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1.
J Food Prot ; 70(2): 363-72, 2007 Feb.
Article in English | MEDLINE | ID: mdl-17340870

ABSTRACT

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. A data set from human feeding trials with Campylobacter jejuni was fitted to the log-logistic dose-response model, and results from the analysis of FoodNet surveillance data provided further information on variability and uncertainty in Campylobacter susceptibility due to the effect of age. Results of our analyses indicate that uncertainty associated with dose-response modeling has a dominating influence on the analytical outcome. In contrast, inclusion of the age factor has a limited impact. While the advocacy of more closely modeling variability in hazard characterization is warranted, the characterization of key sources of uncertainties and their consistent propagation throughout a microbial risk assessment actually appear of greater importance.


Subject(s)
Campylobacter jejuni/pathogenicity , Food Contamination/analysis , Food Microbiology , Models, Biological , Risk Assessment , Adolescent , Adult , Animals , Child , Child, Preschool , Colony Count, Microbial , Consumer Product Safety , Female , Food Contamination/statistics & numerical data , Humans , Infant , Logistic Models , Male , Middle Aged , Monte Carlo Method , Predictive Value of Tests
2.
J Food Prot ; 69(7): 1630-9, 2006 Jul.
Article in English | MEDLINE | ID: mdl-16865897

ABSTRACT

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. Department of Agriculture-recommended consumer storage and handling practices for frankfurters and deli meats. The demographic characteristics of consumers who are unaware of Listeria and who do not follow the recommended storage guidelines were also assessed. In addition, predictive models were developed to determine which consumers engage in risky storage practices. Less than half of the consumers surveyed were aware of Listeria, and most of those aware were unable to identify associated food vehicles. Awareness was lower among adults 60 years of age and older, an at-risk population for listeriosis, and individuals with relatively less education and lower incomes. Most households safely stored and prepared frankfurters. Most households stored unopened packages of vacuum-packed deli meats in the refrigerator within the U.S. Department of Agriculture-recommended storage guidelines (< or =14 days); however, many stored opened packages of vacuum-packed deli meats and freshly sliced deli meats for longer than the recommended time (< or =5 days). Men, more-educated individuals, and individuals living in metropolitan areas were more likely to engage in risky storage practices. This study identified the need to develop targeted educational initiatives on listeriosis prevention.


Subject(s)
Food Handling/methods , Health Knowledge, Attitudes, Practice , Listeria/growth & development , Meat Products/microbiology , Risk Assessment , Adolescent , Adult , Age Distribution , Animals , Consumer Product Safety , Data Collection , Female , Food Microbiology , Health Education , Health Promotion , Humans , Listeriosis/prevention & control , Male , Middle Aged , Sex Distribution , Surveys and Questionnaires , Time Factors , United States
3.
Risk Anal ; 26(1): 89-103, 2006 Feb.
Article in English | MEDLINE | ID: mdl-16492183

ABSTRACT

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. Food and Drug Administration and the U.S. Department of Agriculture (USDA), the purpose of this work was to expand on the consumer phase of the risk assessment to focus on handling practices in the home. One-dimensional Monte Carlo simulation was used to model variability in growth and cross-contamination of L. monocytogenes during food storage and preparation of deli meats. Simulations approximated that 0.3% of the servings were contaminated with >10(4) CFU/g of L. monocytogenes at the time of consumption. The estimated mean risk associated with the consumption of deli meats for the intermediate-age population was approximately 7 deaths per 10(11) servings. Food handling in homes increased the estimated mean mortality by 10(6)-fold. Of all the home food-handling practices modeled, inadequate storage, particularly refrigeration temperatures, provided the greatest contribution to increased risk. The impact of cross-contamination in the home was considerably less. Adherence to USDA Food Safety and Inspection Service recommendations for consumer handling of ready-to-eat foods substantially reduces the risk of listeriosis.


Subject(s)
Food Microbiology , Listeria monocytogenes/isolation & purification , Listeria monocytogenes/pathogenicity , Meat/microbiology , Animals , Food Handling , Foodborne Diseases/etiology , Foodborne Diseases/mortality , Foodborne Diseases/prevention & control , Humans , Listeria monocytogenes/growth & development , Listeriosis/etiology , Listeriosis/mortality , Listeriosis/prevention & control , Models, Biological , Refrigeration , Risk Assessment , United States/epidemiology
4.
Int J Food Microbiol ; 75(1-2): 71-87, 2002 May 05.
Article in English | MEDLINE | ID: mdl-11999119

ABSTRACT

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.


Subject(s)
Eggs/microbiology , Salmonella enteritidis/growth & development , Animals , Chickens , Consumer Product Safety , Egg Yolk/microbiology , Food Contamination , Food Handling/methods , Food Microbiology , Models, Biological , Monte Carlo Method , Seasons , Temperature
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