Evidence map›Paper›PMID 36219833›Full record

ArticleJMIR public health and surveillance2022

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

Paola Daniore, Vasileios Nittas, Tala Ballouz, Dominik Menges, André Moser, Marc Höglinger, Petra Villiger, Krisztina Schmitz-Grosz, Viktor Von Wyl

Abstract read
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Article in JMIR public health and surveillance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Paola DanioreInstitute for Implementation Science in Healthcare, University of Zurich, Zurich, Switzerland.ORCID 0000-0003-3319-1125
Vasileios NittasEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0002-6685-8275
Tala BallouzEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0003-2334-8600
Dominik MengesEpidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0001-5970-1846
André MoserClinical Trials Unit, University of Bern, Bern, Switzerland.ORCID 0000-0001-7178-6539
Marc HöglingerWinterthur Institute of Health Economics, Zurich University of Applied Sciences, Winterthur, Switzerland.ORCID 0000-0003-2743-2199
Petra VilligerMedgate Aktiengesellschaft, Basel, Switzerland.ORCID 0000-0002-9614-5612
Krisztina Schmitz-GroszMedgate Aktiengesellschaft, Basel, Switzerland.ORCID 0000-0002-9799-5176
Viktor Von WylInstitute for Implementation Science in Healthcare, University of Zurich, Zurich, Switzerland.ORCID 0000-0002-8754-9797

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital 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.

objectiveThe 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.

methodsWe 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.

resultsAverage 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.

conclusionsIn 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.

Indexed as

COVID-19Mobile ApplicationsContact TracingCross-Sectional StudiesHumansPandemicsSARS-CoV-2Switzerlandcontact-tracing appCOVID-19digital contact tracingdigital proximitydigital toolexposure notificationmobile apppublic healthSARS-CoV-2surveillanceSwissCovid appSwitzerlandvariant of concern

Identifiers

PMID36219833
PMCPMC9700234

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.