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The global and national response to the COVID-19 pandemic has been inadequate due to a collective lack of preparation and a shortage of available tools for responding to a large-scale pandemic. By applying lessons learned to create better preventative methods and speedier interventions, the harm of a future pandemic may be dramatically reduced. One potential measure is the widespread use of contact tracing apps. While such apps were designed to combat the COVID-19 pandemic, the time scale in which these apps were deployed proved a significant barrier to efficacy. Many companies and governments sprinted to deploy contact tracing apps that were not properly vetted for performance, privacy, or security issues. The hasty development of incomplete contact tracing apps undermined public trust and negatively influenced perceptions of app efficacy. As a result, many of these apps had poor voluntary public uptake, which greatly decreased the apps’ efficacy. Now, with lessons learned from this pandemic, groups can better design and test apps in preparation for the future. In this viewpoint, we outline common strategies employed for contact tracing apps, detail the successes and shortcomings of several prominent apps, and describe lessons learned that may be used to shape effective contact tracing apps for the present and future. Future app designers can keep these lessons in mind to create a version that is suitable for their local culture, especially with regard to local attitudes toward privacy-utility tradeoffs during public health crises.
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Digital exposure tools: Design for privacy, efficacy, and equity
Use of smartphone-based digital contact- tracing apps has shown promise in responding to the COVID-19 pandemic. But such apps can reveal very personal information; thus, their use raises important societal questions, not just during the current pandemic but as we learn and prepare for other inevitable outbreaks ahead. Can privacy-protective versions of such apps work? Are they efficacious? Because the apps influence who is notified of exposure and who gets tested—and possibly treated—we need to consider the apps in the context of health care equity. Exposure-notification apps are predicated on the assumption that if someone is informed of exposure, they will follow instructions to isolate. Such an expectation fails to take into account that isolation—and sometimes even seeking care when ill—is much harder for some populations than others. If apps are to work for all, and not make this worse for disadvantaged populations, there needs to be basic social infrastructure that supports testing, contact tracing, and isolation.
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- Award ID(s):
- 1955805
- PAR ID:
- 10343206
- Date Published:
- Journal Name:
- Science
- Volume:
- 373
- Issue:
- 6560
- ISSN:
- 0036-8075
- Page Range / eLocation ID:
- 1202 to 1204
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)The global coronavirus pandemic has raised important questions regarding how to balance public health concerns with privacy protections for individual citizens. In this essay, we evaluate contact tracing apps, which have been offered as a technological solution to minimize the spread of COVID-19. We argue that apps such as those built on Google and Apple’s “exposure notification system” should be evaluated in terms of the contextual integrity of information flows; in other words, the appropriateness of sharing health and location data will be contextually dependent on factors such as who will have access to data, as well as the transmission principles underlying data transfer. We also consider the role of prevailing social and political values in this assessment, including the large-scale social benefits that can be obtained through such information sharing. However, caution should be taken in violating contextual integrity, even in the case of a pandemic, because it risks a long-term loss of autonomy and growing function creep for surveillance and monitoring technologies.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1126/science.abi9852
