Sherri B. Dennis

FDA-iRISK-A Comparative Risk Assessment System for Evaluating and Ranking Food-Hazard Pairs: Case Studies on Microbial Hazards

Stakeholders in the system of food safety, in particular federal agencies, need evidence-based, transparent, and rigorous approaches to estimate and compare the risk of foodborne illness from microbial and chemical hazards and the public health impact of interventions. FDA-iRISK (referred to here as iRISK), a Web-based quantitative risk assessment system, was developed to meet this need. The modeling tool enables users to assess, compare, and rank the risks posed by multiple food-hazard pairs at all stages of the food supply system, from primary production, through manufacturing and processing, to retail distribution and, ultimately, to the consumer. Using standard data entry templates, built-in mathematical functions, and Monte Carlo simulation techniques, iRISK integrates data and assumptions from seven components: the food, the hazard, the population of consumers, process models describing the introduction and fate of the hazard up to the point of consumption, consumption patterns, dose-response curves, and health effects. Beyond risk ranking, iRISK enables users to estimate and compare the impact of interventions and control measures on public health risk. iRISK provides estimates of the impact of proposed interventions in various ways, including changes in the mean risk of illness and burden of disease metrics, such as losses in disability-adjusted life years. Case studies for Listeria monocytogenes and Salmonella were developed to demonstrate the application of iRISK for the estimation of risks and the impact of interventions for microbial hazards. iRISK was made available to the public at http://irisk.foodrisk.org in October 2012.

Listeria monocytogenes Growth Dynamics on Produce: A Review of the Available Data for Predictive Modeling

Several listeriosis outbreaks have been linked to the consumption of fresh or processed produce in recent years. One major determinant of the listeriosis risk is the ability of a food to support growth of Listeria monocytogenes during storage. However, data regarding the ability to support growth of L. monocytogenes are scarce or nonexisting for many produce commodities. Here we synthesize the available data regarding growth behavior of L. monocytogenes on produce, compare the growth data with listeriosis outbreak data, and evaluate the adequacy of the data for predictive modeling. Growth rates and maximum L. monocytogenes population densities differed markedly among produce commodities, and post-harvest processing had a considerable effect on growth dynamics for certain commodities such as tomatoes. However, data scarcity prevented reliable estimation of growth rates for many commodities. Produce outbreaks seemed frequently associated with processed produce and often involved storage under suboptimal conditions (e.g., at room temperature for several hours or for several months in the refrigerator) or environmental cross-contamination after processing. However, no clear associations between high growth rates of L. monocytogenes on fresh produce and outbreaks were detected. In conclusion, produce commodities differ in the supported growth rate of L. monocytogenes, the maximum attainable L. monocytogenes population density, and possibly in the impact of post-harvest processing, but data are currently insufficient to predict growth behavior, and the listeriosis risk appears to be also governed by additional factors.

Microbial risk assessment.

Microbial risk assessment (MRA) is used to evaluate foodborne hazards, the likelihood of exposure to those hazards, and the resulting public-health impact. It is generally recognized to consist of four parts: hazard identification, hazard characterization, exposure assessment, and risk characterization. Model predictions generated by MRAs are most often expressed as the estimated likelihood of foodborne illness and/or number of deaths in a given population for a given period. MRA is used increasingly to inform decision-making aimed both at managing human health risks from foodborne pathogens and at devising standards for promoting safe and fair international food trade. This chapter discusses how MRA fits into the larger context of risk analysis, describes in detail the process of MRA, reviews examples of recently completed MRAs, and suggests steps towards further improvement of the MRA process.

Listeria monocytogenes Dose Response Revisited—Incorporating Adjustments for Variability in Strain Virulence and Host Susceptibility

Evaluations of Listeria monocytogenes dose-response relationships are crucially important for risk assessment and risk management, but are complicated by considerable variability across population subgroups and L. monocytogenes strains. Despite difficulties associated with the collection of adequate data from outbreak investigations or sporadic cases, the limitations of currently available animal models, and the inability to conduct human volunteer studies, some of the available data now allow refinements of the well-established exponential L. monocytogenes dose response to more adequately represent extremely susceptible population subgroups and highly virulent L. monocytogenes strains. Here, a model incorporating adjustments for variability in L. monocytogenes strain virulence and host susceptibility was derived for 11 population subgroups with similar underlying comorbidities using data from multiple sources, including human surveillance and food survey data. In light of the unique inherent properties of L. monocytogenes dose response, a lognormal-Poisson dose-response model was chosen, and proved able to reconcile dose-response relationships developed based on surveillance data with outbreak data. This model was compared to a classical beta-Poisson dose-response model, which was insufficiently flexible for modeling the specific case of L. monocytogenes dose-response relationships, especially in outbreak situations. Overall, the modeling results suggest that most listeriosis cases are linked to the ingestion of food contaminated with medium to high concentrations of L. monocytogenes. While additional data are needed to refine the derived model and to better characterize and quantify the variability in L. monocytogenes strain virulence and individual host susceptibility, the framework derived here represents a promising approach to more adequately characterize the risk of listeriosis in highly susceptible population subgroups.

Listeria monocytogenes in Retail Delicatessens: an Interagency Risk Assessment-model and baseline results.

The Interagency Risk Assessment-Listeria monocytogenes (Lm) in Retail Delicatessens provides a scientific assessment of the risk of listeriosis associated with the consumption of ready-to-eat (RTE) foods commonly prepared and sold in the delicatessen (deli) of a retail food store. The quantitative risk assessment (QRA) model simulates the behavior of retail employees in a deli department and tracks the Lm potentially present in this environment and in the food. Bacterial growth, bacterial inactivation (following washing and sanitizing actions), and cross-contamination (from object to object, from food to object, or from object to food) are evaluated through a discrete event modeling approach. The QRA evaluates the risk per serving of deli-prepared RTE food for the susceptible and general population, using a dose-response model from the literature. This QRA considers six separate retail baseline conditions and provides information on the predicted risk of listeriosis for each. Among the baseline conditions considered, the model predicts that (i) retail delis without an environmental source of Lm (such as niches), retail delis without niches that do apply temperature control, and retail delis with niches that do apply temperature control lead to lower predicted risk of listeriosis relative to retail delis with niches and (ii) retail delis with incoming RTE foods that are contaminated with Lm lead to higher predicted risk of listeriosis, directly or through cross-contamination, whether the contaminated incoming product supports growth or not. The risk assessment predicts that listeriosis cases associated with retail delicatessens result from a sequence of key events: (i) the contaminated RTE food supports Lm growth; (ii) improper retail and/or consumer storage temperature or handling results in the growth of Lm on the RTE food; and (iii) the consumer of this RTE food is susceptible to listeriosis. The risk assessment model, therefore, predicts that cross-contamination with Lm at retail predominantly results in sporadic cases.

Transfer of Escherichia coli O157:H7 from Simulated Wildlife Scat onto Romaine Lettuce during Foliar Irrigation

A field trial in Salinas Valley, California, was conducted during July 2011 to quantify the microbial load that transfers from wildlife feces onto nearby lettuce during foliar irrigation. Romaine lettuce was grown using standard commercial practices and irrigated using an impact sprinkler design. Five grams of rabbit feces was spiked with 1.29 × 10(8) CFU of Escherichia coli O157:H7 and placed - 3, - 2, and - 1 days and immediately before a 2-h irrigation event. Immediately after irrigation, 168 heads of lettuce ranging from ca. 23 to 69 cm (from 9 to 27 in.) from the fecal deposits were collected, and the concentration of E. coli O157:H7 was determined. Thirty-eight percent of the collected lettuce heads had detectable E. coli O157:H7, ranging from 1 MPN to 2.30 × 10(5) MPN per head and a mean concentration of 7.37 × 10(3) MPN per head. Based on this weighted arithmetic mean concentration of 7.37 × 10(3) MPN of bacteria per positive head, only 0.00573% of the original 5 g of scat with its mean load of 1.29 × 10(8) CFU was transferred to the positive heads of lettuce. Bacterial contamination was limited to the outer leaves of lettuce. In addition, factors associated with the transfer of E. coli O157:H7 from scat to lettuce were distance between the scat and lettuce, age of scat before irrigation, and mean distance between scat and the irrigation sprinkler heads. This study quantified the transfer coefficient between scat and adjacent heads of lettuce as a function of irrigation. The data can be used to populate a quantitative produce risk assessment model for E. coli O157:H7 in romaine lettuce to inform risk management and food safety policies.

Initiating and managing risk assessments within a risk analysis framework: FDA/CFSAN'S practical approach.

Management of risk analysis involves the integration and coordination of activities associated with risk assessment, risk management, and risk communication. Risk analysis is used to guide regulatory decision making, including trade decisions at national and international levels. The U.S. Food and Drug Administration Center for Food Safety and Applied Nutrition (CFSAN) formed a working group to evaluate and improve the quality and consistency of major risk assessments conducted by the Center. Drawing on risk analysis experiences, CFSAN developed a practical framework for initiating and managing risk assessments, including addressing issues related to (i) commissioning a risk assessment, (ii) interactions between risk managers and risk assessors, and (iii) peer review.

Intensive Investigation of Bacterial Foodborne Disease Outbreaks: Proposed Guidelines and Tools for the Collection of Dose-Response Data by Local Health Departments

Local health departments that investigate foodborne disease outbreaks do not have adequate guidelines for collecting data that could be used to estimate dose-response relationships, a key component of hazard characterization in quantitative microbial risk assessment. To meet this need, criteria and a questionnaire template for the collection of appropriate dose-response data in the context of outbreaks were developed and applied in the investigation of a point-source outbreak linked to Salmonella serotype Enteritidis in a salmon entrée in February 2000. In this outbreak, the attack rate and risk of hospitalization increased with the amount of salmon entrée consumed, and detailed data were obtained on illness severity measures and host susceptibility factors. Local health departments might consider broadening investigations to include the collection of additional data when investigating outbreaks that have met a specific set of conditions. These data could provide information needed by federal regulatory agencies and other organizations for quantitative microbial risk assessment. Intensive investigations of outbreaks could prevent future illnesses by providing information needed to develop approaches to minimizing risk.

Survey for Listeria monocytogenes in and on Ready-to-Eat Foods from Retail Establishments in the United States (2010 through 2013): Assessing Potential Changes of Pathogen Prevalence and Levels in a Decade

A multiyear interagency Listeria monocytogenes Market Basket Survey was undertaken for selected refrigerated ready-to-eat foods purchased at retail in four FoodNet sites in the United States. Food samples from 16 food categories in six broad groups (seafood, produce, dairy, meat, eggs, and combination foods) were collected weekly at large national chain supermarkets and independent grocery stores in California, Maryland, Connecticut, and Georgia for 100 weeks between December 2010 and March 2013. Of the 27,389 total samples, 116 samples tested positive by the BAX PCR system for L. monocytogenes , and the pathogen was isolated and confirmed for 102 samples. Among the 16 food categories, the proportion of positive samples (i.e., without considering clustering effects) based on recovery of a viable isolate of L. monocytogenes ranged from 0.00% (95% confidence interval: 0.00, 0.18) for the category of soft-ripened and semisoft cheese to 1.07% (0.63, 1.68) for raw cut vegetables. Among the 571 samples that tested positive for Listeria-like organisms, the proportion of positive samples ranged from 0.79% (0.45, 1.28) for soft-ripened and semisoft cheese to 4.76% (2.80, 7.51) for fresh crab meat or sushi. Across all 16 categories, L. monocytogenes contamination was significantly associated with the four states (P < 0.05) but not with the packaging location (prepackaged by the manufacturer versus made and/or packaged in the store), the type of store (national chain versus independent), or the season. Among the 102 samples positive for L. monocytogenes , levels ranged from <0.036 most probable number per g to 6.1 log CFU/g. For delicatessen (deli) meats, smoked seafood, seafood salads, soft-ripened and semisoft cheeses, and deli-type salads without meat, the percentage of positive samples was significantly lower (P < 0.001) in this survey than that reported a decade ago based on comparable surveys in the United States. Use of mixed logistic regression models to address clustering effects with regard to the stores revealed that L. monocytogenes prevalence ranged from 0.11% (0.03, 0.34) for sprouts (prepackaged) to 1.01% (0.58, 1.74) for raw cut vegetables (prepackaged).

Listeria monocytogenes in Retail Delicatessens: An Interagency Risk Assessment-Risk Mitigations.

Cross-contamination, improper holding temperatures, and insufficient sanitary practices are known retail practices that may lead to product contamination and growth of Listeria monocytogenes. However, the relative importance of control options to mitigate the risk of invasive listeriosis from ready-to-eat (RTE) products sliced or prepared at retail is not well understood. This study illustrates the utility of a quantitative risk assessment model described in a first article of this series (Pouillot, R., D. Gallagher, J. Tang, K. Hoelzer, J. Kause, and S. B. Dennis, J. Food Prot. 78:134-145, 2015) to evaluate the public health impact associated with changes in retail deli practices and interventions. Twenty-two mitigation scenarios were modeled and evaluated under six different baseline conditions. These scenarios were related to sanitation, worker behavior, use of growth inhibitors, cross-contamination, storage temperature control, and reduction of the level of L. monocytogenes on incoming RTE food products. The mean risk per serving of RTE products obtained under these scenarios was then compared with the risk estimated in the baseline condition. Some risk mitigations had a consistent impact on the predicted listeriosis risk in all baseline conditions (e.g. presence or absence of growth inhibitor), whereas others were greatly dependent on the initial baseline conditions or practices in the deli (e.g. preslicing of products). Overall, the control of the bacterial growth and the control of contamination at its source were major factors of listeriosis risk in these settings. Although control of cross-contamination and continued sanitation were also important, the decrease in the predicted risk was not amenable to a simple solution. Findings from these predictive scenario analyses are intended to encourage improvements to retail food safety practices and mitigation strategies to control L. monocytogenes in RTE foods more effectively and to demonstrate the utility of quantitative risk assessment models to inform risk management decisions.