129 / 2019-11-05 01:02:41

Spatial and temporal trends of malaria in China: 1950-2015

Malaria; Incidence; Time series; Autoregressive integrated moving average (ARIMA); Exponential smoothing model; Spatial analysis

PPurpose: Malaria is one of the most important public health problems worldwide. The aim of this study is to analyze the spatial-temporal trend and the spatial autocorrelation of the malaria incidence in China from 1950 to 2015, so as to provide scientific basis for the prevention and control of malaria.
Methods: The national malaria data in China during 1950-2015 were obtained from the Public Health Data Centre of the National Data Sharing Service Platform on Population and Health Science. We described the temporal trends of the malaria incidence in China from 1950 to 2015. ARIMA models and Exponential Smoothing models were built and evaluated by indexes like MAE, MAPE, MSE, SSE. The best model was conducted to predict the incidence of malaria in China from 2016 to 2018. Based on the malaria cases from 2006 to 2015 from 31 provinces across the country, spatial trend of the malaria cases was described with the help of MapInfo software. And based on the malaria incidence of each province from 2006 to 2015, the global spatial autocorrelation Moran's I analysis, local Moran's I spatial analysis and Getis's G hotspot analysis were carried out, respectively, with the help of Geoda software.
Result: The overall incidence of malaria in China showed a downward trend from 1950 to 2015. The best model is ARIMA (1,0,0)(1,1,0)12 model. The result of time trend analysis presented that the monthly incidence of malaria in the next three years is on the downward trend. The result of spatial analysis indicated that the provinces with high number of malarial incidence were gradually reduced from Yunnan, Hainan, Sichuan, Guizhou, Anhui and Jiangsu provinces to three provinces of Yunnan, Guangxi and Guizhou. The result of the global Moran’s I analysis showed that there was a positive spatial correlation in 2012, 2013, and 2015. The result of the local Moran’s I analysis showed that the high aggregation area is mainly in the south, and the low aggregation area is mainly in the northeast. Hot spot analysis shows that the hotspots of malaria incidence mainly clustered in Yunnan, Guizhou and Guangxi in recent years.
Conclusion: The overall incidence of malaria in China showed a downward trend. At present, malaria transmission has been effectively controlled in the country. The current key epidemic provinces were Yunnan, Guangxi, Guizhou and Jiangsu. However, it is still necessary to strengthen the monitoring and management of key provinces and consolidate the elimination of malaria.