title: Assessment of Overlap of Phylogenetic Transmission Clusters and Communities in Simple Sexual Contact Networks: Applications to HIV-1.
abstract: BACKGROUND
  Transmission 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.
  
  
  METHODS
  The 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.
  
  
  CONCLUSIONS
  Analyses 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.
authors: Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Québec, Canada.
authors: Luc
authors: L
authors: Villandre
authors: Department of Mathematics and Statistics, McGill University, Montréal, Québec, Canada.
authors: David A
authors: DA
authors: Stephens
authors: Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Québec, Canada.|Department of Psychiatry, Douglas Mental Health University Institute, Montréal, Québec, Canada.
authors: Aurelie
authors: A
authors: Labbe
authors: Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Kanton Zurich, Switzerland.|Institute of Medical Virology, University of Zurich, Zurich, Switzerland.
authors: Huldrych F
authors: HF
authors: Günthard
authors: Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Kanton Zurich, Switzerland.|Institute of Medical Virology, University of Zurich, Zurich, Switzerland.
authors: Roger
authors: R
authors: Kouyos
authors: Department of Biosystems Science and Engineering, ETH Zürich, Basel, Basel-Landschaft, Switzerland.|Swiss Institute of Bioinformatics, Lausanne, Switzerland.
authors: Tanja
authors: T
authors: Stadler
mesh_terms: D000328:Adult; D016000:Cluster Analysis; D019058:Community Networks / Q000706:statistics & numerical data; D003198:Computer Simulation; D058872:Epidemics / Q000517:prevention & control*; D005838:Genotype; D015658:HIV Infections / Q000453:epidemiology* / Q000523:psychology / Q000635:transmission* / Q000821:virology; D015497:HIV-1 / Q000145:classification / Q000235:genetics*; D018451:Homosexuality, Male; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010802:Phylogeny; D012111:Residence Characteristics / Q000706:statistics & numerical data; D012747:Sexual Partners; D013557:Switzerland / Q000453:epidemiology