Gastrointestinal viruses can be very dangerous for people with pre-existing conditions, especially chronic renal conditions. Understanding how the changing circulation of pathogens in the general population impacts the timing of risk of disease in these groups is needed, so that we can design interventions to prevent their spread.

This research project will develop dynamic transmission models for gastrointestinal viruses such as norovirus and rotavirus, and use electronic health records to detect hospitalisation events in groups with chronic renal disease. We will use these to quantify the links between the timing of events, the circulation of viruses, and other factors (such as climate) on the risk of hospitalisations.

The research project also seeks to quantify the health and economic impact of gastrointestinal viruses on populations with chronic disease. Using the model and the health and economic quantification, we will then estimate the cost-effectiveness of healthcare interventions such as vaccination to mitigate the burden and control the transmission of gastrointestinal infections.

This project will train the student in epidemiology, mathematical modelling of infectious disease, Bayesian parameter inference, health economics, and skills in big data use and management. They will build skills in scientific writing, as well as critical reading of the literature. The student will also learn to give clear scientific presentations communicating their work.

The successful applicant will be part of the Faculty of Epidemiology and Population Health at LSHTM as well as the Modelling and Economics Unit at PHE. The applicant will join the vibrant Centre for Mathematical Modelling of Infectious Diseases at LSHTM which has a focused early-career researcher seminar and team-learning series. The student will also join the Electronic Health Records group at LSHTM. The student will also benefit from interacting with other national experts e.g. through the HPRU in Gastrointestinal Infections.

The principal supervisors will be Dr Rosalind Eggo, Assistant Professor of Infectious Disease Modelling, and Dr Laurie Tomlinson, Associate Professor of Renal Epidemiology. Dr Eggo is a leading researcher in modelling of directly-transmitted pathogens, and in the study of infectious-chronic comorbidity. Dr Tomlinson is a clinical specialist in electronic health records analysis, especially of renal conditions. The student will also benefit from supervision from Dr Frank Sandmann at Public Health England, a specialist in health economics and modelling gastrointestinal infections. A further co-supervisor at Imperial College will also be involved.