Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103901
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dc.contributorSchool of Nursing-
dc.creatorHe, Yen_US
dc.creatorChen, Yen_US
dc.creatorYang, Len_US
dc.creatorZhou, Yen_US
dc.creatorYe, Ren_US
dc.creatorWang, Xen_US
dc.date.accessioned2024-01-10T02:41:19Z-
dc.date.available2024-01-10T02:41:19Z-
dc.identifier.urihttp://hdl.handle.net/10397/103901-
dc.language.isoenen_US
dc.publisherPublic Library of Scienceen_US
dc.rights© 2022 He et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.rightsThe following publication He, Y., Chen, Y., Yang, L., Zhou, Y., Ye, R., & Wang, X. (2022). The impact of multi-level interventions on the second-wave SARS-CoV-2 transmission in China. Plos one, 17(9), e0274590 is available at https://doi.org/10.1371/journal.pone.0274590.en_US
dc.titleThe impact of multi-level interventions on the second-wave SARS-CoV-2 transmission in Chinaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume17en_US
dc.identifier.issue9en_US
dc.identifier.doi10.1371/journal.pone.0274590en_US
dcterms.abstractBackground A re-emergence of COVID-19 occurred in the northeast of China in early 2021. Different levels of non-pharmaceutical interventions, from mass testing to city-level lockdown, were implemented to contain the transmission of SARS-CoV-2. Our study is aimed to evaluate the impact of multi-level control measures on the second-wave SARS-CoV-2 transmission in the most affected cities in China.-
dcterms.abstractMethods Five cities with over 100 reported COVID-19 cases within one month from Dec 2020 to Feb 2021 were included in our analysis. We fitted the exponential growth model to estimate basic reproduction number (R-0), and used a Bayesian approach to assess the dynamics of the time-varying reproduction number (R-t). We fitted linear regression lines on R-t estimates for comparing the decline rates of R-t across cities, and the slopes were tested by analysis of covariance. The effect of non-pharmaceutical interventions (NPIs) was quantified by relative R-t reduction and statistically compared by analysis of variance.-
dcterms.abstractResults A total of 2,609 COVID-19 cases were analyzed in this study. We estimated that R-0 all exceeded 1, with the highest value of 3.63 (1.36, 8.53) in Haerbin and the lowest value of 2.45 (1.44, 3.98) in Shijiazhuang. Downward trends of R-t were found in all cities, and the starting time of R-t < 1 was around the 12th day of the first local COVID-19 cases. Statistical tests on regression slopes of R-t and effect of NPIs both showed no significant difference across five cities (P = 0.126 and 0.157).-
dcterms.abstractConclusion Timely implemented NPIs could control the transmission of SARS-CoV-2 with low-intensity measures for places where population immunity has not been established.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationPLoS one, 2022, v. 17, no. 9, e0274590en_US
dcterms.isPartOfPLoS oneen_US
dcterms.issued2022-
dc.identifier.isiWOS:000933375500042-
dc.identifier.scopus2-s2.0-85138450660-
dc.identifier.pmid36112630-
dc.identifier.eissn1932-6203en_US
dc.identifier.artne0274590en_US
dc.description.validate202401 bcvc-
dc.description.oaVersion of Recorden_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Nature and Science Foundation of China; Three-year Public Health System Construction program of Shanghai,China; National Nature and Science Foundation Committee; Shanghai Municipal Health Commissionen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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