Dr. Kshitij Shrestha, SFRO, DFTQC
Abstract
This study replicates and extends the FDA-iRISK
comparative risk assessment framework, originally described by Chen et al.(2013), within the R statistical programming environment. The primary objective
was to reconstruct the core computational models for assessing the public
health burden of foodborne hazards, specifically Salmonella in peanut
butter and Listeria monocytogenes in soft ripened cheese and
cantaloupe, while introducing advanced visualization capabilities not present
in the original web-based tool. The R-based model faithfully implements the key
components of iRISK: stochastic process models simulating pathogen fate from
production to consumption, population-specific consumption patterns,
dose-response relationships (Beta-Poisson for Salmonella, exponential
for L. monocytogenes), and health impact quantification using
Disability-Adjusted Life Years (DALYs). Monte Carlo simulation techniques (mc2d package)
were employed to propagate variability and uncertainty. The model successfully
reproduced the central findings of the original case studies, confirming the
significant annual DALY burden of Salmonella in peanut butter (61.9
DALYs) and the variable risk of listeriosis across perinatal (9.8 DALYs),
elderly (5.6 DALYs), and intermediate-age (1.0 DALYs) populations. Beyond replication,
this implementation enhances the original iRISK system by generating a suite of
dynamic visualizations, including distributional analyses of concentrations,
doses, and risks, comparative population risk matrices, and detailed
intervention effectiveness plots. These visualizations provide deeper insights
into the underlying risk dynamics and the impact of potential interventions,
such as pathogen log-reduction and temperature control. The R script offers a
transparent, modifiable, and extensible platform for quantitative
microbiological risk assessment (QMRA), making it a valuable tool for
researchers and risk managers seeking to evaluate and communicate food safety
risks. The complete R code is provided for full reproducibility.
Keywords: Quantitative Microbiological Risk Assessment (QMRA), FDA-iRISK, Salmonella, Listeria monocytogenes, Monte Carlo Simulation, R Programming, DALYs, Food Safety, Intervention Analysis.
