Quantifying prevalence and risk factors of HIV multiple infection in Uganda from population-based deep-sequence data

People living with HIV can acquire secondary infections through a process called super- infection, giving rise to simultaneous infection with genetically distinct variants (multiple infection). Multiple infection provides the necessary conditions for the generation of novel recombinant forms of HIV and may worsen clinical outcomes and increase the rate of transmission to HIV seronegative sexual partners. To date, studies of HIV multiple infec- tion have relied on insensitive bulk-sequencing, labor intensive single genome amplifica- tion protocols, or deep-sequencing of short genome regions. Here, we identified multiple infections in whole-genome or near whole-genome HIV RNA deep-sequence data gen- erated from plasma samples of 2,029 people living with viremic HIV who participated in the population-based Rakai Community Cohort Study (RCCS). We estimated individual- and population-level probabilities of being multiply infected and assessed epidemiolog- ical risk factors using the novel Bayesian deep-phylogenetic multiple infection model (deep– phyloMI) which accounts for bias due to partial sequencing success and false- negative and false-positive detection rates. We estimated that between 2010 and 2020, 4.09% (95% highest posterior density interval (HPD) 2.95%–5.45%) of RCCS

Recommended citation: Martin, M.A., Brizzi, A., Xiaoyue, Xi, Galiwango, R.M., Moyo, Sikhulile, Ssemwanga, D., Blenkinsop, A., Redd, A.D., Abeler-Drner, L., Fraser, C., Reynolds, S.J., Quinn, T.C., Kagaayi, J., Bonsall, D., Serwadda, D., Nakigozi, G., Kigozi, G., Grabowski, M.K., Ratmann, O., with the PANGEA-HIV Consortium and the Rakai Health Sciences Program. (2024). Quantifying prevalence and risk factors of HIV multiple infection in Uganda from population-based deep-sequence data. PLOS Pathogens, 21(4), e1013065. 10.1371/journal.ppat.1013065.
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