Estimating the power of a Mycobacterium bovis vaccine trial in Irish badgers

I. Aznar, S.J. More, K. Frankena, M.C.M. de Jong

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)

Abstract

The aim of this study was to estimate the power, using simulation techniques, of a group randomized vaccine field trial designed to assess the effect of vaccination on Mycobacterium bovis transmission in badgers. The effects of sample size (recapture percentage), initial prevalence, sensitivity and specificity of the diagnostic test, transmission rate between unvaccinated badgers, Vaccine Efficacy for Susceptibility (VES) and Vaccine Efficacy for Infectiousness (VEI), on study power were determined. Sample size had a small effect on power. Study power increased with increasing transmission rate between non-vaccinated badgers. Changes in VES had a higher impact on power than changes in VEI. However, the largest effect on study power was associated with changes in the specificity of the diagnostic test, within the range of input values that were used for all other modelled parameters. Specificity values below 99.4% yielded a study power below 50% even when sensitivity was 100% and, VEI and VES were both equal to 80%. The effect of changes in sensitivity on study power was much lower. The results from our study are in line with previous studies, as study power was dependent not only on sample size but on many other variables. In this study, additional variables were studied, i.e. test sensitivity and specificity. In the current vaccine trial, power was highly dependent on the specificity of the diagnostic test. Therefore, it is critical that the diagnostic test used in the badger vaccine trial is optimized to maximize test specificity.
Original languageEnglish
Pages (from-to)297-303
JournalPreventive Veterinary Medicine
Volume111
Issue number3-4
DOIs
Publication statusPublished - 2013

Keywords

  • meles-meles
  • protective immunity
  • endobronchial inoculation
  • experimental tuberculosis
  • infection
  • design
  • bcg
  • challenge

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