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Modeling and optimal control of mutated COVID-19 (Delta strain) with imperfect vaccination

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  • Li, Tingting
  • Guo, Youming

Abstract

As people around the world work to stop the COVID-19 pandemic, mutated COVID-19 (Delta strain) that are more contagious are emerging in many places. How to develop effective and reasonable plans to prevent the spread of mutated COVID-19 is an important issue. In order to simulate the transmission of mutated COVID-19 (Delta strain) in China with a certain proportion of vaccination, we selected the epidemic situation in Jiangsu Province as a case study. To solve this problem, we develop a novel epidemic model with a vaccinated population. The basic properties of the model is analyzed, and the expression of the basic reproduction number R0 is obtained. We collect data on the Delta strain epidemic in Jiangsu Province, China from July 20, to August 5, 2021. The weighted nonlinear least square estimation method is used to fit the daily asymptomatic infected people, common infected people and severe infected people. The estimated parameter values are obtained, the approximate values of the basic reproduction number are calculated R0≈1.378. Through the global sensitivity analysis, we identify some parameters that have a greater impact on the prevalence of the disease. Finally, according to the evaluation results of parameter influence, we consider three control measures (vaccination, isolation and nucleic acid testing) to control the spread of the disease. The results of the study found that the optimal control measure is to dynamically adjust the three control measures to achieve the lowest number of infections at the lowest cost. The research in this paper can not only enrich theoretical research on the transmission of COVID-19, but also provide reliable control suggestions for countries and regions experiencing mutated COVID-19 epidemics.

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  • Li, Tingting & Guo, Youming, 2022. "Modeling and optimal control of mutated COVID-19 (Delta strain) with imperfect vaccination," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:chsofr:v:156:y:2022:i:c:s0960077922000364
    DOI: 10.1016/j.chaos.2022.111825
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    2. Samson Olaniyi & Olusegun A. Ajala & Sulaimon F. Abimbade, 2023. "Optimal Control Analysis of a Mathematical Model for Recurrent Malaria Dynamics," SN Operations Research Forum, Springer, vol. 4(1), pages 1-24, March.
    3. Tingting Li & Youming Guo, 2022. "Optimal Control Strategy of an Online Game Addiction Model with Incomplete Recovery," Journal of Optimization Theory and Applications, Springer, vol. 195(3), pages 780-807, December.
    4. Cai, Junyang & Zhou, Jian, 2022. "How many asymptomatic cases were unconfirmed in the US COVID-19 pandemic? The evidence from a serological survey," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    5. Li, Tingting & Guo, Youming, 2022. "Optimal control and cost-effectiveness analysis of a new COVID-19 model for Omicron strain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    6. Shi, Lei & Chen, Ziang & Wu, Peng, 2023. "Spatial and temporal dynamics of COVID-19 with nonlocal dispersal in heterogeneous environment: Modeling, analysis and simulation," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).

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