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COVIDTAS COVID-19 Tracing App Scale—An Evaluation Framework

Author

Listed:
  • Raghu Raman

    (Amrita CREATE, Amrita Vishwa Vidyapeetham, Amritapuri 690525, India)

  • Krishnashree Achuthan

    (Amrita Center for Cybersecurity Systems and Networks, Amrita Vishwa Vidyapeetham, Amritapuri 690525, India)

  • Ricardo Vinuesa

    (KTH Engineering Mechanics, SE-100 44 Stockholm, Sweden)

  • Prema Nedungadi

    (Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri 690525, India)

Abstract

Mobile apps play an important role in COVID-19 tracing and tracking, with different countries taking different approaches. Our study focuses on 17 government owned COVID-19 Contact Tracing Apps (CTAs) and analyze them using a proposed COVIDTAS framework. User satisfaction is not directly related to the COVIDTAS score or the interaction between users and the app developers. To increase adoption of CTAs, government leadership must offer assurance to its citizens that their identify will be concealed and emphasize the benefits of CTAs as it relates to shared public health. While no country has topped the list on all three major factors (COVIDTAS Score, User Reviews, and User Ratings), the CTA from India seems to have above average performance on all three factors.

Suggested Citation

  • Raghu Raman & Krishnashree Achuthan & Ricardo Vinuesa & Prema Nedungadi, 2021. "COVIDTAS COVID-19 Tracing App Scale—An Evaluation Framework," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:5:p:2912-:d:512653
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    References listed on IDEAS

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    1. Wim Naudé & Ricardo Vinuesa, 2020. "Data, global development, and COVID-19: Lessons and consequences," WIDER Working Paper Series wp-2020-109, World Institute for Development Economic Research (UNU-WIDER).
    2. 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.
    3. Simon Munzert & Peter Selb & Anita Gohdes & Lukas F. Stoetzer & Will Lowe, 2021. "Tracking and promoting the usage of a COVID-19 contact tracing app," Nature Human Behaviour, Nature, vol. 5(2), pages 247-255, February.
    4. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    5. Shamshul Bahri, 2007. "Enhancing quality of data through automated SARS contact tracing method using RFID technology," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 4(2), pages 145-162.
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    Cited by:

    1. Marta Borda & Natalia Grishchenko & Patrycja Kowalczyk-Rólczyńska, 2022. "Impact of Digital Inequality on the COVID-19 Pandemic: Evidence from European Union Countries," Sustainability, MDPI, vol. 14(5), pages 1-13, March.
    2. Raghu Raman & Ricardo Vinuesa & Prema Nedungadi, 2021. "Bibliometric Analysis of SARS, MERS, and COVID-19 Studies from India and Connection to Sustainable Development Goals," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    3. Da-Hee Lim & Dae-Woong Lee, 2021. "Non-Face-to-Face Public Services and Perceptions of Public Organizations," Sustainability, MDPI, vol. 13(21), pages 1-15, November.

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