Old Hundred, NC
Old Hundred wildfire risk explained
USFS scores Old Hundred at the 88th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 154 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Old Hundred at the 89th percentile, close to its 88th-percentile risk score.
What "at risk" means for the buildings here
Of Old Hundred's 154 counted buildings, 99.4% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Old Hundred against the rest of the country
Old Hundred's risk sits at a similar level relative to North Carolina (97th percentile statewide) as it does nationally (88th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Old Hundred ranks 3,881 for wildfire risk (1 is highest) and 26,713 by building count (1 is largest). Within North Carolina alone, it ranks 26 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
Old Hundred and the insurance market
Old Hundred's very high rating (88th 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.
Lowering exposure, not just insuring around it
Old Hundred's 99.4% 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 Old Hundred's figures come from
The methodology guide shows exactly how USFS turned 154 counted buildings into the percentiles shown above for Old Hundred. The exposure-zones guide covers what Old Hundred's dominant direct exposure actually means, with real examples from across the dataset.