20 datasets found
  1. Estimated number of homeless people in the U.S. 2007-2023

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). 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/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, there were about ******* homeless people estimated to be living in the United States, the highest number of homeless people recorded within the provided time period. In comparison, the second-highest number of homeless people living in the U.S. within this time period was in 2007, at *******. How is homelessness calculated? Calculating homelessness is complicated for several different reasons. For one, it is challenging to determine how many people are homeless as there is no direct definition for homelessness. Additionally, it is difficult to try and find every single homeless person that exists. Sometimes they cannot be reached, leaving people unaccounted for. In the United States, the Department of Housing and Urban Development calculates the homeless population by counting the number of people on the streets and the number of people in homeless shelters on one night each year. According to this count, Los Angeles City and New York City are the cities with the most homeless people in the United States. Homelessness in the United States Between 2022 and 2023, New Hampshire saw the highest increase in the number of homeless people. However, California was the state with the highest number of homeless people, followed by New York and Florida. The vast amount of homelessness in California is a result of multiple factors, one of them being the extreme high cost of living, as well as opposition to mandatory mental health counseling and drug addiction. However, the District of Columbia had the highest estimated rate of homelessness per 10,000 people in 2023. This was followed by New York, Vermont, and Oregon.

  2. Rate of homelessness in the U.S. 2023, by state

    • statista.com
    Updated Feb 15, 2024
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    Statista (2024). Rate of homelessness in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/727847/homelessness-rate-in-the-us-by-state/
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    Dataset updated
    Feb 15, 2024
    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.

  3. 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.

  4. c

    Number of Homeless People in U.S. (2007-2024)

    • consumershield.com
    csv
    Updated Jun 9, 2025
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    ConsumerShield Research Team (2025). Number of Homeless People in U.S. (2007-2024) [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 estimated number of homeless people in the United States from 2007 to 2024. The x-axis represents the years, ranging from 2007 to 2023, while the y-axis indicates the number of homeless individuals. The estimated homeless population varies over this period, ranging from a low of 57,645 in 2014 to a high of 771,000 in 2024. From 2007 to 2013, there is a general decline in numbers from 647,258 to 590,364. In 2014, the number drops significantly to 57,645, followed by an increase to 564,708 in 2015. The data shows fluctuations in subsequent years, with another notable low of 55,283 in 2018. From 2019 onwards, the estimated number of homeless people generally increases, reaching its peak in 2024. This data highlights fluctuations in homelessness estimates over the years, with a recent upward trend in the homeless population.

  5. d

    Directory Of Unsheltered Street Homeless To General Population Ratio 2012

    • catalog.data.gov
    • data.cityofnewyork.us
    • +3more
    Updated Sep 2, 2023
    + more versions
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    data.cityofnewyork.us (2023). Directory Of Unsheltered Street Homeless To General Population Ratio 2012 [Dataset]. https://catalog.data.gov/dataset/directory-of-unsheltered-street-homeless-to-general-population-ratio-2012
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    Dataset updated
    Sep 2, 2023
    Dataset provided by
    data.cityofnewyork.us
    Description

    "Ratio of Homeless Population to General Population in major US Cities in 2012. *This represents a list of large U.S. cities for which DHS was able to confirm a recent estimate of the unsheltered population. Unsheltered estimates are from 2011 except for Seattle and New York City (2012) and Chicago (2009). All General Population figures are from the 2010 U.S. Census enumeration."

  6. Number of homeless people in the U.S. 2023, by race

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Number of homeless people in the U.S. 2023, by race [Dataset]. https://www.statista.com/statistics/555855/number-of-homeless-people-in-the-us-by-race/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, there were an estimated ******* white homeless people in the United States, the most out of any ethnicity. In comparison, there were around ******* Black or African American homeless people in the U.S. How homelessness is counted The actual number of homeless individuals in the U.S. is difficult to measure. The Department of Housing and Urban Development uses point-in-time estimates, where employees and volunteers count both sheltered and unsheltered homeless people during the last 10 days of January. However, it is very likely that the actual number of homeless individuals is much higher than the estimates, which makes it difficult to say just how many homeless there are in the United States. Unsheltered homeless in the United States California is well-known in the U.S. for having a high homeless population, and Los Angeles, San Francisco, and San Diego all have high proportions of unsheltered homeless people. While in many states, the Department of Housing and Urban Development says that there are more sheltered homeless people than unsheltered, this estimate is most likely in relation to the method of estimation.

  7. Number of homeless youth U.S. 2023, by state

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Number of homeless youth U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/727835/number-of-homeless-young-people-in-the-us-by-state/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, there were about ****** homeless youth living in California, the most out of any U.S. state. New York had the second-highest number of homeless youth in that year, at *****.

  8. Population demographics.

    • plos.figshare.com
    xls
    Updated Jan 8, 2025
    + more versions
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    Grace Phillips; Emmy Racine; Anna Marie Naughton; Julieann Lane; Patricia M. Kearney (2025). Population demographics. [Dataset]. http://doi.org/10.1371/journal.pone.0312617.t001
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    xlsAvailable download formats
    Dataset updated
    Jan 8, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Grace Phillips; Emmy Racine; Anna Marie Naughton; Julieann Lane; Patricia M. Kearney
    License

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

    Description

    BackgroundEnsuring effective access to vaccinations for people experiencing homelessness is crucial to protecting the health of a vulnerable, yet often overlooked population. Reaching this goal takes more than a one size fits all approach. This study evaluates how a dedicated health team collaborated with multiple agencies to register and deliver the COVID-19 vaccine to people experiencing homelessness.MethodsThis is a mixed methods study co-designed with the Adult Homeless Integrated Team, a multi-disciplinary team who work with local agencies to provide care to people experiencing homelessness in Cork, Ireland’s second largest city. Quantitative data collected at the point of vaccine registration described socio-demographics of the population. To explain the quantitative findings, eleven agencies involved in provision of homeless services were invited to participate in interviews. A manager in each of the agencies acted as a gatekeeper to clients. Interviews explored experiences with the pandemic and the delivery (staff) or receipt (clients) of the COVID-19 vaccine. Interviews were recorded and transcribed, transcriptions were thematically analysed.ResultsThere were 728 vaccine doses administered to people experiencing homelessness during the first roll-out of vaccines; 401 first doses and 325 second doses. Of those who received a vaccine, the majority were male (76%), and more than half were Irish (55%). Ten semi-structured interviews, seven staff members and three clients, were conducted. There were three themes that provided further insights into the quantitative findings: Adapting to unprecedented times, Misinformation causing vaccine hesitancy and The importance of building relationships.ConclusionsThis study provides valuable insights into how a multidisciplinary approach resulted in a successful well received vaccination programme among a traditionally hard to reach group.

  9. Number of homeless people in London 2025, by borough

    • statista.com
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    Statista, Number of homeless people in London 2025, by borough [Dataset]. https://www.statista.com/statistics/381365/london-homelessness-rough-sleepers-by-london-borough/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 1, 2024 - Mar 31, 2025
    Area covered
    United Kingdom (England), London
    Description

    In 2024/25, there were ***** rough sleepers reported in Westminster, making it the London borough with the highest number of rough sleepers in that year. Other boroughs which also had a high number of homeless people included, Camden, Ealing, and Southwark.

  10. S

    Point In Time Homeless Survey Data

    • splitgraph.com
    • data.sonomacounty.ca.gov
    Updated Jul 12, 2019
    + more versions
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    sonomacounty-ca-gov (2019). Point In Time Homeless Survey Data [Dataset]. https://www.splitgraph.com/sonomacounty-ca-gov/point-in-time-homeless-survey-data-d5jk-fziy
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    application/openapi+json, application/vnd.splitgraph.image, jsonAvailable download formats
    Dataset updated
    Jul 12, 2019
    Authors
    sonomacounty-ca-gov
    Description

    The County of Sonoma conducts an annual homeless count for the entire county. The survey data is derived from a sample of about 600 homeless persons countywide per year. The resulting information is statistically reliable only for the county as a whole, not for individual locations. The exception is the City of Santa Rosa, where the sample taken within the city is large enough to be predictive of the overall homeless population in that city.

    Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

    See the Splitgraph documentation for more information.

  11. Tables on homelessness

    • gov.uk
    Updated Nov 27, 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
    Nov 27, 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/6925ffcd2945773cf12dd09f/Statutory_Homelessness_England_Time_Series_2024-25.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">325 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/6925ff49aca6213a492dd0a1/Statutory_Homelessness_Detailed_Local_Authority_Data_2024-2025.ods">Detailed local authority level tables: financial year 2024-25

     <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">1.27 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
    

    https://assets.publishing.service.gov.uk/media/68ee42a2a8398380cb4ad058/Statutory_Homelessness_Detailed_Local_Authority_Data_202506.ods"> <svg class="gem-c-attachment_thumbnail-image gem-c-attachment_thumbnail-image--spreadsheet" version="1.1" viewbox="0 0 99 140" width="99" height="140" aria-hidden="tru

  12. Law Against Rights? A Controversy in São Francisco Square Written in Folha...

    • scielo.figshare.com
    xls
    Updated Jun 1, 2023
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    Viviane de Melo Resende (2023). Law Against Rights? A Controversy in São Francisco Square Written in Folha de S. Paulo: Critical-Discursive Reflections [Dataset]. http://doi.org/10.6084/m9.figshare.20455105.v1
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    SciELOhttp://www.scielo.org/
    Authors
    Viviane de Melo Resende
    License

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

    Description

    ABSTRACT In this paper I present results of a project that, in the context of critical discourse studies and the interdiscursive analysis of public policies, focused on representations in online journalism regarding public policies aimed at the homeless population. The research project (CAPES 88881.172032/2018-01) was developed at the Pompeu Fabra University, Spain. Considering the main newspaper of the city of São Paulo, in its digital platform, we have compiled a comprehensive corpus of news about homeless situation published in a period of three years. The choice to specifically address data from Folha de S Paulo is justified because it is the city with the largest homeless population in Brazil. Also, because our previous study has shown that this is the vehicle, among those studied, that publishes more news related to territorial issues, our focus of interest to investigate via the discursive categories of metaphor and representation of social actors.

  13. Number of homeless veterans in the U.S., by state 2022

    • statista.com
    Updated Nov 28, 2025
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    Statista (2025). Number of homeless veterans in the U.S., by state 2022 [Dataset]. https://www.statista.com/statistics/727819/number-of-homeless-veterans-in-the-us-by-state/
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    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    United States
    Description

    In 2022, about ****** veterans living in California were homeless, the most out of all U.S. states.

  14. d

    Homelessness (Investigation in Part of Town)

    • da-ra.de
    • dbk.gesis.org
    Updated 1995
    + more versions
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    Fritz Sack; Peter Höhmann (1995). Homelessness (Investigation in Part of Town) [Dataset]. http://doi.org/10.4232/1.2578
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    Dataset updated
    1995
    Dataset provided by
    da|ra
    GESIS Data Archive
    Authors
    Fritz Sack; Peter Höhmann
    Time period covered
    1969 - 1970
    Description

    A survey of the homeless in two settlements of the part of town is archived under ZA Study No. 2579.

  15. Seroprevalence of SARS-CoV-2 according to demographic characteristics,...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 7, 2023
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    Sandrine Loubiere; Elisabetta Monfardini; Camille Allaria; Marine Mosnier; Agathe Allibert; Laetitia Ninove; Thomas Bosetti; Cyril Farnarier; Ilyes Hamouda; Pascal Auquier; Emilie Mosnier; Aurélie Tinland (2023). Seroprevalence of SARS-CoV-2 according to demographic characteristics, living conditions, health characteristics and comorbidities (N = 1,156). [Dataset]. http://doi.org/10.1371/journal.pone.0255498.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 7, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Sandrine Loubiere; Elisabetta Monfardini; Camille Allaria; Marine Mosnier; Agathe Allibert; Laetitia Ninove; Thomas Bosetti; Cyril Farnarier; Ilyes Hamouda; Pascal Auquier; Emilie Mosnier; Aurélie Tinland
    License

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

    Description

    Seroprevalence of SARS-CoV-2 according to demographic characteristics, living conditions, health characteristics and comorbidities (N = 1,156).

  16. g

    Obdachlosigkeit (Obdachlosenbefragung)

    • search.gesis.org
    • da-ra.de
    Updated Apr 13, 2010
    + more versions
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    Sack, Fritz; Höhmann, Peter (2010). Obdachlosigkeit (Obdachlosenbefragung) [Dataset]. http://doi.org/10.4232/1.2579
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    Dataset updated
    Apr 13, 2010
    Dataset provided by
    GESIS Data Archive
    GESIS search
    Authors
    Sack, Fritz; Höhmann, Peter
    License

    https://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms

    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.

  17. Rapid serological testing results for SARS-CoV-2 (N = 1,156).

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 10, 2023
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    Sandrine Loubiere; Elisabetta Monfardini; Camille Allaria; Marine Mosnier; Agathe Allibert; Laetitia Ninove; Thomas Bosetti; Cyril Farnarier; Ilyes Hamouda; Pascal Auquier; Emilie Mosnier; Aurélie Tinland (2023). Rapid serological testing results for SARS-CoV-2 (N = 1,156). [Dataset]. http://doi.org/10.1371/journal.pone.0255498.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Sandrine Loubiere; Elisabetta Monfardini; Camille Allaria; Marine Mosnier; Agathe Allibert; Laetitia Ninove; Thomas Bosetti; Cyril Farnarier; Ilyes Hamouda; Pascal Auquier; Emilie Mosnier; Aurélie Tinland
    License

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

    Description

    Rapid serological testing results for SARS-CoV-2 (N = 1,156).

  18. Statutory Homelessness Statistics, England

    • data.wu.ac.at
    html
    Updated Dec 11, 2014
    + more versions
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    Ministry of Housing, Communities and Local Government (2014). Statutory Homelessness Statistics, England [Dataset]. https://data.wu.ac.at/schema/data_gov_uk/OGZhMDRmZWUtNjUzZi00OTVkLWE5Y2EtMDAxYzc5MWVlZmI3
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    htmlAvailable download formats
    Dataset updated
    Dec 11, 2014
    License

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

    Description

    National Statistics on Homelessness. Data on households found to be homeless. Contains most useful or most popular data, presented by type and other variables, including by geographical area or as a time series.

  19. 2021 Population and Housing Census - Ghana

    • microdata.statsghana.gov.gh
    Updated Jul 12, 2023
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    Ghana Statistical Service (2023). 2021 Population and Housing Census - Ghana [Dataset]. https://microdata.statsghana.gov.gh/index.php/catalog/110
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    Dataset updated
    Jul 12, 2023
    Dataset provided by
    Ghana Statistical Services
    Authors
    Ghana Statistical Service
    Time period covered
    2021
    Area covered
    Ghana
    Description

    Abstract

    The population and housing census (PHC) is the unique source of reliable and comprehensive data about the size of population and also on major socio-economic & socio-demographic characteristics of the country. It provides data on geographic and administrative distribution of population and household in addition to the demographic and socio-economic characteristics of all the people in the country. Generally, it provides for comparing and projecting demographic data, social and economic characteristics, as well as household and housing conditions at all levels of the country’s administrative units and dimensions: national, regional, districts and localities. The data from the census is classified, tabulated and disseminated so that researchers, administrators, policy makers and development partners can use the information in formulating and implementing various multi-sectorial development programs at the national and community levels. Data on all key variables namely area, household, population, economic activity, literacy and education, fertility and child survival, housing conditions and sanitation are collected and available in the census data. The 2021 PHC in Ghana had an overarching goal of generating updated demographic, social and economic data, housing characteristics and dwelling conditions to support national development planning activities.

    Geographic coverage

    National Coverage , Region , District

    Analysis unit

    • Individuals
    • Households
    • Emigrants
    • Absentee population
    • Mortality
    • Type of residence (households and non household)

    Universe

    All persons who spent census night (midnight of 27th June 2021) in Ghana

    Kind of data

    Census/enumeration data [cen]

    Sampling procedure

    This 10% sample data for the 2021 PHC is representative at the district/subdistrict level and also by the urban rural classification.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    GSS developed two categories of instruments for the 2021 PHC: the listing form and the enumeration instruments. The listing form was only one, while the enumeration instruments comprised six questionnaires, designated as PHC 1A, PHC 1B, PHC 1C, PHC 1D, PHC 1E and PHC 1F. The PHC 1A was the most comprehensive with the others being its subsets.

    1. Listing Form: The listing form was developed to collect data on type of structures, level of completion, whether occupied or vacant and use(s) of the structures. It was also used to collect information about the availability, number and types of toilet facilities in the structures. It was also used to capture the number of households in a structure, number of persons in households and the sex of the persons residing in the households if occupied. Finally, the listing form was used to capture data on non-household populations such as the population in institutions, floating population and sex of the non-household populations.

    2. PHC 1A: The PHC 1A questionnaire was used to collect data from all households in the country. Primarily, it was used to capture household members and visitors who spent the Census Night in the dwelling of the household, and their relationship with the head of the household. It was also used to collect data on homeless households. Members of the households who were absent were enumerated at the place where they had spent the Census Night. The questionnaire was also used to collect the following household information: emigration; socio-demographic characteristics (sex, age, place of birth and enumeration, survival status of parents, literacy and education; economic activities; difficulty in performing activities; ownership and usage of information, technology and communication facilities; fertility; mortality; housing characteristics and conditions and sanitation.

    3. PHC 1B: The PHC 1B questionnaire was used to collect data from persons in stable institutions comprising boarding houses, hostels and prisons who were present on Census Night. Other information that was captured with this instrument are socio-demographic characteristics, literacy and education, economic activities, difficulty in performing activities; ownership and usage of information, technology and communication facilities; fertility; mortality; housing characteristics and conditions and sanitation.

    4. PHC 1C: The PHC 1C questionnaire was used to collect data from persons in “unstable” institutions such as hospitals and prayer camps who were present at these places on Census Night. The instrument was used to capture only the socio-demographic characteristics of individuals.

    5. PHC 1D: The PHC 1D questionnaire was used to collect data from the floating population. This constitutes persons who were found at airports, seaports, lorry stations and similar locations waiting for or embarking on long-distance travel, as well as outdoor sleepers on Census Night. The instrument captured the socio-demographic information of individuals.

    6. PHC 1E: All persons who spent the Census Night at hotels, motels and guest houses were enumerated using the PHC 1E. The content of the questionnaire was similar to that of the PHC 1D.

    7. PHC 1F: The PHC 1F questionnaire was administered to diplomats in the country.

    Cleaning operations

    The Census data editing was implemented at three levels: 1. data editing by enumerators and supervisors during data collection 2. data editing was done at the regional level by the regional data quality monitors during data collection 3. Final data editing was done at the national level using the batch edits in CSPro and STATA Data editing and cleaning was mainly digital.

    Response rate

    100 percent

    Data appraisal

    A post Enumeration Survey (PES) was conducted to assess the extent of coverage and content error.

  20. Post-imputation pooled coefficient estimates (95% confidence interval) for...

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
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    Patricia O’Campo; Rosane Nisenbaum; Anne G. Crocker; Tonia Nicholls; Faith Eiboff; Carol E. Adair (2023). Post-imputation pooled coefficient estimates (95% confidence interval) for predictors in linear mixed models for repeated measures for continuous outcomes and rate ratios (95% confidence interval) for generalized estimating equations models for count outcomes for the sample of women in the At Home/Chez Soi study (N = 653). [Dataset]. http://doi.org/10.1371/journal.pone.0277074.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Patricia O’Campo; Rosane Nisenbaum; Anne G. Crocker; Tonia Nicholls; Faith Eiboff; Carol E. Adair
    License

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

    Description

    Post-imputation pooled coefficient estimates (95% confidence interval) for predictors in linear mixed models for repeated measures for continuous outcomes and rate ratios (95% confidence interval) for generalized estimating equations models for count outcomes for the sample of women in the At Home/Chez Soi study (N = 653).

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    Learn how you can add new datasets to our index.

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Statista (2025). 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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Estimated number of homeless people in the U.S. 2007-2023

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

In 2023, there were about ******* homeless people estimated to be living in the United States, the highest number of homeless people recorded within the provided time period. In comparison, the second-highest number of homeless people living in the U.S. within this time period was in 2007, at *******. How is homelessness calculated? Calculating homelessness is complicated for several different reasons. For one, it is challenging to determine how many people are homeless as there is no direct definition for homelessness. Additionally, it is difficult to try and find every single homeless person that exists. Sometimes they cannot be reached, leaving people unaccounted for. In the United States, the Department of Housing and Urban Development calculates the homeless population by counting the number of people on the streets and the number of people in homeless shelters on one night each year. According to this count, Los Angeles City and New York City are the cities with the most homeless people in the United States. Homelessness in the United States Between 2022 and 2023, New Hampshire saw the highest increase in the number of homeless people. However, California was the state with the highest number of homeless people, followed by New York and Florida. The vast amount of homelessness in California is a result of multiple factors, one of them being the extreme high cost of living, as well as opposition to mandatory mental health counseling and drug addiction. However, the District of Columbia had the highest estimated rate of homelessness per 10,000 people in 2023. This was followed by New York, Vermont, and Oregon.

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