2018 2020, county-level U.S. heart disease death rates. Dataset developed by the Centers for Disease Control and Prevention, Division for Heart Disease and Stroke Prevention.Create maps of U.S. heart disease death rates by county. Data can be stratified by age, race/ethnicity, and sex.Visit the CDC/DHDSP Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceMortality data were obtained from the National Vital Statistics System. Bridged-Race Postcensal Population Estimates were obtained from the National Center for Health Statistics. International Classification of Diseases, 10th Revision (ICD-10) codes: I00-I09, I11, I13, I20-I51; underlying cause of death.Data DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC/DHDSP excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.'Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., API_M_35UP)  RRR: 3 digits represent race/ethnicity    All - Overall    AIA - American Indian and Alaska Native, non-Hispanic    API - Asian and Pacific Islander, non-Hispanic    BLK - Black, non-Hispanic    HIS - Hispanic    WHT - White, non-Hispanic  S: 1 digit represents sex    A - All    F - Female    M - Male  aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound. Example: The column 'BLK_M_65UP' displays rates per 100,000 black men aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 100,000 population. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and sex).At least one of the following 3 criteria:At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods

This dataset contains model-based county-level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. Project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2022 county population estimates, and American Community Survey (ACS) 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the census 2022 county boundary file in a GIS system to produce maps for 40 measures at the county level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

This dataset contains model-based place (incorporated and census designated places) estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia —at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four 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. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2020 population estimates, and American Community Survey (ACS) 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the 2020 Census place boundary file in a GIS system to produce maps for 40 measures at the place level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

This dataset contains model-based census tract level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four 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. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the Census tract 2022 boundary file in a GIS system to produce maps for 40 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

The means and standard deviations of the 50 MAP estimates based upon data with 400 infected households for each parameter is shown in the form mean(standard deviation) for the BPA and DA-MCMC methods. The last row shows the difference in the mean and standard deviation between the two methods.

This web map provides estimates for the percentage of persons aged ≥ 65 years from the American Community Survey 5-year data for the United States—50 states and the District of Columbia at county, place, census tract, and ZCTA-levels. Data were downloaded from data.census.gov using Census API and processed by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Year: 2017–2021 ACS table(s): S0101 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: September 12, 2023 For questions or feedback send an email to places@cdc.gov.

These data map the rate of coronary heart disease among individuals 18 years of age and older at the census tract level. Provided by the CDC Population Level Analysis and Community Estimates (PLACES). For more information, please visit https://chronicdata.cdc.gov/500-Cities-Places/PLACES-Local-Data-for-Better-Health-Census-Tract-D/cwsq-ngmh.

While not a primary driver of drug overdose in the United States currently, prescription opioids do contribute to opioid-related deaths. The data in the maps show the geographic distribution in the United States, at both the state and county level, of retail pharmacy-dispensed opioid prescriptions per 100 persons per year from 2019–2022. Data are displayed within two types of interactive maps that show the estimated rate of opioid prescriptions per 100 U.S. residents. The state maps portray the rates per year for each of the 50 states and the District of Columbia. The county maps portray these rates for approximately 98% of U.S. counties represented in the IQVIA data for a given year from 2019-2022.

Parameter estimates for the reduced model.

Parameter estimates for the full model.

Create maps of U.S. heart disease death rates by county. Data can be stratified by age, race/ethnicity, and sex. Visit the CDC/DHDSP Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceMortality data were obtained from the National Vital Statistics System. Bridged-Race Postcensal Population Estimates were obtained from the National Center for Health Statistics. International Classification of Diseases, 10th Revision (ICD-10) codes: I00-I09, I11, I13, I20-I51; underlying cause of death.Data DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC/DHDSP excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.' Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., API_M_35UP)   RRR: 3 digits represent race/ethnicity     All - Overall     AIA - American Indian and Alaska Native, non-Hispanic     API - Asian and Pacific Islander, non-Hispanic     BLK - Black, non-Hispanic     HIS - Hispanic     WHT - White, non-Hispanic   S: 1 digit represents sex     A - All    F - Female     M - Male aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound.  Example: The column 'BLK_M_65UP' displays rates per 100,000 black men aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 100,000 population. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and sex).At least one of the following 3 criteria: At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods

This web map provides estimates for the percentage of housing cost burden among households from the American Community Survey 5-year data for the United States—50 states and the District of Columbia at county, place, census tract, and ZCTA-levels. Data were downloaded from data.census.gov using Census API and processed by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Year: 2017–2021 ACS table(s): S2503 Data downloaded from: Census Bureau’s API for American Community Survey Date of API call: September 12, 2023 For questions or feedback send an email to places@cdc.gov.

This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four 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. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2020 population counts, and American Community Survey (ACS) 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the Census 2021 ZCTA boundary file in a GIS system to produce maps for 40 measures at the ZCTA level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

This web map was developed by the USDA Forest Service Forest Inventory and Analysis (FIA) program at the Northern Research Station. The web map depicts the distribution and mean basal area (square feet per acre) of sassafras, the year of laurel wilt disease invasion from 2004-2018 by US county, and estimates of volume, growth, removals and mortality of sassafras for 2006, 2011 and 2016 by US county. The underlying layers have been attributed with outputs from FIA's EVALIDator tool for the following estimates:Net merchantable bole volume of live trees (at least 5 inches d.b.h./d.r.c.), in cubic feet, on forest land 2006Net merchantable bole volume of live trees (at least 5 inches d.b.h./d.r.c.), in cubic feet, on forest land 2011Net merchantable bole volume of live trees (at least 5 inches d.b.h./d.r.c.), in cubic feet, on forest land 2016Average annual gross growth of merchantable bole volume of trees (at least 5 inches d.b.h./d.r.c.), in cubic feet, on forest land 2016Average annual net growth of merchantable bole volume of trees (at least 5 inches d.b.h./d.r.c.), in cubic feet, on forest land 2016Average annual mortality of merchantable bole volume of trees (at least 5 inches d.b.h./d.r.c.), in cubic feet, on forest land 2016Average annual removals of merchantable bole volume of trees (at least 5 inches d.b.h./d.r.c.), in cubic feet, on forest land 2016 Please see individual layers below for additional detail, including how to cite appropriate sources.

This map features new data from the US CDC, mapping Behavioral Risk Factors Data at the Census Tract level for the first time.For more info, see the CDC webpage on Chronic Disease and Health Promotion Data & Indicators: https://chronicdata.cdc.gov/health-area/behavioral-risk-factors.NMCDC has built the feature service that runs this map and made it available for sharing on your own AGOL map. It contains 27 adult behavioral risk factors for 206 census tracts in NM's four major cities (Albuquerque, Rio Rancho, Santa Fe and Las Cruces). Feature service information at - http://nmcdc.maps.arcgis.com/home/item.html?id=bd74a088596e48358b22ae76a32a2631#overview "The purpose of the 500 Cities Project is to provide city- and census tract-level small area estimates for chronic disease risk factors, health outcomes, and clinical preventive service use for the largest 500 cities in the United States. These small area estimates will allow cities and local health departments to better understand the burden and geographic distribution of health-related variables in their jurisdictions, and assist them in planning public health interventions. Learn more about the 500 Cities Project(https://www.cdc.gov/500cities/about.htm)."

This map shows the estimated distribution of areas where the American dog tick (Dermacentor variabilis) could survive and reproduce (yellow), and counties where established populations have been documented (red). Counties classified as “established” are those where six or more D. variabilis of a single life stage (larvae, nymph, or adult) or more than one life stage of the tick were collected in the county within a 12-month period. Counties classified as “reported” are counties where American dog tick(s) were collected, but do not meet the criteria for “established” classification. Counties classified as “no records” may be the result of sampling with no American dog ticks collected, a lack of sampling efforts, or a lack of reporting and publishing the results of sampling efforts. Tooltips, available in the map when users click on a county, provide the state, name of county, and the status of the American dog tick in the county. Using year selection buttons, the user can also select the year the cumulative map data were reported. Data used to make this map are provided through the work of U.S. state and local public health agencies, academic institutions, and partner agencies. Reference MaterialsCDC Ticks Website CDC Tick Surveillance Tickborne Diseases of the United States Contact Informationticksurveillance@cdc.gov

This web map is part of the Centers for Disease Control and Prevention (CDC) PLACES. It provides model-based estimates of stroke prevalence among adults aged 18 years and older at county, place, census tract, and ZCTA levels in the United States. PLACES is an expansion of the original 500 Cities Project and a collaboration between the CDC, the Robert Wood Johnson Foundation, and the CDC Foundation. Data sources used to generate these estimates include the Behavioral Risk Factor Surveillance System (BRFSS), Census 2020 population counts or Census annual county-level population estimates, and the American Community Survey (ACS) estimates. For detailed methodology see www.cdc.gov/places. For questions or feedback send an email to places@cdc.gov.Measure name used for stroke is STROKE.

2019 - 2021, county-level U.S. heart disease hospitalization rates. Dataset developed by the Centers for Disease Control and Prevention, Division for Heart Disease and Stroke Prevention.Create maps of U.S. heart disease hospitalization rates among Medicare fee-for-service beneficiaries aged 65 and older, by county. Data can be stratified by race/ethnicity and sex.Visit the CDC Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceHospitalization data were obtained from the Centers for Medicare and Medicaid Services Medicare Provider Analysis and Review (MEDPAR) file, Part A and the Master Beneficiary Summary File (MBSF). International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes: I00-I09, I11, I13, I20-I51; principle (i.e., first-listed) diagnosis. Medicare fee-for-service beneficiaries 65 and older were included. Visit the Atlas of Heart Disease and Stroke Statistical Methods pages for more detailed Medicare data inclusion criteriaData DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.'Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., API_M_35UP)  RRR: 3 digits represent race/ethnicity    All - Overall   BLK - Black, non-Hispanic    HIS - Hispanic    WHT - White, non-Hispanic  S: 1 digit represents sex    A - All    F - Female    M - Male  aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound. Example: The column 'BLK_M_65UP' displays rates per 1,000 black Medicare beneficiaries aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 1,000 Medicare beneficiaries. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and sex).At least one of the following 3 criteria:At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods

This feature layer was created using the Join Features tool on ArcGIS Online. It contains county by county case counts of Lyme disease from 2000 to 2021. It is primarily used for dot density visualizations. It also contains estimated US county populations for 2020. United states data only.Reference MaterialsLyme Disease WebsiteLyme Disease Maps Contact Informationbdbepigroup@cdc.gov

This map displays data from the Selected Economic Indicators (DP03) dataset from the 2010 American Community Survey 5-Yr Estimates, U.S. Census Bureau. Data is shown at the level of Census Tract, County, and Small Area (aggregation of Census Tracts developed by the New Mexico Department of Health). Measuring poverty is a topic of much current discussion. See the following links: A Different Way to Measure Poverty - http://www.sanders.senate.gov/imo/media/image/census.jpg"Few topics in American society have more myths and stereotypes surrounding them than poverty, misconceptions that distort both our politics and our domestic policy making."They include the notion that poverty affects a relatively small number of Americans, that the poor are impoverished for years at a time, that most of those in poverty live in inner cities, that too much welfare assistance is provided and that poverty is ultimately a result of not working hard enough. Although pervasive, each assumption is flat-out wrong." -Mark Rank, Professor of Social Welfare at Washington University: http://opinionator.blogs.nytimes.com/2013/11/02/poverty-in-america-is-mainstream/