Kincaid, WV
Kincaid wildfire risk explained
Kincaid sits at the 86th percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 167 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Kincaid at the 89th percentile, close to its 86th-percentile risk score.
What "at risk" means for the buildings here
USFS classifies 76.7% of Kincaid's buildings as Direct exposure, higher than its 23.4% Indirect share and far above its 0% Minimal share — a profile where 128 structures sit close enough to vegetation that lot clearing matters most.
Kincaid against the rest of the country
Kincaid scores 86th nationally and 75th within West Virginia — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Kincaid ranks 4,302 for wildfire risk (1 is highest) and 26,158 by building count (1 is largest). Within West Virginia alone, it ranks 107 of 429 places by risk. See the full county-by-county picture for West Virginia on its state page.
Kincaid and the insurance market
Kincaid's very high rating (86th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
Lowering exposure, not just insuring around it
With 76.7% of Kincaid in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Kincaid's figures come from
The methodology guide shows exactly how USFS turned 167 counted buildings into the percentiles shown above for Kincaid. The exposure-zones guide covers what Kincaid's dominant direct exposure actually means, with real examples from across the dataset.