Mathematical modeling and adaptive control to inform real time decision making for the COVID-19 pandemic at the local, regional and national scale

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The world is currently being devastated by a pandemic of coronavirus disease (COVID-19) which, at the time of writing, has resulted in almost 1 million confirmed cases of infection and around 50,000 deaths worldwide. Around one third of the global population are under some form of restriction - causing huge economic burdens - and for many countries, focus has turned to how planning an "exit strategy" from some of the most severe social distancing measures that the world has ever seen.This project will use real time data on the UK COVID-19 outbreak to provide robust predictions, guaging the ability of a model to predict future epidemic behaviour. We will investigate how our short- and long-term predictions change during an outbreak as more information becomes available, how this may effect forecasts of the appropriate control measures that should be introduced and when and how such policies should be relaxed. Finally, taking into account the potential for future waves of infection, we will use our model to determine optimal adaptive control policies that should be implemented to reduce the number of deaths as a result of the COVID-19 outbreak and to minimise the impact on the health service.