Five Points, OH
How exposed is Five Points to wildfire?
Five Points sits at the 19th percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 973 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Five Points's burn probability — fire likelihood with no building count factored in — sits at the 21st percentile nationally.
What "at risk" means for the buildings here
Direct exposure dominates in Five Points: 75.6% of its 973 buildings, versus 0% Indirect and 24.4% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Five Points against the rest of the country
Within Ohio, Five Points ranks higher (50th percentile) than it does nationally (19th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Five Points ranks 25,413 for wildfire risk (1 is highest) and 12,121 by building count (1 is largest). Within Ohio alone, it ranks 634 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
Five Points'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.
What would actually reduce this score
Because Direct exposure dominates in Five Points (75.6%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Five Points's figures come from
Five Points'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 Five Points's dominant direct exposure actually means, with real examples from across the dataset.