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Updated: May 4, 2026
08:57
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
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Inferring the source of transmission with phylogenetic data
Erik M Volz1, Simon D W Frost2
1Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Plos Computational Biology
|December 25, 2013
Summary
Identifying infectious disease transmission sources is challenging with incomplete data. New methods use epidemic data to improve transmission probability estimates, aiding forensic and epidemiological investigations.
Area of Science:
- Epidemiology
- Genetics
- Public Health
Background:
- Identifying pathogen transmission sources is complex due to biological and sampling limitations.
- Incomplete case sampling introduces errors, hindering accurate source attribution and transmission chain analysis.
- Quantifying common source or intermediary transmission is difficult, limiting statistical tests for genetic transmission data.
Purpose of the Study:
- To develop a method integrating epidemic data (incidence, prevalence) with pathogen genetic data.
- To improve estimates of direct host-to-host transmission probability within pathogen gene genealogies.
- To enable forensic and epidemiological applications for infectious diseases with sparse sampling.
Main Methods:
- Incorporation of temporal epidemic data (incidence, prevalence) into phylogenetic analyses.
- Development of statistical methods to estimate transmission probabilities between hosts.
- Application and evaluation of methods using HIV epidemic data from Detroit, Michigan.
Main Results:
- The developed method enhances the accuracy of transmission source attribution in epidemics with incomplete sampling.
- HIV drug resistance sequence databases are generally insufficient for forensic investigations but valuable for identifying transmission risk factors.
- The approach is applicable to high-morbidity pathogens like HIV, Influenza, and Dengue virus.
Conclusions:
- Integrating epidemiological data with genetic analysis provides a robust framework for understanding infectious disease transmission.
- The findings highlight the need for optimized data collection strategies for both forensic and epidemiological purposes.
- The study advances the capability to perform source-case attribution and identify transmission dynamics in real-world public health scenarios.
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