Abstract # 32:

Scheduled for Thursday, June 18, 2015 02:30 PM-02:50 PM: (Cascade AJBCD) Oral Presentation


C. M. McCabe1, F. Jordán2,3 and C. L. Nunn4
1Harvard University, 11 Divinity Ave., Department of Human Evolutionary Biology, Cambridge, Massachusetts 02138, USA, 2The Microsoft Research - University of Trento COSBI, 3Balaton Limnological Institute, 4Duke University
     Living in larger, more complex social groups is assumed to increase disease risk in primates, yet empirical evidence is mixed on how group size or structure influence disease dynamics. We studied the networks of 42 primate social groups of varying size to test whether larger social groups displayed quantitatively different network structures than smaller ones, specifically through subdivisioning. If so, the social subdivisions that form in larger groups may act as barriers to the spread of infection, weakening the association between group size and infectious disease. To investigate this “social bottleneck” hypothesis, we examined the association between group size and four network structure metrics: modularity, clustering, distance, and centralization. Over a large set of PGLS results investigating these metrics, modularity showed positive associations with group size, which was further supported in a meta-analysis of intraspecific variation among certain primate, as well as other mammal, reptile, and invertebrate species. We then used a theoretical model to introduce the effects of subgrouping to those of other factors that influence disease spread in socially structured populations. In this model, outbreaks reached higher prevalence when groups were larger, but subgrouping balanced this effect, reducing prevalence. Subgrouping also decreased the spread of disease from the index subgroup to other subgroups. Building on these theoretical and modeling results, we present suggestions for revising the relationship between group size and disease spread.