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The mechanism shaping the logistic growth of mutation proportion in epidemics at population scale

Infectious Disease Modelling 2023年第1期8卷 107-121页

作者： Shi Zhao Inchi Hu Jingzhi Lou Marc K.C.Chong Lirong Cao Daihai He benny C.Y.zee Maggie H.Wang JC School of Public Health and Primary Care Chinese University of Hong KongHong KongChina CUHK Shenzhen Research Institute ShenzhenChina Department of Information Systems Business Statistics and Operations ManagementHong Kong University of Science and TechnologyHong KongChina Department of Applied Mathematics Hong Kong Polytechnic UniversityHong KongChina

Virus evolution is a common process of pathogen adaption to host population and ***,a small but important fraction of virus mutations are reported to contribute to higher risks of host infection,which is one of the major determinants of infectious diseases outbreaks at population *** key mutations contributing to transmission advantage of a genetic variant often grow and reach fixation *** on classic epidemiology theories of disease transmission,we proposed a mechanistic explanation of the process that between-host transmission advantage may shape the observed logistic curve of the mutation proportion in *** logistic growth of mutation is further generalized by incorporating time-varying selective pressure to account for impacts of external factors on pathogen *** proposed model is implemented in real-world data of COVID-19 to capture the emerging trends and changing dynamics of the B.1.1.7 strains of SARS-CoV-2 in *** model characterizes and establishes the underlying theoretical mechanism that shapes the logistic growth of mutation in population.

关键词： Transmission advantage Logistic growth Population dynamics Selective pressure COVID-19

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