Jean-Baptiste Denis

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A pragmatic quantitative risk assessment (QRA) of the risks of waterborne Cryptosporidium parvum infection and cryptosporidiosis in immunocompetent and immunodeficient French populations is proposed. The model takes into account French specificities such as the French technique for oocyst enumeration performance and tap water consumption. The proportion of(More)
Noroviruses (NoVs) are the major cause of acute epidemic gastroenteritis in industrialized countries. Outbreak strains are predominantly genogroup II (GII) NoV, but genogroup I (GI) strains are regularly found in oyster related outbreaks. The prototype Norwalk virus (GI), has been shown to have high infectivity in a human challenge study. Whether other NoVs(More)
A novel approach to the quantitative assessment of food-borne risks is proposed. The basic idea is to use Bayesian techniques in two distinct steps: first by constructing a stochastic core model via a Bayesian network based on expert knowledge, and second, using the data available to improve this knowledge. Unlike the Monte Carlo simulation approach as(More)
The uncertainty associated with estimates should be taken into account in quantitative risk assessment. Each input's 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(More)
Q fever is a worldwide zoonosis caused by Coxiella burnetii. Although ruminants are recognized as the most important source of human infection, no previous studies have focused on assessing the characteristics of the bacterial spread within a cattle herd and no epidemic model has been proposed in this context. We assess the key epidemiological parameters(More)
A quantitative assessment of the exposure to Listeria monocytogenes from cold-smoked salmon (CSS) consumption in France is developed. The general framework is a second-order (or two-dimensional) Monte Carlo simulation, which characterizes the uncertainty and variability of the exposure estimate. The model takes into account the competitive bacterial growth(More)
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(More)
Stakeholders making decisions in public health and world trade need improved estimations of the burden-of-illness of foodborne infectious diseases. In this article, we propose a Bayesian meta-analysis or more precisely a Bayesian evidence synthesis to assess the burden-of-illness of campylobacteriosis in France. Using this case study, we investigate(More)
This article presents a Listeria monocytogenes growth model in milk at the farm bulk tank stage. The main objective was to judge the feasibility and value to risk assessors of introducing a complex model, including a complete thermal model, within a microbial quantitative risk assessment scheme. Predictive microbiology models are used under varying(More)
The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As(More)