Evidence map›Paper›PMID 33341667›Full record

ArticleEpidemics2021

Network structure and rapid HIV transmission among people who inject drugs: A simulation-based analysis.

Alyson L Singleton, Brandon D L Marshall, S Bessey, Matthew T Harrison, Alison P Galvani, Jesse L Yedinak, Brendan P Jacka, Steven M Goodreau, William C Goedel

Abstract read
In one paragraph

Article in Epidemics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

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

9 authors.

Alyson L SingletonDepartment of Biostatistics, School of Public Health, Brown University, Providence, RI, United States.
Brandon D L MarshallDepartment of Epidemiology, School of Public Health, Brown University, Providence, RI, United States.
S BesseyDepartment of Epidemiology, School of Public Health, Brown University, Providence, RI, United States.
Matthew T HarrisonDivision of Applied Mathematics, Brown University, Providence, RI, United States.
Alison P GalvaniDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT, United States; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States; Centre for Infectious Disease Modelling and Analysis, School of Public Health, Yale University, New Haven, CT, United States.
Jesse L YedinakDepartment of Epidemiology, School of Public Health, Brown University, Providence, RI, United States.
Brendan P JackaDepartment of Epidemiology, School of Public Health, Brown University, Providence, RI, United States.
Steven M GoodreauDepartment of Anthropology, University of Washington, Seattle, WA, United States.
William C GoedelDepartment of Epidemiology, School of Public Health, Brown University, Providence, RI, United States. Electronic address: william_goedel@brown.edu.

Funding

The Brown Initiative in HIV and AIDS Clinical Research for Minority CommunitiesR25MH083620 · NIMH · MIRIAM HOSPITAL · PI NUNN, AMY STEWART · 2008 to 2025
$3.7M
Highly Adaptive Epidemic Control Strategies for HIV Prevention in Drug UsersDP2DA040236 · NIDA · BROWN UNIVERSITY · PI MARSHALL, BRANDON DAVID LEWIS · 2015 to 2015
$2.4M
Leveraging Social Networks to Improve Uptake of a Novel Biomedical HIV Prevention MethodF31MH121112 · NIMH · BROWN UNIVERSITY · PI GOEDEL, WILLIAM CHRISTOPHER · 2019 to 2019
$37k
NIDA NIH HHS DP2 DA040236NIMH NIH HHS F31 MH121112NIMH NIH HHS R25 MH083620
6 · The paper itself

Abstract

As HIV incidence among people who inject drugs grows in the context of an escalating drug overdose epidemic in North America, investigating how network structure may affect vulnerability to rapid HIV transmission is necessary for preventing outbreaks. We compared the characteristics of the observed contact tracing network from the 2015 outbreak in rural Indiana with 1000 networks generated by an agent-based network model with approximately the same number of individuals (n = 420) and ties between them (n = 913). We introduced an initial HIV infection into the simulated networks and compared the subsequent epidemic behavior (e.g., cumulative HIV infections over 5 years). The model was able to produce networks with largely comparable characteristics and total numbers of incident HIV infections. Although the model was unable to produce networks with comparable cohesiveness (where the observed network had a transitivity value 35.7 standard deviations from the mean of the simulated networks), the structural variability of the simulated networks allowed for investigation into their potential facilitation of HIV transmission. These findings emphasize the need for continued development of injection network simulation studies in tandem with empirical data collection to further investigate how network characteristics played a role in this and future outbreaks.

Indexed as

EpidemicsHIV InfectionsPharmaceutical PreparationsSubstance Abuse, IntravenousContact TracingHumansPharmaceutical PreparationsHIVInjection drug useOutbreakRural healthSocial network analysis

Identifiers

PMID33341667
PMCPMC7940592

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.