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1000 Titel
  • Feasibility study of mitigation and suppression strategies for controlling COVID-19 outbreaks in London and Wuhan
1000 Autor/in
  1. Yang, Po |
  2. Qi, Jun |
  3. Zhang, Shuhao |
  4. Wang, Xulong |
  5. Bi, Gaoshan |
  6. Yang, Yun |
  7. Sheng, Bin |
  8. Yang, Geng |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-08-06
1000 Erschienen in
1000 Quellenangabe
  • 15(8):e0236857
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1371/journal.pone.0236857 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Recent outbreaks of coronavirus disease 2019 (COVID-19) has led a global pandemic cross the world. Most countries took two main interventions: suppression like immediate lockdown cities at epicenter or mitigation that slows down but not stopping epidemic for reducing peak healthcare demand. Both strategies have their apparent merits and limitations; it becomes extremely hard to conduct one intervention as the most feasible way to all countries. Targeting at this problem, this paper conducted a feasibility study by defining a mathematical model named SEMCR, it extended traditional SEIR (Susceptible-Exposed-Infectious-Recovered) model by adding two key features: a direct connection between Exposed and Recovered populations, and separating infections into mild and critical cases. It defined parameters to classify two stages of COVID-19 control: active contain by isolation of cases and contacts, passive contain by suppression or mitigation. The model was fitted and evaluated with public dataset containing daily number of confirmed active cases including Wuhan and London during January 2020 and March 2020. The simulated results showed that 1) Immediate suppression taken in Wuhan significantly reduced the total exposed and infectious populations, but it has to be consistently maintained at least 90 days (by the middle of April 2020). Without taking this intervention, we predict the number of infections would have been 73 folders higher by the middle of April 2020. Its success requires efficient government initiatives and effective collaborative governance for mobilizing of corporate resources to provide essential goods. This mode may be not suitable to other countries without efficient collaborative governance and sufficient health resources. 2) In London, it is possible to take a hybrid intervention of suppression and mitigation for every 2 or 3 weeks over a longer period to balance the total infections and economic loss. While the total infectious populations in this scenario would be possibly 2 times than the one taking suppression, economic loss and recovery of London would be less affected. 3) Both in Wuhan and London cases, one important issue of fitting practical data was that there were a portion (probably 62.9% in Wuhan) of self-recovered populations that were asymptomatic or mild symptomatic. This finding has been recently confirmed by other studies that the seroprevalence in Wuhan varied between 3.2% and 3.8% in different sub-regions. It highlights that the epidemic is far from coming to an end by means of herd immunity. Early release of intervention intensity potentially increased a risk of the second outbreak.
1000 Sacherschließung
lokal Epidemiology
gnd 1206347392 COVID-19
lokal Health economics
lokal Infectious disease surveilance
lokal Population density
lokal Human mobility
lokal Cities
lokal Death rates
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-8553-7127|https://frl.publisso.de/adhoc/uri/UWksIEp1bg==|https://frl.publisso.de/adhoc/uri/WmhhbmcsIFNodWhhbw==|https://frl.publisso.de/adhoc/uri/V2FuZywgWHVsb25n|https://frl.publisso.de/adhoc/uri/QmksIEdhb3NoYW4=|https://frl.publisso.de/adhoc/uri/WWFuZywgWXVu|https://frl.publisso.de/adhoc/uri/U2hlbmcsIEJpbg==|https://frl.publisso.de/adhoc/uri/WWFuZywgR2VuZw==
1000 Label
1000 Förderer
  1. University of Sheffield |
  2. State Key Laboratory of Fluid Power and Mechatronic Systems |
  3. National Natural Science Foundation of China |
1000 Fördernummer
  1. -
  2. GZKF-201802
  3. 61876166; 61663046
1000 Förderprogramm
  1. WorldWide Universities Network
  2. -
  3. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer University of Sheffield |
    1000 Förderprogramm WorldWide Universities Network
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer State Key Laboratory of Fluid Power and Mechatronic Systems |
    1000 Förderprogramm -
    1000 Fördernummer GZKF-201802
  3. 1000 joinedFunding-child
    1000 Förderer National Natural Science Foundation of China |
    1000 Förderprogramm -
    1000 Fördernummer 61876166; 61663046
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6422407.rdf
1000 Erstellt am 2020-08-10T07:51:45.431+0200
1000 Erstellt von 122
1000 beschreibt frl:6422407
1000 Bearbeitet von 122
1000 Zuletzt bearbeitet 2020-08-10T07:54:03.383+0200
1000 Objekt bearb. Mon Aug 10 07:53:42 CEST 2020
1000 Vgl. frl:6422407
1000 Oai Id
  1. oai:frl.publisso.de:frl:6422407 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

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