Wachapreague, VA
Wachapreague, VA's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Wachapreague at the 62nd national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 350 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Wachapreague at the 59th national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Wachapreague's buildings actually sit
USFS puts 74% of Wachapreague's 350 buildings in the Indirect exposure zone, versus 25.4% Direct and 0.6% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
How Wachapreague compares
Wachapreague's risk sits at a similar level relative to Virginia (69th percentile statewide) as it does nationally (62nd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Wachapreague ranks 12,022 for wildfire risk (1 is highest) and 20,323 by building count (1 is largest). Within Virginia alone, it ranks 211 of 681 places by risk. See the full county-by-county picture for Virginia on its state page.
Shopping for coverage in Wachapreague
Wachapreague's high rating (62nd 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
Wachapreague's 74% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Wachapreague's figures come from
Wachapreague's 62nd-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 Wachapreague's dominant indirect exposure actually means, with real examples from across the dataset.