Predicting epidemic outbreak from individual features of the spreaders

Physics – Physics and Society

Scientific paper

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8 pages, 5 figures

Scientific paper

Knowing which individuals can be more efficient in spreading a pathogen throughout a determinate environment is a fundamental question in disease control. Indeed, over the last years the spread of epidemic diseases and its relationship with the topology of the involved system have been a recurrent topic in complex network theory, taking into account both network models and real-world data. In this paper we explore possible correlations between the heterogeneous spread of an epidemic disease governed by the susceptible-infected-recovered (SIR) model, and several attributes of the originating vertices, considering Erd\"os-R\'enyi (ER), Barab\'asi-Albert (BA) and random geometric graphs (RGG), as well as a real case of study, the US Air Transportation Network that comprises the US 500 busiest airports along with inter-connections. Among both the theoretical and the real networks considered, we observe high correlation between the total epidemic prevalence and the degree, the strength and the accessibility of the epidemic sources. For attributes such as the betweenness centrality and the k-shell index, however, the correlation depends on the topology considered.

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