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The epidemiological impact of digital and manual contact tracing on the SARS-CoV-2 epidemic in the Netherlands: Empirical evidence

Author

Listed:
  • Wianne Ter Haar
  • Jizzo Bosdriesz
  • Roderick P Venekamp
  • Ewoud Schuit
  • Susan van den Hof
  • Wolfgang Ebbers
  • Mirjam Kretzschmar
  • Jan Kluijtmans
  • Carl Moons
  • Maarten Schim van der Loeff
  • Amy Matser
  • Janneke H H M van de Wijgert

Abstract

The Dutch government introduced the CoronaMelder smartphone application for digital contact tracing (DCT) to complement manual contact tracing (MCT) by Public Health Services (PHS) during the 2020–2022 SARS-CoV-2 epidemic. Modelling studies showed great potential but empirical evidence of DCT and MCT impact is scarce. We determined reasons for testing, and mean exposure-testing intervals by reason for testing, using routine data from PHS Amsterdam (1 December 2020 to 31 May 2021) and data from two SARS-CoV-2 rapid diagnostic test accuracy studies at other PHS sites in the Netherlands (14 December 2020 to 18 June 2021). Throughout the study periods, notification of DCT-identified contacts was via PHS contact-tracers, and self-testing was not yet widely available. The most commonly reported reason for testing was having symptoms. In asymptomatic individuals, it was having been warned by an index case. Only around 2% and 2–5% of all tests took place after DCT or MCT notification, respectively. About 20–36% of those who had received a DCT or MCT notification had symptoms at the time of test request. Test positivity after a DCT notification was significantly lower, and exposure-test intervals after a DCT or MCT notification were longer, than for the above-mentioned other reasons for testing. Our data suggest that the impact of DCT and MCT on the SARS-CoV-2 epidemic in the Netherlands was limited. However, DCT impact might be enlarged if app use coverage is improved, contact-tracers are eliminated from the digital notification process to minimise delays, and DCT is combined with self-testing.Author summary: During the 2020–2022 SARS-CoV-2 epidemic, the Dutch government introduced digital contact tracing (DCT) using a smartphone application to complement manual contact tracing (MCT) by professional contact-tracers. Mathematical models had suggested that DCT could slow down virus spread by identifying more individuals with whom the smartphone user had been in close contact and by reducing notification and testing delays after exposure. We used data collected during the Dutch epidemic to evaluate whether this was indeed the case and found that DCT and MCT had limited impact. Only around 2% of all tests took place after a DCT notification, and 2–5% after a MCT notification depending on MCT capacity at the time. Test positivity was lower after a DCT notification, and exposure-test intervals were longer after a DCT or MCT notification, than for other reasons for testing. About 20–36% of those who had received a DCT or MCT notification had symptoms at the time of test request and might have tested anyway even without having received the notification. However, DCT impact might be enlarged in future epidemics if app use coverage is improved and all exposure-notification-testing delays are minimised (e.g. no involvement of professional contact tracers and enabling self-testing after DCT notification).

Suggested Citation

  • Wianne Ter Haar & Jizzo Bosdriesz & Roderick P Venekamp & Ewoud Schuit & Susan van den Hof & Wolfgang Ebbers & Mirjam Kretzschmar & Jan Kluijtmans & Carl Moons & Maarten Schim van der Loeff & Amy Mats, 2023. "The epidemiological impact of digital and manual contact tracing on the SARS-CoV-2 epidemic in the Netherlands: Empirical evidence," PLOS Digital Health, Public Library of Science, vol. 2(12), pages 1-17, December.
  • Handle: RePEc:plo:pdig00:0000396
    DOI: 10.1371/journal.pdig.0000396
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    1. Ahmed Elmokashfi & Joakim Sundnes & Amund Kvalbein & Valeriya Naumova & Sven-Arne Reinemo & Per Magne Florvaag & Håkon Kvale Stensland & Olav Lysne, 2021. "Nationwide rollout reveals efficacy of epidemic control through digital contact tracing," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    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. Silvia Ussai & Marco Pistis & Eduardo Missoni & Beatrice Formenti & Benedetta Armocida & Tatiana Pedrazzi & Francesco Castelli & Lorenzo Monasta & Baldassare Lauria & Ilaria Mariani, 2022. "“Immuni” and the National Health System: Lessons Learnt from the COVID-19 Digital Contact Tracing in Italy," IJERPH, MDPI, vol. 19(12), pages 1-7, June.
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