Mathematical Modelling of Infectious Diseases

The Mathematical Modelling of Infectious Diseases Group specialises in developing and refining mathematical models to estimate and project the spread and burden of infectious diseases.

Our work encompasses both within-host infection dynamics and between-host transmission dynamics. We focus on within-host dynamics, including pharmacokinetic/pharmacodynamic (PK/PD) models, and investigate their relationship to transmission between hosts. These population models are evaluated using compartmental, network, and agent-based modelling frameworks. Additionally, we develop and implement fast, large-scale simulation frameworks to complement the models.

We utilise data from a variety of sources to parameterise the models, including biological data on immune responses and viral loads, secondary data from surveillance systems, clinical trials, drug trials, and observational studies, as well as primary data collected through our own surveys and trials. This diverse data provides a sustainable feedback loop that enhances our model estimates and projections, guides data collection, and informs experimental design.

Simulations are employed to assess theoretical concepts and practical intervention strategies for their potential impact on health and socioeconomic outcomes. Our work has been applied to epidemics such as HIV, influenza, COVID-19, Ebola, and plague. We aim to provide a comprehensive understanding of infectious disease transmission and control, thereby informing evidence-based public health policy and practice.