Currently submitted to: Online Journal of Public Health Informatics
Date Submitted: Jul 8, 2026
Open Peer Review Period: Jul 16, 2026 - Sep 10, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Contact tracing apps geared towards verified COVID-19 cases
ABSTRACT
Background:
The COVID 19 pandemic triggered an unprecedented global deployment of digital contact tracing applications to complement manual case investigation. These applications varied widely in technical architecture, data governance, and public acceptance, creating a natural experiment in digital public health intervention that merits systematic analysis.
Objective:
To analyse COVID-19 contact tracing applications deployed in 45 countries during the global pandemic (2020 to 2023), providing an initial examination of the technical architectures and coding methodologies employed, and identifying key differences between centralized and decentralized systems.
Methods:
Fifty contact tracing applications implemented in 45 countries were analysed through systematic review of public technical documentation, adoption metrics, and secondary sources. The analysis compared centralized and decentralized architectures, proximity detection technologies (Bluetooth, GPS, and QR codes), technical requirements, developers, privacy frameworks, and public adoption patterns.
Results:
The analysis revealed marked heterogeneity in architectures, technologies, and levels of adoption. Decentralized systems predominated and achieved higher privacy ratings and public acceptance, while centralized systems demonstrated potentially greater epidemiological efficiency. Bluetooth Low Energy was the most widely used detection technology, albeit with relevant technical limitations. Clear correlations were observed between privacy models, institutional trust, and adoption rates, as well as structural barriers related to smartphone dependence that limited coverage among vulnerable populations.
Conclusions:
Applications that achieved high adoption combined privacy protective design, transparent communication, and reliable user experience. Adoption was also dependent on cultural context and levels of institutional trust. Reliance on smartphones created accessibility barriers for older and more vulnerable populations. Clinical Trial: Not applicable. This study is an observational, non‑interventional analysis of publicly available data on contact tracing applications. It did not involve human participants, clinical interventions, or controlled trials, and therefore does not require trial registration.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© 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.