CSH Talk by Eugenio Valdano: “The spread of diseases on time-evolving networks”

Join us for a talk “The spread of diseases on time-evolving networks: from models to data and back” by Eugenio Valdano from Universitat Rovira i Virgili on May 19 at 2:15 pm in seminar room 101 at the Hub.

Abstract:

A wide range of physical, social and biological phenomena can be expressed in terms of spreading processes on networked systems. Notable examples include the spread of infectious diseases through direct contacts, the spatial propagation of epidemics driven by mobility networks, the spread of cyber worms along computer connections, or the diffusion of ideas mediated by social interactions. All these phenomena arise from a complex interplay between the spreading process and the network’s underlying topology and dynamics. Understanding how the time-evolving properties of the network impact the spread of the disease is a crucial step to setting up control and prevention strategies.

The increasing availability of highly-resolved interaction data has made it possible to target a wide variety of settings and diseases, but at the same time new methodological challenges have arisen. In particular, a fundamental property of such phenomena is the presence of an epidemic threshold, i.e., a critical transmission probability above which large-scale propagation occurs, as opposed to quick extinction of the epidemic-like process. Computing this threshold is of utmost importance for epidemic containment and control of information diffusion.

I will present a new analytical framework for the computation of the epidemic threshold for an arbitrary time-varying network. By reinterpreting the tensor formalism of multi-layer networks, this framework allows the analytical calculation of the epidemic threshold, without making any assumption on contact structure and evolution, and can be applied to a wide class of diseases. Along these theoretical developments, challenges related to the analysis and elaboration of the increased amount of data have emerged. I will present the case of diseases affecting farmed cattle. Such diseases compromise both human and animal health and welfare, and represent a major cause of loss in economic revenue. As a result, studying the networks of animal movements is a key step in devising new prevention and containment strategies. Past works have already analyzed cattle networks in several European countries. A comprehensive study, showing the impact of country-specific driving factors on network evolution and topology, is however still missing. I will present a collaborative platform for analyzing and comparing networks from several European countries. Using a bring code to the data approach, our platform overcomes the strict regulations preventing data sharing, and allows an effective comparative analysis. I will describe the framework, and present the result of this analysis, highlighting both properties that are characteristic of livestock markets, and country-specific features.