Data from: Development and application of an alert system to detect cases of food poisoning in Japan

Recent public health concerns regarding commercial food products have increased the need to develop an automated method to detect food product-related health events. We developed and verified a method for the early detection of potentially harmful events caused by commercial food products. We collected data from daily internet-based questionnaires examining the presence or absence of symptoms and information about food purchased by the respondents. Using these data, we developed a method to detect possible health concerns regarding commercialized food products. To achieve this, we combined the signal detection method used in the reporting system of adverse effects of pharmaceutical products and the Early Aberration Reporting System (EARS) used by the United States Centers for Disease Control. The results showed that whiteleg shrimp (Litopenaeus vannamei), which had odds ratio and Odds(?) of 8.99 and 4.13, respectively, was identified as a possible causative food product for diarrhea and vomiting. In conclusion, this study demonstrated that food distributors can implement post-marketing monitoring of the safety of food products purchased via the internet.

近年来，公众对商业食品的公共健康担忧日益加剧，催生了研发用于检测食品相关健康事件的自动化方法的迫切需求。本研究开发并验证了一种可早期识别商业食品引发潜在有害健康事件的方法。我们通过每日线上问卷收集数据，问卷内容涵盖受访者是否出现相关症状，以及其购买食品的相关信息。基于上述数据，我们构建了可识别商业化食品潜在健康风险的检测方法。为实现该目标，我们结合了药品不良反应报告系统中所用的信号检测方法，以及美国疾病控制与预防中心（United States Centers for Disease Control）采用的早期异常报告系统（Early Aberration Reporting System, EARS）。研究结果显示，凡纳滨对虾（Litopenaeus vannamei）的比值比（odds ratio）与优势比（Odds）分别为8.99和4.13，被认定为引发腹泻与呕吐的潜在致病食品。综上，本研究证实，食品经销商可针对线上购买的食品开展上市后安全监测工作。