Evidence map›Paper›PMID 27882678›Full record

ArticleJournal of viral hepatitis2017

A molecular transmission network of recent hepatitis C infection in people with and without HIV: Implications for targeted treatment strategies.

Sofia R Bartlett, Joel O Wertheim, Rowena A Bull, Gail V Matthews, Francois Mj Lamoury, Konrad Scheffler, Margaret Hellard, Lisa Maher, Gregory J Dore, Andrew R Lloyd and 2 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of viral hepatitis, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

23 citing papers in PubMed, 32 citations in OpenAlex.

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  15. Correlates of hepatitis C viral clustering among people who inject drugs in Baltimore.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2020
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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

12 authors at 3 institutions in 2 countries.

Sofia R BartlettKirby Institute, UNSW Australia, Sydney, 2052, Australia.
Joel O WertheimDepartment of Medicine, University of California, San Diego, California, 92093, United States.
Rowena A BullKirby Institute, UNSW Australia, Sydney, 2052, Australia.
Gail V MatthewsKirby Institute, UNSW Australia, Sydney, 2052, Australia.
Francois Mj LamouryKirby Institute, UNSW Australia, Sydney, 2052, Australia.
Konrad SchefflerDepartment of Medicine, University of California, San Diego, California, 92093, United States.
Margaret HellardThe Burnet Institute, Melbourne, 3004, Australia.
Lisa MaherKirby Institute, UNSW Australia, Sydney, 2052, Australia.
Gregory J DoreKirby Institute, UNSW Australia, Sydney, 2052, Australia.
Andrew R LloydKirby Institute, UNSW Australia, Sydney, 2052, Australia.
Tanya L Applegate *Kirby Institute, UNSW Australia, Sydney, 2052, Australia.
Jason Grebely *Kirby Institute, UNSW Australia, Sydney, 2052, Australia.
Data61 · AUUniversity of California, San Diego · USBurnet Institute · AU

Funding

Treatment of recently acquired hepatitis C virus infectionR01DA015999 · NIDA · UNIVERSITY OF NEW SOUTH WALES · PI DORE, GREGORY JOHN · 2003 to 2014
$3.7M
Public Health Implications of HIV Transmission NetworksK01AI110181 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WERTHEIM, JOEL OKRENT · 2014 to 2018
$668k
NIAID NIH HHS K01 AI110181NIDA NIH HHS R01 DA015999
6 · The paper itself

Abstract

Combining phylogenetic and network methodologies has the potential to better inform targeted interventions to prevent and treat infectious diseases. This study reconstructed a molecular transmission network for people with recent hepatitis C virus (HCV) infection and modelled the impact of targeting directly acting antiviral (DAA) treatment for HCV in the network. Participants were selected from three Australian studies of recent HCV from 2004 to 2014. HCV sequence data (Core-E2) from participants at the time of recent HCV detection were analysed to infer a network by connecting pairs of sequences whose divergence was ≤.03 substitutions/site. Logistic regression was used to identify factors associated with connectivity. Impact of targeting HCV DAAs at both HIV co-infected and random nodes was simulated (1 million replicates). Among 236 participants, 21% (n=49) were connected in the network. HCV/HIV co-infected participants (47%) were more likely to be connected compared to HCV mono-infected participants (16%) (OR 4.56; 95% CI; 2.13-9.74). Simulations targeting DAA HCV treatment to HCV/HIV co-infected individuals prevented 2.5 times more onward infections than providing DAAs to randomly selected individuals. Results demonstrate that genetic distance-based network analyses can be used to identify characteristics associated with HCV transmission, informing targeted prevention and treatment strategies.

Indexed as

Disease Transmission, InfectiousAdultAntiviral AgentsAustraliaCluster AnalysisFemaleGenotypeHepacivirusHepatitis CHIV InfectionsHumansMaleMiddle AgedMolecular EpidemiologyPhylogenySequence Analysis, DNAAntiviral Agentshepatitis C virushuman immunodeficiency virusmodellingmolecular epidemiologytreatment as prevention

Identifiers

PMID27882678
PMCPMC5400687
OpenAlexW2556659231

What OpenQuestion holds

Textmetadata
LicenceTDM
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.