Sans Souci, SC
Sans Souci wildfire risk explained
USFS's Wildfire Risk to Communities model puts Sans Souci at the 54th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 4,025 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Sans Souci's burn probability — fire likelihood with no building count factored in — sits at the 57th percentile nationally.
What "at risk" means for the buildings here
USFS puts 35% of Sans Souci's 4,025 buildings in the Indirect exposure zone, versus 30.9% Direct and 34.1% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Where Sans Souci ranks
Inside South Carolina, Sans Souci sits at just the 9th percentile even though it scores 54th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Sans Souci ranks 14,666 for wildfire risk (1 is highest) and 4,223 by building count (1 is largest). Within South Carolina alone, it ranks 434 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
Sans Souci's elevated rating (54th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
Because 35% of Sans Souci's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Sans Souci's figures come from
Every one of the two percentiles behind Sans Souci's 14,666-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Sans Souci's dominant indirect exposure actually means, with real examples from across the dataset.