Predicting the transmission dynamics of novel coronavirus infection in Shanxi province after the implementation of the “Class B infectious disease Class B management” policy - Ma, Yifei; Xu, Shujun; Luo, Yuxin; Peng, Junlin; Guo, Jiaming; Dong, Ali; Xu, Zhibin; Li, Jiantao; Lei, Lijian; He, Lu; Wang, Tong; Yu, Hongmei; et al. (Frontiers in Public Health, 2023)
Background: China managed coronavirus disease 2019 (COVID-19) with measures against Class B infectious diseases, instead of Class A infectious diseases, in a major shift of its epidemic response policies. We aimed to generate robust information on the transmission dynamics of novel coronavirus infection in Shanxi, a province located in northern China, after the implementation of the ‘Class B infectious disease Class B management’ policy. Methods: We consolidated infection data in Shanxi Province from December 6, 2022 to January 14, 2023 through a network questionnaire survey and sentinel surveillance. A dynamics model of the SEIQHCVR was developed to track the infection curves and effective reproduction number (R_t). Results: Our model was effective in estimating the trends of novel coronavirus infection, with the coefficient of determination (R^2) above 90% in infections, inpatients, and critically ill patients. The number of infections in Shanxi Province as well as in urban and rural areas peaked on December 20, 2022, with the peak of inpatients and critically ill patients occurring two to three weeks after the peak of infections. By the end of January 2023, 87.72% of the Shanxi residents were predicted to be infected, and the outbreak subsequently subsided. A small wave of COVID-19 infections may re-emerge at the end of April. In less than a month, the R_t values of positive infections, inpatients and critically ill patients were all below 1.0. Conclusion: The outbreak in Shanxi Province is currently at a low prevalence level. In the face of possible future waves of infection, there is a strong need to strengthen surveillance and early warning.