Rocha, Luis E. C. ORCID: https://orcid.org/0000-0001-9046-8739 and Masuda, Naoki (2016) Individual-based approach to epidemic processes on arbitrary dynamic contact networks. Scientific Reports, 6 (1):31456. ISSN 2045-2322 (Print), 1475-2743 (Online) (doi:10.1038/srep31456)

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Abstract

The dynamics of contact networks and epidemics of infectious diseases often occur on comparable time scales. Ignoring one of these time scales may provide an incomplete understanding of the population dynamics of the infection process. We develop an individual-based approximation for the susceptible-infected-recovered epidemic model applicable to arbitrary dynamic networks. Our framework provides, at the individual-level, the probability flow over time associated with the infection dynamics. This computationally efficient framework discards the correlation between the states of different nodes, yet provides accurate results in approximating direct numerical simulations. It naturally captures the temporal heterogeneities and correlations of contact sequences, fundamental ingredients regulating the timing and size of an epidemic outbreak, and the number of secondary infections. The high accuracy of our approximation further allows us to detect the index individual of an epidemic outbreak in real-life network data.

Item Type:	Article
Additional Information:	© The Author(s) 2016. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Uncontrolled Keywords:	Individual-based model, temporal networks, numerical methods
Subjects:	Q Science > QC Physics
Faculty / School / Research Centre / Research Group:	Faculty of Business Faculty of Business > Networks and Urban Systems Centre (NUSC) > Centre for Business Network Analysis (CBNA) Faculty of Business > Department of International Business & Economics
Last Modified:	08 May 2019 23:25
URI:	http://gala.gre.ac.uk/id/eprint/19630

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