Biomedical subjects

Heejeong K Latimer

Publications and source records attributed to Heejeong K Latimer.

3 recordsLinked to original sources

PubMed2006

Overview and summary of the Food Safety and Inspection Service risk assessment for Salmonella enteritidis in shell eggs, October 2005.

In 1998, the United States Department of Agriculture's Food Safety and Inspection Service (FSIS) and the Food and Drug Administration completed a risk assessment that indicated multiple interventions along the farm-to-table chain were needed to reduce the risk of human illness from Salmonella Enteritidis in shell eggs. Based on newly available data and improved modeling techniques, FSIS completed an updated risk assessment to examine the effect of pasteurization and refrigeration on reducing human illnesses from S. Enteritidis in shell eggs. The risk assessment model was written in Visual Basic for Applications (Microsoft, Redmond, WA) and run using Monte Carlo methods. The model estimated that if all shell eggs produced in the United States were pasteurized for a 3-log10 reduction of S. Enteritidis, the annual number of illnesses from S. Enteritidis in eggs would decrease from approximately 130,000 to 40,000. Pasteurization for a 5-log10 reduction of S. Enteritidis was estimated to reduce the annual number of illnesses to 19,000. The model also estimated that if all eggs produced in the United States were stored and held at 7.2 degrees C within 12 hours of lay, the annual number of illnesses from S. Enteritidis in eggs would decrease from 130,000 to 28,000. As a result, rapid cooling and pasteurization of shell eggs were predicted to be highly effective mitigations for reducing illnesses from consumption of S. Enteritidis in shell eggs.

Animals↗

PubMed2002

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). This biphasic growth model was then applied to various egg handling scenarios based on the farm-to-table continuum, including in-line and off-line processing facilities with consideration of key events in production, processing, transportation, and storage. Seasonal effects were also studied. Monte Carlo simulation was used to characterize variability in temperature and time parameter values influencing the level of SE to which individuals are exposed. The total level of SE consumed was estimated under best, most likely, and time-temperature abusive handling scenarios. The model estimated that, in most cases, there was no SE growth in contaminated eggs handled under most likely practices, because 10-70% of the yolk membrane remained intact. Under abusive handling scenarios, complete loss of yolk membrane integrity frequently occurred by the time eggs reach the distribution phase, followed by subsequent SE growth, which was often quite rapid. In general, the effect of season and processing method (in-line vs. off-line) was minimal. Further sensitivity analysis demonstrated that the initial SE contamination level significantly influenced the final exposure levels only under no-abuse or mildly abusive conditions. The results of our study suggest that, for maximum reduction of SE exposure level, cooling strategies should not only focus on the on-farm or processing phases, but should emphasize the importance of cooling strategies at the distribution and consumer phases of the farm-to-fork continuum.

Animals↗

PubMedDate not supplied

Discerning strain effects in microbial dose-response data.

In order to estimate the risk or probability of adverse events in risk assessment, it is necessary to identify the important variables that contribute to the risk and provide descriptions of distributions of these variables for well-defined populations. One component of modeling dose response that can create uncertainty is the inherent genetic variability among pathogenic bacteria. For many microbial risk assessments, the "default" assumption used for dose response does not account for strain or serotype variability in pathogenicity and virulence, other than perhaps, recognizing the existence of avirulent strains. However, an examination of data sets from human clinical trials in which Salmonella spp. and Campylobacter jejuni strains were administered reveals significant strain differences. This article discusses the evidence for strain variability and concludes that more biologically based alternatives are necessary to replace the default assumptions commonly used in microbial risk assessment, specifically regarding strain variability.

Campylobacter Infections↗