Data drives policy, and flawed data may drive flawed policy. Current methods of tracking homelessness often vastly underestimate the number of unhoused individuals, which can have great ramifications on funding and policy decisions. A University of Washington research team has developed a more accurate method for tracking homelessness in King County, helping to address this crucial gap.
Led by professors Zack Almquist and Amy Hagopian, the team ditched the widely-used Point-in-Time (PIT) tracking method – a single-night census – with social network-based sampling. This new method does not rely on volunteer counting people seen outside, instead incorporating shelter rosters and peer referral to estimate the total population. This method of leveraging people’s social networks produces a much more accurate count, helping to reflect the true reality of homelessness in Seattle.
King County has used this method since 2022, and it has garnered insights about the demographics and structural causes of homelessness. King County has now focused on quarterly homelessness counts, hoping that this approach will provide valuable longitudinal data. This method could also be applied to other populations that are difficult to measure, such as undocumented migrants.