WildfireRiskFinder

Milo, IA

How exposed is Milo to wildfire?

Elevated
52ndpercentile nationally

USFS scores Milo at the 52nd national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 475 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Milo at the 53rd national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.

What "at risk" means for the buildings here

475Total buildings
22.7%Direct exposure
0%Indirect exposure
77.3%Minimal exposure

77.3% of Milo's 475 buildings sit in USFS's Minimal exposure zone, with only 22.7% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.

Where Milo ranks

Within Iowa, Milo ranks higher (71st percentile) than it does nationally (52nd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Milo ranks 15,186 for wildfire risk (1 is highest) and 17,799 by building count (1 is largest). Within Iowa alone, it ranks 293 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.

Shopping for coverage in Milo

Milo's elevated rating (52nd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Hardening a home in Milo

Milo's 77.3% 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 Milo's figures come from

Milo's 52nd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Milo's dominant minimal exposure actually means, with real examples from across the dataset.