Exploiting temporal network structures of human interaction to effectively immunize populations.

PloS One
Sungmin LeePetter Holme

Abstract

Decreasing the number of people who must be vaccinated to immunize a community against an infectious disease could both save resources and decrease outbreak sizes. A key to reaching such a lower threshold of immunization is to find and vaccinate people who, through their behavior, are more likely than average to become infected and to spread the disease further. Fortunately, the very behavior that makes these people important to vaccinate can help us to localize them. Earlier studies have shown that one can use previous contacts to find people that are central in static contact networks. However, real contact patterns are not static. In this paper, we investigate if there is additional information in the temporal contact structure for vaccination protocols to exploit. We answer this affirmative by proposing two immunization methods that exploit temporal correlations and showing that these methods outperform a benchmark static-network protocol in four empirical contact datasets under various epidemic scenarios. Both methods rely only on obtainable, local information, and can be implemented in practice. For the datasets directly related to contact patterns of potential disease spreading (of sexually-transmitted and nosocomial inf...Continue Reading

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Citations

Apr 29, 2014·PloS One·Arkadiusz StopczynskiSune Lehmann
Jun 6, 2014·PloS One·Susan J LittleDavey M Smith
Feb 14, 2013·PloS One·Mario KonschakeThomas Selhorst
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Jul 23, 2013·Journal of Theoretical Biology·Michele StarniniRomualdo Pastor-Satorras
Jul 23, 2013·PLoS Computational Biology·Petter Holme
Mar 15, 2015·PloS One·Seunghyeon KimPan-Jun Kim
Mar 13, 2015·PLoS Computational Biology·Eugenio ValdanoVittoria Colizza
Apr 5, 2013·PLoS Computational Biology·Luis E C Rocha, Vincent D Blondel
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Sep 12, 2017·PLoS Computational Biology·Petter Holme, Nelly Litvak
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Jan 1, 2015·Frontiers of Computer Science·Wei DuanXiaogang Qiu
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