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1000 Titel
  • Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak
1000 Autor/in
  1. Zhao, Shi |
  2. Lin, Qianyin |
  3. Ran, Jinjun |
  4. Musa, Salihu S. |
  5. Yang, Guangpu |
  6. Wang, Weiming |
  7. Lou, Yijun |
  8. Gao, Daozhou |
  9. Yang, Lin |
  10. He, Daihai |
  11. Wang, Maggie H. |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-01-30
1000 Erschienen in
1000 Quellenangabe
  • 92:214-217
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1016/j.ijid.2020.01.050 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7110798/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • BACKGROUNDS An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak. METHODS Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI. FINDINGS The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96–2.55) to 3.58 (95%CI: 2.89–4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0. CONCLUSION The mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks.
1000 Sacherschließung
gnd 1206347392 COVID-19
lokal Basic reproduction number
lokal Novel coronavirus (2019-nCoV)
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/WmhhbywgU2hp|https://frl.publisso.de/adhoc/uri/TGluLCBRaWFueWlu|https://frl.publisso.de/adhoc/uri/UmFuLCBKaW5qdW4g|https://frl.publisso.de/adhoc/uri/TXVzYSwgU2FsaWh1IFMu|https://frl.publisso.de/adhoc/uri/WWFuZywgR3VhbmdwdQ==|https://frl.publisso.de/adhoc/uri/V2FuZywgV2VpbWluZyA=|https://frl.publisso.de/adhoc/uri/TG91LCBZaWp1biA=|https://frl.publisso.de/adhoc/uri/R2FvLCBEYW96aG91|https://frl.publisso.de/adhoc/uri/WWFuZywgTGlu|https://frl.publisso.de/adhoc/uri/SGUsIERhaWhhaQ==|https://frl.publisso.de/adhoc/uri/V2FuZywgTWFnZ2llIEgu
1000 Label
1000 Förderer
  1. Research Grants Council, University Grants Committee |
  2. National Natural Science Foundation of China |
  3. Huaian Key Laboratory for Infectious Diseases Control and Prevention |
1000 Fördernummer
  1. 15205119
  2. 61672013
  3. HAP201704
1000 Förderprogramm
  1. General Research Fund
  2. -
  3. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Research Grants Council, University Grants Committee |
    1000 Förderprogramm General Research Fund
    1000 Fördernummer 15205119
  2. 1000 joinedFunding-child
    1000 Förderer National Natural Science Foundation of China |
    1000 Förderprogramm -
    1000 Fördernummer 61672013
  3. 1000 joinedFunding-child
    1000 Förderer Huaian Key Laboratory for Infectious Diseases Control and Prevention |
    1000 Förderprogramm -
    1000 Fördernummer HAP201704
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6421283.rdf
1000 Erstellt am 2020-06-12T09:57:57.991+0200
1000 Erstellt von 21
1000 beschreibt frl:6421283
1000 Bearbeitet von 218
1000 Zuletzt bearbeitet 2021-09-20T15:51:01.472+0200
1000 Objekt bearb. Mon Sep 20 15:51:01 CEST 2021
1000 Vgl. frl:6421283
1000 Oai Id
  1. oai:frl.publisso.de:frl:6421283 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
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