Modeling the Transmission of Vibrio aestuarianus in Pacific Oysters Using Experimental Infection Data

Abstract

Vibrio aestuarianus is a bacterium related to mortality outbreaks in Pacific oysters, Crassostrea gigas , in France, Ireland, and Scotland since 2011. Knowledge about its transmission dynamics is still lacking, impairing guidance to prevent and control the related disease spread. Mathematical modeling is a relevant approach to better understand the determinants of a disease and predict its dynamics in imperfectly observed pathosystems. We developed here the first marine epidemiological model to estimate the key parameters of V. aestuarianus infection at a local scale in a small and closed oyster population under controlled laboratory conditions. Using a compartmental model accounting for free-living bacteria in seawater, we predicted the infection dynamics using dedicated and model-driven collected laboratory experimental transmission data. We estimated parameters and showed that waterborne transmission of V. aestuarianus is possible under experimental conditions, with a basic reproduction number R 0 of 2.88 (95% CI: 1.86; 3.35), and a generation time of 5.5 days. Our results highlighted a bacterial dose–dependent transmission of vibriosis at local scale. Global sensitivity analyses indicated that the bacteria shedding rate, the concentration of bacteria in seawater that yields a 50% chance of catching the infection, and the initial bacterial exposure dose W 0 were three critical parameters explaining most of the variation in the selected model outputs related to disease spread, i.e., R 0 , the maximum prevalence, oyster survival curve, and bacteria concentration in seawater. Prevention and control should target the exposure of oysters to bacterial concentration in seawater. This combined laboratory–modeling approach enabled us to maximize the use of information obtained through experiments. The identified key epidemiological parameters should be better refined by further dedicated laboratory experiments. These results revealed the importance of multidisciplinary approaches to gain consistent insights into the marine epidemiology of oyster diseases.

Spatial epidemiological modelling of infection by Vibrio aestuarianus shows that connectivity and temperature control oyster mortality

“…We used a previously validated compartmental epidemiological model to account for the local infection dynamics at the small and homogeneous oyster population level (Lupo et al 2019), i.e. within a patch.…”

“…Dedicated experimental trials were designed to measure the epidemiological parameter values at different seawater temperatures, as previously described by Lupo et al (2019) (Text S1 in the Supplement at www. int-res.…”

“…In particular, a longitudinal field study identified environmental risk factors of mortality in adult sentinel oysters (Gangnery et al 2019) in an estuarine ecosystem located in the Baie des Veys, Normandy, where adult oyster mortalities due to V. aestuarianus are regularly reported (Garcia et al 2014). In parallel, the transmission of V. aestuarianus was modelled to identify and estimate the key parameters of the infection in a small and closed oyster population under controlled laboratory conditions (Travers et al 2017, Lupo et al 2019. The experimental local-scale model enabled the mimicking of the oyster intra-population transmission of V. aestuarianus in a tank with homogeneous environmental conditions for 2 wk (Lupo et al 2019).…”

“…In parallel, the transmission of V. aestuarianus was modelled to identify and estimate the key parameters of the infection in a small and closed oyster population under controlled laboratory conditions (Travers et al 2017, Lupo et al 2019. The experimental local-scale model enabled the mimicking of the oyster intra-population transmission of V. aestuarianus in a tank with homogeneous environmental conditions for 2 wk (Lupo et al 2019).…”

“…The longitudinal field study conducted in Baie des Veys (Gangnery et al 2019) was not designed for model validation, but allowed the comparison of predicted versus ob served oyster mortality patterns and related putative risk factors. Therefore, we developed our model by utilising previous studies developed as part of the GIGASSAT project regarding adult oyster mortality (Gangnery et al 2019, Lupo et al 2019. Our objective was to simulate the spatio-temporal dynamics of Pacific oyster mortality due to V. aestuarianus infection using a spatialised epidemiological model to rank the processes involved in the related disease spread in oyster populations at a bay scale.…”