Complex model calibration through emulation, a worked example for a stochastic epidemic model

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; Swallow, Ben

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.

Citation

Dunne, M., Mohammadi, H., Challenor, P., Borgo, R., Porphyre, T., Vernon, I., Firat, E. E., Turkay, C., Torsney-Weir, T., Goldstein, M., Reeve, R., Fang, H., & Swallow, B. (2022). Complex model calibration through emulation, a worked example for a stochastic epidemic model. Epidemics, 39, Article 100574. https://doi.org/10.1016/j.epidem.2022.100574

• Journal Article Type: Article
• Acceptance Date: Apr 29, 2022
• Online Publication Date: May 16, 2022
• Publication Date: 2022-06
• Deposit Date: May 18, 2022
• Publicly Available Date: May 18, 2022
• Journal: Epidemics
• Print ISSN: 1755-4365
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 39
• Article Number: 100574
• DOI: https://doi.org/10.1016/j.epidem.2022.100574
• Public URL: https://durham-repository.worktribe.com/output/1207080