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Epidemic spreading in localized environments with recurrent mobility patterns.

Clara Granell1,2,3, Peter J Mucha3

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Understanding epidemic spread in closed populations is key. Our model shows how mobility patterns influence disease transmission and identifies effective prevention strategies for confined environments.

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Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Network Science

Background:

  • Epidemic spreading is heavily influenced by contact network structures.
  • Individual mobility dynamics significantly impact disease transmission patterns.
  • Confined populations with predictable mobility (e.g., schools, campuses) require specific analysis.

Purpose of the Study:

  • To develop a metapopulation model for disease transmission in confined scenarios with non-random mobility.
  • To analytically determine epidemic onset and identify critical contact structures for prevention.
  • To evaluate the effectiveness and impact of interventions like isolation.

Main Methods:

  • A discrete-time, metapopulation-based modeling approach.
  • Analysis of recurrent travel patterns within localized environments.
  • Mathematical determination of epidemic thresholds and network-based prevention.

Main Results:

  • The model allows for analytical prediction of epidemic onset.
  • Identifies specific contact structures that are most effective in limiting disease spread.
  • Provides insights into the utility and expected impact of isolation measures.

Conclusions:

  • Mobility patterns in confined settings critically affect epidemic dynamics.
  • Targeted interventions based on network structure can be more effective than general measures.
  • The model provides a framework for optimizing disease control in closed populations.