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COVID-19, digital privacy, and the social limits on data-focused public health responses

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  • Fahey, Robert A.
  • Hino, Airo

Abstract

The implementation of digital contact tracing applications around the world to help reduce the spread of the COVID-19 pandemic represents one of the most ambitious uses of massive-scale citizen data ever attempted. There is major divergence among nations, however, between a “privacy-first” approach which protects citizens’ data at the cost of extremely limited access for public health authorities and researchers, and a “data-first” approach which stores large amounts of data which, while of immeasurable value to epidemiologists and other researchers, may significantly intrude upon citizens’ privacy. The lack of a consensus on privacy protection in the contact tracing process creates risks of non-compliance or deliberate obfuscation from citizens who fear revealing private aspects of their lives – a factor greatly exacerbated by recent major scandals over online privacy and the illicit use of citizens’ digital information, which have heightened public consciousness of these issues and created significant new challenges for any collection of large-scale public data. While digital contact tracing for COVID-19 remains in its infancy, the lack of consensus around best practices for its implementation and for reassuring citizens of the protection of their privacy may already have impeded its capacity to contribute to the pandemic response.

Suggested Citation

  • Fahey, Robert A. & Hino, Airo, 2020. "COVID-19, digital privacy, and the social limits on data-focused public health responses," International Journal of Information Management, Elsevier, vol. 55(C).
    • Handle: RePEc:eee:ininma:v:55:y:2020:i:c:s0268401220310239
    DOI: 10.1016/j.ijinfomgt.2020.102181
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    Cited by:

    1. Banita Lal & Yogesh K. Dwivedi & Markus Haag, 2023. "Working from Home During Covid-19: Doing and Managing Technology-enabled Social Interaction With Colleagues at a Distance," Information Systems Frontiers, Springer, vol. 25(4), pages 1333-1350, August.
    2. Zexun Chen & Sean Kelty & Alexandre G. Evsukoff & Brooke Foucault Welles & James Bagrow & Ronaldo Menezes & Gourab Ghoshal, 2022. "Contrasting social and non-social sources of predictability in human mobility," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    3. Garcia-Perez, Alexeis & Cegarra-Navarro, Juan Gabriel & Sallos, Mark Paul & Martinez-Caro, Eva & Chinnaswamy, Anitha, 2023. "Resilience in healthcare systems: Cyber security and digital transformation," Technovation, Elsevier, vol. 121(C).
    4. Veronica Q T Li & Liang Ma & Xun Wu, 2022. "COVID-19, policy change, and post-pandemic data governance: a case analysis of contact tracing applications in East Asia [A survey of COVID-19 contact tracing apps]," Policy and Society, Darryl S. Jarvis and M. Ramesh, vol. 41(1), pages 129-142.
    5. Barbarossa, Camilla & Patrizi, Michela & Vernuccio, Maria & Carmen Di Poce, Maria & Pastore, Alberto, 2023. "The resistance toward COVID-19 contact tracing apps: A study of psychological reactance among young adults in Italy," Health Policy, Elsevier, vol. 136(C).
    6. Ibrahim Zada, 2022. "The Contributions of Customer Knowledge and Artificial Intelligence to Customer Satisfaction," International Review of Management and Marketing, Econjournals, vol. 12(5), pages 1-4, September.

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