Diagnosing COVID-19: The Disease and Tools for Detection

20201,835 citationsReviewbronze Open Access

Authors

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 ·

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.

Topics & Keywords

SARS-CoV-2 detection and testing COVID-19 diagnosis using AI SARS-CoV-2 and COVID-19 Research

UN Sustainable Development Goals

Good health and well-being

Publication Details

Published in: ACS Nano

Volume 14, Issue 4, pp. 3822-3835

DOI: 10.1021/acsnano.0c02624

Field-Weighted Citation Impact: 41.00