Assessing Spillover Effects of Medications for Opioid Use Disorder on HIV Risk Behaviors among a Network of People Who Inject Drugs

Joseph Puleo (), Ashley Buchanan (), Natallia Katenka, M. Elizabeth Halloran, Samuel R. Friedman and Georgios Nikolopoulos
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Joseph Puleo: Department of Computer Science & Statistics, University of Rhode Island, Kingston, RI 02881, USA
Ashley Buchanan: Department of Pharmacy Practice & Clinical Research, University of Rhode Island, Kingston, RI 02881, USA
Natallia Katenka: Department of Computer Science & Statistics, University of Rhode Island, Kingston, RI 02881, USA
M. Elizabeth Halloran: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
Samuel R. Friedman: Department of Population Health, NYU Grossman School of Medicine, New York, NY 10016, USA
Georgios Nikolopoulos: Medical School, University of Cyprus, 1678 Nicosia, Cyprus

Stats, 2024, vol. 7, issue 2, 1-27

Abstract: People who inject drugs (PWID) have an increased risk of HIV infection partly due to injection behaviors often related to opioid use. Medications for opioid use disorder (MOUD) have been shown to reduce HIV infection risk, possibly by reducing injection risk behaviors. MOUD may benefit individuals who do not receive it themselves but are connected through social, sexual, or drug use networks with individuals who are treated. This is known as spillover. Valid estimation of spillover in network studies requires considering the network’s community structure. Communities are groups of densely connected individuals with sparse connections to other groups. We analyzed a network of 277 PWID and their contacts from the Transmission Reduction Intervention Project. We assessed the effect of MOUD on reductions in injection risk behaviors and the possible benefit for network contacts of participants treated with MOUD. We identified communities using modularity-based methods and employed inverse probability weighting with community-level propensity scores to adjust for measured confounding. We found that MOUD may have beneficial spillover effects on reducing injection risk behaviors. The magnitudes of estimated effects were sensitive to the community detection method. Careful consideration should be paid to the significance of community structure in network studies evaluating spillover.

Keywords: causal inference; networks; spillover; community detection; Human Immunodeficiency Virus; People Who Inject Drugs (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2024
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