State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China.
University of Chinese Academy of Sciences, Beijing, China.
Int J Public Health. 2022 Nov 3;67:1605177. doi: 10.3389/ijph.2022.1605177. eCollection 2022.
Waves of epidemics associated with Omicron variant of Coronavirus Disease 2019 (COVID-19) in major cities in China this year have been controlled. It is of great importance to study the transmission characteristics of these cases to support further interventions. We simulate the transmission trajectory and analyze the intervention influences of waves associated with Omicron variant in major cities in China using the Suspected-Exposed-Infectious-Removed (SEIR) model. In addition, we propose a model using a function between the maximum daily infections and the duration of the epidemic, calibrated with data from Chinese cities. An infection period of 5 days and basic reproduction number R between 2 and 8.72 are most appropriate for most cases in China. Control measures show a significant impact on reducing R, and the earlier control measures are implemented, the shorter the epidemic will last. Our proposed model performs well in predicting the duration of the epidemic with an average error of 2.49 days. Our results show great potential in epidemic model simulation and predicting the end date of the Omicron epidemic effectively and efficiently.
今年中国主要城市与 2019 年冠状病毒病（COVID-19）Omicron 变异株相关的疫情波已得到控制。研究这些病例的传播特征对于支持进一步干预措施非常重要。我们使用疑似暴露感染清除（SEIR）模型模拟了与中国主要城市 Omicron 变异株相关的波的传播轨迹，并分析了干预措施的影响。此外，我们提出了一个使用最大日感染量和疫情持续时间之间的函数的模型，并使用中国城市的数据进行了校准。感染期为 5 天，基本繁殖数 R 在 2 和 8.72 之间，最适合中国大多数病例。控制措施对降低 R 有显著影响，控制措施越早实施，疫情持续时间越短。我们提出的模型在预测疫情持续时间方面表现良好，平均误差为 2.49 天。我们的结果表明，该模型在模拟传染病和有效预测 Omicron 疫情结束日期方面具有很大的潜力。
