Grace, MS
Grace wildfire risk explained
Grace sits at the 29th percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 74 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Grace at the 30th percentile, close to its 29th-percentile risk score.
Where Grace's buildings actually sit
Most of Grace's buildings (59.5%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Where Grace ranks
Grace ranks lower within Mississippi (9th percentile statewide) than its 29th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Grace ranks 22,280 for wildfire risk (1 is highest) and 30,135 by building count (1 is largest). Within Mississippi alone, it ranks 383 of 420 places by risk. See the full county-by-county picture for Mississippi on its state page.
What this risk score means for insurance
Grace's moderate rating (29th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Hardening a home in Grace
Because 59.5% of Grace'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 Grace's figures come from
Every one of the two percentiles behind Grace's 22,280-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Grace's dominant indirect exposure actually means, with real examples from across the dataset.