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1000 Titel
  • Evaluation and prediction of the COVID-19 variations at different input population and quarantine strategies, a case study in Guangdong province, China
1000 Autor/in
  1. Hu, Zengyun |
  2. Cui, Qianqian |
  3. Han, Junmei |
  4. Wang, Xia |
  5. Sha, Wei E.I. |
  6. Teng, Zhidong |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-04-22
1000 Erschienen in
1000 Quellenangabe
  • 95:231-240
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1016/j.ijid.2020.04.010 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7175914/ |
1000 Ergänzendes Material
  • https://www.sciencedirect.com/science/article/pii/S1201971220302265#sec0095 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • In this study, an epidemic model was developed to simulate and predict the disease variations of Guangdong province which was focused on the period from Jan 27 to Feb 20, 2020. To explore the impacts of the input population and quarantine strategies on the disease variations at different scenarios, four time points were assumed as Feb 6, Feb 16, Feb 24 and Mar 5 2020. The major results suggest that our model can well capture the disease variations with high accuracy. The simulated peak value of the confirmed cases is 1002 at Feb 10, 2020 which is mostly close to the reported number of 1007 at Feb 9, 2020. The disease will become extinction with peak value of 1397 at May 11, 2020. Moreover, the increased numbers of the input population can mainly shorten the disease extinction days and the increased percentages of the exposed individuals of the input population increase the number of cumulative confirmed cases at a small percentage. Increasing the input population and decreasing the quarantine strategy together around the time point of the peak value of the confirmed cases, may lead to the second outbreak.
1000 Sacherschließung
gnd 1206347392 COVID-19
lokal Guangdong province
lokal SEIRQ model
lokal Coronavirus disease 2019 (COVID-19)
lokal Scenario analysis
lokal Quarantine strategies
lokal Population migration
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/SHUsIFplbmd5dW4=|https://frl.publisso.de/adhoc/uri/Q3VpLCBRaWFucWlhbg==|https://frl.publisso.de/adhoc/uri/SGFuLCBKdW5tZWk=|https://frl.publisso.de/adhoc/uri/V2FuZywgWGlh|https://frl.publisso.de/adhoc/uri/U2hhLCBXZWkgRS5JLg==|https://frl.publisso.de/adhoc/uri/VGVuZywgWmhpZG9uZw==
1000 Label
1000 Förderer
  1. National Natural Science Foundation of China |
1000 Fördernummer
  1. 11771373
1000 Förderprogramm
  1. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer National Natural Science Foundation of China |
    1000 Förderprogramm -
    1000 Fördernummer 11771373
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6422296.rdf
1000 Erstellt am 2020-08-04T08:51:09.061+0200
1000 Erstellt von 21
1000 beschreibt frl:6422296
1000 Bearbeitet von 218
1000 Zuletzt bearbeitet Fri Oct 01 16:09:33 CEST 2021
1000 Objekt bearb. Fri Oct 01 16:09:33 CEST 2021
1000 Vgl. frl:6422296
1000 Oai Id
  1. oai:frl.publisso.de:frl:6422296 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
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