Kshitij Shrestha, Rojeena Shrestha
Department of Food Technology and Quality Control, Babarmahal, Kathmandu, Nepal
Highlights
• FDA-iRISK model successfully replicated in R, validating its computational engine.
• R-based estimates closely aligned with original Salmonella DALY results.
• Contamination reduction and improved cooling lowered risk by 93% and 99.9%.
• Uncertainty analysis revealed 7-fold variation in Listeria risk estimates.
• Open-source R framework offers flexible, reproducible food safety assessment.
Abstract
This study successfully replicated the FDA-iRISK comparative food safety risk assessment model described by Chen et al. (2013) within the R software environment, validating its core computational engine for case studies on Salmonella in peanut butter and Listeria monocytogenes in soft cheese and cantaloupe. Our R-based model, which leverages Monte Carlo simulation, produced results strongly aligned with the original publication; for instance, it estimated 63.05 annual Disability-Adjusted Life Years (DALYs) for Salmonella, compared to the published 63.5 in the original manuscript. The model quantified the profound effectiveness of interventions, demonstrating a 93% risk reduction from a 2-log decrease in initial contamination and a 99.9% reduction from improved refrigeration control. Furthermore, we extended the model's utility through enhanced visualizations and a dedicated uncertainty analysis. This analysis revealed a 7-fold variation in risk estimates for Listeria, providing deeper insights into risk variability, intervention impacts, and the critical influence of parameter uncertainty. The outcome of this work is a transparent and flexible platform for robust food safety decision-making.
The Article was published in the following Journal
Food Control
Volume 192, February 2027, 112513
https://doi.org/10.1016/j.foodcont.2026.112513
Full Article is available in the link below:
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