Prediction of pulmonary tuberculosis incidence in Xinjiang based on seasonal ARIMA model
NIE Yan-wu1, ZHENG Yan-ling2, SUN Ya-hong1, YANG Lei3, ZHANG Li-ping2
1. State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, School of Public Health, Xinjiang Medical University, Urumqi, Xinjiang 830011, China; 2. School of Medical Engineering and Technology, Xinjiang Medical University, Xinjiang, Urumqi 830011,China; 3. School of Nursing, Xinjiang Medical University, Xinjiang, Urumqi 830011,China
Abstract：Objective To explore the application of seasonal autoregressive integrated moving average (ARIMA) model to prediction of pulmonary tuberculosis incidence in Xinjiang, and to verify the feasibility and applicability of the model. Methods Seasonal ARIMA (p, d, q )(P, D, Q)s was used to fit the monthly incidence of pulmonary tuberculosis in Xinjiang from January 2005 to August 2019. Multiple seasonal time series models were established and compared to select the optimal model to predict the incidence of pulmonary tuberculosis from September to December 2019. Results From January 2005 to August 2019, the cumulative incidence of pulmonary tuberculosis in Xinjiang was 627,869 cases, with an average annual incidence of 3,567 cases. The monthly incidence of pulmonary tuberculosis in Xinjiang showed a seasonal pattern. The average incidence from January to May was higher than the average level, while the average incidence from June to December was lower than the average level. The incidence peak was in January and March, whereas the incidence was found to be lower in September. According to the minimum principle of Akaike Information Criterion and Bayesian Information Criterion, ARIMA (1, 1, 1 ) (0, 1, 2)12 was the optimal model, the residual sequence was white noise. The regression coefficients of parameters were statistically significant, and the average absolute percentage error of fitting was 8.723%. The predicted mean absolute percentage error was 18.674%, and the real values were within the 95% confidence interval of the predicted values. Conclusion ARIMA (1, 1, 1) (0, 1, 2)12 model can better fit the incidence data of pulmonary tuberculosis in Xinjiang and make short-term prediction, which has a certain guiding significance for the formulation of health prevention and control measures in Xinjiang.
2021, Vol. 28 
