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

    • statista.com
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    Statista, 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 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. d

    Homelessness and COVID-19

    • datasets.ai
    • data.kingcounty.gov
    • +1more
    21
    Updated Sep 6, 2024
    + more versions
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    King County, Washington (2024). Homelessness and COVID-19 [Dataset]. https://datasets.ai/datasets/homelessness-and-covid-19
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    21Available download formats
    Dataset updated
    Sep 6, 2024
    Dataset authored and provided by
    King County, Washington
    Description

    Updated every Thursday People experiencing homelessness are at risk for infection through community spread of COVID-19. The data below describes impacts of COVID-19 on individuals who are experiencing homelessness, whether they are able to access a congregate shelter or unsheltered (sleeping outside or in places not meant for human habitation).

    For COVID-19 investigation purposes, people experiencing homelessness are defined as those who have lived on the streets or stayed in a shelter, vehicle, abandoned building, encampment, tiny house village/tent city, or supportive housing program (transitional or permanent supportive) at any time during the 12 months prior to COVID-19 testing, without evidence that they were otherwise permanently housed. Public Health, the Department of Community and Human Services, homeless service providers, healthcare providers, and the City of Seattle have partnered for increased testing in this community.

  3. d

    Strategic Measure_Number and percentage of persons who successfully exit...

    • catalog.data.gov
    • datahub.austintexas.gov
    • +2more
    Updated May 25, 2025
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    data.austintexas.gov (2025). Strategic Measure_Number and percentage of persons who successfully exit from homelessness [Dataset]. https://catalog.data.gov/dataset/strategic-measure-number-and-percentage-of-persons-who-successfully-exit-from-homelessness
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    Dataset updated
    May 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    This dataset represents the number of persons who successfully exit from homelessness in a given fiscal year in the Austin/Travis County Continuum of Care (CoC). This measure is comprised of Metric 7b1 and 7b2 from the HUD System Performance Measures. Data Source: The data for this measure was reported to the City of Austin by the Ending Community Homelessness Coalition (ECHO). Each year, ECHO, as the homeless Continuum of Care Lead Agency (CoC Lead), aggregates and reports community wide data (including this measure) to the Department of Housing and Urban Development (HUD). This data is referred to as System Performance Measures as they are designed to examine how well a community is responding to homelessness at a system level. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/xtip-he7k

  4. a

    Survey results: Point-in-Time count

    • hub.arcgis.com
    • open.ottawa.ca
    • +2more
    Updated Apr 28, 2022
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    City of Ottawa (2022). Survey results: Point-in-Time count [Dataset]. https://hub.arcgis.com/datasets/4c598271584a464a87ecb62c3e4f34ca
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    Dataset updated
    Apr 28, 2022
    Dataset authored and provided by
    City of Ottawa
    License

    https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0

    Description

    City staff and community partners work together to survey people experiencing homelessness in Ottawa. So far, the City has led two counts:April 2018October 2021Oct 2024The survey is conducted to gather information about people experiencing homelessness. The goal of this work is to guide new approaches to address homelessness at a local level and help in the planning and delivery of services.Date created: 28 April 2022Update frequency: As needed.Accuracy: Convenience sampling was used to recruit survey respondents. This method of recruiting respondents to answer the survey does not rely on a random selection process. Instead, surveyors approach potential respondents if they are close by at the time the surveyor is delivering the questionnaire. Many factors could determine participation in the survey including:Number of community partners involved in the PiT countLocation of surveyors and their physical proximity to potential respondentsNumber of engagement eventsSeason the survey was conductedDifferences in results between PiT count years may be due to changes within the homeless population and shifts in methodology. For comparisons of emergency shelter use over time, visit the Temporary Emergency Accommodations Dashboard. An analysis of factors related to housing and homelessness during COVID-19 provides context for unique housing market conditions during the pandemic.Results shown in the Survey results: Point-in-Time count dashboard are presented by sector. The name and definition of each sector are below:All: All respondents who answered the surveySingle adult: Respondents aged 25 years or older and not accompanied by anyoneUnaccompanied youth: Respondents under 25 years old and not accompanied by anyoneFamily: Respondents accompanied by children under 18 years oldAttributes:Question: The question that was asked in the surveyTopic: The classification of the survey question by themSector: Refers to the population (total, family, unaccompanied youth, single adults)Period: Month the Point-in-Time count was conductedResponse: Response category of the survey questionNumeratorDenominatorPercentage Author: Housing ServicesAuthor email: pitcount_denombrementponctuel@ottawa.ca

  5. d

    Directory Of Homeless Population By Year

    • catalog.data.gov
    • nycopendata.socrata.com
    • +2more
    Updated Sep 2, 2023
    + more versions
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    data.cityofnewyork.us (2023). Directory Of Homeless Population By Year [Dataset]. https://catalog.data.gov/dataset/directory-of-homeless-population-by-year
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    Dataset updated
    Sep 2, 2023
    Dataset provided by
    data.cityofnewyork.us
    Description

    Table of homeless population by Year (for years 2009 through 2012)

  6. Estimated number of homeless people in the U.S. 2007-2023

    • statista.com
    Updated Sep 5, 2024
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    Statista (2024). Estimated number of homeless people in the U.S. 2007-2023 [Dataset]. https://www.statista.com/statistics/555795/estimated-number-of-homeless-people-in-the-us/
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    Dataset updated
    Sep 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, there were about 653,104 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 647,258. 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.

  7. 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
    

  8. H

    Annual point-in-time (PIT) estimates of homelessness reveal stark...

    • dataverse.harvard.edu
    Updated May 17, 2023
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    Pamela Baginski (2023). Annual point-in-time (PIT) estimates of homelessness reveal stark differences among San Francisco Bay Area counties [Dataset]. http://doi.org/10.7910/DVN/YQZCNK
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 17, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Pamela Baginski
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    San Francisco Bay Area
    Description

    INTRODUCTION: As California’s homeless population continues to grow at an alarming rate, large metropolitan regions like the San Francisco Bay Area face unique challenges in coordinating efforts to track and improve homelessness. As an interconnected region of nine counties with diverse community needs, identifying homeless population trends across San Francisco Bay Area counties can help direct efforts more effectively throughout the region, and inform initiatives to improve homelessness at the city, county, and metropolitan level. OBJECTIVES: The primary objective of this research is to compare the annual Point-in-Time (PIT) counts of homelessness across San Francisco Bay Area counties between the years 2018-2022. The secondary objective of this research is to compare the annual Point-in-Time (PIT) counts of homelessness among different age groups in each of the nine San Francisco Bay Area counties between the years 2018-2022. METHODS: Two datasets were used to conduct research. The first dataset (Dataset 1) contains Point-in-Time (PIT) homeless counts published by the U.S. Department of Housing and Urban Development. Dataset 1 was cleaned using Microsoft Excel and uploaded to Tableau Desktop Public Edition 2022.4.1 as a CSV file. The second dataset (Dataset 2) was published by Data SF and contains shapefiles of geographic boundaries of San Francisco Bay Area counties. Both datasets were joined in Tableau Desktop Public Edition 2022.4 and all data analysis was conducted using Tableau visualizations in the form of bar charts, highlight tables, and maps. RESULTS: Alameda, San Francisco, and Santa Clara counties consistently reported the highest annual count of people experiencing homelessness across all 5 years between 2018-2022. Alameda, Napa, and San Mateo counties showed the largest increase in homelessness between 2018 and 2022. Alameda County showed a significant increase in homeless individuals under the age of 18. CONCLUSIONS: Results from this research reveal both stark and fluctuating differences in homeless counts among San Francisco Bay Area Counties over time, suggesting that a regional approach that focuses on collaboration across counties and coordination of services could prove beneficial for improving homelessness throughout the region. Results suggest that more immediate efforts to improve homelessness should focus on the counties of Alameda, San Francisco, Santa Clara, and San Mateo. Changes in homelessness during the COVID-19 pandemic years of 2020-2022 point to an urgent need to support Contra Costa County.

  9. T

    HOMELESSNESS EXPENSE TRACKER

    • controllerdata.lacity.org
    application/rdfxml +5
    Updated Jun 23, 2025
    + more versions
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    (2025). HOMELESSNESS EXPENSE TRACKER [Dataset]. https://controllerdata.lacity.org/dataset/HOMELESSNESS-EXPENSE-TRACKER/98ve-cuf5
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    application/rdfxml, csv, tsv, xml, application/rssxml, jsonAvailable download formats
    Dataset updated
    Jun 23, 2025
    Description

    City expenditures related to Homelessness efforts in the City of LA starting with fiscal year 2024. Data populated by City departments who code and map expenses to homeless project categories. (Not all departments are included due to the way the department maps homeless expenditures)

  10. w

    Homeless count census tracts

    • data.wu.ac.at
    csv, json, xml
    Updated Aug 30, 2016
    + more versions
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    San Mateo County Human Services Agency (2016). Homeless count census tracts [Dataset]. https://data.wu.ac.at/schema/performance_smcgov_org/aGhkNy1lNjVx
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    json, xml, csvAvailable download formats
    Dataset updated
    Aug 30, 2016
    Dataset provided by
    San Mateo County Human Services Agency
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    The purpose of the San Mateo County Homeless Census and Survey is to gather and analyze information to help us understand who is homeless in our community, why they are homeless and what interventions they need to end their homelessness. This data forms the basis for effective planning to solve this complex and longstanding problem. The San Mateo County Human Services Agency’s Center on Homelessness the San Mateo County Continuum of Care Steering Committee were responsible for overseeing this data collection effort, with assistance from a broad group of community partners, including non-profit social service providers, city and town governments, and homeless and formerly homeless individuals. The Census and Survey was designed to meet two related sets of data needs. The first is the requirement of the U.S. Department of Housing and Urban Development (HUD) that communities applying for McKinney-Vento Homelessness Assistance funds (also known as Continuum of Care or “CoC” funds) must conduct a point-in-time count of homeless people a minimum of every two years. These counts are required to take place in the last ten days of January.

  11. l

    Persons Experiencing Homelessness

    • geohub.lacity.org
    • data.lacounty.gov
    • +2more
    Updated Dec 19, 2023
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    County of Los Angeles (2023). Persons Experiencing Homelessness [Dataset]. https://geohub.lacity.org/datasets/lacounty::persons-experiencing-homelessness
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    Dataset updated
    Dec 19, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    According to U.S. Department of Housing and Urban Development's definition, homelessness includes individuals and families who lack a fixed, regular, and adequate nighttime residence. A homeless count provides a "snapshot in time" to quantify the size of the homeless population at a specific point during the year. Regardless of how successful outreach efforts are, an undercount of people experiencing homelessness is possible. Counts includes persons experiencing unsheltered and sheltered homelessness. Greater Los Angeles Homeless Count occurred in the nights of February 22, 23 and 24, 2022. Glendale's count occurred in the morning and evening of February 25, 2022. Long Beach's count occurred in the early morning of February 24, 2022. Pasadena's count occurred in the evening of February 22, 2022 and morning of February 23, 2022. Data not available for Los Angeles City neighborhoods and unincorporated Los Angeles County; LAHSA does not recommend aggregating census tract-level data to calculate numbers for other geographic levels.Housing affordability is a major concern for many Los Angeles County residents. Housing burden can increase the risk for homelessness. Individuals experiencing homelessness experience disproportionately higher rates of certain health conditions, such as tuberculosis, HIV infection, alcohol and drug abuse, and mental illness. Barriers to accessing care and limited access to resources contribute greatly to these observed disparities.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

  12. Number of homeless people in the city of Los Angeles by sheltered status...

    • statista.com
    Updated Dec 9, 2024
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    Statista (2024). Number of homeless people in the city of Los Angeles by sheltered status 2023 [Dataset]. https://www.statista.com/statistics/1007716/number-homeless-people-city-los-angeles-sheltered-status/
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    Dataset updated
    Dec 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2023
    Area covered
    Los Angeles, United States
    Description

    As of 2023, there were about 32,680 unsheltered homeless people living in Los Angeles, compared to 13,580 sheltered homeless people.

  13. O

    Strategic Measure_Number of returns to homelessness

    • data.austintexas.gov
    • datasets.ai
    • +2more
    application/rdfxml +5
    Updated Apr 22, 2022
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    City of Austin, Texas - data.austintexas.gov (2022). Strategic Measure_Number of returns to homelessness [Dataset]. https://data.austintexas.gov/Health-and-Community-Services/Strategic-Measure_Number-of-returns-to-homelessnes/jy3f-9rpf
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    application/rdfxml, tsv, csv, json, application/rssxml, xmlAvailable download formats
    Dataset updated
    Apr 22, 2022
    Dataset authored and provided by
    City of Austin, Texas - data.austintexas.gov
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This dataset provides information on individuals who exit homelessness to permanent housing destinations and then return to homelessness within 2 years from their exit in the Austin/Travis County Continuum of Care (CoC) in a given fiscal year.

    Data Source: The data for this measure was reported to the City of Austin by the Ending Community Homelessness Coalition (ECHO). Each year, ECHO, as the homeless Continuum of Care Lead Agency (CoC Lead), aggregates and reports community wide data (including this measure) to the Department of Housing and Urban Development (HUD). This data is referred to as System Performance Measures as they are designed to examine how well a community is responding to homelessness at a system level.

    View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/cutp-y8m4

  14. d

    Strategic Measure_Number of persons experiencing homelessness - Point in...

    • catalog.data.gov
    • data.austintexas.gov
    • +1more
    Updated May 25, 2025
    + more versions
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    data.austintexas.gov (2025). Strategic Measure_Number of persons experiencing homelessness - Point in Time Count [Dataset]. https://catalog.data.gov/dataset/strategic-measure-number-of-persons-experiencing-homelessness-point-in-time-count
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    Dataset updated
    May 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    This dataset provides information on individuals experiencing sheltered or unsheltered homelessness in the Austin/Travis County Continuum of Care (CoC) on a single night in January when the Point in Time (PIT) Count occurs. "Sheltered" homelessness refers to individuals residing in emergency shelter, safe haven, or transitional housing project types. Unsheltered homelessness refers to individuals with a primary nighttime residence that is a public or private place not designed for or ordinarily used as a regular sleeping accommodation for human beings, including a car, park, abandoned building, bus or train station, airport, or camping ground on the night designated for the count. This measure overlaps, but is different from, the annual count of sheltered homelessness in HMIS (SD23 Measure EOA.E.1b). Data Source: The data for this measure was reported to the City of Austin by the Ending Community Homelessness Coalition (ECHO). Each year, ECHO, as the homeless Continuum of Care Lead Agency (CoC Lead), aggregates and reports community wide data (including this measure) to the Department of Housing and Urban Development (HUD). This data is referred to as System Performance Measures as they are designed to examine how well a community is responding to homelessness at a system level. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/hjiv-t2tm Last Updated December 2020 with data for 2020 PIT Count.

  15. c

    Homelessness (Survey of Homeless)

    • datacatalogue.cessda.eu
    • search.gesis.org
    • +3more
    Updated Mar 14, 2023
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    Sack, Fritz; Höhmann, Peter (2023). Homelessness (Survey of Homeless) [Dataset]. http://doi.org/10.4232/1.2579
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    Dataset updated
    Mar 14, 2023
    Dataset provided by
    Forschungsinstitut für Soziologie, Universität zu Köln
    Authors
    Sack, Fritz; Höhmann, Peter
    Time period covered
    Oct 1969 - Feb 1970
    Measurement technique
    Oral survey with standardized questionnaire
    Description

    The social situation of the homeless in a Cologne suburb. Topics: Most important problems in the settlement; problems in the relationship between the settlement and surroundings; plans to leave; length of residence in the settlement and year of first utilization of a city shelter; reason for admission into a city shelter; type of quarters on first admission and before admission; frequency of moving into such accomodations and settlements; perceived deterioration from the move; number of rooms; possession of durable economic goods; defects in residence; number of children and schools attended or kindergarten; attitude to establishment of a special school in the part of town; perceived discrimination of one´s children in school; regular pocket-money for the children; place of leisure time of one´s children; contacts of one´s children outside of the settlement; person raising the children; perceived discrimination of the homeless; exercise of an honorary activity in the settlement; attitude to a self-help committee in the settlement; interest in participation in such a committee; assumed effectiveness of a community of interests of the homeless; most important tasks of such a community of interests; most important institutions as contact to improve the situation of the homeless; location of place of work; frequency of change of job; change of occupation; satisfaction with place of work; shopping place; possession of savings; manager of family income; decision-maker for expenditures; debts; eating main meal together; leisure activities in the settlement; contact persons in leisure time; leisure contacts outside the settlement; neighborhood contacts in the settlement; contacts with non-homeless; establishing these contacts on leisure time or through work; identification as Cologne resident or resident of the part of town; desire to move to another part of town; favorite part of town in Cologne; intensity of contact with the population in the part of town; contacts with residents of another settlement; participation in meetings of the Poll Buergerverein; assumed representation of interests of the homeless through this organization; most influencial personalities in the part of town; persons making a particular effort for the homeless; most important differences between the residents of one´s own settlement and another settlement in the part of town; knowledge of press reports and television reports about the homeless and judgement on validity; most important reasons for homelessness; most important measures to prevent homelessness; perceived differences between the homeless; filing a complaint against the city to obtain better housing; experiences with contacts with authorities; satisfaction with the manager of the settlement; most important task of a manager; anomy (scale); comparison of personal housing situation with that of parents; social origins; social mobility compared with father and father-in-law; contacts with relatives; judgement of relatives about living in this settlement; relatives likewise living in emergency shelters; personal condition of health; number of sick family members and type of illnesses; recommendations on dealing with the homeless; society or the individual as responsible for one´s own homelessness; desire for integration in a normal residential area; personal extent of commiting crimes and conviction; type of offenses; perceived improvement in living conditions in the emergency shelter; comparison of the situation between the settlement and a temporary shelter; place of birth; length of residence in Cologne; re-married; religiousness; club memberships; extent of club activity; party preference; assumed effectiveness of this survey on the situation of the homeless. Interviewer rating: name sign on door; description of residential furnishings regarding family pictures, other pictures, knick-knacks, religious figures and possession of books; condition of windows, wallpaper and furniture; length of interview; number of persons present during interview; carrying out house work by the person interviewed during the interview; conduct of other persons present during the conversation; willingness of respondent to cooperate.

  16. h

    Scale of Homelessness

    • open.hamilton.ca
    Updated Sep 8, 2023
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    City of Hamilton (2023). Scale of Homelessness [Dataset]. https://open.hamilton.ca/datasets/scale-of-homelessness/about
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    Dataset updated
    Sep 8, 2023
    Dataset authored and provided by
    City of Hamilton
    License

    https://www.hamilton.ca/city-initiatives/strategies-actions/open-data-licence-terms-and-conditionshttps://www.hamilton.ca/city-initiatives/strategies-actions/open-data-licence-terms-and-conditions

    Description

    The number individuals experiencing homelessness in Hamilton and their length of homelessness. Individuals depicted are shown as being homeless for six months or less, or for more than months. Includes those who have had a shelter stay in the past 90 days. This gives a more fulsome picture of individuals experiencing homelessness who may access shelters in one month and not the next.Data is collected by homeless-serving shelters through the Homeless Individuals and Families Information System (HIFIS).

  17. Rate of homeless individuals by metro area in the U.S. 2017

    • statista.com
    Updated Aug 12, 2024
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    Statista (2024). Rate of homeless individuals by metro area in the U.S. 2017 [Dataset]. https://www.statista.com/statistics/1007757/rate-homeless-individuals-metro-area-us/
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    Dataset updated
    Aug 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2017
    Area covered
    United States
    Description

    This statistic depicts the rate of homeless individuals in the United States in 2017, by metropolitan area. In 2017, the rate of homelessness per 10,000 individuals was highest in New York City, at 88.7.

  18. d

    Number of People Experiencing Homelessness

    • data.ore.dc.gov
    Updated Aug 20, 2024
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    City of Washington, DC (2024). Number of People Experiencing Homelessness [Dataset]. https://data.ore.dc.gov/datasets/number-of-people-experiencing-homelessness
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    Dataset updated
    Aug 20, 2024
    Dataset authored and provided by
    City of Washington, DC
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The most recent rate of homelessness is calculated using ACS population estimates from the previous year, unless otherwise noted.

    Data Source: HUD's Annual Homeless Assessment Report (AHAR) Point-in-Time (PIT) Estimates by State and American Community Survey (ACS) 1-Year Estimates

    Why this MattersSafe, adequate, and stable housing is a human right and essential for the health and well-being of individuals, families, and communities.People who experience homelessness also struggle to maintain access to healthcare, employment, education, healthy relationships, and other basic necessities in life, according to the DC Interagency Council on Homelessness Strategic Plan.BIPOC populations are disproportionately affected by homelessness due to housing discrimination, mass incarceration, and other policies that have limited socioeconomic opportunities for Black, Latino, and other people of color.

    The District's Response Strategic investments in proven strategies for driving down homelessness, including the Career Mobility Action Plan (Career MAP) program, operation of non-congregate housing, and expansion of the District’s shelter capacity.Homelessness prevention programs for at-risk individuals and families, such as emergency rental assistance, targeted affordable housing, and permanent supporting housing.Programs and services to enhance resident’s economic and employment security and ensure access to affordable housing.

  19. c

    Top 15 States by Estimated Number of Homeless People in 2024

    • consumershield.com
    csv
    Updated Jun 9, 2025
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    ConsumerShield Research Team (2025). Top 15 States by Estimated Number of Homeless People in 2024 [Dataset]. https://www.consumershield.com/articles/how-many-homeless-us
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    csvAvailable download formats
    Dataset updated
    Jun 9, 2025
    Dataset authored and provided by
    ConsumerShield Research Team
    License

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

    Area covered
    United States
    Description

    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.

  20. d

    Strategic Measure_Number of persons who have not been served by the...

    • catalog.data.gov
    • datahub.austintexas.gov
    • +1more
    Updated May 25, 2025
    + more versions
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    data.austintexas.gov (2025). Strategic Measure_Number of persons who have not been served by the community’s homeless system in the two years prior to entry into the homeless system [Dataset]. https://catalog.data.gov/dataset/strategic-measure-number-of-persons-who-have-not-been-served-by-the-communitys-homeless-sy
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    Dataset updated
    May 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    This dataset represents the number of persons who are experiencing homelessness for the first time in a fiscal year (October 1 - September 30) in the Austin/Travis County Continuum of Care (CoC). Data Source: The data for this measure was reported to the City of Austin by the Ending Community Homelessness Coalition (ECHO). Each year, ECHO, as the homeless Continuum of Care Lead Agency (CoC Lead), aggregates and reports community wide data (including this measure) to the Department of Housing and Urban Development (HUD). This data is referred to as System Performance Measures as they are designed to examine how well a community is responding to homelessness at a system level. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/wk3t-h5qe

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Statista, 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 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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