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Evolutionary Invasion Analysis of Modern Epidemics Highlights the Context-Dependence of Virulence Evolution.
Surasinghe, Sudam; Kabengele, Ketty; Turner, Paul E; Ogbunugafor, C Brandon.
Afiliação
  • Surasinghe S; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06520, USA.
  • Kabengele K; Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, 06510, USA.
  • Turner PE; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06520, USA.
  • Ogbunugafor CB; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06520, USA.
Bull Math Biol ; 86(8): 88, 2024 Jun 14.
Article em En | MEDLINE | ID: mdl-38877355
ABSTRACT
Models are often employed to integrate knowledge about epidemics across scales and simulate disease dynamics. While these approaches have played a central role in studying the mechanics underlying epidemics, we lack ways to reliably predict how the relationship between virulence (the harm to hosts caused by an infection) and transmission will evolve in certain virus-host contexts. In this study, we invoke evolutionary invasion analysis-a method used to identify the evolution of uninvadable strategies in dynamical systems-to examine how the virulence-transmission dichotomy can evolve in models of virus infections defined by different natural histories. We reveal peculiar patterns of virulence evolution between epidemics with different disease natural histories (SARS-CoV-2 and hepatitis C virus). We discuss the findings with regards to the public health implications of predicting virus evolution, and in broader theoretical canon involving virulence evolution in host-parasite systems.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Hepacivirus / Evolução Biológica / Conceitos Matemáticos / Epidemias / SARS-CoV-2 / COVID-19 / Modelos Biológicos Limite: Humans Idioma: En Revista: Bull Math Biol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Hepacivirus / Evolução Biológica / Conceitos Matemáticos / Epidemias / SARS-CoV-2 / COVID-19 / Modelos Biológicos Limite: Humans Idioma: En Revista: Bull Math Biol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos