National GIS Data

A collection of spatial datasets designed to support public health spatial analyses and visualizations.

Modified

April 23, 2026

Want to know more about recent changes? Check out the recent updates.

500 Cities
Health Outcomes
Description: The 500 Cities Project provided model derived estimates for chronic disease risk factors, health outcomes, and clinical preventive services use for the 500 largest US cities.
Time Frame: Year; 2016 to 2019
Spatial Scale: City and Census Tract
Format: Tables and Shapefiles
Source: Centers for Disease Control and Prevention (CDC)
Original Repository: All Years (Look for datasets labeled GIS Friendly Format)
Living Atlas: 2016 2017 2018 2019

This project reported city- and census tract-level data and used small area estimation methods to obtain 27 chronic disease measures for the 500 largest American cities. Dataset includes estimates for 27 measures (definitions here):

  • Chronic disease-related unhealthy behaviors (5),
  • Health outcomes (13), and
  • Use of preventive services (9).

These estimates can be used to identify emerging health problems and to inform development and implementation of 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.

American Community Survey (ACS) 5-year Estimates
Census
Description: “The American Community Survey (ACS) is an ongoing survey that provides vital information on a yearly basis about our nation and its people. Information from the survey generates data that help determine how more than $675 billion in federal and state funds are distributed each year.” (US Census Bureau)
Time Frame: 5 Years; 2009 to 2024
Spatial Scale: Nation, State (including DC and Puerto Rico), Metropolitan Area, Congressional District, County, Place, Census Tract and Block Group
Format: Feature Layers
Source: US Census Bureau
Original Repository: All Years
Living Atlas: Current

The Living Atlas hosts the current ACS 5-year estimates in a series of several features grouped by topic. Each topic is hosted as both boundaries and centroids. Topics may contain single or multiple ACS tables Layers can be accessed and used within your GIS workflows, for example, make a map about your community.

If you are looking for historical data, the census.gov website can be difficult to go through. Census Reporter can make it easier to find and download tables at various spatial scales.

CMS Approved Facilities - FQHC, RHC, CAH
Facilities
Description: This service provides information on Center of Medicare & Medicaid Services (CMS) approved facilities such as federally qualified health centers (FQHCs), rural health clinics, critical access hospitals and nursing facilities.
Time Frame: Updated on Unknown Basis; Current
Spatial Scale: Point
Format: Feature Service
Source: Health Resources & Services Administration (HRSA)
Original Repository: Current (Additional Information)
Living Atlas: N/A

This is the “Provider of Service” extract from the Quality Improvement Evaluation System (QIES) database maintained by the Centers for Medicare & Medicaid Services (CMS). These data include provider number, name, and address and characterize the participating institutional provider (including hospitals, skilled nursing facilities, home health agencies, and other types of facilities).

Add to an ArcGIS Project by using “Data from Path” and paste the above URL as the server to use. Export using Feature Class to Feature Class.

Cancer Statistics - Data Visualizations
Health Outcomes
Description: The US Cancer Statistics Data Visualizations tool provides incidence, prevalence, and mortality estimates for all sites and specific cancer type.
Time Frame: 1 year or 5 years; 1999 to 2022
Spatial Scale: State, County, and Congressional Districts
Format: Current year data is available as a CSV from the Data Visualizations websites. Prior years data is available as ASCII files.
Source: Centers for Disease Control and Prevention (CDC)
Original Repository: All Years Most Current Year Visualizations
Living Atlas: N/A

Cancer statistics are available by site, sex, race/ethnicity, and age. County-level data can be found in the BYAREA_COUNTY.txt files and state-level data can be found in the BYAREA.txt files.

Note: Historical cancer statistics files are in ACSII delimited format. Although ASCII is not a common file type, you should be able to add these tables to ArcGIS Pro as you would with any other file. Additionally, the files are in long format, which is not ideal for most forms of GIS analysis. You will likely find it easier to rearrange the data in some other software before importing to ArcGIS Pro.
Climate & Economic Justice Screening Tool (CEJST)
Environment
Description: Identifies communities that experience disadvantages due to a combination of environmental and socioeconomic factors. It assists federal agencies in distributing money to improve climate and economic fairness.
Time Frame: Updated on Unknown Basis; Current
Spatial Scale: Census Tract
Format: CSV and Shapefile
Source: Council on Environmental Quality (CEQ)
Original Repository: Original Website Backup: v2.0
Living Atlas: v1.0 Justice 40 Tracts

This dataset focuses on highlighting tracts that are disadvantaged with respect to climate and economic justice. It contains over 100 different measures of burden in addition to aggregate indicators of burden. Burden is organized into the following categories:

  • Climate Change
  • Energy
  • Health
  • Housing
  • Legacy Pollution
  • Transportation
  • Water and wastewater
  • Workforce development

Note: This resource has been since taken down. An archive of the original website along with version two is being hosted by the Environmental Data and Governance Initiative.
County Health Rankings & Roadmaps
Health Outcomes
Description: Provides information on health outcomes and health factors for all 50 states
Time Frame: Year; 2010 to 2024
Spatial Scale: County
Format: CSV and Shapefiles
Source: Robert Wood Johnson Foundation and the University of Wisconsin Population Health Initiative
Original Repository: 2010 to 2023 2024 or 2025
Living Atlas: 2018 2019 to 2025

This dataset offers county level estimates of health outcomes and risk factors. Estimates help identify ares requiring improvement and guide the creation and use of effective, focused health interventions. As a result of the difficulty in finding local intervention effects, users should be careful when using these figures to judge programs or policies.
County Typology Codes
Rurality
Description: The US Department of Agriculture Economic Research Service “County Typology Codes contains a set of Economic Typology codes based on the industrial composition of nonmetropolitan (nonmetro) counties and a set of Demographic Typology Codes based on demographic characteristics of interest to rural policymakers and researchers.”
Time Frame: Year; 1979, 1986, 1989, 2004, 2015, 2025
Spatial Scale: County
Format: CSV and XLXS
Source: US Department of Agriculture (USDA)
Original Repository: All Years
Living Atlas: N/A

Economic Typology Code designations include:

  • High Farming
  • High Mining
  • High Manufacturing
  • High Government
  • Nonspecialized
  • Industry Dependence

Demographic Typology Code designations include:

  • Low Post-SecondaryEducation
  • Low Employment
  • Population Loss
  • Housing Stress
  • Retirement Destination
  • Persistent Poverty
Division for Heart Disease and Stroke Prevention - Heart Disease and Stroke Mortality
Health Outcomes
Description: Heart Disease and Stoke Mortality
Time Frame: Three year average from 2005-2007 to 2021-2023
Spatial Scale: States, Counties
Format: Tables
Source: Centers for Disease Control and Prevention (CDC) Division for Heart Disease and Stroke Prevention
Original Repository: Interactive Data Atlas
Living Atlas: All Years

Offers Heart Disease and Stroke mortality data obtained from the National Vital Statistics System. Data can be stratified by various demographic groups. The Interactive Atlas of Heart Disease and Stroke offers a way to visualize, export, and generate reports from heart disease and stroke mortality data, as well as data regarding…

  • Prevalence
  • Risk Factors
  • Social, Economic, Environmental variables
  • Demographics
  • Health Care Delivery and Insurance
  • Health Care Costs
Environmental Justice Index (EJI)
Environment
Description: A list of all the measures of environmental justice in the United States. This helps communities find and fix environmental injustices, with a focus on vulnerable groups that are gripped by health risks in the environment.
Time Frame: Year; 2022 & 2024
Spatial Scale: Nation, State, County, and Census Tract
Format: CSV and Geodatabase
Source: Centers of Disease Control and Prevention (CDC)
Original Repository: All years
Living Atlas: N/A

The EJI is an aggregate measure of environmental burden that incorporates data from the Census Bureau, Environmenatal Protection Agency, Mine Safety and Health Administation and Centers of Disease Control and Prevention. The index measure is broken down into the modules: Environmental Burden, Social Vulnerability, and Health Vulnerability which are formed by 36 environmental, social, and health factors. The Environmental Burden and Social Vulnerability burden modules also form the Social-Environmental Ranking (SER), which aims to measure distributive and procedural environmental justice factors.
Federal Office of Rural Health Policy Rural Designation
Rurality
Description: The Federal Office of Rural Health Policy Rural Designation combines Rural-Urban Commuting Area (RUCA) codes and the Road Ruggedness Scale (RRS) to create a binary rural classification.
Time Frame: Year; 2025
Spatial Scale: County, Census Tract, and ZIP Code approximations
Format: Excel
Source: Health Resources & Services Administration (HRSA)
Original Repository: 2025
Living Atlas: N/A

HRSA defines rural as the following:

  • Non-metropolitan counties
  • Outlying metropolitan counties with no population from an urban area of 50,000 or more people
  • Census tracts with RUCA codes 4-10 in metropolitan counties
  • Census tracts of at least 400 square miles in area with population density of 35 or fewer people per square mile with RUCA codes 2-3 in metropolitan counties
  • Census tracts with RRS 5 and RUCA codes 2-3 that are at least 20 square miles in area in metropolitan counties
Federally Qualified Health Center Service Delivery and Look-Alike Sites
Facilities
Description: List of federally-funded health centers that provide health services.
Time Frame: Updated Daily; Current
Spatial Scale: Point
Format: CSV with Address and X/Y
Source: Health Resources & Services Administration (HRSA)
Original Repository: Current
Living Atlas: N/A

Health centers are community-based and consumer-run organizations that serve populations with limited access to health care. These include low-income populations, the uninsured, those with limited English proficiency, migratory and seasonal agricultural workers, individuals and families experiencing homelessness, and those living in public housing.
Grocery Gap Atlas
Facilities
Description: The Grocery Gap Atlas produces food access and market concentration estimates for grocery stores.
Time Frame: Year; 2023
Spatial Scale: Tract
Format: CSV and XLXS
Source: Rural Advancement Foundation International-USA (RAFI-USA) and the Open Spatial Lab at the Data Science Institute at the University of Chicago
Original Repository: 2023
Living Atlas: N/A

This dataset offers tract level estimates of food access and market concentration. Food access is using a gravity model with a floating catchment area (FCA) and market concentration is calculated using the Herfindahl-Hirschman Index (HHI).

NOTE: Food access is calculated using euclidian distance. Service areas for grocery stores are calculated using “distance ranges of 5 to 20 minutes driving time with average area traffic, based on reported ranges of how far people are willing to travel in the USDA FoodAPS survey”.
Healthcare Facilities of the Indian Health Service (IHS)
Facilities
Tribal
Description: Point-level representation of the locations of IHS Facilities in the United States
Time Frame: Updated on Unknown Basis; Current
Spatial Scale: Point
Format: Feature Service
Source: Indian Health Service (IHS)
Original Repository: Current
Living Atlas: N/A

The IHS is an agency within the Department of Health and Human Services responsible for providing federal health services to American Indians and Alaska Natives. These services include hospitals, behavioral health facilities, health centers, dental clinics, health stations, Alaska Village Clinics and other services. The IHS is the principal federal health care provider and health advocate for Indian people, and its goal is to raise their health status to the highest possible level. The IHS provides a comprehensive health service delivery system for American Indians and Alaska Natives who are members of 566 federally recognized Tribes across the US.
Mapping Medicare Disparities
Health Outcomes
Description: Health outcomes measures to map Medicare disparities
Time Frame: Updated on Unknown Basis; Current
Spatial Scale: State/Territory, County, Tract (depending on measure)
Format: CSV
Source: Center of Medicare & Medicaid Services
Original Repository: Current (date listed)
Living Atlas: N/A

Composed of multiple tools which display disparities through three views:

  • Population - “The MMD interactive tool contains health outcome measures for disease prevalence, costs, hospitalization for 60 specific chronic conditions, emergency department utilization, readmissions rates, mortality, preventable hospitalizations, and preventive services.”
  • Hospital - “The MMD interactive map hospital tool identifies area of disparities between hospital quality and cost of care. It allows for a way to compare measures at the hospital, county, state, territory, and national levels”
  • Social Determinants of Health - “This addition to the MMD tool identifies areas of disparities by key Social Determinant of Health (SDOH) domains and measures”
Multidimensional Deprivation Index (MDI)
Census
Risk Factors
Description: “The Multidimensional Deprivation Index (MDI) is a new research measure intended to complement, not replace, the Official Poverty Measure or Supplemental Poverty Measure. The MDI has six dimensions: standard of living, education, health, economic security, housing quality, and neighborhood quality. This report presents estimates of poverty using the official definition of poverty and estimates of deprivation using the MDI based on information collected primarily in the American Community Survey.”
Time Frame: Mixed; 2010 to 2019; 2017
Spatial Scale: State and County
Format: Shapefile
Source: US Census Bureau
Original Repository: 2010 to 2019 2017
Living Atlas: N/A

MDI value is equal to the percent of households in that region that qualify as “deprived.” Can be treated as an exposure value. A composite measure based on six dimensions:

  • Neighborhood Quality
  • Standard of Living
  • Education
  • Health
  • Economic Security
  • Housing Quality

Cannot map by individual dimension.
Population Level Analysis and Community Estimates (PLACES)
Health Outcomes
Description: The PLACES Project replaces the 500 Cities Project and provides model-based population-level analysis and community estimates for the entire US at several spatial scales
Time Frame: Year; 2019 to 2025
Spatial Scale: Counties, Places, ZCTAs, and Census Tracts
Format: Tables and Shapefiles
Source: Centers for Disease Control and Prevention (CDC)
Original Repository: All Years
Living Atlas: Current

This project reported city- and census tract-level data and used small area estimation methods to obtain 29 chronic disease measures for the United States.

Dataset includes estimates for 29 measures (definitions here):

  • Chronic Disease Related Health Outcomes (13)
  • Prevention Measures (9)
  • Health Risk Behaviors (4)
  • Disability (7)
  • Health Status (3)

These estimates can be used to identify emerging health problems and to inform development and implementation of 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.
Rural-Urban Commuting Area (RUCA)
Rurality
Description: The rural-urban commuting area (RUCA) codes classify US census tracts using measures of population density, urbanization, and daily commuting. Also approximated at ZIP code level.
Time Frame: Year; 1990, 2000, 2010, and 2020
Spatial Scale: County level representation of counties that are defined as PRCDAs/CHSDA
Format: CSV with GEOIDs
Source: US Department of Agriculture (USDA) Economic Research Service
Original Repository: All Years
Living Atlas: N/A

The classification contains two levels. Whole numbers (1-10) delineate metropolitan, micropolitan, small town, and rural commuting areas based on the size and direction of the primary (largest) commuting flows. These 10 codes are further subdivided based on secondary commuting flows, providing flexibility in combining levels to meet varying definitional needs and preferences.
Rural-Urban Continuum Codes (RUCC)
Rurality
Description: The rural-urban continuum codes (RUCC) classify US counties by their degree of urbanization and adjacency to a metro area.
Time Frame: Year; 1974, 1983, 1993, 2003, 2013, and 2023
Spatial Scale: County
Format: CSV and Excel
Source: US Department of Agriculture (USDA) Economic Research Service
Original Repository: All Years
Living Atlas: N/A

The designation of counties as metro or nonmetro is based on the Office of Management and Budget. These metro and nonmetro designations are further subdivided in is further subdivided into three metro and six nonmetro categories.
Shortage Areas (HPSAs and MUA/Ps)
Facilities
Description: Facility, population, and geographic boundaries for Health Professional Shortage Areas (HPSAs) and Medically Underserved Areas/Populations (MUA/Ps).
Time Frame: Updated Daily; Current
Spatial Scale: Mixed (Point, Tract, County Subdivision, County)
Format: Shapefile and Feature Service
Source: Health Resources & Services Administration
Original Repository: Current
Living Atlas: N/A

HRSA’s Bureau of Health Workforce (BHW) develops shortage designation criteria and uses them to decide whether or not a geographic area or population group is a Health Professional Shortage Area (HPSA), Medically Underserved Area (MUA), or Medically Underserved Population (MUP). For HPSAs, scores range from 1 to 25 for primary care and mental health, 1 to 26 for dental health. The higher the score, the greater the priority. HPSAs may have shortages of primary medical care, dental, or mental health providers; may be urban or rural areas; population groups; or medical or other public facilities.
Small Area Health Insurance Estimate (SAHIE) Program
Census
Risk Factors
Description: Offers estimates of health insurance coverage in countries and states throughout the United States. It aids in the identification of locations with large uninsured populations, as well as policy-making and resource allocation.
Time Frame: Mixed; 2000, 2001, 2005 to 2007, 2008 to 2023
Spatial Scale: State and County
Format: CSV and Shapefile
Source: US Census Bureau
Original Repository: All Years
Living Atlas: N/A

SAHIE estimates are available for several demographic groups. These estimates aid in identifying regions with a significant number of individuals without health insurance coverage.
Small Area Income and Poverty Estimates (SAIPE) Program
Census
Risk Factors
Description: Offers yearly estimates of income and poverty information for every school district, country and state in the United States.
Time Frame: Year; 1989 to 2023
Spatial Scale: State, County, and School District
Format: Tables
Source: US Census Bureau
Original Repository: All Years
Living Atlas: N/A

This research presents yearly estimates of income and poverty data, encompassing:

  • Total number of people in poverty
  • Number of children under age 18 in poverty
  • Number of related children ages 5 to 17 in families in poverty
  • Median household income

Produced for every school district, county, and state, these figures help pinpoint locations with high poverty rates, which in turn informs policy choices and the creation of targeted solutions.
Social Vulnerability Index (SVI)
Risk Factors
Description: The Social Vulnerability Index uses 15 US census variables to help local officials identify communities that may need support before, during, or after disasters.
Time Frame: Year; 2000, 2010, 2014, 2016, 2018, 2020, 2022
Spatial Scale: County and Census Tract
Format: CSV and Geodatabase
Source: Centers for Disease Control and Prevention (CDC)
Original Repository: All Years
Living Atlas: 2018 2020 2022

Ranking by social vulnerability. Can look at rank within a state or within the entire US. A composite measure based on four dimensions:

  • Housing Type and Transportation
  • Household Composition and Disability
  • Socioeconomic Status
  • Minority Status and Language

Can also map by individual dimension.
Tribal Census Tract Boundaries
Census
Tribal
Description: Polygons representing individual tribal census tracts throughout the United States.
Time Frame: Year; 2007 to 2025
Spatial Scale: Tribal Tract
Format: Shapefile
Source: US Census Bureau
Original Repository: All Years
Living Atlas: N/A

Tribal census tracts are small statistical subdivisions of a reservation and off- reservation trust land. Their primary purpose is the same as census tracts: the presentation of statistical data. However, rather than nesting within a county, tribal census tracts nest within a single federally recognized American Indian area, providing coverage across all federally recognized American Indian reservations and off-reservation trust lands. Tribal census tracts have population criteria identical to county-based census tracts.

If you would like attributes associated with these Tribal Census Tract Boundaries, you can visit https://data2.nhgis.org/main. Select Geographic levels -> Native American/Alaskan/Hawaiian -> Tribal Census Tracts. You can then select years, topics, and datasets to filter ACS Tables

Urban Influence Codes (UIC)
Rurality
Description: The Urban Influence Codes (UIC) classify US counties by the size of their neighboring metropolitan areas and micropolitan status to identify the hierarchical economic influence and opportunities provided by nearby urban centers.
Time Frame: Year; 1993, 2003, 2013, and 2024
Spatial Scale: County
Format: CSV and Excel
Source: US Department of Agriculture (USDA) Economic Research Service
Original Repository: All Years
Living Atlas: N/A

The Urban Influence Codes (UIC) focuses on how a county’s economic opportunities are shaped by its proximity to large metropolitan areas. While other systems might just look at how many people live in a county, the UIC looks outward to see if that county “influenced”.

The system breaks all US counties into nine distinct categories based on their size and whether they are physically adjacent to a metro area. It separates counties into Metropolitan, Micropolitan (at least 10,000 people), and Noncore (the most rural areas).
Urban-Rural Classification Scheme
Rurality
Description: The NCHS Urban-Rural Classification Scheme is a six-level categorization system used to analyze health differences across US counties based on their level of urbanization.
Time Frame: Year; 1990, 2006, 2013, and 2023
Spatial Scale: County
Format: Excel and SAS
Source: Centers for Disease Control & Prevention (CDC) National Center for Health Statistics (NCHS)
Original Repository: All Years
Living Atlas: N/A

The classification scheme assignes every US county to one of six distinct categories, allowing for the identification and tracking of health disparities that may vary significantly between metropolitan hubs and rural towns.

The scheme is divided into two primary sections based on Office of Management and Budget (OMB) designations:

  • Metropolitan Counties: These are split into four levels: Large Central, Large Fringe (suburban), Medium, and Small.
  • Nonmetropolitan Counties: These are split into two levels: Micropolitan (centered around a smaller city) and Noncore (rural areas).
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