WildfireRiskFinder

Neffs, OH

Neffs wildfire risk explained

Moderate
38thpercentile nationally

USFS's Wildfire Risk to Communities model puts Neffs at the 38th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 645 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Neffs at the 40th percentile, close to its 38th-percentile risk score.

What "at risk" means for the buildings here

645Total buildings
63.9%Direct exposure
36.1%Indirect exposure
0%Minimal exposure

Direct exposure dominates in Neffs: 63.9% of its 645 buildings, versus 36.1% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.

How Neffs compares

Compare Neffs's two percentiles: 84th within Ohio, only 38th nationally — a gap of 45 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Neffs ranks 19,450 for wildfire risk (1 is highest) and 15,267 by building count (1 is largest). Within Ohio alone, it ranks 208 of 1,264 places by risk. See the full county-by-county picture for Ohio on its state page.

What this risk score means for insurance

Neffs's moderate wildfire rating (38th 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.

Hardening a home in Neffs

Neffs's 63.9% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.

Where Neffs's figures come from

The methodology guide shows exactly how USFS turned 645 counted buildings into the percentiles shown above for Neffs. The exposure-zones guide covers what Neffs's dominant direct exposure actually means, with real examples from across the dataset.