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The challenges of data in future pandemics.
Shadbolt, Nigel; Brett, Alys; Chen, Min; Marion, Glenn; McKendrick, Iain J; Panovska-Griffiths, Jasmina; Pellis, Lorenzo; Reeve, Richard; Swallow, Ben.
  • Shadbolt N; Department of Computer Science, University of Oxford, UK; The Open Data Institute, London, UK. Electronic address: nigel.shadbolt@cs.ox.ac.uk.
  • Brett A; UKAEA Software Engineering Group, UK; Scottish COVID-19 Response Consortium, UK.
  • Chen M; Department of Engineering Science, University of Oxford, UK; Scottish COVID-19 Response Consortium, UK.
  • Marion G; Biomathematics and Statistics Scotland, Edinburgh, UK; Scottish COVID-19 Response Consortium, UK.
  • McKendrick IJ; Biomathematics and Statistics Scotland, Edinburgh, UK; Scottish COVID-19 Response Consortium, UK.
  • Panovska-Griffiths J; The Big Data Institute, University of Oxford, UK; The Wolfson Centre for Mathematical Biology, University of Oxford, UK; The Queen's College, University of Oxford, UK.
  • Pellis L; Department of Mathematics, University of Manchester, UK; The Alan Turing Institute, London, UK.
  • Reeve R; Scottish COVID-19 Response Consortium, UK; Institute of Biodiversity Animal Health & Comparative Medicine, University of Glasgow, UK.
  • Swallow B; Scottish COVID-19 Response Consortium, UK; School of Mathematics and Statistics, University of Glasgow, UK.
Epidemics ; 40: 100612, 2022 09.
Article in English | MEDLINE | ID: covidwho-1936398
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Epidemics Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Epidemics Year: 2022 Document Type: Article