Phylogenetic analysis provides a tool to quantify infectious disease dynamics by leveraging the information contained in genetic sequence data to infer epidemic spread. When pathogen sequences are routinely generated via drug resistance testing - as is the case in many countries for HIV - these data can be analysed using phylogenetic analysis to provide a unique insight into real time epidemic spread.

With the advent of pre-exposure prophylaxis and intensive test-and-treat policies, HIV elimination has become possible. However, to achieve elimination, we will increasingly require new methods to detect and control clusters of transmission. Real time phylogenetic analysis may provide one such method. However, there is scant evidence on whether incorporating phylogenetic analysis within an infectious disease control programme for HIV elimination is effective.

By working closely with the UK Health Security Agency, this project will develop policy-driven methods to understand the utility of how the UK can effectively use phylogenetic tools to complement the existing HIV elimination strategy.

The project will use an interdisciplinary combination of mathematical or statistical modelling, epidemiology, and phylogenetic analysis. The candidate will develop their quantitative skills using these tools. The student will develop or extend their programming expertise in languages, such as R or Python. Emphasis will be placed on developing and sharing code for the wider scientific community through platforms such as GitHub.

The student will learn to communicate their research through publication in peer-reviewed journals and presentation in scientific conferences. By working closely with experts in public health, sequence data, phylogenetic analysis and mathematical modelling, the student will become comfortable working within an interdisciplinary environment and interacting with a diverse scientific team.