Marie Cornu

Estimation of uncertainty and variability in bacterial growth using Bayesian inference. Application to Listeria monocytogenes.

The usefulness of risk assessment is limited by its ability or inability to model and evaluate risk uncertainty and variability separately. A key factor of variability and uncertainty in microbial risk assessment could be growth variability between strains and growth model parameter uncertainty. In this paper, we propose a Bayesian procedure for growth parameter estimation which makes it possible to separate these two components by means of hyperparameters. This model incorporates in a single step the logistic equation with delay as a primary growth model and the cardinal temperature equation as a secondary growth model. The estimation of Listeria monocytogenes growth parameters in milk using literature data is proposed as a detailed application. While this model should be applied on genuine data, it is highlighted that the proposed approach may be convenient for estimating the variability and uncertainty of growth parameters separately, using a complete predictive microbiology model.

Modelling the competitive growth of Listeria monocytogenes and Listeria innocua in enrichment broths

The overgrowth of Listeria innocua in enrichment broths designed for the isolation of Listeria monocytogenes is believed to result from two factors: a selective growth advantage of L. innocua, and/or an inhibitory interspecies interaction. The generation times of 13 isolates of L. innocua and L. monocytogenes were determined in Brain Heart Infusion (BHI) and a variety of enrichment media. No significant differences were found in growth characteristics between either species in the various media, suggesting that the growth advantage of L. innocua in enrichment media was not as significant as previously described. Kinetic analysis of mixed cultures of L. monocytogenes and isolates of L. innocua producing a variety of inhibitory activities demonstrated the possibility of an inhibitory interaction between these two species resulting in the overgrowth of the enrichment culture with L. innocua. Modelling the evolution of the ratio between two populations in an enrichment process was used to analyze the impact of a selective growth advantage in L. innocua in an enrichment process for growth of L. monocytogenes. These findings support the widely held view that an overgrowth of L. innocua in the enrichment process can result from both a selective growth advantage as well as the production of inhibitory compounds. From a practical perspective, these interactions can result in an increase in false negatives.

A contribution to the improvement of Listeria monocytogenes enumeration in cold-smoked salmon

For the enumeration of Listeria monocytogenes in food, a sensitive enumeration method based on membrane filtration followed by transfer of the filter to a selective medium has been developed. This study was carried out with cold-smoked salmon, a product likely to be contaminated with L. monocytogenes. The operating protocol utilizes three filtration runs in parallel (5, 15 and 30 ml) of a 1 in 10 dilution of the salmon suspension through 0.45-microm pore-size cellulose ester membranes, and then culture of the filters on Aloa agar (AES Laboratoires, Combourg, France). The results obtained with the technique were compared with those from the reference EN ISO 11290-2 method and found to provide more precise results in the enumeration of L. monocytogenes from both artificially and naturally contaminated cold-smoked salmon. Moreover, for several samples contaminated at low levels, L. monocytogenes could be recovered only by the filtration method. The examination of increasing volumes of salmon suspension enabled readable results to be obtained for all levels of L. monocytogenes and competitive microflora investigated. In most cases, the optimised operating protocol enabled 5.1 g of salmon to be examined, instead of 0.01-0.1 g with the reference EN ISO 11290-2 method, thus improving the sensitivity of the method.

Design of challenge testing experiments to assess the variability of Listeria monocytogenes growth in foods.

The assessment of the evolution of micro-organisms naturally contaminating food must take into account the variability of biological factors, food characteristics and storage conditions. A research project involving eight French laboratories was conducted to quantify the variability of growth parameters of Listeria monocytogenes obtained by challenge testing in five food products. The residual variability corresponded to a coefficient of variation (CV) of approximately 20% for the growth rate (μ(max)) and 130% for the parameter K = μ(max) × lag. The between-batch and between-manufacturer variability of μ(max) was very dependent on the food tested and mean CV of approximately 20 and 35% were observed for these two sources of variability, respectively. The initial physiological state variability led to a CV of 100% for the parameter K. It appeared that repeating a limited number of three challenge tests with three different batches (or manufacturers) and with different initial physiological states seems often necessary and adequate to accurately assess the variability of the behavior of L. monocytogenes in a specific food produced by a given manufacturer (or for a more general food designation).

Validation of a stochastic modelling approach for Listeria monocytogenes growth in refrigerated foods

A stochastic modelling approach was developed to describe the distribution of Listeria monocytogenes contamination in foods throughout their shelf life. This model was designed to include the main sources of variability leading to a scattering of natural contaminations observed in food portions: the variability of the initial contamination, the variability of the biological parameters such as cardinal values and growth parameters, the variability of individual cell behaviours, the variability of pH and water activity of food as well as portion size, and the variability of storage temperatures. Simulated distributions of contamination were compared to observed distributions obtained on 5 day-old and 11 day-old cheese curd surfaces artificially contaminated with between 10 and 80 stressed cells and stored at 14°C, to a distribution observed in cold smoked salmon artificially contaminated with approximately 13 stressed cells and stored at 8°C, and to contaminations observed in naturally contaminated batches of smoked salmon processed by 10 manufacturers and stored for 10 days a 4°C and then for 20 days at 8°C. The variability of simulated contaminations was close to that observed for artificially and naturally contaminated foods leading to simulated statistical distributions properly describing the observed distributions. This model seems relevant to take into consideration the natural variability of processes governing the microbial behaviour in foods and is an effective approach to assess, for instance, the probability to exceed a critical threshold during the storage of foods like the limit of 100 CFU/g in the case of L. monocytogenes.

Quantitative Risk Assessment of Listeria monocytogenes in French Cold-Smoked Salmon: II. Risk Characterization

A model for the assessment of exposure to Listeria monocytogenes from cold-smoked salmon consumption in France was presented in the first of this pair of articles (Pouillot et al., 2007, Risk Analysis, 27:683-700). In the present study, the exposure model output was combined with an internationally accepted hazard characterization model, adapted to the French situation, to assess the risk of invasive listeriosis from cold-smoked salmon consumption in France in a second-order Monte Carlo simulation framework. The annual number of cases of invasive listeriosis due to cold-smoked salmon consumption in France is estimated to be 307, with a very large credible interval ([10; 12,453]), reflecting data uncertainty. This uncertainty is mainly associated with the dose-response model. Despite the significant uncertainty associated with the predictions, this model provides a scientific base for risk managers and food business operators to manage the risk linked to cold-smoked salmon contaminated with L. monocytogenes. Under the modeling assumptions, risk would be efficiently reduced through a decrease in the prevalence of L. monocytogenes or better control of the last steps of the cold chain (shorter and/or colder storage during the consumer step), whereas reduction of the initial contamination levels of the contaminated products and improvement in the first steps of the cold chain do not seem to be promising strategies. An attempt to apply the recent risk-based concept of FSO (food safety objective) on this example underlines the ambiguity in practical implementation of the risk management metrics and the need for further elaboration on these concepts.

Uncertainty Distribution Associated with Estimating a Proportion in Microbial Risk Assessment

The uncertainty associated with estimates should be taken into account in quantitative risk assessment. Each inputs uncertainty can be characterized through a probabilistic distribution for use under Monte Carlo simulations. In this study, the sampling uncertainty associated with estimating a low proportion on the basis of a small sample size was considered. A common application in microbial risk assessment is the estimation of a prevalence, proportion of contaminated food products, on the basis of few tested units. Three Bayesian approaches (based on beta(0, 0), beta(1/2, 1/2), and beta(l, 1)) and one frequentist approach (based on the frequentist confidence distribution) were compared and evaluated on the basis of simulations. For small samples, we demonstrated some differences between the four tested methods. We concluded that the better method depends on the true proportion of contaminated products, which is by definition unknown in common practice. When no prior information is available, we recommend the beta (1/2, 1/2) prior or the confidence distribution. To illustrate the importance of these differences, the four methods were used in an applied example. We performed two-dimensional Monte Carlo simulations to estimate the proportion of cold smoked salmon packs contaminated by Listeria monocytogenes, one dimension representing within-factory uncertainty, modeled by each of the four studied methods, and the other dimension representing variability between companies.

New Developments in the Restitution of Cultural Property: Alternative means of Dispute Resolution

Alternative methods of dispute resolution are an important resource in matters of cultural heritage in addressing the return, restitution, and repatriation of cultural property. The purpose of this article is to analyze the situations in which such methods might be preferred to the classical judicial means and to examine the problems that might arise. The article is in two parts. The first part describes the actors as well as the current methods used for the restitution and return of cultural property. The second part explores the types of property that lend themselves to alternative dispute resolution techniques and lists the—often original—substantive solutions that have been used in practice. Alternative methods of dispute resolution enable consideration of nonlegal factors, which might be emotional considerations or a sense of “moral obligation,” and this can help the parties find a path to consensus.

Hierarchical Bayesian Models to Assess Between- and Within-Batch Variability of Pathogen Contamination in Food

Assessing within-batch and between-batch variability is of major interest for risk assessors and risk managers in the context of microbiological contamination of food. For example, the ratio between the within-batch variability and the between-batch variability has a large impact on the results of a sampling plan. Here, we designed hierarchical Bayesian models to represent such variability. Compatible priors were built mathematically to obtain sound model comparisons. A numeric criterion is proposed to assess the contamination structure comparing the ability of the models to replicate grouped data at the batch level using a posterior predictive loss approach. Models were applied to two case studies: contamination by Listeria monocytogenes of pork breast used to produce diced bacon and contamination by the same microorganism on cold smoked salmon at the end of the process. In the first case study, a contamination structure clearly exists and is located at the batch level, that is, between batches variability is relatively strong, whereas in the second a structure also exists but is less marked.