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Issue 9, 2021
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Point-of-care testing detection methods for COVID-19

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Abstract

COVID-19 is an acute respiratory disease caused by SARS-CoV-2, which has high transmissibility. People infected with SARS-CoV-2 can develop symptoms including cough, fever, pneumonia and other complications, which in severe cases could lead to death. In addition, a proportion of people infected with SARS-CoV-2 may be asymptomatic. At present, the primary diagnostic method for COVID-19 is reverse transcription-polymerase chain reaction (RT-PCR), which tests patient samples including nasopharyngeal swabs, sputum and other lower respiratory tract secretions. Other detection methods, e.g., isothermal nucleic acid amplification, CRISPR, immunochromatography, enzyme-linked immunosorbent assay (ELISA) and electrochemical sensors are also in use. As the current testing methods are mostly performed at central hospitals and third-party testing centres, the testing systems used mostly employ large, high-throughput, automated equipment. Given the current situation of the epidemic, point-of-care testing (POCT) is advantageous in terms of its ease of use, greater approachability on the user's end, more timely detection, and comparable accuracy and sensitivity, which could reduce the testing load on central hospitals. POCT is thus conducive to daily epidemic control and achieving early detection and treatment. This paper summarises the latest research advances in POCT-based SARS-CoV-2 detection methods, compares three categories of commercially available products, i.e., nucleic acid tests, immunoassays and novel sensors, and proposes the expectations for the development of POCT-based SARS-CoV-2 detection including greater accessibility, higher sensitivity and lower costs.

Graphical abstract: Point-of-care testing detection methods for COVID-19

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Article information


Submitted
15 Nov 2020
Accepted
21 Feb 2021
First published
22 Feb 2021

Lab Chip, 2021,21, 1634-1660
Article type
Critical Review

Point-of-care testing detection methods for COVID-19

Q. Song, X. Sun, Z. Dai, Y. Gao, X. Gong, B. Zhou, J. Wu and W. Wen, Lab Chip, 2021, 21, 1634 DOI: 10.1039/D0LC01156H

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