Conesville, IA
Conesville wildfire risk explained
USFS's Wildfire Risk to Communities model puts Conesville at the 43rd national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 223 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Conesville's burn probability — fire likelihood with no building count factored in — sits at the 43rd percentile nationally.
Where Conesville's buildings actually sit
84.3% of Conesville's 223 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 15.7% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Conesville against the rest of the country
Conesville's 59th-percentile standing inside Iowa outpaces its 43rd national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Conesville ranks 17,863 for wildfire risk (1 is highest) and 24,010 by building count (1 is largest). Within Iowa alone, it ranks 413 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
Conesville's elevated wildfire rating (43rd 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
Because 84.3% of Conesville's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Conesville's figures come from
The methodology guide shows exactly how USFS turned 223 counted buildings into the percentiles shown above for Conesville. The exposure-zones guide covers what Conesville's dominant indirect exposure actually means, with real examples from across the dataset.