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Chaos in Opinion-Driven Disease Dynamics.

Thomas Götz1, Tyll Krüger2, Karol Niedzielewski3

  • 1Mathematical Institute, University of Koblenz, 56070 Koblenz, Germany.

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|April 26, 2024
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Summary

Societal acceptance influences intervention effectiveness during epidemics. This study models coupled opinion-epidemic systems, revealing complex dynamics that impact infection rates and showing a protective pattern.

Keywords:
SIS-modelchaosdisease dynamicsepidemiologyopinion dynamicsq-voter modelsociophysics

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Area of Science:

  • Epidemiology
  • Sociology
  • Mathematical modeling

Background:

  • Societal acceptance is crucial for the success of public health interventions, particularly during pandemics like COVID-19.
  • Opinion formation processes significantly impact public adherence to and acceptance of these measures.
  • Understanding the interplay between public opinion and disease spread is vital for effective epidemic control.

Purpose of the Study:

  • To investigate the dynamics of coupled opinion-epidemic systems.
  • To explore how opinion formation influences epidemic trajectories.
  • To identify potential patterns or behaviors within these coupled systems.

Main Methods:

  • Development of a mathematical model simulating coupled opinion and epidemic dynamics.
  • Analysis of model outputs to identify patterns such as periodic or chaotic behavior.
  • Evaluation of the impact of opinion distribution on infection rates over time.

Main Results:

  • The coupled opinion-epidemic model exhibits complex dynamics, including intricate periodic patterns and chaotic behavior.
  • Significant fluctuations in opinion distribution were observed, directly correlating with variations in total infection numbers.
  • A notable protective pattern emerged from the model's simulations.

Conclusions:

  • Opinion dynamics play a critical role in modulating epidemic outcomes.
  • The interplay between societal opinions and disease spread can lead to unpredictable yet potentially manageable patterns.
  • The identified protective pattern suggests avenues for optimizing public health strategies by considering opinion formation.