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A Privacy Calculus Model for Contact Tracing Apps: Analyzing the German Corona-Warn-App

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ICT Systems Security and Privacy Protection (SEC 2022)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 648))

Abstract

The SARS-CoV-2 pandemic is a pressing societal issue today. The German government promotes a contact tracing app named Corona-Warn-App (CWA), aiming to change citizens’ health behavior during the pandemic by raising awareness about potential infections and enable infection chain tracking. Technical implementations, citizens’ perceptions, and public debates around apps differ between countries, i.e., in Germany there has been a huge discussion on potential privacy issues of the app.

Thus, we analyze effects of privacy concerns regarding the CWA, perceived CWA benefits, and trust in the German healthcare system to answer why citizens use the CWA. We use a sample with 1,752 actual users and non-users and find support for the privacy calculus theory, i.e., individuals weigh privacy concerns and benefits in their use decision. Thus, citizens’ privacy perceptions about health technologies (e.g., shaped by public debates) are crucial as they can hinder adoption and negatively affect future fights against pandemics.

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Notes

  1. 1.

    Measured on a 7-point Likert scale (“strongly disagree” to “strongly agree”).

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Acknowledgements

This work was supported by the Goethe-Corona-Fonds from Goethe University Frankfurt and the European Union’s Horizon 2020 research and innovation program under grant agreement 830929 (CyberSecurity4Europe).

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Authors and Affiliations

  1. Chair of Mobile Business and Multilateral Security, Goethe University Frankfurt, Frankfurt, Germany

    David Harborth & Sebastian Pape

Authors
  1. David Harborth
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Corresponding author

Correspondence to David Harborth .

Editor information

Editors and Affiliations

  1. Technical University of Denmark, Lyngby, Denmark

    Weizhi Meng

  2. Karlstad University, Karlstad, Sweden

    Simone Fischer-Hübner

  3. Technical University of Denmark, Lyngby, Denmark

    Christian D. Jensen

A Questionnaire

A Questionnaire

Demographics

figure a

Privacy concerns related to the Corona-Warn-AppFootnote 1

  • PC1 I think the Corona-Warn-App over-collects my personal information.

  • PC2 I worry that the Corona-Warn-App leaks my personal information to third-parties.

  • PC3 I am concerned that the Corona-Warn-App violates my privacy.

  • PC4 I am concerned that the Corona-Warn-App misuses my personal information.

  • PC5 I think that the Corona-Warn-App collects my location data.

Perceived benefits of the Corona-Warn-App (See footnote 1)

  • PB1 Using the Corona-Warn-App makes me feel safer.

  • PB2 I have a lot to gain by using the Corona-Warn-App.

  • PB3 The Corona-Warn-App can help me to identify contacts to infected individuals.

  • PB4 If I use the Corona-Warn-App I am able to warn others in case I am infected with Covid-19.

  • PB5 The spreading of Covid-19 in Germany can be decelerated by using the Corona-Warn-App.

Trust in the German healthcare system (See footnote 1)

  • TRUST1 The German healthcare system is trustworthy.

  • TRUST2 The players acting in the German healthcare system are trustworthy.

  • TRUST3 The German healthcare system can cope with the burden of Covid 19 infections.

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Harborth, D., Pape, S. (2022). A Privacy Calculus Model for Contact Tracing Apps: Analyzing the German Corona-Warn-App. In: Meng, W., Fischer-Hübner, S., Jensen, C.D. (eds) ICT Systems Security and Privacy Protection. SEC 2022. IFIP Advances in Information and Communication Technology, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-031-06975-8_1

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