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Scaling properties of childhood infectious diseases epidemics before and after mass vaccination in Canada

机译:加拿大大规模疫苗接种前后儿童传染病流行的尺度特征

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摘要

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. © 2005 Elsevier Ltd. All rights reserved.
机译:本文的目的是分析儿童传染病时间序列数据的标度特性。我们对加拿大的麻疹,风疹,百日咳和流行性腮腺炎疫情流行规模分布进行了规模分析。此应用程序提供了一种评估大量接种人群中传染病动态的新方法。逆幂律(IPL)分布函数已适合流行病大小的时间序列,并根据指数基准模型评估了结果。我们已经发现风疹的流行规模分布和高度疫苗接种期间的麻疹遵循IPL。 IPL表明由于个体接触率的异质性,这些疾病存在规模不变的网络。相比之下,人们发现百日咳和腮腺炎的特征是呈指数型传播的统一网络,这表明接触率具有同质性,或者更可能是由于人群中的大量混合而降低了异质性。我们得出结论,传染性接触者网络的拓扑结构取决于疾病类型及其感染率。看来,人口的社会人口结构可能在网络拓扑结构的构成中发挥作用(例如,根据年龄的联系方式)。研究结果表明,在普通传染病时间序列数据的变化中隐藏着相关信息,并且该信息可能与疫苗接种计划的策略有关。 &复制; 2005 Elsevier Ltd.保留所有权利。

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