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.

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.

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.

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.

Financial overview and grant giving statistics of World Aid for Homeless Children Incorported

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

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 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).

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

This dataset is extracted from https://en.wikipedia.org/wiki/List_of_countries_by_homeless_population. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?

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 who inhabit part or all of the physical or census building, usually live together, who eat from one kitchen or organize daily needs together as one unit. - Group quarters: A special household includes people living in dormitories, barracks, or institutions in which daily needs are under the responsibility of a foundation or other organization. Also includes groups of people in lodging houses or buildings, where the total number of lodgers is ten or more.

Universe

All population residing in the geographic area of Indonesia regardless of residence status. Diplomats and their families residing in Indonesia were excluded.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Central Bureau of Statistics

SAMPLE SIZE (person records): 20112539.

SAMPLE DESIGN: Geographically stratified systematic sample (drawn by IPUMS).

Mode of data collection

Face-to-face [f2f]

Research instrument

L1 questionnaire for buildings and households; L2 questionnaire for permanent residents; and L3 questionnaire for non-permanent residents (boat people, homeless persons, etc).

Financial overview and grant giving statistics of Global Partnership for Homeless Health Inc.

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

This article analyzes the evictions faced by the homeless during the preparations of Rio de Janeiro for the 2014 World Cup and the 2016 Olympic Games, framed by social conflicts in favor of the right to the city, by juxtaposing urban security for the elites and disrespect for the rights of subaltern classes. The media’s and the official discourses classify the homeless as those who “live on the streets”, naturalizing their “home-less” condition and establishing the myth that, despite not having a home, that population inhabit somewhere. This process tends to empty the conflicting nature of the social relations that operate within the cities, such as the real reasons for the economic and social exclusion, thus accentuating opportunities for huge real estate investments in accelerated gentrification processes.

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: Yes - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: Dwelling is any inhabited physical place, constructed or adapted for housing people. - Households: Household is a group of people, related or otherwise, who occupy the dwelling. - Group quarters: Collective houshold is a group of people who share the dwelling in a non-familial system, for reasons of work, health, discipline, religion, punishment, etc.

Universe

All the population in the national territory at the moment the census is carried out. Homeless, passengers in transit (international flights), personnel on duty in hospitals, factories, institutions, and other places, employees of the National Institute of Statistics, embassies and consulates

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics, Ministry of Planning and Coordination, Republic of Bolivia

SAMPLE SIZE (person records): 642368.

SAMPLE DESIGN: Systematic sample of every tenth dwelling with a random start; drawn by IPUMS Homeless, passengers in transit (international flights), personnel on duty in hospitals, factories, institutions, and other places, employees of the National Institute of Statistics, embassies and consulates

Mode of data collection

Face-to-face [f2f]

Research instrument

A single booklet that consists of sections on geographic location, dwelling, and population (individual)

Winter Shelter Overflow Monitoring Market Outlook

According to our latest research, the Global Winter Shelter Overflow Monitoring market size was valued at $415 million in 2024 and is projected to reach $1.18 billion by 2033, expanding at a CAGR of 12.2% during the forecast period of 2024–2033. One of the major factors fueling the growth of this market globally is the increasing demand for real-time capacity monitoring and intelligent resource allocation in homeless shelters and emergency response centers, especially during harsh winter months. As urban populations rise and climate change leads to more unpredictable and severe winter conditions, the need for advanced monitoring solutions that ensure the safety and well-being of vulnerable populations is more critical than ever. This has led to a surge in investments in digital infrastructure and smart monitoring platforms by municipalities, non-profit organizations, and government agencies worldwide, further propelling the market’s expansion.

Regional Outlook

North America currently holds the largest share of the Winter Shelter Overflow Monitoring market, accounting for over 38% of the global market value in 2024. The region’s dominance is attributed to its mature technological landscape, robust funding for social welfare programs, and stringent regulatory frameworks that mandate effective shelter management, especially during winter emergencies. The United States and Canada lead the adoption of advanced software and hardware solutions, leveraging IoT, cloud computing, and analytics for real-time occupancy tracking and resource optimization. The presence of numerous non-profit organizations, proactive municipal authorities, and significant federal investments in homelessness prevention further reinforce North America’s leadership in this sector. Ongoing public-private partnerships and integration of AI-driven analytics are expected to keep the region at the forefront of innovation and market growth through 2033.

Asia Pacific is identified as the fastest-growing region in the Winter Shelter Overflow Monitoring market, projected to register a remarkable CAGR of 15.7% from 2024 to 2033. This rapid growth is driven by increasing urbanization, rising incidences of extreme weather events, and heightened government focus on social welfare infrastructure across countries such as China, Japan, South Korea, and Australia. Investments in smart city initiatives and the proliferation of cloud-based monitoring solutions are enabling municipalities and non-profits to adopt scalable and cost-effective shelter overflow management systems. Additionally, regional governments are launching targeted policy reforms and incentives to improve the resilience of social services, which is fostering the adoption of advanced monitoring technologies. The market in Asia Pacific is also benefiting from collaborations with international humanitarian organizations and technology vendors, further accelerating the deployment of innovative solutions.

Emerging economies in Latin America, the Middle East, and Africa are gradually adopting Winter Shelter Overflow Monitoring solutions, although market penetration remains relatively low compared to developed regions. Challenges such as limited digital infrastructure, budgetary constraints, and varying policy frameworks often hinder the widespread implementation of advanced monitoring systems. However, localized demand is rising, particularly in urban centers facing increasing homelessness and unpredictable winter conditions. International aid, NGO partnerships, and localized pilot projects are playing a crucial role in bridging the technology gap and demonstrating the value of real-time monitoring for shelter management. Over the forecast period, as governments in these regions prioritize social protection and invest in digital transformation, the adoption rate of winter shelter monitoring solutions is expected to accelerate, albeit from a smaller base.

Report Scope

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

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes - Special populations: Homeless; nomads

UNIT DESCRIPTIONS: - Households: A standard household is a person or a group of people related or not, living in the same housing unit, often taking their meals together and working together on the other essential needs. This group generally recognizes the authority of one person who is called the Head of Household. - Group quarters: This is a group of people, who for non-family reasons which are mainly related to profession, health, school, denomination, or detention, live together in a specialized establishment or institution like a workers camp, military barracks, dormitories, a hospital with rooms, a convent, an orphanage, a prison.

Universe

All persons present in Cameroon at the time of the census, including visitors from other countries.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Central Bureau of Census and Population Studies

SAMPLE DESIGN: Systematic sample of every 10th dwelling with a random start, drawn by MPC

SAMPLE FRACTION: 10%

SAMPLE UNIVERSE: Systematic sample of every 10th dwelling with a random start, drawn by MPC

SAMPLE SIZE (person records): 1,772,359

Mode of data collection

Face-to-face [f2f]

Research instrument

Four forms: Standard household questionnaire, communal household questionnaire, nomad questionnaire, and homeless questionnaire

Response rate

UNDERCOUNT: No available estimate