This statistic shows the estimated number of homeless veterans in the United States in 2022, by state. In 2022, about 10,395 veterans living in California were homeless.

In 2023, about 3.6 percent of the estimated number of homeless veterans in the United States were Native American. In comparison, 57 percent were white and 31.3 percent were Black or African American.

Policy Map Point-in-time estimates of homeless veterans population in January 2020, HUD, Delaware Statewide CoC, DE (Continuum of Care)

In 2023, about 87.8 percent of the estimated number of homeless veterans in the United States were male, compared to 11.2 percent who were female.

In 2023, about 15,507 homeless veterans in the United States were estimated to be living outside a homeless shelter. In comparison, 20,067 homeless veterans were estimated to be living inside a homeless shelter in that year.

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 73 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 653,104 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 243,000. 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.

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).

Report to the Appropriations Committee of the United States House of Representatives in Response to Conference Committee Report to PL 110-186. In an effort to provide a snapshot of the quality of care provided at VA health care facilities, this report includes information about waiting times, staffing level, infection rates, surgical volumes, quality measures, patient satisfaction, service availability and complexity, accreditation status, and patient safety. The data in this report have been drawn from multiple sources across VHA. This dataset represents the quality of care for defined populations: Gender, Geriatric, Disabled, Homeless, and patients with Mental Health Diagnosis.

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.

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.

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).

Financial overview and grant giving statistics of Vietnam Veterans Workshop Inc.

Financial overview and grant giving statistics of Association Of The United States Army

By 22034033, 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.

description: This data represents all emergency medical services calls related to possible opioid abuse. Opioid Abuse Probable A call may be coded as opioid abuse probable for many reasons, such as * Are there are any medical symptoms indicative of opioid abuse? * Are there physical indicators on scene (i.e. drug paraphernalia, pill bottles, etc.)? * Are there witnesses or patient statements made that point to opioid abuse? * Is there any other evidence that opioid abuse is probable with the patient? Opioid abuse probable is determined by Tempe Fire Medical Rescue Departments Emergency medical technicians and paramedics on scene at the time of the incident. Narcan/Naloxone Given Narcan/Naloxone Given refers to whether the medication Narcan/Naloxone was given to patients who exhibited signs or symptoms of a potential opioid overdose or to patients who fall within treatment protocols that require Narcan/Naloxone to be given. Narcan/Naloxone are the same medication with Narcan being the trade name and Naloxone being the generic name for the medication. Narcan is the reversal medication used by medical providers for opioid overdoses. Groups Groups are used to determine if there are specific populations that have an increase in opioid abuse. * The student population at ASU was being examined for other purposes to determine ASU's overall call volume impact in Tempe. Data collection with the university is consistent with Fire Departments who provide service to the other PAC 12 universities. Since this data set was already being evaluated, it was included in the opioid data collection as well. * The Veteran and Homeless Groups were established as demographic tabs to identify trends and determine needs in conjunction with the City of Tempes Veterans and Homeless programs. Since these data sets were being evaluated already, they were included in the opioid data collection as well. * The unknown group includes incidents where a patient is unable to answer or refuses to answer the demographic questions. Gender Patient gender is documented as male or female when crews are able to obtain this information from the patient. There are some circumstances where this information is not readily determined and the patient is unable to communicate with our crews. In these circumstances, crews may document unknown/unable to determine. Data Set History Data sets were evolving in 2017 due to software upgrades and identifying new parameters to focus data collection on. The 2018 data will be a more comprehensive set of data that includes all the fields identified throughout 2017. Data sets may continue to evolve based on the needs of the community and healthcare trends. Information about the data can be found at Data Documentation; abstract: This data represents all emergency medical services calls related to possible opioid abuse. Opioid Abuse Probable A call may be coded as opioid abuse probable for many reasons, such as * Are there are any medical symptoms indicative of opioid abuse? * Are there physical indicators on scene (i.e. drug paraphernalia, pill bottles, etc.)? * Are there witnesses or patient statements made that point to opioid abuse? * Is there any other evidence that opioid abuse is probable with the patient? Opioid abuse probable is determined by Tempe Fire Medical Rescue Departments Emergency medical technicians and paramedics on scene at the time of the incident. Narcan/Naloxone Given Narcan/Naloxone Given refers to whether the medication Narcan/Naloxone was given to patients who exhibited signs or symptoms of a potential opioid overdose or to patients who fall within treatment protocols that require Narcan/Naloxone to be given. Narcan/Naloxone are the same medication with Narcan being the trade name and Naloxone being the generic name for the medication. Narcan is the reversal medication used by medical providers for opioid overdoses. Groups Groups are used to determine if there are specific populations that have an increase in opioid abuse. * The student population at ASU was being examined for other purposes to determine ASU's overall call volume impact in Tempe. Data collection with the university is consistent with Fire Departments who provide service to the other PAC 12 universities. Since this data set was already being evaluated, it was included in the opioid data collection as well. * The Veteran and Homeless Groups were established as demographic tabs to identify trends and determine needs in conjunction with the City of Tempes Veterans and Homeless programs. Since these data sets were being evaluated already, they were included in the opioid data collection as well. * The unknown group includes incidents where a patient is unable to answer or refuses to answer the demographic questions. Gender Patient gender is documented as male or female when crews are able to obtain this information from the patient. There are some circumstances where this information is not readily determined and the patient is unable to communicate with our crews. In these circumstances, crews may document unknown/unable to determine. Data Set History Data sets were evolving in 2017 due to software upgrades and identifying new parameters to focus data collection on. The 2018 data will be a more comprehensive set of data that includes all the fields identified throughout 2017. Data sets may continue to evolve based on the needs of the community and healthcare trends. Information about the data can be found at Data Documentation

The WSC program, funded through the Workforce Investment Act (WIA); National Emergency Grant (NEG) and other competitive grants, provides employment training and placement services for adults and dislocated workers, with a special emphasis on vulnerable populations, including persons with disabilities, veterans, homeless, English-language learners and older workers. Annual goals are established by California Employment Development Department and the US Department of Labor.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household, enterprise

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: No - Special populations: Persons without any normal residence, foreign nationals, and people in barracks of military and para-military forces, orphanages, rescue homes, ashram and vagrant houses are not covered by survey.

UNIT DESCRIPTIONS: - Households: A group of persons normally living together and taking food from a common kitchen will constitute a household. The members of a household may or may not be related by blood to one another.

Universe

All population in India, except for foreigners, the homeless, or people in barracks of military and para-military forces, orphanages, rescue homes, ashram, and vagrant houses.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Sample Survey Organization, Government of India

SAMPLE DESIGN: Two-stage, stratified samples drawn by the country, coupled with rotation sampling scheme for the central sample. (1) Stage 1: In the central sample, 10,384 first stage units (rural and urban combined) were selected from stratified states in proportion to poluation. Among them, 3,900 of which were revisted. (2) Stage 2: households and enterprises were selected from second-stage strata(hamlet-groups or sub-blocks) by circular systematic sampling with equal probability. (3) Under the rotation sampling scheme which was adopted for the first time in the National Sample Survey, 50% of the sample first stage units in the central sample were revisited in the subsequent three-month period. In state samples, the first stage units were only visited once.

SAMPLE UNIT: Household

SAMPLE FRACTION: .07%

SAMPLE SIZE (person records): 596,688

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form that consists of 8 sections: 1) identification of sample household, 2) household characteristics, 3) demographic and migration particulars, 4) usual principal activity, 5) subsidiary activity, 6) current work activity during the preceding week, 5) follow-up questions for the unemployed, 6) availability for work to working persons, 7) job change of working persons, and 8) questions for females.

Response rate

COVERAGE: 100% of the Indian Union excepting (1) Ladakh and Kargil districts of Jammu and Kashmir, (2) interior villages of Nagaland situated beyond 5 kms. of a bus route, and (3) villages of Andaman and Nicobar Islands remaining inaccessible throughout the year. Also excluded were all the uninhabited villages according to 1991 census.

In 2022, health centers served around 1.4 million patients experiencing homelessness and 389,000 veteran patients in the United States. This statistic depicts the number of special populations served by health centers in the U.S. in 2022.

According to a survey conducted in 2022, 42 percent of Americans blamed the mental health system a lot for homelessness in the United States while 39 percent blamed the federal government a lot. In comparison, only 12 percent of Americans blamed the military or non-profit organizations a lot for homelessness in the United States.