Zack W. Almquist

Zack W. Almquist

Associate Professor of Sociology, Adjunct Associate Professor of Statistics and Senior Data Science Fellow @ eScience

Housing and Homelessness

During the COVID19 pandemic, in December 2021, the United Nations General Assembly adopted resolution 76/133, which recognizes homelessness as a violation of human rights (UN 2021). The UN calls on member states to gather better data on homelessness and implement programs to redress the issue. While this is a call to all participating countries, it offers an opportunity and a challenge to demographers worldwide to provide methods to improve the enumeration and demographic estimates of one of the most powerless populations in the world.

The lack of affordable housing is becoming a global crisis, with the UN estimating 1.6 billion people — 20% of humanity — lack access to adequate housing and basic services. The UN report further warns this number could rise to 3 billion by 2030. The number of people experiencing homelessness worldwide is contested; however, another UN estimate claims at least 150 million people are experiencing homelessness on any given night.

In the United States, the US Department of Housing and Urban Development released the 2023 Annual Homeless Assessment Report (AHAR) on December 15, 2023. The report estimates that 653,100 people in the U.S. experienced homelessness in 2023, a 12% increase from 2022. This estimate comes from the Point-in-Time (PIT) count conducted on a single night in January over communities across the US. The PIT, which is mandated by HUD every two years, is composed of two key elements: (1) the emergency shelter report from administrative records and (2) the unsheltered PIT count typically performed on a single night in January through volunteers walking around the community and tabulating how many people they see. This so-called “visual census” of unsheltered people experiencing homelessness has a number of issues, from methodology (people are undercounted for a number of reasons) to ethics (people don’t get a voice in how they are counted). In other words, there is much room for improvement in understanding our unhoused neighbors.

My research has focused on improving our understanding the size of the population and the needs of people experiencing homelessness. This work is a collaboration between many people at UW, my team, and community partners. Recently, I introduced a new method for adapting respondent-driven sampling (RDS) – a peer referral-based method for generating a quasi-probability sample – to estimate the total number of people living unsheltered in a given HUD-designated jurisdiction. In 2022, I helped King County Regional Homelessness Authority (KCRHA) implement this method, and the estimates are part of the official HUD record (See here). In 2023, a team of UW researchers piloted key improvements and software for this method (discussion on the data can be found here). Most recently, in 2024, my team at UW and KCRHA implemented this updated version of the method for the formal 2024 HUD PIT count. This work has been documented and peer-reviewed and can be found in Almquist et al. (2024). KCRHA has plans to use RDS methods for the unsheltered PIT count going forward. KCRHA and my team are currently engaged in improving the method and need an assessment questionnaire through the UW Population Health Initiative Grant. I am also engaged in investigating the effects of displacement on people experiencing homelessness through administrative data and looking at the effects of sleep on different intervention strategies, such as tent villages and tiny homes.

Working Group

Community Partners

  • King County Regional Homelessness Authority
  • ETS REACH
  • WHEEL/SHARE
  • King County Public Health

Funding

  • 2024 - 2026 Almquist, Z.W. (Lead-PI), Hagopian, A., Hebert, P., McCormick, T., Yang, J., Kajfasz, O., Rothfolk, J., Carey, C. “Community-driven Enumeration and Needs Assessment of People Experiencing Homelessness: A high-frequency method for enumeration and needs assessment of the unsheltered population of people experiencing homelessness Community-driven Enumeration and Needs Assessment of People Experiencing Homelessness: A high-frequency method for enumeration and needs assessment of the unsheltered population of people experiencing homelessness.” University of Washington Population Health Initiative’s Tier 3 Pilot Grant Program with support from CSDE and Sociology. $217,593.
  • 2022 - 2027 Almquist, Z. (PI). “CAREER: Measuring and Modeling the Multi-Modal Networks and Demographics of People Experiencing Homelessness.” Grant #SES-2142964, NSF Social, Social & Economic Sciences (SES), Sociology. $500,000.
  • 2022 - 2023 Hagopian, A., Kajfasz, O., Zhao, B., Hebert, P., Almquist, Z., Luo, G. and Dobra, A. “Innovating better methods to enumerate individuals experiencing homelessness.” The University of Washington Population Health Initiative’s Tier 2 Pilot Grant with support from CSDE and the Department of Health Systems and Population Health. $106,822.
  • 2022-2023 de la Iglesia, H., Martin, M. and Almquist, Z.W. “Sleep health in people experiencing homelessness.” University of Washington Population Health Initiative’s Tier 1 Pilot Grant Program with support from CSDE and the Department of Biology. $38,468.91.

Data

Peer Reviewed Articles

  • Almquist, Z. W., I. Kahveci, A. Hazel, O. Kajfasz, J. Rothfolk, C. Guilmette, M. Anderson, L. Ozeryansky, and A. Hagopian (in press). Innovating a Community-driven Enumeration and Needs Assessment of People Experiencing Homelessness: A Network Sampling Approach for the HUD-Mandated Point-in-Time Count. American Journal of Epidemiology.
  • Anderson, M.C., A. Hazel, J. M. Perkins, and Z. W. Almquist (2024). Identity and Generosity Norms Among People Experiencing Homelessness in Nashville, TN: A Dictator Game Experiment. International Journal on Homelessness, 3(3), 1–13.
  • Anderson, M. C., A. Hazel, J. M. Perkins, and Z. W. Almquist (2021). The Ecology of Unsheltered Homelessness: Environmental and Social-Network Predictors of Well-Being among an Unsheltered Homeless Population. International Journal of Environmental Research and Public Health 18(14), 7328.
  • Almquist, Z. W. (2020). Large-scale Spatial Network Models: An application to modeling information diffusion through the homeless population of San Francisco. Environment and Planning B: Urban Analytics and City Science 47(3), 523–540
  • Almquist, Z. W., N. E. Helwig, and Y. You (2020). Connecting Continuum of Care Point-in-Time Homeless Counts to United States Census Areal Units. Mathematical Population Studies 27(1), 46–58.