Risk Ranking of Emerging Hazards in Fresh Produce and Cereal Grains under Climate Change using Multi-Criteria...

Climate change is expected to alter the occurrence and toxicity of microbial and chemical hazards in food systems. Proactive risk ranking of such hazards is advisable before investing in multidisciplinary, quantitative assessments. This study presents a structured risk ranking of emerging microbial and chemical hazards associated with fresh produce and cereal grains in the European Union, under the scope of climate change. The framework used herein is inspired by EFSA risk ranking principles, where complementary top-down and bottom-up evidence streams were integrated into a Multi-Criteria Decision Analysis (MCDA). The top-down direction captures historical public health impacts from outbreak reports. The bottom-up direction consists of two components. First of these is an Expert Knowledge Elicitation (EKE) survey distributed to international specialists, who ranked various hazard-commodity combinations most likely to be affected by climate change. The second bottom-up component was based on predictive microbiology principles, qualitatively linking environmental conditions with the cardinal parameters for growth or toxin production of each hazard. The resulting prioritization identified Aspergillus mycotoxins in cereal grains as the highest-ranked hazard, followed by a series of hazards associated with leafy vegetables, specifically Campylobacter spp., Listeria monocytogenes, Escherichia coli, and Salmonella spp. Additional priority hazards included Fusarium and Penicillium mycotoxins in cereal grains and Bacillus cereus in fresh produce. This list of prioritized hazards may inform future research on the effect of climate change and the food safety of fresh produce. Furthermore, the risk ranking framework applied herein extends conventional MCDA by incorporating elements of qualitative risk assessment, structuring criteria along the causal pathway from environmental drivers to human health outcomes, thus enhancing the reliability and explainability of the analysis.