FactHub dataset table

CoC-to-Census geography crosswalk

The Census counties and places added or subtracted to rebuild each CoC boundary.

Coverage: 2015-2025 (PIT count years; no ACS 1-year data for 2020)

Node: dataset:homelessness-rate-vs-rent:1:table:coc-geography

Contained in Homelessness rate vs. rent in 67 large U.S. Continuums of Care, 2015-2025.

What this dataset measures

Large urban CoCs whose boundaries can be rebuilt from whole Census counties or places, so each homeless count can be matched to the population and rents of the same area. Built to test the common explanation that high housing costs account for Seattle/King County's homelessness.

Curated data tables

CoC-to-Census geography crosswalk

The Census counties and places added or subtracted to rebuild each CoC boundary.

Unit of observation: CoC

coc_geography_map.csv text/csv · 3.6 KB (3,645 bytes)

All 67 rows 6 columns Download the file

All 67 rows
coc_code code_aliases short_name add_geos subtract_geos note
NY-600 — New York City
county:36005;county:36047;county:36061;county:36081;county:36085
—
Five boroughs
CA-600 — Los Angeles (excl. Long Beach/Pasadena/Glendale)
county:06037
place:0643000;place:0656000;place:0630000
LA County minus the three cities with their own CoCs; rent/vacancy use whole-county values
IL-510 — Chicago
place:1714000
—
City of Chicago
WA-500 — Seattle/King County
county:53033
— —
CO-503 — Metro Denver
county:08001;county:08005;county:08013;county:08014;county:08031;county:08035;county:08059
—
Adams Arapahoe Boulder Broomfield Denver Douglas Jefferson
CA-601 — San Diego
county:06073
— —
CA-500 — San Jose/Santa Clara
county:06085
— —
CA-502 — Oakland/Alameda
county:06001
— —
AZ-502 — Phoenix/Maricopa
county:04013
— —
CA-501 — San Francisco
county:06075
— —
NV-500 — Las Vegas/Clark
county:32003
— —
OR-501 — Portland/Multnomah
county:41051
— —
CA-602 — Orange County CA
county:06059
— —
CA-503 — Sacramento
county:06067
— —
MA-500 — Boston
place:2507000
—
City of Boston
DC-500 — District of Columbia
county:11001
— —
PA-500 — Philadelphia
county:42101
— —
CA-511 — Stockton/San Joaquin
county:06077
— —
HI-501 — Honolulu
county:15003
— —
CA-514 — Fresno/Madera
county:06019;county:06039
— —
CA-609 — San Bernardino
county:06071
— —
CA-608 — Riverside
county:06065
— —
NY-603 — Nassau/Suffolk
county:36059;county:36103
— —
MN-500 — Minneapolis/Hennepin
county:27053
— —
FL-600 — Miami-Dade
county:12086
— —
TX-600 — Dallas/Collin
county:48113;county:48085
—
Dallas and Collin counties (MDHA service area)
TX-500 — San Antonio/Bexar
county:48029
— —
CA-606 — Long Beach
place:0643000
—
City of Long Beach
TX-700 — Houston/Harris/Fort Bend/Montgomery
county:48201;county:48157;county:48339
— —
TX-503 — Austin/Travis
county:48453
— —
GA-500 — Atlanta
place:1304000
—
City of Atlanta
CA-505 — Contra Costa
county:06013
— —
FL-507 — Orlando/Orange/Osceola/Seminole
county:12095;county:12097;county:12117
— —
NM-500 — Albuquerque
place:3502000
—
City of Albuquerque
CA-604 — Bakersfield/Kern
county:06029
— —
WA-503 — Tacoma/Pierce
county:53053
— —
FL-601 — Fort Lauderdale/Broward
county:12011
— —
TX-601 — Fort Worth/Tarrant/Parker
county:48439;county:48367
—
Tarrant and Parker counties
NJ-504 — Newark/Essex
county:34013
— —
UT-500 — Salt Lake
county:49035
— —
OH-503 — Columbus/Franklin
county:39049
— —
CA-611 — Ventura
county:06111
— —
MO-604 MO-604a Kansas City/Jackson/Wyandotte
county:29095;county:20209
—
Jackson Co. MO + Wyandotte Co. KS (KC MO parts in Clay/Platte not included)
AZ-501 — Tucson/Pima
county:04019
— —
CA-512 — San Mateo
county:06081
— —
FL-605 — West Palm Beach/Palm Beach
county:12099
— —
FL-502 — Pinellas
county:12103
— —
NC-505 — Charlotte/Mecklenburg
county:37119
— —
TN-504 — Nashville/Davidson
county:47037
— —
FL-501 — Tampa/Hillsborough
county:12057
— —
OK-502 — Oklahoma City
place:4055000
—
City of Oklahoma City
KY-501 — Louisville/Jefferson
county:21111
— —
OH-502 — Cleveland/Cuyahoga
county:39035
— —
MI-501 — Detroit
place:2622000
—
City of Detroit (CoC also covers Hamtramck and Highland Park; not added)
MD-501 — Baltimore City
county:24510
— —
PA-600 — Pittsburgh/Allegheny
county:42003
— —
WI-501 — Milwaukee
county:55079
— —
IN-503 — Indianapolis/Marion
county:18097
— —
TN-501 — Memphis/Shelby
county:47157
— —
OH-500 — Cincinnati/Hamilton
county:39061
— —
MO-501 — St. Louis City
county:29510
— —
FL-510 — Jacksonville/Duval/Clay
county:12031;county:12019
—
Duval and Clay (CoC name in 2022+)
NC-507 — Raleigh/Wake
county:37183
— —
MD-600 — Prince George's
county:24033
— —
MD-601 — Montgomery County MD
county:24031
— —
VA-601 — Fairfax County
county:51059
—
Fairfax city and Falls Church (too small for ACS 1-yr) not added
LA-503 — New Orleans/Jefferson Parish
county:22071;county:22051
— —
6 field definitions
FieldTypeMeaningUnitsValue type
coc_code string HUD CoC code — observed
code_aliases string Other codes HUD used for the same CoC — observed
short_name string Short display name — derived
add_geos string Semicolon-separated Census geographies (county:FIPS or place:FIPS) summed into the CoC — derived
subtract_geos string Census places subtracted (e.g. cities with their own CoC) — derived
note string Notes on boundary approximations — derived

Supporting files

Source snapshots, manifests, quality reports, documentation, and other materials used to produce or review this release.

  • build_and_analyze.js Transformation manifest · text/javascript · 11.8 KB (12,057 bytes)

    Node.js script that builds coc-panel from the HUD PIT sheets and ACS JSON and fits the per-year regressions.

  • xlsb_to_csv.ps1 Transformation manifest · text/x-powershell · 977 bytes

    PowerShell script that exports each sheet of the HUD .xlsb workbook to CSV through Excel with macros disabled.

  • build_rate_rent.js Transformation manifest · text/javascript · 8.2 KB (8,372 bytes)

    Node.js script that computes king-residuals and the saved analyses (leave-one-out fits, prediction intervals, rent-growth correlations).

  • peers.js Transformation manifest · text/javascript · 10.2 KB (10,432 bytes)

    Node.js script that builds peer-changes (z-scored distances, 2019-to-latest changes, rent growth).

  • findings.md Documentation · text/markdown · 14 KB (14,292 bytes)

    Method notes, results tables and caveats for the panel and regressions.

  • findings-peers.md Documentation · text/markdown · 16.5 KB (16,944 bytes)

    Method notes, results and caveats for the peer comparison, including peers' count-method changes.

Sources

  1. HUD, 2007-2025 Point-in-Time Counts by CoC (AHAR Part 1 data) Homeless counts (total, sheltered, unsheltered) and count type for each CoC and year. Downloaded from the Internet Archive snapshot because huduser.gov blocks scripted requests; contentDigest is the SHA-256 of that downloaded workbook (8,859,426 bytes).

    Retrieved October 10, 2026. U.S. government work (public domain). Public domain; not rehosted here. Retrieve from HUD or the archived copy.

    Archived copy captured May 30, 2026

  2. U.S. Census Bureau, American Community Survey 1-year estimates, tables B01003, B25064, B25004, B25003 (2015-2019, 2021-2024) Population, median gross rent and rental vacancy for the counties and places that make up each CoC.

    Retrieved October 10, 2026. U.S. government work (public domain). Public domain; values used are in coc-panel.

    Archived copy captured May 21, 2026

  3. KCRHA, 2024 Point-in-Time Count FAQ v2 Documents King County's respondent-driven sampling (RDS) method from 2022 and the 2024 revision to 16,868.

    Retrieved October 10, 2026. Public agency document. Linked, not rehosted.

    Archived copy captured October 10, 2026

  4. Almquist ZW et al., "Innovating a community-driven enumeration and needs assessment of people experiencing homelessness," American Journal of Epidemiology 194(6), 2024 Only quantitative comparison of King County's 2022 RDS estimate with a forecast of the old visual-count method; basis for the method-adjustment sensitivity range.

    Retrieved October 10, 2026. Open-access journal article. Linked, not rehosted.

    Archived copy captured October 10, 2026

Limitations and reproducibility

Reproducible from public sources: Download the HUD workbook and ACS tables listed in sources, export the workbook sheets with xlsb-export-script, then run build-panel-script, peers-script and residuals-script (Node.js). Outputs match the tables here.

  • PIT counts are single January nights; methods vary by CoC and change over time.
  • King County changed its unsheltered count method in 2022 (respondent-driven sampling). The estimated effect ranges from 0 to about 3,600 people in 2024.
  • Rates per 10,000 are FactHub calculations. HUD does not publish CoC-level rates.
  • CoC boundaries are rebuilt from whole Census geographies with small gaps (see coc-geography).
  • Multi-county median rent is a renter-weighted average of county medians, not a true median.
  • Rent alone explains 2-14% of the variation in total rates across all 67 CoCs (24-45% among Major City CoCs).
  • All results are associations, not causal estimates.

Publications using this dataset

Version details

The exact citing versions, and the version of this dataset each cites.

  • Article seattle-homelessness-spending-results — version 5 (published) cites version 1
  • Article seattle-homelessness-spending-results — version 4 (published) cites version 1
  • Article seattle-homelessness-spending-results — version 3 (published) cites version 1
  • Article seattle-homelessness-spending-results — version 2 (published) cites version 1
  • Dataset homeless-system-performance — version 1 (published) cites version 1
  • Dataset king-county-homeless-count-beds — version 2 (published) cites version 1