Sylvester, WV
Sylvester wildfire risk explained
USFS scores Sylvester at the 94th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 95 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Sylvester's burn probability — fire likelihood with no building count factored in — sits at the 95th percentile nationally.
What "at risk" means for the buildings here
USFS puts 100% of Sylvester's 95 buildings in the Indirect exposure zone, versus 0% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
How Sylvester compares
There's little gap between Sylvester's 94th national percentile and its 92nd 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, Sylvester ranks 2,065 for wildfire risk (1 is highest) and 29,294 by building count (1 is largest). Within West Virginia alone, it ranks 38 of 429 places by risk. See the full county-by-county picture for West Virginia on its state page.
Shopping for coverage in Sylvester
Sylvester's 94th-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.
Lowering exposure, not just insuring around it
With ember exposure the dominant pattern in Sylvester (100% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Sylvester's figures come from
Sylvester's 94th-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 Sylvester's dominant indirect exposure actually means, with real examples from across the dataset.