Evidence map›Paper›PMID 28068413›Full record

ArticlePLoS pathogens2017

Social and Genetic Networks of HIV-1 Transmission in New York City.

Joel O Wertheim, Sergei L Kosakovsky Pond, Lisa A Forgione, Sanjay R Mehta, Ben Murrell, Sharmila Shah, Davey M Smith, Konrad Scheffler, Lucia V Torian

Open access · goldAbstract read
In one paragraph

Article in PLoS pathogens, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 142 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
142citing papers in PubMed, 2 pooled it
16.5field-weighted citation impact, top 1% 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

142 citing papers in PubMed, 2 syntheses or guidelines pooled it, 212 citations in OpenAlex.

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82 more citing papers are in PubMed but not listed here.

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 at 2 institutions in 2 countries.

Joel O WertheimDepartment of Medicine, University of California San Diego, San Diego, California, United States of America.
Sergei L Kosakovsky PondDepartment of Medicine, University of California San Diego, San Diego, California, United States of America.
Lisa A ForgioneNew York City Department of Health and Mental Hygiene, New York, New York, United States of America.
Sanjay R MehtaDepartment of Medicine, University of California San Diego, San Diego, California, United States of America.
Ben MurrellDepartment of Medicine, University of California San Diego, San Diego, California, United States of America.
Sharmila ShahNew York City Department of Health and Mental Hygiene, New York, New York, United States of America.
Davey M SmithDepartment of Medicine, University of California San Diego, San Diego, California, United States of America.
Konrad SchefflerDepartment of Medicine, University of California San Diego, San Diego, California, United States of America.
Lucia V TorianNew York City Department of Health and Mental Hygiene, New York, New York, United States of America.
University of California, San Diego · USNew York City Department of Health and Mental Hygiene · US

Funding

VirologyP30AI036214 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI David Mitchell Smith · 1994 to 2026
$78.4M
STRUCTURAL NEUROIMAGING COREP30MH062512 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DAVID J MOORE · 2001 to 2026
$50.4M
Molecular Epidemiology for HIV Prevention for Drug Users and Other Risk Groups DP1DA034978 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SMITH, DAVID MITCHELL · 2012 to 2016
$4.1M
Modeling Epidemic Infectious Diseases Using Sequence AnalysisU01GM110749 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI POND, SERGEI L KOSAKOVSKY · 2014 to 2018
$3.0M
HyPhy: Molecular Evolutionary AnalysesR01GM093939 · NIGMS · TEMPLE UNIV OF THE COMMONWEALTH · PI MUSE, SPENCER V., POND, SERGEI L KOSAKOVSKY · 2010 to 2018
$2.5M
Mentoring Translational Research in HIVK24AI100665 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SMITH, DAVID MITCHELL · 2012 to 2021
$1.5M
Public Health Implications of HIV Transmission NetworksK01AI110181 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WERTHEIM, JOEL OKRENT · 2014 to 2018
$668k
Molecular Epidemiology of HIV-1 in the California-Mexico Border RegionK23AI093163 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MEHTA, SANJAY R · 2011 to 2015
$643k
Viral sequence and dynamic determinants of antibody breadthR00AI120851 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MURRELL, BENJAMIN SYLVESTER · 2016 to 2017
$493k
Viral sequence and dynamic determinants of antibody breadthK99AI120851 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MURRELL, BENJAMIN SYLVESTER · 2015 to 2015
$124k
NIAID NIH HHS K01 AI110181NIAID NIH HHS K23 AI093163NIAID NIH HHS K24 AI100665NIAID NIH HHS K99 AI120851NIAID NIH HHS P30 AI036214NIAID NIH HHS R00 AI120851NIDA NIH HHS DP1 DA034978NIGMS NIH HHS R01 GM093939NIGMS NIH HHS U01 GM110749
6 · The paper itself

Abstract

backgroundSexually transmitted infections spread across contact networks. Partner elicitation and notification are commonly used public health tools to identify, notify, and offer testing to persons linked in these contact networks. For HIV-1, a rapidly evolving pathogen with low per-contact transmission rates, viral genetic sequences are an additional source of data that can be used to infer or refine transmission networks. METHODS AND

findingsThe New York City Department of Health and Mental Hygiene interviews individuals newly diagnosed with HIV and elicits names of sexual and injection drug using partners. By law, the Department of Health also receives HIV sequences when these individuals enter healthcare and their physicians order resistance testing. Our study used both HIV sequence and partner naming data from 1342 HIV-infected persons in New York City between 2006 and 2012 to infer and compare sexual/drug-use named partner and genetic transmission networks. Using these networks, we determined a range of genetic distance thresholds suitable for identifying potential transmission partners. In 48% of cases, named partners were infected with genetically closely related viruses, compatible with but not necessarily representing or implying, direct transmission. Partner pairs linked through the genetic similarity of their HIV sequences were also linked by naming in 53% of cases. Persons who reported high-risk heterosexual contact were more likely to name at least one partner with a genetically similar virus than those reporting their risk as injection drug use or men who have sex with men.

conclusionsWe analyzed an unprecedentedly large and detailed partner tracing and HIV sequence dataset and determined an empirically justified range of genetic distance thresholds for identifying potential transmission partners. We conclude that genetic linkage provides more reliable evidence for identifying potential transmission partners than partner naming, highlighting the importance and complementarity of both epidemiological and molecular genetic surveillance for characterizing regional HIV-1 epidemics.

Indexed as

AdultAlgorithmsContact TracingDemographyFemaleGenotypeHIV-1HIV InfectionsHomosexuality, MaleHumansMaleNew York CityPublic HealthRiskSexual BehaviorSexually Transmitted Diseases

Identifiers

PMID28068413
PMCPMC5221827
OpenAlexW2571541240

What OpenQuestion holds

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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.