Tullytown, PA
Tullytown, PA's wildfire risk, in USFS's own numbers
USFS scores Tullytown at the 57th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 963 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Tullytown at the 57th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Most of Tullytown's buildings (96% of 963) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
How Tullytown compares
Within Pennsylvania, Tullytown ranks higher (93rd percentile) than it does nationally (57th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Tullytown ranks 13,627 for wildfire risk (1 is highest) and 12,205 by building count (1 is largest). Within Pennsylvania alone, it ranks 136 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Tullytown and the insurance market
Tullytown's elevated wildfire rating (57th 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 96% of buildings rated Minimal exposure, Tullytown gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Tullytown's figures come from
Every one of the two percentiles behind Tullytown's 13,627-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Tullytown's dominant minimal exposure actually means, with real examples from across the dataset.