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This study introduces a novel mathematical model to analyze the complex dynamics of COVID-19. The research reveals that specific parameter ranges can induce chaotic behavior and multi-stability in the disease

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Complex Systems

Background:

  • The COVID-19 pandemic, originating in late 2019, has caused a global health crisis.
  • Despite containment measures like quarantine and vaccination, understanding the disease's dynamical behavior remains crucial.
  • Mathematical models are essential tools for analyzing epidemic dynamics.

Purpose of the Study:

  • To introduce a novel mathematical system for modeling COVID-19 dynamics.
  • To investigate the complex behaviors of this mathematical model.
  • To analyze the impact of parameters on disease dynamics.

Main Methods:

  • Development of a novel mathematical model for epidemic analysis.
  • Application of dynamical analyses to study model behavior.
  • Comparison of bifurcation diagrams with varying initial conditions.

Main Results:

  • The mathematical model exhibits complex dynamical behaviors.
  • Certain parameter ranges can lead to chaotic dynamics within the model.
  • The model demonstrates multi-stability, indicated by differing outcomes with varied initial conditions.

Conclusions:

  • The novel mathematical model provides insights into COVID-19's complex dynamics.
  • The findings highlight the potential for chaotic behavior and multi-stability in epidemic modeling.
  • Further research using this model can aid in understanding and managing infectious diseases.