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The percent without health insurance of District of Columbia, DC was 7.00% for 18 to 64, all races, both sexes and all income levels in 2014. The percent without health insurance of Loudoun County, VA was 8.90% for 18 to 64, all races, both sexes and all income levels in 2014.

Percent Uninsured

Percent Uninsured by Income Level

Percent Uninsured by Race

The Small Area Health Insurance Estimate (SAHIE) estimates health insurance coverage from the American Community Survey (ACS).

Above charts are based on data from the Small Area Health Insurance Estimate | ODN Dataset | API - Notes:

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to http://opendatanetwork.com. Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g. http://opendatanetwork.com/region/1600000US5363000/Seattle_WA

Health and Health Insurance Datasets Involving District of Columbia, DC or Loudoun County, VA

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    Number Of People Without Health Insurance All States 2005-2012

    opendata.utah.gov | Last Updated 2019-04-19T06:44:33.000Z

    Number Of People Without Health Insurance All States 2005-2012

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    National Immunization Survey Adult COVID Module (NIS-ACM): COVIDVaxViews| Data | Centers for Disease Control and Prevention (cdc.gov)-Archived

    data.cdc.gov | Last Updated 2024-01-24T15:02:36.000Z

    National Immunization Survey Adult COVID Module (NIS-ACM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent, and other behavioral indicators, by demographics and other characteristics.

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    Drug and Alcohol Treatment Facilities May 2018 County Drug and Alcohol Programs

    data.pa.gov | Last Updated 2022-10-17T19:15:44.000Z

    This dataset reports the name, street address, city, county, zip code, telephone number, latitude, and longitude of Pennsylvania Department of Drug and Alcohol Programs (DDAP) drug and alcohol treatment facilities in Pennsylvania as of May 2018. The primary difference between the three types of treatment facilities is their funding. Centers of Excellence (COEs) were grant funded by the Department of Human Services, PacMATs were grant funded by the Department of Health, and all other facilities are funded by either billing insurance or billing the county in the case of uninsured clients. Programmatically, COEs differ from the other types because they are designed to serve as “health homes” for individuals with Opioid Use Disorder (OUD). This means that the care coordination staff at the COE is charged with coordinating all kinds of health care (physical and behavioral health) as well as recovery support services. They do this by developing hub-and-spoke networks with other healthcare providers and other sources for recovery supports, such as housing, transportation, education and training, etc. All COEs are required to accept Medicaid. PacMATs also operate in a hub-and-spoke model, but it is different from COEs. PacMATs endeavor to coordinate the provision of Medication Assisted Treatment (MAT) by identifying a core hub of physicians in a health system that work with other providers in the health system (spokes) to train them about the safe and effective provision of MAT so that there are more providers in a health system that are able to confidently prescribe various forms of MAT. I do not know whether all PacMATs are required to accept Medicaid as a term of their receipt of the grant, but I do know that all currently designated PacMATs are health systems that do accept Medicaid. PacMAT services have been advertised as being available to all people regardless of insurance type, so I assume this means they are required to serve Medicaid clients, commercially insured clients, and uninsured clients. In the PacMAT program the Hub is supported right now by grant funding (in the future funding such as a per patient/per month capitated rate) and the spokes bill insurance (both Medicaid and Commercial) DDAP facilities may also be designated as COEs and/or PacMATs. If they are, it means they applied for a specific grant fund and have committed to carrying out the activities of the grant described above. To be clear, DDAP does not run any treatment facilities; they license them. These can be MAT providers such as methadone clinics, providers of outpatient levels of care (i.e., more traditional drug and alcohol counseling services) or inpatient levels of care, such as residential rehabilitation programs. Every facility is different in terms of the menu of services it provides. Every facility also gets to decide what forms of payment they will accept. Many accept Medicaid, but not all do. Some only accept private commercial insurance. Some accept payment from the county on behalf of uninsured clients. And some charge their clients cash for services.

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    National Immunization Survey Adult COVID Module (NIS-ACM): Trends in Vaccination Status and Intent

    data.cdc.gov | Last Updated 2023-08-03T20:51:54.000Z

    National Immunization Survey-Adult COVID Module (NIS-ACM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent by week for the national-level view, and by month for the jurisdiction-level view.

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    National Immunization Survey Child COVID Module (NIS-CCM): Vaccination Status and Intent by Demographics | Data | Centers for Disease Control and Prevention (cdc.gov)

    data.cdc.gov | Last Updated 2023-08-03T18:27:46.000Z

    National Immunization Survey Child COVID Module (NIS-CCM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent, and other behavioral indicators, by demographics and other characteristics.

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    National Immunization Survey Adult COVID Module (NIS-ACM): Vaccination Status and Intent by Demographics

    data.cdc.gov | Last Updated 2023-08-03T20:51:46.000Z

    National Immunization Survey Adult COVID Module (NIS-ACM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent by demographics. Following collection of August 2021 survey data, an error in data processing led to incorrect categorization of some survey respondents; some respondents who should have been categorized as MSA: Principal City instead were categorized as MSA: Non-Principal City. Data downloaded during the period September 12, 2021 through September 30, 2021 may have incorrect estimates by MSA status, SVI of county of residence, and political leaning of county of residence.

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    National Immunization Survey Adult COVID Module (NIS-ACM): Trends in Behavioral Indicators Among Unvaccinated People

    data.cdc.gov | Last Updated 2023-08-03T20:52:18.000Z

    National Immunization Survey-Adult COVID Module (NIS-ACM): CDC is providing information on COVID-19 vaccine confidence to supplement vaccine administration data. Trends in behavioral indicators represent the percent of unvaccinated people responding to each of the indicators by intent status and by week for the national-level view, and by month for the jurisdiction-level view.

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    SDOH Measures for County, ACS 2017-2021

    data.cdc.gov | Last Updated 2023-12-04T16:59:34.000Z

    This dataset contains county-level social determinants of health (SDOH) measures from the American Community Survey 5-year data for the entire United States—50 states and the District of Columbia. Data were downloaded from data.census.gov using Census API and processed by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. These measures complement existing PLACES measures, including PLACES SDOH measures (e.g., health insurance, routine check-up). These data can be used together with PLACES data to identify which health and SDOH issues overlap in a community to help inform public health planning. To access spatial data, please use the ArcGIS Online service: https://cdcarcgis.maps.arcgis.com/home/item.html?id=d51009ea78b54635be95c6ec9955ec17.

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    NCHS - Teen Birth Rates for Age Group 15-19 in the United States by County

    data.cdc.gov | Last Updated 2022-04-08T19:13:53.000Z

    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).

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    Weekly Respiratory Virus Vaccination Data, Children 6 Months-17 Years and Adults 18 Years and Older, National Immunization Survey

    data.cdc.gov | Last Updated 2024-05-24T16:01:50.000Z

    The weekly respiratory virus vaccination data come from the National Immunization Survey-Adult COVID Module (NIS-ACM), National Immunization Survey-Child COVID Module (NIS-CCM), and the National Immunization Survey-Flu (NIS-Flu). The NIS-ACM provides data on Influenza (flu), COVID-19, and RSV vaccination for adults aged ≥18 years in the United States. The NIS-CCM provides data on COVID-19 vaccination for children aged 6 months-17 years in the United States. The NIS-Flu provides data on Influenza vaccination for children aged 6 months-17 years in the United States National Immunization Survey data are collected by telephone interview using a random-digit-dialed sample of cellular telephone numbers stratified by state, the District of Columbia, five local jurisdictions (Bexar County TX, Chicago IL, Houston TX, New York City NY, and Philadelphia County PA), and Guam, Puerto Rico, and the United States Virgin Islands. Data are weighted to represent the non-institutionalized United States population and mitigate possible bias that can result from incomplete sample frame (exclusion of households with no phone service or only landline telephones) or non-response. All responses are self-reported, or reported by a parent for children 6 months-17 years. For more information about the surveys, see https://www.cdc.gov/vaccines/imz-managers/nis/about.html#current-surveys. Estimates should be interpreted with caution when there is a small sample size or wide confidence interval.