WildfireRiskFinder

Pana, IL

Pana wildfire risk explained

Low
18thpercentile nationally

Pana's 3,453 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 Pana at the 18th percentile, close to its 18th-percentile risk score.

Pana's building exposure, zone by zone

3,453Total buildings
13.7%Direct exposure
32.5%Indirect exposure
53.8%Minimal exposure

Only 13.7% of Pana's 3,453 buildings carry Direct exposure and 32.5% carry Indirect; the remaining 53.8% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.

How Pana compares

Within Illinois, Pana ranks higher (58th percentile) than it does nationally (18th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Pana ranks 25,866 for wildfire risk (1 is highest) and 4,841 by building count (1 is largest). Within Illinois alone, it ranks 602 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.

What this risk score means for insurance

Pana'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.

Lowering exposure, not just insuring around it

Pana's 53.8% 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 Pana's figures come from

Every one of the two percentiles behind Pana's 25,866-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Pana's dominant minimal exposure actually means, with real examples from across the dataset.