National Center for Veterans and Analysis Statistics Population Maps are a compilation of facts related to the count of Veterans at multiple geographies.

Summary of statistics related to veterans in Wyoming, including veteran population and available facilities. Includes data charts and a map of veteran population distribution and VA facilities.

Map and tables with data describing Virginia's veteran population. Data tables cover: Veterans Affairs (VA) facilities and expenditures; veteran population including age distribution, period of service, household income, and educational attainment; veterans' use of VA healthcare and benefits; and projected veteran population changes as well as projections by age, gender, period of service, race/ethnicity, and age distribution over time.

This layer shows Veteran Counts by Sex and Age Group by Census Tract for 2012-2016. This tile layer is best viewed atop a darker basemap such as the Dark Blue Canvas. Click here to view the feature layer that includes margin of error fields and calculated percentages.There are currently over 19.6 million veterans in the United States.Data came from American Community Survey 5-year estimates and were retrieved from the Census Bureau's API on Sept. 27th, 2017 by Diana Lavery.

Map and tables with data describing Indiana's veteran population. Data tables cover: Veterans Affairs (VA) facilities and expenditures; veteran population including age distribution, period of service, household income, and educational attainment; veterans' use of VA healthcare and benefits; and projected veteran population changes as well as projections by age, gender, period of service, race/ethnicity, and age distribution over time.

Layer from Esri, which shows veteran status of adults (18+) broken down by age and sex. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of adults who are veterans. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. (This map is embedded in the Roanoke County Demographics Website, and thus the county has been filtered to be the only geography shown.)

This service contains the 2018-2022 release of data from the American Community Survey (ACS) 5-year data about Veteran Status, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of the civilian population over the age of 18 that are Veterans.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2018-2022ACS Table(s): DP02Data downloaded from: CensusBureau's API for American Community Survey Date of API call: January 18, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

Maps are organized by state and depict the Veteran population using VetPop2011 data as of 9/30/2013 and VA facilities using Veteran Affairs Site Tracking (VAST) data as of FY14Q1.

Map and tables with data describing Pennsylvania's veteran population. Data tables cover: Veterans Affairs (VA) facilities and expenditures; veteran population including age distribution, period of service, household income, and educational attainment; veterans' use of VA healthcare and benefits; and projected veteran population changes as well as projections by age, gender, period of service, race/ethnicity, and age distribution over time.

This service contains the 2017-2021 release of data from the American Community Survey (ACS) 5-year data about Veteran Status, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of the civilian population over the age of 18 that are Veterans.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2017-2021ACS Table(s): DP02Data downloaded from: CensusBureau's API for American Community Survey Date of API call: February 16, 2023National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

The Department of Veterans Affairs (VA) provides healthcare services to its veterans across the USA including territories and possessions. Healthcare services are delivered through 18 geographically divided administrative areas called Veterans Integrated Services Networks (VISN). Each VISN is divided into healthcare areas called Markets and Submarkets. Each Submarket is divided into Sectors and each Sector comprises one or more counties. In 1995 a process was created to coordinate and review the realignment of the Heath Care Networks. The Capital Asset Realignment for Enhanced Services (CARES) process established VISN 'subsets' called Markets, Submarkets and Sectors which, being smaller than VISNs, allowed for more precise analyses for greater access measurement to health care.

The County layer is the base geographic unit of the VISN-Market-Submarket-Sector-County hierarchy. The key attribute in this data set is the FIPS which is defined as a string of 5 characters with unique alphanumeric combinations for each site. The first 2 are the State FIPS code and the next 3 designate the County FIPS code. Example: '01031' is the FIPS for Coffee County, Alabama.

A Sector is a cluster of geographically adjacent counties within a VA Submarket. The process of aggregating counties into sectors uses a combination of automated algorithms and manual inspection of maps. The key attribute in this data set is the SECTOR which is defined as a string of eight characters broken down into four parts in the order of VISN (2-char), Market (1-char), Submarket (1-char), and Sector(1-char) connected by a hyphen. For example, Sector 12-a-3-A indicates VISN 12, Market a, Submarket 3 and Sector A.

Sub-markets reflect a clustering of the enrollee population within a market and are an aggregation of Sectors. The key attribute in this data set is the SUBMARKET which is defined as a string of six characters broken down in three parts in the order of VISN (2-char), Market (1-char), and Submarket (1-char) connected by a hyphen. For example, Submarket 12-a-3 indicates VISN 12, Market a, and Submarket 3.

CARES defines Markets as "an aggregated geographic area having a sufficient population and geographic size to both benefit from the coordination and planning of health care services and to support a full healthcare delivery system (i.e. primary care, mental health care, inpatient care, tertiary care, and long term care)". Each Market is built from Submarkets. The key attribute in this data set is the MARKET which is defined as a string of four characters broken down in two parts in the order of HCN (2-char) and Market (1-char) connected by a hyphen. For example, Market 12-a indicates VISN 12 and Market a.

The key attribute in the VISN data set is defined as a string of two characters from 01-23, excluding 3, 11, 13, 14 and 18; a VISN also has an officially recognized VA title. For example, VISN 06 is the Mid-Atlantic Health Care Network. VISNs can span across neighboring countries to include areas that are not contiguous. For example, VISN 08 includes Florida and Puerto Rico in addition to most of Florida and southern Georgia, and VISN 20 includes Alaska and parts of the northwest conterminous United States. Each VISN is built from Markets, Submarkets, Sectors and Counties derived from Census (2010) County data.

Because VISNs are composed of VHA markets, VISN boundaries align with the outer edges of their constituent markets’ boundaries. Markets cross state borders wherever it is necessary to keep outpatient clinics (e.g. Community-Based Outpatient Clinics(CBOCs)) and their catchment areas in the same market as their parent medical centers. Thus, VISN boundaries also cross state borders. In 2016 senior leadership considered the challenge of conforming VISN boundaries to MyVA Districts, which coincide with state boundaries. It was agreed that VHA would not separate outpatient clinics from their parent medical centers due to added complexity. Many outpatient providers hold clinics at their mother facilities and clinics are on the same health record as their parent facilities. VISN and market maps created by VHA Policy and Planning conform to these principals and are the official maps for VHA VISNs and markets.

While the Planning Systems Support Group (PSSG) develops the feature classes depicting the various VHA geographies, the PSSG does not have the authority to modify or reorganize the boundaries. The boundaries are developed at higher levels of the VHA and passed to the PSSG to be translated into spatial features.

Map and tables with data describing Michigan's veteran population. Data tables cover: Veterans Affairs (VA) facilities and expenditures; veteran population including age distribution, period of service, household income, and educational attainment; veterans' use of VA healthcare and benefits; and projected veteran population changes as well as projections by age, gender, period of service, race/ethnicity, and age distribution over time.

This service contains the 2018-2022 release of data from the American Community Survey (ACS) 5-year data about Veteran Status, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of the civilian population over the age of 18 that are Veterans.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2018-2022ACS Table(s): DP02Data downloaded from: CensusBureau's API for American Community Survey Date of API call: January 18, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

Map and tables with data describing West Virginia's veteran population. Data tables cover: Veterans Affairs (VA) facilities and expenditures; veteran population including age distribution, period of service, household income, and educational attainment; veterans' use of VA healthcare and benefits; and projected veteran population changes as well as projections by age, age distribution over time, gender, period of service, and race/ethnicity.

Map and tables with data describing Arizona's veteran population. Data tables cover: Veterans Affairs (VA) facilities and expenditures; veteran population including age distribution, period of service, household income, and educational attainment; veterans' use of VA healthcare and benefits; and projected veteran population changes as well as projections by age, gender, period of service, race/ethnicity, and age distribution over time.

This map shows the percent of population who are veterans. This pattern is shown by states, counties, and tracts. The data is from the most current American Community Survey (ACS) data from the U.S. Census Bureau. Veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty.The pop-up highlights the breakdown of veterans by gender.Zoom to any area in the country to see a local or regional pattern, or use one of the bookmarks to see distinct patterns of poverty through the US. Data is available for the 50 states plus Washington D.C. and Puerto Rico.The data comes from this ArcGIS Living Atlas of the World layer, which is part of a wider collection of layers that contain the most up-to-date ACS data from the Census. The layers are updated annually when the ACS releases their most current 5-year estimates. Visit the layer for more information about the data source, vintage, and download date for the data.

Map and tables with data describing Mississippi's veteran population. Data tables cover: Veterans Affairs (VA) facilities and expenditures; veteran population including age distribution, period of service, household income, and educational attainment; veterans' use of VA healthcare and benefits; and projected veteran population changes as well as projections by age, age distribution over time, gender, period of service, and race/ethnicity.

Map and tables with data describing Missouri's veteran population. Data tables cover: Veterans Affairs (VA) facilities and expenditures; veteran population including age distribution, period of service, household income, and educational attainment; veterans' use of VA healthcare and benefits; and projected veteran population changes as well as projections by age, age distribution over time, gender, period of service, and race/ethnicity.

Map and tables with data describing Alaska's veteran population. Data tables cover: Veterans Affairs (VA) facilities and expenditures; veteran population including age distribution, period of service, household income, and educational attainment; veterans' use of VA healthcare and benefits; and projected veteran population changes as well as projections by age, age distribution over time, gender, period of service, and race/ethnicity.

This service contains the 2018-2022 release of data from the American Community Survey (ACS) 5-year data about Veteran Status, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of the civilian population over the age of 18 that are Veterans.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2018-2022ACS Table(s): DP02Data downloaded from: CensusBureau's API for American Community Survey Date of API call: January 18, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.