Université de Strasbourg

Social networks, information and disease

Social networks as a trade-off between optimal decision-making, information transmission and reduced disease transmission

USIAS Fellow: Cédric Sueur

Although living in groups has many advantages, it also involves certain disadvantages such as increased disease transmission and the need to make collective decisions. In theory, the social network properties optimizing decision accuracy and the spreading of information should also increase the disease transmission rate, creating a trade-off between decision-making efficiency and infection risk. We aim to explore this trade-off by examining social network properties and investigating how they might interact to maximize decision accuracy and minimize infection risk. We propose an evaluation of this trade-off in insects and non-human primates using both experimental and theoretical approaches.

The project is innovative and multidisciplinary because it: (1) compares information versus disease transmission; (2) uses insect and primate models; (3) combines observation and experimentation with modelling. Our approach is designed to highlight mechanisms underlying decision accuracy and disease transmission, with social networks reflecting a trade-off between these variables. In particular, although information and disease flow networks have been independently studied before, this study aims to directly investigate the costs and benefits of social networks for a specific optimization of this trade-off in diverse species groups. This work thus extends previous pioneer projects into revolutionary new areas.


Investissements d'Avenir