ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2013
Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.
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85 citing papers in PubMed.
- PhyloCNN: Improving Tree Representation and Neural Network Architecture for Deep Learning from Trees in Phylodynamics and Diversification Studies.Systematic biology · 2026Article
- Assessing the inference of single-cell phylogenies and population dynamics from CRISPR lineage recordings.PLoS computational biology · 2026Article
- Estimating the Growth Rate of a Birth and Death Process Using data From a Small Sample.Bulletin of mathematical biology · 2026Article
- Phylogenetics and molecular evolution to understand and curb the HIV pandemic.Nature reviews. Microbiology · 2026Review
- phyddle: Software for Exploring Phylogenetic Models with Deep Learning.Systematic biology · 2025Article
- Robust phylodynamic inference and model specification for HIV transmission dynamics.Epidemics · 2025Article
- MASCOT-Skyline integrates population and migration dynamics to enhance phylogeographic reconstructions.PLoS computational biology · 2025Article
- Bayesian phylodynamic inference of population dynamics with dormancy.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Accounting for contact tracing in epidemiological birth-death models.PLoS computational biology · 2025Article
- Bayesian mixture models for phylogenetic source attribution from consensus sequences and time since infection estimates.Statistical methods in medical research · 2025Article
- phyddle: software for exploring phylogenetic models with deep learning.bioRxiv : the preprint server for biology · 2025Article
- Reading Yule in light of the history and present of macroevolution.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Article
- Phylodynamics beyond neutrality: the impact of incomplete purifying selection on viral phylogenies and inference.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Article
- Bayesian phylodynamic inference of population dynamics with dormancy.bioRxiv : the preprint server for biology · 2025Article
- PhyloJunction: A Computational Framework for Simulating, Developing, and Teaching Evolutionary Models.Systematic biology · 2024Article
- Integrating Contact Tracing Data to Enhance Outbreak Phylodynamic Inference: A Deep Learning Approach.Molecular biology and evolution · 2024Article
- High-resolution epidemiological landscape from ~290,000 SARS-CoV-2 genomes from Denmark.Nature communications · 2024Article
- Fast and Accurate Maximum-Likelihood Estimation of Multi-Type Birth-Death Epidemiological Models from Phylogenetic Trees.Systematic biology · 2023Article
- PhyloJunction: a computational framework for simulating, developing, and teaching evolutionary models.bioRxiv : the preprint server for biology · 2023Article
- Replicating superspreader dynamics with compartmental models.Scientific reports · 2023Article
25 more citing papers are in PubMed but not listed here.
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2 authors.
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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).
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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.