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The population rate of change of District of Columbia, DC was 1.80% in 2018.

Population

Population Change

Above charts are based on data from the U.S. Census American Community Survey | 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.

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Demographics and Population Datasets Involving District of Columbia, DC

  • API

    Virginia Employment Status of the Population by Sex by Race and by Age by Year

    data.virginia.gov | Last Updated 2022-12-09T15:15:31.000Z

    2004 to 2021 Virginia Employment Status of the Civilian Non-Institutional Population by Sex, by Race, Hispanic or Latino ethnicity, and detailed by Age, by Year. Annual averages, numbers in thousands. U.S. Bureau of Labor Statistics; Local Area Unemployment Statistics, Expanded State Employment Status Demographic Data Data accessed from the Bureau of Labor Statistics website (https://www.bls.gov/lau/ex14tables.htm) Statewide data on the demographic and economic characteristics of the labor force are published on an annual-average basis from the Current Population Survey (CPS), the sample survey of households used to calculate the U.S. unemployment rate (https://www.bls.gov/cps/home.htm). For each state and the District of Columbia, employment status data are tabulated for 67 sex, race, Hispanic or Latino ethnicity, marital status, and detailed age categories and evaluated against a minimum base, calculated to reflect an expected maximum coefficient of variation (CV) of 50 percent, to determine reliability for publication. The CPS sample was redesigned in 2014–15 to reflect the distribution of the population as of the 2010 Census. At the same time, BLS developed improved techniques for calculating minimum bases. These changes resulted in generally higher minimum bases of unemployment, leading to the publication of fewer state-demographic groups beginning in 2015. The most notable impact was on the detailed age categories, particularly the teenage and age 65 and older groups. In an effort to extend coverage, BLS introduced a version of the expanded state employment status demographic table with intermediate age categories, collapsing the seven categories historically included down to three. Ages 16–19 and 20–24 were combined into a 16–24 year-old category, ages 25–34, 35–44, and 45–54 were combined into a 25–54 year-old category, and ages 55–64 and 65 and older were combined into a 55-years-and-older category. These intermediate age data are tabulated for the total population, as well as the four race and ethnicity groups, and then are evaluated against the unemployment minimum bases. The more detailed age categories continue to be available in the main version of the expanded table, where the minimum base was met. Additional information on the uses and limitations of statewide data from the CPS can be found in the document Notes on Using Current Population Survey (https://www.bls.gov/lau/notescps.htm) Subnational Data and in Appendix B of the bulletin Geographic Profile of Employment and Unemployment (https://www.bls.gov/opub/geographic-profile/home.htm).

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    COVID-19 Aggregate Cases Current Weekly County Health

    data.pa.gov | Last Updated 2023-03-23T00:55:30.000Z

    This dataset contains aggregate COVID-19 case counts and rates by date of first report for all counties in Pennsylvania and for the state as a whole. Counts include both confirmed and probable cases as defined by the Council of State and Territorial Epidemiologists (CSTE). At present, a person is counted as a case only once. Note that case counts by date of report are influenced by a variety of factors, including but not limited to testing availability, test ordering patterns (such as day of week patterns), labs reporting backlogged test results, and mass screenings in nursing homes, workplaces, schools, etc. Case reports received without a patient address are assigned to the county of the ordering provider or facility based on provider zip code. Cases reported with a residential address that does not match to a known postal address per the commonwealth geocoding service are assigned to a county based on the zip code of residence. Many zip codes cross county boundaries so there is some degree of misclassification of county. All counts may change on a daily basis due to reassignment of jurisdiction, removal of duplicate case reports, correction of errors, and other daily data cleaning activities. Downloaded data represents the best information available as of the previous day. <br> Data will be updated between 11:30 am to 1:30pm each Wednesday.

  • API

    COVID-19 Aggregate Death Data Current Weekly County Health

    data.pa.gov | Last Updated 2023-03-23T00:55:25.000Z

    This dataset contains aggregate death data at the state and county level for Pennsylvania residents. The data are displayed by county, date, death counts, averages, rates based on population. Pennsylvania statewide numbers are listed with Pennsylvania named as the county for the statewide totals. Do not add up the entire file (all rows) or counts will be duplicated. Data will be updated midafternoon each Wednesday.

  • API

    NCHS - Leading Causes of Death: United States

    data.cdc.gov | Last Updated 2022-03-30T14:26:37.000Z

    This dataset presents the age-adjusted death rates for the 10 leading causes of death in the United States beginning in 1999. Data are based on information from all resident death certificates filed in the 50 states and the District of Columbia using demographic and medical characteristics. Age-adjusted death rates (per 100,000 population) are based on the 2000 U.S. standard population. Populations used for computing death rates after 2010 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for non-census years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Causes of death classified by the International Classification of Diseases, Tenth Revision (ICD–10) are ranked according to the number of deaths assigned to rankable causes. Cause of death statistics are based on the underlying cause of death. SOURCES CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES 1. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. 2. Murphy SL, Xu JQ, Kochanek KD, Curtin SC, and Arias E. Deaths: Final data for 2015. National vital statistics reports; vol 66. no. 6. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_06.pdf.

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    Bronx Zip Population and Density

    bronx.lehman.cuny.edu | Last Updated 2012-10-21T14:06:17.000Z

    2010 Census Data on population, pop density, age and ethnicity per zip code

  • API

    PLACES: Local Data for Better Health, Census Tract Data 2022 release

    chronicdata.cdc.gov | Last Updated 2022-12-06T13:49:14.000Z

    This dataset contains model-based census tract-level estimates for the PLACES 2022 release. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. The dataset includes estimates for 29 measures: 13 for health outcomes, 9 for preventive services use, 4 for chronic disease-related health risk behaviors, and 3 for health status. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population data, and American Community Survey 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

  • API

    PLACES: Local Data for Better Health, County Data 2022 release

    chronicdata.cdc.gov | Last Updated 2022-12-06T11:09:44.000Z

    This dataset contains model-based county-level estimates for the PLACES 2022 release. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. This dataset includes estimates for 29 measures: 13 for health outcomes, 9 for preventive services use, 4 for chronic disease-related health risk behaviors, and 3 for health status. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2020 or 2019 county population estimate data, and American Community Survey 2016–2020 or 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

  • API

    PLACES: Local Data for Better Health, ZCTA Data 2022 release

    chronicdata.cdc.gov | Last Updated 2022-12-06T11:18:38.000Z

    This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates for the PLACES 2022 release. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. The dataset includes estimates for 29 measures: 13 for health outcomes, 9 for preventive services use, 4 for chronic disease-related health risk behaviors, and 3 for health status. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population data, and American Community Survey 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

  • API

    NCHS - Birth Rates for Unmarried Women by Age, Race, and Hispanic Origin: United States

    data.cdc.gov | Last Updated 2022-03-29T13:18:43.000Z

    This dataset includes birth rates for unmarried women by age group, race, and Hispanic origin in the United States since 1970. Methods for collecting information on marital status changed over the reporting period and have been documented in: • Ventura SJ, Bachrach CA. Nonmarital childbearing in the United States, 1940–99. National vital statistics reports; vol 48 no 16. Hyattsville, Maryland: National Center for Health Statistics. 2000. Available from: http://www.cdc.gov/nchs/data/nvsr/nvsr48/nvs48_16.pdf. • National Center for Health Statistics. User guide to the 2013 natality public use file. Hyattsville, Maryland: National Center for Health Statistics. 2014. Available from: http://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm. National data on births by Hispanics origin exclude data for Louisiana, New Hampshire, and Oklahoma in 1989; for New Hampshire and Oklahoma in 1990; for New Hampshire in 1991 and 1992. Information on reporting Hispanic origin is detailed in the Technical Appendix for the 1999 public-use natality data file (see (ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/DVS/natality/Nat1999doc.pdf.) All birth data by race before 1980 are based on race of the child. Starting in 1980, birth data by race are based on race of the mother.

  • API

    COVID-19 Case Surveillance Public Use Data

    data.cdc.gov | Last Updated 2023-03-07T18:02:20.000Z

    This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data. <br> <h4><b>CDC has three COVID-19 case surveillance datasets:</b></h4> - <a href="https://data.cdc.gov/Case-Surveillance/COVID-19-Case-Surveillance-Public-Use-Data-with-Ge/n8mc-b4w4">COVID-19 Case Surveillance Public Use Data with Geography</a>: Public use, patient-level dataset with clinical data (including symptoms), demographics, and county and state of residence. (19 data elements) <br> - <a href="https://data.cdc.gov/Case-Surveillance/COVID-19-Case-Surveillance-Public-Use-Data/vbim-akqf">COVID-19 Case Surveillance Public Use Data</a>: Public use, patient-level dataset with clinical and symptom data and demographics, with no geographic data. (12 data elements)<br> - <a href="https://data.cdc.gov/Case-Surveillance/COVID-19-Case-Surveillance-Restricted-Access-Detai/mbd7-r32t">COVID-19 Case Surveillance Restricted Access Detailed Data</a>: Restricted access, patient-level dataset with clinical and symptom data, demographics, and state and county of residence. Access requires a registration process and a data use agreement. (33 data elements) The following apply to all three datasets: - Data elements can be found on the COVID-19 case report form located at <a href="https://www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf">www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf</a>.<br> - Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers. - Some data cells are suppressed to protect individual privacy.<br> - The datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the current datasets. This 14-day lag allows case reporting to be stabilized and ensures that time-dependent outcome data are accurately captured.<br> - Datasets are updated monthly. <br> - Datasets are created using CDC’s <a href="https://www.cdc.gov/maso/policy/policy385.pdf">Policy on Public Health Research and Nonresearch Data Management and Access</a> and include protections designed to protect individual privacy. <br> - For more information about data collection and reporting, please see <a href="https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html">https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.</a><br> - For more information about the COVID-19 case surveillance data, please see <a href="https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html"> https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html</a><br> <h4><b>Overview</b></h4> The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the <a href="https://ndc.services.cdc.gov/search-results-year/"> Nationally Notifiable Condition List </a> and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (<a href="https://cdn.ymaws.com/www.cste.org/resource/resmgr/ps/positionstatement2020/Interim-20-ID-01_COVID-19_NO.pdf">Interim-20-ID-01</a>). CSTE updated the position statement on August 5, 2020 to clarify the interpretation of antigen detection tests and serologic test results within the case classification(<a href="https://cdn.ymaws.com/www.cste.org/resource/resmgr/ps/positionstatement2020/Interim-20-ID-02_COVID-19.pdf">Interim-20-ID-02</a>). The statement also recommended that a