tetano
Editor, Senior Moderator
JMIR Mhealth Uhealth
. 2020 Sep 30.
doi: 10.2196/23148. Online ahead of print.
Performance of digital contact tracing tools for COVID-19 response in Singapore
Zhilian Huang[SUP] 1 [/SUP], Huiling Guo[SUP] 1 [/SUP], Yee Mun Lee[SUP] 2 [/SUP], Eu Chin Ho[SUP] 3 [/SUP], Hou Ang[SUP] 4 [/SUP], Angela Chow[SUP] 1 5 [/SUP]
Affiliations
Abstract
Background: Effective contact tracing is labor- and time-intensive during the coronavirus disease 2019 (COVID-19) pandemic, but essential in the absence of effective treatment and vaccines. Singapore launched the first Bluetooth-based contact tracing app- "TraceTogether" in March 2020 to augment its contact tracing capabilities.
Objective: This study aims to compare the performance of the contact tracing app-"TraceTogether" with a wearable tag-based Real-Time Locating System and validate them against the Electronic Medical Records at the National Centre for Infectious Disease (NCID), the national referral center for COVID-19 screening.
Methods: All patients and physicians in NCID's screening center were issued with RTLS tags for contact tracing. Eighteen physicians deployed to NCID's screening center from May 10-19, 2020 activated the "TraceTogether" app on their smartphones during shifts and urged patients to whom they medically attended to use the app. We compared patient contacts identified by "TraceTogether" and tag-based RTLS within NCID's vicinity during the physicians' 10-day posting. We further validated both digital contact tracing tools by verifying the physician-patient contacts with the EMR of 156 patients who attended at NCID's screening center over a 24-hr time frame within the study period.
Results: RTLS had a high sensitivity of 95.3% in detecting all patient contacts identified either by the system or "TraceTogether" while "TraceTogether" had an overall sensitivity of 6.5%, performing significantly better on Android phones (Android: 9.7%, iPhone: 2.7%, P<.001). When validated against the EMR, RTLS tags had a sensitivity of 96.9% and specificity of 83.1% while "TraceTogether" detected only two patient contacts with physicians who did not attend to them.
Conclusions: "TraceTogether" had a much lower sensitivity than tag-based RTLS in identifying patient contacts in a clinical setting. Although tag-based RTLS performed well for contact tracing in the clinical setting, its implementation in the community would be more challenging than "TraceTogether". Given the uncertainty on the adoption and capabilities of contact tracing apps, policy makers should be cautioned against the over-reliance on such apps for contact tracing. Nonetheless, leveraging on technology to augment conventional manual contact tracing was a necessary move for life to return to some normalcy over the long haul of COVID-19.
. 2020 Sep 30.
doi: 10.2196/23148. Online ahead of print.
Performance of digital contact tracing tools for COVID-19 response in Singapore
Zhilian Huang[SUP] 1 [/SUP], Huiling Guo[SUP] 1 [/SUP], Yee Mun Lee[SUP] 2 [/SUP], Eu Chin Ho[SUP] 3 [/SUP], Hou Ang[SUP] 4 [/SUP], Angela Chow[SUP] 1 5 [/SUP]
Affiliations
- PMID: 33006944
- DOI: 10.2196/23148
Abstract
Background: Effective contact tracing is labor- and time-intensive during the coronavirus disease 2019 (COVID-19) pandemic, but essential in the absence of effective treatment and vaccines. Singapore launched the first Bluetooth-based contact tracing app- "TraceTogether" in March 2020 to augment its contact tracing capabilities.
Objective: This study aims to compare the performance of the contact tracing app-"TraceTogether" with a wearable tag-based Real-Time Locating System and validate them against the Electronic Medical Records at the National Centre for Infectious Disease (NCID), the national referral center for COVID-19 screening.
Methods: All patients and physicians in NCID's screening center were issued with RTLS tags for contact tracing. Eighteen physicians deployed to NCID's screening center from May 10-19, 2020 activated the "TraceTogether" app on their smartphones during shifts and urged patients to whom they medically attended to use the app. We compared patient contacts identified by "TraceTogether" and tag-based RTLS within NCID's vicinity during the physicians' 10-day posting. We further validated both digital contact tracing tools by verifying the physician-patient contacts with the EMR of 156 patients who attended at NCID's screening center over a 24-hr time frame within the study period.
Results: RTLS had a high sensitivity of 95.3% in detecting all patient contacts identified either by the system or "TraceTogether" while "TraceTogether" had an overall sensitivity of 6.5%, performing significantly better on Android phones (Android: 9.7%, iPhone: 2.7%, P<.001). When validated against the EMR, RTLS tags had a sensitivity of 96.9% and specificity of 83.1% while "TraceTogether" detected only two patient contacts with physicians who did not attend to them.
Conclusions: "TraceTogether" had a much lower sensitivity than tag-based RTLS in identifying patient contacts in a clinical setting. Although tag-based RTLS performed well for contact tracing in the clinical setting, its implementation in the community would be more challenging than "TraceTogether". Given the uncertainty on the adoption and capabilities of contact tracing apps, policy makers should be cautioned against the over-reliance on such apps for contact tracing. Nonetheless, leveraging on technology to augment conventional manual contact tracing was a necessary move for life to return to some normalcy over the long haul of COVID-19.