Antibiotic resistance (ABR) is a growing global problem that requires innovative, cross-disciplinary solutions. Mathematical modelling can be used to integrate data from multiple sources to give novel insights and clinically relevant outputs such as the future impact of public health interventions. In this project, clinical and experimental data will be used to parameterise new mechanistic models to explore the reasons for the evolutionary dynamics of ABR from a clinical and potentially One Health framework. Linking changes in antibiotic use with ABR heterogeneity in clinical populations of methicillin resistant Staphylococcus aureus (MRSA), we will design and evaluate new interventions for control, such as the impact of antibiotic stewardship.

The outputs generated by the student will have direct translational impact on clinical practice and will inform our understanding of underlying evolutionary changes and how these can be optimally harnessed for ABR control.

This project would be supervised by Gwen Knight (mathematical modeller, LSHTM, https://www.lshtm.ac.uk/aboutus/people/knight.gwen) and Jodi Lindsay (microbiologist, SGUL, https://www.sgul.ac.uk/research-profiles-a-z/jodi-lindsay). The student will need to apply to the MRC LID programme (http://mrc-lid.lshtm.ac.uk/) and then will be able to choose this project.