Fairforest, SC
Fairforest wildfire risk explained
USFS's Wildfire Risk to Communities model puts Fairforest at the 53rd national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 930 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Fairforest at the 56th national percentile — 3 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Fairforest's buildings actually sit
Most of Fairforest's buildings (52.6% of 930) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
How Fairforest compares
Fairforest ranks lower within South Carolina (6th percentile statewide) than its 53rd national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Fairforest ranks 14,855 for wildfire risk (1 is highest) and 12,472 by building count (1 is largest). Within South Carolina alone, it ranks 445 of 474 places by risk. See the full county-by-county picture for South Carolina on its state page.
Shopping for coverage in Fairforest
At the 53rd national percentile, Fairforest rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Even with 52.6% of Fairforest 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 Fairforest's figures come from
The methodology guide shows exactly how USFS turned 930 counted buildings into the percentiles shown above for Fairforest. The exposure-zones guide covers what Fairforest's dominant minimal exposure actually means, with real examples from across the dataset.