Aviston, IL
Aviston wildfire risk explained
Out of every US place USFS scores, Aviston lands at the 5th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 979 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Aviston at the 6th percentile, close to its 5th-percentile risk score.
Where Aviston's buildings actually sit
USFS puts 52.7% of Aviston's 979 buildings in the Indirect exposure zone, versus 12.2% Direct and 35.1% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Aviston against the rest of the country
Aviston's 30th-percentile standing inside Illinois outpaces its 5th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Aviston ranks 29,837 for wildfire risk (1 is highest) and 12,079 by building count (1 is largest). Within Illinois alone, it ranks 1,013 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.
What this risk score means for insurance
Aviston's low wildfire rating (5th 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
Aviston's 52.7% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Aviston's figures come from
Aviston's 5th-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 Aviston's dominant indirect exposure actually means, with real examples from across the dataset.