Group | Disease and Intervention Dynamics

The Disease and Intervention Dynamics research group focuses on understanding pathogen, host and intervention dynamics and developing new mathematical and statistical approaches to understand disease and prevent disease progression and transmission.  

We are an interdisciplinary group of researchers that develop and use models to understand parasitic or viral diseases and to inform public health decision-making. We develop new statistical and mathematical models and use data analysis and modelling and simulation to support understanding the interactions between infectious diseases within host or at the population level and the medical interventions to prevent and cure disease. We apply novel statistical approaches to calibrate and use complex disease models.

Generate Evidence for Decision-Making

The main aim is to generate evidence for decision-making along the whole pathway of new intervention development against infectious diseases, from preclinical to clinical testing, and at implementation in real populations and health systems, including for pandemic responses and preparedness. Our model-based evidence supports efficient selection of optimal drugs, vaccines, immune therapy or vector control to achieve disease burden reduction and elimination.

Our main research areas are in malaria and SARS-CoV-2.

Melissa Penny

Professor Melissa Penny, PhD, PD

Burgert L et al. Ensemble modeling highlights importance of understanding parasite-host behavior in preclinical antimalarial drug development. Sci Rep. 2020;10:4410. DOI: 10.1038/s41598-020-61304-8

Camponovo F et al. Proteome-wide analysis of a malaria vaccine study reveals personalized humoral immune profiles in Tanzanian adults. Elife. 2020;9:e53080. DOI: 10.7554/eLife.53080

Penny M.A, Camponovo F, Chitnis N, Smith T.A, Tanner M. Future use-cases of vaccines in malaria control and elimination. Parasite Epidemiol Control. 2020;10:e00145. DOI: 10.1016/j.parepi.2020.e00145

Stader F et al. Effect of ageing on antiretroviral drug pharmacokinetics using clinical data combined with modelling and simulation. Br J Clin Pharmacol. 2020(in press). DOI: 10.1111/bcp.14402

Stader F et al. Clinical data combined with modelling and simulation indicate unchanged drug-drug interaction magnitudes in the elderly. Clin Pharmacol Ther. 2020(in press). DOI: 10.1002/cpt.2017