Belington, WV
How exposed is Belington to wildfire?
USFS's Wildfire Risk to Communities model puts Belington at the 46th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 1,119 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Belington at the 47th percentile, close to its 46th-percentile risk score.
What "at risk" means for the buildings here
USFS puts 52.6% of Belington's 1,119 buildings in the Indirect exposure zone, versus 47.4% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
How Belington compares
Inside West Virginia, Belington sits at just the 31st percentile even though it scores 46th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Belington ranks 17,100 for wildfire risk (1 is highest) and 11,161 by building count (1 is largest). Within West Virginia alone, it ranks 297 of 429 places by risk. See the full county-by-county picture for West Virginia on its state page.
What this risk score means for insurance
At the 46th national percentile, Belington rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
With ember exposure the dominant pattern in Belington (52.6% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Belington's figures come from
Every one of the two percentiles behind Belington's 17,100-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Belington's dominant indirect exposure actually means, with real examples from across the dataset.