Epidemic modelling and digital intervention strategies
for infectious disease: a COVID-19 case study of three
English cities
Publication Date
December 11, 2020
Creator
Abstract
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.
Item Type
ethesis
Thesis Type
MRes
Supervisors
Subjects (LC)
Associated Schools / Departments
Department of Chemical and Environmental Engineering (UK)
eprints ID
63852
UoN Repository URI
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Name
Tahsinur_Khan_MRes_Report_Updated.pdf
Type
Full-text
Description
Examined. Thesis for MRes Geospatial Data Science
Size
1.69 MB
Format
Adobe PDF
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