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Stochastic analysis of a COVID-19 model with effects of vaccination and different transition rates: Real data approach

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  • Xu, Changjin
  • Liu, Zixin
  • Pang, Yicheng
  • Akgül, Ali

Abstract

This paper presents a stochastic model for COVID-19 that takes into account factors such as incubation times, vaccine effectiveness, and quarantine periods in the spread of the virus in symptomatically contagious populations. The paper outlines the conditions necessary for the existence and uniqueness of a global solution for the stochastic model. Additionally, the paper employs nonlinear analysis to demonstrate some results on the ergodic aspect of the stochastic model. The model is also simulated and compared to deterministic dynamics. To validate and demonstrate the usefulness of the proposed system, the paper compares the results of the infected class with actual cases from Iraq, Bangladesh, and Croatia. Furthermore, the paper visualizes the impact of vaccination rates and transition rates on the dynamics of infected people in the infected class.

Suggested Citation

  • Xu, Changjin & Liu, Zixin & Pang, Yicheng & Akgül, Ali, 2023. "Stochastic analysis of a COVID-19 model with effects of vaccination and different transition rates: Real data approach," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    • Handle: RePEc:eee:chsofr:v:170:y:2023:i:c:s0960077923002965
    DOI: 10.1016/j.chaos.2023.113395
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    References listed on IDEAS

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    1. Din, Anwarud & Khan, Amir & Baleanu, Dumitru, 2020. "Stationary distribution and extinction of stochastic coronavirus (COVID-19) epidemic model," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    2. Mohammad Bayat & Mehdi Heydari & Mohammad Mahdavi Mazdeh, 2013. "Heuristic for Stochastic Online Flowshop Problem with Preemption Penalties," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-10, September.
    3. Ghosh, Jayanta Kumar & Biswas, Sudhanshu Kumar & Sarkar, Susmita & Ghosh, Uttam, 2022. "Mathematical modelling of COVID-19: A case study of Italy," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 1-18.
    4. Igor Sazonov & Dmitry Grebennikov & Andreas Meyerhans & Gennady Bocharov, 2021. "Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell," Mathematics, MDPI, vol. 9(17), pages 1-19, August.
    5. Adak, Debadatta & Majumder, Abhijit & Bairagi, Nandadulal, 2021. "Mathematical perspective of Covid-19 pandemic: Disease extinction criteria in deterministic and stochastic models," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
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    Cited by:

    1. James, Nick & Menzies, Max, 2023. "Collective infectivity of the pandemic over time and association with vaccine coverage and economic development," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    2. 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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