Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial – BCPP/Ya Tsie trial
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 i...
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2022-03-01
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| Series: | eLife |
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| Online Access: | https://elifesciences.org/articles/72657 |
| _version_ | 1828169512886730752 |
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| author | Lerato E Magosi Yinfeng Zhang Tanya Golubchik Victor DeGruttola Eric Tchetgen Tchetgen Vladimir Novitsky Janet Moore Pam Bachanas Tebogo Segolodi Refeletswe Lebelonyane Molly Pretorius Holme Sikhulile Moyo Joseph Makhema Shahin Lockman Christophe Fraser Myron Max Essex Marc Lipsitch On behalf of The Botswana Combination Prevention Project and PANGEA consortium |
| author_facet | Lerato E Magosi Yinfeng Zhang Tanya Golubchik Victor DeGruttola Eric Tchetgen Tchetgen Vladimir Novitsky Janet Moore Pam Bachanas Tebogo Segolodi Refeletswe Lebelonyane Molly Pretorius Holme Sikhulile Moyo Joseph Makhema Shahin Lockman Christophe Fraser Myron Max Essex Marc Lipsitch On behalf of The Botswana Combination Prevention Project and PANGEA consortium |
| author_sort | Lerato E Magosi |
| collection | DOAJ |
| description | 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). |
| first_indexed | 2024-04-12T02:52:53Z |
| format | Article |
| id | doaj.art-8133e598aa0b4adf86f7f146f59a8afc |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T02:52:53Z |
| publishDate | 2022-03-01 |
| publisher | eLife Sciences Publications Ltd |
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| series | eLife |
| spelling | doaj.art-8133e598aa0b4adf86f7f146f59a8afc2022-12-22T03:50:55ZengeLife Sciences Publications LtdeLife2050-084X2022-03-011110.7554/eLife.72657Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial – BCPP/Ya Tsie trialLerato E Magosi0https://orcid.org/0000-0002-3388-9892Yinfeng Zhang1Tanya Golubchik2https://orcid.org/0000-0003-2765-9828Victor DeGruttola3Eric Tchetgen Tchetgen4Vladimir Novitsky5Janet Moore6Pam Bachanas7Tebogo Segolodi8Refeletswe Lebelonyane9Molly Pretorius Holme10Sikhulile Moyo11Joseph Makhema12Shahin Lockman13Christophe Fraser14Myron Max Essex15Marc Lipsitch16https://orcid.org/0000-0003-1504-9213On behalf of The Botswana Combination Prevention Project and PANGEA consortiumCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, United StatesDivision of Molecular & Genomic Pathology, University of Pittsburgh Medical Center Presbyterian Shadyside, Philadelphia, United StatesOxford Big Data Institute, Li Ka Shing Center for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, United KingdomDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, United StatesDepartment of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, United StatesHarvard 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; Botswana Harvard AIDS Institute Partnership, Gaborone, BotswanaDivision of Global HIV/AIDS and TB, Centers for Disease Control and Prevention, Atlanta, United StatesDivision of Global HIV/AIDS and TB, Centers for Disease Control and Prevention, Atlanta, United StatesHIV Prevention Research Unit, Centers for Disease Control and Prevention, Gaborone, BotswanaMinistry of Health, Republic of Botswana, Gaborone, BotswanaHarvard 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 StatesBotswana Harvard AIDS Institute Partnership, Gaborone, BotswanaBotswana Harvard AIDS Institute Partnership, Gaborone, BotswanaHarvard 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; Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana; Brigham and Women's Hospital, Division of Infectious Diseases, Boston, United StatesOxford Big Data Institute, Li Ka Shing Center for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, United KingdomHarvard 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; Botswana Harvard AIDS Institute Partnership, Gaborone, BotswanaCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, United StatesBackground: 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).https://elifesciences.org/articles/72657HIV transmissionphylogeneticsepidemiologyuniversal testbumblebeeHIV prevention |
| spellingShingle | Lerato E Magosi Yinfeng Zhang Tanya Golubchik Victor DeGruttola Eric Tchetgen Tchetgen Vladimir Novitsky Janet Moore Pam Bachanas Tebogo Segolodi Refeletswe Lebelonyane Molly Pretorius Holme Sikhulile Moyo Joseph Makhema Shahin Lockman Christophe Fraser Myron Max Essex Marc Lipsitch On behalf of The Botswana Combination Prevention Project and PANGEA consortium Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial – BCPP/Ya Tsie trial eLife HIV transmission phylogenetics epidemiology universal test bumblebee HIV prevention |
| title | Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial – BCPP/Ya Tsie trial |
| title_full | Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial – BCPP/Ya Tsie trial |
| title_fullStr | Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial – BCPP/Ya Tsie trial |
| title_full_unstemmed | Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial – BCPP/Ya Tsie trial |
| title_short | Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial – BCPP/Ya Tsie trial |
| title_sort | deep sequence phylogenetics to quantify patterns of hiv transmission in the context of a universal testing and treatment trial bcpp ya tsie trial |
| topic | HIV transmission phylogenetics epidemiology universal test bumblebee HIV prevention |
| url | https://elifesciences.org/articles/72657 |
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