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High—throughput and automated screening for COVID-19

  • Nestor Jonguitud-Borrego
  • , Koray Malcı
  • , Mihir Anand
  • , Erikan Baluku
  • , Calum Webb
  • , Lungang Liang
  • , Carlos Barba-Ostria
  • , Linda P. Guaman
  • , Liu Hui
  • , Leonardo Rios-Solis*
  • *Corresponding author for this work
  • EaStCHEM School of Chemistry, University of Edinburgh
  • Indian Institute of Technology Banaras Hindu University
  • Makerere University
  • BGI-Shenzhen
  • Universidad Tecnológica Equinoccial
  • Newcastle University

Research output: Contribution to journalReview articlepeer-review

14 Scopus citations

Abstract

The COVID-19 pandemic has become a global challenge for the healthcare systems of many countries with 6 million people having lost their lives and 530 million more having tested positive for the virus. Robust testing and a comprehensive track and trace process for positive patients are essential for effective pandemic control, leading to high demand for diagnostic testing. In order to comply with demand and increase testing capacity worldwide, automated workflows have come into prominence as they enable high-throughput screening, faster processing, exclusion of human error, repeatability, reproducibility and diagnostic precision. The gold standard for COVID-19 testing so far has been RT-qPCR, however, different SARS-CoV-2 testing methods have been developed to be combined with high throughput testing to improve diagnosis. Case studies in China, Spain and the United Kingdom have been reviewed and automation has been proven to be promising for mass testing. Free and Open Source scientific and medical Hardware (FOSH) plays a vital role in this matter but there are some challenges to be overcome before automation can be fully implemented. This review discusses the importance of automated high-throughput testing, the different equipment available, the bottlenecks of its implementation and key selected case studies that due to their high effectiveness are already in use in hospitals and research centres.

Original languageEnglish
Article number969203
JournalFrontiers in Medical Technology
Volume4
DOIs
StatePublished - 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • COVID-19
  • SARS-coV-2
  • automation
  • diagnostic
  • high-throughput

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