Abstract

BackgroundMany have proposed the use of Bluetooth technology to help scale up contact tracing for COVID-19. However, much remains unknown about the accuracy of this technology in real-world settings, the attitudes of potential users, and the differences between delivery formats (mobile app vs carriable or wearable devices).ObjectiveWe pilot tested 2 separate Bluetooth contact tracing technologies on a university campus to evaluate their sensitivity and specificity, and to learn from the experiences of the participants.MethodsWe used a convergent mixed methods study design, and participants included graduate students and researchers working on a university campus during June and July 2020. We conducted separate 2-week pilot studies for each Bluetooth technology. The first was for a mobile phone app (“app pilot”), and the second was for a small electronic “tag” (“tag pilot”). Participants validated a list of Bluetooth-identified contacts daily and reported additional close contacts not identified by Bluetooth. We used these data to estimate sensitivity and specificity. Participants completed a postparticipation survey regarding appropriateness, usability, acceptability, and adherence, and provided additional feedback via free text. We used tests of proportions to evaluate differences in survey responses between participants from each pilot, paired t tests to measure differences between compatible survey questions, and qualitative analysis to evaluate the survey’s free-text responses.ResultsAmong 25 participants in the app pilot, 53 contact interactions were identified by Bluetooth and an additional 61 by self-report. Among 17 participants in the tag pilot, 171 contact interactions were identified by Bluetooth and an additional 4 by self-report. The tag had significantly higher sensitivity compared with the app (46/49, 94% vs 35/61, 57%; P<.001), as well as higher specificity (120/126, 95% vs 123/141, 87%; P=.02). Most participants felt that Bluetooth contact tracing was appropriate on campus (26/32, 81%), while significantly fewer participants felt that using other technologies, such as GPS or Wi-Fi, was appropriate (17/31, 55%; P=.02). Most participants preferred technology developed and managed by the university rather than a third party (27/32, 84%) and preferred not to have tracing apps on their personal phones (21/32, 66%), due to “concerns with privacy.” There were no significant differences in self-reported adherence rates across pilots.ConclusionsConvenient and carriable Bluetooth technology may improve tracing efficiency while alleviating privacy concerns by shifting data collection away from personal devices. With accuracy comparable to, and in this case, superior to, mobile phone apps, such approaches may be suitable for workplace or school settings with the ability to purchase and maintain physical devices.

Highlights

  • BackgroundFollowing its identification in Wuhan, China in December 2019, SARS-CoV-2 rapidly spread across the globe, resulting in millions of infections and deaths due to COVID-19 [1]

  • Among 25 participants in the app pilot, 53 contact interactions were identified by Bluetooth and an additional 61 by self-report

  • Among 17 participants in the tag pilot, 171 contact interactions were identified by Bluetooth and an additional 4 by self-report

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Summary

Introduction

BackgroundFollowing its identification in Wuhan, China in December 2019, SARS-CoV-2 rapidly spread across the globe, resulting in millions of infections and deaths due to COVID-19 [1]. The implementation of contact tracing for SARS-CoV-2 has faced many challenges due to high incidence rates, even among asymptomatic individuals [9], presymptomatic transmission [10], and, in many places, a lack of staffing and infrastructure [11]. These challenges made it difficult in many settings to achieve the yield (proportion of cases and contacts interviewed, isolated, and/or quarantined) and timeliness (time from symptom onset or testing to isolation for cases, and time from exposure to quarantine for contacts) thought to be required for effectiveness [12,13]. Much remains unknown about the accuracy of this technology in real-world settings, the attitudes of potential users, and the differences between delivery formats (mobile app vs carriable or wearable devices)

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