Spatio-temporal analysis and short-term prediction of the incidence of dysentery in China
10.16462/j.cnki.zhjbkz.2019.08.005
- Author:
Meng-yuan ZHANG
1
;
Yuan LV
;
Tao-cheng LIU
;
Shang-hui YI
;
Wen-ting ZHA
Author Information
1. Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, Changsha 410013,China
- Publication Type:Research Article
- Keywords:
Dysentery;
Hierarchical map;
Spatial correlation;
ARIMA model
- From:
Chinese Journal of Disease Control & Prevention
2019;23(8):904-910
- CountryChina
- Language:Chinese
-
Abstract:
Objective The aim is to analyze the spatial-temporal correlation of dysentery incidence in 31 provinces, municipalities and autonomous regions in China from 2004 to 2016, and to predict the short-term incidence of dysentery in China. Methods Data about the incidence of dysentery from 2004 to 2016 was collected. Arcgis and Geoda were used to create visualized grading maps and analyze spatial correlation. The auto-regressive integrated moving average model (ARIMA)was used to predict the incidence of dysentery in 2017 and evaluate the prediction accuracy of the model. Results The incidence of dysentery in China declined with each passing year from 2004 to 2016. The incidence of dysentery in the western region was significantly higher than the eastern region, except high incidence rate in Beijing and Tianjin. There was no significantly global correlation in the incidence rate, but there was local aggregation. Qinghai had turned from high-level aggregation to low-level accumulation. Inner Mongolia and Shanxi had changed from no local aggregation to low-high accumulation. Shaanxi has long been high-high, and the southeast coastal areas had been low-low accumulation for a long time. The optimal model ARIMA (1,0,0) (2,1,1)12 was established to predict the incidence of dysentery, and the prediction results were roughly consistent with the observations. Conclusion The incidence of dysentery from 2004 to 2016 is not spatially mobile but clustered. The incidence of dysentery in Beijing, Tianjin, Shaanxi and most of the western regions is severe. The ARIMA model is suitable for forecasting the incidence of short-term dysentery. And our analysis may help prevent and control the incidence of dysentery in China.
