Network Reconstruction and Prediction of Epidemic Outbreaks for NIMFA Processes
Physics and Society
2018-11-19 v1 Dynamical Systems
Abstract
Predicting the viral dynamics of an epidemic process requires the knowledge of the underlying contact network. However, the network is not known for most applications and has to be inferred from observing the viral state evolution instead. We propose a polynomial-time network reconstruction algorithm for the discrete-time NIMFA model based on a basis pursuit formulation. Given only few initial viral state observations, the network reconstruction method allows for an accurate prediction of the further viral state evolution of every node provided that the network is sufficiently sparse.
Keywords
Cite
@article{arxiv.1811.06741,
title = {Network Reconstruction and Prediction of Epidemic Outbreaks for NIMFA Processes},
author = {Bastian Prasse and Piet Van Mieghem},
journal= {arXiv preprint arXiv:1811.06741},
year = {2018}
}