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Evolution and epidemic spread of SARS-CoV-2 in Brazil

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Science  04 Sep 2020:
Vol. 369, Issue 6508, pp. 1255-1260
DOI: 10.1126/science.abd2161
  • Fig. 1 SARS-CoV-2 epidemiology and epidemic spread in Brazil.

    (A) Cumulative number of SARS-CoV-2 reported cases (blue) and deaths (gray) in Brazil. (B) States are colored according to the number of cumulative confirmed cases by 30 April 2020. (C and D) R over time for the cities of São Paulo (C) and Rio de Janeiro (D). R values were estimated using a Bayesian approach incorporating the daily number of deaths and four variables related to mobility data (a social isolation index from Brazilian geolocation company InLoco and Google mobility indices for time spent in transit stations, parks, and the average between groceries and pharmacies, retail and recreational, and workspaces). Dashed horizontal line indicates R = 1. Gray area and geometric symbols show the times at which NPIs were implemented. BCIs of 50 and 95% are shown as shaded areas. The two-letter ISO 3166-1 codes for the 27 federal units in Brazil are provided in the supplementary materials.

  • Fig. 2 Spatially representative genomic sampling.

    (A) Dumbbell plot showing the time intervals between date of collection of sampled genomes, notification of first cases, and first deaths in each state. Red lines indicate the lag between the date of collection of first genome sequence and first reported case. The key for the two-letter ISO 3166-1 codes for Brazilian federal units (or states) are provided in the supplementary materials. (B) Spearman’s rank correlation between the number of SARI SARS-CoV-2 confirmed and SARI cases with unknown etiology against the number of sequences for each of the 21 Brazilian states included in this study (see also fig. S4). Circle sizes are proportional to the number of sequences for each federal unit. (C) Interval between the date of symptom onset and the date of sample collection for the sequences generated in this study.

  • Fig. 3 Evolution and spread of SARS-CoV-2 in Brazil.

    (A) Time-resolved maximum clade credibility phylogeny of 1182 SARS-CoV-2 sequences, 490 of which are from Brazil (salmon) and 692 from outside of Brazil (blue). The largest Brazilian clades are highlighted by gray boxes (Clade 1, Clade 2, and Clade 3). Inset shows a root-to-tip regression of genetic divergence against dates of sample collection. Red tip corresponds to the first reported case in Brazil. (B) Dynamics of SARS-CoV-2 import events in Brazil. Dates of international and national (between federal states) migration events were estimated from virus genomes using a phylogeographic approach. The first phase was dominated by virus migrations from outside of Brazil, whereas the second phase was marked by virus spread within Brazil. Dashed vertical lines correspond to the mean posterior estimate for migration events from outside of Brazil (blue) and within Brazil (red). (C) Locally estimated scatterplot smoothing of the daily number of international (blue) and national (red) air passengers in Brazil in 2020. T0, date of first reported case in Brazil (25 February 2020).

  • Fig. 4 Spread of SARS-CoV-2 in Brazil.

    (A) Spatiotemporal reconstruction of the spread of Brazilian SARS-CoV-2 clusters containing more than two sequences during the first (left) and the second (right) epidemic phase (Fig. 3B). Circles represent nodes of the maximum clade credibility phylogeny and are colored according to their inferred time of occurrence. Shaded areas represent the 80% highest posterior density interval and depict the uncertainty of the phylogeographic estimates for each node. Solid curved lines denote the links between nodes and the directionality of movement. Sequences belonging to clusters with fewer than three sequences were also plotted on the map with no lines connecting them. Background population density for each municipality was obtained from the Brazilian Institute of Geography (https://www.ibge.gov.br/). See fig. S14 for details of virus spread in the southeast region. (B) Estimated number of within-state (or within a given federal unit) and between-state (or between federal units) virus migrations over time. Dashed lines indicate estimates obtained during the period of limited sampling (fig. S2). (C) Average distance in kilometers traveled by an air passenger per day in Brazil. The number of daily air passengers is shown in Fig. 3B. Light gray boxes indicate the starting dates of NPIs across Brazil.

Supplementary Materials

  • Evolution and epidemic spread of SARS-CoV-2 in Brazil

    Darlan S. Candido, Ingra M. Claro, Jaqueline G. de Jesus, William M. Souza, Filipe R. R. Moreira, Simon Dellicour, Thomas A. Mellan, Louis du Plessis, Rafael H. M. Pereira, Flavia C. S. Sales, Erika R. Manuli, Julien Thézé, Luiz Almeida, Mariane T. Menezes, Carolina M. Voloch, Marcilio J. Fumagalli, Thaís M. Coletti, Camila A. M. da Silva, Mariana S. Ramundo, Mariene R. Amorim, Henrique H. Hoeltgebaum, Swapnil Mishra, Mandev S. Gill, Luiz M. Carvalho, Lewis F. Buss, Carlos A. Prete Jr, Jordan Ashworth, Helder I. Nakaya, Pedro S. Peixoto, Oliver J. Brady, Samuel M. Nicholls, Amilcar Tanuri, Átila D. Rossi, Carlos K.V. Braga, Alexandra L. Gerber, Ana Paula de C. Guimarães, Nelson Gaburo Jr, Cecila Salete Alencar, Alessandro C. S. Ferreira, Cristiano X. Lima, José Eduardo Levi, Celso Granato, Giulia M. Ferreira, Ronaldo S. Francisco Jr, Fabiana Granja, Marcia T. Garcia, Maria Luiza Moretti, Mauricio W. Perroud Jr, Terezinha M. P. P. Castiñeiras, Carolina S. Lazari, Sarah C. Hill, Andreza Aruska de Souza Santos, Camila L. Simeoni, Julia Forato, Andrei C. Sposito, Angelica Z. Schreiber, Magnun N. N. Santos, Camila Zolini de Sá, Renan P. Souza, Luciana C. Resende-Moreira, Mauro M. Teixeira, Josy Hubner, Patricia A. F. Leme, Rennan G Moreira, Maurício L. Nogueira, Brazil-UK Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology (CADDE) Genomic Network, Neil M. Ferguson, Silvia F. Costa, José Luiz Proenca-Modena, Ana Tereza R. Vasconcelos, Samir Bhatt, Philippe Lemey, Chieh-Hsi Wu, Andrew Rambaut, Nick J. Loman, Renato S. Aguiar, Oliver G. Pybus, Ester C. Sabino, Nuno Rodrigues Faria

    Materials/Methods, Supplementary Text, Tables, Figures, and/or References

    Download Supplement
    • Materials and Methods
    • Figs. S1 to S7
    • Caption for Fig. S8
    • Figs. S9 to S15
    • Tables S1 to S3
    • Captions for Data S1 and Data S2
    • List of Members of the CADDE Genomic Network
    • References
    Fig. S8
    Detailed annotated maximum clade phylogenetic tree. Time-resolved maximum clade credibility phylogeny of 1,182 SARS-CoV-2 sequences, 490 from Brazil (red) and 692 from outside Brazil (blue). The largest Brazilian clusters are highlighted in grey (Clade 1, Clade 2 and Clade 3). States are defined by their 2-letter ISO 3166-1 codes. The MCC tree can be found at our Dryad repository (see Data Availability).
    Data S1
    Detailed metadata on all 1,182 sequences used in this study. File contains information on epidemiology, demography, location, diagnostics, sequencing statistics and evolution of 427 SARS-CoV-2 sequences generated in this study and 755 sequences downloaded from GISAID.
    Data S2
    Acknowledgment GISAID table. File contains Accession ID, collection date, originating and submitting lab and authors, from https://www.gisaid.org.
    MDAR Reproducibility Checklist

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