Diagnosing COVID-19: The Disease and Tools for Detection | Zendy

Buddhisha Udugama | Zendy; Pranav Kadhiresan | Zendy; H Kozłowski | Zendy; Ayden Malekjahani | Zendy; Matthew Osborne | Zendy; Vanessa Y. C. Li | Zendy; Hongmin Chen | Zendy; Samira Mubareka | Zendy; Jonathan B. Gubbay | Zendy; Warren C. W. Chan | Zendy

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Diagnosing COVID-19: The Disease and Tools for Detection

Author(s) -

Buddhisha Udugama,

Pranav Kadhiresan,

H Kozłowski,

Ayden Malekjahani,

Matthew Osborne,

Vanessa Y. C. Li,

Hongmin Chen,

Samira Mubareka,

Jonathan B. Gubbay,

Warren C. W. Chan

Publication year - 2020

Publication title -

acs nano

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 5.554

H-Index - 382

eISSN - 1936-086X

pISSN - 1936-0851

DOI - 10.1021/acsnano.0c02624

Subject(s) - covid-19 , outbreak , point of care , point of care testing , data science , virology , pandemic , disease , computer science , computational biology , medicine , biology , infectious disease (medical specialty) , pathology

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.

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