title: Predicting the dynamics of norovirus infection using time series models
abstract: Introduction. Norovirus infection (NI) is the most prevalent cause of acute gastroenteritis and outbreaks in semi-closed settings. Forecasting of NI may improve situational awareness and control measures. The aim of the study is to evaluate accuracy of time-series models for forecasting of norovirus incidence (on Sverdlovsk region dataset). Materials and methods. Simple ARIMA time-series models was chosen to forecast NI incidence via regression on its own lagged values. Dataset including passive
journal: Ural Medical Journal