Laeyendecker, O., Kulich, M., Donnell, D., et al. PLOS One (November 2013), Vol. 8 No. 11, p. e78818.
The authors described the development of laboratory and statistical methods used to estimate HIV incidence in Project Accept, a Phase III community randomized controlled trial in Africa and Thailand. They focused on identifying a multiple-assay algorithm (MAA) to estimate HIV incidence in the trial’s African communities, using validation samples from seven cohorts (4,166 samples from approximately 2,300 individuals; subtype D samples were removed). Findings demonstrated that HIV incidence and intervention effects can be accurately estimated using MAA in cross-sectional surveys. In total, 403 MAAs were evaluated, including the BED capture immunoassay (BED-CEIA) alone, an avidity assay alone, and combinations of these assays with various cutoff values and without CD4 or viral load testing on samples. Testing algorithms that included multiple assays outperformed single serologic assays; incidence estimates had lower bias and better precision. Epidemic simulation exercises were conducted to demonstrate that the chosen MAA provided more accurate estimates of intervention and control incidence rates than would have been found by monitoring a cohort for seroconversion over a six-month period. Future studies should evaluate different test methods (e.g., different assays and/or different cutoffs) to identify an effective method for cross-sectional HIV incidence estimation in subtype D epidemics. The authors' methods could be applied for cross-sectional incidence assessment in non-subtype D epidemics in Southern Africa for HIV surveillance and prevention research.