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Modelling the Influence of Dynamic Social Processes on COVID-19 Infection Dynamics

Author

Listed:
  • Farai Nyabadza

    (Department of Mathematics and Applied Mathematics, University of Johannesburg, Johannesburg 2006, South Africa)

  • Josiah Mushanyu

    (Department of Computing, Mathematical, and Statistical Science, University of Namibia, Windhoek 13301, Namibia)

  • Rachel Mbogo

    (Institute of Mathematical Sciences, Strathmore University, P.O. Box 59857, Nairobi 00200, Kenya)

  • Gift Muchatibaya

    (Department of Mathematics and Computational Sciences, University of Zimbabwe, Harare P.O. Box MP167, Zimbabwe)

Abstract

Human behaviour was tipped as the mainstay in the control of further SARS-CoV-2 (COVID-19) spread, especially after the lifting of restrictions by many countries. Countries in which restrictions were lifted soon after the first wave had subsequent waves of COVID-19 infections. In this study, we develop a deterministic model for COVID-19 that includes dynamic non-pharmaceutical interventions known as social dynamics with the goal of simulating the effects of dynamic social processes. The model steady states are determined and their stabilities analysed. The model has a disease-free equilibrium point that is locally asymptotically stable if R 0 < 1 . The model exhibits a backward bifurcation, implying that reducing the reproduction number below one is not sufficient for the elimination of the disease. To ascertain the range of parameters that affect social dynamics, numerical simulations are conducted. The only wave in South Africa in which interventions were purely based on human behavior was the first wave. The model is thus fitted to COVID-19 data on the first wave in South Africa, and the findings given in this research have implications for the trajectory of the pandemic in the presence of evolving societal processes. The model presented has the potential to impact how social processes can be modelled in other infectious disease models.

Suggested Citation

  • Farai Nyabadza & Josiah Mushanyu & Rachel Mbogo & Gift Muchatibaya, 2023. "Modelling the Influence of Dynamic Social Processes on COVID-19 Infection Dynamics," Mathematics, MDPI, vol. 11(4), pages 1-17, February.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:4:p:963-:d:1067271
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    References listed on IDEAS

    as
    1. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "A SIR model assumption for the spread of COVID-19 in different communities," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    2. Asamoah, Joshua Kiddy K. & Jin, Zhen & Sun, Gui-Quan & Seidu, Baba & Yankson, Ernest & Abidemi, Afeez & Oduro, F.T. & Moore, Stephen E. & Okyere, Eric, 2021. "Sensitivity assessment and optimal economic evaluation of a new COVID-19 compartmental epidemic model with control interventions," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    3. Sintunavarat, Wutiphol & Turab, Ali, 2022. "Mathematical analysis of an extended SEIR model of COVID-19 using the ABC-fractional operator," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 198(C), pages 65-84.
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