The challenges of data in future pandemics

Shadbolt, N., Brett, A., Chen, M., Marion, G., McKendrick, I. J., Panovska-Griffiths, J., Pellis, L., Reeve, R. and Swallow, B. (2022) The challenges of data in future pandemics. Epidemics, 40, 100612. (doi: 10.1016/j.epidem.2022.100612) (PMID:35930904) (PMCID:PMC9297658)

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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.

Item Type:Articles
Keywords:Pandemic preparedness, FAIR data, data ecosystem, data lifecycles, COVID-19, data and models.
Glasgow Author(s) Enlighten ID:Swallow, Dr Ben and Reeve, Professor Richard
Authors: Shadbolt, N., Brett, A., Chen, M., Marion, G., McKendrick, I. J., Panovska-Griffiths, J., Pellis, L., Reeve, R., and Swallow, B.
College/School:College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Epidemics
ISSN (Online):1878-0067
Published Online:20 July 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in Epidemics 40: 100612
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
307517Landscape Decisions: Towards a new framework for using land assets programmeRichard ReeveNatural Environment Research Council (NERC)NE/T004193/1M&S - Mathematics
309089Simulating UK plant biodiversity under climate change to aid landscape decision makingRichard ReeveNatural Environment Research Council (NERC)NE/T010355/1M&S - Mathematics
312172RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19Euan FreemanEngineering and Physical Sciences Research Council (EPSRC)DFR06720Computing Science
311856Open Epidemiology for COVID-19: a transparent, traceable, open source pipeline for reproducible scienceRichard ReeveScience and Technology Facilities Council (STFC)ST/V006126/1Institute of Biodiversity, Animal Health and Comparative Medicine