WildfireRiskFinder

Cetronia, PA

Cetronia wildfire risk explained

Low
18thpercentile nationally

Cetronia's 984 buildings earn a 18th-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places nationally. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Cetronia at the 20th percentile, close to its 18th-percentile risk score.

Cetronia's building exposure, zone by zone

984Total buildings
12%Direct exposure
0%Indirect exposure
88%Minimal exposure

Most of Cetronia's buildings (88% of 984) 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.

Where Cetronia ranks

Cetronia scores 18th nationally and 19th within Pennsylvania — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Cetronia ranks 25,979 for wildfire risk (1 is highest) and 12,048 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,622 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

Cetronia's low wildfire rating (18th 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.

Hardening a home in Cetronia

Cetronia's 88% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.

Where Cetronia's figures come from

Cetronia's 18th-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 Cetronia's dominant minimal exposure actually means, with real examples from across the dataset.