Hierarchical statistical modelling of influenza epidemic dynamics in space and time
Hierarchical statistical modelling of influenza epidemic dynamics in space and time
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DOI：
10.1002/sim.1217
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发表时间：
2002-09-30
影响因子：
2
通讯作者：
Gemmell, I
中科院分区：
文献类型：
--
作者：
Mugglin, AS;Cressie, N;Gemmell, I
传染病通常通过感染者和易感者之间的接触传播。由于人与人之间的小规模流动和接触通常没有记录，关于传染病的现有数据往往是空间和时间上的集合，产生连续、定期间隔内感染人数的小面积计数。在本文中，我们开发了一个空间描述性的，时间动态层次模型来拟合这些数据。疾病计数被视为一个实现从一个潜在的多变量自回归过程中，感染的相对风险纳入时空动态。我们采取贝叶斯方法，使用马尔可夫链蒙特卡罗计算后验估计的所有参数的兴趣。我们采用的方法，在苏格兰的流感流行在1989年至1990年。版权所有（C）2002约翰威利父子有限公司
An infectious disease typically spreads via contact between infected and Susceptible individuals. Since the small-scale movements and contacts between people are generally not recorded, available data regarding infectious disease are often aggregations in space and time, yielding small-area counts of the number infected during successive, regular time intervals. In this paper, we develop a spatially descriptive, temporally dynamic hierarchical model to be fitted to such data. Disease counts are viewed as a realization from an underlying multivariate autoregressive process, where the relative risk of infection incorporates the space-time dynamic. We take a Bayesian approach, using Markov chain Monte Carlo to compute posterior estimates of all parameters of interest. We apply the methodology to an influenza epidemic in Scotland during the years 1989-1990. Copyright (C) 2002 John Wiley Sons, Ltd.