In 2023, about **** percent of the estimated number of homeless individuals in the United States were male, compared to ** percent who were female.

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.

Yearly statewide and by-Continuum of Care total counts of individuals receiving homeless response services by age group, race, and gender. 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 7/15/2024.

As of 31 January 2024, 55 percent of homeless people in Germany were men. 43 percent were women and of around two percent, the gender was unknown. Therefore, more than half of the homeless people in homeless accommodation* were men.

In 2024, there were reported to be 3,858 men sleeping rough on a single night in England, and 680 women, with a further 129 people whose gender was not known. Between 2017 and 2024, the majority of rough sleepers reported in England have been men.

Gender demographics of the homeless population in the City of Corona, CA.

In 2023, about 2.1 percent of the estimated number of unaccompanied homeless youth in the United States were transgender. In comparison, 57.3 percent were male.

In 2023, about 87.8 percent of the estimated number of homeless veterans in the United States were male, compared to 11.2 percent who were female.

In 2024/25, ****** men were reported to be sleeping rough in London with a further ***** women, and ** non-binary people. Since 2010/11 there has been an increase in the number of people reported to be sleeping rough in London, increasing from almost ***** in 2010/11 to more than ****** by 2022/23. Throughout this time period, the majority of people seen to be sleeping rough in London have been men. Characteristics of homeless people in London Of the rough sleepers seen in London in 2023/24, the most common age group were those aged between 36 and 45, at *****. In terms of nationality, most rough sleepers were from the United Kingdom at ***** people, with Romanian being the second-highest nationality, at *** people. The London Borough which had the highest number of people sleeping rough was Westminster, at ***** people, while the borough of Sutton had the fewest rough sleepers, at **. Tragic implications of homelessness In 2021, *** homeless people in London lost their lives, which was the highest number of homeless deaths per region in England and Wales. In terms of the homeless death rate, the worst region was also London, at **** deaths per million people in 2021. North West England had the second-highest deaths per million people, at **. Between 2013 and 2019, the number of homeless deaths in England and Wales increased from 392 to ***, before falling to *** in 2020 and *** in 2021.

The Point In Time Unsheltered Homeless Census by Gender data. The Housing Inventory Count Submitted to the U.S. Department of Housing and Urban Development (HUD) Additional information available at: https://www.hudexchange.info/resources/documents/Notice-CPD-17-08-2018-HIC-PIT-Data-Collection-Notice.pdf 2017 data collected January 26, 2017, 2018 data collected February 22, 2018.

This statistic displays the gender distribution of the homeless population in South Korea in 2016. During the measured time period, men accounted for 73.5 percent of the entire population who did not have a permanent dwelling in South Korea.

Accommodated homeless persons: Germany, reference date, nationality, gender, age groups, providers

BC Stats (with partners at the Ministry of Housing, Ministry of Social Development and Poverty Reduction (SDPR), and BC Housing) has developed aggregated summary statistics estimating the homeless population in B.C. These estimates were derived from three administrative service use datasets from the Data Innovation Program (DIP): shelter use from BC Housing, social assistance payments from SDPR, demographic information from the Health medical service plan (MSP) central demographics file. The analytic definition of homelessness includes individuals who received income assistance with no fixed address for at least three consecutive months or those who visited a shelter at any time throughout the year. Estimates have been aggregated into four tables: * Annual estimates of the homeless population by age and gender * Annual estimates of the homeless population by chronicity category (chronic vs non-chronic homelessness) * Annual estimates of the homeless population by census division * Monthly estimates of the homeless population by service use (income assistance with no fixed address, shelter use, or both) \ Estimates are available for 2019-2022. Full methodology details are available in the Homeless Cohort Development - Technical Documentation resource.

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

The information is based on an annual statistical return completed by local authorities in Wales. The information is collected in order to establish the number and type of households that were provided with assistance by local authorities during the period. This data is used by the Welsh Government, homelessness agencies and other housing organisations, in order to help monitor trends in the overall level of statutory homelessness across Wales.

Analysis of ‘COVID-19 Deaths by Population Characteristics Over Time’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/60f5842f-a359-4b03-ad21-1bcfc3bf7fe6 on 13 February 2022.

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

Note: On January 22, 2022, system updates to improve the timeliness and accuracy of San Francisco COVID-19 cases and deaths data were implemented. You might see some fluctuations in historic data as a result of this change.

A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics and by date. Deaths are included on the date the individual died.

Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups.

Data is lagged by five days, meaning the most date included is 5 days prior to today. All data update daily as more information becomes available.

B. HOW THE DATASET IS CREATED COVID-19 deaths are suspected to be associated with COVID-19. This means COVID-19 is listed as a cause of death or significant condition on the death certificate.

Data on the population characteristics of COVID-19 deaths are from: * Case interviews * Laboratories * Medical providers

These multiple streams of data are merged, deduplicated, and undergo data verification processes. It takes time to process this data. Because of this, data is lagged by 5 days and death totals for previous days may increase or decrease. More recent data is less reliable.

Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

Data notes on each population characteristic type is listed below.

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases.

Sexual orientation * Sexual orientation data is collected from individuals who are 18 years old or older. These individuals can choose whether to provide this information during case interviews. Learn more about our data collection guidelines. * The City began asking for this information on April 28, 2020. Gender * The City collects information on gender identity using these guidelines.

Comorbidities * Underlying conditions are reported when a person has one or more underlying health conditions at the time of diagnosis or death.

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.

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.

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. * Facilities are mandated to report COVID-19 cases or deaths among their residents. The City follows up with these facilities to confirm.
* There may be differences between the City’s SNF data and the California Department of Public Health (CDPH) dashboard. The difference may be because the City and the State use dif

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

People experiencing homelessness often come from time- and labour-intensive cross-sectional counts and surveys from selected samples. This study uses comprehensive administrative health data from emergency department (ED) visits to enumerate people experiencing homelessness and characterize demographic and geographic trends in the province of Ontario, Canada, from 2010 to 2017. Data and methods People experiencing homelessness were identified by their postal code, designated as "XX." Outcomes included the number of people experiencing homelessness stratified by year and week, gender and age plotted annually, the location of each ED visit, and composition changes in demographics and geographic distribution

Accommodated homeless persons: Federal states, reference date, nationality, gender, age groups, type of assignment

The information is collected in order to establish the number and type of households that were accepted as homeless by local authorities during the period and the reasons why these households are homeless. It is also used to establish the number of homeless households in temporary accommodation and the types of accommodation provided. This data is used by the Welsh Government, homelessness agencies and other housing organisations, in order to help monitor trends in the overall level of statutory homelessness across Wales. Quality information 1. This data covers the age and sex of the applicant, not the age and sex of every person in the household. 2. Homelessness data may be subject to seasonal variations, however the data shown in this cube has not been seasonally adjusted and care should be taken when making comparisons between successive quarters. 3. All the figures are rounded independently to the nearest 5 to protect the identity of individuals. As a result, there may be a difference between the sum of the constituent items and the total. An asterisk is shown when the data item is disclosive or not sufficiently robust for publication.

Accommodated homeless persons: Germany, reference date, nationality, gender, age groups, household size