1. Monitoring Emergence of the SARS-CoV-2 B.1.1.7 Variant through the Spanish National SARS-CoV-2 Wastewater Surveillance System (VATar COVID-19)
- Author
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Alba Pérez-Cataluña, Gloria Sánchez, Susana Guix, Pilar Truchado, Rosa M. Pintó, Damir Garcia-Cehic, Albert Carcereny, David Polo, Adán Martínez-Velázquez, Josep Quer, Josep Gregori, Marta Lois, Ana Allende, Margarita Palau, Andrés Antón, Azahara Díaz-Reolid, Albert Bosch, Cristina Gonzalez Ruano, Jesús L. Romalde, Jenifer Cascales, Ministerio para la Transición Ecológica y el Reto Demográfico (España), Ministerio de Sanidad, Consumo y Bienestar Social (España), Consejo Superior de Investigaciones Científicas (España), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), European Commission, Xunta de Galicia, Generalitat de Catalunya, Vall d'Hebron Research Institute, Centro para el Desarrollo Tecnológico Industrial (España), Ministerio de Asuntos Económicos y Transformación Digital (España), Romalde, Jesús L., Guix, Susana, Romalde, Jesús L. [0000-0003-4786-4773], and Guix, Susana [0000-0002-1588-3198]
- Subjects
medicine.medical_specialty ,2019-20 coronavirus outbreak ,Coronavirus disease 2019 (COVID-19) ,wastewater-based epidemiology (WBE) ,SARS-CoV-2 ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,RT-qPCR ,B.1.1.7 variant ,COVID-19 ,General Chemistry ,Wastewater-based epidemiology (WBE) ,Wastewater ,Article ,Geography ,Environmental health ,NGS ,Epidemiology ,Pandemic ,medicine ,Environmental Chemistry ,Humans ,Pandemics - Abstract
Since its first identification in the United Kingdom in late 2020, the highly transmissible B.1.1.7 variant of SARS-CoV-2 has become dominant in several countries raising great concern. We developed 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, and used it 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). The B.1.1.7 variant was detected earlier than clinical epidemiological reporting by the local authorities, first in the southern city of Málaga (Andalucía) in week 20_52 (year_week), and multiple introductions during Christmas holidays were inferred in different parts of the country. Wastewater-based B.1.1.7 tracking showed a good correlation with clinical data and provided information at the local level. Data from wastewater treatment plants, which reached B.1.1.7 prevalences higher than 90% for ≥2 consecutive weeks showed that 8.1 ± 2.0 weeks were required for B.1.1.7 to become dominant. The study highlights the applicability of RT-qPCR-based strategies to track specific mutations of variants of concern as soon as they are identified by clinical sequencing and their 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 and the Spanish Ministry of Health, grants from CSIC (202070E101) and MICINN cofounded by AEI FEDER, UE (AGL2017-82909), grant ED431C 2018/18 from the Consellería de Educación, Universidade e Formación Profesional, Xunta de Galicia (Spain), Direcció General de Recerca i Innovació en Salut (DGRIS) Catalan Health Ministry Generalitat de Catalunya through Vall d’Hebron Research Institute (VHIR), and Centro para el Desarrollo Tecnológico Industrial (CDTI) from the Spanish Ministry of Economy and Business, grant number IDI-20200297. P.T. is holding a Ramón y Cajal contract from the Ministerio de Ciencia e Innovación. A.M. 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.
- Published
- 2021