The spatio-temporal analysis of infectious diseases

传染病对整个社会都很重要。麻疹、SARS、流感或口蹄疫等疾病的流行性爆发可对公共卫生构成直接威胁和/或产生严重的经济影响。为了控制这些疾病，必须了解疾病如何随着时间的推移在地理上传播，以及哪些因素导致一些人感染，而另一些人则没有感染。为此，一类新的数学模型，传染病的个体水平模型（ILM），已经开发出来。这些模型直观，灵活，并已被证明可以准确地描述先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，因此有许多传染病的问题，具体的模型还不存在。

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.