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Updated: Aug 12, 2026
16:14
Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
Traffic-driven sequential spread of two interacting epidemics on complex networks
Xing-Li Jing1,2, Mao-Bin Hu3, Ming Tang4
1School of Traffic and Transportation, Shijiazhuang Tiedao University, Shijiazhuang 050043, People's Republic of China.
Chaos (Woodbury, N.Y.)
|August 11, 2026
Summary
This study models sequential epidemics on traffic networks, revealing how prior infection impacts susceptibility to a second disease. The interaction between diseases and traffic flow critically influences outbreak thresholds and spread dynamics.
Area of Science:
- Complex Networks
- Epidemiology
- Traffic Dynamics
Background:
- Previous research on epidemic spreading on complex networks primarily focused on single-pathogen transmission.
- The interplay between traffic dynamics and epidemic spreading is crucial but underexplored for multiple interacting diseases.
Purpose of the Study:
- To investigate the sequential spreading dynamics of two interacting epidemics influenced by traffic flow.
- To analyze how prior infection with one disease affects susceptibility to a subsequent disease.
- To develop a theoretical framework for understanding coupled contagion processes.
Main Methods:
- Development of a heterogeneous mean-field framework for coupled epidemic spreading.
- Derivation of analytical expressions for epidemic thresholds.
- Numerical simulations to validate theoretical predictions across various network structures.
Main Results:
- The interaction parameter (α) and the first epidemic's infection rate (β1) jointly control the second epidemic's outbreak threshold and prevalence.
- Prior infection can suppress (α<1), neutralize (α=1), or synergize (α>1) susceptibility to the second disease.
- Nonlinear threshold responses were observed, with significant increases or decreases in the second epidemic's threshold depending on the interaction regime.
Conclusions:
- Epidemic interactions and network structure are key determinants of sequential spreading dynamics in traffic-driven systems.
- Findings provide novel insights into coupled contagion processes on complex networks.
- The study highlights the importance of considering disease interactions in epidemic modeling.
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