UCLA

Mumps has been long gone from public attention due to developing vaccine programs. In recent year, however, there are random outbreaks of mumps in US, all of which are strongly associated with college campus settings. It is necessary to find out and develop a statistical model with strong forecasting ability to help avoid massive contagion and help surveillance of this epidemic disease in the future. Pennsylvania mumps data is collected from Project Tycho to fit both the point process and SEIR models. Different methods of model evaluation are applied to help determine which one is the best performed. All three methods show quite similarity, but the Recursive model outweighs all others slightly. It is chosen to perform an 75% training vs 25% testing forecasting to see if it is able to catch the dispersal trend of mumps in Pennsylvania. Although the Recursive model predicts well in general, the whole comparison process shed some insights about what could be further done to evaluate and utilize various models.