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Motivation

Questions

This project aims to better quantify and understand the homeless (especially unsheltered) population in King County, Washington. Counting and understanding the experiences of unhoused people is crticial to working towards solutions to this humanitarian crisis.

Background

The US Department of Housing and Urban Development mandates that local “continuum of care” agencies do a count of the unhoused population every other year. Conducting this count helps determine the funding that communities and agencies receive to support people experiencing homelessness.

The census of the unhoused population consists of two parts, (1) a count of people sleeping in shelters and other emergency housing (the sheltered homeless population) and 2) a count of those living unsheltered: tents, cars, in the open, abandoned buildings, or other places considered unfit for human habitation. In most jurisdictions the unsheltered count is performed on a single night in January by volunteers walking around the community in the middle of the night and tabulating how many people they see who are sleeping unsheltered. This so-called “visual census” of unsheltered people experiencing homelessness has a number of issues:

  1. It is invasive and doesn't give people a voice in how they are counted
  2. People are undercounted for a number of reasons
  3. It is not linked to demographic data (demographic data are extrapolated from the sheltered population of people experiencing homelessness)

Because there is much room for improvement in understanding our unhoused neighbors, a team at UW has been working with the King County Regional Homelessness Authority (KCRHA) since 2022 to improve the unsheltered PIT methodology and accompanying demographic and needs assessment surveys. In 2022, the University of Washington and KCRHA implemented a novel, network-based method for counting the unsheltered people experiencing homelessness known as Respondent-Driven Sampling. That was followed by a larger pilot study conducted in 2023, resulting in a dataset containing rich network and demographic information from 1,100+ sheltered and unsheltered people. We need to finalize the 2023 data set, produce policy reports for KCRHA, and create an outward-facing website to host our findings and describe the method for other communities to use. We are especially interested in conducting analysis to develop a deeper understanding of people living in vehicles and their needs.

Data were collected and analyzed, using Respondent Driven Sampling (RDS). The survey data (collected in 2023) contains responses from homeless individuals in King County to a number of demographic items as well as questions about their experiences of being homeless (e.g., duration of homelessness, place(s) they sleep, etc.) and information about their networks of other homeless individuals.

Stakeholders

Key stakeholders for this project included the VA Homeless Patient Aligned Care Team (HPACT), King County Regional Homelessness Authority (KCRHA), and Dr. Graham Pruss with the City of San Jose, all of whom were interested in initial findings from the 2023 survey. We held stakeholder meetings with two groups from the VA, a team of healthcare workers and a team of social workers, in order to understand their needs and interest in the data and to get feedback on initial findings. We also met with a representative from San Jose City who had a particular interest in people living in vehicles and who is interested in adopting the sampling method used in King County. Other stakeholders include future researchers and students who will be using the finalized dataset that was prepared as a part of our project.

Ethics

Given that people experiencing homelessness are a vulnerable population and the survey contains sensitive data about health, substance use and more, measures were taken to ensure that data individuals cannot be identified in summary findings and in externally facing papers and websites. We also worked closely with direct service providers and held a focus group with people experiencing homelessness to better understand their experience taking the survey, solicit feedback on ways to improve the survey and to hear suggestions for using data from the survey to support the unhoused population.