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首页> 外文期刊>International Journal of Food Microbiology >Sample size guidelines for fitting a lognormal probability distribution to censored most probable number data with a Markov chain Monte Carlo method.
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Sample size guidelines for fitting a lognormal probability distribution to censored most probable number data with a Markov chain Monte Carlo method.

机译：使用马尔可夫链蒙特卡罗方法将对数正态概率分布拟合到审查最可能数数据的样本大小准则。

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摘要

Levels of pathogenic organisms in food and water have steadily declined in many parts of the world. A consequence of this reduction is that the proportion of samples that test positive for the most contaminated product-pathogen pairings has fallen to less than 0.1. While this is unequivocally beneficial to public health, datasets with very few enumerated samples present an analytical challenge because a large proportion of the observations are censored values. One application of particular interest to risk assessors is the fitting of a statistical distribution function to datasets collected at some point in the farm-to-table continuum. The fitted distribution forms an important component of an exposure assessment. A number of studies have compared different fitting methods and proposed lower limits on the proportion of samples where the organisms of interest are identified and enumerated, with the recommended lower limit of enumerated samples being 0.2. This recommendation may not be applicable to food safety risk assessments for a number of reasons, which include the development of new Bayesian fitting methods, the use of highly sensitive screening tests, and the generally larger sample sizes found in surveys of food commodities. This study evaluates the performance of a Markov chain Monte Carlo fitting method when used in conjunction with a screening test and enumeration of positive samples by the Most Probable Number technique. The results suggest that levels of contamination for common product-pathogen pairs, such as Salmonella on poultry carcasses, can be reliably estimated with the proposed fitting method and samples sizes in excess of 500 observations. The results do, however, demonstrate that simple guidelines for this application, such as the proportion of positive samples, cannot be provided.
机译：在世界许多地方，食物和水中的致病生物水平一直在下降。减少的结果是，对于受污染最严重的产品-病原体配对检测为阳性的样品比例已降至0.1以下。尽管这无疑对公共卫生有益，但是由于枚举的观察值很大一部分都是经过审查的值，因此枚举样本很少的数据集提出了分析难题。风险评估者特别感兴趣的一种应用是将统计分布函数拟合到从农场到餐桌的连续体中某个点收集的数据集。拟合分布是暴露评估的重要组成部分。大量研究比较了不同的拟合方法，并提出了确定和列举目标生物的样本比例的下限，建议的列举样本下限为0.2。出于多种原因，该建议可能不适用于食品安全风险评估，其中包括开发新的贝叶斯拟合方法，使用高度敏感的筛选测试以及在食品商品调查中发现的通常较大的样本量。这项研究评估了马尔可夫链蒙特卡罗拟合方法与筛选测试和通过最可能数技术对阳性样本进行枚举一起使用时的性能。结果表明，使用建议的拟合方法和超过500个观察值的样本量，可以可靠地估算常见产品-病原体对（例如家禽尸体上的沙门氏菌）的污染水平。但是，结果确实表明无法提供此应用程序的简单指南，例如阳性样品的比例。

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