Individual-level modeling for infectious disease spread

传染病在整个社会都非常重要。流感、人乳头瘤病毒(HPV)、SARS或口蹄疫等疾病的流行暴发可能对公众健康构成直接威胁和/或产生严重的经济影响。为了控制这些疾病，了解疾病是如何随着时间的推移在地理上传播的，以及是什么因素导致一些人被感染，另一些人没有被感染，往往是至关重要的。为此，发展了一类新的数学模型--传染病的个体水平模型(ILM)。这些模型直观、灵活，并已被证明准确地描述了以前观察到的流行病在空间和时间上的模式。然而，ILM相对较新，因此关于如何对各种传染病问题进行建模仍有许多问题有待解决。

Infectious diseases are of great importance across society. Epidemic outbreaks of diseases such as influenza, human papillomavirus (HPV), SARS, or foot-and-mouth disease, can pose direct threats to public health and/or have serious economic effects. In order to control such diseases, it is often vital to understand how the disease spreads geographically over time, and what factors lead to some individuals becoming infected, and some not. To this end, a new class of mathematical models, individual-level models (ILMs) for infectious diseases, has been developed. These models are intuitive, flexible, and have been shown to accurately describe the patterns of previously observed epidemics over space and time. However, ILMs are relatively new and so there are many issues about how to model various infectious disease problems that remain to be resolved.