Performance of the Swiss Digital Contact-Tracing App Over Various SARS-CoV-2 Pandemic Waves: Repeated Cross-sectional Analyses

被引:5
|
作者
Daniore, Paola [1 ,2 ]
Nittas, Vasileios [3 ]
Ballouz, Tala [3 ]
Menges, Dominik [3 ]
Moser, Andre [4 ]
Hoglinger, Marc [5 ]
Villiger, Petra [6 ]
Schmitz-Grosz, Krisztina [6 ]
Von Wyl, Viktor [1 ,2 ,3 ]
机构
[1] Univ Zurich, Inst Implementat Sci Healthcare, Zurich, Switzerland
[2] Univ Zurich, Digital Soc Initiat, Zurich, Switzerland
[3] Univ Zurich, Epidemiol Biostat & Prevent Inst, Zurich, Switzerland
[4] Univ Bern, Clin Trials Unit, Bern, Switzerland
[5] Zurich Univ Appl Sci, Winterthur Inst Hlth Econ, Winterthur, Switzerland
[6] Medgate Aktiengesellschaft, Basel, Switzerland
来源
JMIR PUBLIC HEALTH AND SURVEILLANCE | 2022年 / 8卷 / 11期
关键词
digital contact tracing; exposure notification; COVID-19; SARS-CoV-2; public health; surveillance; digital proximity; contact-tracing app; mobile app; Switzerland; variant of concern; SwissCovid app; digital tool;
D O I
10.2196/41004
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: Digital proximity-tracing apps have been deployed in multiple countries to assist with SARS-CoV-2 pandemic mitigation efforts. However, it is unclear how their performance and effectiveness were affected by changing pandemic contexts and new viral variants of concern. Objective: The aim of this study is to bridge these knowledge gaps through a countrywide digital proximity-tracing app effectiveness assessment, as guided by the World Health Organization/European Center for Prevention and Disease Control (WHO/ECDC) indicator framework to evaluate the public health effectiveness of digital proximity-tracing solutions. Methods: We performed a descriptive analysis of the digital proximity-tracing app SwissCovid in Switzerland for 3 different periods where different SARS-CoV-2 variants of concern (ie, Alpha, Delta, and Omicron, respectively) were most prevalent. In our study, we refer to the indicator framework for the evaluation of public health effectiveness of digital proximity-tracing apps of the WHO/ECDC. We applied this framework to compare the performance and effectiveness indicators of the SwissCovid app. Results: Average daily registered SARS-CoV-2 case rates during our assessment period from January 25, 2021, to March 19, 2022, were 20 (Alpha), 54 (Delta), and 350 (Omicron) per 100,000 inhabitants. The percentages of overall entered authentication codes from positive tests into the SwissCovid app were 9.9% (20,273/204,741), 3.9% (14,372/365,846), and 4.6% (72,324/1,581,506) during the Alpha, Delta, and Omicron variant phases, respectively. Following receipt of an exposure notification from the SwissCovid app, 58% (37/64, Alpha), 44% (7/16, Delta), and 73% (27/37, Omicron) of app users sought testing or performed self-tests. Test positivity among these exposure-notified individuals was 19% (7/37) in the Alpha variant phase, 29% (2/7) in the Delta variant phase, and 41% (11/27) in the Omicron variant phase compared to 6.1% (228,103/3,755,205), 12% (413,685/3,443,364), and 41.7% (1,784,951/4,285,549) in the general population, respectively. In addition, 31% (20/64, Alpha), 19% (3/16, Delta), and 30% (11/37, Omicron) of exposure-notified app users reported receiving mandatory quarantine orders by manual contact tracing or through a recommendation by a health care professional. Conclusions: In constantly evolving pandemic contexts, the effectiveness of digital proximity-tracing apps in contributing to mitigating pandemic spread should be reviewed regularly and adapted based on changing requirements. The WHO/ECDC framework allowed us to assess relevant domains of digital proximity tracing in a holistic and systematic approach. Although the Swisscovid app mostly worked, as reasonably expected, our analysis revealed room for optimizations and further performance improvements. Future implementation of digital proximity-tracing apps should place more emphasis on social, psychological, and organizational aspects to reduce bottlenecks and facilitate their use in pandemic contexts.
引用
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页数:11
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