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.

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

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 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.

The dataset described testing, infection and complication rates of COVID-19 among people with a recent history of homelessness in Ontario

This dataset supports measure S.D.4.c of SD23. The Downtown Austin Community Court (DACC) was established to address quality of life and public order offenses occurring in the downtown Austin area utilizing a restorative justice court model. DACC’s priority population consists of individuals experiencing homelessness and the program’s main goal is to permanently stabilize individuals experiencing homelessness. To effectively serve these individuals, DACC created an Intensive Case Management (ICM) Program, which uses a client-centered and housing-focused approach. The ICM Program focuses on rehabilitating and stabilizing individuals using an evidenced-based model of wraparound interventions to help them achieve long-term stability. Because individuals participating in case management are literally homeless, case managers must actively seek their clients in the community through outreach activities and often times work on behalf of the client via collateral engagement with other social service and housing providers. This measure highlights case management activities accomplished via outreach and collateral engagement.

View more details and insights related to this measure on the story page: https://data.austintexas.gov/stories/s/65cb-wtrs

Data source: manually tracked internally on a monthly checkbox report Calculation: Numerator: number of clients served through outreach Denominator: total number of cases filed that are homeless this dataset on the portal covers an annual range based on the city's fiscal year.

BackgroundAddressing Citizen’s perspectives on homelessness is crucial for the design of effective and durable policy responses, and available research in Europe is not yet substantive. We aim to explore citizens’ opinions about homelessness and to explain the differences in attitudes within the general population of eight European countries: France, Ireland, Italy, the Netherlands, Poland, Portugal, Spain, and Sweden.MethodsA nationally representative telephone survey of European citizens was conducted in 2017. Three domains were investigated: Knowledge, Attitudes, and Practices about homelessness. Based on a multiple correspondence analysis (MCA), a generalized linear model for clustered and weighted samples was used to probe the associations between groups with opposing attitudes.ResultsResponse rates ranged from 30.4% to 33.5% (N = 5,295). Most respondents (57%) had poor knowledge about homelessness. Respondents who thought the government spent too much on homelessness, people who are homeless should be responsible for housing, people remain homeless by choice, or homelessness keeps capabilities/empowerment intact (regarding meals, family contact, and access to work) clustered together (negative attitudes, 30%). Respondents who were willing to pay taxes, welcomed a shelter, or acknowledged people who are homeless may lack some capabilities (i.e. agreed on discrimination in hiring) made another cluster (positive attitudes, 58%). Respondents living in semi-urban or urban areas (ORs 1.33 and 1.34) and those engaged in practices to support people who are homeless (ORs > 1.4; p

Homelessness and Hidden Homelessness in Rural and Northern Ontario is the first study of its kind to empirically challenge these popular perceptions. In fact, as the analysis of data from the recent Canadian Social Survey demonstrates, compared to city dwellers, a higher percentage of people from rural Ontario reported that they had experienced homelessness or hidden homelessness at some point in their lives. The research carried out for this report was based on a survey of service providers (with responses from 204 service providers and 30 service managers), focus groups (with 76 key sector stakeholders), and interviews (with 40 people who had experience of homelessness or hidden homelessness) in 10 communities in northwestern, northeastern, southwestern, and southeastern Ontario. This was augmented by an analysis of Ontario data from Canada’s General Social Survey. The causes of homelessness in rural and northern Ontario were found to be similar to those in big cities: poverty, mental illness and addictions, lack of affordable housing and domestic violence. The study also revealed that many Indigenous peoples are at risk of homelessness and hidden homelessness, particularly those living in northern areas of the province.

Analysis of ‘Strategic Measure_Number and Percentage of instances where people access court services other than in person and outside normal business hours (e.g. phone, mobile application, online, expanded hours)- Client Contacts through Outreach’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/777a206d-0f7a-49ab-9d70-3f6a5138a21f on 26 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset supports measure S.D.4.c of SD23. The Downtown Austin Community Court (DACC) was established to address quality of life and public order offenses occurring in the downtown Austin area utilizing a restorative justice court model. DACC’s priority population consists of individuals experiencing homelessness and the program’s main goal is to permanently stabilize individuals experiencing homelessness. To effectively serve these individuals, DACC created an Intensive Case Management (ICM) Program, which uses a client-centered and housing-focused approach. The ICM Program focuses on rehabilitating and stabilizing individuals using an evidenced-based model of wraparound interventions to help them achieve long-term stability. Because individuals participating in case management are literally homeless, case managers must actively seek their clients in the community through outreach activities and often times work on behalf of the client via collateral engagement with other social service and housing providers. This measure highlights case management activities accomplished via outreach and collateral engagement.

View more details and insights related to this measure on the story page: https://data.austintexas.gov/stories/s/65cb-wtrs

Data source: manually tracked internally on a monthly checkbox report Calculation: Numerator: number of clients served through outreach Denominator: total number of cases filed that are homeless this dataset on the portal covers an annual range based on the city's fiscal year.

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Natural Disasters Data Explorer’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mathurinache/natural-disasters-data-explorer on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Disasters include all geophysical, meteorological and climate events including earthquakes, volcanic activity, landslides, drought, wildfires, storms, and flooding. Decadal figures are measured as the annual average over the subsequent ten-year period.

Content

Thanks to Our World in Data, you can explore death from natural disasters by country and by date.

Acknowledgements

https://www.acacamps.org/sites/default/files/resource_library_images/naturaldisaster4.jpg" alt="Natural Disasters">

Inspiration

List of variables for inspiration: Number of deaths from drought Number of people injured from drought Number of people affected from drought Number of people left homeless from drought Number of total people affected by drought Reconstruction costs from drought Insured damages against drought Total economic damages from drought Death rates from drought Injury rates from drought Number of people affected by drought per 100,000 Homelessness rate from drought Total number of people affected by drought per 100,000 Number of deaths from earthquakes Number of people injured from earthquakes Number of people affected by earthquakes Number of people left homeless from earthquakes Number of total people affected by earthquakes Reconstruction costs from earthquakes Insured damages against earthquakes Total economic damages from earthquakes Death rates from earthquakes Injury rates from earthquakes Number of people affected by earthquakes per 100,000 Homelessness rate from earthquakes Total number of people affected by earthquakes per 100,000 Number of deaths from disasters Number of people injured from disasters Number of people affected by disasters Number of people left homeless from disasters Number of total people affected by disasters Reconstruction costs from disasters Insured damages against disasters Total economic damages from disasters Death rates from disasters Injury rates from disasters Number of people affected by disasters per 100,000 Homelessness rate from disasters Total number of people affected by disasters per 100,000 Number of deaths from volcanic activity Number of people injured from volcanic activity Number of people affected by volcanic activity Number of people left homeless from volcanic activity Number of total people affected by volcanic activity Reconstruction costs from volcanic activity Insured damages against volcanic activity Total economic damages from volcanic activity Death rates from volcanic activity Injury rates from volcanic activity Number of people affected by volcanic activity per 100,000 Homelessness rate from volcanic activity Total number of people affected by volcanic activity per 100,000 Number of deaths from floods Number of people injured from floods Number of people affected by floods Number of people left homeless from floods Number of total people affected by floods Reconstruction costs from floods Insured damages against floods Total economic damages from floods Death rates from floods Injury rates from floods Number of people affected by floods per 100,000 Homelessness rate from floods Total number of people affected by floods per 100,000 Number of deaths from mass movements Number of people injured from mass movements Number of people affected by mass movements Number of people left homeless from mass movements Number of total people affected by mass movements Reconstruction costs from mass movements Insured damages against mass movements Total economic damages from mass movements Death rates from mass movements Injury rates from mass movements Number of people affected by mass movements per 100,000 Homelessness rate from mass movements Total number of people affected by mass movements per 100,000 Number of deaths from storms Number of people injured from storms Number of people affected by storms Number of people left homeless from storms Number of total people affected by storms Reconstruction costs from storms Insured damages against storms Total economic damages from storms Death rates from storms Injury rates from storms Number of people affected by storms per 100,000 Homelessness rate from storms Total number of people affected by storms per 100,000 Number of deaths from landslides Number of people injured from landslides Number of people affected by landslides Number of people left homeless from landslides Number of total people affected by landslides Reconstruction costs from landslides Insured damages against landslides Total economic damages from landslides Death rates from landslides Injury rates from landslides Number of people affected by landslides per 100,000 Homelessness rate from landslides Total number of people affected by landslides per 100,000 Number of deaths from fog Number of people injured from fog Number of people affected by fog Number of people left homeless from fog Number of total people affected by fog Reconstruction costs from fog Insured damages against fog Total economic damages from fog Death rates from fog Injury rates from fog Number of people affected by fog per 100,000 Homelessness rate from fog Total number of people affected by fog per 100,000 Number of deaths from wildfires Number of people injured from wildfires Number of people affected by wildfires Number of people left homeless from wildfires Number of total people affected by wildfires Reconstruction costs from wildfires Insured damages against wildfires Total economic damages from wildfires Death rates from wildfires Injury rates from wildfires Number of people affected by wildfires per 100,000 Homelessness rate from wildfires Total number of people affected by wildfires per 100,000 Number of deaths from extreme temperatures Number of people injured from extreme temperatures Number of people affected by extreme temperatures Number of people left homeless from extreme temperatures Number of total people affected by extreme temperatures Reconstruction costs from extreme temperatures Insured damages against extreme temperatures Total economic damages from extreme temperatures Death rates from extreme temperatures Injury rates from extreme temperatures Number of people affected by extreme temperatures per 100,000 Homelessness rate from extreme temperatures Total number of people affected by extreme temperatures per 100,000 Number of deaths from glacial lake outbursts Number of people injured from glacial lake outbursts Number of people affected by glacial lake outbursts Number of people left homeless from glacial lake outbursts Number of total people affected by glacial lake outbursts Reconstruction costs from glacial lake outbursts Insured damages against glacial lake outbursts Total economic damages from glacial lake outbursts Death rates from glacial lake outbursts Injury rates from glacial lake outbursts Number of people affected by glacial lake outbursts per 100,000 Homelessness rate from glacial lake outbursts Total number of people affected by glacial lake outbursts per 100,000 Total economic damages from disasters as a share of GDP Total economic damages from drought as a share of GDP Total economic damages from earthquakes as a share of GDP Total economic damages from extreme temperatures as a share of GDP Total economic damages from floods as a share of GDP Total economic damages from landslides as a share of GDP Total economic damages from mass movements as a share of GDP Total economic damages from storms as a share of GDP Total economic damages from volcanic activity as a share of GDP Total economic damages from volcanic activity as a share of GDP Entity Year deaths_rate_per_100k_storm injured_rate_per_100k_storm total_affected_rate_per_100k_all_disasters

--- Original source retains full ownership of the source dataset ---

Homeless Shelter Capacity in Canada, bed and shelter counts by target population and geographical location for emergency shelters, transitional housing, and domestic violence shelters.

This dataset supports S.D.5 of SD23. This measure calculates how long it takes to adjudicate a case from the time when the case was filed. The Downtown Austin Community Court (DACC) is dedicated to processing cases efficiently and in alignment with nationally established time standards to reduce delay and ensure timely justice, but cases related to individuals experiencing homelessness typically take longer than 180 days to adjudicate due to the case management activities associated with these cases. Case management activities include but are not limited to acquiring birth certificates, Social Security cards, accessing substance use, mental health and medical services and acquiring permanent housing. Cases related to non-homeless individuals are typically adjudicated within 30-180 days. DACC monitors the length of time it takes to process cases and makes necessary adjustments to ensure compliance with time standards. View more details and insights related to this measure on the story page: https://data.austintexas.gov/stories/s/99up-wwsi The dataset for court cases adjudicated within case processing time standards covers a time period of Fiscal years 2016-first quarter of Fiscal year 2020. Data source: court's electronic case management system Calculation: Numerator-case disposition date Denominator- the date the case was filed. Measure Time Period: Quarterly (Fiscal Year)
Automated: no

Date of last description update: 4/1/2020

Analysis of ‘Strategic Measure_Number and Percentage of instances where people access court services other than in person and outside normal business hours (e.g. phone, mobile application, online, expanded hours) – Downtown Austin Community Court-Correspondence Cases’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/c60b624c-c627-4179-9759-7c7e3b4cfad4 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset supports measure S.D.4.b, S.D.6 of SD23. The Downtown Austin Community Court (DACC) was established to address quality of life and public order offenses occurring in the downtown Austin area utilizing a restorative justice court model. DACC offers alternatives to fines and fees for defendants to handle their cases such as community service restitution and participation in rehabilitation services. Defendants who reside outside of a 40-mile radius from DACC are offered an opportunity to handle their case through correspondence action, meaning the entire judicial process can be handled through email or postal mail. Correspondence action eliminates an undue burden requiring a defendant to travel back to Austin to appear for their case and it allows for quicker access to court services of Austin residents by reducing the number of individuals required to appear for their case. This measure tracks how many cases involving non-homeless individuals have been handled through correspondence action recorded in the court's case management system. The data source for number and percentage of instances where people access court services other than in person for DACC has a annual range based on fiscal year 2015- first quarter fiscal year 2020. View more details and insights related to this measure on the story page: https://data.austintexas.gov/stories/s/vxci-zmm3

Data source: Data for this measure is collected by DACC staff inputting information from citations issued in DACC’s jurisdiction and from court processes. All data is entered in DACC’s electronic court case management platform.

Calculation S.D.4.b Numerator= number of cases with the correspondence action/Denominator= total number of cases involving non-homeless individuals.

Measure Time Period: Annually (Fiscal Year)

Automated: no

Date of last description update: 4/1/2020

--- Original source retains full ownership of the source dataset ---

Percent distribution of homeless individuals by duration of homelessness, according to selected characteristics, Nipissing District, Ontario 2021.

For many residents, York Region is a wonderful place to live, work and play. A welcoming and prosperous community home to over 1.2 million people. Despite a thriving economy, a number of individuals and families struggle to secure safe and affordable housing. Reasons for homelessness are varied and complex, often intersecting with other societal issues, including systemic discrimination and the growing gap between household income and the rising cost of housing. The Regional Municipality of York and United Way Greater Toronto have a long-standing partnership and a commitment to creating healthy, safe and vibrant communities, and have collaborated to share updated data on homelessness in York Region through the Point-in-Time I Count 2021. Delayed by the pandemic and conducted under the constraints of COVID-19, this count overcame a number of obstacles, but they pale in comparison to the daily challenges faced by people experiencing homelessness during this crisis – tough lives made even more difficult. Together with the homelessness service sector, we have learned so much throughout the last few years. We’ve evolved our service provision, keeping pace with waves of COVID-19 and accompanying protocols to continue to meet urgent needs, even under these extenuating circumstances. We’ve understood what is possible when galvanized by this historic moment, working in closer collaboration than ever before. It is in this spirit we share the findings of I Count 2021 and commit to addressing the challenges before us, doing our part to move forward on recommendations in support of those facing homelessness.

The Downtown Austin Community Court (DACC) was established to address quality of life and public order offenses occurring in the downtown Austin area utilizing a restorative justice court model. DACC’s priority population consists of individuals experiencing homelessness and the program’s main goal is to permanently stabilize individuals experiencing homelessness. To effectively serve these individuals, DACC created an Intensive Case Management (ICM) Program, which uses a client-centered and housing-focused approach. The ICM Program focuses on rehabilitating and stabilizing individuals using an evidenced-based model of wraparound interventions to help them achieve long-term stability. Because individuals participating in case management are literally homeless, case managers must actively seek their clients in the community through outreach activities and often times work on behalf of the client via collateral engagement with other social service and housing providers. This measure highlights case management activities accomplished via outreach and collateral engagement.

Percent distribution of homeless individuals by reason for housing loss, according to selected characteristics, Nipissing District, Ontario 2021.

This dataset supports measure S.D.4.b, S.D.6 of SD23. The Downtown Austin Community Court (DACC) was established to address quality of life and public order offenses occurring in the downtown Austin area utilizing a restorative justice court model. DACC offers alternatives to fines and fees for defendants to handle their cases such as community service restitution and participation in rehabilitation services. Defendants who reside outside of a 40-mile radius from DACC are offered an opportunity to handle their case through correspondence action, meaning the entire judicial process can be handled through email or postal mail. Correspondence action eliminates an undue burden requiring a defendant to travel back to Austin to appear for their case and it allows for quicker access to court services of Austin residents by reducing the number of individuals required to appear for their case. This measure tracks how many cases involving non-homeless individuals have been handled through correspondence action recorded in the court's case management system. The data source for number and percentage of instances where people access court services other than in person for DACC has a annual range based on fiscal year 2015- first quarter fiscal year 2020. View more details and insights related to this measure on the story page: https://data.austintexas.gov/stories/s/vxci-zmm3

Data source: Data for this measure is collected by DACC staff inputting information from citations issued in DACC’s jurisdiction and from court processes. All data is entered in DACC’s electronic court case management platform.

Calculation S.D.4.b Numerator= number of cases with the correspondence action/Denominator= total number of cases involving non-homeless individuals.

Measure Time Period: Annually (Fiscal Year)

Automated: no

Date of last description update: 4/1/2020

The Downtown Austin Community Court (DACC) is dedicated to processing cases efficiently and in alignment with nationally established time standards to reduce delay and ensure timely justice, but cases related to individuals experiencing homelessness typically take longer than 180 days to adjudicate due to the case management activities associated with these cases. Case management activities include but are not limited to acquiring birth certificates, Social Security cards, accessing substance use, mental health and medical services and acquiring permanent housing. Cases related to non-homeless individuals are typically adjudicated within 30-180 days. DACC monitors the length of time it takes to process cases and makes necessary adjustments to ensure compliance with time standards.