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A nonlinear mathematical model on the Covid-19 transmission pattern among diabetic and non-diabetic population

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  • Anand, Monalisa
  • Danumjaya, P.
  • Rao, P. Raja Sekhara

Abstract

In this paper, a three tier mathematical model describing the interactions between susceptible population, Covid-19 infected, diabetic population and Covid-19 infected, non diabetic population is proposed. Basic properties of such a dynamic model, namely, non negativity, boundedness of solutions, existence of disease-free and disease equilibria are studied and sufficient conditions are obtained. Basic reproduction number for the system is derived. Sufficient conditions on functionals and parameters of the system are obtained for the local as well as global stability of equilibria, thus, establishing the conditions for eventual prevalence of disease free or disease environment, as the case may be. The stability aspects are discussed in the context of basic reproduction number and vice versa. An important contribution of this article is that a novel technique is presented to estimate some key, influencing parameters of the system so that a pre-specified, assumed equilibrium state is approached eventually. This enables the society to prepare itself with the help of these key, influencing parameters so estimated. Several examples are provided to illustrate the results established and simulations are provided to visualize the examples.

Suggested Citation

  • Anand, Monalisa & Danumjaya, P. & Rao, P. Raja Sekhara, 2023. "A nonlinear mathematical model on the Covid-19 transmission pattern among diabetic and non-diabetic population," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 210(C), pages 346-369.
    • Handle: RePEc:eee:matcom:v:210:y:2023:i:c:p:346-369
    DOI: 10.1016/j.matcom.2023.03.016
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    References listed on IDEAS

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    1. Tyagi, Swati & Martha, Subash C. & Abbas, Syed & Debbouche, Amar, 2021. "Mathematical modeling and analysis for controlling the spread of infectious diseases," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
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    4. Hattaf, Khalid & Dutta, Hemen, 2020. "Modeling the dynamics of viral infections in presence of latently infected cells," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    5. Raja Sekhara Rao, P. & Naresh Kumar, M., 2015. "A dynamic model for infectious diseases: The role of vaccination and treatment," Chaos, Solitons & Fractals, Elsevier, vol. 75(C), pages 34-49.
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