Spread of Q fever within dairy cattle herds: key parameters inferred using a Bayesian approach
Spread of Q fever within dairy cattle herds: key parameters inferred using a Bayesian approach
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DOI：
10.1098/rspb.2010.0575
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发表时间：
2010-09-22
影响因子：
4.7
通讯作者：
Beaudeau, Francois
中科院分区：
文献类型：
--
作者：
Courcoul, Aurelie;Vergu, Elisabeta;Beaudeau, Francois
Q热是由贝氏柯克斯体引起的一种世界性人畜共患病。虽然反刍动物被认为是人类感染的最重要来源，但以前的研究都没有集中在评估牛群内细菌传播的特征，也没有在这种情况下提出流行病模型。我们评估的关键流行病学参数，从现场数据的贝叶斯框架，考虑到现有的知识，缺失的数据和观察过程中的不确定性，由于诊断测试的不完善。我们提出了一个原始的基于个体的离散时间马尔可夫模型，描述了每个动物的感染的演变。马尔可夫链蒙特卡罗方法被用来估计参数的利益，从数据组成的个人健康状况的217头奶牛的5个慢性感染的奶牛群采样，每周为期四周。输出是健康状态和环境细菌负荷之间的转换概率的后验分布。我们的研究结果表明，一些牛群的特点是非常低的感染风险，而其他人有轻微的感染风险和不可忽略的间歇性脱落概率。此外，抗体状态似乎是细菌传播中的关键点（具有抗体的散毒者比不具有抗体的散毒者散毒时间更长）。除了生物学的见解，这些估计也提供了校准模拟模型，以评估控制策略的C。贝氏体感染
Q fever is a worldwide zoonosis caused by Coxiella burnetii. Although ruminants are recognized as the most important source of human infection, no previous studies have focused on assessing the characteristics of the bacterial spread within a cattle herd and no epidemic model has been proposed in this context. We assess the key epidemiological parameters from field data in a Bayesian framework that takes into account the available knowledge, missing data and the uncertainty of the observation process owing to the imperfection of diagnostic tests. We propose an original individual-based Markovian model in discrete time describing the evolution of the infection for each animal. Markov chain Monte Carlo methodology is used to estimate parameters of interest from data consisting of individual health states of 217 cows of five chronically infected dairy herds sampled every week for a four-week period. Outputs are the posterior distributions of the probabilities of transition between health states and of the environmental bacterial load. Our findings show that some herds are characterized by a very low infection risk while others have a mild infection risk and a non-negligible intermittent shedding probability. Moreover, the antibody status seems to be a key point in the bacterial spread (shedders with antibodies shed for a longer period of time than shedders without antibodies). In addition to the biological insights, these estimates also provide information for calibrating simulation models to assess control strategies for C. burnetii infection.