Epidemic modelling and digital intervention strategies for infectious disease: a COVID-19 case study of three English cities

Khan, Tahsinur Rahman (2020) Epidemic modelling and digital intervention strategies for infectious disease: a COVID-19 case study of three English cities. MRes thesis, University of Nottingham.

[img] PDF (Thesis for MRes Geospatial Data Science) (Thesis - as examined) - Repository staff only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB)

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: Thesis (University of Nottingham only) (MRes)
Supervisors: Marsh, Stuart
Kypraios, Theodore
Keywords: COVID-19, Coronavirus, Epidemic modelling, Mathematical models, Agent-based computational models, Public health response.
Subjects: R Medicine > RA Public aspects of medicine > RA 421 Public health. Hygiene. Preventive Medicine
Faculties/Schools: UK Campuses > Faculty of Engineering > Department of Chemical and Environmental Engineering
Item ID: 63852
Depositing User: Khan, Tahsinur
Date Deposited: 07 Jan 2021 16:58
Last Modified: 07 Jan 2021 17:00
URI: http://eprints.nottingham.ac.uk/id/eprint/63852

Actions (Archive Staff Only)

Edit View Edit View