We focus on the evolution of viral infections using a variety of approaches including population genetics, deterministic and stochastic modelling, and the evolutionary analysis of viral sequence data. One of our key aims is to produce better predictive models of how viral populations evolve in response to change, be that in a new individual after a transmission event, in a population after a zoonotic jump, or in response to interventions such as immunisation or treatment.
We are a diverse and interactive group consisting of postdocs, graduate students, 4th year MBiol students, and undergraduates. Some of our current projects include:
- Using viral deep and long-read sequencing data to understand the evolution and within-host population structure of viral populations such as Hepatitis C virus
- Determining how within-host evolutionary processes affect the evolution of viruses at the population scale, with a current focus on HIV
- Developing new methods to identify persistent SARS-CoV-2 infections and within-household transmission chains using data from the ONS Covid Infection Survey
- Designing optimal strategies for the genomic surveillance of viral pathogens
