Link operations for slowing the spread of disease in complex networks

Bishop, AN; Shames, I

Link operations for slowing the spread of disease in complex networks

Bishop, AN

Shames, I

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Publication Type:: Journal Article
Citation:: EPL, 2011, 95 (1)
Issue Date:: 2011-07-01

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Field	Value	Language
dc.contributor.author	Bishop, AN https://orcid.org/0000-0001-8581-8562	en_US
dc.contributor.author	Shames, I	en_US
dc.date.issued	2011-07-01	en_US
dc.identifier.citation	EPL, 2011, 95 (1)	en_US
dc.identifier.issn	0295-5075	en_US
dc.identifier.uri	http://hdl.handle.net/10453/108755
dc.description.abstract	A variety of social, biological and communication networks can be modelled using graph theoretical tools. Similar graphical tools can be used to model the topology by which disease, errors, and/or other undesired phenomenon etc. is spread and propagated through such networks. Certain network operations are proposed in this work that can be used to slow the spread of diseases in complex network topologies. The approach considered in this work differs from existing techniques in that it is based on optimally removing (or immunizing) individual links in the network as opposed to individual nodes. A systematic algorithm is outlined to achieve this edgewise immunization via a relaxed convex optimization protocol. Copyright © 2011 EPLA.	en_US
dc.relation.ispartof	EPL	en_US
dc.relation.isbasedon	10.1209/0295-5075/95/18005	en_US
dc.subject.classification	Fluids & Plasmas	en_US
dc.title	Link operations for slowing the spread of disease in complex networks	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	95	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	02 Physical Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	95	en_US

Abstract:

A variety of social, biological and communication networks can be modelled using graph theoretical tools. Similar graphical tools can be used to model the topology by which disease, errors, and/or other undesired phenomenon etc. is spread and propagated through such networks. Certain network operations are proposed in this work that can be used to slow the spread of diseases in complex network topologies. The approach considered in this work differs from existing techniques in that it is based on optimally removing (or immunizing) individual links in the network as opposed to individual nodes. A systematic algorithm is outlined to achieve this edgewise immunization via a relaxed convex optimization protocol. Copyright © 2011 EPLA.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/108755