Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess.
Identifieur interne : 000344 ( PubMed/Curation ); précédent : 000343; suivant : 000345Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess.
Auteurs : Hiroshi Nishiura [Japon]Source :
- Journal of clinical medicine [ 2077-0383 ] ; 2020.
Abstract
To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.
DOI: 10.3390/jcm9030657
PubMed: 32121356
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The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">32121356</PMID><DateRevised><Year>2020</Year><Month>03</Month><Day>03</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Print">2077-0383</ISSN><JournalIssue CitedMedium="Print"><Volume>9</Volume><Issue>3</Issue><PubDate><Year>2020</Year><Month>Feb</Month><Day>29</Day></PubDate></JournalIssue><Title>Journal of clinical medicine</Title><ISOAbbreviation>J Clin Med</ISOAbbreviation></Journal><ArticleTitle>Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">E657</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.3390/jcm9030657</ELocationID><Abstract><AbstractText>To understand the time-dependent risk of infection on a cruise ship, the Diamond Princess, I estimated the incidence of infection with novel coronavirus (COVID-19). The epidemic curve of a total of 199 confirmed cases was drawn, classifying individuals into passengers with and without close contact and crew members. A backcalculation method was employed to estimate the incidence of infection. The peak time of infection was seen for the time period from 2 to 4 February 2020, and the incidence has abruptly declined afterwards. The estimated number of new infections among passengers without close contact was very small from 5 February on which a movement restriction policy was imposed. Without the intervention from 5 February, it was predicted that the cumulative incidence with and without close contact would have been as large as 1373 (95% CI: 570, 2176) and 766 (95% CI: 587, 946) cases, respectively, while these were kept to be 102 and 47 cases, respectively. Based on an analysis of illness onset data on board, the risk of infection among passengers without close contact was considered to be very limited. Movement restriction greatly reduced the number of infections from 5 February onwards.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Nishiura</LastName><ForeName>Hiroshi</ForeName><Initials>H</Initials><AffiliationInfo><Affiliation>Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012, Japan.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>JPMJCR1413</GrantID><Agency>Core Research for Evolutional Science and Technology</Agency><Country></Country></Grant><Grant><GrantID>JP18fk0108050</GrantID><Agency>Japan Agency for Medical Research and Development</Agency><Country></Country></Grant><Grant><GrantID>17H04701, 17H05808, 18H04895 and 19H01074</GrantID><Agency>Japan Society for the Promotion of Science</Agency><Country></Country></Grant><Grant><GrantID>NA</GrantID><Agency>Inamori Foundation</Agency><Country></Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016421">Editorial</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>02</Month><Day>29</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>J Clin Med</MedlineTA><NlmUniqueID>101606588</NlmUniqueID><ISSNLinking>2077-0383</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">emerging infectious diseases</Keyword><Keyword MajorTopicYN="N">forecasting</Keyword><Keyword MajorTopicYN="N">incidence</Keyword><Keyword MajorTopicYN="N">statistical estimation</Keyword><Keyword MajorTopicYN="N">virus</Keyword></KeywordList><CoiStatement>The author declares no conflict of interest.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>02</Month><Day>25</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>02</Month><Day>25</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>3</Month><Day>4</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>3</Month><Day>4</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>3</Month><Day>4</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32121356</ArticleId><ArticleId IdType="pii">jcm9030657</ArticleId><ArticleId IdType="doi">10.3390/jcm9030657</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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