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On the probability of strain invasion in endemic settings: Accounting for individual heterogeneity and control in multi-strain dynamics.
Meehan, Michael T; Cope, Robert C; McBryde, Emma S.
Afiliación
  • Meehan MT; James Cook University, Australian Institute of Tropical Health and Medicine, Townsville, Australia. Electronic address: Michael.Meehan1@jcu.edu.au.
  • Cope RC; The University of Adelaide, School of Mathematical Sciences, Adelaide, Australia.
  • McBryde ES; James Cook University, Australian Institute of Tropical Health and Medicine, Townsville, Australia.
J Theor Biol ; 487: 110109, 2020 02 21.
Article en En | MEDLINE | ID: mdl-31816294
ABSTRACT
Pathogen evolution is an imminent threat to global health that has warranted, and duly received, considerable attention within the medical, microbiological and modelling communities. Outbreaks of new pathogens are often ignited by the emergence and transmission of mutant variants descended from wild-type strains circulating in the community. In this work we investigate the stochastic dynamics of the emergence of a novel disease strain, introduced into a population in which it must compete with an existing endemic strain. In analogy with past work on single-strain epidemic outbreaks, we apply a branching process approximation to calculate the probability that the new strain becomes established. As expected, a critical determinant of the survival prospects of any invading strain is the magnitude of its reproduction number relative to that of the background endemic strain. Whilst in most circumstances this ratio must exceed unity in order for invasion to be viable, we show that differential control scenarios can lead to less-fit novel strains invading populations hosting a fitter endemic one. This analysis and the accompanying findings will inform our understanding of the mechanisms that have led to past instances of successful strain invasion, and provide valuable lessons for thwarting future drug-resistant strain incursions.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Epidemias Tipo de estudio: Prognostic_studies Idioma: En Revista: J Theor Biol Año: 2020 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Epidemias Tipo de estudio: Prognostic_studies Idioma: En Revista: J Theor Biol Año: 2020 Tipo del documento: Article