Invited commentary: Evaluating vaccination programs using genetic sequence data.
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.
Halloran
M Elizabeth
ME
Statistics and Quantitative Infectious Diseases, Seattle, WA 98109, USA. betz@u.washington.edu
Holmes
Edward C
EC
D000208:Acute Disease; D001483:Base Sequence; D001499:Bayes Theorem; D018563:Disease Notification; D014644:Genetic Variation; D006509:Hepatitis B / Q000453:epidemiology / Q000635:transmission / Q000821:virology*; D017325:Hepatitis B Vaccines; D006515:Hepatitis B virus / Q000235:genetics*; D018451:Homosexuality, Male; D006801:Humans; D008297:Male; D008969:Molecular Sequence Data; D009426:Netherlands; D015397:Program Evaluation
D017325:Hepatitis B Vaccines