Persistent Listeria monocytogenes contamination may occur in a packinghouse if the pathogen successfully infiltrates the facility and reaches a harborage site, from where it is difficult to remove and may contaminate produce within the facility. There is a need for simulation-based decision support tools that can predict which equipment sites are more likely to undergo persistent contamination and simulate potential corrective actions to prevent persistent contamination. Thus, we adapted for longer term simulation two existing applications of an agent-based model of Listeria spp. hourly contamination dynamics in produce packinghouses. Next, we developed a novel approach to identify and analyze persistent and transient Listeria contamination patterns on simulated agents representing equipment sites and employees. Testing of corrective actions showed that methods that involved targeted, facility-specific, risk-based sanitation were the most effective in both reducing the likelihood and duration of persistent contamination. This emphasizes that generic approaches to controlling Listeria (e.g., more concentrated sanitizers) are unlikely to be successful and suggests that usage of sanitation schedules produced through facility-specific root-cause analysis and hygienic design are key in reducing persistence. Hourly Listeria contamination patterns also suggest that transient contamination may be mistaken for persistent, depending on the frequency of environmental sampling. Likewise, as concentrations of Listeria on most contaminated agents were predicted to be very low, there is also a possibility to mistake persistence for transient contamination of sites, or even miss it outright due to false negative environmental Listeria monitoring results. These findings support that agent-based models may be valuable decision-support tools, aiding in the identification of contamination patterns within packinghouses and assessing the viability of specific corrective actions.
KSWFoodWorld
FoodWorld 