title: Simple epidemiological dynamics explain phylogenetic clustering of HIV from patients with recent infection.
abstract: Phylogenies of highly genetically variable viruses such as HIV-1 are potentially informative of epidemiological dynamics. Several studies have demonstrated the presence of clusters of highly related HIV-1 sequences, particularly among recently HIV-infected individuals, which have been used to argue for a high transmission rate during acute infection. Using a large set of HIV-1 subtype B pol sequences collected from men who have sex with men, we demonstrate that virus from recent infections tend to be phylogenetically clustered at a greater rate than virus from patients with chronic infection ('excess clustering') and also tend to cluster with other recent HIV infections rather than chronic, established infections ('excess co-clustering'), consistent with previous reports. To determine the role that a higher infectivity during acute infection may play in excess clustering and co-clustering, we developed a simple model of HIV infection that incorporates an early period of intensified transmission, and explicitly considers the dynamics of phylogenetic clusters alongside the dynamics of acute and chronic infected cases. We explored the potential for clustering statistics to be used for inference of acute stage transmission rates and found that no single statistic explains very much variance in parameters controlling acute stage transmission rates. We demonstrate that high transmission rates during the acute stage is not the main cause of excess clustering of virus from patients with early/acute infection compared to chronic infection, which may simply reflect the shorter time since transmission in acute infection. Higher transmission during acute infection can result in excess co-clustering of sequences, while the extent of clustering observed is most sensitive to the fraction of infections sampled.
authors: Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America. erikvolz@umich.edu
authors: Erik M
authors: EM
authors: Volz
authors: James S
authors: JS
authors: Koopman
authors: Melissa J
authors: MJ
authors: Ward
authors: Andrew Leigh
authors: AL
authors: Brown
authors: Simon D W
authors: SD
authors: Frost
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology; D003198:Computer Simulation; D058872:Epidemics / Q000706:statistics & numerical data; D015981:Epidemiologic Factors; D015751:Genes, pol; D015658:HIV Infections / Q000453:epidemiology / Q000635:transmission / Q000821:virology*; D015497:HIV-1 / Q000145:classification* / Q000235:genetics*; D018451:Homosexuality, Male; D006801:Humans; D008297:Male; D008824:Michigan / Q000453:epidemiology; D008954:Models, Biological; D010802:Phylogeny; D013997:Time Factors