Response to the COVID-19 pandemic
Research
Previous and current modelling work has undertaken problems in the following areas of mathematical epidemiology.
Response to the COVID-19 pandemic: Using real time data on the UK COVID-19 outbreak to provide robust predictions, gauging the ability of a model to predict future epidemic behaviour.
Mathematical & Economic Modelling for Vaccination and Immunisation Evaluation (MEMVIE): Mathematical modelling and analysis of seasonal influenza to underpin vaccination policy for the Department of Health.
Influenza A at the human-animal interface: Influenza inhabits many hosts and has many strains, but there is a worrying gap in the modelling of spillover transmission from animals to humans. Looking at addressing the lack of established modelling tools that represent this interface, with the applied aim of aiding the design and performance assessment of control strategies for influenza among livestock and across the animal-human interface.
Social contagion: Spread of behaviour-linked health problems are amenable to being represented with methodological approaches typically used to model infectious diseases. We explore this with regards to depression, developing novel models that exploit the dynamical behaviour of mood over time to ascertain which mood states spread on social networks, via a contagion-like mechanism, and which do not.
Farmer-led Epidemic & Endemic Disease-management (FEED): Predicting the differences between national-level and farmer-level optimisation of controls using mathematical models that combine disease spread and farmer behaviour.
Visceral leishmaniasis in Brazil: Developing a mathematical model of visceral leishmaniasis in Brazil; a vector borne disease with canines being an animal reservoir.
