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The population count of St. Louis County, MO was 998,684 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.

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

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Demographics and Population Datasets Involving St. Louis County, MO

  • API

    Social Vulnerability Index for Virginia by Census Tract, 2018

    data.virginia.gov | Last Updated 2023-05-22T14:49:26.000Z

    "ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) created Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI or simply SVI, hereafter) to help public health officials and emergency response planners identify and map the communities that will most likely need support before, during, and after a hazardous event. SVI indicates the relative vulnerability of every U.S. Census tract. Census tracts are subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking." For more see https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html

  • API

    Social Vulnerability Index 2018 - United States, county

    data.cdc.gov | Last Updated 2022-02-14T14:19:58.000Z

    ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) created Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI or simply SVI, hereafter) to help public health officials and emergency response planners identify and map the communities that will most likely need support before, during, and after a hazardous event. SVI indicates the relative vulnerability of every U.S. Census tract. Census tracts are subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking. In addition to tract-level rankings, SVI 2018 also has corresponding rankings at the county level. Notes below that describe “tract” methods also refer to county methods.

  • API

    Virginia Social Vulnerability Index (SVI) (2018) by Census Tract (Datathon)

    data.virginia.gov | Last Updated 2023-05-22T14:58:02.000Z

    SVI indicates the relative vulnerability of every U.S. Census tract. Census tracts are subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking.

  • API

    Social Vulnerability Index 2018 - United States, tract

    data.cdc.gov | Last Updated 2022-02-14T14:22:44.000Z

    ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) created Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI or simply SVI, hereafter) to help public health officials and emergency response planners identify and map the communities that will most likely need support before, during, and after a hazardous event. SVI indicates the relative vulnerability of every U.S. Census tract. Census tracts are subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking. In addition to tract-level rankings, SVI 2018 also has corresponding rankings at the county level. Notes below that describe “tract” methods also refer to county methods.

  • API

    Teen Births By ZIP Code 2013

    impact.stlouisco.com | Last Updated 2016-02-05T22:00:14.000Z

    This dataset includes annual counts and rates of live births to girls ages 10-19 who are residents of St. Louis County. Data is collected, maintained and published by the Missouri Department of Health & Senior Services (HSS). Information on each birth and the mothers is gathered from birth certificates. HSS only reports the number of live births along with other health, social and demographic variables through the Missouri Information for Community Assessment (MICA) system. Rates of live births is calculated using both MICA and U.S. Census population estimates. The population estimates are organized by ZIP Code Tabulation Areas (ZCTA). In very rare instances do the ZCTAs not consistently overlap with the postal ZIP Code areas. Live Births Per 1,000 Teen Girls for a specified time period is calculated as: (# Live Births to Girls Ages 10-19/Total Population of Girls Ages 10-19) x 1,000.

  • API

    Births to Teen Girls Ages 10-19

    impact.stlouisco.com | Last Updated 2016-02-05T18:03:29.000Z

    This dataset includes annual counts and rates of live births to girls ages 10-19 who are residents of St. Louis County. Data is collected, maintained and published by the Missouri Department of Health & Senior Services (HSS). Information on each birth and the mothers is gathered from birth certificates. HSS only reports the number of live births along with other health, social and demographic variables through the Missouri Information for Community Assessment (MICA) system. Rates of live births is calculated using both MICA and U.S. Census data. Live Births Per 1,000 Teen Girls for a specified time period is calculated as: (# Live Births to Girls Ages 10-19/Total Population of Girls Ages 10-19) x 1,000.

  • API

    2010 Census/ACS Basic Block Group Data

    data.kcmo.org | Last Updated 2021-11-12T14:15:42.000Z

    basic characteristics of people and housing for individual 2010 census block groups

  • API

    2010 Census/ACS Detailed Block Group Data

    data.kcmo.org | Last Updated 2021-11-12T14:22:17.000Z

    detailed characteristics of people and housing for individual 2010 census block groups

  • API

    2022 Municipal Census - Enumeration Areas

    data.strathcona.ca | Last Updated 2022-11-02T16:33:57.000Z

    Table representing household census data aggregated to Enumeration Area (EA) gathered in the 2022 Municipal Census. The municipal census was conducted in the spring of 2022. The census gathers information such as the number of people who live in the home, their ages and gender; the type of dwelling; and length of residency in Strathcona County. An up-to-date census count ensures the County receives the maximum grant dollars based on population. These dollars go toward municipal programs such as roads, transit, and community and family services. Census information is also used to plan for future services and programs. The GIS Branch may use the household data for analysis; however, areas containing less than 50 people will not be reported. This practice is in line with Statistics Canada reporting. The data is not available directly to Strathcona County staff but is available upon request and permission from LLS. The data is not shared publicly at the household level.

  • API

    Point In Time Homeless Survey Data

    data.sonomacounty.ca.gov | Last Updated 2019-07-12T18:26:35.000Z

    The County of Sonoma conducts an annual homeless count for the entire county. The survey data is derived from a sample of about 600 homeless persons countywide per year. The resulting information is statistically reliable only for the county as a whole, not for individual locations. The exception is the City of Santa Rosa, where the sample taken within the city is large enough to be predictive of the overall homeless population in that city.