Mifflinburg, PA
Mifflinburg, PA's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Mifflinburg lands at the 15th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 1,734 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Mifflinburg's burn probability — fire likelihood with no building count factored in — sits at the 16th percentile nationally.
Mifflinburg's building exposure, zone by zone
Most of Mifflinburg's buildings (76.6% of 1,734) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
How Mifflinburg compares
There's little gap between Mifflinburg's 15th national percentile and its 14th percentile inside Pennsylvania, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Mifflinburg ranks 26,925 for wildfire risk (1 is highest) and 8,283 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,711 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
What this risk score means for insurance
Mifflinburg's low wildfire rating (15th 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.
What would actually reduce this score
With 76.6% of buildings rated Minimal exposure, Mifflinburg gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Mifflinburg's figures come from
The methodology guide shows exactly how USFS turned 1,734 counted buildings into the percentiles shown above for Mifflinburg. The exposure-zones guide covers what Mifflinburg's dominant minimal exposure actually means, with real examples from across the dataset.