A Bayesian MCMC approach to study transmission of influenza:: application to household longitudinal data
A Bayesian MCMC approach to study transmission of influenza:: application to household longitudinal data
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DOI：
10.1002/sim.1912
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发表时间：
2004-11-30
影响因子：
2
通讯作者：
Boëlle, PY
中科院分区：
文献类型：
--
作者：
Cauchemez, S;Carrat, F;Boëlle, PY
我们提出了一个传播模型来估计流感在家庭中传播的主要特征。该模型详细说明了家庭和社区中个人感染的风险。考虑个体易感性和传染性，研究受试者之间的异质性。该模型被应用到一个数据集，包括后续的流感症状在334个家庭在15天后，索引病例访问了全科医生与病毒学确诊的influenza.Estimating参数的传播模型是具有挑战性的，因为很大一部分的传染过程没有观察到：只有新的病例被发现的日期进行了观察。对于每例病例，数据均增加了感染期开始和结束的未观察日期。传播模型采用3层递阶结构：（i）观测层保证增广数据与观测数据的一致性;（ii）传播层描述潜在的流行过程;（iii）先验层指定参数的分布。从贝叶斯的角度，通过马尔可夫链蒙特卡罗（MCMC）抽样探索模型参数和增强数据的联合后验分布，估计流感传染期的平均持续时间为3.8天（95%可信区间，95%CI [3.1，4.6]），标准差为2.0天（95%CI [1.1，2.8]）。在一个家庭中，感染者和易感者之间的流感传播的瞬时风险随着家庭规模的增加而降低，并确定为0.32人/天（-1）（95%CI [0.26，0.39]）;社区感染的瞬时风险为0.0056天（-1）（95%CI（0.0029，0.0087））。关注儿童之间传播的差异在儿童（15岁以下）和成人中，我们估计前者比成人更有可能传播（后验概率大于99%），但儿童（3.6天，95%CI [2.3，5.2]）和成人（3.9天，95%CI [ www.example.com ]）的平均感染期相似3.2.4.9。儿童具有更大社区风险的后验概率为76%，儿童比成人更容易受到影响的后验概率为79%。版权所有（C）2004 John Wiley Sons，Ltd.
We propose a transmission model to estimate the main characteristics of influenza transmission in households. The model details the risks of infection in the household and in the community at the individual scale. Heterogeneity among subjects is investigated considering both individual susceptibility and infectiousness. The model was applied to a data set consisting of the follow-up of influenza symptoms in 334 households during 15 days after an index case visited a general practitioner with virologically confirmed influenza.Estimating the parameters of the transmission model was challenging because a large part of the infectious process was not observed: only the dates when new cases were detected were observed. For each case, the data were augmented with the unobserved dates of the start and the end of the infectious period. The transmission model was included in a 3-levels hierarchical structure: (i) the observation level ensured that the augmented data were consistent with the observed data, (ii) the transmission level described the underlying epidemic process, (iii) the prior level specified the distribution of the parameters. From a Bayesian perspective, the joint posterior distribution of model parameters and augmented data was explored by Markov chain Monte Carlo (MCMC) sampling.The mean duration of influenza infectious period was estimated at 3.8 days (95 per cent credible interval, 95 per cent Cl [3.1,4.6]) with a standard deviation of 2.0 days (95 per cent Cl [1.1,2.8]). The instantaneous risk of influenza transmission between an infective and a susceptible within a household was found to decrease with the size of the household, and established at 0.32 person day(-1) (95 per cent Cl [0.26,0.39]); the instantaneous risk or infection from the community was 0.0056 day(-1) (95 per cent Cl (0.0029,0.0087]). Focusing on the differences in transmission between children (less than 15 years old) and adults, we estimated that the former were more likely to transmit than adults (posterior probability larger than 99 per cent), but that the mean duration of the infectious period was similar in children (3.6 days, 95 per cent Cl [2.3,5.2]) and adults (3.9 days, 95 per cent Cl [3.2.4.9]). The posterior probability that children had a larger community risk was 76 per cent and the posterior probability that they were more susceptible than adults was 79 per cent. Copyright (C) 2004 John Wiley Sons, Ltd.