Abstract
This article discusses improvements made to the methodology of the Housing and Urban Development (HUD) point-in-time (PIT) homeless census. HUD’s PIT results are presented to Congress as official data for policy consideration. Yet, PIT methodology focuses on visible street homeless individuals and those in shelters while neglecting the “marginally housed” or less visible homeless who live in automobiles or temporarily stay with friends and extended family. Being a hidden population, the marginally housed has been a traditionally difficult population to study. We replicated HUD’s PIT count but additionally targeted the marginally housed to improve traditional methods of counting the homeless. We improve the PIT count in two ways: (1) by extensively training counters, and (2) by using the personal networks of hundreds of counters to seek out the marginally housed. Student researchers from a local university located 333 more homeless individuals than the local PIT, of which 153 were marginally housed. We do not claim this to be an exhaustive count of all the marginally housed in the region, but it is an initial step in developing methodologies to include this hidden population when calculating the total homeless population. This approach can also improve traditional homeless counts in other cities.
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