Supplementary data files from Ecological indicators of mammal exposure to Ebolavirus

Much of the basic ecology of Ebolavirus remains unresolved despite accumulating disease outbreaks, viral strains and evidence of animal hosts. Because human Ebolavirus epidemics have been linked to contact with wild mammals other than bats, traits shared by species that have been infected by Ebolavirus and their phylogenetic distribution could suggest ecological mechanisms contributing to human Ebolavirus spillovers. We compiled data on Ebolavirus exposure in mammals and corresponding data on life-history traits, movement, and diet, and used boosted regression trees (BRT) to identify predictors of exposure and infection for 119 species (hereafter hosts). Mapping the phylogenetic distribution of presumptive Ebolavirus hosts reveals that they are scattered across several distinct mammal clades, but concentrated among Old World fruit bats, primates and artiodactyls. While sampling effort was the most important predictor, explaining nearly as much of the variation among hosts as traits, BRT models distinguished hosts from all other species with greater than 97% accuracy, and revealed probable Ebolavirus hosts as large-bodied, frugivorous, and with slow life histories. Provisionally, results suggest that some insectivorous bat genera, Old World monkeys, and forest antelopes should receive priority in Ebolavirus survey efforts.This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’.

尽管埃博拉病毒（Ebolavirus）相关疫情、病毒毒株以及动物宿主相关证据持续积累，但其基础生态学特征仍有诸多未明之处。由于人类埃博拉病毒疫情均与接触蝙蝠以外的野生哺乳动物相关，因此已感染该病毒的物种所共有的特征及其系统发育分布，或可揭示驱动人类埃博拉病毒溢出（spillover）的生态学机制。本研究收集了哺乳动物感染埃博拉病毒的暴露数据，以及对应物种的生活史特征、活动范围与饮食数据，并采用提升回归树（boosted regression trees, BRT）模型，对119个物种（下文简称宿主）的病毒暴露与感染预测因子进行识别。对推定埃博拉病毒宿主的系统发育分布进行绘图分析后发现，这些宿主分散于多个不同的哺乳动物演化支中，但主要集中在旧大陆果蝠、灵长类与偶蹄目类群中。尽管采样强度是最重要的预测因子，其对宿主间变异的解释度与物种特征的解释度几乎持平，但提升回归树模型仍以超过97%的准确率将宿主与其他物种区分开来，并揭示出潜在埃博拉病毒宿主具备体型较大、食果性以及生活史缓慢的特征。初步研究结果表明，部分食虫蝙蝠属类、旧大陆猴类与森林羚羊应作为埃博拉病毒调查的优先关注对象。本文隶属于主题专栏《解析病原体溢出的动态整合研究方法》（Dynamic and integrative approaches to understanding pathogen spillover）。