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Epidemic dynamics on metapopulation networks with node2vec mobility.

Lingqi Meng1, Naoki Masuda2

  • 1Department of Mathematics, State University of New York at Buffalo, Buffalo, NY 14260-2900, USA.

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|November 14, 2021
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Summary
This summary is machine-generated.

This study compares simple random walks with complex node2vec mobility in metapopulation models. Node2vec mobility can suppress epidemic spreading more effectively than simple random walks by altering the epidemic threshold.

Keywords:
Epidemic thresholdMetapopulation modelSecond-order random walkSusceptible-infectious-susceptible model

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Area of Science:

  • Epidemiology
  • Network Science
  • Mathematical Biology

Background:

  • Metapopulation models are crucial for understanding epidemic dynamics across connected subpopulations.
  • Mobility rules significantly influence disease spread, yet comparisons between simple and complex rules are limited.

Purpose of the Study:

  • To investigate the impact of a specific complex mobility rule (node2vec) on epidemic dynamics within metapopulation models.
  • To compare the effects of node2vec mobility against simple random walks on epidemic thresholds.

Main Methods:

  • Simulated susceptible-infectious-susceptible (SIS) dynamics in a metapopulation network.
  • Mapped the second-order node2vec mobility rule to a first-order random walk on an edge network.
  • Derived the epidemic threshold for the node2vec mobility rule.

Main Results:

  • Node2vec mobility, characterized by infrequent backtracking and common neighbor visits, increases the epidemic threshold compared to simple random walks.
  • This increase in the epidemic threshold suggests suppressed epidemic spreading under node2vec mobility.
  • The impact of node2vec mobility on the epidemic threshold can be comparable to changes in individual diffusion rates.

Conclusions:

  • Complex mobility rules like node2vec can significantly alter epidemic thresholds in metapopulation models.
  • Node2vec mobility offers a potential mechanism for controlling or suppressing disease transmission in networked populations.
  • Further research can explore the nuanced effects of various complex mobility patterns on epidemic dynamics.