East Worcester, NY
How exposed is East Worcester to wildfire?
USFS's Wildfire Risk to Communities model puts East Worcester at the 15th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 283 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts East Worcester at the 14th percentile, close to its 15th-percentile risk score.
What "at risk" means for the buildings here
Direct exposure dominates in East Worcester: 74.9% of its 283 buildings, versus 25.1% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Where East Worcester ranks
Compare East Worcester's two percentiles: 35th within New York, only 15th nationally — a gap of 20 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, East Worcester ranks 26,897 for wildfire risk (1 is highest) and 22,096 by building count (1 is largest). Within New York alone, it ranks 844 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.
What this risk score means for insurance
At the 15th national percentile, East Worcester rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
With 74.9% of East Worcester 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 East Worcester's figures come from
East Worcester's 15th-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 East Worcester's dominant direct exposure actually means, with real examples from across the dataset.