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中国大陆下一次新冠疫情大爆发的预测及其疫苗接种策略。

Prediction of the next major outbreak of COVID-19 in Mainland China and a vaccination strategy for it.

作者信息

Wu Yuanyuan, Zhou Weike, Tang Sanyi, Cheke Robert A, Wang Xia

机构信息

School of Mathematics and Statistics, Shaanxi Normal University, Xi'an 710119, People's Republic of China.

School of Mathematics, Northwest University, Xi'an 710127, People's Republic of China.

出版信息

R Soc Open Sci. 2023 Aug 30;10(8):230655. doi: 10.1098/rsos.230655. eCollection 2023 Aug.

Abstract

After the widespread prevalence of COVID-19 at the end of 2022 in Mainland China, a major concern is when will the second major outbreak occur and with what prevalence and fatality rates will it be associated with, as peoples' immunity from natural infection subsides. To address this, we established an age-structured model considering vaccine and infection-derived immunity, fitted an immunity-waning curve, and calibrated the model using the epidemic and vaccination data from Hong Kong in 2022. The model and the situation of the first major epidemic in Mainland China were then used to predict the prevalence rate, fatality rate and peak time of the second wave. In addition, the controlling effects of different vaccination strategies on the second major outbreak are discussed. Finally, a characterization indicator for the level of population immunity was provided. We conclude that if the prevalence of the first major epidemic was 80%, the prevalence rate of the second major outbreak would be about 37.64%, and the peak time would have been July 2 2023. Strengthening vaccination can effectively delay the peak of the second wave of the epidemic and reduce the prevalence.

摘要

2022年底新冠病毒在中国大陆广泛流行后,一个主要担忧是随着人们自然感染产生的免疫力消退,第二次大规模疫情何时会发生,以及其相关的流行率和死亡率会是多少。为解决这个问题,我们建立了一个考虑疫苗和感染获得性免疫的年龄结构模型,拟合了免疫衰减曲线,并利用香港2022年的疫情和疫苗接种数据对模型进行了校准。然后,利用该模型和中国大陆首次大规模疫情的情况来预测第二波疫情的流行率、死亡率和峰值时间。此外,还讨论了不同疫苗接种策略对第二次大规模疫情的控制效果。最后,提供了一个人群免疫水平的表征指标。我们得出结论,如果第一次大规模疫情的流行率为80%,第二次大规模疫情的流行率将约为37.64%,峰值时间将是2023年7月2日。加强疫苗接种可以有效推迟第二波疫情的峰值并降低流行率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4254/10465198/12697c95d1b8/rsos230655f01.jpg

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