Warren, MA
Warren wildfire risk explained
USFS's Wildfire Risk to Communities model puts Warren at the 28th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 592 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Warren at the 26th national percentile — 2 points below its risk-to-structures score, a gap driven by how much is actually built there.
Warren's building exposure, zone by zone
Direct exposure dominates in Warren: 55.2% of its 592 buildings, versus 44.8% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Where Warren ranks
Within Massachusetts, Warren ranks higher (69th percentile) than it does nationally (28th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Warren ranks 22,537 for wildfire risk (1 is highest) and 15,938 by building count (1 is largest). Within Massachusetts alone, it ranks 77 of 248 places by risk. See the full county-by-county picture for Massachusetts on its state page.
Warren and the insurance market
Warren's moderate wildfire rating (28th 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 55.2% of Warren 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 Warren's figures come from
Warren's 28th-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 Warren's dominant direct exposure actually means, with real examples from across the dataset.