Population mobility induced phase separation in SIS epidemic and social dynamics

Area of Science:

• Computational Epidemiology
• Mathematical Modeling
• Network Science

Background:

• Behavior-dependent mobility significantly impacts epidemic and social disorder spread.
• Existing models often lack dynamic adaptation to individual and network states.

Purpose of the Study:

• To develop a novel modeling approach for behavior-dependent mobility in epidemiological studies.
• To analyze the complex spatial patterns arising from dynamic mobility adaptations.
• To characterize phase transitions and determine phase diagrams for epidemic spread.

Main Methods:

• Dynamic modeling of mobility adapting to individual state, contagion state, and network topology.
• Analysis of compartmental network processes.
• Characterization of spatial patterns using phase separation and phase diagrams.

Main Results:

• Demonstrated complex spatial infection patterns in endemic states driven by individual behavior.
• Identified phase separation phenomena and distinct spatial states.
• Highlighted phase transitions influenced by population perceptions.

Conclusions:

• Behavior-dependent mobility modeling reveals critical insights into epidemic and social disorder dynamics.
• Small changes in population perception can drastically alter epidemic spatial extent and morphology.
• The developed model provides a framework for understanding complex contagion phenomena.