Journal article
The first wave of the COVID-19 epidemic in Spain was associated with early introductions and fast spread of a dominating genetic variant
MG López, Á Chiner-Oms, D García de Viedma, P Ruiz-Rodriguez, MA Bracho, I Cancino-Muñoz, G D’Auria, G de Marco, N García-González, GA Goig, I Gómez-Navarro, S Jiménez-Serrano, L Martinez-Priego, P Ruiz-Hueso, L Ruiz-Roldán, M Torres-Puente, J Alberola, E Albert, M Aranzamendi Zaldumbide, MP Bea-Escudero Show all
Nature Genetics | NATURE PORTFOLIO | Published : 2021
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has affected the world radically since 2020. Spain was one of the European countries with the highest incidence during the first wave. As a part of a consortium to monitor and study the evolution of the epidemic, we sequenced 2,170 samples, diagnosed mostly before lockdown measures. Here, we identified at least 500 introductions from multiple international sources and documented the early rise of two dominant Spanish epidemic clades (SECs), probably amplified by superspreading events. Both SECs were related closely to the initial Asian variants of SARS-CoV-2 and spread widely across Spain. We inferred a substantial reduction in the effective r..
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Awarded by Generalitat Valenciana
Funding Acknowledgements
This work was mainly funded by the Instituto de Salud Carlos III project COV20/00140, with additional funding by Spanish National Research Council project CSIC-COV19-021, Ministerio de Ciencia project PID2019-104477RB-100, ERC StG 638553 and ERC CoG 101001038 to I.C., and BFU2017-89594R to F.G.C. M.C. is supported by Ramon y Cajal program from Ministerio de Ciencia and grants RTI2018-094399-A-I00 and Generalitat Valenciana (Regional Government) project SEJI/2019/011. We gratefully acknowledge Hospital Universitari Vall d'Hebron, Instituto de Salud Carlos III, IrsiCaixa AIDS Research Lab and all the international researchers and institutions that submitted sequenced SARS-CoV-2 genomes to the GISAID's EpiCov Database (Supplementary Table 1), as an important part of our analyses has been made possible by the sharing of their work. We also thank Unidad de Bioinformatica y Estadistica, Centro de Investigacion Principe Felipe, for allowing us to use the Computer Cluster to perform some of the bioinformatic analysis.