Real-Time Digital Contact Tracing: Development of a System to Control COVID-19 Outbreaks in Nursing Homes and Long-Term Care Facilities

Abstract

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can spread rapidly in nursing homes and long-term care (LTC) facilities. Symptoms-based screening and manual contact tracing have limitations that render them ineffective for containing the viral spread in LTC facilities. Symptoms-based screening alone cannot identify asymptomatic people who are infected, and the viral spread is too fast in confined living quarters to be contained by slow manual contact tracing processes. Objective We describe the development of a digital contact tracing system that LTC facilities can use to rapidly identify and contain asymptomatic and symptomatic SARS-CoV-2 infected contacts. A compartmental model was also developed to simulate disease transmission dynamics and to assess system performance versus conventional methods. Methods We developed a compartmental model parameterized specifically to assess the coronavirus disease (COVID-19) transmission in LTC facilities. The model was used to quantify the impact of asymptomatic transmission and to assess the performance of several intervention groups to control outbreaks: no intervention, symptom mapping, polymerase chain reaction testing, and manual and digital contact tracing. Results Our digital contact tracing system allows users to rapidly identify and then isolate close contacts, store and track infection data in a respiratory line listing tool, and identify contaminated rooms. Our simulation results indicate that the speed and efficiency of digital contact tracing contributed to superior control performance, yielding up to 52% fewer cases than conventional methods. Conclusions Digital contact tracing systems show promise as an effective tool to control COVID-19 outbreaks in LTC facilities. As facilities prepare to relax restrictions and reopen to outside visitors, such tools will allow them to do so in a surgical, cost-effective manner that controls outbreaks while safely giving residents back the life they once had before this pandemic hit.

Digital contact tracing, community uptake, and proximity awareness technology to fight COVID-19: a systematic review

“…Assuming R eff = 2.6, digital tracing at a 60% adoption rate would produce a 67% reduction in peak incidence. Finally, Wilmink, Summer, and Marsyla (2020)) reported 12% fewer infections for 100% uptake. This study refers to nursing homes and long-term care facilities, and population uptake refers only to personnel, residents, and visitors.…”

“…Of the eight papers, four reported that digital contact tracing alone (i.e., without manual tracing) reduces significantly infections or R eff more than manual tracing ( Abueg et al, 2021 ; Ferretti et al, 2020 ; Kretzschmar & Rozhnova, 2020 ; Wilmink et al, 2020 ), and two reported only a marginal improvement of R eff ( Bradshaw et al, 2021 ; Plank et al, 2020 ). For example, without manual contact tracing, digital tracing reduces R eff from 2.4 to 1.46, while manual contact tracing (in the absence of digital) reduces R eff to 1.5 ( Plank et al, 2020 ).…”

“…There are two main system architecture approaches in digital contact tracing: centralized and decentralized ( Cohen et al, 2020 ). The centralized approach, reported in four papers in this review ( Currie et al, 2020 ; Plank et al, 2020 ; Wilmink et al, 2020 ; Yasaka, Lehrich, & Sahyouni, 2020 ), is a top-down architecture where data are collected from the smartphone through an app and are stored at a central remote server. Therefore, the centralized approach has been criticized for potential privacy infringement ( Cohen et al, 2020 ).…”

“…This review found that BLE is the most widely used technology matched to a decentralized architecture ( Barrat et al, 2020 ; Currie et al, 2020 ; Ferretti et al, 2020 ; Hinch et al, 2020 ; Nakamoto et al, 2020 ; Plank et al, 2020 ; Pollmann et al, 2020 ; Xia & Lee, 2020 ). Wilmink et al (2020) coupled beacons with wearables. Following a centralized architecture, real-time location data are uploaded to cloud-based software to visualize egocentric contact networks.…”

The French Covid-19 contact tracing app: knowledge, attitudes, beliefs and practices of students in the health domain

“…based on a predicted distance and the duration of the contact), and to notify potentially exposed people using a centralized or decentralized network approach (John Leon Singh, Couch, & Yap, 2020). Efficacy of digital contact tracing systems has been assessed in previous studies thus reinforcing the idea that these tools can help limit the spread of the virus (Kretzschmar et al, 2020;Wilmink et al, 2020).…”