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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Fluctuating epidemics on adaptive networks.

Leah B Shaw1, Ira B Schwartz

  • 1Department of Applied Science, College of William and Mary, Williamsburg, Virginia 23187, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|July 23, 2008
PubMed
Summary
This summary is machine-generated.

This study models epidemics on adaptive networks where individuals avoid infection by rewiring connections. This network adaptation can lead to stable endemic or disease-free states, with fluctuations showing power law behavior.

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Area of Science:

  • Epidemiology
  • Network Science
  • Computational Modeling

Background:

  • Epidemic modeling traditionally assumes static networks.
  • Adaptive networks, where connections change based on interactions, are crucial for understanding real-world disease spread.
  • Understanding how network structure influences epidemic dynamics is key.

Purpose of the Study:

  • To develop and analyze a mathematical model for epidemic spread on an adaptive network.
  • To investigate the impact of adaptive rewiring on epidemic dynamics and network structure.
  • To explore the emergence of bistability and the behavior of fluctuations in the endemic state.

Main Methods:

  • A susceptible-infective-recovered-susceptible (SIRS) model on a network with adaptive rewiring.
  • Monte Carlo simulations to capture stochastic effects.
  • Numerical solution of a mean-field model for analytical insights.

Main Results:

  • Network rewiring significantly alters degree distributions and increases the average distance to infective nodes.
  • Adaptive rewiring introduces bistability, allowing for either endemic or disease-free steady states.
  • Fluctuations around the endemic state exhibit power-law behavior, and the lifetime of the endemic state is analyzed.

Conclusions:

  • Adaptive network structures play a critical role in modulating epidemic outcomes.
  • The ability of individuals to change connections can stabilize or destabilize disease presence.
  • Power-law fluctuations suggest complex emergent behavior in adaptive epidemic models.