Lerato E Magosi1, Yinfeng Zhang2, Tanya Golubchik3, Victor DeGruttola4, Eric Tchetgen Tchetgen5, Vladimir Novitsky6,7, Janet Moore8, Pam Bachanas8, Tebogo Segolodi9, Refeletswe Lebelonyane10, Molly Pretorius Holme6, Sikhulile Moyo7, Joseph Makhema7, Shahin Lockman6,7,11, Christophe Fraser3, Myron Max Essex6,7, Marc Lipsitch1. 1. Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, United States. 2. Division of Molecular & Genomic Pathology, University of Pittsburgh Medical Center Presbyterian Shadyside, Philadelphia, United States. 3. Oxford Big Data Institute, Li Ka Shing Center for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, United Kingdom. 4. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, United States. 5. Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, United States. 6. Harvard T.H. Chan School of Public Health AIDS Initiative, Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health, Harvard University, Boston, United States. 7. Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana. 8. Division of Global HIV/AIDS and TB, Centers for Disease Control and Prevention, Atlanta, United States. 9. HIV Prevention Research Unit, Centers for Disease Control and Prevention, Gaborone, Botswana. 10. Ministry of Health, Republic of Botswana, Gaborone, Botswana. 11. Brigham and Women's Hospital, Division of Infectious Diseases, Boston, United States.
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 5114 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] vs. 3% [0.1 - 27.3]) than at baseline (7% [1.5 - 25.3] vs. 5% [0.9 - 22.9]) compatible with a benefit from treatment-as-prevention. Conclusions: 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).
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 5114 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] vs. 3% [0.1 - 27.3]) than at baseline (7% [1.5 - 25.3] vs. 5% [0.9 - 22.9]) compatible with a benefit from treatment-as-prevention. Conclusions: 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).
Entities:
Keywords:
HIV prevention; HIV transmission; bumblebee; epidemiology; genetics; genomics; infectious disease; microbiology; phylogenetics; universal test; universal treat; viruses
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