Mathematical modelling and economic analysis are key tools for understanding the health and economic burden of disease, and for guiding disease control including evaluating the most efficient approaches. We use a range of theoretical and computational methodologies to address some of the most challenging health questions and we’re at the forefront of developing methods in this area.

Our goals

Through engagement with policy makers, clinicians, patient groups and other researchers, we promote multi-disciplinary research that improves health, healthcare and wellbeing.


Mathematical modelling

Mathematical modelling research in the school is mostly applied in the context of infectious diseases. This includes  predicting the impacts of preventive interventions such as vaccination and informs real-time decision support in the face of pandemic threats such as COVID-19. 


Health economics

We use a variety of economic and econometrics methods to help address cost-effectiveness, efficiency, and inequalities in healthcare, and focus on the economic evaluations of:   

  • health management policies and answering interesting policy questions using large and complex datasets 

  • health financing systems in low- and middle-income countries 

  • infectious disease prevention strategies. 


Our expertise

 We specialise in a broad range of cutting-edge tools and techniques including epidemiological models, epidemiological analysis, economic evaluation, economic analysis, and operations research techniques. We apply these tools and techniques across a range of research areas, such as:  

  • Applying mathematical models of COVID-19 transmission and the effect of outbreak responses and movement restrictions.

  • Modelling and cost-effectiveness analyses to inform immunisation strategies for vaccine-preventable diseases.

  • Providing early warnings of new COVID-19 waves. 

  • Modelling the impact of novel population interventions on sexually transmitted infections.

  • Applying econometric methods to guide health policy decisions.

  • Developing new health inequity measures based on big data.

  • Evaluating the burden distribution of paying for health care and the benefits from public spending on health across population groups.

  • Assessing the development and performance of national health insurance systems in low- and middle- income settings.

  • Examining effective health systems design, operation, and performance under normal and surge/stress situations.


Our experts