WildfireRiskFinder

Stout, IA

How exposed is Stout to wildfire?

Low
2ndpercentile nationally

Stout's 161 buildings earn a 2nd-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places nationally. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Stout at the 2nd national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.

What "at risk" means for the buildings here

161Total buildings
14.9%Direct exposure
0%Indirect exposure
85.1%Minimal exposure

Most of Stout's buildings (85.1% of 161) 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 Stout ranks

Stout's risk sits at a similar level relative to Iowa (3rd percentile statewide) as it does nationally (2nd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Stout ranks 30,860 for wildfire risk (1 is highest) and 26,380 by building count (1 is largest). Within Iowa alone, it ranks 987 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.

What this risk score means for insurance

Stout's low wildfire rating (2nd 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 Stout

Even with 85.1% of Stout outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.

Where Stout's figures come from

Stout's 2nd-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 Stout's dominant minimal exposure actually means, with real examples from across the dataset.