Abstract
This paper introduces a novel method to quantify sociality in human and animal populations and explores the connection between social behaviour and the spread of infectious disease. Individuals living in groups tend to distribute their social effort heterogeneously, with some group members receiving more attention than others. By incorporating this heterogeneity into a mathematical model, we find that a single parameter, which we name Social Fluidity, controls the level of social mixing in the population. We estimate the social fluidity of 51 empirical human and animal social systems using maximum likelihood techniques. An analytical formula that connects social fluidity to both the population size and the basic reproductive number of an infectious disease is derived and simulations of the spread of disease are performed. We find that social fluidity outperforms other network-based metrics in predicting the basic reproductive number of an infectious disease and that the effect of population size on disease transmission is insignificant compared to the effect of social fluidity.