Assessing Direct and Spillover Effects of Intervention Packages in Network-randomized Studies

Author:

Buchanan Ashley L.1ORCID,Hernández-Ramírez Raúl U.2,Lok Judith J.3,Vermund Sten H.4,Friedman Samuel R.5ORCID,Forastiere Laura6ORCID,Spiegelman Donna2

Affiliation:

1. Department of Pharmacy Practice and Clinical Research, College of Pharmacy, University of Rhode Island, Kingston, RI

2. Department of Biostatistics, Center for Methods in Implementation and Prevention Science, and Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT

3. Department of Mathematics and Statistics, Boston University, Boston, MA

4. Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT

5. Department of Population Health, New York University Grossman School of Medicine, New York, NY

6. Department of Biostatistics, Yale School of Public Health, New Haven, CT.

Abstract

Background: Intervention packages may result in a greater public health impact than single interventions. Understanding the separate impact of each component on the overall package effectiveness can improve intervention delivery. Methods: We adapted an approach to evaluate the effects of a time-varying intervention package in a network-randomized study. In some network-randomized studies, only a subset of participants in exposed networks receive the intervention themselves. The spillover effect contrasts average potential outcomes if a person was not exposed to themselves under intervention in the network versus no intervention in a control network. We estimated the effects of components of the intervention package in HIV Prevention Trials Network 037, a Phase III network-randomized HIV prevention trial among people who inject drugs and their risk networks using marginal structural models to adjust for time-varying confounding. The index participant in an intervention network received a peer education intervention initially at baseline, then boosters at 6 and 12 months. All participants were followed to ascertain HIV risk behaviors. Results: There were 560 participants with at least one follow-up visit, 48% of whom were randomized to the intervention, and 1,598 participant visits were observed. The spillover effect of the boosters in the presence of initial peer education training was a 39% rate reduction (rate ratio = 0.61; 95% confidence interval = 0.43, 0.87). Conclusions: These methods will be useful for evaluating intervention packages in studies with network features.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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