skip to main content

Explore Research Products in the NSF-PAR

Title: 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.  more » « less
Award ID(s):
1955805
NSF-PAR ID:
10343206
Author(s) / Creator(s):
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
More Like this
  1. ; ( , Social Media + Society)
    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
  2. ; ; ; ; ; ; ; ; ; ; et al ( , PLOS Computational Biology)
    Moreno, Yamir (Ed.)
    Testing, contact tracing, and isolation (TTI) is an epidemic management and control approach that is difficult to implement at scale because it relies on manual tracing of contacts. Exposure notification apps have been developed to digitally scale up TTI by harnessing contact data obtained from mobile devices; however, exposure notification apps provide users only with limited binary information when they have been directly exposed to a known infection source. Here we demonstrate a scalable improvement to TTI and exposure notification apps that uses data assimilation (DA) on a contact network. Network DA exploits diverse sources of health data together with the proximity data from mobile devices that exposure notification apps rely upon. It provides users with continuously assessed individual risks of exposure and infection, which can form the basis for targeting individual contact interventions. Simulations of the early COVID-19 epidemic in New York City are used to establish proof-of-concept. In the simulations, network DA identifies up to a factor 2 more infections than contact tracing when both harness the same contact data and diagnostic test data. This remains true even when only a relatively small fraction of the population uses network DA. When a sufficiently large fraction of the population (≳ 75%) uses network DA and complies with individual contact interventions, targeting contact interventions with network DA reduces deaths by up to a factor 4 relative to TTI. Network DA can be implemented by expanding the computational backend of existing exposure notification apps, thus greatly enhancing their capabilities. Implemented at scale, it has the potential to precisely and effectively control future epidemics while minimizing economic disruption. 
    more » « less
  3. ; ; ; ; ( , JMIR Medical Informatics)
    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. 
    more » « less
  4. ; ( , Journal of Medical Internet Research: Iproceedings)
    Background

    COVID-19 has severely impacted health in vulnerable demographics. As communities transition back to in-person work, learning, and social activities, pediatric patients who are restricted to their homes due to medical conditions face unprecedented isolation. Prior to the pandemic, it was estimated that each year, over 2.5 million US children remained at home due to medical conditions. Confronting gaps in health and technical resources is central to addressing the challenges faced by children who remain at home. Having children use mobile telemedicine units (telerobots) to interact with their outside environment (eg, school and play, etc) is increasingly recognized for its potential to support children’s development. Additionally, social telerobots are emerging as a novel form of telehealth. A social telerobot is a tele-operated unit with a mobile base, 2-way audio/video capabilities, and some semiautonomous features.

     Objective

    In this paper, we aimed to provide a critical review of studies focused on the use of social telerobots for pediatric populations.

     Methods

    To examine the evidence on telerobots as a telehealth intervention, we conducted electronic and full-text searches of private and public databases in June 2010. We included studies with the pediatric personal use of interactive telehealth technologies and telerobot studies that explored effects on child development. We excluded telehealth and telerobot studies with adult (aged >18 years) participants.

     Results

    In addition to telehealth and telerobot advantages, evidence from the literature suggests 3 promising robot-mediated supports that contribute to optimal child development—belonging, competence, and autonomy. These robot-mediated supports may be leveraged for improved pediatric patient socioemotional development, well-being, and quality-of-life activities that transfer traditional developmental and behavioral experiences from organic local environments to the remote child.

     Conclusions

    This review contributes to the creation of the first pediatric telehealth taxonomy of care that includes the personal use of telehealth technologies as a compelling form of telehealth care.

     
    more » « less
  5. ; ; ; ; ; ( , Proceedings of the Annual Hawaii International Conference on System Sciences)
    Technology played a central role during the pandemic for communications and services. It was also touted as a potential solution to control the spread of COVID-19 via proximity tracing applications, also known as contact tracing (CT) apps worldwide. In non-mandated settings, however, these apps did not attain popularity. Privacy concerns were highlighted as one reason. We explored how family perceptions of CT apps can affect the family’s use of such apps. We surveyed parent-teen dyads twice over a 5-month period. We analyzed parent-teen perceptions of each other’s intentions and use of CT apps at time 1 and 2, exploring changes over time. Parents’ use intentions were influenced by their and their teens’ perceptions of the benefits but not privacy concerns. Teen intentions were influenced by their own perceptions of benefits, not their parent’s, and their parent’s concerns for the family. Intentions always influenced usage, including intentions at time 1 influencing use at time 2, demonstrating a longitudinal effect of intentions on usage existed for parents and teens. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email