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The epidemiological impact of the NHS COVID-19 app.
Wymant, Chris; Ferretti, Luca; Tsallis, Daphne; Charalambides, Marcos; Abeler-Dörner, Lucie; Bonsall, David; Hinch, Robert; Kendall, Michelle; Milsom, Luke; Ayres, Matthew; Holmes, Chris; Briers, Mark; Fraser, Christophe.
  • Wymant C; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
  • Ferretti L; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
  • Tsallis D; Zühlke Engineering Ltd, London, UK.
  • Charalambides M; The Alan Turing Institute, London, UK.
  • Abeler-Dörner L; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
  • Bonsall D; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
  • Hinch R; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
  • Kendall M; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
  • Milsom L; Department of Statistics, University of Warwick, Coventry, UK.
  • Ayres M; Department of Economics, University of Oxford, Oxford, UK.
  • Holmes C; The Alan Turing Institute, London, UK.
  • Briers M; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
  • Fraser C; The Alan Turing Institute, London, UK.
Nature ; 594(7863): 408-412, 2021 06.
Article in English | MEDLINE | ID: covidwho-1225509
ABSTRACT
The COVID-19 pandemic has seen the emergence of digital contact tracing to help to prevent the spread of the disease. A mobile phone app records proximity events between app users, and when a user tests positive for COVID-19, their recent contacts can be notified instantly. Theoretical evidence has supported this new public health intervention1-6, but its epidemiological impact has remained uncertain7. Here we investigate the impact of the National Health Service (NHS) COVID-19 app for England and Wales, from its launch on 24 September 2020 to the end of December 2020. It was used regularly by approximately 16.5 million users (28% of the total population), and sent approximately 1.7 million exposure notifications 4.2 per index case consenting to contact tracing. We estimated that the fraction of individuals notified by the app who subsequently showed symptoms and tested positive (the secondary attack rate (SAR)) was 6%, similar to the SAR for manually traced close contacts. We estimated the number of cases averted by the app using two complementary approaches modelling based on the notifications and SAR gave an estimate of 284,000 (central 95% range of sensitivity analyses 108,000-450,000), and statistical comparison of matched neighbouring local authorities gave an estimate of 594,000 (95% confidence interval 317,000-914,000). Approximately one case was averted for each case consenting to notification of their contacts. We estimated that for every percentage point increase in app uptake, the number of cases could be reduced by 0.8% (using modelling) or 2.3% (using statistical analysis). These findings support the continued development and deployment of such apps in populations that are awaiting full protection from vaccines.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Contact Tracing / Mobile Applications / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: Europa Language: English Journal: Nature Year: 2021 Document Type: Article Affiliation country: S41586-021-03606-z

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Contact Tracing / Mobile Applications / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: Europa Language: English Journal: Nature Year: 2021 Document Type: Article Affiliation country: S41586-021-03606-z