East Peru, IA
How exposed is East Peru to wildfire?
USFS's Wildfire Risk to Communities model puts East Peru at the 66th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 105 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, East Peru's burn probability — fire likelihood with no building count factored in — sits at the 67th percentile nationally.
Where East Peru's buildings actually sit
Direct exposure dominates in East Peru: 82.9% of its 105 buildings, versus 17.1% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
How East Peru compares
Within Iowa, East Peru ranks higher (89th percentile) than it does nationally (66th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, East Peru ranks 10,839 for wildfire risk (1 is highest) and 28,798 by building count (1 is largest). Within Iowa alone, it ranks 112 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in East Peru
East Peru's 66th-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 East Peru
East Peru's 82.9% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where East Peru's figures come from
Every one of the two percentiles behind East Peru's 10,839-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what East Peru's dominant direct exposure actually means, with real examples from across the dataset.