Moez Sanaa

Review of epidemiological surveys on the prevalence of contamination of healthy cattle with Escherichia coli serogroup O157:H7.

This paper gathers and critically analyses the results of 26 published epidemiological surveys on the prevalence of contamination of cattle with verocytotoxin-producing E. coli (VTEC) serogroup O157:H7. These surveys have been conducted since 1986 on farms in North America (10 studies), on farms in Europe (6 studies) and at slaughterhouses prior to or just after slaughter (7 studies) or after skinning and evisceration (3 studies). The purpose of this review is to understand the first stages of the epidemiology of the infection in animals and humans (the infection process being obscure in many points) and to prepare herd-based control measures to reduce the risk of O157:H7 human infection. The different statistical methods employed in these surveys, as well as the various laboratory screening methods used for detecting positive animals are presented. The observed frequencies of infected animals (animal prevalence) and herds (herd prevalence) are given as a function of localisation, year, type of industry (beef or dairy) and age. From these measured prevalence values, the risk of contamination of ground beef by E. coli O157:H7 in the first stages of the farm-to-fork continuum is assessed. First, we follow the evolution of contamination frequencies from the living animal on-farm to carcasses before transformation. Then, within each set of measurements (i.e., on farm or at slaughterhouse), we identify the effects of the following factors: target population, sampling strategies and laboratory procedures. We argue that the prevalence values inferred from these measurements are very likely underestimated, due to insufficient sampling and not enough sensitive laboratory procedures (one exception being the immunomagnetic bead separation technique). No firm conclusion can be drawn as to the effects of geographical localisation and season. In those surveys, the effect of hygiene level at slaughterhouse on prevalence values is not quantitatively assessed. In addition, there is growing evidence of other sources of E. coli O157:H7 than live cattle in the farm environment, such as feed, water and water-troughs.

Stochastic, Compartmental, and Dynamic Modeling of Cross-Contamination During Mechanical Smearing of Cheeses

Cheese smearing is a complex process and the potential for cross-contamination with pathogenic or undesirable microorganisms is critical. During ripening, cheeses are salted and washed with brine to develop flavor and remove molds that could develop on the surfaces. Considering the potential for cross-contamination of this process in quantitative risk assessments could contribute to a better understanding of this phenomenon and, eventually, improve its control. The purpose of this article is to model the cross-contamination of smear-ripened cheeses due to the smearing operation under industrial conditions. A compartmental, dynamic, and stochastic model is proposed for mechanical brush smearing. This model has been developed to describe the exchange of microorganisms between compartments. Based on the analytical solution of the model equations and on experimental data collected with an industrial smearing machine, we assessed the values of the transfer parameters of the model. Monte Carlo simulations, using the distributions of transfer parameters, provide the final number of contaminated products in a batch and their final level of contamination for a given scenario taking into account the initial number of contaminated cheeses of the batch and their contaminant load. Based on analytical results, the model provides indicators for smearing efficiency and propensity of the process for cross-contamination. Unlike traditional approaches in mechanistic models, our approach captures the variability and uncertainty inherent in the process and the experimental data. More generally, this model could represent a generic base to use in modeling similar processes prone to cross-contamination.

Risk based microbiological criteria for Campylobacter in broiler meat in the European Union

Quantitative microbiological risk assessment (QMRA) allows evaluating the public health impact of food safety targets to support the control of foodborne pathogens. We estimate the risk reduction of setting microbiological criteria (MCs) for Campylobacter on broiler meat in 25 European countries, applying quantitative data from the 2008 EU baseline survey. We demonstrate that risk based MCs can be derived without explicit consideration of Food Safety Objectives or Performance Objectives. Published QMRA models for the consumer phase and dose response provide a relation between Campylobacter concentration on skin samples and the attending probability of illness for the consumer. Probabilistic modelling is used to evaluate a set of potential MCs. We present the percentage of batches not complying with the potential criteria, in relation to the risk reduction attending totally efficient treatment of these batches. We find different risk estimates and different impacts of MCs in different countries, which offers a practical and flexible tool for risk managers to select the most appropriate MC by weighing the costs (i.e. non-compliant batches) and the benefits (i.e. reduction in public health risk). Our analyses show that the estimated percentage of batches not complying with the MC is better correlated with the risk estimate than surrogate risk measures like the flock prevalence or the arithmetic mean concentration of bacteria on carcasses, and would therefore be a good measure for the risk of Campylobacter on broiler meat in a particular country. Two uncertain parameters in the model are the ratio of within- and between-flock variances in concentrations, and the transition factor of skin sample concentrations to concentrations on the meat. Sensitivity analyses show that these parameters have a considerable effect on our results, but the impact of their uncertainty is small compared to that of the parameters defining the Microbiological Criterion and the concentration on the meat.

Risk-Based Approach for Microbiological Food Safety Management in the Dairy Industry: The Case of Listeria monocytogenes in Soft Cheese Made from Pasteurized Milk

According to Codex Alimentarius Commission recommendations, management options applied at the process production level should be based on good hygiene practices, HACCP system, and new risk management metrics such as the food safety objective. To follow this last recommendation, the use of quantitative microbiological risk assessment is an appealing approach to link new risk-based metrics to management options that may be applied by food operators. Through a specific case study, Listeria monocytogenes in soft cheese made from pasteurized milk, the objective of the present article is to practically show how quantitative risk assessment could be used to direct potential intervention strategies at different food processing steps. Based on many assumptions, the model developed estimates the risk of listeriosis at the moment of consumption taking into account the entire manufacturing process and potential sources of contamination. From pasteurization to consumption, the amplification of a primo-contamination event of the milk, the fresh cheese or the process environment is simulated, over time, space, and between products, accounting for the impact of management options, such as hygienic operations and sampling plans. A sensitivity analysis of the model will help orientating data to be collected prioritarily for the improvement and the validation of the model. What-if scenarios were simulated and allowed for the identification of major parameters contributing to the risk of listeriosis and the optimization of preventive and corrective measures.

Assessment of dietary exposure to bisphenol A in the French population with a special focus on risk characterisation for pregnant French women

Bisphenol A (BPA) is used in a wide variety of products and objects for consumers use (digital media such as CDs and DVDs, sport equipment, food and beverage containers, medical equipment). Here, we demonstrate the ubiquitous presence of this contaminant in foods with a background level of contamination of less than 5 μg/kg in 85% of the 1498 analysed samples. High levels of contamination (up to 400 μg/kg) were found in some foods of animal origin. We used a probabilistic approach to calculate dietary exposure from French individual consumption data for infants under 36 months, children and adolescents from 3 to 17 years, adults over 18 years and pregnant women. The estimated average dietary exposure ranged from 0.12 to 0.14 μg/kg body weight per day (bw/d) for infants, from 0.05 to 0.06 μg/kg bw/d for children and adolescents, from 0.038 to 0.040 μg/kg bw/d for adults and from 0.05 to 0.06 μg/kg bw/d for pregnant women. The main sources of exposure were canned foods (50% of the total exposure), products of animal origin (20%) and 30% as a background level. Based on the toxicological values set by the French Agency for Food, Environmental and Occupational Health & Safety (ANSES) for pregnant women, the risk was non negligible. Thus, we simulated scenarios to study the influence of cans and/or food of animal origin on the BPA-related risk for this specific population.

Quantitative risk assessment of haemolytic and uremic syndrome linked to O157:H7 and non-O157:H7 Shiga-toxin producing Escherichia coli strains in raw milk soft cheeses.

Shiga-toxin producing Escherichia coli (STEC) strains may cause human infections ranging from simple diarrhea to Haemolytic Uremic Syndrome (HUS). The five main pathogenic serotypes of STEC (MPS-STEC) identified thus far in Europe are O157:H7, O26:H11, O103:H2, O111:H8, and O145:H28. Because STEC strains can survive or grow during cheese making, particularly in soft cheeses, a stochastic quantitative microbial risk assessment model was developed to assess the risk of HUS associated with the five MPS-STEC in raw milk soft cheeses. A baseline scenario represents a theoretical worst-case scenario where no intervention was considered throughout the farm-to-fork continuum. The risk level assessed with this baseline scenario is the risk-based level. The impact of seven preharvest scenarios (vaccines, probiotic, milk farm sorting) on the risk-based level was expressed in terms of risk reduction. Impact of the preharvest intervention ranges from 76% to 98% of risk reduction with highest values predicted with scenarios combining a decrease of the number of cow shedding STEC and of the STEC concentration in feces. The impact of postharvest interventions on the risk-based level was also tested by applying five microbiological criteria (MC) at the end of ripening. The five MCs differ in terms of sample size, the number of samples that may yield a value larger than the microbiological limit, and the analysis methods. The risk reduction predicted varies from 25% to 96% by applying MCs without preharvest interventions and from 1% to 96% with combination of pre- and postharvest interventions.

Sensitivity Analysis for Critical Control Points Determination and Uncertainty Analysis to Link FSO and Process Criteria: Application to Listeria monocytogenes in Soft Cheese Made from Pasteurized Milk

Microbiological food safety is an important economic and health issue in the context of globalization and presents food business operators with new challenges in providing safe foods. The hazard analysis and critical control point approach involve identifying the main steps in food processing and the physical and chemical parameters that have an impact on the safety of foods. In the risk-based approach, as defined in the Codex Alimentarius, controlling these parameters in such a way that the final products meet a food safety objective (FSO), fixed by the competent authorities, is a big challenge and of great interest to the food business operators. Process risk models, issued from the quantitative microbiological risk assessment framework, provide useful tools in this respect. We propose a methodology, called multivariate factor mapping (MFM), for establishing a link between process parameters and compliance with a FSO. For a stochastic and dynamic process risk model of Listeriamonocytogenes in soft cheese made from pasteurized milk with many uncertain inputs, multivariate sensitivity analysis and MFM are combined to (i) identify the critical control points (CCPs) for L.monocytogenes throughout the food chain and (ii) compute the critical limits of the most influential process parameters, located at the CCPs, with regard to the specific process implemented in the model. Due to certain forms of interaction among parameters, the results show some new possibilities for the management of microbiological hazards when a FSO is specified.

Source Attribution of Foodborne Diseases: Potentialities, Hurdles, and Future Expectations

Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands, 2 Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands, 3 Risk Assessment Department, French Agency for Food, Environmental and Occupational Health & Safety (Anses), Maisons-Alfort, France, 4 Ecole Nationale Vétérinaire d’Alfort, Maisons-Alfort, France, 5 Ploufragan-Plouzané Laboratory, French Agency for Food, Environmental and Occupational Health & Safety (Anses), Ploufragan, France, NSERC Industrial Research Chair in Meat-Safety (CRSV), Faculty of Veterinary Medicine, University of Montreal, Saint-Hyacinthe, QC, Canada, 7 Laboratory for Food Safety, French Agency for Food, Environmental and Occupational Health & Safety (Anses), Maisons-Alfort, France, 8 The French National Public Health Agency, Saint-Maurice, France, 9 Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI),