Evidence map›Paper›PMID 36839598›Full record

ArticlePathogens (Basel, Switzerland)2023

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

Open access · goldAbstract read
In one paragraph

Article in Pathogens (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. A Review of Network Models for HIV Spread.Journal of acquired immune deficiency syndromes (1999) · 2025
    Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 6 institutions in 2 countries.

Ashley L BuchananDepartment of Pharmacy Practice, University of Rhode Island, Kingston, RI 02881, USA.ORCID 0000-0002-4715-3456
Natallia KatenkaDepartment of Computer Science and Statistics, University of Rhode Island, Kingston, RI 02881, USA.
Youjin LeeDepartment of Biostatistics, Brown University, Providence, RI 02912, USA.
Jing WuDepartment of Computer Science and Statistics, University of Rhode Island, Kingston, RI 02881, USA.
Katerina PantavouMedical School, University of Cyprus, 1678 Nicosia, Cyprus.
Samuel R FriedmanDepartment of Population Health, New York University, New York, NY 10016, USA.ORCID 0000-0003-2083-1226
M Elizabeth HalloranVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA.ORCID 0000-0002-3127-1757
Brandon D L MarshallDepartment of Epidemiology, Brown University School of Public Health, Providence, RI 02912, USA.ORCID 0000-0002-0134-7052
Laura ForastiereDepartment of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.
Georgios K NikolopoulosMedical School, University of Cyprus, 1678 Nicosia, Cyprus.ORCID 0000-0002-3307-0246
University of Rhode Island · USBrown University · USUniversity of Cyprus · CYNew York University · USUniversity of Washington · USYale University · US

Funding

Transdisciplinary Theoretical Svnthesis and Development CoreP30DA011041 · NIDA · NEW YORK UNIVERSITY · PI Holly Hagan · 1998 to 2026
$38.9M
Causal Inference in Infectious Disease Prevention StudiesR01AI085073 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HUDGENS, MICHAEL G · 2010 to 2024
$4.5M
Preventing HIV Transmission by Recently-Infected Drug UsersDP1DA034989 · NIDA · NATIONAL DEVELOPMENT AND RESEARCH INSTITUTES, INC. · PI FRIEDMAN, SAMUEL R · 2012 to 2016
$3.8M
Causal Inference Methods for HIV Prevention Studies Among Networks of People Who Use DrugsDP2DA046856 · NIDA · UNIVERSITY OF RHODE ISLAND · PI BUCHANAN, ASHLEY LYNN · 2018 to 2019
$2.3M
Causal Inference in Infectious Disease Prevention StudiesR37AI085073 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Michael G Hudgens · 2026 to 2026
$394k
NIAID NIH HHS R37 AI085073NIDA NIH HHS DP1 DA034989NIDA NIH HHS DP2 DA046856NIDA NIH HHS P30 DA011041
6 · The paper itself

Abstract

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.

Indexed as

human immunodeficiency virusnetworkspeople who use/inject drugsspillover effects

Identifiers

PMID36839598
PMCPMC9967280
OpenAlexW4320917861

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.