Maarten Nauta

Separation of uncertainty and variability in quantitative microbial risk assessment models

Quantitative risk assessment (QRA) modelling is increasingly used in food microbiology as a tool to evaluate health risks and to support the management of safe food production. Depending on the hazard and the process analysed, a QRA model may involve complex calculations: probability distributions are derived for the model parameters and the model is evaluated using specific risk analysis software. Second-order modelling, involving the separation of uncertainty and variability of model parameters, is considered of increasing importance in several fields of risk analysis. However, it is commonly neglected in microbial risk assessment studies. In this paper the relevance of second-order modelling in microbial risk assessment is illustrated by a simple example of a risk assessment of growth of B. cereus in pasteurised milk. It shows that the prediction of the outbreak size may depend on the way that uncertainty and variability are separated, and that a major outbreak may be overlooked if the distinction between uncertainty and variability is neglected.

Modelling bacterial growth in quantitative microbiological risk assessment: is it possible?

Quantitative microbiological risk assessment (QMRA), predictive modelling and HACCP may be used as tools to increase food safety and can be integrated fruitfully for many purposes. However, when QMRA is applied for public health issues like the evaluation of the status of public health, existing predictive models may not be suited to model bacterial growth. In this context, precise quantification of risks is more important than in the context of food manufacturing alone. In this paper, the modular process risk model (MPRM) is briefly introduced as a QMRA modelling framework. This framework can be used to model the transmission of pathogens through any food pathway, by assigning one of six basic processes (modules) to each of the processing steps. Bacterial growth is one of these basic processes. For QMRA, models of bacterial growth need to be expressed in terms of probability, for example to predict the probability that a critical concentration is reached within a certain amount of time. In contrast, available predictive models are developed and validated to produce point estimates of population sizes and therefore do not fit with this requirement. Recent experience from a European risk assessment project is discussed to illustrate some of the problems that may arise when predictive growth models are used in QMRA. It is suggested that a new type of predictive models needs to be developed that incorporates modelling of variability and uncertainty in growth.

A reconsideration of the Campylobacter dose-response relation.

As a major foodborne pathogen, Campylobacter jejuni receives much attention in quantitative risk assessment. To date, all dose-response assessments have been based on a single human feeding study which unfortunately provides incomplete and possibly biased information on the dose-response relation. An incident at a dairy farm, where several children from a school class became ill as a result of drinking raw milk contaminated with C. jejuni, appeared to show a very clear dose-response relation between the amount of milk consumed and the attack rate. This relation was very nearly exponentially shaped and, therefore, seemed to conflict with the rather slowly rising dose-response relation established in the feeding study. Here we show that both datasets can be reconciled when illness and infection are considered separately. This not only provides new information on the illness dose-response relation for Campylobacter, but also amends the infection dose-response relation because of their conditional dependence.

A retail and consumer phase model for exposure assessment of Bacillus cereus

An exposure assessment is conducted for psychrotrophic and mesophilic Bacillus cereus in a cooked chilled vegetable product. A model is constructed that covers the retail and consumer phase of the food pathway, using the output of a similar model on the industrial process as input. Microbial growth is the predominant process in the model. Variability in time and temperature during transport and storage is included in the model and different domestic refrigerator temperature distributions are compared. As an end point, probable levels of B. cereus colony forming units (cfu) in packages of vegetable purée are predicted at the moment the consumer takes the product from its refrigerator, that is prior to a cooking process. The psychrotrophic strain is predicted to end up above a threshold level of 10(5) cfu/g in 0.9% to 6.3% of the vegetable purée packages, depending on domestic refrigerator temperature. Accounting for spoilage this reduces to 0.3% to 2.4%. Even if the purée is stored at 4 degrees C in the domestic refrigerator and use-by-date (UBD) is respected, the threshold level may be passed. For the mesophilic strain the threshold level is rarely passed, but in contrast to the total viable count, the spore load at the end point is predicted to be higher than in the psychrotrophic strain. Our study illustrates how an exposure assessment model, which may be used in quantitative risk assessment, can integrate expertise in modelling, food processing and microbiology over the food pathway, and thus evaluate food safety, identify gaps in knowledge and compare risk management measures. As important gaps in knowledge, the lack of sporulation and germination models and data, validated non-isothermal growth models and a spoilage model useful for risk assessment are identified. Knowledge of the dose-response relationship is limited and does not allow a full risk assessment. It is shown that exposure can be lowered by lowering domestic refrigerator temperatures, and less so much by monitoring and withdrawing contaminated products at the end of industrial processing.

Estimating the true incidence of campylobacteriosis and salmonellosis in the European Union, 2009

We estimated the true incidence of campylobacteriosis and salmonellosis in the European Union (EU) in 2009. The estimate was based on disease risks of returning Swedish travellers, averaged over the years 2005-2009, and anchored to a Dutch population-based study on incidence and aetiology of gastroenteritis. For the 27 EU member states the incidence of campylobacteriosis was about 9·2 (95% CI 2·8-23) million cases, while the incidence of salmonellosis was 6·2 (95% CI 1·0-19) million cases. Only 1/47 (95% CI 14-117) cases of campylobacteriosis and one 1/58 (95% CI 9-172) cases of salmonellosis were reported in the EU. The incidence rate of campylobacteriosis in EU member states varied between 30 and 13 500/100 000 population and was significantly correlated with the prevalence of Campylobacter spp. in broiler chickens. The incidence rate of salmonellosis in EU member states varied between 16 and 11 800/100 000 population and was significantly correlated with the prevalence of Salmonella Enteritidis in laying hens.

Improving Food Safety in the Domestic Environment: The Need for a Transdisciplinary Approach

Microbial food safety has been the focus of research across various disciplines within the risk analysis community. Natural scientists involved in food microbiology and related disciplines work on the identification of health hazards, and the detection of pathogenic microorganisms. To perform risk assessment, research activities are increasingly focused on the quantification of microbial contamination of food products at various stages in the food chain, and modeling the impact of this contamination on human health. Social scientists conduct research into how consumers perceive food risks, and how best to develop effective risk communication with consumers in order to improve public health through improved food handling practices. The two approaches converge at the end of the food chain, where the activities regarding food preparation and food consumption are considered. Both natural and social sciences may benefit from input and expertise from the perspective of the alternative discipline, although, to date, the integration of social and natural sciences has been somewhat limited. This article therefore explores the potential of a transdisciplinary approach to food risk analysis in terms of delivering additional improvements to public health. Developing knowledge arising from research in both the natural and social sciences, we present a novel framework involving the integration of the two approaches that might provide the most effective way to improve the consumer health associated with food-borne illness.

A Poultry-Processing Model for Quantitative Microbiological Risk Assessment

A poultry-processing model for a quantitative microbiological risk assessment (QMRA) of campylobacter is presented, which can also be applied to other QMRAs involving poultry processing. The same basic model is applied in each consecutive stage of industrial processing. It describes the effects of inactivation and removal of the bacteria, and the dynamics of cross-contamination in terms of the transfer of campylobacter from the intestines to the carcass surface and the environment, from the carcasses to the environment, and from the environment to the carcasses. From the model it can be derived that, in general, the effect of inactivation and removal is dominant for those carcasses with high initial bacterial loads, and cross-contamination is dominant for those with low initial levels. In other QMRA poultry-processing models, the input-output relationship between the numbers of bacteria on the carcasses is usually assumed to be linear on a logarithmic scale. By including some basic mechanistics, it is shown that this may not be realistic. As nonlinear behavior may affect the predicted effects of risk mitigations; this finding is relevant for risk management. Good knowledge of the variability of bacterial loads on poultry entering the process is important. The common practice in microbiology to only present geometric mean of bacterial counts is insufficient: arithmetic mean are more suitable, in particular, to describe the effect of cross-contamination. The effects of logistic slaughter (scheduled processing) as a risk mitigation strategy are predicted to be small. Some additional complications in applying microbiological data obtained in processing plants are discussed.

Research on factors allowing a risk assessment of spore-forming pathogenic bacteria in cooked chilled foods containing vegetables: a FAIR collaborative project

Vegetables are frequent ingredients of cooked chilled foods and are frequently contaminated with spore-forming bacteria (SFB). Therefore, risk assessment studies have been carried out, including the following: hazard identification and characterisation--from an extensive literature review and expertise of the participants, B. cereus and C. botulinum were identified as the main hazards; exposure assessment--consisting of determination of the prevalence of hazardous SFB in cooked chilled foods containing vegetables and in unprocessed vegetables, and identification of SFB representative of the bacterial community in cooked chilled foods containing vegetables, determination of heat-resistance parameters and factors affecting heat resistance of SFB, determination of the growth kinetics of SFB in vegetable substrate and of the influence of controlling factors, validation of previous work in complex food systems and by challenge testing and information about process and storage conditions of cooked chilled foods containing vegetables. The paper illustrates some original results obtained in the course of the project. The results and information collected from scientific literature or from the expertise of the participants are integrated into the microbial risk assessment, using both a Bayesian belief network approach and a process risk model approach, previously applied to other foodborne hazards.

Cross‐contamination in the kitchen: effect of hygiene measures

Aims:  To determine the effect of hygiene measures on cross‐contamination of Campylobacter jejuni at home and to select a safe tracer organism for C. jejuni.

Cross-contamination in the kitchen: estimation of transfer rates for cutting boards, hands and knives

Aims:  To quantify cross‐contamination in the home from chicken to ready‐to‐eat salad.