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.

Homelessness Report April 2025. Published by Department of Housing, Local Government, and Heritage. Available under the license Creative Commons Attribution Share-Alike 4.0 (CC-BY-SA-4.0).Homelessness data Official homelessness data is produced by local authorities through the Pathway Accommodation and Support System (PASS). PASS was rolled-out nationally during the course of 2013. The Department’s official homelessness statistics are published on a monthly basis and refer to the number of homeless persons accommodated in emergency accommodation funded and overseen by housing authorities during a specific count week, typically the last full week of the month. The reports are produced through the Pathway Accommodation & Support System (PASS), collated on a regional basis and compiled and published by the Department. Homelessness reporting commenced in this format in 2014. The format of the data may change or vary over time due to administrative and/or technology changes and improvements. The administration of homeless services is organised across nine administrative regions, with one local authority in each of the regions, “the lead authority”, having overall responsibility for the disbursement of Exchequer funding. In each region a Joint Homelessness Consultative Forum exists which includes representation from the relevant State and non-governmental organisations involved in the delivery of homeless services in a particular region. Delegated arrangements are governed by an annually agreed protocol between the Department and the lead authority in each region. These protocols set out the arrangements, responsibilities and financial/performance data reporting requirements for the delegation of funding from the Department. Under Sections 38 and 39 of the Housing (Miscellaneous Provisions) Act 2009 a statutory Management Group exists for each regional forum. This is comprised of representatives from the relevant housing authorities and the Health Service Executive, and it is the responsibility of the Management Group to consider issues around the need for homeless services and to plan for the implementation, funding and co-ordination of such services. In relation to the terms used in the report for the accommodation types see explanation below: PEA - Private Emergency Accommodation: this may include hotels, B&Bs and other residential facilities that are used on an emergency basis. Supports are provided to services users on a visiting supports basis. STA - Supported Temporary Accommodation: accommodation, including family hubs, hostels, with onsite professional support. TEA - Temporary Emergency Accommodation: emergency accommodation with no (or minimal) support....

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.

Transitional Housing Services Market size was valued at USD 100 Billion in 2023 and is projected to reach USD 342.6 Billion by 2031, growing at a CAGR of 15.2% during the forecast period 2024-2031.

Global Transitional Housing Services Market Drivers

The market drivers for the Transitional Housing Services Market can be influenced by various factors. These may include:

Increasing Homelessness Rates: The rising rates of homelessness globally are a significant market driver for transitional housing services. Factors such as economic instability, lack of affordable housing, and social issues contribute to this increasing trend. Many cities report surges in homelessness, prompting governments and NGOs to seek robust solutions. Transitional housing serves as an intermediary step, offering individuals and families temporary support while they work towards permanent housing solutions.

The research, entitled Homelessness during COVID-19: Homeless Migrants in a Global Crisis, took a biographical life story approach to understand the experiences of 43 non-UK nationals who experienced homelessness during the COVID-19 pandemic. In the first phase of the project, and in order to gain insight into the homelessness sector, we conducted semi-structured interviews with 37 people across nine homelessness organisations. The focus of the interviews was on migrant homelessness before and during the pandemic. Due to ethical reasons, we are not able to upload data from the life story interviews that we conducted with migrants experiencing homelessness. However, the data from the semi-structured interviews with staff in the homelessness sector that we have submitted to the UK Data Service helped us to frame our research and provided much-needed contextual information during the pandemic.

People experiencing homelessness are disproportionately impacted by coronavirus. Despite government efforts to place rough sleepers in hotels to contain the spread of the disease, many migrants sleeping rough with No Recourse to Public Funds (NRPF) have been left behind at the height of a global pandemic. This project, involving researchers from University of Portsmouth, University of Sussex and St Mungo's, the homeless charity, will produce an 18-month qualitative-based study of migrant homelessness framed by the wider global and national context. Working with two of St Mungo's migrant services, Street Legal, St Mungo's legal team and Routes Home, a service supporting people sleeping rough from outside of the UK, a particular focus of the study will be the experience of non-UK nationals and their attempts, during the crisis, to resolve their immigration status. Many of these migrants are at the sharpest end of homelessness: almost 1,000 rough sleepers housed in emergency accommodation in London have NRPF (Heath, 2020).

Most migrant homeless clients are faced with multiple everyday challenges; they experience the hostility and aggression directed toward homeless people, compounded with often intense experiences of racism. Migrant homeless clients are also likely to be afraid of 'authorities' for various reasons including fear of deportation by the Home Office and personal histories of violent persecution by state actors in their original countries of belonging. During the pandemic, increased numbers of police on the streets have created high anxiety for refugees/asylum seekers and destitute migrants who report being retriggered with PTSD symptoms, with no access to NHS mental health services that are now delivered primarily remotely and are restricted access except to those patients who have access to free or cheap wifi, or unlimited phone credit (Munt 2020). A cultural miasma of fear and anxiety due to pandemic can affect such vulnerable minority groups particularly forcefully, with public attitudes generating direct aggression toward perceived 'outsiders' as harbingers of disease. Historically, the discourse of the 'stranger' (Ahmed 1991) or foreigner as bringer of disease has been well recognised within cultural sociology (Munt 2007), and as cultural suspicion grows under such conditions, feelings of alienation and estrangement amongst vulnerable groups intensifies.

The project will innovate by examining the biographical and life history narratives of St Mungo's clients in London in relation to their experiences of homelessness during the coronavirus crisis. Alongside semi-structured interviews, we will use participatory research methods including peer research, autoethnographic diaries, mobile phone photo-ethnographies and life history narratives in order to capture the rich and emotive narratives of those experiencing crisis. In doing so, we will examine the intersection of personal histories, complex global processes and the dynamics of the particular situation (Stewart, 2012, 2013). Researching vulnerable groups requires ethical sensitivity. It carries the danger of risking more disappointment among the respondents and exacerbating intense feelings of loneliness and isolation. To avoid this, and to make a positive intervention, we will seek to engage clients with services and support as part of the research project. Based on its findings, and working with St Mungo's partners, the project will make recommendations for measures that can be taken across the UK and elsewhere to support the homeless, particularly those most vulnerable, during times of crisis.

Financial overview and grant giving statistics of Homeless Children International Inc.

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.

This layer contains detailed Point in Time counts of homeless populations from 2018, 2013, and 2008. A 2019 version is now available!Layer is symbolized to show the count of the overall homeless population in 2018, with overall counts from 2008 and 2013 in the pop-up, as well as a pie chart of breakdown of type of shelter. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. The Point-in-Time (PIT) count is a count of sheltered and unsheltered homeless persons on a single night in January. HUD requires that Continuums of Care Areas (CoCs) conduct an annual count of homeless persons who are sheltered in emergency shelter, transitional housing, and Safe Havens on a single night. CoCs also must conduct a count of unsheltered homeless persons every other year (odd numbered years). Each count is planned, coordinated, and carried out locally.The Point-in-Time values were retrieved from HUD's Historical Data site. The 2018, 2013, and 2008 sheets within the "2007 - 2018 PIT Counts within CoCs.xlsx" (downloaded on 2/7/2019) file were combined and joined to the CoC boundaries available from HUD's Open Data site. As noted in the "Mergers" sheet in the PIT Excel file, some CoC Areas have merged over the years. Use caution when comparing numbers in these CoCs across years. Data note: MO-604 covers territory in both Missouri and Kansas. The record described in this file represents the CoC's total territory, the sum of the point-in-time estimates the CoC separately reported for the portions of its territory in MO and in KS.For more information and attributes on the CoC Areas themselves, including contact information, see this accompanying layer.Suggested Citation: U.S. Department of Housing and Urban Development (HUD)'s Point in Time (PIT) counts for Continuum of Care Grantee Areas, accessed via ArcGIS Living Atlas of the World on (date).

Homlessness Report July 2023. Published by Department of Housing, Local Government, and Heritage. Available under the license Creative Commons Attribution Share-Alike 4.0 (CC-BY-SA-4.0).Homelessness data Official homelessness data is produced by local authorities through the Pathway Accommodation and Support System (PASS). PASS was rolled-out nationally during the course of 2013. The Department’s official homelessness statistics are published on a monthly basis and refer to the number of homeless persons accommodated in emergency accommodation funded and overseen by housing authorities during a specific count week, typically the last full week of the month. The reports are produced through the Pathway Accommodation & Support System (PASS), collated on a regional basis and compiled and published by the Department. Homelessness reporting commenced in this format in 2014. The format of the data may change or vary over time due to administrative and/or technology changes and improvements. The administration of homeless services is organised across nine administrative regions, with one local authority in each of the regions, “the lead authority”, having overall responsibility for the disbursement of Exchequer funding. In each region a Joint Homelessness Consultative Forum exists which includes representation from the relevant State and non-governmental organisations involved in the delivery of homeless services in a particular region. Delegated arrangements are governed by an annually agreed protocol between the Department and the lead authority in each region. These protocols set out the arrangements, responsibilities and financial/performance data reporting requirements for the delegation of funding from the Department. Under Sections 38 and 39 of the Housing (Miscellaneous Provisions) Act 2009 a statutory Management Group exists for each regional forum. This is comprised of representatives from the relevant housing authorities and the Health Service Executive, and it is the responsibility of the Management Group to consider issues around the need for homeless services and to plan for the implementation, funding and co-ordination of such services. In relation to the terms used in the report for the accommodation types see explanation below: PEA - Private Emergency Accommodation: this may include hotels, B&Bs and other residential facilities that are used on an emergency basis. Supports are provided to services users on a visiting supports basis. STA - Supported Temporary Accommodation: accommodation, including family hubs, hostels, with onsite professional support. TEA - Temporary Emergency Accommodation: emergency accommodation with no (or minimal) support....

The global market for Community Food, Housing, and Relief Services is a significant and rapidly growing sector, driven by increasing income inequality, natural disasters, and global conflicts. While precise market sizing data is unavailable, considering the substantial involvement of numerous large NGOs (like Feeding America, World Food Programme, and others) alongside regional and local organizations, a reasonable estimation places the 2025 market value at approximately $500 billion USD. This represents a substantial increase from previous years, reflecting the growing need for these services worldwide. The Compound Annual Growth Rate (CAGR) is difficult to pinpoint precisely without detailed financial data from all participating organizations. However, considering factors like population growth, increasing poverty levels in many regions, and the escalating frequency and severity of climate-related disasters, a conservative estimate would place the CAGR for the forecast period (2025-2033) at around 5-7%. This growth is further fueled by evolving societal attitudes towards social responsibility and corporate social responsibility (CSR) initiatives, which increasingly include support for community relief efforts. Key market segments include emergency relief, long-term housing assistance, food security programs, and support services for vulnerable populations (children, the elderly, disabled individuals). While numerous organizations contribute, the market is characterized by a diverse range of players, from large international NGOs to smaller, local charities. Challenges facing the sector include securing sustainable funding, coordinating resources effectively across various organizations, and ensuring equitable access to services for all those in need. Future growth will depend on addressing these challenges, promoting greater collaboration among stakeholders, and leveraging technological advancements to improve efficiency and outreach. Effective advocacy and public awareness campaigns are also critical to ensuring sustained support for these vital services.

Global Temporary Shelters market size is expected to reach $53.26 billion by 2029 at 5.4%, government funds drive growth in temporary housing market

The global transitional housing services market size was valued at USD 32.43 billion in 2025 and is projected to expand at a CAGR of 5.1% from 2025 to 2033. The market growth is attributed to rising homelessness and the increasing need for temporary housing solutions for victims of domestic violence, sexual assault, and child abuse. Additionally, government initiatives aimed at addressing homelessness and providing support services for low-income individuals and families are driving market expansion. Key market trends include the integration of technology to enhance service delivery, the growing emphasis on affordable and accessible housing options, and the expansion of partnerships between non-profit organizations and government agencies. The market is segmented into various applications, including victims of domestic violence, sexual assault, or child abuse, homeless, runaway youths, low-income individuals and families, and others. Temporary and emergency shelter services, permanent housing support services, transitional and assisted housing services, and volunteer construction or repair services are the primary types of services offered. Major market players include NAICA, The Homeless Hub, Catholic Community Services, SAMHSA, The Salvation Army, UNICEF, ShelterBox, Covenant House, The Bridge, Five Keys, SAHSSI, Hillcrest, Wilder Foundation, A Safe Haven, Pacific Clinics, and Front Steps.

Financial overview and grant giving statistics of International Hunger And Homeless Charity

This layer contains detailed Point in Time counts of homeless populations from 2019. This layer is modeled after a similar layer that contains data for 2018, 2013, and 2008.Layer is symbolized to show the count of the overall homeless population in 2019, with a pie chart of breakdown of type of shelter. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. The Point-in-Time (PIT) count is a count of sheltered and unsheltered homeless persons on a single night in January. HUD requires that Continuums of Care Areas (CoCs) conduct an annual count of homeless persons who are sheltered in emergency shelter, transitional housing, and Safe Havens on a single night. CoCs also must conduct a count of unsheltered homeless persons every other year (odd numbered years). Each count is planned, coordinated, and carried out locally.The Point-in-Time values were retrieved from HUD's Historical Data site. Original source is the 2019 sheet within the "2007 - 2019 PIT Counts by CoCs.xlsx" (downloaded on 3/10/2020) file. Key fields were kept and joined to the CoC boundaries available from HUD's Open Data site.Data note: MO-604 covers territory in both Missouri and Kansas. The record described in this file represents the CoC's total territory, the sum of the point-in-time estimates the CoC separately reported for the portions of its territory in MO and in KS.For more information and attributes on the CoC Areas themselves, including contact information, see this accompanying layer.Suggested Citation: U.S. Department of Housing and Urban Development (HUD)'s Point in Time (PIT) 2019 counts for Continuum of Care Grantee Areas, accessed via ArcGIS Living Atlas of the World on (date).

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 ---

This map shows Point in Time counts of the overall homeless populations from 2019. Layer is symbolized to show the count of the overall homeless population in 2019, with a pie chart of breakdown of type of shelter. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. The Point-in-Time (PIT) count is a count of sheltered and unsheltered homeless persons on a single night in January. HUD requires that Continuums of Care Areas (CoCs) conduct an annual count of homeless persons who are sheltered in emergency shelter, transitional housing, and Safe Havens on a single night. CoCs also must conduct a count of unsheltered homeless persons every other year (odd numbered years). Each count is planned, coordinated, and carried out locally.The Point-in-Time values were retrieved from HUD's Historical Data site. Original source is the 2019 sheet within the "2007 - 2019 PIT Counts by CoCs.xlsx" (downloaded on 3/10/2020) file. Key fields were kept and joined to the CoC boundaries available from HUD's Open Data site.Data note: MO-604 covers territory in both Missouri and Kansas. The record described in this file represents the CoC's total territory, the sum of the point-in-time estimates the CoC separately reported for the portions of its territory in MO and in KS.For more information and attributes on the CoC Areas themselves, including contact information, see this accompanying layer.Suggested Citation: U.S. Department of Housing and Urban Development (HUD)'s Point in Time (PIT) 2019 counts for Continuum of Care Grantee Areas, accessed via ArcGIS Living Atlas of the World on (date).

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

The Mexican residential real estate market, valued at $14.51 billion in 2025, is projected to experience steady growth, with a Compound Annual Growth Rate (CAGR) of 4.14% from 2025 to 2033. This growth is fueled by several key factors. Firstly, a burgeoning middle class and increasing urbanization are driving demand for housing, particularly in major metropolitan areas like Mexico City, Guadalajara, and Monterrey. Secondly, government initiatives aimed at improving infrastructure and boosting affordable housing are contributing positively to market expansion. Furthermore, foreign investment, particularly from North America, continues to play a role, injecting capital and influencing development trends within the luxury segment. However, the market faces challenges such as fluctuating interest rates, economic volatility, and potential regulatory hurdles that could impact construction and land acquisition costs. The market is segmented into apartments and condominiums, which dominate the urban landscape, and landed houses and villas catering to a wealthier demographic seeking more space. Leading developers like Grupo Sordo Madaleno, Consorcio Ara Sab de CV, and Grupo Garza Ponce, are key players shaping the market's evolution through innovative project designs and strategic land acquisition. The market's performance will likely depend on the effectiveness of government policies, the resilience of the Mexican economy, and the evolving preferences of homebuyers, impacting future housing demands. The segmentation of the market into apartments/condominiums and landed houses/villas reflects differing consumer preferences and purchasing power. The apartment and condominium segment is expected to show robust growth, driven by affordability and urban convenience. The landed houses and villas segment, while smaller in volume, will likely see consistent growth fueled by high net-worth individuals seeking luxury homes. Geographical distribution across regions will vary, with concentrations in major urban hubs. International investment, although influential, may be subject to global economic shifts affecting currency fluctuations and overall confidence in the Mexican market. Overall, a careful observation of economic indicators, policy changes and consumer confidence levels will provide a more accurate forecast of the market's trajectory over the forecast period. Understanding these dynamic factors is key for investors and developers to successfully navigate this evolving market. This in-depth report provides a detailed analysis of the dynamic residential real estate market in Mexico, covering the period from 2019 to 2033. With a focus on the key segments of apartments and condominiums, landed houses and villas, and industry developments, this report offers invaluable insights for investors, developers, and industry professionals seeking to navigate this lucrative but complex market. The report leverages data from the base year 2025, with estimations for the estimated year 2025 and forecasts spanning the forecast period 2025-2033, while analyzing historical trends from the historical period 2019-2024. Expect comprehensive coverage of key market drivers, challenges, and emerging trends shaping the future of Mexican real estate. Discover opportunities in millions of USD worth of potential, and understand the competitive landscape, dominated by players like Groupo Sordo Madaleno, Consorcio Ara Sab de CV, and Grupo Garza Ponce, among others. Recent developments include: June 2023: Habi, a prominent real estate technology platform, is set to receive a substantial financial boost of USD 15 million from IDB Invest. This funding, spread over four years, aims to fuel Habi's expansion plans in Mexico. While the structured loan has the potential to reach USD 50 million, its primary focus is to cater to Habi's working capital needs. IDB Invest's strategic move is not just about bolstering Habi's growth; it also aims to leverage technology to enhance liquidity and agility in Mexico's secondary real estate markets. By addressing the housing gap in Mexico, this funding initiative is poised to elevate market efficiency, bolster transparency, encourage local contractors for home renovations, and expand Habi's corridor network., June 2023: Celaya Tequila, a premium tequila brand crafted in small batches and co-founded by brothers Matt & Ryan Kalil, is forging a philanthropic alliance with New Story, a non-profit dedicated to eradicating global homelessness. In a groundbreaking move, Celaya Tequila pledges to contribute a percentage of sales from every bottle towards an affordable housing endeavor in Jalisco, Mexico. This endeavor aims to empower underprivileged families in Jalisco by enhancing their access to homes and land ownership.. Key drivers for this market are: 4., Increasing Residential Real Estate Demand by Young People4.; Increase in Average Housing Price in Mexico. Potential restraints include: 4., Lack of Affordable Housing Inhibiting the Growth of the Market4.; Economic Instability Affecting the Growth of the Market. Notable trends are: Demand for Residential Real Estate Witnessing Notable Surge, Primarily Driven by Young Homebuyers.