Food Safety Risk Assessment Research Articles

Risk Assessment and Reassurance in Food Safety

Risk Assessment and Reassurance in Food Safety

Growth limits of Staphylococcus aureus as a function of temperature, acetic acid, NaCl concentration, and inoculum level

Summary Staphylococcus aureus is one of the most prevalent causes of gastroenteritis worldwide. Knowing the precise boundary for the growth/no growth interface of S. aureus and also determining the period of time needed for bacterial growth initiation is necessary for food safety risk assessment. This study was designed to examine the combined effects of temperature, acetic acid, inoculum level and NaCl concentration on the growth of S. aureus in brain heart infusion broth. Growth was monitored by visible turbidity over a 20 days period. Statistical analysis of data showed significant effects for selected parameters on growth of S. aureus. Stepwise multiple regression was used to predict the growth initiation (R 2 = 0.91, P<0.0001). To obtain a boundary model, logistic regression was used. The models accurately predicted the growth initiation and inhibition of S. aureus.

Current Definitions of Risk for Food Safety and Animal Health Allow Risk Assessments to Provide Substantially Different Outcomes

Risk AnalysisVolume 28, Issue 4 p. 811-813 Current Definitions of Risk for Food Safety and Animal Health Allow Risk Assessments to Provide Substantially Different Outcomes Oliver Cerf, Oliver Cerf Alfort Veterinary School, 7 avenue du Général de Gaulle, FR-94700 Maisons-Alfort, France.Search for more papers by this author Oliver Cerf, Oliver Cerf Alfort Veterinary School, 7 avenue du Général de Gaulle, FR-94700 Maisons-Alfort, France.Search for more papers by this author First published: 29 July 2008 https://doi.org/10.1111/j.1539-6924.2008.01076.xCitations: 1 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume28, Issue4August 2008Pages 811-813 RelatedInformation

How University Researchers Can Contribute to Farm-to-Table Risk Assessments:Listeria monocytogenesas an Example

As a part of the Sanitary and Phytosanitary (SPS) agreement, the World Trade Organization requires that member countries establish SPS measures on the basis of an appropriate risk assessment. In addition, many governments use risk assessment in their management of food safety. Consequently, a number of risk assessments for different foodborne pathogens have been conducted. Risk assessments have also been successfully used as a research tool. While, historically, risk assessments are typically initiated by government agencies, university-based researchers are increasingly becoming involved in risk assessments. The purpose of this article is to illustrate the role that university researchers can play in the development and refinement of food safety risk assessments, including possible roles in (1) de novo development or refinement of risk assessment (including farm-to-table risk assessment), (2) data collection supporting risk assessments, and (3) development of new methodological techniques. Transmission of the foodborne pathogen Listeria monocytogenes through the food production chain and risk assessments addressing transmission of this pathogen are used as an example to highlight the roles of university researchers in food safety risk assessments.

Role of microbial risk assessment in food safety.

Worldwide, food contamination (intentional or unintentional) leading to foodborne diseases is a major public health concern. Over the past 20 - 30 years there has been a major change in the epidemiology of foodborne illness, with global spread of existing and new pathogens.

Survey of internal temperatures of New Zealand domestic refrigerators

PurposeTo collate data on internal temperatures of domestic refrigerators in New Zealand.Design/methodology/approachA survey of 127 domestic refrigerators in urban and rural locations in New Zealand was carried out during 2004‐2005. Data loggers were used to record internal temperatures every ten minutes over a 72‐hour period. A short questionnaire was also administered to participants.FindingsThe overall mean temperature was 5.2 °C (standard deviation 2.5 °C). A significant proportion (34 per cent) had a mean temperature &gt;6 °C, while 55 per cent had a mean temperature of &gt;5 °C. There were no statistically significant differences between mean temperatures in refrigerators in rural and urban (two cities) locations. Most consumers were aware of ideal refrigeration temperatures, but lacked the means (thermometers) to check actual operating temperatures.Research limitations/implicationsThe temperature data collected by this survey will be useful for modelling domestic refrigerator storage as a component of food safety quantitative risk models. These data can indicate the amount of time that refrigerators have an internal temperature above a minimum bacterial growth temperature, although the behaviour of bacteria under such fluctuating conditions is not well understood.Originality/valueThese data can assist with food safety promotion and act as an input into food safety risk assessments.

A farm‐to‐fork stochastic simulation model of pork‐borne salmonellosis in humans: Lessons for risk ranking

AbstractA food systems perspective offers many appealing analytic features to food safety researchers with an interest in the design and targeting of effective and efficient policy responses to the risks posed by foodborne pathogens. These features include the ability to examine comparative questions such as whether it is more efficient to target food safety interventions on‐farm or in the food processing plant. Using the example of a farm‐to‐fork stochastic simulation model of Salmonella in the pork production and consumption system, the authors argue the feasibility of such a food systems approach for food‐safety risk assessment and policy analysis. They present an overview of the farm‐to‐fork model and highlight key assumptions and methods employed. Lessons from their experience in constructing a farm‐to‐fork stochastic simulation model are derived for consideration in other food safety risk assessment efforts and for researchers interested in developing “best practice” benchmarks in the area of food safety risk assessments. [EconLit Citations: Q18, I18, I12]. © 2007 Wiley Periodicals, Inc. Agribusiness 23: 157–172, 2007.

Overview and Summary of the Food Safety and Inspection Service Risk Assessment forSalmonellaEnteritidis 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.

Assessing Risk of Unintended Antigen Occurrence in Food: A Case Instance for Maize-Expressed LT-B

ABSTRACT Plant-based antigen production represents an innovative strategy for low cost vaccine production and delivery. Successfully advancing plant-made antigen production in open field systems requires understanding of confinement integrity and consequences of inadvertent occurrence in the food supply. The food safety implications of confinement loss and inadvertent antigen occurrence in the food supply can be effectively addressed using quantitative exposure assessment along with knowledge of properties of specific antigens. We report here a food safety risk assessment for the maize-expressed heat-labile enterotoxin subunit B of Escherichia coli (LT-B). In addition to dietary exposure assessment, food safety considerations for maize-expressed LT-B included assessment of allergenic potential, levels and sites of transgenic protein expression, history of use, post-translational glycosylation, protein processing and digestive stability, mammalian functionality and toxicity, and compositional characteristics of the transformed plant. As shown for LT-B, inadvertent occurrence in the food supply of a plant-produced antigen constitutes a minimal human health concern principally because of limited exposure potential.

食品の確率論的リスクアセスメントと領域横断的アプローチ

食品の確率論的リスクアセスメントと領域横断的アプローチ

Use of secondary enrichment for isolation of Salmonella from naturally contaminated environmental samples

Since the implementation of Hazard Analysis Critical Control Point (HACCP), the need for on-farm food safety risk assessment and management has greatly increased. In order to provide accurate risk assessments, attention should be focused on better characterization of the Salmonella isolation and identification techniques. In this work, we compared the isolation ability of 4 Salmonella-specific protocols: immunomagnetic separation (DB), tetrathionate (TT) broth, Rappaport-Vassiliadis R10 (RV) broth, and a secondary enrichment (TR) procedure as well as 2 selective solid media (brilliant green agar, BG; and xylose-lysine tergitol 4, XLT4). All 4 methods were compared in litter and drag swab samples that were collected weekly during the broiler grow out period in 7 houses. There were 65/126 (51.6%) pooled litter samples positive and 115/304 (37.8%) drag swab samples positive for Salmonella by at least one method. Of the 65 positive litter samples, DB, RV, and TT isolated 1 (2.7%), 31 (47.7%), and 23 (35.4%) of the samples as positive when using BG agar, respectively. The TR protocol identified 83.1% (54/65) of the positive samples as positive when using BG agar. In the drag swab samples, DB did not identify any samples as positive, whereas TT and RV found 28 (25.7%) and 26 (23.9%) of the 109 samples to be positive when using BG agar, respectively. Again, the TR protocol identified the highest percentage of positive samples (94.5%). An analysis of agreement, kappa, revealed that TT and RV did not always agree on which samples were positive, although the number of samples identified as positive by both were not different. A comparison between the 2 agar plates used, BG and XLT4, showed that they had high agreement when the secondary enrichment protocol was used, but agreement was only moderate to low when the other 3 methods were used.

Antimicrobial Resistance Risk Assessment in Food Safety

Microbiological risk assessments generally focus on estimating adverse human health risks from exposures to human pathogenic microbes. The assessment of potential human health risks posed by pathogens that have acquired resistance to antimicrobial drugs is a new application of risk assessment that is closely related to microbiological risk assessment. Antimicrobial resistance risk assessment is a risk analytical process that focuses on resistance determinants as hazardous agents that might lead to drug-resistant microbial infections in humans exposed to bacteria carrying the determinants. Antimicrobial-resistant infections could occur directly from actively invading or opportunistic pathogens or indirectly from the transfer of resistance genes to other bacteria. Here, we discuss risk assessment models that might be employed to estimate risks from drug-resistant bacteria in the animal food pathway and the types of models and data that may be used for microbiological risk assessments or antimicrobial resistance risk assessments.

Food safety risk assessment of child nutrition programs: a survey of purchasing and food preparation practices

Food safety risk assessment of child nutrition programs: a survey of purchasing and food preparation practices

Fine-tuning Food Safety Objectives and risk assessment

Food Safety Objectives (FSOs) have been proposed as a practical tool to translate public health targets for food safety into tolerable levels of pathogens in a food product. The FSO concept is subject to intensive debate, and has not been developed in detail. We evaluate the proposed definition of FSOs and their implementation from the perspective of Quantitative Microbiological Risk Assessment (QMRA). The relationship between QMRA and FSOs is illustrated by a model for the public health risk of Shiga-producing Escherichia coli in steak tartare. We conclude that the proposed definition of FSOs needs to be modified to properly account for variability in and uncertainty about the contamination of food with pathogenic microorganisms and emphasize that both prevalence and concentration of pathogens must be considered. For this purpose, we propose the P– D equivalence curve, a simple graphical tool to separate “tolerable” from “non-tolerable” combinations of prevalence and concentration (dose).

The ComBase initiative

Food safety professionals in industry, academia and regulatory agencies increasingly use computer modelling tools to improve food safety and shelf life (including the development of Hazard Analysis Critical Control Point (HACCP) plans) and to support microbial food safety risk assessments. Earlier this year, we conducted workshops in Melbourne and Sydney to introduce Australian scientists to one such tool, ComBase, and to provide training in its use

Considering the complexity of microbial community dynamics in food safety risk assessment

The potential for competitive inhibition to limit the growth of microbial pathogens in food raises questions about the external validity of typical predictive microbiology studies and suggests the need to consider microbial community dynamics in food safety risk assessment. Ecological theory indicates, however, that community dynamics are highly complex and may be very sensitive to initial conditions and random variation. Seemingly incongruous empirical results for Escherichia coli O157:H7 in ground beef are shown to be consistent with a simple theoretical model of interspecific competition. A potential means of incorporating community-level microbial dynamics into the food safety risk assessment process is explored.

Northern Ireland Food Safety Night

A meeting on food safety entitled “Food Safety: Is It All ‘“Pie-in-the-Sky?’“was held on June 19, 2003, in Belfast, Northern Ireland. Because Northern Ireland has a largely agrarian economy with a strong agricultural food sector, highlighting the importance of safe food production was timely. The meeting was organized by the Northern Ireland Microbiology Discussion Group (NIMDG) and was well attended by several local stakeholders in food safety, including representatives from hospital and public health microbiology laboratories, the Department of Agriculture and Rural Development of Northern Ireland, academia, and the food industry. The group heard presentations from Hugh Pennington, Department of Medical Microbiology, University of Aberdeen, Aberdeen, United Kingdom, and. Mike Kelly, Head of Food Safety and Environmental Health, British Airways. Professor Pennington examined risk assessment in food safety, and discussed the approach to risk assessment of the oil and rail industries, and compared risk assessment between these industries and the food industry. He emphasized that, although science is important at addressing fundamental issues, an important emerging strategy is the translation of scientific findings into everyday practice to ensure that food safety is maintained. The attendees concluded that a greater interaction between microbiologists and psychologists should be encouraged, to add value to the science and ensure tangible benefits in reducing the incidence of foodborne illnesses. The group also learned that differences exist in the incidence of foodborne illnesses between Northern Ireland and Great Britain (England and Wales/Scotland), particularly with Campylobacter and Salmonella infections, and explored possible reasons for such differences, including climate, lack of consumption of unpasteurized milk, and the social custom of having foods “well done.” Mr. Kelly described 42 documented cases of foodborne infections found in the literature that involved contaminated foods on aircraft and detailed, in practical terms, how the concept of a hazard analysis critical control point (HACP) has been used successfully by airline caterers to reduce such infections to a rare occurrence.

Comparison of Monte Carlo and Fuzzy Math Simulation Methods for Quantitative Microbial Risk Assessment

The objective of food safety risk assessment is to quantify levels of risk for consumers as well as to design improved processing, distribution, and preparation systems that reduce exposure to acceptable limits. Monte Carlo simulation tools have been used to deal with the inherent variability in food systems, but these tools require substantial data for estimates of probability distributions. The objective of this study was to evaluate the use of fuzzy values to represent uncertainty. Fuzzy mathematics and Monte Carlo simulations were compared to analyze the propagation of uncertainty through a number of sequential calculations in two different applications: estimation of biological impacts and economic cost in a general framework and survival of Campylobacter jejuni in a sequence of five poultry processing operations. Estimates of the proportion of a population requiring hospitalization were comparable, but using fuzzy values and interval arithmetic resulted in more conservative estimates of mortality and cost, in terms of the intervals of possible values and mean values, compared to Monte Carlo calculations. In the second application, the two approaches predicted the same reduction in mean concentration (−4 log CFU/ml of rinse), but the limits of the final concentration distribution were wider for the fuzzy estimate (−3.3 to 5.6 log CFU/ml of rinse) compared to the probability estimate (−2.2 to 4.3 log CFU/ml of rinse). Interval arithmetic with fuzzy values considered all possible combinations in calculations and maximum membership grade for each possible result. Consequently, fuzzy results fully included distributions estimated by Monte Carlo simulations but extended to broader limits. When limited data defines probability distributions for all inputs, fuzzy mathematics is a more conservative approach for risk assessment than Monte Carlo simulations.

Modeling microbial growth within food safety risk assessments.

Risk estimates for food-borne infection will usually depend heavily on numbers of microorganisms present on the food at the time of consumption. As these data are seldom available directly, attention has turned to predictive microbiology as a means of inferring exposure at consumption. Codex guidelines recommend that microbiological risk assessment should explicitly consider the dynamics of microbiological growth, survival, and death in foods. This article describes predictive models and resources for modeling microbial growth in foods, and their utility and limitations in food safety risk assessment. We also aim to identify tools, data, and knowledge sources, and to provide an understanding of the microbial ecology of foods so that users can recognize model limits, avoid modeling unrealistic scenarios, and thus be able to appreciate the levels of confidence they can have in the outputs of predictive microbiology models. The microbial ecology of foods is complex. Developing reliable risk assessments involving microbial growth in foods will require the skills of both microbial ecologists and mathematical modelers. Simplifying assumptions will need to be made, but because of the potential for apparently small errors in growth rate to translate into very large errors in the estimate of risk, the validity of those assumptions should be carefully assessed. Quantitative estimates of absolute microbial risk within narrow confidence intervals do not yet appear to be possible. Nevertheless, the expression of microbial ecology knowledge in "predictive microbiology" models does allow decision support using the tools of risk assessment.

Introduction to special section on sensitivity analysis and summary of NCSU/USDA workshop on sensitivity analysis.

This guest editorial is a summary of the NCSU/USDA Workshop on Sensitivity Analysis held June 11-12, 2001 at North Carolina State University and sponsored by the U.S. Department of Agriculture's Office of Risk Assessment and Cost Benefit Analysis. The objective of the workshop was to learn across disciplines in identifying, evaluating, and recommending sensitivity analysis methods and practices for application to food-safety process risk models. The workshop included presentations regarding the Hazard Assessment and Critical Control Points (HACCP) framework used in food-safety risk assessment, a survey of sensitivity analysis methods, invited white papers on sensitivity analysis, and invited case studies regarding risk assessment of microbial pathogens in food. Based on the sharing of interdisciplinary information represented by the presentations, the workshop participants, divided into breakout sessions, responded to three trigger questions: What are the key criteria for sensitivity analysis methods applied to food-safety risk assessment? What sensitivity analysis methods are most promising for application to food safety and risk assessment? and What are the key needs for implementation and demonstration of such methods? The workshop produced agreement regarding key criteria for sensitivity analysis methods and the need to use two or more methods to try to obtain robust insights. Recommendations were made regarding a guideline document to assist practitioners in selecting, applying, interpreting, and reporting the results of sensitivity analysis.