HPTN 071 (PopART): a cluster-randomized trial of the population impact of an HIV combination prevention intervention including universal testing and treatment: mathematical model.
BACKGROUND
The HPTN 052 trial confirmed that antiretroviral therapy (ART) can nearly eliminate HIV transmission from successfully treated HIV-infected individuals within couples. Here, we present the mathematical modeling used to inform the design and monitoring of a new trial aiming to test whether widespread provision of ART is feasible and can substantially reduce population-level HIV incidence.


RESULTS
The HPTN 071 (PopART) trial is a three-arm cluster-randomized trial of 21 large population clusters in Zambia and South Africa, starting in 2013. A combination prevention package including home-based voluntary testing and counseling, and ART for HIV positive individuals, will be delivered in arms A and B, with ART offered universally in arm A and according to national guidelines in arm B. Arm C will be the control arm. The primary endpoint is the cumulative three-year HIV incidence. We developed a mathematical model of heterosexual HIV transmission, informed by recent data on HIV-1 natural history. We focused on realistically modeling the intervention package. Parameters were calibrated to data previously collected in these communities and national surveillance data. We predict that, if targets are reached, HIV incidence over three years will drop by >60% in arm A and >25% in arm B, relative to arm C. The considerable uncertainty in the predicted reduction in incidence justifies the need for a trial. The main drivers of this uncertainty are possible community-level behavioral changes associated with the intervention, uptake of testing and treatment, as well as ART retention and adherence.


CONCLUSIONS
The HPTN 071 (PopART) trial intervention could reduce HIV population-level incidence by >60% over three years. This intervention could serve as a paradigm for national or supra-national implementation. Our analysis highlights the role mathematical modeling can play in trial development and monitoring, and more widely in evaluating the impact of treatment as prevention.
MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Anne
A
Cori
ZAMBART, University of Zambia, School of Medicine, Ridgeway Campus, Lusaka, Zambia ; Department of Clinical Research, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Helen
H
Ayles
Desmond Tutu TB Centre, Department of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, South Africa.
Nulda
N
Beyers
ZAMBART, University of Zambia, School of Medicine, Ridgeway Campus, Lusaka, Zambia ; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Ab
A
Schaap
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Sian
S
Floyd
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Kalpana
K
Sabapathy
MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Jeffrey W
JW
Eaton
Business School, Imperial College London, South Kensington, London, United Kingdom.
Katharina
K
Hauck
Business School, Imperial College London, South Kensington, London, United Kingdom.
Peter
P
Smith
FHI 360, Research Triangle Park, North Carolina, United States of America.
Sam
S
Griffith
FHI 360, Research Triangle Park, North Carolina, United States of America.
Ayana
A
Moore
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
Deborah
D
Donnell
Vanderbilt Institute for Global Health and Department of Pediatrics, Vanderbilt University, Nashville, Tennessee, United States of America.
Sten H
SH
Vermund
Department of Medicine, Imperial College London, London, United Kingdom.
Sarah
S
Fidler
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Richard
R
Hayes
MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Christophe
C
Fraser
D015492:AIDS Serodiagnosis / Q000706:statistics & numerical data*; D019380:Anti-HIV Agents / Q000627:therapeutic use*; D016000:Cluster Analysis; D015658:HIV Infections / Q000175:diagnosis / Q000188:drug therapy / Q000517:prevention & control*; D006801:Humans; D013019:South Africa; D015024:Zambia
D019380:Anti-HIV Agents