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1000 Titel
  • Dynamic variations of the COVID-19 disease at different quarantine strategies in Wuhan and mainland China
1000 Autor/in
  1. Cui, Qianqian |
  2. Hu, Zengyun |
  3. Li, Yingke |
  4. Han, Junmei |
  5. Teng, Zhidong |
  6. Qian, Jing |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-05-22
1000 Erschienen in
1000 Quellenangabe
  • 13(6):849-855
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1016/j.jiph.2020.05.014 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242968/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • BACKGROUND The Coronavirus Disease 2019 (COVID-19) firstly announced in Wuhan of Hubei province, China is rapidly spreading to all the other 31 provinces of China and to more than 140 countries. Quarantine strategies play the key role on the disease controlling and public health in the world with this pandemic of the COVID-19 defined by the World Health Organization. METHODS In this study, a SEIRQ epidemic model was developed to explore the dynamic changes of COVID-19 in Wuhan and mainland China, from January 27, 2020 to March 5, 2020. Moreover, to investigate the effects of the quarantine strategies, two perspectives are employed from the different quarantine magnitudes and quarantine time points. RESULTS The major results suggest that the COVID-19 variations are well captured by the epidemic model with very high accuracy in the cumulative confirmed cases, confirmed cases, cumulative recovered cases and cumulative death cases. The quarantine magnitudes in the susceptible individuals play larger roles on the disease control than the impacts of the quarantines of the exposed individuals and infectious individuals. For the quarantine time points, it shows that the early quarantine strategy is significantly important for the disease controlling. The time delayed quarantining will seriously increase the COVID-19 disease patients and prolongs the days of the disease extinction. CONCLUSIONS Our model can simulate and predict the COVID-19 variations and the quarantine strategies are important for the disease controlling, especially at the early period of the disease outbreak. These conclusions provide important scientific information for the government policymaker in the disease control strategies.
1000 Sacherschließung
gnd 1206347392 COVID-19
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/Q3VpLCBRaWFucWlhbg==|https://frl.publisso.de/adhoc/uri/SHUsIFplbmd5dW4=|https://frl.publisso.de/adhoc/uri/TGksIFlpbmdrZQ==|https://frl.publisso.de/adhoc/uri/SGFuLCBKdW5tZWk=|https://frl.publisso.de/adhoc/uri/VGVuZywgWmhpZG9uZw==|https://frl.publisso.de/adhoc/uri/UWlhbiwgSmluZw==
1000 Label
1000 Förderer
  1. National Natural Science Foundation of China |
  2. Natural Science Foundation of Ningxia University |
  3. Major Innovation Projects for Building First-class Universities in China's Western Region |
1000 Fördernummer
  1. 11771373, 61662060
  2. ZR18011
  3. ZKZD2017009
1000 Förderprogramm
  1. -
  2. -
  3. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer National Natural Science Foundation of China |
    1000 Förderprogramm -
    1000 Fördernummer 11771373, 61662060
  2. 1000 joinedFunding-child
    1000 Förderer Natural Science Foundation of Ningxia University |
    1000 Förderprogramm -
    1000 Fördernummer ZR18011
  3. 1000 joinedFunding-child
    1000 Förderer Major Innovation Projects for Building First-class Universities in China's Western Region |
    1000 Förderprogramm -
    1000 Fördernummer ZKZD2017009
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6421788.rdf
1000 Erstellt am 2020-07-13T08:28:52.351+0200
1000 Erstellt von 21
1000 beschreibt frl:6421788
1000 Bearbeitet von 218
1000 Zuletzt bearbeitet Fri Oct 01 15:31:04 CEST 2021
1000 Objekt bearb. Fri Oct 01 15:31:04 CEST 2021
1000 Vgl. frl:6421788
1000 Oai Id
  1. oai:frl.publisso.de:frl:6421788 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
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