Spreading of infection in a two species reaction-diffusion process in networks

Paschalis Korosoglou1, Aristotelis Kittas, Panos Argyrakis

  • 1Department of Physics, University of Thessaloniki, 54124 Thessaloniki, Greece. pkoro@grid.auth.gr

Insights

Mobile agents and infection spread were studied. Healthy agent density follows exponential decay, with crossover times varying across network types, highlighting connectivity

Area of Science:

  • Epidemiology
  • Network Science
  • Statistical Physics

Background:

  • Traditional infection models focus on static sites.
  • Mobile agents offer a more realistic approach to disease and information spread.

Purpose of the Study:

  • Investigate infection dynamics with mobile healthy and infected agents.
  • Analyze healthy agent density and crossover time across different network structures.

Main Methods:

  • Simulated infection spread via random walks of mobile agents.
  • Monitored healthy agent density (ρ(t)) over time.
  • Analyzed crossover time (t(c)) in various network topologies (lattices, ER, SF networks).

Main Results:

  • Healthy agent density exhibits exponential decay in the long-time limit across all studied networks.
  • Crossover time scales as a power law in lattices and Erdős-Rényi (ER) networks.
  • Scale-free (SF) networks lack a distinct crossover time, emphasizing network connectivity's role.

Conclusions:

  • Mobile agent dynamics significantly alter infection spread compared to static models.
  • Network topology, particularly connectivity in SF networks, critically influences infection dynamics and crossover behavior.
  • Findings provide insights into real-world phenomena like virus propagation in mobile networks and rumor spreading.

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