Heilwood, PA
Heilwood wildfire risk explained
Out of every US place USFS scores, Heilwood lands at the 44th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 219 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Heilwood at the 44th percentile, close to its 44th-percentile risk score.
Where Heilwood's buildings actually sit
Of Heilwood's 219 counted buildings, 66.2% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Where Heilwood ranks
Heilwood's 71st-percentile standing inside Pennsylvania outpaces its 44th 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, Heilwood ranks 17,662 for wildfire risk (1 is highest) and 24,172 by building count (1 is largest). Within Pennsylvania alone, it ranks 583 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Shopping for coverage in Heilwood
At the 44th national percentile, Heilwood rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
With 66.2% of Heilwood in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Heilwood's figures come from
The methodology guide shows exactly how USFS turned 219 counted buildings into the percentiles shown above for Heilwood. The exposure-zones guide covers what Heilwood's dominant direct exposure actually means, with real examples from across the dataset.