Effingham, KS
How exposed is Effingham to wildfire?
Effingham sits at the 69th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 434 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Effingham at the 69th percentile, close to its 69th-percentile risk score.
What "at risk" means for the buildings here
Effingham rates 60.1% Minimal exposure against just 39.9% Direct and 0% Indirect — of 434 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Effingham against the rest of the country
Effingham scores 69th nationally and 65th within Kansas — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Effingham ranks 9,928 for wildfire risk (1 is highest) and 18,563 by building count (1 is largest). Within Kansas alone, it ranks 251 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.
Effingham and the insurance market
Effingham's high rating (69th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
What would actually reduce this score
Even with 60.1% of Effingham outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Effingham's figures come from
Every one of the two percentiles behind Effingham's 9,928-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Effingham's dominant minimal exposure actually means, with real examples from across the dataset.