School of Public Health, Shanxi Medical University, Taiyuan, China.
Shanxi Center for Disease Control and Prevention, Taiyuan, China.
Front Public Health. 2023 Dec 22;11:1322430. doi: 10.3389/fpubh.2023.1322430. eCollection 2023.
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.
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 ().
Our model was effective in estimating the trends of novel coronavirus infection, with the coefficient of determination () 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 2 to 3 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 values of positive infections, inpatients and critically ill patients were all below 1.0.
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.
中国在应对 2019 年冠状病毒病(COVID-19)时,将传染病防控策略从“乙类甲管”调整为“乙类乙管”,这是重大的政策转变。我们旨在提供山西省新型冠状病毒感染传播动力学的有力信息,该省位于中国北方,在实施“乙类传染病乙类管理”政策后。
我们通过网络问卷调查和哨点监测,整合了山西省 2022 年 12 月 6 日至 2023 年 1 月 14 日的感染数据。我们开发了 SEIQHCVR 的动力学模型来跟踪感染曲线和有效繁殖数()。
我们的模型在估计新型冠状病毒感染趋势方面非常有效,感染、住院和重症患者的决定系数()均高于 90%。山西省以及城乡地区的感染人数于 2022 年 12 月 20 日达到峰值,住院和重症患者的峰值比感染峰值晚 2 至 3 周。到 2023 年 1 月底,预计山西省 87.72%的居民已被感染,疫情随后得到缓解。4 月底可能会出现 COVID-19 感染的小高峰。在不到一个月的时间里,阳性感染、住院和重症患者的 值均低于 1.0。
山西省疫情目前处于低流行水平。面对可能出现的未来感染波次,有必要加强监测和预警。