Training in modern statistical methodologies and software tools for the definition and analysis of (stochastic) quantitative microbial risk assessment models with relevant food products for the Italian and Spanish food supply chains - Abdul Muhammad Ehtesham; Virginia Filipello; Pablo S. Fernandèz Escàmez; Alberto Garre Perez (EFSA Journal)
Abstract The fellowship, entitled ‘Training in modern statistical methodologies and software tools for the definition and analysis of (stochastic) quantitative microbial risk assessment models with relevant food products for the Italian and Spanish food supply chains’, was implemented at the Universidad Politécnica de Cartagena (UPCT), Spain. Supervised by Dr. Alberto Garre and Prof. Pablo S. Fernandez and coordinated by Dr. Virginia Filipello of the Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna, Italy, the fellowship aimed to provide hands‐on training in quantitative microbial risk assessment (QMRA). The fellow benefited from UPCT's expertise in microbiological risk assessment, gaining knowledge of methodologies, terminologies and software tools essential for QMRA. The focus of the fellowship was on the risks associated with plant‐based milk products, which are increasingly popular as sustainable alternatives to dairy milk. Despite the heat treatments these beverages undergo to ensure safety, risks persist, such as cross‐contamination during post‐processing or the survival of heat‐resistant spores like Bacillus cereus. A recent European outbreak linked to contaminated oat milk underscored the importance of assessing these risks. The project was conducted in two phases: first, at UPCT's Food Microbiology Laboratory, where the fellow handled and characterised the thermal resistance of various B. cereus strains using a thermoresistometer; and second, through remote analysis of experimental data using risk analysis software tools. The fellow developed skills in microbiological techniques, such as spore preparation and thermal resistance evaluation, and became proficient in data analysis using the R programming language and the biorisk package. The fellowship culminated in the development of a QMRA model to estimate the likelihood of B. cereus‐related foodborne illness from plant‐based milks, considering different heat treatments and bacterial strains. The fellow's training covered all stages of risk assessment, including hazard identification, exposure assessment, hazard characterisation and risk characterisation, providing a comprehensive foundation for a career in food safety and microbial risk assessment.