Assessing the effect on the public health risk of current and alternative border control of Salmonella Typhimurium and Enteritidis in imported frozen poultry meat in Jordan

The JFDA applies border control for Salmonella Typhimurium and Salmonella Enteritidis in frozen poultry products. A QMRA model was developed to evaluate the effectiveness of this system in controlling the risk for consumers. The model consists of three modules; consumer phase, risk estimation, and risk reduction. The model inputs were the occurrence of Salmonella in different types of imported poultry products, the LOD of the Rapid’Salmonella, the number of tested samples of each batch, and the criteria for rejection. The model outputs were public health impact as the Minimum Relative Residual Risk (MRRR) given the batches’ refusal and the percentage of Batches that are Not-compliant with the Microbiological Criteria (BNMC) of rejection. To estimate the overall MRRR of the border control, the estimated country and product-specific MRRR were summarized and weighted by the total imports of each product from each country. The current border control based on one sample per batch gives an overall MRRR value of 27%. The alternative scenarios based on three and five samples per batch are 12% and 8%, respectively. Overall, the higher the prevalence and/or concentration of Salmonella in imported products, the more the likelihood that batches will be rejected. For products with up-to-date data of occurrence, the estimated BNMC was similar to the observed proportion of rejected batches. The lack of data on the Salmonella concentrations in poultry products from different countries is the major source of the uncertainties in the model. It reduces our opportunities to obtain valid estimates of the absolute risk.     

Prior distributions expressing ignorance about convex increasing failure rates

This paper deals with the specification of probability distributions expressing ignorance concerning annual or otherwise discretized failure or mortality rates, when these rates can safely be assumed to be increasing and convex, but are completely unknown otherwise. Such distributions can be used as noninformative priors for Bayesian analysis of failure data. We demonstrate why a uniform distribution used in earlier work is unsatisfactory, especially from the point of view of insensitivity with respect to the time scale that is chosen for the problem at hand. We suggest alternative distributions based on Dirichlet distributed weights for the extreme points of relevant convex sets, and discuss which consequences a requirement for scale neutrality has for the choice of Dirichlet parameters.