IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v594y2021i7863d10.1038_s41586-021-03606-z.html
   My bibliography  Save this article

The epidemiological impact of the NHS COVID-19 app

Author

Listed:
  • 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
    University of Warwick)

  • Luke Milsom

    (University of Oxford)

  • Matthew Ayres

    (The Alan Turing Institute)

  • Chris Holmes

    (University of Oxford
    The Alan Turing Institute
    University of Oxford)

  • Mark Briers

    (The Alan Turing Institute)

  • Christophe Fraser

    (University of Oxford)

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.

Suggested Citation

  • 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 , 2021. "The epidemiological impact of the NHS COVID-19 app," Nature, Nature, vol. 594(7863), pages 408-412, June.
  • Handle: RePEc:nat:nature:v:594:y:2021:i:7863:d:10.1038_s41586-021-03606-z
    DOI: 10.1038/s41586-021-03606-z
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-021-03606-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41586-021-03606-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fetzer, Thiemo, 2021. "Measuring the Epidemiological Impact of a False Negative: Evidence from a Natural Experiment," CAGE Online Working Paper Series 596, Competitive Advantage in the Global Economy (CAGE).
    2. van der Waal, Nadine Elisa & de Wit, Jan & Bol, Nadine & Ebbers, Wolfgang & Hooft, Lotty & Metting, Esther & van der Laan, Laura Nynke, 2022. "Predictors of contact tracing app adoption: Integrating the UTAUT, HBM and contextual factors," Technology in Society, Elsevier, vol. 71(C).
    3. Caspar Geenen & Joren Raymenants & Sarah Gorissen & Jonathan Thibaut & Jodie McVernon & Natalie Lorent & Emmanuel André, 2023. "Individual level analysis of digital proximity tracing for COVID-19 in Belgium highlights major bottlenecks," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    4. Michelle Kendall & Daphne Tsallis & Chris Wymant & Andrea Francia & Yakubu Balogun & Xavier Didelot & Luca Ferretti & Christophe Fraser, 2023. "Epidemiological impacts of the NHS COVID-19 app in England and Wales throughout its first year," Nature Communications, Nature, vol. 14(1), pages 1-10, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:594:y:2021:i:7863:d:10.1038_s41586-021-03606-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.