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Contagion-diffusion processes with recurrent mobility patterns of distinguishable agents.

P Valgañón1, D Soriano-Paños2, A Arenas3

  • 1Department of Condensed Matter Physics, University of Zaragoza, 50009 Zaragoza, Spain.

Chaos (Woodbury, N.Y.)
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Summary
This summary is machine-generated.

Distinguishing agents by residence and destination in metapopulation models reveals more accurate epidemic thresholds. This approach improves understanding of how mobility patterns affect disease spread in urban areas.

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Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Urban Dynamics

Background:

  • Metapopulation models are crucial for understanding disease spread influenced by mobility.
  • Current models often simplify agents as indistinguishable, potentially affecting accuracy.
  • Urban epidemics are complex, influenced by agent distribution and movement patterns.

Purpose of the Study:

  • To investigate the impact of distinguishable agents and recurrent mobility on epidemic trajectories in urban areas.
  • To develop a model that accounts for agent residence and destination.
  • To analytically calculate the epidemic threshold considering agent heterogeneity.

Main Methods:

  • Developed a metapopulation model incorporating distinguishable agents based on residence and destination.
  • Utilized agent-based modeling for spatiotemporal epidemic pattern computation.
  • Employed spectral radius calculation of a mixing matrix to determine the epidemic threshold.

Main Results:

  • The model enables fast computation of epidemic spatiotemporal patterns.
  • The epidemic threshold is analytically derived from agent distribution and commuting patterns.
  • Agent indistinguishability leads to an overestimation of the epidemic threshold.

Conclusions:

  • Distinguishable agents and specific mobility patterns significantly influence epidemic dynamics.
  • The proposed model provides a more accurate assessment of epidemic thresholds in urban settings.
  • Accounting for agent heterogeneity is essential for realistic disease spread analysis.