Four Bridges, OH
How exposed is Four Bridges to wildfire?
USFS's Wildfire Risk to Communities model puts Four Bridges at the 19th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 1,046 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 Four Bridges at the 21st percentile, close to its 19th-percentile risk score.
Where Four Bridges's buildings actually sit
USFS classifies 75.2% of Four Bridges's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 24.8% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Four Bridges ranks
Four Bridges's 49th-percentile standing inside Ohio outpaces its 19th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Four Bridges ranks 25,663 for wildfire risk (1 is highest) and 11,616 by building count (1 is largest). Within Ohio alone, it ranks 648 of 1,264 places by risk. See the full county-by-county picture for Ohio on its state page.
Shopping for coverage in Four Bridges
Four Bridges's low wildfire rating (19th 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
With 75.2% of buildings rated Minimal exposure, Four Bridges gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Four Bridges's figures come from
Four Bridges's 19th-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 Four Bridges's dominant minimal exposure actually means, with real examples from across the dataset.