Back to Search Start Over

A blueprint for the implementation of a validated approach for the detection of SARS-Cov2 in clinical samples in academic facilities [version 2; peer review: 2 approved]

Authors :
Sushmita Sridhar
Sally Forrest
Iain Kean
Jamie Young
Josefin Bartholdson Scott
Mailis Maes
Joana Pereira-Dias
Surendra Parmar
Matthew Routledge
Dominic Sparkes
Lucy Rivett
Gordon Dougan
Michael Weekes
Martin Curran
Ian Goodfellow
Stephen Baker
Source :
Wellcome Open Research, Vol 5 (2020)
Publication Year :
2020
Publisher :
Wellcome, 2020.

Abstract

The COVID-19 pandemic is expanding at an unprecedented rate. As a result, diagnostic services are stretched to their limit, and there is a clear need for the provision of additional diagnostic capacity. Academic laboratories, many of which are closed due to governmental lockdowns, may be in a position to support local screening capacity by adapting their current laboratory practices. Here, we describe the process of developing a SARS-Cov2 diagnostic workflow in a conventional academic Containment Level 2 laboratory. Our outline includes simple SARS-Cov2 deactivation upon contact, the method for a quantitative real-time reverse transcriptase PCR detecting SARS-Cov2, a description of process establishment and validation, and some considerations for establishing a similar workflow elsewhere. This was achieved under challenging circumstances through the collaborative efforts of scientists, clinical staff, and diagnostic staff to mitigate to the ongoing crisis. Within 14 days, we created a validated COVID-19 diagnostics service for healthcare workers in our local hospital. The described methods are not exhaustive, but we hope may offer support to other academic groups aiming to set up something comparable in a short time frame.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
2398502X
Volume :
5
Database :
Directory of Open Access Journals
Journal :
Wellcome Open Research
Publication Type :
Academic Journal
Accession number :
edsdoj.1c64bfcca6dd49fa8785252143de5682
Document Type :
article
Full Text :
https://doi.org/10.12688/wellcomeopenres.15937.2