2020
DOI: 10.1016/j.scitotenv.2020.138875
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Computational analysis of SARS-CoV-2/COVID-19 surveillance by wastewater-based epidemiology locally and globally: Feasibility, economy, opportunities and challenges

Abstract: Journal Pre-proof J o u r n a l P r e -p r o o f 2 Abstract:With the economic and practical limits of medical screening for SARS-CoV-2/COVID-19 coming sharply into focus worldwide, scientists are turning now to wastewater-based epidemiology (WBE) as a potential tool for assessing and managing the pandemic. We employed computational analysis and modeling to examine the feasibility, economy, opportunities and challenges of enumerating active coronavirus infections locally and globally using WBE.Depending on loca… Show more

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Cited by 510 publications
(563 citation statements)
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“…Based on the available data, we have hypothesized that the viral load obtained from wastewater allows modelling that can predict outbreaks with high reliability. In fact, an earlier study has confirmed the theoretical feasibility of combining WBE approaches with SARS-CoV-2/COVID-19 data 52 .…”
Section: Introductionmentioning
confidence: 75%
See 1 more Smart Citation
“…Based on the available data, we have hypothesized that the viral load obtained from wastewater allows modelling that can predict outbreaks with high reliability. In fact, an earlier study has confirmed the theoretical feasibility of combining WBE approaches with SARS-CoV-2/COVID-19 data 52 .…”
Section: Introductionmentioning
confidence: 75%
“…This is a pioneering approach in the context of the SARS-CoV-2 pandemic since, to our knowledge, WBE studies available are still limited to reporting the occurrence of SARS-CoV-2 RNA in WWTPs and sewer networks, in order to establish a direct comparison with declared COVID-19 cases35,37,[46][47][48] . The only precedent52 combines computational analysis and modelling with a theoretical approach in order to identify useful variables and confirm the feasibility and cost-effectiveness of WBE as a prediction tool. Other examples of WBE models have been applied to previous outbreaks of other infectious diseases.…”
mentioning
confidence: 99%
“…Studies involving the identification and potential of contamination can be improved with the development of computational models to improve the monitoring and detection of virus particles per unit in sewers (Casanova, 2009;Casanova and Weaver, 2015). Hart and Halden (2020) highlight the need and difficulty of obtaining information about the potential for contamination of the virus in sewers, due to the current temporary limitations of operation of the research laboratories and biosafety requirements above Level 2 to perform this type of test; they also emphasize that the virus inactivation and detection due to temperature should be better understood.…”
Section: Monitoring Of Viral Levels In Domestic Effluentsmentioning
confidence: 99%
“…Thus, it is vital to monitor the quality of water resources, especially in relation to effluents, which can be a source of contamination for COVID-19. Hart and Halden (2020) highlight the epidemiological monitoring of SARS-CoV-2 in sewers as a tool of great potential due to its cost-benefit and robustness; however, this resource should not be used to replace clinical tests in infected individuals and/or suspected to be contaminated.…”
Section: Introductionmentioning
confidence: 99%
“…In the 2019’s edition, the motto was Computational Science in the Interconnected World , highlighting the role of CS in an increasingly unified planet. As matter of fact, the context in which this editorial paper is being written, just a few months after the declaration of the COVID-19 pandemic, highlights the importance of this interconnected world and keeps CS in the forefront of the needs, reflected in the epidemiological research that is supported in computational methods [ [3] , [4] , [5] , [6] ] or the proved accuracy of many disease propagation models [ [7] , [8] , [9] , [10] , [11] , [12] ]. In short, CS practitioners work on the knowledge fringe, making this research field very attractive to new and old practitioners, obliged to solve modern gratifying and intricate computational problems.…”
Section: Introductionmentioning
confidence: 99%