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Background Since its first identification in the United Kingdom in late 2020, the highly transmissible B.1.1.7 variant of SARS-CoV-2, become dominant in several European countries raising great concern. Aim The aim of this study was to develop a duplex real-time RT-qPCR assay to detect, discriminate and quantitate SARS-CoV-2 variants containing one of its mutation signatures, the ΔHV69/70 deletion, to trace the community circulation of the B.1.1.7 variant in Spain through the Spanish National SARS-CoV-2 Wastewater Surveillance System (VATar COVID-19). Results B.1.1.7 variant was first detected in sewage from the Southern city of Málaga (Andalucía) in week 20_52, and multiple introductions during Christmas holidays were inferred in different parts of the country, earlier than clinical epidemiological reporting by the local authorities. Wastewater-based B.1.1.7 tracking showed a good correlation with clinical data and provided information at the local level. Data from WWTPs which reached B.1.1.7 prevalences higher than 90% for ≥ 2 consecutive weeks showed that 8.1±1.8 weeks were required for B.1.1.7 to become dominant. Conclusion The study highlights the applicability of RT-qPCR-based strategies to track specific mutations of variants of concern (VOCs) as soon as they are identified by clinical sequencing, and its integration into existing wastewater surveillance programs, as a cost-effective approach to complement clinical testing during the COVID-19 pandemic., This work was partially supported by the COVID-19 wastewater surveillance project (VATar COVID19), funded by the Spanish Ministry for the Ecological Transition and the Demographic Challenge of and the Spanish Ministry of Health; grants from CSIC (202070E101) and MICINN co-founded by AEI FEDER, UE (AGL2017-82909); grant ED431C 2018/18 from the Conselleria de Educacion, Universidade e Formacion Profesional, Xunta de Galicia (Spain); Direccio General de Recerca i Innovacio en Salut (DGRIS) Catalan Health Ministry Generalitat de Catalunya through Vall de Hebron Research Institute (VHIR), and Centro para el Desarrollo Tecnologico Industrial (CDTI) from the Spanish Ministry of Economy and Business, grant number IDI-20200297. Pilar Truchado is holding a Ramon y Cajal contract from the Ministerio de Ciencia e Innovacion. Adan Martinez is holding a predoctoral fellowship FI_SDUR from Generalitat de Catalunya. We gratefully acknowledge all the staff involved in the VATar COVID-19 project, working with sample collection and logistics. The authors are grateful to Promega Corporation (Madison, US) for technical advice, and thank Andrea Lopez de Mota for her technical support.