New Cambria, MO
New Cambria wildfire risk explained
Out of every US place USFS scores, New Cambria lands at the 66th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 181 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, New Cambria's burn probability — fire likelihood with no building count factored in — sits at the 68th percentile nationally.
Where New Cambria's buildings actually sit
181 buildings are counted in New Cambria, and 60.8% of them are Indirect exposure — ember-driven risk rather than the 39.2% in Direct exposure or the 0% rated Minimal.
How New Cambria compares
New Cambria scores 66th nationally and 73rd within Missouri — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, New Cambria ranks 10,593 for wildfire risk (1 is highest) and 25,587 by building count (1 is largest). Within Missouri alone, it ranks 289 of 1,062 places by risk. See the full county-by-county picture for Missouri on its state page.
Shopping for coverage in New Cambria
New Cambria's 66th-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.
Hardening a home in New Cambria
Because 60.8% of New Cambria's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where New Cambria's figures come from
Every one of the two percentiles behind New Cambria's 10,593-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what New Cambria's dominant indirect exposure actually means, with real examples from across the dataset.