The basic reproduction number as a predictor for epidemic outbreaks in temporal networks

Abstract

The basic reproduction number R0 -- the number of individuals directly infected by an infectious person in an otherwise susceptible population -- is arguably the most widely used estimator of how severe an epidemic outbreak can be. This severity can be more directly measured as the fraction people infected once the outbreak is over, Ω. In traditional mathematical epidemiology and common formulations of static network epidemiology, there is a deterministic relationship between R0 and Ω. However, if one considers disease spreading on a temporal contact network -- where one knows when contacts happen, not only between whom -- then larger R0 does not necessarily imply larger Ω. In this paper, we numerically investigate the relationship between R0 and Ω for a set of empirical temporal networks of human contacts. Among 31 explanatory descriptors of temporal network structure, we identify those that make R0 an imperfect predictor of Ω. We find that descriptors related to both temporal and topological aspects affect the relationship between R0 and Ω, but in different ways.

References in corpus (10)

• What's in a crowd? Analysis of face-to-face behavioral networks
• Small But Slow World: How Network Topology and Burstiness Slow Down Spreading
• Information dynamics shape the networks of Internet-mediated prostitution
• Structure and Time-Evolution of an Internet Dating Community
• Temporal Heterogeneities Increase the Prevalence of Epidemics on Evolving Networks
• Clustering in complex networks. II. Percolation properties
• Spreading Dynamics Following Bursty Human Activity Patterns
• Predicting epidemic risk from past temporal contact data
• Contagion dynamics in time-varying metapopulation networks
• Structural differences between open and direct communication in an online community

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