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10.1093/ve/veaa102 http://scihub22266oqcxt.onion/10.1093/ve/veaa102 33747543!7955981!33747543     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Virus+Evol 2021 ; 7 (1): veaa102 Nephropedia Template TP {{tp|p=33747543|t=2021. Genomic epidemiology of a densely sampled COVID-19 outbreak in China |pdf=|usr=}}{{33747543}} gab.com Text Genomic epidemiology of a densely sampled COVID-19 outbreak in China JO: Virus Evol http://www.kidney.de/pget.php?&tw=1&pmid=33747543 #FOAvip 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 (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. Twit Text FOAVip Genomic epidemiology of a densely sampled COVID-19 outbreak in China ????Virus Evol http://www.kidney.de/pget.php?&tw=1&pmid=33747543 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33747543 #FOAvip English Wikipedia <ref>{{Cite pmid|33747543}}</ref> Genomic epidemiology of a densely sampled COVID-19 outbreak in China #MMPMID33747543 Geidelberg L; Boyd O; Jorgensen D; Siveroni I; Nascimento FF; Johnson R; Ragonnet-Cronin M; Fu H; Wang H; Xi X; Chen W; Liu D; Chen Y; Tian M; Tan W; Zai J; Sun W; Li J; Li J; Volz EM; Li X; Nie Q Virus Evol 2021[Jan]; 7 (1): veaa102 PMID33747543show ga 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 (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. äGenomic epidemiology of a densely sampled COVID-19 outbreak in China (epmc).pdf DeepDyve Pubget Overpricing