A latent variable model for estimating disease transmission rate from data on household outbreaks

被引：1
|
作者：
Li, Ning [1 ]
Qian, Guoqi [1 ]
Huggins, Richard [1 ]
机构：
[1] La Trobe Univ, Dept Stat Sci, Bundoora, Vic 3086, Australia
来源：
COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2006年 / 50卷 / 11期
关键词：
disease transmission rate; infection chain; outbreak size; data augmentation; Tanner-Wong algorithm; Bayesian statistics;
D O I：
10.1016/j.csda.2005.06.011
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
A Bayesian latent variable model is proposed for studying household epidemics of infectious diseases in this paper. This model is more general and flexible than the commonly used chain binomial epidemic model. In particular, the model allows for the heterogeneity of the infection transmission rates in related to the sizes and generations of the infectives. Moreover, the model assumes the availability of only the household outbreak sizes, which is more reasonable than assuming the availability of the hardly observed infection chains. The Tanner-Wong's IP algorithm is employed for effective simulations and inferences of this model. Finally, this model was applied to analyzing a real data set on F-4 Asian influenza. (C) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码：3354 / 3368
页数：15
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