Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.
BMC Bioinformatics. 2011 Mar 30;12:87. doi: 10.1186/1471-2105-12-87.
Influenza A viruses exhibit complex epidemiological patterns in a number of mammalian and avian hosts. Understanding transmission of these viruses necessitates taking into account their evolution, which represents a challenge for developing mathematical models. This is because the phrasing of multi-strain systems in terms of traditional compartmental ODE models either requires simplifying assumptions to be made that overlook important evolutionary processes, or leads to complex dynamical systems that are too cumbersome to analyse.
Here, we develop an Individual-Based Model (IBM) in order to address simultaneously the ecology, epidemiology and evolution of strain-polymorphic pathogens, using Influenza A viruses as an illustrative example.
We carry out careful validation of our IBM against comparable mathematical models to demonstrate the robustness of our algorithm and the sound basis for this novel framework. We discuss how this new approach can give critical insights in the study of influenza evolution.
甲型流感病毒在许多哺乳动物和禽类宿主中表现出复杂的流行病学模式。要了解这些病毒的传播情况，就必须考虑到它们的进化，这给开发数学模型带来了挑战。这是因为，用传统的隔室 ODE 模型来描述多株系系统，要么需要做出简化假设，从而忽略重要的进化过程，要么导致复杂的动力学系统过于繁琐而难以分析。
在这里，我们开发了一个基于个体的模型（IBM），以便同时解决生态、流行病学和多态病原体的进化问题，以甲型流感病毒作为一个说明性的例子。
我们对 IBM 进行了仔细的验证，以比较数学模型来证明我们算法的稳健性和这个新框架的可靠基础。我们讨论了这种新方法如何为流感进化的研究提供关键的见解。
