Vance, SC
Vance wildfire risk explained
USFS's Wildfire Risk to Communities model puts Vance at the 79th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 116 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Vance at the 78th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
Vance's building exposure, zone by zone
USFS classifies 78.5% of Vance's buildings as Direct exposure, higher than its 21.6% Indirect share and far above its 0% Minimal share — a profile where 91 structures sit close enough to vegetation that lot clearing matters most.
Vance against the rest of the country
Vance's risk sits at a similar level relative to South Carolina (81st percentile statewide) as it does nationally (79th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Vance ranks 6,754 for wildfire risk (1 is highest) and 28,382 by building count (1 is largest). Within South Carolina alone, it ranks 93 of 474 places by risk. See the full county-by-county picture for South Carolina on its state page.
What this risk score means for insurance
At the 79th percentile nationally, Vance carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
What would actually reduce this score
Vance's 78.5% 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 Vance's figures come from
Every one of the two percentiles behind Vance's 6,754-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Vance's dominant direct exposure actually means, with real examples from across the dataset.