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dc.contributorDepartment of Applied Mathematics-
dc.contributorDepartment of Civil and Environmental Engineering-
dc.contributorResearch Institute for Future Food-
dc.creatorZhao, Yen_US
dc.creatorZhao, Sen_US
dc.creatorGuo, Zen_US
dc.creatorYuan, Zen_US
dc.creatorRan, Jen_US
dc.creatorWu, Len_US
dc.creatorYu, Len_US
dc.creatorLi, Hen_US
dc.creatorShi, Yen_US
dc.creatorHe, Den_US
dc.date.accessioned2023-07-18T03:11:32Z-
dc.date.available2023-07-18T03:11:32Z-
dc.identifier.urihttp://hdl.handle.net/10397/99602-
dc.language.isoenen_US
dc.publisherBioMed Central Ltden_US
dc.rights© The Author(s) 2022.en_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.en_US
dc.rightsThe following publication Zhao, Y., Zhao, S., Guo, Z. et al. Differences in the superspreading potentials of COVID-19 across contact settings. BMC Infect Dis 22, 936 (2022) is available at https://doi.org/10.1186/s12879-022-07928-9.en_US
dc.subjectCOVID-19en_US
dc.subjectContact settingsen_US
dc.subjectSuperspreadingen_US
dc.subjectTransmission heterogeneityen_US
dc.titleDifferences in the superspreading potentials of COVID-19 across contact settingsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume22en_US
dc.identifier.issue1en_US
dc.identifier.doi10.1186/s12879-022-07928-9en_US
dcterms.abstractBackground: Superspreading events (SSEs) played a critical role in fueling the COVID-19 outbreaks. Although it is well-known that COVID-19 epidemics exhibited substantial superspreading potential, little is known about the risk of observing SSEs in different contact settings. In this study, we aimed to assess the potential of superspreading in different contact settings in Japan.-
dcterms.abstractMethod: Transmission cluster data from Japan was collected between January and July 2020. Infector-infectee transmission pairs were constructed based on the contact tracing history. We fitted the data to negative binomial models to estimate the effective reproduction number (R) and dispersion parameter (k). Other epidemiological issues relating to the superspreading potential were also calculated.-
dcterms.abstractResults: The overall estimated R and k are 0.561 (95% CrI: 0.496, 0.640) and 0.221 (95% CrI: 0.186, 0.262), respectively. The transmission in community, healthcare facilities and school manifest relatively higher superspreading potentials, compared to other contact settings. We inferred that 13.14% (95% CrI: 11.55%, 14.87%) of the most infectious cases generated 80% of the total transmission events. The probabilities of observing superspreading events for entire population and community, household, health care facilities, school, workplace contact settings are 1.75% (95% CrI: 1.57%, 1.99%), 0.49% (95% CrI: 0.22%, 1.18%), 0.07% (95% CrI: 0.06%, 0.08%), 0.67% (95% CrI: 0.31%, 1.21%), 0.33% (95% CrI: 0.13%, 0.94%), 0.32% (95% CrI: 0.21%, 0.60%), respectively.-
dcterms.abstractConclusion: The different potentials of superspreading in contact settings highlighted the need to continuously monitoring the transmissibility accompanied with the dispersion parameter, to timely identify high risk settings favoring the occurrence of SSEs.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationBMC infectious diseases, 2022, v. 22, no. 1, 936en_US
dcterms.isPartOfBMC infectious diseasesen_US
dcterms.issued2022-
dc.identifier.scopus2-s2.0-85143994082-
dc.identifier.pmid36510138-
dc.identifier.eissn1471-2334en_US
dc.identifier.artn936en_US
dc.description.validate202307 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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