A Comparative Study of Temporal and Static Networks in Modeling Pathogen Transmission within School Environments

In the domain of epidemiology and infectious disease control, understanding the dynamics of pathogen transmission is crucial. This study shows the dynamics of pathogen spread in school environments by comparing two distinct network models: temporal networks and static networks. The objective is to assess their respective effectiveness in modeling the transmission of pathogens within school settings. Temporal networks take into account the evolving nature of social interactions over time, offering a more realistic representation of human contact patterns. In contrast, static networks provide a simplified but stable view of social connections. This research investigates how these two modeling approaches impact our ability to analyze, and control the spread of pathogens, such as viruses, in school environments. We Propose T-GSI (Temporal Global Structure Influence) to measure the influence of the temporal networks, which outperformed the state-of-the-art methods. Our findings reveal the strengths and weaknesses of temporal and static networks in capturing the influence of pathogen transmission within school communities.