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Higher-order interactions in mobile populations significantly impact epidemic spread. This study models these dynamics, revealing hysteresis loops and three endemic states influenced by network structure and initial conditions.

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Area of Science:

  • Epidemiology
  • Network Science
  • Computational Biology

Background:

  • Higher-order interactions are crucial for epidemic spread in mobile populations, yet modeling and understanding their dynamics remain limited.
  • Existing research often simplifies interactions, failing to capture the complexity of real-world mobile crowd behavior and its effect on disease transmission.

Purpose of the Study:

  • To model and simulate higher-order interactions within mobile populations.
  • To explore the impact of these interactions and spatial characteristics on epidemic transmission dynamics.
  • To analyze the influence of crowd density and movement speed on disease propagation and network behavior.

Main Methods:

  • Agent-based modeling to simulate epidemic spread in a spatial higher-order network.
  • Construction of state-specific rate equations under the uniform mixing assumption for analytical insights.
  • Analysis of network snapshots and parameter diagrams to identify equilibrium states.

Main Results:

  • Hysteresis loops were identified as an inherent feature of spatial higher-order networks under specific conditions.
  • Epidemic evolution exhibited three distinct equilibrium states (low, medium, high) influenced by initial values.
  • Higher initial seeding led to increased higher-order interactions and higher infection densities, emphasizing the role of higher-order infection rates.

Conclusions:

  • Higher-order interactions and spatial network structures significantly influence epidemic transmission patterns.
  • Crowd density and movement speed modulate epidemic spread, acting as protective and inhibitory factors respectively.
  • The study highlights the importance of considering complex interaction structures for accurate epidemic modeling and control strategies.