Bayesian synthesis of a pathogen growth model: Listeria monocytogenes under competition

Abstract

The Bayesian synthesis method is applied to data from two studies of Listeria monocytogenes grown in broth monocultures to draw inferences about the joint distribution of two Baranyi growth model parameters–lag time and maximum specific growth rate. The resultant joint distribution is then combined with prior distributions for the initial and maximum pathogen density parameters under competitive growth conditions. Finally, the pathogen growth model is updated using the Sampling/Importance Resampling (SIR) algorithm with data on L. monocytogenes growth in competition with natural microflora in fish. Although the latter data provide no information on the stationary phase to directly estimate the maximum pathogen density parameter, combining them with relevant prior information provides a means to characterize L. monocytogenes growth in a food with mixed microbial populations. Based on a specified tolerance for L. monocytogenes growth, the updated model provides a storage time limit for fish held at 5 °C, pH 6.8, 43% CO 2, 57% N 2.