Stepney, CT
Stepney wildfire risk explained
USFS's Wildfire Risk to Communities model puts Stepney at the 42nd national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 1,903 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Stepney at the 40th national percentile — 2 points below 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 86.7% of Stepney's buildings as Direct exposure, higher than its 13.3% Indirect share and far above its 0% Minimal share — a profile where 1,650 structures sit close enough to vegetation that lot clearing matters most.
How Stepney compares
Within Connecticut, Stepney ranks higher (88th percentile) than it does nationally (42nd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Stepney ranks 18,330 for wildfire risk (1 is highest) and 7,752 by building count (1 is largest). Within Connecticut alone, it ranks 26 of 214 places by risk. See the full county-by-county picture for Connecticut on its state page.
Shopping for coverage in Stepney
At the 42nd national percentile, Stepney rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Stepney
With 86.7% of Stepney 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 Stepney's figures come from
Stepney's 42nd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Stepney's dominant direct exposure actually means, with real examples from across the dataset.