Recent advances in novel lateral flow technologies for detection of COVID-19

Wesley Wei Wen Hsiao, Trong Nghia Le, Dinh Minh Pham, Hui Hsin Ko, Huan Cheng Chang, Cheng Chung Lee, Neha Sharma, Cheng Kang Lee, Wei Hung Chiang

Research output: Contribution to journalReview articlepeer-review

7 Citations (Scopus)

Abstract

The development of reliable and robust diagnostic tests is one of the most efficient methods to limit the spread of coronavirus disease 2019 (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). However, most laboratory diagnostics for COVID-19, such as enzyme-linked immunosorbent assay (ELISA) and reverse transcriptase-polymerase chain reaction (RT-PCR), are expensive, time-consuming, and require highly trained professional operators. On the other hand, the lateral flow immunoassay (LFIA) is a simpler, cheaper device that can be operated by unskilled personnel easily. Unfortunately, the current technique has some limitations, mainly inaccuracy in detection. This review article aims to highlight recent advances in novel lateral flow technologies for detecting SARS-CoV-2 as well as innovative approaches to achieve highly sensitive and specific point-of-care testing. Lastly, we discuss future perspectives on how smartphones and Artificial Intelligence (AI) can be integrated to revolutionize disease detection as well as disease control and surveillance.

Original languageEnglish
Article number295
JournalBiosensors
Volume11
Issue number9
DOIs
Publication statusPublished - Sep 2021
Externally publishedYes

Keywords

  • Artificial intelligence
  • COVID-19
  • Lateral flow assay
  • Point-of-care testing
  • SARS-CoV-2

ASJC Scopus subject areas

  • Clinical Biochemistry

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