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Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics

Overview of attention for article published in PLoS Computational Biology, January 2013
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Title
Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics
Published in
PLoS Computational Biology, January 2013
DOI 10.1371/journal.pcbi.1002876
Pubmed ID
Authors

Gkikas Magiorkinis, Vana Sypsa, Emmanouil Magiorkinis, Dimitrios Paraskevis, Antigoni Katsoulidou, Robert Belshaw, Christophe Fraser, Oliver George Pybus, Angelos Hatzakis

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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 171 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 4%
United Kingdom 5 3%
Brazil 2 1%
Kenya 1 <1%
Uruguay 1 <1%
Portugal 1 <1%
Belgium 1 <1%
Netherlands 1 <1%
Venezuela, Bolivarian Republic of 1 <1%
Other 1 <1%
Unknown 150 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 48 28%
Student > Ph. D. Student 40 23%
Student > Master 17 10%
Student > Bachelor 15 9%
Professor 9 5%
Other 26 15%
Unknown 16 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 61 36%
Medicine and Dentistry 36 21%
Biochemistry, Genetics and Molecular Biology 11 6%
Mathematics 9 5%
Immunology and Microbiology 7 4%
Other 17 10%
Unknown 30 18%