The epidemiological impact of the NHS COVID-19 app

Chris Wymant, Luca Ferretti, Daphne Tsallis, Marcos Charalambides, Lucie Abeler-Dörner, David Bonsall, Robert Hinch, Michelle Kendall, Luke Milsom, Matthew Ayres, Chris Holmes, Mark Briers and Christophe Fraser ()
Additional contact information
Chris Wymant: University of Oxford
Luca Ferretti: University of Oxford
Daphne Tsallis: Zühlke Engineering Ltd
Marcos Charalambides: The Alan Turing Institute
Lucie Abeler-Dörner: University of Oxford
David Bonsall: University of Oxford
Robert Hinch: University of Oxford
Michelle Kendall: University of Oxford
Luke Milsom: University of Oxford
Matthew Ayres: The Alan Turing Institute
Chris Holmes: University of Oxford
Mark Briers: The Alan Turing Institute
Christophe Fraser: University of Oxford

Nature, 2021, vol. 594, issue 7863, 408-412

Abstract: 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.

Date: 2021
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DOI: 10.1038/s41586-021-03606-z

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