Risk assessment strategies as a tool in the application of the Appropriate Level of Protection (ALOP) and Food Safety Objective (FSO) by risk managers

Microbiological Risk Assessment in Foods: Background and Tools, with a Focus on Risk Ranger

Risk assessment is an important phase of the food production path; it is strictly related to the processing chain as a necessary step for safe foods. This paper represents a contribution to understanding what is and how risk assessment could be conducted; it aims to provide some information on the structure of risk assessment, the tools for its identification and measurement and the importance of risk assessment for correct communication. In this context, after a focus on the background and on some commonly used tools (Risk Ranger, FDA-iRisk, decision tree, among others), the paper describes how to perform risk assessment through three case studies: lettuce (for Listeria monocytogenes), chicken salad (for Escherichia coli), and fresh egg pasta (for Staphylococcus aureus) in the first step, and then a comparison of risk for chicken salad contaminated by different pathogens (E. coli O157:H7, Campylobacter spp. and Salmonella sp.). As a final step, a critical evaluation of Risk Ranger was carried out, pointing out its pros and cons.

Estimating Listeria monocytogenes Growth in Ready-to-Eat Chicken Salad Using a Challenge Test for Quantitative Microbial Risk Assessment

Currently, there is a growing preference for convenience food products, such as ready-to-eat (RTE) foods, associated with long refrigerated shelf-lives, not requiring a heat treatment prior to consumption. Because Listeria monocytogenes is able to grow at refrigeration temperatures, inconsistent temperatures during production, distribution, and at consumer's household may allow for the pathogen to thrive, reaching unsafe limits. L. monocytogenes is the causative agent of listeriosis, a rare but severe human illness, with high fatality rates, transmitted almost exclusively by food consumption. With the aim of assessing the quantitative microbial risk of L. monocytogenes in RTE chicken salads, a challenge test was performed. Salads were inoculated with a three-strain mixture of cold-adapted L. monocytogenes and stored at 4, 12, and 16 °C for eight days. Results revealed that the salad was able to support L. monocytogenes' growth, even at refrigeration temperatures. The Baranyi primary model was fitted to microbiological data to estimate the pathogen's growth kinetic parameters. Temperature effect on the maximum specific growth rate (μ_max ) was modeled using a square-root-type model. Storage temperature significantly influenced μ_max of L. monocytogenes (p < 0.05). These predicted growth models for L. monocytogenes were subsequently used to develop a quantitative microbial risk assessment, estimating a median number of 0.00008726 listeriosis cases per year linked to the consumption of these RTE salads. Sensitivity analysis considering different time-temperature scenarios indicated a very low median risk per portion (<-7 log), even if the assessed RTE chicken salad was kept in abuse storage conditions.

A Systematic Review of Beef Meat Quantitative Microbial Risk Assessment Models

Each year in Europe, meat is associated with 2.3 million foodborne illnesses, with a high contribution from beef meat. Many of these illnesses are attributed to pathogenic bacterial contamination and inadequate operations leading to growth and/or insufficient inactivation occurring along the whole farm-to-fork chain. To ensure consumer health, decision-making processes in food safety rely on Quantitative Microbiological Risk Assessment (QMRA) with many applications in recent decades. The present study aims to conduct a critical analysis of beef QMRAs and to identify future challenges. A systematic approach, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was used to collate beef QMRA models, identify steps of the farm-to-fork chain considered, and analyze inputs and outputs included as well as modelling methods. A total of 2343 articles were collected and 67 were selected. These studies focused mainly on western countries and considered Escherichia coli (EHEC) and Salmonella spp. pathogens. Future challenges were identified and included the need of whole-chain assessments, centralization of data collection processes, and improvement of model interoperability through harmonization. The present analysis can serve as a source of data and information to inform QMRA framework for beef meat and will help the scientific community and food safety authorities to identify specific monitoring and research needs.

Salmonella in Foods: A Reemerging Problem

The number of human salmonellosis within the European Union tended to increase since 2013. One of the reasons might be Salmonella Enteritidis rising in laying hens flocks by around 17% in 2015 vs 2014 and by 57% in 2016 vs 2015. The most important sources of food-borne Salmonella outbreaks are still eggs and egg products as well as ready-to-eat foods having a long shelf life. Specific actions are suggested to restart decreasing the number of human salmonellosis: (1) revision of sampling schemes to solve pathogen under detection in both animals and foods; (2) integration of microbiological criteria with fit for purpose performance objectives and food safety objectives; and (3) improvement of epidemiological investigations of human, food, and animal isolates by using whole-genome sequencing in order to effectively track salmonellosis and verify which prevention measures are most effective.

Quantitative microbiological risk assessment in food industry: Theory and practical application

The objective of this article is to bring scientific background as well as practical hints and tips to guide risk assessors and modelers who want to develop a quantitative Microbiological Risk Assessment (MRA) in an industrial context. MRA aims at determining the public health risk associated with biological hazards in a food. Its implementation in industry enables to compare the efficiency of different risk reduction measures, and more precisely different operational settings, by predicting their effect on the final model output. The first stage in MRA is to clearly define the purpose and scope with stakeholders, risk assessors and modelers. Then, a probabilistic model is developed; this includes schematically three important phases. Firstly, the model structure has to be defined, i.e. the connections between different operational processing steps. An important step in food industry is the thermal processing leading to microbial inactivation. Growth of heat-treated surviving microorganisms and/or post-process contamination during storage phase is also important to take into account. Secondly, mathematical equations are determined to estimate the change of microbial load after each processing step. This phase includes the construction of model inputs by collecting data or eliciting experts. Finally, the model outputs are obtained by simulation procedures, they have to be interpreted and communicated to targeted stakeholders. In this latter phase, tools such as what-if scenarios provide an essential added value. These different MRA phases are illustrated through two examples covering important issues in industry. The first one covers process optimization in a food safety context, the second one covers shelf-life determination in a food quality context. Although both contexts required the same methodology, they do not have the same endpoint: up to the human health in the foie gras case-study illustrating here a safety application, up to the food portion in the brioche case-study illustrating here a quality application.

Comparative Exposure Assessment of ESBL-Producing Escherichia coli through Meat Consumption

The presence of extended-spectrum β-lactamase (ESBL) and plasmidic AmpC (pAmpC) producing Escherichia coli (EEC) in food animals, especially broilers, has become a major public health concern. The aim of the present study was to quantify the EEC exposure of humans in The Netherlands through the consumption of meat from different food animals. Calculations were done with a simplified Quantitative Microbiological Risk Assessment (QMRA) model. The model took the effect of pre-retail processing, storage at the consumers home and preparation in the kitchen (cross-contamination and heating) on EEC numbers on/in the raw meat products into account. The contribution of beef products (78%) to the total EEC exposure of the Dutch population through the consumption of meat was much higher than for chicken (18%), pork (4.5%), veal (0.1%) and lamb (0%). After slaughter, chicken meat accounted for 97% of total EEC load on meat, but chicken meat experienced a relatively large effect of heating during food preparation. Exposure via consumption of filet americain (a minced beef product consumed raw) was predicted to be highest (61% of total EEC exposure), followed by chicken fillet (13%). It was estimated that only 18% of EEC exposure occurred via cross-contamination during preparation in the kitchen, which was the only route by which EEC survived for surface-contaminated products. Sensitivity analysis showed that model output is not sensitive for most parameters. However, EEC concentration on meat other than chicken meat was an important data gap. In conclusion, the model assessed that consumption of beef products led to a higher exposure to EEC than chicken products, although the prevalence of EEC on raw chicken meat was much higher than on beef. The (relative) risk of this exposure for public health is yet unknown given the lack of a modelling framework and of exposure studies for other potential transmission routes.

Status and future of Quantitative Microbiological Risk Assessment in China

Since the implementation of the Food Safety Law of the People's Republic of China in 2009 use of Quantitative Microbiological Risk Assessment (QMRA) has increased. QMRA is used to assess the risk posed to consumers by pathogenic bacteria which cause the majority of foodborne outbreaks in China. This review analyses the progress of QMRA research in China from 2000 to 2013 and discusses 3 possible improvements for the future. These improvements include planning and scoping to initiate QMRA, effectiveness of microbial risk assessment utility for risk management decision making, and application of QMRA to establish appropriate Food Safety Objectives.

Proposal of performance objectives and sampling schemes for Listeria monocytogenes in fresh meat intended to be eaten cooked under different storage practices

The goal of this study was to define a practical approach to derive risk management measures, such as performance objectives (POs), for Listeria monocytogenes in pork cuts intended to be eaten cooked. Moreover, sampling plans to verify the compliance of meat lots to such POs are presented. The POs were estimated as prevalence and/or concentration values that should not be exceeded at time of consumption. To derive possible POs for L. monocytogenes, ten lots of pork cuts, collected within the same slaughterhouse along a one-year period, were tested for the presence and concentration of the pathogen under four different scenarios through the product shelf life. Our results indicated that the median values of the prevalence distributions ranged between 0.41 and 0.68. The number of samples to be tested in order to verify lot compliance ranged between six, for samples tested immediately after packaging, and three, for samples tested at the end of the shelf life. The concentration values ranged between 2.02 log10 CFU/g, for samples tested immediately after packaging, up to 3.14 log10 CFU/g for samples tested after final storage at 14°C. The concentration of L. monocytogenes in the samples contaminated by less than 10 CFU/g was estimated between 7 CFU/10g to 7 CFU/g, after storage at retail and abuse temperature, respectively. Basing on the knowledge of log normal distributions, the maximum contamination level of the lots in order to achieve the suggested POs, was calculated. It was obtained that mean concentration estimated as PO should be between -0.43 and 0.48 log10 CFU/g. Other risk management options are further evaluated and discussed. These results would help food operators and authorities to establish safety targets and corrective actions regarding inhibition of L. monocytogenes in fresh pork meat.

The challenge of defining risk-based metrics to improve food safety: inputs from the BASELINE project

In 2002, the Regulation (EC) 178 of the European Parliament and of the Council states that, in order to achieve the general objective of a high level of protection of human health and life, food law shall be based on risk analysis. However, the Commission Regulation No 2073/2005 on microbiological criteria for foodstuffs requires that food business operators ensure that foodstuffs comply with the relevant microbiological criteria. Such criteria define the acceptability of a product, a batch of foodstuffs or a process, based on the absence, presence or number of micro-organisms, and/or on the quantity of their toxins/metabolites, per unit(s) of mass, volume, area or batch. The same Regulation describes a food safety criterion as a mean to define the acceptability of a product or a batch of foodstuff applicable to products placed on the market; moreover, it states a process hygiene criterion as a mean indicating the acceptable functioning of the production process. Both food safety criteria and process hygiene criteria are not based on risk analysis. On the contrary, the metrics formulated by the Codex Alimentarius Commission in 2004, named Food Safety Objective (FSO) and Performance Objective (PO), are risk-based and fit the indications of Regulation 178/2002. The main aims of this review are to illustrate the key differences between microbiological criteria and the risk-based metrics defined by the Codex Alimentarius Commission and to explore the opportunity and also the possibility to implement future European Regulations including PO and FSO as supporting parameters to microbiological criteria. This review clarifies also the implications of defining an appropriate level of human protection, how to establish FSO and PO and how to implement them in practice linked to each other through quantitative risk assessment models. The contents of this review should clarify the context for application of the results collected during the EU funded project named BASELINE (www.baselineeurope.eu) as described in the papers of this special issue. Such results show how to derive POs for specific food/biological hazard combinations selected among fish, egg, dairy, meat and plant products.