Mining networks of human contacts: data, models and applications

Abstract:

Face-to-face contacts between individuals play an important role in social interactions and can also determine the potential transmission routes of infectious diseases, in particular of respiratory pathogens. An accurate description of these patterns is therefore of interest for the fundamental knowledge and understanding of human behaviour and social networks as well as in epidemiology, in order to identify contagion pathways, to inform models of epidemic spread, and to design and evaluate control measures such as the targeting of specific groups of individuals with appropriate prevention strategies or interventions.

In this talk, I will present results obtained by the SocioPatterns collaboration (www.sociopatterns.org), which focuses on measuring and modeling human contacts, and on using the gathered knowledge in fields such as social science or epidemiology. I will first describe the SocioPatterns sensing platform and some of the datasets collected in the last years. I will then discuss the issue of generalizing data through simple models of interactions between agents or through novel data representations. I will finally show how such datasets can be of use to investigate issues of interest in the epidemiology of infectious diseases, such as the relative efficiency of various mitigation measures such as the targeted closure of classes in schools or the closing of whole schools, in case of an epidemic spread.