Listeriosis accounts for 27.6% of all foodborne disease deaths and has a hospitalization rate of nearly 95%, despite the United States’ adoption of a “zero tolerance policy” for L. monocytogenes levels on foods. Other countries have adopted a quantitative threshold of the pathogen on Ready-to-Eat Commodities, while the US typically integrated Environmental Monitoring Programs to monitor the environment for indicators of the pathogen itself. This allows for sanitation efforts to be directed in presence/absence testing for indicators of L. monocytogenes, Listeria spp.; however, these monitoring procedures for produce do not quantify levels of L. monocytogenes contamination. Instead, surfaces are tested for the presence of indicators for the sanitation of the production environments. This study uses Quantitative Microbial Risk Assessment (QMRA) to analyze a Listeriosis outbreak from 2014 associated with contaminated caramel apples to investigate the potential presence of low-level concentrations. QMRA is a modeling framework that commonly uses environmental sampling data and mathematical modeling of fate and transport dynamics to characterize the likelihood of adverse health effects due to pathogen exposure. However, in reverse, epidemiological study results from outbreaks can be used to estimate pathogen concentrations in environmental matrices. Thus, a reverse QMRA (rQMRA) was developed to determine the concentration of L. monocytogenes present within apple packinghouses associated with the 2014 caramel apple outbreak to better understand the limitations of current detection methods for pathogens, such as L. monocytogenes. To capture human variability, two models were constructed with four consumer handling scenarios based on storage temperature (7 °C, twenty-five °C) and storage duration (1 day, 1 week). For immunocompetent populations, the mean estimations were between 0.25 and 0.34 (CFU/g) for the various storage conditions. Much lower median concentrations (0.02-0.07 CFU/g) were estimated for the pregnancy - stillbirth endpoint model. This study indicates that the potential non-zero concentration of pathogens in produce houses calls on the need to integrate prevalence data with more quantitative data to better investigate the potential of missed sampling zones, detection limitations in food safety technology, and to provide more evidence-based reasoning to support policy reform in the future.
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