Read Jonathan M, Keeling Matt J
Department of Biological Sciences and Mathematics Institute, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK.
Theor Popul Biol. 2006 Sep;70(2):201-13. doi: 10.1016/j.tpb.2006.04.006. Epub 2006 May 5.
Traditional explorations of infectious disease evolution have considered the competition between two cross-reactive strains within the standard framework of disease models. Such techniques predict that diseases should evolve to be highly transmissible, benign to the host and possess a long infectious period: in general, diseases do not conform to this ideal. Here we consider a more holistic approach, suggesting that evolution is a trade-off between adaptive pressures at different scales: within host, between hosts and at the population level. We present a model combining within-host pathogen dynamics and transmission between individuals governed by an explicit contact network, where transmission dynamics between hosts are a function of the interaction between the pathogen and the hosts' immune system, though ultimately constrained by the contacts each infected host possesses. Our results show how each of the scales places constraints on the evolutionary behavior, and that complex dynamics may emerge due to the feedbacks between epidemiological and evolutionary dynamics. In particular, multiple stable states can occur with switching between them stochastically driven.
传统上对传染病进化的探索是在疾病模型的标准框架内考虑两种交叉反应菌株之间的竞争。这类技术预测,疾病应该进化为具有高传播性、对宿主无害且感染期长:但总体而言,疾病并不符合这一理想状态。在此,我们考虑一种更全面的方法,认为进化是不同尺度下适应压力之间的权衡:在宿主体内、宿主之间以及种群水平。我们提出了一个模型,该模型结合了宿主体内病原体动态以及由明确接触网络控制的个体间传播,其中宿主之间的传播动态是病原体与宿主免疫系统相互作用的函数,不过最终受每个受感染宿主所拥有的接触情况限制。我们的结果展示了每个尺度如何对进化行为施加限制,以及由于流行病学和进化动态之间的反馈可能出现复杂动态。特别是,可能会出现多个稳定状态,且它们之间的切换由随机驱动。