title: Individual-based approach to epidemic processes on arbitrary dynamic contact networks.
abstract: The dynamics of contact networks and epidemics of infectious diseases often occur on comparable time scales. Ignoring one of these time scales may provide an incomplete understanding of the population dynamics of the infection process. We develop an individual-based approximation for the susceptible-infected-recovered epidemic model applicable to arbitrary dynamic networks. Our framework provides, at the individual-level, the probability flow over time associated with the infection dynamics. This computationally efficient framework discards the correlation between the states of different nodes, yet provides accurate results in approximating direct numerical simulations. It naturally captures the temporal heterogeneities and correlations of contact sequences, fundamental ingredients regulating the timing and size of an epidemic outbreak, and the number of secondary infections. The high accuracy of our approximation further allows us to detect the index individual of an epidemic outbreak in real-life network data.
authors: Department of Mathematics and naXys, Université de Namur, 8 Rempart de la Vierge, B-5000 Namur, Belgium.|Department of Public Health Sciences, Karolinska Institutet, 18A Tomtebodavägen, S-17177 Stockholm, Sweden.
authors: Luis E C
authors: LE
authors: Rocha
authors: Department of Engineering Mathematics, University of Bristol, Woodland Road, Bristol BS8 1UB, United Kingdom.
authors: Naoki
authors: N
authors: Masuda