Zha Wenting, Ni Han, He Yuxi, Kuang Wentao, Zhao Jin, Fu Liuyi, Dai Haoyun, Lv Yuan, Zhou Nan, Yang Xuewen
Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, Changsha, Hunan, People's Republic of China.
Changsha Center for Disease Control and Prevention, Changsha, People's Republic of China.
Hum Vaccin Immunother. 2024 Dec 31;20(1):2338953. doi: 10.1080/21645515.2024.2338953. Epub 2024 Apr 24.
This study aims to examine the development trend of COVID-19 in China and propose a model to assess the impacts of various prevention and control measures in combating the COVID-19 pandemic. Using COVID-19 cases reported by the National Health Commission of China from January 2, 2020, to January 2, 2022, we established a Susceptible-Exposed-Infected-Asymptomatic-Quarantined-Vaccinated-Hospitalized-Removed (SEIAQVHR) model to calculate the COVID-19 transmission rate and R effective reproduction number, and assess prevention and control measures. Additionally, we built a stochastic model to explore the development of the COVID-19 epidemic. We modeled the incidence trends in five outbreaks between 2020 and 2022. Some important features of the COVID-19 epidemic are mirrored in the estimates based on our SEIAQVHR model. Our model indicates that an infected index case entering the community has a 50%-60% chance to cause a COVID-19 outbreak. Wearing masks and getting vaccinated were the most effective measures among all the prevention and control measures. Specifically targeting asymptomatic individuals had no significant impact on the spread of COVID-19. By adjusting prevention and control parameters, we suggest that increasing the rates of effective vaccination and mask-wearing can significantly reduce COVID-19 cases in China. Our stochastic model analysis provides a useful tool for understanding the COVID-19 epidemic in China.
本研究旨在考察中国新冠肺炎的发展趋势,并提出一个模型来评估各项防控措施在抗击新冠肺炎疫情中的影响。利用中国国家卫生健康委员会于2020年1月2日至2022年1月2日报告的新冠肺炎病例,我们建立了一个易感-暴露-感染-无症状-隔离-接种疫苗-住院-移除(SEIAQVHR)模型,以计算新冠肺炎传播率和有效再生数R,并评估防控措施。此外,我们构建了一个随机模型来探索新冠肺炎疫情的发展情况。我们对2020年至2022年期间五次疫情的发病趋势进行了建模。基于我们的SEIAQVHR模型的估计反映了新冠肺炎疫情的一些重要特征。我们的模型表明,一个感染的初始病例进入社区后,有50%-60%的几率引发新冠肺炎疫情爆发。在所有防控措施中,佩戴口罩和接种疫苗是最有效的措施。专门针对无症状个体对新冠肺炎的传播没有显著影响。通过调整防控参数,我们建议提高有效接种率和口罩佩戴率可以显著减少中国的新冠肺炎病例。我们的随机模型分析为了解中国的新冠肺炎疫情提供了一个有用的工具。