MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College of Science, Technology & Medicine, Norfolk Place, London W2 1PG, UK.
J R Soc Interface. 2009 Nov 6;6(40):989-96. doi: 10.1098/rsif.2008.0467. Epub 2009 Jan 21.
We develop mathematical models of the transmission and evolution of multi-strain pathogens that incorporate strain extinction and the stochastic generation of new strains via mutation. The dynamics resulting from these models is then examined with the applied aim of understanding the mechanisms underpinning the evolution and dynamics of rapidly mutating pathogens, such as human influenza viruses. Our approach, while analytically relatively simple, gives results that are qualitatively similar to those obtained from much more complex individually based simulation models. We examine strain dynamics as a function of cross-immunity and key transmission parameters, and show that introducing strain extinction and modelling mutation as a stochastic process significantly changes the model dynamics, leading to lower strain diversity, reduced infection prevalence and shorter strain lifetimes. Finally, we incorporate transient strain-transcending immunity in the model and demonstrate that it reduces strain diversity further, giving patterns of sequential strain replacement similar to that seen in human influenza A viruses.
我们开发了多菌株病原体传播和进化的数学模型，该模型结合了菌株灭绝和通过突变随机产生新菌株的过程。然后，我们应用这些模型来研究动力学，目的是了解快速突变病原体（如人类流感病毒）进化和动态的机制。我们的方法虽然在分析上相对简单，但得到的结果与基于个体的更复杂模拟模型的结果在质量上相似。我们研究了交叉免疫和关键传播参数作为菌株动态的函数，并表明引入菌株灭绝和将突变建模为随机过程会显著改变模型动力学，导致菌株多样性降低、感染率降低和菌株寿命缩短。最后，我们在模型中加入了短暂的菌株跨越免疫，并证明它进一步降低了菌株多样性，产生了类似于人类甲型流感病毒中观察到的连续菌株替代模式。
