Madison, WV
Madison wildfire risk explained
USFS's Wildfire Risk to Communities model puts Madison at the 92nd national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 1,467 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Madison's burn probability — fire likelihood with no building count factored in — sits at the 94th percentile nationally.
What "at risk" means for the buildings here
Indirect exposure is dominant in Madison (82.7% of 1,467 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 17.3% sit in the Direct zone.
Madison against the rest of the country
There's little gap between Madison's 92nd national percentile and its 86th percentile inside West Virginia, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Madison ranks 2,663 for wildfire risk (1 is highest) and 9,329 by building count (1 is largest). Within West Virginia alone, it ranks 61 of 429 places by risk. See the full county-by-county picture for West Virginia on its state page.
Madison and the insurance market
Madison's 92nd-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Madison
With ember exposure the dominant pattern in Madison (82.7% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Madison's figures come from
Madison's 92nd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Madison's dominant indirect exposure actually means, with real examples from across the dataset.