Food Supply Chain Analytics and Sensing Initiative
Food Supply Chains Health Risks
Risk-based Sampling of Food Supply Chains in China
Food adulteration within the supply chain occurs due to negligence, economically motivated adulteration (EMA), or malicious motivations. In China, food safety regulatory organizations, such as the State Administration for Market Regulation (AMR), rely on random sampling for food safety tests (intended to broadly test for adulterants throughout the supply chain). AMR data is then published independently by each province and prefecture.
Our database work developed a method for scraping AMR data from across these various websites and we: 1) constructed our own automated and centralized database of millions of food inspection results nation-wide, 2) generated interactive maps of high-risk farms/manufacturers, and 3) identified food supply chain sectors which are at high risk for food adulteration.
Using our self-constructed database, we developed a framework for risk-based testing, which uses historical data to identify risky products, companies, and supply chain locations that can significantly improve the ability to locate risk. Analysis shows that provinces selling more animals through high-risk markets have more human cases of zoonotic flu. The results illustrate the effectiveness of this method in identifying risk, and it can facilitate a more granular sampling strategy to enhance food safety in China. The hope is that our approach may offer a new way of understanding zoonotic disease risks, as well as informing regulatory approaches to reduce them.
J. Spencer Standish (1945) Professor of ManagementLearn More
Executive Director, Food Supply Chain Analytics and Sensing (FSAS) InitiativeLearn More
Gao, Qihua, Retsef Levi, and Nicholas Renegar. Scientific Reports Vol. 12, (2022): 1650.
Jin, Cangyu, Retsef Levi, Qiao Liang, Nicholas Renegar, Stacy Springs, Jiehong Zhou, and Weihua Zhou. Management Science Vol. 67, No. 5 (2021): 2985-2996. Supplemental Material. Download Paper.
AMR Database Construction Workflow
Technical Associate II and Associate Director, Data Science, FSASLearn More
Research AssociateLearn More