WildfireRiskFinder

Alvo, NE

Alvo wildfire risk explained

Elevated
43rdpercentile nationally

USFS's Wildfire Risk to Communities model puts Alvo at the 43rd national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 121 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Alvo's burn probability — fire likelihood with no building count factored in — sits at the 39th percentile nationally.

What "at risk" means for the buildings here

121Total buildings
12.4%Direct exposure
0%Indirect exposure
87.6%Minimal exposure

Alvo rates 87.6% Minimal exposure against just 12.4% Direct and 0% Indirect — of 121 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.

How Alvo compares

Alvo's 43rd national percentile looks worse in isolation than its 27th ranking inside Nebraska does — this place is on the milder end for its own state, by 16 points. Among the 31,521 US communities USFS scores, Alvo ranks 17,964 for wildfire risk (1 is highest) and 28,116 by building count (1 is largest). Within Nebraska alone, it ranks 424 of 583 places by risk. See the full county-by-county picture for Nebraska on its state page.

What this risk score means for insurance

Alvo's elevated wildfire rating (43rd percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.

Lowering exposure, not just insuring around it

Alvo's 87.6% 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 Alvo's figures come from

Alvo's 43rd-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 Alvo's dominant minimal exposure actually means, with real examples from across the dataset.