Application of Time Series Method to Prediction of Bacillary Dysentery Incidence Rate

Objective:To predict Bacillary Dysentery incidence rate through application of time series method.Methods:To establish a model of seasonal autoregressive integrated moving average ARIMA(p,d,q)(P,D,Q)s based on monthly incidence rate from 2001 to 2007 of Bacillary Dysentery,and to predict the monthly incidence rate of Bacillary Dysentery in 2008.SPSS11.5 softwares was used to perform the above statistical analyses.Results:The model of ARIMA(1,0,0)×(1,1,0)12 was established.The results showed that trend of incidences rate in 2008 estimated by the model was consistent with the actual values.The 95% confidence interval contained all of the actual values,the average of absolute error was 13.02% in 2008,and that was only 4.91% from January to June.Conclusions:The model of ARIMA can be used to forecast incidence rate of Bacillary Dysentery and it might have a high prediction precision for short-term time series.It could be provide scientific evidence for Bacillary Dysentery control and prevention.