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Epidemic spreading in time-varying community networks
Guangming Ren1, Xingyuan Wang2
1School of Electronic & Information, Guangdong Polytechnic Normal University, Guangzhou 510665, China.
Chaos (Woodbury, N.Y.)
|July 3, 2014
Summary
Epidemic spreading in networks with evolving communities depends on individual mobility. A critical mobility rate threshold determines if an infectious disease will spread or die out.
Area of Science:
- Epidemiology
- Network Science
- Mathematical Biology
Background:
- Infectious disease spread occurs on dynamic networks.
- Network evolution and disease spreading share similar timescales.
Purpose of the Study:
- To model epidemic spreading in networks with time-varying community structures.
- To analyze the impact of individual mobility on disease transmission.
Main Methods:
- Developed a simple network model with dynamic community structure.
- Investigated susceptible-infected-susceptible (SIS) epidemic spreading.
- Employed theoretical analysis and numerical simulations.
Main Results:
- Epidemic spreading efficiency is highly sensitive to individual mobility rates (q).
- A critical mobility rate threshold (qc) was identified.
- Disease survival is contingent on mobility: q > qc leads to spread, q < qc leads to extinction.
Conclusions:
- Individual mobility significantly influences epidemic dynamics in evolving networks.
- The identified mobility threshold provides a key parameter for predicting disease spread.
- Findings aid in understanding the role of human travel in disease transmission within complex networks.
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