Application of the time series model in prediction of incidence of hand-foot-mouth disease from 2008 to 2016 in China
10.16462/j.cnki.zhjbkz.2019.11.019
- Author:
Yu-yang XIONG
1
;
Jing-chao REN
;
Guang-cai DUAN
Author Information
1. School of Public Health of Xinxiang Medical University, Xinxiang 453003, China
- Publication Type:Research Article
- Keywords:
HFMD;
ARIMA;
Prediction
- From:
Chinese Journal of Disease Control & Prevention
2019;23(11):1394-1398
- CountryChina
- Language:Chinese
-
Abstract:
Objective To predict the monthly incidence of hand-foot-mouth disease (HFMD) in China by using autoregressive integrated moving average (ARIMA) model and provide evidence for prevention and control of HFMD. Methods The monthly incidence data of HFMD in China from 2008 to 2016 were collected from the Public Health Science data Center. The incidence database was established by Excel 2007 and graphed. SAS 9.1 was used to construct the ARIMA model, based on the data of the monthly reported incidence of HFMD in China from January 2008 to December 2015, and then the data in 2016 were used to verify the predicted results. The monthly incidence in 2017 was predicted in the same way.The difference was statistically significant when P<0.05. Result The model predicting monthly incidence of HFMD in China is ARIMA ((12), 2, 0) sparse coefficient and residuals is white noise. The parameters were as follows: moted mean squared error=3.6490, mean absolute error=2.62, mean absolute percentage error=28.24%. Conclusion The sparse coefficient model could well simulate the trend of HFMD case in time series, which has good reference of early warning and prevention of HFMD.
