Importation and early local transmission of COVID-19 in Brazil, 2020

We conducted the genome sequencing and analysis of the first confirmed COVID-19 infections in Brazil. Rapid sequencing coupled with phylogenetic analyses in the context of travel history corroborate multiple independent importations from Italy and local spread during the initial stage of COVID-19 transmission in Brazil.

Public health surveillance; COVID-19; SARS-CoV-2

Authorship

Jaqueline Goes de Jesus

Universidade de São Paulo, Instituto de Medicina Tropical de São Paulo, São Paulo, São Paulo, BrazilUniversidade de São PauloBrazilSão Paulo, São Paulo, BrazilUniversidade de São Paulo, Instituto de Medicina Tropical de São Paulo, São Paulo, São Paulo, Brazil

* This authors contributed equally

http://orcid.org/0000-0002-5404-272X

Claudio Sacchi

Instituto Adolfo Lutz, Laboratório Estratégico, São Paulo, São Paulo, BrazilInstituto Adolfo LutzBrazilSão Paulo, São Paulo, BrazilInstituto Adolfo Lutz, Laboratório Estratégico, São Paulo, São Paulo, Brazil

* This authors contributed equally

Darlan da Silva Candido

University of Oxford, Department of Zoology, Oxford, United KingdomUniversity of OxfordUnited KingdomOxford, United KingdomUniversity of Oxford, Department of Zoology, Oxford, United Kingdom

* This authors contributed equally

http://orcid.org/0000-0002-5080-3130

Ingra Morales Claro

http://orcid.org/0000-0001-8637-2910

Flávia Cristina Silva Sales

http://orcid.org/0000-0002-9048-0030

Erika Regina Manuli

http://orcid.org/0000-0003-2376-8488

Daniela Bernardes Borges da Silva

Instituto Adolfo Lutz, Centro de Virologia, São Paulo, São Paulo, BrazilInstituto Adolfo LutzBrazilSão Paulo, São Paulo, BrazilInstituto Adolfo Lutz, Centro de Virologia, São Paulo, São Paulo, Brazil

Terezinha Maria de Paiva

Margarete Aparecida Benega Pinho

Katia Correa de Oliveira Santos

Sarah Catherine Hill

University of Oxford, Department of Zoology, Oxford, United KingdomUniversity of OxfordUnited KingdomOxford, United KingdomUniversity of Oxford, Department of Zoology, Oxford, United Kingdom

http://orcid.org/0000-0002-2995-2596

Renato Santana Aguiar

Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, BrazilUniversidade Federal do Rio de JaneiroBrazilRio de Janeiro, Rio de Janeiro,, BrazilUniversidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil

Filipe Romero

Fabiana Cristina Pereira dos Santos

Claudia Regina Gonçalves

Maria do Carmo Timenetsky

http://orcid.org/0000-0001-8317-0539

Joshua Quick

University of Birmingham, Birmingham, United KingdomUniversity of BirminghamUnited KingdomBirmingham, United KingdomUniversity of Birmingham, Birmingham, United Kingdom

http://orcid.org/0000-0001-6376-871X

Julio Henrique Rosa Croda

Ministério da Saúde, Secretaria de Vigilância em Saúde, Coordenação Geral de Laboratórios de Saúde Pública, Brasília, DF, BrazilMinistério da SaúdeBrazilBrasília, DF, BrazilMinistério da Saúde, Secretaria de Vigilância em Saúde, Coordenação Geral de Laboratórios de Saúde Pública, Brasília, DF, Brazil

Universidade Federal da Grande Dourados, Laboratório de Pesquisa em Ciências da Saúde, Dourados, Mato Grosso do Sul, BrazilUniversidade Federal da Grande DouradosBrazilDourados, Mato Grosso do Sul, BrazilUniversidade Federal da Grande Dourados, Laboratório de Pesquisa em Ciências da Saúde, Dourados, Mato Grosso do Sul, Brazil

Fundação Osvaldo Cruz Campo Grande, Mato Grosso do Sul, BrazilFundação Osvaldo Cruz Campo GrandeBrazilMato Grosso do Sul, BrazilFundação Osvaldo Cruz Campo Grande, Mato Grosso do Sul, Brazil

Wanderson de Oliveira

Andrew Rambaut

University of Edinburgh, Institute of Evolutionary Biology, Edinburgh, United KingdomUniversity of EdinburghUnited KingdomEdinburgh, United KingdomUniversity of Edinburgh, Institute of Evolutionary Biology, Edinburgh, United Kingdom

http://orcid.org/0000-0003-4337-3707

Oliver G. Pybus

University of Oxford, Department of Zoology, Oxford, United KingdomUniversity of OxfordUnited KingdomOxford, United KingdomUniversity of Oxford, Department of Zoology, Oxford, United Kingdom

http://orcid.org/0000-0002-8797-2667

Nicholas J. Loman

University of Birmingham, Birmingham, United KingdomUniversity of BirminghamUnited KingdomBirmingham, United KingdomUniversity of Birmingham, Birmingham, United Kingdom

http://orcid.org/0000-0002-9843-8988

Ester Cerdeira Sabino

* This authors contributed equally

http://orcid.org/0000-0003-2623-5126

Nuno Rodrigues Faria

University of Oxford, Department of Zoology, Oxford, United KingdomUniversity of OxfordUnited KingdomOxford, United KingdomUniversity of Oxford, Department of Zoology, Oxford, United Kingdom

Imperial College, School of Public Health, Department of Infectious Disease Epidemiology, London, United KingdomImperial CollegeUnited KingdomLondon, United KingdomImperial College, School of Public Health, Department of Infectious Disease Epidemiology, London, United Kingdom

* This authors contributed equally

http://orcid.org/0000-0002-9747-8822

Correspondence to: Nuno Rodrigues Faria University of Oxford, Department of Zoology, South Parks Rd, Oxford OX1 3SY, United Kingdom E-mail: nuno.faria@zoo.ox.ac.uk

*
This authors contributed equally

AUTHORS’ CONTRIBUTIONS

Conceptualization, Jaqueline de Jesus, Ester Sabino and Nuno Rodrigues Faria; data curation, Darlan da Silva Candido, Oliver G. Pybus and Nuno Rodrigues Faria; formal analysis, Darlan da Silva Candido, Sarah Catherine Hill, Filipe Romero, Andrew Rambaut, Nicholas James Loman and Nuno Rodrigues Faria; funding acquisition, Andrew Rambaut, Nicholas James Loman, Ester Cerdeira Sabino, Nuno Rodrigues Faria; investigation, Jaqueline de Jesus, Claudio Sacchi, Ingra Morales Claro, Flávia Cristina Silva Sales, Erika Regina Manuli, Daniela Bernardes Borges da Silva, Terezinha Maria de Paiva, Margarete Aparecida Benega, Katia Correa de Oliveira Santos, Renato Santana Aguiar, Fabiana Cristina Pereira Santos and Claudia Regina Gonçalves; methodology, Jaqueline de Jesus, Claudio Sacchi, Ingra Morales Claro, Fabiana Cristina Pereira dos Santos, Joshua Quick and Nicholas James Loman; project administration, Andrew Rambaut, Oliver G. Pybus, Nicholas James Loman, Ester Sabino and Nuno Rodrigues Faria; resources, Julio Henrique Rosa Croda and Wanderson de Oliveira, Oliver G Pybus, Andrew Rambaut, Ester Sabino and Nuno Rodrigues Faria; software, Filipe Romero, Andrew Rambaut, Nicholas J Loman; supervision, Maria do Carmo Timenetsky, Oliver G. Pybus, Ester Sabino and Nuno Rodrigues Faria; validation, Joshua Quick, Andrew Rambaut; writing – original draft, Jaqueline de Jesus, Darlan da Silva Candido and Nuno Rodrigues Faria; writing – review & editing, Andrew Rambaut, Oliver G. Pybus, Nicholas James Loman and Ester Sabino.

SCIMAGO INSTITUTIONS RANKINGS

University of Oxford, Department of Zoology, Oxford, United KingdomUniversity of OxfordUnited KingdomOxford, United KingdomUniversity of Oxford, Department of Zoology, Oxford, United Kingdom

University of Birmingham, Birmingham, United KingdomUniversity of BirminghamUnited KingdomBirmingham, United KingdomUniversity of Birmingham, Birmingham, United Kingdom

Fundação Osvaldo Cruz Campo Grande, Mato Grosso do Sul, BrazilFundação Osvaldo Cruz Campo GrandeBrazilMato Grosso do Sul, BrazilFundação Osvaldo Cruz Campo Grande, Mato Grosso do Sul, Brazil

Figures | Tables

Figures (2)
Tables (1)

Thumbnail

Figure 1
Maximum likelihood phylogeny (n=88) including Brazilian SARS-CoV-2 genomes from the first confirmed cases in Brazil. Squares and circles are coloured according to the place of infection and the place of reporting, respectively. Local cases are highlighted with a grey background, imported cases are highlighted with a black background. A full tree (n=347) can be found in the ^{Supplementary Material (Figure S1)} SUPPLEMENTARY MATERIAL Table S1 Sequencing statistics for the Brazilian SARS-COV-2 genomes from this study. Isolate Mapped Reads Average depth coverage Bases covered >10x Bases covered >25x Reference covered (%) SPBR1 552730 3622.14 29426 29106 96.8966 SPBR2 3461754 5117.28 29849 29845 99.5954 We gratefully acknowledge the authors, originating and submitting laboratories of the sequences from GISAID’s EpiFlu™ Database on which this research is based. The list is detailed on Supplementary Table 2, which is available on GitHub (https://github.com/CADDE-CENTRE/REPOSITORY/blob/master/First%20genomes%20from%20Americas.docx). All submitters of data may be contacted directly via www.gisaid.org. Figure S1 SARS-CoV-2 phylogeny of the first confirmed Brazilian cases. A) Global SARS-CoV-2 Maximum Likelihood phylogeny including the six first genomes from Brazil. The tree was estimated using all available sequences in GISAID database (n=347) as of the 10th of March 2020. Tips are coloured according to the location of collection. B) Expansion of the clades containing the six Brazilian SARS-CoV-2 genomes (n=88). Tips are coloured according to the location of collection and only approximate likelihood ratio node supports > 0.80 are shown. Tips were labelled according to sequence name, GISAID accession number, place and date of collection. .

Thumbnail

Figure S1
SARS-CoV-2 phylogeny of the first confirmed Brazilian cases. A) Global SARS-CoV-2 Maximum Likelihood phylogeny including the six first genomes from Brazil. The tree was estimated using all available sequences in GISAID database (n=347) as of the 10th of March 2020. Tips are coloured according to the location of collection. B) Expansion of the clades containing the six Brazilian SARS-CoV-2 genomes (n=88). Tips are coloured according to the location of collection and only approximate likelihood ratio node supports > 0.80 are shown. Tips were labelled according to sequence name, GISAID accession number, place and date of collection.

Thumbnail

Table S1
Sequencing statistics for the Brazilian SARS-COV-2 genomes from this study.

Figure 1 Maximum likelihood phylogeny (n=88) including Brazilian SARS-CoV-2 genomes from the first confirmed cases in Brazil. Squares and circles are coloured according to the place of infection and the place of reporting, respectively. Local cases are highlighted with a grey background, imported cases are highlighted with a black background. A full tree (n=347) can be found in the ^{Supplementary Material (Figure S1)} SUPPLEMENTARY MATERIAL Table S1 Sequencing statistics for the Brazilian SARS-COV-2 genomes from this study. Isolate Mapped Reads Average depth coverage Bases covered >10x Bases covered >25x Reference covered (%) SPBR1 552730 3622.14 29426 29106 96.8966 SPBR2 3461754 5117.28 29849 29845 99.5954 We gratefully acknowledge the authors, originating and submitting laboratories of the sequences from GISAID’s EpiFlu™ Database on which this research is based. The list is detailed on Supplementary Table 2, which is available on GitHub (https://github.com/CADDE-CENTRE/REPOSITORY/blob/master/First%20genomes%20from%20Americas.docx). All submitters of data may be contacted directly via www.gisaid.org. Figure S1 SARS-CoV-2 phylogeny of the first confirmed Brazilian cases. A) Global SARS-CoV-2 Maximum Likelihood phylogeny including the six first genomes from Brazil. The tree was estimated using all available sequences in GISAID database (n=347) as of the 10th of March 2020. Tips are coloured according to the location of collection. B) Expansion of the clades containing the six Brazilian SARS-CoV-2 genomes (n=88). Tips are coloured according to the location of collection and only approximate likelihood ratio node supports > 0.80 are shown. Tips were labelled according to sequence name, GISAID accession number, place and date of collection. .

Figure S1 SARS-CoV-2 phylogeny of the first confirmed Brazilian cases. A) Global SARS-CoV-2 Maximum Likelihood phylogeny including the six first genomes from Brazil. The tree was estimated using all available sequences in GISAID database (n=347) as of the 10th of March 2020. Tips are coloured according to the location of collection. B) Expansion of the clades containing the six Brazilian SARS-CoV-2 genomes (n=88). Tips are coloured according to the location of collection and only approximate likelihood ratio node supports > 0.80 are shown. Tips were labelled according to sequence name, GISAID accession number, place and date of collection.

Table S1 Sequencing statistics for the Brazilian SARS-COV-2 genomes from this study.

Isolate	Mapped Reads	Average depth coverage	Bases covered >10x	Bases covered >25x	Reference covered (%)
SPBR1	552730	3622.14	29426	29106	96.8966
SPBR2	3461754	5117.28	29849	29845	99.5954

We gratefully acknowledge the authors, originating and submitting laboratories of the sequences from GISAID’s EpiFlu^™ Database on which this research is based. The list is detailed on Supplementary Table 2, which is available on GitHub (https://github.com/CADDE-CENTRE/REPOSITORY/blob/master/First%20genomes%20from%20Americas.docx). All submitters of data may be contacted directly via www.gisaid.org.

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E-mail: revimtsp@usp.br

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Importation and early local transmission of COVID-19 in Brazil, 2020

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[1] Correspondence to: Nuno Rodrigues Faria University of Oxford, Department of Zoology, South Parks Rd, Oxford OX1 3SY, United Kingdom E-mail: nuno.faria@zoo.ox.ac.uk