| Literature DB >> 33747543 |
Lily Geidelberg1, Olivia Boyd1, David Jorgensen1, Igor Siveroni1, Fabrícia F Nascimento1, Robert Johnson1, Manon Ragonnet-Cronin1, Han Fu1, Haowei Wang1, Xiaoyue Xi2, Wei Chen3, Dehui Liu3, Yingying Chen3, Mengmeng Tian3, Wei Tan4, Junjie Zai5, Wanying Sun6, Jiandong Li6, Junhua Li6, Erik M Volz1, Xingguang Li7, Qing Nie3.
Abstract
Analysis 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 (R 0) of 3.4 (95% highest posterior density interval: 2.1-5.2) in Weifang, and a mean effective reproduction number (Rt) 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.Entities:
Keywords: SARS-CoV-2; genetic epidemiology; modelling; phylodynamics; phylogenetics; structured coalescent
Year: 2021 PMID: 33747543 PMCID: PMC7955981 DOI: 10.1093/ve/veaa102
Source DB: PubMed Journal: Virus Evol ISSN: 2057-1577