Using the kinematic‐wave overland flow equation and a fractional dispersion‐advection equation, a process‐oriented, physically‐based model is developed for overland solute transport. Two scenarios, one consisting of downslope and the other of upslope rainstorm movements, are considered for numerical computations. Under these conditions, the hydrograph displays a long‐tailed distribution due to the variation in flow velocity in both time and distance. The solute transport exhibits a complex behavior. Pollutographs are characterized by a steep rising limb, with a peak, and a long, stretched receding limb; whereas the solute concentration distributions feature a rapid receding limb followed by a long stretched rising limb. Downslope moving storms cause much higher peak in both hydrographs and pollutographs than do upslope moving storms. Both hydrographs and the pollutographs predicted by the fractional dispersion model are in good agreement with the data measured experimentally using a soil flume and a moving rainfall simulator.

Background: Oyster norovirus outbreaks often pose high risks to human health. However, little is known about environmental factors controlling the outbreaks, and little can be done to prevent the outbreaks because they are generally considered to be unpredictable. Objective: We sought to develop a mathematical model for predicting risks of oyster norovirus outbreaks using environmental predictors. Methods: We developed a novel probability-based Artificial Neural Network model, called NORF model, using 21 years of environmental and norovirus outbreak data collected from Louisiana oyster harvesting areas along the Gulf of Mexico coast, USA. The NORF model involves six input variables that were selected through stepwise regression analysis and sensitivity analysis. Results: We found that the model-based probability of norovirus outbreaks was most sensitive to gage height (the depth of water in an oyster bed) and water temperature, followed by wind, rainfall, and salinity, respectively. The NORF model predicted all historical oyster norovirus outbreaks from 1994 through 2014. Specifically, norovirus outbreaks occurred when the NORF model probability estimate was > 0.6, whereas no outbreaks occurred when the estimated probability was < 0.5. Outbreaks may also occur when the estimated probability is 0.5–0.6. Conclusions: Our findings require further confirmation, but they suggest that oyster norovirus outbreaks may be predictable using the NORF model. The ability to predict oyster norovirus outbreaks at their onset may make it possible to prevent or at least reduce the risk of norovirus outbreaks by closing potentially affected oyster beds. Citation: Wang J, Deng Z. 2016. Modeling and prediction of oyster norovirus outbreaks along Gulf of Mexico coast. Environ Health Perspect 124:627–633; http://dx.doi.org/10.1289/ehp.1509764

Norovirus is the most common cause of outbreaks of non-bacterial gastroenteritis in human. While the winter seasonality of norovirus outbreaks has been widely reported, the association between norovirus outbreak epidemics and environmental factors remains not fully understood. This literature review is intended to improve understanding of environmental factors governing norovirus outbreaks and how the factors affect norovirus transmission. To that end, a large number of studies (67) from countries around the world were critically reviewed and discussed. Results of the literature review show that temperature, humidity, and rainfall are the most important environmental variables governing the norovirus epidemic cycle. It was found that low temperature between −6.6 and 20 °C, relative humidity between 10 and 66 %, and rainfall from 1 day to 3 months before an outbreak are effective ranges of the environmental factors, which favor the prevalence of norovirus. Some other environmental factors might have an association with the cycle of norovirus epidemics. However, further investigations are needed to understand effects of the other factors on norovirus incidence. The findings of this literature review improve our understanding of the relationship between norovirus outbreaks and environmental factors and provide the direction for future research on norovirus outbreaks.