St. Benedict, PA
St. Benedict wildfire risk explained
St. Benedict sits at the 46th percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 230 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, St. Benedict's burn probability — fire likelihood with no building count factored in — sits at the 46th percentile nationally.
What "at risk" means for the buildings here
89.1% of St. Benedict's 230 buildings sit in USFS's Direct exposure zone, roughly 205 structures close enough to burnable vegetation for flame contact, not just embers — 10.9% fall in the Indirect, ember-only zone and 0% are Minimal.
St. Benedict against the rest of the country
Compare St. Benedict's two percentiles: 73rd within Pennsylvania, only 46th nationally — a gap of 28 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, St. Benedict ranks 17,159 for wildfire risk (1 is highest) and 23,805 by building count (1 is largest). Within Pennsylvania alone, it ranks 534 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
St. Benedict and the insurance market
At the 46th national percentile, St. Benedict 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 89.1% of St. Benedict 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 St. Benedict's figures come from
The methodology guide shows exactly how USFS turned 230 counted buildings into the percentiles shown above for St. Benedict. The exposure-zones guide covers what St. Benedict's dominant direct exposure actually means, with real examples from across the dataset.