Developing an Agent-Based Model that Predicts Listeria spp. Transmission to Assess Listeria Control Strategies in Retail Stores

•Agent-based model can aid decision-making for retailers.•Better data on Listeria transfer coefficients can improve model prediction.•Improving supplier qualification may effectively reduce Listeria at retail. Contamination of fresh produce with Listeria monocytogenes can occur throughout the supply chain, including at retail, where Listeria spp., including L. monocytogenes, may be introduced and spread via various routes. However, limited tools are available for retailers to assess practices that can enhance control of Listeria transmission to fresh produce. Therefore, we developed an agent-based model that can simulate Listeria transmission in retail produce sections to optimize environmental sampling programs and evaluate control strategies. A single retail store was used as a model environment, in which various routes of Listeria introduction into and transmission between environmental surfaces were modeled. Model prediction (i.e., Listeria prevalence) was validated using a published longitudinal study for all surfaces that were included in both the model and the validation data. Sensitivity analysis using the Partial Rank Correlation Coefficient showed that (i) initial Listeria concentration from incoming produce, (ii) transfer coefficient from produce to employee’s hands, and (iii) transfer coefficient from consumer to produce were the top three parameters that were significantly (p