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Estimation of HIV-1 Incidence Using a Testing History-Based method; analysis from the Population-based HIV Impact Assessment survey data in 12 African Countries
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3 1 2023
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Source: J Acquir Immune Defic Syndr. 92(3):189-196
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Details:
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Alternative Title:J Acquir Immune Defic Syndr
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Description:Background:
Estimating HIV incidence is essential to monitoring progress in sub-Saharan African nations toward global epidemic control. One method for incidence estimation is to test nationally-representative samples using laboratory-based incidence assays. An alternative method based on reported HIV testing history and the proportion of undiagnosed infections has recently been described.
Methods:
We applied an HIV incidence estimation method which utilizes prior history of testing, to nationally representative cross-sectional survey data from 12 sub-Saharan African nations with varying country-specific HIV prevalence. We compared these estimates with those derived from laboratory-based incidence assays. Participants were tested for HIV using the national rapid test algorithm, and asked about prior HIV testing, date and result of their most recent test, and date of ART initiation.
Results:
The testing history-based method consistently produced results that are comparable and strongly correlated with estimates produced using a laboratory-based HIV incidence assay (ρ = 0.85). The testing history-based method produced incidence estimates that were more precise compared to the biomarker-based method. The testing history-based method identified sex-, age-, and geographic location- specific difference in incidence that were not detected using the biomarker-based method.
Conclusion:
The testing history-based method estimates are more precise and can produce age- and sex-specific incidence estimates that are informative for programmatic decisions. The method also allows for comparisons of the HIV transmission rate and other components of HIV incidence among and within countries. The testing history-based method is a useful tool for estimating and validating HIV incidence from cross-sectional survey data.
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Pubmed ID:36730779
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Pubmed Central ID:PMC9911103
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