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Warish Ahmed et al.
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Amy Xiao et al.
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Shelesh Agrawal et al.
Summary: For community-level monitoring, the European Commission recommends wastewater-based surveillance to track SARS-CoV-2 variants. High-coverage genome sequencing of wastewater samples has been successfully used to detect and track SARS-CoV-2 mutations, which are consistent with the variants reported in clinical data.
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Ananda Tiwari et al.
Summary: Wastewater-based surveillance is a cost-effective method for monitoring the COVID-19 pandemic at a population level. This study in Finland monitored SARS-CoV-2 RNA in wastewater samples from multiple treatment plants over a 10-month period. The detection rate of SARS-CoV-2 RNA in wastewater was 79%, and the surveillance proved to be a reliable indicator for COVID-19 incidence, independent of clinical testing strategies or individual testing willingness.
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Xiaoqing Xu et al.
Summary: To effectively control the ongoing outbreaks of fast-spreading SARS-CoV-2 variants, it is urgent to add rapid variant detection and discrimination methods to the existing sewage surveillance systems worldwide. Researchers designed eight assays based on allele-specific RT-qPCR for real-time allelic discrimination of eight SARS-CoV-2 variants in sewage. The assays demonstrated high specificity and sensitivity, and successfully identified and quantified target variants even in sewage samples containing mixtures of SARS-CoV-2 variants. Integration of this method into routine sewage surveillance in Hong Kong showed promising results in detecting the Beta and Delta variants, and also provided real-time discrimination of the emerging Omicron variant.
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Alexandria B. Boehm et al.
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Rebekka M. Lee et al.
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Fabian Amman et al.
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Wei Lin Lee et al.
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Mohamed Bayati et al.
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Wei Lin Lee et al.
Summary: Arboviral diseases, spread by infected arthropods, have significant economic and social impacts, with dengue, Zika, west nile fever, and yellow fever being the most prominent. The frequency and geographical extent of arboviral epidemics have been increasing in recent decades, and this trend is expected to continue due to climate change and urbanization. However, the actual prevalence of arboviral diseases is often underestimated due to a large number of asymptomatic cases. Existing surveillance systems rely on passive reporting and infrequent laboratory confirmation, leading to the need for alternative methods such as wastewater-based surveillance (WBS). This review explores the feasibility of using WBS to monitor arboviral diseases, discussing factors such as viral shedding loads, persistence in sewage, and recovery efficiency. Furthermore, a simple model is provided to estimate the required volume of wastewater for arbovirus detection. Overall, this review highlights the challenges that need to be addressed for successful implementation of arboviral WBS.
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Marlene K. Wolfe et al.
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ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS
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Liang Zhao et al.
Summary: Wastewater-based epidemiology (WBE) is a useful tool for predicting COVID-19 incidence and providing early warnings. In this study, the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in southeastern Michigan was examined. The results showed a strong correlation between the viral concentrations in wastewater and the daily COVID-19 cases, with a potential 5-week lag time. Statistical models were established to predict COVID-19 cases, and the autoregression model with seasonal patterns and vector autoregression model were found to be more effective. Flow parameters had little impact on the correlation, and the optimum models worked well for both normalized and non-normalized data. The study also discussed the factors contributing to the observed lag time and evaluated the impact of the Omicron variant and different sampling methods.
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G. La Rosa et al.
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Juliana Calabria de Araujo et al.
Summary: The coronavirus pandemic that started in March 2020 has led to millions of deaths worldwide. Wastewater-based epidemiology (WBE) can serve as a valuable tool for tracking the dissemination of SARS-CoV-2 and providing early warnings of COVID-19 outbreaks. A study conducted in Belo Horizonte, Brazil analyzed sewage samples from five public places over a period of 16 months to detect the presence of SARS-CoV-2 RNA. The results showed that sewage from sewage treatment plants, airports, and universities could be monitored for regular surveillance. However, the viral concentrations in the selected public places were generally lower than those in the municipal sewage treatment plants, possibly due to the behavior of asymptomatic individuals who are more likely to visit these places.
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Sarah M. Prasek et al.
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Femi F. Oloye et al.
Summary: Monitoring the communal incidence of COVID-19 is important for decision-making, but relying on a single method may lead to inaccurate results. Wastewater surveillance provides unbiased data that can predict COVID-19 situations in smaller communities.
SCIENCE OF THE TOTAL ENVIRONMENT
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Qingyu Zhan et al.
Summary: Normalizing wastewater concentrations of SARS-CoV-2 against indicators of human waste can improve the tracking of infections. The use of volcano second generation-qPCR chemistry with PMMoV and B2M for normalization showed improved correlations with COVID-19 cases in campus data. The effectiveness of normalizing with measures of human waste depends on the qPCR chemistry and the scale of the sewersheds.
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Kimihito Ito et al.
Summary: The Omicron variant of SARS-CoV-2 is spreading faster than any other variant we have seen so far. The BA.1 and BA.2 sublineages of Omicron are circulating globally, and it is important to evaluate their transmission advantages. By analyzing variant frequencies in Denmark from November 2021 to February 2022, researchers found that the mean generation time of Omicron BA.1 is shorter than Delta, and the effective reproduction number is higher for Omicron BA.1 compared to Delta. Additionally, the mean generation time for Omicron BA.2 is shorter than BA.1, and the effective reproduction number is higher for Omicron BA.2 compared to BA.1.
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Wei Lin Lee et al.
Summary: The study successfully validated a new method for detecting the Omicron variant using wastewater-based monitoring at a wastewater treatment plant in Italy, revealing a rapid displacement trend of the Omicron variant over the Delta variant in wastewater. These data support clinical studies that found the Omicron variant to have an infection advantage in vaccinated populations.
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Mohamed Bayati et al.
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Willis Gwenzi
Summary: The human coronavirus disease COVID-19 is now a global pandemic, with potential faecal-oral transmission being a concern, especially in developing countries. Attention to clean water provision, sanitation, food safety, and hygiene is crucial in combating COVID-19, with further research on faecal-oral transmission direction highlighted.
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Leo Heijnen et al.
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Yuehan Ai et al.
Summary: Wastewater-based epidemiology has been used as a rapid tool for COVID-19 surveillance system and tracking variants of concern. Analysis of wastewater samples from central Ohio showed a strong correlation between SARS-CoV-2 gene concentrations and daily new confirmed COVID-19 cases, with the N2 gene region as the best predictor. The quadratic polynomial model performed the best in correlating and predicting COVID-19 cases from wastewater surveillance data.
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Bradley W. Schmitz et al.
Summary: Wastewater-based epidemiology was effective in identifying and reducing SARS-CoV-2 transmission events in student dormitories, with 79.2% of infections found to be asymptomatic.
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Jennifer Weidhaas et al.
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Summary: Wastewater surveillance can be used to detect SARS-CoV-2 RNA, with reliable detection when daily new COVID-19 cases exceed 2.4 per 100,000 people. Evaluation of normalization biomarkers found crAssphage to have the least spatial and temporal variability. Trends in wastewater surveillance data reflect trends in COVID-19 disease occurrence.
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