An Agent‐Based Model for Pathogen Persistence and Cross‐Contamination Dynamics in a Food Facility

Abstract

We used an agent-based modeling (ABM) framework and developed a mathematical model to explain the complex dynamics of microbial persistence and spread within a food facility and to aid risk managers in identifying effective mitigation options. The model explicitly considered personal hygiene practices by food handlers as well as their activities and simulated a spatially explicit dynamic system representing complex interaction patterns among food handlers, facility environment, and foods. To demonstrate the utility of the model in a decisionmaking context, we created a hypothetical case study and used it to compare different risk mitigation strategies for reducing contamination and spread of Listeria monocytogenes in a food facility. Model results indicated that areas with no direct contact with foods (e.g., loading dock and restroom) can serve as contamination niches and recontaminate areas that have direct contact with food products. Furthermore, food handlers' behaviors, including, for example, hygiene and sanitation practices, can impact the persistence of microbial contamination in the facility environment and the spread of contamination to prepared foods. Using this case study, we also demonstrated benefits of an ABM framework for addressing food safety in a complex system in which emergent system-level responses are predicted using a bottom-up approach that observes individual agents (e.g., food handlers) and their behaviors. Our model can be applied to a wide variety of pathogens, food commodities, and activity patterns to evaluate efficacy of food-safety management practices and quantify contamination reductions associated with proposed mitigation strategies in food facilities.

Leveraging risk assessment for foodborne outbreak investigations: The Quantitative Risk Assessment‐Epidemic Curve Prediction Model

“…FDA‐Melon QRA‐EC used the Agent‐Based Modeling (ABM) framework presented in Mokhtari and Van Doren (2019) to describe fresh‐cut melon processing steps including initial cleaning, transfer on conveyor belts, automated peeling, manual cutting and seeds removal, automated chunking, and manual product assembly (Figure 1). The processing module primarily focused on the cross‐contamination between food handlers, processing equipment surfaces, and melons (whole and cut melons).…”

A tipping point of spreading viruses: Estimating the risk of household contact transmission of COVID-19

“…Mokhtari et al [5] developed an agent-based model of microbial persistence and spread in food facilities, simulating a spatially dynamic system representing the hygiene behavior of food handlers and their interactions between the facility environment and food products. Experimental results showed that areas not in direct contact with food (loading docks and toilets) could act as contamination sites and recontaminate regions in direct contact with food.…”

Agent‐based simulation of cross‐contamination of Escherichia coli O157:H7 on lettuce during processing and temperature fluctuations during storage in a produce facility. Part 2: Model implementation

“…Most cross‐contamination studies rely on mixing inoculated and noninoculated produce and further enumeration (Nou & Luo, 2010). In the absence of reliable pathogen cross‐contamination detection systems in fresh produce, probabilistic system models (Mishra, Pang, Buchanan, Schaffner, & Pradhan, 2017), mechanistic models (Munther, Luo, Wu, Magpantay, & Srinivasan, 2015); risk assessment models (Perez‐Rodríguez, Campos, Ryser, & Buchholz, 2011) and other mathematical models that include the use of agent‐based frameworks (Mokhtari, Oryang, Chen, Pouillot, & Doren, 2018; Mokhtari & Van Doren, 2019; Zoellner, Jennings, Wiedmann, & Ivanek, 2019) have become important information tools.…”