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This study introduces a time-varying human mobility pattern to model travel during epidemics. The pattern slightly reduces overall infections but impacts different population groups uniquely, aiding targeted interventions.

Keywords:
Complex networkEpidemic dynamicsHuman mobility patternReaction–diffusion process

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Area of Science:

  • Epidemiology
  • Network Science
  • Mathematical Modeling

Background:

  • Epidemic outbreaks significantly influence human travel patterns.
  • Understanding these dynamics is crucial for effective disease control.
  • Heterogeneous metapopulation networks are valuable for modeling disease spread.

Purpose of the Study:

  • To introduce a time-varying human mobility pattern reflecting epidemic influences on travel.
  • To investigate the impact of this pattern on epidemic dynamics in complex networks.
  • To analyze how mobility changes affect disease spread in subpopulations of varying connectivity.

Main Methods:

  • Development of a time-varying human mobility pattern.
  • Application of a mean-field approach for epidemic modeling.
  • Analysis of epidemic dynamics in heterogeneous metapopulation networks.

Main Results:

  • The mobility pattern does not change the epidemic threshold.
  • A slight decrease in the overall average density of infected individuals was observed.
  • Nodes with different degrees experienced varied impacts; a critical degree was identified.

Conclusions:

  • The time-varying mobility pattern offers nuanced insights into epidemic spread.
  • Interventions may need to be tailored based on a subpopulation's network degree.
  • High-degree nodes may require different mitigation strategies than low-degree nodes.