In 2023, about ****** homeless veterans in the United States were estimated to be living outside a homeless shelter. In comparison, ****** homeless veterans were estimated to be living inside a homeless shelter in that year.

Yearly statewide and by-Continuum of Care total counts of individuals receiving homeless response services by age group, race, gender, veteran status, and disability status.

This data comes from the Homelessness Data Integration System (HDIS), a statewide data warehouse which compiles and processes data from all 44 California Continuums of Care (CoC)—regional homelessness service coordination and planning bodies. Each CoC collects data about the people it serves through its programs, such as homelessness prevention services, street outreach services, permanent housing interventions and a range of other strategies aligned with California’s Housing First objectives.

The dataset uploaded reflects the 2024 HUD Data Standard Changes. Previously, Race and Ethnicity were separate files but are now combined.

Information updated as of 11/13/2025.

This brief uses data from the 2009 and 2010 Annual Homeless Assessment Reports (AHAR) to Congress. The reports were sponsored by the Department of Housing and Urban Development and the Department of Veterans Affairs.

In 2022, about ****** veterans living in California were homeless, the most out of all U.S. states.

This Data Spotlight from the Treatment Episode Data Set (TEDS) discusses homelessness among military veterans who were admitted to substance abuse treatment during 2011, by age group.

In 2024, about *** percent of the estimated number of homeless veterans in the United States were Native American or Pacific Islanders. In comparison, **** percent were white and ** percent were Black, African American, or African.

The Veterans' Employment and Training Service (VETS) tracks HVRP participant outcomes using data collected from grant recipients. VETS shares HVRP outcomes with the public. These data show the national level targets and outcomes for eleven (11) measures by Program Year (PY), including breakouts by sex, ethnicity, race, age, and grant population. The 11 measures are: Number of Participants Served Percentage of Total Participants Served Number of Exiters Percentage of Total Number of Exiters Number of Participants Co-Enrolled at American Job Centers (AJCs) Average Hourly Wage at Placement Placement Rate (exit-based) Placement Rate – Episodically Homeless (exit-based) Employment Rate 2nd Quarter After Exit Employment Rate 4th Quarter After Exit Median Earnings 2nd Quarter After Exit"

When analyzing the ratio of homelessness to state population, New York, Vermont, and Oregon had the highest rates in 2023. However, Washington, D.C. had an estimated ** homeless individuals per 10,000 people, which was significantly higher than any of the 50 states. Homeless people by race The U.S. Department of Housing and Urban Development performs homeless counts at the end of January each year, which includes people in both sheltered and unsheltered locations. The estimated number of homeless people increased to ******* in 2023 – the highest level since 2007. However, the true figure is likely to be much higher, as some individuals prefer to stay with family or friends - making it challenging to count the actual number of homeless people living in the country. In 2023, nearly half of the people experiencing homelessness were white, while the number of Black homeless people exceeded *******. How many veterans are homeless in America? The  number of homeless veterans in the United States has halved since 2010. The state of California, which is currently suffering a homeless crisis, accounted for the highest number of homeless veterans in 2022. There are many causes of homelessness among veterans of the U.S. military, including post-traumatic stress disorder (PTSD), substance abuse problems, and a lack of affordable housing.

Context

This database contains the data reported in the Annual Homeless Assessment Report to Congress (AHAR). It represents a point-In-time count (PIT) of homeless individuals, as well as a housing inventory count (HIC) conducted annually.

The data represent the most comprehensive national-level assessment of homelessness in America, including PIT and HIC estimates of homelessness, as well as estimates of chronically homeless persons, homeless veterans, and homeless children and youth.

These data can be trended over time and correlated with other metrics of housing availability and affordability, in order to better understand the particular type of housing resources that may be needed from a social determinants of health perspective.

HUD captures these data annually through the Continuum of Care (CoC) program. CoC-level reporting data have been crosswalked to county levels for purposes of analysis of this dataset.

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.sdoh_hud_pit_homelessness

Sample Query

What has been the change in the number of homeless veterans in the state of New York’s CoC Regions since 2012? Determine how the patterns of homeless veterans have changes across the state of New York

homeless_2018 AS ( SELECT Homeless_Veterans AS Vet18, CoC_Name
FROM bigquery-public-data.sdoh_hud_pit_homelessness.hud_pit_by_coc WHERE SUBSTR(CoC_Number,0,2) = "NY" AND Count_Year = 2018 ),

veterans_change AS ( SELECT homeless_2012.COC_Name, Vet12, Vet18, Vet18 - Vet12 AS VetChange FROM homeless_2018 JOIN homeless_2012 ON homeless_2018.CoC_Name = homeless_2012.CoC_Name )

SELECT * FROM veterans_change

The County of Sonoma conducts an annual homeless count for the entire county. The survey data is derived from a sample of about 600 homeless persons countywide per year. The resulting information is statistically reliable only for the county as a whole, not for individual locations. The exception is the City of Santa Rosa, where the sample taken within the city is large enough to be predictive of the overall homeless population in that city.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Quarterly Technical Performance Report (TPR) from HVRP grant recipients. This includes demographic and employment characteristics of HVRP participants aggregated at the grant recipient-level. The TPR is an Excel-based data collection and reporting tool for grant recipients to enter participant and project information. The workbook allows VETS’ Grant Officer’s Technical Representatives (GOTR) to monitor performance and enables the aggregation and analysis of grant recipient data to assess the effectiveness of grant programs and submit reports to Congress. Grant recipients must submit the TPR and its accompanying TPN for a specific grant award for all twelve quarters in the grant Period of Performance (PoP). The TPR Excel workbook is comprised of six worksheets: 1. Planned Goals – Recipient input required 2. Tech Perf Report – Report / minimal recipient input required 3. New Enrollment Entry – Recipient input optional 4. Participant Info – Recipient input required 5. Demographics Summary – Report / No input required 6. Goals v. Actual – Report / No input required

Due to the unprecedented COVID-19 pandemic, the US Department of Housing and Urban Development (HUD) approved the Maricopa Regional Continuum of Care to opt out of the unsheltered Point In Time (PIT) Homeless Count for 2021. Every January, volunteers and outreach teams from local communities collaborate to survey and count the number of homeless. persons in their respective locations. With the information provided by the PIT Count, the Maricopa Regional Continuum of Care and local communities can determine how best to address homelessness. For more information see https://www.azmag.gov/Programs/Homelessness/Point-In-Time-Homeless-Count">https://www.azmag.gov/Programs/Homelessness/Point-In-Time-Homeless-Count.

NOTE: The HUD definition of chronic homelessness is: (1) a person who lives in a place not meant for human habitation, Safe Haven, or Emergency Shelter, (2) has a disability, and (3) has been homeless continuously for one year OR four or more times homeless in the last three years, where the combined length of time homeless is at least 12 months.

**Mesa 2025 Data: 6 interactions documented in cities outside of Mesa. Geolocation confirmed interactions occurred in Mesa, versus documented city. Dataset manually updated to reflect correct interaction location and correct PIT counts reflected in https://maricopacoc.org/data/point-in-time-count/">Maricopa Regional Continuum of Care .

This layer contains detailed Point in Time counts of homeless populations from 2019. This layer is modeled after a similar layer that contains data for 2018, 2013, and 2008.Layer is symbolized to show the count of the overall homeless population in 2019, with a pie chart of breakdown of type of shelter. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. The Point-in-Time (PIT) count is a count of sheltered and unsheltered homeless persons on a single night in January. HUD requires that Continuums of Care Areas (CoCs) conduct an annual count of homeless persons who are sheltered in emergency shelter, transitional housing, and Safe Havens on a single night. CoCs also must conduct a count of unsheltered homeless persons every other year (odd numbered years). Each count is planned, coordinated, and carried out locally.The Point-in-Time values were retrieved from HUD's Historical Data site. Original source is the 2019 sheet within the "2007 - 2019 PIT Counts by CoCs.xlsx" (downloaded on 3/10/2020) file. Key fields were kept and joined to the CoC boundaries available from HUD's Open Data site.Data note: MO-604 covers territory in both Missouri and Kansas. The record described in this file represents the CoC's total territory, the sum of the point-in-time estimates the CoC separately reported for the portions of its territory in MO and in KS.For more information and attributes on the CoC Areas themselves, including contact information, see this accompanying layer.Suggested Citation: U.S. Department of Housing and Urban Development (HUD)'s Point in Time (PIT) 2019 counts for Continuum of Care Grantee Areas, accessed via ArcGIS Living Atlas of the World on (date).

This dataset contains estimates of homelessness, as well as estimates of chronically homeless persons, homeless veterans, and homeless children and youth provided by The U.S. Department of Housing and Urban Development. The estimates cover the period of years 2007-2017 and are at national, state and Continuums of Care (CoC) Point-In-Time (PIT) level.

This map shows Point in Time counts of the overall homeless populations from 2019. Layer is symbolized to show the count of the overall homeless population in 2019, with a pie chart of breakdown of type of shelter. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. The Point-in-Time (PIT) count is a count of sheltered and unsheltered homeless persons on a single night in January. HUD requires that Continuums of Care Areas (CoCs) conduct an annual count of homeless persons who are sheltered in emergency shelter, transitional housing, and Safe Havens on a single night. CoCs also must conduct a count of unsheltered homeless persons every other year (odd numbered years). Each count is planned, coordinated, and carried out locally.The Point-in-Time values were retrieved from HUD's Historical Data site. Original source is the 2019 sheet within the "2007 - 2019 PIT Counts by CoCs.xlsx" (downloaded on 3/10/2020) file. Key fields were kept and joined to the CoC boundaries available from HUD's Open Data site.Data note: MO-604 covers territory in both Missouri and Kansas. The record described in this file represents the CoC's total territory, the sum of the point-in-time estimates the CoC separately reported for the portions of its territory in MO and in KS.For more information and attributes on the CoC Areas themselves, including contact information, see this accompanying layer.Suggested Citation: U.S. Department of Housing and Urban Development (HUD)'s Point in Time (PIT) 2019 counts for Continuum of Care Grantee Areas, accessed via ArcGIS Living Atlas of the World on (date).

The Veterans' Employment and Training Service (VETS) tracks participant outcome measures for the HVRP program. Programmatic performance outcomes are collected from grant recipients through the Technical Performance Report (TPR) form. VETS shares HVRP outcomes with the public. These data show the national level targets and outcomes for eleven (11) measures by Program Year (PY), including breakouts by subpopulation, gender, ethnicity, race, and age. The 11 measures are: 1. Number of Participants Served 2. Percentage of Total Participants Served 3. Number of Exiters 4. Percentage of Total Number of Exiters 5. Number of Participants Co-Enrolled at American Job Centers (AJCs) 6. Average Hourly Wage at Placement 7. Placement Rate (exit-based) 8. Placement Rate – Episodically Homeless (exit-based) 9. Employment Rate 2nd Quarter After Exit 10. Employment Rate 4th Quarter After Exit 11. Median Earnings 2nd Quarter After Exit

This dataset comes from Pierce County's Homeless Management Information System (HMIS). HMIS is a local information technology system used to collect client-level data and data on the provision of housing and services to homeless individuals and families and persons at risk of homelessness.

Federal and State funders require any Continuum of Care receiving federal and state homeless funds use a locally-administered data system to record and analyze homeless information. To comply with this requirement Pierce County has contracted with Bowman Systems L.L.C. for the use of the ServicePoint HMIS database.

This report outlines the key findings of the 2014 Point-In-Time (PIT) and Housing Inventory (HIC) counts conducted in January 2014. Specifically, this report provides 2014 national, state, and CoC-level PIT and HIC estimates of homelessness, as well as estimates of chronically homeless persons, homeless veterans, and homeless children and youth.

Clients (veterans or Veterans w/ family) that were successfully housed through the Veteran Peer Coordinator (VPC) program during Fiscal 2019. This table reports the clients (veterans or Veterans w/ family) that were successfully housed through the Veteran Peer Coordinator (VPC) program. These moves are managed and reported by the Housing & Support Services (HSS) line of action. This data collected by the coordinators at various shelters across the city with the assistance of other city agencies. Each record represents a client intake, which entails a particular homelessness assistance request. The captured in this report can provide insight on the successful moves DVS processes, including some demographic information on the veterans DVS interacts with. The report is manually recorded, compiling information from various systems and databases.

The VA Strategic Plan for 2010–2014 established our enduring principles: people-centric, results-driven, and forward-looking. We will continue to use those principles to increase Veterans’ access to benefits, eliminate the disability claims backlog, and end the rescue phase of Veteran homelessness.