The Use of an Autoregressive Integrated Moving Average Model for Prediction of the Incidence of Dysentery in Jiangsu, China.
The aim of this study is to forecast the incidence of bacillary dysentery with a prediction model. We collected the annual and monthly laboratory data of confirmed cases from January 2004 to December 2014. In this study, we applied an autoregressive integrated moving average (ARIMA) model to forecast bacillary dysentery incidence in Jiangsu, China. The ARIMA (1, 1, 1) × (1, 1, 2)12 model fitted exactly with the number of cases during January 2004 to December 2014. The fitted model was then used to predict bacillary dysentery incidence during the period January to August 2015, and the number of cases fell within the model's CI for the predicted number of cases during January-August 2015. This study shows that the ARIMA model fits the fluctuations in bacillary dysentery frequency, and it can be used for future forecasting when applied to bacillary dysentery prevention and control.
Jiangnan University, Wuxi, Jiangsu, China.
Kewei
K
Wang
Nanchang Center for Disease Control and Prevention, Jiangxi, China.
Wentao
W
Song
Jiangnan University, Wuxi, Jiangsu, China.
Jinping
J
Li
Helie Street Community Health Service Center, Wuxi, Jiangsu, China.
Wu
W
Lu
Lihu Street Community Health Service Center, Wuxi, Jiangsu, China.
Jiangang
J
Yu
Jiangnan University, Wuxi, Jiangsu, China jdhxf168@163.com.
Xiaofeng
X
Han
D002681:China / Q000453:epidemiology; D004405:Dysentery, Bacillary / Q000453:epidemiology*; D005544:Forecasting; D006801:Humans; D015994:Incidence; D015233:Models, Statistical
ARIMA; bacillary dysentery; incidence; model; prediction