In 2023, there were about ******* homeless people estimated to be living in the United States, the highest number of homeless people recorded within the provided time period. In comparison, the second-highest number of homeless people living in the U.S. within this time period was in 2007, at *******. How is homelessness calculated? Calculating homelessness is complicated for several different reasons. For one, it is challenging to determine how many people are homeless as there is no direct definition for homelessness. Additionally, it is difficult to try and find every single homeless person that exists. Sometimes they cannot be reached, leaving people unaccounted for. In the United States, the Department of Housing and Urban Development calculates the homeless population by counting the number of people on the streets and the number of people in homeless shelters on one night each year. According to this count, Los Angeles City and New York City are the cities with the most homeless people in the United States. Homelessness in the United States Between 2022 and 2023, New Hampshire saw the highest increase in the number of homeless people. However, California was the state with the highest number of homeless people, followed by New York and Florida. The vast amount of homelessness in California is a result of multiple factors, one of them being the extreme high cost of living, as well as opposition to mandatory mental health counseling and drug addiction. However, the District of Columbia had the highest estimated rate of homelessness per 10,000 people in 2023. This was followed by New York, Vermont, and Oregon.

The graph displays the top 15 states by an estimated number of homeless people in the United States for the year 2025. The x-axis represents U.S. states, while the y-axis shows the number of homeless individuals in each state. California has the highest homeless population with 187,084 individuals, followed by New York with 158,019, while Hawaii places last in this dataset with 11,637. This bar graph highlights significant differences across states, with some states like California and New York showing notably higher counts compared to others, indicating regional disparities in homelessness levels across the country.

The number of people left homeless due to wildfires in 2023 amounted to **, a considerable decrease when compared to the figures of 2022 and 2021, when ***** and ***** people lost their homes due to such disasters.

In 2023, there were an estimated ******* white homeless people in the United States, the most out of any ethnicity. In comparison, there were around ******* Black or African American homeless people in the U.S. How homelessness is counted The actual number of homeless individuals in the U.S. is difficult to measure. The Department of Housing and Urban Development uses point-in-time estimates, where employees and volunteers count both sheltered and unsheltered homeless people during the last 10 days of January. However, it is very likely that the actual number of homeless individuals is much higher than the estimates, which makes it difficult to say just how many homeless there are in the United States. Unsheltered homeless in the United States California is well-known in the U.S. for having a high homeless population, and Los Angeles, San Francisco, and San Diego all have high proportions of unsheltered homeless people. While in many states, the Department of Housing and Urban Development says that there are more sheltered homeless people than unsheltered, this estimate is most likely in relation to the method of estimation.

The graph displays the estimated number of homeless people in the United States from 2007 to 2024. The x-axis represents the years, ranging from 2007 to 2023, while the y-axis indicates the number of homeless individuals. The estimated homeless population varies over this period, ranging from a low of 57,645 in 2014 to a high of 771,000 in 2024. From 2007 to 2013, there is a general decline in numbers from 647,258 to 590,364. In 2014, the number drops significantly to 57,645, followed by an increase to 564,708 in 2015. The data shows fluctuations in subsequent years, with another notable low of 55,283 in 2018. From 2019 onwards, the estimated number of homeless people generally increases, reaching its peak in 2024. This data highlights fluctuations in homelessness estimates over the years, with a recent upward trend in the homeless population.

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.

BackgroundHomelessness is one of the most disabling and precarious living conditions. The objective of this Delphi consensus study was to identify priority needs and at-risk population subgroups among homeless and vulnerably housed people to guide the development of a more responsive and person-centred clinical practice guideline.MethodsWe used a literature review and expert working group to produce an initial list of needs and at-risk subgroups of homeless and vulnerably housed populations. We then followed a modified Delphi consensus method, asking expert health professionals, using electronic surveys, and persons with lived experience of homelessness, using oral surveys, to prioritize needs and at-risk sub-populations across Canada. Criteria for ranking included potential for impact, extent of inequities and burden of illness. We set ratings of ≥ 60% to determine consensus over three rounds of surveys.FindingsEighty four health professionals and 76 persons with lived experience of homelessness participated from across Canada, achieving an overall 73% response rate. The participants identified priority needs including mental health and addiction care, facilitating access to permanent housing, facilitating access to income support and case management/care coordination. Participants also ranked specific homeless sub-populations in need of additional research including: Indigenous Peoples (First Nations, Métis, and Inuit); youth, women and families; people with acquired brain injury, intellectual or physical disabilities; and refugees and other migrants.InterpretationThe inclusion of the perspectives of both expert health professionals and people with lived experience of homelessness provided validity in identifying real-world needs to guide systematic reviews in four key areas according to priority needs, as well as launch a number of working groups to explore how to adapt interventions for specific at-risk populations, to create evidence-based guidelines.

This layer contains detailed Point in Time counts of homeless populations from 2018, 2013, and 2008. A 2019 version is now available!Layer is symbolized to show the count of the overall homeless population in 2018, with overall counts from 2008 and 2013 in the pop-up, as well as 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. The 2018, 2013, and 2008 sheets within the "2007 - 2018 PIT Counts within CoCs.xlsx" (downloaded on 2/7/2019) file were combined and joined to the CoC boundaries available from HUD's Open Data site. As noted in the "Mergers" sheet in the PIT Excel file, some CoC Areas have merged over the years. Use caution when comparing numbers in these CoCs across years. 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) counts for Continuum of Care Grantee Areas, accessed via ArcGIS Living Atlas of the World on (date).

Number of Businesses statistics on the Community Housing & Homeless Shelters industry in the US

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 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.

BackgroundSubstance use contributes to poor health and increases the risk of mortality in the homeless population. This study assessed the prevalence and risk levels of substance use and associated factors among adults experiencing homelessness in Accra, Ghana.Methods305 adults currently experiencing sheltered and unsheltered homelessness in Accra aged ≥ 18 years were recruited. The World Health Organization’s (WHO) Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) was used to assess substance use risk levels. Association of high-risk substance use with sociodemographic, migration, homelessness, and health characteristics were assessed using logistic regression.ResultsNearly three-quarters (71%, n = 216) of the sample had ever used a substance, almost all of whom engaged in ASSIST-defined moderate-risk (55%) or high-risk (40%) use. Survivors of physical or emotional violence (AOR = 3.54; 95% confidence interval [CI] 1.89–6.65, p

Adjusted odds ratios (and 95% confidence intervals) from binary logistic regression of ever experiencing housing loss due to "housing/financial loss", "health issues", and "interpersonal/family issues" by selected characteristics among homeless individuals (N = 207), Nipissing District, Ontario 2021.

Adjusted odds ratios (and 95% confidence intervals) from binary logistic regression of ever experiencing barriers to housing by selected characteristics among homeless individuals (N = 207), Nipissing District, Ontario 2021.

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).

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: Not available - Households: An individual or group of people living who inhabit part or all of the physical or census building who make common provisions for food and other living essentials. - Group quarters: Institutional households consist of individuals in a residence that manages everyday needs, usually arranged by an organization such as a non-profit institution, school, the military, etc. Includes reformatories, prisons and similar living quarters. Also includes households that rent rooms or parts of buildings lodging ten or more people.

Universe

All population residing in the geographic area of Indonesia regardless of residence status. Homeless, boat people, etc were enumerated.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Central Bureau of Statistics

SAMPLE SIZE (person records): 912544.

SAMPLE DESIGN: Data are derived from the sample of census blocks that received the long form questionnaire, stratified by urban-rural status.

Mode of data collection

Face-to-face [f2f]

Research instrument

Long form questionnaire SP90-S containing houseing and individual questions distributed to 5% of households.

Transitional Housing Services Market size was valued at USD 100 Billion in 2023 and is projected to reach USD 342.6 Billion by 2031, growing at a CAGR of 15.2% during the forecast period 2024-2031.

Global Transitional Housing Services Market Drivers

The market drivers for the Transitional Housing Services Market can be influenced by various factors. These may include:

Increasing Homelessness Rates: The rising rates of homelessness globally are a significant market driver for transitional housing services. Factors such as economic instability, lack of affordable housing, and social issues contribute to this increasing trend. Many cities report surges in homelessness, prompting governments and NGOs to seek robust solutions. Transitional housing serves as an intermediary step, offering individuals and families temporary support while they work towards permanent housing solutions.

BackgroundIndividuals who are homeless or vulnerably housed are at an increased risk for mental illness, other morbidities and premature death. Standard case management interventions as well as more intensive models with practitioner support, such as assertive community treatment, critical time interventions, and intensive case management, may improve healthcare navigation and outcomes. However, the definitions of these models as well as the fidelity and adaptations in real world interventions are highly variable. We conducted a systematic review to examine the effectiveness and cost-effectiveness of case management interventions on health and social outcomes for homeless populations.Methods and findingsWe searched Medline, Embase and 7 other electronic databases for trials on case management or care coordination, from the inception of these databases to July 2019. We sought outcomes on housing stability, mental health, quality of life, substance use, hospitalization, income and employment, and cost-effectiveness. We calculated pooled random effects estimates and assessed the certainty of the evidence using the GRADE approach. Our search identified 13,811 citations; and 56 primary studies met our full inclusion criteria. Standard case management had both limited and short-term effects on substance use and housing outcomes and showed potential to increase hostility and depression. Intensive case management substantially reduced the number of days spent homeless (SMD -0.22 95% CI -0.40 to -0.03), as well as substance and alcohol use. Critical time interventions and assertive community treatment were found to have a protective effect in terms of rehospitalizations and a promising effect on housing stability. Assertive community treatment was found to be cost-effective compared to standard case management.ConclusionsCase management approaches were found to improve some if not all of the health and social outcomes that were examined in this study. The important factors were likely delivery intensity, the number and type of caseloads, hospital versus community programs and varying levels of participant needs. More research is needed to fully understand how to continue to obtain the increased benefits inherent in intensive case management, even in community settings where feasibility considerations lead to larger caseloads and less-intensive follow-up.

A survey of homeless adults in California found that around 82 percent reported they had experienced some mental health condition at some point in their lifetime. This statistic shows the percentage of homeless adults in California with select mental health conditions at some point in life as of 2022.

In 2020, the number of people affected, injured, or left homeless due to storms across the globe amounted to roughly 45.5 million. In the past three decades, the impact of storms were highest in 2002, with over 111 million people affected. Overall, between 1990 and 2020, more than 410 thousand deaths were caused by storms worldwide.