Data quality is treated as a first-class concern
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 distinguish real differences from measurement artifacts.
Reproducible from public sources
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 publicly available. Source files and processing
scripts are tracked in git.
Multiple framings, not one number
Rates can be expressed 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.