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Does Contact Tracing Work? Quasi-Experimental Evidence from an Excel Error in England

Author

Listed:
  • Fetzer, Thiemo

    (University of Warwick, CAGE, CESifo and CEPR)

  • Graeber, Thomas

    (Harvard Business School, CESifo and IZA)

Abstract

Contact tracing has been a central pillar of the public health response to the COVID-19 pandemic. Yet, contact tracing measures face substantive challenges in practice and well-identified evidence about their effectiveness remains scarce. This paper exploits quasi-random variation in COVID-19 contact tracing. Between September 25 and October 2, 2020, a total of 15,841 COVID-19 cases in England (around 15 to 20% of all cases) were not immediately referred to the contact tracing system due to a data processing error. Case information was truncated from an Excel spreadsheet after the row limit had been reached, which was discovered on October 3. There is substantial variation in the degree to which different parts of England areas were exposed – by chance – to delayed referrals of COVID-19 cases to to the contact tracing system. We show that more affected areas subsequently experienced a drastic rise in new COVID-19 infections and deaths alongside an increase in the positivity rate and the number of test performed, as well as a decline in the performance of the contact tracing system. Conservative estimates suggest that the failure of timely contact tracing due to the data glitch is associated with more than 125,000 additional infections and over 1,500 additional COVID-19 related deaths. Our findings provide strong quasi-experimental evidence for the effectiveness of contact tracing.

Suggested Citation

  • Fetzer, Thiemo & Graeber, Thomas, 2020. "Does Contact Tracing Work? Quasi-Experimental Evidence from an Excel Error in England," The Warwick Economics Research Paper Series (TWERPS) 1314, University of Warwick, Department of Economics.
    • Handle: RePEc:wrk:warwec:1314
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    References listed on IDEAS

    as
    1. Thiemo Fetzer, 2022. "Subsidising the spread of COVID-19: Evidence from the UK’S Eat-Out-to-Help-Out Scheme," The Economic Journal, Royal Economic Society, vol. 132(643), pages 1200-1217.
    2. Fetzer, Thiemo & Witte, Marc & Hensel, Lukas & Jachimowicz, Jon M. & Haushofer, Johannes & Ivchenko, Andriy & Reutskaja, Elena & Roth, Christopher & Gomez, Margarita & Kraft-Todd, Gordon & Goetz, Frie, 2020. "Global Behaviors and Perceptions in the COVID-19 Pandemic," CEPR Discussion Papers 14631, C.E.P.R. Discussion Papers.
    3. Hakan Yilmazkuday, 2020. "Stay-at-Home Works to Fight Against COVID-19: International Evidence from Google Mobility Data," Working Papers 2008, Florida International University, Department of Economics.
    4. Don Klinkenberg & Christophe Fraser & Hans Heesterbeek, 2006. "The Effectiveness of Contact Tracing in Emerging Epidemics," PLOS ONE, Public Library of Science, vol. 1(1), pages 1-7, December.
    Full references (including those not matched with items on IDEAS)

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    RePEc Biblio mentions

    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health > Tracing

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    Cited by:

    1. Dirk Niepelt & Mart n Gonzalez-Eiras, 2020. "Optimally Controlling an Epidemic," Diskussionsschriften dp2019, Universitaet Bern, Departement Volkswirtschaft.
    2. Hakan Yilmazkuday, 2020. "Stay-at-Home Works to Fight Against COVID-19: International Evidence from Google Mobility Data," Working Papers 2008, Florida International University, Department of Economics.
    3. David Turner & Balázs Égert & Yvan Guillemette & Jarmila Botev, 2021. "The tortoise and the hare: The race between vaccine rollout and new COVID variants," OECD Economics Department Working Papers 1672, OECD Publishing.
    4. 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.
    5. Cipullo, Davide & Le Moglie, Marco, 2022. "To vote, or not to vote? Electoral campaigns and the spread of COVID-19," European Journal of Political Economy, Elsevier, vol. 72(C).
    6. Charles Courtemanche & Joseph Garuccio & Anh Le & Joshua Pinkston & Aaron Yelowitz, 2021. "Chance elections, social distancing restrictions, and KENTUCKY’s early COVID-19 experience," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-19, July.

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    More about this item

    Keywords

    Health ; Coronavirus JEL codes: I31 ; Z18;
    All these keywords.

    JEL classification:

    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • Z18 - Other Special Topics - - Cultural Economics - - - Public Policy

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