Maben, MS
Maben, MS's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Maben at the 63rd national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 454 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 Maben at the 65th percentile, close to its 63rd-percentile risk score.
Maben's building exposure, zone by zone
Direct exposure dominates in Maben: 68.3% of its 454 buildings, versus 31.7% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Maben against the rest of the country
Inside Mississippi, Maben sits at just the 40th percentile even though it scores 63rd 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, Maben ranks 11,599 for wildfire risk (1 is highest) and 18,190 by building count (1 is largest). Within Mississippi alone, it ranks 251 of 420 places by risk. See the full county-by-county picture for Mississippi on its state page.
Shopping for coverage in Maben
At the 63rd percentile nationally, Maben 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
Maben's 68.3% 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 Maben's figures come from
Maben's 63rd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Maben's dominant direct exposure actually means, with real examples from across the dataset.