Shelocta, PA
Shelocta, PA's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Shelocta at the 35th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 74 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Shelocta's burn probability — fire likelihood with no building count factored in — sits at the 35th percentile nationally.
Shelocta's building exposure, zone by zone
58.1% of Shelocta's 74 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 41.9% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
How Shelocta compares
Shelocta's risk sits at a similar level relative to Pennsylvania (49th percentile statewide) as it does nationally (35th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Shelocta ranks 20,559 for wildfire risk (1 is highest) and 30,149 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,012 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Shopping for coverage in Shelocta
Shelocta's moderate wildfire rating (35th 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
Shelocta's 58.1% 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 Shelocta's figures come from
Shelocta's 35th-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 Shelocta's dominant indirect exposure actually means, with real examples from across the dataset.