Overcoming the bottleneck to widespread testing: a rapid review of nucleic acid testing approaches for COVID-19 detection
Top Cited Papers
Open Access
- 1 May 2020
- journal article
- review article
- Published by Cold Spring Harbor Laboratory in RNA
- Vol. 26 (7), 771-783
- https://doi.org/10.1261/rna.076232.120
Abstract
The current COVID-19 pandemic presents a serious public health crisis, and a better understanding of the scope and spread of the virus would be aided by more widespread testing. Nucleic-acid-based tests currently offer the most sensitive and early detection of COVID-19. However, the “gold standard” test pioneered by the U.S. Centers for Disease Control and Prevention takes several hours to complete and requires extensive human labor, materials such as RNA extraction kits that could become in short supply, and relatively scarce qPCR machines. It is clear that a huge effort needs to be made to scale up current COVID-19 testing by orders of magnitude. There is thus a pressing need to evaluate alternative protocols, reagents, and approaches to allow nucleic-acid testing to continue in the face of these potential shortages. There has been a tremendous explosion in the number of papers written within the first weeks of the pandemic evaluating potential advances, comparable reagents, and alternatives to the “gold-standard” CDC RT-PCR test. Here we present a collection of these recent advances in COVID-19 nucleic acid testing, including both peer-reviewed and preprint articles. Due to the rapid developments during this crisis, we have included as many publications as possible, but many of the cited sources have not yet been peer-reviewed, so we urge researchers to further validate results in their own laboratories. We hope that this review can urgently consolidate and disseminate information to aid researchers in designing and implementing optimized COVID-19 testing protocols to increase the availability, accuracy, and speed of widespread COVID-19 testing.Keywords
Funding Information
- Howard Hughes Medical Institute (CC34430)
- the National Institutes of Health (T32GM098218, T32GM007232)
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