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.

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.

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This topic page studies available data and empirical evidence on homelessness, focusing specifically on how it affects people in high-income countries. Homeless people are among the most vulnerable groups in high-income countries.

You can read our topic page on Extreme Poverty if you are interested in a broader perspective on economic deprivation and a perspective beyond high-income countries.

Homeless people in the US What data is available? One of the most common ways to measure homelessness is through so-called 'point-in-time' counts of people who are sleeping in shelters or on the streets. These are figures that are intended to reflect the number of people who are homeless 'on any given night'.

The main source of point-in-time estimates in the US is the Department of Housing and Urban Development, which releases the Annual Homeless Assessment Report to Congress (AHARC). They calculate 'point-in-time' estimates by counting homeless people in late January of each year.

The main underlying sources of data used to produce the figures published in the AHARC are (i) registries from shelters and (ii) counts and estimates of sheltered and unsheltered homeless persons provided by care organizations, as part of their applications for government funding.

The counts from the care organizations (called 'Continuums of Care' in the US) come from active counts that are undertaken at the community level, by walking around the streets, using pre-established methodologies.1

In these figures, 'Sheltered Homelessness' refers to people who are staying in emergency shelters, transitional housing programs, or safe havens. 'Unsheltered Homelessness', on the other hand, refers to people whose primary nighttime residence is a public or private place not designated for, or ordinarily used as, a regular sleeping accommodation for people – for example, the streets, vehicles, or parks.2

Financial overview and grant giving statistics of Shelter the Homeless International Projects

Financial overview and grant giving statistics of Homeless and Orphanage Children International

BackgroundAddressing Citizen’s perspectives on homelessness is crucial for the design of effective and durable policy responses, and available research in Europe is not yet substantive. We aim to explore citizens’ opinions about homelessness and to explain the differences in attitudes within the general population of eight European countries: France, Ireland, Italy, the Netherlands, Poland, Portugal, Spain, and Sweden.MethodsA nationally representative telephone survey of European citizens was conducted in 2017. Three domains were investigated: Knowledge, Attitudes, and Practices about homelessness. Based on a multiple correspondence analysis (MCA), a generalized linear model for clustered and weighted samples was used to probe the associations between groups with opposing attitudes.ResultsResponse rates ranged from 30.4% to 33.5% (N = 5,295). Most respondents (57%) had poor knowledge about homelessness. Respondents who thought the government spent too much on homelessness, people who are homeless should be responsible for housing, people remain homeless by choice, or homelessness keeps capabilities/empowerment intact (regarding meals, family contact, and access to work) clustered together (negative attitudes, 30%). Respondents who were willing to pay taxes, welcomed a shelter, or acknowledged people who are homeless may lack some capabilities (i.e. agreed on discrimination in hiring) made another cluster (positive attitudes, 58%). Respondents living in semi-urban or urban areas (ORs 1.33 and 1.34) and those engaged in practices to support people who are homeless (ORs > 1.4; p<0.005) were more likely to report positive attitudes, whereas those from France and Poland (p<0.001) were less likely to report positive attitudes.ConclusionThe majority of European citizens hold positive attitudes towards people who are homeless, however there remain significant differences between and within countries. Although it is clear that there is strong support for increased government action and more effective solutions for Europe’s growing homelessness crisis, there also remain public opinion barriers rooted in enduring negative perceptions.

In 2024/25, 13,231 people who were seen to be sleeping rough in London compared with 11,993 in the previous reporting year, and the most reported during this time period. The number of people reported to be sleeping rough has steadily increased throughout this time period, with the dip in 2020/21, and 2022/23, likely related to the COVID-19 pandemic. Demographics of London's homeless As of the most recent reporting year, over 2,000 of London's rough sleepers were in the borough of Westminster, the most of any London borough. In terms of gender, the majority of rough sleepers are male, with more than 10,000 men seen to be sleeping rough, compared with 2,149 women, and 18 non-binary people. The most common age group was among those aged between 36 and 45 years old, at more than 3,900, compared with 1,411 25 and under, 3,580 aged between 26 and 34, 2,860 aged 45 and 55, and around 1,578 over 55s. Homelessness in the U.S. Homelessness is also an important social issue in several other countries. In the United States, for example, there were estimated to be approximately 653,104 people experiencing homelessness in 2023. This was a noticeable increase on the previous year, and the highest number between 2007 and 2023. When looking at U.S. states, New York had the highest homelessness rate, at 52 individuals per 10,000 population, followed by Vermont at 51.

Additional file 5. A condensed version of the data repository from all 77 documents.

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.

BackgroundHomelessness represents a widespread social issue globally, yet the risk of neurodegenerative diseases (NDDs) associated with people experiencing homelessness (PEH) has not received sufficient attention. Therefore, this study aimed to explore the risk of NDDs among PEH and its variation across countries and regions through meta-analysis and systematic review.MethodsSearching from databases such as PubMed and Web of Science, relevant research articles on PEH and NDDs were identified. After multiple screening, eight articles were selected for meta-analysis. Statistical methods and models were used to evaluate the association between PEH and NDDs, stratified by disease type and country.ResultsWe found that PEH had a 51% higher risk of NDDs (OR = 1.51 (95% CI: 1.21, 1.89)) compared with those with stable housing. Specifically, PEH had a significantly higher risk of developing multiple sclerosis (OR = 4.64 (95% CI: 1.96, 10.98)). Alzheimer’s disease and related dementias (ADRD) (OR = 1.93 (95% CI: 1.34, 2.77)), dementia (OR = 1.69 (95% CI: 1.26, 2.27)), and cognitive impairment (OR = 1.07 (95% CI: 0.98, 1.16)) were all at higher risk. Furthermore, country and regional differences were observed, with countries such as Iran (OR = 4.64 (95% CI: 1.96, 10.98)), the Netherlands (OR = 2.14 (95% CI: 1.23, 3.73)), the United States (OR = 1.66 (95% CI: 1.25, 2.22)), and Canada (OR = 1.06 (95% CI: 1.01, 1.10)) showing a higher risk of NDDs among the PEH.ConclusionsThe study emphasizes the significant NDD risks among PEH, providing novel perspectives on this issue and shedding light on national disparities influenced by variations in healthcare systems and social environments. This will be beneficial for academia and government to prioritize the health of PEH with NDDs, aiming to mitigate disease incidence and economic burdens while preserving social stability and upholding basic human rights.

Study-level factors associated with between-study heterogeneity in multivariable meta-regression.