WildfireRiskFinder

Iona, ID

How exposed is Iona to wildfire?

High
77thpercentile nationally

Out of every US place USFS scores, Iona lands at the 77th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 1,091 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Iona's burn probability — fire likelihood with no building count factored in — sits at the 71st percentile nationally.

Iona's building exposure, zone by zone

1,091Total buildings
34%Direct exposure
19.2%Indirect exposure
46.8%Minimal exposure

Iona rates 46.8% Minimal exposure against just 34% Direct and 19.2% Indirect — of 1,091 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.

How Iona compares

Iona's 77th national percentile looks worse in isolation than its 44th ranking inside Idaho does — this place is on the milder end for its own state, by 33 points. Among the 31,521 US communities USFS scores, Iona ranks 7,278 for wildfire risk (1 is highest) and 11,334 by building count (1 is largest). Within Idaho alone, it ranks 131 of 232 places by risk. See the full county-by-county picture for Idaho on its state page.

What this risk score means for insurance

At the 77th percentile nationally, Iona carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.

Lowering exposure, not just insuring around it

Iona's 46.8% 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 Iona's figures come from

The methodology guide shows exactly how USFS turned 1,091 counted buildings into the percentiles shown above for Iona. The exposure-zones guide covers what Iona's dominant minimal exposure actually means, with real examples from across the dataset.