Application of ARIMA model in predicting the incidence of tuberculosis in China from 2018 to 2019

• Published in: Zhōnghuá liúxíngbìng zázhì Vol. 40; no. 6; p. 633
• Main Authors: Yan, C Q, Wang, R B, Liu, H C, Jiang, Y, Li, M C, Yin, S P, Xiao, T Y, Wan, K L, Rang, W Q
• Format: Journal Article
• Language: Chinese
• Published: China 10.06.2019
• Subjects: Autoregressive integrated moving average model; Prediction; Pulmonary tuberculosis
• ISSN: 0254-6450
• DOI: 10.3760/cma.j.issn.0254-6450.2019.06.006

Autoregressive integrated moving average (ARIMA) model was used to predict the incidence of tuberculosis in China from 2018 to 2019, providing references for the prevention and control of pulmonary tuberculosis. The monthly incidence data of tuberculosis in China were collected from January 2005 to December 2017. R 3.4.4 software was used to establish the ARIMA model, based on the monthly incidence data of tuberculosis from January 2005 to June 2017. Both predicted and actual data from July to December 2017 were compared to verify the effectiveness of this model, and the number of tuberculosis cases in 2018-2019 also predicted. From 2005 to 2017, a total of 13 022 675 cases of tuberculosis were reported, the number of pulmonary tuberculosis patients in 2017 was 33.68% lower than that in 2005, and the seasonal character was obvious, with the incidence in winter and spring was higher than that in other seasons. According to the incidence data from 2005 to 2017, we established the model of ARIMA (0,1,2)(0,1,0)(1