Beyond ranking nodes: Predicting epidemic outbreak sizes by network centralities.

ABSTRACT: Identifying important nodes for disease spreading is a central topic in network epidemiology. We investigate how well the position of a node, characterized by standard network measures, can predict its epidemiological importance in any graph of a given number of nodes. This is in contrast to other studies that deal with the easier prediction problem of ranking nodes by their epidemic importance in given graphs. As a benchmark for epidemic importance, we calculate the exact expected outbreak size given a node as the source. We study exhaustively all graphs of a given size, so do not restrict ourselves to certain generative models for graphs, nor to graph data sets. Due to the large number of possible nonisomorphic graphs of a fixed size, we are limited to ten-node graphs. We find that combi

SUBMITTER: Bucur D 

PROVIDER: S-EPMC7398553 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature