Infectious disease control using contact tracing in random and scale-free networks

Area of Science:

• Epidemiology
• Network Science
• Computational Biology

Background:

• Contact tracing is crucial for infectious disease control.
• Network structure significantly impacts epidemic spread and control strategies.
• Scale-free networks exhibit distinct properties influencing disease dynamics.

Purpose of the Study:

• To compare the efficacy of contact tracing on random and scale-free (SF) networks.
• To investigate the impact of tracing hierarchy (prioritizing high-degree nodes) on epidemic control.
• To analyze epidemic size, spread dynamics, and required tracing effort across different network types.

Main Methods:

• Simulated epidemic spread on random and SF networks with identical node count (N) and average connectivity (K).
• Investigated the effect of prioritizing high-degree nodes in contact tracing.
• Analyzed epidemic size, node degrees at different disease stages, and tracing effort.

Main Results:

• SF networks showed smaller final epidemic sizes than random networks above a transmission threshold.
• On SF networks, advanced disease stages concentrated in high-degree nodes.
• Higher tracing effort was needed for SF networks due to rapid initial spread to hubs.
• Increased latency period did not significantly enhance tracing efficacy.
• Contact tracing efficacy decreased with high susceptible node removal rates.

Conclusions:

• Contact tracing on SF networks removes high-risk infection sources but requires greater effort for control.
• Network topology critically influences contact tracing effectiveness.
• The strategy of tracing high-degree nodes is effective but resource-intensive on SF networks.