LAUSR

This paper presents an artificial intelligence-based approach to identifying environmental indicators of oyster norovirus outbreaks in coastal waters. It was found that oyster norovirus outbreaks are generally linked to the extreme combination of antecedent environmental conditions characterized by low water temperature, low solar radiation, low gage height, low salinity, strong wind, and heavy precipitation. Among the six environmental indicators, the most important three indicators, including water temperature, solar radiation and gage height, are capable of explaining 77.7% of model-predicted oyster norovirus outbreaks while the extremely low temperature alone may explain 37.2% of oyster norovirus outbreaks. It is, therefore, recommended that water temperature in oyster harvesting areas be monitored in the cold season and particularly the extremely low temperature during a low gage height be used as the primary indicator of oyster norovirus outbreaks. The findings are of profound significance to reducing the public health risk of norovirus outbreaks associated with consumption of oysters.