Suppression of epidemic spreading process on multiplex networks via active immunization

Area of Science:

• Complex Systems Science
• Epidemiology
• Network Science

Background:

• Spatial epidemic spreading on complex networks is a significant research area.
• Traditional node vaccination is a passive control method.
• Active surveillance mechanisms are needed for efficient epidemic suppression.

Purpose of the Study:

• To propose a novel observer node model for active epidemic control on multiplex networks.
• To investigate the effectiveness of different observer node placement strategies.
• To enhance epidemic suppression through informed vaccination decisions.

Main Methods:

• Developed a multiplex network model with separate epidemic and information spreading layers.
• Implemented an observer node strategy that identifies infections and triggers vaccinations.
• Utilized percolation theory-based algorithms for selecting observer node locations.
• Performed numerical simulations to evaluate control strategies.

Main Results:

• Observer nodes based on high degree in the information layer significantly improve epidemic suppression.
• This active strategy outperforms random placement and strategies based on the epidemic layer degree.
• State probability transition equations accurately validate simulation findings.

Conclusions:

• The proposed observer node model offers an effective active strategy for epidemic control.
• Optimizing observer node placement in the information layer is crucial for maximizing suppression efficacy.
• This research provides insights for developing advanced, real-world epidemic control strategies.