2022
DOI: 10.1016/j.watres.2022.118070
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Metrics to relate COVID-19 wastewater data to clinical testing dynamics

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Cited by 91 publications
(93 citation statements)
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“…,moving averages, polynomial interpolations) that have been used to support the interpretation of WBS D’Aoust et al (2021) . However, we note that less complex modelling options are possible if the focus is on specific epidemiological metrics ( Huisman et al, 2021 , Xiao et al, 2021 ). We also note recent efforts to use machine learning techniques and artificial neural network that incorporate WBS Li et al (2021) .…”
Section: Discussionmentioning
confidence: 99%
“…,moving averages, polynomial interpolations) that have been used to support the interpretation of WBS D’Aoust et al (2021) . However, we note that less complex modelling options are possible if the focus is on specific epidemiological metrics ( Huisman et al, 2021 , Xiao et al, 2021 ). We also note recent efforts to use machine learning techniques and artificial neural network that incorporate WBS Li et al (2021) .…”
Section: Discussionmentioning
confidence: 99%
“… 13 Additionally, wastewater has been proposed as an alternative method for estimating the COVID-19 reproductive number 14 or as an indicator of clinical diagnostic testing capacity. 15 Finally, wastewater monitoring provides a powerful approach for monitoring existing and emerging variants at the community level. 39 , 40 In practice, WBE has been applied in multiple ways.…”
Section: Introductionmentioning
confidence: 99%
“…The reproducibility, repeatability, and reliability of COVID-19 WBE biosensors can be determined by comparing the wastewater surveillance data utilizing the developed biosensors with the PCR-based sensors as previously reported by Xiao et al [ 161 ]. PCR-based WBE data was compared to the gold standard clinical surveillance data by considering significant quantitative metrics including time lag and transfer function between wastewater and clinical reporting.…”
Section: Challenges and Outlookmentioning
confidence: 99%