PubMed · 11366227
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1999. Adoptive immunotherapy.. https://pubmed.ncbi.nlm.nih.gov/11366227/
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BACKGROUND: Estimating the time since HIV infection (TSI) at population level is essential for tracking changes in the global HIV epidemic. Most methods for determining TSI give a binary classification of infections as recent or non-recent within a window of several months, and cannot assess the cumulative impact of an intervention. RESULTS: We developed a Random Forest Regression model, HIV-phyloTSI, which combines measures of within-host diversity and divergence to generate continuous TSI estimates directly from viral deep-sequencing data, with no need for additional variables. HIV-phyloTSI provides a continuous measure of TSI up to 9 years, with a mean absolute error of less than 12 months overall and less than 5 months for infections with a TSI of up to a year. It performs equally well for all major HIV subtypes based on data from African and European cohorts. CONCLUSIONS: We demonstrate how HIV-phyloTSI can be used for incidence estimates on a population level.
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HIV-1 subtype C accounts for the vast majority of infections in South Africa. However, increasingly non-C subtypes are being detected. Here we report 10 viruses that contain sequences that group with subtypes A, D, and G as well as CRF02_AG and 1 that could not be classified. Most of these individuals were from other countries in Africa. Some of these sequences were in combination with subtype C, possibly indicating local recombination events. Although there is no indication of endemic spread of these viruses, continued monitoring is warranted to track genetic changes, which may impact on diagnostic testing, therapeutic responses to antiretroviral therapies, and vaccine design.