Stewart, MS
Stewart wildfire risk explained
Out of every US place USFS scores, Stewart lands at the 68th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 112 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Stewart at the 70th percentile, close to its 68th-percentile risk score.
Where Stewart's buildings actually sit
Of Stewart's 112 counted buildings, 95.5% 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.
Stewart against the rest of the country
Stewart ranks lower within Mississippi (52nd percentile statewide) than its 68th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Stewart ranks 10,055 for wildfire risk (1 is highest) and 28,544 by building count (1 is largest). Within Mississippi alone, it ranks 207 of 420 places by risk. See the full county-by-county picture for Mississippi on its state page.
Shopping for coverage in Stewart
Stewart's high rating (68th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
Lowering exposure, not just insuring around it
With 95.5% of Stewart in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Stewart's figures come from
Stewart's 68th-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 Stewart's dominant direct exposure actually means, with real examples from across the dataset.