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Diagnosing COVID-19: The Disease and Tools for Detection

ACS Nano · 2020 · Vol. 14(4) · pp. 3822–3835

Buddhisha Udugama(University of Toronto)Pranav Kadhiresan(University of Toronto)H Kozłowski(University of Toronto)Ayden Malekjahani(University of Toronto)Matthew Osborne(University of Toronto)Vanessa Y. C. Li(University of Toronto)Hongmin Chen(University of Toronto)Samira Mubareka(Sunnybrook Health Science Centre)Jonathan B. Gubbay(University of Toronto)Warren C. W. Chan✉(University of Toronto)

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Abstract

COVID-19 has spread globally since its discovery in Hubei province, China in December 2019. A combination of computed tomography imaging, whole genome sequencing, and electron microscopy were initially used to screen and identify SARS-CoV-2, the viral etiology of COVID-19. The aim of this review article is to inform the audience of diagnostic and surveillance technologies for SARS-CoV-2 and their performance characteristics. We describe point-of-care diagnostics that are on the horizon and encourage academics to advance their technologies beyond conception. Developing plug-and-play diagnostics to manage the SARS-CoV-2 outbreak would be useful in preventing future epidemics.

SARS-CoV-2 detection and testing COVID-19 diagnosis using AI SARS-CoV-2 and COVID-19 ResearchCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Outbreak2019-20 coronavirus outbreakPoint of carePoint-of-care testingData scienceVirologyPandemicDisease

MeSH terms

Point-of-Care TestingSmartphoneBetacoronavirusCOVID-19SARS-CoV-2COVID-19 TestingHumansPneumonia, ViralPopulation SurveillanceTomography, X-Ray ComputedViral ProteinsCoronavirus InfectionsClinical Laboratory TechniquesNucleic Acid Amplification TechniquesPandemics