Waterborne virus transport and the associated risks in a large lake.

ABSTRACT

Waterborne enteric viruses in lakes, especially at recreational water sites, may have a negative impact on human health. However, their fate and transport in lakes are poorly understood. In this study, we propose a coupled water quality and quantitative microbial risk assessment (QMRA) model to study the transport, fate and infection risk of four common waterborne viruses (adenovirus, enterovirus, norovirus and rotavirus), using Lake Geneva as a study site. The measured virus load in raw sewage entering the lake was used as the source term in the water quality simulations for a hypothetical scenario of discharging raw wastewater at the lake surface. After discharge into the lake, virus inactivation was modeled as a function of water temperature and solar irradiance that varied both spatially and temporally during transport throughout the lake. Finally, the probability of infection, while swimming at a popular beach, was quantified and compared among the four viruses. Norovirus was found to be the most abundant virus that causes an infection probability that is at least 10 times greater than the other viruses studied. Furthermore, environmental inactivation was found to be an essential determinant in the infection risks posed by viruses to recreational water users. We determined that infection risks by enterovirus and rotavirus could be up to 1000 times lower when virus inactivation by environmental stressors was accounted for compared with the scenarios considering hydrodynamic transport only. Finally, the model highlighted the role of the wind field in conveying the contamination plume and hence in determining infection probability. Our simulations revealed that for beaches located west of the sewage discharge, the infection probability under eastward wind was 43% lower than that under westward wind conditions. This study highlights the potential of combining water quality simulation and virus-specific risk assessment for a safe water resources usage and management.