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Modeling COVID-19 dynamic using a two-strain model with vaccination

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  • de León, Ugo Avila-Ponce
  • Avila-Vales, Eric
  • Huang, Kuan-lin

Abstract

Multiple strains of the SARS-CoV-2 have arisen and jointly influence the trajectory of the coronavirus disease (COVID-19) pandemic. However, current models rarely account for this multi-strain dynamics and their different transmission rate and response to vaccines. We propose a new mathematical model that accounts for two virus variants and the deployment of a vaccination program. To demonstrate utility, we applied the model to determine the control reproduction number (Rc) and the per day infection, death and recovery rates of each strain in the US pandemic. The model dynamics predicted the rise of the alpha variant and shed light on potential impact of the delta variant in 2021. We obtained the minimum percentage of fully vaccinated individuals to reduce the spread of the variants in combination with other intervention strategies to deaccelerate the rise of a multi-strain pandemic.

Suggested Citation

  • de León, Ugo Avila-Ponce & Avila-Vales, Eric & Huang, Kuan-lin, 2022. "Modeling COVID-19 dynamic using a two-strain model with vaccination," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:chsofr:v:157:y:2022:i:c:s0960077922001370
    DOI: 10.1016/j.chaos.2022.111927
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    References listed on IDEAS

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    Cited by:

    1. Chen, Jiaqi & Gu, Changgui & Ruan, Zhongyuan & Tang, Ming, 2023. "Competition of SARS-CoV-2 variants on the pandemic transmission dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    2. Vashishth, Anil K. & Basaiti, Komal, 2024. "Modeling the effect of non-pharmaceutical measures and vaccination on the spread of two variants of COVID-19 in India," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 217(C), pages 139-168.

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