The Disease Modelling and Intervention Dynamics research group develops new mathematical models and methodology applied to diseases with highly complex dynamics. We work to understand how pathogen, host and intervention dynamics combine to prevent disease progression and transmission.
We are an interdisciplinary group of researchers that develops and uses models to understand parasitic and viral diseases, and to inform public health decision-making. We use data analysis, and modelling and simulation, to examine complex interactions between infectious diseases, individuals and populations, medical interventions and health systems. We apply novel statistical approaches to calibrate and use complex disease models.
Generate Evidence for Decision-Making
Our 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 drug, vaccine and other intervention development through selection of candidate interventions with optimal properties. Through our close relationships with global health stakeholders, our model-based evidence supports selection of optimal deployment strategies to achieve disease burden reduction or elimination. These strategies can include combination therapies, and take into account complex seasonality and country setting differences.
Our current main diseases of interest are malaria and SARS-CoV-2.
Selected ProjectsAll Projects
Latest PublicationsAll Publications
Nekkab N, Malinga J, Braunack-Mayer L, Kelly S.L, Miller R.S, Penny M.A. Modelling to inform next-generation medical interventions for malaria prevention and treatment. Commun Med (Lond). 2023;3:41. DOI: 10.1038/s43856-023-00274-0
Ali A.M et al. Population pharmacokinetics of antimalarial naphthoquine in combination with artemisinin in Tanzanian children and adults: dose optimization. Antimicrob Agents Chemother. 2022;66(5):e0169621. DOI: 10.1128/aac.01696-21
Burgert L, Reiker T, Golumbeanu M, Möhrle J.J, Penny M.A. Model-informed target product profiles of long-acting-injectables for use as seasonal malaria prevention. PLOS Glob Public Health. 2022;2(3):e0000211. DOI: 10.1371/journal.pgph.0000211
Golumbeanu M et al. Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions. Infect Dis Poverty. 2022;11:61. DOI: 10.1186/s40249-022-00981-1
Kelly S.L, Le Rütte E.A, Richter M, Penny M.A, Shattock A.J. COVID-19 vaccine booster strategies in light of emerging viral variants: frequency, timing, and target groups. Infect Dis Ther. 2022;11(5):2045-2061. DOI: 10.1007/s40121-022-00683-z