Forest Lakes, AZ
Forest Lakes, AZ's wildfire risk, in USFS's own numbers
Forest Lakes sits at the 99th percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 776 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Forest Lakes at the 99th national percentile — 0 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
Of Forest Lakes's 776 counted buildings, 100% 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 Forest Lakes compares
There's little gap between Forest Lakes's 99th national percentile and its 96th percentile inside Arizona, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Forest Lakes ranks 178 for wildfire risk (1 is highest) and 13,848 by building count (1 is largest). Within Arizona alone, it ranks 18 of 441 places by risk. See the full county-by-county picture for Arizona on its state page.
What this risk score means for insurance
Forest Lakes's very high rating (99th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
Hardening a home in Forest Lakes
Because Direct exposure dominates in Forest Lakes (100%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Forest Lakes's figures come from
The methodology guide shows exactly how USFS turned 776 counted buildings into the percentiles shown above for Forest Lakes. The exposure-zones guide covers what Forest Lakes's dominant direct exposure actually means, with real examples from across the dataset.