儿童感染的矩阵模型：一种贝叶斯方法及其在风疹和腮腺炎中的应用
Matrix models for childhood infections: a Bayesian approach with applications to rubella and mumps.
作者信息
Kanaan M N, Farrington C P
机构信息
Department of Epidemiology and Population Health, American University of Beirut, Lebanon.
出版信息
Epidemiol Infect. 2005 Dec;133(6):1009-21. doi: 10.1017/S0950268805004528.
Mathematical modelling is an established tool for planning and monitoring vaccination programmes. However, the matrices describing contact rates are based on subjective choices, which have a large impact on results. This paper reviews published models and obtains prior model probabilities based on publication frequency and expert opinion. Using serological survey data on rubella and mumps, Bayesian methods of model choice are applied to select the most plausible models. Estimates of the basic reproduction number R0 are derived, taking into account model uncertainty and individual heterogeneity in contact rates. Twenty-two models are documented, for which publication frequency and expert opinion are negatively correlated. Using the expert prior with individual heterogeneity, R0=6.1 [95% credible region (CR) 4.3-9.2] for rubella and R0=19.3 (95% CR 4.0-31.5) for mumps. The posterior modes are insensitive to the prior for rubella but not for mumps. Overall, assortative models with individual heterogeneity are recommended.
数学建模是规划和监测疫苗接种计划的既定工具。然而，描述接触率的矩阵基于主观选择，这对结果有很大影响。本文回顾已发表的模型，并根据发表频率和专家意见获得先验模型概率。利用风疹和腮腺炎的血清学调查数据，应用贝叶斯模型选择方法来选择最合理的模型。在考虑模型不确定性和接触率的个体异质性的情况下，推导了基本再生数R0的估计值。记录了22个模型，其发表频率与专家意见呈负相关。使用具有个体异质性的专家先验，风疹的R0 = 6.1 [95%可信区间(CR) 4.3 - 9.2]，腮腺炎的R0 = 19.3 (95% CR 4.0 - 31.5)。后验模式对风疹的先验不敏感，但对腮腺炎的先验敏感。总体而言，推荐具有个体异质性的分类模型。
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