Cross-sectional HIV incidence estimation in HIV prevention research

Ron Brookmeyer, Oliver Laeyendecker, Deborah Donnell, Susan H. Eshleman

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


Accurate methods for estimating HIV incidence from cross-sectional samples would have great utility in prevention research. This report describes recent improvements in crosssectional methods that significantly improve their accuracy. These improvements are based on the use of multiple biomarkers to identify recent HIV infections. These multiassay algorithms (MAAs) use assays in a hierarchical approach for testing that minimizes the effort and cost of incidence estimation. These MAAs do not require mathematical adjustments for accurate estimation of the incidence rates in study populations in the year before sample collection. MAAs provide a practical, accurate, and cost-effective approach for cross-sectional HIV incidence estimation that can be used for HIV prevention research and global epidemic monitoring.

Original languageEnglish (US)
Pages (from-to)S233-S239
JournalJournal of Acquired Immune Deficiency Syndromes
Issue numberSUPPL. 2
StatePublished - Jul 1 2013


  • Cross-sectional
  • HIV
  • Incidence
  • Multiassay algorithm

ASJC Scopus subject areas

  • Infectious Diseases
  • Pharmacology (medical)


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