Artificial Intelligence and Blockchain Applications in Food Safety Traceability and Foodborne Outbreak Prevention in Low- and Middle-Income Countries (LMICs): A Scoping Review

Foodborne diseases remain a major global public health challenge, affecting millions of people annually and contributing significantly to morbidity, mortality, healthcare costs, and economic losses. The burden of foodborne illnesses is disproportionately higher in low- and middle-income countries (LMICs), where challenges such as inadequate food safety infrastructure, weak regulatory systems, limited laboratory capacity, poor surveillance mechanisms, and fragmented food supply chains continue to affect food safety outcomes. Food safety traceability systems play a critical role in identifying the origin, movement, and handling of food products throughout the supply chain. Effective traceability enables rapid identification of contamination sources, supports outbreak investigations, and reduces the spread of foodborne diseases. However, conventional traceability systems in many LMIC settings remain limited due to paper-based documentation, poor data integration, delayed reporting systems, and insufficient coordination among stakeholders. Emerging digital technologies, particularly Artificial Intelligence (AI) and blockchain technology, have gained increasing attention as potential solutions for strengthening food safety systems. Artificial Intelligence technologies, including machine learning, deep learning, and predictive analytics, can support early detection of contamination risks, outbreak prediction, automated monitoring, and improved decision-making. Blockchain technology, through decentralized and immutable record systems, can enhance transparency, accountability, and trust across food supply chains. Despite increasing interest in these technologies, evidence regarding their application, feasibility, challenges, and impact within LMIC contexts remains fragmented. A comprehensive mapping of existing evidence is required to understand how AI and blockchain technologies are currently being applied to food safety traceability and foodborne outbreak prevention. Therefore, this scoping review seeks to identify, map, and synthesize available evidence on AI and blockchain applications in food safety systems across LMICs, while highlighting knowledge gaps and future research priorities.