The challenges of data in future pandemics

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Date
09/2022
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Abstract
The use of data has been essential throughout the unfolding COVID-19 pandemic. We have needed it to populate our models, inform our understanding, and shape our responses to the disease. However, data has not always been easy to find and access, it has varied in quality and coverage, been difficult to reuse or repurpose. This paper reviews these and other challenges and recommends steps to develop a data ecosystem better able to deal with future pandemics by better supporting preparedness, prevention, detection and response.
Citation
Shadbolt , N , Brett , A , Chen , M , Marion , G , McKendrick , I J , Panovska-Griffiths , J , Pellis , L , Reeve , R & Swallow , B 2022 , ' The challenges of data in future pandemics ' , Epidemics , vol. 40 , 100612 . https://doi.org/10.1016/j.epidem.2022.100612
Publication
Epidemics
Status
Peer reviewed
DOI
https://doi.org/10.1016/j.epidem.2022.100612
ISSN
1878-0067
Type
Journal article
Rights
Copyright © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Description
This work was supported by Engineering and Physical Sciences Research Council (EPSRC) grant no. EP/R014604/1. M.C. was funded by the Engineering and Physical Sciences Research Council (EPSRC) grant no. EP/V054236/1. G.M. is supported by the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS). J.P-G’s work is supported by funding from the UK Health Security Agency and the UK Department of Health and Social Care. L.P. is funded by the Wellcome Trust, UK and the Royal Society, UK (grant no. 202562/Z/16/Z). L.P. is supported by the UK Research and Innovation (UKRI) through the JUNIPER modelling consortium (grant no. MR/V038613/1). L.P. is also supported by The Alan Turing Institute for Data Science and Artificial Intelligence, UK. R.R was supported by the Natural Environment Research Council (NERC) grant no. NE/T004193/1 and NE/T010355/1, the Engineering and Physical Sciences Research Council (EPSRC) grant no. EP/V054236/1 and the Science and Technology Facilities Council (STFC) grant no. ST/V006126/1.
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http://hdl.handle.net/10023/26089

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