Trottier Helen, Philippe Pierre
Department of Social and Preventive Medicine, University of Montreal, Pavillon 1420 boul. Mont-Royal, Montréal, Canada H2V 4P3.
J Theor Biol. 2005 Aug 7;235(3):326-37. doi: 10.1016/j.jtbi.2005.01.013.
The goal of this paper is to analyse the scaling properties of childhood infectious disease time-series data. We present a scaling analysis of the distribution of epidemic sizes of measles, rubella, pertussis, and mumps outbreaks in Canada. This application provides a new approach in assessing infectious disease dynamics in a large vaccinated population. An inverse power-law (IPL) distribution function has been fit to the time series of epidemic sizes, and the results assessed against an exponential benchmark model. We have found that the rubella epidemic size distribution and that of measles in highly vaccinated periods follow an IPL. The IPL suggests the presence of a scale-invariant network for these diseases as a result of the heterogeneity of the individual contact rates. By contrast, it was found that pertussis and mumps were characterized by a uniform network of transmission of the exponential type, which suggests homogeneity in the contact rate or, more likely, boiled down heterogeneity by large intermixing in the population. We conclude that the topology of the network of infectious contacts depends on the disease type and its infection rate. It also appears that the socio-demographic structure of the population may play a part (e.g. pattern of contacts according to age) in the structuring of the topology of the network. The findings suggest that there is relevant information hidden in the variation of the common contagious disease time-series data, and that this information can have a bearing on the strategy of vaccination programs.
本文的目标是分析儿童传染病时间序列数据的标度性质。我们对加拿大麻疹、风疹、百日咳和腮腺炎疫情规模的分布进行了标度分析。该应用为评估大规模接种疫苗人群中的传染病动态提供了一种新方法。已将逆幂律(IPL)分布函数拟合到疫情规模的时间序列,并根据指数基准模型评估结果。我们发现,在高接种率时期,风疹疫情规模分布和麻疹疫情规模分布遵循逆幂律。逆幂律表明,由于个体接触率的异质性,这些疾病存在一个标度不变网络。相比之下,发现百日咳和腮腺炎的特征是指数型的均匀传播网络,这表明接触率具有同质性,或者更有可能是由于人群中的大量混合而使异质性减弱。我们得出结论,传染性接触网络的拓扑结构取决于疾病类型及其感染率。人口的社会人口结构似乎也可能在网络拓扑结构的形成中发挥作用(例如按年龄划分的接触模式)。研究结果表明,常见传染病时间序列数据的变化中隐藏着相关信息,并且这些信息可能与疫苗接种计划策略有关。