Bayesian inference for quantifying Listeria monocytogenes prevalence and concentration in minced pork meat from presence/absence microbiological testing

摘要

The purpose of this work was to estimate the prevalence and concentration of Listeria monocytogenes in minced pork meat by the application of a Bayesian modeling approach. Samples (n = 100) collected from local markets were tested for L monocytogenes using in parallel the PALCAM, ALOA and RAPlD'Lmono selective media. Presence of the pathogen was confirmed through biochemical and molecular tests. Independent experiments (n = 10) for validation purposes were performed. No L monocytogenes was enumerated by direct-plating (<10 CFU/g), though the pathogen was detected in 22% of the samples. Sensitivity and specificity varied depending on the culture method. L monocytogenes concentration was estimated at 14-17 CFU/kg. Validation showed good agreement between observed and predicted prevalence (error = -2.17%). The use of at least two culture media in parallel enhanced the efficiency of L monocytogenes detection. Bayesian modeling may reduce the time needed to draw conclusions regarding L monocytogenes presence and the uncertainty of the results obtained.