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1.
J Water Health ; 20(12): 1688-1700, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2197720

ABSTRACT

Scotland introduced wastewater monitoring for COVID-19 early in the pandemic. From May 2020, samples have been taken and analysed using quantitative polymerase chain reaction (qPCR). The programme was expanded to over 100 sites accounting for around 80% of the population. Data are presented publicly via a dashboard and regular reports are produced for both the public and health professionals. Wastewater-based epidemiology (WBE) offers opportunities and challenges. It offers an objective means of measuring COVID-19 prevalence and can be more practical or timely than other methods of mass testing. However, it also has substantial variability impacted by multiple environmental factors. Methods for data collection and analysis have developed significantly through the pandemic, reflecting the evolving situation and policy direction. We discuss the Scottish experience of wastewater monitoring for COVID-19, with a focus on the analysis of data. This includes our approach to flow normalisation, our experience of variability in measurements and anomalous values, and the visualisation and presentation of data to stakeholders. Summarising the Scottish methodology as of March 2022, we also discuss how wastewater data were used for informing policy and public health actions. We draw lessons from our experience and consider future directions for WBE in Scotland.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Wastewater , SARS-CoV-2 , Wastewater-Based Epidemiological Monitoring , Scotland/epidemiology
2.
Environ Sci Technol ; 55(22): 15276-15286, 2021 11 16.
Article in English | MEDLINE | ID: covidwho-1503942

ABSTRACT

Wastewater based epidemiology (WBE) has become an important tool during the COVID-19 pandemic, however the relationship between SARS-CoV-2 RNA in wastewater treatment plant influent (WWTP) and cases in the community is not well-defined. We report here the development of a national WBE program across 28 WWTPs serving 50% of the population of Scotland, including large conurbations, as well as low-density rural and remote island communities. For each WWTP catchment area, we quantified spatial and temporal relationships between SARS-CoV-2 RNA in wastewater and COVID-19 cases. Daily WWTP SARS-CoV-2 influent viral RNA load, calculated using daily influent flow rates, had the strongest correlation (ρ > 0.9) with COVID-19 cases within a catchment. As the incidence of COVID-19 cases within a community increased, a linear relationship emerged between cases and influent viral RNA load. There were significant differences between WWTPs in their capacity to predict case numbers based on influent viral RNA load, with the limit of detection ranging from 25 cases for larger plants to a single case in smaller plants. SARS-CoV-2 viral RNA load can be used to predict the number of cases detected in the WWTP catchment area, with a clear statistically significant relationship observed above site-specific case thresholds.


Subject(s)
COVID-19 , Water Purification , Humans , Pandemics , RNA, Viral , SARS-CoV-2 , Viral Load , Wastewater
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