Journal article
Integrating phylodynamics and epidemiology to estimate transmission diversity in viral epidemics
- Abstract:
- The epidemiology of chronic viral infections, such as those caused by Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV), is affected by the risk group structure of the infected population. Risk groups are defined by each of their members having acquired infection through a specific behavior. However, risk group definitions say little about the transmission potential of each infected individual. Variation in the number of secondary infections is extremely difficult to estimate for HCV and HIV but crucial in the design of efficient control interventions. Here we describe a novel method that combines epidemiological and population genetic approaches to estimate the variation in transmissibility of rapidly-evolving viral epidemics. We evaluate this method using a nationwide HCV epidemic and for the first time co-estimate viral generation times and superspreading events from a combination of molecular and epidemiological data. We anticipate that this integrated approach will form the basis of powerful tools for describing the transmission dynamics of chronic viral diseases, and for evaluating control strategies directed against them.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.1MB, Terms of use)
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- Publisher copy:
- 10.1371/journal.pcbi.1002876
Authors
- Publisher:
- Public Library of Science
- Journal:
- PLoS Computational Biology More from this journal
- Volume:
- 9
- Issue:
- 1
- Pages:
- ARTN e1002876
- Publication date:
- 2013-01-31
- Acceptance date:
- 2012-11-15
- DOI:
- EISSN:
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1553-7358
- ISSN:
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1553-734X
- Language:
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English
- Keywords:
- Pubs id:
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383170
- UUID:
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uuid:67798702-b402-44a4-8b96-8389dd54657d
- Local pid:
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pubs:383170
- Source identifiers:
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383170
- Deposit date:
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2013-11-16
- ARK identifier:
Terms of use
- Copyright holder:
- Magiorkinis et al
- Copyright date:
- 2013
- Notes:
- Copyright: © 2013 Magiorkinis et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Licence:
- CC Attribution (CC BY)
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