WildfireRiskFinder

Ovid, CO

Ovid wildfire risk explained

Elevated
48thpercentile nationally

USFS scores Ovid at the 48th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 256 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Ovid's burn probability — fire likelihood with no building count factored in — sits at the 47th percentile nationally.

Where Ovid's buildings actually sit

256Total buildings
0%Direct exposure
100%Indirect exposure
0%Minimal exposure

100% of Ovid's 256 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 0% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.

How Ovid compares

Ovid ranks lower within Colorado (15th percentile statewide) than its 48th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Ovid ranks 16,346 for wildfire risk (1 is highest) and 22,933 by building count (1 is largest). Within Colorado alone, it ranks 402 of 472 places by risk. See the full county-by-county picture for Colorado on its state page.

Shopping for coverage in Ovid

Ovid's elevated rating (48th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Hardening a home in Ovid

Ovid's 100% 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 Ovid's figures come from

Ovid's 48th-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 Ovid's dominant indirect exposure actually means, with real examples from across the dataset.