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This study presents a novel dynamical system modeling COVID-19

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Economics

Background:

  • The COVID-19 pandemic significantly impacted global economic activity.
  • Existing epidemiological models (e.g., SIR-like) do not fully capture economic dynamics.
  • Understanding the interplay between public health crises and economies is crucial.

Purpose of the Study:

  • To develop a novel dynamical system modeling the complex interactions between COVID-19 and economic activity.
  • To explore the co-dynamics of pandemics and economies beyond traditional epidemiological frameworks.
  • To identify key parameters influencing the observed stylized facts of pandemic-economic interactions.

Main Methods:

  • Introduction of a novel dynamical system incorporating economic factors.
  • Analysis of system equilibrium and stability properties.
  • Numerical simulations to reproduce pandemic waves and economic co-dynamics.
  • Application of Lotka-Volterra principles to model observed interactions.

Main Results:

  • The dynamical system's equilibrium is an unstable focus, leading to increasing fluctuations in size and periodicity.
  • Numerical simulations successfully generated pandemic waves mirroring real-world dynamics.
  • The model demonstrates Lotka-Volterra co-dynamics between the pandemic and economic activity, confirmed by simulations.
  • Qualitative replication of key stylized facts linking pandemics and economic behavior.

Conclusions:

  • The developed dynamical system offers a new approach to modeling coupled pandemic-economic systems.
  • The findings highlight the emergence of Lotka-Volterra co-dynamics, providing insights into cyclical patterns.
  • The study deepens understanding of parameter influences on pandemic-economic interactions and their shaping.