Statistical power and estimation of incidence rate ratios obtained from BED incidence testing for evaluating HIV interventions among young people

PLoS One. 2011;6(8):e21149. doi: 10.1371/journal.pone.0021149. Epub 2011 Aug 10.


Background: The objectives of this study were to determine the capacity of BED incidence testing to a) estimate the effect of a HIV prevention intervention and b) provide adequate statistical power, when used among young people from sub-Saharan African settings with high HIV incidence rates.

Methods: Firstly, after having elaborated plausible scenarios based on empirical data and the characteristics of the BED HIV-1 Capture EIA (BED) assay, we conducted statistical calculations to determine the BED theoretical power and HIV incidence rate ratio (IRR) associated with an intervention when using BED incidence testing. Secondly, we simulated a cross-sectional study conducted in a population among whom an HIV intervention was rolled out. Simulated data were analyzed using a log-linear Poisson model to recalculate the IRR and its confidence interval, and estimate the BED practical power. Calculations were conducted with and without corrections for misclassifications.

Results: Calculations showed that BED incidence testing can yield a BED theoretical power of 75% or more of the power that can be obtained in a classical cohort study conducted over a duration equal to the BED window period. Statistical analyses using simulated populations showed that the effect of a prevention intervention can be estimated with precision using classical statistical analysis of BED incidence testing data, even with an imprecise knowledge of the characteristics of the BED assay. The BED practical power was lower but of the same magnitude as the BED theoretical power.

Conclusions: BED incidence testing can be applied to reasonably small samples to achieve good statistical power when used among young people to estimate IRR.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Africa South of the Sahara / epidemiology
  • Age Distribution
  • Circumcision, Male
  • Computer Simulation
  • Follow-Up Studies
  • HIV Infections / blood
  • HIV Infections / epidemiology*
  • HIV Infections / prevention & control*
  • Humans
  • Immunoenzyme Techniques / methods*
  • Incidence
  • Intention to Treat Analysis
  • Male
  • Models, Statistical*
  • Prevalence
  • Regression Analysis
  • Young Adult