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

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.

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.

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).

Objectives: Homeless people lack a secure, stable place to live, and experience higher rates of serious illness than the housed population. Studies, mainly from the US, have reported increased use of unscheduled health care by homeless individuals. We compared the use of unscheduled ED and inpatient care between housed and homeless hospital patients in a high-income European setting. Setting: A large university teaching hospital serving the south inner city in Dublin, Ireland. Patient data is collected on an electronic patient record within the hospital. Participants: We carried out an observational cross-sectional study using data on all ED visits (n=47,174) and all unscheduled admissions under the general medical take (n=7,031) in 2015. Primary and Secondary Outcome Measures: The address field of the hospital’s electronic patient record was used to identify patients living in emergency accommodation or rough sleeping (hereafter referred to as homeless). Data on demographic details, length of stay and diagnoses was extracted. Results: In comparison to housed individuals in the hospital catchment area, homeless individuals had higher rates of ED attendance (0.16 attendances per person/annum vs 3.0 attendances per person/annum respectively) and inpatient bed days (0.3 bed days per person/annum vs 4.4 bed days per person/annum. The rate of leaving ED before assessment was higher in homeless individuals (40% of ED attendances vs 15% of ED attendances in housed individuals). The mean age of homeless medical inpatients was 44.19 (95% CI 42.98-45.40), whereas that of housed patients was 61.20 (95% CI 60.72-61.68). Homeless patients were more likely to terminate an inpatient admission against medical advice (15% of admissions vs 2% of admissions in homeless individuals). Conclusion: Homeless patients represent a significant proportion of ED attendees and medical inpatients. In contrast to housed patients, the bulk of usage of unscheduled care by homeless people occurs in individuals younger than 65.