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2.
Sci Total Environ ; 856(Pt 1): 159062, 2023 Jan 15.
Article in English | MEDLINE | ID: covidwho-2049908

ABSTRACT

Wastewater analysis is the most attractive alternative way for the quantification and variant profiling of SARS-CoV-2. Infection dynamics can be monitored by RT-qPCR assays while NGS can provide evidence for the presence of existing or new emerging SARS-CoV-2 variants. Herein, apart from the infection dynamic in Attica since June 1st, 2021, the monitoring of 9 mutations of the omicron and 4 mutations of the delta SARS-CoV-2 variants, utilizing both novel Nested-Seq and RT-PCR, is reported and the substitution of the delta variant (B.1.617.2) by the omicron variant (B.1.1.529) in Attica, Greece within approximately one month is highlighted. The key difference between the two methodologies is discovery power. RT-PCR can only detect known sequences cost-effectively, while NGS is a hypothesis-free approach that does not require prior knowledge to detect novel genes. Overall, the potential of wastewater genomic surveillance for the early discovery and monitoring of variants important for disease management at the community level is underlined. This is the first study, reporting the SARS-CoV-2 infection dynamic for an extended time period and the first attempt to monitor two of the most severe variants with two different methodologies in Greece.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , Wastewater , Greece
4.
Sci Total Environ ; 804: 150151, 2022 Jan 15.
Article in English | MEDLINE | ID: covidwho-1401851

ABSTRACT

We measured SARS-CoV-2 RNA load in raw wastewater in Attica, Greece, by RT-qPCR for the environmental surveillance of COVID-19 for 6 months. The lag between RNA load and pandemic indicators (COVID-19 hospital and intensive care unit (ICU) admissions) was calculated using a grid search. Our results showed that RNA load in raw wastewater is a leading indicator of positive COVID-19 cases, new hospitalization and admission into ICUs by 5, 8 and 9 days, respectively. Modelling techniques based on distributed/fixed lag modelling, linear regression and artificial neural networks were utilized to build relationships between SARS-CoV-2 RNA load in wastewater and pandemic health indicators. SARS-CoV-2 mutation analysis in wastewater during the third pandemic wave revealed that the alpha-variant was dominant. Our results demonstrate that clinical and environmental surveillance data can be combined to create robust models to study the on-going COVID-19 infection dynamics and provide an early warning for increased hospital admissions.


Subject(s)
COVID-19 , SARS-CoV-2 , Hospitalization , Humans , Intensive Care Units , RNA, Viral , Wastewater , Wastewater-Based Epidemiological Monitoring
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