Anegam, AZ
Anegam, AZ's wildfire risk, in USFS's own numbers
USFS scores Anegam at the 61st national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 104 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Anegam's burn probability — fire likelihood with no building count factored in — sits at the 59th percentile nationally.
Anegam's building exposure, zone by zone
Direct exposure dominates in Anegam: 100% of its 104 buildings, versus 0% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Anegam against the rest of the country
Anegam's 61st national percentile looks worse in isolation than its 27th ranking inside Arizona does — this place is on the milder end for its own state, by 34 points. Among the 31,521 US communities USFS scores, Anegam ranks 12,216 for wildfire risk (1 is highest) and 28,832 by building count (1 is largest). Within Arizona alone, it ranks 322 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
At the 61st percentile nationally, Anegam carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Hardening a home in Anegam
With 100% of Anegam 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 Anegam's figures come from
Every one of the two percentiles behind Anegam's 12,216-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Anegam's dominant direct exposure actually means, with real examples from across the dataset.