Show simple item record

dc.contributor.authorGeidelberg, Lily
dc.contributor.authorBoyd, Olivia
dc.contributor.authorJorgensen, David
dc.contributor.authorSiveroni, Igor
dc.contributor.authorNascimento, Fabrícia F
dc.contributor.authorJohnson, Robert
dc.contributor.authorRagonnet-Cronin, Manon
dc.contributor.authorFu, Han
dc.contributor.authorWang, Haowei
dc.contributor.authorXi, Xiaoyue
dc.contributor.authorChen, Wei
dc.contributor.authorLiu, Dehui
dc.contributor.authorChen, Yingying
dc.contributor.authorTian, Mengmeng
dc.contributor.authorTan, Wei
dc.contributor.authorZai, Junjie
dc.contributor.authorSun, Wanying
dc.contributor.authorLi, Jiandong
dc.contributor.authorLi, Junhua
dc.contributor.authorVolz, Erik M
dc.contributor.authorLi, Xingguang
dc.contributor.authorNie, Qing
dc.date.accessioned2021-09-08T06:37:26Z
dc.date.available2021-09-08T06:37:26Z
dc.date.issued2021-03-14
dc.identifier.citationGeidelberg, L., Boyd, O., Jorgensen, D., Siveroni, I., Nascimento, F. F., Johnson, R., … Nie, Q. (2021). Genomic epidemiology of a densely sampled COVID-19 outbreak in China. Virus Evolution, 7(1). doi:10.1093/ve/veaa102
dc.identifier.issn2057-1577
dc.identifier.pmid33747543
dc.identifier.doi10.1093/ve/veaa102
dc.identifier.urihttp://hdl.handle.net/10754/671113
dc.description.abstractAnalysis of genetic sequence data from the SARS-CoV-2 pandemic can provide insights into epidemic origins, worldwide dispersal, and epidemiological history. With few exceptions, genomic epidemiological analysis has focused on geographically distributed data sets with few isolates in any given location. Here, we report an analysis of 20 whole SARS- CoV-2 genomes from a single relatively small and geographically constrained outbreak in Weifang, People's Republic of China. Using Bayesian model-based phylodynamic methods, we estimate a mean basic reproduction number ($\textit{R}$ $_{0}$) of 3.4 (95% highest posterior density interval: 2.1-5.2) in Weifang, and a mean effective reproduction number ($\textit{R$_{t)}$}$ that falls below 1 on 4 February. We further estimate the number of infections through time and compare these estimates to confirmed diagnoses by the Weifang Centers for Disease Control. We find that these estimates are consistent with reported cases and there is unlikely to be a large undiagnosed burden of infection over the period we studied.
dc.description.sponsorshipWe gratefully acknowledge China National GeneBank at Shenzhen, China for the sequencing strategy and capacity support. We also gratefully acknowledge the laboratories that have contributed publicly available genomes via GISAID: The Public Health Agency of Sweden, Sweden; Public Health Ontario Laboratories, Canada; Pathogen Discovery, Respiratory Viruses Branch, Division of Viral Diseases, Centers for Disease Control and Prevention, United States; Programme in Emerging Infectious Diseases, Duke-NUS Medical School, United State; Alaska State Virology Laboratory, United States; Respiratory Virus Unit, Microbiology Services Colindale, Public Health England, United Kingdom; Laboratory for Functional Genome Analysis, Dept. Genomics, Gene Center of the LMU Munich, Germany; Michigan Department of Health and Human Services, Bureau of Laboratories, United State; National Public Health Laboratory, National Centre for Infectious Diseases, Singapore; BGI-shenzhen & The First Affiliated Hospital of Guangzhou Medical University, China; NSW Health Pathology - Institute of Clinical Pathology and Medical Research; Westmead Hospital; University of Sydney, Australia; BCCDC Public Health Laboratory, Canada; COVID-19 Genomics UK (COG-UK) Consortium, United Kingdom; Guangdong Provincial Institution of Public Health, China; Department of Microbiology, Guangdong Provincial Center for Diseases Control and Prevention, China; Department of Health Technology and Informatics, Faculty of Health and Social Science, The Hong Kong Polytechnic University, Hong Kong; School of Public Health, The University of Hong Kong, Hong Kong; Pathogen Genomics Center, National Institute of Infectious Diseases, Japan; National Research Center for Translational Medicine (Shanghai), Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine & Shanghai Public Health Clinical Center, China; Seattle Flu Study, United States; UW Virology Lab, United States; National Institute for Viral Disease Control & Prevention, CCDC, China; Beijing Institute of Microbiology and Epidemiology, China; National Institute for Viral Disease Control and Prevention, China CDC, China; Inspection Center of Hangzhou Center for Disease Control and Prevention, China; Pathogen Genomics Lab King Abdullah University of Science and Technology (KAUST), Saudi Arabia; Chinese PLA Institute for Disease Control and Prevention, China; National Institute of Health. Department of medical Sciences, Ministry of Public Health, Thailand; Laboratory of Biology, Department of Medicine, Democritus University of Thrace, Greece; Wellcome Sanger Institute for the COVID-19 Genomics UK Consortium, United Kingdom; State Key Laboratory of Biotherapy of Sichuan University, China; SeqCOVID-SPAIN consortium/IBV(CSIC), Spain; Oxford University Clinical Research Unit, Hanoi, Vietnam; Institute of Environmental Science and Research (ESR), New Zealand; Erasmus Medical Center, Netherlands.
dc.publisherOxford University Press (OUP)
dc.relation.urlhttps://academic.oup.com/ve/article/doi/10.1093/ve/veaa102/6170691
dc.rightsThis is a pre-copyedited, author-produced PDF of an article accepted for publication in Virus evolution following peer review. The version of record is available online at: https://academic.oup.com/ve/article/doi/10.1093/ve/veaa102/6170691.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectGenetic epidemiology
dc.subjectphylogenetics
dc.subjectModelling
dc.subjectPhylodynamics
dc.subjectStructured Coalescent
dc.subjectSars-cov-2
dc.titleGenomic epidemiology of a densely sampled COVID-19 outbreak in China.
dc.typeArticle
dc.identifier.journalVirus evolution
dc.identifier.pmcidPMC7955981
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionDepartment of Infectious Disease Epidemiology and MRC Centre for Global Infectious Disease Analysis, Imperial College London, Norfolk Place W2 1PG, UK
dc.contributor.institutionDepartment of Mathematics, Imperial College London, London SW7 2AZ, UK
dc.contributor.institutionDepartment of Microbiology, Weifang Center for Disease Control and Prevention, Weifang 261061, China
dc.contributor.institutionDepartment of Respiratory Medicine, Weifang People’s Hospital, Weifang 261061, China
dc.contributor.institutionImmunology Innovation Team, School of Medicine, Ningbo University, Ningbo 315211, China
dc.contributor.institutionShenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen 518083, China
dc.contributor.institutionDepartment of Hospital Office, The First People’s Hospital of Fangchenggang, Fangchenggang, 538021, China
dc.identifier.volume7
dc.identifier.issue1
dc.identifier.eid2-s2.0-85104240691
dc.date.published-online2021-03-14
dc.date.published-print2021-01-20


This item appears in the following Collection(s)

Show simple item record

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Virus evolution following peer review. The version of record is available online at: https://academic.oup.com/ve/article/doi/10.1093/ve/veaa102/6170691.
Except where otherwise noted, this item's license is described as This is a pre-copyedited, author-produced PDF of an article accepted for publication in Virus evolution following peer review. The version of record is available online at: https://academic.oup.com/ve/article/doi/10.1093/ve/veaa102/6170691.