Alessandro Vespignani

TL;DR: A dynamical model for the spreading of infections on scale-free networks is defined, finding the absence of an epidemic threshold and its associated critical behavior and this new epidemiological framework rationalizes data of computer viruses and could help in the understanding of other spreading phenomena on communication and social networks.

TL;DR: This work studies the scientific collaboration network and the world-wide air-transportation network, which are representative examples of social and large infrastructure systems, respectively, and defines appropriate metrics combining weighted and topological observables that enable it to characterize the complex statistical properties and heterogeneity of the actual strength of edges and vertices.

TL;DR: A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear.

TL;DR: The results suggest that early detection, hand washing, self-isolation, and household quarantine will likely be more effective than travel restrictions at mitigating this pandemic, and sustained 90% travel restrictions to and from mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.

TL;DR: Real-time mobility data from Wuhan and detailed case data including travel history are used to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures.