Epidemiological dynamics of SARS-CoV-2 VOC Gamma in Rio de Janeiro, Brazil
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Abstract
The emergence and widespread circulation of severe acute respiratory syndrome coronavirus 2 variants of concern (VOCs) or interest impose an enhanced threat to global public health. In Brazil, one of the countries most severely impacted throughout the pandemic, a complex dynamics involving variants co-circulation and turnover events has been recorded with the emergence and spread of VOC Gamma in Manaus in late 2020. In this context, we present a genomic epidemiology investigation based on samples collected between December 2020 and May 2021 in the second major Brazilian metropolis, Rio de Janeiro. By sequencing 244 novel genomes through all epidemiological weeks in this period, we were able to document the introduction and rapid dissemination of VOC Gamma in the city, driving the rise of the third local epidemic wave. Molecular clock analysis indicates that this variant has circulated locally since the first weeks of 2021 and only 7 weeks were necessary for it to achieve a frequency above 70 per cent, consistent with rates of growth observed in Manaus and other states. Moreover, a Bayesian phylogeographic reconstruction indicates that VOC Gamma spread throughout Brazil between December 2020 and January 2021 and that it was introduced in Rio de Janeiro through at least 13 events coming from nearly all regions of the country. Comparative analysis of reverse transcription-quantitative polymerase chain reaction (RT-qPCR) cycle threshold (Ct) values provides further evidence that VOC Gamma induces higher viral loads (N1 target; mean reduction of Ct: 2.7, 95 per cent confidence interval = ± 0.7). This analysis corroborates the previously proposed mechanistic basis for this variant-enhanced transmissibility and distinguished epidemiological behavior. Our results document the evolution of VOC Gamma and provide independent assessment of scenarios previously studied in Manaus, therefore contributing to the better understanding of the epidemiological dynamics currently being surveyed in other Brazilian regions.
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SciScore for 10.1101/2021.07.01.21259404: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Reads from each sample were mapped against the SARS-CoV-2 reference genome (NCBI accession: NC_045512.2) with Bowtie2 v2.4.2 (Langmead and Salzberg, 2012), and mapping files were indexed and sorted with SAMtools v1.12 (Li et al., 2009). Bowtie2suggested: (Bowtie 2, RRID:SCR_016368)SAMtoolssuggested: (SAMTOOLS, RRID:SCR_002105)BCFtools v1.12 was used for variant calling and consensus genome inference, while BEDtools v2.30.0 (Quinlan and Hall, 2010) was used to mask low coverage sites (< 100-fold) BEDtoolssuggested: (BEDTools, RRID:SCR_006646)These sequences were all aligned to the genome … SciScore for 10.1101/2021.07.01.21259404: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Reads from each sample were mapped against the SARS-CoV-2 reference genome (NCBI accession: NC_045512.2) with Bowtie2 v2.4.2 (Langmead and Salzberg, 2012), and mapping files were indexed and sorted with SAMtools v1.12 (Li et al., 2009). Bowtie2suggested: (Bowtie 2, RRID:SCR_016368)SAMtoolssuggested: (SAMTOOLS, RRID:SCR_002105)BCFtools v1.12 was used for variant calling and consensus genome inference, while BEDtools v2.30.0 (Quinlan and Hall, 2010) was used to mask low coverage sites (< 100-fold) BEDtoolssuggested: (BEDTools, RRID:SCR_006646)These sequences were all aligned to the genome sequences herein described with MAFFT v7.475 (Katoh and Standley, 2013) and a maximum likelihood tree was inferred with IQ-tree v2.0.3 (Minh et al., 2020) under the GTR+F+I+G4 model (Tavaré, 1986; Yang, 1994). 2.5 Phylodynamics: To further access the temporal dynamics of introduction of VOC Gamma in Rio de Janeiro city, we performed molecular clock analyses on a fully Bayesian framework using BEAST v1.10.4 (Suchard et al., 2018). MAFFTsuggested: (MAFFT, RRID:SCR_011811)IQ-treesuggested: (IQ-TREE, RRID:SCR_017254)BEASTsuggested: (BEAST, RRID:SCR_010228)Eight independent chains of 50 million generations sampling every 10,000 states were performed and convergence (effective sample size > 200 for all parameters) was verified on Tracer v1.7.1 (Rambaut et al., 2018) after 10% burnin removal. Tracersuggested: (Tracer, RRID:SCR_019121)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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