Evidence map›Paper›PMID 26863322›Full record

ArticlePloS one2016

Assessment of Overlap of Phylogenetic Transmission Clusters and Communities in Simple Sexual Contact Networks: Applications to HIV-1.

Luc Villandre, David A Stephens, Aurelie Labbe, Huldrych F Günthard, Roger Kouyos, Tanja Stadler, Swiss HIV Cohort Study

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In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
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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

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

  1. Pooled it
  2. Review
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  5. Scale-Free Spanning Trees and Their Application in Genomic Epidemiology.Journal of computational biology : a journal of computational molecular cell biology · 2021
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  14. Intelligent Network DisRuption Analysis (INDRA): A targeted strategy for efficient interruption of hepatitis C transmissions.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2018
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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

7 authors.

Luc VillandreDepartment of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Québec, Canada.
David A StephensDepartment of Mathematics and Statistics, McGill University, Montréal, Québec, Canada.
Aurelie LabbeDepartment of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Québec, Canada.
Huldrych F GünthardDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Kanton Zurich, Switzerland.
Roger KouyosDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Kanton Zurich, Switzerland.
Tanja StadlerDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Basel-Landschaft, Switzerland.
Swiss HIV Cohort Study

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTransmission patterns of sexually-transmitted infections (STIs) could relate to the structure of the underlying sexual contact network, whose features are therefore of interest to clinicians. Conventionally, we represent sexual contacts in a population with a graph, that can reveal the existence of communities. Phylogenetic methods help infer the history of an epidemic and incidentally, may help detecting communities. In particular, phylogenetic analyses of HIV-1 epidemics among men who have sex with men (MSM) have revealed the existence of large transmission clusters, possibly resulting from within-community transmissions. Past studies have explored the association between contact networks and phylogenies, including transmission clusters, producing conflicting conclusions about whether network features significantly affect observed transmission history. As far as we know however, none of them thoroughly investigated the role of communities, defined with respect to the network graph, in the observation of clusters.

methodsThe present study investigates, through simulations, community detection from phylogenies. We simulate a large number of epidemics over both unweighted and weighted, undirected random interconnected-islands networks, with islands corresponding to communities. We use weighting to modulate distance between islands. We translate each epidemic into a phylogeny, that lets us partition our samples of infected subjects into transmission clusters, based on several common definitions from the literature. We measure similarity between subjects' island membership indices and transmission cluster membership indices with the adjusted Rand index. RESULTS AND

conclusionAnalyses reveal modest mean correspondence between communities in graphs and phylogenetic transmission clusters. We conclude that common methods often have limited success in detecting contact network communities from phylogenies. The rarely-fulfilled requirement that network communities correspond to clades in the phylogeny is their main drawback. Understanding the link between transmission clusters and communities in sexual contact networks could help inform policymaking to curb HIV incidence in MSMs.

Indexed as

Models, StatisticalPhylogenyAdultCluster AnalysisCommunity NetworksComputer SimulationEpidemicsGenotypeHIV-1HIV InfectionsHomosexuality, MaleHumansIncidenceMaleMiddle AgedResidence Characteristics

Identifiers

PMID26863322
PMCPMC4749335

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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.