Gilchrist Michael A, Sasaki Akira
Department of Biology, Duke University, Durham, NC, 27708-0325, USA.
J Theor Biol. 2002 Oct 7;218(3):289-308. doi: 10.1006/jtbi.2002.3076.
In this study we introduce a mechanistic framework for modeling host-parasite coevolution using a nested modeling approach. The first step in this approach is to construct a mechanistic model of the parasite population dynamics within a host. The second step is to define an epidemiological model which is used to derive the fitness functions for both the host and the parasite. The within-host model is then nested within the epidemiological model by linking the epidemiological parameters such as the transmission rate of the infection or the additional host mortality rate to the dynamics of the within-host model. Nesting the within-host model into an epidemiological model allows us to evaluate the fitness functions for each interactor which in turn allows us to determine the coevolutionary dynamics of the system. This nested approach has the advantage over other approaches in that mechanistic descriptions of the host-parasite biology are used to derive, rather than impose, life-history trade-offs. We illustrate this framework by analysing a simple host-parasite system. In this particular system we find that the coevolutionary equilibrium is always stable and that host survivorship and parasite fitness vary greatly with the cost of the immune response and parasite growth.
在本研究中,我们引入了一个机制框架,用于使用嵌套建模方法对宿主 - 寄生虫协同进化进行建模。该方法的第一步是构建宿主内寄生虫种群动态的机制模型。第二步是定义一个流行病学模型,该模型用于推导宿主和寄生虫的适应度函数。然后,通过将感染传播率或额外宿主死亡率等流行病学参数与宿主内模型的动态联系起来,将宿主内模型嵌套在流行病学模型中。将宿主内模型嵌套到流行病学模型中,使我们能够评估每个相互作用者的适应度函数,进而使我们能够确定系统的协同进化动态。这种嵌套方法相对于其他方法的优势在于,它利用宿主 - 寄生虫生物学的机制描述来推导而非强加生活史权衡。我们通过分析一个简单的宿主 - 寄生虫系统来说明这个框架。在这个特定系统中,我们发现协同进化平衡总是稳定的,并且宿主存活率和寄生虫适应度会随着免疫反应成本和寄生虫生长而有很大变化。