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Supplementary data files from Ecological indicators of mammal exposure to Ebolavirus

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Mendeley Data2024-06-25 更新2024-06-27 收录
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https://rs.figshare.com/articles/Supplementary_data_files_from_Ecological_indicators_of_mammal_exposure_to_Ebolavirus/8868233
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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)相关的疾病暴发、病毒毒株以及动物宿主证据不断积累,但其基础生态学的诸多核心内容仍未得到阐明。由于人类埃博拉病毒疫情被证实与接触除蝙蝠外的野生哺乳动物有关,已感染埃博拉病毒的物种所共有的性状及其系统发育分布特征,或可揭示促成人类埃博拉病毒溢出事件的生态学机制。我们整理了哺乳动物的埃博拉病毒暴露数据,以及对应的生活史特征、活动模式与饮食数据,并采用提升回归树(boosted regression trees, BRT)模型,对119个物种(下称宿主)的暴露与感染预测因子进行了识别。对推定的埃博拉病毒宿主的系统发育分布进行绘图分析后发现,它们零散分布于多个不同的哺乳动物演化支,但主要集中在旧世界果蝠、灵长类与偶蹄目动物类群中。尽管采样强度是最重要的预测因子,其解释的宿主间差异程度与各类特征变量相当,但提升回归树模型能以超过97%的准确率区分宿主与其他物种,并揭示出推定的埃博拉病毒宿主具有体型较大、食果性以及生活史较慢的特征。初步来看,研究结果提示,部分食虫蝙蝠属类、旧世界猴类以及森林羚羊应在埃博拉病毒调查工作中获得优先关注。本文属于"理解病原体溢出的动态整合研究方法"特刊。
创建时间:
2023-06-28
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