Scipio, OK
How exposed is Scipio to wildfire?
USFS scores Scipio at the 98th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 69 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Scipio at the 99th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
USFS classifies 100% of Scipio's buildings as Direct exposure, higher than its 0% Indirect share and far above its 0% Minimal share — a profile where 69 structures sit close enough to vegetation that lot clearing matters most.
Where Scipio ranks
There's little gap between Scipio's 98th national percentile and its 98th percentile inside Oklahoma, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Scipio ranks 578 for wildfire risk (1 is highest) and 30,328 by building count (1 is largest). Within Oklahoma alone, it ranks 16 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
What this risk score means for insurance
Scipio's very high rating (98th 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.
Hardening a home in Scipio
With 100% of Scipio 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 Scipio's figures come from
Every one of the two percentiles behind Scipio's 578-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Scipio's dominant direct exposure actually means, with real examples from across the dataset.