Ivanek Renata, Gröhn Yrjö T, Jui-Jung Ho Alphina, Wiedmann Martin
Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA.
J Theor Biol. 2007 Mar 7;245(1):44-58. doi: 10.1016/j.jtbi.2006.09.031. Epub 2006 Oct 7.
Fecal shedding is an important mechanism of spreading of a number of human and animal pathogens. Understanding of the dynamics of pathogen fecal shedding is critical to be able to control or prevent the spread of diseases caused by these pathogens. The objective of this study was to develop a model for analysis of the dynamics of pathogen fecal shedding. Fecal shedding of Listeria monocytogenes in dairy cattle was used as a model system. A Markov chain model (MCM) with two states, shedding and non-shedding, has been developed for overall L. monocytogenes fecal shedding (all L. monocytogenes subtypes) and fecal shedding of three L. monocytogenes subtypes (ribotypes 1058A, 1039E and 1042B) using data from one study farm. The matrices of conditional probabilities of transition between shedding and non-shedding states for different sets of covariates have been estimated by application of logistic regression. The covariate-specific matrices of conditional probabilities, describing the presence of different risk factors, were used to estimate (i) the stationary prevalence of dairy cows that shed any L. monocytogenes subtype or ribotypes 1058A, 1039E, and 1042B, (ii) the duration of overall and subtype specific fecal shedding, and (iii) the duration of periods without shedding. A non-homogeneous MCM was constructed to study how the prevalence of fecal shedders changes over time. The model was validated with data from the study farm and published literature. The results of our modeling work indicated that (i) the prevalence of L. monocytogenes fecal shedders varies over time and can be higher than 90%, (ii) L. monocytogenes subtypes exhibit different dynamics of fecal shedding, (iii) the dynamics of L. monocytogenes fecal shedding are highly associated with contamination of silage (fermented feed) and cows' exposure to stress, and (iv) the developed approach can be readily used to study the dynamics of fecal shedding in other pathogen-host-environment systems.
粪便排菌是多种人类和动物病原体传播的重要机制。了解病原体粪便排菌的动态对于控制或预防由这些病原体引起的疾病传播至关重要。本研究的目的是建立一个分析病原体粪便排菌动态的模型。以奶牛中单核细胞增生李斯特菌的粪便排菌作为模型系统。利用来自一个研究农场的数据,针对单核细胞增生李斯特菌的总体粪便排菌(所有单核细胞增生李斯特菌亚型)以及三种单核细胞增生李斯特菌亚型(核糖型1058A、1039E和1042B)的粪便排菌,开发了一个具有排菌和非排菌两种状态的马尔可夫链模型(MCM)。通过应用逻辑回归估计了不同协变量集在排菌和非排菌状态之间转换的条件概率矩阵。描述不同风险因素存在情况的协变量特异性条件概率矩阵用于估计:(i)排出任何单核细胞增生李斯特菌亚型或核糖型1058A、1039E和1042B的奶牛的稳态流行率;(ii)总体和亚型特异性粪便排菌的持续时间;(iii)无排菌期的持续时间。构建了一个非齐次MCM来研究粪便排菌者的流行率随时间的变化情况。该模型用研究农场的数据和已发表的文献进行了验证。我们建模工作的结果表明:(i)单核细胞增生李斯特菌粪便排菌者的流行率随时间变化,可能高于90%;(ii)单核细胞增生李斯特菌亚型表现出不同的粪便排菌动态;(iii)单核细胞增生李斯特菌粪便排菌的动态与青贮饲料(发酵饲料)污染以及奶牛受到的应激暴露高度相关;(iv)所开发的方法可很容易地用于研究其他病原体 - 宿主 - 环境系统中的粪便排菌动态。