How can we better identify early HIV infections?. Issue 1 (January 2015)

• Record Type: Journal Article
• Authors: Rosenberg, Nora E.; Pilcher, Christopher D.; Busch, Michael P.; Cohen, Myron S.
• Is Part Of: Current opinion in HIV & AIDS. Volume 10:Issue 1(2015:Jan.)
• Publication Date: 2015-01
• Subjects: acute HIV infection -- early HIV infection -- fourth generation -- multiassay algorithm -- point of care; AIDS (Disease) -- Periodicals; HIV infections -- Periodicals; HIV Infections -- Periodicals; Acquired Immunodeficiency Syndrome -- Periodicals; Infections à VIH -- Périodiques; Sida -- Périodiques; AIDS (Disease); HIV infections; Periodicals; 616.9792005
• DOI: 10.1097/COH.0000000000000121
• Languages: English
• ISSNs: 1746-630X

Abstract

Abstract : Purpose of review: Detection of early HIV infections (EHIs), including acute HIV infection (AHI), is important for individual health, prevention of HIV transmission, and measurement of HIV incidence. We describe markers of EHI, diagnostic strategies for detecting these markers, and ways to incorporate these strategies into diagnostic and HIV incidence algorithms. Recent findings: For individual diagnosis in the USA and Europe, laboratory-based diagnostic algorithms increasingly incorporate fourth-generation HIV antigen tests, allowing for earlier detection. In some sub-Saharan African settings, symptom-based screening is being explored to identify subsets of persons at high risk for AHI. Point-of-care diagnostics designed for AHI detection are in the pipeline and, if validated, represent an opportunity for real-time AHI diagnosis. At the population level, multiassay algorithms are promising new strategies for estimating HIV incidence on the basis of several assays applied to cross-sectional samples. These algorithms can be developed to optimize performance, in addition to cost and logistical considerations. Summary: There are important recent advances in detection of EHIs at the individual and population levels. Applying optimal combinations of tests in diagnostic and HIV incidence algorithms is urgently needed to support the multiple goals derived from enhanced detection and discrimination of EHIs.