Old Forge, PA
Old Forge, PA's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Old Forge at the 52nd national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 4,319 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 Old Forge at the 51st percentile, close to its 52nd-percentile risk score.
What "at risk" means for the buildings here
Indirect exposure is dominant in Old Forge (85.1% of 4,319 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 7.4% sit in the Direct zone.
Old Forge against the rest of the country
Old Forge's 85th-percentile standing inside Pennsylvania outpaces its 52nd national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Old Forge ranks 15,206 for wildfire risk (1 is highest) and 3,967 by building count (1 is largest). Within Pennsylvania alone, it ranks 291 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
What this risk score means for insurance
Old Forge's elevated wildfire rating (52nd percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
What would actually reduce this score
With ember exposure the dominant pattern in Old Forge (85.1% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Old Forge's figures come from
Every one of the two percentiles behind Old Forge's 15,206-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Old Forge's dominant indirect exposure actually means, with real examples from across the dataset.