This map service displays data derived from the 2008-2012 American Community Survey (ACS). Values derived from the ACS and used for this map service include: Total Population, Population Density (per square mile), Percent Minority, Percent Below Poverty Level, Percent Age (less than 5, less than 18, and greater than 64), Percent Housing Units Built Before 1950, Percent (population) 25 years and over (with less than a High School Degree and with a High School Degree), Percent Linguistically Isolated Households, Population of American Indians and Alaskan Natives, Population of American Indians and Alaskan Natives Below Poverty Level, and Percent Low Income Population (Less Than 2X Poverty Level). The map service was created for inclusion in US EPA mapping applications.

Data SourcesAmerican Community Survey (ACS):Conducted by: U.S. Census BureauDescription: The ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.Content: The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.Frequency: The ACS offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.Purpose: ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by: ATSDR’s Geospatial Research, Analysis & Services Program (GRASP)Utilized by: CDCDescription: The SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.Content: SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themes. Each tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability.Purpose: SVI data provides insights into the social vulnerability of communities at both the tract and zip code levels, helping public health officials and emergency response planners allocate resources effectively.Utilization and IntegrationBy integrating data from both the ACS and the SVI, this dataset enables an in-depth analysis and understanding of various socio-economic and demographic indicators at the census tract level. This integrated data is valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United States.ApplicationsTargeted Interventions: Facilitates the development of targeted interventions to address the needs of vulnerable populations within specific zip codes.Resource Allocation: Assists emergency response planners in allocating resources more effectively based on community vulnerability at the zip code level.Research: Provides a rich dataset for academic and applied research in socio-economic and demographic studies at a granular zip code level.Community Planning: Supports the planning and development of community programs and initiatives aimed at improving living conditions and reducing vulnerabilities within specific zip code areas.Note: Due to limitations in the data environment, variable names may be truncated. Refer to the provided table for a clear understanding of the variables. CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2013-2017 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2013-2017 ACSEP_PCIEP_PCIPer capita income estimate, 2013-2017 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2013-2017 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2013-2017 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2013-2017 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2013-2017 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2014-2018 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computerThis table provides a mapping between the CSV variable names and the shapefile variable names, along with a brief description of each variable.

This map service displays data derived from the 2006-2010 American Community Survey (ACS). Values derived from the ACS and used for this map service include: Total Population, Population Density (per square mile), Percent Minority, Percent Below Poverty Level, Percent Age (less than 5, less than 18, and greater than 64), Percent Housing Units Built Before 1950, Percent (population) 25 years and over (with less than a High School Degree and with a High School Degree), Percent Linguistically Isolated Households, Population of American Indians and Alaskan Natives, Population of American Indians and Alaskan Natives Below Poverty Level. The map service was created for inclusion in US EPA mapping applications.

The Vulnerable Population Index (VPI) is intended to guide location selection and stakeholder identification for public involvement and inform Title VI and Environmental Justice (EJ) performance measurement. The Baltimore Regional Transportation Board uses data from the US Census Bureau to determine the concentrations of seven sensitive populations for the region and for each census tract. A tract with a concentration of a sensitive population greater than the concentration of the Baltimore region as a whole is considered to be “vulnerable” for the sensitive population. The Vulnerable Population Index (VPI) indicated the number of vulnerable populations for each tract, and thus provides a general indication of the extent to which each tract is vulnerable. The VPI looks at the following variables:Population in Poverty (American Community Survey 2006-2010 5-Year Estimates)Age 75 and up (Census 2010) Non-Hispanic Minority (people who are non-White and non-Hispanic) (Census 2010) Hispanic or Latino Heritage (Census 2010)Limited English Proficiency (population who speaks English “not well” or “not at all.”) (American Community Survey 2006-2010 5-Year Estimates)Households with No Car (American Community Survey 2006-2010 5-Year Estimates)Disabled Population (Census 2000) This data was used in the interactive mapping application found at http://gis.baltometro.org/Application/VPI/index.html. For more information on Transportation Equity work and studies at BMC, go to http://www.baltometro.org/about-the-brtb/transportation-equity. Note that for ACS and Census 2000 data margins of error are not provided. This data has been modified by the Baltimore Metropolitan Council and should not replace data directly loaded from the Census.Source: Variables are American Community Survey 2006-2010 5-Year Estimates, the 2000 Census (SF3), and the 2010 Census. Census tracts are the 2010 Census. Main Index is calculated by BMC.Date: Index published in May 2015. Date of raw data is either 2000, 2010, or 2006-2010 depending on the variable. See the above list for more information.Update: The VPI is updated approximately every 5 years. Data will be added as a separate layer.Data fields:PCT_NotWhite_NotHisp - Percent of the population in each tract that is a non-Hispanic minority. PCT_Hispanic - Percent of the population in each tract that is Hispanic or Latino. Pct75up - Percent of the population in each tract that is age 75 or higher. PCT_LEP - Percent of the Limited English Proficiency population in each tract.PCT_People_in_Poverty - Percent of the population in each tract that is living below the Federal poverty level.PCT_NOCAR - Percent of households in each tract that do not have a car.PCT_Disabl - Percent of the population in each tract that is disabled. Reg_NotWhite_NotHisp - Regional average for the population that is a non-Hispanic minority. This is for the same time period as the tract data. Reg_Hispanic - Regional average for the population that is Hispanic or Latino. This is for the same time period as the tract data. Reg_75up - Regional average for the population that is age 75 or higher. This is for the same time period as the tract data. Reg_LEP - Regional average for the Limited English Proficiency population. This is for the same time period as the tract data. Reg_Poverty - Regional average for the population that is living below the Federal poverty level. This is for the same time period as the tract data. Reg_NOCAR - Regional average for percent of households that do not have a car. This is for the same time period as the tract data. Reg_Disabl - Regional average for the population that is disabled. This is for the same time period as the tract data. FLAG_NotWhite_NotHisp - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_Hispanic - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_75up - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_LEP - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_Poverty - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_NOCAR - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". FLAG_Disabl - This is used to determine the VPI. It is "1" if the tract number is greater than the regional average. Otherwise it is "0". INDEX - The sum of all the FLAG fields.

we utilized data from two main sources: the United States Census Bureau's American Community Survey (ACS) and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI).American Community Survey (ACS):Conducted by the U.S. Census Bureau, the ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.It offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.The ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) and utilized by the CDC, the SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themesEach tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability.SVI data provides insights into the social vulnerability of communities at both the tract and county levels, helping public health officials and emergency response planners allocate resources effectively. In our utilization of these sources, we likely integrated data from both the ACS and the SVI to analyze and understand various socio-economic and demographic indicators at the state, county, and possibly tract levels. This integrated data would have been valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United StatesNote: Due to limitations in the ArcGIS Pro environment, the data variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2014-2018 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2015-2019 ACSEP_PCIEP_PCIPer capita income estimate, 2015-2019 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2015-2019 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2015-2019 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2015-2019 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2015-2019 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2014-2018 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computerThis table provides a mapping between the CSV variable names and the shapefile variable names, along with a brief description of each variable.

The Public Use Database (PUDB) is released annually to meet FHFA’s requirement under 12 U.S.C. 4543 and 4546(d) to publicly disclose data about the Enterprises’ single-family and multifamily mortgage acquisitions. The datasets supply mortgage lenders, planners, researchers, policymakers, and housing advocates with information concerning the flow of mortgage credit in America’s neighborhoods. Beginning with data for mortgages acquired in 2018, FHFA has ordered that the PUDB be expanded to include additional data that is the same as the data definitions used by the regulations implementing the Home Mortgage Disclosure Act, as required by 12 U.S.C. 4543(a)(2) and 4546(d)(1).The PUDB single-family datasets include loan-level records that include data elements on the income, race, and sex of each borrower as well as the census tract location of the property, loan-to-value (LTV) ratio, age of mortgage note, and affordability of the mortgage. New for 2018 are the inclusion of the borrower’s debt-to-income (DTI) ratio and detailed LTV ratio data at the census tract level. The PUDB multifamily property-level datasets include information on the unpaid principal balance and type of seller/servicer from which the Enterprise acquired the mortgage. New for 2018 is the inclusion of property size data at the census tract level. The multifamily unit-class files also include information on the number and affordability of the units in the property. Both the single-family and multifamily datasets include indicators of whether the purchases are from “underserved” census tracts, as defined in terms of median income and minority percentage of population.Prior to 2010 the single-family PUDB consisted of three files: Census Tract, National A, and National B files. With the 2010 PUDB a fourth file, National C, was added to provide information on high-cost mortgages acquired by the Enterprises. The single-family Census Tract file includes information on the location of the property based on the 2010 Census for acquisition years 2012 through 2021, and the 2020 Census beginning with the 2022 acquisition year. The National files contain other information but lack detailed geographic information in order to protect Enterprise proprietary data. The multifamily datasets also consist of a Census Tract file, and a National file without detailed geographic information.Several dashboards are available to analyze the data:Enterprise Multifamily Public Use Database DashboardThe Enterprise Multifamily Public Use Database (PUDB) Dashboard provides users an interactive way to generate and visualize Enterprise PUDB data of multifamily mortgage acquisitions by Fannie Mae and Freddie Mac. It shows characteristics about multifamily loans, properties and units at the national level, and characteristics about multifamily loans and properties at the state level. It includes key statistics, time series charts, and state maps of multifamily housing characteristics such as median loan amount, number of properties, average number of units per property, and unit affordability. The underlying aggregate statistics presented in the dashboard come from three multifamily data files in the Enterprise PUDB, updated annually since 2008, including two property-level datasets and a data file on the size and affordability of individual units.Enterprise Multifamily Public Use DashboardPress Release - FHFA Releases Data Visualization Dashboard for Enterprises’ Multifamily Mortgage AcquisitionsMortgage Loan and Natural Disaster DashboardFHFA published an interactive Mortgage Loan and Natural Disaster Dashboard that combines FHFA’s PUDB reports on single-family and multifamily acquisitions for the regulated entities, FEMA’s National Risk Index (NRI), and FHFA’s Duty to Serve 2023 High-Needs rural areas. Desired geographies can be exported to .pdf and Excel from the Public Use Database and National Risk Index Dashboard.Mortgage Loan and Natural Disaster DashboardMortgage Loan and Natural Disaster Dashboard FAQs

This map contains the 2020 Vulnerable Population Index along with the component demographic layers. The following seven populations were determined to be vulnerable based on an understanding of both federal requirements and regional demographics: 1) Low-Income Population (below 200% of poverty level) 2) Non-Hispanic Minority Population 3) Hispanic or Latino Population (all races) 4) Population with Limited English Proficiency (LEP) 5) Population with Disabilities 6) Elderly Population (age 75 and up) 7) Households with No CarFor each of these populations, Census tracts with concentrations above the regional mean concentration are divided into two categories above the regional mean. These categories are calculated by dividing the range of values between the regional mean and the regional maximum into two equal-sized intervals. Tracts in the lower interval are given a score of 1 and tracts in the upper interval are given a score of 2 for that demographic variable. The scores are totaled from the seven individual demographic variables to yield the Vulnerable Population Index (VPI). The VPI can range from zero to fourteen (0 to 14). A lower VPI indicates a less vulnerable area, while a higher VPI indicates a more vulnerable area.FIELDSP_PovL100: Percent Below 100% of the Poverty Level, P_PovL200: Percent Below 200% of the Poverty Level, P_Minrty: Percent Minority (non-White, non-Hispanic), P_Hisp: Percent Hispanic, P_LEP: Percent Limited English Proficiency (speak English "not well" or "not at all"), P_Disabld: Percent with Disabilities, P_Elderly: Percent Elderly (age 75 and over), P_NoCarHH: Percent Households with No Vehicle, RG_PovL100: Regional Average (Mean) of Percent Below 100% of the Poverty Level, RG_PovL200: Regional Average (Mean) of Percent Below 200% of the Poverty Level, RG_Minrty: Regional Average (Mean) of Percent Minority (non-White, non-Hispanic), RG_Hisp: Regional Average (Mean) of Percent Hispanic, RG_LEP: Regional Average (Mean) of Percent Limited English Proficiency (speak English "not well" or "not at all"), RG_Disabld: Regional Average (Mean) of Percent with Disabilities, RG_Elderly: Regional Average (Mean) of Percent Elderly (age 75 and over), RG_NoCarHH: Regional Average (Mean) of Percent Households with No Vehicle, [NO SC_PovL100: Note: Percent Below 100% of the Poverty Level not used in VPI 2020 calculation],SC_PovL200: VPI Score for Below 200% of the Poverty Level (Values: 0, 1, or 2),SC_Minrty: VPI Score for Minority (non-White, non-Hispanic) (Values: 0, 1, or 2),SC_Hisp: VPI Score for Hispanic (Values: 0, 1, or 2),SC_LEP: VPI Score for Limited English Proficiency (speak English "not well" or "not at all") (Values: 0, 1, or 2),SC_Disabld: VPI Score for Disabilities (Values: 0, 1, or 2),SC_Elderly: VPI Score for Elderly (age 75 and over) (Values: 0, 1, or 2),SC_NoCarHH: VPI Score for Households with No Vehicle (Values: 0, 1, or 2),VPI_2020: Total VPI Score (0 minimum to 14 maximum).Additional information on equity planning at BMC can be found here.Sources: Baltimore Metropolitan Council, U.S. Census Bureau 2016–2020 American Community Survey 5-Year Estimates. Margins of error are not shown.Updated: April 2022

Data Sources2020 census tract boundaries are from the TIGER/Line Shapefile, 2021, State, Florida, Census Tracts shapefile. More information can be found at https://catalog.data.gov/dataset/tiger-line-shapefile-2021-state-florida-census-tracts. Land cover data was obtained form the National Land Cover Database. The NLCD 2019 Land Cover (CONUS) file was used and can be accessed at https://www.mrlc.gov/data?f%5B0%5D=year%3A2019.Data from the following American community survey 2021 5 year tables were also used. These tables can be accessed at https://data.census.gov/DP02: SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATESDP03: SELECTED ECONOMIC CHARACTERISTICSS0101: AGE AND SEXS1902: MEAN INCOME IN THE PAST 12 MONTHS (IN 2021 INFLATION-ADJUSTED DOLLARS)S2303: WORK STATUS IN THE PAST 12 MONTHSS2501OCCUPANCY CHARACTERISTICSVariablesThe following variables were used to create the index:Percent Ages <18 or >65Percent without a high school diplomaUnemployment ratePoverty RateHousehold IncomePercent with a disabilityPercent who are foreign bornPercent who speak a language other than English at home.Percent without health insurancePercent who live alonePercent ages 65+ who live alonePercent belonging to a minority groupPercent of the tract made up of green spaceMethodsPrincipal component analysis was used to reduce these variables into four factors with the following primary variables:Factor 1 - Socioeconomic: percent without a high school diploma, poverty rate, unemployment rate, household income, percent without health insuranceFactor 2 - Cultural/Environmental: percent foreign born, percent who speak a language other than English at home, percent belonging to a minority group, percent of the tract classified as green spaceFactor 3 - Living Alone: percent with a disability, percent who live alone, percent ages 65+ who live aloneFactor 4 - Biological Vulnerability: percent Ages <18 or >65, percent with a disabilityFactor scores were calculated for each tract and the mean (average) and standard deviation were calculated. The standard deviation is a measure of how far away a tract's score is from the average. The tracts were then split into six categories based on their standard deviation, with standard deviations further above the mean indicating higher vulnerability and standard deviations further below the mean indicating lower vulnerability. This process was repeated for all four factors and these categories are displayed in this map.

we utilized data from two main sources: the United States Census Bureau's American Community Survey (ACS) and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI). American Community Survey (ACS):

Conducted by the U.S. Census Bureau, the ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States. The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions. It offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households. The ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.

CDC/ATSDR Social Vulnerability Index (SVI):

Created by ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) and utilized by the CDC, the SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events. SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themes Each tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability. SVI data provides insights into the social vulnerability of communities at both the tract and county levels, helping public health officials and emergency response planners allocate resources effectively.

In our utilization of these sources, we likely integrated data from both the ACS and the SVI to analyze and understand various socio-economic and demographic indicators at the state, county, and possibly tract levels. This integrated data would have been valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United States

Note: Due to limitations in the ArcGIS Pro environment, the data variable names may be truncated. Refer to the provided table for a clear understanding of the variablesCSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2014-2018 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2014-2018 ACSEP_PCIEP_PCIPer capita income estimate, 2014-2018 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2014-2018 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2014-2018 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2014-2018 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2014-2018 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2014-2018 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computer

US Census Bureau data were matched to U.S. Environmental Protection Agency estimated cancer risks from airborne toxics from 2011 to 2019 to explore environmental inequality with nationwide census tract resolution. Spearman correlations showed modest associations between various socioeconomic status factors and estimated cancer risk. Multiple linear regression analyses show positive associations with increased estimated cancer risk (p < 0.05) for high proportions of Blacks in suburban and rural areas. A positive relationship with estimated cancer risk was found for increasing proportions of Asians and Hispanics in nonurban areas. Urban tracts that suffer from the highest estimated cancer risks were concentrated among the communities with a population of higher proportion of minorities. While environmental inequality seems to have improved across the examined years for certain demographics with respect to estimated cancer risk from air toxics, equity is far from achieved, and future work in identifying the sources of environmental inequality could help in achieving a more just environment.

Overall Social Vulnerability at Census Block Group based on the following 4 themes: Socioeconomic, Household Composition, Minority Status and language, Housing Type and Transportation.

Percentile ranking values range from 0 to 1, with higher values indicating greater social vulnerability.

Every community must prepare for and respond to hazardous events, whether a natural disaster like a tornado or a disease outbreak, or an anthropogenic event such as a harmful chemical spill. The degree to which a community exhibits certain social conditions, including high poverty, low percentage of vehicle access, or crowded households, among others, may affect that community’s ability to prevent human suffering and financial loss in the event of a disaster. These factors describe a community’s social vulnerability.

To learn more about the CDC SVI Methodology please visit: https://www.atsdr.cdc.gov/placeandhealth/svi/index.html

DCR prepared a SVI Data at census block level (CDC analyzes to Census Tract only) from the following sources:

Credit to IPUMS National Historical Geographic Information System (NHGIS) for providing geographic features that correspond to summary data from the U.S. 2020 Decennial Census and American Community Survey, at the geographic summary level of Block Group. NHGIS derived this shapefile from the U.S. Census Bureau's 2020 TIGER/Line Shapefiles.

Credit to Micheal Bryan, 2022 for publishing CDC SVI data at census block scale for more information visit:

https://github.com/OpenEnvironments/blockgroupvulnerability

This map contains the 2020 Vulnerable Population Index along with the component demographic layers. The following seven populations were determined to be vulnerable based on an understanding of both federal requirements and regional demographics: 1) Low-Income Population (below 200% of poverty level) 2) Non-Hispanic Minority Population 3) Hispanic or Latino Population (all races) 4) Population with Limited English Proficiency (LEP) 5) Population with Disabilities 6) Elderly Population (age 75 and up) 7) Households with No CarFor each of these populations, Census tracts with concentrations above the regional mean concentration are divided into two categories above the regional mean. These categories are calculated by dividing the range of values between the regional mean and the regional maximum into two equal-sized intervals. Tracts in the lower interval are given a score of 1 and tracts in the upper interval are given a score of 2 for that demographic variable. The scores are totaled from the seven individual demographic variables to yield the Vulnerable Population Index (VPI). The VPI can range from zero to fourteen (0 to 14). A lower VPI indicates a less vulnerable area, while a higher VPI indicates a more vulnerable area.FIELDSP_PovL100: Percent Below 100% of the Poverty Level, P_PovL200: Percent Below 200% of the Poverty Level, P_Minrty: Percent Minority (non-White, non-Hispanic), P_Hisp: Percent Hispanic, P_LEP: Percent Limited English Proficiency (speak English "not well" or "not at all"), P_Disabld: Percent with Disabilities, P_Elderly: Percent Elderly (age 75 and over), P_NoCarHH: Percent Households with No Vehicle, RG_PovL100: Regional Average (Mean) of Percent Below 100% of the Poverty Level, RG_PovL200: Regional Average (Mean) of Percent Below 200% of the Poverty Level, RG_Minrty: Regional Average (Mean) of Percent Minority (non-White, non-Hispanic), RG_Hisp: Regional Average (Mean) of Percent Hispanic, RG_LEP: Regional Average (Mean) of Percent Limited English Proficiency (speak English "not well" or "not at all"), RG_Disabld: Regional Average (Mean) of Percent with Disabilities, RG_Elderly: Regional Average (Mean) of Percent Elderly (age 75 and over), RG_NoCarHH: Regional Average (Mean) of Percent Households with No Vehicle, [NO SC_PovL100: Note: Percent Below 100% of the Poverty Level not used in VPI 2020 calculation],SC_PovL200: VPI Score for Below 200% of the Poverty Level (Values: 0, 1, or 2),SC_Minrty: VPI Score for Minority (non-White, non-Hispanic) (Values: 0, 1, or 2),SC_Hisp: VPI Score for Hispanic (Values: 0, 1, or 2),SC_LEP: VPI Score for Limited English Proficiency (speak English "not well" or "not at all") (Values: 0, 1, or 2),SC_Disabld: VPI Score for Disabilities (Values: 0, 1, or 2),SC_Elderly: VPI Score for Elderly (age 75 and over) (Values: 0, 1, or 2),SC_NoCarHH: VPI Score for Households with No Vehicle (Values: 0, 1, or 2),VPI_2020: Total VPI Score (0 minimum to 14 maximum).Additional information on equity planning at BMC can be found here.Sources: Baltimore Metropolitan Council, U.S. Census Bureau 2016–2020 American Community Survey 5-Year Estimates. Margins of error are not shown.Updated: April 2022

This dataset includes six tables which were custom ordered from Statistics Canada. All tables include commuting characteristics (mode of commuting, duration/distance), labour characteristics (employment income groups in 2015, Industry by the North American Industry Classification System 2012), and visible minority groups. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and variables: Geography: Place of Work (POW), Census Tract (CT) within CMA Vancouver. The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. However, it will be provided upon request. GNR values for POR and POW are different for each geography. Universe: The Employed Labour Force having a usual place of work for the population aged 15 years and over in private households that are rented (Tenure rented), full year-full time workers (40-52weeks) Variables: Visible minority (15) 1. Total - Visible minority 2. Total visible minority population 3. South Asian 4. Chinese 5. Black 6. Filipino 7. Latin American 8. Arab 9. Southeast Asian 10. West Asian 11. Korean 12. Japanese 13. Visible minority, n.i.e. 14. Multiple visible minorities 15. Not a visible minority Commuting duration and distance (18) 1. Total - Commuting duration 2. Less than 15 minutes 3. 15 to 29 minutes 4. 30 to 44 minutes 5. 45 to 59 minutes 6. 60 minutes and over 7. Total - Commuting distance 8. Less than 1 km 9. 1 to 2.9 km 10. 3 to 4.9 km 11. 5 to 6.9 km 12. 7 to 9.9 km 13. 10 to 14.9 km 14. 15 to 19.9 km 15. 20 to 24.9 Km 16. 25 to 29.9 km 17. 30 to 34.9 km 18. 35 km or more Main mode of commuting (7) 1. Total - Main mode of commuting 2. Driver, alone 3. 2 or more persons shared the ride to work 4. Public transit 5. Walked 6. Bicycle 7. Other method Employment income groups in 2015 (39) 1. Total – Total Employment income groups in 2015 2. Without employment income 3. With employment income 4. Less than $30,000 (including loss) 5. $30,000 to $79,999 6. $30,000 to $39,999 7. $40,000 to $49,999 8. $50,000 to $59,999 9. $60,000 to $69,999 10. $70,000 to $79,999 11. $80,000 and above 12. Median employment income ($) 13. Average employment income ($) 14. Total – Male Employment income groups in 2015 15. Without employment income 16. With employment income 17. Less than $30,000 (including loss) 18. $30,000 to $79,999 19. $30,000 to $39,999 20. $40,000 to $49,999 21. $50,000 to $59,999 22. $60,000 to $69,999 23. $70,000 to $79,999 24. $80,000 and above 25. Median employment income ($) 26. Average employment income ($) 27. Total – Female Employment income groups in 2015 28. Without employment income 29. With employment income 30. Less than $30,000 (including loss) 31. $30,000 to $79,999 32. $30,000 to $39,999 33. $40,000 to $49,999 34. $50,000 to $59,999 35. $60,000 to $69,999 36. $70,000 to $79,999 37. $80,000 and above 38. Median employment income ($) 39. Average employment income ($) Industry - North American Industry Classification System (NAICS) 2012 (54) 1. Total - Industry - North American Industry Classification System (NAICS) 2012 2. 11 Agriculture, forestry, fishing and hunting 3. 21 Mining, quarrying, and oil and gas extraction 4. 22 Utilities 5. 23 Construction 6. 236 Construction of buildings 7. 237 Heavy and civil engineering construction 8. 238 Specialty trade contractors 9. 31-33 Manufacturing 10. 311 Food manufacturing 11. 41 Wholesale trade 12. 44-45 Retail trade 13. 441 Motor vehicle and parts dealers 14. 442 Furniture and home furnishings stores 15. 443 Electronics and appliance stores 16. 444 Building material and garden equipment and supplies dealers 17. 445 Food and beverage stores 18. 446 Health and personal care stores 19. 447 Gasoline stations 20. 448 Clothing and clothing accessories stores 21. 451 Sporting goods, hobby, book and music stores 22. 452 General merchandise stores 23. 453 Miscellaneous store retailers 24. 454 Non-store retailers 25. 48-49 Transportation and warehousing 26. 481 Air transportation 27. 482 Rail transportation 28. 483 Water...

Data SourcesAmerican Community Survey (ACS):Conducted by: U.S. Census BureauDescription: The ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.Content: The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.Frequency: The ACS offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.Purpose: ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by: ATSDR’s Geospatial Research, Analysis & Services Program (GRASP)Utilized by: CDCDescription: The SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.Content: SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themes. Each tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability.Purpose: SVI data provides insights into the social vulnerability of communities at both the tract and county levels, helping public health officials and emergency response planners allocate resources effectively.Utilization and IntegrationBy integrating data from both the ACS and the SVI, this dataset enables an in-depth analysis and understanding of various socio-economic and demographic indicators at the census tract level. This integrated data is valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United States.ApplicationsPolicy Development: Helps policymakers develop targeted interventions to address the needs of vulnerable populations.Resource Allocation: Assists emergency response planners in allocating resources more effectively based on community vulnerability.Research: Provides a robust foundation for academic and applied research in socio-economic and demographic studies.Community Planning: Aids in the planning and development of community programs and initiatives aimed at improving living conditions and reducing vulnerabilities.Note: Due to limitations in the ArcGIS Pro environment, the data variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2013-2017 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2013-2017 ACSEP_PCIEP_PCIPer capita income estimate, 2013-2017 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2013-2017 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2013-2017 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2013-2017 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2013-2017 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2013-2017 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computer

Feature class representing retail alcohol outlet density at the census tract level developed directly from address information from liquor licensee lists that were obtained from the Colorado Department of Revenue-Liquor Enforcement Division (DOR-LED). This file was developed for use in activities and exercises within the Colorado Department of Public Health and Environment (CDPHE), including the Alcohol Outlet Density StoryMap. CDPHE nor DOR-LED are responsible for data products made using this publicly available data. It should be stated that neither agency is acting as an active data steward of this map service/geospatial data layer at this point in time. This dataset is representative of Colorado licensing data gathered in January 2024. The data file contains the following attributes:FIPSTract Name Tract FIPS StateCountyLand Area Square Miles (Area of Land in Square Miles)Water Area SquareMiles (Area of Water in Square Miles)Population Total (Total Population as estimated in ACS 2018-2022)Percent Race White (Percent of population identifying as White as estimated in ACS 2018-2022) Percent Race African American Percent (Percent of population identifying as African American as estimated in ACS 2018-2022)Race American Indian Alaskan Native (Percent of population identifying as American Indian or Alaskan Native as estimated in ACS 2018-2022)Percent Race Asian (Percent of population identifying as Asian as estimated in ACS 2018-2022)Percent Race NHawaiian OPI (Percent of population identifying as Native Hawaiian or Pacific Islander as estimated in 2018-2022)Percent Race Other (Percent of population identifying as another race as estimated in 2018-2022)Percent Ethnicity Hispanic Latino (Percent of population identifying as Hispanic or Latino as estimated in 2018-2022)Percent Ethnicity Not Hispanic or Latino (Percent of population identifying as not Hispanic or Latino as estimated in 2018-2022)Percent Race Minority Race or Hispanic Latino (Percent of population made up of a Race and/or Ethnicity other than White, Non-Hispanic)Percent Population over 24 Years No HS Diploma (Percent of population over 24 years old without a High School Diploma as estimated in 2018-2022)Frequency All Retail Outlets 2024 (All retail alcohol outlets from January 2024)Average Distance Between Outlets in Meters (Average distance in Meters between an alcohol outlet and its nearest neighboring outlet)Frequency Off Premises Outlets 2024 (All Off-premises retail alcohol outlets from January 2024)Frequency On Premises Outlets 2024 (All On-premises retail alcohol outlets from January 2024)Rate Total Outlets per Square Mile (Rate of all retail alcohol outlets per square mile)Rate Total Outlets per 1,000 Residents (Rate of all retail alcohol outlets per 1,000 residents)Rate On Premises Outlets per Square Mile (Rate of On-premises retail alcohol outlets per square mile)Rate Off Premises Outlets per Square Mile (Rate of On-premises retail alcohol outlets per square mile)Rate On Premises Outlets per 1,000 Residents (Rate of on-premises retail alcohol outlets per 1,000 residents)Rate Off Premises Outlets per 1,000 Residents (Rate of off-premises retail alcohol outlets per 1,000 residents)Average Distance Between Outlets in Miles (Average distance in Miles between an alcohol outlet and its nearest neighboring outlet)

we utilized data from two main sources: the United States Census Bureau's American Community Survey (ACS) and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI). American Community Survey (ACS):

Conducted by the U.S. Census Bureau, the ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States. The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions. It offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households. The ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.

CDC/ATSDR Social Vulnerability Index (SVI):

Created by ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) and utilized by the CDC, the SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events. SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themes Each tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability. SVI data provides insights into the social vulnerability of communities at both the tract and county levels, helping public health officials and emergency response planners allocate resources effectively.

In our utilization of these sources, we likely integrated data from both the ACS and the SVI to analyze and understand various socio-economic and demographic indicators at the state, county, and possibly tract levels. This integrated data would have been valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United States

Note: Due to limitations in the ArcGIS Pro environment, the data variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2015-2019 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2015-2019 ACSEP_PCIEP_PCIPer capita income estimate, 2015-2019 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2015-2019 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2015-2019 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2015-2019 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2015-2019 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2014-2018 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computer

we utilized data from two main sources: the United States Census Bureau's American Community Survey (ACS) and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI).American Community Survey (ACS):Conducted by the U.S. Census Bureau, the ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.It offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.The ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) and utilized by the CDC, the SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.

we utilized data from two main sources: the United States Census Bureau's American Community Survey (ACS) and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI). American Community Survey (ACS):

Conducted by the U.S. Census Bureau, the ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States. The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions. It offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households. The ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.

CDC/ATSDR Social Vulnerability Index (SVI):

Created by ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) and utilized by the CDC, the SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events. SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themes Each tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability. SVI data provides insights into the social vulnerability of communities at both the tract and county levels, helping public health officials and emergency response planners allocate resources effectively.

In our utilization of these sources, we likely integrated data from both the ACS and the SVI to analyze and understand various socio-economic and demographic indicators at the state, county, and possibly tract levels. This integrated data would have been valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United States

Note: Due to limitations in the ArcGIS Pro environment, the data variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2014-2018 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2014-2018 ACSEP_PCIEP_PCIPer capita income estimate, 2014-2018 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2014-2018 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2014-2018 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2014-2018 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2014-2018 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2014-2018 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computer

This map shows the percentage of people who identify as something other than non-Hispanic white throughout the US according to the most current American Community Survey. The pattern is shown by states, counties, and Census tracts. Zoom or search for anywhere in the US to see a local pattern. Click on an area to learn more. Filter to your area and save a new version of the map to use for your own mapping purposes.The Arcade expression used was: 100 - B03002_calc_pctNHWhiteE, which is simply 100 minus the percent of population who identifies as non-Hispanic white. The data is from the U.S. Census Bureau's American Community Survey (ACS). The figures in this map update automatically annually when the newest estimates are released by ACS. For more detailed metadata, visit the ArcGIS Living Atlas Layer: ACS Race and Hispanic Origin Variables - Boundaries.The data on race were derived from answers to the question on race that was asked of individuals in the United States. The Census Bureau collects racial data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. The categories represent a social-political construct designed for collecting data on the race and ethnicity of broad population groups in this country, and are not anthropologically or scientifically based. Learn more here.Other maps of interest:American Indian or Alaska Native Population in the US (Current ACS)Asian Population in the US (Current ACS)Black or African American Population in the US (Current ACS)Hawaiian or Other Pacific Islander Population in the US (Current ACS)Hispanic or Latino Population in the US (Current ACS) (some people prefer Latinx)Population who are Some Other Race in the US (Current ACS)Population who are Two or More Races in the US (Current ACS) (some people prefer mixed race or multiracial)White Population in the US (Current ACS)Race in the US by Dot DensityWhat is the most common race/ethnicity?