A contact-tracing system identified potential COVID-19 contacts, providing specific data for location, date and cumulative contact time
As the U.S. heads into the flu and COVID season, a group of doctors have developed a Bluetooth low-energy (BLE) system to improve contact tracing for healthcare workers.
In a paper published by the Cambridge University Press, a team of 13 doctors detail how they built a contact-tracing system that successfully identified potential COVID-19 contacts, providing specific additional data including location, date and cumulative contact time.
The researchers reported the Bluetooth system predicted close contacts with great accuracy and provided an additional contact yield of 14.8 percent and would decrease the effective reproduction number by 56 percent.
Protecting Health Care Workers
Dr. Cristina Vazquez Guillamet, associate professor of medicine at the Washington University School of Medicine and her colleagues developed and tested an automated BLE-based contact-tracing system designed for two COVID-19 hospital units—a medical ward and an ICU.
The groups wrote that health care personnel (HCP) are at “significant risk for contracting and spreading SARS-CoV-2.” Several methods relying on BLE were previously trialed focusing on single individuals.
The system, tested between May and November 2021 with 186 HCPs, consisted of battery-operated wearable BLE devices beacons worn by HCP and transmitted short-range radio signals to small-embedded computers, or anchors, which captured the signals, and an edge server where contact-tracing algorithms were applied to the data.
Using Data Results
The doctors used the data to analyze the proximity between users and close contacts during patient rounds. When an HCP tested positive, the data collected included all potential contacts, location, date and cumulative contact time.
The researchers would then estimate the impact of the system using a modified susceptible, exposed, infected and recovered compartmental model.
The findings were that the overall accuracy for room-level location ranged between 0.96 and 1, improving as the number of anchors increased. This led the doctors to predict close contacts with an accuracy between 0.88 and 1.
Scalable Project
Additionally, the system showed that the core group of HCP during patient rounds consisted of seven people on average. The system’s clustering method accurately identified the personnel present during rounds and the time spent in contact with the group with accuracy above 0.9.
Based on these pilot study findings, the doctors wrote that BLE-based contact tracing results “indicated that BLE wearable tags may be a tool for detecting contacts in hospital settings [and] presents an affordable and scalable system that may function as a screening tool to complement traditional contact-tracing methods.”