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Bounded risk disposition explains Turing patterns and tipping points during spatial contagions.

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  • 1Centre for Complex Systems, Faculty of Engineering, The University of Sydney, Sydney, New South Wales, Australia.

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|October 3, 2024
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Summary
This summary is machine-generated.

This study introduces a new framework to model spatial contagions like pandemics and civil unrest. It reveals that these contagions form complex Turing patterns sensitive to human behavior and vulnerability.

Keywords:
epidemicsopinion polarizationpattern formationsocial mythssocio-economic turbulencesusceptibility acquisition

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Area of Science:

  • Complex Systems Science
  • Mathematical Biology
  • Socio-spatial Dynamics

Background:

  • Spatial contagions (pandemics, opinion polarization, infodemics, civil unrest) display complex spatio-temporal dynamics.
  • These dynamics are driven by intricate human behaviors and population mobility patterns.

Purpose of the Study:

  • To propose a generic framework for modeling diverse spatial contagions.
  • To define a contagion vulnerability space incorporating risk disposition and susceptibility.
  • To analyze the emergent spatio-temporal patterns and their sensitivity to vulnerability parameters.

Main Methods:

  • Development of a generic modeling framework for spatial contagions.
  • Definition of a contagion vulnerability space including bounded risk aversion, adaptive responsiveness, and generalized susceptibility acquisition.
  • Analysis of emergent geospatial contagion configurations as Turing patterns.

Main Results:

  • Spatial contagions generate intricate Turing patterns, analogous to those in reaction-diffusion systems.
  • Pattern formation is highly sensitive to variations in vulnerability parameters.
  • Identified critical regimes (tipping points) demonstrate how minor changes in susceptibility or perceived risk significantly alter population flow and contagion patterns.

Conclusions:

  • The proposed framework effectively models diverse spatial contagions, revealing emergent Turing patterns.
  • Understanding vulnerability parameters is crucial for predicting and managing spatial contagion dynamics.
  • The model's sensitivity analysis highlights potential tipping points in contagion spread and impact.