In a study published in Scientific Advances, Researchers at Cornell University created an innovative computer program known as Environmental Monitoring With an Agent-Based Model of Listeria (EnABLe) that will assist food safety professionals to advance their measure in keeping production facilities free of any food-borne pathogens. This is especially crucial since foodborne illnesses infect roughly 1,600 people in the U.S. each year with flu-like symptoms often resulting in death for one out of five infected.
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EnABLe holds the potential to be modified and could be next important tool in food contamination prevention and protecting from human exposure to pathogens in tainted food. It can be modified for frozen food productions and even to someday detect pathogens in health-care facilities for the prevention of hospital-acquired infections. "A computer model like EnABLe connects those data to help answer questions related to changes in contamination risks, potential sources of contamination and approaches for risk mitigation and management," explains first author Claire Zoellner, a postdoctoral research associate.
Essentially, the program works by stimulating the most likely regions in a processing facility that breeds deadly food-borne pathogen such as Listeria monocytogene. Professionals can then run assessments to test for areas of bacterial presence.
Listeria is one of the most common food-borne pathogens. Credit: Cornell.edu
"The goal is to build a decision-support tool for control of any pathogen in any complex environment," says Renata Ivanek, an associate professor in the Department of Population Medicine and Diagnostic Sciences and senior author of the paper. "Whenever we have an environment that is complex, we always have to rely on expert opinion and general rules for this system, or this company, but what we're trying to offer is a way to make this more quantitative and systematic by creating this digital reality," Ivanek said.