Application of the ARIMA Model in Forecasting the Incidence of Tuberculosis in Anhui During COVID-19 Pandemic from 2021 to 2022

Shuangshuang Chen,1,* Xinqiang Wang,2,* Jiawen Zhao,2 Yongzhong Zhang,3 Xiaohong Kan1,2 1Department of Scientific Research and Education, Anhui Chest Hospital (Anhui Provincial Tuberculosis Institute), Hefei, People’s Republic of China; 2Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, People’s Republic of China; 3Department of Tuberculosis Prevent and Control, Anhui Provincial Tuberculosis Institute, Hefei, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiaohong Kan, Department of Scientific Research and Education, Anhui Chest Hospital (Anhui Provincial Tuberculosis Institute), Hefei, 230022, People’s Republic of China, Tel +86 0551-63615340, Email kanxiaohong@ahmu.edu.cnObjective: Forecasting the seasonality and trend of pulmonary tuberculosis is important for the rational allocation of health resources. In this study, we predict the incidence of pulmonary tuberculosis by establishing the autoregressive integrated moving average (ARIMA) model and providing support for pulmonary tuberculosis prevention and control during COVID-19 pandemic.Methods: Registered tuberculosis(TB) cases from January 2013 to December 2020 in Anhui province were analysed using traditional descriptive epidemiological methods. Then we used the monthly incidence rate of TB from January 2013 through June 2020 to construct ARIMA model, and used the incidence rate from July 2020 to December 2020 to evaluate the forecasting accuracy. Ljung Box test, Akaike’s information criterion(AICc), Bayesian information criterion(BIC) and Realtive error were used to evaluate the model fitting and forecasting effect, Finally, the optimal model was used to forecast the expected monthly incidence of tuberculosis for 2021 and 2022 to learn about the incidence trend.Results: A total of 255,656 TB cases were registered. The reported rate of tuberculosis was highest in 2013 and lowest in