Conehatta, MS
Conehatta, MS's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Conehatta at the 63rd national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 597 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Conehatta at the 65th percentile, close to its 63rd-percentile risk score.
Conehatta's building exposure, zone by zone
100% of Conehatta's 597 buildings sit in USFS's Direct exposure zone, roughly 597 structures close enough to burnable vegetation for flame contact, not just embers — 0% fall in the Indirect, ember-only zone and 0% are Minimal.
Where Conehatta ranks
Conehatta ranks lower within Mississippi (40th percentile statewide) than its 63rd national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Conehatta ranks 11,785 for wildfire risk (1 is highest) and 15,884 by building count (1 is largest). Within Mississippi alone, it ranks 253 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
At the 63rd percentile nationally, Conehatta 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.
Lowering exposure, not just insuring around it
Conehatta'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 Conehatta's figures come from
The methodology guide shows exactly how USFS turned 597 counted buildings into the percentiles shown above for Conehatta. The exposure-zones guide covers what Conehatta's dominant direct exposure actually means, with real examples from across the dataset.