Adaptive dynamic social networks using an agent-based model to study the role of social awareness in infectious disease spread

Abstract

The synergy between the spread of infectious diseases, individual behavior, and group dynamics is widely recognized by epidemiologists and researchers. Our pioneering methodology introduces a model based on agents embedded within adaptive temporal networks, providing a nuanced portrayal of daily interactions through an agent-based paradigm. Each agent encapsulates the interactions of individuals, with external stimuli and environmental cues influencing their behavior. Comprising three intertwined elements — individual behavior, social dynamics, and epidemiological factors — the model has been validated against real-world influenza outbreaks, demonstrating superior performance compared to traditional methodologies. Our framework exhibits extensive versatility and applicability by encapsulating individual-level dynamics through elementary rules and simulating complex social behaviors such as social consciousness.