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The Timing and Targeting of Treatment in Influenza Pandemics Influences the Emergence of Resistance in Structured Populations


Abstract Antiviral resistance in influenza is rampant and has the possibility of causing major morbidity and mortality. Previous models have identified treatment regimes to minimize total infections and keep resistance low. However, the bulk of these studies have ignored stochasticity and heterogeneous contact structures. Here we develop a network model of influenza transmission with treatment and resistance, and present both standard mean-field approximations as well as simulated dynamics. We find differences in the final epidemic sizes for identical transmission parameters (bistability) leading to different optimal treatment timing depending on the number initially infected. We also find, contrary to previous results, that treatment targeted by nu... (more)
Created Date 2013-02-07
Contributor Althouse, Benjamin M. (Author) / Patterson-Lomba, Oscar (ASU author) / Goerg, Georg M. (Author) / Hebert-Dufresne, Laurent (Author) / School of Human Evolution and Social Change / Simon M. Levin Mathematical, Computational and Modeling Sciences Center / College of Liberal Arts and Sciences
Series PLOS COMPUTATIONAL BIOLOGY
Type Text
Extent 6 pages
Language English
Identifier DOI: 10.1371/journal.pcbi.1002912 / ISSN: 1553-734X / ISSN: 1553-7358
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Citation Althouse, B. M., Patterson-Lomba, O., Goerg, G. M., & Hébert-Dufresne, L. (2013). The Timing and Targeting of Treatment in Influenza Pandemics Influences the Emergence of Resistance in Structured Populations. PLoS Computational Biology, 9(2). doi:10.1371/journal.pcbi.1002912
Note The article is published at http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002912
Collaborating Institutions ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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