PhD Studentship in the mathematical modelling of infectious disease transmission and control

The COVID-19 pandemic has demonstrated the urgent need for improved preparedness to control the outbreak of emerging respiratory virus infections. The overall aim of the project will be the development of mathematical and computational tools to improve understanding of i) the replication of respiratory viruses, such as SARS-CoV-2 and influenza, within an individual host, ii) the transmission of viral infections between individuals in highly heterogeneous environments. The tools will be employed to facilitate the development and assessment of novel prophylactic treatments for the prevention of pathogenic respiratory virus infections.

The focus will be on the development of a novel class of within-host models of viral dynamics that would address the challenges of model parametrisation given the available data, improve the description of the dynamical changes of viral load in different risk groups, and generate insights into the impact of antivirals in combination of that of the immune response. The within-host model will be linked to i) a clinical trial simulation, an essential tool in drug development, to inform the clinical trial design prior to the conduct of the actual clinical studies, ii) an individual-based transmission model of disease dynamics that will be used to assess the potential impact of treatments on controlling the transmission of emerging respiratory infections in the community. As part of this, the impact of the heterogeneity in the structure of the individuals contact network on disease transmission will be investigated. The models will be calibrated within a Bayesian framework using the available clinical and epidemiological data.

The candidate will gain experience in a range of mathematical and computational techniques that are useful for the modelling of many real-life systems. These include the development and analysis of stochastic models, computer simulations, differential equations, statistical inference, analysis of clinical and epidemiological data.

The candidate will have the opportunity to plan, carry out and lead high-quality research in the area of infectious diseases, but also be involved in other research activities of the group. They may also have the chance to work with leading researchers from other academic institutions around the world, as well as industrial partners. This PhD project provides an excellent opportunity to develop state-of-the-art mathematical models and computational tools of emerging respiratory pathogens, within a world-renowned research group.

The Mathematics applied to Biology Group undertakes leading interdisciplinary research on infectious diseases, using approaches ranging from mathematical modelling of viral kinetics, through the modelling of disease transmission dynamics and control, to the simulation of clinical trials of potential treatments. The Department of Mathematics at Sussex offers excellent research facilities and a friendly, intellectually stimulating working environment.