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Volume 31, Number 4—April 2025
Research

Predictive Model for Estimating Annual Ebolavirus Spillover Potential

Carson T. TelfordComments to Author , Brian R. Amman, Jonathan S. Towner, Joel M. Montgomery, Justin Lessler, and Trevor Shoemaker
Author affiliation: Centers for Disease Control and Prevention, Atlanta, Georgia, USA (C.T. Telford, B.R. Amman, J.S. Towner, J.M. Montgomery, T. Shoemaker); University of North Carolina, Chapel Hill, North Carolina, USA (C.T. Telford, J. Lessler); Johns Hopkins University, Baltimore, Maryland, USA (J. Lessler)

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Figure 3

RORs for spillover from predictive model for estimating annual Ebolavirus spillover potential. A, B) RORs for spillover in 2022 in the multispecies (A) and ZEBOV-only (B) models. C, D) Top 1% RORs (1-km2 grid cells) in multispecies (C) and ZEBOV-only (D) models. Multispecies model combined BDBV, SUDV, and ZEBOV. RORs were calculated by using the estimated odds of Ebolavirus spillover divided by the average estimate across the entire study area. BDBV, Bundibugyo ebolavirus; ROR, relative odds ratio; SUDV, Sudan ebolavirus; ZEBOV, Zaire ebolavirus.

Figure 3. RORs for spillover from predictive model for estimating annual Ebolavirus spillover potential. A, B) RORs for spillover in 2022 in the multispecies (A) and ZEBOV-only (B) models. C, D) Top 1% RORs (1-km2 grid cells) in multispecies (C) and ZEBOV-only (D) models. Multispecies model combined BDBV, SUDV, and ZEBOV. RORs were calculated by using the estimated odds of Ebolavirus spillover divided by the average estimate across the entire study area. BDBV, Bundibugyo ebolavirus; ROR, relative odds ratio; SUDV, Sudan ebolavirus; ZEBOV, Zaire ebolavirus.

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Page created: February 10, 2025
Page updated: March 24, 2025
Page reviewed: March 24, 2025
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