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

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.

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.

This dataset contains estimates of homelessness, as well as estimates of chronically homeless persons, homeless veterans, and homeless children and youth provided by The U.S. Department of Housing and Urban Development. The estimates cover the period of years 2007-2017 and are at national, state and Continuums of Care (CoC) Point-In-Time (PIT) level.

This report outlines the key findings of the annual Point-In-Time (PIT) count and Housing Inventory Count (HIC) conducted in January of each year. Specifically, this report provides estimates of homelessness self-reported, as well as estimates of chronically homeless persons, homeless veterans, and homeless children and youth.

Current link at the time of dataset creation: https://www.hudexchange.info/resource/4832/2015-ahar-part-1-pit-estimates-of-homelessness/

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

Comprehensive dataset containing 3,632 verified Homeless shelter businesses in United States with complete contact information, ratings, reviews, and location data.

This data tracks the number of beds available for runaway and homeless youth and young adults as well as the number and percent vacant. Data include Crisis Shelters, Crisis Shelters HYA (Homeless Young Adults), Transitional Independent Living, and Transitional Independent Living HYA. For more information about programs, visit https://www1.nyc.gov/site/dycd/services/services.page and https://discoverdycd.dycdconnect.nyc/home. For the RHY Data Collection, please follow this link.

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

This dataset includes the daily number of families and individuals residing in the Department of Homeless Services (DHS) shelter system and the daily number of families applying to the DHS shelter system.

This dataset includes data starting from 01/03/2021. For older records, please refer to https://data.cityofnewyork.us/d/dwrg-kzni

The dataset contains locations and attributes of Homeless Shelters, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. A database provided by the Department of Human Services identified Homeless Shelter locations.

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

This dataset includes the daily number of families and individuals residing in the Department of Homeless Services (DHS) shelter system and the daily number of families applying to the DHS shelter system.

This dataset includes the daily number of families and individuals residing in the Department of Homeless Services (DHS) shelter system and the daily number of families applying to the DHS shelter system.

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

The purpose of the Continuum of Care (CoC) Homeless Assistance Programs is to reduce the incidence of homelessness in CoC communities by assisting homeless individuals and families in quickly transitioning to self-sufficiency and permanent housing. The 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).

What is the Point-In-Time Count?

The U.S. Department of Housing and Urban Development (HUD) and Washington State Department of Commerce require communities to conduct a one-day Point-In-Time (PIT) Count to survey individuals experiencing homelessness. PIT Counts are one source of data among many that help us understand the magnitude and characteristics of people who are homeless in our community.

The Point-In-Time (PIT) Count is a one-day snapshot that captures the characteristics and situations of people living here without a home. The PIT Count includes both sheltered individuals (temporarily living in emergency shelters or transitional housing) and unsheltered individuals (those sleeping outside or living in places that are not meant for human habitation).

The annual PIT Count happens the last Friday in January, and is carried out by volunteers who interview people and asks where they slept the night before, where their last residence was located, what may have contributed to their loss of housing, and disabilities the individual may have. It also asks how long the individual has been homeless, age and demographics, and whether the person is a veteran and/or a survivor of domestic violence.

Like all surveys, the PIT Count has limitations. Results from the Count are influenced by the weather, by availability of overflow shelter beds, by the number of volunteers, and by the level of engagement of the people we are interviewing. Comparisons from year to year should be done with those limitations in mind.

This dataset provides data on youth who sought DYCD Runaway & Homeless Youth services and then were unable to access an RHY bed or subsequently refused services. For more information about programs, visit https://www1.nyc.gov/site/dycd/services/services.page and https://discoverdycd.dycdconnect.nyc/home. For the RHY Data Collection, please follow this link.

In 2023, the around 11.1 percent of the population was living below the national poverty line in the United States. Poverty in the United StatesAs shown in the statistic above, the poverty rate among all people living in the United States has shifted within the last 15 years. The United Nations Educational, Scientific and Cultural Organization (UNESCO) defines poverty as follows: “Absolute poverty measures poverty in relation to the amount of money necessary to meet basic needs such as food, clothing, and shelter. The concept of absolute poverty is not concerned with broader quality of life issues or with the overall level of inequality in society.” The poverty rate in the United States varies widely across different ethnic groups. American Indians and Alaska Natives are the ethnic group with the most people living in poverty in 2022, with about 25 percent of the population earning an income below the poverty line. In comparison to that, only 8.6 percent of the White (non-Hispanic) population and the Asian population were living below the poverty line in 2022. Children are one of the most poverty endangered population groups in the U.S. between 1990 and 2022. Child poverty peaked in 1993 with 22.7 percent of children living in poverty in that year in the United States. Between 2000 and 2010, the child poverty rate in the United States was increasing every year; however,this rate was down to 15 percent in 2022. The number of people living in poverty in the U.S. varies from state to state. Compared to California, where about 4.44 million people were living in poverty in 2022, the state of Minnesota had about 429,000 people living in poverty.