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Cited by 7,344

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR

Open access
Corman, Victor M, Landt, Olfert, Kaiser, Marco, Molenkamp, Richard, Meijer, Adam, Chu, Daniel KW, Bleicker, Tobias, Brünink, Sebastian, Schneider, Julia, Schmidt, Marie Luisa, Mulders, Daphne GJC, Haagmans, Bart L, van der Veer, Bas, van den Brink, Sharon, Wijsman, Lisa, Goderski, Gabriel, Romette, Jean-Louis, Ellis, Joanna, Zambon, Maria, Peiris, Malik, Goossens, Herman, Reusken, Chantal, Koopmans, Marion PG, Drosten, Christian·2020·Eurosurveillance

Abstract

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.

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Metadata

Authors
Corman, V. M., Landt, O., Kaiser, M., Molenkamp, R., Meijer, A., Chu, D. K., Bleicker, T., Brünink, S., Schneider, J., Schmidt, M. L., Mulders, D. G., Haagmans, B. L., van der Veer, B., van den Brink, S., Wijsman, L., Goderski, G., Romette, J.-L., Ellis, J., Zambon, M., Peiris, M., Goossens, H., Reusken, C., Koopmans, M. P., & Drosten, C.
Venue
Eurosurveillance
Published
2020-01-23
Volume
25
Issue
3
ISSN
  • 1025-496X (ISSN-L)
  • 1560-7917
OpenAlex
W3001195213
Cited by
7,344
References
2
FWCI
195.98
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. https://app.cochat.ai/papers/10.2807/1560-7917.es.2020.25.3.2000045
The paper
Corman, V. M., Landt, O., Kaiser, M., Molenkamp, R., Meijer, A., Chu, D. K., Bleicker, T., Brünink, S., Schneider, J., Schmidt, M. L., Mulders, D. G., Haagmans, B. L., van der Veer, B., van den Brink, S., Wijsman, L., Goderski, G., Romette, J.-L., Ellis, J., Zambon, M., . . . Drosten, C. (2020). Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Eurosurveillance. https://doi.org/10.2807/1560-7917.es.2020.25.3.2000045

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.