| Summary: | The emergence of the novel coronavirus and the resulting global pandemic has shown the importance of epidemic modelling and how sound, scientifically driven policies can aid in response efforts. In purely quantitative terms, an epidemic event can be considered as one of the most complex geospatial events to be modelled and make prediction about. However, mathematical and computational models have been applied in the past with success in understanding and tackling such events. In this report we will cover the two main approaches for epidemic modelling – mathematical and agent-based computational models and compare and contrast the results in the context of three English cities – Leicester, Bradford and Blackburn, that have been heavily impacted by the Covid-19 pandemic. We will also discuss some plans on future research directions on constructing a robust pandemic resiliency framework that can be deployed across local geographical regions to aid public health authorities deal with pandemic outbreaks.
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