Data from: Evolution and epidemic spread of SARS-CoV-2 in Brazil
Candido, Darlan S. et al. (2020), Data from: Evolution and epidemic spread of SARS-CoV-2 in Brazil, Dryad, Dataset, https://doi.org/10.5061/dryad.rxwdbrv5z
Brazil currently has one of the fastest growing SARS-CoV-2 epidemics in the world. Owing to limited available data, assessments of the impact of non-pharmaceutical interventions (NPIs) on virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1–1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil. We estimate that most (76%) of the Brazilian strains fell in three clades that were introduced from Europe between 22 February11 March 2020. During the early epidemic phase, we found that SARS-CoV-2 spread mostly locally and within-state borders. After this period, despite sharp decreases in air travel, we estimated multiple exportations from large urban centers that coincided with a 25% increase in average travelled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil, and provide evidence that current interventions remain insufficient to keep virus transmission under control in the country.
Please see Materials and Methods section in Supplementary Materials.
This REPOSITORY contains the data used for the main figures of the manuscript.
Data for main figures:
Fig1a: Cumulative number of Covid-19 confirmed cases and deaths until the 30th of April 2020, as provided by the Brazilian ministry of Health at https://covid.saude.gov.br/;
Fig1b: number of Covid-19 confirmed cases and deaths until the 30th of April 2020, as provided by the Brazilian ministry of Health at https://covid.saude.gov.br/;
Fig1c: reproduction number (Rt) estimates and confidence intervals for São Paulo city.
Fig1d: reproduction number (Rt) estimates and confidence intervals for Rio de Janeiro city.
Fig2a: Dates of first confirmed Covid-19 case and death for each Brazilian state. Dates and states of collection of all 427 sequences generated in this study.
Fig2b: Number of SARI Covid-19 confirmed cases and number of novel genomes generated in this study per Brazilian state.
Fig3c: Number of samples per lag time (in days) between symptom onset and collection date.
Fig3a: Maximum Clade Credibility (MCC) tree of 1,182 SARS-CoV-2 genomes, including 427 novel genomes for Brazil. For details, see supplementary data.
Fig3c: Number of national and international air passengers in Brazil per flight and per day from January to 30th April 2020.
Fig4a: Continuous phylogeography
Fig4b: Discrete phylogeography
Fig4c: Average distance of air travel in Brazil
Medical Research Council, Award: MR/S0195/1
Wellcome Trust, Award: 204311/Z/16/Z
Fundação de Amparo à Pesquisa do Estado de São Paulo, Award: FAPESP 18/14389-0
Fundação de Amparo à Pesquisa do Estado de São Paulo, Award: MR/S0195/1