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.

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.

Homelessness Report April 2025. Published by Department of Housing, Local Government, and Heritage. Available under the license Creative Commons Attribution Share-Alike 4.0 (CC-BY-SA-4.0).Homelessness data Official homelessness data is produced by local authorities through the Pathway Accommodation and Support System (PASS). PASS was rolled-out nationally during the course of 2013. The Department’s official homelessness statistics are published on a monthly basis and refer to the number of homeless persons accommodated in emergency accommodation funded and overseen by housing authorities during a specific count week, typically the last full week of the month. The reports are produced through the Pathway Accommodation & Support System (PASS), collated on a regional basis and compiled and published by the Department. Homelessness reporting commenced in this format in 2014. The format of the data may change or vary over time due to administrative and/or technology changes and improvements. The administration of homeless services is organised across nine administrative regions, with one local authority in each of the regions, “the lead authority”, having overall responsibility for the disbursement of Exchequer funding. In each region a Joint Homelessness Consultative Forum exists which includes representation from the relevant State and non-governmental organisations involved in the delivery of homeless services in a particular region. Delegated arrangements are governed by an annually agreed protocol between the Department and the lead authority in each region. These protocols set out the arrangements, responsibilities and financial/performance data reporting requirements for the delegation of funding from the Department. Under Sections 38 and 39 of the Housing (Miscellaneous Provisions) Act 2009 a statutory Management Group exists for each regional forum. This is comprised of representatives from the relevant housing authorities and the Health Service Executive, and it is the responsibility of the Management Group to consider issues around the need for homeless services and to plan for the implementation, funding and co-ordination of such services. In relation to the terms used in the report for the accommodation types see explanation below: PEA - Private Emergency Accommodation: this may include hotels, B&Bs and other residential facilities that are used on an emergency basis. Supports are provided to services users on a visiting supports basis. STA - Supported Temporary Accommodation: accommodation, including family hubs, hostels, with onsite professional support. TEA - Temporary Emergency Accommodation: emergency accommodation with no (or minimal) support....

This indicator presents available data at national level on the number of people reported by public authorities as homeless. Data are drawn from the OECD Questionnaire on Affordable and Social Housing (QuASH 2021, QuASH 2019, QuASH 2016) and other available sources. Overall, homelessness data are available for 36 countries (Table HC 3.1.1 in Annex I). Further discussion of homelessness can be found in the 2020 OECD Policy Brief, “Better data and policies to fight homelessness in the OECD”, available online (and in French). Discussion of national strategies to combat homelessness can be found in indicator HC3.2 National Strategies for combating homelessness. Comparing homeless estimates across countries is difficult, as countries do not define or count the homeless population in the same way. There is no internationally agreed definition of homelessness. Therefore, this indicator presents a collection of available statistics on homelessness in OECD, EU and key partner countries in line with definitions used in national surveys (comparability issues on the data are discussed below). Even within countries, different definitions of homelessness may co-exist. In this indicator, we refer only to the statistical definition used for data collection purposes. Detail on who is included in the number of homeless in each country, i.e. the definition used for statistical purposes, is presented in Table HC 3.1.2 at the end of this indicator. To facilitate comparison of the content of homeless statistics across countries, it is also indicated whether the definition includes the categories outlined in Box HC3.1, based on “ETHOS Light” (FEANTSA, 2018). Homelessness data from 2020, which are available for a handful of countries and cover at least part of the COVID-19 pandemic, add an additional layer of complexity to cross-country comparison. The homeless population estimate in this case depends heavily on the point in time at which the count took place in the year, the method to estimate the homeless (through a point-in-time count or administrative data, as discussed below), the existence, extent and duration of emergency supports introduced in different countries to provide shelter to the homeless and/or to prevent vulnerable households from becoming homeless (such as eviction bans). Where they are available, homeless data for 2020 are thus compared to data from the previous year in order to facilitate comparison with other countries.

This indicator presents available data at national level on the number of people reported by public authorities as homeless. Data are drawn from the OECD Questionnaire on Affordable and Social Housing (QuASH 2021, QuASH 2019, QuASH 2016) and other available sources. Overall, homelessness data are available for 36 countries (Table HC 3.1.1 in Annex I). Further discussion of homelessness can be found in the 2020 OECD Policy Brief, “Better data and policies to fight homelessness in the OECD”, available online (and in French). Discussion of national strategies to combat homelessness can be found in indicator HC3.2 National Strategies for combating homelessness. Comparing homeless estimates across countries is difficult, as countries do not define or count the homeless population in the same way. There is no internationally agreed definition of homelessness. Therefore, this indicator presents a collection of available statistics on homelessness in OECD, EU and key partner countries in line with definitions used in national surveys (comparability issues on the data are discussed below). Even within countries, different definitions of homelessness may co-exist. In this indicator, we refer only to the statistical definition used for data collection purposes. Detail on who is included in the number of homeless in each country, i.e. the definition used for statistical purposes, is presented in Table HC 3.1.2 at the end of this indicator. To facilitate comparison of the content of homeless statistics across countries, it is also indicated whether the definition includes the categories outlined in Box HC3.1, based on “ETHOS Light” (FEANTSA, 2018). Homelessness data from 2020, which are available for a handful of countries and cover at least part of the COVID-19 pandemic, add an additional layer of complexity to cross-country comparison. The homeless population estimate in this case depends heavily on the point in time at which the count took place in the year, the method to estimate the homeless (through a point-in-time count or administrative data, as discussed below), the existence, extent and duration of emergency supports introduced in different countries to provide shelter to the homeless and/or to prevent vulnerable households from becoming homeless (such as eviction bans). Where they are available, homeless data for 2020 are thus compared to data from the previous year in order to facilitate comparison with other countries.

Financial overview and grant giving statistics of Homeless Children International Inc.

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.

Background: Homelessness is an increasing problem in Western European countries. In the Netherlands, policy reforms and austerity measures induced an urgent need for management information on local homeless citizens. Municipal authorities initiated cross-sectional reviews of Homeless Service (HS) users. The resulting Homeless People Treatment and Recovery (HOP-TR) study developed a health and needs assessment strategy over different domains to comprehensively assess individuals and care networks with the perspective on recovery.Methods: Dutch HS users were selected using a naturalistic meta-snowball sampling. Semi-structured interviews provided the primary data source. The interview content was partly derived from the InterRAI Community Mental Health questionnaire and the “Homelessness Supplement.” Using the raw interview data, algorithmic summary scores were computed and integrating clinical parameters assessed. The data describe health and needs in a rights-based, recovery-oriented frame of reference. The mental health approach is transdiagnostic. The positive health framework is used for structuring health and needs aspects in relation to the symptomatic (physical and mental health), social (daily living, social participation), and personal (quality of life, meaning) dimensions of recovery.Results: Recruitment (between 2015 and 2017) resulted in a saturated sample of 436 HS users in 16 facilities and seven cities. Most participants were long-term or intermittently homeless. The sample characteristics reveal the multi domain character of needs and the relevance of a broad, comprehensive approach. Local authorities used the reports to reflect and discuss needs, care provision, access, and network cooperation. These dialogs incited to improve the quality of care at various ecosystem levels.Discussion: This paper describes new recruitment strategies and data collections of comprehensive data domains, to improve our knowledge in the field of homelessness. Traditional epidemiological literature on homelessness is often domain specific and relies on administrative sources. The HOP-TR study uses an analytical epidemiological approach. It shifts the assessment focus from problem-centered marginalization processes toward a comprehensive, three-dimensional recovery-oriented vision of health. Different perspectives are integrated to explore the interaction of homeless people with care networks.

Background: Homelessness is an increasing problem in Western European countries. In the Netherlands, policy reforms and austerity measures induced an urgent need for management information on local homeless citizens. Municipal authorities initiated cross-sectional reviews of Homeless Service (HS) users. The resulting Homeless People Treatment and Recovery (HOP-TR) study developed a health and needs assessment strategy over different domains to comprehensively assess individuals and care networks with the perspective on recovery.Methods: Dutch HS users were selected using a naturalistic meta-snowball sampling. Semi-structured interviews provided the primary data source. The interview content was partly derived from the InterRAI Community Mental Health questionnaire and the “Homelessness Supplement.” Using the raw interview data, algorithmic summary scores were computed and integrating clinical parameters assessed. The data describe health and needs in a rights-based, recovery-oriented frame of reference. The mental health approach is transdiagnostic. The positive health framework is used for structuring health and needs aspects in relation to the symptomatic (physical and mental health), social (daily living, social participation), and personal (quality of life, meaning) dimensions of recovery.Results: Recruitment (between 2015 and 2017) resulted in a saturated sample of 436 HS users in 16 facilities and seven cities. Most participants were long-term or intermittently homeless. The sample characteristics reveal the multi domain character of needs and the relevance of a broad, comprehensive approach. Local authorities used the reports to reflect and discuss needs, care provision, access, and network cooperation. These dialogs incited to improve the quality of care at various ecosystem levels.Discussion: This paper describes new recruitment strategies and data collections of comprehensive data domains, to improve our knowledge in the field of homelessness. Traditional epidemiological literature on homelessness is often domain specific and relies on administrative sources. The HOP-TR study uses an analytical epidemiological approach. It shifts the assessment focus from problem-centered marginalization processes toward a comprehensive, three-dimensional recovery-oriented vision of health. Different perspectives are integrated to explore the interaction of homeless people with care networks.

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.

Financial overview and grant giving statistics of International Hunger And Homeless Charity

This feature layer represents SDG 1.4.2b 'Number of Homeless Persons by County' for Ireland. Attributes include the number of homeless persons in a particular week of the month stated, from January 2019 to January 2020. Official homelessness data is produced by local authorities thrugh the Pathway Accommodation & Support System (PASS). PASS was rolled-out nationally during the course of 2013. The data produced captures details of individuals in State-funded emergency accommodation, arrangements that are overseen by local authorities. The lead local authorities for homelessness in each region provide monthly reports on homelessness which identify the number of people utilising State-funded emergency accommodation on a regional and county basis. These reports are available from the Department of Housing, Planning and Local Government.In 2015 UN countries adopted a set of 17 goals to end poverty, protect the planet and ensure prosperity for all as part of a new sustainable development agenda. Each goal has specific targets to help achieve the goals set out in the agenda by 2030. Governments are committed to establishing national frameworks for the achievement of the 17 Goals and to review progress using accessible quality data. With these goals in mind the CSO and Tailte Éireann are working together to link geography and statistics to produce indicators that help communicate and monitor Ireland’s performance in relation to achieving the 17 sustainable development goals.The indicator displayed supports the efforts to achieve goal number 1 which aims to end poverty in all its forms everywhere.

Seroprevalence of Toxoplasma gondii has been extensively studied in a variety of different human populations. However, no study has focused on homeless populations. Accordingly, the present study aimed to assess the seroprevalence of anti-T. gondii antibodies and the risk factors associated in homeless persons from homeless shelter of São Paulo city, southeastern Brazil. In addition, anti-HIV antibodies and associated risk of T. gondii and HIV coinfection have been evaluated. Anti-T. gondii antibodies were detected by indirect fluorescent antibody test. In addition, anti-HIV levels were tested by chemiluminescence enzyme immunoassay, with positive samples confirmed by rapid immunoblot assay. Overall, IgG anti-T. gondii seropositivity was found in 43/120 (35.8%) homeless persons, with endpoint titers varying from 16 to 1,024. The only two pregnant women tested were negative for IgM by chemiluminescence enzyme immunoassay, with normal parturition and clinically healthy newborns in both cases. There were no statistical differences in the risk factors for anti-T. gondii serology (p > 0.05). Anti-HIV seropositivity was found in 2/120 (1.7%) homeless persons, confirmed as HIV-1. One HIV seropositive individual was also sero-reactive to IgG anti-T. gondii, and both were negative to IgM anti-T. gondii. This is the first study that reports the serosurvey of T. gondii in homeless persons worldwide. Despite the limited sample size available in the present study, our findings have shown that the prevalence of anti-T. gondii antibodies in homeless persons herein was lower than the general population, probably due to homeless diet habit of eating mainly processed food intake. No statistical differences were found regarding risk factors for anti-T. gondii exposure in homeless persons. Future studies should be conducted to fully establish risk factors for anti-T. gondii exposure in homeless persons.

Additional file 2. Articles.

Homlessness Report July 2023. Published by Department of Housing, Local Government, and Heritage. Available under the license Creative Commons Attribution Share-Alike 4.0 (CC-BY-SA-4.0).Homelessness data Official homelessness data is produced by local authorities through the Pathway Accommodation and Support System (PASS). PASS was rolled-out nationally during the course of 2013. The Department’s official homelessness statistics are published on a monthly basis and refer to the number of homeless persons accommodated in emergency accommodation funded and overseen by housing authorities during a specific count week, typically the last full week of the month. The reports are produced through the Pathway Accommodation & Support System (PASS), collated on a regional basis and compiled and published by the Department. Homelessness reporting commenced in this format in 2014. The format of the data may change or vary over time due to administrative and/or technology changes and improvements. The administration of homeless services is organised across nine administrative regions, with one local authority in each of the regions, “the lead authority”, having overall responsibility for the disbursement of Exchequer funding. In each region a Joint Homelessness Consultative Forum exists which includes representation from the relevant State and non-governmental organisations involved in the delivery of homeless services in a particular region. Delegated arrangements are governed by an annually agreed protocol between the Department and the lead authority in each region. These protocols set out the arrangements, responsibilities and financial/performance data reporting requirements for the delegation of funding from the Department. Under Sections 38 and 39 of the Housing (Miscellaneous Provisions) Act 2009 a statutory Management Group exists for each regional forum. This is comprised of representatives from the relevant housing authorities and the Health Service Executive, and it is the responsibility of the Management Group to consider issues around the need for homeless services and to plan for the implementation, funding and co-ordination of such services. In relation to the terms used in the report for the accommodation types see explanation below: PEA - Private Emergency Accommodation: this may include hotels, B&Bs and other residential facilities that are used on an emergency basis. Supports are provided to services users on a visiting supports basis. STA - Supported Temporary Accommodation: accommodation, including family hubs, hostels, with onsite professional support. TEA - Temporary Emergency Accommodation: emergency accommodation with no (or minimal) support....

This indicator presents an overview of strategies and major legislation tackling homelessness at the national and regional level, as reported by OECD, key partner and EU countries responding to the 2021 and 2019 OECD Questionnaire on Social and Affordable Housing (QuASH), and other sources. Homelessness strategies are defined as policy documents setting out targets and actions to tackle homelessness, requiring links across policy sectors. Further discussion of homelessness can be found in the OECD Policy Brief, Better data and policies to fight homelessness in the OECD, available online (and in French).

The research, entitled Homelessness during COVID-19: Homeless Migrants in a Global Crisis, took a biographical life story approach to understand the experiences of 43 non-UK nationals who experienced homelessness during the COVID-19 pandemic. In the first phase of the project, and in order to gain insight into the homelessness sector, we conducted semi-structured interviews with 37 people across nine homelessness organisations. The focus of the interviews was on migrant homelessness before and during the pandemic. Due to ethical reasons, we are not able to upload data from the life story interviews that we conducted with migrants experiencing homelessness. However, the data from the semi-structured interviews with staff in the homelessness sector that we have submitted to the UK Data Service helped us to frame our research and provided much-needed contextual information during the pandemic.

People experiencing homelessness are disproportionately impacted by coronavirus. Despite government efforts to place rough sleepers in hotels to contain the spread of the disease, many migrants sleeping rough with No Recourse to Public Funds (NRPF) have been left behind at the height of a global pandemic. This project, involving researchers from University of Portsmouth, University of Sussex and St Mungo's, the homeless charity, will produce an 18-month qualitative-based study of migrant homelessness framed by the wider global and national context. Working with two of St Mungo's migrant services, Street Legal, St Mungo's legal team and Routes Home, a service supporting people sleeping rough from outside of the UK, a particular focus of the study will be the experience of non-UK nationals and their attempts, during the crisis, to resolve their immigration status. Many of these migrants are at the sharpest end of homelessness: almost 1,000 rough sleepers housed in emergency accommodation in London have NRPF (Heath, 2020).

Most migrant homeless clients are faced with multiple everyday challenges; they experience the hostility and aggression directed toward homeless people, compounded with often intense experiences of racism. Migrant homeless clients are also likely to be afraid of 'authorities' for various reasons including fear of deportation by the Home Office and personal histories of violent persecution by state actors in their original countries of belonging. During the pandemic, increased numbers of police on the streets have created high anxiety for refugees/asylum seekers and destitute migrants who report being retriggered with PTSD symptoms, with no access to NHS mental health services that are now delivered primarily remotely and are restricted access except to those patients who have access to free or cheap wifi, or unlimited phone credit (Munt 2020). A cultural miasma of fear and anxiety due to pandemic can affect such vulnerable minority groups particularly forcefully, with public attitudes generating direct aggression toward perceived 'outsiders' as harbingers of disease. Historically, the discourse of the 'stranger' (Ahmed 1991) or foreigner as bringer of disease has been well recognised within cultural sociology (Munt 2007), and as cultural suspicion grows under such conditions, feelings of alienation and estrangement amongst vulnerable groups intensifies.

The project will innovate by examining the biographical and life history narratives of St Mungo's clients in London in relation to their experiences of homelessness during the coronavirus crisis. Alongside semi-structured interviews, we will use participatory research methods including peer research, autoethnographic diaries, mobile phone photo-ethnographies and life history narratives in order to capture the rich and emotive narratives of those experiencing crisis. In doing so, we will examine the intersection of personal histories, complex global processes and the dynamics of the particular situation (Stewart, 2012, 2013). Researching vulnerable groups requires ethical sensitivity. It carries the danger of risking more disappointment among the respondents and exacerbating intense feelings of loneliness and isolation. To avoid this, and to make a positive intervention, we will seek to engage clients with services and support as part of the research project. Based on its findings, and working with St Mungo's partners, the project will make recommendations for measures that can be taken across the UK and elsewhere to support the homeless, particularly those most vulnerable, during times of crisis.

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).

Occupational therapists support individuals experiencing homelessness in traditional roles, and occupational therapy positions focussed specifically on homelessness appear to be growing. To develop and refine a framework to guide occupational therapy practice and research in homelessness. We developed a framework and refined it through a stakeholder consultation process conducted with 17 international occupational therapy experts using an online survey. In this survey, we presented an initial framework and requested qualitative feedback. We analyzed this qualitative data using content analysis. Stakeholder feedback was categorized into eight recommendations: (1) Revision to the ‘four processes’; (2) Emphasizing social justice and systems-level advocacy; (3) Reflecting intersectionality; (4) Emphasizing meaningful activity; (5) Emphasizing peer support; (6) Incorporating a focus on independent living skills; (7) Increasing a focus on an activity for addressing substance misuse; and (8) Acknowledging cognitive and physical health. Each of these recommendations was incorporated into a refined version of this framework. These recommendations and a refined version of the framework are presented in this paper. We have developed and refined a framework aimed at guiding practice and research in occupational therapy in homelessness that will be evaluated in future research. Though a range of frameworks exists for guiding the practice of occupational therapists more generally, this framework represents the first that is focussed specifically on guiding occupational therapy practice and research with individuals who experience homelessness. Research and practice implications are discussed.

Journeys Home: A Longitudinal Study of Factors Affecting Housing Stability was a national survey of Australians who were either homeless or at high risk of becoming homeless. Data collection commenced in September 2011 with a further five waves of data collected approximately six months apart. Journeys Home was funded by the Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA), and run by the Melbourne Institute of Applied Economic and Social Research at The University of Melbourne. Roy Morgan Research (RMR) was sub-contracted to undertake the fieldwork. It was designed as a tool for enabling research that would improve understanding of the pathways into and out of homelessness in Australia and the consequences of homelessness for long-term outcomes. Three different data releases are available, depending on your research requirements and location. These releases are General, Restricted, and International. In the General and International releases some variables (such as location, industry and debt) are confidentialised. The International release also limits some income related variables.