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Epidemic dynamics and endemic states in complex networks.
R Pastor-Satorras1, A Vespignani
1Departmento de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Campus Nord, Mòdul B4, 08034 Barcelona, Spain.
Summary
Epidemics spread differently in complex networks. Scale-free networks lack an epidemic threshold, making them vulnerable to persistent infections, unlike networks with bounded connectivity.
Area of Science:
- Complex networks
- Epidemiology
- Network science
Background:
- Epidemic models typically assume a threshold for disease spread.
- Network structure significantly influences epidemic dynamics.
- Understanding spread in complex systems is crucial for public health and cybersecurity.
Purpose of the Study:
- To investigate epidemic spreading dynamics in complex networks.
- To compare epidemic behavior in networks with exponential connectivity versus scale-free networks.
- To identify conditions that lead to epidemic thresholds or their absence.
Main Methods:
- Analytical methods
- Large-scale simulations
- Dynamical modeling of epidemic spread
Main Results:
- Networks with exponentially bounded connectivity exhibit a clear epidemic threshold.
- Scale-free networks demonstrate the absence of an epidemic threshold.
- Infections persist in scale-free networks regardless of the spreading rate.
Conclusions:
- Scale-free networks are inherently susceptible to widespread and persistent infections.
- The absence of a threshold in scale-free networks has implications for controlling epidemics.
- Findings are relevant for understanding computer virus propagation and social network dynamics.