Afton, IA
Afton wildfire risk explained
Out of every US place USFS scores, Afton lands at the 72nd percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 566 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Afton at the 74th percentile, close to its 72nd-percentile risk score.
Afton's building exposure, zone by zone
Most of Afton's buildings (73.7%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Where Afton ranks
Within Iowa, Afton ranks higher (95th percentile) than it does nationally (72nd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Afton ranks 8,854 for wildfire risk (1 is highest) and 16,306 by building count (1 is largest). Within Iowa alone, it ranks 48 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Afton
Afton's 72nd-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Afton
Afton's 73.7% 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 Afton's figures come from
The methodology guide shows exactly how USFS turned 566 counted buildings into the percentiles shown above for Afton. The exposure-zones guide covers what Afton's dominant indirect exposure actually means, with real examples from across the dataset.