Prediction of hand-foot-mouth disease epidemic with seasonal autoregressive integrated moving average model

Objective To describe the prevalence and incidence trend of hand-foot-mouth disease (HFMD) using time series method and to establish a seasonal autoregressive integrated moving average (SARIMA) model for the prediction of HFMD epidemic from July 2017 to December 2018 in Liaoning province.Methods A prediction model was set up based on reported monthly data of HFMD from January 2012 through 2016 in Liaoning province using Excel and SPSS 23.0 software.Then the model was used to predict monthly incidents of HFMD from July 2017 to December 2018 and the prediction efficiency was evaluated.Results Yearly cycle and 12-month seasonal period of HFMD epidemic were observed.There was an incidence peak for HFMD epidemic from June to September during a year in Liaoning pro-vince.The established optimum model was SARIMA(0,1,0)×(1,1,0)₁₂.The Ljung-Box Q statistics is 18.564(P=0.354).The noise of residual series of the ARIMA model was white noise and the mean error was 0.229.Conclusion The established seasonal ARIMA model could well fit the monthly data of HFMD epidemic in Liaoning province and the model could be applied to predict short-term incident trend of HFMD in the province.