Genomic epidemiology reveals the impact of national and international restrictions measures on the SARS-CoV-2 epidemic in Brazil

Abstract

Brazil has experienced some of the highest numbers of COVID-19 cases and deaths globally and from May 2021 made Latin America a pandemic epicenter. Although SARS-CoV-2 established sustained transmission in Brazil early in the pandemic, important gaps remain in our understanding of virus transmission dynamics at the national scale. Here, we describe the genomic epidemiology of SARS-CoV-2 using near-full genomes sampled from 27 Brazilian states and a bordering country - Paraguay. We show that the early stage of the pandemic in Brazil was characterised by the co-circulation of multiple viral lineages, linked to multiple importations predominantly from Europe, and subsequently characterized by large local transmission clusters. As the epidemic progressed under an absence of effective restriction measures, there was a local emergence and onward international spread of Variants of Concern (VOC) and Variants Under Monitoring (VUM), including Gamma (P.1) and Zeta (P.2). In addition, we provide a preliminary genomic overview of the epidemic in Paraguay, showing evidence of importation from Brazil. These data reinforce the usefulness and need for the implementation of widespread genomic surveillance in South America as a toolkit for pandemic monitoring that provides a means to follow the real-time spread of emerging SARS-CoV-2 variants with possible implications for public health and immunization strategies.

Fig. 1.. Key events following the first confirmed infection of SARS-CoV-2 in Brazil.

(A) Timeline of SARS-CoV-2 key events in Brazil. The Brazilian map was colored according to geographical macro region: North (red), Northeast (green), Southeast (purple), Midwest (light blue) South (light orange). (B) Epidemic curve showing the progression of reported daily viral infection numbers in Brazil from the beginning of the epidemic (grey) and deaths (red) in the same period, with restriction phases indicated along the bottom. (C) Map of cumulative SARS-CoV-2 cases per 100,000 inhabitants in Brazil up to June 2021.

Fig. 2.. Phylogenetic analysis and SARS-CoV-2 lineage dynamics in Brazil.

(A) Map of Brazil with the number of sequences in GISAID as of 30th June 2021. (B) Temporal sampling of sequences in Brazilian states through time with VOCs highlighted and annotated according to their PANGO lineage assignment. (C) Time resolved maximum likelihood phylogeny containing high qualitynear-full-genome sequences from Brazil (n=3866) obtained from this study, analysed against a backdrop of global reference sequences (n=25,288). Variants under monitoring (VUM) and concern (VOC) are highlighted on the phylogeny. (D) Sources of viral introductions into Brazil characterized as external introductions from the rest of the world. (E) Sources of viral exchanges (imports and exports) in and outside Brazil. (F) Number of viral exchanges within Brazilian regions by counting the state changes from the root to the tips of the phylogeny in panel C.

Fig. 3.. Spatiotemporal spread of VOC and VUM in Brazil.

(A) Phylogeographic reconstruction of the spread of the Gamma VOC in Brazil. 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. Differences in population density are shown on a dark-white scale; B) Phylogeographic reconstruction of the spread of the Zeta VUM across Brazil. 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. Differences in population density are shown on a dark-white scale; In both Panels (A) and (B) solid curved lines denote the links between nodes and the directionality of movement is anti-clockwise along the curve (as shown in the “dispersal direction” sublegends). (C) Number of exchanges of the Gamma variant between Brazilian regions (N=North; NE=Northeast; MD=Midwest; SE=Southeast; S=South); (D) Number of exchanges of the Zeta variant between Brazilian regions; (E) Sources of viral export of the VOC and VUM from Brazil to the rest of the world.

Fig. 4.. The SARS-CoV-2 epidemic in Paraguay.

(A) Epidemic curve showing the progression of reported viral infection numbers in Paraguay from the beginning of the epidemic (grey) and deaths (red) in the same period; (B) Progressive distribution of the top 20 PANGO lineages in Paraguay over time; (C) Time resolved maximum likelihood tree containing (n=63) high quality near-complete genome sequences from Paraguay obtained in this study analysed against a backdrop of global reference sequences. VUM and VOCs are highlighted on the phylogeny. Small circles indicate genome sequences from Brazil. Bigger circles indicate sequences from Paraguay. New genomic sequences from Paraguay obtained in this study are highlighted with a red border.