Department of Biology, Georgetown University, Washington DC, USA.
Department of Biology, University of Oklahoma, Norman, OK, USA.
Nat Microbiol. 2021 Dec;6(12):1483-1492. doi: 10.1038/s41564-021-00999-5. Epub 2021 Nov 24.
Better methods to predict and prevent the emergence of zoonotic viruses could support future efforts to reduce the risk of epidemics. We propose a network science framework for understanding and predicting human and animal susceptibility to viral infections. Related approaches have so far helped to identify basic biological rules that govern cross-species transmission and structure the global virome. We highlight ways to make modelling both accurate and actionable, and discuss the barriers that prevent researchers from translating viral ecology into public health policies that could prevent future pandemics.
更好的预测和预防人畜共患病毒出现的方法可以支持未来减少传染病风险的努力。我们提出了一个网络科学框架,用于理解和预测人类和动物对病毒感染的易感性。相关方法迄今为止已有助于确定控制跨物种传播和全球病毒组结构的基本生物学规律。我们强调了使建模既准确又可行的方法,并讨论了阻碍研究人员将病毒生态学转化为公共卫生政策以预防未来大流行的障碍。