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Financial Incentives for Downloading COVID–19 Digital Contact Tracing Apps

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  • Frimpong, Jemima A.
  • Helleringer, Stephane

Abstract

Contact tracing is a key approach for controlling the COVID–19 pandemic. Traditional tracing methods might however miss a number of contacts between infected and susceptible persons. Digital contact tracing apps have been developed to assist health departments in notifying individuals of recent exposures to SARS-CoV-2. These apps are used in several countries throughout the world, and some US states have either launched or are planning to launch such apps. The potential effects of digital contact tracing apps depend however on their widespread adoption. Most investigations of the determinants of adoption among potential users have focused on issues related to privacy features (e.g., who can access data, whether location is recorded) and the accuracy of the app in notifying users of exposures to SARS-CoV-2 (e.g., false notifications). In this paper, we investigate whether financial incentives might help further accelerate the adoption of digital contact tracing apps. We conducted a discrete choice experiment with an online sample of 394 US residents aged 18–69 years old. We asked participants to make a series of choices between two hypothetical versions of a digital contact tracing app characterized by several randomly selected attributes, including varying levels of financial cost or incentives to download. In this experiment, financial incentives were more than twice as important in the decision-making process about DCT app downloads than privacy and accuracy. In order to accelerate adoption, US States planning to launch digital contact tracing apps should consider offering financial incentives for download to potential users.

Suggested Citation

  • Frimpong, Jemima A. & Helleringer, Stephane, 2020. "Financial Incentives for Downloading COVID–19 Digital Contact Tracing Apps," SocArXiv 9vp7x, Center for Open Science.
    • Handle: RePEc:osf:socarx:9vp7x
    DOI: 10.31219/osf.io/9vp7x
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    References listed on IDEAS

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    1. Esther Bekker-Grob & Bas Donkers & Marcel Jonker & Elly Stolk, 2015. "Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 8(5), pages 373-384, October.
    2. Buckell, John & Hess, Stephane, 2019. "Stubbing out hypothetical bias: improving tobacco market predictions by combining stated and revealed preference data," Journal of Health Economics, Elsevier, vol. 65(C), pages 93-102.
    3. Danny Campbell & Seda Erdem, 2019. "Including Opt-Out Options in Discrete Choice Experiments: Issues to Consider," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 12(1), pages 1-14, February.
    4. Jorien Veldwijk & Mattijs S Lambooij & Esther W de Bekker-Grob & Henriëtte A Smit & G Ardine de Wit, 2014. "The Effect of Including an Opt-Out Option in Discrete Choice Experiments," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
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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. Caspar Chorus & Erlend Dancke Sandorf & Niek Mouter, 2020. "Diabolical dilemmas of COVID-19: An empirical study into Dutch society’s trade-offs between health impacts and other effects of the lockdown," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-19, September.
    2. Rehse, Dominik & Tremöhlen, Felix, 2020. "Fostering participation in digital public health interventions: The case of digital contact tracing," ZEW Discussion Papers 20-076, ZEW - Leibniz Centre for European Economic Research.

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