Application of seasonal time series analysis to forecasting and early warning of epidemics of smear-positive tuberculosis in Xinjiang region
ZHANG Wei-wen1, HE Xiang-yan2, AIKEBAIER·Gulinazhaer1, CAO Ming-qin1
1. School of Public Health, Xinjiang Medical University, Xinjiang, Urumqi 830011, China; 2. Xinjiang Uygur Municipal People’s Hospital, Xinjiang, Urumqi 830001, China
Abstract：Objective To explore the application of seasonal autoregressive integrated moving average (SARIMA) model in the prediction and early warning of epidemics of smear-positive tuberculosis in Xinjiang. Methods The monthly incidence of smear-positive tuberculosis in Xinjiang from January 2005 to June 2015 was collected to establish a time series analysis model. The monthly incidence from July to December in 2015 was predicted and compared with the actual incidence in the same period. Results The monthly incidence of smear-positive tuberculosis in Xinjiang showed obvious seasonal variations, and the incidence peaked in March and November. Hypothesis test result showed that the regression coefficient of the SARIMA (0,1,1)(0,1,1)12 model parameters was P<0.001, and the model had a good fitting effect for actual monthly incidence. The mean absolute percentage error (MAPE) was 7.985%. Conclusions The SARIMA model demonstrates goodness-of-fit in forecasting the changing trend of epidemics of smear-positive tuberculosis in Xinjiang, which provides references for early warning and prevention of tuberculosis epidemics.
张伟文, 贺湘焱, 古丽娜扎尔·艾克拜尔, 曹明芹. 季节时间序列分析在新疆地区涂阳结核疫情预测预警中的应用[J]. 实用预防医学, 2019, 26(1): 26-29.
ZHANG Wei-wen, HE Xiang-yan, AIKEBAIER·Gulinazhaer, CAO Ming-qin. Application of seasonal time series analysis to forecasting and early warning of epidemics of smear-positive tuberculosis in Xinjiang region. , 2019, 26(1): 26-29.
2019, Vol. 26 
