Title |
Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics
|
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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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
New Zealand | 2 | 22% |
Spain | 1 | 11% |
United States | 1 | 11% |
Belgium | 1 | 11% |
Unknown | 4 | 44% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 44% |
Scientists | 3 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 11% |
Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
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% |