Fragmented social networks promote complex behavioural contagions over infectious disease spread

Abstract

Group living and social interactions among animals provide key benefits, such as the exchange of beneficial social information and novel behaviours, but also often pose the risk of spreading costly infectious diseases, presenting a social trade-off. While both behaviours and infections spread across social networks, they typically have distinct mechanisms of transmission. Here, we model social behaviour spread as a complex contagion governed by a conformist learning rule, while pathogen transmission follows a simple contagion mechanism. Building on theoretical foundations, our study applies computational models to examine how (sub)group structure (modularity) influences the spread of these contagions across diverse animal social structures sourced from the Animal Social Network Repository. Our findings reveal that high modularity and (sub)group structure slow simple contagion spread, whereas complex contagions are less impeded by this fragmentation but with a relatively small effect size compared with theoretical predictions. Consequently, our results suggest that social networks divided into small groups or subgroups can help balance the competing pressures of exploiting beneficial social information and avoiding infectious disease in real-world networks.