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.

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.

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.

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 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.

Homelessness or houselessness – also known as a state of being unhoused or unsheltered – is the condition of lacking stable, safe, and adequate housing. The definition of homelessness differs from country to country, with some countries yet to have any definition in place.

@article{owidhomelessness, author = {Esteban Ortiz-Ospina and Max Roser}, title = {Homelessness}, journal = {Our World in Data}, year = {2017}, note = {https://ourworldindata.org/homelessness} }

The number of people left homeless due to wildfires in 2023 amounted to 81, a considerable decrease when compared to the figures of 2022 and 2021, when 3,933 and 4,893 people lost their homes due to such disasters.

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 ---

Project Overview This study used a community-based participatory approach to identify and investigate the needs of people experiencing homelessness in Dublin, Ireland. The project had several stages: A systematic review on health disparities amongst people experiencing homelessness in the Republic of Ireland; Observation and interviews with homeless attendees of a community health clinic; and Interviews with community experts (CEs) conducted from September 2022 to March 2023 on ongoing work and gaps in the research/health service response. This data deposit stems from stage 3, the community expert interview aspect of this project. Stage 1 of the project has been published (Ingram et al., 2023.) and associated data are available here. De-identified field note data from stage 2 of the project are planned for sharing upon completion of analysis, in January 2024. Data and Data Collection Overview A purposive, criterion-i sampling strategy (Palinkas et al., 2015) – where selected interviewees meet a predetermined criterion of importance – was used to identify professionals working in homeless health and/or addiction services in Dublin, stratified by occupation type. Potential CEs were identified through an internet search of homeless health and addiction services in Dublin. Interviewed CEs were invited to recommend colleagues they felt would have relevant perspectives on community health needs, expanding the sample via snowball strategy. Interview questions were based on World Health Organization Community Health Needs Assessment guidelines (Rowe at al., 2001). Semi-structured interviews were conducted between September 2022 and March 2023 utilising ZOOM™, the phone, or in person according to participant preference. Carolyn Ingram, who has formal qualitative research training, served as the interviewer. CEs were presented with an information sheet and gave audio recorded, informed oral consent – considered appropriate for remote research conducted with non-vulnerable adult participants – in the full knowledge that interviews would be audio recorded, transcribed, and de-identified, as approved by the researchers’ institutional Human Research Ethics Committee (LS-E-125-Ingram-Perrotta-Exemption). Interviewees also gave permission for de-identified transcripts to be shared in a qualitative data archive. Shared Data Organization 16 de-identified transcripts from the CE interviews are being published. Three participants from the total sample (N=19) did not consent to data archival. The transcript from each interviewee is named based on the type of work the interviewee performs, with individuals in the same type of work being differentiated by numbers. The full set of professional categories is as follows: Addiction Services Government Homeless Health Services Hospital Psychotherapist Researcher Social Care Any changes or removal of words or phrases for de-identification purposes are flagged by including [brackets] and italics. The documentation files included in this data project are the consent form and the interview guide used for the study, this data narrative and an administrative README file. References Ingram C, Buggy C, Elabbasy D, Perrotta C. (2023) “Homelessness and health-related outcomes in the Republic of Ireland: a systematic review, meta-analysis and evidence map.” Journal of Public Health (Berl). https://doi.org/10.1007/s10389-023-01934-0 Palinkas LA, Horwitz SM, Green CA, Wisdom JP, Duan N, Hoagwood K. (2015) “Purposeful sampling for qualitative data collection and analysis in mixed method implementation research.” Administration and Policy in Mental Health. Sep;42(5):533–44. https://doi.org/10.1007/s10488-013-0528-y Rowe A, McClelland A, Billingham K, Carey L. (2001) “Community health needs assessment: an introductory guide for the family health nurse in Europe” [Internet]. World Health Organization. Regional Office for Europe. Available at: https://apps.who.int/iris/handle/10665/108440

This round of Eurobarometer surveys diverged from the Standard Eurobarometer measures and queried respondents on the following major areas of focus: (1) poverty and social exclusion, (2) social services, (3) climate change, and (4) the national economic situation and statistics. For the first major focus, poverty and social exclusion, respondents were queried about their own definition of poverty, the extent of poverty in their area, trends in the growth or decline of poverty in their area and in the world, social and personal causes of poverty and homelessness, and negative effects of poverty. Questions also included the risk of poverty for themselves and others, the importance of governmental wealth redistribution, social tension between groups, trust in individual people, trust in and reliability of institutions in fighting poverty, minimal acceptable living standards, and the level of homelessness in their area. In addition, respondents were queried on their ability to keep their job, the relationship between their job and their family, their own personal aid to help the poor, access to financial services, the respondents' satisfaction with life, and the respondents' own living conditions and income. For the second major focus, social services, respondents were asked about such services as long term care, childcare, public employment, social housing, and social assistance. Questions focused on how much they or others around them use social services, the quality and affordability of social services, preferences for elderly care and childcare, the prioritization of group assistance, and the financing of social services. For the third major focus, climate change, respondents were asked about the seriousness of climate change, governmental attempts to fight climate change, personal actions taken to fight climate change, and the relationship between environmental protection and economic growth. Finally, for the fourth major focus, the national economic situation and statistics, respondents were asked to estimate their country's official growth rate, inflation rate, and unemployment rate, and were asked to give their opinions on the importance and trustworthiness of economic statistics. Respondents were also queried on the employment and economic situations in their country. Demographic and other background information includes left-right political placement, occupation, age, gender, marital status, age at completion of full-time education, household composition, ownership of a fixed or a mobile telephone and other durable goods, internet usage, financial situation, level in society, minority group affiliation, region of residence, type and size of locality, and language of interview (in select countries).

The re-emergence of tuberculosis (TB) in the mid-1980s in many parts of the world, including the United States, is often attributed to the emergence and rapid spread of human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS). Although it is well established that TB transmission is particularly amplified in populations with high HIV prevalence, the epidemiology of interaction between TB and HIV is not well understood. This is partly due to the scarcity of HIV-related data, a consequence of the voluntary nature of HIV status reporting and testing, and partly due to current practices of screening high risk populations through separate surveillance programs for HIV and TB. The San Francisco Department of Public Health, TB Control Program, has been conducting active surveillance among the San Francisco high-risk populations since the early 1990s. We present extensive TB surveillance data on HIV and TB infection among the San Francisco homeless to investigate the association between the TB cases and their HIV+ contacts. We applied wavelet coherence and phase analyses to the TB surveillance data from January 1993 through December 2005, to establish and quantify statistical association and synchrony in the highly non-stationary and ostensibly non-periodic waves of TB cases and their HIV+ contacts in San Francisco. When stratified by homelessness, we found that the evolution of TB cases and their HIV+ contacts is highly coherent over time and locked in phase at a specific periodic scale among the San Francisco homeless, but no significant association was observed for the non-homeless. This study confirms the hypothesis that the dynamics of HIV and TB are significantly intertwined and that HIV is likely a key factor in the sustenance of TB transmission among the San Francisco homeless. The findings of this study underscore the importance of contact tracing in detection of HIV+ individuals that may otherwise remain undetected, and thus highlights the ever-increasing need for HIV-related data and an integrative approach to monitoring high-risk populations with respect to HIV and TB transmission.

In 2011, about ** percent of the total population in India was homeless. Urban areas witnessed more homelessness in comparison to the rural areas of the country. Homelessness is a growing issue in India that leads to various other problems like violence and drug addiction among others.

Nearly 11.3 thousand people in Russia were homeless, based on the population census data from 2021. The number of homeless residents decreased by 82 percent compared to 2010. The largest share of homeless people in the country lived in urban areas, at around 95 percent in 2021.

A survey of homeless adults in California found that around 82 percent reported they had experienced some mental health condition at some point in their lifetime. This statistic shows the percentage of homeless adults in California with select mental health conditions at some point in life as of 2022.

Abstract (en): This round of Eurobarometer surveys diverged from the Standard Eurobarometer measures and queried respondents on the following major areas of focus: (1) poverty and social exclusion, (2) mobile phone use, (3) economic crisis, and (4) international trade. For the first major area of focus, poverty and social exclusion, the survey queried respondents about their own definition of poverty, the extent of poverty and homelessness in their area, and whether or not respondents believed poverty had increased in their area and elsewhere. Respondents were queried about what necessities people must be able to afford to meet a minimal acceptable living standard, who is most at risk for poverty, as well as the social, political, and personal causes of poverty and homelessness. Respondents were also asked about how poverty impacts peoples' chances of completing certain activities, such as getting a good education or finding a job. Respondents were then asked whether or not they trust the European Union (EU), their governments, charities, other citizens, and miscellaneous institutions to effectively respond to poverty. Respondents were also asked to whom they assign primary responsibility for reducing or preventing poverty, what policies their governments should focus on in the future in the effort to help people out of poverty, and whether or not respondents approved of their government's existing anti-poverty measures. Respondents were also queried about their perception of social tensions between groups, and about what they have done personally to help poor people. Additionally, respondents were queried about their own living conditions, satisfaction with life, ability to keep a job, efforts to fight poverty, finances, and their own risk of falling into poverty. For the second major area of focus, mobile phone use, the survey asked respondents about whether or not they owned a mobile phone, their mobile phone use in other EU countries, and the cost of cellular phone service in those countries. For the third major area of focus, economic crisis, the survey questioned respondents about the degree to which the crisis personally affected them, how the crisis affected the EU and its policy efforts, who should bear responsibility for the crisis, who should bear the burden of response to the crisis, and how the European Parliament and other bodies should respond to the crisis. For the fourth major area of focus, international trade, the survey queried respondents on whether they pay attention to the country of origin for products they purchase, how trade impacts respondents and their countries, what European Union trade policy should be going into the future, and the European Union's international economic standing. Demographic and other background information collected includes age, gender, nationality, marital status and parental relations, left-right political self-placement, occupation, age when stopped full-time education, household composition, ownership of a fixed or a mobile telephone and other durable goods, difficulties in paying bills, level in society, and Internet use. In addition, country-specific data includes type and size of locality, region of residence, and language of interview (select countries). Please review the ICPSR codebook; "Variable Documentation" section for information concerning individual weights and the "Technical Specifications" section for general weighting information. 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: Checked for undocumented or out-of-range codes.. In all, Eurobarometer 74.1 interviewed 26,635 citizens in the 27 countries of the European Union after the 2004/2007 enlargement (i.e. including the Accession Countries Romania and Bulgaria). All respondents were residents in the respective country, nationals and non-nationals but EU-citizens, and aged 15 and over. Respondents were expected to have sufficient command of one of the respective national language(s) to answer the questionnaire. Separate samples were drawn for Northern Ireland and East Germany. Smallest Geographic Unit: country Multistage national probability samples. 2013-07-02 Data for P...

Various state governments in India set-up shelter homes for those stranded by the coronavirus (COVID-19) lockdown implemented in late March, 2020. The southern state of Kerala topped the list with 15,141 shelter homes in April. This was nearly 70 percent of all government camps across the country. Uttar Pradesh followed with 2,230 camps and Maharashtra ranked third during the same time period.

The country went into lockdown on March 25, 2020, the largest in the world, restricting 1.3 billion people. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

Out of all OECD countries, Cost Rica had the highest poverty rate as of 2022, at over 20 percent. The country with the second highest poverty rate was the United States, with 18 percent. On the other end of the scale, Czechia had the lowest poverty rate at 6.4 percent, followed by Denmark.

The significance of the OECD

The OECD, or the Organisation for Economic Co-operation and Development, was founded in 1948 and is made up of 38 member countries. It seeks to improve the economic and social well-being of countries and their populations. The OECD looks at issues that impact people’s everyday lives and proposes policies that can help to improve the quality of life.

Poverty in the United States

In 2022, there were nearly 38 million people living below the poverty line in the U.S.. About one fourth of the Native American population lived in poverty in 2022, the most out of any ethnicity. In addition, the rate was higher among young women than young men. It is clear that poverty in the United States is a complex, multi-faceted issue that affects millions of people and is even more complex to solve.

A multi-millionaire is defined as someone owning 10 million U.S. dollars or more. It was forecasted that there would be almost 18 thousand individuals in Australia defined as multi-millionaires by 2026. This is in line with the country’s growing economy over the years as well as the growing wealth inequality that was becoming a cause for concern in the island nation.

Distribution of the wealthy

As a rich country with plenty of natural resources and a high Human Development Index, Australia had always had a large number of high net-worth individuals or HNWIs. There were over ten thousand millionaires including a couple dozen of billionaires, with these figures expected to grow significantly over the next few years.

Income inequality

Despite the increase of wealth and economic growth, there was a concern at the level of poverty and homelessness due to the rising wealth inequality nationally. The number of homeless people living in Australia had only been increasing with more than a hundred thousand people currently without shelter. Furthermore, most of the wealth was being pushed from the country to the cities, affecting the livelihood of those living in the countryside or outback.

In 2023, the resident population of California was ***** million. This is a slight decrease from the previous year, with ***** million people in 2022. This makes it the most populous state in the U.S. Californian demographics Along with an increase in population, California’s gross domestic product (GDP) has also been increasing, from *** trillion U.S. dollars in 2000 to **** trillion U.S. dollars in 2023. In the same time period, the per-capita personal income has almost doubled, from ****** U.S. dollars in 2000 to ****** U.S. dollars in 2022. In 2023, the majority of California’s resident population was Hispanic or Latino, although the number of white residents followed as a close second, with Asian residents making up the third-largest demographic in the state. The dark side of the Golden State While California is one of the most well-known states in the U.S., is home to Silicon Valley, and one of the states where personal income has been increasing over the past 20 years, not everyone in California is so lucky: In 2023, the poverty rate in California was about ** percent, and the state had the fifth-highest rate of homelessness in the country during that same year, with an estimated ** homeless people per 10,000 of the population.