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COVID-19 与干预措施的异质混合模型。

The heterogeneous mixing model of COVID-19 with interventions.

机构信息

School of Data Science and Technology, North University of China, Taiyuan 030051, Shanxi, China; Complex Systems Research Center, Shanxi University, Taiyuan 030006, Shanxi, China.

Complex Systems Research Center, Shanxi University, Taiyuan 030006, Shanxi, China; Shanxi Key Laboratory of Mathematical Technique and Big Data Analysis on Disease Control and Prevention, Taiyuan 030006, Shanxi, China.

出版信息

J Theor Biol. 2022 Nov 21;553:111258. doi: 10.1016/j.jtbi.2022.111258. Epub 2022 Aug 28.

DOI:10.1016/j.jtbi.2022.111258
PMID:36041504
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9420055/
Abstract

The emergence of mutant strains of COVID-19 reduces the effectiveness of vaccines in preventing infection, but remains effective in preventing severe illness and death. This paper established a heterogeneous mixing model of age groups with pharmaceutical and non-pharmaceutical interventions by analyzing the transmission mechanism of breakthrough infection caused by the heterogeneity of protection period under the action of vaccine-preventable infection with the original strain. The control reproduction number R of the system is analyzed, and the existence and stability of equilibrium are given by the comparison principle. Numerical simulation was conducted to evaluate the vaccination program and intervention measures in the customized scenario, demonstrating that the group-3 coverage rate p plays a key role in R. It is proposed that accelerating the rate of admission and testing is conducive to epidemic control by further fitting data of COVID-19 transmission in real scenarios. The findings provide a general modeling idea for the emergence of new vaccines to prevent infection by mutant strains, as well as a solid theoretical foundation for mainland China to formulate future vaccination strategies for new vaccines. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

摘要

新冠病毒突变株的出现降低了疫苗预防感染的有效性,但仍能有效预防重症和死亡。本文通过分析疫苗可预防的原始株感染下保护期异质性导致突破感染的传播机制,建立了具有年龄组异质性的混合模型,并考虑了药物和非药物干预措施。分析了系统的控制繁殖数 R,利用比较原理给出了平衡点的存在性和稳定性。通过定制场景下的疫苗接种计划和干预措施的数值模拟,结果表明群体 3 的覆盖率 p 在 R 中起着关键作用。通过进一步拟合真实场景中 COVID-19 传播的数据,提出加快入院和检测速度有助于控制疫情。本研究为预防突变株感染的新型疫苗的出现提供了一种通用的建模思路,为中国大陆制定未来新型疫苗的接种策略提供了坚实的理论基础。本手稿是“建模 COVID-19 与为未来大流行做准备”主题特刊的一部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/5b86522b3e37/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/ca6d199adc45/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/6d1666cf7792/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/fd1c4d6c4e06/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/4213bcbd79fe/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/f8ddae7ac8af/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/5b86522b3e37/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/ca6d199adc45/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/6d1666cf7792/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/fd1c4d6c4e06/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/4213bcbd79fe/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/f8ddae7ac8af/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a45/9420055/5b86522b3e37/gr6_lrg.jpg

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本文引用的文献

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Mathematical modeling of COVID-19 in British Columbia: An age-structured model with time-dependent contact rates.不列颠哥伦比亚省 COVID-19 的数学建模:一个具有时变接触率的年龄结构模型。
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Covid-19 Vaccine Effectiveness against the Omicron (B.1.1.529) Variant.Covid-19 疫苗对奥密克戎(B.1.1.529)变异株的有效性。
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Vaccination and Quarantine Effect on COVID-19 Transmission Dynamics Incorporating Chinese-Spring-Festival Travel Rush: Modeling and Simulations.纳入中国春运的疫苗接种和检疫对 COVID-19 传播动力学的影响:建模与模拟。
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