Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial - BCPP/Ya Tsie trial.

HIV prevention HIV transmission bumblebee epidemiology genetics genomics infectious disease microbiology phylogenetics universal test universal treat viruses

Journal

eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614

Informations de publication

Date de publication:
01 03 2022
Historique:
received: 30 07 2021
accepted: 08 02 2022
pubmed: 2 3 2022
medline: 30 4 2022
entrez: 1 3 2022
Statut: epublish

Résumé

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. 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. 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. Our findings suggest that population mobility patterns are fundamental to HIV transmission dynamics and to the impact of HIV control strategies. 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).

Sections du résumé

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).

Identifiants

pubmed: 35229714
doi: 10.7554/eLife.72657
pii: 72657
pmc: PMC8912920
doi:
pii:

Banques de données

Dryad
['10.5061/dryad.0zpc86706']

Types de publication

Journal Article Randomized Controlled Trial Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : CGH CDC HHS
ID : U01 GH000447
Pays : United States
Organisme : NIAID NIH HHS
ID : K24 AI131928
Pays : United States
Organisme : FIC NIH HHS
ID : D43 TW009610
Pays : United States
Organisme : PEPFAR
Pays : United States
Organisme : NIGMS NIH HHS
ID : U54 GM088558
Pays : United States
Organisme : CGH CDC HHS
ID : U2G GH001911
Pays : United States

Investigateurs

None On Behalf Of The Botswana Combination Prevention Project And Pangea Consortium

Déclaration de conflit d'intérêts

LM, YZ, TG, VD, ET, VN, JM, PB, TS, RL, MP, SM, JM, CF, ME No competing interests declared, SL participates in a data safety monitoring board for NIH-funded study of PK of TB drugs and antiretrovirals in children and on a scientific advisory board for observational study of DTG programmatic rollout in Botswana. Is also a member of the Finance Board and a member of the Board of Directors for the Botswana Harvard AIDS Institute Partnership. Receives no financial compensation for these roles, and has no other competing interests to declare, ML is a Reviewing Editor for eLife. Has received consultancy fees from Merck, University of Virginia Miller Center and Janssen, and has performed unpaid consultancy work for Janssen, Pfizer and Astra Zeneca. Has also received payments or honoraria from Sanofi Pasteur and Bristol Myers Squibb. ML has no other competing interests to declare

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Auteurs

Lerato E Magosi (LE)

Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, United States.

Yinfeng Zhang (Y)

Division of Molecular & Genomic Pathology, University of Pittsburgh Medical Center Presbyterian Shadyside, Philadelphia, United States.

Tanya Golubchik (T)

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.

Victor DeGruttola (V)

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, United States.

Eric Tchetgen Tchetgen (E)

Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, United States.

Vladimir Novitsky (V)

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.
Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.

Janet Moore (J)

Division of Global HIV/AIDS and TB, Centers for Disease Control and Prevention, Atlanta, United States.

Pam Bachanas (P)

Division of Global HIV/AIDS and TB, Centers for Disease Control and Prevention, Atlanta, United States.

Tebogo Segolodi (T)

HIV Prevention Research Unit, Centers for Disease Control and Prevention, Gaborone, Botswana.

Refeletswe Lebelonyane (R)

Ministry of Health, Republic of Botswana, Gaborone, Botswana.

Molly Pretorius Holme (M)

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.

Sikhulile Moyo (S)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.

Joseph Makhema (J)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.

Shahin Lockman (S)

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.
Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
Brigham and Women's Hospital, Division of Infectious Diseases, Boston, United States.

Christophe Fraser (C)

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.

Myron Max Essex (MM)

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.
Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.

Marc Lipsitch (M)

Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, United States.

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