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<p>We developed a mathematical framework for the coinfection of TB with COVID-19 in this paper via a nonlinear dynamical system in which the human population is subdivided into eight compartments. By modifying the existing model of Mekonen and Obsu (Heliyon 8(10), 2022), the newly formulated model is more comprehensive and covers a wide range of concepts because, in this model, we have included classes of exposed people due to TB and coexposed classes of COVID-19 and TB jointly and apply fraction order extension and analysis qualitatively. By assuming a single infection, the model may be readily converted to both the COVID-19 and TB submodels. This provides three models: two more COVID-19 and TB submodels in addition to the general coinfection model. The basic properties of the model are investigated, and the reproductive number is calculated. The stability of the model is studied, followed by bifurcation analysis and sensitivity analysis. Finally, by using fractional order extension, a computational analysis and numerical simulations of the coinfection model are performed. The numerical experiments of the proposed coinfection model agree with the findings of the analytical results. highlights the impact of the fractional order on the model’s dynamics and offers potential avenues for further research.</p>

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Bifurcation and sensitivity for COVID-TB coinfection with simulations

  • 期刊论文

  • 发表日期：

    2025年4月7日

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  • Irfan Ullah,
  • Imtiaz Ahmad,
  • Nigar Ali,
  • Ihtisham Ul Haq,
  • D. K. Almutair,
  • Hasib Khan,
  • Jehad Alzabut

摘要

We developed a mathematical framework for the coinfection of TB with COVID-19 in this paper via a nonlinear dynamical system in which the human population is subdivided into eight compartments. By modifying the existing model of Mekonen and Obsu (Heliyon 8(10), 2022), the newly formulated model is more comprehensive and covers a wide range of concepts because, in this model, we have included classes of exposed people due to TB and coexposed classes of COVID-19 and TB jointly and apply fraction order extension and analysis qualitatively. By assuming a single infection, the model may be readily converted to both the COVID-19 and TB submodels. This provides three models: two more COVID-19 and TB submodels in addition to the general coinfection model. The basic properties of the model are investigated, and the reproductive number is calculated. The stability of the model is studied, followed by bifurcation analysis and sensitivity analysis. Finally, by using fractional order extension, a computational analysis and numerical simulations of the coinfection model are performed. The numerical experiments of the proposed coinfection model agree with the findings of the analytical results. highlights the impact of the fractional order on the model’s dynamics and offers potential avenues for further research.