Ciro Cattuto is presenting a review of our results in the workshop Temporal and Dynamic Networks: From Data to Models taking place on June 3-4, 2013 in Copenhagen, Denmark as a satellite of NetSci2013. Moreover, Laetitia Gauvin presented new results on “The activity-community structure of time-varying networks: A non-negative tensor factorization approach” in the workshop on Dynamic Information and Communication Networks 2013.

A book chapter by Alain Barrat and Ciro Cattuto was published in the new book on Temporal Networks edited by Petter Holme and Jari Saramäki.

Alain Barrat has presented the results of our recent paper “An infectious disease model on empirical networks of human contact: bridging the gap between dynamic network data and contact matrices” at the “Digital Epidemiology” workshop that took place at ISI Foundation, Turin, on May 30-31, 2013.

We have just published a new paper in BMC Infectious Diseases. We use SocioPatterns data collected in a hospital ward to ask which representations of contact data work best to inform models of disease spread. We show that the commonly used contact matrix representation fails to reproduce the size of the epidemic obtained using the high-resolution contact data and also fails to identify the most at-risk classes. We introduce a contact matrix of probability distributions that takes into account the heterogeneity of contact durations between (and within) classes of individuals, and we show that, in the case study presented, this representation yields a good approximation of the epidemic spreading properties obtained by using the high-resolution data.

A new manuscript describing research done using SocioPatterns data collected in two jointly organized conferences is available here.