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The German COVID-19 Digital Contact Tracing App: A Socioeconomic Evaluation

Author

Listed:
  • Stephan Ellmann

    (Department of Radiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, University Hospital Erlangen, Maximiliansplatz 3, 91054 Erlangen, Germany)

  • Markus Maryschok

    (School of Business, Economics and Society, Chair for Health Management, Friedrich-Alexander-Universität Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg, Germany)

  • Oliver Schöffski

    (School of Business, Economics and Society, Chair for Health Management, Friedrich-Alexander-Universität Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg, Germany)

  • Martin Emmert

    (Faculty of Law, Business and Economics, Institute for Healthcare Management and Health Sciences, University of Bayreuth, Prieserstraße 2, 95444 Bayreuth, Germany)

Abstract

The COVID-19 pandemic posed challenges to governments in terms of contact tracing. Like many other countries, Germany introduced a mobile-phone-based digital contact tracing solution (“Corona Warn App”; CWA) in June 2020. At the time of its release, however, it was hard to assess how effective such a solution would be, and a political and societal debate arose regarding its efficiency, also in light of its high costs. This study aimed to analyze the effectiveness of the CWA, considering prevented infections, hospitalizations, intensive care treatments, and deaths. In addition, its efficiency was to be assessed from a monetary point of view, and factors with a significant influence on the effectiveness and efficiency of the CWA were to be determined. Mathematical and statistical modeling was used to calculate infection cases prevented by the CWA, along with the numbers of prevented complications (hospitalizations, intensive care treatments, deaths) using publicly available CWA download numbers and incidences over time. The monetized benefits of these prevented cases were quantified and offset against the costs incurred. Sensitivity analysis was used to identify factors critically influencing these parameters. Between June 2020 and April 2022, the CWA prevented 1.41 million infections, 17,200 hospitalizations, 4600 intensive care treatments, and 7200 deaths. After offsetting costs and benefits, the CWA had a net present value of EUR 765 m in April 2022. Both the effectiveness and efficiency of the CWA are decisively and disproportionately positively influenced by the highest possible adoption rate among the population and a high rate of positive infection test results shared via the CWA.

Suggested Citation

  • Stephan Ellmann & Markus Maryschok & Oliver Schöffski & Martin Emmert, 2022. "The German COVID-19 Digital Contact Tracing App: A Socioeconomic Evaluation," IJERPH, MDPI, vol. 19(21), pages 1-22, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:21:p:14318-:d:960887
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    References listed on IDEAS

    as
    1. Abramova, Olga & Wagner, Amina & Olt, Christian M. & Buxmann, Peter, 2022. "One for all, all for one: Social considerations in user acceptance of contact tracing apps using longitudinal evidence from Germany and Switzerland," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 130569, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. 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.
    3. Hui Li & Yifei Zhu & Yi Niu, 2022. "Contact Tracing Research: A Literature Review Based on Scientific Collaboration Network," IJERPH, MDPI, vol. 19(15), pages 1-16, July.
    4. Jude Dzevela Kong & Edward W Tekwa & Sarah A Gignoux-Wolfsohn, 2021. "Social, economic, and environmental factors influencing the basic reproduction number of COVID-19 across countries," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-17, June.
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    Cited by:

    1. Roberto M. Souza & Bruno S. Cezario & Estefany O. T. Affonso & Andreia D. B. Machado & Danielle P. Vieira & Christine K. Chinelli & Assed N. Haddad & Patricia M. Dusek & Maria G. de Miranda & Carlos A, 2024. "My Human Rights Smart City: Improving Human Rights Transparency Identification System," Sustainability, MDPI, vol. 16(3), pages 1-27, February.

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