Identifying Superspreaders for Epidemics Using R0-adjusted Network Centrality

Abstract

Identifying 'superspreaders' in a network is a key problem to designing an effective mitigation strategy against a spread of an epidemic disease. Superspreaders are a set of nodes that play a hub role in a disease spread network, and classical network centrality measures are often used to identify such hubs. In this research, we test a hypothesis that a node's intrinsic property plays a role in the dynamics of disease spreading in a network. Specifically, we test whether spreading of an epidemic disease is affected by a node's property of being an amplifier or attenuator. Using GEM (Global Epidemic Model), we conducted experiments for epidemic spreading on a hypothetical, global network of 155 cities. We find that node's intrinsic property plays a significant role in disease spreading dynamics. Based on these findings we propose a new metric, R0-adjusted centrality.