考虑疫苗接种和失效的COVID-19传播模型的动力学分析
Dynamics Analysis of a COVID-19 Transmission Model Incorporating Vaccination and Failure
摘要: 疫苗接种是一种控制疫情传播的有效措施。但是随着毒株的变异出现了一个新的问题–免疫逃亡。免疫逃亡会使我们接种的疫苗失去作用,再次面临被感染的风险。重症治疗是应对COVID-19疫情的重要环节,不仅决定了患者的康复率和死亡率,还直接影响了疫情的传播速度和范围。因此本文构建了一个具疫苗失效以及重症住院治疗的COVID-19传播动力学模型,计算了模型的控制再生数,证明了模型无COVID-19平衡点和COVID-19平衡点存在性条件,并进行数值模拟验证了理论结果。
Abstract: Vaccination is an effective measure to control the spread of epidemics. However, as strains of the virus mutate, a new problem arises-immune escape. Immune escape renders the vaccine ineffective and puts us at risk of being infected again. Critical care is an important part of the response to COVID-19 epidemic, which not only determines the recovery rate and mortality rate of patients, but also directly affects the speed and scope of the epidemic. In this paper, we constructed a model of COVID-19 transmission dynamics with vaccine failure and intensive care hospitalisation, calculated the control regeneration number of the model, proved that the model has no COVID-19 equilibrium point and the existence condition of COVID-19 equilibrium point, and conducted numerical simulations to verify the theoretical results.
文章引用:赵勇盛, 张蒙. 考虑疫苗接种和失效的COVID-19传播模型的动力学分析[J]. 应用数学进展, 2024, 13(5): 2348-2357. https://doi.org/10.12677/aam.2024.135222

参考文献

[1] Xu, X., Chen, P., Wang, J., et al. (2020) Evolution of the Novel Coronavirus from the Ongoing Wuhan Outbreak and Modeling of Its Spike Protein for Risk of Human Transmission. Science China Life Sciences, 63, 457-460. [Google Scholar] [CrossRef] [PubMed]
[2] Ciotti, M., Ciccozzi, M., Pieri, M., et al. (2022) The COVID-19 Pandemic: Viral Variants and Vaccine Efficacy. Critical Reviews in Clinical Laboratory Sciences, 59, 66-75. [Google Scholar] [CrossRef] [PubMed]
[3] 中国疾病预防控制中心. 新型冠状病毒感染[EB/OL].
https://www.chinacdc.cn/jkzt/crb/zl/szkb_11803/, 2024-03-25.
[4] 李娜, 汪哲, 包云丽, 唐海茹, 黄俊, 于晓辉, 张久聪. 新冠肺炎后遗症的临床特征及研究进展[J]. 海南医学院学报, 2022, 28(14): 1041-1049.
[5] 陈盼, 杨剑, 肖永红. 新型冠状病毒疫苗的研究进展[J]. 医药导报, 2024, 43(2): 240-248.
[6] Salman, A.M., Ahmed, I., Mohd, M.H., et al. (2021) Scenario Analysis of COVID-19 Transmission Dynamics in Malaysia with the Possibility of Reinfection and Limited Medical Resources Scenarios. Computers in Biology and Medicine, 133, Article 104372. [Google Scholar] [CrossRef] [PubMed]
[7] Wangping, J., Ke, H., Yang, S., et al. (2020) Extended SIR Prediction of the Epidemics Trend of COVID-19 in Italy and Compared with Hunan, China. Frontiers in Medicine, 7, 169-173. [Google Scholar] [CrossRef] [PubMed]
[8] Kain, M.P., Childs, M.L., Becker, A.D., et al. (2021) Chopping the Tail: How Preventing Superspreading Can Help to Maintain COVID-19 Control. Epidemics, 34, Article 100430. [Google Scholar] [CrossRef] [PubMed]
[9] Torneri, A., Libin, P., Vanderlocht, J., et al. (2020) A Prospect on the Use of Antiviral Drugs to Control Local Outbreaks of COVID-19. BMC Medicine, 18, Article No. 191. [Google Scholar] [CrossRef] [PubMed]
[10] Li, T., Liu, Y., Li, M., et al. (2020) Mask or No Mask for COVID-19: A Public Health and Market Study. PLOS ONE, 15, e0237691. [Google Scholar] [CrossRef] [PubMed]
[11] Reiner, R.C., Barber, R.M., Collins, J.K., et al. (2021) Modeling COVID-19 Scenarios for the United States. Nature Medicine, 27, 94-105. [Google Scholar] [CrossRef] [PubMed]
[12] Sonabend, R., Whittles, L.K., Imai, N., et al. (2021) Non-Pharmaceutical Interventions, Vaccination, and the SARS-CoV-2 Delta Variant in England: A Mathematical Modelling Study. The Lancet, 398, 1825-1835. [Google Scholar] [CrossRef
[13] Djaafara, B.A., Whittaker, C., Watson, O.J., et al. (2021) Using Syndromic Measures of Mortality to Capture the Dynamics of COVID-19 in Java, Indonesia, in the Context of Vaccination Rollout. BMC Medicine, 19, Article No. 146. [Google Scholar] [CrossRef] [PubMed]
[14] Davies, N.G., Abbott, S., Barnard, R.C., et al. (2021) Estimated Transmissibility and Impact of SARS-CoV-2 Lineage B.1.1.7 in England. Science, 372, eabg3055. [Google Scholar] [CrossRef] [PubMed]
[15] Buckner, J.H., Chowell, G. and Springborn, M.R. (2021) Dynamic Prioritization of COVID-19 Vaccines When Social Distancing Is Limited for Essential Workers. Proceedings of the National Academy of Sciences, 118, e2025786118. [Google Scholar] [CrossRef] [PubMed]
[16] Moore, S., Hill, E.M., Tildesley, M.J., et al. (2021) Vaccination and Non-Pharmaceutical Interventions for COVID-19: A Mathematical Modelling Study. The Lancet Infectious Diseases, 21, 793-802. [Google Scholar] [CrossRef
[17] 马知恩, 周义仓, 李承治. 常微分方程定性与稳定性方法[M]. 第2版. 北京: 科学出版社, 2015.
[18] Sheng, Y., Cui, J.-A. and Guo, S. (2023) The Modeling and Analysis of the COVID-19 Pandemic with Vaccination and Isolation: A Case Study of Italy. Mathematical Biosciences and Engineering, 20, 5966-5992. [Google Scholar] [CrossRef] [PubMed]
[19] Bai, Y.-Z., Wang, X.-J. and Guo, S.-B. (2021) Global Stability of a Mumps Transmission Model with Quarantine Measure. Acta Mathematicae Applicatae Sinica, English Series, 37, 665-672. [Google Scholar] [CrossRef] [PubMed]
[20] Ao, D., Lan, T., He, X., Liu, J., Chen, L., Baptista-Hon, D.T., Zhang, K. and Wei, X. (2022) SARS-CoV-2 Omicron Variant: Immune Escape and Vaccine Development. MedComm, 3, e126. [Google Scholar] [CrossRef] [PubMed]