Van Vleet, MS
Van Vleet wildfire risk explained
USFS scores Van Vleet at the 59th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 84 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Van Vleet at the 61st national percentile — 3 points above its risk-to-structures score, a gap driven by how much is actually built there.
Van Vleet's building exposure, zone by zone
Of Van Vleet's 84 counted buildings, 100% 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.
Where Van Vleet ranks
Van Vleet ranks lower within Mississippi (32nd percentile statewide) than its 59th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Van Vleet ranks 12,956 for wildfire risk (1 is highest) and 29,731 by building count (1 is largest). Within Mississippi alone, it ranks 289 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
Van Vleet's elevated wildfire rating (59th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Hardening a home in Van Vleet
Van Vleet's 100% 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 Van Vleet's figures come from
Every one of the two percentiles behind Van Vleet's 12,956-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Van Vleet's dominant direct exposure actually means, with real examples from across the dataset.