Fairfield, IA
Fairfield wildfire risk explained
Out of every US place USFS scores, Fairfield lands at the 62nd percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 4,697 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Fairfield's burn probability — fire likelihood with no building count factored in — sits at the 63rd percentile nationally.
What "at risk" means for the buildings here
Most of Fairfield's buildings (85.1% of 4,697) 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.
How Fairfield compares
Compare Fairfield's two percentiles: 85th within Iowa, only 62nd nationally — a gap of 24 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Fairfield ranks 12,096 for wildfire risk (1 is highest) and 3,625 by building count (1 is largest). Within Iowa alone, it ranks 152 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
Fairfield's 62nd-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.
What would actually reduce this score
Fairfield's 85.1% 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 Fairfield's figures come from
Every one of the two percentiles behind Fairfield's 12,096-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Fairfield's dominant minimal exposure actually means, with real examples from across the dataset.