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Phylodynamics on local sexual contact networks
David A Rasmussen1,2, Roger Kouyos3,4, Huldrych F Günthard3,4
1Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Plos Computational Biology
|March 29, 2017
Summary
This study introduces a new phylodynamic framework for analyzing pathogen spread in structured populations. It reveals how contact network structure influences pathogen evolution and can be inferred from genetic data.
Area of Science:
- Epidemiology
- Evolutionary Biology
- Network Science
Background:
- Phylodynamic models commonly assume random host contacts, neglecting realistic structured transmission networks.
- Understanding pathogen spread in networks is crucial for effective disease control.
Purpose of the Study:
- To develop a novel phylodynamic framework for local contact networks.
- To investigate how network structure shapes pathogen phylogenies and infer network properties from genetic data.
Main Methods:
- Developed pairwise epidemiological models for phylodynamics on networks.
- Formulated pairwise coalescent models accounting for network structure.
- Applied likelihood-based inference to estimate network properties from phylogenies.
Main Results:
- Demonstrated that pairwise coalescent models capture the influence of network structure on pathogen phylogenies.
- Showed that phylogenies retain information about underlying contact network structure.
- Successfully inferred the structure of an HIV-1 sexual contact network in Switzerland.
Conclusions:
- The new framework provides a powerful tool for phylodynamic inference on structured populations.
- Phylogenetic data can reveal insights into the topology of transmission networks.
- This approach has implications for understanding and controlling infectious diseases in complex social structures.
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