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Infectious Diseases and Our PlanetReducing the Global HIV Burden: The Importance of Uneven Exposure to the Results of HIV Prevention Trials

Infectious Diseases and Our Planet: Reducing the Global HIV Burden: The Importance of Uneven... [Randomized controlled trials (RCTs) of biomedical interventions for HIV prevention are often designed assuming uniform levels of HIV risk. We employ mathematical models to simulate RCTs testing HIV prevention products among populations with different level of nonuniform HIV exposure between trial participants. Our goal is to show that uneven HIV exposure can affect trial effectiveness when it is estimated by comparing HIV incidence during periods when prevention products are used vs not used. We demonstrate that studies using the traditional RCT design may report effectiveness values significantly below the “true efficacy” calculated from actual risk reduction per sex act. This bias in the effectiveness estimate is due to a growing imbalance between trial arms as highly exposed individuals become more frequently infected and removed from the control arm. Our analysis suggests that the effectiveness decreases with the HIV exposure rate and the length of the trial, but increases if more individuals are exposed to HIV or if they change their exposure status frequently. Heterogeneity in HIV exposure can further complicate stepped-wedge RCT designs where the effect on the observed effectiveness may be positive or negative depending on how study results are analyzed. Our results suggest that RCT power will be improved by enrolling more individuals with equally high risk to be exposed to HIV.]

Infectious Diseases and Our PlanetReducing the Global HIV Burden: The Importance of Uneven Exposure to the Results of HIV Prevention Trials

Part of the Mathematics of Planet Earth Book Series (volume 7)
Editors: Teboh-Ewungkem, Miranda I.; Ngwa, Gideon Akumah

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[Randomized controlled trials (RCTs) of biomedical interventions for HIV prevention are often designed assuming uniform levels of HIV risk. We employ mathematical models to simulate RCTs testing HIV prevention products among populations with different level of nonuniform HIV exposure between trial participants. Our goal is to show that uneven HIV exposure can affect trial effectiveness when it is estimated by comparing HIV incidence during periods when prevention products are used vs not used. We demonstrate that studies using the traditional RCT design may report effectiveness values significantly below the “true efficacy” calculated from actual risk reduction per sex act. This bias in the effectiveness estimate is due to a growing imbalance between trial arms as highly exposed individuals become more frequently infected and removed from the control arm. Our analysis suggests that the effectiveness decreases with the HIV exposure rate and the length of the trial, but increases if more individuals are exposed to HIV or if they change their exposure status frequently. Heterogeneity in HIV exposure can further complicate stepped-wedge RCT designs where the effect on the observed effectiveness may be positive or negative depending on how study results are analyzed. Our results suggest that RCT power will be improved by enrolling more individuals with equally high risk to be exposed to HIV.]

Published: Aug 6, 2020

Keywords: HIV prevention; Mathematical model; Effectiveness; Stepped-wedge design; 92D30; 62P10

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