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整合食源性和环境性疫情数据的大肠杆菌O157剂量反应模型构建

Dose response modelling of Escherichia coli O157 incorporating data from foodborne and environmental outbreaks.

作者信息

Strachan Norval J C, Doyle Michael P, Kasuga Fumiko, Rotariu Ovidiu, Ogden Iain D

机构信息

School of Biological Sciences, University of Aberdeen, Cruickshank Building, Aberdeen, AB24 3UU, UK.

出版信息

Int J Food Microbiol. 2005 Aug 15;103(1):35-47. doi: 10.1016/j.ijfoodmicro.2004.11.023.

Abstract

A human dose response model for Escherichia coli O157 would enable prediction of risk of infection to humans following exposure from either foodborne or environmental pathways. However, due to the severe nature of the disease, volunteer human dose response studies cannot be carried out. Surrogate models from Shigella fed to humans and E. coli O157 to rabbits have been utilised but are significantly different to one another. In addition data obtained by animal exposure may not be representative for human beings. An alternative approach to generating and validating a dose response model is to use quantitative data obtained from actual human outbreaks. This work collates outbreak data obtained from global sources and these are fitted using exponential and beta-Poisson models. The best fitting model was found to be the beta-Poisson model using a beta-binomial likelihood and the authors favour the exact version of this model. The confidence levels in this model encompass a previously published Shigella dose response model. The potential incorporation of this model into QMRAs is discussed together with applications of the model to help explain foodborne outbreaks.

摘要

大肠杆菌O157的人体剂量反应模型能够预测通过食源性或环境途径接触后人类感染的风险。然而,由于该疾病的严重性,无法开展人体志愿者剂量反应研究。已采用给人类喂食志贺氏菌以及给兔子喂食大肠杆菌O157的替代模型,但这些模型彼此差异显著。此外,通过动物接触获得的数据可能无法代表人类。生成和验证剂量反应模型的另一种方法是使用从实际人类疫情中获得的定量数据。这项工作整理了从全球来源获得的疫情数据,并使用指数模型和β-泊松模型进行拟合。发现最佳拟合模型是使用β-二项式似然的β-泊松模型,作者更倾向于该模型的精确版本。该模型的置信水平涵盖了先前发表的志贺氏菌剂量反应模型。讨论了将该模型纳入定量微生物风险评估的可能性以及该模型在帮助解释食源性疫情方面的应用。

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