This study aimed to investigate the impact of small tributaries on seawater and shellfish quality in coastal area subjected to brief episodes leading to fecal contamination. Escherichia coli and F-RNA-specific bacteriophages were selected as fecal indicators and astroviruses were chosen as being representative of pathogens in the human population during winter viral epidemics. A two-dimensional hydrodynamic model was built to simulate the current and dispersion in the model domain, which includes areas uncovered at low tide. The model also includes decay rates to simulate microorganism behavior and assess the influence of fecal input on shellfish quality. The originality lies in the fact that specific features of the study area were considered. Modeling results indicate limited particle movements and long flushing times at the back of the bay, where shellfish are farmed. Computational results showed that under normal conditions, i.e. 94% of the time, when rainfall was less than 10 mm per day, the sector shows acceptable water quality. These results are in agreement with shellfish concentration measured in the field. Under high flow conditions, high concentrations of fecal indicators and astrovirus were measured in the river and tributaries. The corresponding fluxes were over 50 times higher than under normal weather conditions. The location of the shellfish beds near the coast makes them vulnerable and fecal indicators and viruses were detected in shellfish after short rainfall events. Our modeling approach makes a contribution to shellfish management and consumer protection, by indicating the "risk period" as defined by EU regulations. Molecular development such as viral quantification in conjunction with model developments will help to prevent shellfish contamination and thus provide safer products to consumers and an effective tool for shellfish producers.

A production area repeatedly implicated in oyster-related gastroenteritis in France was studied for several months over 2 years. Outbreaks and field samples were analyzed by undertaking triplicate extractions, followed by norovirus (NoV) detection using triplicate wells for genomic amplification. This approach allowed us to demonstrate that some variabilities can be observed for samples with a low level of contamination, but most samples analyzed gave reproducible results. At the first outbreak, implicated oysters were collected at the beginning of the contamination event, which was reflected by the higher NoV levels during the first month of the study. During the second year, NoV concentrations in samples implicated in outbreaks and collected from the production area were similar, confirming the failure of the shellfish depuration process. Contamination was detected mainly during winter-spring months, and a high prevalence of NoV GI contamination was observed. A half-life of 18 days was calculated from NoV concentrations detected in oysters during this study, showing a very slow decrease of the contamination in the production area. Preventing the contamination of coastal waters should be a priority.

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A sentinel network, Obépine, has been designed to monitor SARS-CoV-2 viral load in wastewaters arriving at wastewater treatment plants (WWTPs) in France as an indirect macro-epidemiological parameter. The sources of uncertainty in such a monitoring system are numerous, and the concentration measurements it provides are left-censored and contain outliers, which biases the results of usual smoothing methods. Hence, the need for an adapted pre-processing in order to evaluate the real daily amount of viruses arriving at each WWTP. We propose a method based on an auto-regressive model adapted to censored data with outliers. Inference and prediction are produced via a discretized smoother which makes it a very flexible tool. This method is both validated on simulations and real data from Obépine. The resulting smoothed signal shows a good correlation with other epidemiological indicators and is currently used by Obépine to provide an estimate of virus circulation over the watersheds corresponding to about 200 WWTPs.