A wonderful collaborative work between @_RHSP and @HivPangea. Thanks particularly to Kate Grabowski and Oliver Ratmann. Most importantly, thank you to the participants in the Rakai Community Cohort Study for making this research possible.

We estimated that ~4% of viremic PLHIV in the Rakai Community Cohort Study had multiple infections between 2010 and 2020, which is disproportionately concentrated among people living in high-HIV burden communities along Lake Victoria, particularly those w/ more sexual partners.

We develop a Bayesian classification model accounting for partial sequencing success of the within-sample viral genetic diversity as well as false-positive and false-negative signals to identify HIV multiple infections in whole-genome deep-sequence phylogenies.

Our work on quantifying the HIV multiple infection prevalence in Uganda is now out in PLOS Pathogens. This work introduces an analytical framework for high-throughput surveillance and risk factor identification for HIV multiple infections.

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Thanks to all of the wonderful collaborators and co-authors including @HivPangea, @_RHSP, Andrea Brizzi, and senior authors @KateGrabowski and @olli0601.

We identify MIs in deep-sequencing data from 2,029 participants in the Rakai Community Cohort Study. We estimate ~6% of viremic PLHIV harbor MIs at the time of sampling and that PLHIV in high-HIV burden fishing communities are at a two-fold higher risk of having MI.

Our model accounts for partial sequencing success and false-positive and false-negative rates of divergent phylogenetic sigantures. We also incorporrate a logistic model to identify epidemiological risk factors for harboring multiple infections.

Previously, MI identification has used amplicon deep sequencing, potentially missing MIs that lack diversity in those short genome regions. We develop a Bayesian model to identify MIs from within-host phylogenetic trees inferred from deep-sequence data using phyloscanner.

Our pre-print on identifying multiple infections (MIs) from HIV (near) whole-genome sequence data is now available at:

Hopefully the considerable revisions to the manuscript text make these findings a bit more digestible for readers.