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Population normalisation in wastewater-based epidemiology for improved understanding of SARS-CoV-2 prevalence: A multi-site study (preprint)
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.08.03.21261365
ABSTRACT
This paper aims to determine whether population normalisation significantly alters the SARS-CoV-2 trends revealed by wastewater-based epidemiology, and whether it is beneficial and/or necessary to provide an understanding of prevalence from wastewater SARS-CoV-2 concentrations. It uses wastewater SARS-CoV-2 data collected from 394 sampling sites, and implements normalisation based on concentrations of a) ammoniacal nitrogen, and b) orthophosphate. Wastewater SARS-CoV-2 metrics are evaluated at a site and aggregated level against three indicators prevalence, based on positivity rates from the Office for National Statistics Coronavirus Infection Survey and test results reported by NHS Test and Trace. Normalisation is shown to have little impact on the overall trends in the wastewater SARS-CoV-2 data on average. However, significant variability between the impact of population normalisation at different sites, which is not evident from previous WBE studies focussed on a single site, is also revealed. Critically, it is demonstrated that while the impact of normalisation on SARS-CoV-2 trends is small on average, it is not reasonable to conclude that it is always insignificant. When averaged across many sites, normalisation strengthens the correlation between wastewater SARS-CoV-2 data and indicators of prevalence; however, confidence in the improvement is low. Lastly, it is noted that most data were collected during periods of national lockdown and/or local restrictions, and thus the impacts and benefits of population normalisation are expected to be higher when normal travel habits resume.

Full text: Available Collection: Preprints Database: medRxiv Language: English Year: 2021 Document Type: Preprint

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Full text: Available Collection: Preprints Database: medRxiv Language: English Year: 2021 Document Type: Preprint