Numerical simulation of the fate, transport and public health risks of enteric viruses in Lake Geneva

Lakes are a fundamental feature of nature with brilliance, profoundness and complexity. Various of physical, chemical and biological changes take place three dimensionally in deep lakes, regulated by complicated boundary conditions. To understand and predict such aquatic systems is not an easy task, but scientists have endeavored to accomplish it by field measurements and numerical simulations, focusing on hydrodynamics, water quality and ecology. Although important to the aquatic system and human health, pathogen dynamics in lakes has not been addressed with priority in most studies about lakes, with even less attention for pathogenic virus in general, or specific virus genera or strains. In this study, we propose a coupled 3D hydrodynamic and particle tracking model, to study the fate and transport of the Enterovirus genus with twelve specific strains, followed by a Quantitative Microbial Risk Assessment model to estimate the risk of infection and illness for humans when interacting with lake water in many forms. Lake Geneva is chosen as the study site, as it is the biggest fresh water lake in Western Europe and used as a drinking water source for more than 800,000 people and a recreational site for habitants around it. The hydrodynamic simulation of the lake is validated by field measurement at observation platforms while the particle tracking module is validated by satellite images processed for water quality parameters. Decay of enterovirus is incorporated in the postprocessing part of the model, supported by previous researches in the literature and experiments in the laboratory, considering temperature, solar radiation and microbial activity as the major environmental stressors for enterovirus. Finally, the modeled concentration of enterovirus is employed as an input for a QMRA model to assess the risk of infection and illness to human beings that are exposed to this specific virus genus. Future environmental changes will definitely influence the fate and persistence of the virus and will also be simulated by the proposed model. The perspective of this research is to generate a robust tool to predict virus dynamics in deep lakes and investigate the potential risk concerning human interaction with the contaminated lake water. It is a novel endeavor in water quality modeling and will support decision makers to draw conclusions regarding safe usage of lake water resources.