The ongoing COVID-19 epidemic in Minas Gerais, Brazil: insights from epidemiological data and SARS-CoV-2 whole genome sequencing
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Abstract
The recent emergence of a previously unknown coronavirus (SARS-CoV-2), first confirmed in the city of Wuhan in China in December 2019, has caused serious public health and economic issues due to its rapid dissemination worldwide. Although 61,888 confirmed cases had been reported in Brazil by 28 April 2020, little was known about the SARS-CoV-2 epidemic in the country. To better understand the recent epidemic in the second most populous state in southeast Brazil (Minas Gerais, MG), we looked at existing epidemiological data from 3 states and sequenced 40 complete genomes from MG cases using Nanopore. We found evidence of multiple independent introductions from outside MG, both from genome analyses and the overly dispersed distribution of reported cases and deaths. Epidemiological estimates of the reproductive number using different data sources and theoretical assumptions all suggest a reduction in transmission potential since the first reported case, but potential for sustained transmission in the near future. The estimated date of introduction in Brazil was consistent with epidemiological data from the first case of a returning-traveler from Lombardy, Italy. These findings highlight the unique reality of MG’s epidemic and reinforce the need for real-time and continued genomic surveillance strategies as a way of understanding and therefore preparing against the epidemic spread of emerging viral pathogens.
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SciScore for 10.1101/2020.05.05.20091611: (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 Sequences were aligned using MAFFT (FF-NS-2 algorithm) following default parameters [38]. MAFFTsuggested: (MAFFT, RRID:SCR_011811)The alignment was manually curated to remove artifacts at the ends and within the alignment using Aliview [39]. Aliviewsuggested: (AliView, RRID:SCR_002780)Phylogenetic analysis of these genome sequences was performed using IQ-TREE (version 1.6.10) under the best fit model according to Bayesian Information Criterion (BIC) indicated by the Model Finder application implemented in IQ-TREE [40]. IQ-TREEsuggested: (IQ-TREE, RRID:SCR_017254)ML trees from these three … SciScore for 10.1101/2020.05.05.20091611: (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 Sequences were aligned using MAFFT (FF-NS-2 algorithm) following default parameters [38]. MAFFTsuggested: (MAFFT, RRID:SCR_011811)The alignment was manually curated to remove artifacts at the ends and within the alignment using Aliview [39]. Aliviewsuggested: (AliView, RRID:SCR_002780)Phylogenetic analysis of these genome sequences was performed using IQ-TREE (version 1.6.10) under the best fit model according to Bayesian Information Criterion (BIC) indicated by the Model Finder application implemented in IQ-TREE [40]. IQ-TREEsuggested: (IQ-TREE, RRID:SCR_017254)ML trees from these three sub-datasets were inspected in TempEst v1.5.3 for presence of temporal signal [41]. TempEstsuggested: (TempEst, RRID:SCR_017304)For Bayesian time-scaled phylogenetic analysis we used BEAST 1.10.4 [42]. BEASTsuggested: (BEAST, RRID:SCR_010228)Results from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:As observed in another study [32], due to the described limitations of the available genomic data, the phylogenetic results presented should be approached with caution and considered as hypothesis-generating on the transmission events of SARS-CoV-2 in a local setting. In conclusion, at the end of April 2020, the COVID-19 epidemic in the state of MG was still expanding (R>1) and it is highly dispersed with cases and deaths reported mostly away from the capital city and with approximately only 64% and 35% of the total population being represented in case and death reported data, respectively. Genomic data and other epidemiological information from travel-related cases, allowed us to identify several introduction events that occurred independently in MG, further helping to explain the geographical patchiness of reported cases and deaths. These initial insights based on the restricted data that is available show that transmission is likely to continue in the near future and suggest room to improve reporting. Increasing COVID-19 testing and SARS-CoV-2 genomic sequencing would help to better understand on how the virus is spreading and would thus inform better control of the COVID-19 epidemic in Brazil.
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.
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