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Empirical evidence on the efficiency of backward contact tracing in COVID-19

Author

Listed:
  • Joren Raymenants

    (KU Leuven, Laboratory of Clinical Microbiology
    Algemene Interne Geneeskunde, UZ Leuven)

  • Caspar Geenen

    (KU Leuven, Laboratory of Clinical Microbiology)

  • Jonathan Thibaut

    (KU Leuven, Laboratory of Clinical Microbiology)

  • Klaas Nelissen

    (KU Leuven, Laboratory of Clinical Microbiology)

  • Sarah Gorissen

    (KU Leuven, Laboratory of Clinical Microbiology)

  • Emmanuel Andre

    (KU Leuven, Laboratory of Clinical Microbiology
    Laboratoriumgeneeskunde, UZ Leuven)

Abstract

Standard contact tracing practice for COVID-19 is to identify persons exposed to an infected person during the contagious period, assumed to start two days before symptom onset or diagnosis. In the first large cohort study on backward contact tracing for COVID-19, we extended the contact tracing window by 5 days, aiming to identify the source of the infection and persons infected by the same source. The risk of infection amongst these additional contacts was similar to contacts exposed during the standard tracing window and significantly higher than symptomatic individuals in a control group, leading to 42% more cases identified as direct contacts of an index case. Compared to standard practice, backward traced contacts required fewer tests and shorter quarantine. However, they were identified later in their infectious cycle if infected. Our results support implementing backward contact tracing when rigorous suppression of viral transmission is warranted.

Suggested Citation

  • Joren Raymenants & Caspar Geenen & Jonathan Thibaut & Klaas Nelissen & Sarah Gorissen & Emmanuel Andre, 2022. "Empirical evidence on the efficiency of backward contact tracing in COVID-19," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32531-6
    DOI: 10.1038/s41467-022-32531-6
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    References listed on IDEAS

    as
    1. Maximilian Kasy & Alexander Teytelboym, 2020. "Adaptive targeted infectious disease testing," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 36(Supplemen), pages 77-93.
    2. Benjamin Armbruster & Margaret Brandeau, 2007. "Contact tracing to control infectious disease: when enough is enough," Health Care Management Science, Springer, vol. 10(4), pages 341-355, December.
    3. Emma L. Davis & Tim C. D. Lucas & Anna Borlase & Timothy M. Pollington & Sam Abbott & Diepreye Ayabina & Thomas Crellen & Joel Hellewell & Li Pi & Graham F. Medley & T. Déirdre Hollingsworth & Petra K, 2021. "Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    4. William J. Bradshaw & Ethan C. Alley & Jonathan H. Huggins & Alun L. Lloyd & Kevin M. Esvelt, 2021. "Bidirectional contact tracing could dramatically improve COVID-19 control," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    5. Chad R. Wells & Jeffrey P. Townsend & Abhishek Pandey & Seyed M. Moghadas & Gary Krieger & Burton Singer & Robert H. McDonald & Meagan C. Fitzpatrick & Alison P. Galvani, 2021. "Optimal COVID-19 quarantine and testing strategies," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    6. Joël Mossong & Niel Hens & Mark Jit & Philippe Beutels & Kari Auranen & Rafael Mikolajczyk & Marco Massari & Stefania Salmaso & Gianpaolo Scalia Tomba & Jacco Wallinga & Janneke Heijne & Malgorzata Sa, 2008. "Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases," PLOS Medicine, Public Library of Science, vol. 5(3), pages 1-1, March.
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    Cited by:

    1. 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.

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