Ph. Vanhems Infectious disease spread on a data-driven dynamic contact network Authors: J. Stehle, N. Voirin, A. Barrat, C. Cattuto, V. Colizza, L. Isella, C. Regis, J.-F. Pinton, N. Khanafer, W. Van den Broeck, and Ph. Vanhems Abstract: The spread of infectious diseases depends on the pattern of contacts among individuals. Few empirical studies provide estimates of the number and duration of contacts among social groups and the dynamical aspect of the contacts is disregarded. We consider high resolution data of face-to-face interactions obtained from an infrastructure based on Radio Frequency Identification (RFID) devices that assess mutual face-to-face proximity. Simulated epidemics on the dynamical contacts network defined by the collected data are compared to epidemics evolving on static aggregated versions of the proximity network, in order to assess the role of high temporal resolution in the data. We show that a static network taking into account the duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation would fail in reproducing the size of the epidemic. These results have implications in informing computational models for the understanding and management of real epidemics.