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Measuring the scientific effectiveness of contact tracing: Evidence from a natural experiment

Author

Listed:
  • Thiemo Fetzer

    (Competitive Advantage in the Global Economy Research Centre, Department of Economics, University of Warwick, Coventry CV4 7AL, United Kingdom)

  • Thomas Graeber

    (Harvard Business School, Harvard University, Boston, MA 02163)

Abstract

Contact tracing has for decades been a cornerstone of the public health approach to epidemics, including Ebola, severe acute respiratory syndrome, and now COVID-19. It has not yet been possible, however, to causally assess the method’s effectiveness using a randomized controlled trial of the sort familiar throughout other areas of science. This study provides evidence that comes close to that ideal. It exploits a large-scale natural experiment that occurred by accident in England in late September 2020. Because of a coding error involving spreadsheet data used by the health authorities, a total of 15,841 COVID-19 cases (around 20% of all cases) failed to have timely contact tracing. By chance, some areas of England were much more severely affected than others. This study finds that the random breakdown of contact tracing led to more illness and death. Conservative causal estimates imply that, relative to cases that were initially missed by the contact tracing system, cases subject to proper contact tracing were associated with a reduction in subsequent new infections of 63% and a reduction insubsequent COVID-19–related deaths of 66% across the 6 wk following the data glitch.

Suggested Citation

  • Thiemo Fetzer & Thomas Graeber, 2021. "Measuring the scientific effectiveness of contact tracing: Evidence from a natural experiment," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(33), pages 2100814118-, August.
    • Handle: RePEc:nas:journl:v:118:y:2021:p:e2100814118
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    Citations

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    Cited by:

    1. Fetzer, Thiemo & Rauh, Christopher & Schreiner, Clara, 2024. "The hidden toll of the pandemic: Excess mortality in non-COVID-19 hospital patients," Journal of Health Economics, Elsevier, vol. 95(C).
    2. 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).
    3. Jonathan T. Rothwell & Alexandru Cojocaru & Rajesh Srinivasan & Yeon Soo Kim, 2024. "Global evidence on the economic effects of disease suppression during COVID-19," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    4. Monica Martinez-Bravo & Carlos Sanz, 2022. "The Management of the Pandemic and its Effects on Trust and Accountability," Working Papers wp2022_2207, CEMFI.
    5. Daniel L. Millimet & Christopher F. Parmeter, 2022. "COVID‐19 severity: A new approach to quantifying global cases and deaths," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1178-1215, July.
    6. Howell, Bronwyn E. & Potgieter, Petrus H., 2022. "COVID-19 contact-tracing smartphone application usage—The New Zealand COVID Tracer experience," Telecommunications Policy, Elsevier, vol. 46(8).
    7. Fischer Kai, 2022. "Thinning out spectators: Did football matches contribute to the second COVID-19 wave in Germany?," German Economic Review, De Gruyter, vol. 23(4), pages 595-640, December.

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