Overview of all standardized data sources and combined bundles in the PopHIVE/Ingest repository. Automatically generated from repository files — last updated August 21, 2026 . View full data documentation →
standard/*.csv.gz
files. These describe the data itself — the period it covers.
standard/*.csv.gz
files: when our pipeline last wrote standardized output. It can move without any new
upstream data — for example after an
ingest.R
fix — so it reflects our processing cadence, not the publisher's.
rowsUpdatedAt
field of the metadata saved alongside
each download (
raw/<id>.json
). That is the source's own claim, so
unlike a file-based proxy it cannot be moved by a re-export of identical rows, a
metadata-only refresh, or repository housekeeping. Sources not pulled through the
Socrata API report no such timestamp; those fall back to the most recent commit that
changed a raw data file, and are marked
est.
to show the date is inferred rather than reported. A dash means neither was available.
Caveats.
Last Refreshed is a repository commit date read from the branch this page was built on, so a
branch behind
main
reports it as stale for every dataset. Latest Issue is only as current as the last time we
downloaded the dataset, since it comes from the metadata saved with that download: if a source
has not been fetched in a while, its publisher timestamp is stale too, and the gap between the
two columns understates how far behind we are. It also reflects whatever the publisher chooses
to report — some update the timestamp on a full re-publish that changes no values. The
est.
fallback dates carry the weaknesses of any file-based proxy: a publisher that re-exports
identical rows in a different order changes the file's bytes and moves the date with no new
data behind it, and like Last Refreshed they are read from the current branch.
| Dataset | Content Title | Brief Description | Subject Tags | Spatial Resolution | Age Resolution | Sex Resolution | Other Resolutions | Earliest Data | Latest Data | Time Scale | Last Refreshed | Latest Issue | Data Restrictions | Organization | Source URL | Data URL |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
abcs
|
Active Bacterial Core surveillance (ABCs) | CDC monitors invasive bacterial infections that cause bloodstream infections, sepsis, and meningitis in persons living in the community through Active Bacterial Core surveillance (ABCs), reporting IPD case counts by serotype and age group for years 1998 through 2022. This is supplemented by the CAAP (Community-Acquired Acute Pneumonia) study by Ramirez et al. (2025), which used serotype-specific urinary antigen detection (SSUAD) to identify pneumococcal serotypes causing non-invasive pneumonia in Louisville, Kentucky, extending IPD surveillance findings to the broader spectrum of pneumococcal disease. | Respiratory meningitis pneumococcal | National, State | <1, 1, 2-4, <5 years, 5-17, 5-49 years, 18-34, 18-64, 35-49, 50-64, 50+ years, 65+ | Stratified | Race/Ethnicity | 1997-12-31 | 2024-12-31 | Annual | 2026-08-18 | 2026-05-28 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
area_health_resource_file
|
Area Health Resource File (AHRF) | The Area Health Resource File (AHRF) is an annual county-level database produced by the Health Resources and Services Administration (HRSA). It aggregates data from over 50 sources including the AMA Physician Masterfile, the American Hospital Association Annual Survey, the Bureau of Health Workforce, CMS Medicare claims, the Census Bureau, and EPA air quality monitoring. The AHRF covers all U.S. counties and territories with measures of health workforce supply, health facility counts, demographics, socioeconomic conditions, health expenditures, and environmental factors. It is widely used in health services research to characterize county-level resource availability and identify shortage areas. | County access healthcare access rural | National, State, County | Not Stratified | Not Stratified | — | 1999-12-31 | 2025-12-31 | Annual | 2026-08-18 | — | Public domain. HRSA data is produced by a U.S. federal agency and is generally not subject to copyright restrictions. | Health Resources and Services Administration (HRSA) | Link | GitHub |
beam
|
BEAM Dashboard - Report Data | The CDC BEAM Dashboard reports monthly state-level counts of enteric pathogen isolates (Campylobacter, Salmonella, Shigella, STEC, and Vibrio) sequenced and reported by participating public health laboratories through the System for Enteric Disease Response, Investigation, and Coordination (SEDRIC). It includes total isolate counts, isolates linked to a recognized outbreak, and isolate rates per 100,000 population, by pathogen. | Enteric diseases Campylobacter Salmonella Shigella STEC E. coli Vibrio foodborne illness SEDRIC | National, State | Not Stratified | Not Stratified | — | 2018-01-31 | 2026-05-31 | Monthly | 2026-07-31 | 2026-06-15 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
bls_laus
|
Local Area Unemployment Statistics (LAUS) | Annual average county unemployment rate (not seasonally adjusted) from the Bureau of Labor Statistics' Local Area Unemployment Statistics (LAUS) program, covering the civilian labor force ages 16 and older. | Rural health unemployment labor force economic determinants | National, State, County | Not Stratified | Not Stratified | — | 2025-12-31 | 2025-12-31 | Annual | 2026-08-18 | — | Public domain. U.S. Bureau of Labor Statistics data are generally not subject to copyright restrictions. A registered API key (free, instant signup at https://data.bls.gov/registrationEngine/) is required to request annual-average data and to stay within reasonable daily query limits for a full county-level pull. | U.S. Bureau of Labor Statistics | Link | GitHub |
brfss
|
Behavioral Risk Factor Surveillance System (BRFSS) | The Behavioral Risk Factor Surveillance System (BRFSS) is the nation's premier system of health-related telephone surveys that collect state data about U.S. residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. Established in 1984 with 15 states, BRFSS now collects data in all 50 states, the District of Columbia, and three U.S. territories, completing more than 400,000 adult interviews each year. BRFSS provides state-specific data on health conditions including obesity, diabetes, depression, and health behaviors such as heavy drinking, physical activity, and tobacco use. Data are available by age, sex, race/ethnicity, and education level. BRFSS is a critical resource for public health surveillance and policy-making at both state and national levels. | Chronic diseases | National, State | 18-24 Years, 25-34 Years, 35-44 Years, 45-54 Years, 55-64 Years, 65+ Years | Not Stratified | — | 2011-01-01 | 2025-01-01 | Annual | 2026-07-21 | 2026-07-20 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
cdc_cfa_rt
|
CDC Epidemic Trends and Rt | Weekly estimates of the effective reproduction number (Rt) for COVID-19, Influenza, and RSV at the US national and state level. Rt represents the average number of secondary infections generated by one infectious person and is a key indicator of epidemic trajectory. Values above 1 indicate growth; below 1 indicate decline. Data include the median Rt estimate, 95% credible intervals, and the probability that Rt exceeds 1.0. Through May 2026, estimates were produced using EpiNow2 with independent state-level models; from June 2026 onward, estimates use hierarchical generalized additive models (HGAM) with spatial partial pooling across states. Coverage begins September 2024. | Respiratory Covid flu Rsv | National, State | Not Stratified | Not Stratified | — | 2026-04-01 | 2026-08-04 | Daily | 2026-08-07 | 2026-08-07 | Public domain. CDC data is generally not subject to copyright restrictions. | CDC Center for Forecasting and Outbreak Analytics (CFA) | Link | GitHub |
cdc_vssr
|
NCHS VSRR Provisional Maternal Death Counts and Rates | Provisional national-level maternal death counts, live births, and maternal mortality rate from NCHS's Vital Statistics Rapid Release program, reported as 12-month rolling totals from current mortality and natality data in the National Vital Statistics System. | Maternal health maternal mortality maternal deaths pregnancy-related deaths | National | <25, 25-39, 40+ | Not Stratified | Race/Ethnicity | 2019-01-31 | 2025-12-31 | Monthly | 2026-07-06 | — | Public domain. CDC/NCHS data is generally not subject to copyright restrictions. | National Center for Health Statistics (NCHS) | Link | GitHub |
census
|
2020 Census Urban Area to County Allocation File | The 2020 Census Urban Area to County Allocation File maps Census-defined urban areas to counties, allowing calculation of the percent of each county's population, land area, and housing units that are urban versus rural. This is supplemented by 2024 American Community Survey (ACS) 5-year estimates, powered by Metopio, which provide detailed demographic, social, economic, and housing data — including poverty, housing, education, employment, insurance coverage, and racial/ethnic composition — for small geographic areas including ZIP Code Tabulation Areas. | Maternal health rural demographics | National, State, County | Not Stratified | Not Stratified | — | 2019-12-31 | 2024-12-31 | Annual | 2026-08-18 | 2026-04-28 est. | Public domain. U.S. Census Bureau data are generally not subject to copyright restrictions. | U.S. Census Bureau | Link | GitHub |
cms_mmd
|
Mapping Medicare Disparities by Population Tool | The Mapping Medicare Disparities (MMD) by Population Tool is an interactive map that displays chronic disease prevalence, costs, hospitalization, and preventive care utilization data for Medicare Fee-for-Service beneficiaries. Data are available at the national, state, and county levels, stratified by age, race/ethnicity, and sex. Condition prevalence rates are calculated using ICD-10 diagnosis codes in Medicare claims data, following the Chronic Conditions Warehouse (CCW) definitions. The tool covers over 30 chronic conditions including diabetes, hypertension, COPD, heart failure, and mental health conditions, as well as preventive service utilization metrics. Data are updated annually. | Cancer screening Chronic diseases Youth wellbeing | National, State, County | <65 Years, 65-74 Years, 65+ Years, 75-84 Years, 85+ Years | Stratified | Race/Ethnicity | 2021-01-01 | 2023-01-01 | Annual | 2026-06-09 | 2025-08-29 est. | Public domain. CMS data is generally not subject to copyright restrictions. | Centers for Medicare and Medicaid Services (CMS) | Link | GitHub |
county_health_rankings
|
County Health Rankings & Roadmaps | The County Health Rankings & Roadmaps (CHR&R) program, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, ranks the health of nearly all counties in the nation. The annual rankings measure vital health factors including high school graduation rates, obesity, smoking, unemployment, access to healthy foods, the quality of air and water, income inequality, and teen births that influence how long and how well we live. Data are released annually and cover all U.S. counties. Raw data are publicly available through the Zenodo repository (https://doi.org/10.5281/zenodo.18157681) and span release years 2010 through the present. | Rural Health Maternal health | National, State, County | Not Stratified | Not Stratified | — | 2010-12-31 | 2025-12-31 | Annual | 2026-07-07 | — | CC BY 4.0. Attribution required. Cite as: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps. https://www.countyhealthrankings.org. | University of Wisconsin Population Health Institute | Link | GitHub |
delphi_doctors_claims
|
CMU Delphi COVIDcast - Doctor Visits | The Delphi Doctor Visits signal estimates the percentage of outpatient doctor visits with COVID-related diagnoses based on claims data from health system partners. CMU Delphi receives de-identified medical insurance claims data covering a significant fraction of United States healthcare visits. The signal is calculated as the percentage of outpatient visits with COVID-related ICD-10 diagnosis codes (U071, U072, B9729, J1281, Z03818, B342, J1289). Data are smoothed using a Gaussian linear smoother to reduce day-to-day noise. This signal provides near-real-time insight into COVID-19 activity at the community level based on actual healthcare encounters. Data are available at state and county levels with approximately 3-4 day lag from the date of service. | Respiratory | National, State, County | Not Stratified | Not Stratified | — | 2020-02-01 | 2026-05-30 | Weekly | 2026-06-09 | 2026-06-09 est. | CC-BY Attribution license. Data may be used with attribution to the CMU Delphi Group. | Carnegie Mellon University Delphi Research Group | Link | GitHub |
delphi_hospital_claims
|
CMU Delphi COVIDcast - Hospital Admissions | The Delphi Hospital Admissions signal estimates the percentage of new hospital admissions with COVID-19 or influenza diagnoses based on electronic medical records and claims data from health system partners. CMU Delphi receives de-identified hospital admission data covering a significant fraction of United States hospitals. The signals track inpatient admissions with relevant ICD-10 diagnosis codes for COVID-19 and influenza. Data are smoothed using a Gaussian linear smoother to reduce day-to-day variation. This signal provides near-real-time insight into severe respiratory illness at the community level based on actual hospitalizations. Data are available at state and county levels with approximately 3-4 day lag from the date of admission. | Respiratory | National, State, County | Not Stratified | Not Stratified | — | 2020-02-01 | 2026-05-30 | Daily | 2026-06-09 | 2026-06-09 est. | CC-BY Attribution license. Data may be used with attribution to the CMU Delphi Group. | Carnegie Mellon University Delphi Research Group | Link | GitHub |
delphi_ili_fluview
|
CMU Delphi Epidata - FluView (ILINet) | Influenza-Like Illness (ILI) surveillance data from the CDC's ILINet network, accessed via the CMU Delphi Epidata API. ILINet is a collaborative effort between the CDC, state and local health departments, and approximately 3,000 outpatient healthcare providers across all 50 states, Puerto Rico, the District of Columbia, and the U.S. Virgin Islands. Providers report the total number of patients seen and the number presenting with ILI (defined as fever >=100F plus cough and/or sore throat without a known cause other than influenza). Data are available from 1997 week 40 onward at national, HHS regional, and state levels. Both weighted (population-adjusted) and unweighted percentages are provided. This long-running surveillance system is the primary source for tracking seasonal influenza activity in the United States. | Respiratory | National, State | Not Stratified | Not Stratified | — | 1997-10-04 | 2026-08-08 | Weekly | 2026-08-18 | 2026-08-18 est. | Public domain. Original CDC ILI data is not subject to copyright restrictions. | Carnegie Mellon University Delphi Research Group | Link | GitHub |
delphi_nhsn
|
CMU Delphi COVIDcast - NHSN Respiratory Hospitalizations | Weekly hospital respiratory data reported to CDC's National Healthcare Safety Network (NHSN), accessed via the CMU Delphi Epidata API. NHSN is the nation's most widely used healthcare-associated infection tracking system, collecting data from hospitals across the United States. The data includes COVID-19, influenza, and RSV associated hospital admissions aggregated to national and state levels. Data collection became mandatory for hospitals in November 2024; prior to this, reporting was voluntary with variable participation rates. | Respiratory | National, State | Not Stratified | Not Stratified | — | 2020-08-08 | 2026-08-08 | Weekly | 2026-08-18 | 2026-08-18 est. | CC-BY Attribution license. Data may be used with attribution to the CMU Delphi Group and CDC NHSN. | Carnegie Mellon University Delphi Research Group | Link | GitHub |
epic_chronic
|
Epic Cosmos | Epic Cosmos is a collaborative research platform containing de-identified patient data from over 300 million patients across more than 1,600 hospitals and health systems using Epic electronic health record systems. Data is accessed via SlicerDicer, a self-service analytics tool. The dataset includes emergency department visits, diagnoses, immunizations, laboratory results, and other clinical data. Due to privacy protections, counts fewer than 10 are suppressed and imputed. Coverage extends across all U.S. states and territories. Note that county-level and city-level stratifications could differ markedly in total sample size due to high levels of missingness of county data in some states. | Chronic diseases obesity diabetes | National, State, County | <18 Years, 18-24 Years, 25-34 Years, 35-44 Years, 45-54 Years, 55-64 Years, 65+ Years | Not Stratified | — | 2016-01-01 | 2025-01-01 | Annual | 2026-06-24 | — | The data can be re-used with appropriate attribution. A suggested citation relating to this data is 'Results of research performed with Epic Cosmos were obtained from the PopHIVE platform (https://github.com/PopHIVE/Ingest).' | Epic Systems | Link | GitHub |
epic_diarrhea
|
Epic Cosmos | Weekly Epic Cosmos electronic health record data on emergency department and all-encounter-type visits for all-cause diarrhea, plus cyclospora lab testing volume and percent positivity, by U.S. state and age group. | Enteric diseases diarrhea gastroenteritis cyclospora | National, State | <1 Years, 1-4 Years, 5-17 Years, 18-49 Years, 50-64 Years, 65+ Years | Not Stratified | — | 2022-07-02 | 2026-08-01 | Annual, Weekly | 2026-08-18 | — | The data can be re-used with appropriate attribution. A suggested citation relating to this data is 'Results of research performed with Epic Cosmos were obtained from the PopHIVE platform (https://github.com/PopHIVE/Ingest).' | Epic Systems | Link | GitHub |
epic_health_alerts
|
Epic Research Health Alerts | Epic Research Health Alerts flags U.S. states and counties experiencing an unusual rise in a specific condition, derived from Epic Cosmos de-identified electronic health record data covering over 300 million patients across more than 1,600 hospitals and health systems. Because the source page only ever shows currently active alerts rather than a historical archive, this dataset accumulates one weekly snapshot per ingestion run to build up a time series. | outbreak alerts gastroenteritis pharyngitis hand foot and mouth disease heat illness cyclosporiasis | State, County | Not Stratified | Not Stratified | — | 2026-07-18 | 2026-08-22 | Weekly | 2026-08-20 | 2026-08-20 est. | The data can be re-used with appropriate attribution. A suggested citation relating to this data is 'Results of research performed with Epic Cosmos were obtained from the PopHIVE platform (https://github.com/PopHIVE/Ingest).' | Epic Research | Link | GitHub |
epic_hepb_vax
|
Epic Cosmos | Epic Cosmos is a collaborative research platform containing de-identified patient data from over 300 million patients across more than 1,600 hospitals and health systems using Epic electronic health record systems. Data is accessed via SlicerDicer, a self-service analytics tool. The dataset includes emergency department visits, diagnoses, immunizations, laboratory results, and other clinical data. Due to privacy protections, counts fewer than 10 are suppressed and imputed. Coverage extends across all U.S. states and territories. Note that county-level and city-level stratifications could differ markedly in total sample size due to high levels of missingness of county data in some states. | hepatitis hep b | National, State | Not Stratified | Not Stratified | — | 2017-01-31 | 2026-01-31 | Monthly | 2026-03-11 | — | The data can be re-used with appropriate attribution. A suggested citation relating to this data is 'Results of research performed with Epic Cosmos were obtained from the PopHIVE platform (https://github.com/PopHIVE/Ingest).' | Epic Systems | Link | GitHub |
epic_injury
|
Epic Cosmos | Epic Cosmos is a collaborative research platform containing de-identified patient data from over 300 million patients across more than 1,600 hospitals and health systems using Epic electronic health record systems. Data is accessed via SlicerDicer, a self-service analytics tool. The dataset includes emergency department visits, diagnoses, immunizations, laboratory results, and other clinical data. Due to privacy protections, counts fewer than 10 are suppressed and imputed. Coverage extends across all U.S. states and territories. Note that county-level and city-level stratifications could differ markedly in total sample size due to high levels of missingness of county data in some states. | overdose heat injury guns firearm youth | National, State, County | <15 Years, 15-25 Years, 25-45 Years, 45-64 Years, 65+ Years | Not Stratified | — | 2018-01-01 | 2025-09-01 | Annual, Monthly | 2026-03-11 | — | The data can be re-used with appropriate attribution. A suggested citation relating to this data is 'Results of research performed with Epic Cosmos were obtained from the PopHIVE platform (https://github.com/PopHIVE/Ingest).' | Epic Systems | Link | GitHub |
epic_resp_infections
|
Epic Cosmos | Epic Cosmos is a collaborative research platform containing de-identified patient data from over 300 million patients across more than 1,600 hospitals and health systems using Epic electronic health record systems. Data is accessed via SlicerDicer, a self-service analytics tool. The dataset includes emergency department visits, diagnoses, immunizations, laboratory results, and other clinical data. Due to privacy protections, counts fewer than 10 are suppressed and imputed. Coverage extends across all U.S. states and territories. Note that county-level and city-level stratifications could differ markedly in total sample size due to high levels of missingness of county data in some states. | Respiratory flu pneumonia Rsv | National, State | <1 Years, 1-4 Years, <5 Years, 5-17 Years, 18-39 Years, 18-49 Years, 40-64 Years, 50-64 Years, 65+ Years | Not Stratified | — | 2017-03-31 | 2026-08-01 | Annual, Weekly, Monthly, Quarterly | 2026-08-14 | — | The data can be re-used with appropriate attribution. A suggested citation relating to this data is 'Results of research performed with Epic Cosmos were obtained from the PopHIVE platform (https://github.com/PopHIVE/Ingest).' | Epic Systems | Link | GitHub |
gtrends
|
Google Health Trends API | Google Health Trends data accessed via the Google Health Trends API, processed and collected using Yale DISSC's gtrends_collection framework. The data represents the probability of a short search session including a specific health-related term within a geography and timeframe, multiplied by 10 million for readability. Search volumes are provided at the DMA (Designated Market Area) and state level on a weekly basis. This data source enables tracking of public interest in health topics such as RSV, overdose, and naloxone as potential early indicators of disease activity or public health concerns. | Injury and overdose Respiratory | National, State, County | Not Stratified | Not Stratified | — | 2014-01-07 | 2026-08-15 | Weekly | 2026-08-18 | 2026-08-18 est. | Data can be reused with attribution of data from the Google Health Trends API, obtained via the PopHIVE platform (https://github.com/PopHIVE/Ingest). | Yale Data-Intensive Social Science Center (DISSC) | Link | GitHub |
hud_chas
|
Comprehensive Housing Affordability Strategy (CHAS) data | CHAS data is a custom tabulation of American Community Survey data produced for HUD, providing detailed cross-tabulations of housing problems (cost burden, overcrowding, and facilities adequacy) by income, tenure, and race, at multiple geographic levels including county. | — | State, County | Not Stratified | Not Stratified | — | 2022-12-31 | 2022-12-31 | Annual | 2026-08-18 | — | Public domain. HUD data are generally not subject to copyright restrictions. | U.S. Department of Housing and Urban Development | Link | GitHub |
kinsa_ili
|
Kinsa Insights API | Kinsa collects real-time illness data through its network of smart thermometers and a companion mobile app. Users who record a temperature reading are asked about accompanying symptoms. The Cough, Cold & Flu signal aggregates self-reported symptom data from active users at the national level. Coverage depends on the geographic distribution of Kinsa device owners, which skews toward households with young children. Data are available daily from approximately 2018 onward. | Respiratory cold cough flu | National | Not Stratified | Not Stratified | — | 2019-01-01 | 2026-08-20 | Daily | 2026-08-20 | 2026-08-20 est. | Data can be re-used with appropriate attribution. A suggested citation relating to this data is 'Results of research performed with Kinsa Insights data were obtained via the PopHIVE platform (https://github.com/PopHIVE/Ingest).' | Kinsa | Link | GitHub |
measles_age_cdc2
|
CDC Measles Cases and Outbreaks - Age and Vaccination Status | Weekly new and cumulative case and hospitalization counts for measles in the United States, stratified by age group (<5, 5-19, 20+, and Total) and vaccination status (Total, Unvaccinated/Unknown, One dose MMR, Two doses MMR). Data is updated weekly on the CDC Measles Cases and Outbreaks surveillance page. Negative values in case counts reflect retroactive corrections by the CDC. Cases are classified as confirmed or probable following CSTE case definitions. The source presents cumulative counts or percentages. The number of new counts is derived from the difference in cumulative cases in 2 successive weeks. For the stratification by vaccine status, the source provided the percent in each vaccinated group, and this was multiplied by the cumulative cases to approximate the number in each group | Measles | National | <5 years, 5-19 years, 20+ years | Not Stratified | — | 2025-02-08 | 2026-08-08 | Weekly | 2026-08-07 | 2026-08-07 est. | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
measles_cdc
|
CDC Measles Cases and Outbreaks | The CDC Measles Cases and Outbreaks surveillance system tracks confirmed and probable measles cases reported to CDC by state and local health departments. Data includes weekly national case counts. Measles became a nationally notifiable disease in 1912, and since 2000 (when measles was declared eliminated in the U.S.) CDC has continued enhanced surveillance to detect and respond to imported cases and outbreaks. Case definitions follow CSTE criteria requiring clinical symptoms and either laboratory confirmation or epidemiological linkage to a confirmed case. | Measles | National | Not Stratified | Not Stratified | — | 2022-01-08 | 2026-08-08 | Weekly | 2026-08-07 | 2025-07-31 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
measles_jhu
|
Johns Hopkins University Measles Tracking Team | The Johns Hopkins University Measles Tracking Team compiles laboratory-confirmed measles case data from official state and county health department reports across the United States. The team aggregates data from 37+ jurisdictions, providing both state-level weekly summaries (using rash onset dates when available) and county-level daily case counts (based on official reporting dates). Data is updated on Tuesdays and Fridays at approximately 5:00 PM Eastern Time. The tracking effort was established in response to the 2025 measles outbreak to provide timely, granular geographic data on measles transmission. All data is released under CC BY 4.0 license with attribution required. | Measles | National, State, County | Not Stratified | Not Stratified | — | 2025-01-11 | 2026-08-08 | Weekly | 2026-08-11 | 2026-08-11 est. | CC BY 4.0. Attribution required for reuse. Please cite as JHU Measles Tracking Team Data Repository at Johns Hopkins University or JHU Measles Tracking Team Data for short. Copyright: Johns Hopkins University 2025 | Johns Hopkins Bloomberg School of Public Health | Link | GitHub |
medicaid_quality
|
Medicaid and CHIP Adult and Child Core Set Quality Measures | Annual state-level performance data on the Medicaid and CHIP Adult Core Set and Child Core Set quality measures, as voluntarily reported by states to CMS and analyzed by Mathematica via the Quality Measure Reporting (QMR) system. Measures span behavioral health (e.g., follow-up after ED visits for mental illness, substance use disorder treatment), primary and preventive care (e.g., well-child visits, immunizations), maternal and perinatal health (e.g., prenatal and postpartum care, low birthweight), dental health, care of chronic conditions (e.g., diabetes, asthma, hypertension), and long-term services and supports. Each annual dataset includes state rates and national 25th and 75th percentile benchmarks. Data cover federal fiscal years 2014–2023. Reporting is voluntary; not all states report all measures each year. The wide-format standard file contains one row per state-year-payer-domain combination, with each measure-statistic combination as a separate column following the naming convention medicaid_{measure_abbr}_{population}_{sub_metric}_{stat} where population is 'ch' (child) or 'ad' (adult), sub_metric captures time windows or sub-components, and stat is 'rate', 'pct_25', or 'pct_75'. | Cancer screening Injury and overdose Maternal health Preventative services Youth wellbeing mental health immuizations opioids diabetes | County | Not Stratified | Not Stratified | Payer | 2014-01-01 | 2023-01-01 | Annual | 2026-04-05 | 2026-04-05 est. | Public domain. CMS/Medicaid.gov data is generally not subject to copyright restrictions. | Centers for Medicare & Medicaid Services (CMS) | Link | GitHub |
mmr_healthmap
|
HealthMap MMR Vaccine Coverage Estimates | County, ZIP code, and state-level estimates of MMR (measles, mumps, and rubella) vaccine coverage among US children, developed using small area estimation with multilevel regression and post-stratification (MRP). The methodology integrates participatory surveillance data from digital health platforms with demographic and contextual covariates to produce granular geographic estimates of vaccination coverage gaps. Estimates include posterior mean coverage percentages, risk classifications for under-vaccination, and spatial autocorrelation measures (Local Moran's I) to identify geographic clustering of under-vaccinated areas. This research was conducted in response to the 2025 measles outbreak to support targeted public health interventions. | Measles | National, State, County | Not Stratified | Not Stratified | — | 2024-12-31 | 2024-12-31 | Cross-Sectional | 2026-04-06 | 2026-01-20 est. | MIT License: Copyright (c) 2025 Eric Zhou. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the Software), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:Attribution required. Cite Zhou EG, Brownstein J, Rader B. Assessing MMR Vaccination Coverage Gaps in US Children with Digital Participatory Surveillance. Nature Health. 2025. | HealthMap / Boston Children's Hospital | Link | GitHub |
narms
|
NARMS Now: Human Data - Antimicrobial Resistance | NARMS (National Antimicrobial Resistance Monitoring System) tracks antimicrobial resistance across the food supply chain through four complementary CDC/FDA surveillance programs: human clinical isolates (Campylobacter, E. coli O157, Vibrio, Salmonella, Shigella), FDA retail meat sampling (2002–2021), FDA animal diagnostic pathogen surveillance from veterinary laboratories, and FDA food-producing animal surveillance spanning HACCP slaughter, cecal, and minor-species sampling programs (1997–2023). Resistance is reported by individual antimicrobial agent and by multidrug-resistance pattern, with susceptibility calls based on CLSI breakpoints. | Antimicrobial resistance | National, State | Not Stratified | Not Stratified | — | 1997-12-31 | 2025-12-31 | Annual | 2026-08-05 | 2026-08-05 est. | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
nccr
|
National Childhood Cancer Registry Explorer (NCCR*Explorer) | The National Childhood Cancer Registry (NCCR) is a federated data resource maintained by the National Cancer Institute (NCI) as part of the Childhood Cancer Data Initiative (CCDI). NCCR*Explorer provides precalculated incidence, survival, and prevalence statistics for cancers among children, adolescents, and young adults (ages 0-39) diagnosed from 2001 forward. Incidence data are pooled from up to 29 U.S. cancer registries representing approximately 76% of the U.S. population ages 0-39. Cancers are classified using the International Classification of Childhood Cancer (ICCC). Rates are age-adjusted to the 2000 U.S. standard population and reported at the national level only; NCCR*Explorer does not provide state- or registry-level breakdowns. Statistics are available by sex, race/ethnicity, and age group. This dataset was harvested from the NCCR*Explorer application data API (incidence, trends over time). | cancer | National | 0-19, 0-39, <1, 1-4, 5-9, 10-14, 15-19, 15-39, 20-24, 20-39, 25-29, 30-39 | Stratified | Race/Ethnicity | 2001-12-31 | 2022-12-31 | Annual | 2026-07-03 | 2026-07-03 est. | Public domain. Data from the National Childhood Cancer Registry, produced by the National Cancer Institute, is generally not subject to copyright restrictions. Suggested attribution: National Childhood Cancer Registry Explorer (NCCR*Explorer), National Cancer Institute. | National Cancer Institute (NCI), Childhood Cancer Data Initiative | Link | GitHub |
nchs_mortality
|
NCHS VSRR Provisional Drug Overdose Death Counts (State) | Provisional mortality data from the CDC's Vital Statistics Rapid Release (VSRR) program, covering three related measures: monthly drug overdose death counts by drug type at the state level, monthly drug overdose death counts at the county level (with counts of 1–9 suppressed and imputed), and quarterly age-adjusted mortality rates for 21 selected causes of death. All data are provisional and subject to revision as more death certificates are processed; New York City and New York State are combined in the state-level overdose data. | Injury and overdose cause of death cancer gun firearm | National, State, County | Not Stratified | Not Stratified | — | 2015-01-01 | 2026-01-01 | Monthly, Quarterly | 2026-06-23 | 2026-07-15 ⚠ +22d | Public domain. CDC/NCHS data is generally not subject to copyright restrictions. | National Center for Health Statistics (NCHS) | Link | GitHub |
neiss
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National Electronic Injury Surveillance System (NEISS) | NEISS is a national probability sample of hospital emergency departments (about 100 of the 5,000+ U.S. hospitals with 24-hour EDs) operated by the U.S. Consumer Product Safety Commission, describing injuries treated in the ED including diagnosis, body part, and up to three associated consumer products. Statistical weights scale the sampled records to national estimates. | Injury and overdose injury consumer product safety emergency department | National | 00 months, 01 months, 02 months, 2-4, Under 2, 03 months, 04 months, 05 months, 5-9, 06 months, 07 months, 08 months, 09 months, 10 months, 10-14, 11 months, 12 months, 13 months, 14 months, 15 months, 15-19, 16 months, 17 months, 18 months, 19 months, 20 months, 20-29, 21 months, 22 months, 23 months, 30-39, 40-49, 50-59, 60-69, 70-79, 80+ | Stratified | Race/Ethnicity | 2019-12-31 | 2025-12-31 | Annual | 2026-07-29 | 2026-07-06 est. | Public domain. NEISS data are produced by the U.S. Consumer Product Safety Commission and are generally not subject to copyright restrictions. | U.S. Consumer Product Safety Commission (CPSC) | Link | GitHub |
nhtsa_crash
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Fatality Analysis Reporting System (FARS) | FARS is a nationwide census providing NHTSA, Congress, and the American public with yearly data on fatal injuries suffered in motor vehicle traffic crashes. FARS contains data on all crashes in the United States involving a fatality in a motor vehicle traffic crash on a public road. A fatal crash is one in which a motor vehicle is involved and at least one person dies within 30 days of the crash. Data are collected from police crash reports, state vehicle registration files, state driver licensing files, state highway department data, vital statistics, and other sources. FARS has been operational since 1975 and covers all 50 states, the District of Columbia, and Puerto Rico (national files cover the 50 states and DC). | traffic car cause of death | National, State, County | 0-14, 15-24, 25-44, 45-64, 65+ | Stratified | — | 2000-12-31 | 2024-12-31 | Annual | 2026-06-29 | — | Public domain. NHTSA data is generally not subject to copyright restrictions. | National Highway Traffic Safety Administration (NHTSA) | Link | GitHub |
nis
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National Immunization Survey (NIS) | The National Immunization Surveys (NIS) are a group of telephone surveys used to monitor vaccination coverage among children 19-35 months, teens 13-17 years, flu vaccinations for children 6 months-17 years, and COVID-19 vaccination for children, teens, and adults. The surveys are sponsored and conducted by the National Center for Immunization and Respiratory Diseases (NCIRD) of the CDC and authorized by the Public Health Service Act. NIS provides population-based, state and local area estimates of vaccination coverage using a standard survey methodology. Surveys collect data through telephone interviews with parents or guardians in all 50 states, the District of Columbia, and some U.S. territories. Cell phone numbers are randomly selected and called to enroll age-eligible children. With parental permission, vaccination providers are contacted to verify immunization records. Children and teens are classified as up to date based on ACIP-recommended vaccine doses. | Childhood immunizations | National, State, County | 0-1 Days, 0-2 Days, 0-3 Days, 3 Months, 5 Months, 7 Months, 8 Months, 13 Months, 19 Months, 24 Months, 35 Months | Not Stratified | Birth Cohort, Insurance, Urbanicity | 2011-01-01 | 2024-11-30 | Annual | 2026-07-31 | 2026-04-02 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
nnds
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National Notifiable Diseases Surveillance System (NNDSS) | The National Notifiable Diseases Surveillance System (NNDSS) is a nationwide collaboration that enables all levels of public health to share notifiable disease related health information. Public health uses this information to monitor, control, and prevent the occurrence and spread of state-reportable and nationally notifiable infectious and some non-infectious diseases and conditions. | Measles enterics diarrhea vector-borne | National, State | Not Stratified | Not Stratified | — | 2022-01-08 | 2026-08-15 | Weekly | 2026-08-20 | 2026-08-19 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
noaa_heat_risk
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NOAA WPC HeatRisk | The NOAA Weather Prediction Center HeatRisk product provides a daily, gridded (2.5 km) assessment of heat risk across the contiguous United States for the current day and 7-day forecast period. Risk is classified on a 0–4 scale based on the combination of heat intensity and duration relative to local historical thresholds, with consideration for overnight low temperatures and heat index. The archive provides daily GeoTIFF rasters back to August 1, 2024. County- and state-level summaries in this dataset are computed as the mean pixel value within each geographic boundary using area-weighted zonal statistics. | heat weather environmental | National, State, County | Not Stratified | Not Stratified | — | 2024-08-01 | 2026-08-26 | Daily | 2026-08-20 | 2026-03-26 est. | Public domain. NOAA data is generally not subject to copyright restrictions. | NOAA Weather Prediction Center (WPC) | Link | GitHub |
NREVSS
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National Respiratory and Enteric Virus Surveillance System (NREVSS) | The National Respiratory and Enteric Virus Surveillance System (NREVSS) is a voluntary, laboratory-based surveillance system that monitors temporal and geographic trends for respiratory syncytial virus (RSV), human parainfluenza viruses, respiratory adenoviruses, human metapneumovirus, human coronaviruses, and rotavirus circulation in the United States. Participating laboratories report weekly to CDC on the number of tests performed and the number positive for each virus. NREVSS data are used to characterize seasonal patterns of these viruses and to help public health officials anticipate and prepare for outbreaks. Data are aggregated at the HHS regional and national levels. The system has been operational since 1987 and includes approximately 300 participating laboratories across the United States. | Respiratory flu rsv Covid | National | Not Stratified | Not Stratified | — | 2020-04-11 | 2026-08-08 | Weekly | 2026-08-18 | 2026-08-13 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
nssp
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National Syndromic Surveillance Program (NSSP) | This dataset provides the percentage of emergency department patient visits for the specified pathogen of all ED patient visits for the specified geographic part of the country that were observed for the given week from data submitted to the National Syndromic Surveillance Program (NSSP). Note that the reported sub-state trends are from Health Service Areas (HSA) and the data reported from the health care facilities located within the given HSA. Health Service Areas are regions of one or more counties that align to patterns of care seeking. The HSA level data are reported for each county in the HSA. Some states report state-level data but not county-level data. In these instances, PopHIVE maps the state-level data to the counties in that state so that all counties in the state share the same value. These data are made available by the CDC. | Respiratory flu rsv Covid | National, State, County | Not Stratified | Not Stratified | — | 2022-10-01 | 2026-08-08 | Weekly | 2026-08-18 | 2026-08-12 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
respnet
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Respiratory Virus Hospitalization Surveillance Network (RESP-NET) | The Respiratory Virus Hospitalization Surveillance Network (RESP-NET) monitors laboratory-confirmed hospitalizations associated with influenza, COVID-19, and respiratory syncytial virus (RSV) among children and adults. The data are collected from hospitals in selected counties and county equivalents. This dataset has several important advantages: the area around the hospitals is well described, so rates of disease adjusted for population size can be accurately reported. The selected counties include ~10% of the US population and are demographically representative of the country. Detailed patient demographic information is available, and officials actively search for cases to ensure they capture all cases in the data. A limitation is that the network relies on the clinicians to perform viral tests as part of their routine clinical practice, so they likely miss cases that are not tested. | Respiratory flu rsv Covid | National, State | <1 Years, 1-4 Years, 5-17 Years, 18-49 Years, 50-64 Years, 65+ Years | Not Stratified | — | 2016-10-01 | 2026-08-08 | Weekly | 2026-08-18 | 2026-08-14 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
schoolvax_washpost
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Washington Post School Vaccination Rates | School and county-level kindergarten vaccination rate data compiled by the Washington Post from state health department records, covering school years 2018–2019 through 2024–2025. For Tennessee, county-level data instead come directly from the state's 2024–2025 Kindergarten Immunization Compliance Assessment, an annual census-based survey conducted by the Tennessee Department of Health in collaboration with the Department of Education and public/private schools, which supersedes the Washington Post's Tennessee figures for that year. | Childhood immunizations Measles | State, County | Not Stratified | Not Stratified | School Grade | 2018-09-01 | 2024-09-01 | Annual | 2026-08-20 | 2026-06-09 est. | Attribution required. Cite The Washington Post. | The Washington Post | Link | GitHub |
schoolvaxview
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SchoolVaxView | SchoolVaxView monitors vaccination coverage among U.S. school-aged children. Data are collected annually by states, territories, and select local jurisdictions through school vaccination assessments, which review student vaccination records at kindergarten entry. These data are made available by the CDC. | Childhood immunizations | National, State | Not Stratified | Not Stratified | School Grade | 2009-09-01 | 2025-09-01 | Annual | 2026-08-17 | 2026-08-17 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
usda_food_access
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Food Environment Atlas | Share of the county population that is low-income and lives more than 1 mile (urban) or 10 miles (rural) from a grocery store, from the USDA Economic Research Service's Food Environment Atlas. | Rural health food access food insecurity grocery access | County | Not Stratified | Not Stratified | — | 2019-12-31 | 2019-12-31 | Annual | 2026-08-12 | — | Public domain. USDA data are generally not subject to copyright restrictions. | U.S. Department of Agriculture, Economic Research Service | Link | GitHub |
vaccine_exemptions_fattah
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Medical Exemptions From Childhood Vaccination in the US (Kiang et al. 2025) | A comprehensive study of medical vaccine exemption rates among U.S. kindergartners from 2009-2024, published in JAMA by Kiang et al. The study compiled exemption data from all 50 U.S. states and Washington, DC, providing state- and county-level medical exemption rates for MMR vaccination. The dataset spans prepandemic (2009-2019) and postpandemic (2020-2024) periods, enabling analysis of how exemption patterns changed over time and following the COVID-19 pandemic. Medical exemptions are granted when a physician determines that vaccination poses a health risk to a specific child, distinct from religious or philosophical exemptions. Values are rounded for privacy protection. The research was conducted in collaboration with NBC News and methodology is documented in an accompanying article. Full data and code are available on GitHub. | Measles Childhood immunizations | National, State, County | Not Stratified | Not Stratified | — | 2009-09-01 | 2025-09-01 | Annual | 2026-08-20 | 2026-04-06 est. | Attribution required. Cite Fattah M, Stoffel LA, Bubar KM, Bents SJ, Maldonado Y, Hotez PJ, Kiang MV, Lo NC. Trends in County-Level Childhood Vaccination Exemptions in the US. JAMA. 2026 Feb 10;335(6):546-549. doi: 10.1001/jama.2025.24407. PMID: 41533386; PMCID: PMC12805488. | Stanford University / Massachusetts General Hospital | Link | GitHub |
wastewater
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CDC National Wastewater Surveillance System (NWSS) | The National Wastewater Surveillance System (NWSS) is a national surveillance system coordinated by CDC that monitors SARS-CoV-2, Influenza A, and RSV levels in wastewater across the United States. Wastewater surveillance provides population-level data on pathogen circulation regardless of whether individuals seek healthcare or testing. The Viral Activity Level (VAL) represents the scaled number of standard deviations above a dynamic baseline, allowing comparison across different geographic areas and time periods. Site-level WVAL values are aggregated to state and national levels using population-weighted means. CDC updated the methodology used to calculate the WVAL in August 2025, with updates applied retroactively to all historical data. Data is updated every Friday. | Respiratory flu rsv Covid | National, State | Not Stratified | Not Stratified | — | 2022-01-01 | 2026-08-08 | Weekly | 2026-08-18 | 2026-08-14 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
wastewater_measles
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CDC National Wastewater Surveillance System (NWSS) - Measles | The CDC National Wastewater Surveillance System (NWSS) tracks measles virus RNA in wastewater samples from participating wastewater treatment facilities across the United States. Wastewater surveillance provides a complement to traditional clinical surveillance by detecting viral shedding in a community regardless of healthcare-seeking behavior. The measles wastewater surveillance program was expanded in response to the 2025 measles outbreak to provide early warning of community transmission. Data include detection rates (percentage of samples positive), detection counts, sample counts, and population served by participating sewersheds. Surveillance data are aggregated at state and national levels on a weekly basis. This approach can detect measles circulation before cases are clinically confirmed, supporting rapid public health response. | Measles | National, State, County | Not Stratified | Not Stratified | — | 2024-12-14 | 2026-08-08 | Weekly | 2026-08-07 | 2026-08-07 | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
wisqars
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Web-based Injury Statistics Query and Reporting System (WISQARS) | WISQARS (Web-based Injury Statistics Query and Reporting System) is an interactive, online database that provides fatal and nonfatal injury, violent death, and cost of injury data from a variety of trusted sources. Maintained by CDC's National Center for Injury Prevention and Control, WISQARS enables public health professionals and researchers to access injury-related mortality data from the National Vital Statistics System, nonfatal injury data from the National Electronic Injury Surveillance System (NEISS), and violent death data from the National Violent Death Reporting System (NVDRS). Data are available at national and state levels for various injury mechanisms including motor vehicle crashes, falls, poisonings (including drug overdoses), firearms, and self-harm. WISQARS supports injury surveillance, research, and prevention program planning. | cause of death overdose gun firearm | National, State | 0-14 Years, 15-24 Years, 25-44 Years, 45-64 Years, 65+ Years | Stratified | Race/Ethnicity | 2001-01-01 | 2024-01-01 | Annual | 2026-06-19 | 2026-06-03 est. | Public domain. CDC data is generally not subject to copyright restrictions. | Centers for Disease Control and Prevention | Link | GitHub |
yrbss
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CDC Youth Risk Behavior Surveillance System (YRBSS) | The Youth Risk Behavior Surveillance System (YRBSS) is a set of school-based surveys conducted by the CDC that monitor health-related behaviors among U.S. high school students. The biennial national, state, and local surveys provide weighted prevalence estimates of behaviors contributing to the leading causes of death and disability. Data were accessed via the YRBS Explorer API. Estimates are provided overall and stratified (separately, not crossed) by sex, race/ethnicity, and grade. Estimates that CDC suppressed (e.g., small sample sizes) are omitted rather than imputed. State estimates are available only for jurisdictions that share data with CDC; Minnesota, Oregon, and Washington are not included, and New York state excludes New York City. | mental health substance abuse gun | National, State | 14, 15, 16, 17 | Stratified | Race/Ethnicity | 2005-12-31 | 2023-12-31 | Annual | 2026-06-25 | 2026-08-11 est. ⚠ +47d | Public domain. Suggested attribution: Centers for Disease Control and Prevention (CDC). Youth Risk Behavior Surveillance System (YRBSS). | Centers for Disease Control and Prevention | Link | GitHub |
| Folder | Bundle | # Datasets | Datasets Involved |
|---|---|---|---|
bundle_antimicrobial_resistance
|
Antimicrobial Resistance | 1 | NARMS |
bundle_cancer_screening
|
Cancer Screening | 2 | CMS Mmd, Medicaid Quality |
bundle_childhood_immunizations
|
Childhood Immunizations | 3 | NIS, Schoolvax Washpost, Schoolvaxview |
bundle_chronic_diseases
|
Chronic Diseases | 3 | BRFSS, CMS Mmd, Epic Chronic |
bundle_county_access
|
County Access | 1 | County Health Rankings |
bundle_county_chronic
|
County Chronic | 1 | County Health Rankings |
bundle_enteric_diseases
|
Enteric Diseases | 4 | Beam, Epic Diarrhea, NARMS, NNDS |
bundle_injury_overdose
|
Injury Overdose | 6 | CMS Mmd, Epic Injury, Gtrends, Medicaid Quality, NCHS Mortality, WISQARS |
bundle_maternal_health
|
Maternal Health | 4 | CDC Vssr, Census, County Health Rankings, Medicaid Quality |
bundle_measles
|
Measles | 8 | Measles Age Cdc2, Measles CDC, Measles JHU, MMR Healthmap, NNDS, Schoolvax Washpost, Vaccine Exemptions Fattah, Wastewater Measles |
bundle_preventative_services
|
Preventative Services | 2 | CMS Mmd, Medicaid Quality |
bundle_respiratory
|
Respiratory | 15 | Abcs, CDC Cfa Rt, Delphi Doctors Claims, Delphi Hospital Claims, Delphi ILI Fluview, Delphi NHSN, Epic Resp Infections, Gtrends, Kinsa ILI, NCHS Mortality, NNDS, NREVSS, NSSP, Respnet, Wastewater |
bundle_strep
|
Strep | 2 | Epic Resp Infections, NNDS |
bundle_youth_wellbeing
|
Youth Wellbeing | 9 | County Health Rankings, Epic Chronic, Epic Injury, Medicaid Quality, Neiss, NHTSA Crash, Noaa Heat Risk, WISQARS, YRBSS |