Project description
Understanding the process of spreading
Social movement is a major contributor of epidemic spreading and can abruptly lead to avalanche outbreaks and global pandemics. The EU-funded CAOS project will go beyond asymptotic analysis and focus on the interplay between topology and dynamics of various spreading processes. The main objective is to develop methods for the identification of abrupt transitions and understand the conditions for the onset of pandemics. Researchers will also deploy various strategies to contain such outbreaks, such as the application of vaccines, reducing contact and lowering the infection rates. The development of new algorithms will provide important scientific knowledge on non-equilibrium spreading processes and support policymaking decisions.
Objective
Spreading processes, such as cascading failure of technological networks, epidemic outbreak and contagion in social
networks are ubiquitous and have a significant impact on the modern society. In many cases, transitions to large-scale
blackouts or global pandemics occur abruptly due to tiny changes in system parameters; epidemics and social movements
can spread out explosively, forming avalanche-like outbreaks in a very short period. The drastic transitions are beneficial for
making global impact of boosting charity campaigns and commercial advertising but can also have catastrophic
consequences when epidemics or failures spread to large part of a critical systems abruptly, without any early warning
signals. Moreover, multiple cooperative of competitive spreading processes make the picture even more complex.
Previous work in this area focused on the asymptotic manifestation of the process and typically ignored the interplay
between specific system topology and the dynamics. Methods to monitor, identify and control drastic transitions and
outbreaks in heterogeneous realistic networks are lacking. In this project, we will investigate the signs for abrupt transitions
and avalanche outbreaks both macroscopically and in specific instances, to gain insight into the conditions for their onset.
We will develop methods to contain (or facilitate) the outbreaks by optimal deployment of resources, such as applying
vaccines or distributing promotion material by employing the recently developed dynamic message passing techniques from
statistical physics. We will collaborate with British Telecom to promote product marketing and service provision by using the
new optimisation algorithms. This project will have significant impact on the scientific understanding of non-equilibrium
spreading processes, provide algorithmic solutions for practical problems in specific instances, will support policy making
decisions and offer optimal resource allocation for commercial marketing tasks.
Fields of science
Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EFCoordinator
B4 7ET Birmingham
United Kingdom