Duan Wei, Fan Zongchen, Zhang Peng, Guo Gang, Qiu Xiaogang
Center of Computational Experiments and Parallel Systems Technology, College of Information Systems and Management, National University of Defense Technology, Changsha, 410073 China.
Front Comput Sci (Berl). 2015;9(5):806-826. doi: 10.1007/s11704-014-3369-2. Epub 2015 Oct 9.
Mathematical and computational approaches are important tools for understanding epidemic spread patterns and evaluating policies of disease control. In recent years, epidemiology has become increasingly integrated with mathematics, sociology, management science, complexity science, and computer science. The cross of multiple disciplines has caused rapid development of mathematical and computational approaches to epidemic modeling. In this article, we carry out a comprehensive review of epidemic models to provide an insight into the literature of epidemic modeling and simulation. We introduce major epidemic models in three directions, including mathematical models, complex network models, and agent-based models. We discuss the principles, applications, advantages, and limitations of these models. Meanwhile, we also propose some future research directions in epidemic modeling.
数学和计算方法是理解流行病传播模式以及评估疾病控制政策的重要工具。近年来，流行病学与数学、社会学、管理科学、复杂性科学和计算机科学的融合日益深入。多学科的交叉推动了流行病建模的数学和计算方法的快速发展。在本文中，我们对流行病模型进行了全面综述，以深入了解流行病建模与模拟的文献。我们从三个方向介绍主要的流行病模型，包括数学模型、复杂网络模型和基于主体的模型。我们讨论了这些模型的原理、应用、优点和局限性。同时，我们还提出了流行病建模未来的一些研究方向。
