Second-order modeling of variability and uncertainty in microbial hazard characterization.

This study describes an analytical framework that permits quantitative consideration of variability and uncertainty in microbial hazard characterization. Second-order modeling that used two-dimensional Monte Carlo simulation and stratification into homogeneous population subgroups was applied to integrate uncertainty and variability. Specifically, the bootstrap method was used to simulate sampling error due to the limited sample size in microbial dose-response modeling.

Consumer knowledge, storage, and handling practices regarding Listeria in frankfurters and deli meats: results of a Web-based survey.

Proper storage and handling of refrigerated ready-to-eat foods can help reduce the risk of listeriosis. A national Web-based survey was conducted to measure consumer awareness and knowledge of Listeria and to estimate the prevalence of the U.S.

Consumer phase risk assessment for Listeria monocytogenes in deli meats.

The foodborne disease risk associated with the pathogen Listeria monocytogenes has been the subject of recent efforts in quantitative microbial risk assessment. Building upon one of these efforts undertaken jointly by the U.S.

Sensitivity analysis of Salmonella enteritidis levels in contaminated shell eggs using a biphasic growth model.

Salmonella enteritidis (SE) is a common foodbome pathogen, the transmission of which is primarily associated with the consumption of contaminated Grade A shell eggs. In order to estimate the level of SE present in raw shell eggs, it is necessary to consider the protective effects of the egg albumin, which effectively inhibits SE growth in a time- and temperature-dependent manner. In this study, a SE growth model was produced by combining two mathematical equations that described both the extended lag phase of SE growth (food component) and a SE growth model (pathogen component).