Biography: Zack W. Almquist is currently an Associate Professor in the Department of Sociology, Adjunct Associate Professor of Statistics, and Senior Data Science Fellow at the eScience Institute at the University of Washington. Before coming to UW in 2020, Prof. Almquist held positions as a Research Scientist at Facebook, Inc and as an Assistant Professor of Sociology and Statistics at the University of Minnesota. Dr. Almquist is a recipient of the American Sociological Association’s Section on Methodology’s Leo Goodman Award. He is also a recipient of the NSF’s CAREER Award and the ARO’s Young Investigator Program Award. He is currently the Editor-in-Chief of the Journal of Mathematical Sociology. His research centers on the development and application of mathematical, computational and statistical methodology to problems and theory of social networks, demography, homelessness, and environmental action and governance.
A Qualitative and Quantitative PIT Count using Respondent Driven Sampling (RDS): Understanding and Counting Unsheltered Homelessness in King County
Abstract: Traditionally, unsheltered Point in Time (PIT) Counts are the result of volunteers conducting an in-person head-count of individuals experiencing homelessness on a single night. This resource-intensive method is widely understood to be an undercount. It also fails to capture essential qualitative data about what people living unsheltered experience and need.
This past spring, the King County Regional Homelessness Authority (RHA), in coordination with Professor Zack W. Almquist (University of Washington) and Lived Experience Coalition (LEC), took a novel approach to the PIT. The RHA conducted the 2022 unsheltered PIT count as a combined qualitative interview process and quantitative survey over the course of a month. The respondent selection for both the qualitative and quantitative surveys followed a Respondent Driven Sampling (RDS) protocol. RDS provides a sampling strategy for estimating size and percentages of hard-to-reach populations that lack an administrative sampling frame.
During this seminar, I will provide an overview of the RHA partnership effort, and how we executed this novel approach to the PIT. I will review the history of RDS as a means of sampling vulnerable populations, and I will cover the implementation of the sampling and estimation strategies based on the RHA RDS sample. Finally, I will review the demographics provided to HUD, and what we learned from conducting the RDS sample for the PIT count, and how it can and should affect future PIT counts going forwards.
