Grassly Nicholas C, Fraser Christophe
Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.
Nat Rev Microbiol. 2008 Jun;6(6):477-87. doi: 10.1038/nrmicro1845.
Mathematical analysis and modelling is central to infectious disease epidemiology. Here, we provide an intuitive introduction to the process of disease transmission, how this stochastic process can be represented mathematically and how this mathematical representation can be used to analyse the emergent dynamics of observed epidemics. Progress in mathematical analysis and modelling is of fundamental importance to our growing understanding of pathogen evolution and ecology. The fit of mathematical models to surveillance data has informed both scientific research and health policy. This Review is illustrated throughout by such applications and ends with suggestions of open challenges in mathematical epidemiology.
数学分析与建模是传染病流行病学的核心。在此，我们对疾病传播过程进行直观介绍，说明如何用数学方法表示这一随机过程，以及如何利用这种数学表示来分析观察到的疫情的动态变化。数学分析与建模的进展对于我们不断加深对病原体进化与生态学的理解至关重要。数学模型与监测数据的拟合为科学研究和卫生政策提供了依据。本综述通篇通过此类应用进行阐述，并以数学流行病学中存在的开放性挑战的建议作为结尾。
