The spatio-temporal analysis of infectious diseases

传染病在整个社会都很重要。麻疹、严重急性呼吸系统综合症、流感或口蹄疫等疾病的流行病爆发可对公众健康构成直接威胁和/或造成严重的经济影响。为了控制这类疾病，至关重要的是要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感染，而另一些人没有感染。为此目的，开发了一类新的数学模型，即传染病的个人水平模型。这些模型直观、灵活，并已被证明能够准确描述以前观察到的流行病在空间和时间上的模式。然而，ilm是相对较新的，因此有许多传染病问题的具体模型尚不存在。

Infectious diseases are of great importance across society. Epidemic outbreaks of diseases such as measles, SARS, influenza 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 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 infectious disease problems for which specific models do not yet exist.