Travel-related Importation and Exportation Risks of SARS-CoV-2 Omicron Variant in 367 Prefectures (Cities) — China, 2022
| dc.contributor | Aalto-yliopisto | fi |
| dc.contributor | Aalto University | en |
| dc.contributor.author | Bai, Yuan | en_US |
| dc.contributor.author | Xu, Mingda | en_US |
| dc.contributor.author | Liu, Caifen | en_US |
| dc.contributor.author | Shen, Mingwang | en_US |
| dc.contributor.author | Wang, Lin | en_US |
| dc.contributor.author | Tian, Linwei | en_US |
| dc.contributor.author | Tan, Suoyi | en_US |
| dc.contributor.author | Zhang, Lei | en_US |
| dc.contributor.author | Holme, Petter | en_US |
| dc.contributor.author | Lu, Xin | en_US |
| dc.contributor.author | Lau, Eric H.Y. | en_US |
| dc.contributor.author | Cowling, Benjamin J. | en_US |
| dc.contributor.author | Du, Zhanwei | en_US |
| dc.contributor.department | Department of Computer Science | en |
| dc.contributor.groupauthor | Professorship Holme Petter | en |
| dc.contributor.groupauthor | Computer Science Professors | en |
| dc.contributor.groupauthor | Computer Science - Complex Systems (Cxsys) - Research area | en |
| dc.contributor.organization | University of Hong Kong | en_US |
| dc.contributor.organization | Laboratory of Data Discovery for Health | en_US |
| dc.contributor.organization | Xi'an Jiaotong University | en_US |
| dc.contributor.organization | University of Cambridge | en_US |
| dc.contributor.organization | National University of Defense Technology | en_US |
| dc.date.accessioned | 2022-12-22T09:43:31Z | |
| dc.date.available | 2022-12-22T09:43:31Z | |
| dc.date.issued | 2022-10-07 | en_US |
| dc.description | Funding Information: Funding: Supported by AIR@InnoHK programme from The Innovation and Technology Commission of the Hong Kong Special Administrative Region, National Natural Science Foundation of China (72104208), JSPS KAKENHI (JP21H04595), National Nature Science Foundation of China (72025405, 91846301, 72088101, and 71790615). Publisher Copyright: © 2022, Chinese Center for Disease Control and Prevention. All rights reserved. | |
| dc.description.abstract | Introduction: Minimizing the importation and exportation risks of coronavirus disease 2019 (COVID-19) is a primary concern for sustaining the “Dynamic COVID-zero” strategy in China. Risk estimation is essential for cities to conduct before relaxing border control measures. Methods: Informed by the daily number of passengers traveling between 367 prefectures (cities) in China, this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks. Results: Under the transmission scenario (R0=5.49), this study estimated the cumulative case incidence of Changchun City, Jilin Province as 3,233 (95% confidence interval: 1,480, 4,986) before a lockdown on March 14, 2022, which is close to the 3,168 cases reported in real life by March 16, 2022. In a total of 367 prefectures (cities), 127 (35%) had high exportation risks according to the simulation and could transmit the disease to 50% of all other regions within a period from 17 to 94 days. The average time until a new infection arrives in a location in 1 of the 367 prefectures (cities) ranged from 26 to 101 days. Conclusions: Estimating COVID-19 importation and exportation risks is necessary for preparedness, prevention, and control measures of COVID-19 — especially when new variants emerge. | en |
| dc.description.version | Peer reviewed | en |
| dc.format.extent | 5 | |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.citation | Bai, Y, Xu, M, Liu, C, Shen, M, Wang, L, Tian, L, Tan, S, Zhang, L, Holme, P, Lu, X, Lau, E H Y, Cowling, B J & Du, Z 2022, 'Travel-related Importation and Exportation Risks of SARS-CoV-2 Omicron Variant in 367 Prefectures (Cities) — China, 2022', China CDC Weekly, vol. 4, no. 40, pp. 885-889. https://doi.org/10.46234/ccdcw2022.184 | en |
| dc.identifier.doi | 10.46234/ccdcw2022.184 | en_US |
| dc.identifier.issn | 2096-7071 | |
| dc.identifier.other | PURE UUID: 3ce06985-1896-49a8-b1a1-76466955e225 | en_US |
| dc.identifier.other | PURE ITEMURL: https://research.aalto.fi/en/publications/3ce06985-1896-49a8-b1a1-76466955e225 | en_US |
| dc.identifier.other | PURE FILEURL: https://research.aalto.fi/files/94946169/Travel_related_Importation_and_Exportation_Risks_of_SARS_CoV_2_Omicron_Variant_in_367_Prefectures.pdf | |
| dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/118485 | |
| dc.identifier.urn | URN:NBN:fi:aalto-202212227223 | |
| dc.language.iso | en | en |
| dc.publisher | Chinese Center for Disease Control and Prevention | |
| dc.relation.fundinginfo | Funding: Supported by AIR@InnoHK programme from The Innovation and Technology Commission of the Hong Kong Special Administrative Region, National Natural Science Foundation of China (72104208), JSPS KAKENHI (JP21H04595), National Nature Science Foundation of China (72025405, 91846301, 72088101, and 71790615). | |
| dc.relation.ispartofseries | China CDC Weekly | en |
| dc.relation.ispartofseries | Volume 4, issue 40, pp. 885-889 | en |
| dc.rights | openAccess | en |
| dc.title | Travel-related Importation and Exportation Risks of SARS-CoV-2 Omicron Variant in 367 Prefectures (Cities) — China, 2022 | en |
| dc.type | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä | fi |
| dc.type.version | publishedVersion |