The first wave of the COVID-19 epidemic in Spain was associated with early introductions and fast spread of a dominating genetic variant.

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 reproductive number of both SECs due to public-health interventions (Re < 1), also reflected in the replacement of SECs by a new variant over the summer of 2020. In summary, we reveal a notable difference in the initial genetic makeup of SARS-CoV-2 in Spain compared with other European countries and show evidence to support the effectiveness of lockdown measures in controlling virus spread, even for the most successful genetic variants.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 Ramón 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 Bioinformática y Estadística, Centro de Investigación Príncipe Felipe, for allowing us to use the Computer Cluster to perform some of the bioinformatic analysis.S