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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Jan 18, 2021
Date Accepted: Mar 12, 2021
Date Submitted to PubMed: Mar 31, 2021

The final, peer-reviewed published version of this preprint can be found here:

Analyzing the Essential Attributes of Nationally Issued COVID-19 Contact Tracing Apps: Open-Source Intelligence Approach and Content Analysis

Weiß JP, Esdar M, Hübner U

Analyzing the Essential Attributes of Nationally Issued COVID-19 Contact Tracing Apps: Open-Source Intelligence Approach and Content Analysis

JMIR Mhealth Uhealth 2021;9(3):e27232

DOI: 10.2196/27232

PMID: 33724920

PMCID: 8006898

Tracing the tracers – Exploring essential attributes to assess nationally issued COVID-19 contact tracing apps: An open source intelligence approach

  • Jan-Patrick Weiß; 
  • Moritz Esdar; 
  • Ursula Hübner

ABSTRACT

Background:

Contact tracing apps are a potentially useful pillar in national COVID-19 containment strategies. Various national apps with different technical design features have been commissioned and issued by governments worldwide.

Objective:

Our goal was to develop and propose an item set suitable for describing and monitoring nationally issued COVID-19 contact tracing apps. This item set should lead to a framework for describing the key technical features of the apps and to monitor their usage based on widely available information.

Methods:

We used an open-source intelligence approach to access a multitude of publicly available sources to collect data and information regarding the development and use of tracing apps in different countries over several months from June 2020 to January 2021. The documents found were then iteratively analysed via content analysis methods to extract further information. During this process, the initial subject areas were refined into research areas, i.e. coherent topics, which were then searched for individual features. These features were paraphrased as items in the form of questions and applied on information material from a sample of countries, i.e. from Brazil, China, France, Germany, Italy, Singapore, South Korea and United Kingdom (England and Wales). This sample was selected purposefully with the intention to include apps of different countries from around the world and thus to propose a valid item set covering as many app features as possible.

Results:

After screening the sources for general, technical, privacy and application information initially, five clusters of information needs emerged that could be subsumed by the five research areas: background information, purpose, technology, privacy and experience. The retrieved material was analysed according to these research areas to identify individual items per area. These items were phrased as questions and assigned to the three final categories and their subcategories: basic information (name, release date, number of downloads, open source code, public information, collaborators, purpose), technical information (protocol, tracing technology, exposure notification system, interoperability) and data privacy information (entity of trust, anonymity). They lay the foundation of the item set constituting the evaluation framework which was tested and documented for the eight countries. The comparison of the countries reveals differences especially with regard to the centralisation of the entity of trust and the overall transparency of the apps’ technical make-up.

Conclusions:

We provide a set of criteria for monitoring and evaluating COVID-19 tracing apps that can easily be applied to apps. The application of these criteria might be helpful to identify which design features turn out to be most successful, i.e. lead to widespread adoption among their target populations and across national boundaries. Finally, such evaluation might help to identify the contribution of the COVID-19 tracing apps to the containment of a pandemic.


 Citation

Please cite as:

Weiß JP, Esdar M, Hübner U

Analyzing the Essential Attributes of Nationally Issued COVID-19 Contact Tracing Apps: Open-Source Intelligence Approach and Content Analysis

JMIR Mhealth Uhealth 2021;9(3):e27232

DOI: 10.2196/27232

PMID: 33724920

PMCID: 8006898

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.

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