The United States Department of Agriculture, Food Safety and Inspection Service (USDA/FSIS), in collaboration with Virginia Tech, developed an updated user friendly version of an initial risk assessment model (the “Risk Assessment for Listeria monocytogenes in Deli Meat (May 2003). The updated model – the "In-Plant Deli Meat Model" – is an open source model (see below Downloads & Resources) that evaluates the effectiveness of processing interventions and testing in reducing the risk of listeriosis associated with ready-to-eat meat and poultry products (e.g., deli meats). This risk assessment provided the scientific basis for FSIS' Listeria policies that resulted in industry-wide adoption of more stringent processing controls and a greater focus on identifying and eliminating in-plant environmental sources of Listeria monocytogenes (Lm) that could cross-contaminate ready-to-eat meat and poultry products. These risk-based policies have been attributed to a substantive decline of Lm in ready-to-eat meat and poultry products observed through FSIS's testing programs (Cartwright, 2013).
FSIS makes this fully annotated version of the In-Plant Deli Meat Model available to support reproducibility of results and training in the use of these types of QMRAs (Haas, 2016). The In-Plant Deli Meat model is a dynamic probabilistic model that predicts Lm concentrations at different stages in the food distribution chain, starting from cross-contamination of ready-to-eat meat and poultry products after the cooking step during processing, through retail, to the point of consumption. The 2004 FAO/WHO Lm dose-response model is used to predict the risk of listeriosis among a healthy population and those who are more susceptible (e.g., elderly, immunocompromised, or pregnant individuals).
The In-Plant Deli Meat Model allows users to evaluate the effectiveness of using growth inhibitors, post-lethality interventions, combinations of these interventions, product testing and diversion, and food contact surface testing and sanitation. The model was developed in the statistical programming language R (R Core Team, 2011). Additional resources to support user operation of the model include an overview of the model, a video tutorial on how to use this model, a data dictionary, and input files and output results for comparison.
Cartwright, E.J., Jackson K.A., Johnson S.D., Graves L.M., Silk B.J., and Mahon B.E. 2013. Listeriosis outbreaks and associated food vehicles, United States, 1998-2008. Emerging Infectious Diseases
, 19(1): 1-9.
Haas C. 2016. Reproducible Risk Assessment. Risk Analysis, 36(10): 1829-1833.
R Core Team. 2017. R: A language and environment for statistical computing. R Foundation for Statistical Commuting, Vienna, Austria. ISBN 3-900051-07-0, URS: www.R-project.org