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A Data-Driven Simulation of the Exposure Notification Cascade for Digital Contact Tracing of SARS-CoV-2 in Zurich, Switzerland.
Menges, Dominik; Aschmann, Hélène E; Moser, André; Althaus, Christian L; von Wyl, Viktor.
  • Menges D; Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
  • Aschmann HE; Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
  • Moser A; CTU Bern, University of Bern, Bern, Switzerland.
  • Althaus CL; Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
  • von Wyl V; Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
JAMA Netw Open ; 4(4): e218184, 2021 04 01.
Article in English | MEDLINE | ID: covidwho-1384070
ABSTRACT
Importance Digital contact tracing (DCT) apps have been released in several countries to help interrupt SARS-CoV-2 transmission chains. However, the effect of DCT on pandemic mitigation remains to be demonstrated.

Objective:

To estimate key populations and performance indicators along the exposure notification cascade of the SwissCovid DCT app in a clearly defined regional and temporal context. Design, Setting, and

Participants:

This comparative effectiveness study was based on a simulation informed by measured data from issued quarantine recommendations and positive SARS-CoV-2 test results after DCT exposure notifications in the canton of Zurich. A stochastic model was developed to re-create the DCT notification cascade for Zurich. Population sizes at each cascade step were estimated using triangulation based on publicly available administrative and observational research data for the study duration from September 1 to October 31, 2020. The resultant estimates were checked for internal consistency and consistency with upstream or downstream estimates in the cascade. Stochastic sampling from data-informed parameter distributions was performed to explore the robustness of results. Subsequently, key performance indicators were evaluated to assess the potential contribution of DCT compared with manual contact tracing. Main Outcomes and

Measures:

Receiving a voluntary quarantine recommendation and/or a positive SARS-CoV-2 test result after exposure notification.

Results:

In September 2020, 537 app users received a positive SARS-CoV-2 test result in Zurich, 324 of whom received and entered an upload authorization code. This code triggered an app notification for an estimated 1374 (95% simulation interval [SI], 932-2586) proximity contacts and led to 722 information hotline calls, with an estimated 170 callers (95% SI, 154-186) receiving a quarantine recommendation. An estimated 939 (95% SI, 720-1127) notified app users underwent testing for SARS-CoV-2, of whom 30 (95% SI, 23-36) had positive results after an app notification. Key indicator evaluations revealed that the DCT app triggered quarantine recommendations for the equivalent of 5% of all exposed contacts placed in quarantine by manual contact tracing. For every 10.9 (95% SI, 7.6-15.6) upload authorization codes entered in the app, 1 contact had positive test results for SARS-CoV-2 after app notification. Longitudinal indicator analyses demonstrated bottlenecks in the notification cascade, because capacity limits were reached owing to an increased incidence of SARS-CoV-2 infection in October 2020. Conclusions and Relevance In this simulation study of the notification cascade of the SwissCovid DCT app, receipt of exposure notifications was associated with quarantine recommendations and identification of SARS-CoV-2-positive cases. These findings in notified proximity contacts reflect important intermediary steps toward transmission prevention.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Simulation / Contact Tracing / Disease Transmission, Infectious / Disease Notification / Mobile Applications / COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Adult / Female / Humans / Male Country/Region as subject: Europa Language: English Journal: JAMA Netw Open Year: 2021 Document Type: Article Affiliation country: JAMANETWORKOPEN.2021.8184

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Simulation / Contact Tracing / Disease Transmission, Infectious / Disease Notification / Mobile Applications / COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Adult / Female / Humans / Male Country/Region as subject: Europa Language: English Journal: JAMA Netw Open Year: 2021 Document Type: Article Affiliation country: JAMANETWORKOPEN.2021.8184