38 datasets found
  1. Rate of homelessness in the U.S. 2023, by state

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Rate of homelessness in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/727847/homelessness-rate-in-the-us-by-state/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    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.

  2. Tables on homelessness

    • gov.uk
    Updated Apr 30, 2025
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    Ministry of Housing, Communities and Local Government (2025). Tables on homelessness [Dataset]. https://www.gov.uk/government/statistical-data-sets/live-tables-on-homelessness
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    Dataset updated
    Apr 30, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Housing, Communities and Local Government
    Description

    Statutory homelessness live tables

    Statutory homelessness England Level Time Series

    https://assets.publishing.service.gov.uk/media/680f5de9dbea49d6a3305ec5/StatHomeless_202412.ods">Statutory homelessness England level time series "live tables"

     <p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute"><abbr title="OpenDocument Spreadsheet" class="gem-c-attachment_abbr">ODS</abbr></span>, <span class="gem-c-attachment_attribute">309 KB</span></p>
    
    
    
      <p class="gem-c-attachment_metadata">
       This file is in an <a href="https://www.gov.uk/guidance/using-open-document-formats-odf-in-your-organisation" target="_self" class="govuk-link">OpenDocument</a> format
    

    Detailed local authority-level tables

    For quarterly local authority-level tables prior to the latest financial year, see the Statutory homelessness release pages.

    https://assets.publishing.service.gov.uk/media/680f5e5c172df773f0305ec9/Detailed_LA_202412.ods">Statutory homelessness in England: October to December 2024

     <p class="gem-c-attachment_metadata"><span class="gem-c-attachment_attribute"><abbr title="OpenDocument Spreadsheet" class="gem-c-attachment_abbr">ODS</abbr></span>, <span class="gem-c-attachment_attribute">1.19 MB</span></p>
    
    
    
      <p class="gem-c-attachment_metadata">
       This file is in an <a href="https://www.gov.uk/guidance/using-open-document-formats-odf-in-your-organisation" target="_self" class="govuk-link">OpenDocument</a> format
    

  3. Homelessness Report April 2025

    • datasalsa.com
    csv
    Updated May 31, 2025
    + more versions
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    Department of Housing, Local Government, and Heritage (2025). Homelessness Report April 2025 [Dataset]. https://datasalsa.com/dataset/?catalogue=data.gov.ie&name=homelessness-report-april-2025
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    csvAvailable download formats
    Dataset updated
    May 31, 2025
    Dataset provided by
    Department of Housing, Local Government and Heritage
    Authors
    Department of Housing, Local Government, and Heritage
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Time period covered
    May 31, 2025
    Description

    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....

  4. U.S. beliefs on what is a major cause of homelessness 2023, by political...

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). U.S. beliefs on what is a major cause of homelessness 2023, by political party [Dataset]. https://www.statista.com/statistics/1446063/us-political-beliefs-on-what-causes-homelessness/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 24, 2023 - May 27, 2023
    Area covered
    United States
    Description

    According to a survey conducted in 2023, ** percent of Americans who identified as Independent and ** percent of Americans who identified as Republican believed that drug and alcohol use was a major cause of homelessness in the United States. In comparison, only ** percent of Democrats shared this belief.

  5. Homelessness major causes South Korea 2016

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Homelessness major causes South Korea 2016 [Dataset]. https://www.statista.com/statistics/798280/south-korea-major-causes-of-homelessness/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 17, 2016 - Dec 20, 2016
    Area covered
    South Korea
    Description

    This statistic describes the major causes of homelessness in South Korea as of December 2016. During the surveyed time period, **** percent of the interviewed homeless people answered that personal maladjustment or accident was a decisive factor that caused the homelessness.

  6. f

    Data_Sheet_1_Disparities in all-cause mortality among people experiencing...

    • frontiersin.figshare.com
    docx
    Updated Aug 9, 2024
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    Lucie Richard; Brooke Carter; Linda Wu; Stephen W. Hwang (2024). Data_Sheet_1_Disparities in all-cause mortality among people experiencing homelessness in Toronto, Canada during the COVID-19 pandemic: a cohort study.docx [Dataset]. http://doi.org/10.3389/fpubh.2024.1401662.s001
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    docxAvailable download formats
    Dataset updated
    Aug 9, 2024
    Dataset provided by
    Frontiers
    Authors
    Lucie Richard; Brooke Carter; Linda Wu; Stephen W. Hwang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Canada, Toronto
    Description

    People experiencing homelessness have historically had high mortality rates compared to housed individuals in Canada, a trend believed to have become exacerbated during the COVID-19 pandemic. In this matched cohort study conducted in Toronto, Canada, we investigated all-cause mortality over a one-year period by following a random sample of people experiencing homelessness (n = 640) alongside matched housed (n = 6,400) and low-income housed (n = 6,400) individuals. Matching criteria included age, sex-assigned-at-birth, and Charlson comorbidity index. Data were sourced from the Ku-gaa-gii pimitizi-win cohort study and administrative databases from ICES. People experiencing homelessness had 2.7 deaths/100 person-years, compared to 0.7/100 person-years in both matched unexposed groups, representing an all-cause mortality unadjusted hazard ratio (uHR) of 3.7 (95% CI, 2.1–6.5). Younger homeless individuals had much higher uHRs than older groups (ages 25–44 years uHR 16.8 [95% CI 4.0–70.2]; ages 45–64 uHR 6.8 [95% CI 3.0–15.1]; ages 65+ uHR 0.35 [95% CI 0.1–2.6]). Homeless participants who died were, on average, 17 years younger than unexposed individuals. After adjusting for number of comorbidities and presence of mental health or substance use disorder, people experiencing homelessness still had more than twice the hazard of death (aHR 2.2 [95% CI 1.2–4.0]). Homelessness is an important risk factor for mortality; interventions to address this health disparity, such as increased focus on homelessness prevention, are urgently needed.

  7. l

    Continuum of Care (CoC) Grantee Areas

    • data.lojic.org
    • catalog.data.gov
    • +3more
    Updated Oct 2, 2024
    + more versions
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    Department of Housing and Urban Development (2024). Continuum of Care (CoC) Grantee Areas [Dataset]. https://data.lojic.org/datasets/HUD::continuum-of-care-coc-grantee-areas
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    Dataset updated
    Oct 2, 2024
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    The Continuum of Care (CoC) Homeless Assistance Programs administered by HUD award funds competitively and require the development of a Continuum of Care system in the community where assistance is being sought. A continuum of care system is designed to address the critical problem of homelessness through a coordinated community-based process of identifying needs and building a system to address those needs. The approach is predicated on the understanding that homelessness is not caused merely by a lack of shelter, but involves a variety of underlying, unmet needs - physical, economic, and social. Funds are granted based on the competition following the Notice of Funding Availability (NOFA).To learn more about the CoC Program visit: https://www.hudexchange.info/programs/coc/, for more information about CoC program data, visit https://www.hudexchange.info/programs/coc/coc-program-reports-program-data-and-program-rents/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Continuum of CareDate of Coverage: FY 2024

  8. Deaths of homeless people in England and Wales

    • cy.ons.gov.uk
    • ons.gov.uk
    xlsx
    Updated Nov 23, 2022
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    Office for National Statistics (2022). Deaths of homeless people in England and Wales [Dataset]. https://cy.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/deathsofhomelesspeopleinenglandandwales
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    xlsxAvailable download formats
    Dataset updated
    Nov 23, 2022
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    Wales
    Description

    The number of deaths of homeless people in England and Wales, by sex, five-year age group and underlying cause of death, 2013 to 2021 registrations. Experimental Statistics.

  9. Deaths among homeless people pre- and post-COVID-19, in L.A. by cause of...

    • statista.com
    Updated Apr 22, 2024
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    Statista (2024). Deaths among homeless people pre- and post-COVID-19, in L.A. by cause of death [Dataset]. https://www.statista.com/statistics/1462853/deaths-among-homeless-people-pre-and-post-covid-in-la-by-cause-of-death/
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    Dataset updated
    Apr 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Los Angeles, United States (California), North America
    Description

    In Los Angeles County, the number of deaths among people experiencing homelessness (PEH) had an overall increase when comparing the 12 months pre- and post-COVID-19. Among the leading death causes, drug overdose reported the biggest increase of 78 percent. Additionally, COVID-19 was the third leading cause of death from April 1, 2020 to March 31, 2021, resulting in 179 deaths during that time. This statistic depicts the number of deaths among people experiencing homelessness, 12 months pre- and post-COVID-19 pandemic, in Los Angeles County, by cause of death.

  10. Leading causes of death among homeless persons in New York City 2021-2022

    • statista.com
    Updated Apr 24, 2024
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    Statista (2024). Leading causes of death among homeless persons in New York City 2021-2022 [Dataset]. https://www.statista.com/statistics/1463062/leading-causes-death-among-homeless-persons-new-york-city/
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    Dataset updated
    Apr 24, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    New York
    Description

    From July 1, 2021 to June 30, 2022, New York City's Department of Social Services/Department of Homeless Services (DHS) and Office of the Chief Medical Examiner (OCME) reported 684 deaths among individuals experiencing homelessness. Among these, around 329 were attributed to drug-related causes, making this the primary cause of death within this demographic. This statistic depicts the leading causes of death among persons experiencing homelessness in New York City between 2021 and 2022.

  11. u

    Deaths of People Experiencing Homelessness - Catalogue - Canadian Urban Data...

    • data.urbandatacentre.ca
    • beta.data.urbandatacentre.ca
    Updated Oct 3, 2024
    + more versions
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    (2024). Deaths of People Experiencing Homelessness - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/city-toronto-deaths-of-people-experiencing-homelessness
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    Dataset updated
    Oct 3, 2024
    Description

    Starting in January 2017, Toronto Public Health (TPH) began tracking the deaths of people experiencing homelessness to get a more accurate estimate of the number of deaths and their causes. TPH leads the data collection, analysis and reporting. The Shelter, Support and Housing Administration (SSHA) and health and social service agencies that support people experiencing homelessness share information about a death with TPH and the Office of the Chief Coroner of Ontario (OCCO) verifies some of the data. For this data collection initiative, homelessness is defined as “the situation of an individual or family without stable, permanent, appropriate housing, or the immediate prospect, means and ability of acquiring it”.

  12. u

    Homeless in Rural and Northern Ontario - Catalogue - Canadian Urban Data...

    • beta.data.urbandatacentre.ca
    • data.urbandatacentre.ca
    Updated Feb 5, 2024
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    (2024). Homeless in Rural and Northern Ontario - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://beta.data.urbandatacentre.ca/dataset/homeless-in-rural-and-northern-ontario
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    Dataset updated
    Feb 5, 2024
    Area covered
    Northern Ontario, Canada, Ontario
    Description

    Homelessness and Hidden Homelessness in Rural and Northern Ontario is the first study of its kind to empirically challenge these popular perceptions. In fact, as the analysis of data from the recent Canadian Social Survey demonstrates, compared to city dwellers, a higher percentage of people from rural Ontario reported that they had experienced homelessness or hidden homelessness at some point in their lives. The research carried out for this report was based on a survey of service providers (with responses from 204 service providers and 30 service managers), focus groups (with 76 key sector stakeholders), and interviews (with 40 people who had experience of homelessness or hidden homelessness) in 10 communities in northwestern, northeastern, southwestern, and southeastern Ontario. This was augmented by an analysis of Ontario data from Canada’s General Social Survey. The causes of homelessness in rural and northern Ontario were found to be similar to those in big cities: poverty, mental illness and addictions, lack of affordable housing and domestic violence. The study also revealed that many Indigenous peoples are at risk of homelessness and hidden homelessness, particularly those living in northern areas of the province.

  13. p

    Deaths of People Experiencing Homelessness - Dataset - CKAN

    • ckan0.cf.opendata.inter.prod-toronto.ca
    Updated May 15, 2023
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    (2023). Deaths of People Experiencing Homelessness - Dataset - CKAN [Dataset]. https://ckan0.cf.opendata.inter.prod-toronto.ca/dataset/deaths-of-people-experiencing-homelessness
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    Dataset updated
    May 15, 2023
    Description

    Starting in January 2017, Toronto Public Health (TPH) began tracking the deaths of people experiencing homelessness to get a more accurate estimate of the number of deaths and their causes. TPH leads the data collection, analysis and reporting. The Shelter, Support and Housing Administration (SSHA) and health and social service agencies that support people experiencing homelessness share information about a death with TPH and the Office of the Chief Coroner of Ontario (OCCO) verifies some of the data. For this data collection initiative, homelessness is defined as “the situation of an individual or family without stable, permanent, appropriate housing, or the immediate prospect, means and ability of acquiring it”.

  14. D

    ARCHIVED: COVID-19 Deaths by Population Characteristics Over Time

    • data.sfgov.org
    application/rdfxml +5
    Updated Sep 11, 2023
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    (2023). ARCHIVED: COVID-19 Deaths by Population Characteristics Over Time [Dataset]. https://data.sfgov.org/COVID-19/ARCHIVED-COVID-19-Deaths-by-Population-Characteris/w6fd-iq9e
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    csv, tsv, application/rssxml, xml, json, application/rdfxmlAvailable download formats
    Dataset updated
    Sep 11, 2023
    Description

    A. SUMMARY This archived dataset includes data for population characteristics that are no longer being reported publicly. The date on which each population characteristic type was archived can be found in the field “data_loaded_at”.

    To access the dataset that continues to refresh daily, navigate to this page: COVID-19 Deaths by Population Characteristics Over Time.   The dataset contains data on the following population characteristics that are no longer being reported publicly:

    • Skilled Nursing Facility Occupancy
    • Sexual orientation
    • Comorbidities
    • Homelessness
    • Single room occupancy (SRO) tenancy
    • Transmission Type

    B. HOW THE DATASET IS CREATED COVID-19 deaths are suspected to be associated with COVID-19. This means COVID-19 is listed as a cause of death or significant condition on the death certificate.    Data on the population characteristics of COVID-19 deaths are from:  * Case interviews  * Laboratories  * Medical providers    These multiple streams of data are merged, deduplicated, and undergo data verification processes.      Skilled Nursing Facility (SNF) occupancy * A Skilled Nursing Facility (SNF) is a type of long-term care facility that provides care to individuals, generally in their 60s and older, who need functional assistance in their daily lives.  * This dataset includes data for COVID-19 deaths reported in Skilled Nursing Facilities (SNFs) through 12/31/2022, archived on 1/5/2023. These data were identified where “Characteristic_Type” = ‘Skilled Nursing Facility Occupancy’.

    Sexual orientation    * The City began asking adults 18 years old or older for their sexual orientation identification during case interviews as of April 28, 2020. Sexual orientation data prior to this date is unavailable. * The City doesn’t collect or report information about sexual orientation for persons under 12 years of age. * Case investigation interviews transitioned to Virtual Assistant information gathering starting December 2021. The California Department of Public Health, Virtual Assistant is only sent to adults who are 18+ years old. Learn more about our data collection guidelines pertaining to sexual orientation.

    Comorbidities * Underlying conditions are reported when a person has one or more underlying health conditions at the time of diagnosis or death.

    Homelessness Persons are identified as homeless based on several data sources: * self-reported living situation * the location at the time of testing * Department of Public Health homelessness and health databases * Residents in Single-Room Occupancy hotels are not included in these figures. These methods serve as an estimate of persons experiencing homelessness. They may not meet other homelessness definitions.

    Single Room Occupancy (SRO) tenancy * SRO buildings are defined by the San Francisco Housing Code as having six or more "residential guest rooms" which may be attached to shared bathrooms, kitchens, and living spaces. * The details of a person's living arrangements are verified during case interviews.

    Transmission type * Information on transmission of COVID-19 is based on case interviews with individuals who have a confirmed positive test. Individuals are asked if they have been in close contact with a known COVID-19 case. If they answer yes, transmission category is recorded as contact with a known case. If they report no contact with a known case, transmission category is recorded as community transmission. If the case is not interviewed or was not asked the question, they are counted as unknown.

    C. UPDATE PROCESS This dataset will only update when any population characteristics are archived. Data for existing characteristic types will not change but new characteristic types may be added.   D. HOW TO USE THIS DATASET This dataset may include different types of characteristics. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of deaths on each date.

    New deaths are the count of deaths within that characteristic group on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed.

    E. CHANGE LOG

    • 6/6/2023 - data on deaths by transmission type are no longer being updated. This data is currently through 6/1/2023 (as of 6/6/2023) and will not include any new data after this date.
    • 5/16/2023 - data on deaths by sexual orientation, comorbidities, homelessness, and single room occupancy are no longer being updated. This data is currently through 5/11/2023 (as of 5/16/2023) and will not include any new data after this date.
    • 1/5/2023 - data on SNF deaths are no longer being updated. SNF data is currently through 12/31/2022 (as of 1/5/2023) and will not include any new data after this date.

  15. f

    Percent distribution of homeless individuals by episodes of homelessness,...

    • plos.figshare.com
    xls
    Updated Jul 24, 2024
    + more versions
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    Megan Odd; Amir Erfani (2024). Percent distribution of homeless individuals by episodes of homelessness, according to selected characteristics, Nipissing District, Ontario 2021. [Dataset]. http://doi.org/10.1371/journal.pone.0305485.t003
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    xlsAvailable download formats
    Dataset updated
    Jul 24, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Megan Odd; Amir Erfani
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ontario, Nipissing District
    Description

    Percent distribution of homeless individuals by episodes of homelessness, according to selected characteristics, Nipissing District, Ontario 2021.

  16. c

    Causes of Homelessness among Older People in Four Cities in England, and...

    • datacatalogue.cessda.eu
    Updated Nov 28, 2024
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    Watt, H.; Byrne, K.; Crane, M., University of Sheffield; Warnes, A. M. (2024). Causes of Homelessness among Older People in Four Cities in England, and Boston, Massachusetts, 2001-2003 [Dataset]. http://doi.org/10.5255/UKDA-SN-5276-1
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    Dataset updated
    Nov 28, 2024
    Dataset provided by
    Boston Medical Center
    Committee to End Elder Homelessness
    King
    Sheffield Institute for Studies on Ageing
    Authors
    Watt, H.; Byrne, K.; Crane, M., University of Sheffield; Warnes, A. M.
    Time period covered
    Jul 1, 2001 - Aug 1, 2003
    Area covered
    England
    Variables measured
    Individuals, Cross-national, National
    Measurement technique
    Face-to-face interview, Self-completion, the 'key workers' (case managers) completed questionnaires about their assessments of the respondents’ problems and of the events and states that led to homelessness. Further clarifications and checks were made by telephone.
    Description

    Abstract copyright UK Data Service and data collection copyright owner.


    A comparative study of the causes of new episodes of homelessness among people aged 50 or more years was undertaken in Boston, Massachusetts (USA), Melbourne, Australia, and four English cities. The aims were to make a substantial contribution to the predominantly American debate on the causes of homelessness, and to make practice recommendations for the improvement of prevention.

    The study had several objectives. It aimed to collect information about the antecedents, triggers and risk factors for becoming homeless in later life and about the national and local policy and service contexts. Furthermore, the researchers aimed to analyse and interpret the findings with reference to an integrated model of the causes of homelessness that represented structural and policy factors, including housing, health and social service organisation and delivery factors, and personal circumstances, events, problems and dysfunctions. The aim was to do this collaboratively, by drawing on the project partners' experience and knowledge. Finally, it was hoped to develop recommendations for housing, primary health care and social welfare organisations for the prevention of homelessness. This was to be done by identifying the common sequences and interactions of events that precede homelessness and their markers (or 'early warning' indicators) and by holding workshops in England with practitioners and their representative organisations on new ways of working.

    By the study of contrasting welfare and philanthropic regimes in a relatively homogeneous category of homeless incidence (i.e. recent cases among late middle-aged and older people), it was hoped that valuable insights into the relative contributions of the policy, service and personal factors would be obtained. The study focused on older people who had recently become homeless, purposely to gather detailed and reliable information about the prior and contextual circumstances. To have included people who had been homeless for several years would have reduced the quality of the data because of 'recall' problems.

    Users should note that data from the Australian sample for the study are not included in this dataset.
    Main Topics:

    The data file includes information about the English respondents and those from Boston. It was compiled in two stages. The first stage involved each project partner entering the pre-coded responses into the file. All partners then identified themes and created codes for the open-ended responses, and the resulting variables were added. Data quality-control procedures included blind checks of the data coding and keying.

    The first 200 variables pertain to information collected from the respondents. They comprise descriptive variables of the circumstances prior to homelessness, including housing tenure during the three years prior to the survey, previous homelessness, employment history, income, health and addiction problems, and contacts with family, friends and formal services. The respondents were asked to rate whether specific factors were implicated in becoming homeless, and where appropriate, a following open-ended question sought elaboration.

    The remaining variables comprise information collected from the respondents' 'key workers' about their understanding of the events and states that led to their clients becoming homeless.

  17. Share of overdose deaths among homeless people pre- and post-COVID-19 in...

    • statista.com
    Updated Apr 22, 2024
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    Statista (2024). Share of overdose deaths among homeless people pre- and post-COVID-19 in L.A. by drug [Dataset]. https://www.statista.com/statistics/1462861/share-of-overdose-deaths-among-homeless-people-pre-and-post-covid-in-la-by-drug/
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    Dataset updated
    Apr 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States (California), North America, Los Angeles
    Description

    In Los Angeles County, methamphetamine accounted for the highest share of overdose deaths among people experiencing homelessness (PEH) in the 12 months before and after the COVID-19 pandemic onset, contributing to approximately three-quarters of all overdose deaths in both years. Fentanyl ranked as the second leading cause of overdose death in both periods, but showed the largest increase in its contribution over the analyzed timeframe. This statistic depicts the percentage of deaths among people experiencing homelessness by overdose pre- and post-COVID-19 pandemic in Los Angeles County, by drug type.

  18. d

    Compendium – LBOI section 2: Housing and homelessness

    • digital.nhs.uk
    xlsx
    Updated Sep 22, 2015
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    (2015). Compendium – LBOI section 2: Housing and homelessness [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/compendium-local-basket-of-inequality-indicators-lboi/current/section-2-housing-and-homelessness
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    xlsx(356.0 kB)Available download formats
    Dataset updated
    Sep 22, 2015
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Time period covered
    Jun 1, 2003 - Dec 31, 2014
    Area covered
    England
    Description

    DCLG collects information on the number of households with or expecting dependent children, who are, at the end of each quarter, in any of the following types of temporary accommodation: • Bed and Breakfast (B&B) - typically involves the use of privately managed hotels where households share at least some facilities and meals are provided; • Annexe accommodation - is also generally paid on a nightly basis, privately managed but may not be part of a B&B hotel and may not involve shared facilities. A distinction is made on the basis of whether at least some facilities are shared or there is exclusive use of all facilities; • Hostel accommodation - hostels assumes shared accommodation, owned or leased and managed by either a local authority, housing association or non-profit making organisation; includes reception centres and emergency units; • Private sector accommodation - dwellings may be leased from the private sector, either directly, or by a local authority or a Registered Social Landlord; • Other - includes mobile homes, such as caravans, ‘demountables’, ‘portacabins’ and ‘transposables.’ The last 20 years have seen a rapid increase in homelessness, with the numbers of officially homeless families peaking in the early 1990s. In 1997 102,000 were statutory homeless, i.e. they met the definition of homelessness laid down in the 1977 Housing (Homeless Persons) Act. Other homeless people included rough sleepers - those without any accommodation at all - and hostel users. In 1997, fifty eight per cent of statutory homeless households had dependent children, and a further 10 per cent had a pregnant household member, compared to 51% and 10% respectively in 2003. Poor housing environments contribute to ill health through poor amenities, shared facilities and overcrowding, inadequate heating or energy inefficiency. The highest risks to health in housing are attached to cold, damp and mouldy conditions. In addition, those in very poor housing, such as homeless hostels and bedsits, are more likely to suffer from poor mental and physical health than those whose housing is of higher quality. People living in temporary accommodation of the bed and breakfast kind have high rates of some infections and skin conditions and children have high rates of accidents. Living in such conditions engenders stress in the parents and impairs normal child development through lack of space for safe play and exploration. Whilst cause and effect are hard to determine, at the very least homelessness prevents the resolution of associated health problems. Legacy unique identifier: P01088

  19. f

    Percent distribution of homeless individuals by reason for housing loss,...

    • plos.figshare.com
    xls
    Updated Jul 24, 2024
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    Megan Odd; Amir Erfani (2024). Percent distribution of homeless individuals by reason for housing loss, according to selected characteristics, Nipissing District, Ontario 2021. [Dataset]. http://doi.org/10.1371/journal.pone.0305485.t002
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    xlsAvailable download formats
    Dataset updated
    Jul 24, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Megan Odd; Amir Erfani
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ontario, Nipissing District
    Description

    Percent distribution of homeless individuals by reason for housing loss, according to selected characteristics, Nipissing District, Ontario 2021.

  20. Homelessness Report May 2025

    • datasalsa.com
    csv
    Updated Jul 2, 2025
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    Department of Housing, Local Government and Heritage (2025). Homelessness Report May 2025 [Dataset]. https://datasalsa.com/dataset/?catalogue=data.gov.ie&name=homelessness-report-may-2025
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    csvAvailable download formats
    Dataset updated
    Jul 2, 2025
    Dataset authored and provided by
    Department of Housing, Local Government and Heritage
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Time period covered
    Jul 2, 2025
    Description

    Homelessness Report May 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....

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Statista (2025). Rate of homelessness in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/727847/homelessness-rate-in-the-us-by-state/
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Rate of homelessness in the U.S. 2023, by state

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4 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
United States
Description

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.

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