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.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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 were separate files but are now combined.
Information updated as of 7/29/2025.
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.
The racial demographics of the homeless population in Corona, CA.
In 2023, about *** percent of the estimated number of homeless veterans in the United States were Native American. In comparison, ** percent were white and **** percent were Black or African American.
In 2023, about ** percent of the estimated number of unaccompanied homeless youth in the United States were white. In comparison, **** percent of unaccompanied homeless youth were Black or African American in that year.
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.
The RHY-HMIS Dashboard allows grantees and RHY federal project officers to visualize their data, compare their data against other programs and targets, share data, and easily insert specific data fields into reports. They can see their own grant-level data as well as state, regional, and national RHY-HMIS data. Authorized grantees have special logon credentials that allow them to see their own grant-level data as well as state, regional, and national RHY data. The general public will not need to log on. Public access users will not be able to see any grantee-level data but will be able to access state, regional, and national data. Units of Response: RHY Grantees, Runaway and Homeless Youth Type of Data: Administrative Tribal Data: Unavailable Periodicity: Biannual Demographic Indicators: Disability;Ethnicity;Housing Status;Military;Race SORN: https://www.federalregister.gov/documents/2015/04/02/2015-07440/privacy-act-of-1974-system-of-records-notice Data Use Agreement: Unavailable Data Use Agreement Location: Unavailable Granularity: Grant;Program;State Spatial: United States Geocoding: Region;State
Homelessness is measured by number of homeless individuals per 100,000 individuals in the general population. Homelessness data was available by race and ethnicity, separately. Both sheltered and unsheltered homeless individuals are captured in the homelessness counts, to provide a fuller picture of the homeless population.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This dataset shows the number of persons who have approached Birmingham City Council and presented as homeless or threatened with homelessness. Data is broken down by year and ethnicity.In England, local authorities have a statutory duty to prevent homelessness under the Homelessness Reduction Act 2017. This duty requires them to take reasonable steps to help individuals who are threatened with homelessness within 56 days to secure that accommodation does not cease to be available for their occupation. Small number suppression has been applied to those detailed ethnicities which are less than 10. All those individuals will be listed as a group called Data disclosure protection.
http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence
This dataset contains the numbers of households accepted as homeless and in priority need, broken down by local authority and by ethnicity.
The term "Homelessness" is often considered to apply only to people "sleeping rough". However, most of our statistics on homelessness relate to the statutorily homeless i.e. those households which meet specific criteria of priority need set out in legislation, and to whom a homelessness duty has been accepted by a local authority.
Such households are rarely homeless in the literal sense of being without a roof over their heads, but are more likely to be threatened with the loss of, or are unable to continue with, their current accommodation.
A detailed explanation of the responsibilities of local authorities in this area is available from the DCLG website, here.
A "main homelessness duty" is owed where the authority is satisfied that the applicant is eligible for assistance, unintentionally homeless and falls within a specified priority need group. Such statutorily homeless households are referred to as "acceptances".
This dataset provides statistics on the numbers of households accepted as statutorily homeless. The data is broken down according to the ethnic group of the applicants and by local authority area.
The numbers are presented in terms of households, not individuals. A household is defined as: one person living alone, or a group of people living at the same address who share common housekeeping or a living room.
Values of less than five households have been suppressed. In addition, some values of five or greater have been suppressed to prevent other suppressed values being calculated
This data is also available in Table 784a, available for download as an Excel spreadsheet.
Filtered view for primary race reporting and visualizations. Individuals receiving homeless-related services from a Maricopa County provider, during calendar year 2024 and whose last permanent city of residence prior to becoming homeless was Mesa.
This data set contains calls for service at homeless shelters. Disclaimer - Race/Age/Gender/Ethnicity data is not captured for all records. Update Frequency: Daily
Filtered view for ethnicity reporting and visualizations. Individuals receiving homeless-related services from a Maricopa County provider, whose last permanent city of residence prior to becoming homeless was Mesa.
According to a survey on regional homelessness conducted in September 2018, at around 43 percent, the majority of people living without a shelter in the Auckland region in New Zealand were of Māori ethnicity. In the same year, an estimated 16 percent of the entire population of the country were Māori.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
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
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Homeless Persons Usually Resident in the State by Ethnicity by Statistic, CensusYear and Sex
View data using web pages
Download .px file (Software required)
Aggregated data from the Home-American Rescue Plan Tenant-Based Rental Assistance program provided by the Office of Homelessness and Supportive Housing. This data represents the full life of the grant from January 2022 through December 2024.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This dataset shows the ethnicity of the lead applicant of the household currently in temporary accommodation to avoid homelessness according to the Homelessness Reduction Act 2017. The data includes both broad and detailed ethnicity.In England, local authorities have a statutory duty to prevent homelessness under the Homelessness Reduction Act 2017. This duty requires them to take reasonable steps to help individuals who are threatened with homelessness within 56 days to secure that accommodation does not cease to be available for their occupation. Small number suppression has been applied to those detailed ethnicities which are less than 10. All those individuals will be listed as a group called Data disclosure protection.
Created for the 2023-2025 State of Black Los Angeles County (SBLA) interactive report. To learn more about this effort, please visit the report home page at https://ceo.lacounty.gov/ardi/sbla/. For more information about the purpose of this data, please contact CEO-ARDI. For more information about the configuration of this data, please contact ISD-Enterprise GIS. Table Name Indicator Name Universe Timeframe Source Race Notes Source URL
homeownership_pct % Homeownership Occupied Housing Units 2016-2020 American Community Survey - Table B25003B-I Race alone; White is Non-Hispanic White https://data.census.gov/cedsci/table?g=0500000US06037&tid=ACSDT5Y2020.B25003
renters_pct % Renters Occupied Housing Units 2016-2020 American Community Survey - Table B25003B-I Race alone; White is Non-Hispanic White https://data.census.gov/cedsci/table?g=0500000US06037&tid=ACSDT5Y2020.B25003
mean_home_value Mean Home Value Households 2021 Public Use Microdata Sample (PUMS) All races are Non-Hispanic LA County eGIS-Demography
accepted_mortgage_pct Accepted Mortgate Rate Mortgage Applications 2021 Home Mortgage Disclosure Act HMDA categories - https://files.consumerfinance.gov/f/documents/cfpb_reportable-hmda-data_regulatory-and-reporting-overview-reference-chart-2019.pdf https://ffiec.cfpb.gov/data-browser/data/2021
rent_burden_pct Rent Burdened Renter Households 2019 California Housing Partnership All races are Non-Hispanic https://chpc.net/housingneeds/?view=37.405074,-119.26758,5&county=California,Los+Angeles&group=housingneed&chart=shortfall|current,cost-burden|current,cost-burden-re|current,homelessness,historical-rents,vacancy,asking-rents|2022,budgets|2021,funding|current,state-funding,lihtc|2010:2021:historical,rhna-progress,multifamily-production
rent_burden_severe_pct Severely Rent Burdened Renter Households 2019 California Housing Partnership All races are Non-Hispanic https://chpc.net/housingneeds/?view=37.405074,-119.26758,5&county=California,Los+Angeles&group=housingneed&chart=shortfall|current,cost-burden|current,cost-burden-re|current,homelessness,historical-rents,vacancy,asking-rents|2022,budgets|2021,funding|current,state-funding,lihtc|2010:2021:historical,rhna-progress,multifamily-production
eviction_per_100_hh Eviction Rate Renter Households 2014-2017 The Eviction Lab at Princeton University
https://data-downloads.evictionlab.org/#data-for-analysis/
homeless_count Homeless Count Population excluding Long Beach, Glendale, and Pasadena 2022 LAHSA
https://www.lahsa.org/documents?id=6545-2022-greater-los-angeles-homeless-count-deck
homeless_homeless_pct % Homeless Population Population excluding Long Beach, Glendale, and Pasadena 2022 LAHSA
https://www.lahsa.org/documents?id=6545-2022-greater-los-angeles-homeless-count-deck
homeless_county_pct % County Population Population excluding Long Beach, Glendale, and Pasadena 2022 LAHSA
https://www.lahsa.org/documents?id=6545-2022-greater-los-angeles-homeless-count-deck
unable_pay_mortgage_rent% Delayed or Were Unable to Pay Mortgage or Rent in the past 2 Years Households 2018 LAC Health Survey https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm
homeless_ever% Who Reported Ever Being Homeless or Not Having Their Own Place to Live or Sleep in the past Five Years Adults 2018 LAC Health Survey https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm
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.