Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs.
Ashley L Buchanan, Natallia Katenka, Youjin Lee, Jing Wu, Katerina Pantavou, Samuel R Friedman, M Elizabeth Halloran, Brandon D L Marshall, Laura Forastiere, Georgios K Nikolopoulos
Author Information
Ashley L Buchanan: Department of Pharmacy Practice, University of Rhode Island, Kingston, RI 02881, USA. ORCID
Natallia Katenka: Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI 02881, USA.
Youjin Lee: Department of Biostatistics, Brown University, Providence, RI 02912, USA.
Jing Wu: Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI 02881, USA.
Katerina Pantavou: Medical School, University of Cyprus, 1678 Nicosia, Cyprus.
Samuel R Friedman: Department of Population Health, New York University, New York, NY 10016, USA. ORCID
M Elizabeth Halloran: Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA. ORCID
Brandon D L Marshall: Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912, USA. ORCID
Laura Forastiere: Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.
Georgios K Nikolopoulos: Medical School, University of Cyprus, 1678 Nicosia, Cyprus. ORCID
Human Immunodeficiency Virus (HIV) interventions among people who use drugs (PWUD) often have spillover, also known as interference or dissemination, which occurs when one participant's exposure affects another participant's outcome. PWUD are often members of networks defined by social, sexual, and drug-use partnerships and their receipt of interventions can affect other members in their network. For example, HIV interventions with possible spillover include educational training about HIV risk reduction, pre-exposure prophylaxis, or treatment as prevention. In turn, intervention effects frequently depend on the network structure, and intervention coverage levels and spillover can occur even if not measured in a study, possibly resulting in an underestimation of intervention effects. Recent methodological approaches were developed to assess spillover in the context of network-based studies. This tutorial provides an overview of different study designs for network-based studies and related methodological approaches for assessing spillover in each design. We also provide an overview of other important methodological issues in network studies, including causal influence in networks and missing data. Finally, we highlight applications of different designs and methods from studies of PWUD and conclude with an illustrative example from the Transmission Reduction Intervention Project (TRIP) in Athens, Greece.
