Gog Julia R, Grenfell Bryan T
Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, United Kingdom.
Proc Natl Acad Sci U S A. 2002 Dec 24;99(26):17209-14. doi: 10.1073/pnas.252512799. Epub 2002 Dec 12.
Strain structure is of fundamental importance in the underlying dynamics of a number of pathogens. However, previous models have been too complex to accommodate many strains. This paper offers a solution to this problem, in the form of a simple model that is capable of capturing the dynamics of a large number of antigenic types that interact via host cross-immunity. We derive the structure of the model, which can manage the complexity of many strains by using a status-based formulation, assuming polarized immunity and cross-immunity act to reduced transmission probability. We then apply the model to address basic questions in strain dynamics, focusing particularly on the interpandemic dynamics of influenza. This model shows that strains have a tendency to "cluster." For a long infectious period, relative to host lifetime, clusters may coexist. By contrast, a short infectious period leads to a single dominant cluster at any given time. We show how the speed of cluster replacement depends on the specificity of cross-immunity and on the underlying pathogen mutation rate.
毒株结构在许多病原体的潜在动态中至关重要。然而,先前的模型过于复杂,无法容纳多种毒株。本文以一个简单模型的形式为这一问题提供了一个解决方案,该模型能够捕捉通过宿主交叉免疫相互作用的大量抗原类型的动态。我们推导了模型的结构,该模型通过基于状态的公式来管理多种毒株的复杂性,假设极化免疫和交叉免疫会降低传播概率。然后,我们应用该模型来解决毒株动态中的基本问题,特别关注流感的大流行间期动态。该模型表明,毒株有“聚集”的趋势。对于相对于宿主寿命较长的感染期,多个聚集簇可能共存。相比之下,较短的感染期会导致在任何给定时间出现单一的优势聚集簇。我们展示了聚集簇替换的速度如何取决于交叉免疫的特异性和潜在的病原体突变率。