33 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/
    Explore at:
    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. 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
    Explore at:
    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.

  3. Point-in-Time Homelessness Count

    • kaggle.com
    zip
    Updated May 6, 2020
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    Google BigQuery (2020). Point-in-Time Homelessness Count [Dataset]. https://www.kaggle.com/datasets/bigquery/sdoh-hud-pit-homelessness
    Explore at:
    zip(0 bytes)Available download formats
    Dataset updated
    May 6, 2020
    Dataset provided by
    BigQueryhttps://cloud.google.com/bigquery
    Authors
    Google BigQuery
    Description

    Context

    This database contains the data reported in the Annual Homeless Assessment Report to Congress (AHAR). It represents a point-In-time count (PIT) of homeless individuals, as well as a housing inventory count (HIC) conducted annually.

    The data represent the most comprehensive national-level assessment of homelessness in America, including PIT and HIC estimates of homelessness, as well as estimates of chronically homeless persons, homeless veterans, and homeless children and youth.

    These data can be trended over time and correlated with other metrics of housing availability and affordability, in order to better understand the particular type of housing resources that may be needed from a social determinants of health perspective.

    HUD captures these data annually through the Continuum of Care (CoC) program. CoC-level reporting data have been crosswalked to county levels for purposes of analysis of this dataset.

    Querying BigQuery tables

    You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.sdoh_hud_pit_homelessness

    Sample Query

    What has been the change in the number of homeless veterans in the state of New York’s CoC Regions since 2012? Determine how the patterns of homeless veterans have changes across the state of New York

    homeless_2018 AS ( SELECT Homeless_Veterans AS Vet18, CoC_Name
    FROM bigquery-public-data.sdoh_hud_pit_homelessness.hud_pit_by_coc WHERE SUBSTR(CoC_Number,0,2) = "NY" AND Count_Year = 2018 ),

    veterans_change AS ( SELECT homeless_2012.COC_Name, Vet12, Vet18, Vet18 - Vet12 AS VetChange FROM homeless_2018 JOIN homeless_2012 ON homeless_2018.CoC_Name = homeless_2012.CoC_Name )

    SELECT * FROM veterans_change

  4. C

    People Receiving Homeless Response Services by Age, Race, Gender, Veteran...

    • data.ca.gov
    csv, docx
    Updated May 14, 2025
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    California Interagency Council on Homelessness (2025). People Receiving Homeless Response Services by Age, Race, Gender, Veteran Status, and Disability Status [Dataset]. https://data.ca.gov/dataset/homelessness-demographics
    Explore at:
    csv(242585), csv(6023), csv(6362), csv(69480), csv(182741), docx(26383), csv(140396)Available download formats
    Dataset updated
    May 14, 2025
    Dataset authored and provided by
    California Interagency Council on Homelessness
    License

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

    Description

    Yearly statewide and by-Continuum of Care total counts of individuals receiving homeless response services by age group, race, gender, veteran status, and disability status.

    This data comes from the Homelessness Data Integration System (HDIS), a statewide data warehouse which compiles and processes data from all 44 California Continuums of Care (CoC)—regional homelessness service coordination and planning bodies. Each CoC collects data about the people it serves through its programs, such as homelessness prevention services, street outreach services, permanent housing interventions and a range of other strategies aligned with California’s Housing First objectives.

    The dataset uploaded reflects the 2024 HUD Data Standard Changes. Previously, Race and Ethnicity are separate files but are now combined.

    Information updated as of 2/06/2025.

  5. A

    Strategic Measure_Number of persons experiencing homelessness - Annual...

    • data.amerigeoss.org
    • data.austintexas.gov
    • +2more
    csv, json, rdf, xml
    Updated Apr 26, 2022
    + more versions
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    United States (2022). Strategic Measure_Number of persons experiencing homelessness - Annual Sheltered HMIS Count [Dataset]. https://data.amerigeoss.org/dataset/strategic-measure-number-of-persons-experiencing-homelessness-annual-sheltered-hmis-count
    Explore at:
    rdf, csv, xml, jsonAvailable download formats
    Dataset updated
    Apr 26, 2022
    Dataset provided by
    United States
    Description

    This dataset provides information on individuals experiencing sheltered homelessness in the Austin/Travis County Continuum of Care (CoC) in a given fiscal year. "Sheltered" homelessness refers to individuals residing in emergency shelter, safe haven, or transitional housing project types. This measure overlaps, but is different from, the Point in Time (PIT) Count (SD23 Measure EOA.E.1a), which is a snapshot of both sheltered and unsheltered homelessness on one night in January.

    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/2ejn-hrh2

  6. p

    Homeless Shelters in United States - 2,761 Verified Listings Database

    • poidata.io
    csv, excel, json
    Updated Jun 14, 2025
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    Poidata.io (2025). Homeless Shelters in United States - 2,761 Verified Listings Database [Dataset]. https://www.poidata.io/report/homeless-shelter/united-states
    Explore at:
    csv, excel, jsonAvailable download formats
    Dataset updated
    Jun 14, 2025
    Dataset provided by
    Poidata.io
    Area covered
    United States
    Description

    Comprehensive dataset of 2,761 Homeless shelters in United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

  7. 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
    Explore at:
    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....

  8. D

    ARCHIVED: COVID-19 Cases by Population Characteristics Over Time

    • data.sfgov.org
    • healthdata.gov
    • +2more
    application/rdfxml +5
    Updated Sep 11, 2023
    + more versions
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    (2023). ARCHIVED: COVID-19 Cases by Population Characteristics Over Time [Dataset]. https://data.sfgov.org/Health-and-Social-Services/ARCHIVED-COVID-19-Cases-by-Population-Characterist/j7i3-u9ke
    Explore at:
    xml, csv, json, application/rdfxml, tsv, application/rssxmlAvailable download formats
    Dataset updated
    Sep 11, 2023
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    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”.

    B. HOW THE DATASET IS CREATED Data on the population characteristics of COVID-19 cases are from:  * Case interviews  * Laboratories  * Medical providers    These multiple streams of data are merged, deduplicated, and undergo data verification processes.  

    Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases. * The population estimates for the "Other" or “Multi-racial” groups should be considered with caution. The Census definition is likely not exactly aligned with how the City collects this data. For that reason, we do not recommend calculating population rates for these groups.

    Gender * The City collects information on gender identity using these guidelines.

    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 cases 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 the California Department of Public Health, Virtual Assistant information gathering beginning December 2021. The Virtual Assistant is only sent to adults who are 18+ years old. https://www.sfdph.org/dph/files/PoliciesProcedures/COM9_SexualOrientationGuidelines.pdf">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 has been archived and will no longer update as of 9/11/2023.

    D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS).

    This dataset includes many 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 cases on each date.

    New cases are the count of cases within that characteristic group where the positive tests were collected on that specific specimen collection date. Cumulative cases are the running total of all San Francisco cases in that characteristic group up to the specimen collection date listed.

    This data may not be immediately available for recently reported cases. Data updates as more information becomes available.

    To explore data on the total number of cases, use the ARCHIVED: COVID-19 Cases Over Time dataset.

    E. CHANGE LOG

    • 9/11/2023 - data on COVID-19 cases by population characteristics over time are no longer being updated. The date on which each population characteristic type was archived can be found in the field “data_loaded_at”.
    • 6/6/2023 - data on cases by transmission type have been removed. See section ARCHIVED DATA for more detail.
    • 5/16/2023 - data on cases by sexual orientation, comorbidities, homelessness, and single room occupancy have been removed. See section ARCHIVED DATA for more detail.
    • 4/6/2023 - the State implemented system updates to improve the integrity of historical data.
    • 2/21/2023 - system updates to improve reliability and accuracy of cases data were implemented.
    • 1/31/2023 - updated “population_estimate” column to reflect the 2020 Census Bureau American Community Survey (ACS) San Francisco Population estimates.
    • 1/5/2023 - data on SNF cases removed. See section ARCHIVED DATA for more detail.
    • 3/23/2022 - ‘Native American’ changed to ‘American Indian or Alaska Native’ to align with the census.
    • 1/22/2022 - system updates to improve timeliness and accuracy of cases and deaths data were implemented.
    • 7/15/2022 - reinfections added to cases dataset. See section SUMMARY for more information on how reinfections are identified.

  9. Homelessness Report January 2025 - Dataset - data.gov.ie

    • data.gov.ie
    Updated Jan 20, 2025
    + more versions
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    data.gov.ie (2025). Homelessness Report January 2025 - Dataset - data.gov.ie [Dataset]. https://data.gov.ie/dataset/homelessness-report-january-2025
    Explore at:
    Dataset updated
    Jan 20, 2025
    Dataset provided by
    data.gov.ie
    License

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

    Description

    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.

  10. NYS Runaway And Homeless Youth Programs

    • kaggle.com
    Updated Jan 1, 2021
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    State of New York (2021). NYS Runaway And Homeless Youth Programs [Dataset]. https://www.kaggle.com/datasets/new-york-state/nys-runaway-and-homeless-youth-programs/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 1, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    State of New York
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    New York
    Description

    Content

    Included in this data set are data elements that will help the public identify agencies that are certified to operate programs for runaway and homeless youth. These programs are available to assist runaway and homeless youth in emergency situation and provide independent living skills for youth in transition. Data elements include the agency name, agency business address, phone number, website and type of program offered.

    Context

    This is a dataset hosted by the State of New York. The state has an open data platform found here and they update their information according the amount of data that is brought in. Explore New York State using Kaggle and all of the data sources available through the State of New York organization page!

    • Update Frequency: This dataset is updated annually.

    Acknowledgements

    This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

    Cover photo by Zac Ong on Unsplash
    Unsplash Images are distributed under a unique Unsplash License.

  11. 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
    Explore at:
    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
    

  12. Local Employment Dynamics (LED) for ESG Areas

    • data.lojic.org
    • hub.arcgis.com
    • +1more
    Updated Jul 31, 2023
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    Department of Housing and Urban Development (2023). Local Employment Dynamics (LED) for ESG Areas [Dataset]. https://data.lojic.org/datasets/13f2dd85f2574e2abfd74d0c976cf031
    Explore at:
    Dataset updated
    Jul 31, 2023
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    Department of Housing and Urban Development
    Area covered
    Description

    The Local Employment Dynamics (LED) Partnership is a voluntary federal-state enterprise created for the purpose of merging employee, and employer data to provide a set of enhanced labor market statistics known collectively as Quarterly Workforce Indicators (QWI). The QWI are a set of economic indicators including employment, job creation, earnings, and other measures of employment flows. For the purposes of this dataset, LED data for 2018 is aggregated to Census Summary Level 070 (State + County + County Subdivision + Place/Remainder), and joined with the Emergency Solutions Grantee (ESG) areas spatial dataset for FY2018. The Emergency Solutions Grants (ESG), formally the Emergency Shelter Grants, program is designed to identify sheltered and unsheltered homeless persons, as well as those at risk of homelessness, and provide the services necessary to help those persons quickly regain stability in permanent housing after experiencing a housing crisis and/or homelessness. The ESG is a non-competitive formula grant awarded to recipients which are state governments, large cities, urban counties, and U.S. territories. Recipients make these funds available to eligible sub-recipients, which can be either local government agencies or private nonprofit organizations. The recipient agencies and organizations, which actually run the homeless assistance projects, apply for ESG funds to the governmental grantee, and not directly to HUD. Please note that this version of the data does not include Community Planning and Development (CPD) entitlement grantees. LED data for CPD entitlement areas can be obtained from the LED for CDBG Grantee Areas feature service. To learn more about the Local Employment Dynamics (LED) Partnership visit: https://lehd.ces.census.gov/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_LED for ESG Grantee Areas

    Date of Coverage: ESG-2021/LED-2018

  13. Hospital Encounters for Homeless Patients

    • data.chhs.ca.gov
    • data.ca.gov
    • +2more
    csv, xlsx, zip
    Updated Feb 24, 2025
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    Department of Health Care Access and Information (2025). Hospital Encounters for Homeless Patients [Dataset]. https://data.chhs.ca.gov/dataset/hospital-encounters-for-homeless-patients
    Explore at:
    csv(902), xlsx(2449806), csv(1900), csv(2321), zip, csv(1897), csv(4390123)Available download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Department of Health Care Access and Information
    Description

    This dataset contains counts of inpatient hospitalizations and emergency department visits for persons experiencing homelessness.

  14. A

    ‘COVID-19 Deaths by Population Characteristics Over Time’ analyzed by...

    • analyst-2.ai
    + more versions
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com), ‘COVID-19 Deaths by Population Characteristics Over Time’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-covid-19-deaths-by-population-characteristics-over-time-2fe1/3045abf4/?iid=004-667&v=presentation
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    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘COVID-19 Deaths by Population Characteristics Over Time’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/60f5842f-a359-4b03-ad21-1bcfc3bf7fe6 on 13 February 2022.

    --- Dataset description provided by original source is as follows ---

    Note: On January 22, 2022, system updates to improve the timeliness and accuracy of San Francisco COVID-19 cases and deaths data were implemented. You might see some fluctuations in historic data as a result of this change.

    A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics and by date. Deaths are included on the date the individual died.

    Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups.

    Data is lagged by five days, meaning the most date included is 5 days prior to today. All data update daily as more information becomes available.

    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. It takes time to process this data. Because of this, data is lagged by 5 days and death totals for previous days may increase or decrease. More recent data is less reliable.

    Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

    Data notes on each population characteristic type is listed below.

    Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases.

    Sexual orientation * Sexual orientation data is collected from individuals who are 18 years old or older. These individuals can choose whether to provide this information during case interviews. Learn more about our data collection guidelines. * The City began asking for this information on April 28, 2020. Gender * The City collects information on gender identity using these guidelines.

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

    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.

    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.

    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. * Facilities are mandated to report COVID-19 cases or deaths among their residents. The City follows up with these facilities to confirm.
    * There may be differences between the City’s SNF data and the California Department of Public Health (CDPH) dashboard. The difference may be because the City and the State use dif

    --- Original source retains full ownership of the source dataset ---

  15. A

    Washington DC Metropolitan Area Drug Study Homeless and Transient Population...

    • data.amerigeoss.org
    • healthdata.gov
    • +4more
    html
    Updated Jul 30, 2019
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    United States (2019). Washington DC Metropolitan Area Drug Study Homeless and Transient Population (DC-MADST-1991) [Dataset]. https://data.amerigeoss.org/tr/dataset/washington-dc-metropolitan-area-drug-study-homeless-and-transient-population-dc-madst-1991
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    htmlAvailable download formats
    Dataset updated
    Jul 30, 2019
    Dataset provided by
    United States
    Area covered
    Washington, Washington Metropolitan Area
    Description

    The DC Metropolitan Area Drug Study (DCMADS) was
    conducted in 1991, and included special analyses of homeless and
    transient populations and of women delivering live births in the DC
    hospitals. DC
    MADS was undertaken to assess the full extent of the
    drug problem in one metropolitan area. The study was comprised of 16
    separate studies that focused on different sub-groups, many of which
    are typically not included or are underrepresented in household
    surveys. The Homeless and Transient Population
    study examines the prevalence of illicit drug, alcohol, and tobacco
    use among members of the homeless and transient population aged 12 and
    older in the Washington, DC, Metropolitan Statistical Area (DC
    MSA). The sample frame included respondents from shelters, soup
    kitchens and food banks, major cluster encampments, and literally
    homeless people. Data from the questionnaires include history of
    homelessness, living arrangements and population movement, tobacco,
    drug, and alcohol use, consequences of use, treatment history, illegal
    behavior and arrest, emergency room treatment and hospital stays,
    physical and mental health, pregnancy, insurance, employment and
    finances, and demographics. Drug specific data include age at first
    use, route of administration, needle use, withdrawal symptoms,
    polysubstance use, and perceived risk.This study has 1 Data Set.

  16. a

    Data from: Homeless Shelters

    • hub.arcgis.com
    Updated Apr 17, 2020
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    Ohio Geographically Referenced Information Program (2020). Homeless Shelters [Dataset]. https://hub.arcgis.com/datasets/30ed5046edb04f63b279419d50599e35
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    Dataset updated
    Apr 17, 2020
    Dataset authored and provided by
    Ohio Geographically Referenced Information Program
    Area covered
    Description

    Homeless and battered women's shelters compiled from Reference USA. Reference USA is an internet-based reference service from the Government Division of InfoGroup. This site was designed as a reference to government agencies. ReferenceUSAGov database contains more than 57 million US businesses, 320 million residents, and 855,000 healthcare providers. InfoGroup compiles information from public sources, including yellow pages and business white pages telephone directories, annual reports, federal government data, leading business magazines trade newsletters, major newspapers, industry and specialty directories, and postal service information. Over 350 database specialists make phone calls to verify information on business and healthcare providers in the database, placing in excess of 24 million phone calls annually.

  17. 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
    Explore at:
    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....

  18. Local Employment Dynamics (LED) for COC Grantee Areas

    • hudgis-hud.opendata.arcgis.com
    • data.lojic.org
    • +1more
    Updated Jul 31, 2023
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    Department of Housing and Urban Development (2023). Local Employment Dynamics (LED) for COC Grantee Areas [Dataset]. https://hudgis-hud.opendata.arcgis.com/maps/HUD::local-employment-dynamics-led-for-coc-grantee-areas
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    Dataset updated
    Jul 31, 2023
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    Department of Housing and Urban Development
    Area covered
    Description

    The Local Employment Dynamics (LED) Partnership is a voluntary federal-state enterprise created for the purpose of merging employee, and employer data to provide a set of enhanced labor market statistics known collectively as Quarterly Workforce Indicators (QWI). The QWI are a set of economic indicators including employment, job creation, earnings, and other measures of employment flows. For the purposes of this dataset, LED data for 2018 is aggregated to Census Summary Level 070 (State + County + County Subdivision + Place/Remainder), and joined with the Continuum of Care Program grantee areas spatial dataset for FY2017. 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). Please note that this version of the data does not include Community Planning and Development (CPD) entitlement grantees. LED data for CPD entitlement areas can be obtained from the LED for CDBG Grantee Areas feature service. To learn more about the Local Employment Dynamics (LED) Partnership visit: https://lehd.ces.census.gov/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_LED for CoC Grantee Areas

    Date of Coverage: CoC-2021/LED-2018

  19. Data from: Effectiveness of Prisoner Reentry Services as Crime Control for...

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Mar 12, 2025
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    National Institute of Justice (2025). Effectiveness of Prisoner Reentry Services as Crime Control for Inmates Released in New York, 2000-2005 [Dataset]. https://catalog.data.gov/dataset/effectiveness-of-prisoner-reentry-services-as-crime-control-for-inmates-released-in-n-2000-98dc4
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    New York
    Description

    The Fortune Society, a private not-for-profit organization located in New York City, provides a variety of services that are intended to support former prisoners in becoming stable and productive members of society. The purpose of this evaluation was to explore the extent to which receiving supportive services at the Fortune Society improved clients' prospects for law abiding behavior. More specifically, this study examined the extent to which receipt of these services reduced recidivism and homelessness following release. The research team adopted a quasi-experimental design that compared recidivism outcomes for persons enrolled at Fortune (clients) to persons released from New York State prisons and returning to New York City and, separately, inmates released from the New York City jails, none of whom went to Fortune (non-clients). All -- clients and non-clients alike -- were released after January 1, 2000, and before November 3, 2005 (for state prisoners), and March 3, 2005 (for city jail prisoners). Information about all prisoners released during these time frames was obtained from the New York State Department of Correctional Services for state prisoners and from the New York City Department of Correction for city prisoners. The research team also obtained records from the Fortune Society for its clients and arrest and conviction information for all released prisoners from the New York State Division of Criminal Justice Services' criminal history repository. These records were matched and merged, producing a 72,408 case dataset on 57,349 released state prisoners (Part 1) and a 68,614 case dataset on 64,049 city jail prisoners (Part 2). The research team obtained data from the Fortune Society for 15,685 persons formally registered as clients between 1989 and 2006 (Part 3) and data on 416,943 activities provided to clients at the Fortune Society between September 1999 and March 2006 (Part 4). Additionally, the research team obtained 97,665 records from the New York City Department of Homeless Services of all persons who sought shelter or other homeless services during the period from January 2000 to July 2006 (Part 5). Part 6 contains 96,009 cases and catalogs matches between a New York State criminal record identifier and a Fortune Society client identifier. The New York State Prisons Releases Data (Part 1) contain a total of 124 variables on released prison inmate characteristics including demographic information, criminal history variables, indicator variables, geographic variables, and service variables. The New York City Jails Releases Data (Part 2) contain a total of 92 variables on released jail inmate characteristics including demographic information, criminal history variables, indicator variables, and geographic variables. The Fortune Society Client Data (Part 3) contain 44 variables including demographic, criminal history, needs/issues, and other variables. The Fortune Society Client Activity Data (Part 4) contain seven variables including two identifiers, end date, Fortune service unit, duration in hours, activity type, and activity. The Homelessness Events Data (Part 5) contain four variables including two identifiers, change in homeless status, and date of change. The New York State Criminal Record/Fortune Society Client Match Data (Part 6) contain four variables including three identifiers and a variable that indicates the type of match between a New York State criminal record identifier and a Fortune Society client identifier.

  20. a

    Emergency Solutions Grantee (ESG) Areas

    • hub.arcgis.com
    • data.lojic.org
    • +1more
    Updated Jul 31, 2023
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    Department of Housing and Urban Development (2023). Emergency Solutions Grantee (ESG) Areas [Dataset]. https://hub.arcgis.com/datasets/HUD::emergency-solutions-grantee-esg-areas
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    Dataset updated
    Jul 31, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    The Emergency Solutions Grants (ESG), formally the Emergency Shelter Grants, program is designed to identify sheltered and unsheltered homeless persons, as well as those at risk of homelessness, and provide the services necessary to help those persons quickly regain stability in permanent housing after experiencing a housing crisis and/or homelessness. The ESG is a non-competitive formula grant awarded to recipients which are state governments, large cities, urban counties, and U.S. territories. Recipients make these funds available to eligible sub-recipients, which can be either local government agencies or private nonprofit organizations. The recipient agencies and organizations, which actually run the homeless assistance projects, apply for ESG funds to the governmental grantee, and not directly to HUD. To learn more about the Emergency Solutions Grants (ESG) Program visit: https://www.hudexchange.info/programs/esg/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_ESG Grantee Areas

    Date of Coverage: 2018

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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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