Quantifying Uncertainty Associated with Microbial Count Data: A Bayesian Approach
Quantifying Uncertainty Associated with Microbial Count Data: A Bayesian Approach
复制标题
量化与微生物计数数据相关的不确定性：贝叶斯方法
DOI：
10.1111/j.1541-0420.2005.030903.x
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发表时间：
2005
期刊：
影响因子：
1.9
通讯作者：
Nigel P. French
中科院分区：
文献类型：
--
作者：
Helen E. Clough;Damian Clancy;Philip D. O'Neill;Susan E. Robinson;Nigel P. French
总结我们考虑的问题，估计细菌浓度的物质，给定的微生物计数数据。提出了一种贝叶斯方法，该方法自然允许合并平板计数数据和来自确证性试验（如通过聚合酶链反应（PCR）进行基因分型）的额外信息。估计方法产生细菌浓度的后可信区域，与以前的方法相比，通常只产生点估计。该方法具体参考了通过螺旋平板法对食源性病原体大肠杆菌O157的计数，尽管该方法可以应用于任何感兴趣的细菌或计数方法。所获得的结果为实验者提供了关于应进行的确认试验的数量的指导，并且还表明，在初始平板计数中，应该包括而不是排除基因型似乎不清楚的菌落。
Summary We consider the problem of estimating bacterial concentration in a substance, given microbial count data. A Bayesian approach is proposed which naturally allows the incorporation of both plate‐count data and extra information from confirmatory tests such as genotyping by polymerase chain reaction (PCR). The estimation methods yield posterior credible regions for bacterial concentration, in contrast to the previous methods, which generally only produce point estimates. The approach is illustrated with specific reference to the enumeration of the food‐borne pathogen Escherichia coli O157 by spiral plating, although the methodology can be applied to any bacterium or counting method of interest. The results obtained provide guidance to the experimenter as to the number of confirmatory tests which should be performed, and also suggest that in the initial plate count one should err on the side of including rather than excluding colonies whose genotype seems unclear.