Malcolm, NE
Malcolm wildfire risk explained
Out of every US place USFS scores, Malcolm lands at the 79th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 207 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Malcolm at the 72nd percentile, close to its 79th-percentile risk score.
What "at risk" means for the buildings here
Malcolm rates 88.4% Minimal exposure against just 11.6% Direct and 0% Indirect — of 207 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Where Malcolm ranks
Malcolm scores 79th nationally and 84th within Nebraska — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Malcolm ranks 6,746 for wildfire risk (1 is highest) and 24,606 by building count (1 is largest). Within Nebraska alone, it ranks 97 of 583 places by risk. See the full county-by-county picture for Nebraska on its state page.
Malcolm and the insurance market
Malcolm's 79th-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 Malcolm
With 88.4% of buildings rated Minimal exposure, Malcolm gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Malcolm's figures come from
Every one of the two percentiles behind Malcolm's 6,746-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Malcolm's dominant minimal exposure actually means, with real examples from across the dataset.