n", + "ssri no 37.2 \n", " yes 40 \n", "chemo_or_radio no 37.4 \n", - " yes 28.6 \n", - "lung_cancer no 37.4 \n", " yes 50 \n", - "cancer_excl_lung_and_haem no 37.4 \n", - " yes 40 \n", - "haematological_cancer no 37.5 \n", + "lung_cancer no 37.4 \n", " yes 40 \n", + "cancer_excl_lung_and_haem no 37.2 \n", + " yes 50 \n", + "haematological_cancer no 37.2 \n", + " yes 50 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 2.2 \n", - "sex F 2.4 \n", - " M 2 \n", - "ageband_5yr 0 3.1 \n", + "overall overall 2.1 \n", + "sex F 2 \n", + " M 2.1 \n", + "ageband_5yr 0 0 \n", " 0-15 0 \n", - " 16-29 3.4 \n", - " 30-34 0 \n", - " 35-39 3.1 \n", + " 16-29 3.1 \n", + " 30-34 3.3 \n", + " 35-39 3 \n", " 40-44 0 \n", - " 45-49 3.6 \n", - " 50-54 3.3 \n", - " 55-59 0 \n", + " 45-49 3 \n", + " 50-54 0 \n", + " 55-59 3.2 \n", " 60-64 0 \n", - " 65-69 0 \n", - " 70-74 3.1 \n", - " 75-79 3.2 \n", - " 80-84 3.3 \n", - " 85-89 3 \n", - " 90+ 0 \n", - "ethnicity_6_groups Black 1.2 \n", - " Mixed 2.2 \n", - " Other 1.1 \n", - " South Asian 3.3 \n", - " Unknown 1.2 \n", - " White 3.6 \n", + " 65-69 3.3 \n", + " 70-74 2.9 \n", + " 75-79 3.5 \n", + " 80-84 0 \n", + " 85-89 3.1 \n", + " 90+ 3.2 \n", + "ethnicity_6_groups Black 2.3 \n", + " Mixed 1.3 \n", + " Other 1.2 \n", + " South Asian 2.4 \n", + " Unknown 2.7 \n", + " White 2.3 \n", "ethnicity_16_groups African 0 \n", - " Bangladeshi or British Bangladeshi 4.2 \n", - " Caribbean 3.8 \n", - " Chinese 4 \n", - " Other 4 \n", - " Other Asian 3.7 \n", - " British or Mixed British 3.5 \n", - " Indian or British Indian 0 \n", + " Bangladeshi or British Bangladeshi 3.4 \n", + " Caribbean 3.7 \n", + " Chinese 3.7 \n", + " Other 3.7 \n", + " Other Asian 0 \n", + " British or Mixed British 4 \n", + " Indian or British Indian 4 \n", " Irish 0 \n", - " Other Black 3.8 \n", - " Other White 3.5 \n", + " Other Black 0 \n", + " Other White 4.6 \n", " Other mixed 0 \n", - " Pakistani or British Pakistani 3.6 \n", - " Unknown 2.6 \n", - " White + Asian 0 \n", - " White + Black African 3.5 \n", - " White + Black Caribbean 3.5 \n", - "imd_categories 1 Most deprived 2 \n", + " Pakistani or British Pakistani 0 \n", + " Unknown 1.3 \n", + " White + Asian 3.7 \n", + " White + Black African 0 \n", + " White + Black Caribbean 0 \n", + "imd_categories 1 Most deprived 2.2 \n", " 2 2.1 \n", - " 3 3.3 \n", - " 4 2.9 \n", - " 5 Least deprived 2 \n", + " 3 2 \n", + " 4 2.2 \n", + " 5 Least deprived 2.2 \n", " Unknown 0 \n", - "bmi 30+ 1.9 \n", - " under 30 2.3 \n", - "chronic_cardiac_disease no 2.2 \n", - " yes 0 \n", - "current_copd no 2.2 \n", - " yes 0 \n", - "dialysis no 2.1 \n", - " yes 0 \n", - "dmards no 2.2 \n", + "bmi 30+ 2.7 \n", + " under 30 1.8 \n", + "chronic_cardiac_disease no 2.1 \n", " yes 0 \n", - "dementia no 2.4 \n", + "current_copd no 2.1 \n", + " yes 20 \n", + "dialysis no 2.3 \n", " yes 0 \n", + "dmards no 2.1 \n", + " yes 16.6 \n", + "dementia no 2 \n", + " yes 25 \n", "psychosis_schiz_bipolar no 2.2 \n", " yes 0 \n", - "LD no 2.3 \n", - " yes 8.4 \n", - "ssri no 2.2 \n", + "LD no 2.1 \n", + " yes 11.2 \n", + "ssri no 2.1 \n", " yes 0 \n", - "chemo_or_radio no 2.2 \n", + "chemo_or_radio no 2.1 \n", " yes 0 \n", - "lung_cancer no 2.2 \n", + "lung_cancer no 2.1 \n", " yes 0 \n", - "cancer_excl_lung_and_haem no 2.2 \n", + "cancer_excl_lung_and_haem no 2.1 \n", " yes 0 \n", - "haematological_cancer no 2.2 \n", + "haematological_cancer no 2.1 \n", " yes 0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 06-Sep \n", - "sex F 22-Aug \n", - " M unknown \n", - "ageband_5yr 0 26-Jul \n", + "overall overall 01-Oct \n", + "sex F unknown \n", + " M 04-Oct \n", + "ageband_5yr 0 unknown \n", " 0-15 unknown \n", - " 16-29 17-Jul \n", - " 30-34 unknown \n", - " 35-39 29-Jul \n", + " 16-29 15-Aug \n", + " 30-34 24-Jul \n", + " 35-39 05-Aug \n", " 40-44 unknown \n", - " 45-49 13-Jul \n", - " 50-54 03-Jul \n", - " 55-59 unknown \n", + " 45-49 05-Aug \n", + " 50-54 unknown \n", + " 55-59 06-Aug \n", " 60-64 unknown \n", - " 65-69 unknown \n", - " 70-74 26-Jul \n", - " 75-79 13-Jul \n", - " 80-84 14-Jul \n", - " 85-89 19-Jul \n", - " 90+ unknown \n", - "ethnicity_6_groups Black unknown \n", - " Mixed 16-Sep \n", + " 65-69 31-Jul \n", + " 70-74 19-Aug \n", + " 75-79 22-Jul \n", + " 80-84 unknown \n", + " 85-89 15-Aug \n", + " 90+ 30-Jul \n", + "ethnicity_6_groups Black 22-Sep \n", + " Mixed unknown \n", " Other unknown \n", - " South Asian 13-Jul \n", - " Unknown unknown \n", - " White 30-Jun \n", + " South Asian 02-Sep \n", + " Unknown 27-Aug \n", + " White 16-Sep \n", "ethnicity_16_groups African unknown \n", - " Bangladeshi or British Bangladeshi 18-Jun \n", - " Caribbean 25-Jun \n", - " Chinese 25-Jun \n", - " Other 18-Jun \n", - " Other Asian 01-Jul \n", - " British or Mixed British 25-Jun \n", - " Indian or British Indian unknown \n", + " Bangladeshi or British Bangladeshi 01-Aug \n", + " Caribbean 11-Jul \n", + " Chinese 25-Jul \n", + " Other 11-Jul \n", + " Other Asian unknown \n", + " British or Mixed British 19-Jul \n", + " Indian or British Indian 05-Jul \n", " Irish unknown \n", - " Other Black 10-Jul \n", - " Other White 05-Jul \n", + " Other Black unknown \n", + " Other White 06-Jul \n", " Other mixed unknown \n", - " Pakistani or British Pakistani 06-Jul \n", - " Unknown 15-Aug \n", - " White + Asian unknown \n", - " White + Black African 19-Jul \n", - " White + Black Caribbean 05-Jul \n", - "imd_categories 1 Most deprived unknown \n", - " 2 19-Sep \n", - " 3 12-Jul \n", - " 4 28-Jul \n", - " 5 Least deprived 16-Sep \n", + " Pakistani or British Pakistani unknown \n", " Unknown unknown \n", - "bmi 30+ unknown \n", - " under 30 30-Aug \n", - "chronic_cardiac_disease no 07-Sep \n", - " yes unknown \n", - "current_copd no 06-Sep \n", - " yes unknown \n", - "dialysis no 14-Sep \n", - " yes unknown \n", - "dmards no 06-Sep \n", - " yes unknown \n", - "dementia no 24-Aug \n", + " White + Asian 18-Jul \n", + " White + Black African unknown \n", + " White + Black Caribbean unknown \n", + "imd_categories 1 Most deprived 22-Sep \n", + " 2 07-Oct \n", + " 3 unknown \n", + " 4 19-Sep \n", + " 5 Least deprived 24-Sep \n", + " Unknown unknown \n", + "bmi 30+ 19-Aug \n", + " under 30 unknown \n", + "chronic_cardiac_disease no 01-Oct \n", " yes unknown \n", - "psychosis_schiz_bipolar no 06-Sep \n", + "current_copd no 01-Oct \n", + " yes 03-May \n", + "dialysis no 16-Sep \n", " yes unknown \n", - "LD no 30-Aug \n", + "dmards no 01-Oct \n", " yes 09-May \n", - "ssri no 06-Sep \n", + "dementia no unknown \n", + " yes 27-Apr \n", + "psychosis_schiz_bipolar no 23-Sep \n", + " yes unknown \n", + "LD no 02-Oct \n", + " yes 07-May \n", + "ssri no 02-Oct \n", " yes unknown \n", - "chemo_or_radio no 06-Sep \n", + "chemo_or_radio no 01-Oct \n", " yes unknown \n", - "lung_cancer no 06-Sep \n", + "lung_cancer no 01-Oct \n", " yes unknown \n", - "cancer_excl_lung_and_haem no 06-Sep \n", + "cancer_excl_lung_and_haem no 02-Oct \n", " yes unknown \n", - "haematological_cancer no 06-Sep \n", + "haematological_cancer no 02-Oct \n", " yes unknown " ] }, @@ -2883,7 +2883,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout among **care home** population up to 30 Mar 2021" + "## COVID vaccination rollout among **care home** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -2949,95 +2949,95 @@ " \n", " overall\n", " overall\n", - " 549\n", + " 555\n", " 40.0\n", - " 1372\n", - " 37.8\n", - " 2.2\n", - " 05-Sep\n", + " 1386\n", + " 38.3\n", + " 1.7\n", + " unknown\n", " \n", " \n", " sex\n", " F\n", - " 266\n", - " 37.6\n", - " 707\n", - " 35.6\n", + " 280\n", + " 38.5\n", + " 728\n", + " 36.5\n", " 2\n", " unknown\n", " \n", " \n", " M\n", " 280\n", - " 42.1\n", - " 665\n", - " 40\n", - " 2.1\n", - " 05-Sep\n", + " 42.6\n", + " 658\n", + " 40.4\n", + " 2.2\n", + " 13-Sep\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 42\n", - " 46.2\n", - " 91\n", - " 46.2\n", - " 0\n", - " unknown\n", + " 56\n", + " 50.0\n", + " 112\n", + " 43.8\n", + " 6.2\n", + " 31-May\n", " \n", " \n", " 0-15\n", - " 28\n", - " 36.4\n", + " 35\n", + " 45.5\n", " 77\n", - " 36.4\n", + " 45.5\n", " 0\n", " unknown\n", " \n", " \n", " 16-29\n", - " 42\n", - " 50.0\n", - " 84\n", - " 41.7\n", - " 8.3\n", - " 02-May\n", + " 35\n", + " 38.5\n", + " 91\n", + " 38.5\n", + " 0\n", + " unknown\n", " \n", " \n", " 30-34\n", - " 28\n", - " 36.4\n", - " 77\n", - " 36.4\n", + " 35\n", + " 41.7\n", + " 84\n", + " 41.7\n", " 0\n", " unknown\n", " \n", " \n", " 35-39\n", - " 42\n", - " 42.9\n", + " 35\n", + " 35.7\n", " 98\n", - " 42.9\n", + " 35.7\n", " 0\n", " unknown\n", " \n", " \n", " 40-44\n", - " 21\n", - " 27.3\n", - " 77\n", - " 27.3\n", + " 35\n", + " 41.7\n", + " 84\n", + " 41.7\n", " 0\n", " unknown\n", " \n", " \n", " 45-49\n", " 35\n", - " 41.7\n", - " 84\n", - " 33.3\n", - " 8.4\n", - " 09-May\n", + " 38.5\n", + " 91\n", + " 30.8\n", + " 7.7\n", + " 01-Jun\n", " \n", " \n", " 50-54\n", @@ -3050,39 +3050,39 @@ " \n", " \n", " 55-59\n", - " 42\n", - " 46.2\n", - " 91\n", - " 46.2\n", + " 21\n", + " 33.3\n", + " 63\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " 60-64\n", - " 49\n", - " 50.0\n", - " 98\n", - " 50\n", + " 28\n", + " 33.3\n", + " 84\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " 65-69\n", - " 21\n", - " 25.0\n", - " 84\n", - " 25\n", + " 35\n", + " 38.5\n", + " 91\n", + " 38.5\n", " 0\n", " unknown\n", " \n", " \n", " 70-74\n", - " 28\n", - " 30.8\n", - " 91\n", - " 23.1\n", - " 7.7\n", - " 22-May\n", + " 35\n", + " 41.7\n", + " 84\n", + " 41.7\n", + " 0\n", + " unknown\n", " \n", " \n", " 75-79\n", @@ -3091,108 +3091,108 @@ " 91\n", " 38.5\n", " 7.7\n", - " 08-May\n", + " 25-May\n", " \n", " \n", " 80-84\n", - " 35\n", - " 41.7\n", + " 28\n", + " 33.3\n", " 84\n", - " 41.7\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " 85-89\n", - " 21\n", - " 27.3\n", + " 35\n", + " 45.5\n", " 77\n", - " 27.3\n", + " 45.5\n", " 0\n", " unknown\n", " \n", " \n", " 90+\n", " 35\n", - " 41.7\n", - " 84\n", - " 41.7\n", + " 45.5\n", + " 77\n", + " 45.5\n", " 0\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 91\n", - " 38.2\n", - " 238\n", - " 35.3\n", - " 2.9\n", - " 02-Aug\n", + " 84\n", + " 34.3\n", + " 245\n", + " 34.3\n", + " 0\n", + " unknown\n", " \n", " \n", " Mixed\n", " 98\n", - " 38.9\n", - " 252\n", - " 36.1\n", - " 2.8\n", - " 04-Aug\n", + " 41.2\n", + " 238\n", + " 38.2\n", + " 3\n", + " 07-Aug\n", " \n", " \n", " Other\n", - " 84\n", - " 38.7\n", - " 217\n", - " 38.7\n", + " 91\n", + " 39.4\n", + " 231\n", + " 39.4\n", " 0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 91\n", - " 40.6\n", + " 98\n", + " 43.8\n", " 224\n", - " 37.5\n", - " 3.1\n", - " 19-Jul\n", + " 40.6\n", + " 3.2\n", + " 26-Jul\n", " \n", " \n", " Unknown\n", " 84\n", " 40.0\n", " 210\n", - " 36.7\n", - " 3.3\n", - " 14-Jul\n", + " 40\n", + " 0\n", + " unknown\n", " \n", " \n", " White\n", - " 98\n", - " 42.4\n", - " 231\n", - " 39.4\n", - " 3\n", - " 19-Jul\n", + " 91\n", + " 38.2\n", + " 238\n", + " 38.2\n", + " 0\n", + " unknown\n", " \n", " \n", " dementia\n", " no\n", - " 539\n", - " 39.9\n", - " 1351\n", - " 37.8\n", - " 2.1\n", - " 13-Sep\n", + " 553\n", + " 40.5\n", + " 1365\n", + " 38.5\n", + " 2\n", + " 06-Oct\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", " 0\n", - " 33.3\n", - " 10-Apr\n", + " 0.0\n", + " 14\n", + " 0\n", + " 0\n", + " unknown\n", " \n", " \n", "\n", @@ -3201,123 +3201,123 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 549 40.0 1372 \n", - "sex F 266 37.6 707 \n", - " M 280 42.1 665 \n", - "ageband_5yr 0 42 46.2 91 \n", - " 0-15 28 36.4 77 \n", - " 16-29 42 50.0 84 \n", - " 30-34 28 36.4 77 \n", - " 35-39 42 42.9 98 \n", - " 40-44 21 27.3 77 \n", - " 45-49 35 41.7 84 \n", + "overall overall 555 40.0 1386 \n", + "sex F 280 38.5 728 \n", + " M 280 42.6 658 \n", + "ageband_5yr 0 56 50.0 112 \n", + " 0-15 35 45.5 77 \n", + " 16-29 35 38.5 91 \n", + " 30-34 35 41.7 84 \n", + " 35-39 35 35.7 98 \n", + " 40-44 35 41.7 84 \n", + " 45-49 35 38.5 91 \n", " 50-54 35 41.7 84 \n", - " 55-59 42 46.2 91 \n", - " 60-64 49 50.0 98 \n", - " 65-69 21 25.0 84 \n", - " 70-74 28 30.8 91 \n", + " 55-59 21 33.3 63 \n", + " 60-64 28 33.3 84 \n", + " 65-69 35 38.5 91 \n", + " 70-74 35 41.7 84 \n", " 75-79 42 46.2 91 \n", - " 80-84 35 41.7 84 \n", - " 85-89 21 27.3 77 \n", - " 90+ 35 41.7 84 \n", - "ethnicity_6_groups Black 91 38.2 238 \n", - " Mixed 98 38.9 252 \n", - " Other 84 38.7 217 \n", - " South Asian 91 40.6 224 \n", + " 80-84 28 33.3 84 \n", + " 85-89 35 45.5 77 \n", + " 90+ 35 45.5 77 \n", + "ethnicity_6_groups Black 84 34.3 245 \n", + " Mixed 98 41.2 238 \n", + " Other 91 39.4 231 \n", + " South Asian 98 43.8 224 \n", " Unknown 84 40.0 210 \n", - " White 98 42.4 231 \n", - "dementia no 539 39.9 1351 \n", - " yes 7 33.3 21 \n", + " White 91 38.2 238 \n", + "dementia no 553 40.5 1365 \n", + " yes 0 0.0 14 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 37.8 \n", - "sex F 35.6 \n", - " M 40 \n", - "ageband_5yr 0 46.2 \n", - " 0-15 36.4 \n", - " 16-29 41.7 \n", - " 30-34 36.4 \n", - " 35-39 42.9 \n", - " 40-44 27.3 \n", - " 45-49 33.3 \n", + "overall overall 38.3 \n", + "sex F 36.5 \n", + " M 40.4 \n", + "ageband_5yr 0 43.8 \n", + " 0-15 45.5 \n", + " 16-29 38.5 \n", + " 30-34 41.7 \n", + " 35-39 35.7 \n", + " 40-44 41.7 \n", + " 45-49 30.8 \n", " 50-54 41.7 \n", - " 55-59 46.2 \n", - " 60-64 50 \n", - " 65-69 25 \n", - " 70-74 23.1 \n", + " 55-59 33.3 \n", + " 60-64 33.3 \n", + " 65-69 38.5 \n", + " 70-74 41.7 \n", " 75-79 38.5 \n", - " 80-84 41.7 \n", - " 85-89 27.3 \n", - " 90+ 41.7 \n", - "ethnicity_6_groups Black 35.3 \n", - " Mixed 36.1 \n", - " Other 38.7 \n", - " South Asian 37.5 \n", - " Unknown 36.7 \n", - " White 39.4 \n", - "dementia no 37.8 \n", + " 80-84 33.3 \n", + " 85-89 45.5 \n", + " 90+ 45.5 \n", + "ethnicity_6_groups Black 34.3 \n", + " Mixed 38.2 \n", + " Other 39.4 \n", + " South Asian 40.6 \n", + " Unknown 40 \n", + " White 38.2 \n", + "dementia no 38.5 \n", " yes 0 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 2.2 \n", + "overall overall 1.7 \n", "sex F 2 \n", - " M 2.1 \n", - "ageband_5yr 0 0 \n", + " M 2.2 \n", + "ageband_5yr 0 6.2 \n", " 0-15 0 \n", - " 16-29 8.3 \n", + " 16-29 0 \n", " 30-34 0 \n", " 35-39 0 \n", " 40-44 0 \n", - " 45-49 8.4 \n", + " 45-49 7.7 \n", " 50-54 0 \n", " 55-59 0 \n", " 60-64 0 \n", " 65-69 0 \n", - " 70-74 7.7 \n", + " 70-74 0 \n", " 75-79 7.7 \n", " 80-84 0 \n", " 85-89 0 \n", " 90+ 0 \n", - "ethnicity_6_groups Black 2.9 \n", - " Mixed 2.8 \n", + "ethnicity_6_groups Black 0 \n", + " Mixed 3 \n", " Other 0 \n", - " South Asian 3.1 \n", - " Unknown 3.3 \n", - " White 3 \n", - "dementia no 2.1 \n", - " yes 33.3 \n", + " South Asian 3.2 \n", + " Unknown 0 \n", + " White 0 \n", + "dementia no 2 \n", + " yes 0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 05-Sep \n", + "overall overall unknown \n", "sex F unknown \n", - " M 05-Sep \n", - "ageband_5yr 0 unknown \n", + " M 13-Sep \n", + "ageband_5yr 0 31-May \n", " 0-15 unknown \n", - " 16-29 02-May \n", + " 16-29 unknown \n", " 30-34 unknown \n", " 35-39 unknown \n", " 40-44 unknown \n", - " 45-49 09-May \n", + " 45-49 01-Jun \n", " 50-54 unknown \n", " 55-59 unknown \n", " 60-64 unknown \n", " 65-69 unknown \n", - " 70-74 22-May \n", - " 75-79 08-May \n", + " 70-74 unknown \n", + " 75-79 25-May \n", " 80-84 unknown \n", " 85-89 unknown \n", " 90+ unknown \n", - "ethnicity_6_groups Black 02-Aug \n", - " Mixed 04-Aug \n", + "ethnicity_6_groups Black unknown \n", + " Mixed 07-Aug \n", " Other unknown \n", - " South Asian 19-Jul \n", - " Unknown 14-Jul \n", - " White 19-Jul \n", - "dementia no 13-Sep \n", - " yes 10-Apr " + " South Asian 26-Jul \n", + " Unknown unknown \n", + " White unknown \n", + "dementia no 06-Oct \n", + " yes unknown " ] }, "metadata": {}, @@ -3338,7 +3338,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout among **shielding (aged 16-69)** population up to 30 Mar 2021" + "## COVID vaccination rollout among **shielding (aged 16-69)** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -3404,22 +3404,22 @@ " \n", " overall\n", " overall\n", - " 153\n", - " 37.0\n", - " 413\n", - " 35.4\n", - " 1.6\n", - " unknown\n", + " 180\n", + " 41.5\n", + " 434\n", + " 38.2\n", + " 3.3\n", + " 27-Jul\n", " \n", " \n", - " newly_shielded_since_feb_15\n", - " no\n", - " 154\n", - " 37.9\n", - " 406\n", - " 36.2\n", - " 1.7\n", - " unknown\n", + " newly_shielded_since_feb_15\n", + " no\n", + " 175\n", + " 41.0\n", + " 427\n", + " 37.7\n", + " 3.3\n", + " 28-Jul\n", " \n", " \n", " yes\n", @@ -3433,44 +3433,35 @@ " \n", " sex\n", " F\n", - " 77\n", - " 36.7\n", - " 210\n", - " 33.3\n", - " 3.4\n", - " 17-Jul\n", + " 98\n", + " 45.2\n", + " 217\n", + " 41.9\n", + " 3.3\n", + " 20-Jul\n", " \n", " \n", " M\n", - " 77\n", - " 37.9\n", - " 203\n", - " 34.5\n", - " 3.4\n", - " 15-Jul\n", + " 84\n", + " 38.7\n", + " 217\n", + " 35.5\n", + " 3.2\n", + " 06-Aug\n", " \n", " \n", " ageband\n", " 16-29\n", - " 21\n", - " 37.5\n", - " 56\n", - " 37.5\n", + " 14\n", + " 28.6\n", + " 49\n", + " 28.6\n", " 0\n", " unknown\n", " \n", " \n", " 30-39\n", " 21\n", - " 50.0\n", - " 42\n", - " 50\n", - " 0\n", - " unknown\n", - " \n", - " \n", - " 40-49\n", - " 21\n", " 37.5\n", " 56\n", " 37.5\n", @@ -3478,31 +3469,40 @@ " unknown\n", " \n", " \n", + " 40-49\n", + " 28\n", + " 57.1\n", + " 49\n", + " 42.9\n", + " 14.2\n", + " 02-May\n", + " \n", + " \n", " 50-59\n", - " 14\n", - " 28.6\n", + " 28\n", + " 57.1\n", " 49\n", - " 28.6\n", + " 57.1\n", " 0\n", " unknown\n", " \n", " \n", " 60-69\n", " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", + " 33.3\n", + " 63\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " 70-79\n", - " 35\n", - " 35.7\n", - " 98\n", - " 35.7\n", - " 0\n", - " unknown\n", + " 42\n", + " 35.3\n", + " 119\n", + " 29.4\n", + " 5.9\n", + " 19-Jun\n", " \n", " \n", " 80+\n", @@ -3516,120 +3516,120 @@ " \n", " ethnicity_6_groups\n", " Black\n", - " 21\n", - " 33.3\n", - " 63\n", - " 33.3\n", - " 0\n", - " unknown\n", + " 28\n", + " 40.0\n", + " 70\n", + " 30\n", + " 10\n", + " 21-May\n", " \n", " \n", " Mixed\n", " 35\n", " 45.5\n", " 77\n", - " 45.5\n", - " 0\n", - " unknown\n", + " 36.4\n", + " 9.1\n", + " 20-May\n", " \n", " \n", " Other\n", - " 28\n", - " 36.4\n", + " 35\n", + " 45.5\n", " 77\n", - " 36.4\n", + " 45.5\n", " 0\n", " unknown\n", " \n", " \n", " South Asian\n", - " 28\n", - " 44.4\n", + " 21\n", + " 33.3\n", " 63\n", - " 44.4\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 21\n", - " 33.3\n", - " 63\n", - " 33.3\n", + " 28\n", + " 40.0\n", + " 70\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " White\n", - " 21\n", - " 33.3\n", - " 63\n", - " 33.3\n", - " 0\n", - " unknown\n", + " 35\n", + " 50.0\n", + " 70\n", + " 40\n", + " 10\n", + " 14-May\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 28\n", - " 40.0\n", - " 70\n", - " 40\n", + " 42\n", + " 42.9\n", + " 98\n", + " 42.9\n", " 0\n", " unknown\n", " \n", " \n", " 2\n", - " 28\n", - " 30.8\n", + " 42\n", + " 46.2\n", " 91\n", - " 30.8\n", - " 0\n", - " unknown\n", + " 38.5\n", + " 7.7\n", + " 25-May\n", " \n", " \n", " 3\n", " 28\n", - " 33.3\n", - " 84\n", - " 33.3\n", + " 36.4\n", + " 77\n", + " 36.4\n", " 0\n", " unknown\n", " \n", " \n", " 4\n", - " 35\n", - " 41.7\n", - " 84\n", - " 33.3\n", - " 8.4\n", - " 09-May\n", + " 28\n", + " 40.0\n", + " 70\n", + " 30\n", + " 10\n", + " 21-May\n", " \n", " \n", " 5 Least deprived\n", " 28\n", - " 44.4\n", - " 63\n", - " 44.4\n", + " 40.0\n", + " 70\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", - " 0\n", - " unknown\n", + " 14\n", + " 50.0\n", + " 28\n", + " 25\n", + " 25\n", + " 27-Apr\n", " \n", " \n", " LD\n", " no\n", - " 147\n", - " 36.2\n", - " 406\n", - " 34.5\n", + " 175\n", + " 41.7\n", + " 420\n", + " 40\n", " 1.7\n", " unknown\n", " \n", @@ -3637,7 +3637,7 @@ " yes\n", " 0\n", " 0.0\n", - " 7\n", + " 14\n", " 0\n", " 0\n", " unknown\n", @@ -3649,117 +3649,117 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 153 37.0 413 \n", - "newly_shielded_since_feb_15 no 154 37.9 406 \n", + "overall overall 180 41.5 434 \n", + "newly_shielded_since_feb_15 no 175 41.0 427 \n", " yes 0 NaN 0 \n", - "sex F 77 36.7 210 \n", - " M 77 37.9 203 \n", - "ageband 16-29 21 37.5 56 \n", - " 30-39 21 50.0 42 \n", - " 40-49 21 37.5 56 \n", - " 50-59 14 28.6 49 \n", - " 60-69 21 42.9 49 \n", - " 70-79 35 35.7 98 \n", + "sex F 98 45.2 217 \n", + " M 84 38.7 217 \n", + "ageband 16-29 14 28.6 49 \n", + " 30-39 21 37.5 56 \n", + " 40-49 28 57.1 49 \n", + " 50-59 28 57.1 49 \n", + " 60-69 21 33.3 63 \n", + " 70-79 42 35.3 119 \n", " 80+ 21 37.5 56 \n", - "ethnicity_6_groups Black 21 33.3 63 \n", + "ethnicity_6_groups Black 28 40.0 70 \n", " Mixed 35 45.5 77 \n", - " Other 28 36.4 77 \n", - " South Asian 28 44.4 63 \n", - " Unknown 21 33.3 63 \n", - " White 21 33.3 63 \n", - "imd_categories 1 Most deprived 28 40.0 70 \n", - " 2 28 30.8 91 \n", - " 3 28 33.3 84 \n", - " 4 35 41.7 84 \n", - " 5 Least deprived 28 44.4 63 \n", - " Unknown 7 33.3 21 \n", - "LD no 147 36.2 406 \n", - " yes 0 0.0 7 \n", + " Other 35 45.5 77 \n", + " South Asian 21 33.3 63 \n", + " Unknown 28 40.0 70 \n", + " White 35 50.0 70 \n", + "imd_categories 1 Most deprived 42 42.9 98 \n", + " 2 42 46.2 91 \n", + " 3 28 36.4 77 \n", + " 4 28 40.0 70 \n", + " 5 Least deprived 28 40.0 70 \n", + " Unknown 14 50.0 28 \n", + "LD no 175 41.7 420 \n", + " yes 0 0.0 14 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 35.4 \n", - "newly_shielded_since_feb_15 no 36.2 \n", + "overall overall 38.2 \n", + "newly_shielded_since_feb_15 no 37.7 \n", " yes NaN \n", - "sex F 33.3 \n", - " M 34.5 \n", - "ageband 16-29 37.5 \n", - " 30-39 50 \n", - " 40-49 37.5 \n", - " 50-59 28.6 \n", - " 60-69 42.9 \n", - " 70-79 35.7 \n", + "sex F 41.9 \n", + " M 35.5 \n", + "ageband 16-29 28.6 \n", + " 30-39 37.5 \n", + " 40-49 42.9 \n", + " 50-59 57.1 \n", + " 60-69 33.3 \n", + " 70-79 29.4 \n", " 80+ 37.5 \n", - "ethnicity_6_groups Black 33.3 \n", - " Mixed 45.5 \n", - " Other 36.4 \n", - " South Asian 44.4 \n", - " Unknown 33.3 \n", - " White 33.3 \n", - "imd_categories 1 Most deprived 40 \n", - " 2 30.8 \n", - " 3 33.3 \n", - " 4 33.3 \n", - " 5 Least deprived 44.4 \n", - " Unknown 33.3 \n", - "LD no 34.5 \n", + "ethnicity_6_groups Black 30 \n", + " Mixed 36.4 \n", + " Other 45.5 \n", + " South Asian 33.3 \n", + " Unknown 40 \n", + " White 40 \n", + "imd_categories 1 Most deprived 42.9 \n", + " 2 38.5 \n", + " 3 36.4 \n", + " 4 30 \n", + " 5 Least deprived 40 \n", + " Unknown 25 \n", + "LD no 40 \n", " yes 0 \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 3.3 \n", + "newly_shielded_since_feb_15 no 3.3 \n", " yes 0 \n", - "sex F 3.4 \n", - " M 3.4 \n", + "sex F 3.3 \n", + " M 3.2 \n", "ageband 16-29 0 \n", " 30-39 0 \n", - " 40-49 0 \n", + " 40-49 14.2 \n", " 50-59 0 \n", " 60-69 0 \n", - " 70-79 0 \n", + " 70-79 5.9 \n", " 80+ 0 \n", - "ethnicity_6_groups Black 0 \n", - " Mixed 0 \n", + "ethnicity_6_groups Black 10 \n", + " Mixed 9.1 \n", " Other 0 \n", " South Asian 0 \n", " Unknown 0 \n", - " White 0 \n", + " White 10 \n", "imd_categories 1 Most deprived 0 \n", - " 2 0 \n", + " 2 7.7 \n", " 3 0 \n", - " 4 8.4 \n", + " 4 10 \n", " 5 Least deprived 0 \n", - " Unknown 0 \n", + " Unknown 25 \n", "LD no 1.7 \n", " yes 0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall unknown \n", - "newly_shielded_since_feb_15 no unknown \n", + "overall overall 27-Jul \n", + "newly_shielded_since_feb_15 no 28-Jul \n", " yes unknown \n", - "sex F 17-Jul \n", - " M 15-Jul \n", + "sex F 20-Jul \n", + " M 06-Aug \n", "ageband 16-29 unknown \n", " 30-39 unknown \n", - " 40-49 unknown \n", + " 40-49 02-May \n", " 50-59 unknown \n", " 60-69 unknown \n", - " 70-79 unknown \n", + " 70-79 19-Jun \n", " 80+ unknown \n", - "ethnicity_6_groups Black unknown \n", - " Mixed unknown \n", + "ethnicity_6_groups Black 21-May \n", + " Mixed 20-May \n", " Other unknown \n", " South Asian unknown \n", " Unknown unknown \n", - " White unknown \n", + " White 14-May \n", "imd_categories 1 Most deprived unknown \n", - " 2 unknown \n", + " 2 25-May \n", " 3 unknown \n", - " 4 09-May \n", + " 4 21-May \n", " 5 Least deprived unknown \n", - " Unknown unknown \n", + " Unknown 27-Apr \n", "LD no unknown \n", " yes unknown " ] @@ -3782,7 +3782,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout among **65-69** population up to 30 Mar 2021" + "## COVID vaccination rollout among **65-69** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -3848,126 +3848,135 @@ " \n", " overall\n", " overall\n", - " 900\n", - " 41.1\n", - " 2191\n", - " 38.4\n", - " 2.7\n", - " 03-Aug\n", + " 859\n", + " 39.3\n", + " 2184\n", + " 37.1\n", + " 2.2\n", + " 24-Sep\n", " \n", " \n", " sex\n", " F\n", - " 476\n", - " 41.2\n", - " 1155\n", - " 38.8\n", - " 2.4\n", - " 19-Aug\n", + " 434\n", + " 39.0\n", + " 1113\n", + " 37.1\n", + " 1.9\n", + " unknown\n", " \n", " \n", " M\n", " 427\n", - " 41.2\n", - " 1036\n", - " 37.8\n", - " 3.4\n", - " 08-Jul\n", + " 39.9\n", + " 1071\n", + " 37.3\n", + " 2.6\n", + " 28-Aug\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 154\n", - " 40.7\n", - " 378\n", - " 38.9\n", - " 1.8\n", + " 140\n", + " 38.5\n", + " 364\n", + " 36.5\n", + " 2\n", " unknown\n", " \n", " \n", " Mixed\n", - " 154\n", - " 40.7\n", - " 378\n", - " 38.9\n", - " 1.8\n", + " 140\n", + " 39.2\n", + " 357\n", + " 37.3\n", + " 1.9\n", " unknown\n", " \n", " \n", " Other\n", - " 140\n", - " 38.5\n", - " 364\n", - " 34.6\n", - " 3.9\n", - " 30-Jun\n", + " 154\n", + " 41.5\n", + " 371\n", + " 39.6\n", + " 1.9\n", + " unknown\n", " \n", " \n", " South Asian\n", - " 147\n", - " 39.6\n", - " 371\n", - " 39.6\n", - " 0\n", + " 154\n", + " 39.3\n", + " 392\n", + " 37.5\n", + " 1.8\n", " unknown\n", " \n", " \n", " Unknown\n", - " 126\n", - " 40.9\n", - " 308\n", - " 38.6\n", - " 2.3\n", - " 26-Aug\n", + " 140\n", + " 40.8\n", + " 343\n", + " 36.7\n", + " 4.1\n", + " 09-Jul\n", " \n", " \n", " White\n", - " 168\n", - " 44.4\n", - " 378\n", - " 42.6\n", - " 1.8\n", + " 126\n", + " 36.7\n", + " 343\n", + " 34.7\n", + " 2\n", " unknown\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", " 42\n", - " 40.0\n", - " 105\n", - " 33.3\n", - " 6.7\n", - " 21-May\n", + " 35.3\n", + " 119\n", + " 35.3\n", + " 0\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 49\n", - " 46.7\n", - " 105\n", - " 46.7\n", + " 42\n", + " 37.5\n", + " 112\n", + " 37.5\n", " 0\n", " unknown\n", " \n", " \n", " Caribbean\n", " 42\n", - " 35.3\n", - " 119\n", - " 35.3\n", + " 42.9\n", + " 98\n", + " 42.9\n", " 0\n", " unknown\n", " \n", " \n", " Chinese\n", + " 35\n", + " 35.7\n", + " 98\n", + " 28.6\n", + " 7.1\n", + " 08-Jun\n", + " \n", + " \n", + " Other\n", " 49\n", " 38.9\n", " 126\n", " 33.3\n", " 5.6\n", - " 01-Jun\n", + " 18-Jun\n", " \n", " \n", - " Other\n", + " Other Asian\n", " 42\n", " 37.5\n", " 112\n", @@ -3976,20 +3985,11 @@ " unknown\n", " \n", " \n", - " Other Asian\n", - " 49\n", - " 46.7\n", - " 105\n", - " 46.7\n", - " 0\n", - " unknown\n", - " \n", - " \n", " British or Mixed British\n", " 42\n", - " 37.5\n", - " 112\n", - " 37.5\n", + " 33.3\n", + " 126\n", + " 33.3\n", " 0\n", " unknown\n", " \n", @@ -3998,9 +3998,9 @@ " 49\n", " 41.2\n", " 119\n", - " 41.2\n", - " 0\n", - " unknown\n", + " 35.3\n", + " 5.9\n", + " 12-Jun\n", " \n", " \n", " Irish\n", @@ -4009,201 +4009,201 @@ " 126\n", " 38.9\n", " 5.5\n", - " 27-May\n", + " 13-Jun\n", " \n", " \n", " Other Black\n", - " 56\n", - " 44.4\n", - " 126\n", - " 38.9\n", - " 5.5\n", - " 27-May\n", + " 42\n", + " 40.0\n", + " 105\n", + " 33.3\n", + " 6.7\n", + " 07-Jun\n", " \n", " \n", " Other White\n", - " 56\n", - " 44.4\n", - " 126\n", - " 38.9\n", - " 5.5\n", - " 27-May\n", + " 49\n", + " 43.8\n", + " 112\n", + " 37.5\n", + " 6.3\n", + " 06-Jun\n", " \n", " \n", " Other mixed\n", - " 42\n", - " 37.5\n", - " 112\n", - " 31.2\n", - " 6.3\n", - " 27-May\n", + " 56\n", + " 40.0\n", + " 140\n", + " 35\n", + " 5\n", + " 25-Jun\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 42\n", - " 37.5\n", - " 112\n", - " 37.5\n", + " 49\n", + " 38.9\n", + " 126\n", + " 38.9\n", " 0\n", " unknown\n", " \n", " \n", " Unknown\n", - " 140\n", - " 42.6\n", - " 329\n", - " 38.3\n", - " 4.3\n", - " 15-Jun\n", + " 126\n", + " 39.1\n", + " 322\n", + " 37\n", + " 2.1\n", + " 02-Oct\n", " \n", " \n", " White + Asian\n", - " 63\n", - " 47.4\n", - " 133\n", - " 42.1\n", - " 5.3\n", - " 25-May\n", + " 49\n", + " 41.2\n", + " 119\n", + " 35.3\n", + " 5.9\n", + " 12-Jun\n", " \n", " \n", " White + Black African\n", " 42\n", - " 40.0\n", - " 105\n", - " 40\n", + " 33.3\n", + " 126\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 42\n", - " 37.5\n", - " 112\n", - " 37.5\n", + " 49\n", + " 46.7\n", + " 105\n", + " 46.7\n", " 0\n", " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 182\n", - " 39.4\n", - " 462\n", - " 36.4\n", - " 3\n", - " 26-Jul\n", + " 154\n", + " 39.3\n", + " 392\n", + " 37.5\n", + " 1.8\n", + " unknown\n", " \n", " \n", " 2\n", - " 161\n", - " 39.7\n", - " 406\n", - " 37.9\n", - " 1.8\n", + " 182\n", + " 38.8\n", + " 469\n", + " 37.3\n", + " 1.5\n", " unknown\n", " \n", " \n", " 3\n", - " 168\n", - " 42.1\n", - " 399\n", - " 38.6\n", + " 161\n", + " 39.7\n", + " 406\n", + " 36.2\n", " 3.5\n", - " 03-Jul\n", + " 25-Jul\n", " \n", " \n", " 4\n", - " 175\n", - " 42.4\n", - " 413\n", - " 39\n", - " 3.4\n", - " 06-Jul\n", + " 147\n", + " 36.8\n", + " 399\n", + " 33.3\n", + " 3.5\n", + " 31-Jul\n", " \n", " \n", " 5 Least deprived\n", - " 175\n", - " 41.0\n", - " 427\n", - " 37.7\n", - " 3.3\n", - " 11-Jul\n", + " 154\n", + " 39.3\n", + " 392\n", + " 39.3\n", + " 0\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 42\n", - " 46.2\n", - " 91\n", - " 38.5\n", - " 7.7\n", - " 08-May\n", + " 56\n", + " 44.4\n", + " 126\n", + " 44.4\n", + " 0\n", + " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 280\n", - " 41.7\n", - " 672\n", + " 252\n", " 39.6\n", - " 2.1\n", - " 07-Sep\n", + " 637\n", + " 37.4\n", + " 2.2\n", + " 23-Sep\n", " \n", " \n", " under 30\n", - " 623\n", - " 41.2\n", - " 1512\n", - " 38\n", - " 3.2\n", - " 14-Jul\n", + " 609\n", + " 39.5\n", + " 1540\n", + " 36.8\n", + " 2.7\n", + " 24-Aug\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 889\n", - " 41.0\n", - " 2170\n", - " 38.4\n", - " 2.6\n", - " 08-Aug\n", + " 854\n", + " 39.5\n", + " 2163\n", + " 37.2\n", + " 2.3\n", + " 16-Sep\n", " \n", " \n", " yes\n", + " 0\n", + " 0.0\n", " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 0\n", " 0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 889\n", - " 41.1\n", + " 854\n", + " 39.5\n", " 2163\n", - " 38.5\n", - " 2.6\n", - " 08-Aug\n", + " 37.2\n", + " 2.3\n", + " 16-Sep\n", " \n", " \n", " yes\n", - " 7\n", - " 25.0\n", - " 28\n", - " 25\n", + " 7\n", + " 33.3\n", + " 21\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 889\n", - " 41.0\n", - " 2170\n", - " 38.4\n", - " 2.6\n", - " 08-Aug\n", + " 854\n", + " 39.5\n", + " 2163\n", + " 37.2\n", + " 2.3\n", + " 16-Sep\n", " \n", " \n", " yes\n", @@ -4217,69 +4217,69 @@ " \n", " dementia\n", " no\n", - " 889\n", - " 41.1\n", - " 2163\n", - " 38.5\n", - " 2.6\n", - " 08-Aug\n", + " 854\n", + " 39.4\n", + " 2170\n", + " 37.1\n", + " 2.3\n", + " 17-Sep\n", " \n", " \n", " yes\n", - " 7\n", - " 33.3\n", - " 21\n", - " 33.3\n", + " 0\n", + " 0.0\n", + " 14\n", + " 0\n", " 0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 889\n", - " 41.1\n", + " 854\n", + " 39.5\n", " 2163\n", - " 38.5\n", - " 2.6\n", - " 08-Aug\n", + " 37.2\n", + " 2.3\n", + " 16-Sep\n", " \n", " \n", " yes\n", " 7\n", " 33.3\n", " 21\n", - " 33.3\n", " 0\n", - " unknown\n", + " 33.3\n", + " 27-Apr\n", " \n", " \n", " LD\n", " no\n", - " 882\n", - " 41.3\n", - " 2135\n", - " 38.4\n", - " 2.9\n", - " 25-Jul\n", + " 847\n", + " 39.4\n", + " 2149\n", + " 37.1\n", + " 2.3\n", + " 17-Sep\n", " \n", " \n", " yes\n", - " 21\n", - " 37.5\n", - " 56\n", - " 37.5\n", + " 14\n", + " 50.0\n", + " 28\n", + " 50\n", " 0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 889\n", - " 41.0\n", - " 2170\n", - " 38.1\n", - " 2.9\n", - " 26-Jul\n", + " 847\n", + " 39.3\n", + " 2156\n", + " 37\n", + " 2.3\n", + " 17-Sep\n", " \n", " \n", " yes\n", @@ -4293,76 +4293,76 @@ " \n", " chemo_or_radio\n", " no\n", - " 896\n", - " 41.3\n", - " 2170\n", - " 38.4\n", - " 2.9\n", - " 25-Jul\n", + " 847\n", + " 39.3\n", + " 2156\n", + " 37.3\n", + " 2\n", + " unknown\n", " \n", " \n", " yes\n", " 7\n", " 33.3\n", " 21\n", - " 0\n", " 33.3\n", - " 10-Apr\n", + " 0\n", + " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 889\n", - " 41.2\n", + " 847\n", + " 39.3\n", " 2156\n", - " 38.6\n", - " 2.6\n", - " 08-Aug\n", + " 37\n", + " 2.3\n", + " 17-Sep\n", " \n", " \n", " yes\n", " 14\n", - " 40.0\n", - " 35\n", - " 40\n", - " 0\n", - " unknown\n", + " 66.7\n", + " 21\n", + " 33.3\n", + " 33.4\n", + " 20-Apr\n", " \n", " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 889\n", - " 41.1\n", - " 2163\n", - " 38.2\n", - " 2.9\n", - " 26-Jul\n", + " 847\n", + " 39.3\n", + " 2156\n", + " 37\n", + " 2.3\n", + " 17-Sep\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50\n", + " 7\n", + " 33.3\n", + " 21\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 889\n", - " 41.0\n", - " 2170\n", - " 38.1\n", - " 2.9\n", - " 26-Jul\n", + " 847\n", + " 39.3\n", + " 2156\n", + " 37\n", + " 2.3\n", + " 17-Sep\n", " \n", " \n", " yes\n", - " 14\n", - " 66.7\n", + " 7\n", + " 33.3\n", " 21\n", - " 66.7\n", + " 33.3\n", " 0\n", " unknown\n", " \n", @@ -4373,297 +4373,297 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 900 \n", - "sex F 476 \n", + "overall overall 859 \n", + "sex F 434 \n", " M 427 \n", - "ethnicity_6_groups Black 154 \n", - " Mixed 154 \n", - " Other 140 \n", - " South Asian 147 \n", - " Unknown 126 \n", - " White 168 \n", + "ethnicity_6_groups Black 140 \n", + " Mixed 140 \n", + " Other 154 \n", + " South Asian 154 \n", + " Unknown 140 \n", + " White 126 \n", "ethnicity_16_groups African 42 \n", - " Bangladeshi or British Bangladeshi 49 \n", + " Bangladeshi or British Bangladeshi 42 \n", " Caribbean 42 \n", - " Chinese 49 \n", - " Other 42 \n", - " Other Asian 49 \n", + " Chinese 35 \n", + " Other 49 \n", + " Other Asian 42 \n", " British or Mixed British 42 \n", " Indian or British Indian 49 \n", " Irish 56 \n", - " Other Black 56 \n", - " Other White 56 \n", - " Other mixed 42 \n", - " Pakistani or British Pakistani 42 \n", - " Unknown 140 \n", - " White + Asian 63 \n", + " Other Black 42 \n", + " Other White 49 \n", + " Other mixed 56 \n", + " Pakistani or British Pakistani 49 \n", + " Unknown 126 \n", + " White + Asian 49 \n", " White + Black African 42 \n", - " White + Black Caribbean 42 \n", - "imd_categories 1 Most deprived 182 \n", - " 2 161 \n", - " 3 168 \n", - " 4 175 \n", - " 5 Least deprived 175 \n", - " Unknown 42 \n", - "bmi 30+ 280 \n", - " under 30 623 \n", - "chronic_cardiac_disease no 889 \n", - " yes 14 \n", - "current_copd no 889 \n", - " yes 7 \n", - "dmards no 889 \n", - " yes 7 \n", - "dementia no 889 \n", + " White + Black Caribbean 49 \n", + "imd_categories 1 Most deprived 154 \n", + " 2 182 \n", + " 3 161 \n", + " 4 147 \n", + " 5 Least deprived 154 \n", + " Unknown 56 \n", + "bmi 30+ 252 \n", + " under 30 609 \n", + "chronic_cardiac_disease no 854 \n", + " yes 0 \n", + "current_copd no 854 \n", " yes 7 \n", - "psychosis_schiz_bipolar no 889 \n", + "dmards no 854 \n", " yes 7 \n", - "LD no 882 \n", - " yes 21 \n", - "ssri no 889 \n", - " yes 14 \n", - "chemo_or_radio no 896 \n", + "dementia no 854 \n", + " yes 0 \n", + "psychosis_schiz_bipolar no 854 \n", " yes 7 \n", - "lung_cancer no 889 \n", + "LD no 847 \n", " yes 14 \n", - "cancer_excl_lung_and_haem no 889 \n", + "ssri no 847 \n", " yes 14 \n", - "haematological_cancer no 889 \n", + "chemo_or_radio no 847 \n", + " yes 7 \n", + "lung_cancer no 847 \n", " yes 14 \n", + "cancer_excl_lung_and_haem no 847 \n", + " yes 7 \n", + "haematological_cancer no 847 \n", + " yes 7 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 41.1 2191 \n", - "sex F 41.2 1155 \n", - " M 41.2 1036 \n", - "ethnicity_6_groups Black 40.7 378 \n", - " Mixed 40.7 378 \n", - " Other 38.5 364 \n", - " South Asian 39.6 371 \n", - " Unknown 40.9 308 \n", - " White 44.4 378 \n", - "ethnicity_16_groups African 40.0 105 \n", - " Bangladeshi or British Bangladeshi 46.7 105 \n", - " Caribbean 35.3 119 \n", - " Chinese 38.9 126 \n", - " Other 37.5 112 \n", - " Other Asian 46.7 105 \n", - " British or Mixed British 37.5 112 \n", + "overall overall 39.3 2184 \n", + "sex F 39.0 1113 \n", + " M 39.9 1071 \n", + "ethnicity_6_groups Black 38.5 364 \n", + " Mixed 39.2 357 \n", + " Other 41.5 371 \n", + " South Asian 39.3 392 \n", + " Unknown 40.8 343 \n", + " White 36.7 343 \n", + "ethnicity_16_groups African 35.3 119 \n", + " Bangladeshi or British Bangladeshi 37.5 112 \n", + " Caribbean 42.9 98 \n", + " Chinese 35.7 98 \n", + " Other 38.9 126 \n", + " Other Asian 37.5 112 \n", + " British or Mixed British 33.3 126 \n", " Indian or British Indian 41.2 119 \n", " Irish 44.4 126 \n", - " Other Black 44.4 126 \n", - " Other White 44.4 126 \n", - " Other mixed 37.5 112 \n", - " Pakistani or British Pakistani 37.5 112 \n", - " Unknown 42.6 329 \n", - " White + Asian 47.4 133 \n", - " White + Black African 40.0 105 \n", - " White + Black Caribbean 37.5 112 \n", - "imd_categories 1 Most deprived 39.4 462 \n", - " 2 39.7 406 \n", - " 3 42.1 399 \n", - " 4 42.4 413 \n", - " 5 Least deprived 41.0 427 \n", - " Unknown 46.2 91 \n", - "bmi 30+ 41.7 672 \n", - " under 30 41.2 1512 \n", - "chronic_cardiac_disease no 41.0 2170 \n", - " yes 66.7 21 \n", - "current_copd no 41.1 2163 \n", - " yes 25.0 28 \n", - "dmards no 41.0 2170 \n", + " Other Black 40.0 105 \n", + " Other White 43.8 112 \n", + " Other mixed 40.0 140 \n", + " Pakistani or British Pakistani 38.9 126 \n", + " Unknown 39.1 322 \n", + " White + Asian 41.2 119 \n", + " White + Black African 33.3 126 \n", + " White + Black Caribbean 46.7 105 \n", + "imd_categories 1 Most deprived 39.3 392 \n", + " 2 38.8 469 \n", + " 3 39.7 406 \n", + " 4 36.8 399 \n", + " 5 Least deprived 39.3 392 \n", + " Unknown 44.4 126 \n", + "bmi 30+ 39.6 637 \n", + " under 30 39.5 1540 \n", + "chronic_cardiac_disease no 39.5 2163 \n", + " yes 0.0 14 \n", + "current_copd no 39.5 2163 \n", " yes 33.3 21 \n", - "dementia no 41.1 2163 \n", + "dmards no 39.5 2163 \n", " yes 33.3 21 \n", - "psychosis_schiz_bipolar no 41.1 2163 \n", + "dementia no 39.4 2170 \n", + " yes 0.0 14 \n", + "psychosis_schiz_bipolar no 39.5 2163 \n", " yes 33.3 21 \n", - "LD no 41.3 2135 \n", - " yes 37.5 56 \n", - "ssri no 41.0 2170 \n", + "LD no 39.4 2149 \n", + " yes 50.0 28 \n", + "ssri no 39.3 2156 \n", " yes 66.7 21 \n", - "chemo_or_radio no 41.3 2170 \n", + "chemo_or_radio no 39.3 2156 \n", " yes 33.3 21 \n", - "lung_cancer no 41.2 2156 \n", - " yes 40.0 35 \n", - "cancer_excl_lung_and_haem no 41.1 2163 \n", - " yes 50.0 28 \n", - "haematological_cancer no 41.0 2170 \n", + "lung_cancer no 39.3 2156 \n", " yes 66.7 21 \n", + "cancer_excl_lung_and_haem no 39.3 2156 \n", + " yes 33.3 21 \n", + "haematological_cancer no 39.3 2156 \n", + " yes 33.3 21 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 38.4 \n", - "sex F 38.8 \n", - " M 37.8 \n", - "ethnicity_6_groups Black 38.9 \n", - " Mixed 38.9 \n", - " Other 34.6 \n", - " South Asian 39.6 \n", - " Unknown 38.6 \n", - " White 42.6 \n", - "ethnicity_16_groups African 33.3 \n", - " Bangladeshi or British Bangladeshi 46.7 \n", - " Caribbean 35.3 \n", - " Chinese 33.3 \n", - " Other 37.5 \n", - " Other Asian 46.7 \n", - " British or Mixed British 37.5 \n", - " Indian or British Indian 41.2 \n", + "overall overall 37.1 \n", + "sex F 37.1 \n", + " M 37.3 \n", + "ethnicity_6_groups Black 36.5 \n", + " Mixed 37.3 \n", + " Other 39.6 \n", + " South Asian 37.5 \n", + " Unknown 36.7 \n", + " White 34.7 \n", + "ethnicity_16_groups African 35.3 \n", + " Bangladeshi or British Bangladeshi 37.5 \n", + " Caribbean 42.9 \n", + " Chinese 28.6 \n", + " Other 33.3 \n", + " Other Asian 37.5 \n", + " British or Mixed British 33.3 \n", + " Indian or British Indian 35.3 \n", " Irish 38.9 \n", - " Other Black 38.9 \n", - " Other White 38.9 \n", - " Other mixed 31.2 \n", - " Pakistani or British Pakistani 37.5 \n", - " Unknown 38.3 \n", - " White + Asian 42.1 \n", - " White + Black African 40 \n", - " White + Black Caribbean 37.5 \n", - "imd_categories 1 Most deprived 36.4 \n", - " 2 37.9 \n", - " 3 38.6 \n", - " 4 39 \n", - " 5 Least deprived 37.7 \n", - " Unknown 38.5 \n", - "bmi 30+ 39.6 \n", - " under 30 38 \n", - "chronic_cardiac_disease no 38.4 \n", - " yes 66.7 \n", - "current_copd no 38.5 \n", - " yes 25 \n", - "dmards no 38.4 \n", - " yes 33.3 \n", - "dementia no 38.5 \n", + " Other Black 33.3 \n", + " Other White 37.5 \n", + " Other mixed 35 \n", + " Pakistani or British Pakistani 38.9 \n", + " Unknown 37 \n", + " White + Asian 35.3 \n", + " White + Black African 33.3 \n", + " White + Black Caribbean 46.7 \n", + "imd_categories 1 Most deprived 37.5 \n", + " 2 37.3 \n", + " 3 36.2 \n", + " 4 33.3 \n", + " 5 Least deprived 39.3 \n", + " Unknown 44.4 \n", + "bmi 30+ 37.4 \n", + " under 30 36.8 \n", + "chronic_cardiac_disease no 37.2 \n", + " yes 0 \n", + "current_copd no 37.2 \n", " yes 33.3 \n", - "psychosis_schiz_bipolar no 38.5 \n", + "dmards no 37.2 \n", " yes 33.3 \n", - "LD no 38.4 \n", - " yes 37.5 \n", - "ssri no 38.1 \n", - " yes 66.7 \n", - "chemo_or_radio no 38.4 \n", + "dementia no 37.1 \n", " yes 0 \n", - "lung_cancer no 38.6 \n", - " yes 40 \n", - "cancer_excl_lung_and_haem no 38.2 \n", + "psychosis_schiz_bipolar no 37.2 \n", + " yes 0 \n", + "LD no 37.1 \n", " yes 50 \n", - "haematological_cancer no 38.1 \n", + "ssri no 37 \n", " yes 66.7 \n", + "chemo_or_radio no 37.3 \n", + " yes 33.3 \n", + "lung_cancer no 37 \n", + " yes 33.3 \n", + "cancer_excl_lung_and_haem no 37 \n", + " yes 33.3 \n", + "haematological_cancer no 37 \n", + " yes 33.3 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 2.7 \n", - "sex F 2.4 \n", - " M 3.4 \n", - "ethnicity_6_groups Black 1.8 \n", - " Mixed 1.8 \n", - " Other 3.9 \n", - " South Asian 0 \n", - " Unknown 2.3 \n", - " White 1.8 \n", - "ethnicity_16_groups African 6.7 \n", + "overall overall 2.2 \n", + "sex F 1.9 \n", + " M 2.6 \n", + "ethnicity_6_groups Black 2 \n", + " Mixed 1.9 \n", + " Other 1.9 \n", + " South Asian 1.8 \n", + " Unknown 4.1 \n", + " White 2 \n", + "ethnicity_16_groups African 0 \n", " Bangladeshi or British Bangladeshi 0 \n", " Caribbean 0 \n", - " Chinese 5.6 \n", - " Other 0 \n", + " Chinese 7.1 \n", + " Other 5.6 \n", " Other Asian 0 \n", " British or Mixed British 0 \n", - " Indian or British Indian 0 \n", + " Indian or British Indian 5.9 \n", " Irish 5.5 \n", - " Other Black 5.5 \n", - " Other White 5.5 \n", - " Other mixed 6.3 \n", + " Other Black 6.7 \n", + " Other White 6.3 \n", + " Other mixed 5 \n", " Pakistani or British Pakistani 0 \n", - " Unknown 4.3 \n", - " White + Asian 5.3 \n", + " Unknown 2.1 \n", + " White + Asian 5.9 \n", " White + Black African 0 \n", " White + Black Caribbean 0 \n", - "imd_categories 1 Most deprived 3 \n", - " 2 1.8 \n", + "imd_categories 1 Most deprived 1.8 \n", + " 2 1.5 \n", " 3 3.5 \n", - " 4 3.4 \n", - " 5 Least deprived 3.3 \n", - " Unknown 7.7 \n", - "bmi 30+ 2.1 \n", - " under 30 3.2 \n", - "chronic_cardiac_disease no 2.6 \n", - " yes 0 \n", - "current_copd no 2.6 \n", + " 4 3.5 \n", + " 5 Least deprived 0 \n", + " Unknown 0 \n", + "bmi 30+ 2.2 \n", + " under 30 2.7 \n", + "chronic_cardiac_disease no 2.3 \n", " yes 0 \n", - "dmards no 2.6 \n", + "current_copd no 2.3 \n", " yes 0 \n", - "dementia no 2.6 \n", + "dmards no 2.3 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 2.6 \n", + "dementia no 2.3 \n", " yes 0 \n", - "LD no 2.9 \n", + "psychosis_schiz_bipolar no 2.3 \n", + " yes 33.3 \n", + "LD no 2.3 \n", " yes 0 \n", - "ssri no 2.9 \n", + "ssri no 2.3 \n", " yes 0 \n", - "chemo_or_radio no 2.9 \n", - " yes 33.3 \n", - "lung_cancer no 2.6 \n", + "chemo_or_radio no 2 \n", " yes 0 \n", - "cancer_excl_lung_and_haem no 2.9 \n", + "lung_cancer no 2.3 \n", + " yes 33.4 \n", + "cancer_excl_lung_and_haem no 2.3 \n", " yes 0 \n", - "haematological_cancer no 2.9 \n", + "haematological_cancer no 2.3 \n", " yes 0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 03-Aug \n", - "sex F 19-Aug \n", - " M 08-Jul \n", + "overall overall 24-Sep \n", + "sex F unknown \n", + " M 28-Aug \n", "ethnicity_6_groups Black unknown \n", " Mixed unknown \n", - " Other 30-Jun \n", + " Other unknown \n", " South Asian unknown \n", - " Unknown 26-Aug \n", + " Unknown 09-Jul \n", " White unknown \n", - "ethnicity_16_groups African 21-May \n", + "ethnicity_16_groups African unknown \n", " Bangladeshi or British Bangladeshi unknown \n", " Caribbean unknown \n", - " Chinese 01-Jun \n", - " Other unknown \n", + " Chinese 08-Jun \n", + " Other 18-Jun \n", " Other Asian unknown \n", " British or Mixed British unknown \n", - " Indian or British Indian unknown \n", - " Irish 27-May \n", - " Other Black 27-May \n", - " Other White 27-May \n", - " Other mixed 27-May \n", + " Indian or British Indian 12-Jun \n", + " Irish 13-Jun \n", + " Other Black 07-Jun \n", + " Other White 06-Jun \n", + " Other mixed 25-Jun \n", " Pakistani or British Pakistani unknown \n", - " Unknown 15-Jun \n", - " White + Asian 25-May \n", + " Unknown 02-Oct \n", + " White + Asian 12-Jun \n", " White + Black African unknown \n", " White + Black Caribbean unknown \n", - "imd_categories 1 Most deprived 26-Jul \n", + "imd_categories 1 Most deprived unknown \n", " 2 unknown \n", - " 3 03-Jul \n", - " 4 06-Jul \n", - " 5 Least deprived 11-Jul \n", - " Unknown 08-May \n", - "bmi 30+ 07-Sep \n", - " under 30 14-Jul \n", - "chronic_cardiac_disease no 08-Aug \n", - " yes unknown \n", - "current_copd no 08-Aug \n", + " 3 25-Jul \n", + " 4 31-Jul \n", + " 5 Least deprived unknown \n", + " Unknown unknown \n", + "bmi 30+ 23-Sep \n", + " under 30 24-Aug \n", + "chronic_cardiac_disease no 16-Sep \n", " yes unknown \n", - "dmards no 08-Aug \n", + "current_copd no 16-Sep \n", " yes unknown \n", - "dementia no 08-Aug \n", + "dmards no 16-Sep \n", " yes unknown \n", - "psychosis_schiz_bipolar no 08-Aug \n", + "dementia no 17-Sep \n", " yes unknown \n", - "LD no 25-Jul \n", + "psychosis_schiz_bipolar no 16-Sep \n", + " yes 27-Apr \n", + "LD no 17-Sep \n", " yes unknown \n", - "ssri no 26-Jul \n", + "ssri no 17-Sep \n", " yes unknown \n", - "chemo_or_radio no 25-Jul \n", - " yes 10-Apr \n", - "lung_cancer no 08-Aug \n", + "chemo_or_radio no unknown \n", " yes unknown \n", - "cancer_excl_lung_and_haem no 26-Jul \n", + "lung_cancer no 17-Sep \n", + " yes 20-Apr \n", + "cancer_excl_lung_and_haem no 17-Sep \n", " yes unknown \n", - "haematological_cancer no 26-Jul \n", + "haematological_cancer no 17-Sep \n", " yes unknown " ] }, @@ -4685,7 +4685,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout among **LD (aged 16-64)** population up to 30 Mar 2021" + "## COVID vaccination rollout among **LD (aged 16-64)** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -4751,50 +4751,50 @@ " \n", " overall\n", " overall\n", - " 324\n", - " 41.3\n", - " 784\n", - " 38.1\n", - " 3.2\n", - " 14-Jul\n", + " 344\n", + " 41.6\n", + " 826\n", + " 39.6\n", + " 2\n", + " 02-Oct\n", " \n", " \n", " sex\n", " F\n", - " 154\n", - " 39.3\n", - " 392\n", - " 35.7\n", - " 3.6\n", - " 06-Jul\n", + " 182\n", + " 40.6\n", + " 448\n", + " 39.1\n", + " 1.5\n", + " unknown\n", " \n", " \n", " M\n", - " 168\n", - " 42.1\n", - " 399\n", - " 40.4\n", - " 1.7\n", - " unknown\n", + " 161\n", + " 42.6\n", + " 378\n", + " 40.7\n", + " 1.9\n", + " 07-Oct\n", " \n", " \n", " ageband_5yr\n", " 0\n", - " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", + " 14\n", + " 40.0\n", + " 35\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " 0-15\n", - " 14\n", - " 33.3\n", - " 42\n", - " 33.3\n", - " 0\n", - " unknown\n", + " 28\n", + " 50.0\n", + " 56\n", + " 37.5\n", + " 12.5\n", + " 08-May\n", " \n", " \n", " 16-29\n", @@ -4803,32 +4803,32 @@ " 56\n", " 25\n", " 12.5\n", - " 28-Apr\n", + " 15-May\n", " \n", " \n", " 30-34\n", " 21\n", - " 50.0\n", - " 42\n", - " 33.3\n", - " 16.7\n", - " 15-Apr\n", + " 42.9\n", + " 49\n", + " 42.9\n", + " 0\n", + " unknown\n", " \n", " \n", " 35-39\n", - " 21\n", - " 50.0\n", - " 42\n", - " 50\n", - " 0\n", - " unknown\n", + " 35\n", + " 55.6\n", + " 63\n", + " 44.4\n", + " 11.2\n", + " 07-May\n", " \n", " \n", " 40-44\n", " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", + " 37.5\n", + " 56\n", + " 37.5\n", " 0\n", " unknown\n", " \n", @@ -4839,41 +4839,41 @@ " 49\n", " 28.6\n", " 14.3\n", - " 22-Apr\n", + " 09-May\n", " \n", " \n", " 50-54\n", " 21\n", - " 37.5\n", - " 56\n", - " 37.5\n", + " 42.9\n", + " 49\n", + " 42.9\n", " 0\n", " unknown\n", " \n", " \n", " 55-59\n", - " 14\n", - " 28.6\n", + " 21\n", + " 42.9\n", " 49\n", " 28.6\n", - " 0\n", - " unknown\n", + " 14.3\n", + " 09-May\n", " \n", " \n", " 60-64\n", " 21\n", - " 42.9\n", - " 49\n", - " 28.6\n", - " 14.3\n", - " 22-Apr\n", + " 37.5\n", + " 56\n", + " 37.5\n", + " 0\n", + " unknown\n", " \n", " \n", " 65-69\n", - " 14\n", - " 33.3\n", - " 42\n", - " 33.3\n", + " 21\n", + " 42.9\n", + " 49\n", + " 42.9\n", " 0\n", " unknown\n", " \n", @@ -4889,9 +4889,9 @@ " \n", " 75-79\n", " 21\n", - " 42.9\n", - " 49\n", - " 42.9\n", + " 50.0\n", + " 42\n", + " 50\n", " 0\n", " unknown\n", " \n", @@ -4907,42 +4907,33 @@ " \n", " 85-89\n", " 28\n", - " 44.4\n", - " 63\n", - " 44.4\n", + " 50.0\n", + " 56\n", + " 50\n", " 0\n", " unknown\n", " \n", " \n", " 90+\n", - " 28\n", - " 44.4\n", - " 63\n", - " 33.3\n", - " 11.1\n", - " 27-Apr\n", + " 21\n", + " 37.5\n", + " 56\n", + " 37.5\n", + " 0\n", + " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 49\n", - " 36.8\n", - " 133\n", - " 31.6\n", - " 5.2\n", - " 09-Jun\n", - " \n", - " \n", - " Mixed\n", + " 56\n", + " 40.0\n", + " 140\n", " 35\n", - " 27.8\n", - " 126\n", - " 27.8\n", - " 0\n", - " unknown\n", + " 5\n", + " 25-Jun\n", " \n", " \n", - " Other\n", + " Mixed\n", " 63\n", " 47.4\n", " 133\n", @@ -4951,31 +4942,40 @@ " unknown\n", " \n", " \n", + " Other\n", + " 56\n", + " 40.0\n", + " 140\n", + " 35\n", + " 5\n", + " 25-Jun\n", + " \n", + " \n", " South Asian\n", " 63\n", - " 47.4\n", - " 133\n", - " 42.1\n", - " 5.3\n", - " 25-May\n", + " 45.0\n", + " 140\n", + " 45\n", + " 0\n", + " unknown\n", " \n", " \n", " Unknown\n", " 49\n", - " 46.7\n", - " 105\n", - " 40\n", - " 6.7\n", - " 14-May\n", + " 38.9\n", + " 126\n", + " 33.3\n", + " 5.6\n", + " 18-Jun\n", " \n", " \n", " White\n", - " 70\n", - " 45.5\n", - " 154\n", + " 63\n", " 40.9\n", - " 4.6\n", - " 05-Jun\n", + " 154\n", + " 36.4\n", + " 4.5\n", + " 01-Jul\n", " \n", " \n", "\n", @@ -4984,115 +4984,115 @@ "text/plain": [ " vaccinated percent total \\\n", "category group \n", - "overall overall 324 41.3 784 \n", - "sex F 154 39.3 392 \n", - " M 168 42.1 399 \n", - "ageband_5yr 0 21 42.9 49 \n", - " 0-15 14 33.3 42 \n", + "overall overall 344 41.6 826 \n", + "sex F 182 40.6 448 \n", + " M 161 42.6 378 \n", + "ageband_5yr 0 14 40.0 35 \n", + " 0-15 28 50.0 56 \n", " 16-29 21 37.5 56 \n", - " 30-34 21 50.0 42 \n", - " 35-39 21 50.0 42 \n", - " 40-44 21 42.9 49 \n", + " 30-34 21 42.9 49 \n", + " 35-39 35 55.6 63 \n", + " 40-44 21 37.5 56 \n", " 45-49 21 42.9 49 \n", - " 50-54 21 37.5 56 \n", - " 55-59 14 28.6 49 \n", - " 60-64 21 42.9 49 \n", - " 65-69 14 33.3 42 \n", + " 50-54 21 42.9 49 \n", + " 55-59 21 42.9 49 \n", + " 60-64 21 37.5 56 \n", + " 65-69 21 42.9 49 \n", " 70-74 21 42.9 49 \n", - " 75-79 21 42.9 49 \n", + " 75-79 21 50.0 42 \n", " 80-84 21 42.9 49 \n", - " 85-89 28 44.4 63 \n", - " 90+ 28 44.4 63 \n", - "ethnicity_6_groups Black 49 36.8 133 \n", - " Mixed 35 27.8 126 \n", - " Other 63 47.4 133 \n", - " South Asian 63 47.4 133 \n", - " Unknown 49 46.7 105 \n", - " White 70 45.5 154 \n", + " 85-89 28 50.0 56 \n", + " 90+ 21 37.5 56 \n", + "ethnicity_6_groups Black 56 40.0 140 \n", + " Mixed 63 47.4 133 \n", + " Other 56 40.0 140 \n", + " South Asian 63 45.0 140 \n", + " Unknown 49 38.9 126 \n", + " White 63 40.9 154 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 38.1 \n", - "sex F 35.7 \n", - " M 40.4 \n", - "ageband_5yr 0 42.9 \n", - " 0-15 33.3 \n", + "overall overall 39.6 \n", + "sex F 39.1 \n", + " M 40.7 \n", + "ageband_5yr 0 40 \n", + " 0-15 37.5 \n", " 16-29 25 \n", - " 30-34 33.3 \n", - " 35-39 50 \n", - " 40-44 42.9 \n", + " 30-34 42.9 \n", + " 35-39 44.4 \n", + " 40-44 37.5 \n", " 45-49 28.6 \n", - " 50-54 37.5 \n", + " 50-54 42.9 \n", " 55-59 28.6 \n", - " 60-64 28.6 \n", - " 65-69 33.3 \n", + " 60-64 37.5 \n", + " 65-69 42.9 \n", " 70-74 42.9 \n", - " 75-79 42.9 \n", + " 75-79 50 \n", " 80-84 42.9 \n", - " 85-89 44.4 \n", - " 90+ 33.3 \n", - "ethnicity_6_groups Black 31.6 \n", - " Mixed 27.8 \n", - " Other 47.4 \n", - " South Asian 42.1 \n", - " Unknown 40 \n", - " White 40.9 \n", + " 85-89 50 \n", + " 90+ 37.5 \n", + "ethnicity_6_groups Black 35 \n", + " Mixed 47.4 \n", + " Other 35 \n", + " South Asian 45 \n", + " Unknown 33.3 \n", + " White 36.4 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 3.2 \n", - "sex F 3.6 \n", - " M 1.7 \n", + "overall overall 2 \n", + "sex F 1.5 \n", + " M 1.9 \n", "ageband_5yr 0 0 \n", - " 0-15 0 \n", + " 0-15 12.5 \n", " 16-29 12.5 \n", - " 30-34 16.7 \n", - " 35-39 0 \n", + " 30-34 0 \n", + " 35-39 11.2 \n", " 40-44 0 \n", " 45-49 14.3 \n", " 50-54 0 \n", - " 55-59 0 \n", - " 60-64 14.3 \n", + " 55-59 14.3 \n", + " 60-64 0 \n", " 65-69 0 \n", " 70-74 0 \n", " 75-79 0 \n", " 80-84 0 \n", " 85-89 0 \n", - " 90+ 11.1 \n", - "ethnicity_6_groups Black 5.2 \n", + " 90+ 0 \n", + "ethnicity_6_groups Black 5 \n", " Mixed 0 \n", - " Other 0 \n", - " South Asian 5.3 \n", - " Unknown 6.7 \n", - " White 4.6 \n", + " Other 5 \n", + " South Asian 0 \n", + " Unknown 5.6 \n", + " White 4.5 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 14-Jul \n", - "sex F 06-Jul \n", - " M unknown \n", + "overall overall 02-Oct \n", + "sex F unknown \n", + " M 07-Oct \n", "ageband_5yr 0 unknown \n", - " 0-15 unknown \n", - " 16-29 28-Apr \n", - " 30-34 15-Apr \n", - " 35-39 unknown \n", + " 0-15 08-May \n", + " 16-29 15-May \n", + " 30-34 unknown \n", + " 35-39 07-May \n", " 40-44 unknown \n", - " 45-49 22-Apr \n", + " 45-49 09-May \n", " 50-54 unknown \n", - " 55-59 unknown \n", - " 60-64 22-Apr \n", + " 55-59 09-May \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+ 27-Apr \n", - "ethnicity_6_groups Black 09-Jun \n", + " 90+ unknown \n", + "ethnicity_6_groups Black 25-Jun \n", " Mixed unknown \n", - " Other unknown \n", - " South Asian 25-May \n", - " Unknown 14-May \n", - " White 05-Jun " + " Other 25-Jun \n", + " South Asian unknown \n", + " Unknown 18-Jun \n", + " White 01-Jul " ] }, "metadata": {}, @@ -5113,7 +5113,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout among **60-64** population up to 30 Mar 2021" + "## COVID vaccination rollout among **60-64** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -5179,362 +5179,362 @@ " \n", " overall\n", " overall\n", - " 1044\n", + " 1079\n", " 39.7\n", - " 2632\n", - " 37.5\n", - " 2.2\n", - " 06-Sep\n", + " 2716\n", + " 37.6\n", + " 2.1\n", + " 30-Sep\n", " \n", " \n", " sex\n", " F\n", - " 532\n", - " 39.2\n", - " 1358\n", - " 37.6\n", - " 1.6\n", + " 546\n", + " 38.6\n", + " 1414\n", + " 36.6\n", + " 2\n", " unknown\n", " \n", " \n", " M\n", - " 511\n", - " 40.1\n", - " 1274\n", - " 37.9\n", + " 532\n", + " 40.9\n", + " 1302\n", + " 38.7\n", " 2.2\n", - " 04-Sep\n", + " 19-Sep\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", " 175\n", - " 39.7\n", - " 441\n", - " 34.9\n", - " 4.8\n", - " 11-Jun\n", + " 38.5\n", + " 455\n", + " 36.9\n", + " 1.6\n", + " unknown\n", " \n", " \n", " Mixed\n", - " 154\n", - " 37.9\n", - " 406\n", - " 36.2\n", - " 1.7\n", + " 175\n", + " 39.1\n", + " 448\n", + " 37.5\n", + " 1.6\n", " unknown\n", " \n", " \n", " Other\n", " 175\n", - " 37.3\n", - " 469\n", - " 34.3\n", - " 3\n", - " 30-Jul\n", + " 37.9\n", + " 462\n", + " 36.4\n", + " 1.5\n", + " unknown\n", " \n", " \n", " South Asian\n", - " 196\n", - " 40.6\n", - " 483\n", - " 37.7\n", - " 2.9\n", - " 27-Jul\n", + " 182\n", + " 40.0\n", + " 455\n", + " 36.9\n", + " 3.1\n", + " 06-Aug\n", " \n", " \n", " Unknown\n", - " 161\n", - " 41.1\n", - " 392\n", - " 39.3\n", - " 1.8\n", - " unknown\n", + " 168\n", + " 42.1\n", + " 399\n", + " 38.6\n", + " 3.5\n", + " 20-Jul\n", " \n", " \n", " White\n", - " 189\n", - " 42.9\n", - " 441\n", - " 41.3\n", - " 1.6\n", - " unknown\n", + " 210\n", + " 41.7\n", + " 504\n", + " 38.9\n", + " 2.8\n", + " 14-Aug\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 42\n", - " 35.3\n", - " 119\n", - " 29.4\n", - " 5.9\n", - " 02-Jun\n", + " 63\n", + " 42.9\n", + " 147\n", + " 38.1\n", + " 4.8\n", + " 23-Jun\n", + " \n", + " \n", + " Bangladeshi or British Bangladeshi\n", + " 63\n", + " 40.9\n", + " 154\n", + " 36.4\n", + " 4.5\n", + " 01-Jul\n", " \n", " \n", - " Bangladeshi or British Bangladeshi\n", - " 56\n", - " 40.0\n", - " 140\n", - " 35\n", - " 5\n", - " 08-Jun\n", + " Caribbean\n", + " 84\n", + " 52.2\n", + " 161\n", + " 47.8\n", + " 4.4\n", + " 15-Jun\n", " \n", " \n", - " Caribbean\n", - " 56\n", - " 40.0\n", + " Chinese\n", + " 49\n", + " 35.0\n", " 140\n", - " 40\n", + " 35\n", " 0\n", " unknown\n", " \n", " \n", - " Chinese\n", - " 56\n", - " 47.1\n", - " 119\n", - " 41.2\n", - " 5.9\n", - " 19-May\n", - " \n", - " \n", " Other\n", - " 56\n", - " 42.1\n", - " 133\n", - " 36.8\n", - " 5.3\n", - " 01-Jun\n", + " 49\n", + " 38.9\n", + " 126\n", + " 38.9\n", + " 0\n", + " unknown\n", " \n", " \n", " Other Asian\n", - " 63\n", - " 45.0\n", - " 140\n", - " 40\n", - " 5\n", - " 01-Jun\n", + " 77\n", + " 47.8\n", + " 161\n", + " 43.5\n", + " 4.3\n", + " 23-Jun\n", " \n", " \n", " British or Mixed British\n", - " 56\n", - " 42.1\n", - " 133\n", - " 42.1\n", + " 42\n", + " 28.6\n", + " 147\n", + " 28.6\n", " 0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", - " 56\n", - " 44.4\n", - " 126\n", - " 44.4\n", + " 49\n", + " 35.0\n", + " 140\n", + " 35\n", " 0\n", " unknown\n", " \n", " \n", " Irish\n", - " 49\n", - " 36.8\n", - " 133\n", - " 36.8\n", - " 0\n", - " unknown\n", + " 56\n", + " 34.8\n", + " 161\n", + " 30.4\n", + " 4.4\n", + " 12-Jul\n", " \n", " \n", " Other Black\n", - " 63\n", - " 37.5\n", - " 168\n", - " 33.3\n", - " 4.2\n", - " 25-Jun\n", + " 77\n", + " 50.0\n", + " 154\n", + " 45.5\n", + " 4.5\n", + " 17-Jun\n", " \n", " \n", " Other White\n", - " 56\n", - " 44.4\n", - " 126\n", - " 44.4\n", - " 0\n", - " unknown\n", + " 63\n", + " 40.9\n", + " 154\n", + " 36.4\n", + " 4.5\n", + " 01-Jul\n", " \n", " \n", " Other mixed\n", - " 70\n", - " 47.6\n", - " 147\n", - " 42.9\n", - " 4.7\n", - " 01-Jun\n", - " \n", - " \n", - " Pakistani or British Pakistani\n", - " 56\n", - " 42.1\n", + " 49\n", + " 36.8\n", " 133\n", - " 42.1\n", + " 36.8\n", " 0\n", " unknown\n", " \n", " \n", + " Pakistani or British Pakistani\n", + " 70\n", + " 45.5\n", + " 154\n", + " 40.9\n", + " 4.6\n", + " 22-Jun\n", + " \n", + " \n", " Unknown\n", - " 140\n", + " 133\n", " 34.5\n", - " 406\n", - " 32.8\n", - " 1.7\n", + " 385\n", + " 32.7\n", + " 1.8\n", " unknown\n", " \n", " \n", " White + Asian\n", - " 63\n", - " 40.9\n", - " 154\n", - " 36.4\n", - " 4.5\n", - " 14-Jun\n", + " 56\n", + " 42.1\n", + " 133\n", + " 36.8\n", + " 5.3\n", + " 18-Jun\n", " \n", " \n", " White + Black African\n", " 56\n", - " 38.1\n", - " 147\n", - " 33.3\n", - " 4.8\n", - " 13-Jun\n", + " 44.4\n", + " 126\n", + " 44.4\n", + " 0\n", + " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 63\n", - " 39.1\n", - " 161\n", - " 34.8\n", - " 4.3\n", - " 20-Jun\n", + " 49\n", + " 35.0\n", + " 140\n", + " 30\n", + " 5\n", + " 02-Jul\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 203\n", - " 43.3\n", - " 469\n", - " 40.3\n", - " 3\n", - " 16-Jul\n", + " 210\n", + " 39.5\n", + " 532\n", + " 38.2\n", + " 1.3\n", + " unknown\n", " \n", " \n", " 2\n", - " 196\n", - " 39.4\n", - " 497\n", - " 36.6\n", - " 2.8\n", - " 03-Aug\n", + " 210\n", + " 39.5\n", + " 532\n", + " 38.2\n", + " 1.3\n", + " unknown\n", " \n", " \n", " 3\n", - " 189\n", - " 38.0\n", - " 497\n", - " 35.2\n", + " 210\n", + " 41.7\n", + " 504\n", + " 38.9\n", " 2.8\n", - " 07-Aug\n", + " 14-Aug\n", " \n", " \n", " 4\n", " 189\n", - " 38.0\n", - " 497\n", - " 36.6\n", - " 1.4\n", - " unknown\n", + " 37.5\n", + " 504\n", + " 34.7\n", + " 2.8\n", + " 25-Aug\n", " \n", " \n", " 5 Least deprived\n", - " 203\n", - " 39.2\n", + " 217\n", + " 41.9\n", " 518\n", - " 37.8\n", + " 40.5\n", " 1.4\n", " unknown\n", " \n", " \n", " Unknown\n", - " 63\n", - " 42.9\n", - " 147\n", - " 42.9\n", + " 42\n", + " 31.6\n", + " 133\n", + " 31.6\n", " 0\n", " unknown\n", " \n", " \n", " bmi\n", " 30+\n", - " 350\n", - " 42.0\n", - " 833\n", - " 39.5\n", - " 2.5\n", - " 11-Aug\n", + " 329\n", + " 40.5\n", + " 812\n", + " 37.9\n", + " 2.6\n", + " 27-Aug\n", " \n", " \n", " under 30\n", - " 693\n", - " 38.5\n", - " 1799\n", - " 36.6\n", - " 1.9\n", + " 749\n", + " 39.3\n", + " 1904\n", + " 37.5\n", + " 1.8\n", " unknown\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1029\n", - " 39.5\n", - " 2604\n", - " 37.4\n", + " 1064\n", + " 39.6\n", + " 2688\n", + " 37.5\n", " 2.1\n", - " 14-Sep\n", + " 01-Oct\n", " \n", " \n", " yes\n", " 14\n", - " 66.7\n", - " 21\n", - " 66.7\n", + " 50.0\n", + " 28\n", + " 50\n", " 0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1043\n", - " 39.9\n", - " 2611\n", + " 1071\n", + " 39.8\n", + " 2688\n", " 37.8\n", - " 2.1\n", - " 13-Sep\n", + " 2\n", + " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 21\n", - " 0\n", + " 7\n", + " 25.0\n", + " 28\n", + " 25\n", " 0\n", " unknown\n", " \n", " \n", " dmards\n", " no\n", - " 1036\n", - " 39.9\n", - " 2597\n", + " 1071\n", + " 39.7\n", + " 2695\n", " 37.7\n", - " 2.2\n", - " 05-Sep\n", + " 2\n", + " unknown\n", " \n", " \n", " yes\n", @@ -5548,88 +5548,88 @@ " \n", " dementia\n", " no\n", - " 1029\n", - " 39.5\n", - " 2604\n", - " 37.4\n", + " 1057\n", + " 39.4\n", + " 2681\n", + " 37.3\n", " 2.1\n", - " 14-Sep\n", + " 01-Oct\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50\n", + " 21\n", + " 60.0\n", + " 35\n", + " 60\n", " 0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1036\n", + " 1071\n", " 39.8\n", - " 2604\n", - " 37.6\n", - " 2.2\n", - " 05-Sep\n", + " 2688\n", + " 37.8\n", + " 2\n", + " unknown\n", " \n", " \n", " yes\n", - " 0\n", - " 0.0\n", - " 21\n", - " 0\n", + " 7\n", + " 25.0\n", + " 28\n", + " 25\n", " 0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1036\n", - " 39.9\n", - " 2597\n", - " 37.7\n", - " 2.2\n", - " 05-Sep\n", + " 1064\n", + " 39.7\n", + " 2681\n", + " 37.6\n", + " 2.1\n", + " 30-Sep\n", " \n", " \n", " yes\n", - " 7\n", - " 25.0\n", - " 28\n", - " 25\n", + " 14\n", + " 40.0\n", + " 35\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " chemo_or_radio\n", " no\n", - " 1036\n", - " 39.8\n", - " 2604\n", + " 1064\n", + " 39.7\n", + " 2681\n", " 37.6\n", - " 2.2\n", - " 05-Sep\n", + " 2.1\n", + " 30-Sep\n", " \n", " \n", " yes\n", - " 7\n", - " 25.0\n", - " 28\n", - " 25\n", + " 14\n", + " 40.0\n", + " 35\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " lung_cancer\n", " no\n", - " 1029\n", + " 1064\n", " 39.7\n", - " 2590\n", + " 2681\n", " 37.6\n", " 2.1\n", - " 13-Sep\n", + " 30-Sep\n", " \n", " \n", " yes\n", @@ -5643,38 +5643,38 @@ " \n", " cancer_excl_lung_and_haem\n", " no\n", - " 1036\n", - " 39.9\n", - " 2597\n", - " 37.7\n", - " 2.2\n", - " 05-Sep\n", + " 1064\n", + " 39.6\n", + " 2688\n", + " 37.5\n", + " 2.1\n", + " 01-Oct\n", " \n", " \n", " yes\n", - " 7\n", - " 25.0\n", + " 14\n", + " 50.0\n", " 28\n", - " 25\n", + " 50\n", " 0\n", " unknown\n", " \n", " \n", " haematological_cancer\n", " no\n", - " 1029\n", - " 39.5\n", - " 2604\n", - " 37.4\n", - " 2.1\n", - " 14-Sep\n", + " 1071\n", + " 39.7\n", + " 2695\n", + " 37.7\n", + " 2\n", + " unknown\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50\n", + " 7\n", + " 33.3\n", + " 21\n", + " 33.3\n", " 0\n", " unknown\n", " \n", @@ -5685,287 +5685,287 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1044 \n", - "sex F 532 \n", - " M 511 \n", + "overall overall 1079 \n", + "sex F 546 \n", + " M 532 \n", "ethnicity_6_groups Black 175 \n", - " Mixed 154 \n", + " Mixed 175 \n", " Other 175 \n", - " South Asian 196 \n", - " Unknown 161 \n", - " White 189 \n", - "ethnicity_16_groups African 42 \n", - " Bangladeshi or British Bangladeshi 56 \n", - " Caribbean 56 \n", - " Chinese 56 \n", - " Other 56 \n", - " Other Asian 63 \n", - " British or Mixed British 56 \n", - " Indian or British Indian 56 \n", - " Irish 49 \n", - " Other Black 63 \n", - " Other White 56 \n", - " Other mixed 70 \n", - " Pakistani or British Pakistani 56 \n", - " Unknown 140 \n", - " White + Asian 63 \n", + " South Asian 182 \n", + " Unknown 168 \n", + " White 210 \n", + "ethnicity_16_groups African 63 \n", + " Bangladeshi or British Bangladeshi 63 \n", + " Caribbean 84 \n", + " Chinese 49 \n", + " Other 49 \n", + " Other Asian 77 \n", + " British or Mixed British 42 \n", + " Indian or British Indian 49 \n", + " Irish 56 \n", + " Other Black 77 \n", + " Other White 63 \n", + " Other mixed 49 \n", + " Pakistani or British Pakistani 70 \n", + " Unknown 133 \n", + " White + Asian 56 \n", " White + Black African 56 \n", - " White + Black Caribbean 63 \n", - "imd_categories 1 Most deprived 203 \n", - " 2 196 \n", - " 3 189 \n", + " White + Black Caribbean 49 \n", + "imd_categories 1 Most deprived 210 \n", + " 2 210 \n", + " 3 210 \n", " 4 189 \n", - " 5 Least deprived 203 \n", - " Unknown 63 \n", - "bmi 30+ 350 \n", - " under 30 693 \n", - "chronic_cardiac_disease no 1029 \n", + " 5 Least deprived 217 \n", + " Unknown 42 \n", + "bmi 30+ 329 \n", + " under 30 749 \n", + "chronic_cardiac_disease no 1064 \n", " yes 14 \n", - "current_copd no 1043 \n", - " yes 0 \n", - "dmards no 1036 \n", + "current_copd no 1071 \n", " yes 7 \n", - "dementia no 1029 \n", - " yes 14 \n", - "psychosis_schiz_bipolar no 1036 \n", - " yes 0 \n", - "ssri no 1036 \n", + "dmards no 1071 \n", " yes 7 \n", - "chemo_or_radio no 1036 \n", + "dementia no 1057 \n", + " yes 21 \n", + "psychosis_schiz_bipolar no 1071 \n", " yes 7 \n", - "lung_cancer no 1029 \n", + "ssri no 1064 \n", " yes 14 \n", - "cancer_excl_lung_and_haem no 1036 \n", - " yes 7 \n", - "haematological_cancer no 1029 \n", + "chemo_or_radio no 1064 \n", + " yes 14 \n", + "lung_cancer no 1064 \n", " yes 14 \n", + "cancer_excl_lung_and_haem no 1064 \n", + " yes 14 \n", + "haematological_cancer no 1071 \n", + " yes 7 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 39.7 2632 \n", - "sex F 39.2 1358 \n", - " M 40.1 1274 \n", - "ethnicity_6_groups Black 39.7 441 \n", - " Mixed 37.9 406 \n", - " Other 37.3 469 \n", - " South Asian 40.6 483 \n", - " Unknown 41.1 392 \n", - " White 42.9 441 \n", - "ethnicity_16_groups African 35.3 119 \n", - " Bangladeshi or British Bangladeshi 40.0 140 \n", - " Caribbean 40.0 140 \n", - " Chinese 47.1 119 \n", - " Other 42.1 133 \n", - " Other Asian 45.0 140 \n", - " British or Mixed British 42.1 133 \n", - " Indian or British Indian 44.4 126 \n", - " Irish 36.8 133 \n", - " Other Black 37.5 168 \n", - " Other White 44.4 126 \n", - " Other mixed 47.6 147 \n", - " Pakistani or British Pakistani 42.1 133 \n", - " Unknown 34.5 406 \n", - " White + Asian 40.9 154 \n", - " White + Black African 38.1 147 \n", - " White + Black Caribbean 39.1 161 \n", - "imd_categories 1 Most deprived 43.3 469 \n", - " 2 39.4 497 \n", - " 3 38.0 497 \n", - " 4 38.0 497 \n", - " 5 Least deprived 39.2 518 \n", - " Unknown 42.9 147 \n", - "bmi 30+ 42.0 833 \n", - " under 30 38.5 1799 \n", - "chronic_cardiac_disease no 39.5 2604 \n", - " yes 66.7 21 \n", - "current_copd no 39.9 2611 \n", - " yes 0.0 21 \n", - "dmards no 39.9 2597 \n", - " yes 25.0 28 \n", - "dementia no 39.5 2604 \n", + "overall overall 39.7 2716 \n", + "sex F 38.6 1414 \n", + " M 40.9 1302 \n", + "ethnicity_6_groups Black 38.5 455 \n", + " Mixed 39.1 448 \n", + " Other 37.9 462 \n", + " South Asian 40.0 455 \n", + " Unknown 42.1 399 \n", + " White 41.7 504 \n", + "ethnicity_16_groups African 42.9 147 \n", + " Bangladeshi or British Bangladeshi 40.9 154 \n", + " Caribbean 52.2 161 \n", + " Chinese 35.0 140 \n", + " Other 38.9 126 \n", + " Other Asian 47.8 161 \n", + " British or Mixed British 28.6 147 \n", + " Indian or British Indian 35.0 140 \n", + " Irish 34.8 161 \n", + " Other Black 50.0 154 \n", + " Other White 40.9 154 \n", + " Other mixed 36.8 133 \n", + " Pakistani or British Pakistani 45.5 154 \n", + " Unknown 34.5 385 \n", + " White + Asian 42.1 133 \n", + " White + Black African 44.4 126 \n", + " White + Black Caribbean 35.0 140 \n", + "imd_categories 1 Most deprived 39.5 532 \n", + " 2 39.5 532 \n", + " 3 41.7 504 \n", + " 4 37.5 504 \n", + " 5 Least deprived 41.9 518 \n", + " Unknown 31.6 133 \n", + "bmi 30+ 40.5 812 \n", + " under 30 39.3 1904 \n", + "chronic_cardiac_disease no 39.6 2688 \n", " yes 50.0 28 \n", - "psychosis_schiz_bipolar no 39.8 2604 \n", - " yes 0.0 21 \n", - "ssri no 39.9 2597 \n", + "current_copd no 39.8 2688 \n", " yes 25.0 28 \n", - "chemo_or_radio no 39.8 2604 \n", + "dmards no 39.7 2695 \n", " yes 25.0 28 \n", - "lung_cancer no 39.7 2590 \n", - " yes 40.0 35 \n", - "cancer_excl_lung_and_haem no 39.9 2597 \n", + "dementia no 39.4 2681 \n", + " yes 60.0 35 \n", + "psychosis_schiz_bipolar no 39.8 2688 \n", " yes 25.0 28 \n", - "haematological_cancer no 39.5 2604 \n", + "ssri no 39.7 2681 \n", + " yes 40.0 35 \n", + "chemo_or_radio no 39.7 2681 \n", + " yes 40.0 35 \n", + "lung_cancer no 39.7 2681 \n", + " yes 40.0 35 \n", + "cancer_excl_lung_and_haem no 39.6 2688 \n", " yes 50.0 28 \n", + "haematological_cancer no 39.7 2695 \n", + " yes 33.3 21 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 37.5 \n", - "sex F 37.6 \n", - " M 37.9 \n", - "ethnicity_6_groups Black 34.9 \n", - " Mixed 36.2 \n", - " Other 34.3 \n", - " South Asian 37.7 \n", - " Unknown 39.3 \n", - " White 41.3 \n", - "ethnicity_16_groups African 29.4 \n", - " Bangladeshi or British Bangladeshi 35 \n", - " Caribbean 40 \n", - " Chinese 41.2 \n", - " Other 36.8 \n", - " Other Asian 40 \n", - " British or Mixed British 42.1 \n", - " Indian or British Indian 44.4 \n", - " Irish 36.8 \n", - " Other Black 33.3 \n", - " Other White 44.4 \n", - " Other mixed 42.9 \n", - " Pakistani or British Pakistani 42.1 \n", - " Unknown 32.8 \n", - " White + Asian 36.4 \n", - " White + Black African 33.3 \n", - " White + Black Caribbean 34.8 \n", - "imd_categories 1 Most deprived 40.3 \n", - " 2 36.6 \n", - " 3 35.2 \n", - " 4 36.6 \n", - " 5 Least deprived 37.8 \n", - " Unknown 42.9 \n", - "bmi 30+ 39.5 \n", - " under 30 36.6 \n", - "chronic_cardiac_disease no 37.4 \n", - " yes 66.7 \n", + "overall overall 37.6 \n", + "sex F 36.6 \n", + " M 38.7 \n", + "ethnicity_6_groups Black 36.9 \n", + " Mixed 37.5 \n", + " Other 36.4 \n", + " South Asian 36.9 \n", + " Unknown 38.6 \n", + " White 38.9 \n", + "ethnicity_16_groups African 38.1 \n", + " Bangladeshi or British Bangladeshi 36.4 \n", + " Caribbean 47.8 \n", + " Chinese 35 \n", + " Other 38.9 \n", + " Other Asian 43.5 \n", + " British or Mixed British 28.6 \n", + " Indian or British Indian 35 \n", + " Irish 30.4 \n", + " Other Black 45.5 \n", + " Other White 36.4 \n", + " Other mixed 36.8 \n", + " Pakistani or British Pakistani 40.9 \n", + " Unknown 32.7 \n", + " White + Asian 36.8 \n", + " White + Black African 44.4 \n", + " White + Black Caribbean 30 \n", + "imd_categories 1 Most deprived 38.2 \n", + " 2 38.2 \n", + " 3 38.9 \n", + " 4 34.7 \n", + " 5 Least deprived 40.5 \n", + " Unknown 31.6 \n", + "bmi 30+ 37.9 \n", + " under 30 37.5 \n", + "chronic_cardiac_disease no 37.5 \n", + " yes 50 \n", "current_copd no 37.8 \n", - " yes 0 \n", + " yes 25 \n", "dmards no 37.7 \n", " yes 25 \n", - "dementia no 37.4 \n", - " yes 50 \n", - "psychosis_schiz_bipolar no 37.6 \n", - " yes 0 \n", - "ssri no 37.7 \n", + "dementia no 37.3 \n", + " yes 60 \n", + "psychosis_schiz_bipolar no 37.8 \n", " yes 25 \n", + "ssri no 37.6 \n", + " yes 40 \n", "chemo_or_radio no 37.6 \n", - " yes 25 \n", + " yes 40 \n", "lung_cancer no 37.6 \n", " yes 40 \n", - "cancer_excl_lung_and_haem no 37.7 \n", - " yes 25 \n", - "haematological_cancer no 37.4 \n", + "cancer_excl_lung_and_haem no 37.5 \n", " yes 50 \n", + "haematological_cancer no 37.7 \n", + " yes 33.3 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 2.2 \n", - "sex F 1.6 \n", + "overall overall 2.1 \n", + "sex F 2 \n", " M 2.2 \n", - "ethnicity_6_groups Black 4.8 \n", - " Mixed 1.7 \n", - " Other 3 \n", - " South Asian 2.9 \n", - " Unknown 1.8 \n", - " White 1.6 \n", - "ethnicity_16_groups African 5.9 \n", - " Bangladeshi or British Bangladeshi 5 \n", - " Caribbean 0 \n", - " Chinese 5.9 \n", - " Other 5.3 \n", - " Other Asian 5 \n", + "ethnicity_6_groups Black 1.6 \n", + " Mixed 1.6 \n", + " Other 1.5 \n", + " South Asian 3.1 \n", + " Unknown 3.5 \n", + " White 2.8 \n", + "ethnicity_16_groups African 4.8 \n", + " Bangladeshi or British Bangladeshi 4.5 \n", + " Caribbean 4.4 \n", + " Chinese 0 \n", + " Other 0 \n", + " Other Asian 4.3 \n", " British or Mixed British 0 \n", " Indian or British Indian 0 \n", - " Irish 0 \n", - " Other Black 4.2 \n", - " Other White 0 \n", - " Other mixed 4.7 \n", - " Pakistani or British Pakistani 0 \n", - " Unknown 1.7 \n", - " White + Asian 4.5 \n", - " White + Black African 4.8 \n", - " White + Black Caribbean 4.3 \n", - "imd_categories 1 Most deprived 3 \n", - " 2 2.8 \n", + " Irish 4.4 \n", + " Other Black 4.5 \n", + " Other White 4.5 \n", + " Other mixed 0 \n", + " Pakistani or British Pakistani 4.6 \n", + " Unknown 1.8 \n", + " White + Asian 5.3 \n", + " White + Black African 0 \n", + " White + Black Caribbean 5 \n", + "imd_categories 1 Most deprived 1.3 \n", + " 2 1.3 \n", " 3 2.8 \n", - " 4 1.4 \n", + " 4 2.8 \n", " 5 Least deprived 1.4 \n", " Unknown 0 \n", - "bmi 30+ 2.5 \n", - " under 30 1.9 \n", + "bmi 30+ 2.6 \n", + " under 30 1.8 \n", "chronic_cardiac_disease no 2.1 \n", " yes 0 \n", - "current_copd no 2.1 \n", + "current_copd no 2 \n", " yes 0 \n", - "dmards no 2.2 \n", + "dmards no 2 \n", " yes 0 \n", "dementia no 2.1 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 2.2 \n", + "psychosis_schiz_bipolar no 2 \n", " yes 0 \n", - "ssri no 2.2 \n", + "ssri no 2.1 \n", " yes 0 \n", - "chemo_or_radio no 2.2 \n", + "chemo_or_radio no 2.1 \n", " yes 0 \n", "lung_cancer no 2.1 \n", " yes 0 \n", - "cancer_excl_lung_and_haem no 2.2 \n", + "cancer_excl_lung_and_haem no 2.1 \n", " yes 0 \n", - "haematological_cancer no 2.1 \n", + "haematological_cancer no 2 \n", " yes 0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 06-Sep \n", + "overall overall 30-Sep \n", "sex F unknown \n", - " M 04-Sep \n", - "ethnicity_6_groups Black 11-Jun \n", + " M 19-Sep \n", + "ethnicity_6_groups Black unknown \n", " Mixed unknown \n", - " Other 30-Jul \n", - " South Asian 27-Jul \n", - " Unknown unknown \n", - " White unknown \n", - "ethnicity_16_groups African 02-Jun \n", - " Bangladeshi or British Bangladeshi 08-Jun \n", - " Caribbean unknown \n", - " Chinese 19-May \n", - " Other 01-Jun \n", - " Other Asian 01-Jun \n", + " Other unknown \n", + " South Asian 06-Aug \n", + " Unknown 20-Jul \n", + " White 14-Aug \n", + "ethnicity_16_groups African 23-Jun \n", + " Bangladeshi or British Bangladeshi 01-Jul \n", + " Caribbean 15-Jun \n", + " Chinese unknown \n", + " Other unknown \n", + " Other Asian 23-Jun \n", " British or Mixed British unknown \n", " Indian or British Indian unknown \n", - " Irish unknown \n", - " Other Black 25-Jun \n", - " Other White unknown \n", - " Other mixed 01-Jun \n", - " Pakistani or British Pakistani unknown \n", + " Irish 12-Jul \n", + " Other Black 17-Jun \n", + " Other White 01-Jul \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani 22-Jun \n", " Unknown unknown \n", - " White + Asian 14-Jun \n", - " White + Black African 13-Jun \n", - " White + Black Caribbean 20-Jun \n", - "imd_categories 1 Most deprived 16-Jul \n", - " 2 03-Aug \n", - " 3 07-Aug \n", - " 4 unknown \n", + " White + Asian 18-Jun \n", + " White + Black African unknown \n", + " White + Black Caribbean 02-Jul \n", + "imd_categories 1 Most deprived unknown \n", + " 2 unknown \n", + " 3 14-Aug \n", + " 4 25-Aug \n", " 5 Least deprived unknown \n", " Unknown unknown \n", - "bmi 30+ 11-Aug \n", + "bmi 30+ 27-Aug \n", " under 30 unknown \n", - "chronic_cardiac_disease no 14-Sep \n", + "chronic_cardiac_disease no 01-Oct \n", " yes unknown \n", - "current_copd no 13-Sep \n", + "current_copd no unknown \n", " yes unknown \n", - "dmards no 05-Sep \n", + "dmards no unknown \n", " yes unknown \n", - "dementia no 14-Sep \n", + "dementia no 01-Oct \n", " yes unknown \n", - "psychosis_schiz_bipolar no 05-Sep \n", + "psychosis_schiz_bipolar no unknown \n", " yes unknown \n", - "ssri no 05-Sep \n", + "ssri no 30-Sep \n", " yes unknown \n", - "chemo_or_radio no 05-Sep \n", + "chemo_or_radio no 30-Sep \n", " yes unknown \n", - "lung_cancer no 13-Sep \n", + "lung_cancer no 30-Sep \n", " yes unknown \n", - "cancer_excl_lung_and_haem no 05-Sep \n", + "cancer_excl_lung_and_haem no 01-Oct \n", " yes unknown \n", - "haematological_cancer no 14-Sep \n", + "haematological_cancer no unknown \n", " yes unknown " ] }, @@ -5987,7 +5987,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout among **55-59** population up to 30 Mar 2021" + "## COVID vaccination rollout among **55-59** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -6053,343 +6053,343 @@ " \n", " overall\n", " overall\n", - " 1300\n", - " 41.5\n", - " 3136\n", - " 38.8\n", - " 2.7\n", - " 02-Aug\n", + " 1270\n", + " 39.8\n", + " 3192\n", + " 37.5\n", + " 2.3\n", + " 15-Sep\n", " \n", " \n", " sex\n", " F\n", - " 707\n", - " 43.0\n", + " 637\n", + " 38.7\n", " 1645\n", - " 39.1\n", - " 3.9\n", - " 22-Jun\n", + " 36.2\n", + " 2.5\n", + " 06-Sep\n", " \n", " \n", " M\n", - " 595\n", - " 39.9\n", - " 1491\n", - " 38.5\n", - " 1.4\n", + " 630\n", + " 40.7\n", + " 1547\n", + " 38.9\n", + " 1.8\n", " unknown\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 217\n", - " 40.8\n", - " 532\n", - " 38.2\n", - " 2.6\n", - " 09-Aug\n", + " 224\n", + " 41.0\n", + " 546\n", + " 38.5\n", + " 2.5\n", + " 31-Aug\n", " \n", " \n", " Mixed\n", " 210\n", - " 41.1\n", - " 511\n", - " 38.4\n", - " 2.7\n", - " 03-Aug\n", + " 38.5\n", + " 546\n", + " 35.9\n", + " 2.6\n", + " 01-Sep\n", " \n", " \n", " Other\n", - " 231\n", - " 43.4\n", - " 532\n", - " 40.8\n", - " 2.6\n", - " 02-Aug\n", + " 203\n", + " 39.2\n", + " 518\n", + " 37.8\n", + " 1.4\n", + " unknown\n", " \n", " \n", " South Asian\n", - " 252\n", - " 42.4\n", - " 595\n", - " 40\n", - " 2.4\n", - " 15-Aug\n", - " \n", - " \n", - " Unknown\n", - " 189\n", - " 41.5\n", - " 455\n", - " 38.5\n", - " 3\n", - " 21-Jul\n", + " 196\n", + " 37.3\n", + " 525\n", + " 36\n", + " 1.3\n", + " unknown\n", " \n", " \n", - " White\n", - " 203\n", - " 40.3\n", + " Unknown\n", + " 217\n", + " 43.1\n", " 504\n", - " 37.5\n", + " 40.3\n", " 2.8\n", - " 01-Aug\n", + " 11-Aug\n", + " \n", + " \n", + " White\n", + " 224\n", + " 40.5\n", + " 553\n", + " 38\n", + " 2.5\n", + " 01-Sep\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", - " 63\n", - " 36.0\n", + " 70\n", + " 40.0\n", " 175\n", - " 32\n", - " 4\n", - " 02-Jul\n", + " 40\n", + " 0\n", + " unknown\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", " 56\n", - " 34.8\n", - " 161\n", - " 30.4\n", - " 4.4\n", - " 25-Jun\n", + " 38.1\n", + " 147\n", + " 33.3\n", + " 4.8\n", + " 30-Jun\n", " \n", " \n", " Caribbean\n", - " 77\n", - " 44.0\n", + " 70\n", + " 40.0\n", " 175\n", - " 44\n", + " 40\n", " 0\n", " unknown\n", " \n", " \n", " Chinese\n", " 77\n", - " 44.0\n", - " 175\n", - " 40\n", - " 4\n", - " 18-Jun\n", + " 39.3\n", + " 196\n", + " 35.7\n", + " 3.6\n", + " 23-Jul\n", " \n", " \n", " Other\n", " 77\n", - " 45.8\n", - " 168\n", - " 41.7\n", - " 4.1\n", - " 13-Jun\n", + " 37.9\n", + " 203\n", + " 37.9\n", + " 0\n", + " unknown\n", " \n", " \n", " Other Asian\n", - " 77\n", - " 45.8\n", - " 168\n", - " 41.7\n", - " 4.1\n", - " 13-Jun\n", + " 70\n", + " 38.5\n", + " 182\n", + " 34.6\n", + " 3.9\n", + " 17-Jul\n", " \n", " \n", " British or Mixed British\n", - " 56\n", - " 34.8\n", - " 161\n", - " 30.4\n", - " 4.4\n", - " 25-Jun\n", + " 70\n", + " 41.7\n", + " 168\n", + " 37.5\n", + " 4.2\n", + " 05-Jul\n", " \n", " \n", " Indian or British Indian\n", - " 84\n", - " 48.0\n", - " 175\n", - " 48\n", + " 63\n", + " 40.9\n", + " 154\n", + " 40.9\n", " 0\n", " unknown\n", " \n", " \n", " Irish\n", - " 84\n", - " 46.2\n", - " 182\n", - " 42.3\n", - " 3.9\n", - " 16-Jun\n", + " 63\n", + " 40.9\n", + " 154\n", + " 36.4\n", + " 4.5\n", + " 01-Jul\n", " \n", " \n", " Other Black\n", - " 70\n", - " 41.7\n", - " 168\n", - " 37.5\n", - " 4.2\n", - " 18-Jun\n", + " 63\n", + " 39.1\n", + " 161\n", + " 34.8\n", + " 4.3\n", + " 07-Jul\n", " \n", " \n", " Other White\n", - " 84\n", - " 44.4\n", - " 189\n", - " 40.7\n", - " 3.7\n", - " 24-Jun\n", + " 77\n", + " 42.3\n", + " 182\n", + " 38.5\n", + " 3.8\n", + " 12-Jul\n", " \n", " \n", " Other mixed\n", - " 56\n", - " 40.0\n", - " 140\n", - " 35\n", - " 5\n", - " 08-Jun\n", + " 63\n", + " 37.5\n", + " 168\n", + " 37.5\n", + " 0\n", + " unknown\n", " \n", " \n", " Pakistani or British Pakistani\n", " 63\n", - " 40.9\n", - " 154\n", - " 36.4\n", - " 4.5\n", - " 14-Jun\n", + " 37.5\n", + " 168\n", + " 37.5\n", + " 0\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 182\n", - " 37.7\n", + " 196\n", + " 40.6\n", " 483\n", - " 36.2\n", - " 1.5\n", - " unknown\n", + " 37.7\n", + " 2.9\n", + " 13-Aug\n", " \n", " \n", " White + Asian\n", - " 77\n", - " 45.8\n", - " 168\n", - " 41.7\n", - " 4.1\n", - " 13-Jun\n", + " 63\n", + " 39.1\n", + " 161\n", + " 39.1\n", + " 0\n", + " unknown\n", " \n", " \n", " White + Black African\n", " 56\n", - " 42.1\n", - " 133\n", - " 36.8\n", - " 5.3\n", - " 01-Jun\n", + " 34.8\n", + " 161\n", + " 30.4\n", + " 4.4\n", + " 12-Jul\n", " \n", " \n", " White + Black Caribbean\n", - " 77\n", - " 47.8\n", - " 161\n", - " 43.5\n", - " 4.3\n", - " 06-Jun\n", + " 56\n", + " 38.1\n", + " 147\n", + " 38.1\n", + " 0\n", + " unknown\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 238\n", - " 40.0\n", + " 252\n", + " 42.4\n", " 595\n", - " 37.6\n", - " 2.4\n", - " 22-Aug\n", + " 38.8\n", + " 3.6\n", + " 17-Jul\n", " \n", " \n", " 2\n", - " 252\n", - " 41.9\n", - " 602\n", + " 238\n", " 39.5\n", - " 2.4\n", - " 17-Aug\n", + " 602\n", + " 37.2\n", + " 2.3\n", + " 16-Sep\n", " \n", " \n", " 3\n", - " 252\n", - " 43.4\n", - " 581\n", - " 39.8\n", - " 3.6\n", - " 28-Jun\n", + " 245\n", + " 40.7\n", + " 602\n", + " 37.2\n", + " 3.5\n", + " 23-Jul\n", " \n", " \n", " 4\n", - " 245\n", - " 38.5\n", - " 637\n", - " 36.3\n", - " 2.2\n", - " 09-Sep\n", + " 231\n", + " 37.5\n", + " 616\n", + " 35.2\n", + " 2.3\n", + " 22-Sep\n", " \n", " \n", " 5 Least deprived\n", - " 238\n", - " 44.7\n", - " 532\n", - " 42.1\n", - " 2.6\n", - " 29-Jul\n", + " 252\n", + " 41.4\n", + " 609\n", + " 39.1\n", + " 2.3\n", + " 10-Sep\n", " \n", " \n", " Unknown\n", - " 77\n", - " 42.3\n", - " 182\n", - " 38.5\n", - " 3.8\n", - " 25-Jun\n", + " 63\n", + " 37.5\n", + " 168\n", + " 33.3\n", + " 4.2\n", + " 12-Jul\n", " \n", " \n", " bmi\n", - " 30+\n", - " 392\n", - " 41.2\n", - " 952\n", - " 39\n", - " 2.2\n", - " 01-Sep\n", + " 30+\n", + " 371\n", + " 40.2\n", + " 924\n", + " 37.9\n", + " 2.3\n", + " 14-Sep\n", " \n", " \n", " under 30\n", - " 910\n", - " 41.7\n", - " 2184\n", - " 38.8\n", - " 2.9\n", - " 24-Jul\n", + " 896\n", + " 39.5\n", + " 2268\n", + " 37.3\n", + " 2.2\n", + " 23-Sep\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1288\n", - " 41.4\n", - " 3108\n", - " 38.7\n", - " 2.7\n", - " 03-Aug\n", + " 1260\n", + " 39.8\n", + " 3164\n", + " 37.6\n", + " 2.2\n", + " 22-Sep\n", " \n", " \n", " yes\n", - " 7\n", - " 25.0\n", + " 14\n", + " 50.0\n", " 28\n", " 25\n", - " 0\n", - " unknown\n", + " 25\n", + " 27-Apr\n", " \n", " \n", " current_copd\n", " no\n", - " 1288\n", - " 41.5\n", - " 3101\n", - " 38.8\n", - " 2.7\n", - " 02-Aug\n", + " 1253\n", + " 39.6\n", + " 3164\n", + " 37.4\n", + " 2.2\n", + " 23-Sep\n", " \n", " \n", " yes\n", @@ -6403,57 +6403,57 @@ " \n", " dmards\n", " no\n", - " 1288\n", - " 41.4\n", - " 3108\n", - " 38.7\n", - " 2.7\n", - " 03-Aug\n", + " 1260\n", + " 39.8\n", + " 3164\n", + " 37.4\n", + " 2.4\n", + " 09-Sep\n", " \n", " \n", " yes\n", - " 7\n", - " 25.0\n", + " 14\n", + " 50.0\n", " 28\n", - " 25\n", + " 50\n", " 0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1281\n", - " 41.2\n", - " 3108\n", - " 38.7\n", - " 2.5\n", - " 13-Aug\n", + " 1260\n", + " 39.9\n", + " 3157\n", + " 37.7\n", + " 2.2\n", + " 22-Sep\n", " \n", " \n", " yes\n", - " 14\n", - " 50.0\n", - " 28\n", - " 50\n", + " 7\n", + " 20.0\n", + " 35\n", + " 20\n", " 0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1288\n", - " 41.4\n", - " 3108\n", - " 38.7\n", - " 2.7\n", - " 03-Aug\n", + " 1253\n", + " 39.7\n", + " 3157\n", + " 37.5\n", + " 2.2\n", + " 23-Sep\n", " \n", " \n", " yes\n", " 14\n", - " 50.0\n", - " 28\n", - " 50\n", + " 40.0\n", + " 35\n", + " 40\n", " 0\n", " unknown\n", " \n", @@ -6464,237 +6464,237 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1300 \n", - "sex F 707 \n", - " M 595 \n", - "ethnicity_6_groups Black 217 \n", + "overall overall 1270 \n", + "sex F 637 \n", + " M 630 \n", + "ethnicity_6_groups Black 224 \n", " Mixed 210 \n", - " Other 231 \n", - " South Asian 252 \n", - " Unknown 189 \n", - " White 203 \n", - "ethnicity_16_groups African 63 \n", + " Other 203 \n", + " South Asian 196 \n", + " Unknown 217 \n", + " White 224 \n", + "ethnicity_16_groups African 70 \n", " Bangladeshi or British Bangladeshi 56 \n", - " Caribbean 77 \n", + " Caribbean 70 \n", " Chinese 77 \n", " Other 77 \n", - " Other Asian 77 \n", - " British or Mixed British 56 \n", - " Indian or British Indian 84 \n", - " Irish 84 \n", - " Other Black 70 \n", - " Other White 84 \n", - " Other mixed 56 \n", + " Other Asian 70 \n", + " British or Mixed British 70 \n", + " Indian or British Indian 63 \n", + " Irish 63 \n", + " Other Black 63 \n", + " Other White 77 \n", + " Other mixed 63 \n", " Pakistani or British Pakistani 63 \n", - " Unknown 182 \n", - " White + Asian 77 \n", + " Unknown 196 \n", + " White + Asian 63 \n", " White + Black African 56 \n", - " White + Black Caribbean 77 \n", - "imd_categories 1 Most deprived 238 \n", - " 2 252 \n", - " 3 252 \n", - " 4 245 \n", - " 5 Least deprived 238 \n", - " Unknown 77 \n", - "bmi 30+ 392 \n", - " under 30 910 \n", - "chronic_cardiac_disease no 1288 \n", - " yes 7 \n", - "current_copd no 1288 \n", + " White + Black Caribbean 56 \n", + "imd_categories 1 Most deprived 252 \n", + " 2 238 \n", + " 3 245 \n", + " 4 231 \n", + " 5 Least deprived 252 \n", + " Unknown 63 \n", + "bmi 30+ 371 \n", + " under 30 896 \n", + "chronic_cardiac_disease no 1260 \n", " yes 14 \n", - "dmards no 1288 \n", - " yes 7 \n", - "psychosis_schiz_bipolar no 1281 \n", + "current_copd no 1253 \n", " yes 14 \n", - "ssri no 1288 \n", + "dmards no 1260 \n", + " yes 14 \n", + "psychosis_schiz_bipolar no 1260 \n", + " yes 7 \n", + "ssri no 1253 \n", " yes 14 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 41.5 3136 \n", - "sex F 43.0 1645 \n", - " M 39.9 1491 \n", - "ethnicity_6_groups Black 40.8 532 \n", - " Mixed 41.1 511 \n", - " Other 43.4 532 \n", - " South Asian 42.4 595 \n", - " Unknown 41.5 455 \n", - " White 40.3 504 \n", - "ethnicity_16_groups African 36.0 175 \n", - " Bangladeshi or British Bangladeshi 34.8 161 \n", - " Caribbean 44.0 175 \n", - " Chinese 44.0 175 \n", - " Other 45.8 168 \n", - " Other Asian 45.8 168 \n", - " British or Mixed British 34.8 161 \n", - " Indian or British Indian 48.0 175 \n", - " Irish 46.2 182 \n", - " Other Black 41.7 168 \n", - " Other White 44.4 189 \n", - " Other mixed 40.0 140 \n", - " Pakistani or British Pakistani 40.9 154 \n", - " Unknown 37.7 483 \n", - " White + Asian 45.8 168 \n", - " White + Black African 42.1 133 \n", - " White + Black Caribbean 47.8 161 \n", - "imd_categories 1 Most deprived 40.0 595 \n", - " 2 41.9 602 \n", - " 3 43.4 581 \n", - " 4 38.5 637 \n", - " 5 Least deprived 44.7 532 \n", - " Unknown 42.3 182 \n", - "bmi 30+ 41.2 952 \n", - " under 30 41.7 2184 \n", - "chronic_cardiac_disease no 41.4 3108 \n", - " yes 25.0 28 \n", - "current_copd no 41.5 3101 \n", - " yes 40.0 35 \n", - "dmards no 41.4 3108 \n", - " yes 25.0 28 \n", - "psychosis_schiz_bipolar no 41.2 3108 \n", + "overall overall 39.8 3192 \n", + "sex F 38.7 1645 \n", + " M 40.7 1547 \n", + "ethnicity_6_groups Black 41.0 546 \n", + " Mixed 38.5 546 \n", + " Other 39.2 518 \n", + " South Asian 37.3 525 \n", + " Unknown 43.1 504 \n", + " White 40.5 553 \n", + "ethnicity_16_groups African 40.0 175 \n", + " Bangladeshi or British Bangladeshi 38.1 147 \n", + " Caribbean 40.0 175 \n", + " Chinese 39.3 196 \n", + " Other 37.9 203 \n", + " Other Asian 38.5 182 \n", + " British or Mixed British 41.7 168 \n", + " Indian or British Indian 40.9 154 \n", + " Irish 40.9 154 \n", + " Other Black 39.1 161 \n", + " Other White 42.3 182 \n", + " Other mixed 37.5 168 \n", + " Pakistani or British Pakistani 37.5 168 \n", + " Unknown 40.6 483 \n", + " White + Asian 39.1 161 \n", + " White + Black African 34.8 161 \n", + " White + Black Caribbean 38.1 147 \n", + "imd_categories 1 Most deprived 42.4 595 \n", + " 2 39.5 602 \n", + " 3 40.7 602 \n", + " 4 37.5 616 \n", + " 5 Least deprived 41.4 609 \n", + " Unknown 37.5 168 \n", + "bmi 30+ 40.2 924 \n", + " under 30 39.5 2268 \n", + "chronic_cardiac_disease no 39.8 3164 \n", " yes 50.0 28 \n", - "ssri no 41.4 3108 \n", + "current_copd no 39.6 3164 \n", + " yes 40.0 35 \n", + "dmards no 39.8 3164 \n", " yes 50.0 28 \n", + "psychosis_schiz_bipolar no 39.9 3157 \n", + " yes 20.0 35 \n", + "ssri no 39.7 3157 \n", + " yes 40.0 35 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 38.8 \n", - "sex F 39.1 \n", - " M 38.5 \n", - "ethnicity_6_groups Black 38.2 \n", - " Mixed 38.4 \n", - " Other 40.8 \n", - " South Asian 40 \n", - " Unknown 38.5 \n", - " White 37.5 \n", - "ethnicity_16_groups African 32 \n", - " Bangladeshi or British Bangladeshi 30.4 \n", - " Caribbean 44 \n", - " Chinese 40 \n", - " Other 41.7 \n", - " Other Asian 41.7 \n", - " British or Mixed British 30.4 \n", - " Indian or British Indian 48 \n", - " Irish 42.3 \n", - " Other Black 37.5 \n", - " Other White 40.7 \n", - " Other mixed 35 \n", - " Pakistani or British Pakistani 36.4 \n", - " Unknown 36.2 \n", - " White + Asian 41.7 \n", - " White + Black African 36.8 \n", - " White + Black Caribbean 43.5 \n", - "imd_categories 1 Most deprived 37.6 \n", - " 2 39.5 \n", - " 3 39.8 \n", - " 4 36.3 \n", - " 5 Least deprived 42.1 \n", - " Unknown 38.5 \n", - "bmi 30+ 39 \n", - " under 30 38.8 \n", - "chronic_cardiac_disease no 38.7 \n", + "overall overall 37.5 \n", + "sex F 36.2 \n", + " M 38.9 \n", + "ethnicity_6_groups Black 38.5 \n", + " Mixed 35.9 \n", + " Other 37.8 \n", + " South Asian 36 \n", + " Unknown 40.3 \n", + " White 38 \n", + "ethnicity_16_groups African 40 \n", + " Bangladeshi or British Bangladeshi 33.3 \n", + " Caribbean 40 \n", + " Chinese 35.7 \n", + " Other 37.9 \n", + " Other Asian 34.6 \n", + " British or Mixed British 37.5 \n", + " Indian or British Indian 40.9 \n", + " Irish 36.4 \n", + " Other Black 34.8 \n", + " Other White 38.5 \n", + " Other mixed 37.5 \n", + " Pakistani or British Pakistani 37.5 \n", + " Unknown 37.7 \n", + " White + Asian 39.1 \n", + " White + Black African 30.4 \n", + " White + Black Caribbean 38.1 \n", + "imd_categories 1 Most deprived 38.8 \n", + " 2 37.2 \n", + " 3 37.2 \n", + " 4 35.2 \n", + " 5 Least deprived 39.1 \n", + " Unknown 33.3 \n", + "bmi 30+ 37.9 \n", + " under 30 37.3 \n", + "chronic_cardiac_disease no 37.6 \n", " yes 25 \n", - "current_copd no 38.8 \n", + "current_copd no 37.4 \n", " yes 40 \n", - "dmards no 38.7 \n", - " yes 25 \n", - "psychosis_schiz_bipolar no 38.7 \n", - " yes 50 \n", - "ssri no 38.7 \n", + "dmards no 37.4 \n", " yes 50 \n", + "psychosis_schiz_bipolar no 37.7 \n", + " yes 20 \n", + "ssri no 37.5 \n", + " yes 40 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 2.7 \n", - "sex F 3.9 \n", - " M 1.4 \n", - "ethnicity_6_groups Black 2.6 \n", - " Mixed 2.7 \n", - " Other 2.6 \n", - " South Asian 2.4 \n", - " Unknown 3 \n", - " White 2.8 \n", - "ethnicity_16_groups African 4 \n", - " Bangladeshi or British Bangladeshi 4.4 \n", + "overall overall 2.3 \n", + "sex F 2.5 \n", + " M 1.8 \n", + "ethnicity_6_groups Black 2.5 \n", + " Mixed 2.6 \n", + " Other 1.4 \n", + " South Asian 1.3 \n", + " Unknown 2.8 \n", + " White 2.5 \n", + "ethnicity_16_groups African 0 \n", + " Bangladeshi or British Bangladeshi 4.8 \n", " Caribbean 0 \n", - " Chinese 4 \n", - " Other 4.1 \n", - " Other Asian 4.1 \n", - " British or Mixed British 4.4 \n", + " Chinese 3.6 \n", + " Other 0 \n", + " Other Asian 3.9 \n", + " British or Mixed British 4.2 \n", " Indian or British Indian 0 \n", - " Irish 3.9 \n", - " Other Black 4.2 \n", - " Other White 3.7 \n", - " Other mixed 5 \n", - " Pakistani or British Pakistani 4.5 \n", - " Unknown 1.5 \n", - " White + Asian 4.1 \n", - " White + Black African 5.3 \n", - " White + Black Caribbean 4.3 \n", - "imd_categories 1 Most deprived 2.4 \n", - " 2 2.4 \n", - " 3 3.6 \n", - " 4 2.2 \n", - " 5 Least deprived 2.6 \n", - " Unknown 3.8 \n", - "bmi 30+ 2.2 \n", - " under 30 2.9 \n", - "chronic_cardiac_disease no 2.7 \n", - " yes 0 \n", - "current_copd no 2.7 \n", + " Irish 4.5 \n", + " Other Black 4.3 \n", + " Other White 3.8 \n", + " Other mixed 0 \n", + " Pakistani or British Pakistani 0 \n", + " Unknown 2.9 \n", + " White + Asian 0 \n", + " White + Black African 4.4 \n", + " White + Black Caribbean 0 \n", + "imd_categories 1 Most deprived 3.6 \n", + " 2 2.3 \n", + " 3 3.5 \n", + " 4 2.3 \n", + " 5 Least deprived 2.3 \n", + " Unknown 4.2 \n", + "bmi 30+ 2.3 \n", + " under 30 2.2 \n", + "chronic_cardiac_disease no 2.2 \n", + " yes 25 \n", + "current_copd no 2.2 \n", " yes 0 \n", - "dmards no 2.7 \n", + "dmards no 2.4 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 2.5 \n", + "psychosis_schiz_bipolar no 2.2 \n", " yes 0 \n", - "ssri no 2.7 \n", + "ssri no 2.2 \n", " yes 0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 02-Aug \n", - "sex F 22-Jun \n", + "overall overall 15-Sep \n", + "sex F 06-Sep \n", " M unknown \n", - "ethnicity_6_groups Black 09-Aug \n", - " Mixed 03-Aug \n", - " Other 02-Aug \n", - " South Asian 15-Aug \n", - " Unknown 21-Jul \n", - " White 01-Aug \n", - "ethnicity_16_groups African 02-Jul \n", - " Bangladeshi or British Bangladeshi 25-Jun \n", + "ethnicity_6_groups Black 31-Aug \n", + " Mixed 01-Sep \n", + " Other unknown \n", + " South Asian unknown \n", + " Unknown 11-Aug \n", + " White 01-Sep \n", + "ethnicity_16_groups African unknown \n", + " Bangladeshi or British Bangladeshi 30-Jun \n", " Caribbean unknown \n", - " Chinese 18-Jun \n", - " Other 13-Jun \n", - " Other Asian 13-Jun \n", - " British or Mixed British 25-Jun \n", + " Chinese 23-Jul \n", + " Other unknown \n", + " Other Asian 17-Jul \n", + " British or Mixed British 05-Jul \n", " Indian or British Indian unknown \n", - " Irish 16-Jun \n", - " Other Black 18-Jun \n", - " Other White 24-Jun \n", - " Other mixed 08-Jun \n", - " Pakistani or British Pakistani 14-Jun \n", - " Unknown unknown \n", - " White + Asian 13-Jun \n", - " White + Black African 01-Jun \n", - " White + Black Caribbean 06-Jun \n", - "imd_categories 1 Most deprived 22-Aug \n", - " 2 17-Aug \n", - " 3 28-Jun \n", - " 4 09-Sep \n", - " 5 Least deprived 29-Jul \n", - " Unknown 25-Jun \n", - "bmi 30+ 01-Sep \n", - " under 30 24-Jul \n", - "chronic_cardiac_disease no 03-Aug \n", - " yes unknown \n", - "current_copd no 02-Aug \n", + " Irish 01-Jul \n", + " Other Black 07-Jul \n", + " Other White 12-Jul \n", + " Other mixed unknown \n", + " Pakistani or British Pakistani unknown \n", + " Unknown 13-Aug \n", + " White + Asian unknown \n", + " White + Black African 12-Jul \n", + " White + Black Caribbean unknown \n", + "imd_categories 1 Most deprived 17-Jul \n", + " 2 16-Sep \n", + " 3 23-Jul \n", + " 4 22-Sep \n", + " 5 Least deprived 10-Sep \n", + " Unknown 12-Jul \n", + "bmi 30+ 14-Sep \n", + " under 30 23-Sep \n", + "chronic_cardiac_disease no 22-Sep \n", + " yes 27-Apr \n", + "current_copd no 23-Sep \n", " yes unknown \n", - "dmards no 03-Aug \n", + "dmards no 09-Sep \n", " yes unknown \n", - "psychosis_schiz_bipolar no 13-Aug \n", + "psychosis_schiz_bipolar no 22-Sep \n", " yes unknown \n", - "ssri no 03-Aug \n", + "ssri no 23-Sep \n", " yes unknown " ] }, @@ -6716,7 +6716,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout among **50-54** population up to 30 Mar 2021" + "## COVID vaccination rollout among **50-54** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -6782,343 +6782,343 @@ " \n", " overall\n", " overall\n", - " 1306\n", - " 38.3\n", - " 3409\n", - " 35.7\n", - " 2.6\n", - " 16-Aug\n", + " 1378\n", + " 40.5\n", + " 3402\n", + " 38\n", + " 2.5\n", + " 01-Sep\n", " \n", " \n", " sex\n", " F\n", - " 658\n", - " 37.9\n", - " 1736\n", - " 35.5\n", - " 2.4\n", - " 28-Aug\n", + " 665\n", + " 38.8\n", + " 1715\n", + " 36.7\n", + " 2.1\n", + " 03-Oct\n", " \n", " \n", " M\n", - " 644\n", - " 38.5\n", - " 1673\n", - " 36\n", + " 707\n", + " 41.9\n", + " 1687\n", + " 39.4\n", " 2.5\n", - " 21-Aug\n", + " 28-Aug\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 231\n", - " 39.8\n", - " 581\n", - " 37.3\n", - " 2.5\n", - " 17-Aug\n", + " 245\n", + " 41.7\n", + " 588\n", + " 39.3\n", + " 2.4\n", + " 03-Sep\n", " \n", " \n", " Mixed\n", - " 217\n", - " 40.3\n", - " 539\n", - " 39\n", - " 1.3\n", - " unknown\n", + " 245\n", + " 40.2\n", + " 609\n", + " 37.9\n", + " 2.3\n", + " 14-Sep\n", " \n", " \n", " Other\n", - " 217\n", - " 37.8\n", - " 574\n", - " 35.4\n", - " 2.4\n", - " 29-Aug\n", + " 245\n", + " 40.7\n", + " 602\n", + " 38.4\n", + " 2.3\n", + " 13-Sep\n", " \n", " \n", " South Asian\n", - " 252\n", - " 39.1\n", - " 644\n", - " 37\n", - " 2.1\n", - " 15-Sep\n", + " 238\n", + " 41.5\n", + " 574\n", + " 40.2\n", + " 1.3\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 168\n", - " 34.8\n", - " 483\n", - " 31.9\n", + " 189\n", + " 39.7\n", + " 476\n", + " 36.8\n", " 2.9\n", - " 10-Aug\n", + " 15-Aug\n", " \n", " \n", " White\n", - " 224\n", - " 38.1\n", - " 588\n", - " 34.5\n", - " 3.6\n", - " 08-Jul\n", + " 210\n", + " 38.0\n", + " 553\n", + " 35.4\n", + " 2.6\n", + " 03-Sep\n", " \n", " \n", " ethnicity_16_groups\n", " African\n", " 77\n", - " 39.3\n", - " 196\n", - " 35.7\n", - " 3.6\n", - " 06-Jul\n", + " 44.0\n", + " 175\n", + " 40\n", + " 4\n", + " 05-Jul\n", " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 63\n", - " 36.0\n", + " 70\n", + " 40.0\n", " 175\n", - " 32\n", + " 36\n", " 4\n", - " 02-Jul\n", + " 12-Jul\n", " \n", " \n", " Caribbean\n", - " 56\n", - " 32.0\n", - " 175\n", - " 32\n", + " 70\n", + " 38.5\n", + " 182\n", + " 38.5\n", " 0\n", " unknown\n", " \n", " \n", " Chinese\n", " 63\n", - " 36.0\n", - " 175\n", - " 32\n", - " 4\n", - " 02-Jul\n", + " 39.1\n", + " 161\n", + " 34.8\n", + " 4.3\n", + " 07-Jul\n", " \n", " \n", " Other\n", - " 63\n", - " 37.5\n", - " 168\n", - " 37.5\n", + " 77\n", + " 40.7\n", + " 189\n", + " 40.7\n", " 0\n", " unknown\n", " \n", - " \n", - " Other Asian\n", - " 70\n", - " 41.7\n", - " 168\n", - " 41.7\n", + " \n", + " Other Asian\n", + " 77\n", + " 42.3\n", + " 182\n", + " 42.3\n", " 0\n", " unknown\n", " \n", " \n", " British or Mixed British\n", " 70\n", - " 35.7\n", - " 196\n", - " 35.7\n", + " 33.3\n", + " 210\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " Indian or British Indian\n", " 70\n", - " 37.0\n", - " 189\n", - " 33.3\n", - " 3.7\n", - " 08-Jul\n", + " 40.0\n", + " 175\n", + " 40\n", + " 0\n", + " unknown\n", " \n", " \n", " Irish\n", - " 91\n", - " 46.4\n", + " 77\n", + " 39.3\n", " 196\n", - " 42.9\n", - " 3.5\n", - " 25-Jun\n", + " 35.7\n", + " 3.6\n", + " 23-Jul\n", " \n", " \n", " Other Black\n", - " 70\n", - " 40.0\n", + " 77\n", + " 44.0\n", " 175\n", - " 36\n", + " 40\n", " 4\n", - " 25-Jun\n", + " 05-Jul\n", " \n", " \n", " Other White\n", - " 63\n", - " 34.6\n", - " 182\n", - " 34.6\n", + " 77\n", + " 44.0\n", + " 175\n", + " 44\n", " 0\n", " unknown\n", " \n", " \n", " Other mixed\n", - " 49\n", - " 28.0\n", + " 70\n", + " 40.0\n", " 175\n", - " 28\n", - " 0\n", - " unknown\n", + " 36\n", + " 4\n", + " 12-Jul\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 77\n", - " 37.9\n", - " 203\n", - " 34.5\n", - " 3.4\n", - " 15-Jul\n", + " 70\n", + " 41.7\n", + " 168\n", + " 41.7\n", + " 0\n", + " unknown\n", " \n", " \n", " Unknown\n", - " 210\n", - " 41.1\n", - " 511\n", - " 38.4\n", - " 2.7\n", - " 03-Aug\n", + " 217\n", + " 40.8\n", + " 532\n", + " 38.2\n", + " 2.6\n", + " 26-Aug\n", " \n", " \n", " White + Asian\n", - " 77\n", - " 39.3\n", - " 196\n", - " 39.3\n", - " 0\n", - " unknown\n", + " 63\n", + " 37.5\n", + " 168\n", + " 33.3\n", + " 4.2\n", + " 12-Jul\n", " \n", " \n", " White + Black African\n", - " 70\n", - " 41.7\n", - " 168\n", - " 37.5\n", - " 4.2\n", - " 18-Jun\n", + " 84\n", + " 48.0\n", + " 175\n", + " 48\n", + " 0\n", + " unknown\n", " \n", " \n", " White + Black Caribbean\n", - " 63\n", - " 39.1\n", - " 161\n", - " 34.8\n", - " 4.3\n", - " 20-Jun\n", + " 77\n", + " 42.3\n", + " 182\n", + " 38.5\n", + " 3.8\n", + " 12-Jul\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 245\n", - " 36.5\n", - " 672\n", - " 34.4\n", - " 2.1\n", - " unknown\n", + " 259\n", + " 39.8\n", + " 651\n", + " 37.6\n", + " 2.2\n", + " 22-Sep\n", " \n", " \n", " 2\n", - " 245\n", - " 37.6\n", - " 651\n", - " 36.6\n", - " 1\n", - " unknown\n", + " 238\n", + " 39.1\n", + " 609\n", + " 35.6\n", + " 3.5\n", + " 26-Jul\n", " \n", " \n", " 3\n", - " 238\n", - " 38.2\n", - " 623\n", - " 36\n", - " 2.2\n", - " 10-Sep\n", + " 245\n", + " 37.6\n", + " 651\n", + " 34.4\n", + " 3.2\n", + " 08-Aug\n", " \n", " \n", " 4\n", - " 238\n", - " 38.2\n", - " 623\n", - " 36\n", - " 2.2\n", - " 10-Sep\n", + " 280\n", + " 41.2\n", + " 679\n", + " 39.2\n", + " 2\n", + " 03-Oct\n", " \n", " \n", " 5 Least deprived\n", - " 273\n", - " 40.6\n", - " 672\n", - " 37.5\n", - " 3.1\n", - " 19-Jul\n", + " 280\n", + " 44.0\n", + " 637\n", + " 40.7\n", + " 3.3\n", + " 22-Jul\n", " \n", " \n", " Unknown\n", - " 63\n", - " 37.5\n", - " 168\n", - " 33.3\n", - " 4.2\n", - " 25-Jun\n", + " 77\n", + " 42.3\n", + " 182\n", + " 38.5\n", + " 3.8\n", + " 12-Jul\n", " \n", " \n", " bmi\n", " 30+\n", - " 392\n", - " 37.8\n", - " 1036\n", - " 35.1\n", + " 399\n", + " 39.3\n", + " 1015\n", + " 36.6\n", " 2.7\n", - " 12-Aug\n", + " 25-Aug\n", " \n", " \n", " under 30\n", - " 910\n", - " 38.3\n", - " 2373\n", - " 36\n", - " 2.3\n", - " 03-Sep\n", + " 980\n", + " 41.1\n", + " 2387\n", + " 38.7\n", + " 2.4\n", + " 05-Sep\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 1295\n", - " 38.4\n", - " 3374\n", - " 35.7\n", - " 2.7\n", - " 10-Aug\n", + " 1365\n", + " 40.6\n", + " 3360\n", + " 38.1\n", + " 2.5\n", + " 01-Sep\n", " \n", " \n", " yes\n", " 14\n", - " 40.0\n", - " 35\n", - " 40\n", + " 33.3\n", + " 42\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " current_copd\n", " no\n", - " 1295\n", - " 38.3\n", - " 3381\n", - " 35.8\n", + " 1372\n", + " 40.7\n", + " 3374\n", + " 38.2\n", " 2.5\n", - " 21-Aug\n", + " 01-Sep\n", " \n", " \n", " yes\n", @@ -7132,57 +7132,57 @@ " \n", " dmards\n", " no\n", - " 1295\n", - " 38.3\n", - " 3381\n", - " 35.6\n", - " 2.7\n", - " 11-Aug\n", + " 1365\n", + " 40.6\n", + " 3360\n", + " 38.1\n", + " 2.5\n", + " 01-Sep\n", " \n", " \n", " yes\n", " 14\n", - " 50.0\n", - " 28\n", - " 50\n", + " 33.3\n", + " 42\n", + " 33.3\n", " 0\n", " unknown\n", " \n", " \n", " psychosis_schiz_bipolar\n", " no\n", - " 1295\n", - " 38.4\n", - " 3374\n", - " 35.7\n", - " 2.7\n", - " 10-Aug\n", + " 1358\n", + " 40.3\n", + " 3367\n", + " 37.8\n", + " 2.5\n", + " 02-Sep\n", " \n", " \n", " yes\n", - " 14\n", - " 40.0\n", + " 21\n", + " 60.0\n", " 35\n", - " 40\n", + " 60\n", " 0\n", " unknown\n", " \n", " \n", " ssri\n", " no\n", - " 1295\n", - " 38.4\n", - " 3374\n", - " 35.9\n", + " 1365\n", + " 40.6\n", + " 3360\n", + " 38.1\n", " 2.5\n", - " 21-Aug\n", + " 01-Sep\n", " \n", " \n", " yes\n", - " 7\n", - " 20.0\n", - " 35\n", - " 20\n", + " 14\n", + " 33.3\n", + " 42\n", + " 33.3\n", " 0\n", " unknown\n", " \n", @@ -7193,237 +7193,237 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 1306 \n", - "sex F 658 \n", - " M 644 \n", - "ethnicity_6_groups Black 231 \n", - " Mixed 217 \n", - " Other 217 \n", - " South Asian 252 \n", - " Unknown 168 \n", - " White 224 \n", + "overall overall 1378 \n", + "sex F 665 \n", + " M 707 \n", + "ethnicity_6_groups Black 245 \n", + " Mixed 245 \n", + " Other 245 \n", + " South Asian 238 \n", + " Unknown 189 \n", + " White 210 \n", "ethnicity_16_groups African 77 \n", - " Bangladeshi or British Bangladeshi 63 \n", - " Caribbean 56 \n", + " Bangladeshi or British Bangladeshi 70 \n", + " Caribbean 70 \n", " Chinese 63 \n", - " Other 63 \n", - " Other Asian 70 \n", + " Other 77 \n", + " Other Asian 77 \n", " British or Mixed British 70 \n", " Indian or British Indian 70 \n", - " Irish 91 \n", - " Other Black 70 \n", - " Other White 63 \n", - " Other mixed 49 \n", - " Pakistani or British Pakistani 77 \n", - " Unknown 210 \n", - " White + Asian 77 \n", - " White + Black African 70 \n", - " White + Black Caribbean 63 \n", - "imd_categories 1 Most deprived 245 \n", - " 2 245 \n", - " 3 238 \n", - " 4 238 \n", - " 5 Least deprived 273 \n", - " Unknown 63 \n", - "bmi 30+ 392 \n", - " under 30 910 \n", - "chronic_cardiac_disease no 1295 \n", + " Irish 77 \n", + " Other Black 77 \n", + " Other White 77 \n", + " Other mixed 70 \n", + " Pakistani or British Pakistani 70 \n", + " Unknown 217 \n", + " White + Asian 63 \n", + " White + Black African 84 \n", + " White + Black Caribbean 77 \n", + "imd_categories 1 Most deprived 259 \n", + " 2 238 \n", + " 3 245 \n", + " 4 280 \n", + " 5 Least deprived 280 \n", + " Unknown 77 \n", + "bmi 30+ 399 \n", + " under 30 980 \n", + "chronic_cardiac_disease no 1365 \n", " yes 14 \n", - "current_copd no 1295 \n", + "current_copd no 1372 \n", " yes 7 \n", - "dmards no 1295 \n", + "dmards no 1365 \n", " yes 14 \n", - "psychosis_schiz_bipolar no 1295 \n", + "psychosis_schiz_bipolar no 1358 \n", + " yes 21 \n", + "ssri no 1365 \n", " yes 14 \n", - "ssri no 1295 \n", - " yes 7 \n", "\n", " percent total \\\n", "category group \n", - "overall overall 38.3 3409 \n", - "sex F 37.9 1736 \n", - " M 38.5 1673 \n", - "ethnicity_6_groups Black 39.8 581 \n", - " Mixed 40.3 539 \n", - " Other 37.8 574 \n", - " South Asian 39.1 644 \n", - " Unknown 34.8 483 \n", - " White 38.1 588 \n", - "ethnicity_16_groups African 39.3 196 \n", - " Bangladeshi or British Bangladeshi 36.0 175 \n", - " Caribbean 32.0 175 \n", - " Chinese 36.0 175 \n", - " Other 37.5 168 \n", - " Other Asian 41.7 168 \n", - " British or Mixed British 35.7 196 \n", - " Indian or British Indian 37.0 189 \n", - " Irish 46.4 196 \n", - " Other Black 40.0 175 \n", - " Other White 34.6 182 \n", - " Other mixed 28.0 175 \n", - " Pakistani or British Pakistani 37.9 203 \n", - " Unknown 41.1 511 \n", - " White + Asian 39.3 196 \n", - " White + Black African 41.7 168 \n", - " White + Black Caribbean 39.1 161 \n", - "imd_categories 1 Most deprived 36.5 672 \n", - " 2 37.6 651 \n", - " 3 38.2 623 \n", - " 4 38.2 623 \n", - " 5 Least deprived 40.6 672 \n", - " Unknown 37.5 168 \n", - "bmi 30+ 37.8 1036 \n", - " under 30 38.3 2373 \n", - "chronic_cardiac_disease no 38.4 3374 \n", - " yes 40.0 35 \n", - "current_copd no 38.3 3381 \n", + "overall overall 40.5 3402 \n", + "sex F 38.8 1715 \n", + " M 41.9 1687 \n", + "ethnicity_6_groups Black 41.7 588 \n", + " Mixed 40.2 609 \n", + " Other 40.7 602 \n", + " South Asian 41.5 574 \n", + " Unknown 39.7 476 \n", + " White 38.0 553 \n", + "ethnicity_16_groups African 44.0 175 \n", + " Bangladeshi or British Bangladeshi 40.0 175 \n", + " Caribbean 38.5 182 \n", + " Chinese 39.1 161 \n", + " Other 40.7 189 \n", + " Other Asian 42.3 182 \n", + " British or Mixed British 33.3 210 \n", + " Indian or British Indian 40.0 175 \n", + " Irish 39.3 196 \n", + " Other Black 44.0 175 \n", + " Other White 44.0 175 \n", + " Other mixed 40.0 175 \n", + " Pakistani or British Pakistani 41.7 168 \n", + " Unknown 40.8 532 \n", + " White + Asian 37.5 168 \n", + " White + Black African 48.0 175 \n", + " White + Black Caribbean 42.3 182 \n", + "imd_categories 1 Most deprived 39.8 651 \n", + " 2 39.1 609 \n", + " 3 37.6 651 \n", + " 4 41.2 679 \n", + " 5 Least deprived 44.0 637 \n", + " Unknown 42.3 182 \n", + "bmi 30+ 39.3 1015 \n", + " under 30 41.1 2387 \n", + "chronic_cardiac_disease no 40.6 3360 \n", + " yes 33.3 42 \n", + "current_copd no 40.7 3374 \n", " yes 25.0 28 \n", - "dmards no 38.3 3381 \n", - " yes 50.0 28 \n", - "psychosis_schiz_bipolar no 38.4 3374 \n", - " yes 40.0 35 \n", - "ssri no 38.4 3374 \n", - " yes 20.0 35 \n", + "dmards no 40.6 3360 \n", + " yes 33.3 42 \n", + "psychosis_schiz_bipolar no 40.3 3367 \n", + " yes 60.0 35 \n", + "ssri no 40.6 3360 \n", + " yes 33.3 42 \n", "\n", " vaccinated 7d previous (percent) \\\n", "category group \n", - "overall overall 35.7 \n", - "sex F 35.5 \n", - " M 36 \n", - "ethnicity_6_groups Black 37.3 \n", - " Mixed 39 \n", - " Other 35.4 \n", - " South Asian 37 \n", - " Unknown 31.9 \n", - " White 34.5 \n", - "ethnicity_16_groups African 35.7 \n", - " Bangladeshi or British Bangladeshi 32 \n", - " Caribbean 32 \n", - " Chinese 32 \n", - " Other 37.5 \n", - " Other Asian 41.7 \n", - " British or Mixed British 35.7 \n", - " Indian or British Indian 33.3 \n", - " Irish 42.9 \n", - " Other Black 36 \n", - " Other White 34.6 \n", - " Other mixed 28 \n", - " Pakistani or British Pakistani 34.5 \n", - " Unknown 38.4 \n", - " White + Asian 39.3 \n", - " White + Black African 37.5 \n", - " White + Black Caribbean 34.8 \n", - "imd_categories 1 Most deprived 34.4 \n", - " 2 36.6 \n", - " 3 36 \n", - " 4 36 \n", - " 5 Least deprived 37.5 \n", - " Unknown 33.3 \n", - "bmi 30+ 35.1 \n", - " under 30 36 \n", - "chronic_cardiac_disease no 35.7 \n", - " yes 40 \n", - "current_copd no 35.8 \n", + "overall overall 38 \n", + "sex F 36.7 \n", + " M 39.4 \n", + "ethnicity_6_groups Black 39.3 \n", + " Mixed 37.9 \n", + " Other 38.4 \n", + " South Asian 40.2 \n", + " Unknown 36.8 \n", + " White 35.4 \n", + "ethnicity_16_groups African 40 \n", + " Bangladeshi or British Bangladeshi 36 \n", + " Caribbean 38.5 \n", + " Chinese 34.8 \n", + " Other 40.7 \n", + " Other Asian 42.3 \n", + " British or Mixed British 33.3 \n", + " Indian or British Indian 40 \n", + " Irish 35.7 \n", + " Other Black 40 \n", + " Other White 44 \n", + " Other mixed 36 \n", + " Pakistani or British Pakistani 41.7 \n", + " Unknown 38.2 \n", + " White + Asian 33.3 \n", + " White + Black African 48 \n", + " White + Black Caribbean 38.5 \n", + "imd_categories 1 Most deprived 37.6 \n", + " 2 35.6 \n", + " 3 34.4 \n", + " 4 39.2 \n", + " 5 Least deprived 40.7 \n", + " Unknown 38.5 \n", + "bmi 30+ 36.6 \n", + " under 30 38.7 \n", + "chronic_cardiac_disease no 38.1 \n", + " yes 33.3 \n", + "current_copd no 38.2 \n", " yes 25 \n", - "dmards no 35.6 \n", - " yes 50 \n", - "psychosis_schiz_bipolar no 35.7 \n", - " yes 40 \n", - "ssri no 35.9 \n", - " yes 20 \n", + "dmards no 38.1 \n", + " yes 33.3 \n", + "psychosis_schiz_bipolar no 37.8 \n", + " yes 60 \n", + "ssri no 38.1 \n", + " yes 33.3 \n", "\n", " Uptake over last 7d (percent) \\\n", "category group \n", - "overall overall 2.6 \n", - "sex F 2.4 \n", + "overall overall 2.5 \n", + "sex F 2.1 \n", " M 2.5 \n", - "ethnicity_6_groups Black 2.5 \n", - " Mixed 1.3 \n", - " Other 2.4 \n", - " South Asian 2.1 \n", + "ethnicity_6_groups Black 2.4 \n", + " Mixed 2.3 \n", + " Other 2.3 \n", + " South Asian 1.3 \n", " Unknown 2.9 \n", - " White 3.6 \n", - "ethnicity_16_groups African 3.6 \n", + " White 2.6 \n", + "ethnicity_16_groups African 4 \n", " Bangladeshi or British Bangladeshi 4 \n", " Caribbean 0 \n", - " Chinese 4 \n", + " Chinese 4.3 \n", " Other 0 \n", " Other Asian 0 \n", " British or Mixed British 0 \n", - " Indian or British Indian 3.7 \n", - " Irish 3.5 \n", + " Indian or British Indian 0 \n", + " Irish 3.6 \n", " Other Black 4 \n", " Other White 0 \n", - " Other mixed 0 \n", - " Pakistani or British Pakistani 3.4 \n", - " Unknown 2.7 \n", - " White + Asian 0 \n", - " White + Black African 4.2 \n", - " White + Black Caribbean 4.3 \n", - "imd_categories 1 Most deprived 2.1 \n", - " 2 1 \n", - " 3 2.2 \n", - " 4 2.2 \n", - " 5 Least deprived 3.1 \n", - " Unknown 4.2 \n", + " Other mixed 4 \n", + " Pakistani or British Pakistani 0 \n", + " Unknown 2.6 \n", + " White + Asian 4.2 \n", + " White + Black African 0 \n", + " White + Black Caribbean 3.8 \n", + "imd_categories 1 Most deprived 2.2 \n", + " 2 3.5 \n", + " 3 3.2 \n", + " 4 2 \n", + " 5 Least deprived 3.3 \n", + " Unknown 3.8 \n", "bmi 30+ 2.7 \n", - " under 30 2.3 \n", - "chronic_cardiac_disease no 2.7 \n", + " under 30 2.4 \n", + "chronic_cardiac_disease no 2.5 \n", " yes 0 \n", "current_copd no 2.5 \n", " yes 0 \n", - "dmards no 2.7 \n", + "dmards no 2.5 \n", " yes 0 \n", - "psychosis_schiz_bipolar no 2.7 \n", + "psychosis_schiz_bipolar no 2.5 \n", " yes 0 \n", "ssri no 2.5 \n", " yes 0 \n", "\n", " Date projected to reach 90% \n", "category group \n", - "overall overall 16-Aug \n", - "sex F 28-Aug \n", - " M 21-Aug \n", - "ethnicity_6_groups Black 17-Aug \n", - " Mixed unknown \n", - " Other 29-Aug \n", - " South Asian 15-Sep \n", - " Unknown 10-Aug \n", - " White 08-Jul \n", - "ethnicity_16_groups African 06-Jul \n", - " Bangladeshi or British Bangladeshi 02-Jul \n", + "overall overall 01-Sep \n", + "sex F 03-Oct \n", + " M 28-Aug \n", + "ethnicity_6_groups Black 03-Sep \n", + " Mixed 14-Sep \n", + " Other 13-Sep \n", + " South Asian unknown \n", + " Unknown 15-Aug \n", + " White 03-Sep \n", + "ethnicity_16_groups African 05-Jul \n", + " Bangladeshi or British Bangladeshi 12-Jul \n", " Caribbean unknown \n", - " Chinese 02-Jul \n", + " Chinese 07-Jul \n", " Other unknown \n", " Other Asian unknown \n", " British or Mixed British unknown \n", - " Indian or British Indian 08-Jul \n", - " Irish 25-Jun \n", - " Other Black 25-Jun \n", + " Indian or British Indian unknown \n", + " Irish 23-Jul \n", + " Other Black 05-Jul \n", " Other White unknown \n", - " Other mixed unknown \n", - " Pakistani or British Pakistani 15-Jul \n", - " Unknown 03-Aug \n", - " White + Asian unknown \n", - " White + Black African 18-Jun \n", - " White + Black Caribbean 20-Jun \n", - "imd_categories 1 Most deprived unknown \n", - " 2 unknown \n", - " 3 10-Sep \n", - " 4 10-Sep \n", - " 5 Least deprived 19-Jul \n", - " Unknown 25-Jun \n", - "bmi 30+ 12-Aug \n", - " under 30 03-Sep \n", - "chronic_cardiac_disease no 10-Aug \n", + " Other mixed 12-Jul \n", + " Pakistani or British Pakistani unknown \n", + " Unknown 26-Aug \n", + " White + Asian 12-Jul \n", + " White + Black African unknown \n", + " White + Black Caribbean 12-Jul \n", + "imd_categories 1 Most deprived 22-Sep \n", + " 2 26-Jul \n", + " 3 08-Aug \n", + " 4 03-Oct \n", + " 5 Least deprived 22-Jul \n", + " Unknown 12-Jul \n", + "bmi 30+ 25-Aug \n", + " under 30 05-Sep \n", + "chronic_cardiac_disease no 01-Sep \n", " yes unknown \n", - "current_copd no 21-Aug \n", + "current_copd no 01-Sep \n", " yes unknown \n", - "dmards no 11-Aug \n", + "dmards no 01-Sep \n", " yes unknown \n", - "psychosis_schiz_bipolar no 10-Aug \n", + "psychosis_schiz_bipolar no 02-Sep \n", " yes unknown \n", - "ssri no 21-Aug \n", + "ssri no 01-Sep \n", " yes unknown " ] }, @@ -7445,7 +7445,7 @@ { "data": { "text/markdown": [ - "## COVID vaccination rollout among **16-49, not in other eligible groups shown** population up to 30 Mar 2021" + "## COVID vaccination rollout among **16-49, not in other eligible groups shown** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -7507,116 +7507,116 @@ " \n", " overall\n", " overall\n", - " 12162\n", - " 11440\n", - " 722\n", - " 6.3\n", + " 12150\n", + " 11496\n", + " 654\n", + " 5.7\n", " \n", " \n", " sex\n", " F\n", - " 6202\n", - " 5845\n", - " 357\n", - " 6.1\n", + " 6223\n", + " 5887\n", + " 336\n", + " 5.7\n", " \n", " \n", " M\n", - " 5964\n", - " 5593\n", - " 371\n", - " 6.6\n", + " 5929\n", + " 5607\n", + " 322\n", + " 5.7\n", " \n", " \n", " ageband\n", " 16-29\n", - " 1498\n", - " 1407\n", - " 91\n", - " 6.5\n", + " 1512\n", + " 1428\n", + " 84\n", + " 5.9\n", " \n", " \n", " 30-39\n", - " 1519\n", - " 1421\n", - " 98\n", - " 6.9\n", + " 1512\n", + " 1435\n", + " 77\n", + " 5.4\n", " \n", " \n", " 40-49\n", - " 1505\n", - " 1421\n", - " 84\n", - " 5.9\n", + " 1512\n", + " 1435\n", + " 77\n", + " 5.4\n", " \n", " \n", " 50-59\n", - " 1575\n", - " 1491\n", - " 84\n", - " 5.6\n", + " 1589\n", + " 1498\n", + " 91\n", + " 6.1\n", " \n", " \n", " 60-69\n", - " 1547\n", - " 1463\n", + " 1505\n", + " 1421\n", " 84\n", - " 5.7\n", + " 5.9\n", " \n", " \n", " 70-79\n", - " 3080\n", - " 2877\n", - " 203\n", - " 7.1\n", + " 2982\n", + " 2828\n", + " 154\n", + " 5.4\n", " \n", " \n", " 80+\n", - " 1442\n", - " 1351\n", + " 1540\n", + " 1449\n", " 91\n", - " 6.7\n", + " 6.3\n", " \n", " \n", " ethnicity_6_groups\n", " Black\n", - " 2079\n", - " 1939\n", - " 140\n", - " 7.2\n", + " 1995\n", + " 1883\n", + " 112\n", + " 5.9\n", " \n", " \n", " Mixed\n", - " 2072\n", - " 1967\n", - " 105\n", - " 5.3\n", + " 2107\n", + " 1995\n", + " 112\n", + " 5.6\n", " \n", " \n", " Other\n", - " 2051\n", - " 1939\n", - " 112\n", - " 5.8\n", + " 2121\n", + " 1981\n", + " 140\n", + " 7.1\n", " \n", " \n", " South Asian\n", - " 2093\n", - " 1974\n", - " 119\n", - " 6\n", + " 2135\n", + " 2037\n", + " 98\n", + " 4.8\n", " \n", " \n", " Unknown\n", - " 1827\n", - " 1701\n", - " 126\n", - " 7.4\n", + " 1792\n", + " 1694\n", + " 98\n", + " 5.8\n", " \n", " \n", " White\n", - " 2030\n", - " 1925\n", + " 2002\n", + " 1897\n", " 105\n", " 5.5\n", " \n", @@ -7630,29 +7630,29 @@ " \n", " \n", " Bangladeshi or British Bangladeshi\n", - " 616\n", - " 574\n", - " 42\n", - " 7.3\n", + " 651\n", + " 630\n", + " 21\n", + " 3.3\n", " \n", " \n", " Caribbean\n", + " 672\n", " 637\n", - " 602\n", " 35\n", - " 5.8\n", + " 5.5\n", " \n", " \n", " Chinese\n", - " 637\n", - " 609\n", + " 672\n", + " 644\n", " 28\n", - " 4.6\n", + " 4.3\n", " \n", " \n", " Other\n", - " 665\n", - " 630\n", + " 658\n", + " 623\n", " 35\n", " 5.6\n", " \n", @@ -7665,146 +7665,146 @@ " \n", " \n", " British or Mixed British\n", - " 630\n", - " 588\n", + " 637\n", + " 595\n", " 42\n", " 7.1\n", " \n", " \n", " Indian or British Indian\n", + " 672\n", " 637\n", - " 595\n", - " 42\n", - " 7.1\n", + " 35\n", + " 5.5\n", " \n", " \n", " Irish\n", - " 679\n", - " 644\n", - " 35\n", - " 5.4\n", + " 665\n", + " 616\n", + " 49\n", + " 8\n", " \n", " \n", " Other Black\n", - " 665\n", - " 630\n", - " 35\n", - " 5.6\n", + " 651\n", + " 623\n", + " 28\n", + " 4.5\n", " \n", " \n", " Other White\n", - " 651\n", - " 616\n", + " 602\n", + " 567\n", " 35\n", - " 5.7\n", + " 6.2\n", " \n", " \n", " Other mixed\n", - " 630\n", - " 595\n", - " 35\n", - " 5.9\n", + " 616\n", + " 602\n", + " 14\n", + " 2.3\n", " \n", " \n", " Pakistani or British Pakistani\n", - " 693\n", - " 651\n", - " 42\n", - " 6.5\n", + " 616\n", + " 581\n", + " 35\n", + " 6\n", " \n", " \n", " Unknown\n", - " 1862\n", - " 1736\n", - " 126\n", - " 7.3\n", + " 1813\n", + " 1722\n", + " 91\n", + " 5.3\n", " \n", " \n", " White + Asian\n", - " 637\n", - " 602\n", - " 35\n", - " 5.8\n", + " 672\n", + " 630\n", + " 42\n", + " 6.7\n", " \n", " \n", " White + Black African\n", - " 644\n", - " 609\n", + " 658\n", + " 623\n", " 35\n", - " 5.7\n", + " 5.6\n", " \n", " \n", " White + Black Caribbean\n", - " 602\n", - " 567\n", + " 623\n", + " 588\n", " 35\n", - " 6.2\n", + " 6\n", " \n", " \n", " imd_categories\n", " 1 Most deprived\n", - " 2275\n", - " 2149\n", + " 2296\n", + " 2170\n", " 126\n", - " 5.9\n", + " 5.8\n", " \n", " \n", " 2\n", - " 2366\n", - " 2219\n", - " 147\n", - " 6.6\n", + " 2345\n", + " 2205\n", + " 140\n", + " 6.3\n", " \n", " \n", " 3\n", - " 2268\n", - " 2135\n", - " 133\n", - " 6.2\n", + " 2296\n", + " 2184\n", + " 112\n", + " 5.1\n", " \n", " \n", " 4\n", - " 2387\n", - " 2247\n", - " 140\n", - " 6.2\n", + " 2254\n", + " 2128\n", + " 126\n", + " 5.9\n", " \n", " \n", " 5 Least deprived\n", - " 2289\n", - " 2142\n", - " 147\n", - " 6.9\n", + " 2331\n", + " 2212\n", + " 119\n", + " 5.4\n", " \n", " \n", " Unknown\n", - " 588\n", - " 553\n", - " 35\n", - " 6.3\n", + " 623\n", + " 595\n", + " 28\n", + " 4.7\n", " \n", " \n", " bmi\n", " 30+\n", - " 3654\n", - " 3437\n", - " 217\n", - " 6.3\n", + " 3647\n", + " 3465\n", + " 182\n", + " 5.3\n", " \n", " \n", " under 30\n", " 8505\n", - " 8001\n", - " 504\n", - " 6.3\n", + " 8029\n", + " 476\n", + " 5.9\n", " \n", " \n", " chronic_cardiac_disease\n", " no\n", - " 12040\n", - " 11319\n", - " 721\n", - " 6.4\n", + " 12019\n", + " 11375\n", + " 644\n", + " 5.7\n", " \n", " \n", " yes\n", @@ -7816,40 +7816,40 @@ " \n", " current_copd\n", " no\n", - " 12026\n", - " 11319\n", - " 707\n", - " 6.2\n", + " 12019\n", + " 11375\n", + " 644\n", + " 5.7\n", " \n", " \n", " yes\n", - " 133\n", + " 126\n", " 119\n", - " 14\n", - " 11.8\n", + " 7\n", + " 5.9\n", " \n", " \n", " dmards\n", " no\n", " 12033\n", - " 11319\n", - " 714\n", - " 6.3\n", + " 11382\n", + " 651\n", + " 5.7\n", " \n", " \n", " yes\n", - " 126\n", " 119\n", + " 112\n", " 7\n", - " 5.9\n", + " 6.2\n", " \n", " \n", " ssri\n", " no\n", - " 12040\n", - " 11326\n", - " 714\n", - " 6.3\n", + " 12033\n", + " 11382\n", + " 651\n", + " 5.7\n", " \n", " \n", " yes\n", @@ -7865,210 +7865,210 @@ "text/plain": [ " vaccinated \\\n", "category group \n", - "overall overall 12162 \n", - "sex F 6202 \n", - " M 5964 \n", - "ageband 16-29 1498 \n", - " 30-39 1519 \n", - " 40-49 1505 \n", - " 50-59 1575 \n", - " 60-69 1547 \n", - " 70-79 3080 \n", - " 80+ 1442 \n", - "ethnicity_6_groups Black 2079 \n", - " Mixed 2072 \n", - " Other 2051 \n", - " South Asian 2093 \n", - " Unknown 1827 \n", - " White 2030 \n", + "overall overall 12150 \n", + "sex F 6223 \n", + " M 5929 \n", + "ageband 16-29 1512 \n", + " 30-39 1512 \n", + " 40-49 1512 \n", + " 50-59 1589 \n", + " 60-69 1505 \n", + " 70-79 2982 \n", + " 80+ 1540 \n", + "ethnicity_6_groups Black 1995 \n", + " Mixed 2107 \n", + " Other 2121 \n", + " South Asian 2135 \n", + " Unknown 1792 \n", + " White 2002 \n", "ethnicity_16_groups African 637 \n", - " Bangladeshi or British Bangladeshi 616 \n", - " Caribbean 637 \n", - " Chinese 637 \n", - " Other 665 \n", + " Bangladeshi or British Bangladeshi 651 \n", + " Caribbean 672 \n", + " Chinese 672 \n", + " Other 658 \n", " Other Asian 630 \n", - " British or Mixed British 630 \n", - " Indian or British Indian 637 \n", - " Irish 679 \n", - " Other Black 665 \n", - " Other White 651 \n", - " Other mixed 630 \n", - " Pakistani or British Pakistani 693 \n", - " Unknown 1862 \n", - " White + Asian 637 \n", - " White + Black African 644 \n", - " White + Black Caribbean 602 \n", - "imd_categories 1 Most deprived 2275 \n", - " 2 2366 \n", - " 3 2268 \n", - " 4 2387 \n", - " 5 Least deprived 2289 \n", - " Unknown 588 \n", - "bmi 30+ 3654 \n", + " British or Mixed British 637 \n", + " Indian or British Indian 672 \n", + " Irish 665 \n", + " Other Black 651 \n", + " Other White 602 \n", + " Other mixed 616 \n", + " Pakistani or British Pakistani 616 \n", + " Unknown 1813 \n", + " White + Asian 672 \n", + " White + Black African 658 \n", + " White + Black Caribbean 623 \n", + "imd_categories 1 Most deprived 2296 \n", + " 2 2345 \n", + " 3 2296 \n", + " 4 2254 \n", + " 5 Least deprived 2331 \n", + " Unknown 623 \n", + "bmi 30+ 3647 \n", " under 30 8505 \n", - "chronic_cardiac_disease no 12040 \n", + "chronic_cardiac_disease no 12019 \n", " yes 126 \n", - "current_copd no 12026 \n", - " yes 133 \n", - "dmards no 12033 \n", + "current_copd no 12019 \n", " yes 126 \n", - "ssri no 12040 \n", + "dmards no 12033 \n", + " yes 119 \n", + "ssri no 12033 \n", " yes 119 \n", "\n", " vaccinated 7d previous \\\n", "category group \n", - "overall overall 11440 \n", - "sex F 5845 \n", - " M 5593 \n", - "ageband 16-29 1407 \n", - " 30-39 1421 \n", - " 40-49 1421 \n", - " 50-59 1491 \n", - " 60-69 1463 \n", - " 70-79 2877 \n", - " 80+ 1351 \n", - "ethnicity_6_groups Black 1939 \n", - " Mixed 1967 \n", - " Other 1939 \n", - " South Asian 1974 \n", - " Unknown 1701 \n", - " White 1925 \n", + "overall overall 11496 \n", + "sex F 5887 \n", + " M 5607 \n", + "ageband 16-29 1428 \n", + " 30-39 1435 \n", + " 40-49 1435 \n", + " 50-59 1498 \n", + " 60-69 1421 \n", + " 70-79 2828 \n", + " 80+ 1449 \n", + "ethnicity_6_groups Black 1883 \n", + " Mixed 1995 \n", + " Other 1981 \n", + " South Asian 2037 \n", + " Unknown 1694 \n", + " White 1897 \n", "ethnicity_16_groups African 602 \n", - " Bangladeshi or British Bangladeshi 574 \n", - " Caribbean 602 \n", - " Chinese 609 \n", - " Other 630 \n", + " Bangladeshi or British Bangladeshi 630 \n", + " Caribbean 637 \n", + " Chinese 644 \n", + " Other 623 \n", " Other Asian 588 \n", - " British or Mixed British 588 \n", - " Indian or British Indian 595 \n", - " Irish 644 \n", - " Other Black 630 \n", - " Other White 616 \n", - " Other mixed 595 \n", - " Pakistani or British Pakistani 651 \n", - " Unknown 1736 \n", - " White + Asian 602 \n", - " White + Black African 609 \n", - " White + Black Caribbean 567 \n", - "imd_categories 1 Most deprived 2149 \n", - " 2 2219 \n", - " 3 2135 \n", - " 4 2247 \n", - " 5 Least deprived 2142 \n", - " Unknown 553 \n", - "bmi 30+ 3437 \n", - " under 30 8001 \n", - "chronic_cardiac_disease no 11319 \n", - " yes 119 \n", - "current_copd no 11319 \n", + " British or Mixed British 595 \n", + " Indian or British Indian 637 \n", + " Irish 616 \n", + " Other Black 623 \n", + " Other White 567 \n", + " Other mixed 602 \n", + " Pakistani or British Pakistani 581 \n", + " Unknown 1722 \n", + " White + Asian 630 \n", + " White + Black African 623 \n", + " White + Black Caribbean 588 \n", + "imd_categories 1 Most deprived 2170 \n", + " 2 2205 \n", + " 3 2184 \n", + " 4 2128 \n", + " 5 Least deprived 2212 \n", + " Unknown 595 \n", + "bmi 30+ 3465 \n", + " under 30 8029 \n", + "chronic_cardiac_disease no 11375 \n", " yes 119 \n", - "dmards no 11319 \n", + "current_copd no 11375 \n", " yes 119 \n", - "ssri no 11326 \n", + "dmards no 11382 \n", + " yes 112 \n", + "ssri no 11382 \n", " yes 112 \n", "\n", " Uptake over last 7d \\\n", "category group \n", - "overall overall 722 \n", - "sex F 357 \n", - " M 371 \n", - "ageband 16-29 91 \n", - " 30-39 98 \n", - " 40-49 84 \n", - " 50-59 84 \n", + "overall overall 654 \n", + "sex F 336 \n", + " M 322 \n", + "ageband 16-29 84 \n", + " 30-39 77 \n", + " 40-49 77 \n", + " 50-59 91 \n", " 60-69 84 \n", - " 70-79 203 \n", + " 70-79 154 \n", " 80+ 91 \n", - "ethnicity_6_groups Black 140 \n", - " Mixed 105 \n", - " Other 112 \n", - " South Asian 119 \n", - " Unknown 126 \n", + "ethnicity_6_groups Black 112 \n", + " Mixed 112 \n", + " Other 140 \n", + " South Asian 98 \n", + " Unknown 98 \n", " White 105 \n", "ethnicity_16_groups African 35 \n", - " Bangladeshi or British Bangladeshi 42 \n", + " Bangladeshi or British Bangladeshi 21 \n", " Caribbean 35 \n", " Chinese 28 \n", " Other 35 \n", " Other Asian 42 \n", " British or Mixed British 42 \n", - " Indian or British Indian 42 \n", - " Irish 35 \n", - " Other Black 35 \n", + " Indian or British Indian 35 \n", + " Irish 49 \n", + " Other Black 28 \n", " Other White 35 \n", - " Other mixed 35 \n", - " Pakistani or British Pakistani 42 \n", - " Unknown 126 \n", - " White + Asian 35 \n", + " Other mixed 14 \n", + " Pakistani or British Pakistani 35 \n", + " Unknown 91 \n", + " White + Asian 42 \n", " White + Black African 35 \n", " White + Black Caribbean 35 \n", "imd_categories 1 Most deprived 126 \n", - " 2 147 \n", - " 3 133 \n", - " 4 140 \n", - " 5 Least deprived 147 \n", - " Unknown 35 \n", - "bmi 30+ 217 \n", - " under 30 504 \n", - "chronic_cardiac_disease no 721 \n", + " 2 140 \n", + " 3 112 \n", + " 4 126 \n", + " 5 Least deprived 119 \n", + " Unknown 28 \n", + "bmi 30+ 182 \n", + " under 30 476 \n", + "chronic_cardiac_disease no 644 \n", + " yes 7 \n", + "current_copd no 644 \n", " yes 7 \n", - "current_copd no 707 \n", - " yes 14 \n", - "dmards no 714 \n", + "dmards no 651 \n", " yes 7 \n", - "ssri no 714 \n", + "ssri no 651 \n", " yes 7 \n", "\n", " Increase in uptake (%) \n", "category group \n", - "overall overall 6.3 \n", - "sex F 6.1 \n", - " M 6.6 \n", - "ageband 16-29 6.5 \n", - " 30-39 6.9 \n", - " 40-49 5.9 \n", - " 50-59 5.6 \n", - " 60-69 5.7 \n", - " 70-79 7.1 \n", - " 80+ 6.7 \n", - "ethnicity_6_groups Black 7.2 \n", - " Mixed 5.3 \n", - " Other 5.8 \n", - " South Asian 6 \n", - " Unknown 7.4 \n", + "overall overall 5.7 \n", + "sex F 5.7 \n", + " M 5.7 \n", + "ageband 16-29 5.9 \n", + " 30-39 5.4 \n", + " 40-49 5.4 \n", + " 50-59 6.1 \n", + " 60-69 5.9 \n", + " 70-79 5.4 \n", + " 80+ 6.3 \n", + "ethnicity_6_groups Black 5.9 \n", + " Mixed 5.6 \n", + " Other 7.1 \n", + " South Asian 4.8 \n", + " Unknown 5.8 \n", " White 5.5 \n", "ethnicity_16_groups African 5.8 \n", - " Bangladeshi or British Bangladeshi 7.3 \n", - " Caribbean 5.8 \n", - " Chinese 4.6 \n", + " Bangladeshi or British Bangladeshi 3.3 \n", + " Caribbean 5.5 \n", + " Chinese 4.3 \n", " Other 5.6 \n", " Other Asian 7.1 \n", " British or Mixed British 7.1 \n", - " Indian or British Indian 7.1 \n", - " Irish 5.4 \n", - " Other Black 5.6 \n", - " Other White 5.7 \n", - " Other mixed 5.9 \n", - " Pakistani or British Pakistani 6.5 \n", - " Unknown 7.3 \n", - " White + Asian 5.8 \n", - " White + Black African 5.7 \n", - " White + Black Caribbean 6.2 \n", - "imd_categories 1 Most deprived 5.9 \n", - " 2 6.6 \n", - " 3 6.2 \n", - " 4 6.2 \n", - " 5 Least deprived 6.9 \n", - " Unknown 6.3 \n", - "bmi 30+ 6.3 \n", - " under 30 6.3 \n", - "chronic_cardiac_disease no 6.4 \n", + " Indian or British Indian 5.5 \n", + " Irish 8 \n", + " Other Black 4.5 \n", + " Other White 6.2 \n", + " Other mixed 2.3 \n", + " Pakistani or British Pakistani 6 \n", + " Unknown 5.3 \n", + " White + Asian 6.7 \n", + " White + Black African 5.6 \n", + " White + Black Caribbean 6 \n", + "imd_categories 1 Most deprived 5.8 \n", + " 2 6.3 \n", + " 3 5.1 \n", + " 4 5.9 \n", + " 5 Least deprived 5.4 \n", + " Unknown 4.7 \n", + "bmi 30+ 5.3 \n", + " under 30 5.9 \n", + "chronic_cardiac_disease no 5.7 \n", " yes 5.9 \n", - "current_copd no 6.2 \n", - " yes 11.8 \n", - "dmards no 6.3 \n", + "current_copd no 5.7 \n", " yes 5.9 \n", - "ssri no 6.3 \n", + "dmards no 5.7 \n", + " yes 6.2 \n", + "ssri no 5.7 \n", " yes 6.2 " ] }, @@ -8100,14 +8100,14 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **80+** population up to 30 Mar 2021" + " ## COVID vaccination rollout among **80+** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -8119,7 +8119,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **sex**" + "### COVID vaccinations among **80+** population by **sex**" ], "text/plain": [ "" @@ -8130,7 +8130,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8143,7 +8143,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **ageband 5yr**" + "### COVID vaccinations among **80+** population by **ageband 5yr**" ], "text/plain": [ "" @@ -8154,7 +8154,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8167,7 +8167,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **ethnicity 6 groups**" + "### COVID vaccinations among **80+** population by **ethnicity 6 groups**" ], "text/plain": [ "" @@ -8178,7 +8178,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8191,7 +8191,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **imd categories**" + "### COVID vaccinations among **80+** population by **imd categories**" ], "text/plain": [ "" @@ -8202,7 +8202,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8215,7 +8215,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **bmi**" + "### COVID vaccinations among **80+** population by **bmi**" ], "text/plain": [ "" @@ -8226,7 +8226,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8239,7 +8239,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **chronic cardiac disease**" + "### COVID vaccinations among **80+** population by **chronic cardiac disease**" ], "text/plain": [ "" @@ -8250,7 +8250,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8263,7 +8263,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **current copd**" + "### COVID vaccinations among **80+** population by **current copd**" ], "text/plain": [ "" @@ -8274,7 +8274,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8287,7 +8287,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **dialysis**" + "### COVID vaccinations among **80+** population by **dialysis**" ], "text/plain": [ "" @@ -8298,7 +8298,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8311,7 +8311,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **dementia**" + "### COVID vaccinations among **80+** population by **dementia**" ], "text/plain": [ "" @@ -8322,7 +8322,7 @@ }, { "data": { - "image/png": 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BgpwFvAtsIOjzeBhwU5hAr3D3xRW4NhGRjFRa61VJjvPOO2/jX/7yl9b5+fl21llnfVK/fn0fP378/qNHj/6madOmhZ9++mn9Bg0a+M6dO22fffbJ//Wvf/3NXnvtVfDggw+2KP/oPyqvJPmeu1+fYNvfzWwfQMNCiIig1qs1qWHDht6vX7/NzZo1K6hXrx5nnnnm5qVLlzbs3bt3R4A99tijcNKkSZ8uX758t2uuuaZNnTp1qFevnt99990VGuO0zCTp7i/HvzezPdx9W9z2DQSlSxERIQuqWFNEQUEBCxYsaDRlypSVsXXXXXfdhuuuu26XnNS5c+cfzjrrrGWVPU+khjtm1s/MlgHLw/fdzezuyp5URCRTxGbtOOfed0o01JHkmD9/fsMDDzywa//+/Td37dr1h2SeK2oXkAnAicALAO6+yMyOSlpUIiJpQlWsNa9Xr17ff/HFFx/UxLki95N099XBdJBFKtSMVkQkU2VZFWthYWGh1alTJ2NmZyosLDSgsLRtUftJrjazfoCbWX0z+x3wYXUFKCKSbmLVrFlYxbokLy+vaZhY0l5hYaHl5eU1JejaWELUkuTFBNNctSaY2mo6cEm1RCgikobiq1mzqYo1Pz//V+vXr39g/fr1XciMAWkKgSX5+fm/Km1j1CRp4TRXIiJZS7N4QK9evTYAp9Z2HDUl6reAt8xsupldaGbNkhqRiEiK0hyQ2SdSSdLdDzOzPgSTJ/8x7A7ypLs/ntToRERSTDaWHrNZRVq3vge8Z2Z/Bf4OPAIoSYpIRsqKWTykXJGSpJk1Ac4gKEkeDExFEyeLSAYoLRkCvPvpNwAc3r550TpVsWafqCXJRcBzwJ/c/Z0kxiMiUqPiW6nGO7x9c07Lac3PD9fw1NksapI8yN0zpuOoiGQ3tVKVqMqbKusf7j4WeMHMSiRJd8+aZsAikv5iyTG+KlVVqFKW8kqSj4U/b012ICIiyRarWlVVqkRV3lRZ88PFHHe/PX6bmV0GzE5WYCIi1UFVq1IVUQcTGFHKupHVGIeISFJoAACpivKeSQ4Dfg60N7MX4jY1Br5JZmAiItVFpUeprPKeSb4NrANaALfFrd8CLE5WUCIiVVFaFatIZZT3TPIz4DNAX8FEJG1oImSpLlFH3DkCuAP4CdAAqAt85+76eiYiKUENdCQZog4mcCfBkHRTgFzgl8BhyQpKRCQq9X2UZKrIAOcfm1lddy8A/mlm7wPXJC80EZHyqe+jJFPUJLnNzBoAC83sZoLGPJkwI7WIpIlEA5GralWSKWqiO4/gOeRvgO+AtsBZyQpKRKS4+P6O8VS1KskUddLlz8LF7cANyQtHRCQxlRilppU3mMAHQMLZP9y9W7VHJCISUn9HqW3llSQH10gUIiJx1GJVUkWUwQRERGqUWqxKqog6mMAWfqx2bQDUR4MJiEg10mAAkoqiNtxpHFs2MwNOA45IVlAikn00lJykosiDCcS4uwPPmdn1wNXVH5KIZDL1d5R0ErW69cy4t3UIhqb7vpx9GgJzgN3C8zzt7tebWXvgSWBvYD5wnrvvqETsIpJGSmuME0+lR0lFUUuSp8Qt5wOrCKpcy/IDcKy7bzWz+sCbZvYqcDkwwd2fNLN7gAuB/6tY2CKSbtQYR9JR1GeS51f0wGG17Nbwbf3w5cCxBBM5AzwCjEdJUiQjqTGOpLuo1a3tgUuBdvH7uPup5exXl6BK9RDgLmAlsNHd88OPfAGUWr9iZqOB0QAHHKBvnCLpIj4xqp+jpLuo1a3PAQ8CLwKFUQ8ezhiSY2bNgKlAxwrsex9wH0Bubm7CUX9EJLXEt1JV1aqku6hJ8nt3n1jZk7j7RjN7HegLNDOzemFpsg1QspmbiKQ1VatKpoiaJG8Pu3xMJ2iQA4C7L0i0g5m1BHaGCXJ34Hjgb8DrwBCCFq4jgOcrGbuIpAiNsSqZKmqS7EowXdax/FjdGmuEk8h+wCPhc8k6wFPu/pKZLQOeNLM/A+8TVOOKSBrTQACSqaImyaHAQRXpz+jui4Eepaz/BOgT9Tgikh5UxSqZKOqky0uAZskMREREJNVELUk2A5ab2Vx2fSZZZhcQEck8pQ0rp+eQkqmiJsnrkxqFiKS0RH0fY/QcUjJV1BF3Zic7EBFJXer7KNlK80mKSCRqmCPZSPNJikip1PdRJHrr1iIeeA44MQnxiEiKiFWxgp45SvZK2nySIpKeYiVIzdohktz5JEUkTSRqvarSo2S7pM0nKSLpQ61XRUoXtbr1EeAyd98Yvt8LuM3dL0hmcCJSc1S1KlJS1OrWbrEECeDu35pZiXFZRSR9qPWqSPmitm6tE5YeATCz5kRPsCKSgtR6VaR8URPdbcA7ZjYlfD8U+EtyQhKRZCmt9KgqVpHEIpUk3f1R4Ezgy/B1prs/lszARKT6qfQoUjFlliTNrJG7bwVw92XAsrI+IyKpo6zZOlR6FImmvJLk82Z2m5kdZWZ7xlaa2UFmdqGZvQaclNwQRaQy4kuNMSo9ilRMmSVJdz/OzE4GLgKODBvs7ARWAC8DI9x9ffLDFJHKUKlRpGrKbbjj7q8Ar9RALCJSRerWIVK9KjzAuYikLjXMEale6usokmFUxSpSfZQkRTJA8Zk7RKR6lNcFpHlZ2939m+oNR0Si0swdIslXXklyPuCAAQcA34bLzYDPgfZJjU5EEtLMHSLJV14XkPYAZnY/MDVs6YqZ/Qw4PfnhiUg8DSsnUrOitm49IpYgAdz9VaBfckISkUTUelWkZkVtuLPWzK4FHg/fDwfWJickEQENKyeSCqKWJIcBLYGpwLPh8rBkBSUiGlZOJBVEKkmGrVgvM7M93f27JMckIiGVGkVqV6QkaWb9gAeARsABZtYduMjdf53M4ESyjYaVE0ktUZ9JTgBOBF4AcPdFZnZU0qISyXClPW+EXfs7qmpVpPZFHnHH3VebWfyqguoPRyQ7JBodR/0dRVJL1CS5OqxydTOrD1wGfJi8sEQyU/Hh4/S8USS1RU2SFwO3A62BNcB0QM8jRSLQ8HEi6Stqkuzg7sPjV5jZkcBb1R+SSGbR8HEi6StqkrwD6BlhnYig4eNEMkV5s4D0JRh+rqWZXR63qQlQN5mBiaSL0lqqqpWqSGYoryTZgKBvZD2gcdz6zcCQsnY0s7bAo8C+BDOJ3Ofut4fTb00G2gGrgLPd/dvKBC+SCkprqapqVZHMUN4sILOB2Wb2sLt/VsFj5wNXuPsCM2sMzDezfwEjgZnufpOZXQ1cDVxVidhFalSivo2qThXJXFGfSW4zs1uAzkDD2Ep3PzbRDu6+DlgXLm8xsw8JWseeBhwdfuwRYBZKkpIGEvVtVHWqSOaKmiQnEVSRDiboDjICyIt6EjNrB/QA3gX2DRMowHqC6liRlKQGOCLZLWqS3NvdHzSzy+KqYOdG2dHMGgHPAGPdfXP8qD3u7mbmCfYbDYwGOOAAPdeRmhVLjmqAI5LdoibJneHPdWY2iGAuyebl7RSOzvMMMMndnw1Xf2lm+7n7OjPbD9hQ2r7ufh9wH0Bubm6piVQkWWJVq2qAI5LdoibJP5tZU+AKgv6RTYDflrWDBUXGB4EP3f3vcZteIKiuvSn8+XxFgxapCapaFZGo80m+FC5uAo6JeOwjgfOAD8xsYbjuDwTJ8SkzuxD4DDg7ergiyaNpqkSkuKjzSbYERhH0bSzax90vSLSPu78JWILNx0UPUaRmxLde1fNHEYHo1a3PA28AM9AUWZJB1HpVRMoSNUnu4e7qyygZIdGsHCo9ikhxUZPkS2Z2sru/ktRoRGqAZuUQkaiiJsnLgD+Y2Q8E3UGMoJujWjZIWlK1qohEEbV1a+PyPyUiIpJZypsqq6O7LzezUueNdPcFyQlLpPrFnkWqe4eIRFVeSfJygqHhbitlmwMJBzgXSQWJGumogY6IRFHeVFmjw59RBxAQSSlqpCMiVRF1MIFLCMZf3Ri+3wsY5u53JzM4kcpQ30cRqS5RW7eOcve7Ym/c/VszGwUoSUpKUN9HEUmGqEmyrpmZuzuAmdUFGiQvLJGKUbWqiCRD1CQ5DZhsZveG7y8K14nUquItVlWtKiLVKWqSvIqgleuY8P2/gAeSEpFIOdRiVURqStQkuTtwv7vfA0XVrbsB25IVmEgiqloVkZoSNUnOBAYCW8P3uwPTgX7JCEqkOLVYFZHaEDVJNnT3WILE3bea2R5JikkEUItVEal9UZPkd2bWMzYMnZn1ArYnLywRVauKSO2LmiTHAlPMbC3BDCCtgHOSFpVkNbVYFZFUEXUWkLlm1hHoEK5a4e47kxeWZLP4BKlqVRGpTVFLkhAkyE5AQ6CnmeHujyYnLMl2KkGKSCqIOnbr9cDRBEnyFeBnwJuAkqRUi9Jar4qI1LY6ET83BDgOWO/u5wPdgaZJi0qyTqyKFVA1q4ikjKjVrdvdvdDM8s2sCbABaJvEuCQLqO+jiKS6qElynpk1A+4H5hMMKvBO0qKSjKW+jyKSTqK2bv11uHiPmU0Dmrj74uSFJZlKfR9FJJ1EbbjzAvAk8Ly7r0pqRJLxVK0qIukianXrbQSDB/yvmc0lSJgvufv3SYtM0l581WqMWq6KSDqJ1LrV3WeHVa4HAfcCZxM03hFJKL7FaoyePYpIOok8mICZ7Q6cQlCi7Ak8kqygJHOoalVE0lnUZ5JPAX2AacCdwGx3L0xmYCIiIrUtaknyQWCYuxckMxhJfxo5R0QySdRnkq8pQUoUGjlHRDJJRQY4F4lEzyFFJFMoSUqlqYuHiGS6SNWtZjYzyjrJLuriISKZrsySpJk1BPYAWpjZXoCFm5oA+ksoqloVkYxWXnXrRcBYYH+Cgc1jSXIzQVcQyTJqvSoi2aTMJOnutwO3m9ml7n5HDcUkKUYzd4hItoo6C8gdZtYPaBe/j7s/mmgfM3sIGAxscPcu4brmwOTwOKuAs93920rGLjVEM3eISLaKOuLOY8DBwEIg1l/SgYRJEniYoEo2/jNXAzPd/SYzuzp8f1UFY5ZaoGePIpKNonYByQU6ubtHPbC7zzGzdsVWnwYcHS4/AsxCSTJlxapZ9exRRLJVpC4gwBKgVTWcb193Xxcurwf2TfRBMxttZvPMbF5eXl41nFoqKj5B6tmjiGSjqCXJFsAyM3sP+CG20t1PreyJ3d3NLGHJ1N3vA+4DyM3NjVyClaoprfWqqllFJFtFTZLjq+l8X5rZfu6+zsz2Q3NSppz40qNKkCKS7aK2bp1tZgcCh7r7DDPbA6hbifO9AIwAbgp/Pl+JY0g1U+lRRKR0UVu3jgJGA80JWrm2Bu4BjitjnycIGum0MLMvgOsJkuNTZnYh8BlwdlWCl8pT30cRkfJFrW69hGDS5XcB3P0jM9unrB3cfViCTQkTq9Qc9X0UESlf1CT5g7vvMAtGpTOzegT9JCXNFO/WoWpVEZHEoibJ2Wb2B2B3Mzse+DXwYvLCkuqUqGpV1aoiImWLmiSvBi4EPiAY9PwV4IFkBSXVS1WrIiKVEzVJ7g485O73A5hZ3XDdtmQFJlWjFqsiIlUXNUnOBAYCW8P3uwPTgX7JCEoqRy1WRUSqV9Qk2dDdYwkSd98a9pWUFKJqVRGR6hU1SX5nZj3dfQGAmfUCticvLKkItVgVEUmOqEnyMmCKma0FjGCw83OSFpVUiAYiFxFJjnKTpJnVARoAHYEO4eoV7r4zmYFJxagEKSJS/cpNku5eaGZ3uXsPgimzJAWU1npVRESqV9T5JGea2VkWG3JHal2sihVQNauISJJEfSZ5EXA5UGBm2wmeS7q7q/hSg9T3UUSkZkWdKqtxsgOR0qnvo4hI7Yk6VZYBw4H27n6jmbUF9nP395Ianajvo4hILYpa3Xo3UAgcC9xIMPLOXUDvJMWV9dT3UUSk9kVNkoe7e08zex/A3b81swZJjCsrabYOEZHUEjVJ7gwHNXcAM2tJULKUaqSqVRGR1BI1SU4EpgL7mNlfgCHAtUmLKouoxaqISOqK2rp1kpnNB44j6P5xurt/mNTIMpharIqIpIcyk6SZNQQuBg4hmHD5XnfPr4nAMpmqVUVE0kN5JclHgJ3AG8DPgJ8AY5MdVCaJLzXGqFpVRCQ9lJckO7l7VwAze8kN4FoAAA04SURBVBBQv8gKii81xqhaVUQkPZSXJItm+nD3fA3dGo0a44iIZIbykmR3M9scLhuwe/heY7cWo8Y4IiKZp8wk6e51ayqQdKfGOCIimSdqP0lJQMPHiYhkLiXJStDwcSIi2UFJshJUtSoikh2UJCNSi1URkeyjJFkGtVgVEcluSpJlULWqiEh2U5IshVqsiogIQJ3aDiAVxSdIVauKiGQvlSRDapgjIiLFZXWSVMMcEREpS1YnSTXMERGRsmRlklTDHBERiSJrkqSGkhMRkYqqlSRpZicBtwN1gQfc/aZkn1NVqyIiUlE1niTNrC5wF3A88AUw18xecPdlyT63qlZFRKQiaqMk2Qf42N0/ATCzJ4HTgGpPkv+5exSNN34IwO92FLBHg7rwz6bVfRoRkeRo1RV+lvSKNilDbQwm0BpYHff+i3DdLsxstJnNM7N5eXl5VT7pHg3q0qLRblU+joiIZI+Ubbjj7vcB9wHk5uZ6ZY5xxK/vr9aYREQku9RGSXIN0DbufZtwnYiISEqpjSQ5FzjUzNqbWQPgXOCFWohDRESkTDVe3eru+Wb2G+A1gi4gD7n70pqOQ0REpDy18kzS3V8BXqmNc4uIiESlqbJEREQSUJIUERFJQElSREQkASVJERGRBMy9Uv30a5SZ5QGfVXL3FsBX1RhOKtG1padMvbZMvS5I32s70N1b1nYQ6SwtkmRVmNk8d8+t7TiSQdeWnjL12jL1uiCzr03KpupWERGRBJQkRUREEsiGJHlfbQeQRLq29JSp15ap1wWZfW1Shox/JikiIlJZ2VCSFBERqRQlSRERkQRSOkma2UlmtsLMPjazq+PWH2tmC8xsiZk9YmYlBmo3s6PNbJOZvR8eY46ZDa7ZKyidmbU1s9fNbJmZLTWzy+K2dTezd8zsAzN70cyalLJ/OzPbHl7bh2b2npmNrNGLiMDMHjKzDWa2pNj6HDP7j5ktNLN5ZtanlH2PNrOXai7a6Mq4L98Ir2mhma01s+dK2Td2X8Y+N6Occ403s98l4zqKnaese3JyXLyrzGxhKfvH7smFca8GZZxvpJndmazrKeV8ie7FqL9vbmZ/jlvXwsx21uQ1SC1x95R8EUyjtRI4CGgALAI6EST21cBh4ef+BFxYyv5HAy/Fvc8BVgHHpcC17Qf0DJcbA/8FOoXv5wIDwuULgBtL2b8dsCTu/UHAQuD82r62YnEeBfSMjzVcPx34Wbh8MjCrvP+/VHklui9L+dwzwC+rel3AeOB3NXBdCe/JYp+7DRhXyvpd7skI5xsJ3FmD/2+J7sWov2+fAO/HrRsT/s5FvgagXk1dr17V90rlkmQf4GN3/8TddwBPAqcBewM73P2/4ef+BZxV3sHcfSFBQv0NgJm1NLNnzGxu+DoyXN/IzP4ZfrNcbGblHrui3H2duy8Il7cAHwKtw82HAXPC5ajX9glwOfA/4TXsGX5zfi8sbZ4Wrq9rZreGJfDFZnZp9V5ZibjmAN+UtgmIfWNvCqwt6zhm1if8tv++mb1tZh3C9SPN7Fkzm2ZmH5nZzdV6AaVLdF/Gx9sEOBYoUZJMJNH9GIqVdj4ys1HVcRHFlXNPxmI04GzgiajHTXQvhtqa2azwuq6vhstIqIx7Merv2zbgQzOLDShwDvBUbKOZnWJm74bXOMPM9g3Xjzezx8zsLeCx6rgWqVm1Mp9kRK0JSowxXwCHEwwNVc/Mct19HjAEaBvxmAuAK8Pl24EJ7v6mmR1AMAn0T4DrgE3u3hXAzPaq8pWUwczaAT2Ad8NVSwn+6D4HDKVi19YxXP4j8G93v8DMmgHvhdV6vyT4VpzjweTXzavjGiphLPCamd1KUDPQr5zPLwf6hzEPBP7Kj3/Mcgj+/X4AVpjZHe6+OsFxqkOi+zLe6cBMd9+c4Bj946osp7j7X0h8PwJ0A44A9gTeN7OX3b3MLxZVUco9WRQ38KW7f5Rg14Pjrustd7+ExPciBF84uhAkoLnhdc2rxkuJoiK/b08C55rZl0ABwZe7/cNtbwJHuLub2a+A3wNXhNs6AT919+1JiF+SLJWTZKnCm/BcYIKZ7UZQdVcQcXeLWx4IdAq+HAPQxMwahevPjTvft1WPOkEwwfmeAcbG/UG9AJhoZtcBLwA7oh4ubvkE4NS4Z1kNgQMIru0ed88HcPfSvlnXhDHAb939GTM7G3gwjC2RpsAjZnYoQSm0fty2me6+CcDMlgEHsmsSqw3DgAfK2P6Guxd/Pp7ofgR4PvwDu93MXidILpFLqRWR4J6MGUbZpciV7p5TbF2iexHgX+7+dXjeZ4GfAjWdJCvy+zYNuBH4EphcbFsbYLKZ7UdQDf9p3LYXlCDTVyonyTXs+q2uTbgOd3+H4FstZnYCQZVJFD0IqpEgKMEc4e7fx38g7o9UUplZfYI/RpPc/dnYendfTvCHBTM7DBgU8ZDx12bAWe6+otg5qxp2dRkBxBqGTKHshALBH6bX3f2MsJQzK27bD3HLBST/nk54X0LQoIMgiZ1RweOWdT8W78yclM7Nie7JcFs94EygV0UPS+n34uHU0HWVpSK/b+6+w8zmE5QQOwGnxm2+A/i7u79gZkcTPEuO+a6aw5YalMrPJOcCh5pZewtayZ1L8E0PM9sn/LkbcBVwT3kHM7NuBFWpd4WrpgOXxm2PfQP+F3BJ3Ppqr24Nn+08CHzo7n8vti12bXWAa4l2be2AWwl+USGoqrs0PA9m1iNc/y/govAPHrVY3boWGBAuHwskqr6LacqPiWhkkmKKKuF9GRpC0DDn+1L3TizR/Qhwmpk1NLO9CRr+zK1U5GUo654MDQSWu/sXFTx0onsR4Hgza25muxNUUb9VidCrpBK/b7cBV5VSCxN/j46o1iClVqVskgyrBH9D8Ev2IfCUuy8NN19pZh8Ci4EX3f3fCQ7TP3yQvoIgOf6Pu88Mt/0PkGtBA5ZlwMXh+j8De1nQuGURcEz1Xx1HAucBx9qPzeVPDrcNM7P/EjyHWwv8M8ExDg6v7UOCBgQT3T322RsJqiQXm9nS8D0EJbbPw/WLgJ9X+5XFMbMngHeADmb2hZldGG4aBdwWxvBXYHQpu9fjx1LizcD/mtn71HLtRzn3JQRJM3LDljiJ7kcI7vPXgf8QtL5MxvPIsu5JqPx1JboXAd4jKLkuBp5J5vPIMu7FqL9vALj7Und/pJRN44EpYUkzHafUkgQ0LJ2kJAv66bV299/Xdiwikr1S+ZmkZCkze5Cg1ePZtR2LiGQ3lSRFREQSSNlnkiIiIrVNSVJERCQBJUkREZEElCQlpZlZQdgdYamZLTKzK8I+bWXt087Mktq9paLM7O0q7DvSzPYv/5O77NPOis14ISIVpyQpqW67u+e4e2fgeOBnQHmDYbcjyX1AK8rdyxuftiwj+XGMUBGpQUqSkjbcfQPBwAO/sUA7C+ZwXBC+YonoJsJBxM3stxbMfnKLBbNrLDazi4of28xuMrP4kZbGm9nvLJgVZmZ4/A8sbhYLM/tleLxFZvZYuG5fM5sarlsUi8nMtoY/j7Zg5ounzWy5mU2KG41mXBjjEjO7L7zGIUAuMCm8nt3NrJeZzTaz+Wb2mgXjhRKuXxQO0lB0LSJSBbU9V5deepX1AraWsm4jsC+wB9AwXHcoMC9cPppd5xIdDVwbLu9GMIh2+2LH7AHMjnu/jGCM1npAk3BdC+BjgvFIOxPMudgi3NY8/DmZYHBwCOaebBp/HWFsmwjGfK1DMArMT+OPES4/BpwSLs8CcsPl+sDbQMvw/TnAQ+HyYuCocPkWKjC/o1566VX6S4MJSDqrD9wZjnNaQOKB7k8AuoWlMgjG2TyUuJka3P19M9snfPbXEvjW3VdbMOj3X83sKKCQYKqsfQnGnJ3i7l+F+8fG8jyWYEoy3L2AICEW956HY6BaMLVUO4Kplo4xs98TJP/mBNM4vVhs3w4EAy38KyyA1gXWWTANVTMP5k2EIMn+LMG/h4hEpCQpacXMDiJIiBsInk1+CXQnKJUlGlTcgEvd/bVyDj+FYIDyVvw4FdJwgqTZy913mtkqgumeqqLEzCVm1hC4m6DEuNrMxic4jwFL3b3vLiuDJCki1UzPJCVtmFlLglka7nR3JygRrnP3QoLBueuGH90CNI7b9TVgTFgqxMwOM7M9SznFZIKBvIcQJEzCc2wIE+QxBPNVAvwbGGrBzBzxM6rMJJgvk/BZaNOIlxdLiF9ZMKfjkLht8dezAmhpZn3Dc9Q3s87uvhHYaGY/DT83POJ5RaQMSpKS6naPdQEBZhBMKXVDuO1uYETYUKUjP87btxgoCBux/JZg9pNlwIKwW8S9lFKL4sFsHo2BNe6+Llw9iWB2jg8IqlGXx332L8Ds8Pyx6aUuI6g2/QCYTzDvYLnCJHc/sIQgqcdPh/UwcE9YNVuXIIH+LTzvQiDWYOl84K7wcykzeahIOtPYrSIiIgmoJCkiIpKAkqSIiEgCSpIiIiIJKEmKiIgkoCQpIiKSgJKkiIhIAkqSIiIiCfx/STVZCbOow3sAAAAASUVORK5CYII=\n", + "image/png": 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\n", 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" ] @@ -8335,7 +8335,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **psychosis schiz bipolar**" + "### COVID vaccinations among **80+** population by **psychosis schiz bipolar**" ], "text/plain": [ "" @@ -8346,7 +8346,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8359,7 +8359,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **LD**" + "### COVID vaccinations among **80+** population by **LD**" ], "text/plain": [ "" @@ -8370,7 +8370,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8383,7 +8383,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **80+** population by **ssri**" + "### COVID vaccinations among **80+** population by **ssri**" ], "text/plain": [ "" @@ -8394,7 +8394,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8408,7 +8408,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **70-79** population up to 30 Mar 2021" + " ## COVID vaccination rollout among **70-79** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -8420,7 +8420,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **sex**" + "### COVID vaccinations among **70-79** population by **sex**" ], "text/plain": [ "" @@ -8431,7 +8431,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8444,7 +8444,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **ageband 5yr**" + "### COVID vaccinations among **70-79** population by **ageband 5yr**" ], "text/plain": [ "" @@ -8455,7 +8455,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8468,7 +8468,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **ethnicity 6 groups**" + "### COVID vaccinations among **70-79** population by **ethnicity 6 groups**" ], "text/plain": [ "" @@ -8479,7 +8479,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8492,7 +8492,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **imd categories**" + "### COVID vaccinations among **70-79** population by **imd categories**" ], "text/plain": [ "" @@ -8503,7 +8503,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8516,7 +8516,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **bmi**" + "### COVID vaccinations among **70-79** population by **bmi**" ], "text/plain": [ "" @@ -8527,7 +8527,7 @@ }, { "data": { - "image/png": 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\n", 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y6HlcXyA9117SPfuLw1i7IKlLN3Jo3lZ++JcKL3RRVFRkc+fOXThp0qSc3/3ud60GDBjwyZgxYw5t0KDBns8//3z+u+++26BPnz55AKtXr67z+9//vuWMGTM+ady48Z6bbrqpxW233dY8MkNYkyZNihYsWBDzXss77rij2V//+tfmu3btqvXaa68tBli5cmW93r17F98G0qpVq51ffvllPeC7RONPWUvZ3W909zbungsMA/7j7sOBacCQ8GUXA8+lKgYRkXT7cPk3rNoYfDE8vElD9Run2NChQ78BOP74479bsWJFPYCZM2cedOGFF26AYIrO9u3bbwWYPn16wyVLltTv1atXx44dO+Y98cQTTZYvX168BvNFF130Tbz3ufHGG9d9+eWX80aPHr3i1ltvbZms+FPap1z8JmYnA9eFt0S1I7gl6hDgQ+DH7r6jtOMLCws91jdyEZFMV9X9yNGqY5/ykiVL6p5++untlyxZMh/g17/+dcuioiIbO3bsqui+4tWrV9cpLCzstHLlyrn9+/c/8pe//OXaQYMGbQbIy8vrNG7cuGUrVqyo+/jjjx8yZcqUL0q+T+vWrfNnzZq1sGXLlqXeA7p7924OPvjggs2bN8+58cYbWwDccccdawD69u179OjRo1f1799/n5ZyWvqUo7n7dHcfGD7+3N17uftR7j60rIQsIpItYt3ypFudkqtNmzZFX3/9dZ01a9bU3rZtm73yyiulz+IE9O3bd8vEiRMPAXj//ffrf/LJJwcCnHzyyd/NmjXroHnz5h0AsGnTploff/zxAaWdC2Du3LnFr5k0aVLO4YcfvgPgnHPO+Xby5MmHbNu2zRYtWlRv6dKl9U8++eSES9dQw6bZFBFJpcgtT9HTY+pWp+Q64IAD/Fe/+tXqnj17dmrevPmuo446av8ZoEq47rrr1g4bNuyIdu3adT7qqKO25+XlfQfQqlWrogceeGDpsGHD2u3cudMAbr311pVdu3YttbE4duzYQ994443GderU8ZycnKLx48d/AVBYWLj9hz/84dft27fvXLt2bcaOHbus5MjrslRJ+bqyVL4WkWyQ1FL1SzcEf3//zgqfojqWr6uD0srXaimLiFRQUheRmPUozI1a/3zZTDi8byUjlGyjpCwiUkEly9XlLlVHJ+JlM4O/I4n48L6QPyT2cVJtKSmLiFRChRaRiCTj6EQcScKFlyQ/yOTas2fPHqtVq1bm931moD179hiwJ95+JWURkQSULFVDJcrVc5+CNXOzKRFHm7du3bq8Zs2abVRiLp89e/bYunXrcoB58V6jpCwikoCkjKyOtJDXzIUW+XDJCymINLWKiop+umbNmofWrFnThSq6rbYa2QPMKyoq+mm8Fygpi4gkqFKlati3XJ2l/cXHHHPMWmBQuuOorpSURURCsUrUEeUuVWd3v7GkiZKyiEgoVok6otyl6uzuN5Y0UVIWEYlSoRJ1RHSpOov7jSV9lJRFpEZK6mjqWKXqFvlZ228s6aOkLCI1UlJHU5ccwKVStVSQkrKI1FiVKlWD+o0l6ZSURaTaS0mpGtRvLEmnpCwi1V6FS9UlF4kA9RtLSikpi0iNUK5Sday+4giVqiWFlJRFJKuVNuFHRLlL1eorljRRUhaRrFbahB8R5R5VDeorlrRQUhaRrFfpUdQRJReMEKliSsoikjWSOoo6opotGCHZTUlZRLJGUib8KCm6Zaw+ZEkzJWURySopK1Wr/1gygJKyiGSUpC6fGEu8qTFFMoCSsohklKQun1jW5B8qVUuGUVIWkYyTtBJ1rJHUSsaSwZSURaR60dzUksXKTMpm1gYYBpwAtAK2AfOAF4CX3H1PSiMUkWonJf3GWtNYqoFSk7KZPQq0Bv4N/AFYC9QH2gMDgJvM7AZ3n5HqQEWk+khJv7H6iqUaKKulfI+7z4uxfR4w2czqAW2TH5aIVHdJ7zdWMpZqoNSkHJ2QzawB0NbdF0ft3wl8lrrwRCSbJLI4BCR5Fi71G0s1ktBALzMbBNwN1AOOMLMC4HfuPiiVwYlIdklkcQhIwq1N6jeWairR0de3Ar2A6QDuPsfMjkhVUCKSvZI+4xbsv66xStVSTSWalHe5+0Yzi97mKYhHRLJEShaHiKY5qaUGSjQpzzezC4DaZnY08EvgrdSFJSKZLiWLQ4DmpJYaLdGkfCVwE7AD+CfwCnB7qoISkeyQ8lK1+oqlhkk0KXd095sIEnNCzKw+MAM4IHyfp9z91rAv+gmgCTAbuDAcxS0iGaxkuVqlapHkSzQp32NmLYCngElx7l0uaQdwqrtvMbO6wEwzewm4Fvijuz9hZuOAnwB/q0jwIlJ1Spark1KqjqZStUhiSdndTwmT8rnAA2bWmCA5xy1hu7sDW8KndcM/DpwKXBBunwCMRklZJCskrVwdUbL/WKSGS3hBCndfA9xnZtOAXwO3UEa/spnVJihRHwX8BVgCfOvuReFLVhBM4ykiGSTlI6u1prFITIlOHtIJOA84B9gATAJ+VdZx7r4bKDCzg4FngI6JBmZmI4GRAG3baiZPkaqUspHVEZoaUySmRFvKjxAk4jPcfVV538Tdvw1b2McBB5tZnbC13AaIOSefuz8IPAhQWFioe6JFqljSS9UlqQ9ZZD+J9imX+3+mmTUjmHTk23De7NMIVpqaBgwhGIF9MfBcec8tIslTZaXqaOpDFomprKUbn3T3c81sLvvO4GUEY7m6lnJ4S2BC2K9cC3jS3f9tZguAJ8zsduBD4OHKfQQRqYyUTwJScopM0HzVInGU1VK+Kvx7YHlP7O4fA91jbP+cYB5tEckQKSlVq99YpNzKWrpxdfjwf9z9+uh9ZvYH4Pr9jxKRTJXyUnVJ6jcWKZdEB3qdxv4J+PsxtolIBkt5qTqa+o1Fyq2sPuXLgf8B2pnZx1G7GgFvpjIwEUmNKllaEdRvLFIBZbWU/wm8BNwB3BC1fbO7f52yqEQkKVIyX3WsAVzqNxZJirL6lDcCG4HzAczsUKA+cJCZHeTuy1MfoohUVErmq9YALpGUSXRGr7OAsUArYC1wOLAQ6Jy60EQkGVIysloDuERSItGBXrcDvYHX3b27mZ0C/Dh1YYlIomKNqI5IySQgGsAlkjKJJuVd7r7BzGqZWS13n2Zmf0ppZCKSkFgjqiMqXa6ON5hLA7hEUiLRpPytmR0EzAAmmtla4LvUhSUi5ZGyJRU1mEukSiWalAcD24FrgOFADvC7VAUlIqWLLlmnZPIPDeYSSYtEF6SIbhVPSFEsIpKg6JJ1UpdULNlvrMFcIlWqrMlDNrPvQhTFuwgWpEjR3HwiUpaUzletiT9E0qKs+5QbVVUgIpIm0YO51EIWSatE71NuG2u7Jg8RSZ0qu9UpunWsFrJIWiU60Cv6a3N94AhgMZo8RCRlUnqrE6j/WCQDJTrQa5+ZAsysB8FCFSKSQim71Ql037FIBkq0pbwPd//AzI5NdjAiNVXK1znWfcciWSHRPuVro57WAnoAq1ISkUgNlLJ1jiN037FIVki0pRw9CruIoI/56eSHI1JzpWSd4wj1G4tkhUT7lH+b6kBEaoqkl6pLJuHoEnWERlWLZIVEy9eFwE0ESzYWH+PuXVMUl0i1lZRSdbwBW5G/VaIWyUqJlq8nAqOAucCe1IUjUjNUulQdfSuTkrBItZFoUl7n7s+nNBKRaiRlE3/o3mKRai3RpHyrmT0ETAV2RDa6++SURCWS5ZI68YfuLRapMRJNypcAHYG67C1fO6CkLBJHpUvUurdYpMZJNCn3dPcOKY1EpBqIlK2TMvGH7i0WqXESTcpvmVmeuy9IaTQiWS46IVd44g/1G4vUWIkm5d7AHDP7gqBPObKesm6JEimhXGXrWBN9qN9YpMZKNCkPSGkUIlkkqSOro1vEESpXi9RYiSZlT2kUIlkk6UsqqkQtIqHyrKfsBGVrracsNV6lRlZHl6xLtpJFpEbTesoipUjqPNWxbnHSnNQiEkXrKYuUIqnzVJccwKU+YxEpQespi5QhafNUKxmLSBm0nrJIDJWeBCRWv7EGc4lIGbSeskgMFZ4ERP3GIlIJiZavXwOGuvu34fPvAU+4+xmpDE4knSo0CYj6jUWkEhItXzeLJGQAd//GzA4t7QAzOwz4B9Cc4HaqB939XjM7BJgE5AJLgXPd/ZsKxC6SFEkZYa1+YxFJgloJvm63mbWNPDGzwyl7QpEi4FfunkcwTecvzCwPuAGY6u5HEywFeUP5wxZJnkipOlqlJgFRQhaRCkq0pXwTMNPM/kswgcgJwMjSDnD31cDq8PFmM1sItAYGAyeHL5sATAeuL2/gIslUoRHWmgRERJIs0YFeL4cThvQON13t7usTfRMzywW6A+8CzcOEDbCGoLwd65iRhIm/bdu2sV4iUm5JKVVrMJeIpEipSdnMct19KUCYhP9dYr8Brd19RSnnOIjg9qmr3X1TcEjA3d3MYpbB3f1B4EGAwsJCzb0tSZGUyUDUfywiKVJWS/luM6sFPAfMBtYRzH19FHAK0A+4FYiZlM2sLkFCnujuk8PNX5lZS3dfbWYtgbWV/xgiiUtaqVr3HYtIkpWalN19aDg4azhwKdAS2AosBF4E/tfdt8c6NmxFPwwsdPexUbueBy4G7gz/fq6yH0IkZVSqFpEqVGafsrsvIBjoVV59gAuBuWY2J9z2G4Jk/KSZ/QRYBpxbgXOLlEm3OolItqnQghSJcPeZBCO1Y+mXqvcViUhK/zGoVC0iVSZlSVkkE1R4MYlI2Vq3OolIFVJSlmqjZLk64VJ19CCuiJLTZYqIVIGEZvQys6mJbBNJp5IzcyVcqo60iKMd3hcG/kkzdIlIlSrrPuX6wIFA03ARikgfcWOC2blEMkqFy9XqNxaRDFBW+frnwNVAK4L7lCNJeRNwfwrjEokp1ojqiArPzKV+YxHJEGXdp3wvcK+ZXenuf66imETiijWiOiKhcnV0/7H6jUUkwyQ69/Wfzex4guUW60Rt/0eK4hKJq1IzckUnYt17LCIZJqGkbGaPAUcCc4Dd4WYnWC9ZJKWiS9blLlFHaBIQEckCid4SVQjkubsWhpAqF12yLtfkH5qvWkSyTKJJeR7QgnB9ZJGqVq6StearFpEslWhSbgosMLP3gB2Rje4+KCVRSY1VqfmqYyVjlapFJIskmpRHpzIIkYhyz1dd2mhqJWMRyTKJjr7+r5kdDhzt7q+b2YFA7dSGJjVVuUrV0fcZKxmLSJZLdPT1z4CRwCEEo7BbA+PQak+SJJGydblL1RrAJSLVSEJzXwO/IFgfeROAu38KHJqqoKTmiU7I5ZqvWgO4RKQaSbRPeYe77zQLZtk0szoE9ymLJE1CZWu1kEWkGku0pfxfM/sN0MDMTgP+BUxJXVhSU/zz3eWc98Db+6zuVCq1kEWkGku0pXwD8BNgLsEiFS8CD6UqKKk5EipbaxIQEakhEk3KDYBH3P3vAGZWO9y2NVWBSc0Rt2ytSUBEpIZJNClPBfoDW8LnDYBXgeNTEZRUL+VablH3HYtIDZZoUq7v7pGEjLtvCe9VFilTuZZb1H3HIlKDJZqUvzOzHu7+AYCZHQNsS11YUt2UObJao6pFRBJOylcB/zKzVYARLE5xXsqikqyX8HKL8earFhGpgcpMymZWC6gHdAQ6hJsXu/uuVAYm2a3U5RbVbywiElOZSdnd95jZX9y9O8ESjiIJiVuyVr+xiEhMCY++NrNzgMnurpm8BCjnqGpQv7GISBkSTco/B64FdpvZNoJ+ZXf3BFYOkOqqtFHVV+bMZPCOt+DR+ns3qt9YRKRUiS7d2CjVgUh2ymvZmEnHLNrbRxyxOkzAjfru3aZStYhIqRJdutGA4cAR7n6bmR0GtHT391IanWSH6JJ0hBKwiEi5JVq+/iuwBzgVuI1gZq+/AD1TFJdkiIT7jdVHLCJSaYmuEnWsu/8C2A7g7t8Q3CYl1Vyk3ziWK3Nmct+Om4NWsoiIVFqiLeVd4SIUDmBmzQhazlIDxL216dHbYc2nWiRCRCRJEk3K9wHPAIea2f8CQ4CbUxaVpEWsUnWps3GBytYiIkmU6OjriWY2G+hHcDvUD919YUojkyoX6xan4tm4omfhiig5uEtERCql1MN1H08AAA/zSURBVKRsZvWBy4CjgLnAA+5eVBWBSXrsV6qe9SjMvX3fe4wjVLYWEUmqslrKE4BdwBvA94FOwNWpDkpSp9yzcEVud9ItTiIiKVdWUs5z93wAM3sY0H3JWa5caxtHqN9YRKRKlJWUi1eCcveiYA6RxJjZI8BAYK27dwm3HQJMAnKBpcC54e1VUoXKXNsY9p+nWkREUq6spNzNzCI3qRrQIHyeyNzX44H7gX9EbbsBmOrud5rZDeHz6ysUucRV4YUiommeahGRKldqUnb32hU9sbvPMLPcEpsHAyeHjycA01FSTrqEStTx1jSOUB+yiEiVS/Q+5WRp7u6rw8drgObxXmhmI4GRAG3btq2C0KqXMkvUj2pNYxGRTFPVSbmYu7uZxV2b2d0fBB4EKCws1BrOyaI1jUVEMlZVJ+WvzKylu682s5bA2ip+/5orkozVVywikrGqOik/D1wM3Bn+/VwVv3/NEq/fWKVqEZGMlLKkbGaPEwzqampmK4BbCZLxk2b2E2AZcG6q3r+mKHW+6rnqNxYRySYpS8rufn6cXf1S9Z41UanzVS9A/cYiIlkkbQO9JHnizletiT9ERLKKknIWiVWqzls9mSH13oZHc/Zu1GAuEZGspKScRWKVqofUe5uj9ywFuu19ofqPRUSykpJylikuVUdGVttyaN1N/cYiItWAknIGK1mu3qdUrRK1iEi1o6ScwSLl6itzZtJn2zQ6Mxd2AvRViVpEpBpSUs5weS0bM7LeB7B9uRKxiEg1p6ScIUodWW3Ldb+xiEgNoKScIUqWqoG95Wr1G4uI1AhKyukUNTf1LRs2Qj3ovHFusO/wvoDK1SIiNYmSchUqWaK+ZcPD5O76nKV127F1524OrFdb/cYiIjWYknIVKlmijiTk3zW5G4DBBa3pfGzbNEcpIiLpoqRchfptfZFb6k3bp0TdOX8IkwqPK/1AERGpEZSUUy2q33jkRq1pLCIi8Skpp0ik/3iffmPy+DCnPyMvuS3d4YmISAZSUk6RSP8x9div31hERCQWJeUUKe4/Dif+mHSJ+o1FRKR0SspJFilbX7fxdXJtGbTtrok/REQkIUrKSbblrb9z3cbXybNlbPleJxpqakwREUmQknKS9dk2jVxbRsO23WmoFrKIiJSDknIlxFpE4rqdu1larx2d1UIWEZFyUlKuhFiLSOTaMrYc1CnNkYmISDZSUq6EWDN0gcrWIiJSMUrKCYpZqo6MsNYMXSIikgRKygmKW6rWCGsREUkSJeUEqVQtIiKppqQcQ3Sput/WF+mzbRojd0YlY5WqRUQkBZSUY4iUqvNaNi5e93h+vXy2HH02xw79VbrDExGRakpJOYbiUnW9HLDl0La77jsWEZGUU1Jmb7l6v1I1faFFvuauFhGRKqGkzN75qnuyAEClahERSQslZfbOV03bYBBXZw3iEhGRNKhxSVnzVYuISKaqcUlZ81WLiEimqnFJWZOAiIhIpqoRSTm6ZK35qkVEJFOlJSmb2QDgXqA28JC735nK94uMrj6wXm3NVy0iIhmrypOymdUG/gKcBqwA3jez5919QdLf7KUbYM1cRm6cGTxvqVK1iIhkrnS0lHsBn7n75wBm9gQwGEh6Un7niw00+nYjW8njw5z+jLzktmS/hYiISNKkIym3Br6Mer4COLbki8xsJDASoG3bthV6o1cOu5oFtTcBMLigdYXOISIiUlUydqCXuz8IPAhQWFjoFTnHrWd1TmpMIiIiqVQrDe+5Ejgs6nmbcJuIiEiNlo6k/D5wtJkdYWb1gGHA82mIQ0REJKNUefna3YvM7ArgFYJboh5x9/lVHYeIiEimSUufsru/CLyYjvcWERHJVOkoX4uIiEgMSsoiIiIZQklZREQkQygpi4iIZAhzr9C8HFXKzNYByyp4eFNgfRLDqWrZHH82xw7ZHX82xw7ZHX8mxX64uzdLdxCSuKxIypVhZrPcvTDdcVRUNsefzbFDdsefzbFDdsefzbFL+ql8LSIikiGUlEVERDJETUjKD6Y7gErK5vizOXbI7vizOXbI7vizOXZJs2rfpywiIpItakJLWUREJCsoKYuIiGSIjE7KZjbAzBab2WdmdkPU9lPN7AMzm2dmE8xsv4U1zOxkM9toZh+G55hhZgOrMPbDzGyamS0ws/lmdlXUvm5m9raZzTWzKWbWOMbxuWa2LYx/oZm9Z2Yjqir+ErE8YmZrzWxeie0FZvaOmc0xs1lm1ivGsSeb2b+rLtp93jve9fNGGPMcM1tlZs/GODZy/URe93oZ7zXazK5LUtylXTuTomJaamZzYhwfuXbmRP2pV8r7jTCz+5MRe3i+eNdLote9m9ntUduamtmuZMZYllKunX7h7545ZjbTzI4q5RzPmtk7VROxVBvunpF/CJZ1XAK0A+oBHwF5BF8kvgTah6/7HfCTGMefDPw76nkBsBToV0XxtwR6hI8bAZ8AeeHz94GTwseXArfFOD4XmBf1vB0wB7gkDf8WJwI9ouMJt78KfD98/ANgeln/Dum+fmK87mngosrGDYwGrkv1tVPidfcAt5R17STwfiOA+6vgekn0uv8c+DBq2+XhtZ9wjECdVFw74b9Fp/Dx/wDj45zj4PD31EKgXTnfv8Kx60/2/8nklnIv4DN3/9zddwJPAIOBJsBOd/8kfN1rwDllnczd5xAk8CsAzKyZmT1tZu+Hf/qE2w8ys0fDb/Mfm1mZ547zfqvd/YPw8WaC/5ytw93tgRnljP9z4Frgl2GcDcMWyXtha3pwuL22mY0Jqwgfm9mVFYm/xHvPAL6OtQuItHZygFWlncfMeoUtpQ/N7C0z6xBuH2Fmk83sZTP71MzuqmzMxL9+ouNpDJwK7NdSLuUzxLxuQpGW4Kdm9rOKBl7GtROJw4BzgcfLEXvMayZ0mJlND2O/taKxhzHHu14Sve63AgvNLDIBx3nAk1Gf4ywzezf8DK+bWfNw+2gze8zM3gQeq8RHKO3aSfSa/xEwJTx2WFTs481sXFhZ+sTC6l34f+B5M/sPMLUSsUuWS8t6yglqTfBNM2IFcCzB9HV1zKzQ3WcBQ4DDEjznB8Co8PG9wB/dfaaZtQVeAToB/w/Y6O75AGb2vcp+EDPLBboD74ab5hP8J38WGFrO+DuGj28C/uPul5rZwcB7YYn1IoLWRoG7F5nZIZWNvxRXA6+Y2RiCCsbxZbx+EXBCGFd/4Pfs/cVcQPAz2gEsNrM/u/uXcc6TiHjXT7QfAlPdfVOcc5wQVR7+l7v/L/GvG4CuQG+gIfChmb3g7qV+USlLjGunODbgK3f/NM6hR0bF/qa7/4L41wwEiagLQUJ8P4x9VmVij6E81/0TwDAz+wrYTZD8WoX7ZgK93d3N7KfAr4FfhfvygL7uvq0ScZZ27fwUeNHMtgGbCP69YzmfoBHwFUE15vdR+3IJft5HAtOiSuA9gK7uHusLjdQQmZyUYwr/Iw4D/mhmBxCUUHcneLhFPe4P5AUNDgAam9lB4fbib7bu/k1l4g3P+TRwddQv/0uB+8zs/wHPAzsTPV3U49OBQba3H7M+0JYg/nHuXhTGn8r/4JcD17j702Z2LvBw+P7x5AATzOxoghZH3ah9U919I4CZLQAOZ99fjKlwPvBQKfvfcPeS4xDiXTcAz4XJYJuZTSP4xZtwK7ykONdOdOyltZKXuHtBiW3xrhmA19x9Q/i+k4G+QLKTcnmu+5eB2wiS2qQS+9oAk8ysJUF5+Yuofc9XMiGX5RrgB+7+rpmNAsYSJOpiYcv9aGBm+Ptql5l1cfdIH/uT7r4H+NTMPmfvF+3XlJAlk5PySvb9Jt0m3Ia7v03QUsDMTicoiyWiO0EpEIKWXW933x79gqhftpVmZnUJfqlOdPfJke3uvojgFyRm1h44M8FTRsdvwDnuvrjEe1Y27PK4GIgMQvoXpSc4CH7JTnP3s8MW4PSofTuiHu+m8tdm3OsHgsFDBEnz7HKet7TrpuRN/xWeBCDetRPuq0NQHj2mvKcl9jVzbIxYkz6BQXmue3ffaWazCVrAecCgqN1/Bsa6+/NmdjJBf37Ed0kINea1Y2bNgG7uHqlaTCL48lDSucD3gC/C66IxwZeom8L98X7WyYhdslwm9ym/DxxtZkdYMHJ0GMG3a8zs0PDvA4DrgXFlnczMuhKUpv8SbnoVuDJqf6RV8Rrwi6jtFSpfh31+DwML3X1siX2R+GsBNycYfy4whuAXEgRl0yvD98HMukfF//PwFzcpLl+vAk4KH58KxCulRuSwNzGOSFFMEXGvn9AQgoFc22MeHV+86wZgsJnVN7MmBAPF3q9I4KVdO6H+wCJ3X1HOU8e7ZgBOM7NDzKwBQVn/zQqEXqoKXPf3ANfHaD1GX0cXJzXIQLxr5xsgJ/xCAXAae78kRzsfGODuue6eS/DlaVjU/qFmVsvMjiQYTLY4xjmkhsrYpByWX68g+EWykKDkMz/cPcrMFgIfA1Pc/T9xTnNCOBhkMUEy/qW7RwZR/BIotGAw1ALgsnD77cD3LBgo9RFwSgU/Qh/gQuBU23tbyg/Cfeeb2ScEfayrgEfjnOPIMP6FBANd7nP3yGtvIyj/fmxm88PnELRWl4fbPwIuqGD8xczsceBtoIOZrTCzn4S7fgbcE77P74GRMQ6vw95W8F3AHWb2ISmu0pRx/UDwSzLhQVJR4l03EFyP04B3CEYWV7Q/ubRrpzKxx7tmAN4jaJl/DDxdmf7kUq6XRK97ANx9vrtPiLFrNPCvsCWd9CUS41074fafAU+H1/yF7B2jAhR/eT6c4BqInO8LYGNYkYDg/+d7wEvAZRX4YijVmKbZlJSy4B7b1u7+63THIpJuZjaeoELzVLpjkcyUyX3KkuXM7GGCEb3npjsWEZFsoJayiIhIhsjYPmUREZGaRklZREQkQygpi4iIZAglZZESzGx3eBvSfDP7yMx+Fd5bW9oxuWZW6dvPRKRmU1IW2d82dy9w984EE0R8HyhrkYZcknBPuIjUbBp9LVKCmW1x94OinrcjmOWpKcHEEI8RLDoBcIW7v2XBurmdCOZhngDcB9xJMLPXAcBf3P2BKvsQIpKVlJRFSiiZlMNt3wIdgM3AHnffHi6s8bi7F4ZzMF8XWcDCzEYCh7r77eF0sG8CQ8PZnUREYtLkISLlUxe4P5zzejfxF0M5HehqZkPC5zkEKwcpKYtIXErKImUIy9e7gbUEfctfAd0IxmTEm7fYgCvd/ZUqCVJEqgUN9BIpRbhc3zjgfg/6enKA1eF6uBcCtcOXbgYaRR36CnB5uAQjZtbezBoiIlIKtZRF9tfAzOYQlKqLCAZ2RZZQ/CvBKkEXEaylG1kD92Ngd7h60HjgXoIR2R+ESyWuI1gSUUQkLg30EhERyRAqX4uIiGQIJWUREZEMoaQsIiKSIZSURUREMoSSsoiISIZQUhYREckQSsoiIiIZ4v8D01kak2BlZ0oAAAAASUVORK5CYII=\n", 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" ] @@ -8540,7 +8540,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **chronic cardiac disease**" + "### COVID vaccinations among **70-79** population by **chronic cardiac disease**" ], "text/plain": [ "" @@ -8551,7 +8551,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8564,7 +8564,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **current copd**" + "### COVID vaccinations among **70-79** population by **current copd**" ], "text/plain": [ "" @@ -8575,7 +8575,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8588,7 +8588,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **dialysis**" + "### COVID vaccinations among **70-79** population by **dialysis**" ], "text/plain": [ "" @@ -8599,7 +8599,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8612,7 +8612,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **dementia**" + "### COVID vaccinations among **70-79** population by **dementia**" ], "text/plain": [ "" @@ -8623,7 +8623,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8636,7 +8636,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **psychosis schiz bipolar**" + "### COVID vaccinations among **70-79** population by **psychosis schiz bipolar**" ], "text/plain": [ "" @@ -8647,7 +8647,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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aFKxatape/fr1fc+ePdayZcu8X/ziF98ccMAB+ffee2/z5Gf/gZKkiEgFFVarKjFWnQYNGni/fv22Nm3aNL9u3br87Gc/27ps2bIGvXv37giw3377FTz00EOrVqxYsc/vf//7NllZWdStW9fvuOOOz8tyHSVJEZFyUrtj9cnPz2fx4sUNH3vssU8Lt11zzTWbrrnmmk2xr+vcufOuYcOGLS/vdTSZgIhIOWlSgOqxaNGiBocddljX/v37b+3atWupC2RUlEqSIiJlENs5RyXI6tGrV6/v16xZ80FVXEtJUkQkgdiEWCi2c04tLUEWFBQUWFZWVurXWawiBQUFBhTE26ckKSKSQGx1aiF1zmFpbm5upxYtWmypCYmyoKDAcnNzmwBL4+1XkhQRKUYdchLLy8u7aMOGDdM2bNjQhZrRr6UAWJqXl3dRvJ1KkiIioXjjHWthdWqpevXqtQk4vbrjqCpKkiIiIY13lOKUJEWkVlNvVSlNTahPFhEpt8LSI1Bbe6tKKVSSFJFaSZ1zJAolSRGpVdQ5R8pCSVJEarzSlrBS5xwpjZKkiNRYWsJKKkpJUkRqLA3pkIpSkhSRGkVDOqQyKUmKSI0Qr2pVQzqkopQkRSSjJeqtqqpVqQxKkiKS0dTuKKmkJCkiGUftjlJVlCRFJO0VX/xY7Y5SVZQkRSQtJZoAoPBfVa1KVVCSFJG0ogkAJJ0oSYpItdO0cZKulCRFpNrFrsah5CjpRElSRNKCeqhKOkqaJM2sDXAO0B84BNgJLAWeA15w94KURigiNVbxNR1F0k2pSdLM/gG0Bp4F/gJsAhoARwODgavM7Ep3n5/qQEWk5tCajpIpkpUk/+ruS+NsXwo8YWb1ATUciEiZaJYcyRSlJsnYBGlm+wKHuvvKmP27gU/iHWtmDYD5wD7hdWa6+7Vm1h54BDgQWAScF55HRGowzZIjmSgryovM7HRgCTA7fJ5tZs8kOWwXcKK7dweygcFmdixBte0Udz8S+Ba4sLzBi0j6+9fbX3D2XW/yhyc/KKpe1Sw5kimi9m69FugDzANw9yVhiTAhd3dge/i0XvjjwInAz8Pt9wOTgf8rS9Aikv60OofUBFGT5B5332Jmsds82UFmVoegSvVI4HbgU2Czu+eFL1lD0DEo3rFjgbEAhx6qPyqRTKBJAaSmiZokl5nZz4E6ZnYU8CvgjWQHuXs+kG1mTYEngY5RA3P3u4G7AXJycpImZBGpfpoUQGqaqEnycuAqgnbGfwEvAn+KehF332xmc4G+QFMzqxuWJtsAa0s/WkTSXfHxjuqQIzVF1CTZ0d2vIkiUkZhZC4Jq2s1hz9iTCDrtzAWGE/RwHQ08XbaQRSQdlFa1KlJTRE2SfzWzVsBMYEaCsZPFHQzcH7ZLZgGPuvuzZrYceMTM/gS8C9xbnsBFpHpolQ6pTSIlSXc/IUySZwF3mVljgmSZsMrV3d8HesTZ/hlBT1kRyUCaCEBqk8gTnLv7BmBq2Lb4O2ASZWiXFJGaQ+2OUltEnUzgR2Y22cw+AG4l6NnaJqWRiUhaKZwUYPn6rdUdikiViVqSvA+YAZzi7utSGI+IpBF1zpHaLmqbpOpVRGohjXuU2i7ZUlmPuvtZYTVr7IB+I5h5rltKoxORaqFxjyKBZCXJX4f/Dk11ICKSPmITpKpWpTZLtlTW+vDhL9x9Yuw+M/sLMLHkUSKSqVSCFNlb1I47J1EyIf4kzjYRyTDqnCOSWLI2yXHAL4DDzez9mF2NgNdTGZiIVA11zhFJLFlJ8l/AC8D/AlfGbN/m7t+kLCoRSTlVrYokl6xNcguwBRgJYGYtgQZAQzNr6O5fpD5EEaksqloVKZtIbZJmdhrwN+AQYBNwGPAh0Dl1oYlIZVPVqkjZRO248yfgWGCOu/cwsxOAc1MXlohUJlWtipRPpLlbCdaF/BrIMrMsd58L5KQwLhGpRBr3KFI+UUuSm82sITAfeMjMNgHfpS4sESmv2HbHQipBipRP1CR5BvA98N/AKKAJ8MdUBSUiZRdvMeRCKkGKlE/UCc5jS433pygWESmHeMlRHXJEKkeyyQS2sffE5kW7CCY4b5ySqESkVKUN5VByFKk8ycZJNqqqQEQkOg3lEKkaUcdJxv3r02QCIlVLQzlEqlbUjjvPxTxuALQHVqLJBESqlIZyiFStqB13usY+N7OeBBOfi0iKxbY/qgQpUrWiliT34u6LzeyYyg5GRH4Qr9eqSpAiVStqm+QVMU+zgJ7AupREJFLLaUiHSPqIWpKM7eWaR9BG+XjlhyNSO2lIh0h6itomeV2qAxGpzTSkQyQ9Ra1uzQGuIlgiq+gYd++WorhEagUN6RBJb1GrWx8CJgAfAAWpC0ekdtGQDpH0FjVJ5rr7MymNRKSW0JAOkcwRNUlea2bTgJeBXYUb3f2JlEQlUgNpSIdI5omaJM8HOgL1+KG61QElSZEkNKRDJHNFTZK93b1DSiMRqUE0pEOkZoiaJN8ws07uvjyl0YhkuHilRiVHkcwVNUkeCywxs1UEbZKF60lqCIhIjMLeqkqMIjVD1CQ5OKVRiGQ4jXcUqZmiJklPaRQiGU7jHUVqprKsJ+kE1axaT1IEjXcUqQ20nqRIGWm8o0jtofUkRcpInXNEao+UrSdpZm2BB4CDCKpq73b3W8ysGTADaAesBs5y92/LHLlIFVLVqkjtlBXxdY1ifvYhaKM8I8kxecBv3L0TwRCSy8ysE3Al8LK7H0Uwzd2V5QlcpCoVlh4BVa2K1CIpW0/S3dcD68PH28zsQ6A1QXI9PnzZ/cA8YGJZzy9SFTS0Q6R2i1SSNLN/m1nTmOcHmNmLUS9iZu2AHsDbwEFhAgXYQFAdG++YsWa20MwW5ubmRr2USKXS0A6R2i1qx50W7r658Im7f2tmLaMcaGYNgceB8e6+1cyK9rm7m1ncMZjufjdwN0BOTo7GaUqVUglSRCB6m2S+mRV14TOzw4gwwYCZ1SNIkA/FLKu10cwODvcfDGwqW8giqacSpIhA9JLkVcBrZvYKwYQC/YGxpR1gQZHxXuBDd/9bzK5ngNHADeG/T5c1aJFUUA9WESkuased2eEEAseGm8a7+1dJDjsOOA/4wMyWhNv+QJAcHzWzC4HPgbPKHrZI5dHkACKSSKlJ0szauftqgDApPltsvwGt3X1N8WPd/TWCUmc8A8sVrUgKaHIAEUkkWUnyJjPLIqgSXQTkEszdeiRwAkGyuxYokSRF0p0654hIMqUmSXcfEU4AMAq4ADgY2AF8CDwP/Nndv095lCKVJLbdMbZ6VVWrIhJP0jZJd19O0HFHJOPFlhxVvSoiyZRrgnORTKOqVREpDyVJqbFUtSoiFaUkKTWWqlZFpKKiLpX1srsPTLZNJB2oalVEKkuycZINgP2A5mZ2AD+Me2xMsKKHSNrRlHIiUlmSlSQvAcYDhxCMkyxMkluB21IYl0iZqQQpIpUt2TjJW4BbzOxyd7+1imISiUydc0QklaLO3XqrmfUD2sUe4+4PpCgukVLFm29VnXNEpLJF7bjzIHAEsATIDzc7oCQp1ULzrYpIVYg6BCQH6OTuWvxYqpXaHUWkKkVddHkp0CqVgYhEoZ6rIlKVopYkmwPLzewdYFfhRnc/PSVRicTQYsgiUl2iJsnJqQxCpDSxpUeVIEWkKkXt3fqKmR0GHOXuc8xsP6BOakOT2k7tjyJS3aL2br0YGAs0I+jl2hq4k2DRZZFKo3GPIpJOola3Xgb0Ad4GcPePzaxlyqKSWkuTkotIOomaJHe5+26zYFY6M6tLME5SpFKoalVE0lHUISCvmNkfgH3N7CTgMWBW6sKS2kZDO0QkHUUtSV4JXAh8QDDp+fPAtFQFJbWHSpAiks6iJsl9gfvc/R4AM6sTbtuRqsCkdlAJUkTSWdQk+TIwCNgePt8XeAnol4qgpGbT5AAikimiJskG7l6YIHH37eFYSZHI4q3coRKkiKSzqEnyOzPr6e6LAcysF7AzdWFJTaSVO0Qk00RNkr8GHjOzdYARTHZ+dsqikhpFnXNEJFMlTZJmlgXUBzoCHcLNK919TyoDk8ymmXNEpCZImiTdvcDMbnf3HgRLZokkFK/dUdWrIpKpIvduNbNhwBNaeFmKK63UqMQoIpksapK8BLgCyDeznQTtku7ujVMWmaQ9lRpFpKaLulRWo1QHIplHvVVFpKaLulSWAaOA9u5+vZm1BQ5293dSGp2kPfVWFZGaLGp16x1AAXAicD3BzDu3A71TFJekmdh2x0KFQzpERGqqqEnyGHfvaWbvArj7t2ZWP4VxSZqI1+5YSLPliEhNFzVJ7gknNXcAM2tBULKUGk7tjiJSm0VNklOBJ4GWZvZnYDhwdcqikmqnWXJERKL3bn3IzBYBAwmGf/zU3T9MaWRS5TRLjojI3kpNkmbWALgUOJJgweW73D0vyonN7D5gKLDJ3buE25oBM4B2wGrgLHf/trzBS+XQeEcRkfiSlSTvB/YArwI/AX4EjI947unAbcADMduuBF529xvM7Mrw+cSyBCyVT+2OIiLxJUuSndy9K4CZ3QtEHhfp7vPNrF2xzWcAx4eP7wfmoSRZLbTwsYhIcsmSZNFKH+6eF8wpUCEHufv68PEG4KCKnlDKRgsfi4hElyxJdjezreFjA/YNn1d47lZ3dzNLOFm6mY0FxgIceqiq/yoqXnJU1aqISOlKTZLuXqeSr7fRzA529/VmdjCwqZRr3w3cDZCTk6OVRypI7Y4iImUXdZxkZXkGGA3cEP77dBVfv1ZRu6OISMVkperEZvYw8CbQwczWmNmFBMnxJDP7GBgUPpcUKSw9gqaQExEpj5SVJN19ZIJdA1N1TQlothwRkcqRspKkVJ/YBKnSo4hI+VV1m6SkiNofRUQqn5JkhtO4RxGR1FGSzFAa9ygiknpKkhlK4x5FRFJPSTKDqN1RRKRqKUlmALU7iohUDyXJNKZ2RxGR6qUkmcbU7igiUr2UJNOM2h1FRNKHkmSaULujiEj6UZKsRrGlRrU7ioikHyXJahCv1KjkKCKSfpQkq4E65IiIZAYlySqkJaxERDKLkmSKldbuKCIi6U1JMsViS46qXhURySxKkimiqlURkcyXVd0B1FSxCVJVqyIimUklyRRSCVJEJLOpJCkiIpKASpKVrHhbpIiIZC6VJCuZ2iJFRGoOlSQrgVbuEBGpmZQkK0Ard4iI1GxKkhWgOVhFRGo2JckyUtWqiEjtoY47ZVRYegRUtSoiUsOpJBmRppkTEal9lCSTiNc5R6VHEZHaQUkyjtKWt1LnHBGR2kNJMg4tbyUiIqAkuRe1O4qISCwlSdTuKCIi8SlJokkBREQkvlqbJDUpgIiIJFPrkqTmWxURkahqXZJU1aqIiERVK5KkqlZFRKQ8qiVJmtlg4BagDjDN3W9IxXWum7WM5eu2qmpVRETKpcqTpJnVAW4HTgLWAAvM7Bl3X56qa6pqVUREyqM6SpJ9gE/c/TMAM3sEOAOo9CR5bd0Hof4HwZPlqbiCiEgKteoKP0lJRZtEVB1LZbUGvox5vibcthczG2tmC81sYW5ubpUFJyIiUihtO+64+93A3QA5OTlerpPoG5iIiFRAdZQk1wJtY563CbeJiIiklepIkguAo8ysvZnVB84BnqmGOEREREpV5dWt7p5nZr8EXiQYAnKfuy+r6jhERESSqZY2SXd/Hni+Oq4tIiISVXVUt4qIiGQEJUkREZEElCRFREQSUJIUERFJwNzLN06/KplZLvB5OQ9vDnxVieFUtUyOP5Njh8yOP5Njh8yOP51iP8zdW1R3EJksI5JkRZjZQnfPqe44yiuT48/k2CGz48/k2CGz48/k2KUkVbeKiIgkoCQpIiKSQG1IkndXdwAVlMnxZ3LskNnxZ3LskNnxZ3LsUkyNb5MUEREpr9pQkhQRESkXJUkREZEE0jpJmtlgM1tpZp+Y2ZUx2080s8VmttTM7jezEhO1m9nxZrbFzN4NzzHfzIZWYextzWyumS03s2Vm9uuYfd3N7E0z+8DMZplZ4zjHtzOznWH8H5rZO2Y2pqriLxbLfWa2ycyWFtuebWZvmdkSM1toZn3iHHu8mT1bddHude1E98+rYcxLzGydmT0V546NcL4AAAlPSURBVNjC+6fwdXOSXGuymf22kuIu7d6ZERPTajNbEuf4wntnScxP/VKuN8bMbquM2MPzJbpfot73bmZ/itnW3Mz2VGaMyZRy7wwMP3uWmNlrZnZkKed4yszeqpqIJWXcPS1/CJbR+hQ4HKgPvAd0IkjsXwJHh6/7I3BhnOOPB56NeZ4NrAYGVlH8BwM9w8eNgI+ATuHzBcCA8PEFwPVxjm8HLI15fjiwBDi/Gv4vfgz0jI0n3P4S8JPw8anAvGT/D9V9/8R53ePAf1U0bmAy8NtU3zvFXvdXYFKyeyfC9cYAt1XB/RL1vv8MeDdm27jw3o8cI1A3FfdO+H/xo/DxL4DpCc7RNPyc+hA4vIzXL3fs+qn8n3QuSfYBPnH3z9x9N/AIcAZwILDb3T8KX/dvYFiyk7n7EoKE+ksAM2thZo+b2YLw57hwe0Mz+0f4bfd9M0t67gTXW+/ui8PH2wj+WFqHu48G5pcx/s+AK4BfhXHuH35jfycsbZ4Rbq9jZjeHpez3zezy8sRf7NrzgW/i7QIKSwNNgHWlncfM+oQliXfN7A0z6xBuH2NmT5jZbDP72MxurGjMJL5/YuNpDJwIlChJlvIe4t43ocKS0sdmdnF5A09y7xTGYcBZwMNliD3uPRNqa2bzwtivLW/sYcyJ7peo9/0O4EMzKxyQfzbwaMz7OM3M3g7fwxwzOyjcPtnMHjSz14EHK/AWSrt3ot7zPwNmhceeExP7dDO7M6x5+cjC2q3wb+AZM/sP8HIFYpdKVi3rSUbUmuCbWKE1wDEE0z3VNbMcd18IDAfaRjznYmBC+PgWYIq7v2ZmhxIsAv0j4Bpgi7t3BTCzAyr6RsysHdADeDvctIzgj+4pYEQZ4+8YPr4K+I+7X2BmTYF3wirB/yL4Np7twQLXzSoafynGAy+a2c0EJfx+SV6/AugfxjUI+B9++KDMJvgd7QJWmtmt7v5lgvNEkej+ifVT4GV335rgHP1jqjMfc/c/k/i+AegGHAvsD7xrZs+5e6lfHJKJc+8UxQZsdPePExx6REzsr7v7ZSS+ZyBIDF0IEtSCMPaFFYk9jrLc948A55jZRiCfIBkdEu57DTjW3d3MLgJ+B/wm3NcJ+H/uvrMCcZZ271wEPG9mO4GtBP/f8Ywk+FK+kaC24n9i9rUj+H0fAcyNqbLtCXRz93hfMKSapHOSjCv8wzgHmGJm+xBU+eVHPNxiHg8COgVfyAFobGYNw+1F3/zc/duKxBue83FgfMyH8QXAVDO7BngG2B31dDGPTwZOtx/awRoAhxLEf6e754Xxp/IPbhzw3+7+uJmdBdwbXj+RJsD9ZnYUwTfyejH7Xnb3LQBmthw4jL0/qFJhJDCtlP2vunvxduxE9w3A0+GH804zm0vwQRi5lFpcgnsnNvbSSpGfunt2sW2J7hmAf7v71+F1nwD+H1DZSbIs9/1s4HqCJDOj2L42wAwzO5igOnRVzL5nKpggk/lv4FR3f9vMJgB/I0icRcKS7VHAa+Hn1R4z6+LuhW20j7p7AfCxmX3GD198/60EmX7SOUmuZe9vmm3Cbbj7mwTfpDGzkwmqcaLoQVB1BUHJ51h3/z72BTEffhVmZvUIPuQecvcnCre7+wqCDyzM7GhgSMRTxsZvwDB3X1nsmhUNuyxGA4WdSh6j9IQDwYfeXHc/MywhzYvZtyvmcT4VvzcT3j8QdAYhSGJnlvG8pd03xQcdl3sQcqJ7J9xXl6A6r1dZT0v8e+aYOLFW+gDqstz37r7bzBYRlBA7AafH7L4V+Ju7P2NmxxO0Bxf6rhJCjXvvmFkLoLu7F5bqZxAk8+LOAg4AVoX3RWOCLzVXhfsT/a4rI3apZOncJrkAOMrM2lvQM+8cgm+fmFnL8N99gInAnclOZmbdCKpSbw83vQRcHrO/8Fv3v4HLYraXq7o1bDO6F/jQ3f9WbF9h/FnA1RHjbwfcTPABAUE13+XhdTCzHjHxXxJ+kJLi6tZ1wIDw8YlAoqq/Qk34IVGNSVFMhRLeP6HhBB1zvo97dGKJ7huAM8ysgZkdSNDxZ0F5Ai/t3gkNAla4+5oynjrRPQNwkpk1M7N9CaqhXy9H6KUqx33/V2BinNJV7H00ulKDDCS6d74FmoQJHuAkfvjSGmskMNjd27l7O4IvM+fE7B9hZllmdgRB56CVcc4haSJtk2RYXfhLgj/sDwmqKJaFuyeY2YfA+8Asd/9PgtP0Dxv3VxIkx1+5e2Gj+K+AHAs6tywHLg23/wk4wIKOL+8BJ5TzLRwHnAecaD90wz813DfSzD4iaKNbB/wjwTmOCOP/kKDjwlR3L3zt9QTVle+b2bLwOQSluS/C7e8BPy9n/EXM7GHgTaCDma0xswvDXRcDfw2v8z/A2DiH1+WHUuKNwP+a2bukuBYjyf0DwYdW5E4vMRLdNxDcj3OBtwh6bpa3PbK0e6cisSe6ZwDeISi5vg88XpH2yFLul6j3PQDuvszd74+zazLwWFjSrPQlqRLdO+H2i4HHw3v+PH7o4wAUfZk9jOAeKDzfKmBLWGKH4O/zHeAF4NJyfFGTKqRp6SSlLBjj19rdf1fdsYhUNzObTlCDMbO6Y5Fo0rlNUjKcmd1L0GPyrOqORUSkPFSSFBERSSBt2yRFRESqm5KkiIhIAkqSIiIiCShJihRjZvnhsItlZvaemf0mHNtX2jHtzKzCw21EJL0oSYqUtNPds929M8GA8Z8AySb9bkcljEkVkfSi3q0ixZjZdndvGPP8cIJZWJoTDBR/kGASc4BfuvsbFqwb+COCeUTvB6YCNxDMvLMPcLu731Vlb0JEKoWSpEgxxZNkuG0z0AHYBhS4+/fhRO0Pu3tOOIfobwsnRDezsUBLd/9TOH3i68CIcPYVEckQmkxApGzqAbeFc7bmk3hy/ZOBbmY2PHzehGBlCCVJkQyiJCmSRFjdmg9sImib3Ah0J2jTTzTvpgGXu/uLVRKkiKSEOu6IlCJcHulO4DYP2iaaAOvD9QDPA+qEL90GNIo59EVgXLjkFWZ2tJntj4hkFJUkRUra18yWEFSt5hF01ClcsuoOglUg/otgLcHCNQDfB/LD1SGmA7cQ9HhdHC5NlUuwBJWIZBB13BEREUlA1a0iIiIJKEmKiIgkoCQpIiKSgJKkiIhIAkqSIiIiCShJioiIJKAkKSIiksD/B1b5MyYp21T8AAAAAElFTkSuQmCC\n", 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" ] @@ -8660,7 +8660,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **LD**" + "### COVID vaccinations among **70-79** population by **LD**" ], "text/plain": [ "" @@ -8671,7 +8671,7 @@ }, { "data": { - "image/png": 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dtPvSSy/97wEHHFA8fvz4FhUf/RsVVbe+6+7XJdl2q5kdBFT4NcfdpxEkWtz9EyD5A3giIrVAfGJ859P/AnBku+alJUgpX35+vvft23fT/vvvX1yvXj3OPPPMTYsXL87v3bv34QCNGjUqeeyxxz794IMPGvzyl79sU6dOHerVq+f33HPPZ5U5T7lJ0t33qBMws0buvi1u+1qC0qWIiFTC8/NWlJYaj2zXfJ+rVmub4uJi5s6d2/ipp576OLbuN7/5zdrf/OY3e+Skzp077xgyZMiSvY8QTaSOO2bWF3gAaAwcZmbdgIvcvWoTMIqI1EJrNm9n/ZYdXB/X7qhq1cqbM2dO/hlnnPGdU0899avCwsId6TxX1N6ttwGnAC8AuPt8MzsmbVGJiOSQWNXqFeu3lq5TtWrV9erVa/vy5curZWLOyI+AuPsXZha/Kntm/hURyaBY1WqT/Hq0aNwg20uPJSUlJVanTp30DddWzUpKSgwoSbQtapL8IqxydTOrz97jsYqISJxEPVY75zXLcFQpsWjdunWdWrZsuTEXEmVJSYmtW7euGcGjjXuJmiQvJhgIoDXBw/+vAj9NSYQiIjmiwh6rVe4+UnPs3r37J6tXr35g9erVXaieSTLSrQRYtHv37p8k2hg1SZq7D09dTCIiuSFZYkzYYzUHkmSvXr3WAoMyHUd1iZokZ5rZMmASwWg5G9IXkohI9tCjHLktUpJ09w5mdgQwDPi1mS0BnnD3R9ManYhIDRUrQepRjtxWmd6t7wLvmtkfgFsJ5olUkhSRWiNZ1aoe5chdUQcTaAoMJihJfguYjIaWE5FaoFJtjpJzopYk5wPPAde7+94TzImI5Ci1OdZuUZNke69oTi0RkRylNsfaq6Kpsm5399HAC2a2V5J091rTDVhEapeyHXOkdqqoJPlI+PPmdAciIpJp6pgjZVU0VdaccLG7u98Rv83MLgempyswEZHqpvZHKStqm+QFBMPSxRuRYJ2ISFZJNMaq2h8lpqI2yXOB84B2ZvZC3KYmwH/TGZiISLpUOMaqSKiikuSbwCqgBXBL3PrNwIJ0BSUikk6qVpWoKmqT/Az4DFDdg4hkPQ0lJ5UVaZoTMzvKzGaZ2RYz22lmxWa2Kd3BiYikUnyCVLWqRBG1485dBEPSPQUUAecDHdIVlIhIqqhjjuyLyBNmuvtHQF13L3b3CcCA9IUlIpIasdIjoBKkVFrUkuQ2M8sD5pnZTQSdeXJhRmoRqS6zJ8DCp6vlVGs2b2f9lh0AXLWzmEZ5demc1yzYuITMTX68eiEUFGbo5FIVURPdD4G6wM+ArcChwJB0BSUiOWjh00GSSJM1m7ezeNVGFq/ayKfrt7J5+24AGuXVpUXjBmk7b6UUFELh0ExHIZUQddLlz8LFr4Hfpi8cEclpBYVw4cspPWSszfGdld887wjosQ5JiYoGE1gIJJ39w927pjwiEZFKiLU56nlHSYeKSpIDqyUKEZF9oB6rki5RBhMQEalREj3WIZIOkdokzWwz31S75gH1ga3urjtTRKqFxluVTIjacadJbNnMDDgDOCpdQYmIlKXxViUToj4nWcrdHXjOzK4Drk59SCIiAY2WI5kWtbr1zLi3dQiGptuelohERELxpUdVq0omRC1Jnh63vBtYRlDlKiKScpqtQ2qKqG2SF6Y7EBGp3ZJ1zFHpUTIpanVrO+AyoG38Pu4+KD1hiUhto445UhNFrW59DhgPvAiURNnBzPKBGUCD8DxPu/t1YcJ9AjgQmAP80N13VjZwEcl+6pgjNV3UJLnd3e+s5LF3ACe4+xYzqw+8YWZ/B64EbnP3J8zsXuDHwF8qeWwRyQHqmCM1XdQkeUf4yMerBMkPAHefm2yH8FGRLeHb+uHLgROA88L1DwHjUJIUqTVUepRsEjVJFhJMl3UC31S3xhJeUmZWl6BK9dvA3cDHwAZ33x1+ZDmQ8KujmY0CRgEcdpjaJUSyXWyOx18tDabL0mg5kg2iJsmzgPaVbTt092Kgu5ntD0wGDq/EvvcB9wEUFRUlnYlERGqu+FLjFeu3AqhTjmSVqElyEbA/sLYqJ3H3DWb2OtAH2N/M6oWlyTbAiqocU0Rqvvg2xyb59WjRuIGqViWrRE2S+wMfmNks9myTTPoIiJm1BHaFCbIhcBLwR+B1YChBD9cLgOerGLuI1EBJ2xwnNMtwZCKVFzVJXleFYx8CPBS2S9YBnnT3l8xsCfCEmf0eeI/g0RIRyRHqsSq5JOqIO9Mre2B3XwD0SLD+E+CIyh5PRGou9ViVXFUnyofMbLOZbQpf282s2Mw2pTs4EckOsdIjoNKj5BTNJykiVaaByCXXRSpJxvPAc8ApaYhHRLJIfIJU6VFykeaTFJFKUfuj1CaaT1JEKkW9V6U20XySIlIhlR6ltopa3foQcLm7bwjfHwDc4u4/SmdwIpI5ySZBVulRapOo1a1dYwkSwN2/MrO9noEUkewXS47xiVHjrUptFTVJ1jGzA9z9KwAza16JfUUki8TaHJUYRaInuluAt8zsqfD9WcAN6QlJRKqb2hxFEov0nKS7PwycCawJX2e6+yPpDExEqo9GzBFJrNySpJk1dvctAO6+BFhS3mdEJHuo9ChSsYqqW583s3kE01nNcfetAGbWHjgeOBu4H3g6rVGKSEqox6pI5ZSbJN39RDP7HnAR0C/ssLMLWAq8DFzg7qvTH6aIpEL8QADqmCNSsQo77rj7K8Ar1RCLiKSJBiIXqRo9xiGSo5JVrapaVSQ6JUmRqpg9ARbWvKb4NZu3s37LDgDab9/NFUCT/HrQFFo0bsDBeflB97u9uuBVg9ULoaAwAycWqTolSZGqWPh0jfyjv37LDrbtLKZRXl2a5NcLEmOT/EyHFSgohMKhmY5CpFIqegSkeXnb3f2/qQ1HJIsUFMKFL2c6CiCuzXGn2hxFUqmikuQcwAEDDgO+Cpf3Bz4H2qU1OhGJRJMfi6RHRY+AtAMws/uByWFPV8zsVOD76Q9PRJLRYAAi6Re1TfIodx8Ze+Pufzezm9IUk4gkocEARKpX1CS50syuAR4N3w8HVqYnJBFJRoMBiFSvqEnyXOA6YDJBG+WMcJ2IpJmqVUUyJ1KSDHuxXm5m+8XGbxWR9Eo0+bGqVUWqV6QkaWZ9gQeAxsBhZtYNuMjdL01ncCK1TXmj5KhaVaT6Ra1uvQ04BXgBwN3nm9kxaYtKpBZJlhiVHEUyL/KIO+7+hZnFrypOfTgitY8644jUXFGT5BdhlaubWX3gcuD99IUlktvUGUckO0RNkhcDdwCtgRXAq4DaI0UqSZ1xRLJL1CTZ0d2Hx68ws37AzNSHJJK7YlWrqlYVyQ5Rk+SfgZ4R1olIGapaFcleFc0C0gfoC7Q0syvjNjUF6qYzMJFspuHjRHJDRSXJPIJnI+sBTeLWbwI0MZxIEuqxKpIbKpoFZDow3cwmuvtn1RSTSE5QtapI9ovaJrnNzP4EdAZKpzl39xPSEpVIFkrU9igi2S1qknwMmAQMJHgc5AJgXXk7mNmhwMPAwQSDot/n7neYWfPwWG2BZcDZ7v5VVYIXqQn0WIdI7oqaJA909/FmdnlcFeysCvbZDfzc3eeaWRNgjpn9ExgBTHX3G83sauBqYGxVL0AkE9Zs3s76LTu4/q9vaYxVkRwWNUnuCn+uMrPTCOaSbF7eDu6+ClgVLm82s/cJBiM4Azgu/NhDwDSUJCXLrN+yg207g5EZlRxFclfUJPl7M2sG/Jzg+cimwBVRT2JmbYEewDvAwWECBVhNUB0rknUa5dVVxxyRHBd1PsmXwsWNwPGVOYGZNQaeAUa7+6b4QdLd3c3Mk+w3ChgFcNhh+oYumRHfGSfeVTuLaZSnR4VFcl3U+SRbAiMJOtuU7uPuP6pgv/oECfIxd382XL3GzA5x91VmdgiwNtG+7n4fcB9AUVFRwkQqkm7xzzvGa5RXlxaNG2QoKhGpLlGrW58H/g28RsQpsiwoMo4H3nf3W+M2vUDQO/bG8OfzkaMVyYCEzztOaJaZYESkWkVNko3cvbKda/oBPwQWmtm8cN2vCJLjk2b2Y+Az4OxKHlck7WLVrHreUaR2i5okXzKz77n7K1EP7O5vAJZk84lRjyNSXZKNt6rnHUVqr6hJ8nLgV2a2g+BxECPod6Ov2JIzNN6qiJQVtXdrk4o/JZJ9NI2ViJSnoqmyDnf3D8ws4byR7j43PWGJpI+msRKRqCoqSV5J8KziLQm2OaABziVrJBpjVdWqIlKeiqbKGhX+rNQAAiI1UazNUYlRRKKKOpjATwkGBNgQvj8AONfd70lncCL7Sm2OIrIv6kT83MhYggQIp7YamZ6QRFInVnoE1OYoIpUW9RGQumZm7u4AZlYXyEtfWCKpo9KjiFRV1CQ5BZhkZn8N318UrhOpcRJVsYqIVEXUJDmWoJfrJeH7fwIPpCUiyW6zJ8DCp6v9tLFJkAHab9/NFUCT/HqQBy12NIAJ+ak94eqFUFCY2mOKSI0TNUk2BO5393uhtLq1AbAtXYFJllr4dEYSSGwS5EZ5dWmSX48WjRtwcJMUJ8Z4BYVQODR9xxeRGiFqkpwK9Ae2hO8bAq8CfdMRlGS5gkK48OW0HT7RHI9LdqrnqoikXtTerfnuHkuQhMuN0hOSSPnie6zGqOeqiKRD1JLkVjPrGRuGzsx6AV+nLyyRPel5RxHJhKhJcjTwlJmtJJgBpAA4J21RiZQRP0OHSo0iUl2izgIyy8wOBzqGq5a6+670hSWi0qOIZF7UkiQECbITkA/0NDPc/eH0hCW1WaKByFV6FJFMiDp263XAcQRJ8hXgVOANQElSUk4DkYtITRG1JDkU6Aa85+4XmtnBwKPpC0tqG1WtikhNFDVJfu3uJWa228yaAmuBQ9MYl9QCmvxYRGq6qElytpntD9wPzCEYVOCttEUltUJ8j1VVrYpITRS1d+ul4eK9ZjYFaOruC9IXluQqVauKSDaJ2nHnBeAJ4Hl3X5bWiCQnqceqiGSjqNWttxAMHvD/zGwWQcJ8yd23py0yySnqsSoi2Shqdet0YHo4+8cJwEjgQUAT9UlSqloVkWwXdYBzzKwhMAS4GOgNPJSuoCQ3xA9ErqpVEclGUdsknwSOAKYAdwHT3b0knYFJdopNfnz9X99S6VFEsl7UNsnxwLnuXpzOYCR7xapWr1i/tXSdSo8iku2itkn+I92BSHaLVa02ya9Hi8YNVHoUkZxQmQHORfaQqGNO57xmGY5KRCR1lCSlUiocSm5JJqMTEUmtqB13prr7iRWtk9yULDEmfOZRSVJEcki5SdLM8oFGQAszOwCwcFNTQD0yclyiUXI0GICI1CYVlSQvAkYDrQgGNo8lyU0Ej4JIDtMoOSJS25WbJN39DuAOM7vM3f9cTTFJBmmUHBGRb0R9BOTPZtYXaBu/j7s/nKa4JEPip6/Sc44iUttF7bjzCPAtYB4QG1DAASXJHKDSo4hIYlEfASkCOrm7Rz2wmT0IDATWunuXcF1zYBJBiXQZcLa7f1WZgCX1VHoUEUksapJcBBQAqypx7IkEnXviS5tXA1Pd/UYzuzp8P7YSx5QUUelRRKRiUZNkC2CJmb0L7IitdPdByXZw9xlm1rbM6jOA48Llh4BpKElmhEqPIiIVi5okx6XofAe7e6w0uho4ONkHzWwUMArgsMP06EE6qPQoIlK+SPNJhpMuLwPqh8uzgLn7cuKwfTNpG6e73+fuRe5e1LJly305lcT52zufc044jZWIiJQvau/WkQSluuYEvVxbA/cClR2Wbo2ZHeLuq8zsEGBtJfeXKkg2rJyqWEVEyhe1uvWnBJMuvwPg7h+a2UFVON8LwAXAjeHP56twDEkiPhnG07ByIiJVEzVJ7nD3nWbBqHRmVo9yqkrDzzxO0EmnhZktB64jSI5PmtmPgc+As6sYtyQQ3xknnhKjiEjVRE2S083sV0BDMzsJuBR4sbwd3P3cJJs0c0iKxUqQepRDRCS1InXcIXiecR2wkGDQ81eAa9IVlFROfIJUO6OISOpELUk2BB509/sBzKxuuG5bugKT8u3zYACzJ8DCp1Mf2OqFUFCY+uOKiGRA1CQ5FegPbAnfNwReBfqmIyhJLFkv1SqVIEBSrDgAAA8iSURBVBc+nZ6EVlAIhUNTe0wRkQyJmiTz3T2WIHH3LWbWKE0xSRLx1aop6YxTUAgXvpy6AEVEckzUJLnVzHq6+1wAM+sFfJ2+sCQZdcwREak+UZPk5cBTZrYSMILBzs9JW1RSKlHbo4iIVI8Kk6SZ1QHygMOBjuHqpe6+K52B1Xax5LjPbY8iIlJlFSZJdy8xs7vdvQfBlFlSDWLtjxoIQEQkcyL3bjWzIcCzlZl4WfaN2h9FRDIrapK8CLgSKDazrwnaJd3d1UCWQmp/FBGpWaJOldXE3eu4e313bxq+11/wFItVsQJqfxQRqQGiTpVlwHCgnbv/zswOBQ5x93fTGl0tsM8j54iISNpEHbv1HqAPcF74fgtwd1oiqmVUehQRqbmitkke6e49zew9AHf/yszy0hhXTlPpUUQkO0QtSe4KBzV3ADNrCZSkLaocp9KjiEh2iFqSvBOYDBxkZjcAQ9FUWZWmeR9FRLJLpCTp7o+Z2RyCCZMN+L67v5/WyLJYfHVqvPjRc1R6FBGp+cpNkmaWD1wMfJtgwuW/uvvu6ggsm8WXFuNp9BwRkexSUUnyIWAX8G/gVOB/gdHpDiobqTOOiEjuqShJdnL3QgAzGw/oucgk4kuP6owjIpIbKkqSpTN9uPvuYEwBSUalRxGR3FJRkuxmZpvCZQMahu81dmuobI9VERHJHeUmSXevW12BZKv4BKkqVhGR3BL1OUkph6pZRURyk5JkFWhKKxGR2iHqsHQSR8PKiYjUDipJRqTnIEVEah8lyXLEJ8b4IeVUehQRqR2UJBOIJcf4xKgh5UREah8lyQRibY5KjCIitZuSZBJqcxQRESXJkB7rEBGRsvQISEiPdYiISFm1uiSpxzpERKQ8tTJJJuq9qtKjiIiUVSuTpHqviohIFBlJkmY2ALgDqAs84O43pvucqloVEZHKqvYkaWZ1gbuBk4DlwCwze8Hdl6T6XL99cTFLVgadcVS1KiIilZWJkuQRwEfu/gmAmT0BnAGkPEme8sXtDN3wfvCmKbRo3ICD8/KD90vSccYssnohFBRmOgoRkRotE0myNfBF3PvlwJFlP2Rmo4BRAIcdVrU2w6PaHQirm1Vp35xXUAiFQzMdhYhIjVZjO+64+33AfQBFRUVepYOcmvamThERyWGZGExgBXBo3Ps24ToREZEaJRNJchbwHTNrZ2Z5wDDghQzEISIiUq5qr251991m9jPgHwSPgDzo7ourOw4REZGKZKRN0t1fAV7JxLlFRESi0gDnIiIiSShJioiIJKEkKSIikoSSpIiISBLmXrXn9KuTma0DPqvi7i2A9SkMpybRtWWnXL22XL0uyN5r+x93b5npILJZViTJfWFms929KNNxpIOuLTvl6rXl6nVBbl+blE/VrSIiIkkoSYqIiCRRG5LkfZkOII10bdkpV68tV68LcvvapBw53yYpIiJSVbWhJCkiIlIlSpIiIiJJ1OgkaWYDzGypmX1kZlfHrT/BzOaa2SIze8jM9hqo3cyOM7ONZvZeeIwZZjaweq8gMTM71MxeN7MlZrbYzC6P29bNzN4ys4Vm9qKZNU2wf1sz+zq8tvfN7F0zG1GtFxGBmT1oZmvNbFGZ9d3N7G0zm2dms83siAT7HmdmL1VftNGVc1/+O7ymeWa20syeS7Bv7L6Mfe61Cs41zsyuSsd1lDlPeffkpLh4l5nZvAT7x+7JeXGvvHLON8LM7krX9SQ4X7J7Mervm5vZ7+PWtTCzXdV5DZIh7l4jXwTTaH0MtAfygPlAJ4LE/gXQIfzc9cCPE+x/HPBS3PvuwDLgxBpwbYcAPcPlJsB/gE7h+1nAseHyj4DfJdi/LbAo7n17YB5wYaavrUycxwA942MN178KnBoufw+YVtH/X015JbsvE3zuGeD8fb0uYBxwVTVcV9J7ssznbgGuTbB+j3sywvlGAHdV4/9bsnsx6u/bJ8B7cesuCX/nIl8DUK+6rlev1L1qcknyCOAjd//E3XcCTwBnAAcCO939P+Hn/gkMqehg7j6PIKH+DMDMWprZM2Y2K3z1C9c3NrMJ4TfLBWZW4bEry91XufvccHkz8D7QOtzcAZgRLke9tk+AK4H/C69hv/Cb87thafOMcH1dM7s5LIEvMLPLUntle8U1A/hvok1A7Bt7M2BleccxsyPCb/vvmdmbZtYxXD/CzJ41sylm9qGZ3ZTSC0gs2X0ZH29T4ARgr5JkMsnux1CstPOhmY1MxUWUVcE9GYvRgLOBx6MeN9m9GDrUzKaF13VdCi4jqXLuxai/b9uA980sNqDAOcCTsY1mdrqZvRNe42tmdnC4fpyZPWJmM4FHUnEtUr0yMp9kRK0JSowxy4EjCYaGqmdmRe4+GxgKHBrxmHOBMeHyHcBt7v6GmR1GMAn0/wK/ATa6eyGAmR2wz1dSDjNrC/QA3glXLSb4o/sccBaVu7bDw+VfA/9y9x+Z2f7Au2G13vkE34q7ezD5dfNUXEMVjAb+YWY3E9QM9K3g8x8AR4cx9wf+wDd/zLoT/PvtAJaa2Z/d/Yskx0mFZPdlvO8DU919U5JjHB1XZfmUu99A8vsRoCtwFLAf8J6Zvezu5X6x2BcJ7snSuIE17v5hkl2/FXddM939pyS/FyH4wtGFIAHNCq9rdgovJYrK/L49AQwzszVAMcGXu1bhtjeAo9zdzewnwC+An4fbOgHfdfev0xC/pFlNTpIJhTfhMOA2M2tAUHVXHHF3i1vuD3QKvhwD0NTMGofrh8Wd76t9jzpJMMH5ngFGx/1B/RFwp5n9BngB2Bn1cHHLJwOD4tqy8oHDCK7tXnffDeDuib5ZV4dLgCvc/RkzOxsYH8aWTDPgITP7DkEptH7ctqnuvhHAzJYA/8OeSSwTzgUeKGf7v929bPt4svsR4PnwD+zXZvY6QXKJXEqtjCT3ZMy5lF+K/Njdu5dZl+xeBPinu38ZnvdZ4LtAdSfJyvy+TQF+B6wBJpXZ1gaYZGaHEFTDfxq37QUlyOxVk5PkCvb8VtcmXIe7v0XwrRYzO5mgyiSKHgTVSBCUYI5y9+3xH4j7I5VWZlaf4I/RY+7+bGy9u39A8IcFM+sAnBbxkPHXZsAQd19a5pz7GnaqXADEOoY8RfkJBYI/TK+7++CwlDMtbtuOuOVi0n9PJ70vIejQQZDEBlfyuOXdj2UfZk7Lw83J7slwWz3gTKBXZQ9L4nvxSKrpuspTmd83d99pZnMISoidgEFxm/8M3OruL5jZcQRtyTFbUxy2VKOa3CY5C/iOmbWzoJfcMIJvepjZQeHPBsBY4N6KDmZmXQmqUu8OV70KXBa3PfYN+J/AT+PWp7y6NWzbGQ+87+63ltkWu7Y6wDVEu7a2wM0Ev6gQVNVdFp4HM+sRrv8ncFH4B48MVreuBI4Nl08AklXfxTTjm0Q0Ik0xRZX0vgwNJeiYsz3h3sklux8BzjCzfDM7kKDjz6wqRV6O8u7JUH/gA3dfXslDJ7sXAU4ys+Zm1pCginpmFULfJ1X4fbsFGJugFib+Hr0gpUFKRtXYJBlWCf6M4JfsfeBJd18cbh5jZu8DC4AX3f1fSQ5zdNiQvpQgOf6fu08Nt/0fUGRBB5YlwMXh+t8DB1jQuWU+cHzqr45+wA+BE+yb7vLfC7eda2b/IWiHWwlMSHKMb4XX9j5BB4I73T322d8RVEkuMLPF4XsISmyfh+vnA+el/MrimNnjwFtARzNbbmY/DjeNBG4JY/gDMCrB7vX4ppR4E/D/zOw9Mlz7UcF9CUHSjNyxJU6y+xGC+/x14G2C3pfpaI8s756Eql9XsnsR4F2CkusC4Jl0tkeWcy9G/X0DwN0Xu/tDCTaNA54KS5rZOKWWJKFh6aRGsuA5vdbu/otMxyIitVdNbpOUWsrMxhP0ejw707GISO2mkqSIiEgSNbZNUkREJNOUJEVERJJQkhQREUlCSVJqNDMrDh9HWGxm883s5+EzbeXt09bM0vp4S2WZ2Zv7sO8IM2tV8Sf32KetlZnxQkQqT0lSarqv3b27u3cGTgJOBSoaDLstaX4GtLLcvaLxacszgm/GCBWRaqQkKVnD3dcSDDzwMwu0tWAOx7nhK5aIbiQcRNzMrrBg9pM/WTC7xgIzu6jssc3sRjOLH2lpnJldZcGsMFPD4y+0uFkszOz88HjzzeyRcN3BZjY5XDc/FpOZbQl/HmfBzBdPm9kHZvZY3Gg014YxLjKz+8JrHAoUAY+F19PQzHqZ2XQzm2Nm/7BgvFDC9fPDQRpKr0VE9kGm5+rSS6/yXsCWBOs2AAcDjYD8cN13gNnh8nHsOZfoKOCacLkBwSDa7cocswcwPe79EoIxWusBTcN1LYCPCMYj7Uww52KLcFvz8OckgsHBIZh7sln8dYSxbSQY87UOwSgw340/Rrj8CHB6uDwNKAqX6wNvAi3D9+cAD4bLC4BjwuU/UYn5HfXSS6/ELw0mINmsPnBXOM5pMckHuj8Z6BqWyiAYZ/M7xM3U4O7vmdlBYdtfS+Ard//CgkG//2BmxwAlBFNlHUww5uxT7r4+3D82lucJBFOS4e7FBAmxrHc9HAPVgqml2hJMtXS8mf2CIPk3J5jG6cUy+3YkGGjhn2EBtC6wyoJpqPb3YN5ECJLsqUn+PUQkIiVJySpm1p4gIa4laJtcA3QjKJUlG1TcgMvc/R8VHP4pggHKC/hmKqThBEmzl7vvMrNlBNM97Yu9Zi4xs3zgHoIS4xdmNi7JeQxY7O599lgZJEkRSTG1SUrWMLOWBLM03OXuTlAiXOXuJQSDc9cNP7oZaBK36z+AS8JSIWbWwcz2S3CKSQQDeQ8lSJiE51gbJsjjCearBPgXcJYFM3PEz6gylWC+TMK20GYRLy+WENdbMKfj0Lht8dezFGhpZn3Cc9Q3s87uvgHYYGbfDT83POJ5RaQcSpJS0zWMPQICvEYwpdRvw233ABeEHVUO55t5+xYAxWEnlisIZj9ZAswNH4v4KwlqUTyYzaMJsMLdV4WrHyOYnWMhQTXqB3GfvQGYHp4/Nr3U5QTVpguBOQTzDlYoTHL3A4sIknr8dFgTgXvDqtm6BAn0j+F55wGxDksXAneHn6sxk4eKZDON3SoiIpKESpIiIiJJKEmKiIgkoSQpIiKShJKkiIhIEkqSIiIiSShJioiIJKEkKSIiksT/ByG6TZyTsLwtAAAAAElFTkSuQmCC\n", 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MFbZjxw5at25Nw4YNefXVV0tKaU2bNmXXrl0l25199tk8/PDDJSWTjRs3snXrVjZt2kTjxo25+OKLmTBhAkuWLIm5f0TXrl1Zv349a9cG4y088sgjDBo0CIBBgwaxZMkSHnjgAUaPHg3AySefzJtvvlmy/VdffcWHH34Y873s2rWLtm3bcuDAAWbMmJH076Bp06a0b9+ep59+GoB9+/axZ88eBg4cyMyZMykqKqKgoID58+fTv3//uMdJ9N5inTPW7yeWHTt20K5dOwCmT58e9xhnnXUW99xzT8nrpUuXJnV8EZHySHYwgW+b2SQzWwZEWra2T2LXPwO/ACKDoB8NbHf3SFFkA8HYsNVizJgxLFq0iJycHP72t79x4oknBkEdfTSnnnoqPXr0YMKECZx11ln88Ic/ZMCAAeTk5DBixAh27drFsmXL6N+/P7m5udx6663cdNNNAIwbN46hQ4ce0nAnKyuLqVOnMnLkSHJycqhXrx5XX301EJTIzj33XF566aWSRjutWrVi2rRpXHTRRfTs2ZMBAwawevXqmO/ltttu46STTuLUU08teR/JeuSRR5g8eTI9e/bklFNOIT8/n/PPP5+ePXvSq1cvzjjjDP7whz+QnZ0d9xiJ3ltpY8eO5eqrr47ZcKe0SZMmMXLkSPr27UvLli1Llp933nk89dRTJQ13Jk+ezKJFi+jZsyfdunXj/vvvL9fvQEQkGeZedndHM3sbmAk87u5JdXgzs3OB77n7j83sNOB/gLHAO+5+fLhNB4KZRA65z2lm44BxAB07duwbfW9OROqAqecEPzULSIWZ2WJ3z0t3HJks2XuSAypw7FOBYWb2PYKZQ5oBdwNHmlmDsDTZHtgY55xTgCkAnTt39mnTph20vnv37vTr1y9udWNubi65ubns2bOHxx9//JD1eXl59OjRgx07dvDUU08dsn7AgAF07dqVbdu28fzzzx+y/jvf+Q7HHnss+fn5zJkz55D1gwcPpkOHDnz22WfMmzfvkPVDhw4lOzubTz755KAGLxHnnnsuLVu2ZM2aNbz99tuHrD///PNp3rw5y5cvZ9GiRYesHzVqFI0bN2bp0qUxqyLHjBlDw4YNWbhwYczGMWPHjgXgrbfeOqTKt0GDBlx88cUAvP7666xbt+6g9YcffnhJY5y5c+eyYcOGg9Y3a9aMCy64AIA5c+aQn59/0Pqjjz6a8847D4DnnnuOzz///KD12dnZDB06FIDZs2ezc+fOg9a3b9+eIUOGADBz5sxDSq+dO3cuqRr+v//7v0PusXbp0oVTTjkFCAZCKE3XXjVde2u/5MP8r8CmlazTtVe5a0/KL2F1q5k9Hv5cZmYfRD2WmdkHifZ191+6e3t370QwH+U/3X0M8CoQmWX0UuCZSr8LEZFa5umlG3l6acwyhFSjhNWtZtbW3Teb2TGx1rt7UnWgkepWdz/XzI4FHgNaAO8BF7v7vkT75+XleaxvrCJSi9XR6ta/v/tvnlm6kXfXfcFJnVsw80cVqcgLqLq18hJWt7r75vDpj919YvQ6M/s9MPHQvWIe5zXgtfD5JwSDpYuI1GmRhBjt3XVfAHBS5xYMz622do0SR1L3JIEzOTQhfjfGMhERKUN0aRGChBgRSY4/PEnz2dcECZOkmV0D/Bg4ttQ9yKaABssUEamAZ5ZuZOXmnUqIGaCskuTfgZeA/wdcH7V8l7t/kbKoRERqoUgJcuXmnXRr26xS9xulepR1T3IHwYwfFwGYWWuC7hxNzKyJu/879SGKiGSu6PuOut+YeZK6J2lm5wF/Ar4FbAWOIRiPtXvqQhMRySxlNcRR9WrmSbbhzm+Ak4G57t7bzE4HLk5dWCIimSe6KjVCiTGzJZskD7j752ZWz8zqufurZvbnlEYmIpIhdK+x9ko2SW43sybAfGCGmW0FvkpdWCIiNV+srhy611i7JJskhwNfAz8HxgDNgV+nKigRkZoqUUMcVanWPskOcB5dapwed0MRkVpEDXGkrMEEdgGxBnc1wN29WYx1IiIZTSPiSERZ/SSbVlcgIiLpFu8eoxJi3ZVsP8mYV4gGExCR2kTDxUlpyTbciZ6rJgvoDKxBgwmISIaLvu+oLhxSWrINd3KiX5tZH4KBz0VEMlKsqtVubZupC4ccJNmS5EHcfYmZnVTVwYiIpJruO0p5JHtP8rqol/WAPsCmlEQkIlJFkpnUWMlREkm2JBndyrWQ4B7lk1UfjoiwaCosm5XuKNIvfxlk55S9XSnxOvtHKDlKeSR7T/LWVAciIqFlsyqcIGqV7BzIGZH05rGqUZUQpbKSrW7NA24kmCKrZB9375miuETqtuwcuOyFsrcT3WOUlEq2unUGMAFYBhSnLhwRkbJp/FSpLskmyQJ3fzalkYiIRInV6CZCVapSXZJNkreY2YPAPGBfZKG7z05JVCJS58WawDhCiVGqS7JJ8jLgRKAh31S3OqAkKSJVShMYS02SbJLs5+5dUxqJiNRZie4xiqRTsknyLTPr5u4rkz2wmWUB84HDwvPMcvdbzKwz8BhwNLAYuMTd95czbhGpRaJLjqpKlZok2SR5MrDUzNYR3JOMzCeZqAvIPuAMd99tZg2BN8zsJeA64C53f8zM7geuAP634m9BRDJN6UY5qlqVmirZJDm0vAd2dwd2hy8bhg8HzgB+GC6fDkxCSVKk1ks0Eo4GFpeaKtkk6RU5uJnVJ6hSPR74C/AxsN3dC8NNNgD6zxCphUqXFtVtQzJReeaTdIJq1qTnk3T3IiDXzI4EniJoIZsUMxsHjAPo2FH/SCKZpnQXDiVGyUTVMp+ku283s1eBAcCRZtYgLE22B2L2Fnb3KcAUgLy8vAqVZEWkemkCY6ltUjafpJm1Ag6ECfJw4Ezg98CrwAiCFq6XAs9UJAYRqTk0gbHUVqmcT7ItMD28L1kPeNzdnzezlcBjZvYb4D3gofKHLSLppvFTpS5I2XyS7v4B0DvG8k+A/skGKCI1i6akkrpE80mKSLlEGuQoMUpdkGx16yvASHffHr4+CnjM3c9OZXAikl6xZuJQgxypS5Ktbm0VSZAA7v6lmbVOUUwikmaxqlQj1CBH6pJkk2SRmXV0938DmNkxVHCAARGp+VSlKhJINkneSDD26usEAwoMJOzoLyK1h6apEjlYsg135oQDCJwcLhrv7ttSF5aIVBdNUyUSX8IkaWad3H09QJgUny+13oB27r4hZRGKSEqoK4dI2coqSd5hZvUIRsVZDBQQjN16PHA6MBi4hWCgchGp4TQAgEj5JEyS7j7SzLoBY4DLCUbR2QOsAl4EfuvuX6c8ShGpFJUaRSqmzHuS7r6SoOGOiGSAWH0bVWoUqZgKDXAuIjVX6SmqQMlRpKKUJEUyUKzSYoS6b4hUnXrpDkBEyi9SWoxFI+KIVJ1kx26d5+6Dy1omIqmlzv4i1ausfpJZQGOgZTiouYWrmgH6qipSDdTZXyR9yipJ/ggYD3yLoJ9kJEnuBO5NYVwidZ66bYikX1n9JO8G7jaza939nmqKSaTOiS4t/urzHQDcsGYZoJapIumU7Nit95jZKUCn6H3c/W8pikukTlG3DZGaKdmGO48AxwFLgaJwsQNKkiKVELMhztTmAMy8TI1yRNIt2X6SeUA3d9cckiKVpIY4Ipkj2SS5HMgGNqcwFpFaTQ1xRDJPskmyJbDSzP4F7IssdPdhKYlK6o5FU2HZrHRHUeW27Pqabbv3HbTs2K8L+TnQtFkDWjY5jDaNsoIVK8NHRP4yyM6prlBFJIFkk+SkVAYhddiyWbUyKWzbvY89+4to3Kh+ybKmWWFybJqVeOfsHMgZkeIIRSQZybZufd3MjgFOcPe5ZtYYqF/WfiJJyc6By15IdxRVoqQhzn6NiCNSGyTbuvUqYBzQgqCVazvgfoJJl0XqvFj3G9UQRyTzJVvd+hOgP/AugLt/ZGatE+1gZh0Iuoi0IeguMsXd7zazFsBMgj6X64FR7v5lhaIXqSEi3TjUEEekdkk2Se5z9/1mwah0ZtaAIPElUgj8t7svMbOmwGIzewUYC8xz99vN7HrgemBihaIXSYNY01RpwHGR2inZqbJeN7MbgMPN7EzgCeC5RDu4+2Z3XxI+3wWsIqimHQ5MDzebDny/IoGLpEusaao0PZVI7ZRsSfJ64ApgGcGg5y8CDyZ7EjPrBPQmqK5t4+6R/pb5BNWxIjWSSo0idVuySfJw4GF3fwDAzOqHy/aUtaOZNQGeBMa7+85IlS2Au7uZxay2NbNxBI2F6NhR93ckPWKNqapSo0jdkWySnAcMAXaHrw8HXgZOSbSTmTUkSJAz3H12uHiLmbV1981m1hbYGmtfd58CTAHIy8vTcHhSrTS5sYhA8kkyy90jCRJ33x32lYzLgiLjQ8Aqd/9T1KpngUuB28Ofz5QvZJHU0JiqIlJasknyKzPrE2mIY2Z9gb1l7HMqcAmwzMyWhstuIEiOj5vZFcCnwKjyhy1S9aJLjurKISKQfJL8L+AJM9sEGMFg5z9ItIO7vxFuG4sGIZAaQ1WrIhJPmUnSzOoBjYATga7h4jXufiCVgYmkmkbJEZGylJkk3b3YzP7i7r0JpswSyViJ7juqalVESku6dauZXQjM1sTLkok0l6OIVESySfJHwHVAkZntJbjX6O7eLPFuIumjUqOIVFayU2U1TXUgIlVFpUYRqSrJTpVlwBigs7vfFs7w0dbd/5XS6ETKIV5DHCVGEamoZKtb7wOKgTOA2whG3vkL0C9FcYkkRVWqIpJKySbJk9y9j5m9B+DuX5pZoxTGJZKQqlRFpDokmyQPhIOaO4CZtSIoWYqkhSY5FpHqkGySnAw8BbQ2s98CI4CbUhaVSBRNVyUi6ZJs69YZZraYYDg5A77v7qtSGplISNNViUi6JEySZpYFXA0cTzDh8l/dvbA6AhPRmKoikm5llSSnAweABcB3gW8D41MdlNRdmq5KRGqSspJkN3fPATCzhwD1i5SU0nRVIlKTlJUkS2b6cPfCYEwBkaqnqlURqYnKSpK9zGxn+NyAw8PXGrtVqsSWXV+zbfc+blizDFDVqojULAmTpLvXr65ApPaL1ZXj59u+AjRKjojUTMn2kxSptFhdOZpmNaBlk8NUvSoiNZKSpKRE0gMATG1ezZGJiCRPSVKqVKwxVSM0AICIZBolSak0zcQhIrWVkqRUmGbiEJHaTklSKkwzcYhIbackKUnRTBwiUhcpSUpCaogjInVZypKkmT0MnAtsdfce4bIWwEygE7AeGOXuX6Yqhjpv0VRYNqtSh+i1eQcn7C+icbP6tGxyGG0aZR28wcrwUVH5yyA7pzIhioikTL0UHnsaMLTUsuuBee5+AjAvfC2psmxWkISStGXX16zYvOOgx579RTRuVJ/ubZvTpmlW2Qcpr+wcyBlR9ccVEakCKStJuvt8M+tUavFw4LTw+XTgNWBiqmIQgiR02QsJNympUt10aJUqwPDcdnRXoxwRqYOq+55kG3ffHD7PB9pU8/klpL6NIiJlS1vDHXd3M/N4681sHDAOoGNHfWhXFfVtFBFJXnUnyS1m1tbdN5tZW2BrvA3dfQowBSAvLy9uMpXkxEqOSowiIolVd5J8FrgUuD38+Uw1n79OiczV+Ou/vq3kKCJSAansAvIoQSOdlma2AbiFIDk+bmZXAJ8Co1J1/rosUmqMzNUISo4iIhWRytatF8VZNThV56zLYjXEadpMczWKiFSGRtzJcIka4nRfqbkaRUQqQ0kyQyXVEKcyI+GIiIiSZCZR30YRkeqlJJlBIlNTdWvbTMlRRKQaKEnWYKWnp9LUVCIi1UtJsoaJV6UKmppKRKS6KUnWEBouTkSk5lGSTIPS1aighjgiIjWRkmQaRDfAiVByFBGpeZQkq1GkBKkGOCIimUFJMsUS9W0UEZGaTUkyRdQQR0Qk8ylJpkikWlWJUUQkcylJVjHddxQRqT3qpTuA2iY6Qeq+o4hIZlNJsgpEN85RCVJEpPZQkqyEWI1zVIIUEak9lCTLSdNViYjUHUqSSVKXDhGRukdJsgyxkqMSo4hI3aAkGYOqVEVEBJQkD6IqVRERiaYkiapURUQkNiVJNISciIjEVmeTpAYAEBGRsqQlSZrZUPSv+V4AAAuOSURBVOBuoD7woLvfXl3n1gAAIiKSrGpPkmZWH/gLcCawAVhoZs+6+8pUnVOtVUVEpCLSUZLsD6x1908AzOwxYDhQ5Uny1udWsHLTTrVWFRGRCklHkmwHfBb1egNwUipOdPZnf2bE9lXQDFo2OYw2jbKCFStJQUqugfKXQXZOuqMQEclYNbbhjpmNA8YBdOxYsVLfyZ2PhvzmVRlWZsnOgZwR6Y5CRCRjpSNJbgQ6RL1uHy47iLtPAaYA5OXleYXO9N1qaw8kIiK1UDomXV4InGBmnc2sETAaeDYNcYiIiCRU7SVJdy80s58C/yDoAvKwu6+o7jhERETKkpZ7ku7+IvBiOs4tIiKSrHRUt4qIiGQEJUkREZE4lCRFRETiUJIUERGJQ0lSREQkDnOvWD/96mRmBcCnFdy9JbCtCsOpbpkcfybHDpkdfybHDpkdf02K/Rh3b5XuIDJZRiTJyjCzRe6el+44KiqT48/k2CGz48/k2CGz48/k2OVQqm4VERGJQ0lSREQkjrqQJKekO4BKyuT4Mzl2yOz4Mzl2yOz4Mzl2KaXW35MUERGpqLpQkhQREamQGp0kzWyoma0xs7Vmdn3U8jPMbImZLTez6WZ2yEDtZnaame0ws/fCY8w3s3OrMfYOZvaqma00sxVm9l9R63qZ2dtmtszMnjOzZjH272Rme8P4V5nZv8xsbHXFXyqWh81sq5ktL7U818zeMbOlZrbIzPrH2Pc0M3u++qI96Nzxrp8FYcxLzWyTmT0dY9/I9RPZbm4Z55pkZv9TRXEnunZmRsW03syWxtg/cu0sjXo0SnC+sWZ2b1XEHh4v3vWS7HXvZvabqGUtzexAVcZYlgTXzuDws2epmb1hZscnOMbTZvZO9UQsKePuNfJBMI3Wx8CxQCPgfaAbQWL/DOgSbvdr4IoY+58GPB/1OhdYDwyupvjbAn3C502BD4Fu4euFwKDw+eXAbTH27wQsj3p9LLAUuCwNf4vvAH2i4wmXvwx8N3z+PeC1sv4O6b5+Ymz3JPCflY0bmAT8T6qvnVLb/RH4VVnXThLnGwvcWw3XS7LX/SfAe1HLrgmv/aRjBBqk4toJ/xbfDp//GJgW5xhHhp9Tq4Bjy3n+CseuR9U/anJJsj+w1t0/cff9wGPAcOBoYL+7fxhu9wpwYVkHc/elBAn1pwBm1srMnjSzheHj1HB5EzObGn7b/cDMyjx2nPNtdvcl4fNdBP8s7cLVXYD55Yz/E+A64GdhnEeE39j/FZY2h4fL65vZnWEp+wMzu7Yi8Zc693zgi1irgEhpoDmwKdFxzKx/WJJ4z8zeMrOu4fKxZjbbzOaY2Udm9ofKxkz86yc6nmbAGcAhJckE7yHmdROKlJQ+MrOrKhp4GddOJA4DRgGPliP2mNdMqIOZvRbGfktFYw9jjne9JHvd7wFWmVmkr+EPgMej3sd5ZvZu+B7mmlmbcPkkM3vEzN4EHqnEW0h07SR7zV8APBfuOzoq9mlmdn9Y8/KhhbVb4f/As2b2T2BeJWKXKpaW+SST1I7gm1jEBuAkgpEsGphZnrsvAkYAHZI85hJgQvj8buAud3/DzDoSTAL9beBmYIe75wCY2VGVfSNm1gnoDbwbLlpB8E/3NDCynPGfGD6/Efinu19uZkcC/wqrBP+T4Nt4rgcTXLeobPwJjAf+YWZ3EpTwTylj+9XAwDCuIcDv+OaDMpfgd7QPWGNm97j7Z3GOk4x410+07wPz3H1nnGMMjKrOfMLdf0v86wagJ3AycATwnpm94O4JvziUJca1UxIbsMXdP4qz63FRsb/p7j8h/jUDQWLoQZCgFoaxL6pM7DGU57p/DBhtZluAIoJk9K1w3RvAye7uZnYl8Avgv8N13YD/cPe9lYgz0bVzJfCime0FdhL8vWO5iOBL+RaC2orfRa3rRPD7Pg54NarKtg/Q091jfcGQNKnJSTKm8B9jNHCXmR1GUOVXlOTuFvV8CNAt+EIOQDMzaxIuL/nm5+5fVibe8JhPAuOjPowvByab2c3As8D+ZA8X9fwsYJh9cx8sC+hIEP/97l4Yxp/Kf7hrgJ+7+5NmNgp4KDx/PM2B6WZ2AsE38oZR6+a5+w4AM1sJHMPBH1SpcBHwYIL1C9y99H3seNcNwDPhh/NeM3uV4IMw6VJqaXGunejYE5UiP3b33FLL4l0zAK+4++fheWcD/wFUdZIsz3U/B7iNIMnMLLWuPTDTzNoSVIeui1r3bCUTZFl+DnzP3d81swnAnwgSZ4mwZHsC8Eb4eXXAzHq4e+Qe7ePuXgx8ZGaf8M0X31eUIGuempwkN3LwN8324TLc/W2Cb9KY2VkE1TjJ6E1QdQVByedkd/86eoOoD79KM7OGBB9yM9x9dmS5u68m+MDCzLoA5yR5yOj4DbjQ3deUOmdlwy6PS4FIo5InSJxwIPjQe9Xdzw9LSK9FrdsX9byIyl+bca8fCBqDECSx88t53ETXTen+VBXuXxXv2gnXNSCozutb3sMS+5o5KUasVd43rDzXvbvvN7PFBCXEbsCwqNX3AH9y92fN7DSC+8ERX1VBqDGvHTNrBfRy90ipfiZBMi9tFHAUsC68LpoRfKm5MVwf73ddFbFLFavJ9yQXAieYWWcLWuaNJvj2iZm1Dn8eBkwE7i/rYGbWk6Aq9S/hopeBa6PWR751vwL8JGp5hapbw3tGDwGr3P1PpdZF4q8H3JRk/J2AOwk+ICCo5rs2PA9m1jsq/h+FH6SkuLp1EzAofH4GEK/qL6I53ySqsSmKKSLu9RMaQdAw5+uYe8cX77oBGG5mWWZ2NEHDn4UVCTzRtRMaAqx29w3lPHS8awbgTDNrYWaHE1RDv1mB0BOqwHX/R2BijNJV9HV0aZUGGYh37XwJNA8TPMCZfPOlNdpFwFB37+TunQi+zIyOWj/SzOqZ2XEEjYPWxDiG1BA1NkmG1YU/JfjHXkVQRbEiXD3BzFYBHwDPufs/4xxmYHhzfw1BcvyZu0duiv8MyLOgcctK4Opw+W+Aoyxo+PI+cHoF38KpwCXAGfZNM/zvhesuMrMPCe7RbQKmxjnGcWH8qwgaLkx298i2txFUV35gZivC1xCU5v4dLn8f+GEF4y9hZo8CbwNdzWyDmV0RrroK+GN4nt8B42Ls3oBvSol/AP6fmb1Himsxyrh+IPjQSrrRS5R41w0E1+OrwDsELTcrej8y0bVTmdjjXTMA/yIouX4APFmZ+5EJrpdkr3sA3H2Fu0+PsWoS8ERY0qzy2TbiXTvh8quAJ8Nr/hK+aeMAlHyZPYbgGogcbx2wIyyxQ/D/+S/gJeDqCnxRk2qkEXckpSzo49fO3X+R7lhE0s3MphHUYMxKdyySnJp8T1IynJk9RNBiclS6YxERqQiVJEVEROKosfckRURE0k1JUkREJA4lSRERkTiUJEVKMbOisNvFCjN738z+O+zbl2ifTmZW6e42IlKzKEmKHGqvu+e6e3eCDuPfBcoa9LsTVdAnVURqFrVuFSnFzHa7e5Oo18cSjMLSkqCj+CMEg5gD/NTd37Jg3sBvE4wjOh2YDNxOMPLOYcBf3P2v1fYmRKRKKEmKlFI6SYbLtgNdgV1Asbt/HQ7U/qi754VjiP5PZEB0MxsHtHb334TDJ74JjAxHXxGRDKHBBETKpyFwbzhmaxHxB9c/C+hpZiPC180JZoZQkhTJIEqSImUIq1uLgK0E9ya3AL0I7unHG3fTgGvd/R/VEqSIpIQa7ogkEE6PdD9wrwf3JpoDm8P5AC8B6oeb7gKaRu36D+CacMorzKyLmR2BiGQUlSRFDnW4mS0lqFotJGioE5my6j6CWSD+k2AuwcgcgB8AReHsENOAuwlavC4Jp6YqIJiCSkQyiBruiIiIxKHqVhERkTiUJEVEROJQkhQREYlDSVJERCQOJUkREZE4lCRFRETiUJIUERGJQ0lSREQkjv8PKnPG8tyhOKwAAAAASUVORK5CYII=\n", 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" ] @@ -8684,7 +8684,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **70-79** population by **ssri**" + "### COVID vaccinations among **70-79** population by **ssri**" ], "text/plain": [ "" @@ -8695,7 +8695,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8709,7 +8709,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **65-69** population up to 30 Mar 2021" + " ## COVID vaccination rollout among **65-69** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -8721,7 +8721,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **65-69** population by **sex**" + "### COVID vaccinations among **65-69** population by **sex**" ], "text/plain": [ "" @@ -8732,7 +8732,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8745,7 +8745,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **65-69** population by **ethnicity 6 groups**" + "### COVID vaccinations among **65-69** population by **ethnicity 6 groups**" ], "text/plain": [ "" @@ -8756,7 +8756,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8769,7 +8769,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **65-69** population by **imd categories**" + "### COVID vaccinations among **65-69** population by **imd categories**" ], "text/plain": [ "" @@ -8780,7 +8780,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8793,7 +8793,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **65-69** population by **bmi**" + "### COVID vaccinations among **65-69** population by **bmi**" ], "text/plain": [ "" @@ -8804,7 +8804,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8817,7 +8817,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **65-69** population by **chronic cardiac disease**" + "### COVID vaccinations among **65-69** population by **chronic cardiac disease**" ], "text/plain": [ "" @@ -8828,7 +8828,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8841,7 +8841,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **65-69** population by **current copd**" + "### COVID vaccinations among **65-69** population by **current copd**" ], "text/plain": [ "" @@ -8852,7 +8852,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8865,7 +8865,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **65-69** population by **dementia**" + "### COVID vaccinations among **65-69** population by **dementia**" ], "text/plain": [ "" @@ -8876,7 +8876,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8889,7 +8889,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **65-69** population by **psychosis schiz bipolar**" + "### COVID vaccinations among **65-69** population by **psychosis schiz bipolar**" ], "text/plain": [ "" @@ -8900,7 +8900,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8913,7 +8913,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **65-69** population by **LD**" + "### COVID vaccinations among **65-69** population by **LD**" ], "text/plain": [ "" @@ -8924,7 +8924,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8937,7 +8937,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **65-69** population by **ssri**" + "### COVID vaccinations among **65-69** population by **ssri**" ], "text/plain": [ "" @@ -8948,7 +8948,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -8962,7 +8962,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **shielding (aged 16-69)** population up to 30 Mar 2021" + " ## COVID vaccination rollout among **shielding (aged 16-69)** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -8974,7 +8974,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **shielding (aged 16-69)** population by **newly shielded since feb 15**" + "### COVID vaccinations among **shielding (aged 16-69)** population by **newly shielded since feb 15**" ], "text/plain": [ "" @@ -8985,7 +8985,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8998,7 +8998,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **shielding (aged 16-69)** population by **sex**" + "### COVID vaccinations among **shielding (aged 16-69)** population by **sex**" ], "text/plain": [ "" @@ -9009,7 +9009,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9022,7 +9022,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **shielding (aged 16-69)** population by **ageband**" + "### COVID vaccinations among **shielding (aged 16-69)** population by **ageband**" ], "text/plain": [ "" @@ -9033,7 +9033,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9046,7 +9046,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **shielding (aged 16-69)** population by **ethnicity 6 groups**" + "### COVID vaccinations among **shielding (aged 16-69)** population by **ethnicity 6 groups**" ], "text/plain": [ "" @@ -9057,7 +9057,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9070,7 +9070,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **shielding (aged 16-69)** population by **imd categories**" + "### COVID vaccinations among **shielding (aged 16-69)** population by **imd categories**" ], "text/plain": [ "" @@ -9081,7 +9081,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9094,7 +9094,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **shielding (aged 16-69)** population by **LD**" + "### COVID vaccinations among **shielding (aged 16-69)** population by **LD**" ], "text/plain": [ "" @@ -9105,7 +9105,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9119,7 +9119,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **60-64** population up to 30 Mar 2021" + " ## COVID vaccination rollout among **60-64** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -9131,7 +9131,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **60-64** population by **sex**" + "### COVID vaccinations among **60-64** population by **sex**" ], "text/plain": [ "" @@ -9142,7 +9142,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9155,7 +9155,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **60-64** population by **ethnicity 6 groups**" + "### COVID vaccinations among **60-64** population by **ethnicity 6 groups**" ], "text/plain": [ "" @@ -9166,7 +9166,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9179,7 +9179,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **60-64** population by **imd categories**" + "### COVID vaccinations among **60-64** population by **imd categories**" ], "text/plain": [ "" @@ -9190,7 +9190,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9203,7 +9203,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **60-64** population by **bmi**" + "### COVID vaccinations among **60-64** population by **bmi**" ], "text/plain": [ "" @@ -9214,7 +9214,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9227,7 +9227,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **60-64** population by **chronic cardiac disease**" + "### COVID vaccinations among **60-64** population by **chronic cardiac disease**" ], "text/plain": [ "" @@ -9238,7 +9238,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9251,7 +9251,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **60-64** population by **current copd**" + "### COVID vaccinations among **60-64** population by **current copd**" ], "text/plain": [ "" @@ -9262,7 +9262,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9275,7 +9275,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **60-64** population by **dementia**" + "### COVID vaccinations among **60-64** population by **dementia**" ], "text/plain": [ "" @@ -9286,7 +9286,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9299,7 +9299,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **60-64** population by **psychosis schiz bipolar**" + "### COVID vaccinations among **60-64** population by **psychosis schiz bipolar**" ], "text/plain": [ "" @@ -9310,7 +9310,7 @@ }, { "data": { - "image/png": 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vffrpp5teffXVbadNm7bpxhtvXBP1PGUmSTO7hiBBzgDeAtYRDDF3CHBdmEAvc/dFFbg2EZGslO45R5UYq9/ZZ5+94dprr21bUFBgQ4cO/bB+/fo+YcKEfceMGfNV06ZNiz766KP6DRo08B07dljr1q0LfvnLX3611157Fd5///0tyz/698orSb7t7uPTbPubmbUG9JCPiOQEPeeYORo2bOj9+/ff1KxZs8J69epx+umnb1qyZEnDPn36HAqw++67Fz322GMfLVu2bLff/e537erUqUO9evX8zjvv/Lgi5ykzSbr7P5Lfm9nu7r41afs6gtKliEhOyNmq1QxTWFjI/Pnz95w8efKKxLqrr7563dVXX71TTurSpct3Q4cOXbqr54nUccfM+pvZUmBZ+L6HmZU5KLmISG3wf299wpl3v1k8CLnUvHnz5jXcf//9uw0YMGBTt27dvovzXFEfAZkIHA88D+DuC83syNiiEhGpYYn2R42xmnl69+797WefffZudZwr8nOS7v6pmSWvqlA3WhGRbJJof1TbYylFRUVFVqdOnfjnWawmRUVFBhSl2hY1SX5qZv0BN7P6wCXAe1UUn4hIRtD0VZEsXr9+fedWrVptrA2JsqioyNavX9+U4NHGUqImyQuAW4C2wCrgFeCiKolQRCRDJPdeVdVqagUFBb9Yu3btfWvXru1K7RiQpghYXFBQ8ItUG6MmSXP3kVUXk4hIZlDpsWJ69+69DjilpuOoLlGT5OtmthKYBDzt7hviC0lEJF6a/FiiipQk3f0QM+sLnAX8IXwc5Al3fzTW6EREqlCqHqvqmCNlqUjv1reBt83sL8DfgIcAJUkRyRrqsSoVFSlJmlkT4DSCkuSBwBSgb4xxiYjEQm2OUhFRS5ILgWeBP7r7mzHGIyJSpVJ1zBGJKmqSPMDds/55GBHJDeqYI1WlvKmybnb3scDzZlYqSbp7znQDFpHMli4xqv1RKqO8kuQj4b83xh2IiEhlaBoriUN5U2XNCxfz3P2W5G1mdgkwM67ARESiSJQgNRCAxCFqm+QogmHpko1OsU5EJHbpqlbV3ihVrbw2yRHAT4COZvZ80qbGwFdxBiYikkxtjlITyitJvgGsAVoCNyWt3wwsiisoERFQYpSaV16b5MfAx4Aq+UWk2qkzjtS0qCPuHA7cBvwAaADUBb5xdz2VKyJVTp1xJFNE7bhzO8GQdJOBfOBnwCFxBSUiuUedcSQTVWSA8w/MrK67FwJ/N7N3gN/FF5qI5BJVrUomipokt5pZA2CBmV1P0JmnNsxILSIZRFWrkmmiJsmzCdohfwX8GmgPDI0rKBHJDRp8XDJd1EmXPw4XtwHXxBeOiNR2Gnxcskl5gwm8C6Sd/cPdu1d5RCJSKyWSo553lGxSXklySLVEISK1XqJjjhKjZJMogwmIiFQJdcyRbBN1MIHNfF/t2gCojwYTEJFyqGOOZLuoHXcaJ5bNzIBTgcPL2sfMGgKzgN3C8zzl7uPNrCPwBNACmAec7e7bdy18Eck06pgjtYm5p+2XU/aOZu+4e88ythuwh7tvMbP6wGvAJcClwDPu/oSZ3QUsdPf/V9a58vPzfe7cubsUp4jEL11iBNT+WIPMbJ6759d0HNksanXr6Ulv6xAMTfdtWft4kH23hG/rhy8HjiGYfgvgIWACUGaSFJHMptFypLaKOpjAyUnLBcBKgirXMplZXYIq1YOAO4AVwAZ3Lwg/8hmQsv7FzMYAYwD220+/bCKZTp1ypDaK2iZ5zq4cPBznNc/MmgFTgEMrsO89wD0QVLfuyvlFJF4lZ+sQqW2iVrd2BC4GOiTv4+6nRNnf3TeY2asE81I2M7N6YWmyHbCqokGLSM3RbB2SS6JWtz4L3A+8ABRF2cHMWgE7wgTZCPgR8FfgVWAYQQ/XUcBzFQ1aRGqO2h8ll0RNkt+6+60VPPY+wENhu2Qd4El3f9HMlgJPmNmfgXcIkq+IZBG1P0quiJokbzGz8cArwHeJle4+P90O7r4IKPWIiLt/CPStYJwiUoM0KIDkqqhJshvBdFnH8H11a+JxDhGphTQogEj0JDkcOEAj44jkDrU9ikRPkouBZsC6GGMRkQxQ8rEOtT1KLouaJJsBy8xsDju3SUZ6BEREskdyglS1quS6qElyfKxRiEiNStUxRyVIkegj7syMOxARqV7qmCNSPs0nKZJD0iVGdcwRSS22+SRFJPOox6pIxURtkywWToH1bDi4wJVVH5KIVIXkUmOC2htFKia2+SRFpPqVNfkxoPZGkQqKdT5JEaleqk4VqVqxzicpItVDAwCIxKNOlA+Z2UPhxMmJ93uZ2QPxhSUiFaEBAETiEbW6tbu7b0i8cfevzazUDB8iEq9UnXFAHXJE4hI1SdYxs73c/WsAM2tegX1FpBLK64wD6pAjEpeoie4m4E0zmxy+Hw5cG09IIpJMnXFEak7UjjsPm9lcvp8/8nR3XxpfWCKSTFWpIjWjzCRpZnu6+xaAMCmWSozJnxGRqlOyx6qIVL/yerc+Z2Y3mdmRZrZHYqWZHWBmPzezl4ET4g1RJDepx6pIzSuzJOnux5rZScD5wBFhh50dwHLgH8Aod18bf5giuUFTVolklnLbJN39JeClaohFJOcllx5VghSpeXqMQyTDqPQokjmUJEVqWKoqVhHJDJGGpROR+CSqWEGDAohkmvIeAWle1nZ3/6pqwxHJDeqgI5IdyqtunQc4YMB+wNfhcjPgE6BjrNGJ1DKJ5Jg8vJxKjyKZq7xHQDoCmNm9wJSwpytmdiLw4/jDE6ldElWrGl5OJDtE7bhzuLufl3jj7v80s+tjikmkVlPVqkj2iJokV5vZVcCj4fuRwOp4QhLJfuVNaSUi2SFqkhwBjAemELRRzgrXiUhIU1qJ1D5RZwH5CrjEzPZw929ijkkkK2lKK5HaJ1KSNLP+wH3AnsB+ZtYDON/dfxlncCLZoORsHWpvFKk9og4mMBE4HvgSwN0XAkfGFZRINtFsHSK1V+Rh6dz9UzNLXlVY9eGIZAcNBiCSG6ImyU/DKlc3s/rAJcB78YUlknnSdcxRCVKk9oqaJC8AbgHaAquAVwC1R0pOUccckdwTNUl2cveRySvM7Ajg9aoPSSRzqVpVJLdETZK3Ab0irBOpVTSNlUhuK28WkH5Af6CVmV2atKkJULecfdsDDwN7EwxAcI+73xLOLDIJ6ACsBM5w96939QJE4qCByEUEyi9JNiB4NrIe0Dhp/SZgWDn7FgCXuft8M2sMzDOzfwGjgenufp2ZXQlcCVyxK8GLxEUDkYsIlD8LyExgppk96O4fV+TA7r4GWBMubzaz9wg6/pwKHBV+7CFgBkqSkgH0WIeIlBS1TXKrmd0AdAEaJla6+zFRdjazDkBP4C1g7zCBAqwlqI5Ntc8YYAzAfvvpW7zEQ491iEhZoibJxwjaEYcQPA4yClgfZUcz2xN4Ghjr7puSByRwdzczT7Wfu98D3AOQn5+f8jMilaXHOkSkLFGTZAt3v9/MLkmqgp1T3k7hwANPA4+5+zPh6s/NbB93X2Nm+wDrdi10kaqhalURSSfq2K07wn/XmNlgM+sJNC9rBwuKjPcD77n735I2PU9QEiX897kKxCsiIlJtopYk/2xmTYHLCJ6PbAL8upx9jgDOBt41swXhut8D1wFPmtnPgY+BMyoctUgl6NlHEYkq6nySL4aLG4GjI+7zGmBpNh8b5RgicUhuh1QHHREpS9T5JFsB5xEMAFC8j7ufG09YIlUjudSYoMc7RCSqqNWtzwGzgWloiizJIsmlxgSVHkUkqqhJcnd31wP/kpVUahSRXRU1Sb5oZie5+0uxRiOyi1JVq4I65ohI5UR9BOQSgkS5zcw2mdlmM9sUZ2AiFZGoVi1JVasiUhlRe7c2Lv9TItUvUYJUZxwRiUN5U2Ud6u7LzCzlvJHuPj+esESiSU6QKjGKSFUrryR5KcEg4zel2OZApAHOReKkEqSIxKW8qbLGhP9GGkBApDpoxBwRqS5RBxO4iGCQ8g3h+72AEe5+Z5zBiSRoSisRqQlRHwE5z93vSLxx96/N7DxASVJiky4xakorEakuUZNkXTMzd3cAM6sLNIgvLBHN9SgiNS9qkpwKTDKzu8P354frRKqcHusQkUwRNUleQdDL9cLw/b+A+2KJSHKeHusQkUwRNUk2Au5197uguLp1N2BrXIFJbknVY1UlSBGpaVGHpZtOkCgTGhHMCCJSJZKHlVMJUkQyRdSSZEN335J44+5bzGz3mGKSHKXSo4hkmqhJ8hsz65UYhs7MegPb4gtLcoEGBRCRTBc1SY4FJpvZasCANsCZsUUltZYGBRCRbBJ1FpA5ZnYo0Clctdzdd8QXltQ2ieSoQQFEJJtELUlCkCA7Aw2BXmaGuz8cT1hS2yQ65igxikg2iTp263jgKIIk+RJwIvAaoCQpkaljjohkm6glyWFAD+Addz/HzPYGHo0vLKkN1DFHRLJd1CS5zd2LzKzAzJoA64D2McYlWUodc0SkNomaJOeaWTPgXmAesAV4M7aoJOuoY46I1EZRe7f+Mly8y8ymAk3cfVF8YUm2UcccEamNonbceR54AnjO3VfGGpFkLXXMEZHaJmp1600Egwf8r5nNIUiYL7r7t7FFJhlPHXNEpLaLNMC5u88Mq1wPAO4GziDovCM5TIOSi0htF3kwATNrBJxMUKLsBTwUV1CSPVTFKiK1WdQ2ySeBvsBU4HZgprsXxRmYZCZVsYpILolakrwfGOHuhXEGI5lJzz6KSK6K+gjIy3EHIplHzz6KSK6ryADnkmP07KOI5DolSSmTOuaISC6L2nFnursfW946yX7qmCMi8r0yk6SZNQR2B1qa2V6AhZuaAOqxUUuoY46ISGrllSTPB8YC+xIMbJ5IkpsIHgWRLJUuMar9UUTke2UmSXe/BbjFzC5299uqKSapBolOOZ33aaLEKCKSRtRHQG4zs/5Ah+R93P3hdPuY2QPAEGCdu3cN1zUHJoXHWQmc4e5f72LssgsSJchEglSnHBGR9CKN3WpmjwA3Aj8E+oSv/HJ2exA4ocS6K4Hp7n4wMD18L9UoOUGqvVFEpGxRHwHJBzq7u0c9sLvPMrMOJVafChwVLj8EzACuiHpM2TWpeqyqBCkiUr6oSXIx0AZYU8nz7e3uiWOsBfZO90EzGwOMAdhvP7WVVZR6rIqIVF7UJNkSWGpmbwPfJVa6+ym7emJ3dzNLWzJ193uAewDy8/Mjl2AloI45IiKVFzVJTqii831uZvu4+xoz2wfNSVmlVK0qIlK1Ik+6TNAbtX64PAeYvwvnex4YFS6PAp7bhWNIGpoEWUSkakUdlu48gvbB5sCBBKPt3AWkHZbOzB4n6KTT0sw+A8YD1wFPmtnPgY+BMyoTfC5LLjUmqPQoIlK1ola3XkQw6fJbAO7+vpm1LmsHdx+RZpPGe60CyW2OCSo9iohUrahJ8jt3324WjEpnZvUAdaapYSo1iojEK2qSnGlmvwcamdmPgF8CL8QXlqSiGTpERKpX1CR5JfBz4F2CQc9fAu6LKyj5np53FBGpOVGTZCPgAXe/F8DM6obrtsYVmAT0vKOISM2JmiSnA4OALeH7RsArQP84gpKdqe1RRKRmRE2SDd09kSBx9y1mtntMMQmlZ+sQEZHqFzVJfmNmvdx9PoCZ9Qa2xRdWbkrX/qi2RxGRmhE1SV4CTDaz1YARDHZ+ZmxR5Si1P4qIZJZyk6SZ1QEaAIcCncLVy919R5yB5QqNtyoikrnKHbvV3YuAO9x9h7svDl9KkFVE462KiGSuyL1bzWwo8ExFJl6W1FR6FBHJDpFmASEYQGAysN3MNpnZZjPbFGNctZpKjyIi2SFSSdLdG8cdSC4o+ViHSo8iIpktUknSAj81s6vD9+3NrG+8odU+yQlSpUcRkcwXtU3yTqAIOAb4E8HIO3cAfWKKq9ZQ+6OISPaK2iZ5mLtfBHwL4O5fEzwWIuVQ+6OISPaKWpLcEQ5q7gBm1oqgZCkpqPQoIlI7RC1J3gpMAVqb2bXAa8BfYosqy6n0KCJSO0Tt3fqYmc0DjiUYlu7H7v5erJFlOZUeRUSyX5lJ0swaAhcABxFMuHy3uxdURytvRrcAAA1hSURBVGDZJlUVq4iIZLfySpIPATuA2cCJwA+AsXEHlU0SyTF51g5VsYqI1A7lJcnO7t4NwMzuB96OP6TMV9aUVpq1Q0Sk9igvSRYPZO7uBWYWczjZQVNaiYjkhvKSZI+kMVoNaBS+N8DdPWcb3tQxR0Sk9iszSbp73eoKJNOpY46ISO6JOphATkrX9qiOOSIiuUFJsgxqexQRyW1KkuVQ26OISO6KOiydiIhIzlFJMoWSkyOLiEhuUpIMlTVAgIiI5KacTpLpEqM66YiICOR4klTvVRERKUtOJ0lQ71UREUkvJ5OkOuaIiEgUOZMk1TFHREQqKmeSpNofRUSkonImSYLaH0VEpGJqJEma2QnALUBd4D53vy6O81zzwhKWrg5m+lL7o4iIVFS1D0tnZnWBO4ATgc7ACDPrHPd5NXOHiIhUVE2UJPsCH7j7hwBm9gRwKrC0qk80vt4j0ODd71csjeMsIiIxadMNToylok0iqokBztsCnya9/yxctxMzG2Nmc81s7vr166stOBERkYSM7bjj7vcA9wDk5+f7Lh1E38BERKQSaqIkuQpon/S+XbhOREQko9REkpwDHGxmHc2sAXAW8HwNxCEiIlKmaq9udfcCM/sV8DLBIyAPuPuS6o5DRESkPDXSJunuLwEv1cS5RUREoqqJ6lYREZGsoCQpIiKShpKkiIhIGkqSIiIiaZj7rj2nX53MbD3w8S7u3hL4ogrDySS6tuxUW6+ttl4XZO+17e/urWo6iGyWFUmyMsxsrrvn13QccdC1Zafaem219bqgdl+blE3VrSIiImkoSYqIiKSRC0nynpoOIEa6tuxUW6+ttl4X1O5rkzLU+jZJERGRXZULJUkREZFdoiQpIiKSRkYnSTM7wcyWm9kHZnZl0vpjzGy+mS02s4fMrNRA7WZ2lJltNLN3wmPMMrMh1XsFqZlZezN71cyWmtkSM7skaVsPM3vTzN41sxfMrEmK/TuY2bbw2t4zs7fNbHS1XkQEZvaAma0zs8Ul1ueZ2X/MbIGZzTWzvin2PcrMXqy+aKMr476cHV7TAjNbbWbPptg3cV8mPjetnHNNMLPfxHEdJc5T1j05KSnelWa2IMX+iXtyQdKrQRnnG21mt8d1PSnOl+5ejPr75mb256R1Lc1sR3Veg9QQd8/IF8E0WiuAA4AGwEKgM0Fi/xQ4JPzcH4Gfp9j/KODFpPd5wErg2Ay4tn2AXuFyY+C/QOfw/RxgYLh8LvCnFPt3ABYnvT8AWACcU9PXViLOI4FeybGG618BTgyXTwJmlPf/lymvdPdlis89DfysstcFTAB+Uw3XlfaeLPG5m4BxKdbvdE9GON9o4PZq/H9Ldy9G/X37EHgnad2F4e9c5GsA6lXX9epVda9MLkn2BT5w9w/dfTvwBHAq0ALY7u7/DT/3L2BoeQdz9wUECfVXAGbWysyeNrM54euIcP2eZvb38JvlIjMr99gV5e5r3H1+uLwZeA9oG24+BJgVLke9tg+BS4H/Ca9hj/Cb89thafPUcH1dM7sxLIEvMrOLq/bKSsU1C/gq1SYg8Y29KbC6rOOYWd/w2/47ZvaGmXUK1482s2fMbKqZvW9m11fpBaSW7r5MjrcJcAxQqiSZTrr7MZQo7bxvZudVxUWUVM49mYjRgDOAx6MeN929GGpvZjPC6xpfBZeRVhn3YtTft63Ae2aWGFDgTODJxEYzO9nM3gqvcZqZ7R2un2Bmj5jZ68AjVXEtUr1qZD7JiNoSlBgTPgMOIxgaqp6Z5bv7XGAY0D7iMecDl4fLtwAT3f01M9uPYBLoHwBXAxvdvRuAme1V6Sspg5l1AHoCb4WrlhD80X0WGE7Fru3QcPkPwL/d/Vwzawa8HVbr/YzgW3GeB5NfN6+Ka9gFY4GXzexGgpqB/uV8fhkwIIx5EPAXvv9jlkfw8/sOWG5mt7n7p2mOUxXS3ZfJfgxMd/dNaY4xIKnKcrK7X0v6+xGgO3A4sAfwjpn9w93L/GJRGSnuyeK4gc/d/f00ux6YdF2vu/tFpL8XIfjC0ZUgAc0Jr2tuFV5KFBX5fXsCOMvMPgcKCb7c7Rtuew043N3dzH4B/Ba4LNzWGfihu2+LIX6JWSYnyZTCm/AsYKKZ7UZQdVcYcXdLWh4EdA6+HAPQxMz2DNeflXS+rysfdZpggvM9DYxN+oN6LnCrmV0NPA9sj3q4pOXjgFOS2rIaAvsRXNtd7l4A4O6pvllXhwuBX7v702Z2BnB/GFs6TYGHzOxgglJo/aRt0919I4CZLQX2Z+ckVhNGAPeVsX22u5dsH093PwI8F/6B3WZmrxIkl8il1IpIc08mjKDsUuQKd88rsS7dvQjwL3f/MjzvM8APgepOkhX5fZsK/An4HJhUYls7YJKZ7UNQDf9R0rbnlSCzVyYnyVXs/K2uXbgOd3+T4FstZnYcQZVJFD0JqpEgKMEc7u7fJn8g6Y9UrMysPsEfo8fc/ZnEendfRvCHBTM7BBgc8ZDJ12bAUHdfXuKclQ27qowCEh1DJlN2QoHgD9Or7n5aWMqZkbTtu6TlQuK/p9PelxB06CBIYqdV8Lhl3Y8lH2aO5eHmdPdkuK0ecDrQu6KHJfW9eBjVdF1lqcjvm7tvN7N5BCXEzsApSZtvA/7m7s+b2VEEbckJ31Rx2FKNMrlNcg5wsJl1tKCX3FkE3/Qws9bhv7sBVwB3lXcwM+tOUJV6R7jqFeDipO2Jb8D/Ai5KWl/l1a1h2879wHvu/rcS2xLXVge4imjX1gG4keAXFYKquovD82BmPcP1/wLOD//gUYPVrauBgeHyMUC66ruEpnyfiEbHFFNUae/L0DCCjjnfptw7vXT3I8CpZtbQzFoQdPyZs0uRl6GsezI0CFjm7p9V8NDp7kWAH5lZczNrRFBF/fouhF4pu/D7dhNwRYpamOR7dFSVBik1KmOTZFgl+CuCX7L3gCfdfUm4+XIzew9YBLzg7v9Oc5gBYUP6coLk+D/uPj3c9j9AvgUdWJYCF4Tr/wzsZUHnloXA0VV/dRwBnA0cY993lz8p3DbCzP5L0A63Gvh7mmMcGF7bewQdCG5198Rn/0RQJbnIzJaE7yEosX0Srl8I/KTKryyJmT0OvAl0MrPPzOzn4abzgJvCGP4CjEmxez2+LyVeD/yvmb1DDdd+lHNfQpA0I3dsSZLufoTgPn8V+A9B78s42iPLuidh168r3b0I8DZByXUR8HSc7ZFl3ItRf98AcPcl7v5Qik0TgMlhSTMbp9SSNDQsnWQkC57Ta+vuv63pWEQkd2Vym6TkKDO7n6DX4xk1HYuI5DaVJEVERNLI2DZJERGRmqYkKSIikoaSpIiISBpKkpLRzKwwfBxhiZktNLPLwmfaytqng5nF+nhLRZnZG5XYd7SZ7Vv+J3fap4OVmPFCRCpOSVIy3TZ3z3P3LsCPgBOB8gbD7kDMz4BWlLuXNz5tWUbz/RihIlKNlCQla7j7OoKBB35lgQ4WzOE4P3wlEtF1hIOIm9mvLZj95AYLZtdYZGbnlzy2mV1nZskjLU0ws99YMCvM9PD471rSLBZm9rPweAvN7JFw3d5mNiVctzARk5ltCf89yoKZL54ys2Vm9ljSaDTjwhgXm9k94TUOA/KBx8LraWRmvc1sppnNM7OXLRgvlHD9wnCQhuJrEZFKqOm5uvTSq6wXsCXFug3A3sDuQMNw3cHA3HD5KHaeS3QMcFW4vBvBINodSxyzJzAz6f1SgjFa6wFNwnUtgQ8IxiPtQjDnYstwW/Pw30kEg4NDMPdk0+TrCGPbSDDmax2CUWB+mHyMcPkR4ORweQaQHy7XB94AWoXvzwQeCJcXAUeGyzdQgfkd9dJLr9QvDSYg2aw+cHs4zmkh6Qe6Pw7oHpbKIBhn82CSZmpw93fMrHXY9tcK+NrdP7Vg0O+/mNmRQBHBVFl7E4w5O9ndvwj3T4zleQzBlGS4eyFBQizpbQ/HQLVgaqkOBFMtHW1mvyVI/s0JpnF6ocS+nQgGWvhXWACtC6yxYBqqZh7MmwhBkj0xzc9DRCJSkpSsYmYHECTEdQRtk58DPQhKZekGFTfgYnd/uZzDTyYYoLwN30+FNJIgafZ29x1mtpJguqfKKDVziZk1BO4kKDF+amYT0pzHgCXu3m+nlUGSFJEqpjZJyRpm1opglobb3d0JSoRr3L2IYHDuuuFHNwONk3Z9GbgwLBViZoeY2R4pTjGJYCDvYQQJk/Ac68IEeTTBfJUA/waGWzAzR/KMKtMJ5sskbAttGvHyEgnxCwvmdByWtC35epYDrcysX3iO+mbWxd03ABvM7Ifh50ZGPK+IlEFJUjJdo8QjIMA0gimlrgm33QmMCjuqHMr38/YtAgrDTiy/Jpj9ZCkwP3ws4m5S1KJ4MJtHY2CVu68JVz9GMDvHuwTVqMuSPnstMDM8f2J6qUsIqk3fBeYRzDtYrjDJ3QssJkjqydNhPQjcFVbN1iVIoH8Nz7sASHRYOge4I/xcxkweKpLNNHariIhIGipJioiIpKEkKSIikoaSpIiISBpKkiIiImkoSYqIiKShJCkiIpKGkqSIiEga/x/HuHH+l8p/8wAAAABJRU5ErkJggg==\n", + "image/png": 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\n", 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" ] @@ -9323,7 +9323,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **60-64** population by **ssri**" + "### COVID vaccinations among **60-64** population by **ssri**" ], "text/plain": [ "" @@ -9334,7 +9334,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9348,7 +9348,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **55-59** population up to 30 Mar 2021" + " ## COVID vaccination rollout among **55-59** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -9360,7 +9360,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **55-59** population by **sex**" + "### COVID vaccinations among **55-59** population by **sex**" ], "text/plain": [ "" @@ -9371,7 +9371,7 @@ }, { "data": { - "image/png": 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q8Jaom1lDvhn2EIu7zwJmhc8/AlIvVCcikkVSVn8P/BbWvQ8tUrTtZW/Ft2Tjxo3d27RpsyXTE2FxcbFt3LixFcGwvqTiJsFLCNrz2hO04U0HflLtCEVEslzK6i97K71y7d69+0fr1q27d926dT3J/DVpi4Elu3fv/lGqN8RNgubuo2smJhGR3JK0+sveSq9c/fv33wCcUtdx1JS4SfB1M1sBTAb+7u6b0xeSiEgWCHt3XvdZOGPXA61ytvrLZbGSoLsfZmYDgbOAX5vZUuAxd/9bWqMTEckg0fa/6z67j4JdH7HND6Zpo/rBG3K0+stllekd+ibwppn9DvgjwZRnSoIiktsi4/n6fLqFQ3fuoWmj+hTs+ogVDbtwywE3c2phe3rU8DJIUjviDpZvCZxGUAkeAkxFPTxFJA+sn/M3mn+xjBUNu7AtTIA92rUC+tKj10gmD8iRybDzVNxKcDHwFPAbd5+bxnhERDJC4tbnzzd9BXTi1rY3A6jqyzFxk2AXz4Yl6EVEakhi6EOLxg1o3Xyf3Fn+SEopNwma2Z/c/QrgaTPbKwm6e850kxURiTpu2/Nc12gmPeyT1APeJetVVAk+FP57S7oDERHJJEO2z6Rg10fQqa96fOawipZSWhA+LXT326L7zOxyYHa6AhMRqRWR3p/rt37NpqIdAHTc+SErGh1CD435y2lxp7w5L8m2MTUYh4hI3Uis5gBsKtrBtp3B2gCrGh1C0aGn1WVkUgsqahM8GzgH6GxmT0d2tQA+T2dgIiJpE6n+dq5ZzPv1CvjNznEs3VnB8keScypqE5wDfAq0Bv4Q2b4VeDtdQYmIpFVkLb/36xXwxM4g6SVd/FZyWkVtgiuBlYD+LBKR7JeoACNzfP7m7mDos6q//BSrTdDMjjCzeWZWZGY7zWyPmX2Z7uBERGpUNAGqx6cQf7D8HQRTpk0BBgD/ARyWrqBERNJh/dav2eSd+M3OcbAAWDC3ZC1AyU+VmUD7AzOr7+57gAfM7C3gl+kLTUSkiiIdX6Kaf7GMT/zgUtvUDpjf4ibBbWbWCFhkZjcRdJbJ9BWFRSRfRW57Rsf+bfODeavVMLX/SYm4SfBcoD7wU+DnQEfg9HQFJSJSadHqL9Lx5Wd3z2Xp59/c8lTVJ1FxF9VdGT7dDlyfvnBERKooWv01O5Rpm/sx4+5v2vxU/UkyFQ2WfwdIuXqEu/eu8YhERCojrACjg97fWBvM5TGos9r8pHwVVYIjaiUKEZGqCivA6KD3QZ3359TC9pyjdf+kAnEGy4uIZJYk056dtfO/dNtTKi3uYPmtZvZl+Phag+VFpE5FJr1OVIC67SlVEbdjTIvEczMz4FTgiHQFJSJS1htT/kDz96cCULDrI1Y07KJJr6XaKj3WzwNPASemIR4RkaSavz+Vjjs/BGBFwy683uQYQB1fpHpiVYJm9oPIy3oEU6d9nZaIRERC0eqv484PWdXoEHr86jUAegBj6zA2yQ1xB8ufHHm+G1hBcEtURCRtEtXfqkaHaJFbSYu4bYLnpzsQEclzkR6fianOylZ/IjUt7u3QzsBlQEH0M+5+SnrCEpG8E5nxZVPRDrbt3KPqT9Iu7u3Qp4D7gGeA4vSFIyJ5Jcl4P/X4lNoUNwl+7e63pzUSEck/keovOuOLenxKbYmbBG8zs/HAdGBHYqO7L0xLVCKSF6KL3Kr6k7oQNwn2IlhO6Vi+uR3q4WsRkSpJtP2Bqj+pG3GT4BlAF3ffGffAZtYYeAXYJ/yeJ9x9fNjJ5jHgAGABcG5ljisi2Sk65i8h0ftT1Z/UlbgzxiwB9q3ksXcAx7p7H6AQGG5mRwC/B251938DvgAurORxRSRLPPLGJ4y6ey6j7p6LvzOFjjs+LLVfvT+lrsWtBPcF3jOzeZRuE0w5RMLdHSgKXzYMH4lbqOeE2x8EJgD/W6moRSQrFM2ZyFVbXqZpo/oU1P+Eov260+NnM+o6LJEScZPg+Koc3MzqE9zy/DfgTuBDYLO77w7fshpI2ghgZmMJZ0Xq1ElrgolkoyHbZ1JgK2nWri/Ql2a9RtZ1SCKlxJ0xZnZVDu7ue4BCM9sXmAp0q8Rn7wHuARgwYEDK1e1FJANExvtFJVZ76HH+c3UQlEjF4s4Ys5XgViZAI4Jbm1+5e8s4n3f3zWY2ExgM7GtmDcJqsAOwpvJhi0hGiYz3S0x5BrDND+atJsfQo47DE0klbesJmlkbYFeYAJsAxxN0ipkJjCToIXoeMK1qoYtInUtUgGEC5Pzn+Nndc1n6eTDmD9CwB8locdsES4QdXp4KB89fW85b2wEPhu2C9YDH3f1ZM1sKPGZmvwXeIpiOTUSyUZgA1zc7lGmb+zHj7rks/VSD3iV7pG09QXd/G+ibZPtHwMBKxCgimSTa/hdWgD/bOS5Ifk016F2yi9YTFJHKibb/hRXg0i2q/iQ7aT1BEUkuRY/Pvdr/wtufqv4kG8WaMcbMHgyHOSRe72dm96cvLBGpc4mKr4z1zQ7lns39GFWm/e+cQRrPK9kn7u3Q3u6+OfHC3b8ws73a+0QkByTp8RlVUv2p/U9yQNwkWM/M9nP3LwDMbP9KfFZEskk0AYYzvDzyxidMWxQM6VXvT8klcRPZH4C5ZjYlfH0G8N/pCUlE6lyZCnDaojUlyU/Vn+SSuB1j/mpm8/lm/cAfuPvS9IUlIrUq0glm55rFvF+vgN/cPbdkt6o/yVXlJkEza+7uRQBh0tsr8UXfIyLZaf2cv9H8i2WsaNiFrTs7MG3PwGDFz5CqP8lVFVWC08xsEcHUZgvc/SsAM+sCHAOcCUwEkvSjFpGMk2LYQ/MvlrHUD+aWA24GgqnO/ke9PSUPlJsE3f04M/secDEwJOwQswtYDjwHnOfu69IfpojUiPImum41TLc7Je9U2Cbo7s8Dz9dCLCJSk5JVfZroWqQUDXMQyVXRoQ4hTXQtUpqSoEguSTK5dXSogwa6i5SmJCiSS5JMbj1DQx1EUqpoiMT+5e13989rNhwRiS1Om19Y9SWo+hMpraJKcAHggAGdgC/C5/sCnwCd0xqdiKSmNj+RaqtoiERnADObCEwNe4piZt8Fvp/+8EQkzpJGCWrzE6mcuG2CR7j7RYkX7v4PM7spTTGJSFSSig8oNcF1lKo/kfjiJsG1ZjYO+Fv4ejSwNj0hiQhQ4ZJGIlJ9cZPg2cB4YCpBG+Er4TYRSZckSxpFRZc3Ski0A4pIPHFXkfgcuNzMmiXmDxWRGlKJNr+o6PJGCWoHFKmcWEnQzI4E7gWaA53MrA9wsbv/OJ3BieSFSrb5Ran9T6R64t4OvRU4EXgawN0Xm9l30haVSK6rYGaXVJKt8C4iVVcv7hvdfVWZTXtqOBaR/JGo/iBWxZeQuAUKuvUpUhPiVoKrwluibmYNgcuBZekLSyRHVaHHZ7LqT7dARWpG3ErwEuAnQHtgDVAIqD1QpLIq6PGZjKo/kfSJWwl2dffR0Q1mNgR4veZDEskBVezxGZWoAFX9iaRP3ErwzzG3iQiUbvOLqkIFqOpPJH0qWkViMHAk0MbMrozsagnUT2dgIlmnij0+o9T+J1K7KqoEGxGMDWwAtIg8vgTi/Tkrki+q2OMzSu1/IrWrolUkZgOzzWySu6+spZhEsks15/hU9SdSd+J2jNlmZjcDPYDGiY3ufmxaohLJJlXo8RkVbftT9SdSu+ImwYeBycAIguES5wEb0xWUSMargRlfElT9idSduL1DD3D3+4Bd7j7b3S8AVAVK/qqBGV8SVP2J1J24leCu8N9PzewkgrUE909PSCIZpIrj/ZJVfKCqTyTTxK0Ef2tmrYBfAFcRrCjx8/I+YGYdzWymmS01s3fN7PJw+/5m9pKZvR/+u1+1zkAknao43i9ZxQeq+kQyTdz1BJ8Nn24Bjol57N3AL9x9oZm1ABaY2UvAGGCGu99oZtcC1wLXVC5skVpUxVXdVfGJZL646wm2AS4CCqKfCdsGk3L3T4FPw+dbzWwZwdyjpwJHh297EJiFkqBkmrLDHmLQMkci2Sdum+A04FXgZaqwhJKZFQB9gTeAg8IECbAOOCjFZ8YCYwE6depU2a8UqZ5qTHStoQ4i2SNuEmzq7lWq1sysOfB34Ap3/9LMSva5u5uZJ/ucu98D3AMwYMCApO8RqVHVHPagTi8i2Sdux5hnzex7lT14uPbg34GH3f3JcPN6M2sX7m8HbKjscUXSoprDHlT9iWSfuJXg5cCvzGwHwXAJIyjkUjZ6WFDy3Qcsc/c/RnY9TTDY/sbw32lVCVwkllRDHJLRQrcieSdWJejuLdy9nrs3cfeW4euKWv2HAOcCx5rZovDxPYLkd7yZvQ8MC1+LpEeqIQ7JaKFbkbxT0VJK3dz9PTPrl2y/uy9M9Vl3f42gYkzmuPghilRSDSxplIyqP5HcU9Ht0CsJemj+Ick+R1OnSSaK9uys4qTWyaj3p0juqWgppbHhv3EHyIvUrmRtfqr+RCSmWG2CZvYTM9s38no/M/tx+sISiSlZm18aqj9Q259ILorbO/Qid78z8cLdvzCzi4C/pCcskXLUQptfgqo/kdwWd5xgfYuMcjez+kCj9IQkUoEqjueriJY5Esk/cSvBF4DJZnZ3+PricJtI7VCPTxFJg7hJ8BqCXqKXhq9fIlhOSaR21GCPz2jie+PjzwEY1Hl/VX0ieShuEmwCTHT3u6Dkdug+wLZ0BSaSruovOtRhUOf9ObWwPecM0iTtIvkobhKcQTC7S1H4ugkwHTgyHUGJADU+3k8TXYtIWXGTYGN3TyRA3L3IzJqmKSbJd2XX8quB6g800bWI7C1uEvzKzPolpkkzs/7A9vSFJXmtCmv5paKOLyJSnrhJ8ApgipmtJZgPtC0wKm1RSf6phfY/VYAiUlasJOju88ysG9A13LTc3XelLyzJO2nq/anqT0TKE7cShCABdgcaA/3MDHf/a3rCkpxT0bp+qv5EpA7ESoJmNh44miAJPg98F3gNUBKUeKKVXjKq/kSkDsStBEcCfYC33P18MzsI+Fv6wpKckKZ2vmRU/YlIVcRNgtvdvdjMdptZS2AD0DGNcUkuSNO6flEa+yci1RE3Cc4Pl1KaCCwgGDQ/N21RSfaqxeoPNPZPRKonbu/QxNqBd5nZC0BLd387fWFJ1qrF6g/U/ici1RO3Y8zTwGPANHdfkdaIJHukeVX3VNT+JyI1Je7t0D8QDI7/HzObR5AQn3X3r9MWmWS+ZD0+Vf2JSBaJezt0NjA7XD3iWOAi4H6gZRpjk0xUi21+WvJIRNIt9mB5M2sCnExQEfYDHkxXUJLBaqHNL0FLHolIusVtE3wcGEiwmvwdwGx3L05nYJLB0tzmp2EPIlJb4laC9wFnu/uedAYjGSrZLdA00rAHEaktcdsEX0x3IJLBNOxBRHJUZSbQlnyTpsVtk9GwBxGpC0qCkloNLm6bjKo/EalrcTvGzHD34yraJlkq1TJHmvRaRHJcuUnQzBoDTYHWZrYfwaryEIwP1G+sXJFqmaMarACjVV+Cqj8RqWsVVYIXA1cA3yKYODuRBL8kGCoh2aoOJ7pOUPUnInWt3CTo7rcBt5nZZe7+51qKSWpDLQ56T1DVJyKZJu4QiT+b2ZFAQfQz7q6V5bNBHU10LSKS6eJ2jHkIOARYBCQGzDugJJgN6mii66iyt0JFRDJB3CESA4Du7u7pDEbSqJaqvmRtf6D2PxHJTHGT4BKgLfBp3AOb2f3ACGCDu/cMt+0PTCa4rboCONPdv6hEvJKhNN+niGSjuEmwNbDUzN4EdiQ2uvsp5XxmEkEP0ugt02uBGe5+o5ldG76+plIRSzy1MN9nqqWOVPGJSLaImwQnVPbA7v6KmRWU2XwqcHT4/EFgFkqC6VELvT+11JGIZLvYi+qa2cHAoe7+spk1BepX4fsOcvfELdV1wEGp3mhmY4GxAJ066RdruWqx96emOhORXFIvzpvM7CLgCeDucFN74KnqfHHYySZlRxt3v8fdB7j7gDZt2lTnq3JfouqLSnP1B+rsIiLZL+7t0J8QLKr7BoC7v29mB1bh+9abWTt3/9TM2gEbqnAMSSaNvT9V/YlIropVCQI73H1n4oWZNaCcKq4cTwPnhc/PA6ZV4RhSyzEJwbAAABB1SURBVFT9iUiuilsJzjazXwFNzOx44MfAM+V9wMweJegE09rMVgPjgRuBx83sQmAlcGZVA8971ez9mWpQezKq/kQkV8VNgtcCFwLvEEyq/Txwb3kfcPezU+zS8ks1oZq9P1MNak9G1Z+I5Kq4SbAJcL+7TwQws/rhtm3pCkySqIGVHzSoXUTkG3HbBGcQJL2EJsDLNR+OlCvaC7SKvT+jCVDVnYjku7iVYGN3L0q8cPeicKygpFsNVn+g9j0Rkai4leBXZtYv8cLM+gPb0xOSlFKD1R+ofU9EJCpuJXg5MMXM1hKsLt8WGJW2qOSbCrAS1V9Fyxip+hMRKa3CJGhm9YBGQDega7h5ubvvSmdgeS+aAGNWf1rGSESkcipMgu5ebGZ3untfgiWVJF1qoP1PFZ+ISHyxe4ea2elmZmmNJt9Vsf3vkTc+YdTdc0va/UREJJ64bYIXA1cCe8xsO0G7oLt7xSOtZW/JVn2AKld/GvYgIlI1cZdSapHuQPJKtL0vqoLqTx1fRERqVqwkGN4GHQ10dvcbzKwj0M7d30xrdLmsmhVflCpAEZGqiXs79C9AMXAscANQBNwJHJ6muPJesqpPFZ+ISM2K2zFmkLv/BPgawN2/IBg2IWkSHeCeoIpPRKRmxa0Ed4WTZjuAmbUhqAylMsoOgC9D05uJiNSuuJXg7cBU4EAz+2/gNeB3aYsqV1UwAF7Tm4mI1K64vUMfNrMFBGsBGvB9d1+W1shyRZIB8I90/1+mLVgDC+aWequqPxGR2lVuEjSzxsAlwL8RLKh7t7vvro3AckaSxW+nLVAvTxGRTFBRJfggsAt4Ffgu8G3ginQHlfVSTH/2yBuflEqAqvhEROpWRUmwu7v3AjCz+wCNC4wjSfUHmtlFRCTTVJQES1aKcPfdmjq0HJHqb+eaxbxfr4Df7BwX7FsALJirClBEJMNUlAT7mFlisJoBTcLXmjs0lBjWcN1n91Gw6yNWNOzC1p0dmLZnIBxQ+r2qAEVEMku5SdDd69dWINmqaM5ErtryMgW2khUNu/CbA24G4NTC9vzPoE51HJ2IiJQn7mB5iYgOar9qy8t0t5U069SXHr1GMnmAbnWKiGQLJcEqSFR/TRvVp8BWUrTft2lWycmwRUSk7ikJxpS0+mvXF+hLs5iL34qISGZREoxJ1Z+ISO5REkwi2TJGqv5ERHKPkmASiUHtl7V6jSHbZwKo+hMRyUFKgil0b9eSsY0WwtefhMseqfoTEck1SoJJHLft+aACtE9K5v0UEZHck9dJMFnbH1Ay+J1OfZOu+yciIrkhr5NgtMdnlNr/RETyQ14mwUQFWLrHZ5Ta/0RE8kFeJsFEBdhdFZ+ISF7LmySYar5PVXwiIvmrTpKgmQ0HbgPqA/e6+43p+J7rn3mXpWuDlaC6fDKFn9efQ4vGDdTmJyIiQB0kQTOrD9wJHA+sBuaZ2dPuvjSd3/vDZm9yaPFqGrXrg9r8REQE6qYSHAh84O4fAZjZY8CpQI0nwfENHoJG7wQv7BNo30dj/kREpES9OvjO9sCqyOvV4bZSzGysmc03s/kbN26s/re27aUxfyIiUkrGdoxx93uAewAGDBjgVTrId9PS1CgiIjmiLirBNUDHyOsO4TYREZFaVRdJcB5wqJl1NrNGwFnA03UQh4iI5Llavx3q7rvN7KfAiwRDJO5393drOw4REZE6aRN09+eB5+viu0VERBLq4naoiIhIRlASFBGRvKUkKCIieUtJUERE8pa5V20cem0ys43Ayip+vDWwqQbDySQ6t+yUq+eWq+cF2XtuB7t7m7oOIpNlRRKsDjOb7+4D6jqOdNC5ZadcPbdcPS/I7XPLd7odKiIieUtJUERE8lY+JMF76jqANNK5ZadcPbdcPS/I7XPLaznfJigiIpJKPlSCIiIiSSkJiohI3sroJGhmw81suZl9YGbXRrYfa2YLzWyJmT1oZntNBG5mR5vZFjN7KzzGK2Y2onbPIDkz62hmM81sqZm9a2aXR/b1MbO5ZvaOmT1jZi2TfL7AzLaH57bMzN40szG1ehIxmNn9ZrbBzJaU2V5oZv80s0VmNt/MBib57NFm9mztRRtfOdflq+E5LTKztWb2VJLPJq7LxPteruC7JpjZVek4jzLfU941OTkS7wozW5Tk84lrclHk0aic7xtjZnek63ySfF+qazHuz5ub2W8j21qb2a7aPAdJE3fPyAfBMksfAl2ARsBioDtB4l4FHBa+7zfAhUk+fzTwbOR1IbACOC4Dzq0d0C983gL4F9A9fD0PGBo+vwC4IcnnC4AlkdddgEXA+XV9bmXi/A7QLxpruH068N3w+feAWRX9/8uUR6rrMsn7/g78R3XPC5gAXFUL55Xymizzvj8A1yXZXuqajPF9Y4A7avH/W6prMe7P20fAW5Ftl4Y/c7HPAWhQW+erR/xHJleCA4EP3P0jd98JPAacChwA7HT3f4Xvewk4vaKDufsigoT5UwAza2NmfzezeeFjSLi9uZk9EP5l+LaZVXjsynL3T919Yfh8K7AMaB/uPgx4JXwe99w+Aq4EfhaeQ7PwL983w2rx1HB7fTO7Jayg3zazy2r2zPaK6xXg82S7gMRf3K2AteUdx8wGhn+tv2Vmc8ysa7h9jJk9aWYvmNn7ZnZTjZ5Acqmuy2i8LYFjgb0qwVRSXY+hRLXyvpldVBMnUVYF12QiRgPOBB6Ne9xU12Koo5nNCs9rfA2cRkrlXItxf962AcvMLDFgfhTweGKnmZ1sZm+E5/iymR0Ubp9gZg+Z2evAQzVxLlKz6mQ9wZjaE1R8CauBQQRTFzUwswHuPh8YCXSMecyFwNXh89uAW939NTPrRLDI77eB/wK2uHsvADPbr9pnUg4zKwD6Am+Em94l+KX6FHAGlTu3buHzXwP/5+4XmNm+wJvhbbf/IPirttCDxY33r4lzqIIrgBfN7BaCyv7ICt7/HnBUGPMw4Hd888uqkOC/3w5guZn92d1XpThOTUh1XUZ9H5jh7l+mOMZRkVuKU9z9v0l9PQL0Bo4AmgFvmdlz7l7uHw7VkeSaLIkbWO/u76f46CGR83rd3X9C6msRgj8oehIkmHnhec2vwVOJozI/b48BZ5nZemAPwR9v3wr3vQYc4e5uZj8C/hP4RbivO/Dv7r49DfFLNWVyEkwqvMjOAm41s30Ibq3tiflxizwfBnQP/rgFoKWZNQ+3nxX5vi+qH3WKYILv+ztwReQX5gXA7Wb2X8DTwM64h4s8PwE4JdKW1BjoRHBud7n7bgB3T/aXcW24FPi5u//dzM4E7gtjS6UV8KCZHUpQRTaM7Jvh7lsAzGwpcDClk1RdOBu4t5z9r7p72fbpVNcjwLTwF+h2M5tJkDxiV5mVkeKaTDib8qvAD929sMy2VNciwEvu/ln4vU8C/w7UdhKszM/bC8ANwHpgcpl9HYDJZtaO4Db5x5F9TysBZq5MToJrKP1XWYdwG+4+l+CvUszsBIJbGnH0JbjNA0EFcoS7fx19Q+SXUFqZWUOCXzYPu/uTie3u/h7BLw7M7DDgpJiHjJ6bAae7+/Iy31ndsGvKeUCi48UUyk8YEPzimenup4VVyqzIvh2R53tI/zWd8rqEoMMEQZI6rZLHLe96LDuYNy2De1Ndk+G+BsAPgP6VPSzJr8VB1NJ5lacyP2/uvtPMFhBUeN2BUyK7/wz80d2fNrOjCdpyE76q4bClBmVym+A84FAz62xBL7OzCP5Sw8wODP/dB7gGuKuig5lZb4JbnXeGm6YDl0X2J/6CfQn4SWR7jd8ODdtW7gOWufsfy+xLnFs9YBzxzq0AuIXgBxGCW2mXhd+DmfUNt78EXBz+QqMOb4euBYaGz48FUt1eS2jFN4lmTJpiiivldRkaSdDx5eukn04t1fUIcKqZNTazAwg61syrUuTlKO+aDA0D3nP31ZU8dKprEeB4M9vfzJoQ3EJ+vQqhV0sVft7+AFyT5C5K9Bo9r0aDlLTK2CQY3rL7KcEP0TLgcXd/N9x9tZktA94GnnH3/0txmKPChurlBMnvZ+4+I9z3M2CABR1ElgKXhNt/C+xnQeeRxcAxNX92DAHOBY61b7qTfy/cd7aZ/YugHWwt8ECKYxwSntsyggb629098d4bCG4Zvm1m74avIai4Pgm3LwbOqfEzizCzR4G5QFczW21mF4a7LgL+EMbwO2Bsko834Jsq7ybgf8zsLer47kUF1yUESTF2x5GIVNcjBNf5TOCfBL0X09EeWN41CVU/r1TXIsCbBJXn28Df09keWM61GPfnDQB3f9fdH0yyawIwJawUs3HJpbyladMkI1kwTq29u/9nXcciIrkrk9sEJU+Z2X0EvQbPrOtYRCS3qRIUEZG8lbFtgiIiIummJCgiInlLSVBERPKWkqBkNDPbE3bXf9fMFpvZL8IxXeV9psDM0jr8o7LMbE41PjvGzL5V8TtLfabAyqyYICJ7UxKUTLfd3QvdvQdwPPBdoKLJlgtI8xjIynL3iuZHLc8YvpmjUkRqkJKgZA1330AwsP6nFiiwYA2/heEjkWhuJJyk2sx+bsHqGTdbsDrD22Z2cdljm9mNZhadKWiCmV1lwaoiM8Ljv2ORVRDM7D/C4y02s4fCbQeZ2dRw2+JETGZWFP57tAUrJzxhZu+Z2cOR2VSuC2NcYmb3hOc4EhgAPByeTxMz629ms81sgZm9aMF8lYTbF4eTEJSci4iUo67XctJDj/IeQFGSbZuBg4CmQONw26HA/PD50ZReS3IsMC58vg/BJM2dyxyzLzA78nopwRyhDYCW4bbWwAcE82H2IFhzr3W4b//w38kEk09DsPZgq+h5hLFtIZhztB7BLCb/Hj1G+Pwh4OTw+SxgQPi8ITAHaBO+HgXcHz5/G/hO+PxmKrG+nx565OtDg+UlmzUE7gjn2dxD6onUTwB6h1UVBPM8Hkpkpn93f8vMDgzb3toAX7j7Kgsmlf6dmX0HKCZYSukggjlPp7j7pvDzibkkjyVYsgp330OQ8Mp608M5OC1YeqiAYCmeY8zsPwmS+/4Ey/w8U+azXQkmEngpLCDrA59asEzRvh6smwdBEv1uiv8eIhJSEpSsYmZdCBLeBoK2wfVAH4KqKtWk1QZc5u4vVnD4KQQTYLflm6VyRhMkxf7uvsvMVhAsB1Qde618YWaNgb8QVHyrzGxCiu8x4F13H1xqY5AERaSS1CYoWcPM2hDM8n+HuztBRfepuxcTTP5cP3zrVqBF5KMvApeGVR1mdpiZNUvyFZMJJooeSZAQCb9jQ5gAjyFYrxDg/4AzLFjZIboixwyC9RIJ2yJbxTy9RMLbZMGafiMj+6LnsxxoY2aDw+9oaGY93H0zsNnM/j183+iY3yuS15QEJdM1SQyRAF4mWHLo+nDfX4Dzwo4g3fhm3ba3gT1hJ5GfE6yesRRYGA4buJskd0E8WA2iBbDG3T8NNz9MsLrDOwS3Od+LvPe/gdnh9yeWH7qc4LbmO8ACgnXnKhQmsYnAEoKkHV0uaRJwV3jrtD5Bgvx9+L2LgESHoPOBO8P3ZczikSKZTHOHiohI3lIlKCIieUtJUERE8paSoIiI5C0lQRERyVtKgiIikreUBEVEJG8pCYqISN76f2k9C3SBnjJEAAAAAElFTkSuQmCC\n", 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\n", 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" ] @@ -9384,7 +9384,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **55-59** population by **ethnicity 6 groups**" + "### COVID vaccinations among **55-59** population by **ethnicity 6 groups**" ], "text/plain": [ "" @@ -9395,7 +9395,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9408,7 +9408,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **55-59** population by **imd categories**" + "### COVID vaccinations among **55-59** population by **imd categories**" ], "text/plain": [ "" @@ -9419,7 +9419,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9432,7 +9432,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **55-59** population by **bmi**" + "### COVID vaccinations among **55-59** population by **bmi**" ], "text/plain": [ "" @@ -9443,7 +9443,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9456,7 +9456,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **55-59** population by **chronic cardiac disease**" + "### COVID vaccinations among **55-59** population by **chronic cardiac disease**" ], "text/plain": [ "" @@ -9467,7 +9467,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9480,7 +9480,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **55-59** population by **current copd**" + "### COVID vaccinations among **55-59** population by **current copd**" ], "text/plain": [ "" @@ -9491,7 +9491,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9504,7 +9504,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **55-59** population by **psychosis schiz bipolar**" + "### COVID vaccinations among **55-59** population by **psychosis schiz bipolar**" ], "text/plain": [ "" @@ -9515,7 +9515,7 @@ }, { "data": { - "image/png": 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nnkn37t3p0aMHJ5xwArfccgutWrVKeoxUZStt1KhRXHLJJQk77pQ2fvx4zj77bHr37k3z5t/OjXraaacxderUPR137rzzTubNm0f37t3p0qUL9957b5n+DUREorAotxrNbIG79yq17F1375mxyOIUFhb6vHnzquJUIlIWDw8Ofl7w99TbSVaY2Xx3L8x2HLks3T3J4cCPgQ5m9nzcqiYEz0pWiS+++IJHHnlkr2Vdu3alT58+SZsbCwoKKCgoYNu2bTz11FP7rC8sLKRbt25s2rSJqVOn7rO+X79+dOrUic8//5wXX3xxn/XHHnssRxxxBOvWrWPatGn7rD/xxBNp164dn332GTNnztxn/amnnkqrVq34+OOPmTNnzj7rhwwZQvPmzVmxYgVvvvnmPuvPPPNMmjZtypIlS0j0BeKcc86hcePGLFy4MGFT5IgRI6hfvz5z585l6dKl+6wfNWoUAG+88cY+Tb716tXjJz8JxpKYPXs2n3zyyV7rGzVqtKczzowZM1i1atVe6/Py8jjrrLMAmDZtGuvWrdtr/cEHH8xpp50GwAsvvMAXX3yx1/pWrVpx6qmnAvDMM8+wefPmvda3bduWQYMGATBp0qR9aq8dOnTY0zT8t7/9bZ97rB07dqR///4A+1x3oGtvr2vvX+H/rT2yZ72uvep77UnZpevdGnsmsjl734PcAizKVFAiIrXdswtXA/CjgjZZjqR2i9Tcmm1qbhWpptTcWun+39v/4bmFq3n7ky85qkMzJl3cL/1OSai5teKijrhztJnNNbOtZrbTzIrNbHP6PUVEpCyeW7iaZWs3c1SHZpyhWmTWRR1M4C7gPGAyUAj8FOgYZUczqwvMA1a7+xAz6wA8CRwMzAfOd/edZQ1cRKSmiNUeAZat3UyX1nkVqkFK5YmaJHH3D82srrsXAw+b2bvANRF2vRx4H8gLP/8JmODuT5rZvcCFwP+WMW4RkZwWnxjf/iToB3lUh2Z0aZ2nGmQ1EjVJbjOzBsBCM7uFoDNP2qZaM2sLDAb+CFxhZgacQNBjFoKZRMajJCkitUysWbVL67w9Tas/PuqwbIclpURNkucDdYFfAb8G2gFDI+x3O/AbgkdGIGhi3ejusX7Pq4CEX5nMbDQwGuCww3ThiEjuU7Nq7omUJN390/DtduDGKPuY2RBgg7vPN7PjyhqYu98H3AdB79ay7i8iUl3E91gFNavmknSDCSwGkiYod++eYvdjgNPN7IdAQ4J7kncAB5pZvbA22RZYXeaoRUSquWT3HNWsmlvS1SSHlPfA7n4NYceesCZ5lbuPMLPJwDCCHq4jgefKew4RkepK9xxrhpRJMq6ZtTKNA540sz8A7wIPZuAcIiJVTvcca55I9yTNbAvfNrs2AOoDX7t7XvK9vuXus4BZ4fuPgeRzMImI5Kj42qPuOdYMUTvuxHqnEj7GcQZwdKaCEhHJFao91myRBxOI8WCw12fN7Abg6soPSUSk+lOP1dohanPrWXEf6xAMTfdNRiISEamm1GO19olakzwt7v1uYCVBk6uISI2WLDEqOdYOUe9JXpDpQEREqiM9ylG7RW1u7QBcBrSP38fdT89MWCIi1Yc649ReUZtbnyV4nvEFoCRz4YiIVA+xZtZYLVJqp6hJ8ht3vzOjkYiIZFmqjjlSO0VNkneEj3xMB3bEFrr7goxEJSKSBbr/KKVFTZL5BNNlncC3za0efhYRyVkaDEBSiZokzwaOcPedmQxGRKSqaSg5SSVqklwCHAhsyGAsIiJVQrVHiSpqkjwQWG5mc9n7nqQeARGRnKGh5KSsoibJGzIahYhIFYg1rapTjkQVdcSd2ZkOREQkE9S0KhVRJfNJiohUpWTPO6ppVcpK80mKSI2j5x2lsmg+SRHJafG1xhg1q0pl0XySIpLTEo2vqmZVqSyaT1JEcp5qjZIpmk9SRHJOoh6rIpkQtbn1UeByd98Yfj4I+LO7/yyTwYmIxKjHqmRD1ObW7rEECeDuX5lZzwzFJCKyD/VYlWyImiTrmNlB7v4VgJk1K8O+IiJloh6rUl1ETXR/Bt40s8nh57OBP2YmJBGp7dRjVaqLqB13HjOzeXw7f+RZ7r4sc2GJSG2j4eOkOkqZJM3sAHffChAmxX0SY/w2IiLlpXkdpTpKV5N8zswWAs8B8939awAzOwI4HjgHuB+YktEoRaRGUu1Rqrs6qVa6+4nATOBiYKmZbTazL4C/Aa2Ake6uBCki5RKrPYLuOUr1lPaepLu/BLxU1gObWUNgDrBfeJ4p7n6DmXUAngQOBuYD57v7zrIeX0Ryi3qsSi5KWZOsoB3ACe7eAygATjWzo4E/ARPc/bvAV8CFGYxBRKqJ+FpjjGqPUt1l7FnHcLaQWIee+uHLCXrI/jhc/igwHvjfTMUhItmje46S6zJZk8TM6oYdfzYArwAfARvdfXe4ySog4ddIMxttZvPMbF5RUVEmwxSRDNE9R8l16R4BaZZqvbt/mWZ9MVBgZgcCU4HOUQNz9/uA+wAKCws96n4ikl2qPUpNkq65dT5BE6kBhxHcQzTgQOA/QIcoJ3H3jWb2KtAPONDM6oW1ybbA6tR7i0h1p8HHpaZKmSTdvQOAmd0PTA17umJmPwB+lGpfM2sB7AoTZCPgJIJOO68Cwwh6uI4keAZTRHLQ+i3f8PnWHfx2xWIgSIwafFxqkqgdd45294tiH9z9H2Z2S5p9WgOPmlldgnufT7n7i2a2DHjSzP4AvAs8WJ7ARST7Pt+6g207i5UYpcaKmiTXmNm1BIMIAIwA1qTawd0XAftMp+XuHwN9yxKkiFQf8U2rV+0spnGDurrnKDVW1N6tw4EWBJ1vngnfD89UUCJSfcX3WG3coC7ND9gvyxGJZE7UWUC+BC43s/1j47eKSO2RtMfqw02zHJlIZkVKkmbWH3gAOAA4zMx6ABe7+y8yGZyIVL1Ew8epx6rUVlHvSU4ATgGeB3D398zs2IxFJSJZk2jCY3XMkdoq8rB07v6ZmcUvKq78cEQkGzQAgEhiUTvufBY2ubqZ1Tezq4D3MxiXiFQhDR8nkljUmuQlwB0E46yuBqYDuh8pksNUexRJL2pNspO7j3D3Q9y9pbv/BPheJgMTkcxS7VEkvag1yb8CvSIsE5FqSBMei5RPullA+gH9gRZmdkXcqjygbiYDE5GKSTboeIxqjyLppatJNiB4NrIe0CRu+WaCQcpFpJqKf5RDj3CIlE+6WUBmA7PN7BF3/7SKYhKRclJnHJHKFfWe5DYzuxXoCjSMLXT3EzISlUhtMu9hWDylUg7VY+0mjgwHHacBNN+xHzzcMP2O5bVuMbTKz9zxRbIsapKcCEwChhA8DjISKMpUUCK1yuIpFU42sXkdt4UJsmvrKhpTtVU+5OvOi9RcUZPkwe7+oJldHtcEOzeTgYnUKq3y4YK/l2mXvTrmrPm2Y84ZBW3oqnuPIpUiapLcFf5ca2aDCeaSbJZiexHJgGQ9VtUxRyQzoibJP5hZU+BKgucj84BfZywqEdlDiVEke6LOJ/li+HYTcHzmwhGR0vQoh0j2RJ1PsgVwEdA+fh93/1lmwhKRWA1Sj3KIZE/U5tbngNeAGWiKLJGMSda0qpFxRLIjapJs7O7jMhqJSC0Ve3zj9//3pu45ilQzUZPki2b2Q3d/KaPRiNRCsecbASVGkWomapK8HPitme0geBzEAHf3vIxFJlKDxTerXhUOAKB7jiLVT9TerU3SbyUi6cSSY3yzauMGdWl+wH5ZjkxEEkk3VVZnd19uZgnnjXT3BZkJS6TmSNUZ58dHHQYPV9EQciJSZulqklcAo4E/J1jngAY4F0lAAwCI1AzppsoaHf7UAAIiZaABAERqhqiDCfwSmOjuG8PPBwHD3f2eTAYnkks0l6NIzVMn4nYXxRIkgLt/RTACj4iEYrVHgC6t8zQAgEgNEPURkLpmZu7uAGZWF2iQagczawc8BhxCcP/yPne/w8yaEcxN2R5YCZwTJl2RnKTh40Rqrqg1yWnAJDM70cxOBJ4Il6WyG7jS3bsARwO/NLMuwNXATHc/EpgZfhbJWfEJUrVHkZolak1yHEEv10vDz68AD6Tawd3XAmvD91vM7H2gDXAGcFy42aPArPD4IjlD9x9FaoeoSbIRcL+73wt7mlv3A7ZF2dnM2gM9gbeBQ8IECrCOoDk20T6jCRIzhx2mXoGSfcke61ANUqTmipokZwKDgK3h50bAdKB/uh3N7ADgaWCMu282sz3r3N3NzBPt5+73AfcBFBYWJtxGJNP0vKNI7RY1STZ091iCxN23mlnjdDuZWX2CBDnR3Z8JF683s9buvtbMWgMbyhy1SBXR844itVvUJPm1mfWKDUNnZr2B7al2sKDK+CDwvrv/JW7V88BI4Obw53Nljlokw9RjVUQgepIcA0w2szUEM4C0As5Ns88xwPnAYjNbGC77LUFyfMrMLgQ+Bc4pc9QiGaAJj0WktKizgMw1s85Ap3DRCnfflWaffxEk1EROjB6iSObonqOIpBK1JglBguwCNAR6mRnu/lhmwhLJHCVGEYkq6titNxA829gFeAn4AfAvghF1RHJCorkclRhFJJWoNclhQA/gXXe/wMwOAf6WubBEKkfauRxFRFKImiS3u3uJme02szyCxzbaZTAukUqhRzhEpCKiJsl5ZnYgcD8wn2BQgTczFpVIBWjIOBGpLFF7t/4ifHuvmU0D8tx9UebCEikbDRknIpkQtePO88CTwHPuvjKjEYmUgTrjiEgmRW1u/TPB4AH/Y2ZzCRLmi+7+TcYiE4kgds9RiVFEMiFqc+tsYHY4+8cJwEXAQ0BeBmMTSUj3HEWkqkSddBkzawQMBS4B+hDMBSlS5WK1R0D3HEUko6Lek3wK6AtMA+4CZrt7SSYDE4mn2qOIZEPUe5IPAsPdvTiTwYjEU49VEcm2qPckX850ICKlaSAAEcm2sgxwLlIlNJejiFQXkTvuiFSV+ASpZlURyaaoHXdmuvuJ6ZaJlJc65ohIdZQySZpZQ6Ax0NzMDuLbSZTzAH3FlzKLT4bx1DFHRKqjdDXJi4ExwKEEA5vHkuRmgkdBRCJJNHxcPHXMEZHqKGWSdPc7gDvM7DJ3/2sVxSQ1kIaPE5FcFPURkL+aWX+gffw+7v5YhuKSGkD3GUUk10XtuPM48B1gIRAbUMABJUnZiwYAEJGaJOpzkoVAF3f3TAYjuU8DAIhITRI1SS4BWgFrMxiL5JhEPVXVrCoiNUnUJNkcWGZm7wA7Ygvd/fSMRCU5Ib7WGKNmVRGpSaImyfGZDEJyl2qNIlKTRZ502cwOB4509xlm1hiom9nQpDpK1GNVRKSmitq79SJgNNCMoJdrG+BeQMPS1QLqsSoitVXU5tZfEky6/DaAu39gZi0zFpVUC4lGyVGPVRGpTaImyR3uvtMsGJXOzOoRPCeZlJk9BAwBNrh7t3BZM2ASwaAEK4Fz3P2rckUuGZGs1qjEKCK1UdQkOdvMfgs0MrOTgF8AL6TZ5xGC8V3jBxy4Gpjp7jeb2dXh53FlC1kqW7LEqOQoIrVd1CR5NXAhsJhg0POXgAdS7eDuc8ysfanFZwDHhe8fBWahJJkVSowiIulFTZKNgIfc/X4AM6sbLttWxvMd4u6xAQnWAYeUcX+pIN1nFBGJLmqSnAkMAraGnxsB04H+5T2xu7uZJb2vaWajCXrUcthh+uNdEbrPKCJSPlGTZEN3jyVI3H1r+KxkWa03s9buvtbMWgMbkm3o7vcB9wEUFhZqzNgK0HiqIiLlEzVJfm1mvdx9AYCZ9Qa2l+N8zwMjgZvDn8+V4xgSgaapEhGpuKhJ8nJgspmtAYxgsPNzU+1gZk8QdNJpbmargBsIkuNTZnYh8ClwTjnjljTia4966F9EpHzSJkkzqwM0ADoDncLFK9x9V6r93H14klUapSdDVHsUEalcddJt4O4lwN3uvsvdl4SvlAlSsiNWewTNxiEiUhki9241s6HAM5p4ufqJ1SBVexQRqVxRk+TFwBVAsZltJ7gv6e6uKSCyJNVjHSIiUjmiTpXVJNOBSNnosQ4RkcyLOlWWASOADu5+k5m1A1q7+zsZjU72oo45IiJVK2pz6z1ACXACcBPByDt3A9vgEM0AAA3xSURBVH0yFJeENJejiEj2RE2SR7l7LzN7F8DdvzKzBhmMS0JqVhURyZ6oSXJXOKi5A5hZC4KapWSIeqyKiGRf1CR5JzAVaGlmfwSGAddmLKpaSj1WRUSql6i9Wyea2XyC0XIM+JG7v5/RyGoJzesoIlJ9pUySZtYQuAT4LsGEy//n7rurIrCaTIlRRCQ3pKtJPgrsAl4DfgB8DxiT6aBqOnXGERHJDemSZBd3zwcwswcBPRdZAeqMIyKSW9IlyT0Dmbv77mBMASkLdcYREcld6ZJkDzPbHL43oFH4WWO3pqB7jiIiNUPKJOnudasqkFynxCgiUvNEfU5S0lBnHBGRmkdJsoLUGUdEpOaqk+0Acl18glRnHBGRmkU1yXLQlFUiIrWDkmREmrJKRKT2UZKMSB1zRERqHyXJFNSsKiJSuylJJhBLjmpWFRGp3ZQkE4g1rapZVUSkdlOSDKlpVURESqvVSVI9VkVEJJVamSQT3XNU06qIiJRWa5JkqimrlBhFRCSRrCRJMzsVuAOoCzzg7jdn+px6zlFERMqqypOkmdUF7gZOAlYBc83seXdfVtnnuvGFpSxbE0yHqc44IiJSVtmoSfYFPnT3jwHM7EngDKDSk+Qpn93OsI3vBx8aQPMd+8HDDSv7NCIVs24xtMrPdhQikkA2kmQb4LO4z6uAo0pvZGajgdEAhx1WvmbRozscDOualmtfkSrTKh/yh2U7ChFJoNp23HH3+4D7AAoLC71cB/lBxm91iohIDZaN+SRXA+3iPrcNl4mIiFQr2UiSc4EjzayDmTUAzgOez0IcIiIiKVV5c6u77zazXwEvEzwC8pC7L63qOERERNLJyj1Jd38JeCkb5xYREYkqG82tIiIiOUFJUkREJAklSRERkSSUJEVERJIw9/I9p1+VzKwI+LScuzcHPq/EcKoTlS031dSy1dRyQe6W7XB3b5HtIHJZTiTJijCzee5emO04MkFly001tWw1tVxQs8smqam5VUREJAklSRERkSRqQ5K8L9sBZJDKlptqatlqarmgZpdNUqjx9yRFRETKqzbUJEVERMpFSVJERCSJap0kzexUM1thZh+a2dVxy08wswVmtsTMHjWzfQZqN7PjzGyTmb0bHmOOmQ2p2hIkZmbtzOxVM1tmZkvN7PK4dT3M7E0zW2xmL5hZXoL925vZ9rBs75vZO2Y2qkoLEYGZPWRmG8xsSanlBWb2lpktNLN5ZtY3wb7HmdmLVRdtdCmuy9fCMi00szVm9myCfWPXZWy7GWnONd7MrspEOUqdJ9U1OSku3pVmtjDB/rFrcmHcq0GK840ys7syVZ4E50t2LUb9fXMz+0PcsuZmtqsqyyBZ4u7V8kUwjdZHwBFAA+A9oAtBYv8M6Bhu93vgwgT7Hwe8GPe5AFgJnFgNytYa6BW+bwL8G+gSfp4LDAzf/wy4KcH+7YElcZ+PABYCF2S7bKXiPBboFR9ruHw68IPw/Q+BWen+/6rLK9l1mWC7p4GfVrRcwHjgqiooV9JrstR2fwauT7B8r2sywvlGAXdV4f9bsmsx6u/bx8C7ccsuDX/nIpcBqFdV5dWr8l7VuSbZF/jQ3T92953Ak8AZwMHATnf/d7jdK8DQdAdz94UECfVXAGbWwsyeNrO54euYcPkBZvZw+M1ykZmlPXZZuftad18Qvt8CvA+0CVd3BOaE76OW7WPgCuC/wjLsH35zfiesbZ4RLq9rZreFNfBFZnZZ5ZZsn7jmAF8mWgXEvrE3BdakOo6Z9Q2/7b9rZm+YWadw+Sgze8bMppnZB2Z2S6UWILFk12V8vHnACcA+Nclkkl2PoVht5wMzu6gyClFammsyFqMB5wBPRD1usmsx1M7MZoXluqESipFUimsx6u/bNuB9M4sNKHAu8FRspZmdZmZvh2WcYWaHhMvHm9njZvY68HhllEWqVlbmk4yoDUGNMWYVcBTB0FD1zKzQ3ecBw4B2EY+5ABgbvr8DmODu/zKzwwgmgf4ecB2wyd3zAczsoAqXJAUzaw/0BN4OFy0l+KP7LHA2ZStb5/D974B/uvvPzOxA4J2wWe+nBN+KCzyY/LpZZZShHMYAL5vZbQQtA/3TbL8cGBDGPAj4b779Y1ZA8O+3A1hhZn9198+SHKcyJLsu4/0ImOnum5McY0Bck+Vkd/8jya9HgO7A0cD+wLtm9nd3T/nFoiISXJN74gbWu/sHSXb9Tly5Xnf3X5L8WoTgC0c3ggQ0NyzXvEosShRl+X17EjjPzNYDxQRf7g4N1/0LONrd3cx+DvwGuDJc1wX4vrtvz0D8kmHVOUkmFF6E5wETzGw/gqa74oi7W9z7QUCX4MsxAHlmdkC4/Ly4831V8aiTBBOc72lgTNwf1J8Bd5rZdcDzwM6oh4t7fzJwety9rIbAYQRlu9fddwO4e6Jv1lXhUuDX7v60mZ0DPBjGlkxT4FEzO5KgFlo/bt1Md98EYGbLgMPZO4llw3DggRTrX3P30vfHk12PAM+Ff2C3m9mrBMklci21LJJckzHDSV2L/MjdC0otS3YtArzi7l+E530G+D5Q1UmyLL9v04CbgPXApFLr2gKTzKw1QTP8J3HrnleCzF3VOUmuZu9vdW3DZbj7mwTfajGzkwmaTKLoSdCMBEEN5mh3/yZ+g7g/UhllZvUJ/hhNdPdnYsvdfTnBHxbMrCMwOOIh48tmwFB3X1HqnBUNu7KMBGIdQyaTOqFA8IfpVXc/M6zlzIpbtyPufTGZv6aTXpcQdOggSGJnlvG4qa7H0g8zZ+Th5mTXZLiuHnAW0LushyXxtXgUVVSuVMry++buO81sPkENsQtwetzqvwJ/cffnzew4gnvJMV9XcthSharzPcm5wJFm1sGCXnLnEXzTw8xahj/3A8YB96Y7mJl1J2hKvTtcNB24LG597BvwK8Av45ZXenNreG/nQeB9d/9LqXWxstUBriVa2doDtxH8okLQVHdZeB7MrGe4/BXg4vAPHllsbl0DDAzfnwAka76Lacq3iWhUhmKKKul1GRpG0DHnm4R7J5fsegQ4w8wamtnBBB1/5pYr8hRSXZOhQcByd19VxkMnuxYBTjKzZmbWiKCJ+vVyhF4h5fh9+zMwLkErTPw1OrJSg5SsqrZJMmwS/BXBL9n7wFPuvjRcPdbM3gcWAS+4+z+THGZAeCN9BUFy/C93nxmu+y+g0IIOLMuAS8LlfwAOsqBzy3vA8ZVfOo4BzgdOsG+7y/8wXDfczP5NcB9uDfBwkmN8Jyzb+wQdCO5099i2NxE0SS4ys6XhZwhqbP8Jl78H/LjSSxbHzJ4A3gQ6mdkqM7swXHUR8Ocwhv8GRifYvR7f1hJvAf7HzN4ly60faa5LCJJm5I4tcZJdjxBc568CbxH0vszE/chU1ySUv1zJrkWAdwhqrouApzN5PzLFtRj19w0Ad1/q7o8mWDUemBzWNHNxSi1JQsPSSbVkwXN6bdz9N9mORURqr+p8T1JqKTN7kKDX4znZjkVEajfVJEVERJKotvckRUREsk1JUkREJAklSRERkSSUJKVaM7Pi8HGEpWb2npldGT7Tlmqf9maW0cdbysrM3qjAvqPM7ND0W+61T3srNeOFiJSdkqRUd9vdvcDduwInAT8A0g2G3Z4MPwNaVu6ebnzaVEbx7RihIlKFlCQlZ7j7BoKBB35lgfYWzOG4IHzFEtHNhIOIm9mvLZj95FYLZtdYZGYXlz62md1sZvEjLY03s6ssmBVmZnj8xRY3i4WZ/TQ83ntm9ni47BAzmxouey8Wk5ltDX8eZ8HMF1PMbLmZTYwbjeb6MMYlZnZfWMZhQCEwMSxPIzPrbWazzWy+mb1swXihhMvfCwdp2FMWEamAbM/VpZdeqV7A1gTLNgKHAI2BhuGyI4F54fvj2Hsu0dHAteH7/QgG0e5Q6pg9gdlxn5cRjNFaD8gLlzUHPiQYj7QrwZyLzcN1zcKfkwgGB4dg7smm8eUIY9tEMOZrHYJRYL4ff4zw/ePAaeH7WUBh+L4+8AbQIvx8LvBQ+H4RcGz4/lbKML+jXnrplfilwQQkl9UH7grHOS0m+UD3JwPdw1oZBONsHkncTA3u/q6ZtQzv/bUAvnL3zywY9Pu/zexYoIRgqqxDCMacnezun4f7x8byPIFgSjLcvZggIZb2jodjoFowtVR7gqmWjjez3xAk/2YE0zi9UGrfTgQDLbwSVkDrAmstmIbqQA/mTYQgyf4gyb+HiESkJCk5xcyOIEiIGwjuTa4HehDUypINKm7AZe7+cprDTyYYoLwV306FNIIgafZ2911mtpJguqeK2GfmEjNrCNxDUGP8zMzGJzmPAUvdvd9eC4MkKSKVTPckJWeYWQuCWRrucncnqBGudfcSgsG564abbgGaxO36MnBpWCvEzDqa2f4JTjGJYCDvYQQJk/AcG8IEeTzBfJUA/wTOtmBmjvgZVWYSzJdJeC+0acTixRLi5xbM6Tgsbl18eVYALcysX3iO+mbW1d03AhvN7PvhdiMinldEUlCSlOquUewREGAGwZRSN4br7gFGhh1VOvPtvH2LgOKwE8uvCWY/WQYsCB+L+D8StKJ4MJtHE2C1u68NF08kmJ1jMUEz6vK4bf8IzA7PH5te6nKCZtPFwHyCeQfTCpPc/cASgqQePx3WI8C9YdNsXYIE+qfwvAuBWIelC4C7w+2qzeShIrlMY7eKiIgkoZqkiIhIEkqSIiIiSShJioiIJKEkKSIikoSSpIiISBJKkiIiIkkoSYqIiCTx/wHK6Jp0kuncNAAAAABJRU5ErkJggg==\n", + "image/png": 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+uEmTJj59+vQDJk6c+FWrVq1KV65c2aRp06a+a9cua9euXfFPf/rTr/bdd9+SO++8s031Z/+OkqSISB1pSkfqNWvWzAcNGrR5n332KWncuDE//OEPNy9durRZ//79jwDYa6+9Su+7776Vy5cv3+OSSy7plJeXR+PGjf3mm2/+pCbXUZIUEakjTelIvZKSEt58883mDz300Edl2y6//PINl19++YbY1/Xo0WPH6NGjl9X2OkqSIiK1pCkd6bFo0aJmo0aNOuykk076Oj8/f0cyr6UkKSJSA7H9jhXv2CGp0a9fv29Xr179biqupSQpIlIDsTXHHG1eLS0tLbW8vLzk3GcxDUpLSw0ojbdPSVJEJAI1rZZbUlRU1L1t27abGkKiLC0ttaKiolbAknj7lSRFRBJQ02plxcXF561fv/6O9evX9wTy0h1PPSgFlhQXF58Xb6eSpIhIBfGmdORo02ol/fr12wCcku44UkVJUkSkAk3pkDJKkiIiIfU7SkVKkiKS09TvKFVRkhSRnKR+R4lCSVJEcpL6HSUKJUkRyVnqd5TqKEmKSE6pODhHpCoNYSKoiEhksQlSg3OkOqpJikiDFTtytYymd0hNKEmKSIOSaEpHGdUgpSaUJEWkQdCUDkkGJUkRyWrxkqMSo9QXJUkRyTpVrZKj5Cj1SUlSRLKObnwsqaIkKSIZr+IoVY1QlVTRPEkRyXhlNccyGqEqqaKapIhkBdUcJR2UJEUkI8U2sWoJOUkXNbeKSEaKbWJV86qkS7U1STPrBJwODAYOALYDS4CngWfdvTSpEYpITqm4ALmaWCWdqkySZvYXoCPwFPAHYAPQDDgcGA5camYXu/v8ZAcqIg1XVfMeRdKpuprkH919SZztS4BHzawpoMlJIlInmvcomarKJBmbIM1sT+BAd18Rs38n8GHywhORhkxNq5LpIo1uNbNTgGuBpkBXMysAfuvup1RxTDNgPrBHeJ2H3f0KM+sKPADsBywCzgqTrYjkiETrrYpkmqhTQK4ABgDzANx9cZjsqrIDOM7dt5pZE+AVM3sWuAiY4e4PmNktwI+B/6tV9CKSlcpqj2palUwXNUnucvdNZha7zas6wN0d2Bo+bRL+OHAccGa4/W5gOkqSIjlHzauSDaImyaVmdibQyMwOA34BvFbdQWbWiKBJ9VDgJuAjYKO7F4cvWU0wejbesROBiQAHHqhvmSLZTosDSDaKupjAhUAPgibUvwGbgMnVHeTuJe5eAHQiaK49Impg7n6buxe6e2Hbtm2jHiYiGUqLA0g2ilqTPMLdLwUurc1F3H2jmb0IDAT2MbPGYW2yE7Cm6qNFpKFQE6tkm6g1yT+a2XtmdpWZ9YxygJm1NbN9wsd7AscD7wEvAmPCl50NPFHDmEUki/ztjU8Zd+vru93FQyRbRKpJuvuxZtYeOA241cxaArPd/XdVHNYBuDvsl8wDHnT3p8xsGfCAmf0OeAu4s25vQUQykaZ5SENgwSDUGhxglg/8Ghjn7k2TElUFhYWFvnDhwlRcSkTqSVntsaz/UdM8Us/MFrl7YbrjyGZRFxP4HjAOGA18CcwGfpnEuEQkC8Ubwao+SMlmUQfu3EWQGE9097VJjEdEslC8plWNYJWGIGqfpL4KikhCWkFHGqrqbpX1oLufZmbvsvsKO0awqE6vpEYnIhlLTauSC6qrSf5X+O/IZAciItkl9u4dalqVhqq6W2WtCx/+1N2nxu4zsz8AUysfJSINmW5vJbkk6sCd46mcEE+Ks01EGijNe5RcVF2f5CTgp8DBZvZOzK4WwKvJDExE0i+237FictTgHMkF1dUk/wY8C/wvcHHM9i3u/lXSohKRjBDbrKrkKLmouj7JTQR3/DgDwMzaAc2A5mbW3N0/TX6IIpJq6ncUCURdcedk4E/AAcAG4CCCxcp7JC80EUk19TuK7C7qwJ3fAUcBc929j5kdC/woeWGJSKqo31EksahJcpe7f2lmeWaW5+4vmtn1SY1MRJIqXq1RyVFkd1GT5EYzaw7MB+4zsw3AN8kLS0SSTUvJiVQvapIcBXwL/DcwHmgF/DZZQYlIamhQjkjVoi5wHltrvDtJsYhIksVbb1VEEqtuMYEt7L6wefkuggXO9RcmkgV0KyuR2qlunmSLVAUiIsmj/keR2ok6TzLuX5QWExDJbFoUQKRuog7ceTrmcTOgK7ACLSYgknGqmvcoIjUTdeBOfuxzM+tLsPC5iGQYrbcqUn+i1iR34+5vmtmR9R2MiNSemlZF6l/UPsmLYp7mAX2BtUmJSERqROutiiRP1Jpk7CjXYoI+ykfqPxwRiULrrYqkRtQ+ySuTHYiIVE/rrYqkVtTm1kLgUoJbZJUf4+69khSXiIRUaxRJn6jNrfcBU4B3gdLkhSMiFWm0qkj6RE2SRe7+ZFIjERFg95ojoNGqImkUNUleYWZ3AC8AO8o2uvujSYlKJIfF1hwBrbEqkkZRk+Q5wBFAE75rbnVASVKkHsS7O4dqjiLpFzVJ9nf3bkmNRCSHxdYeVXMUyRxRk+RrZtbd3ZclNRqRHKNVckQyW9QkeRSw2MxWEvRJlt1PUlNARGpIC5CLZI+oSXJ4UqMQyQFaCEAk+0RNkp7UKERygG58LJJ9anI/SSdoZtX9JEVqQP2OItlL95MUqUcVFwIA9TuKZDPdT1KkHlVcCAC0zqpINkva/STNrDNwD7A/QVPtbe5+g5m1BmYDXYBVwGnu/nWNIxfJIGpSFWmYknk/yWLgl2GtswWwyMz+AUwAXnD3q83sYuBiYGrNwhZJP03lEGn4knY/SXdfB6wLH28xs/eAjsAo4JjwZXcD81CSlCyku3OINHxRm1v/AYx1943h832BB9z9xIjHdwH6AG8A+4cJFGA9QXOsSNZQ02qSLfwLvPtwuqPIDO3z4aSr0x1FTova3Nq2LEECuPvXZtYuyoFm1pygaXayu282s/J97u5mFncOpplNBCYCHHigvp1LeqlpNYXefRjWvxskCJE0i5okS8zsQHf/FMDMDiLCAgNm1oQgQd4Xc1utz82sg7uvM7MOwIZ4x7r7bcBtAIWFhVrMQNJKTasp1j4fznk63VGIRE6SlwKvmNlLBAsKDCas5SViQZXxTuA9d/9TzK4ngbOBq8N/n6hp0CLpoKZVkdwTdeDOc+ECAkeFmya7+xfVHHY0cBbwrpktDrf9hiA5PmhmPwY+AU6redgiqVGx/1FEckuVSdLMurj7KoAwKT5VYb8BHd19dcVj3f0VglpnPENrFa1IisRbjFz9jyK5p7qa5LVmlkfQJLoIKCJYu/VQ4FiCZHcFUClJimQzLUYuIlBNknT3sWbWHRgPnAt0ALYB7wHPAL9392+THqVICsSOYNX0DhGBCH2S7r6MYOCOSIMUr2m1e4eWal4VkdotcC7SkKhpVUQSUZKUnKWVc0SkOnnpDkAkXWITpJpWRSSeqGu3vuDuQ6vbJpLpNDhHRGqiunmSzYC9gDbhouZl8x5bEtzRQyQraHCOiNRGdTXJnwCTgQMI5kmWJcnNwI1JjEukXmlwjojURnXzJG8AbjCzC939zymKSSQp1LQqIjUVde3WP5vZIKBL7DHufk+S4hKptdh+xzJae1VEaiPqwJ17gUOAxUBJuNkBJUnJOPEWJFf/o4jURtR5koVAd3fXfR0lY2neo4jUt6hJcgnQHliXxFhEaiy2aVV37BCR+hY1SbYBlpnZv4EdZRvd/ZSkRCUSUWzNUSNXRaS+RU2S05MZhEhNqWlVRFIh6ujWl8zsIOAwd59rZnsBjZIbmkhluhmyiKRS1NGt5wMTgdYEo1w7ArcQ3HRZJKmq6ndU06qIJFPU5tafAQOANwDc/QMza5e0qESIX2tUchSRVIqaJHe4+06zYFU6M2tMME9SpF6p1igimSRqknzJzH4D7GlmxwM/BeYkLyzJNao1ikgmipokLwZ+DLxLsOj5M8AdyQpKco8WIBeRTBQ1Se4J3OXutwOYWaNw27ZkBSa5QVM5RCST5UV83QsESbHMnsDc+g9Hck1sgtRUDhHJNFFrks3cfWvZE3ffGs6VFKmx2ME5qkGKSCaLmiS/MbO+7v4mgJn1A7YnLyxpiOINzlENUkQyWdQk+V/AQ2a2FjCCxc7HJS0qaZA0OEdEsk21SdLM8oCmwBFAt3DzCnfflczApOHQ4BwRyVbVJkl3LzWzm9y9D8Ets0RqRINzRCRbRW1ufcHMRgOP6sbLUhuqQYpINoqaJH8CXASUmNl2gn5Jd/eWSYtMslq8EawiItkm6q2yWiQ7EGkYNIJVRBqSqLfKMmA80NXdrzKzzkAHd/93UqOTrKMRrCLSkERtbr0ZKAWOA64CtgI3Af2TFJdkES0OICINVdQkeaS79zWztwDc/Wsza5rEuCQLqGlVRBq6qElyV7iouQOYWVuCmqXkMDWtikhDFzVJzgQeA9qZ2e+BMcBlSYtKMpoWBxCRXBF1dOt9ZrYIGEow/eMH7v5eUiOTjKXFAUQkV1SZJM2sGXABcCjBDZdvdffiVAQmmUWDc0QkF1VXk7wb2AW8DJwEfA+YHOXEZnYXMBLY4O49w22tgdlAF2AVcJq7f12bwCU1NDhHRHJZdUmyu7vnA5jZnUBN5kXOAm4E7onZdjHwgrtfbWYXh8+n1uCckmIanCMiuay6JFl+pw93Lw7WFIjG3eebWZcKm0cBx4SP7wbmoSSZkTQ4R0Sk+iTZ28w2h48N2DN8Xtu1W/d393Xh4/XA/oleaGYTgYkABx6o2ksqxPY7xjavqmlVRHJVlUnS3Rsl68Lu7maW8I4i7n4bcBtAYWGh7jySRPH6HdW8KiISfZ5kffnczDq4+zoz6wBsSPH1JVRVrVGJUUQkkOok+SRwNnB1+O8TKb5+zlOtUUQkuqQlSTO7n2CQThszWw1cQZAcHzSzHwOfAKcl6/qyu3jJUYlRRKRqSUuS7n5Ggl1Dk3VN2Z2aVEVE6ibVza2SQrFTOJQcRURqTkmyAdIcRxGR+pGX7gCk/mkBchGR+qGaZAOhBchFROqfapINRFntEVANUkSknqgmmeXU/ygikjxKklkq0bxHERGpP0qSWUq3sBIRST4lySwQOyinjJpXRUSSTwN3skDsoJwyGpwjIpJ8qklmMA3KERFJLyXJDKMbH4uIZA4lyQyhW1iJiGQeJckModGqIiKZR0kyjbSUnIhIZtPo1jTSUnIiIplNNck00KhVEZHsoCSZQlpKTkQkuyhJJllVUzo0OEdEJLMpSSaJpnSIiGQ/Jcl6lqhJVYlRRCT7KEnWM813FBFpOJQk64HmO4qINEyaJ1kPNN9RRKRhUk2ynqj2KCLS8ChJ1kHFRQFERKRhUZKsId3KSkQkdyhJRqR5jyIiuUdJMiJN7RARyT1KktXQYuQiIrlLU0CqEZsg1e8oIpJbVJOMQ4sDiIgIKEnuJt7gHNUgRURyl5IkWpRcRETiU5JEI1dFRCS+nE2S6ncUEZHq5OzoVi1KLiIi1cm5mqTmPYqISFRpSZJmNhy4AWgE3OHuVyfjOlfOWcqytZt326b1VkVEJKqUJ0kzawTcBBwPrAYWmNmT7r4sFdfX4BwREYkqHTXJAcCH7v4xgJk9AIwC6j1JXtH4Xmj6buUdy5JxNRGpF+vfhfb56Y5CBEjPwJ2OwGcxz1eH23ZjZhPNbKGZLSwqKkpZcCKSZu3zIX9MuqMQATJ44I673wbcBlBYWOi1OslJSenqFBGRHJGOmuQaoHPM807hNhERkYySjiS5ADjMzLqaWVPgdODJNMQhIiJSpZQ3t7p7sZn9HPg7wRSQu9x9aarjEBERqU5a+iTd/RngmXRcW0REJKqcXZZORESkOkqSIiIiCShJioiIJKAkKSIikoC5126efiqZWRHwSS0PbwN8UY/hpFo2x5/NsUN2x5/NsUN2x59JsR/k7m3THUQ2y4okWRdmttDdC9MdR21lc/zZHDtkd/zZHDtkd/zZHLtUpuZWERGRBJQkRUREEsiFJHlbugOoo2yOP5tjh+yOP5tjh+yOP5tjlwoafJ+kiIhIbeVCTVJERKRWlCRFREQSyOgkaWbDzWyFmX1oZhfHbD/OzN40syVmdreZVVqo3cyOMbNNZvZWeI75ZpVxaEQAAAmuSURBVDYyhbF3NrMXzWyZmS01s/+K2dfbzF43s3fNbI6ZtYxzfBcz2x7G/56Z/dvMJqQq/gqx3GVmG8xsSYXtBWb2LzNbbGYLzWxAnGOPMbOnUhftbtdOVH5eDmNebGZrzezxOMeWlZ+y182t5lrTzexX9RR3VWVndkxMq8xscZzjy8rO4pifplVcb4KZ3VgfsYfnS1ReopZ7N7PfxWxrY2a76jPG6lRRdoaGnz2LzewVMzu0inM8bmb/Sk3EkjTunpE/BLfR+gg4GGgKvA10J0jsnwGHh6/7LfDjOMcfAzwV87wAWAUMTVH8HYC+4eMWwPtA9/D5AmBI+Phc4Ko4x3cBlsQ8PxhYDJyThv+L/wD6xsYTbn8eOCl8/H1gXnX/D+kuP3Fe9wjwn3WNG5gO/CrZZafC6/4ITKuu7ES43gTgxhSUl6jl/mPgrZhtk8KyHzlGoHEyyk74f/G98PFPgVkJzrFP+Dn1HnBwDa9f69j1U/8/mVyTHAB86O4fu/tO4AFgFLAfsNPd3w9f9w9gdHUnc/fFBAn15wBm1tbMHjGzBeHP0eH25mb2l/Db7jtmVu25E1xvnbu/GT7eQvDH0jHcfTgwv4bxfwxcBPwijHPv8Bv7v8Pa5qhweyMzuy6sZb9jZhfWJv4K154PfBVvF1BWG2gFrK3qPGY2IKxJvGVmr5lZt3D7BDN71MyeM7MPzOyausZM4vITG09L4DigUk2yivcQt9yEympKH5jZ+bUNvJqyUxaHAacB99cg9rhlJtTZzOaFsV9R29jDmBOVl6jlfhvwnpmVTcgfBzwY8z5ONrM3wvcw18z2D7dPN7N7zexV4N46vIWqyk7UMv9DYE547Okxsc8ys1vClpf3LWzdCv8GnjSzfwIv1CF2qWdpuZ9kRB0JvomVWQ0cSbDcU2MzK3T3hcAYoHPEc74JTAkf3wDMcPdXzOxAgptAfw+4HNjk7vkAZrZvXd+ImXUB+gBvhJuWEvzRPQ6MrWH8R4SPLwX+6e7nmtk+wL/DJsH/JPg2XuDBDa5b1zX+KkwG/m5m1xHU8AdV8/rlwOAwrmHA//DdB2UBwe9oB7DCzP7s7p8lOE8UicpPrB8AL7j75gTnGBzTnPmQu/+exOUGoBdwFLA38JaZPe3uVX5xqE6cslMeG/C5u3+Q4NBDYmJ/1d1/RuIyA0Fi6EmQoBaEsS+sS+xx1KTcPwCcbmafAyUEyeiAcN8rwFHu7mZ2HvBr4Jfhvu7A/3P37XWIs6qycx7wjJltBzYT/H/HcwbBl/LPCVor/idmXxeC3/chwIsxTbZ9gV7uHu8LhqRJJifJuMI/jNOBGWa2B0GTX0nEwy3m8TCge/CFHICWZtY83F7+zc/dv65LvOE5HwEmx3wYnwvMNLPLgSeBnVFPF/P4BOAU+64frBlwIEH8t7h7cRh/Mv/gJgH/7e6PmNlpwJ3h9RNpBdxtZocRfCNvErPvBXffBGBmy4CD2P2DKhnOAO6oYv/L7l6xHztRuQF4Ivxw3m5mLxJ8EEaupVaUoOzExl5VLfIjdy+osC1RmQH4h7t/GV73UeD/AfWdJGtS7p8DriJIMrMr7OsEzDazDgTNoStj9j1ZxwRZnf8Gvu/ub5jZFOBPBImzXFizPQx4Jfy82mVmPd29rI/2QXcvBT4ws4/57ovvP5QgM08mJ8k17P5Ns1O4DXd/neCbNGZ2AkEzThR9CJquIKj5HOXu38a+IObDr87MrAnBh9x97v5o2XZ3X07wgYWZHQ6MiHjK2PgNGO3uKypcs65h18TZQNmgkoeoOuFA8KH3orufGtaQ5sXs2xHzuIS6l82E5QeCwSAESezUGp63qnJTcdJxrSchJyo74b7GBM15/Wp6WuKXmSPjxFrvE6hrUu7dfaeZLSKoIXYHTonZ/WfgT+7+pJkdQ9AfXOabegg1btkxs7ZAb3cvq9XPJkjmFZ0G7AusDMtFS4IvNZeG+xP9rusjdqlnmdwnuQA4zMy6WjAy73SCb5+YWbvw3z2AqcAt1Z3MzHoRNKXeFG56HrgwZn/Zt+5/AD+L2V6r5tawz+hO4D13/1OFfWXx5wGXRYy/C3AdwQcEBM18F4bXwcz6xMT/k/CDlCQ3t64FhoSPjwMSNf2VacV3iWpCkmIqk7D8hMYQDMz5Nu7RiSUqNwCjzKyZme1HMPBnQW0Cr6rshIYBy919dQ1PnajMABxvZq3NbE+CZuhXaxF6lWpR7v8ITI1Tu4otR2fXa5CBRGXna6BVmOABjue7L62xzgCGu3sXd+9C8GXm9Jj9Y80sz8wOIRgctCLOOSRDZGySDJsLf07wh/0eQRPF0nD3FDN7D3gHmOPu/0xwmsFh5/4KguT4C3cv6xT/BVBoweCWZcAF4fbfAftaMPDlbeDYWr6Fo4GzgOPsu2H43w/3nWFm7xP00a0F/pLgHIeE8b9HMHBhpruXvfYqgubKd8xsafgcgtrcp+H2t4Ezaxl/OTO7H3gd6GZmq83sx+Gu84E/htf5H2BinMMb810t8Rrgf83sLZLcilFN+YHgQyvyoJcYicoNBOXxReBfBCM3a9sfWVXZqUvsicoMwL8Jaq7vAI/UpT+yivIStdwD4O5L3f3uOLumAw+FNc16vyVVorITbj8feCQs82fx3RgHoPzL7EEEZaDsfCuBTWGNHYK/z38DzwIX1OKLmqSQlqWTpLJgjl9Hd/91umMRSTczm0XQgvFwumORaDK5T1KynJndSTBi8rR0xyIiUhuqSYqIiCSQsX2SIiIi6aYkKSIikoCSpIiISAJKkiIVmFlJOO1iqZm9bWa/DOf2VXVMFzOr83QbEcksSpIilW139wJ370EwYfwkoLpFv7tQD3NSRSSzaHSrSAVmttXdm8c8P5hgFZY2BBPF7yVYxBzg5+7+mgX3DfwewTqidwMzgasJVt7ZA7jJ3W9N2ZsQkXqhJClSQcUkGW7bCHQDtgCl7v5tuFD7/e5eGK4h+quyBdHNbCLQzt1/Fy6f+CowNlx9RUSyhBYTEKmZJsCN4ZqtJSReXP8EoJeZjQmftyK4M4SSpEgWUZIUqUbY3FoCbCDom/wc6E3Qp59o3U0DLnT3v6ckSBFJCg3cEalCeHukW4AbPeibaAWsC+8HeBbQKHzpFqBFzKF/ByaFt7zCzA43s70RkayimqRIZXua2WKCptVigoE6ZbesupngLhD/SXAvwbJ7AL4DlIR3h5gF3EAw4vXN8NZURQS3oBKRLKKBOyIiIgmouVVERCQBJUkREZEElCRFREQSUJIUERFJQElSREQkASVJERGRBJQkRUREEvj/P+4dmOiOgrQAAAAASUVORK5CYII=\n", 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" ] @@ -9528,7 +9528,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **55-59** population by **ssri**" + "### COVID vaccinations among **55-59** population by **ssri**" ], "text/plain": [ "" @@ -9539,7 +9539,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9553,7 +9553,7 @@ "data": { "text/markdown": [ "## \n", - " ## COVID vaccination rollout among **50-54** population up to 30 Mar 2021" + " ## COVID vaccination rollout among **50-54** population up to 16 Apr 2021" ], "text/plain": [ "" @@ -9565,7 +9565,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **50-54** population by **sex**" + "### COVID vaccinations among **50-54** population by **sex**" ], "text/plain": [ "" @@ -9576,7 +9576,7 @@ }, { "data": { - "image/png": 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jIneWd/eKrYD2pDvGzBqb2SKCV6Yvu3ts8qzfmNm7ZnaHmTVPcuwEM1tgZguKi4ujFlNEpG7EdYCPZYB5kv2VlpaWWn0XIqqwrKXJtkfNBFeb2VGAm1lT4DJgebqD3H0PUGhm7YEZZtYP+DmwHmgGTAauAX6V4NjJ4XaKioqUQYpI/Ygf8ixOHtf/LS0uLu7TqVOnzY0aNcrq382lpaVWXFzcjqBbX0JRg+BFwJ3AAcBaYCZwSdSCuPsmM3sVGOnut4Wrd5jZQ8BVUc8jIlLn4qc+ipOv9X+7d+/+yfr16x9Yv359P7J/6M1SYOnu3bt/kmyHqEHQ3H1sVa5sZp2AXWEAbAl8B/itmXV193VmZsBppIjQIiL1JsHkt39+8xOeWbQWIN+yvzKDBw/eCJxS3+WoLVGD4D/MbCUwFfiLu2+KcExX4BEza0zw18KT7v68mf09DJAGLCLIMkVEskuCyW8180PDEykIuvuhZjYEOAf4Rdhd4gl3/1OKY94FBiZYf1x1CysiklEJpjz6c5//45mFa2Ghxv1siKrSOvQtd78CGAJ8ATySsVKJiNSHuBafsQwwlv1BftX95YtImaCZtQVOJ8gEDwZmEARDEZHcE6HFJwALUfbXwEWtE1wMPA38yt3nZbA8IiKZF6HFZ4yyv4YtahA8KBwBRkQkdyUY4zNevrb4zGfpplL6X3e/HHjWzCoFQXdvMM1kRSQPJBjjM56yvvyTLhN8NPz3tpR7iYhkK43xKSmkbB3q7gvDxUJ3nx3/IZgZQkQku+XvGJ8SQdQ6wXEEw6bFG59gnYhI3UrS0jMmj8f4lAjS1QmOAX4A9DKzZ+M2tSHoKygiUr+StPSMydcxPiWadJngXGAd0BG4PW79VuDdTBVKRCSlBCO78OO/lm3WGJ8SVcog6O6rgFWAnh4RyR7x2V/c2J4xGuNTooo6YsyRwO+BbxLMA9gY+Mrd22awbCIieyXJ/v785idlY3vGaJQXiSrq2KF3A2OAD4CWwE+AezJVKBGRShKM6wmUG9szRtmfRBW1dSju/qGZNQ5ni3/IzN4hmCVeRKTm0rTyTJb9KeuTmoiaCW4zs2bAIjO7xcx+VoVjRUTSi8/0EkmS/Snrk5qImgmeS1AP+FPgZ0B34IxMFUpE8lSKVp4ALETZn9SqqJPqrgoXtwM3RjnGzFoAc4Dm4XWmu/tEM+sFPAHsR/BIn+vuO6tacBFp+OJbecZT9ie1JV1n+SVA0tkj3H1AisN3AMe5e4mZNQXeMLO/AVcAd7j7E2Z2H3A+8H9VL7qI5LxELT7ZmwEq45NMS5cJjqruicOpl0rCr03DjwPHEYxCA8Hs9JNQEBTJT0n6+8UHQGV8kklROstXm5k1Jnjl+Q2CLhUfAZvcfXe4yxog4RNuZhOACQA9evSoSTFEJJtE6O+nDFDqSqQWnma21cy2hJ+vzWyPmW1Jd5y773H3QqAbMAToHbVg7j7Z3YvcvahTp05RDxORbBehv58yQKkrURvGtIktm5kBpwJHRr2Iu28ys1cJhl9rb2ZNwmywG7A29dEi0iAkm9VdLT6lHlW5r58HngZOTLWfmXUys/bhckvgO8By4FUgNtDfOOCZqpZBRHKQZnWXLBR17NDvx31tBBQBX6c5rCvwSFgv2Ah40t2fN7NlwBNm9mvgHeDBqhdbRHJBfD+/Gz7fDPTQrO6SVaJ2lj85bnk3sJLglWhS7v4uMDDB+o8J6gdFpIErmTuFqza/wj7NGtNz18esbHqQMj7JKlHrBH+c6YKISMMQn/1dtfkV+tgqWnUdCAykb//RTC1SBijZI+rr0F7ApUDP+GPc/ZTMFEtEclW57M9WUbLvN2kVNxSaSDaJ+jr0aYK6u+eA0swVR0RyVSwDrJj9taow4a1INokaBL9297syWhIRyWmxDLCPsj/JIVGD4J1mNhGYSTAmKADu/nZGSiUiOSFh/V8PZX+SO6IGwf4E0ykdx97XobFxQEUkT6n+T3Jd1CB4JnCQpjwSkVStP5UBSq6JGgSXAu2BjRksi4hkq7hBrwvWbeaQnXuU/UmDEDUItgfeN7P5lK8TVBcJkQYslvXd8PmDZZ3dt4UBsG/Xdij7k1wXNQhOzGgpRCQrxer8etoqVjY9iF/tdysApxYeQN8jNMWZ5L6oI8bMznRBRCQ7JGvxqdFepCGKOmLMVoLWoADNCGaJ/8rd22aqYCJSh1TnJ3mqTuYTFJHstmHun2j95XLV+UneiVonWMbdHXg67Dx/be0XSUTqRFz21/rL5SzzA7lNdX6SZzI5n6CIZLFy2Z8fyDvtRmiOP8k7GZtP0My6A38EOhPUJ0529zvNbBJwAVAc7nqdu79QhTKLSFXFZX0xibI/kXyTyfkEdwNXuvvbZtYGWGhmL4fb7nD326pxThGphvisL0bZn0j016GPAJe5+6bw+77A7e5+XrJj3H0dsC5c3mpmywH9qSlSV1LU+cUo+5N8F/V16IBYAARw9y/NbGDUi5hZT2Ag8CYwDPipmf0IWECQLX4ZucQiEonq/ETSixoEG5nZvrFgZWYdoh5rZq2BvwCXu/sWM/s/4CaCesKbgNuBShmlmU0AJgD06KFWaiKRpGnxKSLlRQ2CtwPzzGxa+P1M4DfpDjKzpgQB8DF3fwrA3TfEbZ8CPJ/oWHefDEwGKCoq8kT7iEgg4Rifyv5E0oraMOaPZraAvfMHft/dl6U6JuxU/yCw3N1/F7e+a1hfCHA6wQwVIlJVCUZ5STTGp4gklzIImllrdy8BCINepcAXv08Fwwgm4l1iZovCddcBY8yskOB16ErgwuoXXyR/JRrlpVVXjfEpUhXpMsFnwgD2DLDQ3b8CMLODgGOBs4ApwPSKB7r7G4AlOKf6BIpU05vTbqf1BzMA6L7jI5b4gdzRRaO8iFRXyiDo7seb2fcIsrVhYYOYXcAK4K/AOHdfn/liighA6w9m0H3nR6xudjCrmx+MHXI6U89U1idSXWnrBMPRXJS9idSTctlfGAD7XvdGPZdKpGFoVN8FEJHUYtkfwOpmB1NyyOn1XCKRhqPKs0iISObET2h7/LYXGLb9VWV/IhmkTFAkizyzaC3L1m0BYNj2V+m562NlfyIZlK6LRIdU2939i9otjkj+ic/++qx7ihuazaNvs3Zgn0CPgfTVrO4iGZPudehCgv58BvQAvgyX2wOfAL0yWjqRPBDL/vp0bcvoZvM4pHQlUABd+oNmdRfJqHRdJHpB2fBmM2Lz/pnZd4HTMl88kYYlPuuLqZT9HVAAyv5E6kTUOsEj4ye+dfe/AUdlpkgiDVd8nV/M3uwPZX8idSxq69BPzex64E/h97HAp5kpkkjDEp/9xV57Th38/t6Z3pX9idSbqJngGKATMAN4Klwek6lCiTQk8dlfn65tg0Gtl0yH9UuCHZT9idSbqLNIfAFcZmatYuOHikhyCbO/+CmNlhEEP2V/IvUqUiZoZkeZ2TJgefi9wMzuzWjJRHJYwuwPgumPHjppbxYoIvUqap3gHcCJwLMA7r7YzL6dsVKJ5KC02R/sfQ2qV6AiWSHysGnuvjqYJ7fMntovjkjuiu/vd2m7Nzh1x1x4qEX5nWIBUK9BRbJC1IYxq83sKMDNrKmZXUX4alQk3/35zU84+/555bK/Ce3fpvNXH1TeWRmgSFaJmgleBNwJHACsBWYC/5nqADPrDvwR6Eww6sxkd78zHIptKtCTYGb5s9z9y+oUXiQbxDLActmfMj6RnBA1EzzM3ce6e2d339/dfwh8M80xu4Er3b0PcCRwiZn1Aa4FZrn7IcCs8LtITuvTtW357E8Zn0hOiJoJ/h4YFGFdGXdfB6wLl7ea2XKCTPJU4Jhwt0eA14BrIpdYJMvEpjzCPlH2J5Jj0s0iMZRgeLROZnZF3Ka2QOOoFzGznsBA4E2gcxggAdYTvC5NdMwEYAJAjx49ol5KpE7EtwS9avMr9LRV0GOgsj+RHJMuE2wGtA73axO3fgsQ6afdzFoDfwEud/ct8S1M3d3NzBMd5+6TgckARUVFCfcRqS8lc6dw1eZX2KdZY3raKkr2/SatlAGK5Jx0s0jMBmab2cPuvqqqJzezpgQB8DF3fypcvcHMurr7OjPrCmyscqlF6kiiWR8gyP762CpadR0IDKSVMkCRnBS1TnCbmd0K9AXKOj65+3HJDrAg5XsQWO7uv4vb9CwwDrg5/PeZqhZapK7E9/0rq/sDZX8iDUTUIPgYQbeGUQTdJcYBxWmOGQacCywxs0XhuusIgt+TZnY+sAo4q6qFFsm0WAZYbuSXh34NX4eNX5T9iTQIUYPgfu7+oJldFveKdH6qA9z9DYJZ6BM5viqFFKlr8XV+HXc0V98/kQYqahDcFf67zsxOIphLsENmiiRSd6LV+YXU90+kwYkaBH9tZu2AKwn6B7YFfpaxUonUEdX5ieS3qPMJPh8ubgaOzVxxROqe6vxE8lekIGhmnYALCMb7LDvG3c/LTLFE6kZZ9vdQO9X5ieShqK9DnwFeB15BUyhJjkpU/1c22gsDVecnkoeiBsF93F3je0pOi2/xGaO6P5H8FjUIPm9m33P3FzJaGpFaVnGMz0otPlX3J5LXogbBy4DrzGwHQXcJIxj6s23GSiZSCzTGp4ikErV1aJv0e4lkh+TZn7I+ESkv3VRKvd39fTNLOG+gu7+dmWKJVF983799mjWmpLWyPxFJLF0meAXBnH63J9jmQNIBtEXqWuLxPtvVd7FEJIulm0ppQvivOshL1ks53qeISAJRO8tfQjAn4Kbw+77AGHe/N5OFE0lE432KSG2J2jr0Ane/J/bF3b80swsABUGpcxrvU0RqS9Qg2NjMzN0dwMwaA80yVyyR8uKzP83xJyK1JWoQfBGYamb3h98vDNeJ1In47O/Sdm9w6o65muNPRGqsUcT9rgH+DlwcfmYB/53qADP7g5ltNLOlcesmmdlaM1sUfr5X3YJL/ollfxPav03nrz4IVqrOT0RqIGom2BKY4u73Qdnr0ObAthTHPAzcDfyxwvo73P22KpZT8pxmexCRTIgaBGcBI4CS8HtLYCZwVLID3H2OmfWsSeEkfyRr8Rmj2R5EJBOiBsEW7h4LgLh7iZntU81r/tTMfgQsAK509y8T7WRmEwg66tOjR49qXkpyRXydX7xYBqiWnyKSCVGD4FdmNig2TJqZDQa2V+N6/wfcRDDazE0EI9EknJjX3ScDkwGKioq8GteSLJe0xWe8WOvPHmr5KSK1L2oQvByYZmafEswg0QU4u6oXc/cNsWUzmwI8X9VzSMMRn/316dqWUwsPCDYseAiWTA+WVf8nIhkUdRaJ+WbWGzgsXLXC3XdV9WJm1tXd14VfTweWptpfGqaEY3zGWzJ9b/BT/Z+IZFDUTBCCANgHaAEMMjPcvWLLzzJm9jhwDNDRzNYAE4FjzKyQ4HXoSoL+hpJn4gNgWfZXkbI/EakDUccOnUgQ0PoALwDfBd6gcveHMu4+JsHqB6teRMlVyVp8JswAE70CFRHJsKid5UcDxwPr3f3HQAGgOWokpVjGV1HCDDD2ChT0ClRE6kzU16Hb3b3UzHabWVtgI9A9g+WSHBWpxWeMGsCISD2LmgkuMLP2wBRgIfA2MC9jpZKcFZ/9pazzA2V/IlLvorYO/c9w8T4zexFo6+7vZq5YkmvStviMF8sAlf2JSD2LlAma2bNm9gMza+XuKxUApaJILT5j4gOgsj8RqUdR6wRvJ+gc///MbD7wBPC8u3+dsZJJzlH9n4jkmkiZoLvPDl+JHgTcD5xF0DhGJBrV/4lIForcWd7MWgInE2SEg4BHMlUoyV7p+v6Vo+xPRLJc1DrBJ4HlwHEEcwQe7O6XZrJgkp3U909EGpKomeCDwBh335PJwkh2Ut8/EWmootYJvqQAmL/U909EGqqqDKAteUx9/0SkIYo6YoxIaur7JyI5KOosErPc/fh06yT3JWr9mbDlJ6j+T0RyXspM0MxamFkHgjkB9zWzDuGnJ5BmWBDJRYlafyatB1T9n4jkuHSZ4IXA5cB/EAycbeH6LQRdJZIysz8Ao4CN7t4vXNcBmAr0JJhU9yx3/7KaZZdaotafIpKvUmaC7n6nu/cCrnL3g9y9V/gpcK4hvUAAABILSURBVPeUQRB4GBhZYd21wCx3PwSYFX6XeqbWnyKSr6LOIvF7MzuKIINrErc+1czyc8LXpvFOJZihHoIRZ14DrolaWKk9kbK/+KwvRtmfiDQgUUeMeRS4DfgWcHj4KarG9Tq7+7pweT3QOcU1J5jZAjNbUFxcXI1LSSqRsr/4rC9G2Z+INCBR+wkWAX3c3Wvrwu7uZpb0fO4+GZgMUFRUVGvXzXdp5/1TnZ+I5JGo/QSXAl1q4XobzKwrQPivZqKoY2nn/VOdn4jkkaiZYEdgmZm9BeyIrXT3U6p4vWeBccDN4b/PVPF4qYa09X/K/kQkT0UNgpOqemIze5ygEUxHM1sDTCQIfk+a2fnAKoJ5CSXD4rO/lLM9dOmv7E9E8krU1qGzzexA4BB3f8XM9gEapzlmTJJNGmWmDij7ExFJL2rr0AuA6QSzykMwWszTmSqU1Fza1p+q+xMRifw69BJgCPAmgLt/YGb7Z6xUUivSzvyg7E9E8lzU1qE73H1n7IuZNQHUbUFERHJa1ExwtpldB7Q0s+8A/wk8l7liSVWknfkh1cgvIiJ5LGomeC1QDCwhGFT7BeD6TBVKqibtzA8a+UVEJKGomWBL4A/uPgXAzBqH67ZlqmBSWaKMD1K1/vw1LEOtP0VEkoiaCc4iCHoxLYFXar84kkqijA/U+lNEpLqiZoIt3L0k9sXdS8K+glLHNNefiEjtiZoJfmVmg2JfzGwwsD0zRZJqU/YnIlIlUTPBy4BpZvYpwezyXYCzM1YqSd/iM14sA1T2JyJSJWmDoJk1ApoBvYHDwtUr3H1XJguW7+LH+4xJO/ODsj8RkSpJGwTdvdTM7nH3gQRTKkmGRJrtPRllgCIiVRb1degsMzsDeKo2J9aV8tLO9pCo0zuo47uISDVFDYIXAlcAe8xsO0G9oLt7ggoqqYoqZX/xrz3j6TWoiEi1RJ1KqU2mC5KvkmZ/qYY602tPEZFaESkImpkBY4Fe7n6TmXUHurr7WxktXQOTqsVnpewvUdanjE9EpFZFfR16L1AKHAfcBJQA9wCHV+eiZrYS2ArsAXa7e1F1zpNr0rb4VGd3EZE6FTUIHuHug8zsHQB3/9LMmtXw2se6+2c1PEfOiVznp6xPRCTjogbBXeGg2Q5gZp0IMkOpKWV/IiL1JmoQvAuYAexvZr8BRlOzqZQcmGlmDtzv7pMr7mBmE4AJAD169KjBpepeutkeylH2JyJSb6K2Dn3MzBYCxxN0jzjN3ZfX4Lrfcve1ZrY/8LKZve/ucypcczIwGaCoqCin+iYmqvuDJPV/yv5EROpNyiBoZi2Ai4BvEEyoe7+7767pRd19bfjvRjObAQwB5qQ+KvvFMsBIo71oqDMRkXqXLhN8BNgFvA58F/gmcHlNLmhmrYBG7r41XD4B+FVNzpkt4gNgwjE+Vf8nIpJV0gXBPu7eH8DMHgRqo19gZ2BG0PWQJsCf3f3FWjhvvaj2iC/KAEVE6l26IFg2U4S77w4DV424+8dAQY1PlCUSjviSboxPZX8iIlkhXRAsMLMt4bIBLcPvGjs0TqXs7yGN8SkikgtSBkF3b1xXBWkQ1OJTRCSnRO0nKHES1QMCavEpIpJjFAQjig98B30yjZ81nkubFk2gGXTc0RweaqEMUEQkxygIRhTfAOaHrd7ikNI1NOtaoX2PMkARkZyiIJhGLAPss+4pbmg2j77N2oF9AgcUKOMTEclxjeq7ANkulgGObjaPQ0pXBiuV8YmINAjKBBOIr/8rywCV/YmINDjKBBOIZX/A3gxQ2Z+ISIOT15lgsimPVP8nIpIf8joTjM/44qn+T0QkP+R1JghxQ57Fj/ep7E9EJC/kdSZYTmy0F1D2JyKSJ/InE4zL9DZs/ZrPSnZw1c497NOsMTzUTqO9iIjkofzJBOMyvc9KdrAtDIAdWzcPtiv7ExHJO/WSCZrZSOBOoDHwgLvfXCcXDjO9X90/DyD55LciIpIX6jwTNLPGwD3Ad4E+wBgz61PX5RAREamPTHAI8GE4wzxm9gRwKrCsti/0z3svoM2m5QD03PUxK5sexK/un1d++iMREclb9VEneACwOu77mnBdOWY2wcwWmNmC4uLiGl90ZdOD+EfLY4GgW8SphZUuKSIieSZrW4e6+2RgMkBRUZFX5xxH/ueUct/7AhNqXDIREWko6iMTXAt0j/veLVwnIiJSp+ojCM4HDjGzXmbWDDgHeLYeyiEiInmuzl+HuvtuM/sp8BJBF4k/uPt7dV0OERGReqkTdPcXgBfq49oiIiIx+TNijIiISAUKgiIikrcUBEVEJG8pCIqISN4y92r1Q69TZlYMrKrm4R2Bz2qxONlE95abdG+5J1fv60B371TfhchmOREEa8LMFrh7UX2XIxN0b7lJ95Z7Gup9iV6HiohIHlMQFBGRvJUPQXByfRcgg3RvuUn3lnsa6n3lvQZfJygiIpJMPmSCIiIiCSkIiohI3sr6IGhmI81shZl9aGbXxq0/zszeNrOlZvaImVUaDNzMjjGzzWb2TniOOWY2qm7voDIz625mr5rZMjN7z8wui9tWYGbzzGyJmT1nZm0THN/TzLaH97XczN4ys/F1ehMRmNkfzGyjmS2tsL7QzP5pZovMbIGZDUlw7DFm9nzdlTa6FM/k6+E9LTKzT83s6QTHxp7J2H6vpLnWJDO7KhP3keBaqZ7LqXFlXmlmixIcH3suF8V9mqW43ngzuztT91PhWsmexag/b25mv45b19HMdtVV+SWD3D1rPwRTLX0EHAQ0AxYDfQiC92rg0HC/XwHnJzj+GOD5uO+FwErg+Hq+r67AoHC5DfAvoE/4fT4wPFw+D7gpwfE9gaVx3w8CFgE/ru//ZxXK+W1gUHxZw/Uzge+Gy98DXkv3/y5bPsmeyQT7/QX4UU3vC5gEXFVH95b0uayw3+3ADQnWl3suI1xvPHB3Hd1bsmcx6s/bx8A7cesuDn/mIpcfaFIX96pP1T7ZngkOAT5094/dfSfwBHAqsB+w093/Fe73MnBGupO5+yKCgPlTADPrZGZ/MbP54WdYuL61mT0U/nX4rpmlPXdVuPs6d387XN4KLAcOCDcfCsyp4n19DFwB/FdY/lbhX75vhdniqeH6xmZ2W5g9v2tml9bmfSUo1xzgi0SbgNhf3O2AT1Odx8yGhH+tv2Nmc83ssHD9eDN7ysxeNLMPzOyWWr2BxJI9k/HlbQscB1TKBJNJ9iyGYtnKB2Z2QW3cRCJpnstYOQ04C3g86nmTPY+h7mb2WnhvE2vhNhJK8SxG/XnbBiw3s1iH+bOBJ2MbzexkM3szvL9XzKxzuH6SmT1qZv8AHq2Ne5HaVS/zCVbBAQQZX8wa4AiC4YuamFmRuy8ARgPdI57zbeDqcPlO4A53f8PMehBM9PtN4JfAZnfvD2Bm+9b4TpIws57AQODNcNV7BL9UnwbOpGr31Ttc/gXwd3c/z8zaA2+Fr91+RPBXbaEHkxt3qI17qIbLgZfM7DaCrP6oNPu/DxwdlnkE8D/s/WVVSPDfbwewwsx+7+6rk5ynNiR7JuOdBsxy9y1JznF03OvEae7+G5I/iwADgCOBVsA7ZvZXd0/5h0NNJXguy8oObHD3D5IcenDcvf3D3S8h+fMIwR8V/QiCzPzw3hbU4q2kU5WftyeAc8xsA7CH4I+3/wi3vQEc6e5uZj8B/hu4MtzWB/iWu2/PQPmlhrI9CCYUPmjnAHeYWXOC12t7Ih5uccsjgD7BH7cAtDWz1uH6c+Ku92XNS52gIMG1/gJcHvcL8zzgLjP7JfAssDPq6eKWTwBOiatLagH0ILiv+9x9N4C7J/rLuC5cDPzM3f9iZmcBD4ZlS6Yd8IiZHUKQRTaN2zbL3TcDmNky4EDKB6n6MAZ4IMX21929Yt10smcR4JnwF+h2M3uVIHBEzjKrKslzGTOG1FngR+5eWGFdsucR4GV3/zy87lPAt4C6DIJV+Xl7EbgJ2ABMrbCtGzDVzLoSvCb/d9y2ZxUAs1e2B8G1lP/LrFu4DnefR/BXKWZ2AsFrjSgGErzmgSALOdLdv47fIe4XUcaYWVOCXzSPuftTsfXu/j7BLw3M7FDgpIinjL8vA85w9xUVrlnTYteWcUCs0cU0UgcMCH7xvOrup4cZymtx23bELe8h88900mcSggYTBEHq9CqeN9WzWLEzb8Y69yZ7LsNtTYDvA4OreloSP49HUIf3lkhVft7cfaeZLSTI8PoAp8Rt/j3wO3d/1syOIajLjfmqlosttSjb6wTnA4eYWS8LWpmdQ/DXGma2f/hvc+Aa4L50JzOzAQSvOu8JV80ELo3bHvsL9mXgkrj1tfo6NKxXeRBY7u6/q7Atdl+NgOuJdl89gdsIfhAheJV2aXgdzGxguP5l4MLwlxn1+Dr0U2B4uHwckOzVWkw79gaa8RkqU1RJn8nQaIKGL18nPDq5ZM8iwKlm1sLM9iNoWDO/WiVPI9VzGRoBvO/ua6p46mTPI8B3zKyDmbUkeI38j2oUvdqq8fN2O3BNgrco8c/ouFotpGRUVgfB8LXdTwl+iJYDT7r7e+Hmq81sOfAu8Jy7/z3JaY4OK6tXEAS//3L3WeG2/wKKLGgksgy4KFz/a2BfCxqQLAaOreVbGwacCxxne5uSfy/cNsbM/kVQD/Yp8FCScxwc3tdyggr6u9w9tu9NBK8M3zWz98LvEGRcn4TrFwM/qOX7KsfMHgfmAYeZ2RozOz/cdAFwe1iG/wEmJDi8CXuzvFuA/2dm71DPby/SPJMQBMXIjUbiJHsWIXjGXwX+SdB6MVP1gameS6j+vSV7HgHeIsg83wX+kqn6wBTPYtSfNwDc/T13fyTBpknAtDBTzMUpl/KWhk2TrGRBH7UD3P2/67ssItJwZXudoOQhM3uQoMXgWfVdFhFp2JQJiohI3srqOkEREZFMUhAUEZG8pSAoIiJ5S0FQspqZ7Qmb6r9nZovN7MqwT1eqY3qaWUa7f1SVmc2twbHjzew/0u9Z7pieVmHGBBGpTEFQst12dy90977Ad4DvAukGWu5JhvtAVpW7pxsfNZXx7B2jUkRqkYKg5Ax330jQsf6nFuhpwRx+b4efWKC5mXCQajP7mQWzZ9xqwewM75rZhRXPbWY3m1n8KEGTzOwqC2YUmRWef4nFzYBgZj8Kz7fYzB4N13U2sxnhusWxMplZSfjvMRbMmjDdzN43s8fiRlK5ISzjUjObHN7jaKAIeCy8n5ZmNtjMZpvZQjN7yYLxKgnXLw4HISi7FxFJob7nctJHn1QfoCTBuk1AZ2AfoEW47hBgQbh8DOXnkZwAXB8uNycYoLlXhXMOBGbHfV9GMEZoE6BtuK4j8CHBWJh9Cebb6xhu6xD+O5Vg4GkI5h5sF38fYdk2E4w52ohgFJNvxZ8jXH4UODlcfg0oCpebAnOBTuH3s4E/hMvvAt8Ol2+lCnP76aNPvn7UWV5yWVPg7nCczT0kH0T9BGBAmFVBMM7jIcSN9O/u75jZ/mHdWyfgS3dfbcGA0v9jZt8GSgmmUupMMObpNHf/LDw+NpbkcQRTVuHuewgCXkVveTj+pgXTDvUkmIrnWDP7b4Lg3oFgmp/nKhx7GMFAAi+HCWRjYJ0FUxS192DePAiC6HeT/PcQkZCCoOQUMzuIIOBtJKgb3AAUEGRVyQatNuBSd38pzemnEQyA3YW9U+WMJQiKg919l5mtJJgKqCYqzXxhZi2AewkyvtVmNinJdQx4z92HllsZBEERqSLVCUrOMLNOBKP83+3uTpDRrXP3UoKBnxuHu24F2sQd+hJwcZjVYWaHmlmrBJeYSjBI9GiCgEh4jY1hADyWYL5CgL8DZ1ows0P8jByzCOZLJKyLbBfx9mIB7zML5vMbHbct/n5WAJ3MbGh4jaZm1tfdNwGbzOxb4X5jI15XJK8pCEq2axnrIgG8QjDl0I3htnuBcWFDkN7snbftXWBP2EjkZwSzZywD3g67DdxPgrcgHswG0QZY6+7rwtWPEczusITgNef7cfv+BpgdXj829dBlBK81lwALCeadSysMYlOApQRBO366pIeB+8JXp40JAuRvw+suAmINgn4M3BPulzWTR4pkM40dKiIieUuZoIiI5C0FQRERyVsKgiIikrcUBEVEJG8pCIqISN5SEBQRkbylICgiInnr/wMmKefPEFTqGgAAAABJRU5ErkJggg==\n", 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\n", 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" ] @@ -9589,7 +9589,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **50-54** population by **ethnicity 6 groups**" + "### COVID vaccinations among **50-54** population by **ethnicity 6 groups**" ], "text/plain": [ "" @@ -9600,7 +9600,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9613,7 +9613,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **50-54** population by **imd categories**" + "### COVID vaccinations among **50-54** population by **imd categories**" ], "text/plain": [ "" @@ -9624,7 +9624,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9637,7 +9637,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **50-54** population by **bmi**" + "### COVID vaccinations among **50-54** population by **bmi**" ], "text/plain": [ "" @@ -9648,7 +9648,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9661,7 +9661,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **50-54** population by **chronic cardiac disease**" + "### COVID vaccinations among **50-54** population by **chronic cardiac disease**" ], "text/plain": [ "" @@ -9672,7 +9672,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9685,7 +9685,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **50-54** population by **current copd**" + "### COVID vaccinations among **50-54** population by **current copd**" ], "text/plain": [ "" @@ -9696,7 +9696,7 @@ }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -9709,7 +9709,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **50-54** population by **psychosis schiz bipolar**" + "### COVID vaccinations among **50-54** population by **psychosis schiz bipolar**" ], "text/plain": [ "" @@ -9720,7 +9720,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -9733,7 +9733,7 @@ { "data": { "text/markdown": [ - "### COVID vaccinations among **50-54** population by **ssri**" + "### COVID vaccinations among **50-54** population by **ssri**" ], "text/plain": [ "" @@ -9744,7 +9744,7 @@ }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -9770,13 +9770,13 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "Total **80+** population with ethnicity recorded 1,813 (85.5%)" + "Total **80+** population with ethnicity recorded 1,743 (85.3%)" ], "text/plain": [ "" @@ -9788,7 +9788,7 @@ { "data": { "text/markdown": [ - "Total **70-79** population with ethnicity recorded 3,017 (84.5%)" + "Total **70-79** population with ethnicity recorded 2,905 (84.5%)" ], "text/plain": [ "" @@ -9800,7 +9800,7 @@ { "data": { "text/markdown": [ - "Total **care home** population with ethnicity recorded 1,155 (84.2%)" + "Total **care home** population with ethnicity recorded 1,176 (84.8%)" ], "text/plain": [ "" @@ -9812,7 +9812,7 @@ { "data": { "text/markdown": [ - "Total **shielding (aged 16-69)** population with ethnicity recorded 343 (83.1%)" + "Total **shielding (aged 16-69)** population with ethnicity recorded 357 (82.3%)" ], "text/plain": [ "" @@ -9824,7 +9824,7 @@ { "data": { "text/markdown": [ - "Total **65-69** population with ethnicity recorded 1,876 (85.6%)" + "Total **65-69** population with ethnicity recorded 1,834 (84.0%)" ], "text/plain": [ "" @@ -9836,7 +9836,7 @@ { "data": { "text/markdown": [ - "Total **LD (aged 16-64)** population with ethnicity recorded 679 (86.6%)" + "Total **LD (aged 16-64)** population with ethnicity recorded 707 (85.6%)" ], "text/plain": [ "" @@ -9848,7 +9848,7 @@ { "data": { "text/markdown": [ - "Total **60-64** population with ethnicity recorded 2,240 (85.1%)" + "Total **60-64** population with ethnicity recorded 2,317 (85.3%)" ], "text/plain": [ "" @@ -9860,7 +9860,7 @@ { "data": { "text/markdown": [ - "Total **55-59** population with ethnicity recorded 2,681 (85.5%)" + "Total **55-59** population with ethnicity recorded 2,688 (84.2%)" ], "text/plain": [ "" @@ -9872,7 +9872,7 @@ { "data": { "text/markdown": [ - "Total **50-54** population with ethnicity recorded 2,926 (85.8%)" + "Total **50-54** population with ethnicity recorded 2,926 (86.0%)" ], "text/plain": [ "" @@ -9884,7 +9884,7 @@ { "data": { "text/markdown": [ - "Total **vaccinated 16-49, not in other eligible groups shown** population with ethnicity recorded 25,774 (84.8%)" + "Total **vaccinated 16-49, not in other eligible groups shown** population with ethnicity recorded 25,809 (85.0%)" ], "text/plain": [ "" diff --git a/project.yaml b/project.yaml index 84ce18e..4e96735 100644 --- a/project.yaml +++ b/project.yaml @@ -6,10 +6,10 @@ expectations: actions: generate_delivery_cohort: - run: cohortextractor:latest generate_cohort --study-definition study_definition_delivery + run: cohortextractor:latest generate_cohort --study-definition study_definition_delivery --output-format=csv.gz outputs: highly_sensitive: - cohort: output/input_delivery.csv + cohort: output/input_delivery.csv.gz generate_notebook: run: jupyter:latest jupyter nbconvert /workspace/notebooks/population_characteristics.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by ethnicity 6 groups_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by ethnicity 6 groups_tpp.csv new file mode 100644 index 0000000..70d99c1 --- /dev/null +++ b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by ethnicity 6 groups_tpp.csv @@ -0,0 +1,130 @@ +covid_vacc_date,Black,Mixed,Other,South Asian,Unknown,White,Black_total,Mixed_total,Other_total,South Asian_total,Unknown_total,White_total +2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,37471,15225,28315,85197,189392,1202558 +2020-12-08,0.0,0.0,7.0,21.0,28.0,182.0,37471,15225,28315,85197,189392,1202558 +2020-12-09,14.0,7.0,14.0,56.0,63.0,518.0,37471,15225,28315,85197,189392,1202558 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percent among 55-59 population by imd categories_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 55-59 population by imd categories_tpp.csv new file mode 100644 index 0000000..2f5b044 --- /dev/null +++ b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 55-59 population by imd categories_tpp.csv @@ -0,0 +1,131 @@ +covid_vacc_date,1 Most deprived,2,3,4,5 Least deprived,Unknown,1 Most deprived_total,2_total,3_total,4_total,5 Least deprived_total,Unknown_total +2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,245280,275737,322966,324135,309988,29967 +2020-12-06,0.0,0.0,0.0,0.0,0.0,0.0,245280,275737,322966,324135,309988,29967 +2020-12-08,42.0,28.0,56.0,70.0,63.0,0.0,245280,275737,322966,324135,309988,29967 +2020-12-09,119.0,105.0,147.0,168.0,161.0,7.0,245280,275737,322966,324135,309988,29967 +2020-12-10,175.0,168.0,217.0,252.0,259.0,21.0,245280,275737,322966,324135,309988,29967 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population by imd categories_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 60-64 population by imd categories_tpp.csv new file mode 100644 index 0000000..3ba52fd --- /dev/null +++ b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 60-64 population by imd categories_tpp.csv @@ -0,0 +1,129 @@ +covid_vacc_date,1 Most deprived,2,3,4,5 Least deprived,Unknown,1 Most deprived_total,2_total,3_total,4_total,5 Least deprived_total,Unknown_total +2020-12-08,28.0,28.0,28.0,42.0,28.0,0.0,198170,231259,276976,278523,265034,25956 +2020-12-09,84.0,98.0,112.0,98.0,126.0,14.0,198170,231259,276976,278523,265034,25956 +2020-12-10,133.0,154.0,182.0,168.0,217.0,21.0,198170,231259,276976,278523,265034,25956 +2020-12-11,182.0,210.0,245.0,252.0,301.0,28.0,198170,231259,276976,278523,265034,25956 +2020-12-12,210.0,252.0,301.0,322.0,357.0,35.0,198170,231259,276976,278523,265034,25956 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not in other eligible groups shown",70-79,55-59,50 03 Dec,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 04 Dec,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 06 Dec,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 -08 Dec,2219.0,714.0,35.0,259.0,252.0,161.0,539.0,56.0,203.0,0.0,0.0 -09 Dec,6699.0,2051.0,98.0,707.0,672.0,532.0,2002.0,168.0,462.0,7.0,0.0 -10 Dec,11613.0,3444.0,168.0,1085.0,1036.0,875.0,3920.0,280.0,770.0,28.0,7.0 -11 Dec,16541.0,4914.0,238.0,1484.0,1463.0,1211.0,5733.0,399.0,1064.0,28.0,7.0 -12 Dec,21049.0,6545.0,294.0,1897.0,1883.0,1477.0,7028.0,497.0,1379.0,35.0,14.0 -13 Dec,24584.0,7756.0,329.0,2198.0,2198.0,1722.0,8197.0,574.0,1554.0,42.0,14.0 -14 Dec,29631.0,9324.0,406.0,2639.0,2597.0,2016.0,10115.0,679.0,1799.0,42.0,14.0 -15 Dec,56133.0,11851.0,609.0,3353.0,3248.0,2499.0,31311.0,896.0,2254.0,98.0,14.0 -16 Dec,97839.0,14952.0,882.0,4305.0,4151.0,3129.0,66367.0,1120.0,2674.0,238.0,21.0 -17 Dec,137536.0,18620.0,1505.0,5446.0,5208.0,3969.0,97769.0,1414.0,3213.0,364.0,28.0 -18 Dec,165809.0,22148.0,2072.0,6503.0,6258.0,4746.0,118034.0,1729.0,3766.0,511.0,42.0 -19 Dec,197631.0,25179.0,2744.0,7399.0,7077.0,5467.0,142891.0,2044.0,4186.0,595.0,49.0 -20 Dec,228375.0,29267.0,3311.0,8687.0,8204.0,6384.0,164717.0,2387.0,4683.0,672.0,63.0 -21 Dec,252658.0,34356.0,3969.0,10346.0,9730.0,7511.0,177737.0,2800.0,5383.0,756.0,70.0 -22 Dec,287182.0,39032.0,4585.0,11732.0,11116.0,8498.0,201985.0,3206.0,6090.0,861.0,77.0 -23 Dec,317737.0,45234.0,5306.0,13482.0,12747.0,9793.0,219254.0,3710.0,6937.0,1183.0,91.0 -24 Dec,328384.0,48342.0,5635.0,14301.0,13566.0,10437.0,223090.0,3955.0,7343.0,1617.0,98.0 -25 Dec,328433.0,48370.0,5635.0,14308.0,13573.0,10437.0,223097.0,3955.0,7343.0,1617.0,98.0 -26 Dec,328727.0,48559.0,5642.0,14336.0,13608.0,10451.0,223097.0,3962.0,7357.0,1617.0,98.0 -27 Dec,330792.0,49609.0,5663.0,14595.0,13832.0,10626.0,223286.0,4025.0,7441.0,1617.0,98.0 -28 Dec,334516.0,51387.0,5761.0,14945.0,14245.0,10948.0,223755.0,4137.0,7616.0,1624.0,98.0 -29 Dec,351974.0,55895.0,6202.0,16023.0,15365.0,11732.0,231756.0,4466.0,8099.0,2324.0,112.0 -30 Dec,397096.0,65863.0,8316.0,18690.0,17969.0,13706.0,251671.0,5278.0,9499.0,5915.0,189.0 -31 Dec,435106.0,75600.0,10528.0,21315.0,20517.0,15547.0,265972.0,6090.0,10815.0,8449.0,273.0 -01 Jan,443646.0,78232.0,11095.0,21938.0,21210.0,16023.0,268604.0,6272.0,11116.0,8855.0,301.0 -02 Jan,452921.0,81655.0,11844.0,22680.0,21994.0,16513.0,270970.0,6454.0,11438.0,9058.0,315.0 -03 Jan,459620.0,84595.0,11998.0,23254.0,22631.0,16933.0,272496.0,6587.0,11662.0,9142.0,322.0 -04 Jan,470281.0,89691.0,12208.0,24367.0,23786.0,17731.0,273910.0,6867.0,12145.0,9247.0,329.0 -05 Jan,491057.0,98840.0,12663.0,26607.0,26159.0,19257.0,277039.0,7399.0,13055.0,9674.0,364.0 -06 Jan,525140.0,111300.0,15330.0,29645.0,29190.0,21546.0,284669.0,8232.0,14231.0,10584.0,413.0 -07 Jan,606270.0,129108.0,24969.0,34349.0,33663.0,25039.0,319340.0,9611.0,16128.0,13573.0,490.0 -08 Jan,701400.0,148358.0,37758.0,39333.0,38570.0,28651.0,360934.0,11172.0,18375.0,17619.0,630.0 -09 Jan,784840.0,165515.0,48405.0,43827.0,42861.0,31780.0,398377.0,12607.0,20475.0,20300.0,693.0 -10 Jan,827106.0,176869.0,52969.0,46417.0,45535.0,33467.0,415352.0,13328.0,21483.0,20965.0,721.0 -11 Jan,870968.0,193228.0,56553.0,50232.0,49448.0,35987.0,423738.0,14182.0,23240.0,23562.0,798.0 -12 Jan,944013.0,213360.0,63952.0,55097.0,54383.0,39102.0,448819.0,15400.0,25305.0,27636.0,959.0 -13 Jan,1043238.0,235487.0,80297.0,60445.0,59780.0,42728.0,487585.0,16947.0,27503.0,31297.0,1169.0 -14 Jan,1150345.0,259658.0,99036.0,66339.0,65653.0,46865.0,527044.0,18802.0,30093.0,35462.0,1393.0 -15 Jan,1279306.0,286678.0,121380.0,72919.0,72324.0,51604.0,576751.0,20944.0,33712.0,41279.0,1715.0 -16 Jan,1404431.0,310310.0,139699.0,78638.0,78015.0,55643.0,635873.0,22792.0,36610.0,44940.0,1911.0 -17 Jan,1469013.0,327285.0,147371.0,82474.0,81900.0,58359.0,661010.0,23947.0,38339.0,46333.0,1995.0 -18 Jan,1529465.0,347067.0,155617.0,86842.0,86429.0,61446.0,675143.0,25221.0,40334.0,49161.0,2205.0 -19 Jan,1650222.0,369327.0,190547.0,91882.0,91483.0,65212.0,716975.0,27055.0,43484.0,51765.0,2492.0 -20 Jan,1790243.0,394149.0,236726.0,97517.0,96894.0,69307.0,761600.0,29302.0,47824.0,54138.0,2786.0 -21 Jan,1935514.0,419328.0,289695.0,103285.0,102795.0,73570.0,800485.0,31969.0,53620.0,57575.0,3192.0 -22 Jan,2135567.0,447342.0,373639.0,109823.0,109536.0,78743.0,851417.0,35756.0,61894.0,63609.0,3808.0 -23 Jan,2334647.0,470344.0,479353.0,115157.0,114821.0,82950.0,893053.0,39011.0,70539.0,65233.0,4186.0 -24 Jan,2413404.0,484127.0,516418.0,118377.0,118041.0,85610.0,904995.0,40915.0,74725.0,65884.0,4312.0 -25 Jan,2490222.0,500808.0,547834.0,122227.0,121870.0,88340.0,917021.0,42756.0,78547.0,66360.0,4459.0 -26 Jan,2589104.0,520121.0,592081.0,126504.0,126203.0,91609.0,931497.0,45052.0,84329.0,66976.0,4732.0 -27 Jan,2685620.0,538090.0,637161.0,130578.0,130431.0,94794.0,943362.0,47768.0,90909.0,67480.0,5047.0 -28 Jan,2825214.0,556577.0,714847.0,134806.0,134736.0,98147.0,958489.0,51499.0,102704.0,68019.0,5390.0 -29 Jan,3012576.0,576338.0,834204.0,139636.0,139293.0,102221.0,974162.0,56056.0,116256.0,68670.0,5740.0 -30 Jan,3201695.0,592361.0,963627.0,143570.0,143080.0,105448.0,985320.0,59724.0,133693.0,68943.0,5929.0 -31 Jan,3314185.0,604653.0,1037505.0,146356.0,145880.0,107842.0,989667.0,63497.0,143724.0,69041.0,6020.0 -01 Feb,3417064.0,616091.0,1098916.0,149016.0,148470.0,110124.0,995358.0,69195.0,154350.0,69342.0,6202.0 -02 Feb,3535798.0,628278.0,1170232.0,152019.0,151466.0,112875.0,1001280.0,75110.0,168427.0,69650.0,6461.0 -03 Feb,3686536.0,641655.0,1261918.0,155400.0,154581.0,116032.0,1007286.0,83195.0,189497.0,70133.0,6839.0 -04 Feb,3849909.0,656236.0,1357160.0,159047.0,158193.0,119623.0,1013355.0,93471.0,214851.0,70651.0,7322.0 -05 Feb,4007794.0,670418.0,1445668.0,162757.0,161651.0,123242.0,1019081.0,104832.0,241143.0,71232.0,7770.0 -06 Feb,4208785.0,682955.0,1560832.0,166320.0,164948.0,126784.0,1022973.0,121107.0,283122.0,71498.0,8246.0 -07 Feb,4310453.0,690438.0,1618533.0,168462.0,166894.0,128968.0,1024807.0,130445.0,301903.0,71610.0,8393.0 -08 Feb,4406766.0,698271.0,1667008.0,170492.0,168833.0,130991.0,1028083.0,142282.0,320194.0,71876.0,8736.0 -09 Feb,4539458.0,708078.0,1726228.0,173250.0,171297.0,134071.0,1031884.0,169645.0,343504.0,72289.0,9212.0 -10 Feb,4681586.0,719201.0,1771315.0,176750.0,174153.0,139104.0,1036532.0,213962.0,367731.0,72933.0,9905.0 -11 Feb,4849796.0,732592.0,1813735.0,181566.0,177933.0,146734.0,1040781.0,277690.0,394450.0,73605.0,10710.0 -12 Feb,5025979.0,748615.0,1849295.0,187964.0,182959.0,157542.0,1044883.0,351099.0,417732.0,74270.0,11620.0 -13 Feb,5207223.0,765954.0,1880249.0,194180.0,187915.0,169764.0,1047438.0,435953.0,438718.0,74564.0,12488.0 -14 Feb,5284216.0,775698.0,1889342.0,198450.0,191030.0,175343.0,1048390.0,472934.0,445669.0,74627.0,12733.0 -15 Feb,5365829.0,787290.0,1896895.0,202678.0,194397.0,181363.0,1049888.0,513275.0,451878.0,75012.0,13153.0 -16 Feb,5495308.0,806547.0,1903370.0,213556.0,202202.0,200508.0,1051323.0,566678.0,461573.0,75313.0,14238.0 -17 Feb,5673710.0,836108.0,1909152.0,234178.0,216062.0,232855.0,1052849.0,626416.0,474264.0,75614.0,16212.0 -18 Feb,5833499.0,866705.0,1913702.0,254107.0,229439.0,261779.0,1054249.0,672826.0,486486.0,75964.0,18242.0 -19 Feb,5963279.0,894362.0,1917132.0,269528.0,240275.0,284144.0,1055453.0,708848.0,497252.0,76328.0,19957.0 -20 Feb,6088250.0,922488.0,1920177.0,285103.0,251601.0,307069.0,1056139.0,739998.0,507822.0,76419.0,21434.0 -21 Feb,6136095.0,934661.0,1921080.0,290500.0,255955.0,315049.0,1056384.0,751898.0,512246.0,76440.0,21882.0 -22 Feb,6196687.0,948731.0,1922543.0,297143.0,261310.0,324044.0,1056930.0,768579.0,518231.0,76517.0,22659.0 -23 Feb,6313594.0,978544.0,1924769.0,313838.0,273910.0,345688.0,1057931.0,787577.0,530348.0,76692.0,24297.0 -24 Feb,6475231.0,1018654.0,1927730.0,335839.0,290353.0,380247.0,1058988.0,812875.0,546707.0,76930.0,26908.0 -25 Feb,6651099.0,1062852.0,1931041.0,359121.0,307846.0,420238.0,1060171.0,836367.0,566293.0,77133.0,30037.0 -26 Feb,6837047.0,1109815.0,1934107.0,384489.0,325934.0,465605.0,1061284.0,859474.0,585942.0,77308.0,33089.0 -27 Feb,6982703.0,1149470.0,1936137.0,404187.0,340165.0,501655.0,1061865.0,875385.0,600971.0,77371.0,35497.0 -28 Feb,7048573.0,1166571.0,1936914.0,410858.0,345611.0,522354.0,1062033.0,883820.0,606809.0,77406.0,36197.0 -01 Mar,7105000.0,1181026.0,1937754.0,416045.0,349825.0,543011.0,1062418.0,889091.0,611394.0,77504.0,36932.0 -02 Mar,7171003.0,1196412.0,1938755.0,422576.0,355173.0,568890.0,1062999.0,894684.0,616147.0,77630.0,37737.0 -03 Mar,7270774.0,1224181.0,1940036.0,434336.0,364385.0,602602.0,1063734.0,901264.0,623238.0,77763.0,39235.0 -04 Mar,7405272.0,1258670.0,1941856.0,450240.0,377769.0,649537.0,1064539.0,910623.0,632499.0,77924.0,41615.0 -05 Mar,7549507.0,1298087.0,1943984.0,470232.0,392189.0,695618.0,1065421.0,920234.0,641270.0,78099.0,44373.0 -06 Mar,7700910.0,1341543.0,1945545.0,492072.0,408226.0,743610.0,1065932.0,928830.0,650286.0,78127.0,46739.0 -07 Mar,7752633.0,1353765.0,1945909.0,499142.0,412279.0,766556.0,1066044.0,930902.0,652771.0,78134.0,47131.0 -08 Mar,7814723.0,1366470.0,1946595.0,508501.0,416367.0,794507.0,1066324.0,934276.0,655683.0,78218.0,47782.0 -09 Mar,7883442.0,1381933.0,1947372.0,522774.0,421848.0,819315.0,1066919.0,937447.0,658938.0,78302.0,48594.0 -10 Mar,7962661.0,1402198.0,1948219.0,541310.0,428757.0,844410.0,1067493.0,940415.0,662067.0,78386.0,49406.0 -11 Mar,8041593.0,1419278.0,1949024.0,564032.0,436184.0,868700.0,1067941.0,943180.0,664594.0,78449.0,50211.0 -12 Mar,8172542.0,1452759.0,1950144.0,600327.0,453677.0,901145.0,1068473.0,947464.0,668451.0,78575.0,51527.0 -13 Mar,8373134.0,1500737.0,1951285.0,660212.0,491442.0,942445.0,1068851.0,952910.0,673295.0,78603.0,53354.0 -14 Mar,8467046.0,1521947.0,1951705.0,691915.0,505582.0,963424.0,1068984.0,955647.0,675339.0,78610.0,53893.0 -15 Mar,8600648.0,1549366.0,1952335.0,748286.0,523845.0,986818.0,1069271.0,959161.0,678195.0,78645.0,54726.0 -16 Mar,8756664.0,1583253.0,1953035.0,811818.0,554862.0,1006845.0,1069628.0,962115.0,680687.0,78764.0,55657.0 -17 Mar,8922158.0,1620598.0,1953721.0,870044.0,601251.0,1023477.0,1069985.0,964488.0,683242.0,78848.0,56504.0 -18 Mar,9119593.0,1661681.0,1954512.0,927647.0,676060.0,1040319.0,1070426.0,967085.0,685594.0,78960.0,57309.0 -19 Mar,9334122.0,1709554.0,1955240.0,990507.0,754908.0,1058421.0,1070811.0,969381.0,688121.0,79051.0,58128.0 -20 Mar,9630705.0,1777027.0,1955954.0,1063307.0,883316.0,1078217.0,1071105.0,972433.0,691152.0,79093.0,59101.0 -21 Mar,9755354.0,1809850.0,1956241.0,1097411.0,930216.0,1086372.0,1071210.0,973308.0,692279.0,79100.0,59367.0 -22 Mar,9867235.0,1839845.0,1956654.0,1126545.0,972426.0,1093393.0,1071420.0,974393.0,693714.0,79135.0,59710.0 -23 Mar,9980005.0,1874747.0,1957144.0,1152298.0,1014510.0,1099420.0,1071700.0,975534.0,695310.0,79219.0,60123.0 -24 Mar,10091711.0,1914871.0,1957718.0,1174348.0,1053325.0,1105587.0,1072036.0,976710.0,697242.0,79324.0,60550.0 -25 Mar,10208898.0,1962912.0,1958348.0,1194375.0,1092028.0,1111229.0,1072512.0,977914.0,699125.0,79429.0,61026.0 -26 Mar,10341849.0,2022167.0,1959020.0,1215963.0,1133055.0,1117193.0,1072988.0,979097.0,701281.0,79548.0,61537.0 -27 Mar,10520951.0,2111795.0,1959804.0,1240386.0,1185247.0,1124263.0,1073366.0,980574.0,703626.0,79597.0,62293.0 -28 Mar,10614814.0,2160970.0,1960119.0,1254253.0,1210160.0,1127581.0,1073506.0,981260.0,704732.0,79618.0,62615.0 -29 Mar,10688349.0,2199001.0,1960539.0,1264704.0,1229221.0,1130577.0,1073765.0,981981.0,705915.0,79688.0,62958.0 -30 Mar,10760897.0,2240077.0,1961029.0,1273552.0,1245867.0,1133300.0,1074192.0,982793.0,707056.0,79758.0,63273.0 -31 Mar,10835531.0,2283337.0,1961624.0,1282001.0,1262758.0,1135687.0,1074549.0,983591.0,708491.0,79835.0,63658.0 -01 Apr,10885266.0,2315551.0,1962121.0,1287755.0,1270255.0,1137178.0,1074934.0,984130.0,709499.0,79891.0,63952.0 -02 Apr,10915723.0,2334731.0,1962443.0,1292270.0,1274721.0,1138046.0,1075193.0,984375.0,709940.0,79905.0,64099.0 -03 Apr,10946691.0,2353253.0,1962667.0,1297282.0,1279810.0,1139110.0,1075389.0,984634.0,710388.0,79940.0,64218.0 -04 Apr,10961167.0,2362178.0,1962758.0,1299760.0,1281917.0,1139579.0,1075445.0,984746.0,710584.0,79940.0,64260.0 -05 Apr,10968097.0,2366455.0,1962814.0,1300852.0,1282827.0,1139845.0,1075480.0,984823.0,710745.0,79947.0,64309.0 -06 Apr,10985982.0,2379062.0,1963087.0,1302504.0,1284738.0,1140398.0,1075648.0,985033.0,711144.0,79989.0,64379.0 -07 Apr,11008585.0,2394364.0,1963493.0,1304373.0,1287419.0,1141287.0,1075998.0,985355.0,711767.0,80024.0,64505.0 +07 Dec,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 +08 Dec,2226.0,714.0,42.0,259.0,252.0,161.0,539.0,56.0,203.0,0.0,0.0 +09 Dec,6706.0,2051.0,98.0,707.0,672.0,532.0,2002.0,168.0,462.0,14.0,0.0 +10 Dec,11613.0,3444.0,175.0,1085.0,1036.0,875.0,3913.0,280.0,770.0,28.0,7.0 +11 Dec,16541.0,4914.0,238.0,1484.0,1463.0,1211.0,5726.0,399.0,1064.0,35.0,7.0 +12 Dec,21035.0,6538.0,294.0,1897.0,1883.0,1477.0,7014.0,497.0,1379.0,42.0,14.0 +13 Dec,24570.0,7749.0,329.0,2198.0,2198.0,1722.0,8183.0,574.0,1554.0,49.0,14.0 +14 Dec,29638.0,9324.0,406.0,2639.0,2597.0,2016.0,10108.0,679.0,1806.0,49.0,14.0 +15 Dec,56126.0,11851.0,609.0,3353.0,3248.0,2499.0,31290.0,896.0,2254.0,112.0,14.0 +16 Dec,97783.0,14945.0,882.0,4312.0,4151.0,3129.0,66297.0,1120.0,2674.0,252.0,21.0 +17 Dec,137452.0,18613.0,1505.0,5453.0,5208.0,3969.0,97664.0,1414.0,3213.0,385.0,28.0 +18 Dec,165704.0,22141.0,2072.0,6510.0,6251.0,4746.0,117915.0,1729.0,3766.0,532.0,42.0 +19 Dec,197505.0,25172.0,2744.0,7406.0,7077.0,5467.0,142744.0,2044.0,4186.0,616.0,49.0 +20 Dec,228214.0,29253.0,3311.0,8687.0,8204.0,6384.0,164542.0,2387.0,4683.0,700.0,63.0 +21 Dec,252497.0,34342.0,3969.0,10360.0,9737.0,7511.0,177534.0,2807.0,5383.0,784.0,70.0 +22 Dec,286979.0,39011.0,4585.0,11739.0,11116.0,8498.0,201754.0,3206.0,6097.0,896.0,77.0 +23 Dec,317499.0,45220.0,5306.0,13489.0,12747.0,9793.0,218981.0,3710.0,6944.0,1218.0,91.0 +24 Dec,328160.0,48335.0,5635.0,14315.0,13573.0,10430.0,222817.0,3955.0,7350.0,1652.0,98.0 +25 Dec,328223.0,48363.0,5635.0,14322.0,13580.0,10437.0,222824.0,3962.0,7350.0,1652.0,98.0 +26 Dec,328524.0,48552.0,5642.0,14350.0,13608.0,10451.0,222831.0,3969.0,7371.0,1652.0,98.0 +27 Dec,330582.0,49609.0,5663.0,14609.0,13839.0,10626.0,223013.0,4025.0,7448.0,1652.0,98.0 +28 Dec,334306.0,51387.0,5761.0,14959.0,14252.0,10948.0,223482.0,4137.0,7630.0,1652.0,98.0 +29 Dec,351743.0,55888.0,6202.0,16037.0,15372.0,11732.0,231462.0,4466.0,8113.0,2359.0,112.0 +30 Dec,396809.0,65856.0,8309.0,18704.0,17976.0,13706.0,251307.0,5278.0,9513.0,5971.0,189.0 +31 Dec,434763.0,75593.0,10507.0,21336.0,20524.0,15540.0,265566.0,6090.0,10822.0,8512.0,273.0 +01 Jan,443296.0,78225.0,11074.0,21952.0,21217.0,16023.0,268191.0,6272.0,11130.0,8911.0,301.0 +02 Jan,452578.0,81648.0,11830.0,22701.0,22001.0,16513.0,270557.0,6454.0,11445.0,9114.0,315.0 +03 Jan,459277.0,84595.0,11977.0,23268.0,22638.0,16940.0,272076.0,6594.0,11669.0,9198.0,322.0 +04 Jan,469945.0,89691.0,12187.0,24388.0,23793.0,17731.0,273490.0,6874.0,12152.0,9310.0,329.0 +05 Jan,490693.0,98840.0,12642.0,26628.0,26166.0,19264.0,276598.0,7399.0,13062.0,9730.0,364.0 +06 Jan,524776.0,111300.0,15316.0,29666.0,29197.0,21553.0,284207.0,8239.0,14245.0,10640.0,413.0 +07 Jan,605836.0,129122.0,24941.0,34377.0,33670.0,25046.0,318822.0,9618.0,16142.0,13608.0,490.0 +08 Jan,700889.0,148365.0,37723.0,39361.0,38577.0,28651.0,360367.0,11179.0,18389.0,17647.0,630.0 +09 Jan,784259.0,165522.0,48370.0,43855.0,42868.0,31780.0,397733.0,12614.0,20496.0,20328.0,693.0 +10 Jan,826490.0,176876.0,52934.0,46438.0,45542.0,33474.0,414687.0,13328.0,21497.0,20993.0,721.0 +11 Jan,870345.0,193242.0,56518.0,50260.0,49455.0,35994.0,423052.0,14189.0,23261.0,23576.0,798.0 +12 Jan,943327.0,213381.0,63903.0,55132.0,54390.0,39116.0,448084.0,15400.0,25326.0,27636.0,959.0 +13 Jan,1042482.0,235508.0,80248.0,60480.0,59794.0,42735.0,486801.0,16947.0,27524.0,31276.0,1169.0 +14 Jan,1149582.0,259728.0,98980.0,66381.0,65674.0,46879.0,526183.0,18809.0,30121.0,35434.0,1393.0 +15 Jan,1278501.0,286776.0,121317.0,72961.0,72345.0,51625.0,575806.0,20951.0,33747.0,41258.0,1715.0 +16 Jan,1403570.0,310436.0,139622.0,78680.0,78036.0,55657.0,634858.0,22799.0,36652.0,44919.0,1911.0 +17 Jan,1468152.0,327425.0,147287.0,82516.0,81928.0,58387.0,659967.0,23961.0,38381.0,46305.0,1995.0 +18 Jan,1528583.0,347221.0,155526.0,86891.0,86457.0,61467.0,674065.0,25228.0,40383.0,49140.0,2205.0 +19 Jan,1649305.0,369509.0,190435.0,91931.0,91511.0,65240.0,715848.0,27062.0,43533.0,51744.0,2492.0 +20 Jan,1789333.0,394345.0,236621.0,97566.0,96936.0,69342.0,760438.0,29316.0,47880.0,54110.0,2779.0 +21 Jan,1934716.0,419608.0,289597.0,103348.0,102844.0,73612.0,799288.0,31983.0,53690.0,57547.0,3199.0 +22 Jan,2134895.0,447678.0,373597.0,109900.0,109599.0,78792.0,850185.0,35784.0,61971.0,63567.0,3822.0 +23 Jan,2334031.0,470722.0,479325.0,115227.0,114905.0,83006.0,891779.0,39039.0,70623.0,65205.0,4200.0 +24 Jan,2412865.0,484526.0,516432.0,118454.0,118132.0,85666.0,903707.0,40950.0,74823.0,65856.0,4319.0 +25 Jan,2489746.0,501242.0,547876.0,122311.0,121968.0,88403.0,915698.0,42798.0,78638.0,66339.0,4473.0 +26 Jan,2588768.0,520569.0,592207.0,126595.0,126308.0,91686.0,930167.0,45101.0,84434.0,66955.0,4746.0 +27 Jan,2685354.0,538594.0,637308.0,130669.0,130543.0,94878.0,941997.0,47824.0,91014.0,67473.0,5054.0 +28 Jan,2825011.0,557130.0,714994.0,134904.0,134862.0,98245.0,957082.0,51555.0,102816.0,68019.0,5404.0 +29 Jan,3012471.0,576947.0,834379.0,139741.0,139433.0,102326.0,972713.0,56119.0,116382.0,68677.0,5754.0 +30 Jan,3201611.0,592984.0,963823.0,143675.0,143227.0,105546.0,983850.0,59787.0,133826.0,68950.0,5943.0 +31 Jan,3314129.0,605290.0,1037701.0,146475.0,146034.0,107947.0,988183.0,63567.0,143850.0,69055.0,6027.0 +01 Feb,3417001.0,616735.0,1099084.0,149142.0,148631.0,110236.0,993853.0,69265.0,154476.0,69363.0,6216.0 +02 Feb,3535714.0,628936.0,1170393.0,152138.0,151627.0,112987.0,999754.0,75187.0,168546.0,69671.0,6475.0 +03 Feb,3686431.0,642327.0,1262023.0,155533.0,154756.0,116151.0,1005746.0,83272.0,189609.0,70161.0,6853.0 +04 Feb,3849783.0,656922.0,1357251.0,159180.0,158375.0,119742.0,1011787.0,93555.0,214956.0,70679.0,7336.0 +05 Feb,4007633.0,671104.0,1445731.0,162890.0,161826.0,123361.0,1017485.0,104916.0,241262.0,71274.0,7784.0 +06 Feb,4208596.0,683648.0,1560881.0,166453.0,165130.0,126910.0,1021370.0,121191.0,283220.0,71540.0,8253.0 +07 Feb,4310236.0,691138.0,1618561.0,168595.0,167076.0,129101.0,1023190.0,130536.0,301987.0,71652.0,8400.0 +08 Feb,4406549.0,698992.0,1667015.0,170625.0,169022.0,131124.0,1026452.0,142380.0,320271.0,71925.0,8743.0 +09 Feb,4539136.0,708799.0,1726186.0,173383.0,171479.0,134204.0,1030225.0,169722.0,343574.0,72345.0,9219.0 +10 Feb,4681180.0,719929.0,1771245.0,176883.0,174335.0,139237.0,1034831.0,214032.0,367787.0,72989.0,9912.0 +11 Feb,4849327.0,733320.0,1813644.0,181706.0,178115.0,146867.0,1039045.0,277739.0,394506.0,73668.0,10717.0 +12 Feb,5025447.0,749336.0,1849176.0,188097.0,183134.0,157668.0,1043133.0,351148.0,417795.0,74340.0,11620.0 +13 Feb,5206614.0,766668.0,1880102.0,194306.0,188083.0,169876.0,1045674.0,436016.0,438760.0,74634.0,12495.0 +14 Feb,5283593.0,776405.0,1889195.0,198576.0,191198.0,175462.0,1046626.0,472976.0,445718.0,74704.0,12733.0 +15 Feb,5365164.0,787990.0,1896741.0,202804.0,194565.0,181482.0,1048110.0,513303.0,451927.0,75082.0,13160.0 +16 Feb,5494594.0,807233.0,1903209.0,213675.0,202363.0,200620.0,1049545.0,566692.0,461629.0,75383.0,14245.0 +17 Feb,5672954.0,836794.0,1908991.0,234297.0,216216.0,232960.0,1051050.0,626416.0,474327.0,75684.0,16219.0 +18 Feb,5832729.0,867377.0,1913527.0,254233.0,229593.0,261884.0,1052443.0,672819.0,486570.0,76027.0,18256.0 +19 Feb,5962488.0,895020.0,1916950.0,269640.0,240422.0,284235.0,1053647.0,708841.0,497371.0,76398.0,19964.0 +20 Feb,6087438.0,923139.0,1919995.0,285215.0,251748.0,307146.0,1054333.0,739984.0,507955.0,76482.0,21441.0 +21 Feb,6135276.0,935298.0,1920905.0,290605.0,256095.0,315126.0,1054571.0,751884.0,512386.0,76510.0,21896.0 +22 Feb,6195805.0,949361.0,1922361.0,297241.0,261457.0,324114.0,1055117.0,768558.0,518343.0,76587.0,22666.0 +23 Feb,6312705.0,979139.0,1924580.0,313929.0,274050.0,345709.0,1056111.0,787549.0,530558.0,76769.0,24311.0 +24 Feb,6474321.0,1019235.0,1927548.0,335930.0,290493.0,380261.0,1057161.0,812840.0,546931.0,77000.0,26922.0 +25 Feb,6650133.0,1063405.0,1930852.0,359212.0,307986.0,420238.0,1058330.0,836325.0,566517.0,77210.0,30058.0 +26 Feb,6836039.0,1110354.0,1933918.0,384580.0,326067.0,465591.0,1059436.0,859425.0,586173.0,77378.0,33117.0 +27 Feb,6981646.0,1150002.0,1935948.0,404278.0,340284.0,501613.0,1060010.0,875322.0,601216.0,77448.0,35525.0 +28 Feb,7047502.0,1167096.0,1936725.0,410949.0,345737.0,522305.0,1060178.0,883757.0,607061.0,77476.0,36218.0 +01 Mar,7103922.0,1181551.0,1937551.0,416143.0,349944.0,542955.0,1060563.0,889028.0,611653.0,77574.0,36960.0 +02 Mar,7169911.0,1196923.0,1938559.0,422674.0,355292.0,568820.0,1061144.0,894614.0,616413.0,77707.0,37765.0 +03 Mar,7269654.0,1224692.0,1939840.0,434427.0,364497.0,602511.0,1061872.0,901194.0,623518.0,77840.0,39263.0 +04 Mar,7404103.0,1259160.0,1941653.0,450324.0,377881.0,649432.0,1062677.0,910546.0,632793.0,77994.0,41643.0 +05 Mar,7548289.0,1298563.0,1943781.0,470309.0,392294.0,695499.0,1063545.0,920164.0,641564.0,78169.0,44401.0 +06 Mar,7699671.0,1341991.0,1945335.0,492149.0,408331.0,743477.0,1064063.0,928753.0,650594.0,78204.0,46774.0 +07 Mar,7751401.0,1354185.0,1945699.0,499184.0,412370.0,766381.0,1064175.0,930825.0,653219.0,78211.0,47152.0 +08 Mar,7813463.0,1366883.0,1946385.0,508536.0,416458.0,794311.0,1064448.0,934199.0,656145.0,78295.0,47803.0 +09 Mar,7882182.0,1382339.0,1947169.0,522802.0,421939.0,819119.0,1065036.0,937363.0,659414.0,78386.0,48615.0 +10 Mar,7961366.0,1402590.0,1948009.0,541338.0,428848.0,844186.0,1065617.0,940324.0,662557.0,78470.0,49427.0 +11 Mar,8040263.0,1419663.0,1948821.0,564046.0,436268.0,868462.0,1066051.0,943089.0,665091.0,78540.0,50232.0 +12 Mar,8171212.0,1453074.0,1949941.0,600327.0,453747.0,900893.0,1066583.0,947373.0,669060.0,78659.0,51555.0 +13 Mar,8371874.0,1501038.0,1951082.0,660219.0,491512.0,942256.0,1066968.0,952826.0,673904.0,78687.0,53382.0 +14 Mar,8465744.0,1522234.0,1951502.0,691908.0,505624.0,963235.0,1067094.0,955563.0,675962.0,78701.0,53921.0 +15 Mar,8599360.0,1549660.0,1952132.0,748272.0,523887.0,986622.0,1067381.0,959077.0,678839.0,78736.0,54754.0 +16 Mar,8755362.0,1583568.0,1952825.0,811797.0,554897.0,1006642.0,1067731.0,962031.0,681331.0,78855.0,55685.0 +17 Mar,8920933.0,1620962.0,1953518.0,870009.0,601300.0,1023281.0,1068081.0,964411.0,683907.0,78939.0,56525.0 +18 Mar,9118368.0,1662052.0,1954302.0,927591.0,676109.0,1040123.0,1068515.0,967015.0,686273.0,79051.0,57337.0 +19 Mar,9332932.0,1709918.0,1955037.0,990451.0,754964.0,1058225.0,1068900.0,969311.0,688821.0,79149.0,58156.0 +20 Mar,9629487.0,1777342.0,1955744.0,1063244.0,883358.0,1078007.0,1069201.0,972356.0,691922.0,79184.0,59129.0 +21 Mar,9754115.0,1810144.0,1956031.0,1097334.0,930237.0,1086162.0,1069306.0,973238.0,693070.0,79191.0,59402.0 +22 Mar,9865996.0,1840139.0,1956437.0,1126461.0,972454.0,1093190.0,1069509.0,974323.0,694505.0,79233.0,59745.0 +23 Mar,9978745.0,1875027.0,1956927.0,1152200.0,1014531.0,1099224.0,1069796.0,975457.0,696108.0,79317.0,60158.0 +24 Mar,10090451.0,1915144.0,1957501.0,1174250.0,1053346.0,1105384.0,1070132.0,976640.0,698047.0,79422.0,60585.0 +25 Mar,10208030.0,1963325.0,1958131.0,1194333.0,1092217.0,1111040.0,1070601.0,977844.0,699944.0,79527.0,61068.0 +26 Mar,10341100.0,2022671.0,1958796.0,1215928.0,1133237.0,1117004.0,1071077.0,979013.0,702135.0,79653.0,61586.0 +27 Mar,10520643.0,2112656.0,1959573.0,1240358.0,1185471.0,1124081.0,1071448.0,980497.0,704501.0,79709.0,62349.0 +28 Mar,10614534.0,2161831.0,1959895.0,1254225.0,1210384.0,1127399.0,1071595.0,981183.0,705621.0,79730.0,62671.0 +29 Mar,10688083.0,2199876.0,1960308.0,1264669.0,1229459.0,1130395.0,1071847.0,981904.0,706811.0,79800.0,63014.0 +30 Mar,10760722.0,2241001.0,1960805.0,1273517.0,1246119.0,1133125.0,1072274.0,982716.0,707966.0,79870.0,63329.0 +31 Mar,10835580.0,2284387.0,1961414.0,1281980.0,1263024.0,1135533.0,1072638.0,983521.0,709408.0,79954.0,63721.0 +01 Apr,10885770.0,2316944.0,1961918.0,1287755.0,1270549.0,1137031.0,1073030.0,984053.0,710451.0,80017.0,64022.0 +02 Apr,10916556.0,2336376.0,1962247.0,1292284.0,1275043.0,1137906.0,1073289.0,984305.0,710892.0,80038.0,64176.0 +03 Apr,10947734.0,2355059.0,1962464.0,1297317.0,1280174.0,1138963.0,1073478.0,984564.0,711354.0,80073.0,64288.0 +04 Apr,10962329.0,2364061.0,1962555.0,1299802.0,1282295.0,1139439.0,1073534.0,984676.0,711557.0,80073.0,64337.0 +05 Apr,10969322.0,2368422.0,1962611.0,1300894.0,1283205.0,1139705.0,1073569.0,984753.0,711711.0,80073.0,64379.0 +06 Apr,10988012.0,2381624.0,1962905.0,1302581.0,1285158.0,1140286.0,1073758.0,984977.0,712131.0,80136.0,64456.0 +07 Apr,11011511.0,2397542.0,1963325.0,1304513.0,1287895.0,1141210.0,1074150.0,985313.0,712782.0,80185.0,64596.0 +08 Apr,11032413.0,2411332.0,1963850.0,1306207.0,1290485.0,1142155.0,1074444.0,985663.0,713314.0,80241.0,64722.0 +09 Apr,11057879.0,2427719.0,1964333.0,1308468.0,1294104.0,1143184.0,1074787.0,986062.0,714000.0,80332.0,64890.0 +10 Apr,11087139.0,2448131.0,1964830.0,1310659.0,1297968.0,1144031.0,1075039.0,986447.0,714637.0,80374.0,65023.0 +11 Apr,11101678.0,2459051.0,1965061.0,1311422.0,1299620.0,1144402.0,1075158.0,986594.0,714896.0,80395.0,65079.0 +12 Apr,11110281.0,2464574.0,1965327.0,1312101.0,1300747.0,1144745.0,1075298.0,986776.0,715176.0,80423.0,65114.0 +13 Apr,11126017.0,2476985.0,1965663.0,1312843.0,1301895.0,1145109.0,1075452.0,986979.0,715456.0,80472.0,65163.0 +14 Apr,11154136.0,2501954.0,1966006.0,1313536.0,1302966.0,1145431.0,1075578.0,987175.0,715757.0,80514.0,65219.0 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by ethnicity 6 groups_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by ethnicity 6 groups_tpp.csv deleted file mode 100644 index 4db9d4b..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by ethnicity 6 groups_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,Black,Mixed,Other,South Asian,Unknown,White,Black_total,Mixed_total,Other_total,South Asian_total,Unknown_total,White_total -2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,37436,15218,28294,85176,189952,1202054 -2020-12-08,0.0,0.0,7.0,21.0,35.0,182.0,37436,15218,28294,85176,189952,1202054 -2020-12-09,14.0,7.0,14.0,56.0,63.0,518.0,37436,15218,28294,85176,189952,1202054 -2020-12-10,14.0,14.0,21.0,84.0,91.0,805.0,37436,15218,28294,85176,189952,1202054 -2020-12-11,28.0,14.0,35.0,119.0,140.0,1134.0,37436,15218,28294,85176,189952,1202054 -2020-12-12,28.0,21.0,42.0,147.0,175.0,1463.0,37436,15218,28294,85176,189952,1202054 -2020-12-13,35.0,28.0,49.0,182.0,203.0,1701.0,37436,15218,28294,85176,189952,1202054 -2020-12-14,42.0,28.0,56.0,224.0,266.0,1981.0,37436,15218,28294,85176,189952,1202054 -2020-12-15,63.0,35.0,70.0,280.0,315.0,2492.0,37436,15218,28294,85176,189952,1202054 -2020-12-16,70.0,49.0,84.0,357.0,392.0,3199.0,37436,15218,28294,85176,189952,1202054 -2020-12-17,91.0,56.0,105.0,448.0,490.0,4018.0,37436,15218,28294,85176,189952,1202054 -2020-12-18,112.0,70.0,126.0,560.0,581.0,4809.0,37436,15218,28294,85176,189952,1202054 -2020-12-19,133.0,77.0,147.0,637.0,644.0,5439.0,37436,15218,28294,85176,189952,1202054 -2020-12-20,154.0,91.0,161.0,735.0,763.0,6307.0,37436,15218,28294,85176,189952,1202054 -2020-12-21,168.0,98.0,189.0,875.0,917.0,7483.0,37436,15218,28294,85176,189952,1202054 -2020-12-22,189.0,105.0,224.0,1015.0,1050.0,8533.0,37436,15218,28294,85176,189952,1202054 -2020-12-23,210.0,126.0,266.0,1190.0,1211.0,9744.0,37436,15218,28294,85176,189952,1202054 -2020-12-24,224.0,133.0,287.0,1288.0,1288.0,10339.0,37436,15218,28294,85176,189952,1202054 -2020-12-25,224.0,140.0,287.0,1295.0,1295.0,10339.0,37436,15218,28294,85176,189952,1202054 -2020-12-26,224.0,140.0,294.0,1302.0,1295.0,10360.0,37436,15218,28294,85176,189952,1202054 -2020-12-27,231.0,140.0,301.0,1316.0,1316.0,10528.0,37436,15218,28294,85176,189952,1202054 -2020-12-28,238.0,147.0,308.0,1358.0,1344.0,10850.0,37436,15218,28294,85176,189952,1202054 -2020-12-29,259.0,168.0,343.0,1477.0,1449.0,11669.0,37436,15218,28294,85176,189952,1202054 -2020-12-30,294.0,196.0,399.0,1701.0,1645.0,13727.0,37436,15218,28294,85176,189952,1202054 -2020-12-31,336.0,224.0,455.0,1897.0,1876.0,15729.0,37436,15218,28294,85176,189952,1202054 -2021-01-01,343.0,224.0,483.0,1946.0,1939.0,16275.0,37436,15218,28294,85176,189952,1202054 -2021-01-02,357.0,231.0,490.0,1995.0,2002.0,16919.0,37436,15218,28294,85176,189952,1202054 -2021-01-03,364.0,238.0,497.0,2037.0,2058.0,17430.0,37436,15218,28294,85176,189952,1202054 -2021-01-04,385.0,252.0,518.0,2128.0,2135.0,18361.0,37436,15218,28294,85176,189952,1202054 -2021-01-05,434.0,280.0,588.0,2331.0,2338.0,20195.0,37436,15218,28294,85176,189952,1202054 -2021-01-06,511.0,315.0,630.0,2534.0,2618.0,22582.0,37436,15218,28294,85176,189952,1202054 -2021-01-07,581.0,343.0,721.0,2835.0,3045.0,26131.0,37436,15218,28294,85176,189952,1202054 -2021-01-08,665.0,392.0,819.0,3164.0,3500.0,30037.0,37436,15218,28294,85176,189952,1202054 -2021-01-09,721.0,427.0,889.0,3451.0,3892.0,33481.0,37436,15218,28294,85176,189952,1202054 -2021-01-10,770.0,455.0,938.0,3598.0,4123.0,35651.0,37436,15218,28294,85176,189952,1202054 -2021-01-11,840.0,483.0,1015.0,3822.0,4494.0,38794.0,37436,15218,28294,85176,189952,1202054 -2021-01-12,938.0,518.0,1085.0,4074.0,4977.0,42784.0,37436,15218,28294,85176,189952,1202054 -2021-01-13,1057.0,574.0,1183.0,4326.0,5488.0,47145.0,37436,15218,28294,85176,189952,1202054 -2021-01-14,1176.0,637.0,1281.0,4634.0,6006.0,51905.0,37436,15218,28294,85176,189952,1202054 -2021-01-15,1323.0,693.0,1358.0,4942.0,6587.0,57414.0,37436,15218,28294,85176,189952,1202054 -2021-01-16,1428.0,742.0,1428.0,5250.0,7119.0,62048.0,37436,15218,28294,85176,189952,1202054 -2021-01-17,1512.0,784.0,1470.0,5432.0,7476.0,65219.0,37436,15218,28294,85176,189952,1202054 -2021-01-18,1617.0,833.0,1519.0,5642.0,7903.0,68915.0,37436,15218,28294,85176,189952,1202054 -2021-01-19,1750.0,889.0,1596.0,5845.0,8358.0,73045.0,37436,15218,28294,85176,189952,1202054 -2021-01-20,1876.0,938.0,1680.0,6111.0,8792.0,77490.0,37436,15218,28294,85176,189952,1202054 -2021-01-21,2051.0,1015.0,1743.0,6412.0,9317.0,82257.0,37436,15218,28294,85176,189952,1202054 -2021-01-22,2240.0,1085.0,1827.0,6720.0,9933.0,87731.0,37436,15218,28294,85176,189952,1202054 -2021-01-23,2366.0,1134.0,1890.0,6951.0,10381.0,92099.0,37436,15218,28294,85176,189952,1202054 -2021-01-24,2443.0,1162.0,1925.0,7098.0,10661.0,94752.0,37436,15218,28294,85176,189952,1202054 -2021-01-25,2562.0,1197.0,1974.0,7273.0,11018.0,97846.0,37436,15218,28294,85176,189952,1202054 -2021-01-26,2702.0,1246.0,2023.0,7462.0,11424.0,101353.0,37436,15218,28294,85176,189952,1202054 -2021-01-27,2842.0,1288.0,2072.0,7665.0,11788.0,104769.0,37436,15218,28294,85176,189952,1202054 -2021-01-28,2989.0,1337.0,2128.0,7868.0,12173.0,108234.0,37436,15218,28294,85176,189952,1202054 -2021-01-29,3122.0,1379.0,2184.0,8078.0,12607.0,111923.0,37436,15218,28294,85176,189952,1202054 -2021-01-30,3213.0,1414.0,2226.0,8260.0,12936.0,115031.0,37436,15218,28294,85176,189952,1202054 -2021-01-31,3297.0,1449.0,2254.0,8407.0,13174.0,117299.0,37436,15218,28294,85176,189952,1202054 -2021-02-01,3360.0,1470.0,2289.0,8547.0,13405.0,119399.0,37436,15218,28294,85176,189952,1202054 -2021-02-02,3444.0,1498.0,2331.0,8729.0,13678.0,121779.0,37436,15218,28294,85176,189952,1202054 -2021-02-03,3556.0,1526.0,2380.0,8932.0,13902.0,124285.0,37436,15218,28294,85176,189952,1202054 -2021-02-04,3675.0,1575.0,2422.0,9170.0,14196.0,127148.0,37436,15218,28294,85176,189952,1202054 -2021-02-05,3787.0,1610.0,2485.0,9373.0,14511.0,129885.0,37436,15218,28294,85176,189952,1202054 -2021-02-06,3864.0,1645.0,2513.0,9604.0,14784.0,132531.0,37436,15218,28294,85176,189952,1202054 -2021-02-07,3913.0,1673.0,2541.0,9751.0,14931.0,134078.0,37436,15218,28294,85176,189952,1202054 -2021-02-08,4004.0,1694.0,2562.0,9905.0,15106.0,135562.0,37436,15218,28294,85176,189952,1202054 -2021-02-09,4109.0,1722.0,2590.0,10066.0,15316.0,137487.0,37436,15218,28294,85176,189952,1202054 -2021-02-10,4200.0,1764.0,2639.0,10311.0,15547.0,139685.0,37436,15218,28294,85176,189952,1202054 -2021-02-11,4319.0,1820.0,2688.0,10612.0,15806.0,142688.0,37436,15218,28294,85176,189952,1202054 -2021-02-12,4501.0,1883.0,2772.0,10969.0,16142.0,146685.0,37436,15218,28294,85176,189952,1202054 -2021-02-13,4606.0,1925.0,2835.0,11354.0,16471.0,150724.0,37436,15218,28294,85176,189952,1202054 -2021-02-14,4669.0,1960.0,2877.0,11613.0,16702.0,153202.0,37436,15218,28294,85176,189952,1202054 -2021-02-15,4760.0,1988.0,2926.0,11942.0,16940.0,155834.0,37436,15218,28294,85176,189952,1202054 -2021-02-16,4921.0,2072.0,3017.0,12523.0,17444.0,162225.0,37436,15218,28294,85176,189952,1202054 -2021-02-17,5145.0,2156.0,3157.0,13321.0,18249.0,174027.0,37436,15218,28294,85176,189952,1202054 -2021-02-18,5362.0,2275.0,3290.0,14105.0,19075.0,185332.0,37436,15218,28294,85176,189952,1202054 -2021-02-19,5537.0,2352.0,3402.0,14833.0,19726.0,194418.0,37436,15218,28294,85176,189952,1202054 -2021-02-20,5663.0,2436.0,3521.0,15428.0,20503.0,204050.0,37436,15218,28294,85176,189952,1202054 -2021-02-21,5747.0,2464.0,3584.0,15785.0,20769.0,207599.0,37436,15218,28294,85176,189952,1202054 -2021-02-22,5873.0,2520.0,3654.0,16247.0,21112.0,211911.0,37436,15218,28294,85176,189952,1202054 -2021-02-23,6062.0,2590.0,3801.0,16898.0,21938.0,222628.0,37436,15218,28294,85176,189952,1202054 -2021-02-24,6293.0,2681.0,3955.0,17808.0,22995.0,236628.0,37436,15218,28294,85176,189952,1202054 -2021-02-25,6559.0,2800.0,4179.0,18963.0,24010.0,251335.0,37436,15218,28294,85176,189952,1202054 -2021-02-26,6853.0,2954.0,4389.0,19964.0,25221.0,266553.0,37436,15218,28294,85176,189952,1202054 -2021-02-27,7077.0,3066.0,4571.0,20783.0,26194.0,278474.0,37436,15218,28294,85176,189952,1202054 -2021-02-28,7203.0,3129.0,4641.0,21238.0,26600.0,282800.0,37436,15218,28294,85176,189952,1202054 -2021-03-01,7266.0,3171.0,4704.0,21476.0,26957.0,286251.0,37436,15218,28294,85176,189952,1202054 -2021-03-02,7385.0,3234.0,4837.0,21812.0,27335.0,290563.0,37436,15218,28294,85176,189952,1202054 -2021-03-03,7553.0,3325.0,4970.0,22428.0,27958.0,298158.0,37436,15218,28294,85176,189952,1202054 -2021-03-04,7777.0,3444.0,5103.0,23296.0,28896.0,309253.0,37436,15218,28294,85176,189952,1202054 -2021-03-05,8036.0,3577.0,5278.0,24213.0,29932.0,321153.0,37436,15218,28294,85176,189952,1202054 -2021-03-06,8337.0,3724.0,5523.0,25123.0,31108.0,334411.0,37436,15218,28294,85176,189952,1202054 -2021-03-07,8421.0,3759.0,5572.0,25466.0,31353.0,337701.0,37436,15218,28294,85176,189952,1202054 -2021-03-08,8512.0,3794.0,5628.0,25774.0,31647.0,341005.0,37436,15218,28294,85176,189952,1202054 -2021-03-09,8652.0,3843.0,5712.0,26257.0,31997.0,345380.0,37436,15218,28294,85176,189952,1202054 -2021-03-10,8813.0,3913.0,5817.0,26719.0,32543.0,350952.0,37436,15218,28294,85176,189952,1202054 -2021-03-11,8988.0,3997.0,5957.0,27202.0,33124.0,356909.0,37436,15218,28294,85176,189952,1202054 -2021-03-12,9359.0,4151.0,6223.0,28266.0,34797.0,370874.0,37436,15218,28294,85176,189952,1202054 -2021-03-13,9828.0,4410.0,6622.0,29806.0,38493.0,402290.0,37436,15218,28294,85176,189952,1202054 -2021-03-14,10059.0,4522.0,6839.0,30583.0,39795.0,413784.0,37436,15218,28294,85176,189952,1202054 -2021-03-15,10325.0,4648.0,7091.0,31696.0,41426.0,428645.0,37436,15218,28294,85176,189952,1202054 -2021-03-16,10675.0,4851.0,7420.0,32928.0,44618.0,454370.0,37436,15218,28294,85176,189952,1202054 -2021-03-17,11235.0,5166.0,8008.0,35105.0,49882.0,491841.0,37436,15218,28294,85176,189952,1202054 -2021-03-18,12033.0,5642.0,8904.0,37513.0,59017.0,552937.0,37436,15218,28294,85176,189952,1202054 -2021-03-19,12950.0,6209.0,9968.0,40313.0,68236.0,617239.0,37436,15218,28294,85176,189952,1202054 -2021-03-20,14287.0,7070.0,11410.0,43890.0,84588.0,722078.0,37436,15218,28294,85176,189952,1202054 -2021-03-21,14826.0,7364.0,12026.0,45367.0,90706.0,759920.0,37436,15218,28294,85176,189952,1202054 -2021-03-22,15477.0,7700.0,12677.0,46998.0,96264.0,793303.0,37436,15218,28294,85176,189952,1202054 -2021-03-23,16058.0,8008.0,13377.0,48762.0,101857.0,826455.0,37436,15218,28294,85176,189952,1202054 -2021-03-24,16653.0,8295.0,13986.0,50596.0,107177.0,856611.0,37436,15218,28294,85176,189952,1202054 -2021-03-25,17332.0,8603.0,14637.0,52423.0,112455.0,886571.0,37436,15218,28294,85176,189952,1202054 -2021-03-26,18067.0,8932.0,15204.0,54320.0,118090.0,918435.0,37436,15218,28294,85176,189952,1202054 -2021-03-27,19047.0,9317.0,15946.0,56735.0,125447.0,958755.0,37436,15218,28294,85176,189952,1202054 -2021-03-28,19453.0,9485.0,16338.0,57792.0,129311.0,977774.0,37436,15218,28294,85176,189952,1202054 -2021-03-29,19817.0,9639.0,16758.0,58779.0,132202.0,992026.0,37436,15218,28294,85176,189952,1202054 -2021-03-30,20160.0,9772.0,17094.0,59563.0,134708.0,1004570.0,37436,15218,28294,85176,189952,1202054 -2021-03-31,20559.0,9926.0,17409.0,60452.0,137242.0,1017163.0,37436,15218,28294,85176,189952,1202054 -2021-04-01,20804.0,9989.0,17549.0,60949.0,138271.0,1022686.0,37436,15218,28294,85176,189952,1202054 -2021-04-02,20930.0,10031.0,17619.0,61208.0,139006.0,1025927.0,37436,15218,28294,85176,189952,1202054 -2021-04-03,21070.0,10066.0,17717.0,61516.0,139699.0,1029735.0,37436,15218,28294,85176,189952,1202054 -2021-04-04,21140.0,10087.0,17752.0,61684.0,140007.0,1031240.0,37436,15218,28294,85176,189952,1202054 -2021-04-05,21168.0,10094.0,17794.0,61761.0,140126.0,1031870.0,37436,15218,28294,85176,189952,1202054 -2021-04-06,21238.0,10122.0,17857.0,61964.0,140350.0,1033193.0,37436,15218,28294,85176,189952,1202054 -2021-04-07,21329.0,10164.0,17920.0,62286.0,140679.0,1035027.0,37436,15218,28294,85176,189952,1202054 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by imd categories_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by imd categories_tpp.csv deleted file mode 100644 index df5bfac..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by imd categories_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,1 Most deprived,2,3,4,5 Least deprived,Unknown,1 Most deprived_total,2_total,3_total,4_total,5 Least deprived_total,Unknown_total -2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,272230,291816,326585,324597,311731,31178 -2020-12-08,35.0,42.0,49.0,63.0,63.0,0.0,272230,291816,326585,324597,311731,31178 -2020-12-09,105.0,105.0,126.0,154.0,175.0,14.0,272230,291816,326585,324597,311731,31178 -2020-12-10,147.0,168.0,196.0,238.0,266.0,21.0,272230,291816,326585,324597,311731,31178 -2020-12-11,203.0,231.0,280.0,336.0,378.0,28.0,272230,291816,326585,324597,311731,31178 -2020-12-12,245.0,301.0,385.0,448.0,469.0,35.0,272230,291816,326585,324597,311731,31178 -2020-12-13,294.0,343.0,448.0,532.0,546.0,35.0,272230,291816,326585,324597,311731,31178 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bipolar_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by psychosis schiz bipolar_tpp.csv deleted file mode 100644 index 56d6a36..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 50-54 population by psychosis schiz bipolar_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,no,yes,no_total,yes_total -2020-12-01,0.0,0.0,1538425,19712 -2020-12-08,252.0,0.0,1538425,19712 -2020-12-09,672.0,0.0,1538425,19712 -2020-12-10,1036.0,0.0,1538425,19712 -2020-12-11,1463.0,0.0,1538425,19712 -2020-12-12,1876.0,7.0,1538425,19712 -2020-12-13,2191.0,7.0,1538425,19712 -2020-12-14,2583.0,14.0,1538425,19712 -2020-12-15,3227.0,21.0,1538425,19712 -2020-12-16,4123.0,28.0,1538425,19712 -2020-12-17,5180.0,28.0,1538425,19712 -2020-12-18,6216.0,35.0,1538425,19712 -2020-12-19,7035.0,35.0,1538425,19712 -2020-12-20,8162.0,42.0,1538425,19712 -2020-12-21,9688.0,42.0,1538425,19712 -2020-12-22,11067.0,49.0,1538425,19712 -2020-12-23,12698.0,56.0,1538425,19712 -2020-12-24,13510.0,63.0,1538425,19712 -2020-12-25,13517.0,63.0,1538425,19712 -2020-12-26,13545.0,63.0,1538425,19712 -2020-12-27,13769.0,63.0,1538425,19712 -2020-12-28,14182.0,63.0,1538425,19712 -2020-12-29,15295.0,77.0,1538425,19712 -2020-12-30,17878.0,91.0,1538425,19712 -2020-12-31,20405.0,112.0,1538425,19712 -2021-01-01,21098.0,119.0,1538425,19712 -2021-01-02,21875.0,126.0,1538425,19712 -2021-01-03,22505.0,126.0,1538425,19712 -2021-01-04,23653.0,133.0,1538425,19712 -2021-01-05,26012.0,140.0,1538425,19712 -2021-01-06,29036.0,154.0,1538425,19712 -2021-01-07,33481.0,182.0,1538425,19712 -2021-01-08,38360.0,217.0,1538425,19712 -2021-01-09,42623.0,238.0,1538425,19712 -2021-01-10,45283.0,252.0,1538425,19712 -2021-01-11,49175.0,273.0,1538425,19712 -2021-01-12,54068.0,308.0,1538425,19712 -2021-01-13,59416.0,357.0,1538425,19712 -2021-01-14,65261.0,392.0,1538425,19712 -2021-01-15,71876.0,448.0,1538425,19712 -2021-01-16,77525.0,490.0,1538425,19712 -2021-01-17,81375.0,525.0,1538425,19712 -2021-01-18,85862.0,567.0,1538425,19712 -2021-01-19,90874.0,609.0,1538425,19712 -2021-01-20,96236.0,658.0,1538425,19712 -2021-01-21,102088.0,707.0,1538425,19712 -2021-01-22,108738.0,798.0,1538425,19712 -2021-01-23,113981.0,840.0,1538425,19712 -2021-01-24,117173.0,868.0,1538425,19712 -2021-01-25,120960.0,903.0,1538425,19712 -2021-01-26,125251.0,952.0,1538425,19712 -2021-01-27,129437.0,987.0,1538425,19712 -2021-01-28,133700.0,1036.0,1538425,19712 -2021-01-29,138208.0,1078.0,1538425,19712 -2021-01-30,141960.0,1113.0,1538425,19712 -2021-01-31,144746.0,1127.0,1538425,19712 -2021-02-01,147308.0,1155.0,1538425,19712 -2021-02-02,150283.0,1183.0,1538425,19712 -2021-02-03,153363.0,1218.0,1538425,19712 -2021-02-04,156933.0,1260.0,1538425,19712 -2021-02-05,160349.0,1295.0,1538425,19712 -2021-02-06,163618.0,1330.0,1538425,19712 -2021-02-07,165543.0,1344.0,1538425,19712 -2021-02-08,167468.0,1365.0,1538425,19712 -2021-02-09,169890.0,1400.0,1538425,19712 -2021-02-10,172711.0,1442.0,1538425,19712 -2021-02-11,176421.0,1512.0,1538425,19712 -2021-02-12,181328.0,1624.0,1538425,19712 -2021-02-13,186207.0,1708.0,1538425,19712 -2021-02-14,189280.0,1757.0,1538425,19712 -2021-02-15,192577.0,1820.0,1538425,19712 -2021-02-16,200144.0,2058.0,1538425,19712 -2021-02-17,213514.0,2541.0,1538425,19712 -2021-02-18,226422.0,3024.0,1538425,19712 -2021-02-19,236887.0,3388.0,1538425,19712 -2021-02-20,247835.0,3766.0,1538425,19712 -2021-02-21,252070.0,3885.0,1538425,19712 -2021-02-22,257285.0,4025.0,1538425,19712 -2021-02-23,269416.0,4494.0,1538425,19712 -2021-02-24,285257.0,5096.0,1538425,19712 -2021-02-25,302064.0,5789.0,1538425,19712 -2021-02-26,319522.0,6412.0,1538425,19712 -2021-02-27,333263.0,6902.0,1538425,19712 -2021-02-28,338569.0,7035.0,1538425,19712 -2021-03-01,342678.0,7147.0,1538425,19712 -2021-03-02,347844.0,7322.0,1538425,19712 -2021-03-03,356734.0,7651.0,1538425,19712 -2021-03-04,369670.0,8099.0,1538425,19712 -2021-03-05,383565.0,8624.0,1538425,19712 -2021-03-06,399063.0,9163.0,1538425,19712 -2021-03-07,403011.0,9268.0,1538425,19712 -2021-03-08,406973.0,9387.0,1538425,19712 -2021-03-09,412300.0,9548.0,1538425,19712 -2021-03-10,418999.0,9758.0,1538425,19712 -2021-03-11,426258.0,9926.0,1538425,19712 -2021-03-12,443450.0,10227.0,1538425,19712 -2021-03-13,480774.0,10668.0,1538425,19712 -2021-03-14,494760.0,10822.0,1538425,19712 -2021-03-15,512764.0,11081.0,1538425,19712 -2021-03-16,543459.0,11396.0,1538425,19712 -2021-03-17,589561.0,11690.0,1538425,19712 -2021-03-18,664048.0,12005.0,1538425,19712 -2021-03-19,742602.0,12306.0,1538425,19712 -2021-03-20,870555.0,12761.0,1538425,19712 -2021-03-21,917315.0,12901.0,1538425,19712 -2021-03-22,959364.0,13055.0,1538425,19712 -2021-03-23,1001266.0,13237.0,1538425,19712 -2021-03-24,1039913.0,13405.0,1538425,19712 -2021-03-25,1078434.0,13587.0,1538425,19712 -2021-03-26,1119279.0,13769.0,1538425,19712 -2021-03-27,1171247.0,13993.0,1538425,19712 -2021-03-28,1196062.0,14091.0,1538425,19712 -2021-03-29,1215018.0,14203.0,1538425,19712 -2021-03-30,1231552.0,14315.0,1538425,19712 -2021-03-31,1248324.0,14427.0,1538425,19712 -2021-04-01,1255744.0,14504.0,1538425,19712 -2021-04-02,1260175.0,14539.0,1538425,19712 -2021-04-03,1265229.0,14574.0,1538425,19712 -2021-04-04,1267322.0,14588.0,1538425,19712 -2021-04-05,1268225.0,14595.0,1538425,19712 -2021-04-06,1270108.0,14616.0,1538425,19712 -2021-04-07,1272761.0,14651.0,1538425,19712 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 55-59 population by ethnicity 6 groups_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 55-59 population by ethnicity 6 groups_tpp.csv deleted file mode 100644 index 1f33494..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 55-59 population by ethnicity 6 groups_tpp.csv +++ /dev/null @@ -1,124 +0,0 @@ -covid_vacc_date,Black,Mixed,Other,South Asian,Unknown,White,Black_total,Mixed_total,Other_total,South Asian_total,Unknown_total,White_total -2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,30877,12236,22022,59759,171458,1211903 -2020-12-06,0.0,0.0,0.0,0.0,0.0,0.0,30877,12236,22022,59759,171458,1211903 -2020-12-08,0.0,0.0,0.0,14.0,28.0,210.0,30877,12236,22022,59759,171458,1211903 -2020-12-09,7.0,14.0,0.0,28.0,63.0,588.0,30877,12236,22022,59759,171458,1211903 -2020-12-10,14.0,14.0,7.0,56.0,98.0,896.0,30877,12236,22022,59759,171458,1211903 -2020-12-11,14.0,14.0,14.0,77.0,133.0,1225.0,30877,12236,22022,59759,171458,1211903 -2020-12-12,28.0,14.0,21.0,98.0,182.0,1561.0,30877,12236,22022,59759,171458,1211903 -2020-12-13,35.0,21.0,28.0,119.0,203.0,1799.0,30877,12236,22022,59759,171458,1211903 -2020-12-14,35.0,21.0,35.0,154.0,238.0,2149.0,30877,12236,22022,59759,171458,1211903 -2020-12-15,49.0,28.0,42.0,203.0,308.0,2716.0,30877,12236,22022,59759,171458,1211903 -2020-12-16,63.0,35.0,49.0,252.0,392.0,3514.0,30877,12236,22022,59759,171458,1211903 -2020-12-17,84.0,42.0,77.0,329.0,490.0,4438.0,30877,12236,22022,59759,171458,1211903 -2020-12-18,91.0,56.0,84.0,399.0,581.0,5292.0,30877,12236,22022,59759,171458,1211903 -2020-12-19,98.0,63.0,91.0,462.0,658.0,6034.0,30877,12236,22022,59759,171458,1211903 -2020-12-20,112.0,77.0,112.0,567.0,770.0,7042.0,30877,12236,22022,59759,171458,1211903 -2020-12-21,133.0,84.0,133.0,637.0,903.0,8456.0,30877,12236,22022,59759,171458,1211903 -2020-12-22,147.0,98.0,147.0,735.0,1029.0,9569.0,30877,12236,22022,59759,171458,1211903 -2020-12-23,182.0,119.0,168.0,840.0,1204.0,10969.0,30877,12236,22022,59759,171458,1211903 -2020-12-24,196.0,126.0,189.0,889.0,1295.0,11613.0,30877,12236,22022,59759,171458,1211903 -2020-12-25,196.0,126.0,189.0,889.0,1295.0,11613.0,30877,12236,22022,59759,171458,1211903 -2020-12-26,196.0,126.0,189.0,889.0,1295.0,11634.0,30877,12236,22022,59759,171458,1211903 -2020-12-27,196.0,133.0,189.0,903.0,1316.0,11858.0,30877,12236,22022,59759,171458,1211903 -2020-12-28,203.0,133.0,196.0,924.0,1344.0,12145.0,30877,12236,22022,59759,171458,1211903 -2020-12-29,217.0,140.0,210.0,980.0,1428.0,13048.0,30877,12236,22022,59759,171458,1211903 -2020-12-30,266.0,161.0,245.0,1141.0,1680.0,15197.0,30877,12236,22022,59759,171458,1211903 -2020-12-31,301.0,175.0,287.0,1288.0,1904.0,17360.0,30877,12236,22022,59759,171458,1211903 -2021-01-01,315.0,182.0,294.0,1309.0,1960.0,17871.0,30877,12236,22022,59759,171458,1211903 -2021-01-02,329.0,189.0,308.0,1351.0,2009.0,18501.0,30877,12236,22022,59759,171458,1211903 -2021-01-03,336.0,189.0,308.0,1386.0,2058.0,18970.0,30877,12236,22022,59759,171458,1211903 -2021-01-04,364.0,203.0,329.0,1435.0,2149.0,19887.0,30877,12236,22022,59759,171458,1211903 -2021-01-05,399.0,217.0,350.0,1547.0,2324.0,21777.0,30877,12236,22022,59759,171458,1211903 -2021-01-06,448.0,245.0,385.0,1673.0,2583.0,24311.0,30877,12236,22022,59759,171458,1211903 -2021-01-07,532.0,273.0,441.0,1862.0,2975.0,28266.0,30877,12236,22022,59759,171458,1211903 -2021-01-08,616.0,308.0,504.0,2093.0,3395.0,32424.0,30877,12236,22022,59759,171458,1211903 -2021-01-09,672.0,343.0,546.0,2247.0,3808.0,36204.0,30877,12236,22022,59759,171458,1211903 -2021-01-10,707.0,357.0,574.0,2359.0,4025.0,38395.0,30877,12236,22022,59759,171458,1211903 -2021-01-11,763.0,392.0,609.0,2478.0,4340.0,41650.0,30877,12236,22022,59759,171458,1211903 -2021-01-12,840.0,427.0,665.0,2625.0,4739.0,45801.0,30877,12236,22022,59759,171458,1211903 -2021-01-13,938.0,469.0,721.0,2807.0,5222.0,50295.0,30877,12236,22022,59759,171458,1211903 -2021-01-14,1043.0,497.0,770.0,3017.0,5719.0,55293.0,30877,12236,22022,59759,171458,1211903 -2021-01-15,1162.0,546.0,833.0,3220.0,6272.0,60886.0,30877,12236,22022,59759,171458,1211903 -2021-01-16,1260.0,581.0,882.0,3437.0,6825.0,65660.0,30877,12236,22022,59759,171458,1211903 -2021-01-17,1330.0,609.0,917.0,3549.0,7161.0,68901.0,30877,12236,22022,59759,171458,1211903 -2021-01-18,1421.0,644.0,959.0,3696.0,7560.0,72562.0,30877,12236,22022,59759,171458,1211903 -2021-01-19,1533.0,686.0,1015.0,3864.0,8001.0,76776.0,30877,12236,22022,59759,171458,1211903 -2021-01-20,1645.0,735.0,1064.0,4095.0,8435.0,81543.0,30877,12236,22022,59759,171458,1211903 -2021-01-21,1778.0,784.0,1113.0,4263.0,8897.0,86443.0,30877,12236,22022,59759,171458,1211903 -2021-01-22,1925.0,833.0,1183.0,4487.0,9401.0,92001.0,30877,12236,22022,59759,171458,1211903 -2021-01-23,2016.0,889.0,1232.0,4662.0,9821.0,96537.0,30877,12236,22022,59759,171458,1211903 -2021-01-24,2093.0,910.0,1260.0,4753.0,10087.0,99274.0,30877,12236,22022,59759,171458,1211903 -2021-01-25,2177.0,945.0,1302.0,4872.0,10409.0,102529.0,30877,12236,22022,59759,171458,1211903 -2021-01-26,2275.0,980.0,1344.0,5040.0,10773.0,106092.0,30877,12236,22022,59759,171458,1211903 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-2021-04-06,18690.0,8638.0,14833.0,46627.0,131978.0,1081731.0,30877,12236,22022,59759,171458,1211903 -2021-04-07,18753.0,8652.0,14882.0,46739.0,132216.0,1083124.0,30877,12236,22022,59759,171458,1211903 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 55-59 population by imd categories_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 55-59 population by imd categories_tpp.csv deleted file mode 100644 index e52f0c3..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 55-59 population by imd categories_tpp.csv +++ /dev/null @@ -1,124 +0,0 @@ -covid_vacc_date,1 Most deprived,2,3,4,5 Least deprived,Unknown,1 Most deprived_total,2_total,3_total,4_total,5 Least deprived_total,Unknown_total -2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,245343,275730,323015,324184,310065,29918 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psychosis schiz bipolar_tpp.csv +++ /dev/null @@ -1,124 +0,0 @@ -covid_vacc_date,no,yes,no_total,yes_total -2020-12-01,0.0,0.0,1489509,18753 -2020-12-06,0.0,0.0,1489509,18753 -2020-12-08,259.0,0.0,1489509,18753 -2020-12-09,700.0,0.0,1489509,18753 -2020-12-10,1085.0,0.0,1489509,18753 -2020-12-11,1477.0,0.0,1489509,18753 -2020-12-12,1890.0,7.0,1489509,18753 -2020-12-13,2191.0,14.0,1489509,18753 -2020-12-14,2625.0,14.0,1489509,18753 -2020-12-15,3339.0,14.0,1489509,18753 -2020-12-16,4291.0,21.0,1489509,18753 -2020-12-17,5425.0,21.0,1489509,18753 -2020-12-18,6482.0,21.0,1489509,18753 -2020-12-19,7378.0,21.0,1489509,18753 -2020-12-20,8659.0,28.0,1489509,18753 -2020-12-21,10311.0,35.0,1489509,18753 -2020-12-22,11683.0,42.0,1489509,18753 -2020-12-23,13426.0,56.0,1489509,18753 -2020-12-24,14245.0,56.0,1489509,18753 -2020-12-25,14252.0,56.0,1489509,18753 -2020-12-26,14280.0,56.0,1489509,18753 -2020-12-27,14539.0,56.0,1489509,18753 -2020-12-28,14889.0,56.0,1489509,18753 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-2021-04-01,1273272.0,14483.0,1489509,18753 -2021-04-02,1277745.0,14518.0,1489509,18753 -2021-04-03,1282736.0,14539.0,1489509,18753 -2021-04-04,1285207.0,14546.0,1489509,18753 -2021-04-05,1286292.0,14553.0,1489509,18753 -2021-04-06,1287930.0,14567.0,1489509,18753 -2021-04-07,1289771.0,14595.0,1489509,18753 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 60-64 population by ethnicity 6 groups_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 60-64 population by ethnicity 6 groups_tpp.csv deleted file mode 100644 index 1573ebd..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 60-64 population by ethnicity 6 groups_tpp.csv +++ /dev/null @@ -1,122 +0,0 @@ -covid_vacc_date,Black,Mixed,Other,South Asian,Unknown,White,Black_total,Mixed_total,Other_total,South Asian_total,Unknown_total,White_total -2020-12-08,0.0,0.0,0.0,14.0,14.0,126.0,19530,7938,16177,52346,141351,1039206 -2020-12-09,0.0,7.0,7.0,21.0,49.0,441.0,19530,7938,16177,52346,141351,1039206 -2020-12-10,7.0,7.0,14.0,35.0,84.0,728.0,19530,7938,16177,52346,141351,1039206 -2020-12-11,14.0,14.0,14.0,56.0,112.0,1001.0,19530,7938,16177,52346,141351,1039206 -2020-12-12,14.0,14.0,21.0,63.0,140.0,1225.0,19530,7938,16177,52346,141351,1039206 -2020-12-13,21.0,21.0,21.0,84.0,161.0,1421.0,19530,7938,16177,52346,141351,1039206 -2020-12-14,21.0,21.0,21.0,98.0,196.0,1652.0,19530,7938,16177,52346,141351,1039206 -2020-12-15,28.0,28.0,35.0,119.0,245.0,2044.0,19530,7938,16177,52346,141351,1039206 -2020-12-16,35.0,35.0,49.0,140.0,301.0,2569.0,19530,7938,16177,52346,141351,1039206 -2020-12-17,42.0,42.0,56.0,175.0,385.0,3276.0,19530,7938,16177,52346,141351,1039206 -2020-12-18,56.0,42.0,63.0,224.0,455.0,3906.0,19530,7938,16177,52346,141351,1039206 -2020-12-19,63.0,42.0,70.0,266.0,525.0,4494.0,19530,7938,16177,52346,141351,1039206 -2020-12-20,70.0,49.0,84.0,308.0,616.0,5250.0,19530,7938,16177,52346,141351,1039206 -2020-12-21,84.0,56.0,91.0,371.0,707.0,6195.0,19530,7938,16177,52346,141351,1039206 -2020-12-22,98.0,70.0,112.0,434.0,798.0,6986.0,19530,7938,16177,52346,141351,1039206 -2020-12-23,112.0,77.0,126.0,518.0,903.0,8057.0,19530,7938,16177,52346,141351,1039206 -2020-12-24,119.0,77.0,133.0,553.0,973.0,8582.0,19530,7938,16177,52346,141351,1039206 -2020-12-25,119.0,77.0,133.0,553.0,973.0,8582.0,19530,7938,16177,52346,141351,1039206 -2020-12-26,119.0,77.0,133.0,553.0,973.0,8596.0,19530,7938,16177,52346,141351,1039206 -2020-12-27,119.0,77.0,140.0,553.0,980.0,8757.0,19530,7938,16177,52346,141351,1039206 -2020-12-28,119.0,84.0,140.0,560.0,1008.0,9037.0,19530,7938,16177,52346,141351,1039206 -2020-12-29,133.0,84.0,154.0,609.0,1078.0,9667.0,19530,7938,16177,52346,141351,1039206 -2020-12-30,161.0,98.0,175.0,707.0,1239.0,11319.0,19530,7938,16177,52346,141351,1039206 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-2021-01-11,441.0,252.0,406.0,1715.0,3164.0,30009.0,19530,7938,16177,52346,141351,1039206 -2021-01-12,497.0,266.0,434.0,1834.0,3444.0,32634.0,19530,7938,16177,52346,141351,1039206 -2021-01-13,546.0,294.0,462.0,1960.0,3787.0,35679.0,19530,7938,16177,52346,141351,1039206 -2021-01-14,630.0,315.0,504.0,2107.0,4158.0,39158.0,19530,7938,16177,52346,141351,1039206 -2021-01-15,693.0,350.0,546.0,2268.0,4599.0,43148.0,19530,7938,16177,52346,141351,1039206 -2021-01-16,742.0,378.0,588.0,2429.0,4956.0,46550.0,19530,7938,16177,52346,141351,1039206 -2021-01-17,791.0,392.0,602.0,2527.0,5194.0,48853.0,19530,7938,16177,52346,141351,1039206 -2021-01-18,833.0,413.0,630.0,2632.0,5446.0,51492.0,19530,7938,16177,52346,141351,1039206 -2021-01-19,889.0,441.0,665.0,2800.0,5775.0,54635.0,19530,7938,16177,52346,141351,1039206 -2021-01-20,959.0,469.0,700.0,2989.0,6097.0,58093.0,19530,7938,16177,52346,141351,1039206 -2021-01-21,1022.0,504.0,749.0,3171.0,6489.0,61635.0,19530,7938,16177,52346,141351,1039206 -2021-01-22,1113.0,546.0,791.0,3416.0,6902.0,65961.0,19530,7938,16177,52346,141351,1039206 -2021-01-23,1162.0,574.0,819.0,3584.0,7252.0,69566.0,19530,7938,16177,52346,141351,1039206 -2021-01-24,1197.0,595.0,847.0,3696.0,7469.0,71806.0,19530,7938,16177,52346,141351,1039206 -2021-01-25,1253.0,616.0,875.0,3822.0,7672.0,74109.0,19530,7938,16177,52346,141351,1039206 -2021-01-26,1316.0,637.0,903.0,3955.0,7959.0,76832.0,19530,7938,16177,52346,141351,1039206 -2021-01-27,1400.0,665.0,945.0,4123.0,8211.0,79450.0,19530,7938,16177,52346,141351,1039206 -2021-01-28,1456.0,686.0,973.0,4284.0,8456.0,82292.0,19530,7938,16177,52346,141351,1039206 -2021-01-29,1540.0,707.0,1008.0,4494.0,8785.0,85687.0,19530,7938,16177,52346,141351,1039206 -2021-01-30,1596.0,721.0,1050.0,4662.0,8988.0,88424.0,19530,7938,16177,52346,141351,1039206 -2021-01-31,1631.0,742.0,1078.0,4809.0,9191.0,90391.0,19530,7938,16177,52346,141351,1039206 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-2021-03-13,9590.0,4816.0,8967.0,36589.0,87934.0,794542.0,19530,7938,16177,52346,141351,1039206 -2021-03-14,9800.0,4900.0,9191.0,37072.0,90517.0,811944.0,19530,7938,16177,52346,141351,1039206 -2021-03-15,10052.0,5012.0,9450.0,37723.0,93380.0,831194.0,19530,7938,16177,52346,141351,1039206 -2021-03-16,10276.0,5103.0,9653.0,38157.0,96019.0,847630.0,19530,7938,16177,52346,141351,1039206 -2021-03-17,10458.0,5187.0,9842.0,38661.0,98196.0,861133.0,19530,7938,16177,52346,141351,1039206 -2021-03-18,10661.0,5271.0,10017.0,39081.0,100401.0,874881.0,19530,7938,16177,52346,141351,1039206 -2021-03-19,10878.0,5383.0,10185.0,39494.0,102844.0,889630.0,19530,7938,16177,52346,141351,1039206 -2021-03-20,11130.0,5460.0,10374.0,39949.0,105406.0,905884.0,19530,7938,16177,52346,141351,1039206 -2021-03-21,11214.0,5502.0,10486.0,40173.0,106575.0,912429.0,19530,7938,16177,52346,141351,1039206 -2021-03-22,11333.0,5551.0,10598.0,40383.0,107499.0,918022.0,19530,7938,16177,52346,141351,1039206 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-2021-04-02,12376.0,5873.0,11361.0,42469.0,113575.0,952385.0,19530,7938,16177,52346,141351,1039206 -2021-04-03,12404.0,5880.0,11375.0,42525.0,113715.0,953190.0,19530,7938,16177,52346,141351,1039206 -2021-04-04,12425.0,5887.0,11382.0,42560.0,113778.0,953540.0,19530,7938,16177,52346,141351,1039206 -2021-04-05,12432.0,5887.0,11389.0,42588.0,113799.0,953736.0,19530,7938,16177,52346,141351,1039206 -2021-04-06,12446.0,5894.0,11403.0,42637.0,113862.0,954149.0,19530,7938,16177,52346,141351,1039206 -2021-04-07,12474.0,5901.0,11417.0,42714.0,113974.0,954793.0,19530,7938,16177,52346,141351,1039206 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 60-64 population by imd categories_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 60-64 population by imd categories_tpp.csv deleted file mode 100644 index 0bdafe4..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 60-64 population by imd categories_tpp.csv +++ /dev/null @@ -1,122 +0,0 @@ -covid_vacc_date,1 Most deprived,2,3,4,5 Least deprived,Unknown,1 Most deprived_total,2_total,3_total,4_total,5 Least deprived_total,Unknown_total -2020-12-08,28.0,28.0,28.0,42.0,28.0,0.0,198303,231392,277137,278649,265188,25886 -2020-12-09,84.0,98.0,112.0,98.0,126.0,14.0,198303,231392,277137,278649,265188,25886 -2020-12-10,133.0,154.0,182.0,168.0,217.0,21.0,198303,231392,277137,278649,265188,25886 -2020-12-11,182.0,210.0,238.0,252.0,301.0,28.0,198303,231392,277137,278649,265188,25886 -2020-12-12,210.0,252.0,301.0,322.0,357.0,35.0,198303,231392,277137,278649,265188,25886 -2020-12-13,238.0,301.0,350.0,371.0,420.0,35.0,198303,231392,277137,278649,265188,25886 -2020-12-14,266.0,357.0,413.0,448.0,490.0,42.0,198303,231392,277137,278649,265188,25886 -2020-12-15,336.0,441.0,518.0,567.0,581.0,49.0,198303,231392,277137,278649,265188,25886 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population by psychosis schiz bipolar_tpp.csv deleted file mode 100644 index 0c8686c..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 60-64 population by psychosis schiz bipolar_tpp.csv +++ /dev/null @@ -1,122 +0,0 @@ -covid_vacc_date,no,yes,no_total,yes_total -2020-12-08,161.0,0.0,1261848,14700 -2020-12-09,525.0,0.0,1261848,14700 -2020-12-10,875.0,0.0,1261848,14700 -2020-12-11,1211.0,0.0,1261848,14700 -2020-12-12,1477.0,0.0,1261848,14700 -2020-12-13,1715.0,0.0,1261848,14700 -2020-12-14,2009.0,0.0,1261848,14700 -2020-12-15,2492.0,7.0,1261848,14700 -2020-12-16,3115.0,14.0,1261848,14700 -2020-12-17,3955.0,14.0,1261848,14700 -2020-12-18,4732.0,14.0,1261848,14700 -2020-12-19,5446.0,21.0,1261848,14700 -2020-12-20,6363.0,21.0,1261848,14700 -2020-12-21,7490.0,28.0,1261848,14700 -2020-12-22,8463.0,28.0,1261848,14700 -2020-12-23,9751.0,35.0,1261848,14700 -2020-12-24,10395.0,42.0,1261848,14700 -2020-12-25,10395.0,42.0,1261848,14700 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-2021-03-31,1123633.0,12054.0,1261848,14700 -2021-04-01,1125096.0,12075.0,1261848,14700 -2021-04-02,1125950.0,12089.0,1261848,14700 -2021-04-03,1127000.0,12096.0,1261848,14700 -2021-04-04,1127462.0,12103.0,1261848,14700 -2021-04-05,1127735.0,12110.0,1261848,14700 -2021-04-06,1128274.0,12117.0,1261848,14700 -2021-04-07,1129149.0,12131.0,1261848,14700 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 65-69 population by LD_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 65-69 population by LD_tpp.csv deleted file mode 100644 index 3726c21..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 65-69 population by LD_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,no,yes,no_total,yes_total -2020-12-04,0.0,0.0,1069096,2527 -2020-12-08,56.0,0.0,1069096,2527 -2020-12-09,168.0,0.0,1069096,2527 -2020-12-10,280.0,0.0,1069096,2527 -2020-12-11,399.0,0.0,1069096,2527 -2020-12-12,497.0,0.0,1069096,2527 -2020-12-13,574.0,0.0,1069096,2527 -2020-12-14,679.0,0.0,1069096,2527 -2020-12-15,896.0,0.0,1069096,2527 -2020-12-16,1120.0,0.0,1069096,2527 -2020-12-17,1414.0,0.0,1069096,2527 -2020-12-18,1729.0,0.0,1069096,2527 -2020-12-19,2044.0,0.0,1069096,2527 -2020-12-20,2387.0,0.0,1069096,2527 -2020-12-21,2800.0,0.0,1069096,2527 -2020-12-22,3206.0,0.0,1069096,2527 -2020-12-23,3710.0,0.0,1069096,2527 -2020-12-24,3955.0,0.0,1069096,2527 -2020-12-25,3955.0,0.0,1069096,2527 -2020-12-26,3962.0,0.0,1069096,2527 -2020-12-27,4025.0,0.0,1069096,2527 -2020-12-28,4137.0,0.0,1069096,2527 -2020-12-29,4466.0,0.0,1069096,2527 -2020-12-30,5278.0,0.0,1069096,2527 -2020-12-31,6090.0,0.0,1069096,2527 -2021-01-01,6272.0,0.0,1069096,2527 -2021-01-02,6454.0,0.0,1069096,2527 -2021-01-03,6587.0,0.0,1069096,2527 -2021-01-04,6867.0,0.0,1069096,2527 -2021-01-05,7392.0,0.0,1069096,2527 -2021-01-06,8232.0,0.0,1069096,2527 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mode 100644 index b6eb611..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 65-69 population by ethnicity 6 groups_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,Black,Mixed,Other,South Asian,Unknown,White,Black_total,Mixed_total,Other_total,South Asian_total,Unknown_total,White_total -2020-12-04,0.0,0.0,0.0,0.0,0.0,0.0,10787,4921,11872,43351,101290,899402 -2020-12-08,0.0,0.0,0.0,0.0,7.0,49.0,10787,4921,11872,43351,101290,899402 -2020-12-09,0.0,0.0,0.0,7.0,14.0,140.0,10787,4921,11872,43351,101290,899402 -2020-12-10,0.0,0.0,0.0,14.0,21.0,238.0,10787,4921,11872,43351,101290,899402 -2020-12-11,0.0,0.0,0.0,21.0,28.0,336.0,10787,4921,11872,43351,101290,899402 -2020-12-12,7.0,0.0,0.0,28.0,35.0,413.0,10787,4921,11872,43351,101290,899402 -2020-12-13,7.0,0.0,0.0,35.0,49.0,476.0,10787,4921,11872,43351,101290,899402 -2020-12-14,14.0,7.0,7.0,49.0,56.0,546.0,10787,4921,11872,43351,101290,899402 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65-69 population by imd categories_tpp.csv deleted file mode 100644 index ffe58f3..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 65-69 population by imd categories_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,1 Most deprived,2,3,4,5 Least deprived,Unknown,1 Most deprived_total,2_total,3_total,4_total,5 Least deprived_total,Unknown_total -2020-12-04,0.0,0.0,0.0,0.0,0.0,0.0,153111,188461,236838,239421,232064,21728 -2020-12-08,0.0,7.0,7.0,14.0,21.0,0.0,153111,188461,236838,239421,232064,21728 -2020-12-09,21.0,28.0,28.0,42.0,49.0,0.0,153111,188461,236838,239421,232064,21728 -2020-12-10,35.0,49.0,49.0,63.0,77.0,0.0,153111,188461,236838,239421,232064,21728 -2020-12-11,56.0,77.0,63.0,98.0,98.0,7.0,153111,188461,236838,239421,232064,21728 -2020-12-12,70.0,98.0,84.0,112.0,112.0,14.0,153111,188461,236838,239421,232064,21728 -2020-12-13,91.0,105.0,105.0,126.0,133.0,14.0,153111,188461,236838,239421,232064,21728 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bipolar_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 65-69 population by psychosis schiz bipolar_tpp.csv deleted file mode 100644 index 43f942b..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 65-69 population by psychosis schiz bipolar_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,no,yes,no_total,yes_total -2020-12-04,0.0,0.0,1059975,11648 -2020-12-08,56.0,0.0,1059975,11648 -2020-12-09,168.0,0.0,1059975,11648 -2020-12-10,280.0,0.0,1059975,11648 -2020-12-11,399.0,0.0,1059975,11648 -2020-12-12,490.0,0.0,1059975,11648 -2020-12-13,574.0,0.0,1059975,11648 -2020-12-14,672.0,0.0,1059975,11648 -2020-12-15,889.0,0.0,1059975,11648 -2020-12-16,1113.0,0.0,1059975,11648 -2020-12-17,1400.0,7.0,1059975,11648 -2020-12-18,1722.0,7.0,1059975,11648 -2020-12-19,2030.0,7.0,1059975,11648 -2020-12-20,2380.0,14.0,1059975,11648 -2020-12-21,2786.0,14.0,1059975,11648 -2020-12-22,3185.0,14.0,1059975,11648 -2020-12-23,3689.0,14.0,1059975,11648 -2020-12-24,3934.0,14.0,1059975,11648 -2020-12-25,3941.0,14.0,1059975,11648 -2020-12-26,3948.0,14.0,1059975,11648 -2020-12-27,4004.0,14.0,1059975,11648 -2020-12-28,4116.0,14.0,1059975,11648 -2020-12-29,4445.0,21.0,1059975,11648 -2020-12-30,5250.0,28.0,1059975,11648 -2020-12-31,6062.0,28.0,1059975,11648 -2021-01-01,6237.0,35.0,1059975,11648 -2021-01-02,6419.0,35.0,1059975,11648 -2021-01-03,6552.0,35.0,1059975,11648 -2021-01-04,6832.0,35.0,1059975,11648 -2021-01-05,7357.0,42.0,1059975,11648 -2021-01-06,8190.0,42.0,1059975,11648 -2021-01-07,9562.0,49.0,1059975,11648 -2021-01-08,11109.0,70.0,1059975,11648 -2021-01-09,12537.0,70.0,1059975,11648 -2021-01-10,13251.0,77.0,1059975,11648 -2021-01-11,14098.0,91.0,1059975,11648 -2021-01-12,15295.0,105.0,1059975,11648 -2021-01-13,16828.0,112.0,1059975,11648 -2021-01-14,18662.0,147.0,1059975,11648 -2021-01-15,20783.0,168.0,1059975,11648 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-2021-03-27,970739.0,9835.0,1059975,11648 -2021-03-28,971404.0,9849.0,1059975,11648 -2021-03-29,972111.0,9863.0,1059975,11648 -2021-03-30,972909.0,9877.0,1059975,11648 -2021-03-31,973686.0,9905.0,1059975,11648 -2021-04-01,974204.0,9919.0,1059975,11648 -2021-04-02,974442.0,9926.0,1059975,11648 -2021-04-03,974701.0,9933.0,1059975,11648 -2021-04-04,974806.0,9933.0,1059975,11648 -2021-04-05,974883.0,9933.0,1059975,11648 -2021-04-06,975093.0,9933.0,1059975,11648 -2021-04-07,975408.0,9940.0,1059975,11648 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by LD_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by LD_tpp.csv deleted file mode 100644 index 895729d..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by LD_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,no,yes,no_total,yes_total -2020-12-01,0.0,0.0,2063271,3045 -2020-12-08,35.0,0.0,2063271,3045 -2020-12-09,98.0,0.0,2063271,3045 -2020-12-10,168.0,0.0,2063271,3045 -2020-12-11,238.0,0.0,2063271,3045 -2020-12-12,294.0,0.0,2063271,3045 -2020-12-13,329.0,0.0,2063271,3045 -2020-12-14,406.0,0.0,2063271,3045 -2020-12-15,609.0,0.0,2063271,3045 -2020-12-16,882.0,0.0,2063271,3045 -2020-12-17,1505.0,0.0,2063271,3045 -2020-12-18,2072.0,0.0,2063271,3045 -2020-12-19,2744.0,0.0,2063271,3045 -2020-12-20,3304.0,0.0,2063271,3045 -2020-12-21,3969.0,0.0,2063271,3045 -2020-12-22,4585.0,0.0,2063271,3045 -2020-12-23,5299.0,0.0,2063271,3045 -2020-12-24,5635.0,0.0,2063271,3045 -2020-12-25,5635.0,0.0,2063271,3045 -2020-12-26,5642.0,0.0,2063271,3045 -2020-12-27,5663.0,0.0,2063271,3045 -2020-12-28,5761.0,0.0,2063271,3045 -2020-12-29,6202.0,0.0,2063271,3045 -2020-12-30,8309.0,0.0,2063271,3045 -2020-12-31,10507.0,14.0,2063271,3045 -2021-01-01,11074.0,21.0,2063271,3045 -2021-01-02,11830.0,21.0,2063271,3045 -2021-01-03,11977.0,21.0,2063271,3045 -2021-01-04,12187.0,21.0,2063271,3045 -2021-01-05,12642.0,21.0,2063271,3045 -2021-01-06,15309.0,28.0,2063271,3045 -2021-01-07,24934.0,35.0,2063271,3045 -2021-01-08,37695.0,63.0,2063271,3045 -2021-01-09,48335.0,70.0,2063271,3045 -2021-01-10,52892.0,77.0,2063271,3045 -2021-01-11,56476.0,84.0,2063271,3045 -2021-01-12,63861.0,91.0,2063271,3045 -2021-01-13,80185.0,112.0,2063271,3045 -2021-01-14,98889.0,147.0,2063271,3045 -2021-01-15,121205.0,175.0,2063271,3045 -2021-01-16,139510.0,189.0,2063271,3045 -2021-01-17,147175.0,196.0,2063271,3045 -2021-01-18,155400.0,217.0,2063271,3045 -2021-01-19,190302.0,245.0,2063271,3045 -2021-01-20,236453.0,280.0,2063271,3045 -2021-01-21,289352.0,343.0,2063271,3045 -2021-01-22,373184.0,455.0,2063271,3045 -2021-01-23,478821.0,532.0,2063271,3045 -2021-01-24,515865.0,553.0,2063271,3045 -2021-01-25,547253.0,581.0,2063271,3045 -2021-01-26,591451.0,637.0,2063271,3045 -2021-01-27,636475.0,686.0,2063271,3045 -2021-01-28,714077.0,770.0,2063271,3045 -2021-01-29,833322.0,882.0,2063271,3045 -2021-01-30,962640.0,987.0,2063271,3045 -2021-01-31,1036455.0,1043.0,2063271,3045 -2021-02-01,1097817.0,1099.0,2063271,3045 -2021-02-02,1169056.0,1169.0,2063271,3045 -2021-02-03,1260623.0,1288.0,2063271,3045 -2021-02-04,1355760.0,1393.0,2063271,3045 -2021-02-05,1444156.0,1512.0,2063271,3045 -2021-02-06,1559187.0,1645.0,2063271,3045 -2021-02-07,1616818.0,1715.0,2063271,3045 -2021-02-08,1665209.0,1799.0,2063271,3045 -2021-02-09,1724317.0,1904.0,2063271,3045 -2021-02-10,1769306.0,2009.0,2063271,3045 -2021-02-11,1811614.0,2114.0,2063271,3045 -2021-02-12,1847048.0,2247.0,2063271,3045 -2021-02-13,1877911.0,2331.0,2063271,3045 -2021-02-14,1886997.0,2338.0,2063271,3045 -2021-02-15,1894522.0,2366.0,2063271,3045 -2021-02-16,1900976.0,2394.0,2063271,3045 -2021-02-17,1906730.0,2415.0,2063271,3045 -2021-02-18,1911245.0,2450.0,2063271,3045 -2021-02-19,1914654.0,2471.0,2063271,3045 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-2021-03-15,1949584.0,2744.0,2063271,3045 -2021-03-16,1950277.0,2751.0,2063271,3045 -2021-03-17,1950963.0,2758.0,2063271,3045 -2021-03-18,1951747.0,2758.0,2063271,3045 -2021-03-19,1952475.0,2765.0,2063271,3045 -2021-03-20,1953175.0,2772.0,2063271,3045 -2021-03-21,1953469.0,2772.0,2063271,3045 -2021-03-22,1953875.0,2779.0,2063271,3045 -2021-03-23,1954358.0,2786.0,2063271,3045 -2021-03-24,1954925.0,2786.0,2063271,3045 -2021-03-25,1955548.0,2793.0,2063271,3045 -2021-03-26,1956220.0,2793.0,2063271,3045 -2021-03-27,1956997.0,2793.0,2063271,3045 -2021-03-28,1957319.0,2793.0,2063271,3045 -2021-03-29,1957732.0,2800.0,2063271,3045 -2021-03-30,1958215.0,2800.0,2063271,3045 -2021-03-31,1958817.0,2807.0,2063271,3045 -2021-04-01,1959307.0,2807.0,2063271,3045 -2021-04-02,1959629.0,2807.0,2063271,3045 -2021-04-03,1959853.0,2807.0,2063271,3045 -2021-04-04,1959937.0,2807.0,2063271,3045 -2021-04-05,1959993.0,2807.0,2063271,3045 -2021-04-06,1960273.0,2807.0,2063271,3045 -2021-04-07,1960672.0,2807.0,2063271,3045 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by ethnicity 6 groups_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by ethnicity 6 groups_tpp.csv deleted file mode 100644 index 5fff816..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by ethnicity 6 groups_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,Black,Mixed,Other,South Asian,Unknown,White,Black_total,Mixed_total,Other_total,South Asian_total,Unknown_total,White_total -2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,14700,6440,15337,54950,145257,1829632 -2020-12-08,0.0,0.0,0.0,0.0,0.0,28.0,14700,6440,15337,54950,145257,1829632 -2020-12-09,0.0,0.0,0.0,0.0,7.0,77.0,14700,6440,15337,54950,145257,1829632 -2020-12-10,0.0,0.0,0.0,7.0,14.0,140.0,14700,6440,15337,54950,145257,1829632 -2020-12-11,0.0,0.0,0.0,7.0,14.0,203.0,14700,6440,15337,54950,145257,1829632 -2020-12-12,0.0,0.0,0.0,14.0,14.0,252.0,14700,6440,15337,54950,145257,1829632 -2020-12-13,0.0,0.0,0.0,14.0,21.0,287.0,14700,6440,15337,54950,145257,1829632 -2020-12-14,0.0,0.0,0.0,21.0,28.0,350.0,14700,6440,15337,54950,145257,1829632 -2020-12-15,7.0,0.0,7.0,28.0,35.0,532.0,14700,6440,15337,54950,145257,1829632 -2020-12-16,7.0,0.0,7.0,42.0,56.0,756.0,14700,6440,15337,54950,145257,1829632 -2020-12-17,14.0,0.0,21.0,84.0,84.0,1295.0,14700,6440,15337,54950,145257,1829632 -2020-12-18,21.0,7.0,21.0,175.0,112.0,1729.0,14700,6440,15337,54950,145257,1829632 -2020-12-19,28.0,14.0,28.0,238.0,147.0,2289.0,14700,6440,15337,54950,145257,1829632 -2020-12-20,35.0,14.0,28.0,294.0,182.0,2758.0,14700,6440,15337,54950,145257,1829632 -2020-12-21,35.0,14.0,35.0,357.0,210.0,3311.0,14700,6440,15337,54950,145257,1829632 -2020-12-22,49.0,21.0,42.0,455.0,238.0,3780.0,14700,6440,15337,54950,145257,1829632 -2020-12-23,56.0,28.0,56.0,553.0,266.0,4347.0,14700,6440,15337,54950,145257,1829632 -2020-12-24,56.0,28.0,56.0,595.0,280.0,4620.0,14700,6440,15337,54950,145257,1829632 -2020-12-25,56.0,28.0,56.0,595.0,280.0,4620.0,14700,6440,15337,54950,145257,1829632 -2020-12-26,56.0,28.0,56.0,595.0,280.0,4627.0,14700,6440,15337,54950,145257,1829632 -2020-12-27,56.0,28.0,56.0,595.0,280.0,4648.0,14700,6440,15337,54950,145257,1829632 -2020-12-28,56.0,28.0,56.0,602.0,287.0,4739.0,14700,6440,15337,54950,145257,1829632 -2020-12-29,63.0,28.0,56.0,658.0,301.0,5096.0,14700,6440,15337,54950,145257,1829632 -2020-12-30,70.0,35.0,70.0,749.0,378.0,7014.0,14700,6440,15337,54950,145257,1829632 -2020-12-31,77.0,42.0,77.0,847.0,476.0,9002.0,14700,6440,15337,54950,145257,1829632 -2021-01-01,77.0,42.0,84.0,861.0,504.0,9527.0,14700,6440,15337,54950,145257,1829632 -2021-01-02,77.0,42.0,84.0,875.0,532.0,10227.0,14700,6440,15337,54950,145257,1829632 -2021-01-03,84.0,42.0,84.0,889.0,539.0,10360.0,14700,6440,15337,54950,145257,1829632 -2021-01-04,84.0,42.0,91.0,896.0,546.0,10542.0,14700,6440,15337,54950,145257,1829632 -2021-01-05,84.0,49.0,98.0,924.0,581.0,10934.0,14700,6440,15337,54950,145257,1829632 -2021-01-06,105.0,56.0,112.0,994.0,728.0,13335.0,14700,6440,15337,54950,145257,1829632 -2021-01-07,161.0,91.0,189.0,1365.0,1225.0,21938.0,14700,6440,15337,54950,145257,1829632 -2021-01-08,252.0,126.0,315.0,1883.0,1876.0,33299.0,14700,6440,15337,54950,145257,1829632 -2021-01-09,364.0,161.0,406.0,2352.0,2436.0,42686.0,14700,6440,15337,54950,145257,1829632 -2021-01-10,406.0,175.0,427.0,2548.0,2702.0,46704.0,14700,6440,15337,54950,145257,1829632 -2021-01-11,434.0,182.0,448.0,2688.0,2835.0,49973.0,14700,6440,15337,54950,145257,1829632 -2021-01-12,455.0,203.0,483.0,2842.0,3199.0,56763.0,14700,6440,15337,54950,145257,1829632 -2021-01-13,574.0,259.0,574.0,3248.0,4032.0,71624.0,14700,6440,15337,54950,145257,1829632 -2021-01-14,693.0,322.0,721.0,3822.0,5012.0,88459.0,14700,6440,15337,54950,145257,1829632 -2021-01-15,868.0,392.0,868.0,4494.0,6447.0,108311.0,14700,6440,15337,54950,145257,1829632 -2021-01-16,1001.0,448.0,980.0,5089.0,7518.0,124663.0,14700,6440,15337,54950,145257,1829632 -2021-01-17,1050.0,462.0,1029.0,5257.0,8001.0,131565.0,14700,6440,15337,54950,145257,1829632 -2021-01-18,1127.0,483.0,1085.0,5523.0,8470.0,138929.0,14700,6440,15337,54950,145257,1829632 -2021-01-19,1316.0,574.0,1288.0,6412.0,10542.0,170422.0,14700,6440,15337,54950,145257,1829632 -2021-01-20,1617.0,714.0,1603.0,7847.0,13104.0,211841.0,14700,6440,15337,54950,145257,1829632 -2021-01-21,1911.0,854.0,1883.0,9205.0,16114.0,259728.0,14700,6440,15337,54950,145257,1829632 -2021-01-22,2373.0,1113.0,2548.0,11361.0,20916.0,335321.0,14700,6440,15337,54950,145257,1829632 -2021-01-23,2793.0,1351.0,3157.0,13685.0,27286.0,431081.0,14700,6440,15337,54950,145257,1829632 -2021-01-24,3003.0,1477.0,3514.0,14917.0,29526.0,463974.0,14700,6440,15337,54950,145257,1829632 -2021-01-25,3206.0,1596.0,3759.0,16114.0,31395.0,491757.0,14700,6440,15337,54950,145257,1829632 -2021-01-26,3500.0,1757.0,4158.0,17640.0,33950.0,531076.0,14700,6440,15337,54950,145257,1829632 -2021-01-27,3864.0,1939.0,4613.0,19460.0,36701.0,570584.0,14700,6440,15337,54950,145257,1829632 -2021-01-28,4291.0,2156.0,5152.0,21896.0,40985.0,640367.0,14700,6440,15337,54950,145257,1829632 -2021-01-29,4774.0,2443.0,5803.0,24206.0,48034.0,748951.0,14700,6440,15337,54950,145257,1829632 -2021-01-30,5278.0,2695.0,6468.0,26768.0,55895.0,866523.0,14700,6440,15337,54950,145257,1829632 -2021-01-31,5551.0,2884.0,6846.0,28259.0,60480.0,933478.0,14700,6440,15337,54950,145257,1829632 -2021-02-01,5824.0,3045.0,7168.0,29463.0,64169.0,989247.0,14700,6440,15337,54950,145257,1829632 -2021-02-02,6167.0,3213.0,7588.0,31052.0,68621.0,1053591.0,14700,6440,15337,54950,145257,1829632 -2021-02-03,6454.0,3374.0,8050.0,32543.0,74774.0,1136716.0,14700,6440,15337,54950,145257,1829632 -2021-02-04,6860.0,3612.0,8526.0,34279.0,80843.0,1223040.0,14700,6440,15337,54950,145257,1829632 -2021-02-05,7217.0,3808.0,9023.0,35847.0,87087.0,1302679.0,14700,6440,15337,54950,145257,1829632 -2021-02-06,7560.0,4053.0,9499.0,37513.0,95522.0,1406678.0,14700,6440,15337,54950,145257,1829632 -2021-02-07,7735.0,4179.0,9737.0,38374.0,100121.0,1458387.0,14700,6440,15337,54950,145257,1829632 -2021-02-08,7924.0,4277.0,9989.0,39193.0,103880.0,1501738.0,14700,6440,15337,54950,145257,1829632 -2021-02-09,8127.0,4410.0,10276.0,40040.0,108542.0,1554819.0,14700,6440,15337,54950,145257,1829632 -2021-02-10,8358.0,4501.0,10472.0,40992.0,112147.0,1594852.0,14700,6440,15337,54950,145257,1829632 -2021-02-11,8603.0,4585.0,10710.0,41727.0,115633.0,1632477.0,14700,6440,15337,54950,145257,1829632 -2021-02-12,8827.0,4676.0,10899.0,42336.0,118629.0,1663921.0,14700,6440,15337,54950,145257,1829632 -2021-02-13,8960.0,4746.0,11074.0,42861.0,120981.0,1691620.0,14700,6440,15337,54950,145257,1829632 -2021-02-14,9016.0,4774.0,11144.0,43078.0,121709.0,1699621.0,14700,6440,15337,54950,145257,1829632 -2021-02-15,9079.0,4795.0,11200.0,43323.0,122374.0,1706117.0,14700,6440,15337,54950,145257,1829632 -2021-02-16,9149.0,4823.0,11263.0,43512.0,122955.0,1711668.0,14700,6440,15337,54950,145257,1829632 -2021-02-17,9233.0,4844.0,11319.0,43799.0,123445.0,1716505.0,14700,6440,15337,54950,145257,1829632 -2021-02-18,9303.0,4886.0,11368.0,44030.0,123816.0,1720292.0,14700,6440,15337,54950,145257,1829632 -2021-02-19,9352.0,4900.0,11431.0,44212.0,124096.0,1723141.0,14700,6440,15337,54950,145257,1829632 -2021-02-20,9394.0,4921.0,11466.0,44345.0,124334.0,1725724.0,14700,6440,15337,54950,145257,1829632 -2021-02-21,9408.0,4921.0,11473.0,44415.0,124404.0,1726452.0,14700,6440,15337,54950,145257,1829632 -2021-02-22,9450.0,4928.0,11487.0,44527.0,124516.0,1727628.0,14700,6440,15337,54950,145257,1829632 -2021-02-23,9506.0,4935.0,11522.0,44674.0,124740.0,1729385.0,14700,6440,15337,54950,145257,1829632 -2021-02-24,9562.0,4963.0,11564.0,44814.0,124985.0,1731842.0,14700,6440,15337,54950,145257,1829632 -2021-02-25,9632.0,4977.0,11606.0,45024.0,125244.0,1734551.0,14700,6440,15337,54950,145257,1829632 -2021-02-26,9681.0,5005.0,11662.0,45206.0,125517.0,1737022.0,14700,6440,15337,54950,145257,1829632 -2021-02-27,9723.0,5026.0,11690.0,45353.0,125699.0,1738639.0,14700,6440,15337,54950,145257,1829632 -2021-02-28,9744.0,5033.0,11704.0,45402.0,125769.0,1739255.0,14700,6440,15337,54950,145257,1829632 -2021-03-01,9758.0,5033.0,11718.0,45451.0,125832.0,1739948.0,14700,6440,15337,54950,145257,1829632 -2021-03-02,9772.0,5040.0,11732.0,45514.0,125909.0,1740781.0,14700,6440,15337,54950,145257,1829632 -2021-03-03,9800.0,5047.0,11760.0,45633.0,126007.0,1741789.0,14700,6440,15337,54950,145257,1829632 -2021-03-04,9842.0,5068.0,11781.0,45766.0,126154.0,1743245.0,14700,6440,15337,54950,145257,1829632 -2021-03-05,9898.0,5075.0,11802.0,45864.0,126336.0,1745002.0,14700,6440,15337,54950,145257,1829632 -2021-03-06,9933.0,5089.0,11830.0,45962.0,126469.0,1746255.0,14700,6440,15337,54950,145257,1829632 -2021-03-07,9940.0,5096.0,11837.0,46004.0,126504.0,1746521.0,14700,6440,15337,54950,145257,1829632 -2021-03-08,9961.0,5103.0,11844.0,46060.0,126546.0,1747081.0,14700,6440,15337,54950,145257,1829632 -2021-03-09,9982.0,5103.0,11851.0,46123.0,126602.0,1747704.0,14700,6440,15337,54950,145257,1829632 -2021-03-10,10010.0,5110.0,11858.0,46179.0,126651.0,1748404.0,14700,6440,15337,54950,145257,1829632 -2021-03-11,10031.0,5117.0,11879.0,46228.0,126721.0,1749041.0,14700,6440,15337,54950,145257,1829632 -2021-03-12,10059.0,5131.0,11893.0,46305.0,126819.0,1749937.0,14700,6440,15337,54950,145257,1829632 -2021-03-13,10094.0,5138.0,11921.0,46396.0,126924.0,1750805.0,14700,6440,15337,54950,145257,1829632 -2021-03-14,10108.0,5138.0,11928.0,46424.0,126959.0,1751141.0,14700,6440,15337,54950,145257,1829632 -2021-03-15,10129.0,5145.0,11942.0,46480.0,127008.0,1751624.0,14700,6440,15337,54950,145257,1829632 -2021-03-16,10143.0,5152.0,11949.0,46543.0,127071.0,1752177.0,14700,6440,15337,54950,145257,1829632 -2021-03-17,10157.0,5159.0,11963.0,46634.0,127120.0,1752688.0,14700,6440,15337,54950,145257,1829632 -2021-03-18,10185.0,5173.0,11977.0,46690.0,127197.0,1753283.0,14700,6440,15337,54950,145257,1829632 -2021-03-19,10206.0,5180.0,11998.0,46753.0,127260.0,1753836.0,14700,6440,15337,54950,145257,1829632 -2021-03-20,10227.0,5187.0,12012.0,46795.0,127330.0,1754403.0,14700,6440,15337,54950,145257,1829632 -2021-03-21,10234.0,5194.0,12019.0,46837.0,127358.0,1754599.0,14700,6440,15337,54950,145257,1829632 -2021-03-22,10248.0,5201.0,12026.0,46865.0,127393.0,1754921.0,14700,6440,15337,54950,145257,1829632 -2021-03-23,10262.0,5201.0,12040.0,46907.0,127428.0,1755299.0,14700,6440,15337,54950,145257,1829632 -2021-03-24,10276.0,5208.0,12047.0,46956.0,127477.0,1755747.0,14700,6440,15337,54950,145257,1829632 -2021-03-25,10297.0,5215.0,12068.0,46998.0,127519.0,1756244.0,14700,6440,15337,54950,145257,1829632 -2021-03-26,10318.0,5222.0,12089.0,47047.0,127575.0,1756762.0,14700,6440,15337,54950,145257,1829632 -2021-03-27,10346.0,5229.0,12096.0,47103.0,127645.0,1757385.0,14700,6440,15337,54950,145257,1829632 -2021-03-28,10353.0,5229.0,12096.0,47138.0,127680.0,1757616.0,14700,6440,15337,54950,145257,1829632 -2021-03-29,10367.0,5229.0,12103.0,47159.0,127722.0,1757945.0,14700,6440,15337,54950,145257,1829632 -2021-03-30,10381.0,5236.0,12110.0,47194.0,127750.0,1758344.0,14700,6440,15337,54950,145257,1829632 -2021-03-31,10402.0,5236.0,12124.0,47222.0,127799.0,1758841.0,14700,6440,15337,54950,145257,1829632 -2021-04-01,10416.0,5236.0,12131.0,47257.0,127827.0,1759240.0,14700,6440,15337,54950,145257,1829632 -2021-04-02,10423.0,5243.0,12131.0,47271.0,127862.0,1759506.0,14700,6440,15337,54950,145257,1829632 -2021-04-03,10430.0,5243.0,12138.0,47285.0,127890.0,1759674.0,14700,6440,15337,54950,145257,1829632 -2021-04-04,10430.0,5243.0,12138.0,47299.0,127897.0,1759744.0,14700,6440,15337,54950,145257,1829632 -2021-04-05,10430.0,5250.0,12138.0,47306.0,127897.0,1759786.0,14700,6440,15337,54950,145257,1829632 -2021-04-06,10430.0,5250.0,12145.0,47327.0,127911.0,1760010.0,14700,6440,15337,54950,145257,1829632 -2021-04-07,10444.0,5250.0,12159.0,47383.0,127932.0,1760318.0,14700,6440,15337,54950,145257,1829632 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by imd categories_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by imd categories_tpp.csv deleted file mode 100644 index 56df471..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by imd categories_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,1 Most deprived,2,3,4,5 Least deprived,Unknown,1 Most deprived_total,2_total,3_total,4_total,5 Least deprived_total,Unknown_total -2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,272972,350917,459844,475573,468713,38290 -2020-12-08,7.0,0.0,0.0,7.0,14.0,0.0,272972,350917,459844,475573,468713,38290 -2020-12-09,14.0,21.0,21.0,14.0,28.0,0.0,272972,350917,459844,475573,468713,38290 -2020-12-10,28.0,28.0,28.0,35.0,42.0,0.0,272972,350917,459844,475573,468713,38290 -2020-12-11,28.0,42.0,49.0,49.0,63.0,0.0,272972,350917,459844,475573,468713,38290 -2020-12-12,42.0,49.0,63.0,70.0,70.0,0.0,272972,350917,459844,475573,468713,38290 -2020-12-13,42.0,56.0,70.0,77.0,84.0,0.0,272972,350917,459844,475573,468713,38290 -2020-12-14,49.0,63.0,84.0,105.0,98.0,0.0,272972,350917,459844,475573,468713,38290 -2020-12-15,91.0,105.0,126.0,140.0,140.0,7.0,272972,350917,459844,475573,468713,38290 -2020-12-16,133.0,140.0,182.0,217.0,196.0,14.0,272972,350917,459844,475573,468713,38290 -2020-12-17,245.0,245.0,336.0,336.0,315.0,21.0,272972,350917,459844,475573,468713,38290 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bipolar_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by psychosis schiz bipolar_tpp.csv deleted file mode 100644 index 6ba52df..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 70-79 population by psychosis schiz bipolar_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,no,yes,no_total,yes_total -2020-12-01,0.0,0.0,2045792,20524 -2020-12-08,35.0,0.0,2045792,20524 -2020-12-09,91.0,0.0,2045792,20524 -2020-12-10,168.0,0.0,2045792,20524 -2020-12-11,231.0,0.0,2045792,20524 -2020-12-12,287.0,0.0,2045792,20524 -2020-12-13,329.0,0.0,2045792,20524 -2020-12-14,406.0,0.0,2045792,20524 -2020-12-15,609.0,0.0,2045792,20524 -2020-12-16,875.0,0.0,2045792,20524 -2020-12-17,1498.0,7.0,2045792,20524 -2020-12-18,2058.0,14.0,2045792,20524 -2020-12-19,2723.0,21.0,2045792,20524 -2020-12-20,3290.0,21.0,2045792,20524 -2020-12-21,3948.0,21.0,2045792,20524 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a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 80+ population by LD_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,no,yes,no_total,yes_total -2020-12-01,0.0,0.0,1123668,546 -2020-12-08,539.0,0.0,1123668,546 -2020-12-09,2002.0,0.0,1123668,546 -2020-12-10,3920.0,0.0,1123668,546 -2020-12-11,5733.0,0.0,1123668,546 -2020-12-12,7028.0,0.0,1123668,546 -2020-12-13,8197.0,0.0,1123668,546 -2020-12-14,10115.0,0.0,1123668,546 -2020-12-15,31311.0,0.0,1123668,546 -2020-12-16,66353.0,14.0,1123668,546 -2020-12-17,97755.0,21.0,1123668,546 -2020-12-18,118013.0,21.0,1123668,546 -2020-12-19,142863.0,28.0,1123668,546 -2020-12-20,164682.0,35.0,1123668,546 -2020-12-21,177695.0,42.0,1123668,546 -2020-12-22,201943.0,42.0,1123668,546 -2020-12-23,219205.0,49.0,1123668,546 -2020-12-24,223041.0,49.0,1123668,546 -2020-12-25,223048.0,49.0,1123668,546 -2020-12-26,223048.0,49.0,1123668,546 -2020-12-27,223237.0,49.0,1123668,546 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-2021-04-07,1075487.0,511.0,1123668,546 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 80+ population by ethnicity 6 groups_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 80+ population by ethnicity 6 groups_tpp.csv deleted file mode 100644 index 883cb21..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among 80+ population by ethnicity 6 groups_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,Black,Mixed,Other,South Asian,Unknown,White,Black_total,Mixed_total,Other_total,South Asian_total,Unknown_total,White_total -2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,11088,3262,6783,28525,63280,1011276 -2020-12-08,0.0,0.0,0.0,0.0,14.0,525.0,11088,3262,6783,28525,63280,1011276 -2020-12-09,0.0,0.0,21.0,21.0,63.0,1890.0,11088,3262,6783,28525,63280,1011276 -2020-12-10,7.0,7.0,35.0,49.0,126.0,3696.0,11088,3262,6783,28525,63280,1011276 -2020-12-11,14.0,14.0,42.0,70.0,175.0,5418.0,11088,3262,6783,28525,63280,1011276 -2020-12-12,21.0,14.0,49.0,84.0,210.0,6643.0,11088,3262,6783,28525,63280,1011276 -2020-12-13,21.0,14.0,63.0,105.0,245.0,7749.0,11088,3262,6783,28525,63280,1011276 -2020-12-14,28.0,14.0,70.0,140.0,308.0,9555.0,11088,3262,6783,28525,63280,1011276 -2020-12-15,126.0,56.0,154.0,497.0,1344.0,29141.0,11088,3262,6783,28525,63280,1011276 -2020-12-16,308.0,119.0,287.0,1127.0,3087.0,61439.0,11088,3262,6783,28525,63280,1011276 -2020-12-17,483.0,182.0,420.0,1708.0,4585.0,90405.0,11088,3262,6783,28525,63280,1011276 -2020-12-18,588.0,217.0,511.0,2156.0,5439.0,109123.0,11088,3262,6783,28525,63280,1011276 -2020-12-19,756.0,294.0,637.0,2940.0,6405.0,131866.0,11088,3262,6783,28525,63280,1011276 -2020-12-20,854.0,329.0,735.0,3381.0,7406.0,152012.0,11088,3262,6783,28525,63280,1011276 -2020-12-21,931.0,357.0,805.0,3675.0,7931.0,164038.0,11088,3262,6783,28525,63280,1011276 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population by imd categories_tpp.csv +++ /dev/null @@ -1,123 +0,0 @@ -covid_vacc_date,1 Most deprived,2,3,4,5 Least deprived,Unknown,1 Most deprived_total,2_total,3_total,4_total,5 Least deprived_total,Unknown_total -2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,145845,188342,250740,259175,260155,19964 -2020-12-08,42.0,84.0,105.0,161.0,140.0,14.0,145845,188342,250740,259175,260155,19964 -2020-12-09,287.0,329.0,413.0,462.0,469.0,42.0,145845,188342,250740,259175,260155,19964 -2020-12-10,525.0,637.0,784.0,945.0,959.0,70.0,145845,188342,250740,259175,260155,19964 -2020-12-11,763.0,896.0,1134.0,1407.0,1435.0,98.0,145845,188342,250740,259175,260155,19964 -2020-12-12,924.0,1078.0,1428.0,1757.0,1736.0,105.0,145845,188342,250740,259175,260155,19964 -2020-12-13,1050.0,1239.0,1701.0,2058.0,2023.0,119.0,145845,188342,250740,259175,260155,19964 -2020-12-14,1225.0,1540.0,2128.0,2541.0,2534.0,147.0,145845,188342,250740,259175,260155,19964 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-2020-12-01,0.0,0.0,1115513,8701 -2020-12-08,539.0,0.0,1115513,8701 -2020-12-09,1988.0,14.0,1115513,8701 -2020-12-10,3899.0,21.0,1115513,8701 -2020-12-11,5705.0,35.0,1115513,8701 -2020-12-12,6986.0,42.0,1115513,8701 -2020-12-13,8148.0,42.0,1115513,8701 -2020-12-14,10066.0,56.0,1115513,8701 -2020-12-15,31157.0,154.0,1115513,8701 -2020-12-16,66038.0,329.0,1115513,8701 -2020-12-17,97258.0,511.0,1115513,8701 -2020-12-18,117418.0,623.0,1115513,8701 -2020-12-19,142149.0,742.0,1115513,8701 -2020-12-20,163877.0,840.0,1115513,8701 -2020-12-21,176813.0,924.0,1115513,8701 -2020-12-22,200935.0,1057.0,1115513,8701 -2020-12-23,218099.0,1148.0,1115513,8701 -2020-12-24,221914.0,1176.0,1115513,8701 -2020-12-25,221921.0,1176.0,1115513,8701 -2020-12-26,221921.0,1176.0,1115513,8701 -2020-12-27,222110.0,1176.0,1115513,8701 -2020-12-28,222579.0,1176.0,1115513,8701 -2020-12-29,230531.0,1225.0,1115513,8701 -2020-12-30,250334.0,1337.0,1115513,8701 -2020-12-31,264537.0,1435.0,1115513,8701 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-2021-04-05,1067472.0,8001.0,1115513,8701 -2021-04-06,1067640.0,8008.0,1115513,8701 -2021-04-07,1067983.0,8008.0,1115513,8701 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among shielding (aged 16-69) population by LD_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among shielding (aged 16-69) population by LD_tpp.csv deleted file mode 100644 index 4190aae..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among shielding (aged 16-69) population by LD_tpp.csv +++ /dev/null @@ -1,124 +0,0 @@ -covid_vacc_date,no,yes,no_total,yes_total -2020-12-01,0.0,0.0,797146,26796 -2020-12-03,0.0,0.0,797146,26796 -2020-12-08,203.0,0.0,797146,26796 -2020-12-09,455.0,0.0,797146,26796 -2020-12-10,770.0,0.0,797146,26796 -2020-12-11,1064.0,0.0,797146,26796 -2020-12-12,1379.0,0.0,797146,26796 -2020-12-13,1547.0,0.0,797146,26796 -2020-12-14,1799.0,0.0,797146,26796 -2020-12-15,2247.0,0.0,797146,26796 -2020-12-16,2674.0,0.0,797146,26796 -2020-12-17,3206.0,7.0,797146,26796 -2020-12-18,3752.0,14.0,797146,26796 -2020-12-19,4172.0,14.0,797146,26796 -2020-12-20,4669.0,14.0,797146,26796 -2020-12-21,5369.0,14.0,797146,26796 -2020-12-22,6076.0,14.0,797146,26796 -2020-12-23,6916.0,21.0,797146,26796 -2020-12-24,7315.0,28.0,797146,26796 -2020-12-25,7315.0,28.0,797146,26796 -2020-12-26,7336.0,28.0,797146,26796 -2020-12-27,7413.0,28.0,797146,26796 -2020-12-28,7588.0,28.0,797146,26796 -2020-12-29,8064.0,35.0,797146,26796 -2020-12-30,9401.0,98.0,797146,26796 -2020-12-31,10633.0,182.0,797146,26796 -2021-01-01,10920.0,196.0,797146,26796 -2021-01-02,11221.0,217.0,797146,26796 -2021-01-03,11438.0,224.0,797146,26796 -2021-01-04,11914.0,231.0,797146,26796 -2021-01-05,12810.0,245.0,797146,26796 -2021-01-06,13958.0,273.0,797146,26796 -2021-01-07,15778.0,350.0,797146,26796 -2021-01-08,17906.0,469.0,797146,26796 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-2021-03-21,668850.0,23422.0,797146,26796 -2021-03-22,670243.0,23464.0,797146,26796 -2021-03-23,671783.0,23520.0,797146,26796 -2021-03-24,673666.0,23569.0,797146,26796 -2021-03-25,675479.0,23632.0,797146,26796 -2021-03-26,677579.0,23702.0,797146,26796 -2021-03-27,679847.0,23772.0,797146,26796 -2021-03-28,680932.0,23793.0,797146,26796 -2021-03-29,682059.0,23842.0,797146,26796 -2021-03-30,683165.0,23884.0,797146,26796 -2021-03-31,684537.0,23947.0,797146,26796 -2021-04-01,685517.0,23975.0,797146,26796 -2021-04-02,685944.0,23989.0,797146,26796 -2021-04-03,686371.0,24010.0,797146,26796 -2021-04-04,686567.0,24010.0,797146,26796 -2021-04-05,686721.0,24017.0,797146,26796 -2021-04-06,687106.0,24031.0,797146,26796 -2021-04-07,687701.0,24059.0,797146,26796 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among shielding (aged 16-69) population by ethnicity 6 groups_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among shielding (aged 16-69) population by ethnicity 6 groups_tpp.csv deleted file mode 100644 index d013d90..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among shielding (aged 16-69) population by ethnicity 6 groups_tpp.csv +++ /dev/null @@ -1,124 +0,0 @@ -covid_vacc_date,Black,Mixed,Other,South Asian,Unknown,White,Black_total,Mixed_total,Other_total,South Asian_total,Unknown_total,White_total -2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,44485,14252,18123,108255,32389,606431 -2020-12-03,0.0,0.0,0.0,0.0,0.0,0.0,44485,14252,18123,108255,32389,606431 -2020-12-08,0.0,7.0,0.0,14.0,0.0,168.0,44485,14252,18123,108255,32389,606431 -2020-12-09,14.0,14.0,14.0,42.0,14.0,364.0,44485,14252,18123,108255,32389,606431 -2020-12-10,28.0,21.0,21.0,70.0,28.0,609.0,44485,14252,18123,108255,32389,606431 -2020-12-11,49.0,21.0,28.0,98.0,35.0,833.0,44485,14252,18123,108255,32389,606431 -2020-12-12,56.0,28.0,35.0,140.0,42.0,1085.0,44485,14252,18123,108255,32389,606431 -2020-12-13,56.0,35.0,35.0,168.0,49.0,1211.0,44485,14252,18123,108255,32389,606431 -2020-12-14,63.0,35.0,42.0,196.0,56.0,1407.0,44485,14252,18123,108255,32389,606431 -2020-12-15,77.0,42.0,49.0,252.0,63.0,1771.0,44485,14252,18123,108255,32389,606431 -2020-12-16,98.0,42.0,56.0,287.0,77.0,2107.0,44485,14252,18123,108255,32389,606431 -2020-12-17,119.0,56.0,63.0,357.0,98.0,2513.0,44485,14252,18123,108255,32389,606431 -2020-12-18,147.0,63.0,77.0,420.0,119.0,2933.0,44485,14252,18123,108255,32389,606431 -2020-12-19,161.0,70.0,84.0,490.0,126.0,3255.0,44485,14252,18123,108255,32389,606431 -2020-12-20,182.0,77.0,98.0,567.0,140.0,3612.0,44485,14252,18123,108255,32389,606431 -2020-12-21,217.0,98.0,112.0,672.0,161.0,4130.0,44485,14252,18123,108255,32389,606431 -2020-12-22,245.0,105.0,126.0,791.0,182.0,4641.0,44485,14252,18123,108255,32389,606431 -2020-12-23,294.0,112.0,154.0,910.0,210.0,5257.0,44485,14252,18123,108255,32389,606431 -2020-12-24,301.0,126.0,168.0,987.0,217.0,5537.0,44485,14252,18123,108255,32389,606431 -2020-12-25,301.0,126.0,168.0,987.0,217.0,5537.0,44485,14252,18123,108255,32389,606431 -2020-12-26,301.0,126.0,175.0,994.0,224.0,5544.0,44485,14252,18123,108255,32389,606431 -2020-12-27,308.0,126.0,175.0,1001.0,224.0,5607.0,44485,14252,18123,108255,32389,606431 -2020-12-28,315.0,133.0,175.0,1029.0,231.0,5740.0,44485,14252,18123,108255,32389,606431 -2020-12-29,336.0,147.0,189.0,1106.0,252.0,6076.0,44485,14252,18123,108255,32389,606431 -2020-12-30,392.0,161.0,224.0,1295.0,294.0,7140.0,44485,14252,18123,108255,32389,606431 -2020-12-31,434.0,182.0,245.0,1449.0,343.0,8162.0,44485,14252,18123,108255,32389,606431 -2021-01-01,448.0,182.0,252.0,1484.0,350.0,8400.0,44485,14252,18123,108255,32389,606431 -2021-01-02,455.0,196.0,266.0,1526.0,357.0,8638.0,44485,14252,18123,108255,32389,606431 -2021-01-03,469.0,203.0,273.0,1561.0,371.0,8785.0,44485,14252,18123,108255,32389,606431 -2021-01-04,497.0,217.0,287.0,1624.0,385.0,9142.0,44485,14252,18123,108255,32389,606431 -2021-01-05,553.0,231.0,322.0,1743.0,420.0,9793.0,44485,14252,18123,108255,32389,606431 -2021-01-06,602.0,245.0,364.0,1897.0,462.0,10661.0,44485,14252,18123,108255,32389,606431 -2021-01-07,700.0,287.0,413.0,2226.0,532.0,11977.0,44485,14252,18123,108255,32389,606431 -2021-01-08,812.0,315.0,462.0,2583.0,602.0,13601.0,44485,14252,18123,108255,32389,606431 -2021-01-09,938.0,350.0,504.0,2814.0,686.0,15190.0,44485,14252,18123,108255,32389,606431 -2021-01-10,994.0,364.0,518.0,2940.0,714.0,15953.0,44485,14252,18123,108255,32389,606431 -2021-01-11,1085.0,399.0,560.0,3115.0,756.0,17318.0,44485,14252,18123,108255,32389,606431 -2021-01-12,1218.0,441.0,595.0,3318.0,826.0,18907.0,44485,14252,18123,108255,32389,606431 -2021-01-13,1372.0,483.0,651.0,3577.0,917.0,20517.0,44485,14252,18123,108255,32389,606431 -2021-01-14,1526.0,525.0,700.0,3836.0,1001.0,22505.0,44485,14252,18123,108255,32389,606431 -2021-01-15,1743.0,581.0,756.0,4151.0,1113.0,25368.0,44485,14252,18123,108255,32389,606431 -2021-01-16,1890.0,637.0,784.0,4466.0,1211.0,27615.0,44485,14252,18123,108255,32389,606431 -2021-01-17,1995.0,672.0,812.0,4641.0,1274.0,28945.0,44485,14252,18123,108255,32389,606431 -2021-01-18,2135.0,721.0,854.0,4837.0,1344.0,30450.0,44485,14252,18123,108255,32389,606431 -2021-01-19,2352.0,777.0,903.0,5180.0,1449.0,32830.0,44485,14252,18123,108255,32389,606431 -2021-01-20,2611.0,854.0,980.0,5698.0,1554.0,36127.0,44485,14252,18123,108255,32389,606431 -2021-01-21,2926.0,952.0,1057.0,6202.0,1708.0,40782.0,44485,14252,18123,108255,32389,606431 -2021-01-22,3255.0,1057.0,1162.0,6832.0,1932.0,47649.0,44485,14252,18123,108255,32389,606431 -2021-01-23,3556.0,1204.0,1274.0,7427.0,2156.0,54915.0,44485,14252,18123,108255,32389,606431 -2021-01-24,3731.0,1246.0,1337.0,7791.0,2254.0,58359.0,44485,14252,18123,108255,32389,606431 -2021-01-25,3955.0,1309.0,1428.0,8246.0,2359.0,61250.0,44485,14252,18123,108255,32389,606431 -2021-01-26,4179.0,1400.0,1526.0,8813.0,2499.0,65912.0,44485,14252,18123,108255,32389,606431 -2021-01-27,4459.0,1484.0,1694.0,9401.0,2653.0,71225.0,44485,14252,18123,108255,32389,606431 -2021-01-28,4858.0,1624.0,1834.0,10444.0,2891.0,81053.0,44485,14252,18123,108255,32389,606431 -2021-01-29,5264.0,1785.0,2030.0,11417.0,3255.0,92505.0,44485,14252,18123,108255,32389,606431 -2021-01-30,5593.0,1932.0,2240.0,12558.0,3647.0,107723.0,44485,14252,18123,108255,32389,606431 -2021-01-31,5838.0,2037.0,2387.0,13552.0,3850.0,116053.0,44485,14252,18123,108255,32389,606431 -2021-02-01,6104.0,2156.0,2548.0,14406.0,4053.0,125076.0,44485,14252,18123,108255,32389,606431 -2021-02-02,6503.0,2296.0,2793.0,15477.0,4347.0,137004.0,44485,14252,18123,108255,32389,606431 -2021-02-03,6951.0,2471.0,3017.0,16723.0,4788.0,155547.0,44485,14252,18123,108255,32389,606431 -2021-02-04,7574.0,2744.0,3311.0,18368.0,5327.0,177520.0,44485,14252,18123,108255,32389,606431 -2021-02-05,8267.0,3003.0,3696.0,20041.0,5936.0,200200.0,44485,14252,18123,108255,32389,606431 -2021-02-06,8925.0,3339.0,4032.0,21966.0,7035.0,237825.0,44485,14252,18123,108255,32389,606431 -2021-02-07,9191.0,3479.0,4235.0,23114.0,7497.0,254380.0,44485,14252,18123,108255,32389,606431 -2021-02-08,9653.0,3696.0,4431.0,24304.0,7910.0,270200.0,44485,14252,18123,108255,32389,606431 -2021-02-09,10101.0,3913.0,4641.0,25522.0,8498.0,290829.0,44485,14252,18123,108255,32389,606431 -2021-02-10,10661.0,4144.0,4907.0,27132.0,9121.0,311766.0,44485,14252,18123,108255,32389,606431 -2021-02-11,11361.0,4424.0,5208.0,28973.0,9856.0,334628.0,44485,14252,18123,108255,32389,606431 -2021-02-12,12082.0,4690.0,5516.0,30527.0,10577.0,354333.0,44485,14252,18123,108255,32389,606431 -2021-02-13,12621.0,4935.0,5768.0,31878.0,11200.0,372316.0,44485,14252,18123,108255,32389,606431 -2021-02-14,12873.0,5019.0,5894.0,32627.0,11473.0,377790.0,44485,14252,18123,108255,32389,606431 -2021-02-15,13153.0,5082.0,6006.0,33418.0,11739.0,382487.0,44485,14252,18123,108255,32389,606431 -2021-02-16,13608.0,5257.0,6230.0,34853.0,12250.0,389375.0,44485,14252,18123,108255,32389,606431 -2021-02-17,14168.0,5467.0,6524.0,36736.0,13055.0,398307.0,44485,14252,18123,108255,32389,606431 -2021-02-18,14749.0,5691.0,6804.0,38591.0,13846.0,406798.0,44485,14252,18123,108255,32389,606431 -2021-02-19,15260.0,5873.0,7091.0,40271.0,14581.0,414176.0,44485,14252,18123,108255,32389,606431 -2021-02-20,15736.0,6041.0,7301.0,41727.0,15351.0,421666.0,44485,14252,18123,108255,32389,606431 -2021-02-21,15995.0,6118.0,7434.0,42721.0,15610.0,424368.0,44485,14252,18123,108255,32389,606431 -2021-02-22,16366.0,6237.0,7581.0,44002.0,15988.0,428057.0,44485,14252,18123,108255,32389,606431 -2021-02-23,17066.0,6461.0,7938.0,46109.0,16828.0,435939.0,44485,14252,18123,108255,32389,606431 -2021-02-24,17843.0,6776.0,8372.0,48916.0,17955.0,446845.0,44485,14252,18123,108255,32389,606431 -2021-02-25,18914.0,7119.0,8883.0,52822.0,19208.0,459340.0,44485,14252,18123,108255,32389,606431 -2021-02-26,20048.0,7525.0,9387.0,56504.0,20517.0,471954.0,44485,14252,18123,108255,32389,606431 -2021-02-27,20916.0,7826.0,9772.0,59430.0,21427.0,481579.0,44485,14252,18123,108255,32389,606431 -2021-02-28,21224.0,7959.0,9954.0,60942.0,21798.0,484925.0,44485,14252,18123,108255,32389,606431 -2021-03-01,21490.0,8057.0,10094.0,61894.0,22113.0,487732.0,44485,14252,18123,108255,32389,606431 -2021-03-02,21784.0,8148.0,10255.0,62930.0,22407.0,490616.0,44485,14252,18123,108255,32389,606431 -2021-03-03,22288.0,8302.0,10472.0,64624.0,22855.0,494683.0,44485,14252,18123,108255,32389,606431 -2021-03-04,22862.0,8477.0,10731.0,66766.0,23415.0,500248.0,44485,14252,18123,108255,32389,606431 -2021-03-05,23415.0,8666.0,10976.0,68600.0,23919.0,505680.0,44485,14252,18123,108255,32389,606431 -2021-03-06,23989.0,8862.0,11270.0,70406.0,24402.0,511343.0,44485,14252,18123,108255,32389,606431 -2021-03-07,24157.0,8925.0,11354.0,71085.0,24535.0,512708.0,44485,14252,18123,108255,32389,606431 -2021-03-08,24346.0,8995.0,11452.0,71743.0,24675.0,514458.0,44485,14252,18123,108255,32389,606431 -2021-03-09,24647.0,9072.0,11557.0,72520.0,24850.0,516285.0,44485,14252,18123,108255,32389,606431 -2021-03-10,24913.0,9142.0,11655.0,73276.0,24976.0,518091.0,44485,14252,18123,108255,32389,606431 -2021-03-11,25109.0,9205.0,11732.0,73962.0,25095.0,519484.0,44485,14252,18123,108255,32389,606431 -2021-03-12,25473.0,9296.0,11872.0,74802.0,25263.0,521738.0,44485,14252,18123,108255,32389,606431 -2021-03-13,25851.0,9415.0,12033.0,75936.0,25480.0,524573.0,44485,14252,18123,108255,32389,606431 -2021-03-14,26005.0,9457.0,12096.0,76468.0,25585.0,525721.0,44485,14252,18123,108255,32389,606431 -2021-03-15,26236.0,9520.0,12180.0,77182.0,25732.0,527338.0,44485,14252,18123,108255,32389,606431 -2021-03-16,26425.0,9576.0,12229.0,77812.0,25851.0,528787.0,44485,14252,18123,108255,32389,606431 -2021-03-17,26649.0,9632.0,12306.0,78533.0,25984.0,530131.0,44485,14252,18123,108255,32389,606431 -2021-03-18,26838.0,9695.0,12376.0,79009.0,26089.0,531573.0,44485,14252,18123,108255,32389,606431 -2021-03-19,27041.0,9758.0,12446.0,79597.0,26208.0,533057.0,44485,14252,18123,108255,32389,606431 -2021-03-20,27286.0,9835.0,12530.0,80178.0,26369.0,534947.0,44485,14252,18123,108255,32389,606431 -2021-03-21,27356.0,9870.0,12558.0,80451.0,26446.0,535591.0,44485,14252,18123,108255,32389,606431 -2021-03-22,27489.0,9898.0,12621.0,80794.0,26509.0,536396.0,44485,14252,18123,108255,32389,606431 -2021-03-23,27664.0,9933.0,12684.0,81200.0,26593.0,537229.0,44485,14252,18123,108255,32389,606431 -2021-03-24,27881.0,9975.0,12747.0,81760.0,26698.0,538181.0,44485,14252,18123,108255,32389,606431 -2021-03-25,28112.0,10031.0,12810.0,82222.0,26768.0,539175.0,44485,14252,18123,108255,32389,606431 -2021-03-26,28350.0,10080.0,12873.0,82817.0,26866.0,540295.0,44485,14252,18123,108255,32389,606431 -2021-03-27,28602.0,10157.0,12936.0,83391.0,26992.0,541527.0,44485,14252,18123,108255,32389,606431 -2021-03-28,28721.0,10185.0,12978.0,83643.0,27048.0,542136.0,44485,14252,18123,108255,32389,606431 -2021-03-29,28854.0,10220.0,13020.0,83951.0,27104.0,542759.0,44485,14252,18123,108255,32389,606431 -2021-03-30,28980.0,10241.0,13062.0,84231.0,27153.0,543382.0,44485,14252,18123,108255,32389,606431 -2021-03-31,29148.0,10297.0,13125.0,84567.0,27216.0,544131.0,44485,14252,18123,108255,32389,606431 -2021-04-01,29274.0,10318.0,13153.0,84847.0,27251.0,544649.0,44485,14252,18123,108255,32389,606431 -2021-04-02,29337.0,10332.0,13174.0,84931.0,27265.0,544894.0,44485,14252,18123,108255,32389,606431 -2021-04-03,29393.0,10346.0,13188.0,85015.0,27286.0,545160.0,44485,14252,18123,108255,32389,606431 -2021-04-04,29407.0,10353.0,13195.0,85071.0,27293.0,545258.0,44485,14252,18123,108255,32389,606431 -2021-04-05,29428.0,10353.0,13202.0,85120.0,27300.0,545335.0,44485,14252,18123,108255,32389,606431 -2021-04-06,29463.0,10367.0,13216.0,85253.0,27321.0,545517.0,44485,14252,18123,108255,32389,606431 -2021-04-07,29533.0,10388.0,13237.0,85456.0,27349.0,545797.0,44485,14252,18123,108255,32389,606431 diff --git a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among shielding (aged 16-69) population by imd categories_tpp.csv b/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among shielding (aged 16-69) population by imd categories_tpp.csv deleted file mode 100644 index ca859c0..0000000 --- a/released-outputs/machine_readable_outputs/figure_csvs/Cumulative vaccination percent among shielding (aged 16-69) population by imd categories_tpp.csv +++ /dev/null @@ -1,124 +0,0 @@ -covid_vacc_date,1 Most deprived,2,3,4,5 Least deprived,Unknown,1 Most deprived_total,2_total,3_total,4_total,5 Least deprived_total,Unknown_total -2020-12-01,0.0,0.0,0.0,0.0,0.0,0.0,243761,186487,156240,122486,95158,19796 -2020-12-03,0.0,0.0,0.0,0.0,0.0,0.0,243761,186487,156240,122486,95158,19796 -2020-12-08,35.0,42.0,35.0,42.0,42.0,7.0,243761,186487,156240,122486,95158,19796 -2020-12-09,98.0,84.0,77.0,98.0,77.0,14.0,243761,186487,156240,122486,95158,19796 -2020-12-10,168.0,154.0,147.0,147.0,126.0,28.0,243761,186487,156240,122486,95158,19796 -2020-12-11,238.0,203.0,203.0,196.0,182.0,35.0,243761,186487,156240,122486,95158,19796 -2020-12-12,294.0,266.0,266.0,259.0,245.0,49.0,243761,186487,156240,122486,95158,19796 -2020-12-13,329.0,301.0,308.0,294.0,273.0,49.0,243761,186487,156240,122486,95158,19796 -2020-12-14,378.0,357.0,364.0,343.0,315.0,56.0,243761,186487,156240,122486,95158,19796 -2020-12-15,476.0,434.0,455.0,420.0,392.0,63.0,243761,186487,156240,122486,95158,19796 -2020-12-16,581.0,504.0,553.0,504.0,469.0,70.0,243761,186487,156240,122486,95158,19796 -2020-12-17,693.0,595.0,672.0,609.0,567.0,84.0,243761,186487,156240,122486,95158,19796 -2020-12-18,791.0,714.0,791.0,714.0,651.0,105.0,243761,186487,156240,122486,95158,19796 -2020-12-19,875.0,784.0,875.0,798.0,742.0,112.0,243761,186487,156240,122486,95158,19796 -2020-12-20,987.0,903.0,959.0,882.0,819.0,133.0,243761,186487,156240,122486,95158,19796 -2020-12-21,1183.0,1036.0,1078.0,1008.0,917.0,161.0,243761,186487,156240,122486,95158,19796 -2020-12-22,1323.0,1190.0,1197.0,1155.0,1029.0,196.0,243761,186487,156240,122486,95158,19796 -2020-12-23,1533.0,1372.0,1358.0,1302.0,1148.0,217.0,243761,186487,156240,122486,95158,19796 -2020-12-24,1617.0,1463.0,1442.0,1379.0,1218.0,224.0,243761,186487,156240,122486,95158,19796 -2020-12-25,1617.0,1463.0,1442.0,1379.0,1218.0,231.0,243761,186487,156240,122486,95158,19796 -2020-12-26,1624.0,1470.0,1442.0,1386.0,1218.0,231.0,243761,186487,156240,122486,95158,19796 -2020-12-27,1638.0,1491.0,1456.0,1393.0,1232.0,231.0,243761,186487,156240,122486,95158,19796 -2020-12-28,1673.0,1533.0,1484.0,1421.0,1267.0,231.0,243761,186487,156240,122486,95158,19796 -2020-12-29,1799.0,1638.0,1589.0,1484.0,1337.0,245.0,243761,186487,156240,122486,95158,19796 -2020-12-30,2128.0,1939.0,1911.0,1736.0,1512.0,280.0,243761,186487,156240,122486,95158,19796 -2020-12-31,2492.0,2198.0,2156.0,1967.0,1687.0,308.0,243761,186487,156240,122486,95158,19796 -2021-01-01,2562.0,2261.0,2226.0,2023.0,1736.0,315.0,243761,186487,156240,122486,95158,19796 -2021-01-02,2632.0,2352.0,2282.0,2079.0,1771.0,322.0,243761,186487,156240,122486,95158,19796 -2021-01-03,2674.0,2394.0,2331.0,2128.0,1806.0,329.0,243761,186487,156240,122486,95158,19796 -2021-01-04,2772.0,2506.0,2415.0,2219.0,1890.0,336.0,243761,186487,156240,122486,95158,19796 -2021-01-05,2954.0,2688.0,2618.0,2380.0,2037.0,371.0,243761,186487,156240,122486,95158,19796 -2021-01-06,3178.0,2996.0,2863.0,2590.0,2198.0,406.0,243761,186487,156240,122486,95158,19796 -2021-01-07,3647.0,3423.0,3220.0,2940.0,2450.0,455.0,243761,186487,156240,122486,95158,19796 -2021-01-08,4263.0,3927.0,3668.0,3276.0,2730.0,504.0,243761,186487,156240,122486,95158,19796 -2021-01-09,4739.0,4424.0,4095.0,3647.0,3017.0,560.0,243761,186487,156240,122486,95158,19796 -2021-01-10,4935.0,4627.0,4312.0,3850.0,3178.0,581.0,243761,186487,156240,122486,95158,19796 -2021-01-11,5383.0,5012.0,4676.0,4144.0,3402.0,630.0,243761,186487,156240,122486,95158,19796 -2021-01-12,5943.0,5453.0,5082.0,4487.0,3647.0,693.0,243761,186487,156240,122486,95158,19796 -2021-01-13,6461.0,6006.0,5474.0,4851.0,3955.0,756.0,243761,186487,156240,122486,95158,19796 -2021-01-14,7126.0,6538.0,6055.0,5243.0,4312.0,819.0,243761,186487,156240,122486,95158,19796 -2021-01-15,8092.0,7322.0,6818.0,5831.0,4753.0,896.0,243761,186487,156240,122486,95158,19796 -2021-01-16,8750.0,7945.0,7385.0,6370.0,5201.0,959.0,243761,186487,156240,122486,95158,19796 -2021-01-17,9135.0,8253.0,7770.0,6685.0,5495.0,1001.0,243761,186487,156240,122486,95158,19796 -2021-01-18,9688.0,8687.0,8169.0,7000.0,5754.0,1043.0,243761,186487,156240,122486,95158,19796 -2021-01-19,10402.0,9436.0,8841.0,7560.0,6139.0,1113.0,243761,186487,156240,122486,95158,19796 -2021-01-20,11501.0,10367.0,9695.0,8344.0,6706.0,1211.0,243761,186487,156240,122486,95158,19796 -2021-01-21,13146.0,11466.0,10878.0,9331.0,7441.0,1358.0,243761,186487,156240,122486,95158,19796 -2021-01-22,15281.0,13349.0,12537.0,10773.0,8414.0,1533.0,243761,186487,156240,122486,95158,19796 -2021-01-23,17220.0,15099.0,14259.0,12537.0,9688.0,1743.0,243761,186487,156240,122486,95158,19796 -2021-01-24,17941.0,15869.0,15246.0,13356.0,10423.0,1883.0,243761,186487,156240,122486,95158,19796 -2021-01-25,18900.0,16765.0,15981.0,14056.0,10878.0,1960.0,243761,186487,156240,122486,95158,19796 -2021-01-26,20202.0,18165.0,17248.0,15113.0,11522.0,2086.0,243761,186487,156240,122486,95158,19796 -2021-01-27,21623.0,19684.0,18578.0,16345.0,12432.0,2247.0,243761,186487,156240,122486,95158,19796 -2021-01-28,24374.0,22113.0,20832.0,18417.0,14483.0,2485.0,243761,186487,156240,122486,95158,19796 -2021-01-29,27342.0,25116.0,23849.0,20881.0,16324.0,2751.0,243761,186487,156240,122486,95158,19796 -2021-01-30,30632.0,28476.0,27342.0,24486.0,19593.0,3171.0,243761,186487,156240,122486,95158,19796 -2021-01-31,32711.0,30681.0,29589.0,26166.0,21196.0,3381.0,243761,186487,156240,122486,95158,19796 -2021-02-01,34699.0,32851.0,31899.0,28287.0,23037.0,3570.0,243761,186487,156240,122486,95158,19796 -2021-02-02,37667.0,36036.0,34951.0,30807.0,25116.0,3850.0,243761,186487,156240,122486,95158,19796 -2021-02-03,42035.0,40250.0,39417.0,34762.0,28728.0,4305.0,243761,186487,156240,122486,95158,19796 -2021-02-04,48034.0,45619.0,44667.0,39151.0,32508.0,4872.0,243761,186487,156240,122486,95158,19796 -2021-02-05,54215.0,51065.0,50183.0,43974.0,36253.0,5446.0,243761,186487,156240,122486,95158,19796 -2021-02-06,62265.0,59416.0,59045.0,52003.0,43939.0,6447.0,243761,186487,156240,122486,95158,19796 -2021-02-07,65989.0,63091.0,63203.0,55517.0,47159.0,6937.0,243761,186487,156240,122486,95158,19796 -2021-02-08,70245.0,67277.0,66808.0,58702.0,49819.0,7336.0,243761,186487,156240,122486,95158,19796 -2021-02-09,75663.0,72219.0,71568.0,62979.0,53291.0,7777.0,243761,186487,156240,122486,95158,19796 -2021-02-10,82019.0,77483.0,76328.0,66997.0,56630.0,8281.0,243761,186487,156240,122486,95158,19796 -2021-02-11,89649.0,83356.0,81326.0,71288.0,59885.0,8939.0,243761,186487,156240,122486,95158,19796 -2021-02-12,95732.0,88753.0,85869.0,74942.0,62846.0,9590.0,243761,186487,156240,122486,95158,19796 -2021-02-13,101353.0,93233.0,90111.0,78274.0,65625.0,10108.0,243761,186487,156240,122486,95158,19796 -2021-02-14,103166.0,94773.0,91553.0,79359.0,66556.0,10255.0,243761,186487,156240,122486,95158,19796 -2021-02-15,105273.0,96222.0,92673.0,80157.0,67151.0,10402.0,243761,186487,156240,122486,95158,19796 -2021-02-16,108451.0,98462.0,94514.0,81459.0,68026.0,10654.0,243761,186487,156240,122486,95158,19796 -2021-02-17,112994.0,101486.0,96754.0,83034.0,69020.0,10976.0,243761,186487,156240,122486,95158,19796 -2021-02-18,117117.0,104468.0,98966.0,84630.0,70035.0,11270.0,243761,186487,156240,122486,95158,19796 -2021-02-19,120631.0,107219.0,100954.0,85939.0,70966.0,11536.0,243761,186487,156240,122486,95158,19796 -2021-02-20,124012.0,109543.0,102914.0,87360.0,72142.0,11851.0,243761,186487,156240,122486,95158,19796 -2021-02-21,125615.0,110656.0,103740.0,87808.0,72478.0,11942.0,243761,186487,156240,122486,95158,19796 -2021-02-22,127841.0,112182.0,104769.0,88459.0,72884.0,12089.0,243761,186487,156240,122486,95158,19796 -2021-02-23,131887.0,115164.0,106897.0,90118.0,73906.0,12369.0,243761,186487,156240,122486,95158,19796 -2021-02-24,137445.0,119119.0,109886.0,92239.0,75257.0,12754.0,243761,186487,156240,122486,95158,19796 -2021-02-25,144221.0,123648.0,113519.0,94717.0,76930.0,13251.0,243761,186487,156240,122486,95158,19796 -2021-02-26,150822.0,128401.0,117124.0,97118.0,78687.0,13783.0,243761,186487,156240,122486,95158,19796 -2021-02-27,156219.0,131768.0,119658.0,98973.0,80143.0,14189.0,243761,186487,156240,122486,95158,19796 -2021-02-28,158361.0,133126.0,120750.0,99554.0,80626.0,14385.0,243761,186487,156240,122486,95158,19796 -2021-03-01,159824.0,134337.0,121653.0,100093.0,80976.0,14504.0,243761,186487,156240,122486,95158,19796 -2021-03-02,161434.0,135513.0,122507.0,100667.0,81382.0,14630.0,243761,186487,156240,122486,95158,19796 -2021-03-03,164073.0,137333.0,123634.0,101472.0,81914.0,14798.0,243761,186487,156240,122486,95158,19796 -2021-03-04,167370.0,139580.0,125272.0,102557.0,82698.0,15015.0,243761,186487,156240,122486,95158,19796 -2021-03-05,170618.0,141582.0,126826.0,103614.0,83370.0,15239.0,243761,186487,156240,122486,95158,19796 -2021-03-06,173915.0,143591.0,128338.0,104734.0,84224.0,15470.0,243761,186487,156240,122486,95158,19796 -2021-03-07,174902.0,144193.0,128744.0,104979.0,84399.0,15547.0,243761,186487,156240,122486,95158,19796 -2021-03-08,176015.0,144921.0,129199.0,105315.0,84595.0,15624.0,243761,186487,156240,122486,95158,19796 -2021-03-09,177226.0,145838.0,129752.0,105581.0,84798.0,15736.0,243761,186487,156240,122486,95158,19796 -2021-03-10,178409.0,146664.0,130284.0,105889.0,85022.0,15799.0,243761,186487,156240,122486,95158,19796 -2021-03-11,179375.0,147336.0,130669.0,106148.0,85190.0,15862.0,243761,186487,156240,122486,95158,19796 -2021-03-12,180978.0,148239.0,131285.0,106547.0,85449.0,15953.0,243761,186487,156240,122486,95158,19796 -2021-03-13,182980.0,149387.0,132013.0,107051.0,85764.0,16100.0,243761,186487,156240,122486,95158,19796 -2021-03-14,183666.0,149975.0,132342.0,107296.0,85904.0,16149.0,243761,186487,156240,122486,95158,19796 -2021-03-15,184765.0,150738.0,132783.0,107576.0,86107.0,16212.0,243761,186487,156240,122486,95158,19796 -2021-03-16,185822.0,151326.0,133140.0,107856.0,86261.0,16268.0,243761,186487,156240,122486,95158,19796 -2021-03-17,186935.0,151935.0,133497.0,108087.0,86443.0,16324.0,243761,186487,156240,122486,95158,19796 -2021-03-18,187838.0,152537.0,133875.0,108353.0,86611.0,16373.0,243761,186487,156240,122486,95158,19796 -2021-03-19,188776.0,153174.0,134295.0,108633.0,86786.0,16450.0,243761,186487,156240,122486,95158,19796 -2021-03-20,189931.0,153832.0,134820.0,108976.0,87052.0,16534.0,243761,186487,156240,122486,95158,19796 -2021-03-21,190316.0,154119.0,135002.0,109102.0,87157.0,16576.0,243761,186487,156240,122486,95158,19796 -2021-03-22,190876.0,154490.0,135226.0,109242.0,87262.0,16611.0,243761,186487,156240,122486,95158,19796 -2021-03-23,191520.0,154875.0,135478.0,109410.0,87374.0,16646.0,243761,186487,156240,122486,95158,19796 -2021-03-24,192311.0,155372.0,135765.0,109613.0,87486.0,16695.0,243761,186487,156240,122486,95158,19796 -2021-03-25,193032.0,155848.0,136066.0,109823.0,87619.0,16723.0,243761,186487,156240,122486,95158,19796 -2021-03-26,193879.0,156359.0,136444.0,110068.0,87745.0,16779.0,243761,186487,156240,122486,95158,19796 -2021-03-27,194789.0,156870.0,136808.0,110341.0,87969.0,16849.0,243761,186487,156240,122486,95158,19796 -2021-03-28,195202.0,157157.0,136976.0,110460.0,88046.0,16884.0,243761,186487,156240,122486,95158,19796 -2021-03-29,195692.0,157437.0,137130.0,110600.0,88130.0,16912.0,243761,186487,156240,122486,95158,19796 -2021-03-30,196133.0,157738.0,137319.0,110712.0,88200.0,16940.0,243761,186487,156240,122486,95158,19796 -2021-03-31,196672.0,158081.0,137592.0,110873.0,88284.0,16975.0,243761,186487,156240,122486,95158,19796 -2021-04-01,197127.0,158326.0,137739.0,110957.0,88347.0,17003.0,243761,186487,156240,122486,95158,19796 -2021-04-02,197302.0,158431.0,137802.0,111006.0,88375.0,17010.0,243761,186487,156240,122486,95158,19796 -2021-04-03,197449.0,158564.0,137886.0,111055.0,88410.0,17017.0,243761,186487,156240,122486,95158,19796 -2021-04-04,197540.0,158606.0,137907.0,111076.0,88424.0,17024.0,243761,186487,156240,122486,95158,19796 -2021-04-05,197617.0,158634.0,137935.0,111090.0,88431.0,17031.0,243761,186487,156240,122486,95158,19796 -2021-04-06,197785.0,158725.0,137991.0,111139.0,88452.0,17045.0,243761,186487,156240,122486,95158,19796 -2021-04-07,198065.0,158872.0,138082.0,111195.0,88480.0,17073.0,243761,186487,156240,122486,95158,19796 diff --git a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 16-49, not in other eligible groups shown population_tpp.csv b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 16-49, not in other eligible groups shown population_tpp.csv index a0f41e7..a53e8f4 100644 --- a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 16-49, not in other eligible groups shown population_tpp.csv +++ b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 16-49, not in other eligible groups shown population_tpp.csv @@ -1,46 +1,46 @@ -Category,Group,Vaccinated at 07 Apr (n),Previous week's vaccination figure (n),Vaccinated over last 7d (n),Increase in coverage over last 7d (%) -overall,overall,2394367,2283336.0,111031.0,4.9 -Sex,F,1461145,1405159.0,55986.0,4.0 -Sex,M,933142,878101.0,55041.0,6.3 -Age band,16-29,572502,549612.0,22890.0,4.2 -Age band,30-39,712726,684397.0,28329.0,4.1 -Age band,40-49,1109059,1049251.0,59808.0,5.7 -Ethnicity (broad categories),Black,50526,48419.0,2107.0,4.4 -Ethnicity (broad categories),Mixed,33145,31752.0,1393.0,4.4 -Ethnicity (broad categories),Other,47565,45094.0,2471.0,5.5 -Ethnicity (broad categories),South Asian,203252,193151.0,10101.0,5.2 -Ethnicity (broad categories),Unknown,209853,197554.0,12299.0,6.2 -Ethnicity (broad categories),White,1849953,1767290.0,82663.0,4.7 -ethnicity 16 groups, African,33936,32487.0,1449.0,4.5 -ethnicity 16 groups, Bangladeshi or British Bangladeshi,16205,15498.0,707.0,4.6 -ethnicity 16 groups, Caribbean,6566,6293.0,273.0,4.3 -ethnicity 16 groups, Chinese,9674,9177.0,497.0,5.4 -ethnicity 16 groups, Other,37877,35910.0,1967.0,5.5 -ethnicity 16 groups, Other Asian,45290,43414.0,1876.0,4.3 -ethnicity 16 groups,British or Mixed British,1685257,1610490.0,74767.0,4.6 -ethnicity 16 groups,Indian or British Indian,88508,84329.0,4179.0,5.0 -ethnicity 16 groups,Irish,10381,9975.0,406.0,4.1 -ethnicity 16 groups,Other Black,10017,9625.0,392.0,4.1 -ethnicity 16 groups,Other White,154301,146818.0,7483.0,5.1 -ethnicity 16 groups,Other mixed,11914,11438.0,476.0,4.2 -ethnicity 16 groups,Pakistani or British Pakistani,53249,49910.0,3339.0,6.7 -ethnicity 16 groups,Unknown,209853,197547.0,12306.0,6.2 -ethnicity 16 groups,White + Asian,7889,7539.0,350.0,4.6 -ethnicity 16 groups,White + Black African,6454,6188.0,266.0,4.3 -ethnicity 16 groups,White + Black Caribbean,6923,6622.0,301.0,4.5 -Index of Multiple Deprivation (quintiles),1 Most deprived,461692,440048.0,21644.0,4.9 -Index of Multiple Deprivation (quintiles),2,472332,451024.0,21308.0,4.7 -Index of Multiple Deprivation (quintiles),3,490560,469413.0,21147.0,4.5 -Index of Multiple Deprivation (quintiles),4,467047,445319.0,21728.0,4.9 -Index of Multiple Deprivation (quintiles),5 Least deprived,430647,408919.0,21728.0,5.3 -Index of Multiple Deprivation (quintiles),Unknown,72009,68537.0,3472.0,5.1 -BMI,30+,551978,532462.0,19516.0,3.7 -BMI,under 30,1842309,1750791.0,91518.0,5.2 -Chronic cardiac disease,no,2337888,2228079.0,109809.0,4.9 -Chronic cardiac disease,yes,56399,55181.0,1218.0,2.2 -Current COPD,no,2380630,2269897.0,110733.0,4.9 -Current COPD,yes,13657,13363.0,294.0,2.2 -DMARDs,no,2359623,2249380.0,110243.0,4.9 -DMARDs,yes,34664,33880.0,784.0,2.3 -SSRI (last 12 months),no,2027914,1930334.0,97580.0,5.1 -SSRI (last 12 months),yes,366373,352926.0,13447.0,3.8 +Category,Group,Vaccinated at 14 Apr (n),Previous week's vaccination figure (n),Vaccinated over last 7d (n),Increase in coverage over last 7d (%) +overall,overall,2501957,2397541.0,104416.0,4.4 +Sex,F,1512819,1462755.0,50064.0,3.4 +Sex,M,989051,934703.0,54348.0,5.8 +Age band,16-29,582386,572964.0,9422.0,1.6 +Age band,30-39,734951,713398.0,21553.0,3.0 +Age band,40-49,1184533,1111089.0,73444.0,6.6 +Ethnicity (broad categories),Black,52437,50666.0,1771.0,3.5 +Ethnicity (broad categories),Mixed,34426,33208.0,1218.0,3.7 +Ethnicity (broad categories),Other,49931,47712.0,2219.0,4.7 +Ethnicity (broad categories),South Asian,212086,203931.0,8155.0,4.0 +Ethnicity (broad categories),Unknown,220626,209398.0,11228.0,5.4 +Ethnicity (broad categories),White,1932350,1852536.0,79814.0,4.3 +ethnicity 16 groups, African,35182,34020.0,1162.0,3.4 +ethnicity 16 groups, Bangladeshi or British Bangladeshi,16807,16233.0,574.0,3.5 +ethnicity 16 groups, Caribbean,6825,6580.0,245.0,3.7 +ethnicity 16 groups, Chinese,10227,9695.0,532.0,5.5 +ethnicity 16 groups, Other,39683,38003.0,1680.0,4.4 +ethnicity 16 groups, Other Asian,47110,45437.0,1673.0,3.7 +ethnicity 16 groups,British or Mixed British,1758365,1687546.0,70819.0,4.2 +ethnicity 16 groups,Indian or British Indian,92190,88879.0,3311.0,3.7 +ethnicity 16 groups,Irish,10913,10402.0,511.0,4.9 +ethnicity 16 groups,Other Black,10423,10066.0,357.0,3.5 +ethnicity 16 groups,Other White,163072,154588.0,8484.0,5.5 +ethnicity 16 groups,Other mixed,12397,11928.0,469.0,3.9 +ethnicity 16 groups,Pakistani or British Pakistani,55993,53382.0,2611.0,4.9 +ethnicity 16 groups,Unknown,220626,209398.0,11228.0,5.4 +ethnicity 16 groups,White + Asian,8197,7903.0,294.0,3.7 +ethnicity 16 groups,White + Black African,6713,6461.0,252.0,3.9 +ethnicity 16 groups,White + Black Caribbean,7147,6937.0,210.0,3.0 +Index of Multiple Deprivation (quintiles),1 Most deprived,480788,462259.0,18529.0,4.0 +Index of Multiple Deprivation (quintiles),2,491596,472927.0,18669.0,3.9 +Index of Multiple Deprivation (quintiles),3,511245,490959.0,20286.0,4.1 +Index of Multiple Deprivation (quintiles),4,489734,467586.0,22148.0,4.7 +Index of Multiple Deprivation (quintiles),5 Least deprived,453138,431312.0,21826.0,5.1 +Index of Multiple Deprivation (quintiles),Unknown,75369,72422.0,2947.0,4.1 +BMI,30+,569513,552636.0,16877.0,3.1 +BMI,under 30,1932357,1844822.0,87535.0,4.7 +Chronic cardiac disease,no,2444736,2341038.0,103698.0,4.4 +Chronic cardiac disease,yes,57134,56420.0,714.0,1.3 +Current COPD,no,2487933,2383794.0,104139.0,4.4 +Current COPD,yes,13937,13664.0,273.0,2.0 +DMARDs,no,2466492,2362724.0,103768.0,4.4 +DMARDs,yes,35378,34734.0,644.0,1.9 +SSRI (last 12 months),no,2121924,2029720.0,92204.0,4.5 +SSRI (last 12 months),yes,379946,367738.0,12208.0,3.3 diff --git a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 50-54 population_tpp.csv b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 50-54 population_tpp.csv index edc1bbe..8fbc403 100644 --- a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 50-54 population_tpp.csv +++ b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 50-54 population_tpp.csv @@ -1,45 +1,45 @@ -Category,Group,Vaccinated at 07 Apr (n),Vaccinated at 07 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) -overall,overall,1287418,82.6,1558144,81.0,1.6 -Sex,F,652631,85.9,759808,84.5,1.4 -Sex,M,634781,79.5,798322,77.7,1.8 -Ethnicity (broad categories),Black,21329,57.0,37436,54.9,2.1 -Ethnicity (broad categories),Mixed,10164,66.8,15218,65.2,1.6 -Ethnicity (broad categories),Other,17920,63.3,28294,61.5,1.8 -Ethnicity (broad categories),South Asian,62286,73.1,85176,71.0,2.1 -Ethnicity (broad categories),Unknown,140679,74.1,189952,72.3,1.8 -Ethnicity (broad categories),White,1035027,86.1,1202054,84.6,1.5 -ethnicity 16 groups, African,11557,58.5,19754,56.2,2.3 -ethnicity 16 groups, Bangladeshi or British Bangladeshi,3878,79.1,4900,77.1,2.0 -ethnicity 16 groups, Caribbean,4921,52.4,9387,50.9,1.5 -ethnicity 16 groups, Chinese,4746,70.0,6783,67.6,2.4 -ethnicity 16 groups, Other,13181,61.3,21504,59.7,1.6 -ethnicity 16 groups, Other Asian,15190,73.2,20748,71.4,1.8 -ethnicity 16 groups,British or Mixed British,958482,88.7,1080275,87.2,1.5 -ethnicity 16 groups,Indian or British Indian,27692,78.4,35336,76.6,1.8 -ethnicity 16 groups,Irish,6160,79.6,7742,78.4,1.2 -ethnicity 16 groups,Other Black,4844,58.4,8295,56.4,2.0 -ethnicity 16 groups,Other White,70378,61.7,114044,60.4,1.3 -ethnicity 16 groups,Other mixed,3633,65.6,5537,64.1,1.5 -ethnicity 16 groups,Pakistani or British Pakistani,15526,64.2,24185,61.1,3.1 -ethnicity 16 groups,Unknown,140679,74.1,189959,72.2,1.9 -ethnicity 16 groups,White + Asian,2261,76.7,2947,75.1,1.6 -ethnicity 16 groups,White + Black African,2065,62.5,3304,60.8,1.7 -ethnicity 16 groups,White + Black Caribbean,2212,64.2,3444,62.8,1.4 -Index of Multiple Deprivation (quintiles),1 Most deprived,198821,73.0,272230,71.0,2.0 -Index of Multiple Deprivation (quintiles),2,230755,79.1,291816,77.3,1.8 -Index of Multiple Deprivation (quintiles),3,273371,83.7,326585,82.3,1.4 -Index of Multiple Deprivation (quintiles),4,280322,86.4,324597,85.0,1.4 -Index of Multiple Deprivation (quintiles),5 Least deprived,278215,89.2,311731,87.8,1.4 -Index of Multiple Deprivation (quintiles),Unknown,25921,83.1,31178,81.5,1.6 -BMI,30+,298690,88.4,337855,87.1,1.3 -BMI,under 30,988722,81.0,1220282,79.4,1.6 -Chronic cardiac disease,no,1246581,82.5,1510985,80.9,1.6 -Chronic cardiac disease,yes,40831,86.6,47145,85.7,0.9 -Current COPD,no,1271557,82.6,1539482,81.0,1.6 -Current COPD,yes,15855,85.0,18655,84.1,0.9 -DMARDs,no,1270717,82.5,1539636,80.9,1.6 -DMARDs,yes,16695,90.3,18494,89.4,0.9 -"Psychosis, schizophrenia, or bipolar",no,1272761,82.7,1538425,81.1,1.6 -"Psychosis, schizophrenia, or bipolar",yes,14651,74.3,19712,73.2,1.1 -SSRI (last 12 months),no,1122695,81.7,1373365,80.1,1.6 -SSRI (last 12 months),yes,164710,89.1,184765,87.7,1.4 +Category,Group,Vaccinated at 14 Apr (n),Vaccinated at 14 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) +overall,overall,1302965,83.6,1558172,82.7,0.9 +Sex,F,659232,86.8,759843,85.9,0.9 +Sex,M,643727,80.6,798322,79.5,1.1 +Ethnicity (broad categories),Black,21875,58.4,37471,57.0,1.4 +Ethnicity (broad categories),Mixed,10374,68.1,15225,66.9,1.2 +Ethnicity (broad categories),Other,18291,64.6,28315,63.4,1.2 +Ethnicity (broad categories),South Asian,63665,74.7,85197,73.2,1.5 +Ethnicity (broad categories),Unknown,142156,75.1,189392,74.0,1.1 +Ethnicity (broad categories),White,1046591,87.0,1202558,86.1,0.9 +ethnicity 16 groups, African,11900,60.2,19768,58.6,1.6 +ethnicity 16 groups, Bangladeshi or British Bangladeshi,3941,80.3,4907,79.0,1.3 +ethnicity 16 groups, Caribbean,5012,53.4,9394,52.4,1.0 +ethnicity 16 groups, Chinese,4837,71.2,6797,69.9,1.3 +ethnicity 16 groups, Other,13454,62.5,21511,61.4,1.1 +ethnicity 16 groups, Other Asian,15484,74.6,20769,73.2,1.4 +ethnicity 16 groups,British or Mixed British,968751,89.6,1080625,88.8,0.8 +ethnicity 16 groups,Indian or British Indian,28161,79.6,35357,78.4,1.2 +ethnicity 16 groups,Irish,6230,80.3,7756,79.6,0.7 +ethnicity 16 groups,Other Black,4963,59.7,8316,58.3,1.4 +ethnicity 16 groups,Other White,71554,62.7,114121,61.7,1.0 +ethnicity 16 groups,Other mixed,3703,66.9,5537,65.7,1.2 +ethnicity 16 groups,Pakistani or British Pakistani,16079,66.5,24178,64.3,2.2 +ethnicity 16 groups,Unknown,142219,75.1,189455,74.0,1.1 +ethnicity 16 groups,White + Asian,2289,77.9,2940,76.9,1.0 +ethnicity 16 groups,White + Black African,2121,64.3,3297,62.6,1.7 +ethnicity 16 groups,White + Black Caribbean,2247,65.4,3437,64.2,1.2 +Index of Multiple Deprivation (quintiles),1 Most deprived,202839,74.5,272216,73.1,1.4 +Index of Multiple Deprivation (quintiles),2,234220,80.3,291844,79.1,1.2 +Index of Multiple Deprivation (quintiles),3,276164,84.5,326641,83.7,0.8 +Index of Multiple Deprivation (quintiles),4,282933,87.2,324562,86.4,0.8 +Index of Multiple Deprivation (quintiles),5 Least deprived,280427,90.0,311647,89.3,0.7 +Index of Multiple Deprivation (quintiles),Unknown,26376,84.4,31248,83.1,1.3 +BMI,30+,301630,89.3,337904,88.4,0.9 +BMI,under 30,1001329,82.1,1220254,81.1,1.0 +Chronic cardiac disease,no,1261729,83.5,1510950,82.5,1.0 +Chronic cardiac disease,yes,41223,87.3,47208,86.7,0.6 +Current COPD,no,1286978,83.6,1539489,82.6,1.0 +Current COPD,yes,15981,85.6,18669,85.0,0.6 +DMARDs,no,1286145,83.5,1539657,82.6,0.9 +DMARDs,yes,16807,90.8,18501,90.3,0.5 +"Psychosis, schizophrenia, or bipolar",no,1288098,83.7,1538453,82.8,0.9 +"Psychosis, schizophrenia, or bipolar",yes,14854,75.4,19705,74.4,1.0 +SSRI (last 12 months),no,1136338,82.8,1373162,81.8,1.0 +SSRI (last 12 months),yes,166614,90.1,184996,89.2,0.9 diff --git a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 55-59 population_tpp.csv b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 55-59 population_tpp.csv index 54338d0..5dbf597 100644 --- a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 55-59 population_tpp.csv +++ b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 55-59 population_tpp.csv @@ -1,45 +1,45 @@ -Category,Group,Vaccinated at 07 Apr (n),Vaccinated at 07 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) -overall,overall,1304372,86.5,1508269,85.0,1.5 -Sex,F,656453,88.6,741006,87.3,1.3 -Sex,M,647913,84.4,767256,82.8,1.6 -Ethnicity (broad categories),Black,18753,60.7,30877,59.1,1.6 -Ethnicity (broad categories),Mixed,8652,70.7,12236,69.5,1.2 -Ethnicity (broad categories),Other,14882,67.6,22022,65.8,1.8 -Ethnicity (broad categories),South Asian,46739,78.2,59759,76.7,1.5 -Ethnicity (broad categories),Unknown,132216,77.1,171458,75.4,1.7 -Ethnicity (broad categories),White,1083124,89.4,1211903,87.9,1.5 -ethnicity 16 groups, African,7917,62.2,12719,60.4,1.8 -ethnicity 16 groups, Bangladeshi or British Bangladeshi,2436,81.9,2975,80.7,1.2 -ethnicity 16 groups, Caribbean,6384,58.2,10969,56.9,1.3 -ethnicity 16 groups, Chinese,4438,72.4,6132,70.2,2.2 -ethnicity 16 groups, Other,10437,65.7,15890,64.1,1.6 -ethnicity 16 groups, Other Asian,11445,77.0,14854,75.4,1.6 -ethnicity 16 groups,British or Mixed British,1015994,91.3,1113350,89.8,1.5 -ethnicity 16 groups,Indian or British Indian,23450,83.0,28252,81.9,1.1 -ethnicity 16 groups,Irish,6349,83.0,7651,81.9,1.1 -ethnicity 16 groups,Other Black,4459,62.0,7196,60.2,1.8 -ethnicity 16 groups,Other White,60802,66.9,90923,65.7,1.2 -ethnicity 16 groups,Other mixed,3052,70.4,4333,69.3,1.1 -ethnicity 16 groups,Pakistani or British Pakistani,9408,68.8,13678,66.6,2.2 -ethnicity 16 groups,Unknown,132195,77.1,171430,75.4,1.7 -ethnicity 16 groups,White + Asian,1778,78.6,2261,77.7,0.9 -ethnicity 16 groups,White + Black African,1575,67.8,2324,66.0,1.8 -ethnicity 16 groups,White + Black Caribbean,2247,67.7,3318,66.5,1.2 -Index of Multiple Deprivation (quintiles),1 Most deprived,193403,78.8,245343,76.9,1.9 -Index of Multiple Deprivation (quintiles),2,230419,83.6,275730,81.9,1.7 -Index of Multiple Deprivation (quintiles),3,281967,87.3,323015,85.9,1.4 -Index of Multiple Deprivation (quintiles),4,289191,89.2,324184,87.9,1.3 -Index of Multiple Deprivation (quintiles),5 Least deprived,283353,91.4,310065,90.1,1.3 -Index of Multiple Deprivation (quintiles),Unknown,26026,87.0,29918,85.4,1.6 -BMI,30+,317114,91.0,348502,89.8,1.2 -BMI,under 30,987252,85.1,1159753,83.6,1.5 -Chronic cardiac disease,no,1239777,86.3,1436358,84.8,1.5 -Chronic cardiac disease,yes,64589,89.8,71904,89.1,0.7 -Current COPD,no,1279929,86.4,1480619,84.9,1.5 -Current COPD,yes,24437,88.4,27636,87.8,0.6 -DMARDs,no,1284997,86.4,1487220,84.9,1.5 -DMARDs,yes,19362,92.0,21042,91.2,0.8 -"Psychosis, schizophrenia, or bipolar",no,1289771,86.6,1489509,85.1,1.5 -"Psychosis, schizophrenia, or bipolar",yes,14595,77.8,18753,76.8,1.0 -SSRI (last 12 months),no,1152711,85.9,1341998,84.4,1.5 -SSRI (last 12 months),yes,151655,91.2,166264,90.0,1.2 +Category,Group,Vaccinated at 14 Apr (n),Vaccinated at 14 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) +overall,overall,1313536,87.1,1508080,86.5,0.6 +Sex,F,660534,89.1,740964,88.6,0.5 +Sex,M,652995,85.1,767102,84.5,0.6 +Ethnicity (broad categories),Black,19103,61.9,30870,60.8,1.1 +Ethnicity (broad categories),Mixed,8736,71.4,12229,70.7,0.7 +Ethnicity (broad categories),Other,15078,68.4,22029,67.6,0.8 +Ethnicity (broad categories),South Asian,47334,79.2,59794,78.3,0.9 +Ethnicity (broad categories),Unknown,132937,77.8,170968,77.1,0.7 +Ethnicity (broad categories),White,1090348,89.9,1212176,89.4,0.5 +ethnicity 16 groups, African,8078,63.5,12719,62.3,1.2 +ethnicity 16 groups, Bangladeshi or British Bangladeshi,2457,82.4,2982,81.7,0.7 +ethnicity 16 groups, Caribbean,6482,59.2,10955,58.3,0.9 +ethnicity 16 groups, Chinese,4487,73.2,6132,72.4,0.8 +ethnicity 16 groups, Other,10591,66.6,15904,65.8,0.8 +ethnicity 16 groups, Other Asian,11571,77.9,14861,77.1,0.8 +ethnicity 16 groups,British or Mixed British,1022427,91.8,1113539,91.3,0.5 +ethnicity 16 groups,Indian or British Indian,23695,83.8,28287,83.0,0.8 +ethnicity 16 groups,Irish,6384,83.4,7658,82.9,0.5 +ethnicity 16 groups,Other Black,4543,63.1,7196,62.1,1.0 +ethnicity 16 groups,Other White,61537,67.6,90986,66.9,0.7 +ethnicity 16 groups,Other mixed,3073,71.0,4326,70.4,0.6 +ethnicity 16 groups,Pakistani or British Pakistani,9611,70.3,13671,69.0,1.3 +ethnicity 16 groups,Unknown,132930,77.8,170954,77.1,0.7 +ethnicity 16 groups,White + Asian,1792,79.3,2261,78.6,0.7 +ethnicity 16 groups,White + Black African,1589,68.4,2324,67.5,0.9 +ethnicity 16 groups,White + Black Caribbean,2275,68.4,3325,67.8,0.6 +Index of Multiple Deprivation (quintiles),1 Most deprived,195748,79.8,245280,78.9,0.9 +Index of Multiple Deprivation (quintiles),2,232582,84.3,275737,83.6,0.7 +Index of Multiple Deprivation (quintiles),3,283654,87.8,322966,87.3,0.5 +Index of Multiple Deprivation (quintiles),4,290717,89.7,324135,89.2,0.5 +Index of Multiple Deprivation (quintiles),5 Least deprived,284529,91.8,309988,91.4,0.4 +Index of Multiple Deprivation (quintiles),Unknown,26299,87.8,29967,87.0,0.8 +BMI,30+,318878,91.5,348390,91.0,0.5 +BMI,under 30,994651,85.8,1159683,85.1,0.7 +Chronic cardiac disease,no,1248464,86.9,1436043,86.3,0.6 +Chronic cardiac disease,yes,65065,90.3,72030,89.9,0.4 +Current COPD,no,1288945,87.1,1480423,86.5,0.6 +Current COPD,yes,24584,88.9,27650,88.4,0.5 +DMARDs,no,1294076,87.0,1487024,86.4,0.6 +DMARDs,yes,19453,92.4,21042,92.1,0.3 +"Psychosis, schizophrenia, or bipolar",no,1298745,87.2,1489320,86.6,0.6 +"Psychosis, schizophrenia, or bipolar",yes,14784,78.9,18746,77.9,1.0 +SSRI (last 12 months),no,1160740,86.5,1341676,85.9,0.6 +SSRI (last 12 months),yes,152789,91.8,166397,91.3,0.5 diff --git a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 60-64 population_tpp.csv b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 60-64 population_tpp.csv index 0a67154..4f137a6 100644 --- a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 60-64 population_tpp.csv +++ b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 60-64 population_tpp.csv @@ -1,55 +1,55 @@ -Category,Group,Vaccinated at 07 Apr (n),Vaccinated at 07 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) -overall,overall,1141289,89.4,1276562,89.0,0.4 -Sex,F,576009,90.7,634725,90.3,0.4 -Sex,M,565271,88.1,641823,87.6,0.5 -Ethnicity (broad categories),Black,12474,63.9,19530,62.9,1.0 -Ethnicity (broad categories),Mixed,5901,74.3,7938,73.8,0.5 -Ethnicity (broad categories),Other,11417,70.6,16177,69.9,0.7 -Ethnicity (broad categories),South Asian,42714,81.6,52346,80.8,0.8 -Ethnicity (broad categories),Unknown,113974,80.6,141351,80.1,0.5 -Ethnicity (broad categories),White,954793,91.9,1039206,91.5,0.4 -ethnicity 16 groups, African,4935,64.1,7700,62.9,1.2 -ethnicity 16 groups, Bangladeshi or British Bangladeshi,1904,84.7,2247,83.8,0.9 -ethnicity 16 groups, Caribbean,4900,62.4,7847,61.6,0.8 -ethnicity 16 groups, Chinese,3535,74.3,4760,73.5,0.8 -ethnicity 16 groups, Other,7875,69.0,11410,68.3,0.7 -ethnicity 16 groups, Other Asian,8841,79.6,11102,78.9,0.7 -ethnicity 16 groups,British or Mixed British,899486,93.5,962290,93.1,0.4 -ethnicity 16 groups,Indian or British Indian,22512,85.8,26229,85.3,0.5 -ethnicity 16 groups,Irish,5628,86.0,6545,85.6,0.4 -ethnicity 16 groups,Other Black,2646,66.3,3990,65.6,0.7 -ethnicity 16 groups,Other White,49672,70.6,70371,70.1,0.5 -ethnicity 16 groups,Other mixed,2233,73.7,3031,73.2,0.5 -ethnicity 16 groups,Pakistani or British Pakistani,9464,74.1,12768,72.7,1.4 -ethnicity 16 groups,Unknown,113981,80.6,141358,80.1,0.5 -ethnicity 16 groups,White + Asian,1232,84.2,1463,83.3,0.9 -ethnicity 16 groups,White + Black African,1057,71.2,1484,70.3,0.9 -ethnicity 16 groups,White + Black Caribbean,1379,70.4,1960,70.0,0.4 -Index of Multiple Deprivation (quintiles),1 Most deprived,164668,83.0,198303,82.3,0.7 -Index of Multiple Deprivation (quintiles),2,201579,87.1,231392,86.6,0.5 -Index of Multiple Deprivation (quintiles),3,249634,90.1,277137,89.7,0.4 -Index of Multiple Deprivation (quintiles),4,254926,91.5,278649,91.2,0.3 -Index of Multiple Deprivation (quintiles),5 Least deprived,247429,93.3,265188,93.0,0.3 -Index of Multiple Deprivation (quintiles),Unknown,23044,89.0,25886,88.2,0.8 -BMI,30+,287938,93.0,309708,92.6,0.4 -BMI,under 30,853342,88.3,966840,87.8,0.5 -Chronic cardiac disease,no,1055334,89.2,1183252,88.7,0.5 -Chronic cardiac disease,yes,85953,92.1,93296,91.9,0.2 -Current COPD,no,1109724,89.3,1242045,88.9,0.4 -Current COPD,yes,31556,91.5,34503,91.2,0.3 -DMARDs,no,1121827,89.3,1255821,88.9,0.4 -DMARDs,yes,19453,93.9,20727,93.6,0.3 -Dementia,no,1137941,89.4,1272873,89.0,0.4 -Dementia,yes,3339,90.9,3675,90.3,0.6 -"Psychosis, schizophrenia, or bipolar",no,1129149,89.5,1261848,89.0,0.5 -"Psychosis, schizophrenia, or bipolar",yes,12131,82.5,14700,82.0,0.5 -SSRI (last 12 months),no,1021727,89.0,1148315,88.5,0.5 -SSRI (last 12 months),yes,119553,93.2,128240,92.8,0.4 -Chemo or radiotherapy,no,1124333,89.3,1258544,88.9,0.4 -Chemo or radiotherapy,yes,16954,94.2,18004,93.8,0.4 -Cancer (lung),no,1140237,89.4,1275379,89.0,0.4 -Cancer (lung),yes,1043,88.7,1176,88.1,0.6 -Cancer (excluding lung/haem),no,1073947,89.2,1204574,88.7,0.5 -Cancer (excluding lung/haem),yes,67333,93.6,71974,93.2,0.4 -Cancer (haematological),no,1138193,89.4,1273223,89.0,0.4 -Cancer (haematological),yes,3087,92.8,3325,92.8,0.0 +Category,Group,Vaccinated at 14 Apr (n),Vaccinated at 14 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) +overall,overall,1145434,89.8,1275925,89.4,0.4 +Sex,F,577962,91.1,634543,90.8,0.3 +Sex,M,567462,88.5,641375,88.1,0.4 +Ethnicity (broad categories),Black,12635,64.8,19509,63.9,0.9 +Ethnicity (broad categories),Mixed,5950,74.9,7945,74.4,0.5 +Ethnicity (broad categories),Other,11522,71.1,16198,70.6,0.5 +Ethnicity (broad categories),South Asian,43120,82.3,52388,81.7,0.6 +Ethnicity (broad categories),Unknown,114086,81.0,140763,80.7,0.3 +Ethnicity (broad categories),White,958111,92.2,1039108,91.9,0.3 +ethnicity 16 groups, African,5005,65.1,7686,64.1,1.0 +ethnicity 16 groups, Bangladeshi or British Bangladeshi,1925,85.4,2254,84.5,0.9 +ethnicity 16 groups, Caribbean,4963,63.4,7833,62.6,0.8 +ethnicity 16 groups, Chinese,3556,74.8,4753,74.4,0.4 +ethnicity 16 groups, Other,7973,69.7,11445,69.0,0.7 +ethnicity 16 groups, Other Asian,8904,80.3,11088,79.7,0.6 +ethnicity 16 groups,British or Mixed British,902412,93.8,962227,93.5,0.3 +ethnicity 16 groups,Indian or British Indian,22645,86.2,26264,85.9,0.3 +ethnicity 16 groups,Irish,5656,86.4,6545,86.0,0.4 +ethnicity 16 groups,Other Black,2667,66.8,3990,66.3,0.5 +ethnicity 16 groups,Other White,50029,71.1,70315,70.6,0.5 +ethnicity 16 groups,Other mixed,2254,74.2,3038,73.7,0.5 +ethnicity 16 groups,Pakistani or British Pakistani,9639,75.5,12775,74.2,1.3 +ethnicity 16 groups,Unknown,114100,81.0,140791,80.7,0.3 +ethnicity 16 groups,White + Asian,1239,84.7,1463,84.2,0.5 +ethnicity 16 groups,White + Black African,1071,72.2,1484,71.2,1.0 +ethnicity 16 groups,White + Black Caribbean,1386,70.7,1960,70.4,0.3 +Index of Multiple Deprivation (quintiles),1 Most deprived,165746,83.6,198170,83.1,0.5 +Index of Multiple Deprivation (quintiles),2,202538,87.6,231259,87.2,0.4 +Index of Multiple Deprivation (quintiles),3,250383,90.4,276976,90.1,0.3 +Index of Multiple Deprivation (quintiles),4,255675,91.8,278523,91.5,0.3 +Index of Multiple Deprivation (quintiles),5 Least deprived,247891,93.5,265034,93.3,0.2 +Index of Multiple Deprivation (quintiles),Unknown,23198,89.4,25956,89.0,0.4 +BMI,30+,288974,93.3,309631,93.0,0.3 +BMI,under 30,856450,88.6,966280,88.3,0.3 +Chronic cardiac disease,no,1059121,89.6,1182545,89.2,0.4 +Chronic cardiac disease,yes,86303,92.4,93366,92.2,0.2 +Current COPD,no,1113777,89.7,1241429,89.4,0.3 +Current COPD,yes,31654,91.8,34482,91.5,0.3 +DMARDs,no,1125901,89.7,1255177,89.4,0.3 +DMARDs,yes,19523,94.1,20741,93.9,0.2 +Dementia,no,1142064,89.8,1272243,89.4,0.4 +Dementia,yes,3360,91.4,3675,91.0,0.4 +"Psychosis, schizophrenia, or bipolar",no,1133223,89.9,1261218,89.5,0.4 +"Psychosis, schizophrenia, or bipolar",yes,12208,83.0,14700,82.5,0.5 +SSRI (last 12 months),no,1025248,89.3,1147531,89.0,0.3 +SSRI (last 12 months),yes,120183,93.6,128387,93.3,0.3 +Chemo or radiotherapy,no,1128407,89.7,1257900,89.4,0.3 +Chemo or radiotherapy,yes,17017,94.4,18018,94.2,0.2 +Cancer (lung),no,1144374,89.8,1274735,89.4,0.4 +Cancer (lung),yes,1057,89.3,1183,88.8,0.5 +Cancer (excluding lung/haem),no,1077783,89.5,1203867,89.2,0.3 +Cancer (excluding lung/haem),yes,67648,93.9,72051,93.6,0.3 +Cancer (haematological),no,1142323,89.8,1272586,89.4,0.4 +Cancer (haematological),yes,3101,93.1,3332,92.9,0.2 diff --git a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 65-69 population_tpp.csv b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 65-69 population_tpp.csv index efe0a2c..6ef4304 100644 --- a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 65-69 population_tpp.csv +++ b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 65-69 population_tpp.csv @@ -1,57 +1,57 @@ -Category,Group,Vaccinated at 07 Apr (n),Vaccinated at 07 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) -overall,overall,985358,91.9,1071630,91.8,0.1 -Sex,F,506926,92.6,547519,92.4,0.2 -Sex,M,478429,91.3,524104,91.1,0.2 -Ethnicity (broad categories),Black,7301,67.7,10787,67.2,0.5 -Ethnicity (broad categories),Mixed,3787,77.0,4921,76.4,0.6 -Ethnicity (broad categories),Other,8771,73.9,11872,73.6,0.3 -Ethnicity (broad categories),South Asian,36421,84.0,43351,83.6,0.4 -Ethnicity (broad categories),Unknown,84644,83.6,101290,83.4,0.2 -Ethnicity (broad categories),White,844431,93.9,899402,93.7,0.2 -ethnicity 16 groups, African,2779,65.0,4277,64.5,0.5 -ethnicity 16 groups, Bangladeshi or British Bangladeshi,1477,85.8,1722,85.4,0.4 -ethnicity 16 groups, Caribbean,3066,68.3,4487,67.7,0.6 -ethnicity 16 groups, Chinese,2835,74.9,3787,74.5,0.4 -ethnicity 16 groups, Other,5936,73.4,8085,73.1,0.3 -ethnicity 16 groups, Other Asian,6692,82.7,8092,82.4,0.3 -ethnicity 16 groups,British or Mixed British,799540,95.0,841981,94.8,0.2 -ethnicity 16 groups,Indian or British Indian,20062,88.1,22778,87.8,0.3 -ethnicity 16 groups,Irish,5859,89.6,6538,89.4,0.2 -ethnicity 16 groups,Other Black,1456,72.2,2016,71.9,0.3 -ethnicity 16 groups,Other White,39004,76.7,50855,76.5,0.2 -ethnicity 16 groups,Other mixed,1463,77.1,1897,76.8,0.3 -ethnicity 16 groups,Pakistani or British Pakistani,8190,76.1,10759,75.3,0.8 -ethnicity 16 groups,Unknown,84679,83.6,101318,83.4,0.2 -ethnicity 16 groups,White + Asian,868,85.5,1015,84.8,0.7 -ethnicity 16 groups,White + Black African,630,71.4,882,69.8,1.6 -ethnicity 16 groups,White + Black Caribbean,826,73.8,1120,73.8,0.0 -Index of Multiple Deprivation (quintiles),1 Most deprived,133119,86.9,153111,86.6,0.3 -Index of Multiple Deprivation (quintiles),2,169953,90.2,188461,90.0,0.2 -Index of Multiple Deprivation (quintiles),3,218792,92.4,236838,92.2,0.2 -Index of Multiple Deprivation (quintiles),4,223797,93.5,239421,93.4,0.1 -Index of Multiple Deprivation (quintiles),5 Least deprived,219807,94.7,232064,94.6,0.1 -Index of Multiple Deprivation (quintiles),Unknown,19887,91.5,21728,91.3,0.2 -BMI,30+,252931,94.5,267708,94.3,0.2 -BMI,under 30,732417,91.1,803915,90.9,0.2 -Chronic cardiac disease,no,881125,91.7,960505,91.6,0.1 -Chronic cardiac disease,yes,104230,93.8,111111,93.6,0.2 -Current COPD,no,947338,91.9,1030974,91.7,0.2 -Current COPD,yes,38017,93.5,40649,93.4,0.1 -DMARDs,no,966497,91.9,1051827,91.7,0.2 -DMARDs,yes,18858,95.3,19796,95.2,0.1 -Dementia,no,980147,91.9,1065981,91.8,0.1 -Dementia,yes,5208,92.3,5642,91.9,0.4 -"Psychosis, schizophrenia, or bipolar",no,975408,92.0,1059975,91.9,0.1 -"Psychosis, schizophrenia, or bipolar",yes,9940,85.3,11648,85.0,0.3 -Learning disability,no,983087,92.0,1069096,91.8,0.2 -Learning disability,yes,2261,89.5,2527,88.9,0.6 -SSRI (last 12 months),no,898989,91.7,980693,91.5,0.2 -SSRI (last 12 months),yes,86366,95.0,90930,94.8,0.2 -Chemo or radiotherapy,no,966602,91.9,1051918,91.7,0.2 -Chemo or radiotherapy,yes,18753,95.2,19698,95.1,0.1 -Cancer (lung),no,983710,91.9,1069838,91.8,0.1 -Cancer (lung),yes,1645,92.2,1785,92.2,0.0 -Cancer (excluding lung/haem),no,902132,91.7,984011,91.5,0.2 -Cancer (excluding lung/haem),yes,83223,95.0,87612,94.9,0.1 -Cancer (haematological),no,981918,91.9,1067955,91.8,0.1 -Cancer (haematological),yes,3437,93.9,3661,93.7,0.2 +Category,Group,Vaccinated at 14 Apr (n),Vaccinated at 14 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) +overall,overall,987174,92.1,1071287,92.0,0.1 +Sex,F,507808,92.8,547449,92.6,0.2 +Sex,M,479360,91.5,523831,91.3,0.2 +Ethnicity (broad categories),Black,7364,68.2,10801,67.7,0.5 +Ethnicity (broad categories),Mixed,3815,77.5,4921,77.0,0.5 +Ethnicity (broad categories),Other,8827,74.2,11893,73.9,0.3 +Ethnicity (broad categories),South Asian,36645,84.5,43372,84.0,0.5 +Ethnicity (broad categories),Unknown,84567,83.8,100863,83.7,0.1 +Ethnicity (broad categories),White,845943,94.1,899430,93.9,0.2 +ethnicity 16 groups, African,2814,65.6,4291,64.9,0.7 +ethnicity 16 groups, Bangladeshi or British Bangladeshi,1491,86.6,1722,86.2,0.4 +ethnicity 16 groups, Caribbean,3080,68.6,4487,68.3,0.3 +ethnicity 16 groups, Chinese,2849,75.2,3787,74.9,0.3 +ethnicity 16 groups, Other,5978,73.8,8099,73.5,0.3 +ethnicity 16 groups, Other Asian,6734,83.1,8106,82.7,0.4 +ethnicity 16 groups,British or Mixed British,800947,95.1,842086,95.0,0.1 +ethnicity 16 groups,Indian or British Indian,20132,88.4,22778,88.1,0.3 +ethnicity 16 groups,Irish,5873,89.7,6545,89.5,0.2 +ethnicity 16 groups,Other Black,1463,72.3,2023,72.0,0.3 +ethnicity 16 groups,Other White,39109,77.0,50792,76.7,0.3 +ethnicity 16 groups,Other mixed,1470,77.5,1897,77.1,0.4 +ethnicity 16 groups,Pakistani or British Pakistani,8288,77.0,10759,76.2,0.8 +ethnicity 16 groups,Unknown,84588,83.8,100884,83.7,0.1 +ethnicity 16 groups,White + Asian,875,85.6,1022,84.9,0.7 +ethnicity 16 groups,White + Black African,644,72.4,889,70.9,1.5 +ethnicity 16 groups,White + Black Caribbean,833,74.4,1120,73.8,0.6 +Index of Multiple Deprivation (quintiles),1 Most deprived,133637,87.3,153020,87.0,0.3 +Index of Multiple Deprivation (quintiles),2,170359,90.4,188398,90.2,0.2 +Index of Multiple Deprivation (quintiles),3,219121,92.6,236740,92.4,0.2 +Index of Multiple Deprivation (quintiles),4,224098,93.6,239358,93.5,0.1 +Index of Multiple Deprivation (quintiles),5 Least deprived,219989,94.8,231987,94.7,0.1 +Index of Multiple Deprivation (quintiles),Unknown,19971,91.7,21777,91.5,0.2 +BMI,30+,253372,94.7,267645,94.5,0.2 +BMI,under 30,733803,91.3,803635,91.1,0.2 +Chronic cardiac disease,no,882602,91.9,960043,91.8,0.1 +Chronic cardiac disease,yes,104573,94.0,111237,93.8,0.2 +Current COPD,no,949067,92.1,1030638,91.9,0.2 +Current COPD,yes,38108,93.7,40649,93.6,0.1 +DMARDs,no,968268,92.1,1051470,91.9,0.2 +DMARDs,yes,18900,95.4,19810,95.2,0.2 +Dementia,no,981932,92.1,1065624,92.0,0.1 +Dementia,yes,5236,92.6,5656,92.3,0.3 +"Psychosis, schizophrenia, or bipolar",no,977179,92.2,1059639,92.0,0.2 +"Psychosis, schizophrenia, or bipolar",yes,9996,85.9,11641,85.4,0.5 +Learning disability,no,984900,92.2,1068760,92.0,0.2 +Learning disability,yes,2275,90.3,2520,89.7,0.6 +SSRI (last 12 months),no,900585,91.9,980336,91.7,0.2 +SSRI (last 12 months),yes,86583,95.2,90944,95.0,0.2 +Chemo or radiotherapy,no,968366,92.1,1051561,91.9,0.2 +Chemo or radiotherapy,yes,18809,95.4,19719,95.2,0.2 +Cancer (lung),no,985509,92.1,1069488,92.0,0.1 +Cancer (lung),yes,1659,92.6,1792,92.2,0.4 +Cancer (excluding lung/haem),no,903707,91.9,983556,91.7,0.2 +Cancer (excluding lung/haem),yes,83468,95.1,87731,95.0,0.1 +Cancer (haematological),no,983724,92.1,1067612,92.0,0.1 +Cancer (haematological),yes,3444,93.9,3668,93.7,0.2 diff --git a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 70-79 population_tpp.csv b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 70-79 population_tpp.csv index d081397..20d7c08 100644 --- a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 70-79 population_tpp.csv +++ b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 70-79 population_tpp.csv @@ -1,61 +1,61 @@ -Category,Group,Vaccinated at 07 Apr (n),Vaccinated at 07 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) -overall,overall,1963490,95.0,2066323,94.9,0.1 -Sex,F,1031163,95.2,1083320,95.1,0.1 -Sex,M,932323,94.8,982996,94.8,0.0 -Age band,70-74,1134938,94.6,1199786,94.5,0.1 -Age band,75-79,828548,95.6,866530,95.5,0.1 -Ethnicity (broad categories),Black,10444,71.0,14700,70.8,0.2 -Ethnicity (broad categories),Mixed,5250,81.5,6440,81.3,0.2 -Ethnicity (broad categories),Other,12159,79.3,15337,79.1,0.2 -Ethnicity (broad categories),South Asian,47383,86.2,54950,85.9,0.3 -Ethnicity (broad categories),Unknown,127932,88.1,145257,88.0,0.1 -Ethnicity (broad categories),White,1760318,96.2,1829632,96.1,0.1 -ethnicity 16 groups, African,3430,65.2,5257,64.8,0.4 -ethnicity 16 groups, Bangladeshi or British Bangladeshi,1540,85.3,1806,84.9,0.4 -ethnicity 16 groups, Caribbean,5201,74.7,6958,74.4,0.3 -ethnicity 16 groups, Chinese,3185,78.4,4060,78.3,0.1 -ethnicity 16 groups, Other,8974,79.6,11277,79.3,0.3 -ethnicity 16 groups, Other Asian,9303,83.2,11179,83.0,0.2 -ethnicity 16 groups,British or Mixed British,1673756,96.7,1731366,96.6,0.1 -ethnicity 16 groups,Indian or British Indian,27321,90.1,30324,89.9,0.2 -ethnicity 16 groups,Irish,14133,93.1,15176,93.0,0.1 -ethnicity 16 groups,Other Black,1813,73.2,2478,72.9,0.3 -ethnicity 16 groups,Other White,72422,87.2,83097,87.0,0.2 -ethnicity 16 groups,Other mixed,2086,82.8,2520,82.8,0.0 -ethnicity 16 groups,Pakistani or British Pakistani,9226,79.2,11648,78.7,0.5 -ethnicity 16 groups,Unknown,127918,88.1,145243,88.0,0.1 -ethnicity 16 groups,White + Asian,1190,87.2,1365,87.2,0.0 -ethnicity 16 groups,White + Black African,812,75.8,1071,75.2,0.6 -ethnicity 16 groups,White + Black Caribbean,1162,77.9,1491,77.9,0.0 -Index of Multiple Deprivation (quintiles),1 Most deprived,251069,92.0,272972,91.8,0.2 -Index of Multiple Deprivation (quintiles),2,329217,93.8,350917,93.7,0.1 -Index of Multiple Deprivation (quintiles),3,438158,95.3,459844,95.2,0.1 -Index of Multiple Deprivation (quintiles),4,456029,95.9,475573,95.8,0.1 -Index of Multiple Deprivation (quintiles),5 Least deprived,452984,96.6,468713,96.6,0.0 -Index of Multiple Deprivation (quintiles),Unknown,36036,94.1,38290,93.9,0.2 -BMI,30+,492856,96.4,511021,96.4,0.0 -BMI,under 30,1470630,94.6,1555295,94.5,0.1 -Chronic cardiac disease,no,1607116,94.8,1695855,94.7,0.1 -Chronic cardiac disease,yes,356370,96.2,370461,96.1,0.1 -Current COPD,no,1774444,94.9,1869952,94.8,0.1 -Current COPD,yes,189042,96.3,196364,96.2,0.1 -Dialysis,no,1959573,95.0,2062235,94.9,0.1 -Dialysis,yes,3906,95.7,4081,95.5,0.2 -DMARDs,no,1893465,94.9,1994244,94.9,0.0 -DMARDs,yes,70021,97.2,72072,97.0,0.2 -Dementia,no,1921906,95.0,2022706,94.9,0.1 -Dementia,yes,41580,95.3,43610,95.2,0.1 -"Psychosis, schizophrenia, or bipolar",no,1944957,95.1,2045792,95.0,0.1 -"Psychosis, schizophrenia, or bipolar",yes,18522,90.2,20524,90.1,0.1 -Learning disability,no,1960672,95.0,2063271,94.9,0.1 -Learning disability,yes,2807,92.2,3045,92.2,0.0 -SSRI (last 12 months),no,1813336,94.9,1911581,94.8,0.1 -SSRI (last 12 months),yes,150150,97.0,154735,96.9,0.1 -Chemo or radiotherapy,no,1896216,95.0,1996946,94.9,0.1 -Chemo or radiotherapy,yes,67263,97.0,69370,96.9,0.1 -Cancer (lung),no,1951313,95.0,2053639,94.9,0.1 -Cancer (lung),yes,12173,96.0,12677,95.9,0.1 -Cancer (excluding lung/haem),no,1686391,94.7,1780261,94.6,0.1 -Cancer (excluding lung/haem),yes,277095,96.9,286055,96.8,0.1 -Cancer (haematological),no,1934100,95.0,2035922,94.9,0.1 -Cancer (haematological),yes,29386,96.7,30394,96.6,0.1 +Category,Group,Vaccinated at 14 Apr (n),Vaccinated at 14 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) +overall,overall,1966007,95.2,2064944,95.1,0.1 +Sex,F,1032514,95.4,1082774,95.2,0.2 +Sex,M,933492,95.0,982163,94.9,0.1 +Age band,70-74,1136296,94.8,1199163,94.6,0.2 +Age band,75-79,829710,95.8,865781,95.7,0.1 +Ethnicity (broad categories),Black,10500,71.5,14686,71.1,0.4 +Ethnicity (broad categories),Mixed,5264,81.8,6433,81.6,0.2 +Ethnicity (broad categories),Other,12229,79.7,15344,79.4,0.3 +Ethnicity (broad categories),South Asian,47572,86.6,54936,86.3,0.3 +Ethnicity (broad categories),Unknown,127757,88.3,144655,88.2,0.1 +Ethnicity (broad categories),White,1762677,96.4,1828883,96.3,0.1 +ethnicity 16 groups, African,3458,65.8,5257,65.2,0.6 +ethnicity 16 groups, Bangladeshi or British Bangladeshi,1540,84.9,1813,84.6,0.3 +ethnicity 16 groups, Caribbean,5229,75.2,6958,74.7,0.5 +ethnicity 16 groups, Chinese,3199,78.8,4060,78.4,0.4 +ethnicity 16 groups, Other,9037,80.0,11298,79.7,0.3 +ethnicity 16 groups, Other Asian,9345,83.6,11172,83.4,0.2 +ethnicity 16 groups,British or Mixed British,1675926,96.8,1730701,96.7,0.1 +ethnicity 16 groups,Indian or British Indian,27391,90.4,30303,90.2,0.2 +ethnicity 16 groups,Irish,14147,93.3,15162,93.2,0.1 +ethnicity 16 groups,Other Black,1820,73.4,2478,73.2,0.2 +ethnicity 16 groups,Other White,72583,87.4,83006,87.2,0.2 +ethnicity 16 groups,Other mixed,2100,83.6,2513,83.3,0.3 +ethnicity 16 groups,Pakistani or British Pakistani,9289,79.8,11634,79.3,0.5 +ethnicity 16 groups,Unknown,127771,88.3,144669,88.2,0.1 +ethnicity 16 groups,White + Asian,1197,87.7,1365,87.2,0.5 +ethnicity 16 groups,White + Black African,812,75.8,1071,75.8,0.0 +ethnicity 16 groups,White + Black Caribbean,1169,78.8,1484,78.3,0.5 +Index of Multiple Deprivation (quintiles),1 Most deprived,251496,92.2,272657,92.0,0.2 +Index of Multiple Deprivation (quintiles),2,329805,94.1,350637,93.9,0.2 +Index of Multiple Deprivation (quintiles),3,438606,95.4,459522,95.3,0.1 +Index of Multiple Deprivation (quintiles),4,456519,96.0,475335,95.9,0.1 +Index of Multiple Deprivation (quintiles),5 Least deprived,453446,96.8,468468,96.7,0.1 +Index of Multiple Deprivation (quintiles),Unknown,36134,94.3,38325,94.1,0.2 +BMI,30+,493458,96.6,510713,96.5,0.1 +BMI,under 30,1472541,94.7,1554224,94.6,0.1 +Chronic cardiac disease,no,1608831,95.0,1694392,94.8,0.2 +Chronic cardiac disease,yes,357168,96.4,370552,96.3,0.1 +Current COPD,no,1776649,95.1,1868650,94.9,0.2 +Current COPD,yes,189350,96.5,196294,96.3,0.2 +Dialysis,no,1962086,95.2,2060863,95.1,0.1 +Dialysis,yes,3913,95.9,4081,95.7,0.2 +DMARDs,no,1895845,95.1,1992865,95.0,0.1 +DMARDs,yes,70161,97.3,72079,97.2,0.1 +Dementia,no,1924237,95.2,2021278,95.1,0.1 +Dementia,yes,41762,95.6,43666,95.4,0.2 +"Psychosis, schizophrenia, or bipolar",no,1947421,95.3,2044434,95.1,0.2 +"Psychosis, schizophrenia, or bipolar",yes,18578,90.6,20503,90.4,0.2 +Learning disability,no,1963178,95.2,2061899,95.1,0.1 +Learning disability,yes,2821,92.6,3045,92.2,0.4 +SSRI (last 12 months),no,1815478,95.0,1910125,94.9,0.1 +SSRI (last 12 months),yes,150528,97.2,154812,97.1,0.1 +Chemo or radiotherapy,no,1898631,95.1,1995574,95.0,0.1 +Chemo or radiotherapy,yes,67368,97.1,69363,97.0,0.1 +Cancer (lung),no,1953791,95.2,2052274,95.1,0.1 +Cancer (lung),yes,12208,96.4,12663,96.2,0.2 +Cancer (excluding lung/haem),no,1688218,94.9,1778707,94.8,0.1 +Cancer (excluding lung/haem),yes,277788,97.1,286230,96.9,0.2 +Cancer (haematological),no,1936529,95.2,2034515,95.1,0.1 +Cancer (haematological),yes,29477,96.9,30422,96.7,0.2 diff --git a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 80+ population_tpp.csv b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 80+ population_tpp.csv index a0711db..fbd666d 100644 --- a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 80+ population_tpp.csv +++ b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among 80+ population_tpp.csv @@ -1,62 +1,62 @@ -Category,Group,Vaccinated at 07 Apr (n),Vaccinated at 07 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) -overall,overall,1076001,95.7,1124221,95.6,0.1 -Sex,F,623224,95.6,651700,95.5,0.1 -Sex,M,452774,95.8,472514,95.7,0.1 -Age band,80-84,565845,96.0,589470,95.9,0.1 -Age band,85-89,336497,95.8,351155,95.7,0.1 -Age band,90+,173656,94.6,183589,94.4,0.2 -Ethnicity (broad categories),Black,8232,74.2,11088,73.9,0.3 -Ethnicity (broad categories),Mixed,2688,82.4,3262,82.2,0.2 -Ethnicity (broad categories),Other,5579,82.2,6783,82.0,0.2 -Ethnicity (broad categories),South Asian,24563,86.1,28525,85.9,0.2 -Ethnicity (broad categories),Unknown,54600,86.3,63280,86.2,0.1 -Ethnicity (broad categories),White,980336,96.9,1011276,96.8,0.1 -ethnicity 16 groups, African,1365,65.0,2100,64.7,0.3 -ethnicity 16 groups, Bangladeshi or British Bangladeshi,1064,80.9,1316,80.3,0.6 -ethnicity 16 groups, Caribbean,5901,77.1,7651,76.8,0.3 -ethnicity 16 groups, Chinese,1351,79.1,1708,79.1,0.0 -ethnicity 16 groups, Other,4228,83.3,5075,83.0,0.3 -ethnicity 16 groups, Other Asian,3654,82.9,4410,82.7,0.2 -ethnicity 16 groups,British or Mixed British,931336,97.2,958062,97.1,0.1 -ethnicity 16 groups,Indian or British Indian,13657,90.9,15022,90.7,0.2 -ethnicity 16 groups,Irish,9198,94.6,9723,94.5,0.1 -ethnicity 16 groups,Other Black,966,71.9,1344,71.4,0.5 -ethnicity 16 groups,Other White,39802,91.5,43498,91.3,0.2 -ethnicity 16 groups,Other mixed,1001,86.1,1162,85.5,0.6 -ethnicity 16 groups,Pakistani or British Pakistani,6188,79.6,7770,79.3,0.3 -ethnicity 16 groups,Unknown,54593,86.3,63273,86.2,0.1 +Category,Group,Vaccinated at 14 Apr (n),Vaccinated at 14 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) +overall,overall,1075580,95.9,1121701,95.8,0.1 +Sex,F,623112,95.8,650377,95.7,0.1 +Sex,M,452459,96.0,471317,95.9,0.1 +Age band,80-84,566041,96.2,588637,96.0,0.2 +Age band,85-89,336294,96.0,350294,95.9,0.1 +Age band,90+,173236,94.8,182763,94.6,0.2 +Ethnicity (broad categories),Black,8267,74.7,11067,74.3,0.4 +Ethnicity (broad categories),Mixed,2702,82.8,3262,82.6,0.2 +Ethnicity (broad categories),Other,5593,82.6,6769,82.4,0.2 +Ethnicity (broad categories),South Asian,24619,86.5,28455,86.2,0.3 +Ethnicity (broad categories),Unknown,54320,86.5,62776,86.4,0.1 +Ethnicity (broad categories),White,980070,97.1,1009365,97.0,0.1 +ethnicity 16 groups, African,1372,65.6,2093,65.2,0.4 +ethnicity 16 groups, Bangladeshi or British Bangladeshi,1071,81.4,1316,80.9,0.5 +ethnicity 16 groups, Caribbean,5929,77.6,7637,77.3,0.3 +ethnicity 16 groups, Chinese,1351,79.8,1694,79.3,0.5 +ethnicity 16 groups, Other,4249,83.6,5082,83.5,0.1 +ethnicity 16 groups, Other Asian,3661,83.1,4403,83.0,0.1 +ethnicity 16 groups,British or Mixed British,931063,97.4,956277,97.2,0.2 +ethnicity 16 groups,Indian or British Indian,13671,91.2,14994,91.0,0.2 +ethnicity 16 groups,Irish,9191,94.9,9681,94.8,0.1 +ethnicity 16 groups,Other Black,966,72.3,1337,71.7,0.6 +ethnicity 16 groups,Other White,39816,91.7,43421,91.6,0.1 +ethnicity 16 groups,Other mixed,994,86.1,1155,86.1,0.0 +ethnicity 16 groups,Pakistani or British Pakistani,6216,80.2,7749,79.8,0.4 +ethnicity 16 groups,Unknown,54306,86.5,62755,86.4,0.1 ethnicity 16 groups,White + Asian,469,87.0,539,87.0,0.0 -ethnicity 16 groups,White + Black African,266,71.7,371,69.8,1.9 +ethnicity 16 groups,White + Black African,266,71.7,371,71.7,0.0 ethnicity 16 groups,White + Black Caribbean,966,80.2,1204,79.7,0.5 -Index of Multiple Deprivation (quintiles),1 Most deprived,134764,92.4,145845,92.2,0.2 -Index of Multiple Deprivation (quintiles),2,178024,94.5,188342,94.3,0.2 -Index of Multiple Deprivation (quintiles),3,240835,96.0,250740,95.9,0.1 -Index of Multiple Deprivation (quintiles),4,250390,96.6,259175,96.5,0.1 -Index of Multiple Deprivation (quintiles),5 Least deprived,252987,97.2,260155,97.1,0.1 -Index of Multiple Deprivation (quintiles),Unknown,18991,95.1,19964,95.0,0.1 -BMI,30+,189588,96.9,195615,96.8,0.1 -BMI,under 30,886403,95.5,928599,95.3,0.2 -Chronic cardiac disease,no,750337,95.2,787899,95.1,0.1 -Chronic cardiac disease,yes,325661,96.8,336315,96.7,0.1 -Current COPD,no,962150,95.6,1006642,95.5,0.1 -Current COPD,yes,113848,96.8,117572,96.7,0.1 -Dialysis,no,1074003,95.7,1122142,95.6,0.1 -Dialysis,yes,1995,96.6,2065,96.6,0.0 -DMARDs,no,1042167,95.7,1089529,95.5,0.2 -DMARDs,yes,33831,97.6,34678,97.4,0.2 -Dementia,no,985971,95.7,1030113,95.6,0.1 -Dementia,yes,90020,95.7,94101,95.5,0.2 -"Psychosis, schizophrenia, or bipolar",no,1067983,95.7,1115513,95.6,0.1 -"Psychosis, schizophrenia, or bipolar",yes,8008,92.0,8701,91.9,0.1 -Learning disability,no,1075487,95.7,1123668,95.6,0.1 +Index of Multiple Deprivation (quintiles),1 Most deprived,134855,92.7,145411,92.5,0.2 +Index of Multiple Deprivation (quintiles),2,177975,94.7,187866,94.6,0.1 +Index of Multiple Deprivation (quintiles),3,240646,96.2,250138,96.1,0.1 +Index of Multiple Deprivation (quintiles),4,250236,96.7,258650,96.6,0.1 +Index of Multiple Deprivation (quintiles),5 Least deprived,252840,97.4,259658,97.3,0.1 +Index of Multiple Deprivation (quintiles),Unknown,19019,95.3,19964,95.1,0.2 +BMI,30+,189469,97.1,195125,97.0,0.1 +BMI,under 30,886109,95.6,926569,95.5,0.1 +Chronic cardiac disease,no,749889,95.4,785918,95.3,0.1 +Chronic cardiac disease,yes,325689,97.0,335783,96.9,0.1 +Current COPD,no,961807,95.8,1004395,95.6,0.2 +Current COPD,yes,113771,97.0,117299,96.9,0.1 +Dialysis,no,1073576,95.9,1119629,95.8,0.1 +Dialysis,yes,1995,96.6,2065,96.3,0.3 +DMARDs,no,1041754,95.8,1087072,95.7,0.1 +DMARDs,yes,33817,97.7,34622,97.6,0.1 +Dementia,no,985425,95.9,1027719,95.8,0.1 +Dementia,yes,90153,95.9,93982,95.7,0.2 +"Psychosis, schizophrenia, or bipolar",no,1067563,95.9,1113021,95.8,0.1 +"Psychosis, schizophrenia, or bipolar",yes,8008,92.3,8673,92.1,0.2 +Learning disability,no,1075060,95.9,1121148,95.8,0.1 Learning disability,yes,511,93.6,546,93.6,0.0 -SSRI (last 12 months),no,1008854,95.6,1055313,95.5,0.1 -SSRI (last 12 months),yes,67137,97.4,68901,97.3,0.1 -Chemo or radiotherapy,no,1039178,95.7,1086379,95.5,0.2 -Chemo or radiotherapy,yes,36813,97.3,37835,97.2,0.1 -Cancer (lung),no,1068655,95.7,1116605,95.6,0.1 -Cancer (lung),yes,7343,96.5,7609,96.3,0.2 -Cancer (excluding lung/haem),no,880313,95.4,923041,95.2,0.2 -Cancer (excluding lung/haem),yes,195678,97.3,201166,97.2,0.1 -Cancer (haematological),no,1055950,95.7,1103592,95.6,0.1 -Cancer (haematological),yes,20048,97.2,20622,97.1,0.1 +SSRI (last 12 months),no,1008371,95.8,1052863,95.6,0.2 +SSRI (last 12 months),yes,67200,97.6,68831,97.5,0.1 +Chemo or radiotherapy,no,1038772,95.8,1083943,95.7,0.1 +Chemo or radiotherapy,yes,36806,97.5,37751,97.4,0.1 +Cancer (lung),no,1068256,95.9,1114134,95.8,0.1 +Cancer (lung),yes,7322,96.9,7560,96.7,0.2 +Cancer (excluding lung/haem),no,879921,95.6,920857,95.4,0.2 +Cancer (excluding lung/haem),yes,195657,97.4,200837,97.3,0.1 +Cancer (haematological),no,1055523,95.9,1101107,95.7,0.2 +Cancer (haematological),yes,20055,97.4,20587,97.3,0.1 diff --git a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among LD (aged 16-64) population_tpp.csv b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among LD (aged 16-64) population_tpp.csv index 6842531..bd11b76 100644 --- a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among LD (aged 16-64) population_tpp.csv +++ b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among LD (aged 16-64) population_tpp.csv @@ -1,18 +1,18 @@ -Category,Group,Vaccinated at 07 Apr (n),Vaccinated at 07 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) -overall,overall,64507,79.5,81102,78.5,1.0 -Sex,F,25172,82.2,30632,81.2,1.0 -Sex,M,39333,77.9,50470,76.8,1.1 -Age band,16-29,24164,72.4,33355,71.1,1.3 -Age band,30-34,8274,78.5,10535,77.5,1.0 -Age band,35-39,6258,82.2,7609,81.2,1.0 -Age band,40-44,5082,85.0,5978,84.3,0.7 -Age band,45-49,5208,85.6,6083,84.9,0.7 -Age band,50-54,5642,87.7,6433,86.8,0.9 -Age band,55-59,5642,88.4,6384,87.6,0.8 -Age band,60-64,4235,89.6,4725,88.9,0.7 -Ethnicity (broad categories),Black,707,53.2,1330,51.6,1.6 -Ethnicity (broad categories),Mixed,651,60.4,1078,59.7,0.7 -Ethnicity (broad categories),Other,434,64.6,672,63.5,1.1 -Ethnicity (broad categories),South Asian,2919,63.0,4634,61.5,1.5 -Ethnicity (broad categories),Unknown,5054,77.1,6559,75.9,1.2 -Ethnicity (broad categories),White,54740,81.9,66836,80.9,1.0 +Category,Group,Vaccinated at 14 Apr (n),Vaccinated at 14 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) +overall,overall,65217,80.3,81249,79.5,0.8 +Sex,F,25410,82.8,30681,82.2,0.6 +Sex,M,39809,78.7,50561,77.9,0.8 +Age band,16-29,24409,73.0,33453,72.3,0.7 +Age band,30-34,8400,79.6,10549,78.5,1.1 +Age band,35-39,6321,82.9,7623,82.2,0.7 +Age band,40-44,5117,85.5,5985,84.9,0.6 +Age band,45-49,5271,86.6,6090,85.6,1.0 +Age band,50-54,5719,88.8,6440,87.8,1.0 +Age band,55-59,5698,89.4,6377,88.5,0.9 +Age band,60-64,4277,90.5,4725,89.9,0.6 +Ethnicity (broad categories),Black,721,54.2,1330,53.2,1.0 +Ethnicity (broad categories),Mixed,658,61.0,1078,60.4,0.6 +Ethnicity (broad categories),Other,434,63.9,679,63.9,0.0 +Ethnicity (broad categories),South Asian,2996,64.6,4641,63.2,1.4 +Ethnicity (broad categories),Unknown,5082,77.6,6552,76.9,0.7 +Ethnicity (broad categories),White,55321,82.6,66969,81.9,0.7 diff --git a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among care home population_tpp.csv b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among care home population_tpp.csv index f3c0185..8bb63b2 100644 --- a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among care home population_tpp.csv +++ b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among care home population_tpp.csv @@ -1,18 +1,18 @@ -Category,Group,Vaccinated at 07 Apr (n),Vaccinated at 07 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) -overall,overall,80022,95.6,83727,95.4,0.2 -Sex,F,56966,95.9,59402,95.7,0.2 -Sex,M,23051,94.8,24325,94.5,0.3 -Age band,65-69,4347,91.9,4732,91.4,0.5 -Age band,70-74,6706,93.4,7182,93.1,0.3 -Age band,75-79,9289,94.9,9793,94.6,0.3 -Age band,80-84,13944,95.8,14553,95.6,0.2 -Age band,85-89,18732,96.3,19453,96.1,0.2 -Age band,90+,26999,96.4,28021,96.2,0.2 -Ethnicity (broad categories),Black,392,86.2,455,86.2,0.0 -Ethnicity (broad categories),Mixed,210,90.9,231,90.9,0.0 -Ethnicity (broad categories),Other,343,92.5,371,92.5,0.0 -Ethnicity (broad categories),South Asian,623,92.7,672,92.7,0.0 -Ethnicity (broad categories),Unknown,2030,93.9,2163,93.5,0.4 -Ethnicity (broad categories),White,76419,95.7,79835,95.5,0.2 -Dementia,no,36197,94.4,38332,94.2,0.2 -Dementia,yes,43827,96.5,45395,96.4,0.1 +Category,Group,Vaccinated at 14 Apr (n),Vaccinated at 14 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) +overall,overall,80514,96.0,83888,95.6,0.4 +Sex,F,57302,96.3,59500,95.9,0.4 +Sex,M,23212,95.2,24381,94.8,0.4 +Age band,65-69,4389,92.3,4753,91.8,0.5 +Age band,70-74,6769,94.0,7203,93.4,0.6 +Age band,75-79,9394,95.4,9849,94.9,0.5 +Age band,80-84,14049,96.2,14609,95.8,0.4 +Age band,85-89,18865,96.6,19523,96.3,0.3 +Age band,90+,27048,96.8,27951,96.4,0.4 +Ethnicity (broad categories),Black,399,86.4,462,84.8,1.6 +Ethnicity (broad categories),Mixed,203,90.6,224,90.6,0.0 +Ethnicity (broad categories),Other,343,94.2,364,94.2,0.0 +Ethnicity (broad categories),South Asian,623,91.8,679,91.8,0.0 +Ethnicity (broad categories),Unknown,2037,93.9,2170,93.2,0.7 +Ethnicity (broad categories),White,76909,96.1,79996,95.8,0.3 +Dementia,no,36421,94.9,38395,94.4,0.5 +Dementia,yes,44093,96.9,45486,96.6,0.3 diff --git a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among shielding (aged 16-69) population_tpp.csv b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among shielding (aged 16-69) population_tpp.csv index a524d21..2a28f51 100644 --- a/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among shielding (aged 16-69) population_tpp.csv +++ b/released-outputs/machine_readable_outputs/table_csvs/Cumulative vaccination figures among shielding (aged 16-69) population_tpp.csv @@ -1,25 +1,25 @@ -Category,Group,Vaccinated at 07 Apr (n),Vaccinated at 07 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) -overall,overall,711770,86.4,823949,86.0,0.4 -newly shielded since feb 15,no,453194,90.2,502355,90.0,0.2 -newly shielded since feb 15,yes,258573,80.4,321594,79.7,0.7 -Sex,F,395619,85.5,462448,85.1,0.4 -Sex,M,316141,87.5,361494,87.1,0.4 -Age band,16-29,51429,74.7,68831,74.1,0.6 -Age band,30-39,97153,76.9,126392,76.3,0.6 -Age band,40-49,139454,84.4,165151,83.9,0.5 -Age band,50-59,203455,89.6,227052,89.3,0.3 -Age band,60-69,220269,93.1,236509,92.9,0.2 -Ethnicity (broad categories),Black,29533,66.4,44485,65.5,0.9 -Ethnicity (broad categories),Mixed,10388,72.9,14252,72.2,0.7 -Ethnicity (broad categories),Other,13237,73.0,18123,72.4,0.6 -Ethnicity (broad categories),South Asian,85456,78.9,108255,78.1,0.8 -Ethnicity (broad categories),Unknown,27349,84.4,32389,84.0,0.4 -Ethnicity (broad categories),White,545797,90.0,606431,89.7,0.3 -Index of Multiple Deprivation (quintiles),1 Most deprived,198065,81.3,243761,80.7,0.6 -Index of Multiple Deprivation (quintiles),2,158872,85.2,186487,84.8,0.4 -Index of Multiple Deprivation (quintiles),3,138082,88.4,156240,88.1,0.3 -Index of Multiple Deprivation (quintiles),4,111195,90.8,122486,90.5,0.3 -Index of Multiple Deprivation (quintiles),5 Least deprived,88480,93.0,95158,92.8,0.2 -Index of Multiple Deprivation (quintiles),Unknown,17073,86.2,19796,85.7,0.5 -Learning disability,no,687701,86.3,797146,85.9,0.4 -Learning disability,yes,24059,89.8,26796,89.4,0.4 +Category,Group,Vaccinated at 14 Apr (n),Vaccinated at 14 Apr (%),Total eligible,Previous week's vaccination coverage (%),Vaccinated over last 7d (%) +overall,overall,715755,86.8,824887,86.4,0.4 +newly shielded since feb 15,no,454153,90.5,501942,90.3,0.2 +newly shielded since feb 15,yes,261604,81.0,322952,80.4,0.6 +Sex,F,397880,85.9,462980,85.6,0.3 +Sex,M,317870,87.8,361900,87.5,0.3 +Age band,16-29,51695,74.9,68978,74.7,0.2 +Age band,30-39,97951,77.4,126553,76.9,0.5 +Age band,40-49,140483,85.0,165340,84.5,0.5 +Age band,50-59,204575,90.0,227360,89.7,0.3 +Age band,60-69,221039,93.4,236642,93.2,0.2 +Ethnicity (broad categories),Black,29890,67.2,44478,66.5,0.7 +Ethnicity (broad categories),Mixed,10479,73.5,14266,72.9,0.6 +Ethnicity (broad categories),Other,13370,73.7,18151,73.0,0.7 +Ethnicity (broad categories),South Asian,86317,79.7,108248,79.0,0.7 +Ethnicity (broad categories),Unknown,27412,84.8,32340,84.4,0.4 +Ethnicity (broad categories),White,548268,90.3,607390,90.0,0.3 +Index of Multiple Deprivation (quintiles),1 Most deprived,199367,81.8,243726,81.3,0.5 +Index of Multiple Deprivation (quintiles),2,159831,85.6,186697,85.2,0.4 +Index of Multiple Deprivation (quintiles),3,138880,88.7,156548,88.4,0.3 +Index of Multiple Deprivation (quintiles),4,111664,91.0,122675,90.8,0.2 +Index of Multiple Deprivation (quintiles),5 Least deprived,88830,93.1,95375,92.9,0.2 +Index of Multiple Deprivation (quintiles),Unknown,17185,86.6,19845,86.3,0.3 +Learning disability,no,691523,86.7,798035,86.3,0.4 +Learning disability,yes,24227,90.3,26838,89.9,0.4 diff --git a/released-outputs/opensafely_vaccine_report_overall.html b/released-outputs/opensafely_vaccine_report_overall.html index 6374ad2..ff7aff4 100644 --- a/released-outputs/opensafely_vaccine_report_overall.html +++ b/released-outputs/opensafely_vaccine_report_overall.html @@ -13100,7 +13100,7 @@

OpenSAFELY COVID Vaccine cover
-

Report last updated 12 Apr 2021

+

Report last updated 19 Apr 2021

@@ -13109,7 +13109,7 @@

Report last updated 12 Apr 2021
-

Vaccinations included up to 07 Apr 2021 inclusive

+

Vaccinations included up to 14 Apr 2021 inclusive

@@ -13178,8 +13178,8 @@

- first dose as at 07 Apr 2021 - second dose as at 07 Apr 2021 + first dose as at 14 Apr 2021 + second dose as at 14 Apr 2021 Group @@ -13190,58 +13190,58 @@

Vaccine types and second doses -

Second doses (% of all vaccinated): 17.8% (1,956,815)

+

Second doses (% of all vaccinated): 25.4% (2,829,204)

@@ -13283,7 +13283,17 @@

Vaccine types and second doses -

Oxford-AZ vaccines (% of all first doses): 65.5% (7,208,474)

+

Oxford-AZ vaccines (% of all first doses): 65.8% (7,334,173)

+ + + + + +
+ + +
+

Moderna vaccines (% of all first doses): 0.0% (2,380)

@@ -13347,10 +13357,10 @@

- + - + @@ -13376,18 +13386,17 @@

- + - + - - + - + @@ -13398,19 +13407,19 @@

- + - + - + - + @@ -13421,36 +13430,39 @@

- + - + - - + - - + + - - - + + + - + - - + + + + + + - + @@ -13461,18 +13473,18 @@

- + - + - + - + @@ -13483,18 +13495,18 @@

- + - + - + - + @@ -13522,10 +13534,10 @@

- + - + @@ -13538,12 +13550,12 @@

- + - + @@ -13551,7 +13563,7 @@

- + @@ -13559,7 +13571,7 @@

- + @@ -13567,7 +13579,7 @@

- + @@ -13575,7 +13587,7 @@

- + @@ -13583,7 +13595,7 @@

- + @@ -13591,7 +13603,7 @@

- + @@ -13599,19 +13611,19 @@

- + - + - + @@ -13624,13 +13636,11 @@

- - - + @@ -13650,62 +13660,51 @@

- - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + - + - + - + - + - + - + - + - + - + - + - + @@ -13720,7 +13719,7 @@

- + @@ -13734,7 +13733,6 @@

- @@ -13779,8 +13777,8 @@

- - + + @@ -13863,6 +13861,9 @@

+ + + @@ -14030,7 +14031,7 @@

+ @@ -14046,7 +14047,7 @@

-

Trends in vaccination rates of 80+ population according to demographic/clinical features, cumulatively by day.

*National rate calculated as at latest date for vaccinations recorded across all TPP practices.

+

Trends in vaccination rates of 80+ population according to demographic/clinical features, cumulatively by day.

*Latest overall cohort rate calculated as at latest date for vaccinations recorded across all TPP practices.

@@ -14086,7 +14087,7 @@

COVID vaccinations among 80+ po - + @@ -14096,10 +14097,10 @@

COVID vaccinations among 80+ po - + - + @@ -14112,7 +14113,7 @@

COVID vaccinations among 80+ po - + @@ -14125,7 +14126,7 @@

COVID vaccinations among 80+ po - + @@ -14134,7 +14135,7 @@

COVID vaccinations among 80+ po - + @@ -14147,7 +14148,7 @@

COVID vaccinations among 80+ po - + @@ -14158,7 +14159,7 @@

COVID vaccinations among 80+ po - + @@ -14171,7 +14172,7 @@

COVID vaccinations among 80+ po - + @@ -14181,7 +14182,7 @@

COVID vaccinations among 80+ po - + @@ -14194,12 +14195,12 @@

COVID vaccinations among 80+ po - + - + @@ -14212,7 +14213,7 @@

COVID vaccinations among 80+ po - + @@ -14221,7 +14222,7 @@

COVID vaccinations among 80+ po - + @@ -14234,7 +14235,7 @@

COVID vaccinations among 80+ po - + @@ -14243,7 +14244,7 @@

COVID vaccinations among 80+ po - + @@ -14254,29 +14255,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -14284,10 +14271,10 @@

COVID vaccinations among 80+ po - + - + @@ -14300,12 +14287,12 @@

COVID vaccinations among 80+ po - + - + @@ -14314,7 +14301,7 @@

COVID vaccinations among 80+ po - + @@ -14322,7 +14309,7 @@

COVID vaccinations among 80+ po - + @@ -14331,12 +14318,12 @@

COVID vaccinations among 80+ po - + - + @@ -14345,7 +14332,7 @@

COVID vaccinations among 80+ po - + @@ -14353,7 +14340,7 @@

COVID vaccinations among 80+ po - + @@ -14362,12 +14349,12 @@

COVID vaccinations among 80+ po - + - + @@ -14375,16 +14362,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -14393,40 +14382,29 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -14447,7 +14425,7 @@

COVID vaccinations among 80+ po - + @@ -14481,22 +14459,22 @@

COVID vaccinations among 80+ po - + - + - + - + @@ -14504,7 +14482,7 @@

COVID vaccinations among 80+ po - + @@ -14534,7 +14512,7 @@

COVID vaccinations among 80+ po - + @@ -14544,10 +14522,10 @@

COVID vaccinations among 80+ po - + - + @@ -14573,7 +14551,7 @@

COVID vaccinations among 80+ po - + @@ -14582,7 +14560,7 @@

COVID vaccinations among 80+ po - + @@ -14595,7 +14573,7 @@

COVID vaccinations among 80+ po - + @@ -14606,7 +14584,7 @@

COVID vaccinations among 80+ po - + @@ -14619,7 +14597,7 @@

COVID vaccinations among 80+ po - + @@ -14629,7 +14607,7 @@

COVID vaccinations among 80+ po - + @@ -14642,12 +14620,12 @@

COVID vaccinations among 80+ po - + - + @@ -14660,7 +14638,7 @@

COVID vaccinations among 80+ po - + @@ -14669,7 +14647,7 @@

COVID vaccinations among 80+ po - + @@ -14682,7 +14660,7 @@

COVID vaccinations among 80+ po - + @@ -14691,7 +14669,7 @@

COVID vaccinations among 80+ po - + @@ -14702,29 +14680,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -14732,10 +14696,10 @@

COVID vaccinations among 80+ po - + - + @@ -14748,12 +14712,12 @@

COVID vaccinations among 80+ po - + - + @@ -14762,7 +14726,7 @@

COVID vaccinations among 80+ po - + @@ -14770,7 +14734,7 @@

COVID vaccinations among 80+ po - + @@ -14779,12 +14743,12 @@

COVID vaccinations among 80+ po - + - + @@ -14793,7 +14757,7 @@

COVID vaccinations among 80+ po - + @@ -14801,7 +14765,7 @@

COVID vaccinations among 80+ po - + @@ -14810,12 +14774,12 @@

COVID vaccinations among 80+ po - + - + @@ -14823,16 +14787,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -14841,52 +14807,41 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -14907,7 +14862,7 @@

COVID vaccinations among 80+ po - + @@ -14966,6 +14921,7 @@

COVID vaccinations among 80+ po + @@ -15056,7 +15012,7 @@

COVID vaccinations among 80+ po - + @@ -15086,7 +15042,7 @@

COVID vaccinations among 80+ po - + @@ -15096,10 +15052,10 @@

COVID vaccinations among 80+ po - + - + @@ -15125,7 +15081,7 @@

COVID vaccinations among 80+ po - + @@ -15134,7 +15090,7 @@

COVID vaccinations among 80+ po - + @@ -15147,7 +15103,7 @@

COVID vaccinations among 80+ po - + @@ -15158,7 +15114,7 @@

COVID vaccinations among 80+ po - + @@ -15171,7 +15127,7 @@

COVID vaccinations among 80+ po - + @@ -15181,7 +15137,7 @@

COVID vaccinations among 80+ po - + @@ -15194,12 +15150,12 @@

COVID vaccinations among 80+ po - + - + @@ -15212,7 +15168,7 @@

COVID vaccinations among 80+ po - + @@ -15221,7 +15177,7 @@

COVID vaccinations among 80+ po - + @@ -15234,7 +15190,7 @@

COVID vaccinations among 80+ po - + @@ -15243,7 +15199,7 @@

COVID vaccinations among 80+ po - + @@ -15254,29 +15210,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -15284,10 +15226,10 @@

COVID vaccinations among 80+ po - + - + @@ -15300,12 +15242,12 @@

COVID vaccinations among 80+ po - + - + @@ -15314,7 +15256,7 @@

COVID vaccinations among 80+ po - + @@ -15322,7 +15264,7 @@

COVID vaccinations among 80+ po - + @@ -15331,12 +15273,12 @@

COVID vaccinations among 80+ po - + - + @@ -15345,7 +15287,7 @@

COVID vaccinations among 80+ po - + @@ -15353,7 +15295,7 @@

COVID vaccinations among 80+ po - + @@ -15362,12 +15304,12 @@

COVID vaccinations among 80+ po - + - + @@ -15375,16 +15317,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -15393,52 +15337,41 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -15459,7 +15392,7 @@

COVID vaccinations among 80+ po - + @@ -15498,6 +15431,9 @@

COVID vaccinations among 80+ po + + + @@ -15602,7 +15538,7 @@

COVID vaccinations among 80+ po - + @@ -15632,7 +15568,7 @@

COVID vaccinations among 80+ po - + @@ -15642,10 +15578,10 @@

COVID vaccinations among 80+ po - + - + @@ -15671,7 +15607,7 @@

COVID vaccinations among 80+ po - + @@ -15680,7 +15616,7 @@

COVID vaccinations among 80+ po - + @@ -15693,7 +15629,7 @@

COVID vaccinations among 80+ po - + @@ -15704,7 +15640,7 @@

COVID vaccinations among 80+ po - + @@ -15717,7 +15653,7 @@

COVID vaccinations among 80+ po - + @@ -15727,7 +15663,7 @@

COVID vaccinations among 80+ po - + @@ -15740,12 +15676,12 @@

COVID vaccinations among 80+ po - + - + @@ -15758,7 +15694,7 @@

COVID vaccinations among 80+ po - + @@ -15767,7 +15703,7 @@

COVID vaccinations among 80+ po - + @@ -15780,7 +15716,7 @@

COVID vaccinations among 80+ po - + @@ -15789,7 +15725,7 @@

COVID vaccinations among 80+ po - + @@ -15800,29 +15736,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -15830,10 +15752,10 @@

COVID vaccinations among 80+ po - + - + @@ -15846,12 +15768,12 @@

COVID vaccinations among 80+ po - + - + @@ -15860,7 +15782,7 @@

COVID vaccinations among 80+ po - + @@ -15868,7 +15790,7 @@

COVID vaccinations among 80+ po - + @@ -15877,12 +15799,12 @@

COVID vaccinations among 80+ po - + - + @@ -15891,7 +15813,7 @@

COVID vaccinations among 80+ po - + @@ -15899,7 +15821,7 @@

COVID vaccinations among 80+ po - + @@ -15908,12 +15830,12 @@

COVID vaccinations among 80+ po - + - + @@ -15921,16 +15843,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -15939,40 +15863,29 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -15993,7 +15906,7 @@

COVID vaccinations among 80+ po - + @@ -16048,6 +15961,9 @@

COVID vaccinations among 80+ po + + + @@ -16063,7 +15979,7 @@

COVID vaccinations among 80+ po - + @@ -16093,7 +16009,7 @@

COVID vaccinations among 80+ po - + @@ -16103,10 +16019,10 @@

COVID vaccinations among 80+ po - + - + @@ -16132,7 +16048,7 @@

COVID vaccinations among 80+ po - + @@ -16141,7 +16057,7 @@

COVID vaccinations among 80+ po - + @@ -16154,7 +16070,7 @@

COVID vaccinations among 80+ po - + @@ -16165,7 +16081,7 @@

COVID vaccinations among 80+ po - + @@ -16178,7 +16094,7 @@

COVID vaccinations among 80+ po - + @@ -16188,7 +16104,7 @@

COVID vaccinations among 80+ po - + @@ -16201,12 +16117,12 @@

COVID vaccinations among 80+ po - + - + @@ -16219,7 +16135,7 @@

COVID vaccinations among 80+ po - + @@ -16228,7 +16144,7 @@

COVID vaccinations among 80+ po - + @@ -16241,7 +16157,7 @@

COVID vaccinations among 80+ po - + @@ -16250,7 +16166,7 @@

COVID vaccinations among 80+ po - + @@ -16261,29 +16177,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -16291,10 +16193,10 @@

COVID vaccinations among 80+ po - + - + @@ -16307,12 +16209,12 @@

COVID vaccinations among 80+ po - + - + @@ -16321,7 +16223,7 @@

COVID vaccinations among 80+ po - + @@ -16329,7 +16231,7 @@

COVID vaccinations among 80+ po - + @@ -16338,12 +16240,12 @@

COVID vaccinations among 80+ po - + - + @@ -16352,7 +16254,7 @@

COVID vaccinations among 80+ po - + @@ -16360,7 +16262,7 @@

COVID vaccinations among 80+ po - + @@ -16369,12 +16271,12 @@

COVID vaccinations among 80+ po - + - + @@ -16382,16 +16284,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -16400,40 +16304,29 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -16454,7 +16347,7 @@

COVID vaccinations among 80+ po - + @@ -16517,7 +16410,7 @@

COVID vaccinations among 80+ po - + @@ -16547,7 +16440,7 @@

COVID vaccinations among 80+ po - + @@ -16557,10 +16450,10 @@

COVID vaccinations among 80+ po - + - + @@ -16586,7 +16479,7 @@

COVID vaccinations among 80+ po - + @@ -16595,7 +16488,7 @@

COVID vaccinations among 80+ po - + @@ -16608,7 +16501,7 @@

COVID vaccinations among 80+ po - + @@ -16619,7 +16512,7 @@

COVID vaccinations among 80+ po - + @@ -16632,7 +16525,7 @@

COVID vaccinations among 80+ po - + @@ -16642,7 +16535,7 @@

COVID vaccinations among 80+ po - + @@ -16655,12 +16548,12 @@

COVID vaccinations among 80+ po - + - + @@ -16673,7 +16566,7 @@

COVID vaccinations among 80+ po - + @@ -16682,7 +16575,7 @@

COVID vaccinations among 80+ po - + @@ -16695,7 +16588,7 @@

COVID vaccinations among 80+ po - + @@ -16704,7 +16597,7 @@

COVID vaccinations among 80+ po - + @@ -16715,29 +16608,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -16745,10 +16624,10 @@

COVID vaccinations among 80+ po - + - + @@ -16761,12 +16640,12 @@

COVID vaccinations among 80+ po - + - + @@ -16775,7 +16654,7 @@

COVID vaccinations among 80+ po - + @@ -16783,7 +16662,7 @@

COVID vaccinations among 80+ po - + @@ -16792,12 +16671,12 @@

COVID vaccinations among 80+ po - + - + @@ -16806,7 +16685,7 @@

COVID vaccinations among 80+ po - + @@ -16814,7 +16693,7 @@

COVID vaccinations among 80+ po - + @@ -16823,12 +16702,12 @@

COVID vaccinations among 80+ po - + - + @@ -16836,16 +16715,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -16854,40 +16735,29 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -16908,7 +16778,7 @@

COVID vaccinations among 80+ po - + @@ -16971,7 +16841,7 @@

COVID vaccinations among 80+ po - + @@ -17001,7 +16871,7 @@

COVID vaccinations among 80+ po - + @@ -17011,10 +16881,10 @@

COVID vaccinations among 80+ po - + - + @@ -17040,7 +16910,7 @@

COVID vaccinations among 80+ po - + @@ -17049,7 +16919,7 @@

COVID vaccinations among 80+ po - + @@ -17062,7 +16932,7 @@

COVID vaccinations among 80+ po - + @@ -17073,7 +16943,7 @@

COVID vaccinations among 80+ po - + @@ -17086,7 +16956,7 @@

COVID vaccinations among 80+ po - + @@ -17096,7 +16966,7 @@

COVID vaccinations among 80+ po - + @@ -17109,12 +16979,12 @@

COVID vaccinations among 80+ po - + - + @@ -17127,7 +16997,7 @@

COVID vaccinations among 80+ po - + @@ -17136,7 +17006,7 @@

COVID vaccinations among 80+ po - + @@ -17149,7 +17019,7 @@

COVID vaccinations among 80+ po - + @@ -17158,7 +17028,7 @@

COVID vaccinations among 80+ po - + @@ -17169,29 +17039,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -17199,10 +17055,10 @@

COVID vaccinations among 80+ po - + - + @@ -17215,7 +17071,7 @@

COVID vaccinations among 80+ po - + @@ -17229,7 +17085,7 @@

COVID vaccinations among 80+ po - + @@ -17246,7 +17102,7 @@

COVID vaccinations among 80+ po - + @@ -17260,7 +17116,7 @@

COVID vaccinations among 80+ po - + @@ -17277,7 +17133,7 @@

COVID vaccinations among 80+ po - + @@ -17290,16 +17146,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -17308,40 +17166,29 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -17362,7 +17209,7 @@

COVID vaccinations among 80+ po - + @@ -17425,7 +17272,7 @@

COVID vaccinations among 80+ po - + @@ -17455,7 +17302,7 @@

COVID vaccinations among 80+ po - + @@ -17465,10 +17312,10 @@

COVID vaccinations among 80+ po - + - + @@ -17494,7 +17341,7 @@

COVID vaccinations among 80+ po - + @@ -17503,7 +17350,7 @@

COVID vaccinations among 80+ po - + @@ -17516,7 +17363,7 @@

COVID vaccinations among 80+ po - + @@ -17527,7 +17374,7 @@

COVID vaccinations among 80+ po - + @@ -17540,7 +17387,7 @@

COVID vaccinations among 80+ po - + @@ -17550,7 +17397,7 @@

COVID vaccinations among 80+ po - + @@ -17563,12 +17410,12 @@

COVID vaccinations among 80+ po - + - + @@ -17581,7 +17428,7 @@

COVID vaccinations among 80+ po - + @@ -17590,7 +17437,7 @@

COVID vaccinations among 80+ po - + @@ -17603,7 +17450,7 @@

COVID vaccinations among 80+ po - + @@ -17612,7 +17459,7 @@

COVID vaccinations among 80+ po - + @@ -17623,29 +17470,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -17653,10 +17486,10 @@

COVID vaccinations among 80+ po - + - + @@ -17669,12 +17502,12 @@

COVID vaccinations among 80+ po - + - + @@ -17683,7 +17516,7 @@

COVID vaccinations among 80+ po - + @@ -17691,7 +17524,7 @@

COVID vaccinations among 80+ po - + @@ -17700,12 +17533,12 @@

COVID vaccinations among 80+ po - + - + @@ -17714,7 +17547,7 @@

COVID vaccinations among 80+ po - + @@ -17722,7 +17555,7 @@

COVID vaccinations among 80+ po - + @@ -17731,12 +17564,12 @@

COVID vaccinations among 80+ po - + - + @@ -17744,16 +17577,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -17762,40 +17597,29 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -17816,7 +17640,7 @@

COVID vaccinations among 80+ po - + @@ -17879,7 +17703,7 @@

COVID vaccinations among 80+ po - + @@ -17909,7 +17733,7 @@

COVID vaccinations among 80+ po - + @@ -17919,10 +17743,10 @@

COVID vaccinations among 80+ po - + - + @@ -17935,7 +17759,7 @@

COVID vaccinations among 80+ po - + @@ -17948,7 +17772,7 @@

COVID vaccinations among 80+ po - + @@ -17957,7 +17781,7 @@

COVID vaccinations among 80+ po - + @@ -17970,7 +17794,7 @@

COVID vaccinations among 80+ po - + @@ -17981,7 +17805,7 @@

COVID vaccinations among 80+ po - + @@ -17994,7 +17818,7 @@

COVID vaccinations among 80+ po - + @@ -18004,7 +17828,7 @@

COVID vaccinations among 80+ po - + @@ -18017,12 +17841,12 @@

COVID vaccinations among 80+ po - + - + @@ -18035,7 +17859,7 @@

COVID vaccinations among 80+ po - + @@ -18044,7 +17868,7 @@

COVID vaccinations among 80+ po - + @@ -18057,7 +17881,7 @@

COVID vaccinations among 80+ po - + @@ -18066,7 +17890,7 @@

COVID vaccinations among 80+ po - + @@ -18077,29 +17901,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -18107,15 +17917,15 @@

COVID vaccinations among 80+ po - + - + - + @@ -18123,12 +17933,12 @@

COVID vaccinations among 80+ po - + - + @@ -18137,7 +17947,7 @@

COVID vaccinations among 80+ po - + @@ -18145,7 +17955,7 @@

COVID vaccinations among 80+ po - + @@ -18154,12 +17964,12 @@

COVID vaccinations among 80+ po - + - + @@ -18168,7 +17978,7 @@

COVID vaccinations among 80+ po - + @@ -18176,7 +17986,7 @@

COVID vaccinations among 80+ po - + @@ -18185,12 +17995,12 @@

COVID vaccinations among 80+ po - + - + @@ -18198,16 +18008,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -18216,40 +18028,29 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -18270,7 +18071,7 @@

COVID vaccinations among 80+ po - + @@ -18304,18 +18105,18 @@

COVID vaccinations among 80+ po - + - + - + @@ -18323,7 +18124,7 @@

COVID vaccinations among 80+ po - + @@ -18333,7 +18134,7 @@

COVID vaccinations among 80+ po - + @@ -18363,7 +18164,7 @@

COVID vaccinations among 80+ po - + @@ -18373,10 +18174,10 @@

COVID vaccinations among 80+ po - + - + @@ -18389,7 +18190,7 @@

COVID vaccinations among 80+ po - + @@ -18402,7 +18203,7 @@

COVID vaccinations among 80+ po - + @@ -18411,7 +18212,7 @@

COVID vaccinations among 80+ po - + @@ -18424,7 +18225,7 @@

COVID vaccinations among 80+ po - + @@ -18435,7 +18236,7 @@

COVID vaccinations among 80+ po - + @@ -18448,7 +18249,7 @@

COVID vaccinations among 80+ po - + @@ -18458,7 +18259,7 @@

COVID vaccinations among 80+ po - + @@ -18471,12 +18272,12 @@

COVID vaccinations among 80+ po - + - + @@ -18489,7 +18290,7 @@

COVID vaccinations among 80+ po - + @@ -18498,7 +18299,7 @@

COVID vaccinations among 80+ po - + @@ -18511,7 +18312,7 @@

COVID vaccinations among 80+ po - + @@ -18520,7 +18321,7 @@

COVID vaccinations among 80+ po - + @@ -18531,29 +18332,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -18561,10 +18348,10 @@

COVID vaccinations among 80+ po - + - + @@ -18577,12 +18364,12 @@

COVID vaccinations among 80+ po - + - + @@ -18591,7 +18378,7 @@

COVID vaccinations among 80+ po - + @@ -18599,7 +18386,7 @@

COVID vaccinations among 80+ po - + @@ -18608,12 +18395,12 @@

COVID vaccinations among 80+ po - + - + @@ -18622,7 +18409,7 @@

COVID vaccinations among 80+ po - + @@ -18630,7 +18417,7 @@

COVID vaccinations among 80+ po - + @@ -18639,12 +18426,12 @@

COVID vaccinations among 80+ po - + - + @@ -18652,16 +18439,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -18670,40 +18459,29 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -18724,7 +18502,7 @@

COVID vaccinations among 80+ po - + @@ -18758,18 +18536,18 @@

COVID vaccinations among 80+ po - + - + - + @@ -18777,7 +18555,7 @@

COVID vaccinations among 80+ po - + @@ -18787,7 +18565,7 @@

COVID vaccinations among 80+ po - + @@ -18817,7 +18595,7 @@

COVID vaccinations among 80+ po - + @@ -18827,10 +18605,10 @@

COVID vaccinations among 80+ po - + - + @@ -18856,7 +18634,7 @@

COVID vaccinations among 80+ po - + @@ -18865,7 +18643,7 @@

COVID vaccinations among 80+ po - + @@ -18878,7 +18656,7 @@

COVID vaccinations among 80+ po - + @@ -18889,7 +18667,7 @@

COVID vaccinations among 80+ po - + @@ -18902,7 +18680,7 @@

COVID vaccinations among 80+ po - + @@ -18912,7 +18690,7 @@

COVID vaccinations among 80+ po - + @@ -18925,12 +18703,12 @@

COVID vaccinations among 80+ po - + - + @@ -18943,7 +18721,7 @@

COVID vaccinations among 80+ po - + @@ -18952,7 +18730,7 @@

COVID vaccinations among 80+ po - + @@ -18965,7 +18743,7 @@

COVID vaccinations among 80+ po - + @@ -18974,7 +18752,7 @@

COVID vaccinations among 80+ po - + @@ -18985,29 +18763,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -19015,10 +18779,10 @@

COVID vaccinations among 80+ po - + - + @@ -19031,12 +18795,12 @@

COVID vaccinations among 80+ po - + - + @@ -19045,7 +18809,7 @@

COVID vaccinations among 80+ po - + @@ -19053,7 +18817,7 @@

COVID vaccinations among 80+ po - + @@ -19062,12 +18826,12 @@

COVID vaccinations among 80+ po - + - + @@ -19076,7 +18840,7 @@

COVID vaccinations among 80+ po - + @@ -19084,7 +18848,7 @@

COVID vaccinations among 80+ po - + @@ -19093,12 +18857,12 @@

COVID vaccinations among 80+ po - + - + @@ -19106,16 +18870,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -19124,40 +18890,29 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -19178,7 +18933,7 @@

COVID vaccinations among 80+ po - + @@ -19241,7 +18996,7 @@

COVID vaccinations among 80+ po - + @@ -19271,7 +19026,7 @@

COVID vaccinations among 80+ po - + @@ -19281,10 +19036,10 @@

COVID vaccinations among 80+ po - + - + @@ -19310,7 +19065,7 @@

COVID vaccinations among 80+ po - + @@ -19319,7 +19074,7 @@

COVID vaccinations among 80+ po - + @@ -19332,7 +19087,7 @@

COVID vaccinations among 80+ po - + @@ -19343,7 +19098,7 @@

COVID vaccinations among 80+ po - + @@ -19356,7 +19111,7 @@

COVID vaccinations among 80+ po - + @@ -19366,7 +19121,7 @@

COVID vaccinations among 80+ po - + @@ -19379,12 +19134,12 @@

COVID vaccinations among 80+ po - + - + @@ -19397,7 +19152,7 @@

COVID vaccinations among 80+ po - + @@ -19406,7 +19161,7 @@

COVID vaccinations among 80+ po - + @@ -19419,7 +19174,7 @@

COVID vaccinations among 80+ po - + @@ -19428,7 +19183,7 @@

COVID vaccinations among 80+ po - + @@ -19439,29 +19194,15 @@

COVID vaccinations among 80+ po - + - - - - + - - - - - - - - - - - @@ -19469,10 +19210,10 @@

COVID vaccinations among 80+ po - + - + @@ -19485,12 +19226,12 @@

COVID vaccinations among 80+ po - + - + @@ -19499,7 +19240,7 @@

COVID vaccinations among 80+ po - + @@ -19507,7 +19248,7 @@

COVID vaccinations among 80+ po - + @@ -19516,12 +19257,12 @@

COVID vaccinations among 80+ po - + - + @@ -19530,7 +19271,7 @@

COVID vaccinations among 80+ po - + @@ -19538,7 +19279,7 @@

COVID vaccinations among 80+ po - + @@ -19547,12 +19288,12 @@

COVID vaccinations among 80+ po - + - + @@ -19560,16 +19301,18 @@

COVID vaccinations among 80+ po - + + + - + @@ -19578,43 +19321,32 @@

COVID vaccinations among 80+ po - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + @@ -19635,7 +19367,7 @@

COVID vaccinations among 80+ po - + @@ -19721,7 +19453,7 @@

COVID vaccinations among 80+ po - + @@ -19777,7 +19509,7 @@

COVID vaccinations among 70-7 - + @@ -19787,10 +19519,10 @@

COVID vaccinations among 70-7 - + - + @@ -19816,18 +19548,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -19838,20 +19570,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -19862,19 +19594,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -19885,14 +19617,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -19903,18 +19635,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -19925,18 +19657,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -19945,29 +19677,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -19975,10 +19693,10 @@

COVID vaccinations among 70-7 - + - + @@ -19991,12 +19709,12 @@

COVID vaccinations among 70-7 - + - + @@ -20005,15 +19723,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -20022,12 +19737,12 @@

COVID vaccinations among 70-7 - + - + @@ -20036,7 +19751,7 @@

COVID vaccinations among 70-7 - + @@ -20044,7 +19759,7 @@

COVID vaccinations among 70-7 - + @@ -20053,12 +19768,12 @@

COVID vaccinations among 70-7 - + - + @@ -20066,16 +19781,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -20084,40 +19801,29 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -20138,7 +19844,7 @@

COVID vaccinations among 70-7 - + @@ -20195,7 +19901,7 @@

COVID vaccinations among 70-7 - + @@ -20225,7 +19931,7 @@

COVID vaccinations among 70-7 - + @@ -20235,10 +19941,10 @@

COVID vaccinations among 70-7 - + - + @@ -20264,18 +19970,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -20286,20 +19992,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -20310,19 +20016,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -20333,14 +20039,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -20351,18 +20057,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -20373,18 +20079,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -20393,29 +20099,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -20423,10 +20115,10 @@

COVID vaccinations among 70-7 - + - + @@ -20439,12 +20131,12 @@

COVID vaccinations among 70-7 - + - + @@ -20453,15 +20145,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -20470,12 +20159,12 @@

COVID vaccinations among 70-7 - + - + @@ -20484,7 +20173,7 @@

COVID vaccinations among 70-7 - + @@ -20492,7 +20181,7 @@

COVID vaccinations among 70-7 - + @@ -20501,12 +20190,12 @@

COVID vaccinations among 70-7 - + - + @@ -20514,16 +20203,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -20532,52 +20223,41 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -20598,7 +20278,7 @@

COVID vaccinations among 70-7 - + @@ -20657,6 +20337,7 @@

COVID vaccinations among 70-7 + @@ -20747,7 +20428,7 @@

COVID vaccinations among 70-7 - + @@ -20777,7 +20458,7 @@

COVID vaccinations among 70-7 - + @@ -20787,10 +20468,10 @@

COVID vaccinations among 70-7 - + - + @@ -20816,18 +20497,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -20838,20 +20519,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -20862,19 +20543,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -20885,14 +20566,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -20903,18 +20584,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -20925,18 +20606,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -20945,29 +20626,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -20975,10 +20642,10 @@

COVID vaccinations among 70-7 - + - + @@ -20991,12 +20658,12 @@

COVID vaccinations among 70-7 - + - + @@ -21005,15 +20672,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -21022,12 +20686,12 @@

COVID vaccinations among 70-7 - + - + @@ -21036,7 +20700,7 @@

COVID vaccinations among 70-7 - + @@ -21044,7 +20708,7 @@

COVID vaccinations among 70-7 - + @@ -21053,12 +20717,12 @@

COVID vaccinations among 70-7 - + - + @@ -21066,16 +20730,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -21084,52 +20750,41 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -21150,7 +20805,7 @@

COVID vaccinations among 70-7 - + @@ -21189,6 +20844,9 @@

COVID vaccinations among 70-7 + + + @@ -21293,7 +20951,7 @@

COVID vaccinations among 70-7 - + @@ -21323,7 +20981,7 @@

COVID vaccinations among 70-7 - + @@ -21333,10 +20991,10 @@

COVID vaccinations among 70-7 - + - + @@ -21362,18 +21020,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -21384,20 +21042,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -21408,19 +21066,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -21431,14 +21089,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -21449,18 +21107,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -21471,18 +21129,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -21491,29 +21149,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -21521,10 +21165,10 @@

COVID vaccinations among 70-7 - + - + @@ -21537,12 +21181,12 @@

COVID vaccinations among 70-7 - + - + @@ -21551,15 +21195,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -21568,12 +21209,12 @@

COVID vaccinations among 70-7 - + - + @@ -21582,7 +21223,7 @@

COVID vaccinations among 70-7 - + @@ -21590,7 +21231,7 @@

COVID vaccinations among 70-7 - + @@ -21599,12 +21240,12 @@

COVID vaccinations among 70-7 - + - + @@ -21612,16 +21253,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -21630,40 +21273,29 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -21684,7 +21316,7 @@

COVID vaccinations among 70-7 - + @@ -21739,6 +21371,9 @@

COVID vaccinations among 70-7 + + + @@ -21754,7 +21389,7 @@

COVID vaccinations among 70-7 - + @@ -21784,7 +21419,7 @@

COVID vaccinations among 70-7 - + @@ -21794,10 +21429,10 @@

COVID vaccinations among 70-7 - + - + @@ -21823,18 +21458,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -21845,20 +21480,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -21869,19 +21504,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -21892,14 +21527,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -21910,18 +21545,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -21932,18 +21567,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -21952,29 +21587,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -21982,10 +21603,10 @@

COVID vaccinations among 70-7 - + - + @@ -21998,12 +21619,12 @@

COVID vaccinations among 70-7 - + - + @@ -22012,15 +21633,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -22029,12 +21647,12 @@

COVID vaccinations among 70-7 - + - + @@ -22043,7 +21661,7 @@

COVID vaccinations among 70-7 - + @@ -22051,7 +21669,7 @@

COVID vaccinations among 70-7 - + @@ -22060,12 +21678,12 @@

COVID vaccinations among 70-7 - + - + @@ -22073,16 +21691,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -22091,40 +21711,29 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -22145,7 +21754,7 @@

COVID vaccinations among 70-7 - + @@ -22208,7 +21817,7 @@

COVID vaccinations among 70-7 - + @@ -22238,7 +21847,7 @@

COVID vaccinations among 70-7 - + @@ -22248,10 +21857,10 @@

COVID vaccinations among 70-7 - + - + @@ -22277,18 +21886,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -22299,20 +21908,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -22323,19 +21932,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -22346,14 +21955,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -22364,18 +21973,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -22386,18 +21995,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -22406,29 +22015,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -22436,10 +22031,10 @@

COVID vaccinations among 70-7 - + - + @@ -22452,12 +22047,12 @@

COVID vaccinations among 70-7 - + - + @@ -22466,15 +22061,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -22483,12 +22075,12 @@

COVID vaccinations among 70-7 - + - + @@ -22497,7 +22089,7 @@

COVID vaccinations among 70-7 - + @@ -22505,7 +22097,7 @@

COVID vaccinations among 70-7 - + @@ -22514,12 +22106,12 @@

COVID vaccinations among 70-7 - + - + @@ -22527,16 +22119,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -22545,40 +22139,29 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -22599,7 +22182,7 @@

COVID vaccinations among 70-7 - + @@ -22662,7 +22245,7 @@

COVID vaccinations among 70-7 - + @@ -22692,7 +22275,7 @@

COVID vaccinations among 70-7 - + @@ -22702,10 +22285,10 @@

COVID vaccinations among 70-7 - + - + @@ -22718,7 +22301,7 @@

COVID vaccinations among 70-7 - + @@ -22731,18 +22314,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -22753,20 +22336,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -22777,19 +22360,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -22800,14 +22383,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -22818,18 +22401,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -22840,18 +22423,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -22860,29 +22443,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -22890,10 +22459,10 @@

COVID vaccinations among 70-7 - + - + @@ -22906,12 +22475,12 @@

COVID vaccinations among 70-7 - + - + @@ -22920,15 +22489,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -22937,12 +22503,12 @@

COVID vaccinations among 70-7 - + - + @@ -22951,7 +22517,7 @@

COVID vaccinations among 70-7 - + @@ -22959,7 +22525,7 @@

COVID vaccinations among 70-7 - + @@ -22968,12 +22534,12 @@

COVID vaccinations among 70-7 - + - + @@ -22981,16 +22547,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -22999,40 +22567,29 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -23053,7 +22610,7 @@

COVID vaccinations among 70-7 - + @@ -23087,18 +22644,18 @@

COVID vaccinations among 70-7 - + - + - + @@ -23106,7 +22663,7 @@

COVID vaccinations among 70-7 - + @@ -23116,7 +22673,7 @@

COVID vaccinations among 70-7 - + @@ -23146,7 +22703,7 @@

COVID vaccinations among 70-7 - + @@ -23156,10 +22713,10 @@

COVID vaccinations among 70-7 - + - + @@ -23185,18 +22742,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -23207,20 +22764,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -23231,19 +22788,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -23254,14 +22811,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -23272,18 +22829,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -23294,18 +22851,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -23314,29 +22871,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -23344,10 +22887,10 @@

COVID vaccinations among 70-7 - + - + @@ -23360,12 +22903,12 @@

COVID vaccinations among 70-7 - + - + @@ -23374,15 +22917,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -23391,12 +22931,12 @@

COVID vaccinations among 70-7 - + - + @@ -23405,7 +22945,7 @@

COVID vaccinations among 70-7 - + @@ -23413,7 +22953,7 @@

COVID vaccinations among 70-7 - + @@ -23422,12 +22962,12 @@

COVID vaccinations among 70-7 - + - + @@ -23435,16 +22975,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -23453,40 +22995,29 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -23507,7 +23038,7 @@

COVID vaccinations among 70-7 - + @@ -23570,7 +23101,7 @@

COVID vaccinations among 70-7 - + @@ -23600,7 +23131,7 @@

COVID vaccinations among 70-7 - + @@ -23610,10 +23141,10 @@

COVID vaccinations among 70-7 - + - + @@ -23626,7 +23157,7 @@

COVID vaccinations among 70-7 - + @@ -23639,18 +23170,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -23661,20 +23192,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -23685,19 +23216,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -23708,14 +23239,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -23726,18 +23257,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -23748,18 +23279,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -23768,29 +23299,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -23798,10 +23315,10 @@

COVID vaccinations among 70-7 - + - + @@ -23814,12 +23331,12 @@

COVID vaccinations among 70-7 - + - + @@ -23828,15 +23345,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -23845,12 +23359,12 @@

COVID vaccinations among 70-7 - + - + @@ -23859,7 +23373,7 @@

COVID vaccinations among 70-7 - + @@ -23867,7 +23381,7 @@

COVID vaccinations among 70-7 - + @@ -23876,12 +23390,12 @@

COVID vaccinations among 70-7 - + - + @@ -23889,16 +23403,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -23907,40 +23423,29 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -23961,7 +23466,7 @@

COVID vaccinations among 70-7 - + @@ -23995,18 +23500,18 @@

COVID vaccinations among 70-7 - + - + - + @@ -24014,7 +23519,7 @@

COVID vaccinations among 70-7 - + @@ -24024,7 +23529,7 @@

COVID vaccinations among 70-7 - + @@ -24054,7 +23559,7 @@

COVID vaccinations among 70-7 - + @@ -24064,10 +23569,10 @@

COVID vaccinations among 70-7 - + - + @@ -24093,18 +23598,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -24115,20 +23620,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -24139,19 +23644,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -24162,14 +23667,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -24180,18 +23685,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -24202,18 +23707,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -24222,29 +23727,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -24252,10 +23743,10 @@

COVID vaccinations among 70-7 - + - + @@ -24268,12 +23759,12 @@

COVID vaccinations among 70-7 - + - + @@ -24282,15 +23773,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -24299,12 +23787,12 @@

COVID vaccinations among 70-7 - + - + @@ -24313,7 +23801,7 @@

COVID vaccinations among 70-7 - + @@ -24321,7 +23809,7 @@

COVID vaccinations among 70-7 - + @@ -24330,12 +23818,12 @@

COVID vaccinations among 70-7 - + - + @@ -24343,16 +23831,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -24361,40 +23851,29 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -24415,7 +23894,7 @@

COVID vaccinations among 70-7 - + @@ -24478,7 +23957,7 @@

COVID vaccinations among 70-7 - + @@ -24508,7 +23987,7 @@

COVID vaccinations among 70-7 - + @@ -24518,10 +23997,10 @@

COVID vaccinations among 70-7 - + - + @@ -24547,18 +24026,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -24569,20 +24048,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -24593,19 +24072,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -24616,14 +24095,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -24634,18 +24113,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -24656,18 +24135,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -24676,29 +24155,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -24706,10 +24171,10 @@

COVID vaccinations among 70-7 - + - + @@ -24722,12 +24187,12 @@

COVID vaccinations among 70-7 - + - + @@ -24736,15 +24201,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -24753,12 +24215,12 @@

COVID vaccinations among 70-7 - + - + @@ -24767,7 +24229,7 @@

COVID vaccinations among 70-7 - + @@ -24775,7 +24237,7 @@

COVID vaccinations among 70-7 - + @@ -24784,12 +24246,12 @@

COVID vaccinations among 70-7 - + - + @@ -24797,16 +24259,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -24815,40 +24279,29 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -24869,7 +24322,7 @@

COVID vaccinations among 70-7 - + @@ -24932,7 +24385,7 @@

COVID vaccinations among 70-7 - + @@ -24962,7 +24415,7 @@

COVID vaccinations among 70-7 - + @@ -24972,10 +24425,10 @@

COVID vaccinations among 70-7 - + - + @@ -25001,18 +24454,18 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -25023,20 +24476,20 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -25047,19 +24500,19 @@

COVID vaccinations among 70-7 - + - + - + - + - + @@ -25070,14 +24523,14 @@

COVID vaccinations among 70-7 - + - - + + - + @@ -25088,18 +24541,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -25110,18 +24563,18 @@

COVID vaccinations among 70-7 - + - + - + - + @@ -25130,29 +24583,15 @@

COVID vaccinations among 70-7 - + - - - - + - - - - - - - - - - - @@ -25160,10 +24599,10 @@

COVID vaccinations among 70-7 - + - + @@ -25176,12 +24615,12 @@

COVID vaccinations among 70-7 - + - + @@ -25190,15 +24629,12 @@

COVID vaccinations among 70-7 - + - - - - + @@ -25207,12 +24643,12 @@

COVID vaccinations among 70-7 - + - + @@ -25221,7 +24657,7 @@

COVID vaccinations among 70-7 - + @@ -25229,7 +24665,7 @@

COVID vaccinations among 70-7 - + @@ -25238,12 +24674,12 @@

COVID vaccinations among 70-7 - + - + @@ -25251,16 +24687,18 @@

COVID vaccinations among 70-7 - + + + - + @@ -25269,40 +24707,29 @@

COVID vaccinations among 70-7 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -25323,7 +24750,7 @@

COVID vaccinations among 70-7 - + @@ -25363,6 +24790,7 @@

COVID vaccinations among 70-7 + @@ -25394,7 +24822,7 @@

COVID vaccinations among 70-7 - + @@ -25460,10 +24888,10 @@

COVID vaccin - + - + @@ -25489,7 +24917,7 @@

COVID vaccin - + @@ -25498,7 +24926,7 @@

COVID vaccin - + @@ -25511,7 +24939,7 @@

COVID vaccin - + @@ -25522,7 +24950,7 @@

COVID vaccin - + @@ -25535,7 +24963,7 @@

COVID vaccin - + @@ -25545,7 +24973,7 @@

COVID vaccin - + @@ -25558,12 +24986,12 @@

COVID vaccin - + - + @@ -25576,7 +25004,7 @@

COVID vaccin - + @@ -25585,7 +25013,7 @@

COVID vaccin - + @@ -25598,7 +25026,7 @@

COVID vaccin - + @@ -25607,7 +25035,7 @@

COVID vaccin - + @@ -25618,29 +25046,15 @@

COVID vaccin - + - - - - + - - - - - - - - - - - @@ -25648,10 +25062,10 @@

COVID vaccin - + - + @@ -25664,12 +25078,12 @@

COVID vaccin - + - + @@ -25678,12 +25092,12 @@

COVID vaccin - + - + @@ -25692,12 +25106,12 @@

COVID vaccin - + - + @@ -25706,7 +25120,7 @@

COVID vaccin - + @@ -25714,23 +25128,25 @@

COVID vaccin - + - + + + - + @@ -25739,40 +25155,29 @@

COVID vaccin - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -25793,7 +25198,7 @@

COVID vaccin - + @@ -25856,7 +25261,7 @@

COVID vaccin - + @@ -25886,7 +25291,7 @@

COVID vaccin - + @@ -25896,10 +25301,10 @@

COVID vaccin - + - + @@ -25925,7 +25330,7 @@

COVID vaccin - + @@ -25934,7 +25339,7 @@

COVID vaccin - + @@ -25947,7 +25352,7 @@

COVID vaccin - + @@ -25958,7 +25363,7 @@

COVID vaccin - + @@ -25971,7 +25376,7 @@

COVID vaccin - + @@ -25981,7 +25386,7 @@

COVID vaccin - + @@ -25994,12 +25399,12 @@

COVID vaccin - + - + @@ -26012,7 +25417,7 @@

COVID vaccin - + @@ -26021,7 +25426,7 @@

COVID vaccin - + @@ -26034,7 +25439,7 @@

COVID vaccin - + @@ -26043,7 +25448,7 @@

COVID vaccin - + @@ -26054,29 +25459,15 @@

COVID vaccin - + - - - - + - - - - - - - - - - - @@ -26084,10 +25475,10 @@

COVID vaccin - + - + @@ -26100,12 +25491,12 @@

COVID vaccin - + - + @@ -26114,12 +25505,12 @@

COVID vaccin - + - + @@ -26128,12 +25519,12 @@

COVID vaccin - + - + @@ -26142,7 +25533,7 @@

COVID vaccin - + @@ -26150,7 +25541,7 @@

COVID vaccin - + @@ -26159,12 +25550,12 @@

COVID vaccin - + - + @@ -26172,16 +25563,18 @@

COVID vaccin - + + + - + @@ -26190,49 +25583,38 @@

COVID vaccin - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + @@ -26253,7 +25635,7 @@

COVID vaccin - + @@ -26367,7 +25749,7 @@

COVID vaccin - + @@ -26407,10 +25789,10 @@

COVID vaccin - + - + @@ -26436,7 +25818,7 @@

COVID vaccin - + @@ -26445,7 +25827,7 @@

COVID vaccin - + @@ -26458,7 +25840,7 @@

COVID vaccin - + @@ -26469,7 +25851,7 @@

COVID vaccin - + @@ -26482,7 +25864,7 @@

COVID vaccin - + @@ -26492,7 +25874,7 @@

COVID vaccin - + @@ -26505,12 +25887,12 @@

COVID vaccin - + - + @@ -26523,7 +25905,7 @@

COVID vaccin - + @@ -26532,7 +25914,7 @@

COVID vaccin - + @@ -26545,7 +25927,7 @@

COVID vaccin - + @@ -26554,7 +25936,7 @@

COVID vaccin - + @@ -26565,29 +25947,15 @@

COVID vaccin - + - - - - + - - - - - - - - - - - @@ -26595,10 +25963,10 @@

COVID vaccin - + - + @@ -26611,12 +25979,12 @@

COVID vaccin - + - + @@ -26625,12 +25993,12 @@

COVID vaccin - + - + @@ -26639,12 +26007,12 @@

COVID vaccin - + - + @@ -26653,7 +26021,7 @@

COVID vaccin - + @@ -26661,23 +26029,25 @@

COVID vaccin - + - + + + - + @@ -26686,40 +26056,29 @@

COVID vaccin - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -26740,7 +26099,7 @@

COVID vaccin - + @@ -26797,7 +26156,7 @@

COVID vaccin - + @@ -26837,10 +26196,10 @@

COVID vaccin - + - + @@ -26866,7 +26225,7 @@

COVID vaccin - + @@ -26875,7 +26234,7 @@

COVID vaccin - + @@ -26888,7 +26247,7 @@

COVID vaccin - + @@ -26899,7 +26258,7 @@

COVID vaccin - + @@ -26912,7 +26271,7 @@

COVID vaccin - + @@ -26922,7 +26281,7 @@

COVID vaccin - + @@ -26935,12 +26294,12 @@

COVID vaccin - + - + @@ -26953,7 +26312,7 @@

COVID vaccin - + @@ -26962,7 +26321,7 @@

COVID vaccin - + @@ -26975,7 +26334,7 @@

COVID vaccin - + @@ -26984,7 +26343,7 @@

COVID vaccin - + @@ -26995,29 +26354,15 @@

COVID vaccin - + - - - - + - - - - - - - - - - - @@ -27025,10 +26370,10 @@

COVID vaccin - + - + @@ -27041,12 +26386,12 @@

COVID vaccin - + - + @@ -27055,12 +26400,12 @@

COVID vaccin - + - + @@ -27069,12 +26414,12 @@

COVID vaccin - + - + @@ -27083,7 +26428,7 @@

COVID vaccin - + @@ -27091,23 +26436,25 @@

COVID vaccin - + - + + + - + @@ -27116,52 +26463,41 @@

COVID vaccin - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -27182,7 +26518,7 @@

COVID vaccin - + @@ -27241,6 +26577,7 @@

COVID vaccin + @@ -27331,7 +26668,7 @@

COVID vaccin - + @@ -27361,7 +26698,7 @@

COVID vaccin - + @@ -27371,10 +26708,10 @@

COVID vaccin - + - + @@ -27400,7 +26737,7 @@

COVID vaccin - + @@ -27409,7 +26746,7 @@

COVID vaccin - + @@ -27422,7 +26759,7 @@

COVID vaccin - + @@ -27433,7 +26770,7 @@

COVID vaccin - + @@ -27446,7 +26783,7 @@

COVID vaccin - + @@ -27456,7 +26793,7 @@

COVID vaccin - + @@ -27469,12 +26806,12 @@

COVID vaccin - + - + @@ -27487,7 +26824,7 @@

COVID vaccin - + @@ -27496,7 +26833,7 @@

COVID vaccin - + @@ -27509,7 +26846,7 @@

COVID vaccin - + @@ -27518,7 +26855,7 @@

COVID vaccin - + @@ -27529,29 +26866,15 @@

COVID vaccin - + - - - - + - - - - - - - - - - - @@ -27559,10 +26882,10 @@

COVID vaccin - + - + @@ -27575,12 +26898,12 @@

COVID vaccin - + - + @@ -27589,12 +26912,12 @@

COVID vaccin - + - + @@ -27603,12 +26926,12 @@

COVID vaccin - + - + @@ -27617,7 +26940,7 @@

COVID vaccin - + @@ -27625,7 +26948,7 @@

COVID vaccin - + @@ -27634,12 +26957,12 @@

COVID vaccin - + - + @@ -27647,16 +26970,18 @@

COVID vaccin - + + + - + @@ -27665,52 +26990,41 @@

COVID vaccin - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -27731,7 +27045,7 @@

COVID vaccin - + @@ -27770,6 +27084,9 @@

COVID vaccin + + + @@ -27874,7 +27191,7 @@

COVID vaccin - + @@ -27914,10 +27231,10 @@

COVID vaccin - + - + @@ -27930,7 +27247,7 @@

COVID vaccin - + @@ -27943,7 +27260,7 @@

COVID vaccin - + @@ -27952,7 +27269,7 @@

COVID vaccin - + @@ -27965,7 +27282,7 @@

COVID vaccin - + @@ -27976,7 +27293,7 @@

COVID vaccin - + @@ -27989,7 +27306,7 @@

COVID vaccin - + @@ -27999,7 +27316,7 @@

COVID vaccin - + @@ -28012,12 +27329,12 @@

COVID vaccin - + - + @@ -28030,7 +27347,7 @@

COVID vaccin - + @@ -28039,7 +27356,7 @@

COVID vaccin - + @@ -28052,7 +27369,7 @@

COVID vaccin - + @@ -28061,7 +27378,7 @@

COVID vaccin - + @@ -28072,29 +27389,15 @@

COVID vaccin - + - - - - + - - - - - - - - - - - @@ -28102,10 +27405,10 @@

COVID vaccin - + - + @@ -28118,12 +27421,12 @@

COVID vaccin - + - + @@ -28132,12 +27435,12 @@

COVID vaccin - + - + @@ -28146,12 +27449,12 @@

COVID vaccin - + - + @@ -28160,7 +27463,7 @@

COVID vaccin - + @@ -28168,23 +27471,25 @@

COVID vaccin - + - + + + - + @@ -28193,40 +27498,29 @@

COVID vaccin - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -28247,7 +27541,7 @@

COVID vaccin - + @@ -28281,18 +27575,18 @@

COVID vaccin - + - + - + @@ -28300,7 +27594,7 @@

COVID vaccin - + @@ -28310,7 +27604,7 @@

COVID vaccin - + @@ -28358,7 +27652,7 @@

COVID vaccinations among 65-6
- +

COVID vaccinations among 65-6 - + - + - + - + @@ -28392,7 +27686,7 @@

COVID vaccinations among 65-6 - + @@ -28405,7 +27699,7 @@

COVID vaccinations among 65-6 - + @@ -28414,7 +27708,7 @@

COVID vaccinations among 65-6 - + @@ -28427,7 +27721,7 @@

COVID vaccinations among 65-6 - + @@ -28439,7 +27733,7 @@

COVID vaccinations among 65-6 - + @@ -28452,7 +27746,7 @@

COVID vaccinations among 65-6 - + @@ -28462,7 +27756,7 @@

COVID vaccinations among 65-6 - + @@ -28475,12 +27769,12 @@

COVID vaccinations among 65-6 - + - + @@ -28493,7 +27787,7 @@

COVID vaccinations among 65-6 - + @@ -28502,7 +27796,7 @@

COVID vaccinations among 65-6 - + @@ -28515,7 +27809,7 @@

COVID vaccinations among 65-6 - + @@ -28524,7 +27818,7 @@

COVID vaccinations among 65-6 - + @@ -28535,29 +27829,15 @@

COVID vaccinations among 65-6 - + - - - - + - - - - - - - - - - - @@ -28565,15 +27845,15 @@

COVID vaccinations among 65-6 - + - + - + @@ -28581,12 +27861,12 @@

COVID vaccinations among 65-6 - + - + @@ -28595,12 +27875,12 @@

COVID vaccinations among 65-6 - + - + @@ -28609,12 +27889,12 @@

COVID vaccinations among 65-6 - + - + @@ -28623,7 +27903,7 @@

COVID vaccinations among 65-6 - + @@ -28631,7 +27911,7 @@

COVID vaccinations among 65-6 - + @@ -28640,12 +27920,12 @@

COVID vaccinations among 65-6 - + - + @@ -28653,16 +27933,18 @@

COVID vaccinations among 65-6 - + + + - + @@ -28671,52 +27953,41 @@

COVID vaccinations among 65-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -28725,7 +27996,7 @@

COVID vaccinations among 65-6 - + @@ -28756,25 +28027,25 @@

COVID vaccinations among 65-6 - + - + - + - + - + @@ -28782,8 +28053,8 @@

COVID vaccinations among 65-6 - - + + @@ -28812,7 +28083,7 @@

COVID vaccinations among 65-6 - + @@ -28822,10 +28093,10 @@

COVID vaccinations among 65-6 - + - + @@ -28851,7 +28122,7 @@

COVID vaccinations among 65-6 - + @@ -28860,7 +28131,7 @@

COVID vaccinations among 65-6 - + @@ -28873,7 +28144,7 @@

COVID vaccinations among 65-6 - + @@ -28885,7 +28156,7 @@

COVID vaccinations among 65-6 - + @@ -28898,7 +28169,7 @@

COVID vaccinations among 65-6 - + @@ -28908,7 +28179,7 @@

COVID vaccinations among 65-6 - + @@ -28921,12 +28192,12 @@

COVID vaccinations among 65-6 - + - + @@ -28939,7 +28210,7 @@

COVID vaccinations among 65-6 - + @@ -28948,7 +28219,7 @@

COVID vaccinations among 65-6 - + @@ -28961,7 +28232,7 @@

COVID vaccinations among 65-6 - + @@ -28970,7 +28241,7 @@

COVID vaccinations among 65-6 - + @@ -28981,29 +28252,15 @@

COVID vaccinations among 65-6 - + - - - - + - - - - - - - - - - - @@ -29011,10 +28268,10 @@

COVID vaccinations among 65-6 - + - + @@ -29027,12 +28284,12 @@

COVID vaccinations among 65-6 - + - + @@ -29041,12 +28298,12 @@

COVID vaccinations among 65-6 - + - + @@ -29055,12 +28312,12 @@

COVID vaccinations among 65-6 - + - + @@ -29069,7 +28326,7 @@

COVID vaccinations among 65-6 - + @@ -29077,7 +28334,7 @@

COVID vaccinations among 65-6 - + @@ -29086,12 +28343,12 @@

COVID vaccinations among 65-6 - + - + @@ -29099,16 +28356,18 @@

COVID vaccinations among 65-6 - + + + - + @@ -29117,52 +28376,41 @@

COVID vaccinations among 65-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -29183,7 +28431,7 @@

COVID vaccinations among 65-6 - + @@ -29242,6 +28490,7 @@

COVID vaccinations among 65-6 + @@ -29332,7 +28581,7 @@

COVID vaccinations among 65-6 - + @@ -29362,7 +28611,7 @@

COVID vaccinations among 65-6 - + @@ -29372,10 +28621,10 @@

COVID vaccinations among 65-6 - + - + @@ -29401,7 +28650,7 @@

COVID vaccinations among 65-6 - + @@ -29410,7 +28659,7 @@

COVID vaccinations among 65-6 - + @@ -29423,7 +28672,7 @@

COVID vaccinations among 65-6 - + @@ -29435,7 +28684,7 @@

COVID vaccinations among 65-6 - + @@ -29448,7 +28697,7 @@

COVID vaccinations among 65-6 - + @@ -29458,7 +28707,7 @@

COVID vaccinations among 65-6 - + @@ -29471,12 +28720,12 @@

COVID vaccinations among 65-6 - + - + @@ -29489,7 +28738,7 @@

COVID vaccinations among 65-6 - + @@ -29498,7 +28747,7 @@

COVID vaccinations among 65-6 - + @@ -29511,7 +28760,7 @@

COVID vaccinations among 65-6 - + @@ -29520,7 +28769,7 @@

COVID vaccinations among 65-6 - + @@ -29531,29 +28780,15 @@

COVID vaccinations among 65-6 - + - - - - + - - - - - - - - - - - @@ -29561,10 +28796,10 @@

COVID vaccinations among 65-6 - + - + @@ -29577,12 +28812,12 @@

COVID vaccinations among 65-6 - + - + @@ -29591,12 +28826,12 @@

COVID vaccinations among 65-6 - + - + @@ -29605,12 +28840,12 @@

COVID vaccinations among 65-6 - + - + @@ -29619,7 +28854,7 @@

COVID vaccinations among 65-6 - + @@ -29627,7 +28862,7 @@

COVID vaccinations among 65-6 - + @@ -29636,12 +28871,12 @@

COVID vaccinations among 65-6 - + - + @@ -29649,16 +28884,18 @@

COVID vaccinations among 65-6 - + + + - + @@ -29667,52 +28904,41 @@

COVID vaccinations among 65-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -29733,7 +28959,7 @@

COVID vaccinations among 65-6 - + @@ -29772,6 +28998,9 @@

COVID vaccinations among 65-6 + + + @@ -29876,7 +29105,7 @@

COVID vaccinations among 65-6 - + @@ -29906,7 +29135,7 @@

COVID vaccinations among 65-6 - + @@ -29916,10 +29145,10 @@

COVID vaccinations among 65-6 - + - + @@ -29932,7 +29161,7 @@

COVID vaccinations among 65-6 - + @@ -29945,7 +29174,7 @@

COVID vaccinations among 65-6 - + @@ -29954,7 +29183,7 @@

COVID vaccinations among 65-6 - + @@ -29967,7 +29196,7 @@

COVID vaccinations among 65-6 - + @@ -29979,7 +29208,7 @@

COVID vaccinations among 65-6 - + @@ -29992,7 +29221,7 @@

COVID vaccinations among 65-6 - + @@ -30002,7 +29231,7 @@

COVID vaccinations among 65-6 - + @@ -30015,12 +29244,12 @@

COVID vaccinations among 65-6 - + - + @@ -30033,7 +29262,7 @@

COVID vaccinations among 65-6 - + @@ -30042,7 +29271,7 @@

COVID vaccinations among 65-6 - + @@ -30055,7 +29284,7 @@

COVID vaccinations among 65-6 - + @@ -30064,7 +29293,7 @@

COVID vaccinations among 65-6 - + @@ -30075,29 +29304,15 @@

COVID vaccinations among 65-6 - + - - - - + - - - - - - - - - - - @@ -30105,10 +29320,10 @@

COVID vaccinations among 65-6 - + - + @@ -30121,12 +29336,12 @@

COVID vaccinations among 65-6 - + - + @@ -30135,12 +29350,12 @@

COVID vaccinations among 65-6 - + - + @@ -30149,12 +29364,12 @@

COVID vaccinations among 65-6 - + - + @@ -30163,7 +29378,7 @@

COVID vaccinations among 65-6 - + @@ -30171,7 +29386,7 @@

COVID vaccinations among 65-6 - + @@ -30180,12 +29395,12 @@

COVID vaccinations among 65-6 - + - + @@ -30193,16 +29408,18 @@

COVID vaccinations among 65-6 - + + + - + @@ -30211,40 +29428,29 @@

COVID vaccinations among 65-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -30265,7 +29471,7 @@

COVID vaccinations among 65-6 - + @@ -30299,7 +29505,7 @@

COVID vaccinations among 65-6 - + @@ -30308,19 +29514,22 @@

COVID vaccinations among 65-6 - + - + - + + + + @@ -30335,7 +29544,7 @@

COVID vaccinations among 65-6 - + @@ -30365,7 +29574,7 @@

COVID vaccinations among 65-6 - + @@ -30375,10 +29584,10 @@

COVID vaccinations among 65-6 - + - + @@ -30404,7 +29613,7 @@

COVID vaccinations among 65-6 - + @@ -30413,7 +29622,7 @@

COVID vaccinations among 65-6 - + @@ -30426,7 +29635,7 @@

COVID vaccinations among 65-6 - + @@ -30438,7 +29647,7 @@

COVID vaccinations among 65-6 - + @@ -30451,7 +29660,7 @@

COVID vaccinations among 65-6 - + @@ -30461,7 +29670,7 @@

COVID vaccinations among 65-6 - + @@ -30474,12 +29683,12 @@

COVID vaccinations among 65-6 - + - + @@ -30492,7 +29701,7 @@

COVID vaccinations among 65-6 - + @@ -30501,7 +29710,7 @@

COVID vaccinations among 65-6 - + @@ -30514,7 +29723,7 @@

COVID vaccinations among 65-6 - + @@ -30523,7 +29732,7 @@

COVID vaccinations among 65-6 - + @@ -30534,29 +29743,15 @@

COVID vaccinations among 65-6 - + - - - - + - - - - - - - - - - - @@ -30564,10 +29759,10 @@

COVID vaccinations among 65-6 - + - + @@ -30580,12 +29775,12 @@

COVID vaccinations among 65-6 - + - + @@ -30594,12 +29789,12 @@

COVID vaccinations among 65-6 - + - + @@ -30608,12 +29803,12 @@

COVID vaccinations among 65-6 - + - + @@ -30622,7 +29817,7 @@

COVID vaccinations among 65-6 - + @@ -30630,7 +29825,7 @@

COVID vaccinations among 65-6 - + @@ -30639,12 +29834,12 @@

COVID vaccinations among 65-6 - + - + @@ -30652,16 +29847,18 @@

COVID vaccinations among 65-6 - + + + - + @@ -30670,40 +29867,29 @@

COVID vaccinations among 65-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -30724,7 +29910,7 @@

COVID vaccinations among 65-6 - + @@ -30787,7 +29973,7 @@

COVID vaccinations among 65-6 - + @@ -30817,7 +30003,7 @@

COVID vaccinations among 65-6 - + @@ -30827,10 +30013,10 @@

COVID vaccinations among 65-6 - + - + @@ -30856,7 +30042,7 @@

COVID vaccinations among 65-6 - + @@ -30865,7 +30051,7 @@

COVID vaccinations among 65-6 - + @@ -30878,7 +30064,7 @@

COVID vaccinations among 65-6 - + @@ -30890,7 +30076,7 @@

COVID vaccinations among 65-6 - + @@ -30903,7 +30089,7 @@

COVID vaccinations among 65-6 - + @@ -30913,7 +30099,7 @@

COVID vaccinations among 65-6 - + @@ -30926,12 +30112,12 @@

COVID vaccinations among 65-6 - + - + @@ -30944,7 +30130,7 @@

COVID vaccinations among 65-6 - + @@ -30953,7 +30139,7 @@

COVID vaccinations among 65-6 - + @@ -30966,7 +30152,7 @@

COVID vaccinations among 65-6 - + @@ -30975,7 +30161,7 @@

COVID vaccinations among 65-6 - + @@ -30986,29 +30172,15 @@

COVID vaccinations among 65-6 - + - - - - + - - - - - - - - - - - @@ -31016,10 +30188,10 @@

COVID vaccinations among 65-6 - + - + @@ -31032,12 +30204,12 @@

COVID vaccinations among 65-6 - + - + @@ -31046,12 +30218,12 @@

COVID vaccinations among 65-6 - + - + @@ -31060,12 +30232,12 @@

COVID vaccinations among 65-6 - + - + @@ -31074,7 +30246,7 @@

COVID vaccinations among 65-6 - + @@ -31082,7 +30254,7 @@

COVID vaccinations among 65-6 - + @@ -31091,12 +30263,12 @@

COVID vaccinations among 65-6 - + - + @@ -31104,16 +30276,18 @@

COVID vaccinations among 65-6 - + + + - + @@ -31122,40 +30296,29 @@

COVID vaccinations among 65-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -31176,7 +30339,7 @@

COVID vaccinations among 65-6 - + @@ -31239,7 +30402,7 @@

COVID vaccinations among 65-6 - + @@ -31261,7 +30424,7 @@

COVID vaccinations among 65-6
- +

COVID vaccinations among 65-6 - + - + - + - + @@ -31295,7 +30458,7 @@

COVID vaccinations among 65-6 - + @@ -31308,7 +30471,7 @@

COVID vaccinations among 65-6 - + @@ -31317,7 +30480,7 @@

COVID vaccinations among 65-6 - + @@ -31330,7 +30493,7 @@

COVID vaccinations among 65-6 - + @@ -31342,7 +30505,7 @@

COVID vaccinations among 65-6 - + @@ -31355,7 +30518,7 @@

COVID vaccinations among 65-6 - + @@ -31365,7 +30528,7 @@

COVID vaccinations among 65-6 - + @@ -31378,12 +30541,12 @@

COVID vaccinations among 65-6 - + - + @@ -31396,7 +30559,7 @@

COVID vaccinations among 65-6 - + @@ -31405,7 +30568,7 @@

COVID vaccinations among 65-6 - + @@ -31418,7 +30581,7 @@

COVID vaccinations among 65-6 - + @@ -31427,7 +30590,7 @@

COVID vaccinations among 65-6 - + @@ -31438,29 +30601,15 @@

COVID vaccinations among 65-6 - + - - - - + - - - - - - - - - - - @@ -31468,15 +30617,15 @@

COVID vaccinations among 65-6 - + - + - + @@ -31484,12 +30633,12 @@

COVID vaccinations among 65-6 - + - + @@ -31498,12 +30647,12 @@

COVID vaccinations among 65-6 - + - + @@ -31512,12 +30661,12 @@

COVID vaccinations among 65-6 - + - + @@ -31526,7 +30675,7 @@

COVID vaccinations among 65-6 - + @@ -31534,7 +30683,7 @@

COVID vaccinations among 65-6 - + @@ -31543,7 +30692,7 @@

COVID vaccinations among 65-6 - + @@ -31556,16 +30705,18 @@

COVID vaccinations among 65-6 - + + + - + @@ -31574,52 +30725,41 @@

COVID vaccinations among 65-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -31628,7 +30768,7 @@

COVID vaccinations among 65-6 - + @@ -31659,21 +30799,21 @@

COVID vaccinations among 65-6 - + - + - + - + @@ -31681,7 +30821,7 @@

COVID vaccinations among 65-6 - + @@ -31691,8 +30831,8 @@

COVID vaccinations among 65-6 - - + + @@ -31713,7 +30853,7 @@

COVID vaccinations among 65-6
- +

COVID vaccinations among 65-6 - + - + - + - + @@ -31747,7 +30887,7 @@

COVID vaccinations among 65-6 - + @@ -31760,7 +30900,7 @@

COVID vaccinations among 65-6 - + @@ -31769,7 +30909,7 @@

COVID vaccinations among 65-6 - + @@ -31782,7 +30922,7 @@

COVID vaccinations among 65-6 - + @@ -31794,7 +30934,7 @@

COVID vaccinations among 65-6 - + @@ -31807,7 +30947,7 @@

COVID vaccinations among 65-6 - + @@ -31817,7 +30957,7 @@

COVID vaccinations among 65-6 - + @@ -31830,12 +30970,12 @@

COVID vaccinations among 65-6 - + - + @@ -31848,7 +30988,7 @@

COVID vaccinations among 65-6 - + @@ -31857,7 +30997,7 @@

COVID vaccinations among 65-6 - + @@ -31870,7 +31010,7 @@

COVID vaccinations among 65-6 - + @@ -31879,7 +31019,7 @@

COVID vaccinations among 65-6 - + @@ -31890,29 +31030,15 @@

COVID vaccinations among 65-6 - + - - - - + - - - - - - - - - - - @@ -31920,15 +31046,15 @@

COVID vaccinations among 65-6 - + - + - + @@ -31936,12 +31062,12 @@

COVID vaccinations among 65-6 - + - + @@ -31950,12 +31076,12 @@

COVID vaccinations among 65-6 - + - + @@ -31964,12 +31090,12 @@

COVID vaccinations among 65-6 - + - + @@ -31978,7 +31104,7 @@

COVID vaccinations among 65-6 - + @@ -31986,7 +31112,7 @@

COVID vaccinations among 65-6 - + @@ -31995,12 +31121,12 @@

COVID vaccinations among 65-6 - + - + @@ -32008,16 +31134,18 @@

COVID vaccinations among 65-6 - + + + - + @@ -32026,52 +31154,41 @@

COVID vaccinations among 65-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -32080,7 +31197,7 @@

COVID vaccinations among 65-6 - + @@ -32111,21 +31228,21 @@

COVID vaccinations among 65-6 - + - + - + - + @@ -32133,7 +31250,7 @@

COVID vaccinations among 65-6 - + @@ -32143,8 +31260,8 @@

COVID vaccinations among 65-6 - - + + @@ -32165,7 +31282,7 @@

COVID vaccinations among 65-6
- +

COVID vaccinations among 65-6 - + - + - + - + @@ -32199,7 +31316,7 @@

COVID vaccinations among 65-6 - + @@ -32212,7 +31329,7 @@

COVID vaccinations among 65-6 - + @@ -32221,7 +31338,7 @@

COVID vaccinations among 65-6 - + @@ -32234,7 +31351,7 @@

COVID vaccinations among 65-6 - + @@ -32246,7 +31363,7 @@

COVID vaccinations among 65-6 - + @@ -32259,7 +31376,7 @@

COVID vaccinations among 65-6 - + @@ -32269,7 +31386,7 @@

COVID vaccinations among 65-6 - + @@ -32282,12 +31399,12 @@

COVID vaccinations among 65-6 - + - + @@ -32300,7 +31417,7 @@

COVID vaccinations among 65-6 - + @@ -32309,7 +31426,7 @@

COVID vaccinations among 65-6 - + @@ -32322,7 +31439,7 @@

COVID vaccinations among 65-6 - + @@ -32331,7 +31448,7 @@

COVID vaccinations among 65-6 - + @@ -32342,29 +31459,15 @@

COVID vaccinations among 65-6 - + - - - - + - - - - - - - - - - - @@ -32372,15 +31475,15 @@

COVID vaccinations among 65-6 - + - + - + @@ -32388,12 +31491,12 @@

COVID vaccinations among 65-6 - + - + @@ -32402,12 +31505,12 @@

COVID vaccinations among 65-6 - + - + @@ -32416,12 +31519,12 @@

COVID vaccinations among 65-6 - + - + @@ -32430,7 +31533,7 @@

COVID vaccinations among 65-6 - + @@ -32438,7 +31541,7 @@

COVID vaccinations among 65-6 - + @@ -32447,12 +31550,12 @@

COVID vaccinations among 65-6 - + - + @@ -32460,16 +31563,18 @@

COVID vaccinations among 65-6 - + + + - + @@ -32478,52 +31583,41 @@

COVID vaccinations among 65-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -32532,7 +31626,7 @@

COVID vaccinations among 65-6 - + @@ -32563,21 +31657,21 @@

COVID vaccinations among 65-6 - + - + - + - + @@ -32585,7 +31679,7 @@

COVID vaccinations among 65-6 - + @@ -32595,8 +31689,8 @@

COVID vaccinations among 65-6 - - + + @@ -32625,7 +31719,7 @@

COVID vaccinations among 65-6 - + @@ -32635,10 +31729,10 @@

COVID vaccinations among 65-6 - + - + @@ -32664,7 +31758,7 @@

COVID vaccinations among 65-6 - + @@ -32673,7 +31767,7 @@

COVID vaccinations among 65-6 - + @@ -32686,7 +31780,7 @@

COVID vaccinations among 65-6 - + @@ -32698,7 +31792,7 @@

COVID vaccinations among 65-6 - + @@ -32711,7 +31805,7 @@

COVID vaccinations among 65-6 - + @@ -32721,7 +31815,7 @@

COVID vaccinations among 65-6 - + @@ -32734,12 +31828,12 @@

COVID vaccinations among 65-6 - + - + @@ -32752,7 +31846,7 @@

COVID vaccinations among 65-6 - + @@ -32761,7 +31855,7 @@

COVID vaccinations among 65-6 - + @@ -32774,7 +31868,7 @@

COVID vaccinations among 65-6 - + @@ -32783,7 +31877,7 @@

COVID vaccinations among 65-6 - + @@ -32794,29 +31888,15 @@

COVID vaccinations among 65-6 - + - - - - + - - - - - - - - - - - @@ -32824,10 +31904,10 @@

COVID vaccinations among 65-6 - + - + @@ -32840,12 +31920,12 @@

COVID vaccinations among 65-6 - + - + @@ -32854,12 +31934,12 @@

COVID vaccinations among 65-6 - + - + @@ -32868,12 +31948,12 @@

COVID vaccinations among 65-6 - + - + @@ -32882,7 +31962,7 @@

COVID vaccinations among 65-6 - + @@ -32890,7 +31970,7 @@

COVID vaccinations among 65-6 - + @@ -32899,12 +31979,12 @@

COVID vaccinations among 65-6 - + - + @@ -32912,16 +31992,18 @@

COVID vaccinations among 65-6 - + + + - + @@ -32930,40 +32012,29 @@

COVID vaccinations among 65-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -32984,7 +32055,7 @@

COVID vaccinations among 65-6 - + @@ -33047,7 +32118,7 @@

COVID vaccinations among 65-6 - + @@ -33095,7 +32166,7 @@

COVID vaccinations among 60-6
- +

COVID vaccinations among 60-6 - + - + - + - + @@ -33129,7 +32200,7 @@

COVID vaccinations among 60-6 - + @@ -33142,7 +32213,7 @@

COVID vaccinations among 60-6 - + @@ -33150,7 +32221,7 @@

COVID vaccinations among 60-6 - + @@ -33163,7 +32234,7 @@

COVID vaccinations among 60-6 - + @@ -33175,7 +32246,7 @@

COVID vaccinations among 60-6 - + @@ -33188,7 +32259,7 @@

COVID vaccinations among 60-6 - + @@ -33198,7 +32269,7 @@

COVID vaccinations among 60-6 - + @@ -33211,12 +32282,12 @@

COVID vaccinations among 60-6 - + - + @@ -33229,7 +32300,7 @@

COVID vaccinations among 60-6 - + @@ -33238,7 +32309,7 @@

COVID vaccinations among 60-6 - + @@ -33251,7 +32322,7 @@

COVID vaccinations among 60-6 - + @@ -33260,7 +32331,7 @@

COVID vaccinations among 60-6 - + @@ -33271,29 +32342,15 @@

COVID vaccinations among 60-6 - + - - - - + - - - - - - - - - - - @@ -33301,15 +32358,15 @@

COVID vaccinations among 60-6 - + - + - + @@ -33317,12 +32374,12 @@

COVID vaccinations among 60-6 - + - + @@ -33331,7 +32388,7 @@

COVID vaccinations among 60-6 - + @@ -33339,7 +32396,7 @@

COVID vaccinations among 60-6 - + @@ -33348,12 +32405,12 @@

COVID vaccinations among 60-6 - + - + @@ -33362,28 +32419,45 @@

COVID vaccinations among 60-6 - + - + - - + + + + + + + + + + + + + + + + + + + - + @@ -33392,61 +32466,50 @@

COVID vaccinations among 60-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - - - - + - + + + + - + - + - + - + - + - + @@ -33477,25 +32540,25 @@

COVID vaccinations among 60-6 - + - - + + - - + + - + - - + + - - + + - + @@ -33503,8 +32566,8 @@

COVID vaccinations among 60-6 - - + + @@ -33525,7 +32588,7 @@

COVID vaccinations among 60-6
- +

COVID vaccinations among 60-6 - + - + - + - + @@ -33559,7 +32622,7 @@

COVID vaccinations among 60-6 - + @@ -33572,7 +32635,7 @@

COVID vaccinations among 60-6 - + @@ -33580,7 +32643,7 @@

COVID vaccinations among 60-6 - + @@ -33593,7 +32656,7 @@

COVID vaccinations among 60-6 - + @@ -33605,7 +32668,7 @@

COVID vaccinations among 60-6 - + @@ -33618,7 +32681,7 @@

COVID vaccinations among 60-6 - + @@ -33628,7 +32691,7 @@

COVID vaccinations among 60-6 - + @@ -33641,12 +32704,12 @@

COVID vaccinations among 60-6 - + - + @@ -33659,7 +32722,7 @@

COVID vaccinations among 60-6 - + @@ -33668,7 +32731,7 @@

COVID vaccinations among 60-6 - + @@ -33681,7 +32744,7 @@

COVID vaccinations among 60-6 - + @@ -33690,7 +32753,7 @@

COVID vaccinations among 60-6 - + @@ -33701,29 +32764,15 @@

COVID vaccinations among 60-6 - + - - - - + - - - - - - - - - - - @@ -33731,15 +32780,15 @@

COVID vaccinations among 60-6 - + - + - + @@ -33747,12 +32796,12 @@

COVID vaccinations among 60-6 - + - + @@ -33761,7 +32810,7 @@

COVID vaccinations among 60-6 - + @@ -33769,7 +32818,7 @@

COVID vaccinations among 60-6 - + @@ -33778,12 +32827,12 @@

COVID vaccinations among 60-6 - + - + @@ -33792,12 +32841,12 @@

COVID vaccinations among 60-6 - + - + @@ -33806,7 +32855,7 @@

COVID vaccinations among 60-6 - + @@ -33819,16 +32868,18 @@

COVID vaccinations among 60-6 - + + + - + @@ -33837,64 +32888,53 @@

COVID vaccinations among 60-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + - + - + - + - + @@ -33903,7 +32943,7 @@

COVID vaccinations among 60-6 - + @@ -33934,10 +32974,10 @@

COVID vaccinations among 60-6 - + - + @@ -33946,7 +32986,7 @@

COVID vaccinations among 60-6 - + @@ -33955,15 +32995,16 @@

COVID vaccinations among 60-6 - + + - + @@ -33972,7 +33013,7 @@

COVID vaccinations among 60-6 - + @@ -33980,7 +33021,7 @@

COVID vaccinations among 60-6 - + @@ -33989,7 +33030,7 @@

COVID vaccinations among 60-6 - + @@ -33997,7 +33038,7 @@

COVID vaccinations among 60-6 - + @@ -34012,7 +33053,7 @@

COVID vaccinations among 60-6 - + @@ -34021,7 +33062,7 @@

COVID vaccinations among 60-6 - + @@ -34032,7 +33073,7 @@

COVID vaccinations among 60-6 - + @@ -34040,7 +33081,7 @@

COVID vaccinations among 60-6 - + @@ -34052,8 +33093,8 @@

COVID vaccinations among 60-6 - - + + @@ -34082,7 +33123,7 @@

COVID vaccinations among 60-6 - + @@ -34092,10 +33133,10 @@

COVID vaccinations among 60-6 - + - + @@ -34121,7 +33162,7 @@

COVID vaccinations among 60-6 - + @@ -34129,7 +33170,7 @@

COVID vaccinations among 60-6 - + @@ -34142,7 +33183,7 @@

COVID vaccinations among 60-6 - + @@ -34154,7 +33195,7 @@

COVID vaccinations among 60-6 - + @@ -34167,7 +33208,7 @@

COVID vaccinations among 60-6 - + @@ -34177,7 +33218,7 @@

COVID vaccinations among 60-6 - + @@ -34190,12 +33231,12 @@

COVID vaccinations among 60-6 - + - + @@ -34208,7 +33249,7 @@

COVID vaccinations among 60-6 - + @@ -34217,7 +33258,7 @@

COVID vaccinations among 60-6 - + @@ -34230,7 +33271,7 @@

COVID vaccinations among 60-6 - + @@ -34239,7 +33280,7 @@

COVID vaccinations among 60-6 - + @@ -34250,29 +33291,15 @@

COVID vaccinations among 60-6 - + - - - - + - - - - - - - - - - - @@ -34280,10 +33307,10 @@

COVID vaccinations among 60-6 - + - + @@ -34296,12 +33323,12 @@

COVID vaccinations among 60-6 - + - + @@ -34310,7 +33337,7 @@

COVID vaccinations among 60-6 - + @@ -34318,7 +33345,7 @@

COVID vaccinations among 60-6 - + @@ -34327,12 +33354,12 @@

COVID vaccinations among 60-6 - + - + @@ -34341,12 +33368,12 @@

COVID vaccinations among 60-6 - + - + @@ -34355,12 +33382,12 @@

COVID vaccinations among 60-6 - + - + @@ -34368,16 +33395,18 @@

COVID vaccinations among 60-6 - + + + - + @@ -34386,52 +33415,41 @@

COVID vaccinations among 60-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -34452,7 +33470,7 @@

COVID vaccinations among 60-6 - + @@ -34491,6 +33509,9 @@

COVID vaccinations among 60-6 + + + @@ -34596,7 +33617,7 @@

COVID vaccinations among 60-6 - + @@ -34626,7 +33647,7 @@

COVID vaccinations among 60-6 - + @@ -34636,10 +33657,10 @@

COVID vaccinations among 60-6 - + - + @@ -34652,7 +33673,7 @@

COVID vaccinations among 60-6 - + @@ -34665,7 +33686,7 @@

COVID vaccinations among 60-6 - + @@ -34673,7 +33694,7 @@

COVID vaccinations among 60-6 - + @@ -34686,7 +33707,7 @@

COVID vaccinations among 60-6 - + @@ -34698,7 +33719,7 @@

COVID vaccinations among 60-6 - + @@ -34711,7 +33732,7 @@

COVID vaccinations among 60-6 - + @@ -34721,7 +33742,7 @@

COVID vaccinations among 60-6 - + @@ -34734,12 +33755,12 @@

COVID vaccinations among 60-6 - + - + @@ -34752,7 +33773,7 @@

COVID vaccinations among 60-6 - + @@ -34761,7 +33782,7 @@

COVID vaccinations among 60-6 - + @@ -34774,7 +33795,7 @@

COVID vaccinations among 60-6 - + @@ -34783,7 +33804,7 @@

COVID vaccinations among 60-6 - + @@ -34794,29 +33815,15 @@

COVID vaccinations among 60-6 - + - - - - + - - - - - - - - - - - @@ -34824,15 +33831,15 @@

COVID vaccinations among 60-6 - + - + - + @@ -34840,12 +33847,12 @@

COVID vaccinations among 60-6 - + - + @@ -34854,7 +33861,7 @@

COVID vaccinations among 60-6 - + @@ -34862,7 +33869,7 @@

COVID vaccinations among 60-6 - + @@ -34871,12 +33878,12 @@

COVID vaccinations among 60-6 - + - + @@ -34885,12 +33892,12 @@

COVID vaccinations among 60-6 - + - + @@ -34899,12 +33906,12 @@

COVID vaccinations among 60-6 - + - + @@ -34912,16 +33919,18 @@

COVID vaccinations among 60-6 - + + + - + @@ -34930,40 +33939,29 @@

COVID vaccinations among 60-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -34984,7 +33982,7 @@

COVID vaccinations among 60-6 - + @@ -35018,7 +34016,7 @@

COVID vaccinations among 60-6 - + @@ -35027,19 +34025,22 @@

COVID vaccinations among 60-6 - + - + - + + + + @@ -35054,7 +34055,7 @@

COVID vaccinations among 60-6 - + @@ -35076,7 +34077,7 @@

COVID vaccinations among 60-6
- +

COVID vaccinations among 60-6 - + - + - + - + @@ -35110,7 +34111,7 @@

COVID vaccinations among 60-6 - + @@ -35123,7 +34124,7 @@

COVID vaccinations among 60-6 - + @@ -35131,7 +34132,7 @@

COVID vaccinations among 60-6 - + @@ -35144,7 +34145,7 @@

COVID vaccinations among 60-6 - + @@ -35156,7 +34157,7 @@

COVID vaccinations among 60-6 - + @@ -35169,7 +34170,7 @@

COVID vaccinations among 60-6 - + @@ -35179,7 +34180,7 @@

COVID vaccinations among 60-6 - + @@ -35192,12 +34193,12 @@

COVID vaccinations among 60-6 - + - + @@ -35210,7 +34211,7 @@

COVID vaccinations among 60-6 - + @@ -35219,7 +34220,7 @@

COVID vaccinations among 60-6 - + @@ -35232,7 +34233,7 @@

COVID vaccinations among 60-6 - + @@ -35241,7 +34242,7 @@

COVID vaccinations among 60-6 - + @@ -35252,29 +34253,15 @@

COVID vaccinations among 60-6 - + - - - - + - - - - - - - - - - - @@ -35282,15 +34269,15 @@

COVID vaccinations among 60-6 - + - + - + @@ -35298,12 +34285,12 @@

COVID vaccinations among 60-6 - + - + @@ -35312,7 +34299,7 @@

COVID vaccinations among 60-6 - + @@ -35320,7 +34307,7 @@

COVID vaccinations among 60-6 - + @@ -35329,12 +34316,12 @@

COVID vaccinations among 60-6 - + - + @@ -35343,12 +34330,12 @@

COVID vaccinations among 60-6 - + - + @@ -35357,7 +34344,7 @@

COVID vaccinations among 60-6 - + @@ -35370,16 +34357,18 @@

COVID vaccinations among 60-6 - + + + - + @@ -35388,52 +34377,41 @@

COVID vaccinations among 60-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -35442,7 +34420,7 @@

COVID vaccinations among 60-6 - + @@ -35473,21 +34451,21 @@

COVID vaccinations among 60-6 - + - + - + - + @@ -35495,7 +34473,7 @@

COVID vaccinations among 60-6 - + @@ -35505,8 +34483,8 @@

COVID vaccinations among 60-6 - - + + @@ -35527,7 +34505,7 @@

COVID vaccinations among 60-6
- +

COVID vaccinations among 60-6 - + - + - + - + @@ -35561,7 +34539,7 @@

COVID vaccinations among 60-6 - + @@ -35574,7 +34552,7 @@

COVID vaccinations among 60-6 - + @@ -35582,7 +34560,7 @@

COVID vaccinations among 60-6 - + @@ -35595,7 +34573,7 @@

COVID vaccinations among 60-6 - + @@ -35607,7 +34585,7 @@

COVID vaccinations among 60-6 - + @@ -35620,7 +34598,7 @@

COVID vaccinations among 60-6 - + @@ -35630,7 +34608,7 @@

COVID vaccinations among 60-6 - + @@ -35643,12 +34621,12 @@

COVID vaccinations among 60-6 - + - + @@ -35661,7 +34639,7 @@

COVID vaccinations among 60-6 - + @@ -35670,7 +34648,7 @@

COVID vaccinations among 60-6 - + @@ -35683,7 +34661,7 @@

COVID vaccinations among 60-6 - + @@ -35692,7 +34670,7 @@

COVID vaccinations among 60-6 - + @@ -35703,29 +34681,15 @@

COVID vaccinations among 60-6 - + - - - - + - - - - - - - - - - - @@ -35733,15 +34697,15 @@

COVID vaccinations among 60-6 - + - + - + @@ -35749,12 +34713,12 @@

COVID vaccinations among 60-6 - + - + @@ -35763,7 +34727,7 @@

COVID vaccinations among 60-6 - + @@ -35771,7 +34735,7 @@

COVID vaccinations among 60-6 - + @@ -35780,12 +34744,12 @@

COVID vaccinations among 60-6 - + - + @@ -35794,12 +34758,12 @@

COVID vaccinations among 60-6 - + - + @@ -35808,7 +34772,7 @@

COVID vaccinations among 60-6 - + @@ -35821,16 +34785,18 @@

COVID vaccinations among 60-6 - + + + - + @@ -35839,52 +34805,41 @@

COVID vaccinations among 60-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -35893,7 +34848,7 @@

COVID vaccinations among 60-6 - + @@ -35924,21 +34879,21 @@

COVID vaccinations among 60-6 - + - + - + - + @@ -35946,7 +34901,7 @@

COVID vaccinations among 60-6 - + @@ -35956,8 +34911,8 @@

COVID vaccinations among 60-6 - - + + @@ -35978,7 +34933,7 @@

COVID vaccinations among 60-6
- +

COVID vaccinations among 60-6 - + - + - + - + @@ -36012,7 +34967,7 @@

COVID vaccinations among 60-6 - + @@ -36025,7 +34980,7 @@

COVID vaccinations among 60-6 - + @@ -36033,7 +34988,7 @@

COVID vaccinations among 60-6 - + @@ -36046,7 +35001,7 @@

COVID vaccinations among 60-6 - + @@ -36058,7 +35013,7 @@

COVID vaccinations among 60-6 - + @@ -36071,7 +35026,7 @@

COVID vaccinations among 60-6 - + @@ -36081,7 +35036,7 @@

COVID vaccinations among 60-6 - + @@ -36094,12 +35049,12 @@

COVID vaccinations among 60-6 - + - + @@ -36112,7 +35067,7 @@

COVID vaccinations among 60-6 - + @@ -36121,7 +35076,7 @@

COVID vaccinations among 60-6 - + @@ -36134,7 +35089,7 @@

COVID vaccinations among 60-6 - + @@ -36143,7 +35098,7 @@

COVID vaccinations among 60-6 - + @@ -36154,29 +35109,15 @@

COVID vaccinations among 60-6 - + - - - - + - - - - - - - - - - - @@ -36184,15 +35125,15 @@

COVID vaccinations among 60-6 - + - + - + @@ -36200,12 +35141,12 @@

COVID vaccinations among 60-6 - + - + @@ -36214,7 +35155,7 @@

COVID vaccinations among 60-6 - + @@ -36222,7 +35163,7 @@

COVID vaccinations among 60-6 - + @@ -36231,12 +35172,12 @@

COVID vaccinations among 60-6 - + - + @@ -36245,28 +35186,45 @@

COVID vaccinations among 60-6 - + - + - - + + + + + + + + + + + + + + + + + + + - + @@ -36275,61 +35233,50 @@

COVID vaccinations among 60-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - - - - + - + + + + - + - + - + - + - + - + @@ -36360,29 +35307,29 @@

COVID vaccinations among 60-6 - + - - + + - - + + - + - - + + - - + + - + @@ -36392,8 +35339,8 @@

COVID vaccinations among 60-6 - - + + @@ -36432,10 +35379,10 @@

COVID vaccinations among 60-6 - + - + @@ -36461,7 +35408,7 @@

COVID vaccinations among 60-6 - + @@ -36469,7 +35416,7 @@

COVID vaccinations among 60-6 - + @@ -36482,7 +35429,7 @@

COVID vaccinations among 60-6 - + @@ -36494,7 +35441,7 @@

COVID vaccinations among 60-6 - + @@ -36507,7 +35454,7 @@

COVID vaccinations among 60-6 - + @@ -36517,7 +35464,7 @@

COVID vaccinations among 60-6 - + @@ -36530,12 +35477,12 @@

COVID vaccinations among 60-6 - + - + @@ -36548,7 +35495,7 @@

COVID vaccinations among 60-6 - + @@ -36557,7 +35504,7 @@

COVID vaccinations among 60-6 - + @@ -36570,7 +35517,7 @@

COVID vaccinations among 60-6 - + @@ -36579,7 +35526,7 @@

COVID vaccinations among 60-6 - + @@ -36590,29 +35537,15 @@

COVID vaccinations among 60-6 - + - - - - + - - - - - - - - - - - @@ -36620,10 +35553,10 @@

COVID vaccinations among 60-6 - + - + @@ -36636,12 +35569,12 @@

COVID vaccinations among 60-6 - + - + @@ -36650,7 +35583,7 @@

COVID vaccinations among 60-6 - + @@ -36658,7 +35591,7 @@

COVID vaccinations among 60-6 - + @@ -36667,12 +35600,12 @@

COVID vaccinations among 60-6 - + - + @@ -36681,28 +35614,30 @@

COVID vaccinations among 60-6 - + - + - + + + - + @@ -36711,40 +35646,29 @@

COVID vaccinations among 60-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -36765,7 +35689,7 @@

COVID vaccinations among 60-6 - + @@ -36828,7 +35752,7 @@

COVID vaccinations among 60-6 - + @@ -36858,7 +35782,7 @@

COVID vaccinations among 60-6 - + @@ -36868,10 +35792,10 @@

COVID vaccinations among 60-6 - + - + @@ -36884,7 +35808,7 @@

COVID vaccinations among 60-6 - + @@ -36897,7 +35821,7 @@

COVID vaccinations among 60-6 - + @@ -36905,7 +35829,7 @@

COVID vaccinations among 60-6 - + @@ -36918,7 +35842,7 @@

COVID vaccinations among 60-6 - + @@ -36930,7 +35854,7 @@

COVID vaccinations among 60-6 - + @@ -36943,7 +35867,7 @@

COVID vaccinations among 60-6 - + @@ -36953,7 +35877,7 @@

COVID vaccinations among 60-6 - + @@ -36966,12 +35890,12 @@

COVID vaccinations among 60-6 - + - + @@ -36984,7 +35908,7 @@

COVID vaccinations among 60-6 - + @@ -36993,7 +35917,7 @@

COVID vaccinations among 60-6 - + @@ -37006,7 +35930,7 @@

COVID vaccinations among 60-6 - + @@ -37015,7 +35939,7 @@

COVID vaccinations among 60-6 - + @@ -37026,29 +35950,15 @@

COVID vaccinations among 60-6 - + - - - - + - - - - - - - - - - - @@ -37056,15 +35966,15 @@

COVID vaccinations among 60-6 - + - + - + @@ -37072,12 +35982,12 @@

COVID vaccinations among 60-6 - + - + @@ -37086,7 +35996,7 @@

COVID vaccinations among 60-6 - + @@ -37094,7 +36004,7 @@

COVID vaccinations among 60-6 - + @@ -37103,12 +36013,12 @@

COVID vaccinations among 60-6 - + - + @@ -37117,12 +36027,12 @@

COVID vaccinations among 60-6 - + - + @@ -37131,12 +36041,12 @@

COVID vaccinations among 60-6 - + - + @@ -37144,16 +36054,18 @@

COVID vaccinations among 60-6 - + + + - + @@ -37162,40 +36074,29 @@

COVID vaccinations among 60-6 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -37216,7 +36117,7 @@

COVID vaccinations among 60-6 - + @@ -37250,18 +36151,18 @@

COVID vaccinations among 60-6 - + - + - + @@ -37269,7 +36170,7 @@

COVID vaccinations among 60-6 - + @@ -37279,7 +36180,7 @@

COVID vaccinations among 60-6 - + @@ -37345,10 +36246,10 @@

COVID vaccinations among 55-5 - + - + @@ -37374,7 +36275,7 @@

COVID vaccinations among 55-5 - + @@ -37383,7 +36284,7 @@

COVID vaccinations among 55-5 - + @@ -37396,7 +36297,7 @@

COVID vaccinations among 55-5 - + @@ -37407,7 +36308,7 @@

COVID vaccinations among 55-5 - + @@ -37420,7 +36321,7 @@

COVID vaccinations among 55-5 - + @@ -37430,7 +36331,7 @@

COVID vaccinations among 55-5 - + @@ -37443,12 +36344,12 @@

COVID vaccinations among 55-5 - + - + @@ -37461,7 +36362,7 @@

COVID vaccinations among 55-5 - + @@ -37470,7 +36371,7 @@

COVID vaccinations among 55-5 - + @@ -37483,7 +36384,7 @@

COVID vaccinations among 55-5 - + @@ -37492,7 +36393,7 @@

COVID vaccinations among 55-5 - + @@ -37503,29 +36404,15 @@

COVID vaccinations among 55-5 - + - - - - + - - - - - - - - - - - @@ -37533,10 +36420,10 @@

COVID vaccinations among 55-5 - + - + @@ -37549,12 +36436,12 @@

COVID vaccinations among 55-5 - + - + @@ -37563,12 +36450,12 @@

COVID vaccinations among 55-5 - + - + @@ -37577,12 +36464,12 @@

COVID vaccinations among 55-5 - + - + @@ -37591,7 +36478,7 @@

COVID vaccinations among 55-5 - + @@ -37599,23 +36486,25 @@

COVID vaccinations among 55-5 - + - + + + - + @@ -37624,40 +36513,29 @@

COVID vaccinations among 55-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -37678,7 +36556,7 @@

COVID vaccinations among 55-5 - + @@ -37735,7 +36613,7 @@

COVID vaccinations among 55-5 - + @@ -37775,10 +36653,10 @@

COVID vaccinations among 55-5 - + - + @@ -37804,7 +36682,7 @@

COVID vaccinations among 55-5 - + @@ -37813,7 +36691,7 @@

COVID vaccinations among 55-5 - + @@ -37826,7 +36704,7 @@

COVID vaccinations among 55-5 - + @@ -37837,7 +36715,7 @@

COVID vaccinations among 55-5 - + @@ -37850,7 +36728,7 @@

COVID vaccinations among 55-5 - + @@ -37860,7 +36738,7 @@

COVID vaccinations among 55-5 - + @@ -37873,12 +36751,12 @@

COVID vaccinations among 55-5 - + - + @@ -37891,7 +36769,7 @@

COVID vaccinations among 55-5 - + @@ -37900,7 +36778,7 @@

COVID vaccinations among 55-5 - + @@ -37913,7 +36791,7 @@

COVID vaccinations among 55-5 - + @@ -37922,7 +36800,7 @@

COVID vaccinations among 55-5 - + @@ -37933,29 +36811,15 @@

COVID vaccinations among 55-5 - + - - - - + - - - - - - - - - - - @@ -37963,10 +36827,10 @@

COVID vaccinations among 55-5 - + - + @@ -37979,12 +36843,12 @@

COVID vaccinations among 55-5 - + - + @@ -37993,12 +36857,12 @@

COVID vaccinations among 55-5 - + - + @@ -38007,12 +36871,12 @@

COVID vaccinations among 55-5 - + - + @@ -38021,7 +36885,7 @@

COVID vaccinations among 55-5 - + @@ -38029,23 +36893,25 @@

COVID vaccinations among 55-5 - + - + + + - + @@ -38054,52 +36920,41 @@

COVID vaccinations among 55-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -38120,7 +36975,7 @@

COVID vaccinations among 55-5 - + @@ -38179,6 +37034,7 @@

COVID vaccinations among 55-5 + @@ -38269,7 +37125,7 @@

COVID vaccinations among 55-5 - + @@ -38291,7 +37147,7 @@

COVID vaccinations among 55-5
- +

COVID vaccinations among 55-5 - + - + - + - + @@ -38325,7 +37181,7 @@

COVID vaccinations among 55-5 - + @@ -38338,7 +37194,7 @@

COVID vaccinations among 55-5 - + @@ -38347,7 +37203,7 @@

COVID vaccinations among 55-5 - + @@ -38360,7 +37216,7 @@

COVID vaccinations among 55-5 - + @@ -38371,7 +37227,7 @@

COVID vaccinations among 55-5 - + @@ -38384,7 +37240,7 @@

COVID vaccinations among 55-5 - + @@ -38394,7 +37250,7 @@

COVID vaccinations among 55-5 - + @@ -38407,12 +37263,12 @@

COVID vaccinations among 55-5 - + - + @@ -38425,7 +37281,7 @@

COVID vaccinations among 55-5 - + @@ -38434,7 +37290,7 @@

COVID vaccinations among 55-5 - + @@ -38447,7 +37303,7 @@

COVID vaccinations among 55-5 - + @@ -38456,7 +37312,7 @@

COVID vaccinations among 55-5 - + @@ -38467,29 +37323,15 @@

COVID vaccinations among 55-5 - + - - - - + - - - - - - - - - - - @@ -38497,15 +37339,15 @@

COVID vaccinations among 55-5 - + - + - + @@ -38513,12 +37355,12 @@

COVID vaccinations among 55-5 - + - + @@ -38527,12 +37369,12 @@

COVID vaccinations among 55-5 - + - + @@ -38541,12 +37383,12 @@

COVID vaccinations among 55-5 - + - + @@ -38555,7 +37397,7 @@

COVID vaccinations among 55-5 - + @@ -38563,7 +37405,7 @@

COVID vaccinations among 55-5 - + @@ -38572,7 +37414,7 @@

COVID vaccinations among 55-5 - + @@ -38585,16 +37427,18 @@

COVID vaccinations among 55-5 - + + + - + @@ -38603,64 +37447,53 @@

COVID vaccinations among 55-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + - + - + - + - + @@ -38669,7 +37502,7 @@

COVID vaccinations among 55-5 - + @@ -38700,15 +37533,18 @@

COVID vaccinations among 55-5 - + - + - + + + + @@ -38727,17 +37563,17 @@

COVID vaccinations among 55-5 - + - + - + @@ -38745,22 +37581,22 @@

COVID vaccinations among 55-5 - + - + - + - + @@ -38768,7 +37604,7 @@

COVID vaccinations among 55-5 - + @@ -38788,7 +37624,7 @@

COVID vaccinations among 55-5 - + @@ -38798,7 +37634,7 @@

COVID vaccinations among 55-5 - + @@ -38812,8 +37648,8 @@

COVID vaccinations among 55-5 - - + + @@ -38834,7 +37670,7 @@

COVID vaccinations among 55-5
- +

COVID vaccinations among 55-5 - + - + - + - + @@ -38868,7 +37704,7 @@

COVID vaccinations among 55-5 - + @@ -38881,7 +37717,7 @@

COVID vaccinations among 55-5 - + @@ -38890,7 +37726,7 @@

COVID vaccinations among 55-5 - + @@ -38903,7 +37739,7 @@

COVID vaccinations among 55-5 - + @@ -38914,7 +37750,7 @@

COVID vaccinations among 55-5 - + @@ -38927,7 +37763,7 @@

COVID vaccinations among 55-5 - + @@ -38937,7 +37773,7 @@

COVID vaccinations among 55-5 - + @@ -38950,12 +37786,12 @@

COVID vaccinations among 55-5 - + - + @@ -38968,7 +37804,7 @@

COVID vaccinations among 55-5 - + @@ -38977,7 +37813,7 @@

COVID vaccinations among 55-5 - + @@ -38990,7 +37826,7 @@

COVID vaccinations among 55-5 - + @@ -38999,7 +37835,7 @@

COVID vaccinations among 55-5 - + @@ -39010,29 +37846,15 @@

COVID vaccinations among 55-5 - + - - - - + - - - - - - - - - - - @@ -39040,15 +37862,15 @@

COVID vaccinations among 55-5 - + - + - + @@ -39056,12 +37878,12 @@

COVID vaccinations among 55-5 - + - + @@ -39070,12 +37892,12 @@

COVID vaccinations among 55-5 - + - + @@ -39084,12 +37906,12 @@

COVID vaccinations among 55-5 - + - + @@ -39098,7 +37920,7 @@

COVID vaccinations among 55-5 - + @@ -39106,7 +37928,7 @@

COVID vaccinations among 55-5 - + @@ -39115,7 +37937,7 @@

COVID vaccinations among 55-5 - + @@ -39128,16 +37950,18 @@

COVID vaccinations among 55-5 - + + + - + @@ -39146,52 +37970,41 @@

COVID vaccinations among 55-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -39200,7 +38013,7 @@

COVID vaccinations among 55-5 - + @@ -39231,10 +38044,10 @@

COVID vaccinations among 55-5 - + - + @@ -39243,19 +38056,22 @@

COVID vaccinations among 55-5 - + - + - + + + + @@ -39270,8 +38086,8 @@

COVID vaccinations among 55-5 - - + + @@ -39310,10 +38126,10 @@

COVID vaccinations among 55-5 - + - + @@ -39339,7 +38155,7 @@

COVID vaccinations among 55-5 - + @@ -39348,7 +38164,7 @@

COVID vaccinations among 55-5 - + @@ -39361,7 +38177,7 @@

COVID vaccinations among 55-5 - + @@ -39372,7 +38188,7 @@

COVID vaccinations among 55-5 - + @@ -39385,7 +38201,7 @@

COVID vaccinations among 55-5 - + @@ -39395,7 +38211,7 @@

COVID vaccinations among 55-5 - + @@ -39408,12 +38224,12 @@

COVID vaccinations among 55-5 - + - + @@ -39426,7 +38242,7 @@

COVID vaccinations among 55-5 - + @@ -39435,7 +38251,7 @@

COVID vaccinations among 55-5 - + @@ -39448,7 +38264,7 @@

COVID vaccinations among 55-5 - + @@ -39457,7 +38273,7 @@

COVID vaccinations among 55-5 - + @@ -39468,29 +38284,15 @@

COVID vaccinations among 55-5 - + - - - - + - - - - - - - - - - - @@ -39498,10 +38300,10 @@

COVID vaccinations among 55-5 - + - + @@ -39514,12 +38316,12 @@

COVID vaccinations among 55-5 - + - + @@ -39528,12 +38330,12 @@

COVID vaccinations among 55-5 - + - + @@ -39542,12 +38344,12 @@

COVID vaccinations among 55-5 - + - + @@ -39556,7 +38358,7 @@

COVID vaccinations among 55-5 - + @@ -39564,23 +38366,25 @@

COVID vaccinations among 55-5 - + - + + + - + @@ -39589,40 +38393,29 @@

COVID vaccinations among 55-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -39643,7 +38436,7 @@

COVID vaccinations among 55-5 - + @@ -39706,7 +38499,7 @@

COVID vaccinations among 55-5 - + @@ -39746,10 +38539,10 @@

COVID vaccinations among 55-5 - + - + @@ -39762,7 +38555,7 @@

COVID vaccinations among 55-5 - + @@ -39775,7 +38568,7 @@

COVID vaccinations among 55-5 - + @@ -39784,7 +38577,7 @@

COVID vaccinations among 55-5 - + @@ -39797,7 +38590,7 @@

COVID vaccinations among 55-5 - + @@ -39808,7 +38601,7 @@

COVID vaccinations among 55-5 - + @@ -39821,7 +38614,7 @@

COVID vaccinations among 55-5 - + @@ -39831,7 +38624,7 @@

COVID vaccinations among 55-5 - + @@ -39844,12 +38637,12 @@

COVID vaccinations among 55-5 - + - + @@ -39862,7 +38655,7 @@

COVID vaccinations among 55-5 - + @@ -39871,7 +38664,7 @@

COVID vaccinations among 55-5 - + @@ -39884,7 +38677,7 @@

COVID vaccinations among 55-5 - + @@ -39893,7 +38686,7 @@

COVID vaccinations among 55-5 - + @@ -39904,29 +38697,15 @@

COVID vaccinations among 55-5 - + - - - - + - - - - - - - - - - - @@ -39934,10 +38713,10 @@

COVID vaccinations among 55-5 - + - + @@ -39950,12 +38729,12 @@

COVID vaccinations among 55-5 - + - + @@ -39964,12 +38743,12 @@

COVID vaccinations among 55-5 - + - + @@ -39978,12 +38757,12 @@

COVID vaccinations among 55-5 - + - + @@ -39992,7 +38771,7 @@

COVID vaccinations among 55-5 - + @@ -40000,23 +38779,25 @@

COVID vaccinations among 55-5 - + - + + + - + @@ -40025,40 +38806,29 @@

COVID vaccinations among 55-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -40079,7 +38849,7 @@

COVID vaccinations among 55-5 - + @@ -40113,18 +38883,18 @@

COVID vaccinations among 55-5 - + - + - + @@ -40132,7 +38902,7 @@

COVID vaccinations among 55-5 - + @@ -40142,7 +38912,7 @@

COVID vaccinations among 55-5 - + @@ -40182,10 +38952,10 @@

COVID vaccinations among 55-5 - + - + @@ -40211,7 +38981,7 @@

COVID vaccinations among 55-5 - + @@ -40220,7 +38990,7 @@

COVID vaccinations among 55-5 - + @@ -40233,7 +39003,7 @@

COVID vaccinations among 55-5 - + @@ -40244,7 +39014,7 @@

COVID vaccinations among 55-5 - + @@ -40257,7 +39027,7 @@

COVID vaccinations among 55-5 - + @@ -40267,7 +39037,7 @@

COVID vaccinations among 55-5 - + @@ -40280,12 +39050,12 @@

COVID vaccinations among 55-5 - + - + @@ -40298,7 +39068,7 @@

COVID vaccinations among 55-5 - + @@ -40307,7 +39077,7 @@

COVID vaccinations among 55-5 - + @@ -40320,7 +39090,7 @@

COVID vaccinations among 55-5 - + @@ -40329,7 +39099,7 @@

COVID vaccinations among 55-5 - + @@ -40340,29 +39110,15 @@

COVID vaccinations among 55-5 - + - - - - + - - - - - - - - - - - @@ -40370,10 +39126,10 @@

COVID vaccinations among 55-5 - + - + @@ -40386,12 +39142,12 @@

COVID vaccinations among 55-5 - + - + @@ -40400,12 +39156,12 @@

COVID vaccinations among 55-5 - + - + @@ -40414,12 +39170,12 @@

COVID vaccinations among 55-5 - + - + @@ -40428,7 +39184,7 @@

COVID vaccinations among 55-5 - + @@ -40436,23 +39192,25 @@

COVID vaccinations among 55-5 - + - + + + - + @@ -40461,40 +39219,29 @@

COVID vaccinations among 55-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -40515,7 +39262,7 @@

COVID vaccinations among 55-5 - + @@ -40578,7 +39325,7 @@

COVID vaccinations among 55-5 - + @@ -40600,7 +39347,7 @@

COVID vaccinations among 55-5
- +

COVID vaccinations among 55-5 - + - + - + - + @@ -40634,7 +39381,7 @@

COVID vaccinations among 55-5 - + @@ -40647,7 +39394,7 @@

COVID vaccinations among 55-5 - + @@ -40656,7 +39403,7 @@

COVID vaccinations among 55-5 - + @@ -40669,7 +39416,7 @@

COVID vaccinations among 55-5 - + @@ -40680,7 +39427,7 @@

COVID vaccinations among 55-5 - + @@ -40693,7 +39440,7 @@

COVID vaccinations among 55-5 - + @@ -40703,7 +39450,7 @@

COVID vaccinations among 55-5 - + @@ -40716,12 +39463,12 @@

COVID vaccinations among 55-5 - + - + @@ -40734,7 +39481,7 @@

COVID vaccinations among 55-5 - + @@ -40743,7 +39490,7 @@

COVID vaccinations among 55-5 - + @@ -40756,7 +39503,7 @@

COVID vaccinations among 55-5 - + @@ -40765,7 +39512,7 @@

COVID vaccinations among 55-5 - + @@ -40776,29 +39523,15 @@

COVID vaccinations among 55-5 - + - - - - + - - - - - - - - - - - @@ -40806,15 +39539,15 @@

COVID vaccinations among 55-5 - + - + - + @@ -40822,12 +39555,12 @@

COVID vaccinations among 55-5 - + - + @@ -40836,12 +39569,12 @@

COVID vaccinations among 55-5 - + - + @@ -40850,12 +39583,12 @@

COVID vaccinations among 55-5 - + - + @@ -40864,7 +39597,7 @@

COVID vaccinations among 55-5 - + @@ -40872,7 +39605,7 @@

COVID vaccinations among 55-5 - + @@ -40881,12 +39614,12 @@

COVID vaccinations among 55-5 - + - + @@ -40894,16 +39627,18 @@

COVID vaccinations among 55-5 - + + + - + @@ -40912,52 +39647,41 @@

COVID vaccinations among 55-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -40966,7 +39690,7 @@

COVID vaccinations among 55-5 - + @@ -40997,21 +39721,21 @@

COVID vaccinations among 55-5 - + - + - + - + @@ -41019,7 +39743,7 @@

COVID vaccinations among 55-5 - + @@ -41029,8 +39753,8 @@

COVID vaccinations among 55-5 - - + + @@ -41095,10 +39819,10 @@

COVID vaccinations among 50-5 - + - + @@ -41124,7 +39848,7 @@

COVID vaccinations among 50-5 - + @@ -41133,7 +39857,7 @@

COVID vaccinations among 50-5 - + @@ -41146,7 +39870,7 @@

COVID vaccinations among 50-5 - + @@ -41157,7 +39881,7 @@

COVID vaccinations among 50-5 - + @@ -41170,7 +39894,7 @@

COVID vaccinations among 50-5 - + @@ -41180,7 +39904,7 @@

COVID vaccinations among 50-5 - + @@ -41193,12 +39917,12 @@

COVID vaccinations among 50-5 - + - + @@ -41211,7 +39935,7 @@

COVID vaccinations among 50-5 - + @@ -41220,7 +39944,7 @@

COVID vaccinations among 50-5 - + @@ -41233,7 +39957,7 @@

COVID vaccinations among 50-5 - + @@ -41242,7 +39966,7 @@

COVID vaccinations among 50-5 - + @@ -41253,29 +39977,15 @@

COVID vaccinations among 50-5 - + - - - - + - - - - - - - - - - - @@ -41283,10 +39993,10 @@

COVID vaccinations among 50-5 - + - + @@ -41299,12 +40009,12 @@

COVID vaccinations among 50-5 - + - + @@ -41313,7 +40023,7 @@

COVID vaccinations among 50-5 - + @@ -41321,7 +40031,7 @@

COVID vaccinations among 50-5 - + @@ -41330,12 +40040,12 @@

COVID vaccinations among 50-5 - + - + @@ -41344,7 +40054,7 @@

COVID vaccinations among 50-5 - + @@ -41352,23 +40062,25 @@

COVID vaccinations among 50-5 - + - + + + - + @@ -41377,40 +40089,29 @@

COVID vaccinations among 50-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -41431,7 +40132,7 @@

COVID vaccinations among 50-5 - + @@ -41488,7 +40189,7 @@

COVID vaccinations among 50-5 - + @@ -41528,10 +40229,10 @@

COVID vaccinations among 50-5 - + - + @@ -41557,7 +40258,7 @@

COVID vaccinations among 50-5 - + @@ -41566,7 +40267,7 @@

COVID vaccinations among 50-5 - + @@ -41579,7 +40280,7 @@

COVID vaccinations among 50-5 - + @@ -41590,7 +40291,7 @@

COVID vaccinations among 50-5 - + @@ -41603,7 +40304,7 @@

COVID vaccinations among 50-5 - + @@ -41613,7 +40314,7 @@

COVID vaccinations among 50-5 - + @@ -41626,12 +40327,12 @@

COVID vaccinations among 50-5 - + - + @@ -41644,7 +40345,7 @@

COVID vaccinations among 50-5 - + @@ -41653,7 +40354,7 @@

COVID vaccinations among 50-5 - + @@ -41666,7 +40367,7 @@

COVID vaccinations among 50-5 - + @@ -41675,7 +40376,7 @@

COVID vaccinations among 50-5 - + @@ -41686,29 +40387,15 @@

COVID vaccinations among 50-5 - + - - - - + - - - - - - - - - - - @@ -41716,10 +40403,10 @@

COVID vaccinations among 50-5 - + - + @@ -41732,12 +40419,12 @@

COVID vaccinations among 50-5 - + - + @@ -41746,7 +40433,7 @@

COVID vaccinations among 50-5 - + @@ -41754,7 +40441,7 @@

COVID vaccinations among 50-5 - + @@ -41763,12 +40450,12 @@

COVID vaccinations among 50-5 - + - + @@ -41777,7 +40464,7 @@

COVID vaccinations among 50-5 - + @@ -41785,23 +40472,25 @@

COVID vaccinations among 50-5 - + - + + + - + @@ -41810,52 +40499,41 @@

COVID vaccinations among 50-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -41876,7 +40554,7 @@

COVID vaccinations among 50-5 - + @@ -41935,6 +40613,7 @@

COVID vaccinations among 50-5 + @@ -42025,7 +40704,7 @@

COVID vaccinations among 50-5 - + @@ -42065,10 +40744,10 @@

COVID vaccinations among 50-5 - + - + @@ -42094,7 +40773,7 @@

COVID vaccinations among 50-5 - + @@ -42103,7 +40782,7 @@

COVID vaccinations among 50-5 - + @@ -42116,7 +40795,7 @@

COVID vaccinations among 50-5 - + @@ -42127,7 +40806,7 @@

COVID vaccinations among 50-5 - + @@ -42140,7 +40819,7 @@

COVID vaccinations among 50-5 - + @@ -42150,7 +40829,7 @@

COVID vaccinations among 50-5 - + @@ -42163,12 +40842,12 @@

COVID vaccinations among 50-5 - + - + @@ -42181,7 +40860,7 @@

COVID vaccinations among 50-5 - + @@ -42190,7 +40869,7 @@

COVID vaccinations among 50-5 - + @@ -42203,7 +40882,7 @@

COVID vaccinations among 50-5 - + @@ -42212,7 +40891,7 @@

COVID vaccinations among 50-5 - + @@ -42223,29 +40902,15 @@

COVID vaccinations among 50-5 - + - - - - + - - - - - - - - - - - @@ -42253,10 +40918,10 @@

COVID vaccinations among 50-5 - + - + @@ -42269,12 +40934,12 @@

COVID vaccinations among 50-5 - + - + @@ -42283,7 +40948,7 @@

COVID vaccinations among 50-5 - + @@ -42291,7 +40956,7 @@

COVID vaccinations among 50-5 - + @@ -42300,12 +40965,12 @@

COVID vaccinations among 50-5 - + - + @@ -42314,7 +40979,7 @@

COVID vaccinations among 50-5 - + @@ -42322,23 +40987,25 @@

COVID vaccinations among 50-5 - + - + + + - + @@ -42347,52 +41014,41 @@

COVID vaccinations among 50-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + - + - + - + - + @@ -42413,7 +41069,7 @@

COVID vaccinations among 50-5 - + @@ -42452,6 +41108,9 @@

COVID vaccinations among 50-5 + + + @@ -42556,7 +41215,7 @@

COVID vaccinations among 50-5 - + @@ -42596,10 +41255,10 @@

COVID vaccinations among 50-5 - + - + @@ -42612,7 +41271,7 @@

COVID vaccinations among 50-5 - + @@ -42625,7 +41284,7 @@

COVID vaccinations among 50-5 - + @@ -42634,7 +41293,7 @@

COVID vaccinations among 50-5 - + @@ -42647,7 +41306,7 @@

COVID vaccinations among 50-5 - + @@ -42658,7 +41317,7 @@

COVID vaccinations among 50-5 - + @@ -42671,7 +41330,7 @@

COVID vaccinations among 50-5 - + @@ -42681,7 +41340,7 @@

COVID vaccinations among 50-5 - + @@ -42694,12 +41353,12 @@

COVID vaccinations among 50-5 - + - + @@ -42712,7 +41371,7 @@

COVID vaccinations among 50-5 - + @@ -42721,7 +41380,7 @@

COVID vaccinations among 50-5 - + @@ -42734,7 +41393,7 @@

COVID vaccinations among 50-5 - + @@ -42743,7 +41402,7 @@

COVID vaccinations among 50-5 - + @@ -42754,29 +41413,15 @@

COVID vaccinations among 50-5 - + - - - - + - - - - - - - - - - - @@ -42784,10 +41429,10 @@

COVID vaccinations among 50-5 - + - + @@ -42800,12 +41445,12 @@

COVID vaccinations among 50-5 - + - + @@ -42814,7 +41459,7 @@

COVID vaccinations among 50-5 - + @@ -42822,7 +41467,7 @@

COVID vaccinations among 50-5 - + @@ -42831,12 +41476,12 @@

COVID vaccinations among 50-5 - + - + @@ -42845,7 +41490,7 @@

COVID vaccinations among 50-5 - + @@ -42853,23 +41498,25 @@

COVID vaccinations among 50-5 - + - + + + - + @@ -42878,40 +41525,29 @@

COVID vaccinations among 50-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -42932,7 +41568,7 @@

COVID vaccinations among 50-5 - + @@ -42966,7 +41602,7 @@

COVID vaccinations among 50-5 - + @@ -42975,19 +41611,22 @@

COVID vaccinations among 50-5 - + - + - + + + + @@ -43002,7 +41641,7 @@

COVID vaccinations among 50-5 - + @@ -43042,10 +41681,10 @@

COVID vaccinations among 50-5 - + - + @@ -43058,7 +41697,7 @@

COVID vaccinations among 50-5 - + @@ -43071,7 +41710,7 @@

COVID vaccinations among 50-5 - + @@ -43080,7 +41719,7 @@

COVID vaccinations among 50-5 - + @@ -43093,7 +41732,7 @@

COVID vaccinations among 50-5 - + @@ -43104,7 +41743,7 @@

COVID vaccinations among 50-5 - + @@ -43117,7 +41756,7 @@

COVID vaccinations among 50-5 - + @@ -43127,7 +41766,7 @@

COVID vaccinations among 50-5 - + @@ -43140,12 +41779,12 @@

COVID vaccinations among 50-5 - + - + @@ -43158,7 +41797,7 @@

COVID vaccinations among 50-5 - + @@ -43167,7 +41806,7 @@

COVID vaccinations among 50-5 - + @@ -43180,7 +41819,7 @@

COVID vaccinations among 50-5 - + @@ -43189,7 +41828,7 @@

COVID vaccinations among 50-5 - + @@ -43200,29 +41839,15 @@

COVID vaccinations among 50-5 - + - - - - + - - - - - - - - - - - @@ -43230,10 +41855,10 @@

COVID vaccinations among 50-5 - + - + @@ -43246,12 +41871,12 @@

COVID vaccinations among 50-5 - + - + @@ -43260,7 +41885,7 @@

COVID vaccinations among 50-5 - + @@ -43268,7 +41893,7 @@

COVID vaccinations among 50-5 - + @@ -43277,12 +41902,12 @@

COVID vaccinations among 50-5 - + - + @@ -43291,7 +41916,7 @@

COVID vaccinations among 50-5 - + @@ -43299,23 +41924,25 @@

COVID vaccinations among 50-5 - + - + + + - + @@ -43324,40 +41951,29 @@

COVID vaccinations among 50-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -43378,7 +41994,7 @@

COVID vaccinations among 50-5 - + @@ -43412,18 +42028,18 @@

COVID vaccinations among 50-5 - + - + - + @@ -43431,7 +42047,7 @@

COVID vaccinations among 50-5 - + @@ -43441,7 +42057,7 @@

COVID vaccinations among 50-5 - + @@ -43481,10 +42097,10 @@

COVID vaccinations among 50-5 - + - + @@ -43510,7 +42126,7 @@

COVID vaccinations among 50-5 - + @@ -43519,7 +42135,7 @@

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COVID vaccinations among 50-5 - + @@ -43566,7 +42182,7 @@

COVID vaccinations among 50-5 - + @@ -43579,12 +42195,12 @@

COVID vaccinations among 50-5 - + - + @@ -43597,7 +42213,7 @@

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COVID vaccinations among 50-5 - + @@ -43628,7 +42244,7 @@

COVID vaccinations among 50-5 - + @@ -43639,29 +42255,15 @@

COVID vaccinations among 50-5 - + - - - - + - - - - - - - - - - - @@ -43669,10 +42271,10 @@

COVID vaccinations among 50-5 - + - + @@ -43685,12 +42287,12 @@

COVID vaccinations among 50-5 - + - + @@ -43699,7 +42301,7 @@

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COVID vaccinations among 50-5 - + - + @@ -43730,7 +42332,7 @@

COVID vaccinations among 50-5 - + @@ -43738,23 +42340,25 @@

COVID vaccinations among 50-5 - + - + + + - + @@ -43763,40 +42367,29 @@

COVID vaccinations among 50-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -43817,7 +42410,7 @@

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COVID vaccinations among 50-5 - + - + @@ -43949,7 +42542,7 @@

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COVID vaccinations among 50-5 - + @@ -44058,7 +42651,7 @@

COVID vaccinations among 50-5 - + @@ -44067,7 +42660,7 @@

COVID vaccinations among 50-5 - + @@ -44078,29 +42671,15 @@

COVID vaccinations among 50-5 - + - - - - + - - - - - - - - - - - @@ -44108,10 +42687,10 @@

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COVID vaccinations among 50-5 - + @@ -44177,23 +42756,25 @@

COVID vaccinations among 50-5 - + - + + + - + @@ -44202,40 +42783,29 @@

COVID vaccinations among 50-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -44256,7 +42826,7 @@

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COVID vaccinations among 50-5 - + - + @@ -44375,7 +42945,7 @@

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COVID vaccinations among 50-5 - + - + @@ -44475,7 +43045,7 @@

COVID vaccinations among 50-5 - + @@ -44484,7 +43054,7 @@

COVID vaccinations among 50-5 - + @@ -44497,7 +43067,7 @@

COVID vaccinations among 50-5 - + @@ -44506,7 +43076,7 @@

COVID vaccinations among 50-5 - + @@ -44517,29 +43087,15 @@

COVID vaccinations among 50-5 - + - - - - + - - - - - - - - - - - @@ -44547,10 +43103,10 @@

COVID vaccinations among 50-5 - + - + @@ -44563,12 +43119,12 @@

COVID vaccinations among 50-5 - + - + @@ -44577,7 +43133,7 @@

COVID vaccinations among 50-5 - + @@ -44585,7 +43141,7 @@

COVID vaccinations among 50-5 - + @@ -44594,12 +43150,12 @@

COVID vaccinations among 50-5 - + - + @@ -44608,7 +43164,7 @@

COVID vaccinations among 50-5 - + @@ -44616,23 +43172,25 @@

COVID vaccinations among 50-5 - + - + + + - + @@ -44641,40 +43199,29 @@

COVID vaccinations among 50-5 - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - + - + - + @@ -44695,7 +43242,7 @@

COVID vaccinations among 50-5 - + @@ -44729,18 +43276,18 @@

COVID vaccinations among 50-5 - + - + - + @@ -44748,7 +43295,7 @@

COVID vaccinations among 50-5 - + @@ -44758,7 +43305,7 @@

COVID vaccinations among 50-5 - + @@ -44816,8 +43363,8 @@

- Vaccinated at 07 Apr (n) - Vaccinated at 07 Apr (%) + Vaccinated at 14 Apr (n) + Vaccinated at 14 Apr (%) Total eligible Previous week's vaccination coverage (%) Vaccinated over last 7d (%) @@ -44836,214 +43383,214 @@

Sex F - 623224 - 95.6 - 651700 - 95.5 + 623112 + 95.8 + 650377 + 95.7 0.1 M - 452774 - 95.8 - 472514 - 95.7 + 452459 + 96.0 + 471317 + 95.9 0.1 Age band 80-84 - 565845 + 566041 + 96.2 + 588637 96.0 - 589470 - 95.9 - 0.1 + 0.2 85-89 - 336497 - 95.8 - 351155 - 95.7 + 336294 + 96.0 + 350294 + 95.9 0.1 90+ - 173656 + 173236 + 94.8 + 182763 94.6 - 183589 - 94.4 0.2 Ethnicity (broad categories) Black - 8232 - 74.2 - 11088 - 73.9 - 0.3 + 8267 + 74.7 + 11067 + 74.3 + 0.4 Mixed - 2688 - 82.4 + 2702 + 82.8 3262 - 82.2 + 82.6 0.2 Other - 5579 - 82.2 - 6783 - 82.0 + 5593 + 82.6 + 6769 + 82.4 0.2 South Asian - 24563 - 86.1 - 28525 - 85.9 - 0.2 + 24619 + 86.5 + 28455 + 86.2 + 0.3 Unknown - 54600 - 86.3 - 63280 - 86.2 + 54320 + 86.5 + 62776 + 86.4 0.1 White - 980336 - 96.9 - 1011276 - 96.8 + 980070 + 97.1 + 1009365 + 97.0 0.1 ethnicity 16 groups African - 1365 - 65.0 - 2100 - 64.7 - 0.3 + 1372 + 65.6 + 2093 + 65.2 + 0.4 Bangladeshi or British Bangladeshi - 1064 - 80.9 + 1071 + 81.4 1316 - 80.3 - 0.6 + 80.9 + 0.5 Caribbean - 5901 - 77.1 - 7651 - 76.8 + 5929 + 77.6 + 7637 + 77.3 0.3 Chinese 1351 - 79.1 - 1708 - 79.1 - 0.0 + 79.8 + 1694 + 79.3 + 0.5 Other - 4228 - 83.3 - 5075 - 83.0 - 0.3 + 4249 + 83.6 + 5082 + 83.5 + 0.1 Other Asian - 3654 - 82.9 - 4410 - 82.7 - 0.2 + 3661 + 83.1 + 4403 + 83.0 + 0.1 British or Mixed British - 931336 + 931063 + 97.4 + 956277 97.2 - 958062 - 97.1 - 0.1 + 0.2 Indian or British Indian - 13657 - 90.9 - 15022 - 90.7 + 13671 + 91.2 + 14994 + 91.0 0.2 Irish - 9198 - 94.6 - 9723 - 94.5 + 9191 + 94.9 + 9681 + 94.8 0.1 Other Black 966 - 71.9 - 1344 - 71.4 - 0.5 + 72.3 + 1337 + 71.7 + 0.6 Other White - 39802 - 91.5 - 43498 - 91.3 - 0.2 + 39816 + 91.7 + 43421 + 91.6 + 0.1 Other mixed - 1001 + 994 86.1 - 1162 - 85.5 - 0.6 + 1155 + 86.1 + 0.0 Pakistani or British Pakistani - 6188 - 79.6 - 7770 - 79.3 - 0.3 + 6216 + 80.2 + 7749 + 79.8 + 0.4 Unknown - 54593 - 86.3 - 63273 - 86.2 + 54306 + 86.5 + 62755 + 86.4 0.1 @@ -45059,8 +43606,8 @@

Index of Multiple Deprivation (quintiles) 1 Most deprived - 134764 - 92.4 - 145845 - 92.2 + 134855 + 92.7 + 145411 + 92.5 0.2 2 - 178024 - 94.5 - 188342 - 94.3 - 0.2 + 177975 + 94.7 + 187866 + 94.6 + 0.1 3 - 240835 - 96.0 - 250740 - 95.9 + 240646 + 96.2 + 250138 + 96.1 0.1 4 - 250390 + 250236 + 96.7 + 258650 96.6 - 259175 - 96.5 0.1 5 Least deprived - 252987 - 97.2 - 260155 - 97.1 + 252840 + 97.4 + 259658 + 97.3 0.1 Unknown - 18991 - 95.1 + 19019 + 95.3 19964 - 95.0 - 0.1 + 95.1 + 0.2 BMI 30+ - 189588 - 96.9 - 195615 - 96.8 + 189469 + 97.1 + 195125 + 97.0 0.1 under 30 - 886403 + 886109 + 95.6 + 926569 95.5 - 928599 - 95.3 - 0.2 + 0.1 Chronic cardiac disease no - 750337 - 95.2 - 787899 - 95.1 + 749889 + 95.4 + 785918 + 95.3 0.1 yes - 325661 - 96.8 - 336315 - 96.7 + 325689 + 97.0 + 335783 + 96.9 0.1 Current COPD no - 962150 + 961807 + 95.8 + 1004395 95.6 - 1006642 - 95.5 - 0.1 + 0.2 yes - 113848 - 96.8 - 117572 - 96.7 + 113771 + 97.0 + 117299 + 96.9 0.1 Dialysis no - 1074003 - 95.7 - 1122142 - 95.6 + 1073576 + 95.9 + 1119629 + 95.8 0.1 @@ -45184,67 +43731,67 @@

DMARDs no - 1042167 + 1041754 + 95.8 + 1087072 95.7 - 1089529 - 95.5 - 0.2 + 0.1 yes - 33831 + 33817 + 97.7 + 34622 97.6 - 34678 - 97.4 - 0.2 + 0.1 Dementia no - 985971 - 95.7 - 1030113 - 95.6 + 985425 + 95.9 + 1027719 + 95.8 0.1 yes - 90020 + 90153 + 95.9 + 93982 95.7 - 94101 - 95.5 0.2 Psychosis, schizophrenia, or bipolar no - 1067983 - 95.7 - 1115513 - 95.6 + 1067563 + 95.9 + 1113021 + 95.8 0.1 yes 8008 - 92.0 - 8701 - 91.9 - 0.1 + 92.3 + 8673 + 92.1 + 0.2 Learning disability no - 1075487 - 95.7 - 1123668 - 95.6 + 1075060 + 95.9 + 1121148 + 95.8 0.1 @@ -45258,86 +43805,86 @@

SSRI (last 12 months) no - 1008854 + 1008371 + 95.8 + 1052863 95.6 - 1055313 - 95.5 - 0.1 + 0.2 yes - 67137 - 97.4 - 68901 - 97.3 + 67200 + 97.6 + 68831 + 97.5 0.1 Chemo or radiotherapy no - 1039178 + 1038772 + 95.8 + 1083943 95.7 - 1086379 - 95.5 - 0.2 + 0.1 yes - 36813 - 97.3 - 37835 - 97.2 + 36806 + 97.5 + 37751 + 97.4 0.1 Cancer (lung) no - 1068655 - 95.7 - 1116605 - 95.6 + 1068256 + 95.9 + 1114134 + 95.8 0.1 yes - 7343 - 96.5 - 7609 - 96.3 + 7322 + 96.9 + 7560 + 96.7 0.2 Cancer (excluding lung/haem) no - 880313 + 879921 + 95.6 + 920857 95.4 - 923041 - 95.2 0.2 yes - 195678 + 195657 + 97.4 + 200837 97.3 - 201166 - 97.2 0.1 Cancer (haematological) no - 1055950 + 1055523 + 95.9 + 1101107 95.7 - 1103592 - 95.6 - 0.1 + 0.2 yes - 20048 - 97.2 - 20622 - 97.1 + 20055 + 97.4 + 20587 + 97.3 0.1 @@ -45417,8 +43964,8 @@

- Vaccinated at 07 Apr (n) - Vaccinated at 07 Apr (%) + Vaccinated at 14 Apr (n) + Vaccinated at 14 Apr (%) Total eligible Previous week's vaccination coverage (%) Vaccinated over last 7d (%) @@ -45437,501 +43984,501 @@

Sex F - 1031163 + 1032514 + 95.4 + 1082774 95.2 - 1083320 - 95.1 - 0.1 + 0.2 M - 932323 - 94.8 - 982996 - 94.8 - 0.0 + 933492 + 95.0 + 982163 + 94.9 + 0.1 Age band 70-74 - 1134938 + 1136296 + 94.8 + 1199163 94.6 - 1199786 - 94.5 - 0.1 + 0.2 75-79 - 828548 - 95.6 - 866530 - 95.5 + 829710 + 95.8 + 865781 + 95.7 0.1 Ethnicity (broad categories) Black - 10444 - 71.0 - 14700 - 70.8 - 0.2 + 10500 + 71.5 + 14686 + 71.1 + 0.4 Mixed - 5250 - 81.5 - 6440 - 81.3 + 5264 + 81.8 + 6433 + 81.6 0.2 Other - 12159 - 79.3 - 15337 - 79.1 - 0.2 + 12229 + 79.7 + 15344 + 79.4 + 0.3 South Asian - 47383 - 86.2 - 54950 - 85.9 + 47572 + 86.6 + 54936 + 86.3 0.3 Unknown - 127932 - 88.1 - 145257 - 88.0 + 127757 + 88.3 + 144655 + 88.2 0.1 White - 1760318 - 96.2 - 1829632 - 96.1 + 1762677 + 96.4 + 1828883 + 96.3 0.1 ethnicity 16 groups African - 3430 - 65.2 + 3458 + 65.8 5257 - 64.8 - 0.4 + 65.2 + 0.6 Bangladeshi or British Bangladeshi 1540 - 85.3 - 1806 84.9 - 0.4 + 1813 + 84.6 + 0.3 Caribbean - 5201 - 74.7 + 5229 + 75.2 6958 - 74.4 - 0.3 + 74.7 + 0.5 Chinese - 3185 - 78.4 + 3199 + 78.8 4060 - 78.3 - 0.1 + 78.4 + 0.4 Other - 8974 - 79.6 - 11277 - 79.3 + 9037 + 80.0 + 11298 + 79.7 0.3 Other Asian - 9303 - 83.2 - 11179 - 83.0 + 9345 + 83.6 + 11172 + 83.4 0.2 British or Mixed British - 1673756 + 1675926 + 96.8 + 1730701 96.7 - 1731366 - 96.6 0.1 Indian or British Indian - 27321 - 90.1 - 30324 - 89.9 + 27391 + 90.4 + 30303 + 90.2 0.2 Irish - 14133 - 93.1 - 15176 - 93.0 + 14147 + 93.3 + 15162 + 93.2 0.1 Other Black - 1813 - 73.2 + 1820 + 73.4 2478 - 72.9 - 0.3 + 73.2 + 0.2 Other White - 72422 + 72583 + 87.4 + 83006 87.2 - 83097 - 87.0 0.2 Other mixed - 2086 - 82.8 - 2520 - 82.8 - 0.0 + 2100 + 83.6 + 2513 + 83.3 + 0.3 Pakistani or British Pakistani - 9226 - 79.2 - 11648 - 78.7 + 9289 + 79.8 + 11634 + 79.3 0.5 Unknown - 127918 - 88.1 - 145243 - 88.0 + 127771 + 88.3 + 144669 + 88.2 0.1 White + Asian - 1190 - 87.2 + 1197 + 87.7 1365 87.2 - 0.0 + 0.5 White + Black African 812 75.8 1071 - 75.2 - 0.6 + 75.8 + 0.0 White + Black Caribbean - 1162 - 77.9 - 1491 - 77.9 - 0.0 + 1169 + 78.8 + 1484 + 78.3 + 0.5 Index of Multiple Deprivation (quintiles) 1 Most deprived - 251069 + 251496 + 92.2 + 272657 92.0 - 272972 - 91.8 0.2 2 - 329217 - 93.8 - 350917 - 93.7 - 0.1 + 329805 + 94.1 + 350637 + 93.9 + 0.2 3 - 438158 + 438606 + 95.4 + 459522 95.3 - 459844 - 95.2 0.1 4 - 456029 + 456519 + 96.0 + 475335 95.9 - 475573 - 95.8 0.1 5 Least deprived - 452984 - 96.6 - 468713 - 96.6 - 0.0 + 453446 + 96.8 + 468468 + 96.7 + 0.1 Unknown - 36036 + 36134 + 94.3 + 38325 94.1 - 38290 - 93.9 0.2 BMI 30+ - 492856 - 96.4 - 511021 - 96.4 - 0.0 + 493458 + 96.6 + 510713 + 96.5 + 0.1 under 30 - 1470630 + 1472541 + 94.7 + 1554224 94.6 - 1555295 - 94.5 0.1 Chronic cardiac disease no - 1607116 + 1608831 + 95.0 + 1694392 94.8 - 1695855 - 94.7 - 0.1 + 0.2 yes - 356370 - 96.2 - 370461 - 96.1 + 357168 + 96.4 + 370552 + 96.3 0.1 Current COPD no - 1774444 + 1776649 + 95.1 + 1868650 94.9 - 1869952 - 94.8 - 0.1 + 0.2 yes - 189042 + 189350 + 96.5 + 196294 96.3 - 196364 - 96.2 - 0.1 + 0.2 Dialysis no - 1959573 - 95.0 - 2062235 - 94.9 + 1962086 + 95.2 + 2060863 + 95.1 0.1 yes - 3906 - 95.7 + 3913 + 95.9 4081 - 95.5 + 95.7 0.2 DMARDs no - 1893465 - 94.9 - 1994244 - 94.9 - 0.0 + 1895845 + 95.1 + 1992865 + 95.0 + 0.1 yes - 70021 + 70161 + 97.3 + 72079 97.2 - 72072 - 97.0 - 0.2 + 0.1 Dementia no - 1921906 - 95.0 - 2022706 - 94.9 + 1924237 + 95.2 + 2021278 + 95.1 0.1 yes - 41580 - 95.3 - 43610 - 95.2 - 0.1 + 41762 + 95.6 + 43666 + 95.4 + 0.2 Psychosis, schizophrenia, or bipolar no - 1944957 + 1947421 + 95.3 + 2044434 95.1 - 2045792 - 95.0 - 0.1 + 0.2 yes - 18522 - 90.2 - 20524 - 90.1 - 0.1 + 18578 + 90.6 + 20503 + 90.4 + 0.2 Learning disability no - 1960672 - 95.0 - 2063271 - 94.9 + 1963178 + 95.2 + 2061899 + 95.1 0.1 yes - 2807 - 92.2 + 2821 + 92.6 3045 92.2 - 0.0 + 0.4 SSRI (last 12 months) no - 1813336 + 1815478 + 95.0 + 1910125 94.9 - 1911581 - 94.8 0.1 yes - 150150 - 97.0 - 154735 - 96.9 + 150528 + 97.2 + 154812 + 97.1 0.1 Chemo or radiotherapy no - 1896216 + 1898631 + 95.1 + 1995574 95.0 - 1996946 - 94.9 0.1 yes - 67263 + 67368 + 97.1 + 69363 97.0 - 69370 - 96.9 0.1 Cancer (lung) no - 1951313 - 95.0 - 2053639 - 94.9 + 1953791 + 95.2 + 2052274 + 95.1 0.1 yes - 12173 - 96.0 - 12677 - 95.9 - 0.1 + 12208 + 96.4 + 12663 + 96.2 + 0.2 Cancer (excluding lung/haem) no - 1686391 - 94.7 - 1780261 - 94.6 + 1688218 + 94.9 + 1778707 + 94.8 0.1 yes - 277095 + 277788 + 97.1 + 286230 96.9 - 286055 - 96.8 - 0.1 + 0.2 Cancer (haematological) no - 1934100 - 95.0 - 2035922 - 94.9 + 1936529 + 95.2 + 2034515 + 95.1 0.1 yes - 29386 + 29477 + 96.9 + 30422 96.7 - 30394 - 96.6 - 0.1 + 0.2 @@ -46010,8 +44557,8 @@

- Vaccinated at 07 Apr (n) - Vaccinated at 07 Apr (%) + Vaccinated at 14 Apr (n) + Vaccinated at 14 Apr (%) Total eligible Previous week's vaccination coverage (%) Vaccinated over last 7d (%) @@ -46030,143 +44577,143 @@

Sex F - 56966 + 57302 + 96.3 + 59500 95.9 - 59402 - 95.7 - 0.2 + 0.4 M - 23051 + 23212 + 95.2 + 24381 94.8 - 24325 - 94.5 - 0.3 + 0.4 Age band 65-69 - 4347 - 91.9 - 4732 - 91.4 + 4389 + 92.3 + 4753 + 91.8 0.5 70-74 - 6706 + 6769 + 94.0 + 7203 93.4 - 7182 - 93.1 - 0.3 + 0.6 75-79 - 9289 + 9394 + 95.4 + 9849 94.9 - 9793 - 94.6 - 0.3 + 0.5 80-84 - 13944 + 14049 + 96.2 + 14609 95.8 - 14553 - 95.6 - 0.2 + 0.4 85-89 - 18732 + 18865 + 96.6 + 19523 96.3 - 19453 - 96.1 - 0.2 + 0.3 90+ - 26999 + 27048 + 96.8 + 27951 96.4 - 28021 - 96.2 - 0.2 + 0.4 Ethnicity (broad categories) Black - 392 - 86.2 - 455 - 86.2 - 0.0 + 399 + 86.4 + 462 + 84.8 + 1.6 Mixed - 210 - 90.9 - 231 - 90.9 + 203 + 90.6 + 224 + 90.6 0.0 Other 343 - 92.5 - 371 - 92.5 + 94.2 + 364 + 94.2 0.0 South Asian 623 - 92.7 - 672 - 92.7 + 91.8 + 679 + 91.8 0.0 Unknown - 2030 + 2037 93.9 - 2163 - 93.5 - 0.4 + 2170 + 93.2 + 0.7 White - 76419 - 95.7 - 79835 - 95.5 - 0.2 + 76909 + 96.1 + 79996 + 95.8 + 0.3 Dementia no - 36197 + 36421 + 94.9 + 38395 94.4 - 38332 - 94.2 - 0.2 + 0.5 yes - 43827 - 96.5 - 45395 - 96.4 - 0.1 + 44093 + 96.9 + 45486 + 96.6 + 0.3 @@ -46233,8 +44780,8 @@

- Vaccinated at 07 Apr (n) - Vaccinated at 07 Apr (%) + Vaccinated at 14 Apr (n) + Vaccinated at 14 Apr (%) Total eligible Previous week's vaccination coverage (%) Vaccinated over last 7d (%) @@ -46253,200 +44800,200 @@

newly shielded since feb 15 no - 453194 - 90.2 - 502355 - 90.0 + 454153 + 90.5 + 501942 + 90.3 0.2 yes - 258573 + 261604 + 81.0 + 322952 80.4 - 321594 - 79.7 - 0.7 + 0.6 Sex F - 395619 - 85.5 - 462448 - 85.1 - 0.4 + 397880 + 85.9 + 462980 + 85.6 + 0.3 M - 316141 + 317870 + 87.8 + 361900 87.5 - 361494 - 87.1 - 0.4 + 0.3 Age band 16-29 - 51429 + 51695 + 74.9 + 68978 74.7 - 68831 - 74.1 - 0.6 + 0.2 30-39 - 97153 + 97951 + 77.4 + 126553 76.9 - 126392 - 76.3 - 0.6 + 0.5 40-49 - 139454 - 84.4 - 165151 - 83.9 + 140483 + 85.0 + 165340 + 84.5 0.5 50-59 - 203455 - 89.6 - 227052 - 89.3 + 204575 + 90.0 + 227360 + 89.7 0.3 60-69 - 220269 - 93.1 - 236509 - 92.9 + 221039 + 93.4 + 236642 + 93.2 0.2 Ethnicity (broad categories) Black - 29533 - 66.4 - 44485 - 65.5 - 0.9 + 29890 + 67.2 + 44478 + 66.5 + 0.7 Mixed - 10388 + 10479 + 73.5 + 14266 72.9 - 14252 - 72.2 - 0.7 + 0.6 Other - 13237 + 13370 + 73.7 + 18151 73.0 - 18123 - 72.4 - 0.6 + 0.7 South Asian - 85456 - 78.9 - 108255 - 78.1 - 0.8 + 86317 + 79.7 + 108248 + 79.0 + 0.7 Unknown - 27349 + 27412 + 84.8 + 32340 84.4 - 32389 - 84.0 0.4 White - 545797 + 548268 + 90.3 + 607390 90.0 - 606431 - 89.7 0.3 Index of Multiple Deprivation (quintiles) 1 Most deprived - 198065 + 199367 + 81.8 + 243726 81.3 - 243761 - 80.7 - 0.6 + 0.5 2 - 158872 + 159831 + 85.6 + 186697 85.2 - 186487 - 84.8 0.4 3 - 138082 + 138880 + 88.7 + 156548 88.4 - 156240 - 88.1 0.3 4 - 111195 + 111664 + 91.0 + 122675 90.8 - 122486 - 90.5 - 0.3 + 0.2 5 Least deprived - 88480 - 93.0 - 95158 - 92.8 + 88830 + 93.1 + 95375 + 92.9 0.2 Unknown - 17073 - 86.2 - 19796 - 85.7 - 0.5 + 17185 + 86.6 + 19845 + 86.3 + 0.3 Learning disability no - 687701 + 691523 + 86.7 + 798035 86.3 - 797146 - 85.9 0.4 yes - 24059 - 89.8 - 26796 - 89.4 + 24227 + 90.3 + 26838 + 89.9 0.4 @@ -46514,8 +45061,8 @@

- Vaccinated at 07 Apr (n) - Vaccinated at 07 Apr (%) + Vaccinated at 14 Apr (n) + Vaccinated at 14 Apr (%) Total eligible Previous week's vaccination coverage (%) Vaccinated over last 7d (%) @@ -46534,465 +45081,465 @@

Sex F - 506926 + 507808 + 92.8 + 547449 92.6 - 547519 - 92.4 0.2 M - 478429 + 479360 + 91.5 + 523831 91.3 - 524104 - 91.1 0.2 Ethnicity (broad categories) Black - 7301 + 7364 + 68.2 + 10801 67.7 - 10787 - 67.2 0.5 Mixed - 3787 - 77.0 + 3815 + 77.5 4921 - 76.4 - 0.6 + 77.0 + 0.5 Other - 8771 + 8827 + 74.2 + 11893 73.9 - 11872 - 73.6 0.3 South Asian - 36421 + 36645 + 84.5 + 43372 84.0 - 43351 - 83.6 - 0.4 + 0.5 Unknown - 84644 - 83.6 - 101290 - 83.4 - 0.2 + 84567 + 83.8 + 100863 + 83.7 + 0.1 White - 844431 + 845943 + 94.1 + 899430 93.9 - 899402 - 93.7 0.2 ethnicity 16 groups African - 2779 - 65.0 - 4277 - 64.5 - 0.5 + 2814 + 65.6 + 4291 + 64.9 + 0.7 Bangladeshi or British Bangladeshi - 1477 - 85.8 + 1491 + 86.6 1722 - 85.4 + 86.2 0.4 Caribbean - 3066 - 68.3 + 3080 + 68.6 4487 - 67.7 - 0.6 + 68.3 + 0.3 Chinese - 2835 - 74.9 + 2849 + 75.2 3787 - 74.5 - 0.4 + 74.9 + 0.3 Other - 5936 - 73.4 - 8085 - 73.1 + 5978 + 73.8 + 8099 + 73.5 0.3 Other Asian - 6692 + 6734 + 83.1 + 8106 82.7 - 8092 - 82.4 - 0.3 + 0.4 British or Mixed British - 799540 + 800947 + 95.1 + 842086 95.0 - 841981 - 94.8 - 0.2 + 0.1 Indian or British Indian - 20062 - 88.1 + 20132 + 88.4 22778 - 87.8 + 88.1 0.3 Irish - 5859 - 89.6 - 6538 - 89.4 + 5873 + 89.7 + 6545 + 89.5 0.2 Other Black - 1456 - 72.2 - 2016 - 71.9 + 1463 + 72.3 + 2023 + 72.0 0.3 Other White - 39004 + 39109 + 77.0 + 50792 76.7 - 50855 - 76.5 - 0.2 + 0.3 Other mixed - 1463 - 77.1 + 1470 + 77.5 1897 - 76.8 - 0.3 + 77.1 + 0.4 Pakistani or British Pakistani - 8190 - 76.1 + 8288 + 77.0 10759 - 75.3 + 76.2 0.8 Unknown - 84679 - 83.6 - 101318 - 83.4 - 0.2 + 84588 + 83.8 + 100884 + 83.7 + 0.1 White + Asian - 868 - 85.5 - 1015 - 84.8 + 875 + 85.6 + 1022 + 84.9 0.7 White + Black African - 630 - 71.4 - 882 - 69.8 - 1.6 + 644 + 72.4 + 889 + 70.9 + 1.5 White + Black Caribbean - 826 - 73.8 + 833 + 74.4 1120 73.8 - 0.0 + 0.6 Index of Multiple Deprivation (quintiles) 1 Most deprived - 133119 - 86.9 - 153111 - 86.6 + 133637 + 87.3 + 153020 + 87.0 0.3 2 - 169953 + 170359 + 90.4 + 188398 90.2 - 188461 - 90.0 0.2 3 - 218792 + 219121 + 92.6 + 236740 92.4 - 236838 - 92.2 0.2 4 - 223797 + 224098 + 93.6 + 239358 93.5 - 239421 - 93.4 0.1 5 Least deprived - 219807 + 219989 + 94.8 + 231987 94.7 - 232064 - 94.6 0.1 Unknown - 19887 + 19971 + 91.7 + 21777 91.5 - 21728 - 91.3 0.2 BMI 30+ - 252931 + 253372 + 94.7 + 267645 94.5 - 267708 - 94.3 0.2 under 30 - 732417 + 733803 + 91.3 + 803635 91.1 - 803915 - 90.9 0.2 Chronic cardiac disease no - 881125 - 91.7 - 960505 - 91.6 + 882602 + 91.9 + 960043 + 91.8 0.1 yes - 104230 + 104573 + 94.0 + 111237 93.8 - 111111 - 93.6 0.2 Current COPD no - 947338 + 949067 + 92.1 + 1030638 91.9 - 1030974 - 91.7 0.2 yes - 38017 - 93.5 + 38108 + 93.7 40649 - 93.4 + 93.6 0.1 DMARDs no - 966497 + 968268 + 92.1 + 1051470 91.9 - 1051827 - 91.7 0.2 yes - 18858 - 95.3 - 19796 + 18900 + 95.4 + 19810 95.2 - 0.1 + 0.2 Dementia no - 980147 - 91.9 - 1065981 - 91.8 + 981932 + 92.1 + 1065624 + 92.0 0.1 yes - 5208 + 5236 + 92.6 + 5656 92.3 - 5642 - 91.9 - 0.4 + 0.3 Psychosis, schizophrenia, or bipolar no - 975408 + 977179 + 92.2 + 1059639 92.0 - 1059975 - 91.9 - 0.1 + 0.2 yes - 9940 - 85.3 - 11648 - 85.0 - 0.3 + 9996 + 85.9 + 11641 + 85.4 + 0.5 Learning disability no - 983087 + 984900 + 92.2 + 1068760 92.0 - 1069096 - 91.8 0.2 yes - 2261 - 89.5 - 2527 - 88.9 + 2275 + 90.3 + 2520 + 89.7 0.6 SSRI (last 12 months) no - 898989 + 900585 + 91.9 + 980336 91.7 - 980693 - 91.5 0.2 yes - 86366 + 86583 + 95.2 + 90944 95.0 - 90930 - 94.8 0.2 Chemo or radiotherapy no - 966602 + 968366 + 92.1 + 1051561 91.9 - 1051918 - 91.7 0.2 yes - 18753 + 18809 + 95.4 + 19719 95.2 - 19698 - 95.1 - 0.1 + 0.2 Cancer (lung) no - 983710 - 91.9 - 1069838 - 91.8 + 985509 + 92.1 + 1069488 + 92.0 0.1 yes - 1645 - 92.2 - 1785 + 1659 + 92.6 + 1792 92.2 - 0.0 + 0.4 Cancer (excluding lung/haem) no - 902132 + 903707 + 91.9 + 983556 91.7 - 984011 - 91.5 0.2 yes - 83223 + 83468 + 95.1 + 87731 95.0 - 87612 - 94.9 0.1 Cancer (haematological) no - 981918 - 91.9 - 1067955 - 91.8 + 983724 + 92.1 + 1067612 + 92.0 0.1 yes - 3437 + 3444 93.9 - 3661 + 3668 93.7 0.2 @@ -47085,8 +45632,8 @@

- Vaccinated at 07 Apr (n) - Vaccinated at 07 Apr (%) + Vaccinated at 14 Apr (n) + Vaccinated at 14 Apr (%) Total eligible Previous week's vaccination coverage (%) Vaccinated over last 7d (%) @@ -47105,142 +45652,142 @@

Sex F - 25172 + 25410 + 82.8 + 30681 82.2 - 30632 - 81.2 - 1.0 + 0.6 M - 39333 + 39809 + 78.7 + 50561 77.9 - 50470 - 76.8 - 1.1 + 0.8 Age band 16-29 - 24164 - 72.4 - 33355 - 71.1 - 1.3 + 24409 + 73.0 + 33453 + 72.3 + 0.7 30-34 - 8274 + 8400 + 79.6 + 10549 78.5 - 10535 - 77.5 - 1.0 + 1.1 35-39 - 6258 + 6321 + 82.9 + 7623 82.2 - 7609 - 81.2 - 1.0 + 0.7 40-44 - 5082 - 85.0 - 5978 - 84.3 - 0.7 + 5117 + 85.5 + 5985 + 84.9 + 0.6 45-49 - 5208 + 5271 + 86.6 + 6090 85.6 - 6083 - 84.9 - 0.7 + 1.0 50-54 - 5642 - 87.7 - 6433 - 86.8 - 0.9 + 5719 + 88.8 + 6440 + 87.8 + 1.0 55-59 - 5642 - 88.4 - 6384 - 87.6 - 0.8 + 5698 + 89.4 + 6377 + 88.5 + 0.9 60-64 - 4235 - 89.6 + 4277 + 90.5 4725 - 88.9 - 0.7 + 89.9 + 0.6 Ethnicity (broad categories) Black - 707 - 53.2 + 721 + 54.2 1330 - 51.6 - 1.6 + 53.2 + 1.0 Mixed - 651 - 60.4 + 658 + 61.0 1078 - 59.7 - 0.7 + 60.4 + 0.6 Other 434 - 64.6 - 672 - 63.5 - 1.1 + 63.9 + 679 + 63.9 + 0.0 South Asian - 2919 - 63.0 - 4634 - 61.5 - 1.5 + 2996 + 64.6 + 4641 + 63.2 + 1.4 Unknown - 5054 - 77.1 - 6559 - 75.9 - 1.2 + 5082 + 77.6 + 6552 + 76.9 + 0.7 White - 54740 + 55321 + 82.6 + 66969 81.9 - 66836 - 80.9 - 1.0 + 0.7 @@ -47307,8 +45854,8 @@

- Vaccinated at 07 Apr (n) - Vaccinated at 07 Apr (%) + Vaccinated at 14 Apr (n) + Vaccinated at 14 Apr (%) Total eligible Previous week's vaccination coverage (%) Vaccinated over last 7d (%) @@ -47327,450 +45874,450 @@

Sex F - 576009 - 90.7 - 634725 - 90.3 - 0.4 + 577962 + 91.1 + 634543 + 90.8 + 0.3 M - 565271 + 567462 + 88.5 + 641375 88.1 - 641823 - 87.6 - 0.5 + 0.4 Ethnicity (broad categories) Black - 12474 + 12635 + 64.8 + 19509 63.9 - 19530 - 62.9 - 1.0 + 0.9 Mixed - 5901 - 74.3 - 7938 - 73.8 + 5950 + 74.9 + 7945 + 74.4 0.5 Other - 11417 + 11522 + 71.1 + 16198 70.6 - 16177 - 69.9 - 0.7 + 0.5 South Asian - 42714 - 81.6 - 52346 - 80.8 - 0.8 + 43120 + 82.3 + 52388 + 81.7 + 0.6 Unknown - 113974 - 80.6 - 141351 - 80.1 - 0.5 + 114086 + 81.0 + 140763 + 80.7 + 0.3 White - 954793 + 958111 + 92.2 + 1039108 91.9 - 1039206 - 91.5 - 0.4 + 0.3 ethnicity 16 groups African - 4935 + 5005 + 65.1 + 7686 64.1 - 7700 - 62.9 - 1.2 + 1.0 Bangladeshi or British Bangladeshi - 1904 - 84.7 - 2247 - 83.8 + 1925 + 85.4 + 2254 + 84.5 0.9 Caribbean - 4900 - 62.4 - 7847 - 61.6 + 4963 + 63.4 + 7833 + 62.6 0.8 Chinese - 3535 - 74.3 - 4760 - 73.5 - 0.8 + 3556 + 74.8 + 4753 + 74.4 + 0.4 Other - 7875 + 7973 + 69.7 + 11445 69.0 - 11410 - 68.3 0.7 Other Asian - 8841 - 79.6 - 11102 - 78.9 - 0.7 + 8904 + 80.3 + 11088 + 79.7 + 0.6 British or Mixed British - 899486 + 902412 + 93.8 + 962227 93.5 - 962290 - 93.1 - 0.4 + 0.3 Indian or British Indian - 22512 - 85.8 - 26229 - 85.3 - 0.5 + 22645 + 86.2 + 26264 + 85.9 + 0.3 Irish - 5628 - 86.0 + 5656 + 86.4 6545 - 85.6 + 86.0 0.4 Other Black - 2646 - 66.3 + 2667 + 66.8 3990 - 65.6 - 0.7 + 66.3 + 0.5 Other White - 49672 + 50029 + 71.1 + 70315 70.6 - 70371 - 70.1 0.5 Other mixed - 2233 + 2254 + 74.2 + 3038 73.7 - 3031 - 73.2 0.5 Pakistani or British Pakistani - 9464 - 74.1 - 12768 - 72.7 - 1.4 + 9639 + 75.5 + 12775 + 74.2 + 1.3 Unknown - 113981 - 80.6 - 141358 - 80.1 - 0.5 - - + 114100 + 81.0 + 140791 + 80.7 + 0.3 + + White + Asian - 1232 - 84.2 + 1239 + 84.7 1463 - 83.3 - 0.9 + 84.2 + 0.5 White + Black African - 1057 - 71.2 + 1071 + 72.2 1484 - 70.3 - 0.9 + 71.2 + 1.0 White + Black Caribbean - 1379 - 70.4 + 1386 + 70.7 1960 - 70.0 - 0.4 + 70.4 + 0.3 Index of Multiple Deprivation (quintiles) 1 Most deprived - 164668 - 83.0 - 198303 - 82.3 - 0.7 + 165746 + 83.6 + 198170 + 83.1 + 0.5 2 - 201579 - 87.1 - 231392 - 86.6 - 0.5 + 202538 + 87.6 + 231259 + 87.2 + 0.4 3 - 249634 + 250383 + 90.4 + 276976 90.1 - 277137 - 89.7 - 0.4 + 0.3 4 - 254926 + 255675 + 91.8 + 278523 91.5 - 278649 - 91.2 0.3 5 Least deprived - 247429 + 247891 + 93.5 + 265034 93.3 - 265188 - 93.0 - 0.3 + 0.2 Unknown - 23044 + 23198 + 89.4 + 25956 89.0 - 25886 - 88.2 - 0.8 + 0.4 BMI 30+ - 287938 + 288974 + 93.3 + 309631 93.0 - 309708 - 92.6 - 0.4 + 0.3 under 30 - 853342 + 856450 + 88.6 + 966280 88.3 - 966840 - 87.8 - 0.5 + 0.3 Chronic cardiac disease no - 1055334 + 1059121 + 89.6 + 1182545 89.2 - 1183252 - 88.7 - 0.5 + 0.4 yes - 85953 - 92.1 - 93296 - 91.9 + 86303 + 92.4 + 93366 + 92.2 0.2 Current COPD no - 1109724 - 89.3 - 1242045 - 88.9 - 0.4 + 1113777 + 89.7 + 1241429 + 89.4 + 0.3 yes - 31556 + 31654 + 91.8 + 34482 91.5 - 34503 - 91.2 0.3 DMARDs no - 1121827 - 89.3 - 1255821 - 88.9 - 0.4 + 1125901 + 89.7 + 1255177 + 89.4 + 0.3 yes - 19453 + 19523 + 94.1 + 20741 93.9 - 20727 - 93.6 - 0.3 + 0.2 Dementia no - 1137941 + 1142064 + 89.8 + 1272243 89.4 - 1272873 - 89.0 0.4 yes - 3339 - 90.9 + 3360 + 91.4 3675 - 90.3 - 0.6 + 91.0 + 0.4 Psychosis, schizophrenia, or bipolar no - 1129149 + 1133223 + 89.9 + 1261218 89.5 - 1261848 - 89.0 - 0.5 + 0.4 yes - 12131 - 82.5 + 12208 + 83.0 14700 - 82.0 + 82.5 0.5 SSRI (last 12 months) no - 1021727 + 1025248 + 89.3 + 1147531 89.0 - 1148315 - 88.5 - 0.5 + 0.3 yes - 119553 - 93.2 - 128240 - 92.8 - 0.4 + 120183 + 93.6 + 128387 + 93.3 + 0.3 Chemo or radiotherapy no - 1124333 - 89.3 - 1258544 - 88.9 - 0.4 + 1128407 + 89.7 + 1257900 + 89.4 + 0.3 yes - 16954 + 17017 + 94.4 + 18018 94.2 - 18004 - 93.8 - 0.4 + 0.2 Cancer (lung) no - 1140237 + 1144374 + 89.8 + 1274735 89.4 - 1275379 - 89.0 0.4 yes - 1043 - 88.7 - 1176 - 88.1 - 0.6 + 1057 + 89.3 + 1183 + 88.8 + 0.5 Cancer (excluding lung/haem) no - 1073947 + 1077783 + 89.5 + 1203867 89.2 - 1204574 - 88.7 - 0.5 + 0.3 yes - 67333 + 67648 + 93.9 + 72051 93.6 - 71974 - 93.2 - 0.4 + 0.3 Cancer (haematological) no - 1138193 + 1142323 + 89.8 + 1272586 89.4 - 1273223 - 89.0 0.4 yes - 3087 - 92.8 - 3325 - 92.8 - 0.0 + 3101 + 93.1 + 3332 + 92.9 + 0.2 @@ -47849,8 +46396,8 @@

- Vaccinated at 07 Apr (n) - Vaccinated at 07 Apr (%) + Vaccinated at 14 Apr (n) + Vaccinated at 14 Apr (%) Total eligible Previous week's vaccination coverage (%) Vaccinated over last 7d (%) @@ -47869,365 +46416,365 @@

Sex F - 656453 + 660534 + 89.1 + 740964 88.6 - 741006 - 87.3 - 1.3 + 0.5 M - 647913 - 84.4 - 767256 - 82.8 - 1.6 + 652995 + 85.1 + 767102 + 84.5 + 0.6 Ethnicity (broad categories) Black - 18753 - 60.7 - 30877 - 59.1 - 1.6 + 19103 + 61.9 + 30870 + 60.8 + 1.1 Mixed - 8652 + 8736 + 71.4 + 12229 70.7 - 12236 - 69.5 - 1.2 + 0.7 Other - 14882 + 15078 + 68.4 + 22029 67.6 - 22022 - 65.8 - 1.8 + 0.8 South Asian - 46739 - 78.2 - 59759 - 76.7 - 1.5 + 47334 + 79.2 + 59794 + 78.3 + 0.9 Unknown - 132216 + 132937 + 77.8 + 170968 77.1 - 171458 - 75.4 - 1.7 + 0.7 White - 1083124 + 1090348 + 89.9 + 1212176 89.4 - 1211903 - 87.9 - 1.5 + 0.5 ethnicity 16 groups African - 7917 - 62.2 + 8078 + 63.5 12719 - 60.4 - 1.8 + 62.3 + 1.2 Bangladeshi or British Bangladeshi - 2436 - 81.9 - 2975 - 80.7 - 1.2 + 2457 + 82.4 + 2982 + 81.7 + 0.7 Caribbean - 6384 - 58.2 - 10969 - 56.9 - 1.3 + 6482 + 59.2 + 10955 + 58.3 + 0.9 Chinese - 4438 - 72.4 + 4487 + 73.2 6132 - 70.2 - 2.2 + 72.4 + 0.8 Other - 10437 - 65.7 - 15890 - 64.1 - 1.6 + 10591 + 66.6 + 15904 + 65.8 + 0.8 Other Asian - 11445 - 77.0 - 14854 - 75.4 - 1.6 + 11571 + 77.9 + 14861 + 77.1 + 0.8 British or Mixed British - 1015994 + 1022427 + 91.8 + 1113539 91.3 - 1113350 - 89.8 - 1.5 + 0.5 Indian or British Indian - 23450 + 23695 + 83.8 + 28287 83.0 - 28252 - 81.9 - 1.1 + 0.8 Irish - 6349 - 83.0 - 7651 - 81.9 - 1.1 + 6384 + 83.4 + 7658 + 82.9 + 0.5 Other Black - 4459 - 62.0 + 4543 + 63.1 7196 - 60.2 - 1.8 + 62.1 + 1.0 Other White - 60802 + 61537 + 67.6 + 90986 66.9 - 90923 - 65.7 - 1.2 + 0.7 Other mixed - 3052 + 3073 + 71.0 + 4326 70.4 - 4333 - 69.3 - 1.1 + 0.6 Pakistani or British Pakistani - 9408 - 68.8 - 13678 - 66.6 - 2.2 + 9611 + 70.3 + 13671 + 69.0 + 1.3 Unknown - 132195 + 132930 + 77.8 + 170954 77.1 - 171430 - 75.4 - 1.7 + 0.7 White + Asian - 1778 - 78.6 + 1792 + 79.3 2261 - 77.7 - 0.9 + 78.6 + 0.7 White + Black African - 1575 - 67.8 + 1589 + 68.4 2324 - 66.0 - 1.8 + 67.5 + 0.9 White + Black Caribbean - 2247 - 67.7 - 3318 - 66.5 - 1.2 + 2275 + 68.4 + 3325 + 67.8 + 0.6 Index of Multiple Deprivation (quintiles) 1 Most deprived - 193403 - 78.8 - 245343 - 76.9 - 1.9 + 195748 + 79.8 + 245280 + 78.9 + 0.9 2 - 230419 + 232582 + 84.3 + 275737 83.6 - 275730 - 81.9 - 1.7 + 0.7 3 - 281967 + 283654 + 87.8 + 322966 87.3 - 323015 - 85.9 - 1.4 + 0.5 4 - 289191 + 290717 + 89.7 + 324135 89.2 - 324184 - 87.9 - 1.3 + 0.5 5 Least deprived - 283353 + 284529 + 91.8 + 309988 91.4 - 310065 - 90.1 - 1.3 + 0.4 Unknown - 26026 + 26299 + 87.8 + 29967 87.0 - 29918 - 85.4 - 1.6 + 0.8 BMI 30+ - 317114 + 318878 + 91.5 + 348390 91.0 - 348502 - 89.8 - 1.2 + 0.5 under 30 - 987252 + 994651 + 85.8 + 1159683 85.1 - 1159753 - 83.6 - 1.5 + 0.7 Chronic cardiac disease no - 1239777 + 1248464 + 86.9 + 1436043 86.3 - 1436358 - 84.8 - 1.5 + 0.6 yes - 64589 - 89.8 - 71904 - 89.1 - 0.7 + 65065 + 90.3 + 72030 + 89.9 + 0.4 Current COPD no - 1279929 - 86.4 - 1480619 - 84.9 - 1.5 + 1288945 + 87.1 + 1480423 + 86.5 + 0.6 yes - 24437 + 24584 + 88.9 + 27650 88.4 - 27636 - 87.8 - 0.6 + 0.5 DMARDs no - 1284997 + 1294076 + 87.0 + 1487024 86.4 - 1487220 - 84.9 - 1.5 + 0.6 yes - 19362 - 92.0 + 19453 + 92.4 21042 - 91.2 - 0.8 + 92.1 + 0.3 Psychosis, schizophrenia, or bipolar no - 1289771 + 1298745 + 87.2 + 1489320 86.6 - 1489509 - 85.1 - 1.5 + 0.6 yes - 14595 - 77.8 - 18753 - 76.8 + 14784 + 78.9 + 18746 + 77.9 1.0 SSRI (last 12 months) no - 1152711 + 1160740 + 86.5 + 1341676 85.9 - 1341998 - 84.4 - 1.5 + 0.6 yes - 151655 - 91.2 - 166264 - 90.0 - 1.2 + 152789 + 91.8 + 166397 + 91.3 + 0.5 @@ -48306,8 +46853,8 @@

- Vaccinated at 07 Apr (n) - Vaccinated at 07 Apr (%) + Vaccinated at 14 Apr (n) + Vaccinated at 14 Apr (%) Total eligible Previous week's vaccination coverage (%) Vaccinated over last 7d (%) @@ -48324,367 +46871,367 @@

Sex F - 652631 + 659232 + 86.8 + 759843 85.9 - 759808 - 84.5 - 1.4 + 0.9 M - 634781 - 79.5 + 643727 + 80.6 798322 - 77.7 - 1.8 + 79.5 + 1.1 Ethnicity (broad categories) Black - 21329 + 21875 + 58.4 + 37471 57.0 - 37436 - 54.9 - 2.1 + 1.4 Mixed - 10164 - 66.8 - 15218 - 65.2 - 1.6 + 10374 + 68.1 + 15225 + 66.9 + 1.2 Other - 17920 - 63.3 - 28294 - 61.5 - 1.8 + 18291 + 64.6 + 28315 + 63.4 + 1.2 South Asian - 62286 - 73.1 - 85176 - 71.0 - 2.1 + 63665 + 74.7 + 85197 + 73.2 + 1.5 Unknown - 140679 - 74.1 - 189952 - 72.3 - 1.8 + 142156 + 75.1 + 189392 + 74.0 + 1.1 White - 1035027 + 1046591 + 87.0 + 1202558 86.1 - 1202054 - 84.6 - 1.5 + 0.9 ethnicity 16 groups African - 11557 - 58.5 - 19754 - 56.2 - 2.3 + 11900 + 60.2 + 19768 + 58.6 + 1.6 Bangladeshi or British Bangladeshi - 3878 - 79.1 - 4900 - 77.1 - 2.0 + 3941 + 80.3 + 4907 + 79.0 + 1.3 Caribbean - 4921 + 5012 + 53.4 + 9394 52.4 - 9387 - 50.9 - 1.5 + 1.0 Chinese - 4746 - 70.0 - 6783 - 67.6 - 2.4 + 4837 + 71.2 + 6797 + 69.9 + 1.3 Other - 13181 - 61.3 - 21504 - 59.7 - 1.6 + 13454 + 62.5 + 21511 + 61.4 + 1.1 Other Asian - 15190 + 15484 + 74.6 + 20769 73.2 - 20748 - 71.4 - 1.8 + 1.4 British or Mixed British - 958482 - 88.7 - 1080275 - 87.2 - 1.5 + 968751 + 89.6 + 1080625 + 88.8 + 0.8 Indian or British Indian - 27692 + 28161 + 79.6 + 35357 78.4 - 35336 - 76.6 - 1.8 + 1.2 Irish - 6160 + 6230 + 80.3 + 7756 79.6 - 7742 - 78.4 - 1.2 + 0.7 Other Black - 4844 - 58.4 - 8295 - 56.4 - 2.0 + 4963 + 59.7 + 8316 + 58.3 + 1.4 Other White - 70378 + 71554 + 62.7 + 114121 61.7 - 114044 - 60.4 - 1.3 + 1.0 Other mixed - 3633 - 65.6 + 3703 + 66.9 5537 - 64.1 - 1.5 + 65.7 + 1.2 Pakistani or British Pakistani - 15526 - 64.2 - 24185 - 61.1 - 3.1 + 16079 + 66.5 + 24178 + 64.3 + 2.2 Unknown - 140679 - 74.1 - 189959 - 72.2 - 1.9 + 142219 + 75.1 + 189455 + 74.0 + 1.1 White + Asian - 2261 - 76.7 - 2947 - 75.1 - 1.6 + 2289 + 77.9 + 2940 + 76.9 + 1.0 White + Black African - 2065 - 62.5 - 3304 - 60.8 + 2121 + 64.3 + 3297 + 62.6 1.7 White + Black Caribbean - 2212 + 2247 + 65.4 + 3437 64.2 - 3444 - 62.8 - 1.4 + 1.2 Index of Multiple Deprivation (quintiles) 1 Most deprived - 198821 - 73.0 - 272230 - 71.0 - 2.0 + 202839 + 74.5 + 272216 + 73.1 + 1.4 2 - 230755 + 234220 + 80.3 + 291844 79.1 - 291816 - 77.3 - 1.8 + 1.2 3 - 273371 + 276164 + 84.5 + 326641 83.7 - 326585 - 82.3 - 1.4 + 0.8 4 - 280322 + 282933 + 87.2 + 324562 86.4 - 324597 - 85.0 - 1.4 + 0.8 5 Least deprived - 278215 - 89.2 - 311731 - 87.8 - 1.4 + 280427 + 90.0 + 311647 + 89.3 + 0.7 Unknown - 25921 + 26376 + 84.4 + 31248 83.1 - 31178 - 81.5 - 1.6 + 1.3 BMI 30+ - 298690 + 301630 + 89.3 + 337904 88.4 - 337855 - 87.1 - 1.3 + 0.9 under 30 - 988722 - 81.0 - 1220282 - 79.4 - 1.6 + 1001329 + 82.1 + 1220254 + 81.1 + 1.0 Chronic cardiac disease no - 1246581 + 1261729 + 83.5 + 1510950 82.5 - 1510985 - 80.9 - 1.6 + 1.0 yes - 40831 - 86.6 - 47145 - 85.7 - 0.9 + 41223 + 87.3 + 47208 + 86.7 + 0.6 Current COPD no - 1271557 + 1286978 + 83.6 + 1539489 82.6 - 1539482 - 81.0 - 1.6 + 1.0 yes - 15855 + 15981 + 85.6 + 18669 85.0 - 18655 - 84.1 - 0.9 + 0.6 DMARDs no - 1270717 - 82.5 - 1539636 - 80.9 - 1.6 + 1286145 + 83.5 + 1539657 + 82.6 + 0.9 yes - 16695 + 16807 + 90.8 + 18501 90.3 - 18494 - 89.4 - 0.9 + 0.5 Psychosis, schizophrenia, or bipolar no - 1272761 - 82.7 - 1538425 - 81.1 - 1.6 + 1288098 + 83.7 + 1538453 + 82.8 + 0.9 yes - 14651 - 74.3 - 19712 - 73.2 - 1.1 + 14854 + 75.4 + 19705 + 74.4 + 1.0 SSRI (last 12 months) no - 1122695 - 81.7 - 1373365 - 80.1 - 1.6 + 1136338 + 82.8 + 1373162 + 81.8 + 1.0 yes - 164710 - 89.1 - 184765 - 87.7 - 1.4 + 166614 + 90.1 + 184996 + 89.2 + 0.9 @@ -48763,7 +47310,7 @@

- Vaccinated at 07 Apr (n) + Vaccinated at 14 Apr (n) Previous week's vaccination figure (n) Vaccinated over last 7d (n) Increase in coverage over last 7d (%) @@ -48781,328 +47328,328 @@

Sex F - 1461145 - 1405159.0 - 55986.0 - 4.0 + 1512819 + 1462755.0 + 50064.0 + 3.4 M - 933142 - 878101.0 - 55041.0 - 6.3 + 989051 + 934703.0 + 54348.0 + 5.8 Age band 16-29 - 572502 - 549612.0 - 22890.0 - 4.2 + 582386 + 572964.0 + 9422.0 + 1.6 30-39 - 712726 - 684397.0 - 28329.0 - 4.1 + 734951 + 713398.0 + 21553.0 + 3.0 40-49 - 1109059 - 1049251.0 - 59808.0 - 5.7 + 1184533 + 1111089.0 + 73444.0 + 6.6 Ethnicity (broad categories) Black - 50526 - 48419.0 - 2107.0 - 4.4 + 52437 + 50666.0 + 1771.0 + 3.5 Mixed - 33145 - 31752.0 - 1393.0 - 4.4 + 34426 + 33208.0 + 1218.0 + 3.7 Other - 47565 - 45094.0 - 2471.0 - 5.5 + 49931 + 47712.0 + 2219.0 + 4.7 South Asian - 203252 - 193151.0 - 10101.0 - 5.2 + 212086 + 203931.0 + 8155.0 + 4.0 Unknown - 209853 - 197554.0 - 12299.0 - 6.2 + 220626 + 209398.0 + 11228.0 + 5.4 White - 1849953 - 1767290.0 - 82663.0 - 4.7 + 1932350 + 1852536.0 + 79814.0 + 4.3 ethnicity 16 groups African - 33936 - 32487.0 - 1449.0 - 4.5 + 35182 + 34020.0 + 1162.0 + 3.4 Bangladeshi or British Bangladeshi - 16205 - 15498.0 - 707.0 - 4.6 + 16807 + 16233.0 + 574.0 + 3.5 Caribbean - 6566 - 6293.0 - 273.0 - 4.3 + 6825 + 6580.0 + 245.0 + 3.7 Chinese - 9674 - 9177.0 - 497.0 - 5.4 + 10227 + 9695.0 + 532.0 + 5.5 Other - 37877 - 35910.0 - 1967.0 - 5.5 + 39683 + 38003.0 + 1680.0 + 4.4 Other Asian - 45290 - 43414.0 - 1876.0 - 4.3 + 47110 + 45437.0 + 1673.0 + 3.7 British or Mixed British - 1685257 - 1610490.0 - 74767.0 - 4.6 + 1758365 + 1687546.0 + 70819.0 + 4.2 Indian or British Indian - 88508 - 84329.0 - 4179.0 - 5.0 + 92190 + 88879.0 + 3311.0 + 3.7 Irish - 10381 - 9975.0 - 406.0 - 4.1 + 10913 + 10402.0 + 511.0 + 4.9 Other Black - 10017 - 9625.0 - 392.0 - 4.1 + 10423 + 10066.0 + 357.0 + 3.5 Other White - 154301 - 146818.0 - 7483.0 - 5.1 + 163072 + 154588.0 + 8484.0 + 5.5 Other mixed - 11914 - 11438.0 - 476.0 - 4.2 + 12397 + 11928.0 + 469.0 + 3.9 Pakistani or British Pakistani - 53249 - 49910.0 - 3339.0 - 6.7 + 55993 + 53382.0 + 2611.0 + 4.9 Unknown - 209853 - 197547.0 - 12306.0 - 6.2 + 220626 + 209398.0 + 11228.0 + 5.4 White + Asian - 7889 - 7539.0 - 350.0 - 4.6 + 8197 + 7903.0 + 294.0 + 3.7 White + Black African - 6454 - 6188.0 - 266.0 - 4.3 + 6713 + 6461.0 + 252.0 + 3.9 White + Black Caribbean - 6923 - 6622.0 - 301.0 - 4.5 + 7147 + 6937.0 + 210.0 + 3.0 Index of Multiple Deprivation (quintiles) 1 Most deprived - 461692 - 440048.0 - 21644.0 - 4.9 + 480788 + 462259.0 + 18529.0 + 4.0 2 - 472332 - 451024.0 - 21308.0 - 4.7 + 491596 + 472927.0 + 18669.0 + 3.9 3 - 490560 - 469413.0 - 21147.0 - 4.5 + 511245 + 490959.0 + 20286.0 + 4.1 4 - 467047 - 445319.0 - 21728.0 - 4.9 + 489734 + 467586.0 + 22148.0 + 4.7 5 Least deprived - 430647 - 408919.0 - 21728.0 - 5.3 + 453138 + 431312.0 + 21826.0 + 5.1 Unknown - 72009 - 68537.0 - 3472.0 - 5.1 + 75369 + 72422.0 + 2947.0 + 4.1 BMI 30+ - 551978 - 532462.0 - 19516.0 - 3.7 + 569513 + 552636.0 + 16877.0 + 3.1 under 30 - 1842309 - 1750791.0 - 91518.0 - 5.2 + 1932357 + 1844822.0 + 87535.0 + 4.7 Chronic cardiac disease no - 2337888 - 2228079.0 - 109809.0 - 4.9 + 2444736 + 2341038.0 + 103698.0 + 4.4 yes - 56399 - 55181.0 - 1218.0 - 2.2 + 57134 + 56420.0 + 714.0 + 1.3 Current COPD no - 2380630 - 2269897.0 - 110733.0 - 4.9 + 2487933 + 2383794.0 + 104139.0 + 4.4 yes - 13657 - 13363.0 - 294.0 - 2.2 + 13937 + 13664.0 + 273.0 + 2.0 DMARDs no - 2359623 - 2249380.0 - 110243.0 - 4.9 + 2466492 + 2362724.0 + 103768.0 + 4.4 yes - 34664 - 33880.0 - 784.0 - 2.3 + 35378 + 34734.0 + 644.0 + 1.9 SSRI (last 12 months) no - 2027914 - 1930334.0 - 97580.0 - 5.1 + 2121924 + 2029720.0 + 92204.0 + 4.5 yes - 366373 - 352926.0 - 13447.0 - 3.8 + 379946 + 367738.0 + 12208.0 + 3.3 @@ -49204,47 +47751,47 @@

Ap 80+ - 1124221 + 1121701 94.4 70-79 - 2066323 + 2064944 93.0 care home - 83727 + 83888 97.4 shielding (aged 16-69) - 823949 + 824887 96.1 65-69 - 1071630 - 90.5 + 1071287 + 90.6 LD (aged 16-64) - 81102 + 81249 91.9 60-64 - 1276562 - 88.9 + 1275925 + 89.0 55-59 - 1508269 - 88.6 + 1508080 + 88.7 50-54 - 1558144 + 1558172 87.8 diff --git a/released-outputs/opensafely_vaccine_report_overall.pdf b/released-outputs/opensafely_vaccine_report_overall.pdf index 9837651..cd723a9 100644 Binary files a/released-outputs/opensafely_vaccine_report_overall.pdf and b/released-outputs/opensafely_vaccine_report_overall.pdf differ