Hiram, GA
How exposed is Hiram to wildfire?
Out of every US place USFS scores, Hiram lands at the 74th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 1,995 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Hiram's burn probability — fire likelihood with no building count factored in — sits at the 78th percentile nationally.
Where Hiram's buildings actually sit
USFS puts 55.8% of Hiram's 1,995 buildings in the Indirect exposure zone, versus 41% Direct and 3.2% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Hiram against the rest of the country
There's little gap between Hiram's 74th national percentile and its 79th percentile inside Georgia, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Hiram ranks 8,185 for wildfire risk (1 is highest) and 7,489 by building count (1 is largest). Within Georgia alone, it ranks 141 of 669 places by risk. See the full county-by-county picture for Georgia on its state page.
What this risk score means for insurance
Hiram's 74th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Hiram
Because 55.8% of Hiram's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Hiram's figures come from
Every one of the two percentiles behind Hiram's 8,185-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Hiram's dominant indirect exposure actually means, with real examples from across the dataset.