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Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Swallow, Ben 
Birrell, Paul 
Blake, Joshua 
Burgman, Mark 
Challenor, Peter 

Abstract

The estimation of parameters and model structure for informing infectious disease response has become a focal point of the recent pandemic. However, it has also highlighted a plethora of challenges remaining in the fast and robust extraction of information using data and models to help inform policy. In this paper, we identify and discuss four broad challenges in the estimation paradigm relating to infectious disease modelling, namely the Uncertainty Quantification framework, data challenges in estimation, model-based inference and prediction, and expert judgement. We also postulate priorities in estimation methodology to facilitate preparation for future pandemics.

Description

Keywords

Expert elicitation, Pandemic modelling, Statistical estimation, Uncertainty quantification, Forecasting, Pandemics, Uncertainty

Journal Title

Epidemics

Conference Name

Journal ISSN

1755-4365
1878-0067

Volume Title

38

Publisher

Elsevier BV
Sponsorship
Engineering and Physical Sciences Research Council (EP/R014604/1)
MRC (via University of Warwick) (MR/V038613/1)