Laboratory for Foodborne Zoonoses, Public Health Agency of Canada, Faculté de Médecine Vétérinaire, Pavillon de Santé Publique Vétérinaire, Saint-Hyacinthe, Québec, Canada.
Foodborne Pathog Dis. 2010 Dec;7(12):1463-72. doi: 10.1089/fpd.2010.0582. Epub 2010 Aug 12.
The study used a structured expert elicitation survey to derive estimates of the foodborne attributable proportion for nine illnesses caused by enteric pathogens in Canada. It was based on a similar study conducted in the United States and focused on Campylobacter, Escherichia coli O157:H7, Listeria monocytogenes, nontyphoidal Salmonella enterica, Shigella spp., Vibrio spp., Yersinia enterocolitica, Cryptosporidium parvum, and Norwalk-like virus. For each pathogen, experts were asked to provide their best estimate and low and high limits for the proportion of foodborne illness relative to total cases. In addition, they provided background information with regard to food safety experience, including self-evaluated expertise for each pathogen on a 5-point scale. A snowball approach was used to identify 152 experts within Canada. The experts' background details were summarized using descriptive statistics. Factor analysis was used to determine whether the variability in best estimates was related to self-assessed level of expertise or other background information. Cluster analysis followed by beta function fitting was undertaken on best estimates from experts who self-evaluated their expertise 3 or higher. In parallel, Monte Carlo resampling was run using triangular distributions based on each expert's best estimate and its limits. Sixty-six experts encompassing various academic backgrounds, fields of expertise, and experiences relevant to food safety provided usable data. Considerable variation between experts in their estimated foodborne attributable proportions was observed over all diseases, without any relationship to the expert's background. Uncertainty about their estimate (measured by the low and high limits) varied between experts and between pathogens as well. Both cluster analysis and Monte Carlo resampling clearly indicated disagreement between experts for Campylobacter, E. coli O157, L. monocytogenes, Salmonella, Vibrio, and Y. enterocolitica. In the absence of more reliable estimates, the observed discrepancy between experts must be explored and understood before one can judge which opinion is the best.
本研究采用结构化专家 elicitation 调查方法,对加拿大九种食源性病原体引起的疾病的食源性归因比例进行了估计。该研究基于在美国进行的一项类似研究,重点关注空肠弯曲菌、大肠杆菌 O157:H7、李斯特菌单核细胞增生李斯特菌、非伤寒沙门氏菌、志贺氏菌、弧菌、耶尔森氏菌 enterocolitica、微小隐孢子虫和诺如病毒。对于每种病原体,专家被要求提供其最佳估计值以及食源性疾病相对总病例的低限和高限。此外,他们还提供了食品安全经验方面的背景信息,包括对每种病原体的自我评估专业知识进行五分制评估。采用滚雪球方法在加拿大确定了 152 名专家。使用描述性统计方法总结专家的背景详细信息。因子分析用于确定最佳估计值的变异性是否与自我评估的专业知识水平或其他背景信息有关。对自我评估专业知识水平为 3 或更高的专家的最佳估计值进行聚类分析和贝塔函数拟合。同时,基于每个专家的最佳估计值及其范围,使用基于三角分布的蒙特卡罗重采样进行并行处理。来自不同学术背景、专业领域和食品安全相关经验的 66 名专家提供了可用数据。在所有疾病中,观察到专家对食源性归因比例的估计值存在很大差异,且与专家的背景无关。专家对其估计值的不确定性(通过低限和高限衡量)在不同专家和不同病原体之间也存在差异。聚类分析和蒙特卡罗重采样都清楚地表明,在空肠弯曲菌、大肠杆菌 O157、李斯特菌、沙门氏菌、弧菌和耶尔森氏菌方面,专家之间存在意见分歧。在缺乏更可靠的估计值的情况下,在判断哪种意见最佳之前,必须探讨和理解专家之间的这种差异。