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COVID-19 Contact Tracing Mobile Applications in New York State (NYS): an Empirical Study

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HCI International 2023 – Late Breaking Papers (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14059))

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Abstract

In this paper, we surveyed to examine individual use of mobile apps for COVID-19 contact tracing in New York State (NYS). Additionally, we investigated the impact of privacy and security concerns on adopting these apps and whether there are differences in adoption rates among different racial and age groups. We adopted the Antecedent-Privacy Concerns-Outcomes (APCO) framework to identify factors affecting the individual-level adoption of these apps. Results indicate no significant correlation between race and the perceived usefulness of the NYS COVID-Alert app. Only certain demographic variables affected privacy concerns, trust, or behavioral intentions related to contact tracing apps. Specifically, the more influential factors were pandemic experiences, political affiliation, education, and income. Political affiliation and education were more influential demographic factors regarding the adoption and perceived usefulness of contact tracing applications.

Interestingly, respondents with the highest and lowest income were less likely to be concerned about the privacy and security concerns of the COVID-19 mobile apps. However, middle-income respondents were more likely to be concerned about privacy and security. Our findings shed light on the challenges and opportunities associated with contact-tracing mobile apps in the context of the COVID-19 pandemic and provide insights into how these apps can be optimized to improve their effectiveness and reach.

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Authors and Affiliations

  1. College of Emergency Preparedness, Homeland Security and Cybersecurity, University at Albany, State University of New York, Albany, USA

    Xiaojun Yuan, DeeDee Bennett Gayle, Ellie Seoe Jung & Yvonne Appiah Dadson

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  1. Xiaojun Yuan
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  2. DeeDee Bennett Gayle
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  3. Ellie Seoe Jung
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  4. Yvonne Appiah Dadson
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Correspondence to Xiaojun Yuan .

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Editors and Affiliations

  1. Siemens Corporation, Princeton, NJ, USA

    Helmut Degen

  2. Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Stavroula Ntoa

  3. San Jose State University, San Jose, CA, USA

    Abbas Moallem

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Yuan, X., Bennett Gayle, D., Jung, E.S., Dadson, Y.A. (2023). COVID-19 Contact Tracing Mobile Applications in New York State (NYS): an Empirical Study. In: Degen, H., Ntoa, S., Moallem, A. (eds) HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14059. Springer, Cham. https://doi.org/10.1007/978-3-031-48057-7_32

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  • DOI: https://doi.org/10.1007/978-3-031-48057-7_32

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