Rhodes C J, Jensen H J, Anderson R M
Wellcome Trust Centre for the Epidemiology of Infectious Disease, Department of Zoology, University of Oxford, UK.
Proc Biol Sci. 1997 Nov 22;264(1388):1639-46. doi: 10.1098/rspb.1997.0228.
We show how ideas and models which were originally introduced to gain an understanding of critical phenomena can be used to interpret the dynamics of epidemics of communicable disease in real populations. Specifically, we present an analysis of the dynamics of disease outbreaks for three common communicable infections from a small isolated island population. The strongly fluctuating nature of the temporal incidence of disease is captured by the model, and comparisons between exponents calculated from the data and from simulations are made. A forest-fire model with sparks is used to classify the observed scaling dynamics of the epidemics and provides a unified picture of the epidemiology which conventional epidemiological analysis is unable to reproduce. This study suggests that power-law scaling can emerge in natural systems when they are driven on widely separated time-scales, in accordance with recent analytic renormalization group calculations.
我们展示了最初为理解临界现象而引入的思想和模型如何能够用于解释实际人群中传染病流行的动态变化。具体而言，我们对一个小的孤立岛屿人群中三种常见传染病的疾病暴发动态进行了分析。该模型捕捉到了疾病时间发病率的强烈波动特性，并对根据数据计算出的指数与模拟得出的指数进行了比较。一个带火花的森林火灾模型被用于对观察到的流行病标度动态进行分类，并提供了一个传统流行病学分析无法再现的统一流行病学图景。这项研究表明，根据最近的解析重整化群计算，当自然系统在广泛分离的时间尺度上受到驱动时，幂律标度可能会出现。
