Abstract
The COVID-19 pandemic has put unprecedented pressure on public health resources around the world. From adversity, opportunities have arisen to measure the state and dynamics of human disease at a scale not seen before. In the United Kingdom, the evidence that wastewater could be used to monitor the SARS-CoV-2 virus prompted the development of National wastewater surveillance programmes. The scale and pace of this work has proven to be unique in monitoring of virus dynamics at a national level, demonstrating the importance of wastewater-based epidemiology (WBE) for public health protection. Beyond COVID-19, it can provide additional value for monitoring and informing on a range of biological and chemical markers of human health. A discussion of measurement uncertainty associated with surveillance of wastewater, focusing on lessons-learned from the UK programmes monitoring COVID-19 is presented, showing that sources of uncertainty impacting measurement quality and interpretation of data for public health decision-making, are varied and complex. While some factors remain poorly understood, we present approaches taken by the UK programmes to manage and mitigate the more tractable sources of uncertainty. This work provides a platform to integrate uncertainty management into WBE activities as part of global One Health initiatives beyond the pandemic.
Highlights
While some factors remain poorly understood, we present approaches taken by the United Kingdom (UK) programmes to manage and mitigate the more tractable sources of uncertainty
This is evident with wastewater, a conduit for an array of bio- and chemical markers that can be analysed to provide information on human activities, behaviours, and health status in populations (Castiglioni et al, 2013; Daughton, 2018; O’Brien, 2017; Subedi, 2019), but which has remained a relatively untapped resource given its known potential (Gonzalez-Marino et al, 2020; Kasprzyk-Hordern et al, 2021; Lorenzo and Pico, 2019; Pruden, 2014; Singer et al, 2013)
Parallel studies with duplicate wastewater samples showed no significant differences in recovery between the two methods for SARS-CoV-2 RNA
Summary
An increasing technological and computational capacity for deriving knowledge from measurements and data has manifested in efforts to ‘smarten’ the water industry (Wade et al, 2020a), fusing data science with fundamental science and engi neering principles This provides opportunities for greater utilisation of sewage for the common good, be it in the production of resources such as energy and high value chemicals (Kehrein et al, 2020), or as a proxy of human health and behaviours, which will have transformative impacts for society
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