| Inferring epidemiological parameters on the basis of allele frequencies. | |
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MedLine Citation:
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PMID: 21546541 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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In this article, I develop a methodology for inferring the transmission rate and reproductive value of an epidemic on the basis of genotype data from a sample of infected hosts. The epidemic is modeled by a birth-death process describing the transmission dynamics in combination with an infinite-allele model describing the evolution of alleles. I provide a recursive formulation for the probability of the allele frequencies in a sample of hosts and a Bayesian framework for estimating transmission rates and reproductive values on the basis of observed allele frequencies. Using the Bayesian method, I reanalyze tuberculosis data from the United States. I estimate a net transmission rate of 0.19/year [0.13, 0.24] and a reproductive value of 1.02 [1.01, 1.04]. I demonstrate that the allele frequency probability under the birth-death model does not follow the well-known Ewens' sampling formula that holds under Kingman's coalescent. |
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Authors:
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Tanja Stadler |
Publication Detail:
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Type: Journal Article Date: 2011-05-05 |
Journal Detail:
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Title: Genetics Volume: 188 ISSN: 1943-2631 ISO Abbreviation: Genetics Publication Date: 2011 Jul |
Date Detail:
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Created Date: 2011-07-11 Completed Date: 2012-01-17 Revised Date: 2012-07-02 |
Medline Journal Info:
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Nlm Unique ID: 0374636 Medline TA: Genetics Country: United States |
Other Details:
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Languages: eng Pagination: 663-72 Citation Subset: IM |
Affiliation:
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Institut für Integrative Biologie, ETH Zürich, 8092 Zürich, Switzerland. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Alleles Bayes Theorem* Birth Rate Epidemics Gene Frequency Genetics, Population / methods*, statistics & numerical data Genotype Humans Models, Genetic Models, Theoretical Mutation Mycobacterium tuberculosis / growth & development Tuberculosis / genetics*, mortality, transmission United States / epidemiology |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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