COS 178-8 - Disease implications of animal social organization and network structure: A quantitative analysis

Friday, August 11, 2017: 10:30 AM
D137, Oregon Convention Center
Pratha Sah and Shweta Bansal, Biology, Georgetown University, Washington, DC

Past studies examining the disease costs of sociality have generally explored hypotheses that link larger group size to higher rates of infection transmission. However, beyond a simple dependence on group size, infection spread is largely influenced by the organization of infection-spreading interactions between individuals. Network analysis tools have allowed for rapid advances in our understanding of the disease consequences of sociality at an individual scale, but studies on species level sociality are still lacking.

Here we conduct a comparative analysis of 666 interaction networks across 47 species to investigate the relationship between network complexity and the costs of disease transmission for four social systems – solitary, fission-fusion, social and socially hierarchical. Specifically, we use phylogenetically-controlled Bayesian MCMC modelling and in-silico disease simulations to identify the relative costs of disease transmission for each social system as mediated by their network structure. Because group sizes are inherently dynamic in nature, we also determine how pathogen transmission scales across groups of different social systems by comparing their behavioral response towards increasing group size.


We find that solitary, fission-fusion, and higher social organizations can be distinguished from each other based on (a) degree of variation among social partners, (b) the extent to which the interaction network is fragmented and (c) the proportion of individuals that occupy socially central positions within the interaction networks. In particular, individuals of solitary species demonstrate the highest variation in the number of social partners, while the interaction networks of fission-fusion species are the most fragmented. The results of disease simulations show that the structure of interaction networks can alleviate the disease costs of group living for social, but not socially hierarchical species. We also find clear behavioral differences between the four social systems towards increasing group size. Socially hierarchical species maintain network connectivity with increasing group size, whereas non-hierarchical social species reduce effort towards each pairwise interaction when engaging with new social partners. Consequently, our results suggest that density-dependent transmission models can be used for socially hierarchical species irrespective of pathogen transmission mode, but not for other social or solitary species. In conclusion, our findings offer new perspectives on the debate about the disease costs of group living by evaluating how social organization strategies mediate pathogen pressures.