WildfireRiskFinder

Quinebaug, CT

How exposed is Quinebaug to wildfire?

Moderate
26thpercentile nationally

Quinebaug's 729 buildings earn a 26th-percentile wildfire-risk score nationally under USFS's model — close to the middle of USFS's national wildfire-risk range. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Quinebaug at the 24th percentile, close to its 26th-percentile risk score.

What "at risk" means for the buildings here

729Total buildings
75.7%Direct exposure
24.3%Indirect exposure
0%Minimal exposure

Of Quinebaug's 729 counted buildings, 75.7% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.

How Quinebaug compares

Quinebaug's risk sits at a similar level relative to Connecticut (29th percentile statewide) as it does nationally (26th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Quinebaug ranks 23,345 for wildfire risk (1 is highest) and 14,346 by building count (1 is largest). Within Connecticut alone, it ranks 152 of 214 places by risk. See the full county-by-county picture for Connecticut on its state page.

Shopping for coverage in Quinebaug

Quinebaug's moderate rating (26th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

What would actually reduce this score

Quinebaug's 75.7% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.

Where Quinebaug's figures come from

The methodology guide shows exactly how USFS turned 729 counted buildings into the percentiles shown above for Quinebaug. The exposure-zones guide covers what Quinebaug's dominant direct exposure actually means, with real examples from across the dataset.