Model of multiple seasonal autoregressive integrated moving average model and its application in prediction of the hand-foot-mouth disease incidence in Changsha
10.11817/j.issn.1672-7347.2014.11.011
- VernacularTitle:乘积季节自回归积分滑动平均模型在长沙市手足口病发病率预测中的应用
- Author:
Ting TAN
;
Lizhang CHEN
;
Fuqiang LIU
- Publication Type:Journal Article
- Keywords:
hand-foot-mouth disease;
time series;
multiple seasonal autoregressive integrated moving average model
- From:
Journal of Central South University(Medical Sciences)
2014;(11):1170-1176
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To establish multiple seasonal autoregressive integrated moving average model (ARIMA) according to the hand-foot-mouth disease incidence in Changsha, and to explore the feasibility of the multiple seasonal ARIMA in predicting the hand-foot-mouth disease incidence. Methods: EVIEWS 6.0 was used to establish multiple seasonal ARIMA according to the hand-foot-mouth disease incidence from May 2008 to August 2013 in Changsha, and the data of the hand-foot-mouth disease incidence from September 2013 to February 2014 were served as the examinedsamples of the multiple seasonal ARIMA, then the errors were compared between the forecasted incidence and the real value. Finally, the incidence of hand-foot-mouth disease from March 2014 to August 2014 was predicted by the model. Results: Atfer the data sequence was handled by smooth sequence, model identiifcation and model diagnosis, the multiple seasonal ARIMA (1, 0, 1)×(0, 1, 1)12 was established. The R2 value of the model iftting degree was 0.81, the root mean square prediction error was 8.29 and the mean absolute error was 5.83. Conclusion: hTe multiple seasonal ARIMA is a good prediction model, and the iftting degree is good. It can provide reference for the prevention and control work in hand-foot-mouth disease.
