Team members: Tori Arriola, Yifei Cao, Kylee Grant, Leah Handel, Sana Jessani, Catie Lutz, and Rana Saber
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Machine Learning (Scikit-Learn)
-
At least two of the following:
- Python Pandas
- Python Matplotlib
- HTML/CSS/Bootstrap
- JavaScript Plotly
- JavaScript D3
- JavaScript Leaflet
- SQL Database
- MongoDB Database
- Google Cloud SQL
- Amazon AWS
- Tableau
Building upon our prior work, we aim to use machine learning to predict the effect access to contraception and family planning services has on teen pregnancy and birth rates. We hope that the resulting models of this project will help elucidate the most efficacious interventions in the outcomes of teen pregnancies and births.
The Guttmacher Institute estimated the total number of women who received publicly supported contraceptive care in 2015 using service data for all agencies and clinics that provided publicly funded family planning services in the 50 states and the District of Columbia. They obtained clinic and client data from several federal sources, such as the Office of Population Affairs (OPA) and U.S. Department of Health and Human Services.
No metadata available. Tables described below are from the full report:
TABLE 1. Number of clinics providing publicly supported contraceptive services and percentage change, by state—2001, 2006, 2010 and 2015
TABLE 2. Number of women receiving publicly supported contraceptive services, by state—2001, 2006, 2010 and 2015
TABLE 3. Number of clinics providing publicly funded contraceptive services, by clinic type, for all publicly funded clinics and for Title X–funded clinics—2001, 2010 and 2015 national summary and 2015 state detail
TABLE 4. Number of female contraceptive clients served at publicly funded clinics and at Title X–funded clinics, by clinic type—2001, 2010 and 2015 national summary and 2015 regional and state detail
TABLE 5. Number and distribution of clinics providing publicly funded contraceptive services and the number and distribution of female contraceptive clients served, by clinic type and Title X funding status, 2001, 2010 and 2015, and the percentage change in clinics and clients, 2001–2010 and 2010–2015
TABLE 6. Number of unintended pregnancies, unplanned births and abortions averted among clients served by all publicly supported providers and by Title X–funded providers, by state, 2015
TABLE 7. Number of teenage contraceptive clients served at publicly funded clinics, and the numbers of unintended pregnancies, unplanned births and abortions among teens averted by all publicly supported providers and by Title X–funded providers, by state, 2015
Publicly Supported Family Planning Services in the United States: Likely Need, Availability and Impact (Guttmacher Institute, 2016):
The Guttmacher Institute estimated for 2016 for the following key indicators measuring the likely need for, actual provision of, and the impact of publicly supported contraceptive/sexual and reproductive health services:
- The numbers of women likely in need of public support for contraceptive services according to age, income level, race and ethnicity, and health insurance status.
- The numbers of women who received contraceptive services at all publicly supported family planning providers.
- The numbers of reproductive health outcomes prevented among women who received publicly supported contraceptive care, such as pregnancies as well as STIs.
- The cost savings in public funds that result from preventing negative health outcomes.
The dataset was based on information from data from the U.S. Census Bureau in 2016, the 2014–2016 American Community Survey (ACS), and the 2011–2015 National Survey of Family Growth (NSFG).
No metadata available. Tables described below are from the full report:
TABLE 1. Number of women who likely need public support for contraceptive services and supplies, by age-group, income level, and race and ethnicity, and percentage change between years—2000, 2010 and 2016
TABLE 2. Number of women who likely need public support for contraceptive services and supplies, by age-group and income level—2010 and 2016 national summary, and 2016 state detail
TABLE 3. Number of women who likely need public support for contraceptive services and supplies, by race and ethnicity, age-group and income—2010 and 2016 national summary, and 2016 state detail
TABLE 4. Number of women who likely need public support for contraceptive services and supplies, and percentage change between 2010 and 2016—national summary and state detail, 2000, 2010 and 2016
TABLE 5. Estimated number of women who likely need public support for contraceptive services and supplies who are uninsured and the percentage of women who are uninsured, both by age group and income level—2010, 2013 and 2016 national summary and 2016 state detail
TABLE 6. Percentage, estimated number and percentage change in the number of women who likely need public support for contraceptive services and supplies who are uninsured, by state and state Medicaid expansion status under the Affordable Care Act— 2013 and 2016
TABLE 7. Number of female patients receiving publicly supported contraceptive services from all provider types, national summary, and by state for publicly supported clinics—2001, 2010 and 2016
TABLE 8. Number of women receiving contraceptive services from publicly supported clinics by clinic funding type, and percentage change—national summary and state detail, 2010 and 2016
TABLE 9. Number of female adolescents receiving publicly supported contraceptive services from all provider types, national summary and by state for publicly supported clinics—2010 and 2016
TABLE 10. Number of female adolescents receiving contraceptive services from publicly supported clinics by clinic funding type, and percentage change—national summary and state detail, 2010 and 2016
TABLE 11. Percentage of women who likely need public support for contraceptive services who are served by publicly supported providers, all women and adolescent women—national summary and state detail, 2010 and 2016
TABLE 12. Percentage of women who likely need public support for contraceptive services who are served by clinics, according to clinic funding type, all women and adolescent women, by state—2010 and 2016
TABLE 13. Health benefits from contraceptive and related noncontraceptive services received during publicly funded family planning visits, according to provider type, national summary, 2016
TABLE 14. Health benefits from contraceptive and related noncontraceptive services received during publicly supported family planning visits at all provider types, national summary and by state for publicly supported clinics, 2016
TABLE 15. Health benefits from contraceptive and related noncontraceptive services received during publicly supported family planning visits at clinics receiving Title X funds, by state, 2016
TABLE 16. Health benefits from contraceptive and related noncontraceptive services received during publicly supported family planning visits at clinics receiving other (non–Title X) public funds, by state, 2016
TABLE 17. Number of pregnancies, births and abortions averted among patients younger than 20 at all provider types, national summary, and by state for publicly supported clinics, 2016
TABLE 18. Public cost savings from contraceptive and related noncontraceptive services received during publicly supported family planning visits at all providers, including savings from averted pregnancies, STI sequelae and cancers, national summary, and by state for publicly supported clinics, 2016
TABLE 19. Public cost savings from contraceptive and related noncontraceptive services received during family planning visits at Title X–funded clinics, including savings from averted pregnancies, STI sequelae and cancers, by state, 2016
TABLE 20. Public cost savings from contraceptive and related noncontraceptive services received during family planning visits at clinics receiving other (non–Title X) public funds, including savings from averted pregnancies, STI sequelae and cancers, by state, 2016
This is a collection of annual population estimates, estimated components of resident population change, and rates of the components of resident population change for the United States and Puerto Rico from April 1, 2010 to July 1, 2019.
Metadata is available here
Social vulnerability refers to the potential negative effects on communities caused by external stresses on human health. Such stresses include natural or human-caused disasters, or disease outbreaks. Reducing social vulnerability can decrease both human suffering and economic loss. The CDC/ATSDR Social Vulnerability Index (CDC/ATSDR SVI) uses 15 U.S. census variables to help local officials identify communities that may need support before, during, or after disasters. Read more about the Social Vulnerability Index here.
Metadata is available here.
This dataset details estimated birth rates, expressed per 1,000 females aged 15–19, for 3,137 U.S. counties. This data spans 2003 to 2018 and largely is sourced from the National Vital Statistics System birth data files. For further information, please see the documentation at the link above.
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description: "This data set contains estimated teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) by county and year. DEFINITIONS Estimated teen birth rate: Model-based estimates of teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) for a specific county and year. Estimated county teen birth rates were obtained using the methods described elsewhere (1,2,3,4). These annual county-level teen birth estimates “borrow strength” across counties and years to generate accurate estimates where data are sparse due to small population size (1,2,3,4). The inferential method uses information—including the estimated teen birth rates from neighboring counties across years and the associated explanatory variables—to provide a stable estimate of the county teen birth rate. Median teen birth rate: The middle value of the estimated teen birth rates for the age group 15–19 for counties in a state. Bayesian credible intervals: A range of values within which there is a 95% probability that the actual teen birth rate will fall, based on the observed teen births data and the model. NOTES Data on the number of live births for women aged 15–19 years were extracted from the National Center for Health Statistics’ (NCHS) National Vital Statistics System birth data files for 2003–2015 (5). Population estimates were extracted from the files containing intercensal and postcensal bridged-race population estimates provided by NCHS. For each year, the July population estimates were used, with the exception of the year of the decennial census, 2010, for which the April estimates were used. Hierarchical Bayesian space–time models were used to generate hierarchical Bayesian estimates of county teen birth rates for each year during 2003–2015 (1,2,3,4). The Bayesian analogue of the frequentist confidence interval is defined as the Bayesian credible interval. A 100*(1-α)% Bayesian credible interval for an unknown parameter vector θ and observed data vector y is a subset C of parameter space Ф such that 1-α≤P({C│y})=∫p{θ │y}dθ, where integration is performed over the set and is replaced by summation for discrete components of θ. The probability that θ lies in C given the observed data y is at least (1- α) (6). County borders in Alaska changed, and new counties were formed and others were merged, during 2003–2015. These changes were reflected in the population files but not in the natality files. For this reason, two counties in Alaska were collapsed so that the birth and population counts were comparable. Additionally, Kalawao County, a remote island county in Hawaii, recorded no births, and census estimates indicated a denominator of 0 (i.e., no females between the ages of 15 and 19 years residing in the county from 2003 through 2015). For this reason, Kalawao County was removed from the analysis. Also , Bedford City, Virginia, was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. For consistency, Bedford City was merged with Bedford County, Virginia, for the entire 2003–2015 period. Final analysis was conducted on 3,137 counties for each year from 2003 through 2015. County boundaries are consistent with the vintage 2005–2007 bridged-race population file geographies (7). SOURCES National Center for Health Statistics. Vital statistics data available online, Natality all-county files. Hyattsville, MD. Published annually. For details about file release and access policy, see NCHS data release and access policy for micro-data and compressed vital statistics files, available from: http://www.cdc.gov/nchs/nvss/dvs_data_release.htm. For natality public-use files, see vital statistics data available online, available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. National Center for Health Statistics. U.S. Census populations with bridged race categories. Estimated population data available. Postcensal and intercensal files. Hyattsville, MD",
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identifier: "https://data.cdc.gov/api/views/3h58-x6cd",
issued: "2020-01-27",
keyword: [
"county teen birth trends",
"county trends on teen births",
"nchs",
"teen births",
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name: "Centers for Disease Control and Prevention"
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title: "NCHS - Teen Birth Rates for Age Group 15-19 in the United States by County"
}
This dataset assembles all final birth data for females aged 15–19, 15–17, and 18–19 for the United States and each of the 50 states, expressed per 1,000 females in each age range. This data spans 1990–2018 and is based on 100% of birth certificates filed in 50 states.
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description: "This dataset assembles all final birth data for females aged 15–19, 15–17, and 18–19 for the United States and each of the 50 states. Data are based on 100% of birth certificates filed in all 50 states. All the teen birth rates in this dashboard reflect the latest revisions to Census populations (i.e., the intercensal populations) and thus provide a consistent series of accurate rates for the past 25 years. The denominators of the teen birth rates for 1991–1999 have been revised to incorporate the results of the 2000 Census. The denominators of the teen birth rates for 2001–2009 have revised to incorporate the results of the 2010 Census.",
distribution: [
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downloadURL: "https://data.cdc.gov/api/views/y268-sna3/rows.csv?accessType=DOWNLOAD",
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identifier: "https://data.cdc.gov/api/views/y268-sna3",
issued: "2018-07-09",
keyword: [
"nchs",
"state teen birth trends",
"teen births",
"united states",
"u.s. and state trends on teen births",
"u.s. teen birth rate"
],
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license: "http://opendefinition.org/licenses/odc-odbl/",
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"009:020"
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publisher: {
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name: "Centers for Disease Control and Prevention"
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theme: [
"NCHS"
],
title: "NCHS - U.S. and State Trends on Teen Births"
}
For this project, we referenced the work of Eric Celeste, who has taken the United States Census Cartographic Boundary Files and converted them to GeoJSON using the MyGeoData vector converter.
All CSVs were loaded and cleaned using Jupyter Notebook. These cleaned dataframes were loaded to SQLite. In order to allow an automap and class-based queries, our team used DB Browser for SQLite to quickly identify the primary key for each table. Separately, the JSON of the U.S. and State Trends on Teen Births dataset and GeoJSONs of the state and county boundaries were needed to complete the map visualizations; these are stored separate to the SQLite in directly in the repo.
For more information on prior data cleaning, please see the README.md of Project-2.
- Chart.js
- CSS
- D3.js
- DB Browser for SQLite
- Heroku
- HTML
- Leaflet.js
- Pandas
- Plotly
- Scikit-Learn
- SQLAlchemy
- SQLite
Once the SQLite database was ready, we proceeded with organizing the flow of information on our website according to the following structure:
The cleaned data was stored in a SQLite database. We used a Flask application with SQLAlchemy to query the SQLite and serve the data. The data from the Flask app was prepared with Jinja, and the JavaScript used that data for the visualizations. This website was deployed using Heroku and connected to this GitHub repository.
Pickle was used to serialize the machine learning model to make it usable within the Flask application. Then, a HTML form was linked to a POST route to take user input placed into the HTML calculator to predict the birth rate for any given county. This calculator is prepopulated using a specific county's data—matched using the FIPS code—selected from the tooltip of any county-based visualization on the website.
This choropleth map visualizes the average teen birth rate per 1,000 females aged 15-19 for each state or county from 2003 to 2018. This map reflects a concentration of higher birth rates in the South and central areas of the U.S. as well as lower birth rates particularly in the Northeast.
This choropleth map displays the number of publicly funded health clinics available per county during the years 2010 and 2015. Over the 5 years, 2,300 new clinics were opened nationally, with the greatest increase in availability in California with 145 new clinics and the greatest number of closures in Iowa at 17.
This visualization charts the teen birth rates from 2003 to 2018, separated by ages 15-17 and 18-19 and selectable by state. It can be observed from this chart that the birth rate amongst the teens aged 18-19 years is higher than that of the teens aged 15-17 years; we believed this was an important observation as it may provide a counterpoint to a common bias in regards to this topic. Media often focuses on early teen pregnancies, however the data suggests that these young pregnancies are not representative of the majority of teen pregnancies.
This visualization charts each state’s teen birth rate per 1,000 females aged 15-19 by year from 2003 to 2018. This chart reflects a universal trend of decreasing teen birth rates during this range of years. According to the Pew Research Center, the teen birth rate in 2018 was less than half of what it had been in 2008. The Pew Research Center noted that, while the teen birth rate has been on a steep decline since the early 1990s, the decline accelerated after the onset of the Great Recession in 2007.
This visualization charts the change in the teen birth rate per 1,000 females aged 15-19 from 2003 to 2018, organized by state in the top chart and county in the bottom chart. States and counties with the least and greatest amount of change have been pre-selected. Although most counties reflect the overall trend of declining teen birth rates across the U.S., that change is not true of every county. Counties that experienced an increase in their teen birth rates warrant further investigation; preliminary examination indicated that an increase would occur more often in smaller communities.
If time allowed, our team would have liked to address the following:
- Revise the calculator to be more user-friendly, including limiting user input to the most influential parts of the model.
- Implement further data on other contributing factors, such as transportation availability, regional health education, and client residency/distance travelled.
- Optimizing SQLAlchemy requests to reduce queries initiated while loading, and reduce duplicate code throughout the project to avoid versions issues.
- Utilize Cloud services, such as AWS, to store and retrieve our data, allowing us to offload our SQLite and GeoJSON/JSON files from the project’s repo.