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.

This database contains the data reported in the Annual Homeless Assessment Report to Congress (AHAR). It represents a point-In-time count (PIT) of homeless individuals, as well as a housing inventory count (HIC) conducted annually. The data represent the most comprehensive national-level assessment of homelessness in America, including PIT and HIC estimates of homelessness, as well as estimates of chronically homeless persons, homeless veterans, and homeless children and youth. These data can be trended over time and correlated with other metrics of housing availability and affordability, in order to better understand the particular type of housing resources that may be needed from a social determinants of health perspective. HUD captures these data annually through the Continuum of Care (CoC) program. CoC-level reporting data have been crosswalked to county levels for purposes of analysis of this dataset. For more information about these data, please see here .

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.

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<0.005) were more likely to report positive attitudes, whereas those from France and Poland (p<0.001) were less likely to report positive attitudes.ConclusionThe majority of European citizens hold positive attitudes towards people who are homeless, however there remain significant differences between and within countries. Although it is clear that there is strong support for increased government action and more effective solutions for Europe’s growing homelessness crisis, there also remain public opinion barriers rooted in enduring negative perceptions.

BackgroundHomelessness is one of the most disabling and precarious living conditions. The objective of this Delphi consensus study was to identify priority needs and at-risk population subgroups among homeless and vulnerably housed people to guide the development of a more responsive and person-centred clinical practice guideline.MethodsWe used a literature review and expert working group to produce an initial list of needs and at-risk subgroups of homeless and vulnerably housed populations. We then followed a modified Delphi consensus method, asking expert health professionals, using electronic surveys, and persons with lived experience of homelessness, using oral surveys, to prioritize needs and at-risk sub-populations across Canada. Criteria for ranking included potential for impact, extent of inequities and burden of illness. We set ratings of ≥ 60% to determine consensus over three rounds of surveys.FindingsEighty four health professionals and 76 persons with lived experience of homelessness participated from across Canada, achieving an overall 73% response rate. The participants identified priority needs including mental health and addiction care, facilitating access to permanent housing, facilitating access to income support and case management/care coordination. Participants also ranked specific homeless sub-populations in need of additional research including: Indigenous Peoples (First Nations, Métis, and Inuit); youth, women and families; people with acquired brain injury, intellectual or physical disabilities; and refugees and other migrants.InterpretationThe inclusion of the perspectives of both expert health professionals and people with lived experience of homelessness provided validity in identifying real-world needs to guide systematic reviews in four key areas according to priority needs, as well as launch a number of working groups to explore how to adapt interventions for specific at-risk populations, to create evidence-based guidelines.

Background: Homelessness is an increasing problem in Western European countries. In the Netherlands, policy reforms and austerity measures induced an urgent need for management information on local homeless citizens. Municipal authorities initiated cross-sectional reviews of Homeless Service (HS) users. The resulting Homeless People Treatment and Recovery (HOP-TR) study developed a health and needs assessment strategy over different domains to comprehensively assess individuals and care networks with the perspective on recovery.Methods: Dutch HS users were selected using a naturalistic meta-snowball sampling. Semi-structured interviews provided the primary data source. The interview content was partly derived from the InterRAI Community Mental Health questionnaire and the “Homelessness Supplement.” Using the raw interview data, algorithmic summary scores were computed and integrating clinical parameters assessed. The data describe health and needs in a rights-based, recovery-oriented frame of reference. The mental health approach is transdiagnostic. The positive health framework is used for structuring health and needs aspects in relation to the symptomatic (physical and mental health), social (daily living, social participation), and personal (quality of life, meaning) dimensions of recovery.Results: Recruitment (between 2015 and 2017) resulted in a saturated sample of 436 HS users in 16 facilities and seven cities. Most participants were long-term or intermittently homeless. The sample characteristics reveal the multi domain character of needs and the relevance of a broad, comprehensive approach. Local authorities used the reports to reflect and discuss needs, care provision, access, and network cooperation. These dialogs incited to improve the quality of care at various ecosystem levels.Discussion: This paper describes new recruitment strategies and data collections of comprehensive data domains, to improve our knowledge in the field of homelessness. Traditional epidemiological literature on homelessness is often domain specific and relies on administrative sources. The HOP-TR study uses an analytical epidemiological approach. It shifts the assessment focus from problem-centered marginalization processes toward a comprehensive, three-dimensional recovery-oriented vision of health. Different perspectives are integrated to explore the interaction of homeless people with care networks.

Background: Homeless people are a socially excluded group whose health reflects exposures to intersecting social determinants of health. The aim of this study was to describe and compare the demographic composition, certain social determinants of health, and self-reported health among homeless people in Stockholm, Sweden, in 2006 and 2018.Methods: Analysis of data from face-to-face interviews with homeless people in Stockholm 2006 (n = 155) and 2018 (n = 148), based on a public health survey questionnaire adapted to the group, including the EQ-5D-3L instrument. The chi-squared test was employed to test for statistical significance between groups and the independent t-test for comparison of mean scores and values. Ordinary Least Squares (OLS) regression, with Robust Standard Errors (RSE) was performed on merged 2006 and 2018 data with mean observed EQ VAS score as outcome variable.Results: In 2018 more homeless people originated from countries outside Europe, had temporary social assistance than long-term social insurance, compared to in 2006. In 2018 more respondents reported lack of social support, exposure to violence, and refrained from seeking health care because of economic reasons. Daily smoking, binge drinking, and use of narcotic drugs was lower 2018 than 2006. In 2018 a higher proportion reported problems in the EQ-5D-3L dimensions, the mean TTO index value and the VAS index value was significantly lower than in 2006. In the regression analysis of merged data there was no significant difference between the years.Conclusions: Homeless people are an extremely disadvantaged group, have high rates of illness and disease and report poor health in all EQ-5D-3L dimensions. The EQ VAS score among the homeless people in 2018 is comparable to the score among persons aged 95–104 years in the general Swedish population 2017. The EQ-5D-3L instrument was easily administered to this group, its use allows comparison with larger population groups. Efforts are needed regarding housing, but also intensified collaboration by public authorities with responsibilities for homeless people's health and social welfare. Further studies should evaluate the impact of such efforts by health and social care services on the health and well-being of homeless people.

This dataset "Global hotspots of climate related disasters" shows the number of people impacted by climate-related disasters recorded in the EM-DAT database between 2000 and 2020. This dataset was used to prepare the maps and the analysis of the paper Donatti C.I., Nicholas K., Fedele G., Delforge D., Speybroeck N., Moraga P., Blatter J., Below R., Zvoleff A. 2024. Global hotspots of climate-related disasters. International Journal of Disaster Risk Reduction. https://doi.org/10.1016/j.ijdrr.2024.104488. This dataset includes information on people impacted by Drought, tropical cyclones, flash flood, riverine flood, forest fire, land fire, heat wave, landslide and mudslide. Data on coastal flood was not included because the database only had recordings until 2013. Data on disaster sub-types “landslides” and “mudslides” as presented in the EM-DAT were further combined as one single climate-related disaster (“land and mudslides”) for the analyses. Likewise, data on disaster sub-types “forest fire” and “land fire” were further combined as one climate-related disaster (“wildfire”). The data was accessed directly from the EM-DAT database and then summarized as show in the dataset. We used this database, downloaded on June 2nd 2021, to access data on “total affected” people and the “total deaths” per disaster event impacting a country (i.e., an entry in the EM-DAT), which were combined in this study to create the variable “total people impacted”. In the EM-DAT database, “total affected” represents the sum of people “injured,” “affected,” and “homeless” resulting from a particular event. “Injured” were considered those that have suffered from physical injuries, trauma, or an illness requiring immediate medical assistance, including people hospitalized, as a direct result of a disaster, “affected” were considered people requiring immediate assistance during an emergency and “homeless” were considered those whose homes were destroyed or heavily damaged and therefore needed shelter after an event. “Total deaths” include people that have died or were considered missing, those whose whereabouts since the disaster were unknown and presumed dead based on official figures. More details can be found under “documentation, data structure and content description” at emdat.be. In the dataset, "ADM-CODE" refers to the code used to identify each administrative area, which refers to the code of FAO's Global Administrative Unit Layer, GAUL.

Abstract (en): The DC Metropolitan Area Drug Study (DC*MADS) was conducted in 1991, and included special analyses of homeless and transient populations and of women delivering live births in the DC hospitals. DC*MADS was undertaken to assess the full extent of the drug problem in one metropolitan area. The study was comprised of 16 separate studies that focused on different sub-groups, many of which are typically not included or are underrepresented in household surveys. The Homeless and Transient Population study examines the prevalence of illicit drug, alcohol, and tobacco use among members of the homeless and transient population aged 12 and older in the Washington, DC, Metropolitan Statistical Area (DC MSA). The sample frame included respondents from shelters, soup kitchens and food banks, major cluster encampments, and literally homeless people. Data from the questionnaires include history of homelessness, living arrangements and population movement, tobacco, drug, and alcohol use, consequences of use, treatment history, illegal behavior and arrest, emergency room treatment and hospital stays, physical and mental health, pregnancy, insurance, employment and finances, and demographics. Drug specific data include age at first use, route of administration, needle use, withdrawal symptoms, polysubstance use, and perceived risk. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Created variable labels and/or value labels.; Standardized missing values.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. Response Rates: The institutional response rate (i.e., for shelters and soup kitchens) was 82.6 percent. The individual interview response rate was 86.1 percent. The overall response rate was 71 percent. Persons aged 12 and older in the DC MSA who were either literally homeless or at imminent risk of becoming homeless, including persons who spent the previous night in an emergency shelter, in a nondomicile (e.g., vacant building, city park, car, or on the street) or who were using soup kitchens or emergency food banks. The Homeless and Transient Population study consisted of 908 interviews from four overlapping sampling frames: 477 interviews with residents in 93 shelters, 224 interviews with patrons of 31 soup kitchens and food banks, 143 interviews with "literally homeless" people from 18 major cluster encampments, and 64 interviews with literally homeless people from an area probability sample of 432 census blocks in the MSA. People who were cognitively impaired and could not complete the interview were excluded from the survey. Impairment was defined as extreme intoxification or scoring more than nine on the Short Blessed Exam (Katzman, Brown, Fuld, Peck, Schecter, and Schimmel, 1983). 2008-07-24 New files were added. These files included one or more of the following: Stata setup, SAS transport (CPORT), SPSS system, Stata system, SAS supplemental syntax, and Stata supplemental syntax files, and a tab-delimited ASCII data file. Also, the CASEID variable has been added to the dataset.2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions. Funding insitution(s): United States Department of Health and Human Services. National Institutes of Health. National Institute on Drug Abuse. Produced by Research Triangle Institute in Research Triangle Park, NC.

ABSTRACT This study aimed to identify the state of the art on the health care of homeless persons in the daily life of Primary Health Care. The scoping review method proposed by the Joanna Briggs Institute (JBI) was adopted, and the PRISMA Extension for Scoping Reviews (PRISMA-ScR) checklist was used for greater methodological transparency and rigor in the presentation of results. The database search took place in October 2021, and included PubMed, LILACS, Scopus, Cochrane Central, Web of Science and CINAHL. A total of 21.940 articles were found in the six databases, of which 31 articles constituted the final sample of this study. This review corroborated that the health care of homeless persons is a public health challenge and requires more professional investment and cross-cutting policies. As the health needs of these people have a different configuration and call for immediate attention, building a bond and developing health promotion actions is a challenge, considering the multifactorial and multifaceted aspects that involve homeless persons.

Abstract

The central focus of the National Baseline Household Survey for the year 2009 (NBHS 2009) is to provide indicators and reference statistics for the living condition of all Sudanese. The NBHS 2009 was conducted in all the 25 States of Sudan in a uniform way whereas CBS collected and processed the data for the 15 Northern States and the Southern Sudan Centre for Census, Statistics and Evaluation (SSCCSE) had similar responsibility for the 10 Southern States. The current report covers the 15 Northern States of Sudan.

The objective with the present document is to summarize the findings from all parts of the extensive NBHS 2009 survey questionnaire. Hopefully this will inspire for further and deeper special analyses of this vast dataset.

Geographic coverage

This survey is representative for the 15 states of Northern Sudan, including urban and rural areas.

Analysis unit

Households and individuals.

Universe

The survered covered all private households and their memebers. It did not cove special types of households such as institutional households (hostels, hospitals etc), refugee camps, IDP camps, cattle camps, and homeless people.

Kind of data

Données échantillonées [ssd]

Sampling procedure

The sample selected for the NBHS2009 was based on a stratified two stage sampling procedure. The preliminary count of households per enumeration area (EA) as well as the cartographic work from the 2008 National Population and Housing Census were used as the sampling frame. The EAs from the census constituted the primary sampling units. For the NBHS2009, the Census EAs were stratified by urban and rural in each State. Some of the sample EAs could not be covered because of security or other problems, in which case they were replaced by EAs within the same geographical areas. In addition, the sample did not include nomadic population due to lack of proper sampling frame for them and problems of accessibility. Also institutional households, camps etc as well as the homeless part of the population were excluded from the sample.

A second sampling stage was conducted by listing all households within the selected EAs in the sample and thereafter selecting a fixed random sample of 12 households to be interviewed. A total sample size of 528 households in each State was distributed into 44 primary sampling units (PSUs).

The sample size was designed to obtain reliable estimates for key survey variables at the State level and for urban and rural domains at the national level, the State 15 level and the State 10 level.

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire was designed in English and translated into Arabic with the same wording and modules. It was distributed to the respondents in Arabic only.

In addition a comprehensive field manual (English) was prepared to assist the fieldworkers in filling out each section of the questionnaire. A summary manual was translated to Arabic and used for the training in the 15 Northern States.

The questionnaire was designed for Optical Character Recognition (OCR) using a commonly available software. It was printed on standard 80 grams A4 paper and stapled to a booklet.

A technical working group was established in July 2008. This group oversaw the development of the questionnaire, with inputs from different stakeholders and technical consultants.

Cleaning operations

The questionnaires for the 15 Northern states were scanned centrally at CBS premises in Khartoum. A high capacity scanner and optical character recognition (OCR) software were used. Approximately 96-97% of all characters filled in was automatically interpreted and entered into the software internal database. The scanning procedure included manual on-screen verification of remaining data that could not be automatically interpreted. Finally, the scanned data were exported as ASCII files with corresponding digital images of each questionnaire. The data files were converted, further processed/edited and also tabulated using the software SPSS/PASW.

The NBHS2009 was edited as a combination of post-scanning automated edits and manual back-checks on electronic images (TIF-files) stored for each questionnaire. The latter mainly used for verifying outliers due to possible scanning or fieldworker errors.

The automated edits were pre-programmed to identify and correct consistency errors within each thematic section of the questionnaire and, especially for age related variables (marital status, education and work), also across section checks were applied.

Outliers were defined as outside the range of MEAN +/- 3 x STDV of actual variable in stratum. Outliers were listed and, unless manual intervention from subject matter specialist, the outliers were automatically imputed to MEDIAN value of stratum. However, for the very thorough edits of the questionnaire section M (purchase and consumption) additional information on local market prices were used to correct the raw data.

If skip was missing or inconsistent with responses given in the related detailed question, the detailed question response overruled the skip and the skip was adjusted.

The difficulties with achieving consistency between age and level of current school attending was approached by introducing a predefined acceptable age range with upper and lower cut-off for each level of school from Primary 1 to University. People defined too old for a certain school level reported, was corrected to “not currently attending” and the initially reported school level was imputed in the “highest ever school level” variable.

To keep track of the amount and type of edits done, all variables with automated or manual intervention were flagged.

Two cleaned data master files are produced from the NBHS2009. One file with individuals distributed (section B-D) and one file with households distribute (E-O). In addition special files are produced for commodities (section M) used for poverty and food security calculation and for the agriculture (section N) concerning crop production and structures.

There were some challenges encountered in the implementation of the survey: · Change from Quick Baseline Poverty Survey (QBPS) to the NBHS concept resulted in addition of other modules that inflated the questionnaire which involved much more work and additional funds were required to conduct the survey · Delay of transfer of filed work budget to the CBS statistical offices at the states to almost one month had delayed the start of data collection stage from April to May 2009. · Due to insecurity situations in some parts of Darfur region; six clusters in South Darfur, three in North Darfur and one in West Darfur were replaced in the same geographical areas. In addition, due to respondents refusal to cooperate with the field work teams in two EAs (clusters) one in each of Blue Nile and Nahr Elnil states, these selected EAs were replaced and the field work was completed. · The collection of consumption information for some items was made especially hard by the lack of standardized units of measurement in North Sudan. Because, consumption of these items is sourced in non-standardized units (such as heaps, cups, bundles, rubu etc.), it is hard to calculate consumption in standardized comparable units (such as kilograms and litres). Accordingly, the questionnaire allowed respondents to report consumption in non-standardized units. A market survey, conducted at state level, provided specific conversion factors for the non-standardized measurement units. While this was the only feasible solution, it may still be prone to non-trivial measurement errors.

Response rate

The response rate for the NBHS 2009 15 Northern States, including replacements, is 99.9.

At least 116 people killed, more than 68 missing and over 13,500 left homeless in Nicaragua. At least 1,300 houses and 185 fishing boats were destroyed along the west coast of Nicaragua.

PurposeHomeless persons have a high risk for tuberculosis. The prevalence of latent tuberculosis infection and the risk for a progression to active tuberculosis is higher in the homeless than in the general population. The objective was to assess the prevalence and risk factors of tuberculosis/latent tuberculosis infection in a homeless population in Germany.MethodsHomeless individuals (n = 150) were enrolled in a cross-sectional study at three shelters in Münster, Germany (October 2017–July 2018). All participants were screened using an ELISPOT interferon-γ release assay (IGRA). Those participants tested positive/borderline by IGRA provided three sputa for microbiological analysis (line probe assay, microscopy, culture) and underwent a chest X-ray to screen for active pulmonary TB. Risk factors for tuberculosis/latent tuberculosis infection were analysed using a standardized questionnaire.ResultsOf the 142 evaluable IGRA, 21 (15%) were positive and two (1%) were borderline. No participant with a positive/borderline IGRA had an active tuberculosis as assessed by chest X-ray and microbiology. A negative IGRA was associated with a citizenship of a low-incidence country for tuberculosis (according to WHO, p = 0.01), low-incidence country of birth (p<0.001) or main residence in a low-incidence country in the past five years (p = 0.002).ConclusionsThe prevalence of latent tuberculosis infection (diagnosed by a positive/borderline IGRA) was 16%; no active tuberculosis was detected. The highest risk for latent tuberculosis infection was found in patients from high-incidence countries. This population at risk should be either treated for latent tuberculosis infection or need to be monitored to early detect a progression into active disease.

Rao-Scott chi-square statistic and p-values for group comparisons on prevalence of mental disorder.

Demographic characteristics by level of criminal-legal involvement.