Behaviour 2019
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The relative spread of infectious disease and information in group-living societies
Matthew Silk1, Julian Evans2, Neeltje Boogert3, David Hodgson3. 1NIMBioS, University of Tennessee, Knoxville, , United States; 2University of Zurich, Zurich, , Switzerland; 3University of Exeter, Penryn, , United Kingdom

Social interactions provide opportunities for gaining beneficial information, yet interacting with others can also risk infection with pathogens or parasites. Many animals live in social groups, and theoretical models have suggested that group/modular structure in social networks can impact how infection and information spread in different ways. Modular structure in networks slows the spread of infectious disease but does not necessarily impact the diffusion of information, especially when it is spread by a complex contagion. I will present results from a model that explores how both group size and the likelihood of individuals from different groups interacting (network modularity) influence the relative speed with which infection and information (via conformist social learning) can spread through a population. The findings have important implications for understanding the types of social structures that can maximise the informational benefits of sociality while minimising the costs imposed by infectious disease.