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Complex model calibration through emulation, a worked example for a stochastic epidemic model
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Dunne, Michael, Mohammadi, Hossein, Challenor, Peter, Borgo, Rita, Porphyre, Thibaud, Vernon, Ian, Firat, Elif E., Turkay, Cagatay, Torsney-Weir, Thomas, Goldstein, Michael, Reeve, Richard, Fang, Hui and Swallow, Ben (2022) Complex model calibration through emulation, a worked example for a stochastic epidemic model. Epidemics, 39 . 100574. doi:10.1016/j.epidem.2022.100574 ISSN 1755-4365.
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Official URL: https://doi.org/10.1016/j.epidem.2022.100574
Abstract
Uncertainty quantification is a formal paradigm of statistical estimation that aims to account for all uncertainties inherent in the modelling process of real-world complex systems. The methods are directly applicable to stochastic models in epidemiology, however they have thus far not been widely used in this context. In this paper, we provide a tutorial on uncertainty quantification of stochastic epidemic models, aiming to facilitate the use of the uncertainty quantification paradigm for practitioners with other complex stochastic simulators of applied systems. We provide a formal workflow including the important decisions and considerations that need to be taken, and illustrate the methods over a simple stochastic epidemic model of UK SARS-CoV-2 transmission and patient outcome. We also present new approaches to visualisation of outputs from sensitivity analyses and uncertainty quantification more generally in high input and/or output dimensions.
Item Type: | Journal Article | |||||||||||||||
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Subjects: | Q Science > QA Mathematics R Medicine > RA Public aspects of medicine |
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Divisions: | Faculty of Social Sciences > Centre for Interdisciplinary Methodologies | |||||||||||||||
SWORD Depositor: | Library Publications Router | |||||||||||||||
Library of Congress Subject Headings (LCSH): | Measurement uncertainty (Statistics), Stochastic models, Stochastic processes, Epidemiology -- Mathematical models | |||||||||||||||
Journal or Publication Title: | Epidemics | |||||||||||||||
Publisher: | Elsevier BV | |||||||||||||||
ISSN: | 1755-4365 | |||||||||||||||
Official Date: | June 2022 | |||||||||||||||
Dates: |
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Volume: | 39 | |||||||||||||||
Article Number: | 100574 | |||||||||||||||
DOI: | 10.1016/j.epidem.2022.100574 | |||||||||||||||
Status: | Peer Reviewed | |||||||||||||||
Publication Status: | Published | |||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||||||||
Date of first compliant deposit: | 6 December 2022 | |||||||||||||||
Date of first compliant Open Access: | 8 December 2022 | |||||||||||||||
RIOXX Funder/Project Grant: |
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