Independent Research
Gaither Research builds interactive dashboards and analysis from HUD's homelessness data. We use the Continuum of Care framework HUD reports on, so our numbers reconcile against the published federal totals.
Dashboard
Per-CoC and per-state homelessness rates, with sheltered vs. unsheltered breakdowns, urban-vs-rural decomposition, and an undercount-risk audit flagging CoCs whose reported rates are likely understated.
Open dashboard →Analysis
A correlation analysis testing housing market conditions, eviction rates, federal funding, and labor market indicators against the CoC homelessness rate. Restricted to data-quality-vetted CoCs.
Open analysis →Every CoC in our analyses carries a data-quality tier. Communities that count well can appear to have higher homelessness rates than communities that count poorly. We flag this explicitly so readers can tell real differences from measurement artifacts.
Our datasets are HUD's PIT counts, HUD's CoC funding awards, HUD's Housing Inventory Counts, and the UCSF BHHI CoC Data project. All are publicly available. Source files and processing scripts are tracked in git.
Rates can be shown per 10,000 residents, as a percentage, or as "1 in N." Counts can be sliced by sheltered, unsheltered, or total. Geographic decomposition shows whether a state's rate is driven by its major cities or distributed across the whole state.