Predictive Modeling of Influenza Shows the Promise of Applied Evolutionary Biology
作者： Dylan H. Morris , Katelyn M. Gostic , Simone Pompei , Trevor Bedford , Marta Łuksza
DOI: 10.1016/J.TIM.2017.09.004
关键词:
摘要: Seasonal influenza is controlled through vaccination campaigns. Evolution of virus antigens means that vaccines must be updated to match novel strains, and vaccine effectiveness depends on the ability scientists predict nearly a year in advance which variants will dominate upcoming seasons. In this review, we highlight promising new surveillance tool: predictive models. Based data-sharing close collaboration between World Health Organization academic scientists, these models use data make quantitative predictions regarding evolution. Predictive demonstrate potential applied evolutionary biology improve public health disease control. We review state modeling discuss next steps recommendations ensure deliver upon their considerable biomedical promise.
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