9 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/
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    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. i

    Grant Giving Statistics for World Aid for Homeless Children Incorported

    • instrumentl.com
    Updated Oct 17, 2021
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    (2021). Grant Giving Statistics for World Aid for Homeless Children Incorported [Dataset]. https://www.instrumentl.com/990-report/world-aid-for-homeless-children-incorported
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    Dataset updated
    Oct 17, 2021
    Description

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

  4. i

    Grant Giving Statistics for Global Partnership for Homeless Health Inc.

    • instrumentl.com
    Updated Feb 28, 2023
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    (2023). Grant Giving Statistics for Global Partnership for Homeless Health Inc. [Dataset]. https://www.instrumentl.com/990-report/global-partnership-for-homeless-health-inc
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    Dataset updated
    Feb 28, 2023
    Variables measured
    Total Assets, Total Giving
    Description

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

  5. Global number of people left homeless by wildfires 1990-2023

    • statista.com
    Updated Jun 14, 2025
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    Statista (2025). Global number of people left homeless by wildfires 1990-2023 [Dataset]. https://www.statista.com/statistics/1423747/global-number-of-homeless-people-due-to-wildfires/
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    Dataset updated
    Jun 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    The number of people left homeless due to wildfires in 2023 amounted to **, a considerable decrease when compared to the figures of 2022 and 2021, when ***** and ***** people lost their homes due to such disasters.

  6. Social Housing Provision by County and Method

    • kaggle.com
    zip
    Updated Dec 20, 2023
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    The Devastator (2023). Social Housing Provision by County and Method [Dataset]. https://www.kaggle.com/datasets/thedevastator/social-housing-provision-by-county-and-method
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    zip(9415 bytes)Available download formats
    Dataset updated
    Dec 20, 2023
    Authors
    The Devastator
    Description

    Social Housing Provision by County and Method

    Annual Breakdown of Social Housing Provisions by County and Method from 2016

    By Ian Baldwin [source]

    About this dataset

    This structured dataset encompasses a wealth of specifics such as the local government authority's name that is responsible for social housing provisions within each county. It reveals the year when the data was recorded and also offers information on period time – whether it was during a specific quarter within that year (Q1, Q2, Q3, Q4), or an annual data record.

    One of its most notable aspects covers details about delivery type - showing various methods via which Social Housing Provisions were delivered. This could range from new construction builds to property acquisitions or leasing agreements among others.

    Another enriching detail it provides is on categories of social housing. It exhibits how these provisions were categorized based on certain criteria such as general needs houses, specialized residences for older people or homes specifically made available for alleviating homelessness etc.

    Equally important is information about who delivered these housing provisions- be it different entities like local authority itself directly involved , approved external bodies related with housing authorities processor private developers who have played their role in this regard Moreover amount denotes units provided during specified period thus enabling readers understand scale operation .

    Last but not least , file provides full annual target - showcasing total units planned provisioned during defined year enhancing comprehension around planning effectiveness implementation aforementioned activities . All diverse specifics uniquely consolidated forming invaluable resource diverse stakeholders particularly those involved urban development planning population management research analysis purposes

    How to use the dataset

    This dataset can serve as an excellent resource for anyone looking to explore the specifics of social housing provision in different counties. It provides a comprehensive view of how social housing has been delivered, who delivers it, what types of houses have been constructed and how many were planned versus the actual amount delivered.

    Here are some ways you could use this dataset:

    • Benchmarking and Comparative Analysis: One can compare the overall performance of different local authorities in delivering their full annual targets for social housing. This will help stakeholders understand which areas are performing well or poorly.

    • Trend Analysis over years: Analyse trends in social housing provision over multiple years to identify patterns and predict future needs or shortfalls.

    • Category Wise Study: Break down the data by category (general needs, older persons, homeless) and gain insights on specific demands catered by the local authorities across counties.

    • Provider profiles: The Delivered By column can give information about particular entities involved in providing social houses as well as their contributions towards meeting demand for such housings over several years.

    • Policy Feedback: The data from this dataset could provide significant inputs into policymaking processes related to infrastructure, public housing projects etc., allowing you to measure impact or suggest improvements based on empirical evidence collected over time.

    • Housing Provision Method Overview: Compare effectiveness of various delivery methods like new builds, acquisitions or leasing etc In terms of fulfilling requirements set under full annual target - providing insight into which methods might be most efficient for achieving goals

    To get started with analyzing this dataset: - You may want to start by cleaning up any missing values. - Create aggregate statistics per year/per quarter/per category - Calculate ratios between delivery targets and actual number provided. - Use visualization tools like bar graphs or pie charts for better understanding

    Remember that correlation does not imply causation – so make sure context is considered when interpreting your data. Always use a critical eye and consider all possible factors. Happy analyzing!

    Research Ideas

    • Policy Decision-making: Policy makers at the local and national level could use this data to understand the effectiveness of different methods of housing provision in meeting annual targets. This can be crucial for future planning and deciding which method or entity to prioritise.
    • Housing Research: Researchers studying housing policy, homelessness, or urban development could use this dataset to explore correlations be...
  7. a

    Family Health Centers, San Diego County

    • hhubsandiego-ucsdonline.hub.arcgis.com
    Updated Feb 8, 2023
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    University of California San Diego (2023). Family Health Centers, San Diego County [Dataset]. https://hhubsandiego-ucsdonline.hub.arcgis.com/datasets/family-health-centers-san-diego-county-2024
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    Dataset updated
    Feb 8, 2023
    Dataset authored and provided by
    University of California San Diego
    Area covered
    Description

    Locations and health center information was sourced from https://www.fhcsd.org/clinic-location-list/. This list was digitized into a spreadsheet and geolocated using ArcGIS World Geocoding Service. To be hosted by Homelessness Hub at UC San Diego. Data is current to April 2024.

  8. C

    Global Pop-Up Housing Solutions Market Key Success Factors 2025-2032

    • statsndata.org
    excel, pdf
    Updated Oct 2025
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    Stats N Data (2025). Global Pop-Up Housing Solutions Market Key Success Factors 2025-2032 [Dataset]. https://www.statsndata.org/report/pop-up-housing-solutions-market-279720
    Explore at:
    excel, pdfAvailable download formats
    Dataset updated
    Oct 2025
    Dataset authored and provided by
    Stats N Data
    License

    https://www.statsndata.org/how-to-orderhttps://www.statsndata.org/how-to-order

    Area covered
    Global
    Description

    The Pop-Up Housing Solutions market has emerged as a transformative force in the real estate and housing industry, providing innovative temporary housing options that address various needs ranging from disaster relief to urban homelessness. As the global population continues to rise and urban areas face increasing d

  9. Government shelter homes during COVID-19 in India 2020 by state

    • statista.com
    Updated Apr 9, 2020
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    Statista (2020). Government shelter homes during COVID-19 in India 2020 by state [Dataset]. https://www.statista.com/statistics/1116192/india-government-shelter-homes-during-covid-19-by-state/
    Explore at:
    Dataset updated
    Apr 9, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    Various state governments in India set-up shelter homes for those stranded by the coronavirus (COVID-19) lockdown implemented in late March, 2020. The southern state of Kerala topped the list with 15,141 shelter homes in April. This was nearly 70 percent of all government camps across the country. Uttar Pradesh followed with 2,230 camps and Maharashtra ranked third during the same time period.

    The country went into lockdown on March 25, 2020, the largest in the world, restricting 1.3 billion people. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

  10. Not seeing a result you expected?
    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

Explore at:
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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