Background The ongoing outbreak of the recently emerged novel coronavirus (2019-nCoV) poses a challenge for public health laboratories as virus isolates are unavailable while there is growing evidence that the outbreak is more widespread than initially thought, and international spread through travellers does already occur. Aim We aimed to develop and deploy robust diagnostic methodology for use in public health laboratory settings without having virus material available. Methods Here we present a validated diagnostic workflow for 2019-nCoV, its design relying on close genetic relatedness of 2019-nCoV with SARS coronavirus, making use of synthetic nucleic acid technology. Results The workflow reliably detects 2019-nCoV, and further discriminates 2019-nCoV from SARS-CoV. Through coordination between academic and public laboratories, we confirmed assay exclusivity based on 297 original clinical specimens containing a full spectrum of human respiratory viruses. Control material is made available through European Virus Archive – Global (EVAg), a European Union infrastructure project. Conclusion The present study demonstrates the enormous response capacity achieved through coordination of academic and public laboratories in national and European research networks.
Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR
V. Corman,O. Landt,M. Kaiser,R. Molenkamp,A. Meijer,D. Chu,T. Bleicker,Sebastian Brünink,J. Schneider,Marie L Schmidt,D. Mulders,B. Haagmans,B. van der Veer,Sharon van den Brink,Lisa A. Wijsman,G. Goderski,J. Romette,J. Ellis,M. Zambon,M. Peiris,H. Goossens,C. Reusken,M. Koopmans,C. Drosten
Published 2020 in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin
ABSTRACT
PUBLICATION RECORD
- Publication year
2020
- Venue
Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin
- Publication date
2020-01-01
- Fields of study
Medicine, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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REFERENCES
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