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

Ashley L Buchanan1, Raúl Ulises Hernández-Ramírez2, Judith J Lok3

  • 1Department of Pharmacy Practice, College of Pharmacy, University of Rhode Island, Kingston, RI 02881.

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Booster sessions in HIV prevention trials significantly reduced risk behaviors by 39% through network spillover effects. This highlights the impact of intervention packages on public health.

Keywords:
Causal inferenceCluster-randomized trialsHIV/AIDSImplementation ScienceInterferencePackage InterventionsSpillover/Indirect effectsSubstance use

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Area of Science:

  • Public Health
  • Epidemiology
  • Biostatistics

Background:

  • Intervention packages can yield greater public health impact than single interventions.
  • Evaluating individual component effects within intervention packages is crucial for optimizing delivery.
  • Network-randomized studies present unique challenges in assessing intervention effects, especially with partial exposure and spillover.

Approach:

  • Adapted an approach to evaluate time-varying intervention packages in a network-randomized study.
  • Utilized Marginal Structural Models to adjust for time-varying confounding in HIV Prevention Trials Network 037.
  • Estimated the spillover effects of intervention components, specifically peer education boosters, among people who inject drugs.

Key Points:

  • The study evaluated an HIV prevention trial among people who inject drugs and their risk networks.
  • The intervention involved peer education with boosters at 6 and 12 months for index participants.
  • Spillover effects of boosters, combined with initial training, resulted in a 39% reduction in HIV risk behaviors (Rate Ratio = 0.61).

Conclusions:

  • The adapted approach effectively evaluated intervention package components in a network-randomized trial.
  • Intervention boosters demonstrated a significant spillover effect, reducing HIV risk behaviors within networks.
  • These methods are valuable for assessing complex intervention packages in network-based public health studies.