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.
Updated every Thursday People experiencing homelessness are at risk for infection through community spread of COVID-19. The data below describes impacts of COVID-19 on individuals who are experiencing homelessness, whether they are able to access a congregate shelter or unsheltered (sleeping outside or in places not meant for human habitation).
For COVID-19 investigation purposes, people experiencing homelessness are defined as those who have lived on the streets or stayed in a shelter, vehicle, abandoned building, encampment, tiny house village/tent city, or supportive housing program (transitional or permanent supportive) at any time during the 12 months prior to COVID-19 testing, without evidence that they were otherwise permanently housed. Public Health, the Department of Community and Human Services, homeless service providers, healthcare providers, and the City of Seattle have partnered for increased testing in this community.
This dataset represents the number of persons who successfully exit from homelessness in a given fiscal year in the Austin/Travis County Continuum of Care (CoC). This measure is comprised of Metric 7b1 and 7b2 from the HUD System Performance Measures. Data Source: The data for this measure was reported to the City of Austin by the Ending Community Homelessness Coalition (ECHO). Each year, ECHO, as the homeless Continuum of Care Lead Agency (CoC Lead), aggregates and reports community wide data (including this measure) to the Department of Housing and Urban Development (HUD). This data is referred to as System Performance Measures as they are designed to examine how well a community is responding to homelessness at a system level. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/xtip-he7k
The primary goal of this study was to develop an understanding of the role of violence in the lives of homeless women and men. The objectives were to determine how many women and men have experienced some form of violence in their lives either as children or adults, the factors associated with experiences of violence, the consequences of violence, and the types of interactions with the justice system. The survey sample was comprised of about 200 face-to-face interviews with homeless women in each of four Florida cities (Jacksonville, Miami, Orlando, and Tampa). In all, 737 women were interviewed. In addition, 91 face-to-face interviews with homeless men were also conducted only in Orlando. For Part 1 (Female Interviews), the data include information related to the respondent's living conditions in the past month, as well as experiences with homelessness, childhood violence, adult violence, forced sexual situations, and stalking. Additional variables include basic demographic information, a self-report of criminal history, information related to how the respondent spent her days and evenings, and the physical environment surrounding the respondent during the day and evening. For Part 2 (Male Interviews), the data include much of the same information as was collected in Part 1. Information from Part 1 not included in Part 2 primarily includes questions pertaining to experience with forced sexual situations, and questions related to pregnancy and children.
https://www.hamilton.ca/city-initiatives/strategies-actions/open-data-licence-terms-and-conditionshttps://www.hamilton.ca/city-initiatives/strategies-actions/open-data-licence-terms-and-conditions
Inflow and Outflow are two of the most important measures for monitoring progress towards our goal of ending homelessness. The goal is to see outflow exceed inflow. When this happens, it means that more people are exiting from homelessness than are entering the homeless-serving system.Inflow represents: the number of individuals newly identified as homeless, returned to homelessness from housing, returned to homelessness from inactive status (they have accessed the homeless-serving system within the last 90 days). Outflow represents: the number of individuals who have moved from housing to housed and those who have moved to inactive status (they have not interacted with the homeless-serving system for 90+ days). Data includes individuals who have had a shelter stay since October 2019 (the date which our homeless-serving system started using the newly released HIFIS 4.0). Data depicted is collected by homeless-serving shelters through the Homeless Individuals and Families Information System (HIFIS).
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.
City expenditures related to Homelessness efforts in the City of LA starting with fiscal year 2024. Data populated by City departments who code and map expenses to homeless project categories. (Not all departments are included due to the way the department maps homeless expenditures)
"Ratio of Homeless Population to General Population in major US Cities in 2009. *This represents a list of large U.S. cities with a similar street count methodology for which DHS was able to confirm a recent Census; 2009 results are not yet available for LA, SF, and Chicago. All population figures are from the 2007 U.S. Census Bureau Population Estimate."
https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0https://ottawa.ca/en/city-hall/get-know-your-city/open-data#open-data-licence-version-2-0
City staff and community partners work together to survey people experiencing homelessness in Ottawa. So far, the City has led two counts:April 2018October 2021Oct 2024The survey is conducted to gather information about people experiencing homelessness. The goal of this work is to guide new approaches to address homelessness at a local level and help in the planning and delivery of services.Date created: 28 April 2022Update frequency: As needed.Accuracy: Convenience sampling was used to recruit survey respondents. This method of recruiting respondents to answer the survey does not rely on a random selection process. Instead, surveyors approach potential respondents if they are close by at the time the surveyor is delivering the questionnaire. Many factors could determine participation in the survey including:Number of community partners involved in the PiT countLocation of surveyors and their physical proximity to potential respondentsNumber of engagement eventsSeason the survey was conductedDifferences in results between PiT count years may be due to changes within the homeless population and shifts in methodology. For comparisons of emergency shelter use over time, visit the Temporary Emergency Accommodations Dashboard. An analysis of factors related to housing and homelessness during COVID-19 provides context for unique housing market conditions during the pandemic.Results shown in the Survey results: Point-in-Time count dashboard are presented by sector. The name and definition of each sector are below:All: All respondents who answered the surveySingle adult: Respondents aged 25 years or older and not accompanied by anyoneUnaccompanied youth: Respondents under 25 years old and not accompanied by anyoneFamily: Respondents accompanied by children under 18 years oldAttributes:Question: The question that was asked in the surveyTopic: The classification of the survey question by themSector: Refers to the population (total, family, unaccompanied youth, single adults)Period: Month the Point-in-Time count was conductedResponse: Response category of the survey questionNumeratorDenominatorPercentage Author: Housing ServicesAuthor email: pitcount_denombrementponctuel@ottawa.ca
Homelessness is a social crisis in the United States of America. According to McKinney–Vento Homeless Assistance Act, homeless people are those who lack a fixed, regular and adequate nighttime residence. "Ratio of Homeless Population to General Population in major US Cities in 2012.
Table of homeless population by Year (for years 2009 through 2012)
"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."
This statistic depicts the rate of homeless individuals in the United States in 2017, by metropolitan area. In 2017, the rate of homelessness per 10,000 individuals was highest in New York City, at ****.
As of 2023, there were about ****** unsheltered homeless people living in Los Angeles, compared to ****** sheltered homeless people.
From July 1, 2021 to June 30, 2022, New York City's Department of Social Services/Department of Homeless Services (DHS) and Office of the Chief Medical Examiner (OCME) reported 684 deaths among persons experiencing homelessness. Of this total, around 345 deaths occurred in hospitals, while 155 occurred in shelters. This statistic depicts the number of deaths among persons experiencing homelessness in New York City as reported by the DHS and the OCME between 2021 and 2022, by location of death
A novel and comprehensive cross-sectional dataset (2017) was developed to document and measure municipal supportive housing policy choices and key political factors associated with these choices. The dataset is comprised of 232 municipalities of 354 municipal continuums of care (CoCs) from the HUD 2016 CoC database in order to control for cities directly receiving federal homeless funding. The final sample accounts for 66 percent of all CoCs in the U.S. Municipalities were chosen based on their inclusion in the HUD 2016 Point in Time (PIT) count survey, therefore selecting municipalities with a CoC that are receiving federal funding for homelessness solutions. This is a comprehensive, cross-sectional dataset of municipalities across the United States that includes measures of local homeless policies; measures of local political indicators including local policy conservatism, fragmentation, municipal governmental structure; other relevant social policies (Sanctuary City status, Medicaid expansion, state level supportive housing policy); local demographic characteristics; local economic factors.
U.S. Government Workshttps://www.usa.gov/government-works
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The purpose of the San Mateo County Homeless Census and Survey is to gather and analyze information to help us understand who is homeless in our community, why they are homeless and what interventions they need to end their homelessness. This data forms the basis for effective planning to solve this complex and longstanding problem. The San Mateo County Human Services Agency’s Center on Homelessness the San Mateo County Continuum of Care Steering Committee were responsible for overseeing this data collection effort, with assistance from a broad group of community partners, including non-profit social service providers, city and town governments, and homeless and formerly homeless individuals. The Census and Survey was designed to meet two related sets of data needs. The first is the requirement of the U.S. Department of Housing and Urban Development (HUD) that communities applying for McKinney-Vento Homelessness Assistance funds (also known as Continuum of Care or “CoC” funds) must conduct a point-in-time count of homeless people a minimum of every two years. These counts are required to take place in the last ten days of January.
Homelessness has been a consistent problem for the city of Louisville for decades now. Despite efforts from the city government and local nonprofits, homelessness increased 139% last year alone. The Covid-19 pandemic significantly worsened the crisis, but the risk factors that contribute to homelessness are still endemic across the city: lack of affordable housing, lack of access to physical and mental healthcare, stagnant wages, etc. Homelessness has negative effects on mortality, personal health of the homeless, and public health in general (also see here, no paywall). When I recently attended a strategy meeting for the Louisville Downtown Partnership, one of the top issues voted by attendees was the rise of homelessness downtown. This could come from genuine care or that many Americans associate homeless people with crime. Everyone benefits when the issues that cause homelessness are addressed effectively, and a vital part of that is knowing what areas are most at-risk.The app above was made to map certain risk factors across Jefferson County. The risk factors include percent of households with 50%+ income going to rent, persons without health insurance coverage, percent of households at or below the poverty line, percent of households using public assistance, percent of persons reporting extensive physical and mental distress, unemployment, along with other economic and health-based factors. This doesn’t include every possible factor that could cause homelessness, but many that have strong effects. A dummy census tract was made with all the worst possible outcomes for risk factors, which was then used to rank the similarity of every census tract in Jefferson County; the lower the rank, the more at-risk the tract is. The app allows you to click through every tract in the county and see the ten most at-risk ones.The most at-risk places tend to line up with the west end and areas of the city that were historically redlined. These areas also saw mass amounts of “urban renewal” in the 60s and 70s. They also tend to line up with areas of the city that face the highest eviction rates (thanks to Ryan Massey for pointing this out).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The goal of this research was to determine the quality of life of homeless older persons living in Housing First facilities in the City of Tshwane. This research aimed to provide interdisciplinary teams with valuable, effective, and practical recommendations and best practice guidelines on ways to promote the quality of life of homeless older persons in Housing First facilities. This study was underpinned by pragmatism as the research paradigm and adopted a mixed-methods research approach. The study was exploratory and descriptive in nature and followed an explanatory sequential mixed methods design. Firstly, the researcher collected and analysed quantitative data and thereafter explained the results in further detail using qualitative data. Quantitative data was collected through face-to-face surveys, and qualitative data was generated through face-to-face semi-structured interviews. This study adopted the use of non-probability sampling in the form of purposive sampling. The quantitative data collection instrument was piloted with two homeless older persons in the Housing First facilities, and the qualitative data instrument was piloted with one member of the interdisciplinary team. Quantitative data analysis focused on descriptive and inferential statistics, and qualitative data followed the reflexive thematic analysis process.
This dataset provides information on individuals who exit homelessness to permanent housing destinations and then return to homelessness within 2 years from their exit in the Austin/Travis County Continuum of Care (CoC) in a given fiscal year. Data Source: The data for this measure was reported to the City of Austin by the Ending Community Homelessness Coalition (ECHO). Each year, ECHO, as the homeless Continuum of Care Lead Agency (CoC Lead), aggregates and reports community wide data (including this measure) to the Department of Housing and Urban Development (HUD). This data is referred to as System Performance Measures as they are designed to examine how well a community is responding to homelessness at a system level. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/cutp-y8m4
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.