Centre for Disease Modelling, Department of Mathematics and Statistics, York University, Toronto, Canada.
J Theor Biol. 2013 Mar 21;321:28-35. doi: 10.1016/j.jtbi.2012.12.024. Epub 2013 Jan 5.
Understanding the geographic and temporal spread of food-borne diseases associated with fresh produce is crucial for informing adequate surveillance and control. As a first step towards this goal, we develop and analyze a novel three stage model at the processing/sanitization juncture in the fresh produce supply chain. The key feature of our model is its ability to describe the dynamics of cross-contamination during commercial wash procedures. In general, we quantify the degree of cross-contamination in terms of model parameters. Applying these results in the case of Escherichia coli O157:H7 contamination of fresh-cut romaine lettuce, we identify the mean wash time and free chlorine concentration as critical parameters. In addition to showing how these parameters affect contamination levels, we recommend that in order to prevent potential source misidentification, at least 2.2 mg/L of free chlorine should be used during a wash lasting at least 30s.
了解与新鲜农产品相关的食源性疾病的地理和时间分布对于提供充分的监测和控制至关重要。作为实现这一目标的第一步,我们在新鲜农产品供应链的加工/消毒环节开发并分析了一个新颖的三阶段模型。我们模型的关键特征是能够描述商业清洗过程中的交叉污染动态。通常,我们根据模型参数来量化交叉污染的程度。将这些结果应用于大肠杆菌 O157:H7 污染的新鲜切碎生菜的情况,我们确定平均清洗时间和游离氯浓度为关键参数。除了展示这些参数如何影响污染水平外,我们还建议为了防止潜在的源误识别,在至少 30 秒的清洗过程中,应使用至少 2.2 毫克/升的游离氯。