Author(s)

Wenbohao Zhu, Xiaofeng Li, and Bo Sun

Corresponding Author

Bo Sun

Abstract

Abstract: In order to analyse and predict the short-term trend of China's 2019 Novel Coronavirus (2019-nCoV/ COVID-19) epidemic, the study uses historical statistical data of China’s COVID-19 cases between December 1, 2019 and July 31, 2020. Based on the characteristics and trends of its time series, a differential integrated moving autoregressive average model (ARIMA) is established and used with STATA 16.0. This model detects and predicts the future short-term data of China's COVID-19 epidemic situation. In the first half of Augusts, the maximum number of newly confirmed cases in China should be 319 and the minimum should be 199. There will be no erratic fluctuation or sudden large increases in the number of new infected individuals or accumulative confirmed cases. The research proves that, the prevention and control measures of China's COVID-19 epidemic by the Chinese government are effective, epidemic has been gradually controlled and defence against disease has entered normalization. The analysis and prediction on China's COVID-19 epidemic based on the ARIMA model can help China better respond to the outbreak of COVID-19 epidemic in the short term and provides decision-making suggestions for control of the disease in short term.

Keywords

Keywords: ARIMA Model; China's Novel Coronavirus (2019-nCoV) Epidemic; Prediction