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DOI: 10.1016/j.tree.2016.07.010
论文题名:
Forecasting Epidemiological and Evolutionary Dynamics of Infectious Diseases
作者: Gandon S.; Day T.; Metcalf C.J.E.; Grenfell B.T.
刊名: Trends in Ecology and Evolution
ISSN: 1695347
出版年: 2016
卷: 31, 期:10
起始页码: 776
结束页码: 788
语种: 英语
英文摘要: Mathematical models have been powerful tools in developing mechanistic understanding of infectious diseases. Furthermore, they have allowed detailed forecasting of epidemiological phenomena such as outbreak size, which is of considerable public-health relevance. The short generation time of pathogens and the strong selection they are subjected to (by host immunity, vaccines, chemotherapy, etc.) mean that evolution is also a key driver of infectious disease dynamics. Accurate forecasting of pathogen dynamics therefore calls for the integration of epidemiological and evolutionary processes, yet this integration remains relatively rare. We review previous attempts to model and predict infectious disease dynamics with or without evolution and discuss major challenges facing the development of the emerging science of epidemic forecasting. © 2016
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/67006
Appears in Collections:全球变化的国际研究计划
气候变化与战略

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作者单位: CEFE UMR 5175, CNRS–Université de Montpellier–Université Paul-Valéry Montpellier–EPHE, 1919 route de Mende, Montpellier cedex 5, France; Department of Biology, Queen's University, Kingston, Canada; Department of Ecology and Evolutionary Biology and Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ, United States

Recommended Citation:
Gandon S.,Day T.,Metcalf C.J.E.,et al. Forecasting Epidemiological and Evolutionary Dynamics of Infectious Diseases[J]. Trends in Ecology and Evolution,2016-01-01,31(10)
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