title: Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods.
abstract: Host population structure has a major influence on epidemiological dynamics. However, in particular for sexually transmitted diseases, quantitative data on population contact structure are hard to obtain. Here, we introduce a new method that quantifies host population structure based on phylogenetic trees, which are obtained from pathogen genetic sequence data. Our method is based on a maximum-likelihood framework and uses a multi-type branching process, under which each host is assigned to a type (subpopulation). In a simulation study, we show that our method produces accurate parameter estimates for phylogenetic trees in which each tip is assigned to a type, as well for phylogenetic trees in which the type of the tip is unknown. We apply the method to a Latvian HIV-1 dataset, quantifying the impact of the intravenous drug user epidemic on the heterosexual epidemic (known tip states), and identifying superspreader dynamics within the men-having-sex-with-men epidemic (unknown tip states).
authors: Institut für Integrative Biologie, ETH Zürich, Universitätsstrasse 16, 8092 Zürich, Switzerland. tanja.stadler@env.ethz.ch
authors: Tanja
authors: T
authors: Stadler
authors: Sebastian
authors: S
authors: Bonhoeffer
mesh_terms: D003198:Computer Simulation; D015658:HIV Infections / Q000453:epidemiology* / Q000235:genetics / Q000635:transmission; D015497:HIV-1 / Q000235:genetics*; D020010:Heterosexuality / Q000706:statistics & numerical data; D018451:Homosexuality, Male / Q000706:statistics & numerical data; D054884:Host-Pathogen Interactions / Q000235:genetics*; D006801:Humans; D007844:Latvia / Q000453:epidemiology; D016013:Likelihood Functions; D008297:Male; D008954:Models, Biological; D008957:Models, Genetic; D010802:Phylogeny; D015819:Substance Abuse, Intravenous / Q000453:epidemiology*
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