Population normalisation in wastewater-based epidemiology for improved understanding of SARS-CoV-2 prevalence: A multi-site study (preprint)

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.

Building knowledge of university campus population dynamics to enhance near-to-source sewage surveillance for SARS-CoV-2 detection (preprint)

Wastewater surveillance has been widely implemented for monitoring of SARS-CoV-2 during the global COVID-19 pandemic, and near-to-source monitoring is of particular interest for outbreak management in discrete populations. However, variation in population size poses a challenge to the triggering of public health interventions using wastewater SARS-CoV-2 concentrations. This is especially important for near-to-source sites that are subject to significant daily variability in upstream populations. Focusing on a university campus in England, this study investigates methods to account for variation in upstream populations at a site with highly transient footfall and provides a better understanding of the impact of variable populations on the SARS-CoV-2 trends provided by wastewater-based epidemiology. The potential for complementary data to help direct response activities within the near-to-source population is also explored, and potential concerns arising due to the presence of heavily diluted samples during wet weather are addressed. Using wastewater biomarkers, it is demonstrated that population normalisation can reveal significant differences between days where SARS-CoV-2 concentrations are very similar. Confidence in the trends identified is strongest when samples are collected during dry weather periods; however, wet weather samples can still provide valuable information. It is also shown that building-level occupancy estimates based on complementary data aid identification of potential sources of SARS-CoV-2 and can enable targeted actions to be taken to identify and manage potential sources of pathogen transmission in localised communities.