Epidemic spreading on mixing group with face-to-face interaction.

This article focuses on modeling the dynamics of infectious disease spread within mixing groups—populations gathered in enclosed spaces engaging in face-to-face interactions—using a susceptible-infected-susceptible (SIS) agent-based model. The model incorporates a mixing matrix to represent group-specific interaction preferences and constructs an aggregated temporal contact network to capture the evolving face-to-face interactions over time. Theoretical analysis via mean-field theory and the next-generation matrix method reveals that both the relative sizes of groups and their intra- and inter-group mixing preferences significantly influence disease transmission dynamics: strong intra-group contact preferences tend to inhibit spread in balanced groups, while asymmetric mixing patterns and unbalanced group sizes can either restrain or facilitate transmission depending on the minority group's interaction tendencies. This framework provides a quantitative basis for understanding complex epidemic spreading phenomena in real-world scenarios such as schools or conferences where distinct groups interact face-to-face.