Discipline
Infectious disease epidemiology; genomics; network science; mathematical biology
Methodology
Phylodynamic modelling; transmission-network reconstruction; phylogenetic analysis; simulation; statistical classification
Date
30 Jul 2026
Description
Superspreading events can drive infectious disease outbreaks, but identifying them from routine surveillance data is difficult. This project will investigate whether phylodynamic modelling and genomic epidemiological methods can identify transmission networks that contain superspreaders or unusually intense transmission. The student will develop and test network-level indicators based on phylogenetic structure, genetic similarity, cluster growth and inferred transmission histories, using simulated outbreaks and suitable published genomic datasets.
Keywords
Superspreading;transmission networks;genomic epidemiology;phylogenetics
Would Suit Applicants Who
Are interested in infectious disease outbreaks, genomics, networks or quantitative epidemiology and have some programming experience