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Anomalous epidemic spreading in heterogeneous networks
1State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology, Cheng'du, Si'chuan 610059, China and Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Cheng'du, Si'chuan 610059, China.
Physical Review. E
|August 16, 2020
Summary
This study introduces a susceptible-infected-susceptible model incorporating random waiting times in heterogeneous networks. It reveals a fractional memory effect in power-law waiting times, influencing anomalous epidemic spreading dynamics.
Area of Science:
- Epidemiology
- Network Science
- Statistical Mechanics
Background:
- Epidemic spreading in complex networks is a significant area of research.
- Understanding the impact of individual behavior, like residence time, is crucial for accurate modeling.
- Heterogeneous networks present unique challenges for contagion dynamics.
Purpose of the Study:
- To investigate epidemic spreading in heterogeneous networks considering individual residence time.
- To analyze the effect of random waiting times on epidemic dynamics.
- To uncover novel mechanisms driving anomalous spreading patterns.
Main Methods:
- Utilized a susceptible-infected-susceptible (SIS) model.
- Incorporated random waiting times with a power-law distribution.
- Analyzed epidemic dynamics in heterogeneous network structures.
- Derived analytical expressions for the time evolution of infected individuals.
Main Results:
- Identified a fractional memory effect stemming from power-law waiting times.
- Demonstrated how this memory effect influences anomalous epidemic spreading.
- Provided quantitative insights into contagion processes.
Conclusions:
- The study offers a refined model for epidemic spreading in heterogeneous networks.
- Highlights the importance of incorporating waiting time distributions for understanding anomalous diffusion.
- Suggests applicability to modeling other spreading phenomena in various network types.
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