Face-to-face interactions of humans play a crucial role in social relationships as well as in the potential transmission of infectious diseases. Here we discuss recent research efforts and advances concerning the measure, analysis and modelling of such interactions measured using decentralised infrastructures based on wearable sensors. We present the empirical data, which takes the form of temporal networks, and novel techniques aimed at describing the data and at uncovering structures in these data. We describe recent modelling efforts and studies of spreading processes on temporal networks. We finally discuss several ways of practically using the data and how the issue of incomplete data can be tackled.
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