ArticlePLoS computational biology2017
Phylodynamics on local sexual contact networks.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 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
- Accounting for contact tracing in epidemiological birth-death models.PLoS computational biology · 2025Article
- Leveraging insect-specific viruses to elucidate mosquito population structure and dynamics.PLoS pathogens · 2023Review
- Deep learning from phylogenies to uncover the epidemiological dynamics of outbreaks.Nature communications · 2022Article
- The role of high-risk geographies in the perpetuation of the HIV epidemic in rural South Africa: A spatial molecular epidemiology study.PLOS global public health · 2022Article
- Reconstructing contact network structure and cross-immunity patterns from multiple infection histories.PLoS computational biology · 2021Article
- Identifying likely transmissions in Mycobacterium bovis infected populations of cattle and badgers using the Kolmogorov Forward Equations.Scientific reports · 2020Article
- Inferring transmission heterogeneity using virus genealogies: Estimation and targeted prevention.PLoS computational biology · 2020Article
- Assessing biases in phylodynamic inferences in the presence of super-spreaders.Veterinary research · 2019Article
- Phylogenies from dynamic networks.PLoS computational biology · 2019Article
- Detection of HIV transmission clusters from phylogenetic trees using a multi-state birth-death model.Journal of the Royal Society, Interface · 2018Article
- Tracking external introductions of HIV using phylodynamics reveals a major source of infections in rural KwaZulu-Natal, South Africa.Virus evolution · 2018Article
- Genetic Cluster Analysis for HIV Prevention.Current HIV/AIDS reports · 2018Review
- Quantifying the fitness cost of HIV-1 drug resistance mutations through phylodynamics.PLoS pathogens · 2018Observational
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4 authors.
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Abstract
Phylodynamic models are widely used in infectious disease epidemiology to infer the dynamics and structure of pathogen populations. However, these models generally assume that individual hosts contact one another at random, ignoring the fact that many pathogens spread through highly structured contact networks. We present a new framework for phylodynamics on local contact networks based on pairwise epidemiological models that track the status of pairs of nodes in the network rather than just individuals. Shifting our focus from individuals to pairs leads naturally to coalescent models that describe how lineages move through networks and the rate at which lineages coalesce. These pairwise coalescent models not only consider how network structure directly shapes pathogen phylogenies, but also how the relationship between phylogenies and contact networks changes depending on epidemic dynamics and the fraction of infected hosts sampled. By considering pathogen phylogenies in a probabilistic framework, these coalescent models can also be used to estimate the statistical properties of contact networks directly from phylogenies using likelihood-based inference. We use this framework to explore how much information phylogenies retain about the underlying structure of contact networks and to infer the structure of a sexual contact network underlying a large HIV-1 sub-epidemic in Switzerland.
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