WildfireRiskFinder

Osgood, MO

How exposed is Osgood to wildfire?

High
63rdpercentile nationally

Osgood's 38 buildings earn a 63rd-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Osgood at the 64th percentile, close to its 63rd-percentile risk score.

Where Osgood's buildings actually sit

38Total buildings
73.7%Direct exposure
26.3%Indirect exposure
0%Minimal exposure

Of Osgood's 38 counted buildings, 73.7% 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.

How Osgood compares

Osgood's risk sits at a similar level relative to Missouri (63rd percentile statewide) as it does nationally (63rd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Osgood ranks 11,695 for wildfire risk (1 is highest) and 31,210 by building count (1 is largest). Within Missouri alone, it ranks 395 of 1,062 places by risk. See the full county-by-county picture for Missouri on its state page.

Shopping for coverage in Osgood

Osgood's 63rd-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.

Lowering exposure, not just insuring around it

Because Direct exposure dominates in Osgood (73.7%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Osgood's figures come from

The methodology guide shows exactly how USFS turned 38 counted buildings into the percentiles shown above for Osgood. The exposure-zones guide covers what Osgood's dominant direct exposure actually means, with real examples from across the dataset.