ArticleAmerican journal of epidemiology2025
Innovating a community-driven enumeration and needs assessment of people experiencing homelessness: a network sampling approach for the HUD-mandated point-in-time count.
Article in American journal of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Understanding the Personal Networks of People Experiencing Homelessness in King County, WA with Aggregate Relational Data.Social networks · 2026Article
- Encampments as neighbors: Encampment location and proximity to amenities among Seattle, WA's unhoused population.Cities (London, England) · 2026Article
- Sleep in People Experiencing Homelessness Under Different Conditions and Seasons.bioRxiv : the preprint server for biology · 2025Article
- Does demography have a role in measuring homelessness? Insights and approaches in the United States.Vienna yearbook of population research · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
To enumerate people experiencing homelessness in the United States, the federal Department of Housing and Urban Development (HUD) mandates its designated local jurisdictions regularly conduct a crude census of this population. This Point-in-Time (PIT) body count, typically conducted on a January night by volunteers with flashlights and clipboards, is often followed by interviews with a separate convenience sample. Here, we propose employing a network-based (peer-referral) respondent-driven sampling (RDS) method to generate a representative sample of unsheltered people, accompanied by a novel method to generate a statistical estimate of the number of unsheltered people in the jurisdiction. First, we develop a power analysis for the sample size of our RDS survey to count unsheltered people experiencing homelessness. Then, we conducted 3 large-scale population-representative samples in King County, WA (Seattle metro) in 2022, 2023, and 2024. We describe the data collection and the application of our new method, comparing the 2020 PIT count (the last visual PIT count performed in King County) to the new method of 2022 and 2024 PIT counts. We conclude with a discussion and future directions. This article is part of a Special Collection on Methods in Social Epidemiology.
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Registered trials
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