论文标题：Predicting wildlife reservoirs and global vulnerability to zoonotic Flaviviruses

期刊：

作者：Pranav S. Pandit, Megan M. Doyle, Katrina M. Smart, Cristin C. W. Young, Gaylen W. Drape, Christine K. Johnson

发表时间：2018/12/21

数字识别码： 10.1038/s41467-018-07896-2

原文链接：

黄病毒持续在全球范围内引发相关的疫情，并且还在蔓延至未被感染过的区域，反复不断。目前研究者们还不能完全了解导致黄病毒出现的原因，以及导致其在丛林生态中持续循环的影响因素。

来自加州大学戴维斯分校的Pranav S. Pandit及其同事确定了黄病毒潜在的丛林寄主，并对已知野生动物寄主的常见的宏观生态特点进行了表征，以预测黄病毒在野生动物间传播的风险，并识别容易暴发黄病毒疫情的地区。作者评估了动物传染性黄病毒的野生动物宿主的多样性，发现黄病毒明显地分别聚集于相似的宿主。

作者的模型整合了生态学和气候变量以及黄病毒所共有的历史特征，然后用以预测具有相似特征的新的宿主物种。通过综合矢量分布数据和黄病毒的宿主模型，作者能够预测出黄病毒的全球易暴发区域，从而为监测疾病在野生动物和人中的传播提供了潜在目标。

摘要：Flaviviruses continue to cause globally relevant epidemics and have emerged or re-emerged in regions that were previously unaffected. Factors determining emergence of flaviviruses and continuing circulation in sylvatic cycles are incompletely understood. Here we identify potential sylvatic reservoirs of flaviviruses and characterize the macro-ecological traits common to known wildlife hosts to predict the risk of sylvatic flavivirus transmission among wildlife and identify regions that could be vulnerable to outbreaks. We evaluate variability in wildlife hosts for zoonotic flaviviruses and find that flaviviruses group together in distinct clusters with similar hosts.Models incorporating ecological and climatic variables as well as life history traits shared by flaviviruses predict new host species with similar host characteristics. The combination of vector distribution data with models for flavivirushosts allows for prediction of global vulnerability to flaviviruses and provides potential targets for disease surveillance in animals and humans.

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