Wastewater-based epidemiology: the crucial role of viral shedding dynamics in small communities

Marc-Denis Rioux; François Guillemette; Karine Lemarchand; Kim Doiron; Jean-François Lemay; Thomas Maere; Patrick Dolcé; Patrik Quessy; Nanouk Abonnenc; Peter A Vanrolleghem; Dominic Frigon

doi:10.3389/fpubh.2023.1141837

Wastewater-based epidemiology: the crucial role of viral shedding dynamics in small communities

Front Public Health. 2023 Aug 2:11:1141837. doi: 10.3389/fpubh.2023.1141837. eCollection 2023.

Authors

Affiliations

¹ Department of Mathematics and Engineering, Université du Québec à Rimouski, Quebec, QC, Canada.
² Department of Environmental Science, Université du Québec à Trois-Rivière, Quebec, QC, Canada.
³ Institut des Sciences de la Mer, Université du Québec à Rimouski, Quebec, QC, Canada.
⁴ Northern Institute for Research in Environment and Occupational Health and Safety, Quebec, QC, Canada.
⁵ Centre National en Électrochimie et Technologies Environnementales, Cegep of Shawinigan, Quebec, QC, Canada.
⁶ modelEAU, Département de génie civil et de génie des eaux, Université Laval, Quebec, QC, Canada.
⁷ Centre Intégré de Santé et de services sociaux du Bas-Saint-Laurent, Quebec, QC, Canada.
⁸ Department of Civil Engineering, McGill University, Quebec, QC, Canada.

Abstract

Background: Wastewater surveillance (WWS) of pathogens is a rapidly evolving field owing to the 2019 coronavirus disease pandemic, which brought about a paradigm shift in public health authorities for the management of pathogen outbreaks. However, the interpretation of WWS in terms of clinical cases remains a challenge, particularly in small communities where large variations in pathogen concentrations are routinely observed without a clear relation to clinical incident cases.

Methods: Results are presented for WWS from six municipalities in the eastern part of Canada during the spring of 2021. We developed a numerical model based on viral kinetics reduction functions to consider both prevalent and incident cases to interpret the WWS data in light of the reported clinical cases in the six surveyed communities.

Results: The use of the proposed numerical model with a viral kinetics reduction function drastically increased the interpretability of the WWS data in terms of the clinical cases reported for the surveyed community. In line with our working hypothesis, the effects of viral kinetics reduction modeling were more important in small communities than in larger communities. In all but one of the community cases (where it had no effect), the use of the proposed numerical model led to a change from a +1.5% (for the larger urban center, Quebec City) to a +48.8% increase in the case of a smaller community (Drummondville).

Conclusion: Consideration of prevalent and incident cases through the proposed numerical model increases the correlation between clinical cases and WWS data. This is particularly the case in small communities. Because the proposed model is based on a biological mechanism, we believe it is an inherent part of any wastewater system and, hence, that it should be used in any WWS analysis where the aim is to relate WWS measurement to clinical cases.

Keywords: pathogens; small communities; viral shedding dynamics; wastewater surveillance; wastewater-based epidemiology.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Canada / epidemiology
Coronavirus*
Virus Shedding
Wastewater*
Wastewater-Based Epidemiological Monitoring

Substances

Wastewater

Grants and funding

This work was made possible by funding from the Fond de Recherche du Québec—Nature et Technologie (1,000,000$), the Molson Foundation (300,000$), the Trottier Foundation (357,000$), the Centre Intégré de Santé et Services Sociaux du Bas-Saint-Laurent and Santé Publique du Bas-Saint-Laurent (20,000$), CentrEau (20,000$), CNETE (50,000$), and the McGill Interdisciplinary Initiative in Infection Immunity (300,000$).