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.

"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."

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.

"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."

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 ****.

The graph displays the estimated number of homeless people in the United States from 2007 to 2024. The x-axis represents the years, ranging from 2007 to 2023, while the y-axis indicates the number of homeless individuals. The estimated homeless population varies over this period, ranging from a low of 57,645 in 2014 to a high of 771,000 in 2024. From 2007 to 2013, there is a general decline in numbers from 647,258 to 590,364. In 2014, the number drops significantly to 57,645, followed by an increase to 564,708 in 2015. The data shows fluctuations in subsequent years, with another notable low of 55,283 in 2018. From 2019 onwards, the estimated number of homeless people generally increases, reaching its peak in 2024. This data highlights fluctuations in homelessness estimates over the years, with a recent upward trend in the homeless population.

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.

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.

"Ratio of Homeless Population to General Population in major US Cities in 2011.

*This represents a list of large U.S. cities for which DHS was able to confirm a recent estimate of the unsheltered population. A 2011 result is available for Seattle, WA, Miami, FL, and Boston, MA.. 2011 results are not yet available for the other cities, and their 2009 data are displayed in this chart. General population figures are 2010 estimates in New York, San Francisco, and Chicago, and 2009 estimates elsewhere."

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

BackgroundEnsuring effective access to vaccinations for people experiencing homelessness is crucial to protecting the health of a vulnerable, yet often overlooked population. Reaching this goal takes more than a one size fits all approach. This study evaluates how a dedicated health team collaborated with multiple agencies to register and deliver the COVID-19 vaccine to people experiencing homelessness.MethodsThis is a mixed methods study co-designed with the Adult Homeless Integrated Team, a multi-disciplinary team who work with local agencies to provide care to people experiencing homelessness in Cork, Ireland’s second largest city. Quantitative data collected at the point of vaccine registration described socio-demographics of the population. To explain the quantitative findings, eleven agencies involved in provision of homeless services were invited to participate in interviews. A manager in each of the agencies acted as a gatekeeper to clients. Interviews explored experiences with the pandemic and the delivery (staff) or receipt (clients) of the COVID-19 vaccine. Interviews were recorded and transcribed, transcriptions were thematically analysed.ResultsThere were 728 vaccine doses administered to people experiencing homelessness during the first roll-out of vaccines; 401 first doses and 325 second doses. Of those who received a vaccine, the majority were male (76%), and more than half were Irish (55%). Ten semi-structured interviews, seven staff members and three clients, were conducted. There were three themes that provided further insights into the quantitative findings: Adapting to unprecedented times, Misinformation causing vaccine hesitancy and The importance of building relationships.ConclusionsThis study provides valuable insights into how a multidisciplinary approach resulted in a successful well received vaccination programme among a traditionally hard to reach group.

In 2023, there were about ****** homeless youth living in California, the most out of any U.S. state. New York had the second-highest number of homeless youth in that year, at *****.

"Ratio of Homeless Population to General Population in major US Cities in 2010.

*This represents a list of large U.S. cities for which DHS was able to confirm a recent estimate of the unsheltered population. A 2010 result is only available for Seattle, WA. Other cities either did not conduct a count in 2010, or their 2010 results are not yet available. 2009 unsheltered census figures were used for Los Angeles, San Francisco, Miami, and Washington, DC, and Boston; the 2007 estimate is used for Chicago. General population figures are the latest estimates from the U.S. Census Bureau."

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

The County of Sonoma conducts an annual homeless count for the entire county. The survey data is derived from a sample of about 600 homeless persons countywide per year. The resulting information is statistically reliable only for the county as a whole, not for individual locations. The exception is the City of Santa Rosa, where the sample taken within the city is large enough to be predictive of the overall homeless population in that city.

Community integration of homeless in a Cologne suburb. Topics: Characterization of the suburb Poll; closeness with the suburb or with the city of Cologne; length of residence in the suburb; previous place of residence and moving frequency; rent costs; size of household and number of rooms; possession of durable economic goods; year of construction of building; satisfaction with residence; moving plans; possible destination of moving; particular advantages of the residential area in Poll; favorite part of town of Cologne; familial relations in the part of town or in the entire city; frequency of contact with parents, grandparents, children, siblings and the rest of the relatives; distribution of circle of friends about the part of town and the other parts of the city; contacts with neighbors and colleagues; location of place of work; frequency of change of place of work; occupational mobility; desire for remaining in the part of town given a change of occupation; shopping habits; frequency of trips downtown; leisure activities and place of these leisure activities; club membership; time extent of club activity; participation in activities of the Poll Buergerverein; significance of this organization; judgement on the moving of schools; most influencial personalities in the suburb; most important integration factors in the part of town; influence of the part of town on the entire city; anomy (scale); evaluation of despicability of selected crimes; most important reasons for development of so-called Rocker groups; most effective measures to reduce crime; perceived differences in the old and new part of town; identification of areas that belong together in the part of town and assignment of different social groups to the parts of town; assignment of social groups to the homeless settlement; significance of the homeless problem and preferred measures to eliminate it; measures to prevent homelessness; attitude to differential treatment of the homeless and the rest of the population; recommendations on treatment of the homeless; judgement on the proportion of homeless in the part of town; personal contacts with the homeless; intensity of contacts; fear of contact and social distance to the homeless; preferred measures in view of the two homeless settlements in Poll; perceived differences among the homeless; typical characteristics with which one can recognize the homeless; judgement on a media report about the homeless in Poll; judgement on the municipal facilities in the part of town; personal importance of the existence of such facilities; religiousness. Interviewer rating: residential building size and willingness of respondent to cooperate. Gemeindliche Integration von Obdachlosen in einem Kölner Vorort. Themen: Charakterisierung des Vororts Poll; Verbundenheit mit dem Vorort oder mit der Stadt Köln; Wohndauer im Vorort; vorheriger Wohnort und Umzugshäufigkeit; Mietkosten; Haushaltsgröße und Anzahl der Räume; Besitz langlebiger Wirtschaftsgüter; Baujahr des Hauses; Zufriedenheit mit der Wohnung; Umzugspläne; mögliches Umzugsziel; besondere Vorzüge der Wohnlage in Poll; beliebtester Stadtteil von Köln; verwandtschaftliche Beziehungen im Stadtteil bzw. in der gesamten Stadt; Kontakthäufigkeit mit den Eltern, Großeltern, Kindern, Geschwistern und den übrigen Verwandten; Verteilung des Bekanntenkreises über den Stadtteil und die übrigen Teile der Stadt; Kontakte zu Nachbarn und Arbeitskollegen; Ortslage der Arbeitsstätte; Häufigkeit des Wechselns der Arbeitsstätte; berufliche Mobilität; Wunsch nach Verbleiben im Stadtteil bei Berufswechsel; Einkaufsgewohnheiten; Besuchshäufigkeit in der City; Freizeitaktivitäten und Ort dieser Freizeitaktivitäten; Vereinsmitgliedschaft; zeitlicher Umfang von Vereinstätigkeit; Teilnahme an Aktivitäten des Poller Bürgervereins; Bedeutung dieses Vereins; Beurteilung der Verlegung von Schulen; einflußreichste Persönlichkeiten im Vorort; wichtigste Integrationsfaktoren im Stadtteil; Einfluß des Stadtteils auf die ganze Stadt; Anomie (Skala); Bewertung der Verwerflichkeit von ausgewählten Straftaten; wichtigste Ursachen für das Entstehen sogenannter Rockergruppen; wirksamste Maßnahmen zur Reduzierung der Kriminalität; perzipierte Unterschiede im alten und neuen Stadtteil; Identifizierung zusammengehörender Gebiete im Stadtteil und Zuordnung unterschiedlicher sozialer Gruppen zu den Stadtteilen; Zuordnung sozialer Gruppen zur Obdachlosensiedlung; Bedeutung des Obdachlosenproblems und präferierte Maßnahmen zur Beseitigung; vorbeugende Maßnahmen zur Verhinderung von Obdachlosigkeit; Einstellung zur differenzierten Behandlung von Obdachlosen und der übrigen Bevölkerung; Vorschläge zur Behandlung von Obdachlosen; Beurteilung des Obdachlosenanteils im Stadtteil; eigene Kontakte zu Obdachlosen; Intensität der Kontakte; Berührungsängste und soziale Distanz zu Obdachlosen; präferierte Maßnahmen im Hinblick auf die beiden Obdachlosensiedlungen in Poll; perzipierte Unterschiede bei den Obdachlosen; charakteristische Merkmale, an denen man Obdachlose erkennen kann; Beurteilung eines Medienberichts über die Obdachlosen in Poll; Beurteilung der kommunalen Einrichtungen im Stadtteil; persönliche Wichtigkeit der Existenz solcher Einrichtungen; Religiosität. Demographie: Alter; Familienstand; Kinderzahl; Kirchgangshäufigkeit; Schulbildung; Berufstätigkeit; Einkommen; Haushaltsgröße. Interviewerrating: Wohnhausgröße und Kooperationsbereitschaft des Befragten.

ABSTRACT In this paper I present results of a project that, in the context of critical discourse studies and the interdiscursive analysis of public policies, focused on representations in online journalism regarding public policies aimed at the homeless population. The research project (CAPES 88881.172032/2018-01) was developed at the Pompeu Fabra University, Spain. Considering the main newspaper of the city of São Paulo, in its digital platform, we have compiled a comprehensive corpus of news about homeless situation published in a period of three years. The choice to specifically address data from Folha de S Paulo is justified because it is the city with the largest homeless population in Brazil. Also, because our previous study has shown that this is the vehicle, among those studied, that publishes more news related to territorial issues, our focus of interest to investigate via the discursive categories of metaphor and representation of social actors.

In 2022, about ****** veterans living in California were homeless, the most out of all U.S. states.

The social situation of the homeless in a Cologne suburb. Topics: Most important problems in the settlement; problems in the relationship between the settlement and surroundings; plans to leave; length of residence in the settlement and year of first utilization of a city shelter; reason for admission into a city shelter; type of quarters on first admission and before admission; frequency of moving into such accomodations and settlements; perceived deterioration from the move; number of rooms; possession of durable economic goods; defects in residence; number of children and schools attended or kindergarten; attitude to establishment of a special school in the part of town; perceived discrimination of one´s children in school; regular pocket-money for the children; place of leisure time of one´s children; contacts of one´s children outside of the settlement; person raising the children; perceived discrimination of the homeless; exercise of an honorary activity in the settlement; attitude to a self-help committee in the settlement; interest in participation in such a committee; assumed effectiveness of a community of interests of the homeless; most important tasks of such a community of interests; most important institutions as contact to improve the situation of the homeless; location of place of work; frequency of change of job; change of occupation; satisfaction with place of work; shopping place; possession of savings; manager of family income; decision-maker for expenditures; debts; eating main meal together; leisure activities in the settlement; contact persons in leisure time; leisure contacts outside the settlement; neighborhood contacts in the settlement; contacts with non-homeless; establishing these contacts on leisure time or through work; identification as Cologne resident or resident of the part of town; desire to move to another part of town; favorite part of town in Cologne; intensity of contact with the population in the part of town; contacts with residents of another settlement; participation in meetings of the Poll Buergerverein; assumed representation of interests of the homeless through this organization; most influencial personalities in the part of town; persons making a particular effort for the homeless; most important differences between the residents of one´s own settlement and another settlement in the part of town; knowledge of press reports and television reports about the homeless and judgement on validity; most important reasons for homelessness; most important measures to prevent homelessness; perceived differences between the homeless; filing a complaint against the city to obtain better housing; experiences with contacts with authorities; satisfaction with the manager of the settlement; most important task of a manager; anomy (scale); comparison of personal housing situation with that of parents; social origins; social mobility compared with father and father-in-law; contacts with relatives; judgement of relatives about living in this settlement; relatives likewise living in emergency shelters; personal condition of health; number of sick family members and type of illnesses; recommendations on dealing with the homeless; society or the individual as responsible for one´s own homelessness; desire for integration in a normal residential area; personal extent of commiting crimes and conviction; type of offenses; perceived improvement in living conditions in the emergency shelter; comparison of the situation between the settlement and a temporary shelter; place of birth; length of residence in Cologne; re-married; religiousness; club memberships; extent of club activity; party preference; assumed effectiveness of this survey on the situation of the homeless. Interviewer rating: name sign on door; description of residential furnishings regarding family pictures, other pictures, knick-knacks, religious figures and possession of books; condition of windows, wallpaper and furniture; length of interview; number of persons present during interview; carrying out house work by the person interviewed during the interview; conduct of other persons present during the conversation; willingness of respondent to cooperate.

Rapid serological testing results for SARS-CoV-2 (N = 1,156).

In 2024/25, there were ***** rough sleepers reported in Westminster, making it the London borough with the highest number of rough sleepers in that year. Other boroughs which also had a high number of homeless people included, Camden, Ealing, and Southwark.