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1.
Environ Sci Technol ; 55(17): 11756-11766, 2021 09 07.
Article in English | MEDLINE | ID: covidwho-1358335

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.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Pandemics , Wastewater
2.
Sci Total Environ ; 786: 147534, 2021 Sep 10.
Article in English | MEDLINE | ID: covidwho-1226368

ABSTRACT

The presence of SARS-CoV-2 in wastewater pose the question of whether this new pandemic virus could be released into watercourses and potentially continue to finally reach coastal waters. In this study, we employed two bivalve molluscan species from the genus Ruditapes as sentinel organisms to investigate the presence of SARS-CoV-2 signals in the marine coastal environment. Estuarine sediments from the natural clam banks were also analyzed. Viral RNA was detected by RT-qPCR, targeting IP4, E and N1 genomic regions. Positive samples were also subjected to a PMAxx-triton viability RT-qPCR assay in order to discriminate between intact and altered capsids, obtaining indirect information about the viability of the virus. SARS-CoV-2 RNA traces were detected in 9/12 clam samples by RT-qPCR, from which 4 were positive for two different target regions. Viral quantification ranged from

Subject(s)
Bivalvia , COVID-19 , Animals , Geologic Sediments , Humans , RNA, Viral , SARS-CoV-2
3.
Water Res ; 186: 116404, 2020 Nov 01.
Article in English | MEDLINE | ID: covidwho-779749

ABSTRACT

The presence of SARS-CoV-2 in the feces of infected patients and wastewater has drawn attention, not only to the possibility of fecal-oral transmission but also to the use of wastewater as an epidemiological tool. The COVID-19 pandemic has highlighted problems in evaluating the epidemiological scope of the disease using classical surveillance approaches, due to a lack of diagnostic capacity, and their application to only a small proportion of the population. As in previous pandemics, statistics, particularly the proportion of the population infected, are believed to be widely underestimated. Furthermore, analysis of only clinical samples cannot predict outbreaks in a timely manner or easily capture asymptomatic carriers. Threfore, community-scale surveillance, including wastewater-based epidemiology, can bridge the broader community and the clinic, becoming a valuable indirect epidemiological prediction tool for SARS-CoV-2 and other pandemic viruses. This article summarizes current knowledge and discusses the critical factors for implementing wastewater-based epidemiology of COVID-19.


Subject(s)
Betacoronavirus , Coronavirus Infections , Pandemics , Pneumonia, Viral , COVID-19 , Humans , SARS-CoV-2 , Wastewater-Based Epidemiological Monitoring
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