Reducing Listeria Contamination in Produce Packinghouses Through Agent-Based Modeling

Abstract

The complex environment of fresh produce packinghouses can facilitate the spread of pathogens such as Listeria monocytogenes, which can enter a facility and establish itself within harborage sites. From here, food being shipped from the packinghouse is at risk of being contaminated with L. monocytogenes, endangering public health. Thus, reducing pathogen presence and cross-contamination within these facilities are crucial. The studies presented here demonstrate the development of Agent-Based Models of Listeria contamination dynamics in packinghouses and the analysis of contamination behavior. These models were used to compare the effectiveness of different corrective actions on a short-term scale, as well as observe persistent contamination and the effectiveness of corrective actions on reducing it. Overall, results indicate that both data-informed corrective actions and reduction of Listeria in incoming raw produce are effective in the short-term, but only the former produces long-term improvement in controlling Listeria in the packinghouse environment.