Contagion-diffusion processes with recurrent mobility patterns of distinguishable agents

Area of Science:

• Epidemiology
• Mathematical Modeling
• Urban Dynamics

Background:

• Metapopulation models are crucial for understanding disease spread influenced by mobility.
• Current models often simplify agents as indistinguishable, potentially affecting accuracy.
• Urban epidemics are complex, influenced by agent distribution and movement patterns.

Purpose of the Study:

• To investigate the impact of distinguishable agents and recurrent mobility on epidemic trajectories in urban areas.
• To develop a model that accounts for agent residence and destination.
• To analytically calculate the epidemic threshold considering agent heterogeneity.

Main Methods:

• Developed a metapopulation model incorporating distinguishable agents based on residence and destination.
• Utilized agent-based modeling for spatiotemporal epidemic pattern computation.
• Employed spectral radius calculation of a mixing matrix to determine the epidemic threshold.

Main Results:

• The model enables fast computation of epidemic spatiotemporal patterns.
• The epidemic threshold is analytically derived from agent distribution and commuting patterns.
• Agent indistinguishability leads to an overestimation of the epidemic threshold.

Conclusions:

• Distinguishable agents and specific mobility patterns significantly influence epidemic dynamics.
• The proposed model provides a more accurate assessment of epidemic thresholds in urban settings.
• Accounting for agent heterogeneity is essential for realistic disease spread analysis.