Development, Implementation and Normalization of SARS-CoV-2 Wastewater and Environmental Monitoring
type: CreativeWork
description: Wastewater and environmental monitoring (WEM) has for decades been a valuable resource for monitoring public health trends and providing insights into community-wide substance use, such as pharmaceuticals and illicit drugs, tracking infectious diseases like poliomyelitis and viral hepatitis. Despite its promise, WEM was historically underutilized, mainly limited to targeted studies or research efforts, and rarely integrated into real-time public health systems. The onset of the COVID-19 pandemic transformed WEM into a highly sought epidemiological tool, capable of complementing clinical testing and offering community-level data to better inform public health strategies. The COVID-19 pandemic exposed significant gaps in public health surveillance, emphasizing the need for tools that could monitor SARS-CoV-2 viral spread in real-time. WEM emerged as a promising approach, but early efforts faced several challenges: limited detection of the SARS-CoV-2 viral signal in wastewater during periods of low prevalence (low method sensitivity), pronounced variability in wastewater composition by location and season, the initial difficulty of scaling these methods to underserved, rural communities, and the lack of a universal biomarker or method of normalization to reduce the impact of flow and wastewater composition changes. The overarching hypothesis of this work was that WEM for SARS-CoV-2 could be established and refined through optimized sampling and sample processing methodologies, and that novel normalization strategies could improve the robustness of data interpretation and allow WEM to have predictive power as a public health tool. This dissertation addresses this hypothesis and bridges critical knowledge gaps by conducting six studies, establishing the methodologies, normalization strategies, and applications of normalization to WEM to improve its reliability and utility as a public health tool. The first objective of the dissertation was to develop methodologies for SA…
abstract: Wastewater and environmental monitoring (WEM) has for decades been a valuable resource for monitoring public health trends and providing insights into community-wide substance use, such as pharmaceuticals and illicit drugs, tracking infectious diseases like poliomyelitis and viral hepatitis. Despite its promise, WEM was historically underutilized, mainly limited to targeted studies or research efforts, and rarely integrated into real-time public health systems. The onset of the COVID-19 pandemic transformed WEM into a highly sought epidemiological tool, capable of complementing clinical testing and offering community-level data to better inform public health strategies. The COVID-19 pandemic exposed significant gaps in public health surveillance, emphasizing the need for tools that could monitor SARS-CoV-2 viral spread in real-time. WEM emerged as a promising approach, but early efforts faced several challenges: limited detection of the SARS-CoV-2 viral signal in wastewater during periods of low prevalence (low method sensitivity), pronounced variability in wastewater composition by location and season, the initial difficulty of scaling these methods to underserved, rural communities, and the lack of a universal biomarker or method of normalization to reduce the impact of flow and wastewater composition changes. The overarching hypothesis of this work was that WEM for SARS-CoV-2 could be established and refined through optimized sampling and sample processing methodologies, and that novel normalization strategies could improve the robustness of data interpretation and allow WEM to have predictive power as a public health tool. This dissertation addresses this hypothesis and bridges critical knowledge gaps by conducting six studies, establishing the methodologies, normalization strategies, and applications of normalization to WEM to improve its reliability and utility as a public health tool. The first objective of the dissertation was to develop methodologies for SA…
author: D'Aoust, Patrick Marcel
language: en
keywords: wastewater and environmental surveillance, sars-cov-2, covid-19, public health, pmmov, wastewater based epidemiology
license: http://creativecommons.org/licenses/by-nd/4.0/
date published: 2025-04-25T16:31:09Z
date modified: 2026-07-24T03:39:31Z
provider: University of Ottawa
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Université d'Ottawa / University of Ottawa

PropertyValue
property ID: Handle
value: http://hdl.handle.net/10393/50375

PropertyValue
property ID: DOI
value: 10.20381/ruor-31047