ArticleJournal of acquired immune deficiency syndromes (1999)2019
A Multiplex HIV Incidence Assay for Inferring Recent HIV-1 Transmission and Time of Infection.
Article in Journal of acquired immune deficiency syndromes (1999), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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11 authors at 4 institutions in 1 country.
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Abstract
backgroundLaboratory assays for determining recent HIV-1 infection are an important public health tool for aiding in the estimation of HIV incidence. Some incidence assay analytes are remarkably predictive of time since seroconversion and may be useful for additional applications, such as predicting recent transmission events during HIV outbreaks and informing prevention strategies.
methodsPlasma samples (n = 154) from a recent HIV-1 outbreak in a rural community in Indiana were tested with the customized HIV-1 Multiplex assay, based on the Bio-Rad Bio-Plex platform, which measures antibody response to HIV envelope antigens, gp120, gp160, and gp41. Assay cutoffs for each analyte were established to determine whether an individual seroconverted within 30, 60, or 90 days of the sample collection date. In addition, a novel bioinformatics method was implemented to infer infection dates of persons newly diagnosed with HIV during the outbreak.
resultsSensitivity/specificity of the HIV-1 Multiplex assay for predicting seroconversion within 30, 60, and 90 days, based on a training data set, was 90.5%/95.4%, 94.1%/90%, and 89.4%/82.9%, respectively. Of 154 new diagnoses in Indiana between December 2014 and August 2016, the majority (71%) of recent infections (≤3 months since seroconversion) were identified between February and May 2016. The epidemiologic curve derived from the bioinformatics analysis indicated HIV transmission began as early as 2010, grew exponentially in 2014, and leveled off in April 2015.
conclusionsThe HIV-1 Multiplex assay has the potential to identify and monitor trends in recent infection during an epidemic to assess the efficacy of programmatic or treatment interventions.
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