Journal article
Post-COVID Public Health Surveillance and Privacy Expectations in the United States: Scenario-Based Interview Study
JMIR mHealth and uHealth, v 9(10), pp e30871-e30871
01 Oct 2021
PMCID: PMC8494069
PMID: 34519667
Abstract
Background: Smartphone-based apps designed and deployed to mitigate the COVID-19 pandemic may become infrastructure for postpandemic public health surveillance in the United States. Through the lenses of privacy concerns and user expectations of digital pandemic mitigation techniques, we identified possible long-term sociotechnical implications of such an infrastructure.
Objective: We explored how people in the United States perceive the possible routinization of pandemic tracking apps for public health surveillance in general. Our interdisciplinary analysis focused on the interplay between privacy concerns, data practices of surveillance capitalism, and trust in health care providers. We conducted this analysis to achieve a richer understanding of the sociotechnical issues raised by the deployment and use of technology for pandemic mitigation.
Methods: We conducted scenario-based, semistructured interviews (n=19) with adults in the United States. The interviews focused on how people perceive the short- and long-term privacy concerns associated with a fictional smart thermometer app deployed to mitigate the "outbreak of a contagious disease." In order to elicit future-oriented discussions, the scenario indicated that the app would continue functioning "after the disease outbreak has dissipated." We analyzed interview transcripts using reflexive thematic analysis.
Results: In the context of pandemic mitigation technology, including app-based tracking, people perceive a core trade-off between public health and personal privacy. People tend to rationalize this trade-off by invoking the concept of "the greater good." The interplay between the trade-off and rationalization forms the core of sociotechnical issues that pandemic mitigation technologies raise. Participants routinely expected that data collected through apps related to public health would be shared with unknown third parties for the financial gain of the app makers. This expectation suggests a perceived alignment between an app-based infrastructure for public health surveillance and the broader economics of surveillance capitalism. Our results highlight unintended and unexpected sociotechnical impacts of routinizing app-based tracking on postpandemic life, which are rationalized by invoking a nebulous concept of the greater good.
Conclusions: While technologies such as app-based tracking could be useful for pandemic mitigation and preparedness, the routinization of such apps as a form of public health surveillance may have broader, unintentional sociotechnical implications for individuals and the societies in which they live. Although technology has the potential to increase the efficacy of pandemic mitigation, it exists within a broader network of sociotechnical concerns. Therefore, it is necessary to consider the long-term implications of pandemic mitigation technologies beyond the immediate needs of addressing the COVID-19 pandemic. Potential negative consequences include the erosion of patient trust in health care systems and providers, grounded in concerns about privacy violations and overly broad surveillance.
Metrics
Details
- Title
- Post-COVID Public Health Surveillance and Privacy Expectations in the United States: Scenario-Based Interview Study
- Creators
- John S. Seberger - Michigan State UniversitySameer Patil - University of Utah
- Publication Details
- JMIR mHealth and uHealth, v 9(10), pp e30871-e30871
- Publisher
- Jmir Publications, Inc
- Number of pages
- 15
- Grant note
- Indiana University Indiana University Office of the Vice President for Research
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Web of Science ID
- WOS:000709012500010
- Scopus ID
- 2-s2.0-85117365871
- Other Identifier
- 991021861873704721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Health Care Sciences & Services
- Medical Informatics