Maywood, NJ
Maywood wildfire risk explained
Maywood sits at the 17th percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 3,345 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Maywood at the 19th national percentile — 3 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
94.1% of Maywood's 3,345 buildings sit in USFS's Minimal exposure zone, with only 5.9% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Where Maywood ranks
Maywood's risk sits at a similar level relative to New Jersey (2nd percentile statewide) as it does nationally (17th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Maywood ranks 26,259 for wildfire risk (1 is highest) and 4,987 by building count (1 is largest). Within New Jersey alone, it ranks 684 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
What this risk score means for insurance
Maywood's low rating (17th 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
Even with 94.1% of Maywood outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Maywood's figures come from
The methodology guide shows exactly how USFS turned 3,345 counted buildings into the percentiles shown above for Maywood. The exposure-zones guide covers what Maywood's dominant minimal exposure actually means, with real examples from across the dataset.