Bayesian inference in an extended SEIR model with nonparametric disease transmission rate: an application to the Ebola epidemic in Sierra Leone
Bayesian inference in an extended SEIR model with nonparametric disease transmission rate: an application to the Ebola epidemic in Sierra Leone
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DOI：
10.1093/biostatistics/kxw027
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发表时间：
2016-10-01
期刊：
影响因子：
2.1
通讯作者：
Lambert, Philippe
中科院分区：
文献类型：
--
作者：
Frasso, Gianluca;Lambert, Philippe
2014年塞拉利昂的埃博拉疫情是使用易感-暴露-传染病消除(SEIR)疫情区隔模型进行分析的。将流行病演化的离散时间-随机模型耦合到一组描述每个流行病状态下受试者的预期比例的动态的常微分方程组。未知参数是在贝叶斯框架内估计的，方法是将卫生部报告的新增(实验室确认)埃博拉病例数量的数据与利用世卫组织在跟踪特定埃博拉病例期间收集的信息得出的转化率的先前分布相结合。用惩罚B-样条法以灵活的方式模拟时变的疾病传播率。我们的框架为研究流行病动态提供了一个有价值的随机工具，即使在只有不规则观测和可能聚集的数据可用时也是如此。对2014年塞拉利昂埃博拉数据的模拟和分析突出了拟议方法的优点。特别是，疾病传播率的灵活建模使有效繁殖数量的估计对初始流行状态的错误指定和对传染病病例的漏报具有稳健性。
The 2014 Ebola outbreak in Sierra Leone is analyzed using a susceptible-exposed-infectious-removed (SEIR) epidemic compartmental model. The discrete time-stochastic model for the epidemic evolution is coupled to a set of ordinary differential equations describing the dynamics of the expected proportions of subjects in each epidemic state. The unknown parameters are estimated in a Bayesian framework by combining data on the number of new (laboratory confirmed) Ebola cases reported by the Ministry of Health and prior distributions for the transition rates elicited using information collected by the WHO during the follow-up of specific Ebola cases. The time-varying disease transmission rate is modeled in a flexible way using penalized B-splines. Our framework represents a valuable stochastic tool for the study of an epidemic dynamic even when only irregularly observed and possibly aggregated data are available. Simulations and the analysis of the 2014 Sierra Leone Ebola data highlight the merits of the proposed methodology. In particular, the flexible modeling of the disease transmission rate makes the estimation of the effective reproduction number robust to the misspecification of the initial epidemic states and to underreporting of the infectious cases.