The Food and Agriculture Organization of the United Nations (FAO) and Wageningen University recently held a workshop about early warning tools and systems that can be used to manage imminent and emerging food safety issues.
In attendance at the webinar, which took place December 16, 2022, were food safety authorities, researchers, and academics from 31 countries. The two virtual sessions provided an opportunity to present a draft technical report that outlines various early warning tools and systems in food safety. Additionally, the webinar solicited feedback on the feasibility of applying the solutions proposed in the paper, such as Artificial Intelligence (AI) and Big Data, in low- and medium-income countries (LMICs). Also identified during the event were matters of operational or strategic interest for further research or normative work in the area of food safety early warnings.
Identifying emerging food safety risks and having early warning signals have become vital as it allows for food safety managers to apply a proactive approach and avoid food safety incidents before they occur. Using real-time data and digital tools, such as AI, would enhance proactive food safety.
The technical report, currently being drafted by FAO and Wageningen University food safety experts, is aimed at:
- Enhancing awareness and understanding of early warning and emerging risk identification tools and systems in food safety
- Encouraging the application of Big Data and AI in food safety early warning systems
- Considering prospective and innovative ways to implement food safety early warning tools LMICs
- Providing examples of open-access tools to support early warning of food safety issues.
Three systems to support food safety early warning and emerging issues identification were presented in the virtual workshop, specifically:
- Medical Information System of the European Media Monitor (MedISys): a 24/7 media monitoring system based on event surveillance
- MediSys-Food Fraud (MedISys-FF): a media monitoring system providing event-based surveillance to rapidly identify potential public health threats using information from media reports
- SGS DIGICOMPLY: a data-driven platform for food risk prediction and compliance intelligence.
A practical session demonstrated how to create dedicated search queries based on users’ areas of interest that may relate to incidents, regulations, policy news, scientific publications, or social news, choosing topics such as policies and laws, labeling, additives, official controls, or standards.
The timely availability of and accessibility to updated diverse sources and various types of food safety information is critical both for food safety early warning, for getting insights into emerging risks and for supporting the informed and faster risk management decision-making. One of the conclusions from the study and the workshop is that the identification of early warning signals for risks in food and feed is considered important but is not always prioritized, therefore awareness needs to be further enhanced together with developing capability for the application of early warning digital tools.
