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.

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

In 2024, about **** percent of the estimated number of homeless veterans in the United States were male, compared to **** percent who were female.

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.

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.

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"

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

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.

In 2020, surveys conducted among people experiencing homelessness in King County, Washington found that 55 percent of those who were veterans suffered from post-traumatic stress disorder (PTSD), compared to 39 percent of those who were not veterans. This statistic shows the percentage of veteran and non-veteran homeless persons in King County, Washington who stated they had select health conditions as of 2020.

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 dataset contains daily records of shelter capacity, number of people sheltered, and estimated homeless population across various urban locations. It includes demographic details such as average age, percentage of families, veterans, and disabled individuals, along with seasonal temperature data. The dataset is designed to support analysis and prediction of shelter demand, resource planning, and understanding factors influencing homelessness.

Percentages in parentheses reflect the percentage of participants from the initial assessment who took part in the respective follow-up.

Results of univariate and multivariable Cox Proportional Hazards regression models of initiation of HCV treatment in 11,082 U.S. Veterans with evidence of homelessness and with chronic hepatitis C (HCV) diagnosis who were treatment naïve for HCV, 2004–2009.

Results of univariate and multivariable Cox Proportional Hazards regression models of initiation of HCV treatment in 101,444 U.S. Veterans with chronic hepatitis C (HCV) diagnosis who were treatment naïve for HCV, 2004–2009.

BackgroundA small but significant proportion of military veterans become involved in the criminal justice system (CJS) after leaving service. Liaison and Diversion (L&D) services aim to identify vulnerable offenders in order to provide them with the health/welfare support they need, and (where possible) divert them away from custody. An administrative database of L&D service-users was utilised to compare the needs of veterans with those of non-veteran L&D service-users.MethodNational data collected from 29 L&D services in 2015–2016 was utilised. Of the 62,397 cases, 1,067 (2%) reported previous service in the Armed Forces, and 48,578 had no previous service history. The associations between veteran status and socio-demographic characteristics, offending behaviour, health- and mental health-problems were explored. The associations between specific types of offending and mental health problems within the veterans in the sample were also investigated.ResultsVeterans tended to be older, and less likely to be unemployed than non-veterans, but just as likely to have unstable living arrangements (including homelessness). Veteran status was associated with increased levels of interpersonal violence, motoring offences, anxiety disorders and hazardous drinking patterns. Veteran status was associated with decreased levels of acquisitive offending, schizophrenia, ADHD, and substance misuse. Among veterans, the presence of an anxiety disorder (umbrella term which included GAD, Phobias, PTSD etc.) was associated with increased interpersonal violence, alcohol misuse was associated with increased motoring offences, and substance use was associated with increased acquisitive offending.ConclusionsOur study indicates that among offenders in the CJS who have been identified as needing health or welfare support, veterans differ from non-veterans in terms of their health and welfare needs and offending behaviour. These differences may be influenced by the impact of military service and the transition into civilian life. Our findings support the identification of military personnel within the CJS to provide appropriate interventions and support to improve outcomes and reduce offending.

By 2034, the number of military retirees in the United States is expected to reach 2.37 million; an increase from an estimated 2.27 million retirees in 2024. Military retirement pay In the U.S., military retirement refers to pension and benefit plans for those who have accumulated 20 or more years of active service. There are different factors that influence how much is paid out to different veterans, which includes length of service, disability percentage, the year the person entered the military, and type of retirement. The total payment for military retirees is expected to continue to increase, as well as their average benefits. However, the total outlays for the military retirement trust fund is expected to fluctuate, but ultimately rise over the next decade. U.S veterans The United States has one of the largest militaries in the world based on active personnel and has the largest defense budget in the world. However, many veterans in the U.S. struggle to find a job and find affordable housing when they return from deployment due to factors such as post-traumatic stress disorder and physical disabilities. The Department of Veteran Affairs seeks to help those coming back from training or combat assimilate back into everyday life.

According to a survey conducted in 2023, ** percent of Americans strongly supported their local government establishing or expanding programs that support veterans experiencing homelessness or at risk of experiencing homelessness in the United States. In comparison, ** percent of Americans strongly opposed their local government increasing penalties for loitering, panhandling, or sleeping/camping on public property as a way to combat homelessness.

"Benchmark" refers to the original Option A. SD 1:SD 1 keeps Azusa whole - there is no reason to split up Rosedale from the rest of AzusaSame with San GabrielSD 1 connects middle income Asian community in SGV - high Asian population areas like Monterey Park, San Gabriel, Rosemead, Alhambra with Rowland Heights and Hacienda Heights (more affluent Asians in SD 5 in cities like San Marino, Arcadia, Temple City, Walnut share more common interests with Whites)Keeps San Gabriel Valley into only two pieces - Montebello is part of SGVCOG and is moved to SD 1, Industry and Diamond Bar moved to SD 1Unites Heights communities along Puente HillsMoves Pomona to SD 1 as requested by Mayor of PomonaRemains majority Latino (51.59% Latino CVAP compared to 54.52% benchmark map)Asian representation improves - 25.52% Asian CVAP compared to 22.97% benchmark mapSD 2:New SD 2 includes renter dominant communities on the Westside - Palms, Sawtelle Japantown, renter heavy portions of Brentwood, Westwood Bl corridor, UCLA campusDoes not split Park La BreaIncludes VA hospital property - many homeless veterans have origins in SD 2Connects UCLA with many of its students who live in PalmsKeeps the central part of Westchester with SD 2Unites Japanese American communities in Gardena, Sawtelle Japantown (Little Osaka) and Little TokyoSD 2 remains Black influence - 29.79% Black CVAP compared to 30.85% benchmark mapSD 3:Cheviot Hills is moved to SD 3 due to high homeowner and affluent population to join other high income communities in the Hollywood Hills and Beverly HillsKeeps Lakeview Terrace in SD 3 while moving Kagel Canyon to SD 5Cuts at Glenoaks Bl to extent possible to respect Shadow Hills community boundarySD 3/SD 5 boundary in rest of San Fernando Valley remains the same.Remains predominantly White - 54.14% White CVAP compared to 54.73% benchmark.Keeps El Segundo in SD 3(Note due to technical limitations LAX is in SD 3 when it should be in SD 2)SD 4:SD 4 covers all Gateway Cities and SELAKeeps Long Beach wholeKeeps Whittier wholeDoes not include finger to TorranceExcludes San Gabriel ValleyWatts is moved to SD 4 for population balance and to connect with Florence Firestone - Watts is 62% Latino CVAP, 34% Black so putting it with Latino district helps improve Latino numbersMore Latino - 55.77% Latino compared to 50.15% benchmark map.SD 5:SD 5 boundary in NE SFV changes to put Shadow Hills and Kagel Canyon in SD 5 and group more Latino communities in SD 3 with other cities in the ValleySD 3/5 boundary in rest of SFV remains the sameDuarte is moved to SD 5 as a whole to join its other Foothill cities. Duarte is 44% Latino CVAP and so including it in SD 1 would slightly reduce the Latino percentage in SD 1. Compare with Azusa which is 57% Latino CVAP and should be included in a Latino district. The underpopulation should as much as possible be in VRA target districts 1, 2, and 4 to reflect the undercount of Latino population in census due to citizenship question uncertainty and lack of language assistance available due to the pandemic, as well as reduced access to technology for Blacks. This does this.