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Due to the sheer number of COVID-19 (coronavirus disease 2019) cases there is a need for increased world-wide SARS-CoV-2 testing capability that is both efficient and effective. Having open and easy access to detailed information about these tests, their sensitivity, the types of samples they use, etc. would be highly useful to ensure their reproducibility, to help clients compare and decide which tests would be best suited for their applications, and to avoid costs of reinventing similar or identical tests. Additionally, this resource would provide a means of comparing the many innovative diagnostic tools that are currently being developed in order to provide a foundation of technologies and methods for the rapid development and deployment of tests for future emerging diseases. Such a resource might thus help to avert the delays in testing and screening that was observed in the early stages of the pandemic and plausibly led to more COVID-19-related deaths than necessary. We aim to address these needs via a relational database containing standardized ontology and curated data about COVID-19 diagnostic tests that have been granted Emergency Use Authorizations (EUAs) by the FDA (US Food and Drug Administration). Simple queries of this actively growing database demonstrate considerable variation among these tests with respect to sensitivity (limits of detection, LoD), controls and targets used, criteria used for calling results, sample types, reagents and instruments, and quality and amount of information provided.


This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Alyssa Woronik is also affiliated with the Biology Department at New York University.

Mariah Daley is an undergraduate student in the Department of Biology at Sacred Heart University.



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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.



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