Assessing the use of surveillance data to estimate the impact of prevention interventions on HIV incidence in cluster-randomized controlled trials

Assessing the use of surveillance data to estimate the impact of prevention interventions on HIV incidence in cluster-randomized controlled trials

Background: In cluster-randomized controlled trials (C-RCTs) of HIV prevention strategies, HIV incidence is expensive to measure directly. Surveillance data on HIV diagnoses or viral suppression could provide cheaper incidence estimates. We used mathematical modelling to evaluate whether these measu...

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Bibliographic Details
Main Authors: Kate M. Mitchell, Dobromir Dimitrov, James P. Hughes, Mia Moore, Eric Vittinghoff, Albert Liu, Myron S. Cohen, Chris Beyrer, Deborah Donnell, Marie-Claude Boily
Format: Article
Language:English
Published: Elsevier 2020-12-01
Series:Epidemics
Subjects:
Surveillance data
Trials
Incidence
Marker
Mathematical modelling
HIV
Online Access:http://www.sciencedirect.com/science/article/pii/S1755436520300438

Internet

http://www.sciencedirect.com/science/article/pii/S1755436520300438

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