Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial - BCPP/ Ya Tsie trial
Abstract
Background: Mathematical models predict that community-wide access to HIV testing-and-treatment can rapidly and substantially reduce new HIV infections. Yet several large universal test-and-treat HIV prevention trials in high-prevalence epidemics demonstrated variable reduction in population-level incidence.
Methods: To elucidate patterns of HIV spread in universal test-and-treat trials we quantified the contribution of geographic-location, gender, age and randomized-HIV-intervention to HIV transmissions in the 30-community Ya Tsie trial in Botswana. We sequenced HIV viral whole genomes from 5,114 trial participants among the 30 trial communities.
Results: Deep-sequence phylogenetic analysis revealed that most inferred HIV transmissions within the trial occurred within the same or between neighboring communities, and between similarly-aged partners. Transmissions into intervention communities from control communities were more common than the reverse post-baseline (30% [12.2 - 56.7] versus 3% [0.1 - 27.3]) than at baseline (7% [1.5 - 25.3] versus 5% [0.9 - 22.9]) compatible with a benefit from treatment-as-prevention.
Conclusion: Our findings suggest that population mobility patterns are fundamental to HIV transmission dynamics and to the impact of HIV control strategies.
Funding: This study was supported by the National Institute of General Medical Sciences (U54GM088558); the Fogarty International Center (FIC) of the U.S. National Institutes of Health (D43 TW009610); and the President’s Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention (CDC) (Cooperative agreements U01 GH000447 and U2G GH001911).
Data availability
All relevant data are within the paper, figures and tables. HIV-1 viral whole genome consensus sequences are provided as a Dryad dataset (https://doi.org/10.5061/dryad.0zpc86706). HIV-1 reads are available on reasonable request through a concept sheet proposal to the PANGEA consortium. Contact details are provided on the consortium website (www.pangea-hiv.org).Code availability: Algorithms to estimate HIV transmission flows within and between population groups accounting for sampling variability and corresponding confidence intervals have been implemented as an R package, bumblebee that will be made available at the following URL: https://magosil86.github.io/bumblebee . A step-by-step tutorial on how to estimate HIV transmission flows with bumblebee and accompanying example datasets can be accessed at: https://github.com/magosil86/bumblebee/blob/master/vignettes/bumblebee-estimate-transmission-flows-and-ci-tutotial.md .
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Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial - BCPP/ Ya Tsie trialDryad Digital Repository, doi:10.5061/dryad.0zpc86706.
Article and author information
Author details
Funding
Fogarty International Center (D43 TW009610)
- Lerato E Magosi
Centers for Disease Control and Prevention (U01 GH000447 and U2G GH001911)
- Lerato E Magosi
- Janet Moore
- Pam Bachanas
- Refeletswe Lebelonyane
- Molly Pretorius Holme
- Shahin Lockman
- Myron (Max) Essex
National Institutes of Health
- Christophe Fraser
- Marc Lipsitch
Bill and Melinda Gates Foundation
- Christophe Fraser
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Francesca Di Giallonardo
Ethics
Human subjects: The BCPP study was approved by the Botswana Health Research and Development Committee and the institutional review board of the Centers for Disease Control and Prevention; and was monitored by a data and safety monitoring board and Westat. Written informed consent for enrollment in the study and viral HIV genotyping was obtained from all participants.
Version history
- Preprint posted: June 23, 2021 (view preprint)
- Received: July 30, 2021
- Accepted: February 8, 2022
- Accepted Manuscript published: March 1, 2022 (version 1)
- Version of Record published: March 10, 2022 (version 2)
Copyright
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
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