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. 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.