Transmission dynamics of the COVID-19 outbreak and effectiveness of government interventions: A data-driven analysis.
Identifieur interne : 000780 ( PubMed/Curation ); précédent : 000779; suivant : 000781Transmission dynamics of the COVID-19 outbreak and effectiveness of government interventions: A data-driven analysis.
Auteurs : Yaqing Fang [République populaire de Chine] ; Yiting Nie [République populaire de Chine] ; Marshare Penny [États-Unis]Source :
- Journal of medical virology [ 1096-9071 ] ; 2020.
Abstract
Using the parameterized susceptible-exposed-infectious-recovered model, we simulated the spread dynamics of coronavirus disease 2019 (COVID-19) outbreak and impact of different control measures, conducted the sensitivity analysis to identify the key factor, plotted the trend curve of effective reproductive number (R), and performed data fitting after the simulation. By simulation and data fitting, the model showed the peak existing confirmed cases of 59 769 arriving on 15 February 2020, with the coefficient of determination close to 1 and the fitting bias 3.02%, suggesting high precision of the data-fitting results. More rigorous government control policies were associated with a slower increase in the infected population. Isolation and protective procedures would be less effective as more cases accrue, so the optimization of the treatment plan and the development of specific drugs would be of more importance. There was an upward trend of R in the beginning, followed by a downward trend, a temporary rebound, and another continuous decline. The feature of high infectiousness for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) led to an upward trend, and government measures contributed to the temporary rebound and declines. The declines of R could be exploited as strong evidence for the effectiveness of the interventions. Evidence from the four-phase stringent measures showed that it was significant to ensure early detection, early isolation, early treatment, adequate medical supplies, patients' being admitted to designated hospitals, and comprehensive therapeutic strategy. Collaborative efforts are required to combat the novel coronavirus, focusing on both persistent strict domestic interventions and vigilance against exogenous imported cases.
DOI: 10.1002/jmv.25750
PubMed: 32141624
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By simulation and data fitting, the model showed the peak existing confirmed cases of 59 769 arriving on 15 February 2020, with the coefficient of determination close to 1 and the fitting bias 3.02%, suggesting high precision of the data-fitting results. More rigorous government control policies were associated with a slower increase in the infected population. Isolation and protective procedures would be less effective as more cases accrue, so the optimization of the treatment plan and the development of specific drugs would be of more importance. There was an upward trend of R in the beginning, followed by a downward trend, a temporary rebound, and another continuous decline. The feature of high infectiousness for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) led to an upward trend, and government measures contributed to the temporary rebound and declines. The declines of R could be exploited as strong evidence for the effectiveness of the interventions. Evidence from the four-phase stringent measures showed that it was significant to ensure early detection, early isolation, early treatment, adequate medical supplies, patients' being admitted to designated hospitals, and comprehensive therapeutic strategy. Collaborative efforts are required to combat the novel coronavirus, focusing on both persistent strict domestic interventions and vigilance against exogenous imported cases.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32141624</PMID><DateRevised><Year>2020</Year><Month>03</Month><Day>24</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1096-9071</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Mar</Month><Day>06</Day></PubDate></JournalIssue><Title>Journal of medical virology</Title><ISOAbbreviation>J. Med. Virol.</ISOAbbreviation></Journal><ArticleTitle>Transmission dynamics of the COVID-19 outbreak and effectiveness of government interventions: A data-driven analysis.</ArticleTitle><ELocationID EIdType="doi" ValidYN="Y">10.1002/jmv.25750</ELocationID><Abstract><AbstractText>Using the parameterized susceptible-exposed-infectious-recovered model, we simulated the spread dynamics of coronavirus disease 2019 (COVID-19) outbreak and impact of different control measures, conducted the sensitivity analysis to identify the key factor, plotted the trend curve of effective reproductive number (R), and performed data fitting after the simulation. By simulation and data fitting, the model showed the peak existing confirmed cases of 59 769 arriving on 15 February 2020, with the coefficient of determination close to 1 and the fitting bias 3.02%, suggesting high precision of the data-fitting results. More rigorous government control policies were associated with a slower increase in the infected population. Isolation and protective procedures would be less effective as more cases accrue, so the optimization of the treatment plan and the development of specific drugs would be of more importance. There was an upward trend of R in the beginning, followed by a downward trend, a temporary rebound, and another continuous decline. The feature of high infectiousness for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) led to an upward trend, and government measures contributed to the temporary rebound and declines. The declines of R could be exploited as strong evidence for the effectiveness of the interventions. Evidence from the four-phase stringent measures showed that it was significant to ensure early detection, early isolation, early treatment, adequate medical supplies, patients' being admitted to designated hospitals, and comprehensive therapeutic strategy. Collaborative efforts are required to combat the novel coronavirus, focusing on both persistent strict domestic interventions and vigilance against exogenous imported cases.</AbstractText><CopyrightInformation>© 2020 Wiley Periodicals, Inc.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Fang</LastName><ForeName>Yaqing</ForeName><Initials>Y</Initials><Identifier Source="ORCID">http://orcid.org/0000-0002-9963-4462</Identifier><AffiliationInfo><Affiliation>School of Public Health, Hangzhou Medical College, Hangzhou, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Nie</LastName><ForeName>Yiting</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Graduate School, Harbin Medical University, Harbin, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Penny</LastName><ForeName>Marshare</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Public Health Sciences, California Baptist University, Riverside, California.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>03</Month><Day>06</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>J Med Virol</MedlineTA><NlmUniqueID>7705876</NlmUniqueID><ISSNLinking>0146-6615</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID-19</Keyword><Keyword MajorTopicYN="N">SARS-CoV-2</Keyword><Keyword MajorTopicYN="N">SEIR</Keyword><Keyword MajorTopicYN="N">basic reproductive number</Keyword><Keyword MajorTopicYN="N">data fitting</Keyword><Keyword MajorTopicYN="N">data simulation</Keyword><Keyword MajorTopicYN="N">effective reproductive number</Keyword><Keyword MajorTopicYN="N">effectiveness</Keyword><Keyword MajorTopicYN="N">intervention</Keyword><Keyword MajorTopicYN="N">sensitivity analysis</Keyword><Keyword MajorTopicYN="N">transmission</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>02</Month><Day>25</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>03</Month><Day>04</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>3</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>3</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>3</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32141624</ArticleId><ArticleId IdType="doi">10.1002/jmv.25750</ArticleId></ArticleIdList><ReferenceList><Title>REFERENCES</Title><Reference><Citation>Li Q The 2019-nCoV Outbreak Joint Field Epidemiology Investigation Team. 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