The challenges of data in future pandemics

Nigel Shadbolt; Alys Brett; Min Chen; Glenn Marion; Iain J McKendrick; Jasmina Panovska-Griffiths; Lorenzo Pellis; Richard Reeve; Ben Swallow

doi:10.1016/j.epidem.2022.100612

The challenges of data in future pandemics

Nigel Shadbolt^*, Alys Brett, Min Chen, Glenn Marion, Iain J McKendrick, Jasmina Panovska-Griffiths, Lorenzo Pellis, Richard Reeve, Ben Swallow

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Article number	100612
Number of pages	16
Journal	Epidemics
Volume	40
Early online date	2 Aug 2022
DOIs	https://doi.org/10.1016/j.epidem.2022.100612
Publication status	Published - Sept 2022

Keywords

Data and models
Data ecosystem
Data lifecycles
FAIR data
Pandemic preparedness
COVID-19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.epidem.2022.100612Licence: CC BY

Shadbolt_2022_Epidemics_Challenges-data_CC
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/).
Final published version, 953 KBLicence: CC BY

Cite this

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title = "The challenges of data in future pandemics",

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.",

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author = "Nigel Shadbolt and Alys Brett and Min Chen and Glenn Marion and McKendrick, {Iain J} and Jasmina Panovska-Griffiths and Lorenzo Pellis and Richard Reeve and Ben Swallow",

note = "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{\textquoteright}s Rural and Environment Science and Analytical Services Division (RESAS). J.P-G{\textquoteright}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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AU - McKendrick, Iain J

AU - Panovska-Griffiths, Jasmina

AU - Pellis, Lorenzo

AU - Reeve, Richard

AU - Swallow, Ben

N1 - 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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The challenges of data in future pandemics

Abstract

Keywords

UN SDGs

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