Abstract
During the global COVID-19 pandemic, different SARS-CoV-2 variants of concern (VOCs) emerged, causing massive transmission waves that affected infection outcomes, economies and public health. From January to July 2021 in Uruguay, the transmission wave was primarily driven by the Gamma VOC amidst a largely immunologically naive population. Following the implementation of a nationwide vaccination campaign, the detection of the Delta VOC in July 2021 did not trigger a significant transmission wave, even in the face of increased mobility during the winter holidays (late June to mid-July). We present a comprehensive analysis of the dynamics of SARS-CoV-2 in Uruguay until September 2021. By analysing 1792 viral genomes, we integrate genomic data with vaccination records, variant surveillance and epidemiological information at both regional and global scales. Our study highlights the role of timely vaccination combined with real-time genomic surveillance programmes in effectively monitoring and mitigating critical phases of the COVID-19 epidemic.
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Data availability
SARS-CoV-2 genomic consensus sequences generated in this study can be found in the EpiCoV/GISAID database, available at: https://gisaid.org. The accession numbers and metadata available can be found in Table S3. Additionally, the South America build for the background dataset used for the phylodynamic analysis was retrieved from EpiCoV/GISAID on December 31, 2021. Phylogenetic data generated in this study were deposited in Mendeley Data (https://data.mendeley.com/preview/2y4xjcm84s?a=ba557727-f20b-4bac-a08e-a49b60ae3b0a). Epidemiological and statistical data from the COVID-19 pandemic and population mobility in Uruguay (Grupo Uruguayo Interdisciplinario de Análisis de Datos de COVID-19) are available at: https://guiad-covid.github.io/. Vaccination data (Catálogo de datos abiertos, Ministerio de Salud Pública) is available at: https://catalogodatos.gub.uy/dataset/vacunacion-por-covid-19. Global statistics are available at: https://ourworldindata.org/. All data analysis was performed using the following open source software: PoreCov pipeline is available through the Nextflow system at: https://github.com/replikation/poreCov. Pangolin is available through Bioconda at: https://github.com/cov-lineages/pangolin; Nextclade CLI is available through Docker hub at: https://hub.docker.com/r/nextstrain/nextclade. Custom R scripts for tables and data visualization are available in the project GitHub repository at: https://github.com/Ceci07/SARS-CoV-2_URU.
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Acknowledgements
Authors would like to acknowledge the invaluable efforts of all the members of the Interinstitutional Working Group (IiWG) and the institutions involved in the COVID-19 testing and sample/data collection in Uruguay during the pandemic. Authors would also like to acknowledge the Grupo Uruguayo Interdisciplinario de Análisis de Datos de COVID-19 (https://guiad-covid.github.io/) for collecting and openly sharing COVID-19 epidemiological data of Uruguay. We also acknowledge all the authors and institutions around the world that shared SARS-CoV-2 genomic sequences through the EpiCoV/GISAID database. A detailed description of the authors of sequences used in this study is available in EPI_SET_240229hw (https://doi.org/10.55876/gis8.240229hw).
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The opinions expressed in this article are those of the authors and do not reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government.
Funding
FOCEM COF 03/11, G4 program, Institut Pasteur de Montevideo funded by the BSE of Uruguay, Fondo de Solidaridad para Proyectos Innovadores, Sociedad Civil, Francofonía y Desarrollo Humano, Ambassade de France, Centro Latinoamericano de Biotecnología, Agencia Nacional de Investigación e Innovación, International Programme, British Embassy Montevideo, Uruguay and Fundación Manuel Perez, Facultad de Medicina, Universidad de la República.
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CS: conceptualization, data generation, analysis, manuscript drafting, editing, and review. NST: conceptualization, analysis, manuscript editing, and review. IF: analysis, manuscript drafting and review. AC, MP, PP: data generation and manuscript review. AM, VB, RC, BR, MA, MM: data generation. NR, TFC, LS: funding, conceptualization, manuscript editing and review. GI: funding, conceptualization, analysis, manuscript drafting. GM: funding, conceptualization, work lab coordination and supervision, manuscript drafting, editing and review. PM: funding, conceptualization, work lab coordination and supervision, manuscript drafting, editing and review.
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Salazar, C., Trovão, N.S., Ferrés, I. et al. Impact of timely vaccination and genomic surveillance on controlling consecutive waves of SARS-CoV-2 variants. Sci Rep (2026). https://doi.org/10.1038/s41598-026-48131-z
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DOI: https://doi.org/10.1038/s41598-026-48131-z
