Linked Life Data

19910381

Source:http://linkedlifedata.com/resource/pubmed/id/19910381

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2009-12-7
pubmed:abstractText
Genomic data will become an increasingly important component of epidemiologic studies in coming years. The authors of the accompanying Journal article, van Ballegooijen et al. (Am J Epidemiol. 2009;170(12):1455-1463), are to be commended for attempting to use the coalescent analysis of viral sequence data to evaluate a hepatitis B vaccination program. Coalescent theory attempts to link the phylogenetic history of populations with rates of population growth and decline. In particular, under certain assumptions, a reduction in genetic diversity can be interpreted as a reduction in disease incidence. However, the authors of this commentary contend that van Ballegooijen et al.'s interpretation of changes in viral genetic diversity as a measure of hepatitis B vaccine effectiveness has major limitations. Because of the potential use of these methods in future vaccination studies, the authors discuss the utility of these methods and the data requirements needed for them to be convincing. First, data sets should be large enough to provide sufficient epidemiologic-scale resolution. Second, data need to reflect sufficiently fine-grained temporal sampling. Third, other processes that can potentially influence genetic diversity and confuse demographic inferences should be considered.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1476-6256
pubmed:author
pubmed:issnType
Electronic
pubmed:day
15
pubmed:volume
170
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1464-6; discussion 1467-8
pubmed:dateRevised
2010-12-16
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Invited commentary: Evaluating vaccination programs using genetic sequence data.
pubmed:affiliation
Statistics and Quantitative Infectious Diseases, Seattle, WA 98109, USA. betz@u.washington.edu
pubmed:publicationType
Journal Article, Comment, Research Support, N.I.H., Extramural