A novel analytical tool for complex propagation processes in networks: High-order dynamic equation.
1School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, People's Republic of China.
Chaos (Woodbury, N.Y.)
|December 13, 2024
Summary
This study introduces novel dynamic equations to analyze epidemic spread in complex networks, revealing the crucial role of higher-order structures in transmission dynamics and offering new tools for control.
Area of Science:
- Network science
- Epidemiology
- Complex systems analysis
Background:
- Controlling epidemic spread in complex networks is a key challenge.
- Existing models often overlook the significant impact of higher-order network structures on transmission.
- Current analysis is limited to lower-dimensional, node-level interactions.
Purpose of the Study:
- To develop a new analytical framework for understanding complex epidemic propagation.
- To investigate the influence of higher-order network structures on epidemic dynamics.
- To provide advanced tools for analyzing and controlling epidemic spread.
Main Methods:
- Formulation of closed dynamic higher-order structure equations.
- Application to a susceptible-infection-recovery epidemiological model.
- Extensive numerical simulations on real and synthetic networks.
Main Results:
- The proposed equations provide insights into complex propagation from a higher-order perspective.
- Demonstrated effectiveness of the higher-order dynamic analysis approach.
- Quantified the impact of network higher-order structures on epidemic transmission.
Conclusions:
- Higher-order network structures significantly influence epidemic spread dynamics.
- The developed framework offers a novel approach to analyze complex propagation.
- Provides a theoretical basis for enhanced epidemic prediction and control.
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