Severn, NC
Severn, NC's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Severn at the 43rd national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 237 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Severn's burn probability — fire likelihood with no building count factored in — sits at the 43rd percentile nationally.
Severn's building exposure, zone by zone
51.5% of Severn's 237 buildings sit in USFS's Direct exposure zone, roughly 122 structures close enough to burnable vegetation for flame contact, not just embers — 48.5% fall in the Indirect, ember-only zone and 0% are Minimal.
How Severn compares
Inside North Carolina, Severn sits at just the 21st percentile even though it scores 43rd 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, Severn ranks 17,971 for wildfire risk (1 is highest) and 23,563 by building count (1 is largest). Within North Carolina alone, it ranks 606 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
Shopping for coverage in Severn
Severn's elevated wildfire rating (43rd percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Lowering exposure, not just insuring around it
With 51.5% of Severn 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 Severn's figures come from
The methodology guide shows exactly how USFS turned 237 counted buildings into the percentiles shown above for Severn. The exposure-zones guide covers what Severn's dominant direct exposure actually means, with real examples from across the dataset.