Telford Carson T, Amman Brian R, Towner Jonathan S, Montgomery Joel M, Lessler Justin, Shoemaker Trevor
Emerg Infect Dis. 2025 Apr;31(4):689-698. doi: 10.3201/eid3104.241193.
Forest changes, human population dynamics, and meteorologic conditions have been associated with zoonotic Ebolavirus spillover into humans. High-resolution spatial data for those variables can be used to produce estimates of spillover potential and assess possible annual changes. We developed a model of Ebolavirus spillover during 2001-2021, accounting for variables measured across multiple spatial and temporal scales. We estimated the annual relative odds of Ebolavirus spillover during 2021 and 2022. The highest relative spillover odds estimates occurred in patches that closely followed the spatial distribution of forest loss and fragmentation. Regions throughout equatorial Africa had increased spillover estimates related to changes in forests and human populations. Spillover events in 2022 occurred in locations in the top 0.1% of overall spillover odds estimates or where estimates increased from 2021 to 2022. This model can be used to preemptively target surveillance to identify outbreaks, mitigate disease spread, and educate the public on risk factors for infection.
森林变化、人口动态和气象条件与埃博拉病毒跨物种传播至人类有关。这些变量的高分辨率空间数据可用于估算传播潜力并评估可能的年度变化。我们建立了一个2001年至2021年期间埃博拉病毒跨物种传播模型，纳入了在多个空间和时间尺度上测量的变量。我们估算了2021年和2022年埃博拉病毒跨物种传播的年度相对概率。最高的相对传播概率估算值出现在紧密跟随森林损失和破碎化空间分布的区域。赤道非洲各地与森林和人口变化相关的传播估算值有所增加。2022年的传播事件发生在总体传播概率估算值处于前0.1%的地点，或估算值从2021年到2022年有所增加的地点。该模型可用于预先确定监测目标，以发现疫情、减轻疾病传播，并就感染风险因素对公众进行教育。
