Time series modelling for wastewater-based epidemiology of COVID-19: A nationwide study in 40 wastewater treatment plants of Belgium, February 2021 to June 2022.


Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
15 Nov 2023
Historique:
received: 18 02 2023
revised: 11 07 2023
accepted: 15 07 2023
medline: 20 9 2023
pubmed: 21 7 2023
entrez: 20 7 2023
Statut: ppublish

Résumé

Wastewater-based epidemiology (WBE) has been implemented to monitor surges of COVID-19. Yet, multiple factors impede the usefulness of WBE and quantitative adjustment may be required. We aimed to model the relationship between WBE data and incident COVID-19 cases, while adjusting for confounders and autocorrelation. This nationwide WBE study includes data from 40 wastewater treatment plants (WWTPs) in Belgium (02/2021-06/2022). We applied ARIMA-based modelling to assess the effect of daily flow rate, pepper mild mottle virus (PMMoV) concentration, a measure of human faeces in wastewater, and variants (alpha, delta, and omicron strains) on SARS-CoV-2 RNA levels in wastewater. Secondly, adjusted WBE metrics at different lag times were used to predict incident COVID-19 cases. Model selection was based on AICc minimization. In 33/40 WWTPs, RNA levels were best explained by incident cases, flow rate, and PMMoV. Flow rate and PMMoV were associated with -13.0 % (95 % prediction interval: -26.1 to +0.2 %) and +13.0 % (95 % prediction interval: +5.1 to +21.0 %) change in RNA levels per SD increase, respectively. In 38/40 WWTPs, variants did not explain variability in RNA levels independent of cases. Furthermore, our study shows that RNA levels can lead incident cases by at least one week in 15/40 WWTPs. The median population size of leading WWTPs was 85.1 % larger than that of non‑leading WWTPs. In 17/40 WWTPs, however, RNA levels did not lead or explain incident cases in addition to autocorrelation. This study provides quantitative insights into key determinants of WBE, including the effects of wastewater flow rate, PMMoV, and variants. Substantial inter-WWTP variability was observed in terms of explaining incident cases. These findings are of practical importance to WBE practitioners and show that the early-warning potential of WBE is WWTP-specific and needs validation.

Sections du résumé

BACKGROUND BACKGROUND
Wastewater-based epidemiology (WBE) has been implemented to monitor surges of COVID-19. Yet, multiple factors impede the usefulness of WBE and quantitative adjustment may be required.
AIM OBJECTIVE
We aimed to model the relationship between WBE data and incident COVID-19 cases, while adjusting for confounders and autocorrelation.
METHODS METHODS
This nationwide WBE study includes data from 40 wastewater treatment plants (WWTPs) in Belgium (02/2021-06/2022). We applied ARIMA-based modelling to assess the effect of daily flow rate, pepper mild mottle virus (PMMoV) concentration, a measure of human faeces in wastewater, and variants (alpha, delta, and omicron strains) on SARS-CoV-2 RNA levels in wastewater. Secondly, adjusted WBE metrics at different lag times were used to predict incident COVID-19 cases. Model selection was based on AICc minimization.
RESULTS RESULTS
In 33/40 WWTPs, RNA levels were best explained by incident cases, flow rate, and PMMoV. Flow rate and PMMoV were associated with -13.0 % (95 % prediction interval: -26.1 to +0.2 %) and +13.0 % (95 % prediction interval: +5.1 to +21.0 %) change in RNA levels per SD increase, respectively. In 38/40 WWTPs, variants did not explain variability in RNA levels independent of cases. Furthermore, our study shows that RNA levels can lead incident cases by at least one week in 15/40 WWTPs. The median population size of leading WWTPs was 85.1 % larger than that of non‑leading WWTPs. In 17/40 WWTPs, however, RNA levels did not lead or explain incident cases in addition to autocorrelation.
CONCLUSION CONCLUSIONS
This study provides quantitative insights into key determinants of WBE, including the effects of wastewater flow rate, PMMoV, and variants. Substantial inter-WWTP variability was observed in terms of explaining incident cases. These findings are of practical importance to WBE practitioners and show that the early-warning potential of WBE is WWTP-specific and needs validation.

Identifiants

pubmed: 37474075
pii: S0048-9697(23)04226-2
doi: 10.1016/j.scitotenv.2023.165603
pii:
doi:

Substances chimiques

RNA, Viral 0
Wastewater 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

165603

Informations de copyright

Copyright © 2023. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Delphine Brogna reports financial support was provided by E-BIOM. Catherine Linard reports financial support was provided by E-BIOM. Christian Didy reports financial support was provided by SPGE. Rosalie Pype reports financial support was provided by SPGE. Jonathan Marescaux reports financial support was provided by E-BIOM. Sven Hanoteaux reports a relationship with Sciensano that includes: employment. Raphael Janssens reports a relationship with Sciensano that includes: employment. Hadrien Maloux reports a relationship with Sciensano that includes: employment. Bavo Verhaegen reports a relationship with Sciensano that includes: employment. Jonathan Marescaux reports a relationship with E-BIOM that includes: employment. Koenraad Van Hoorde reports a relationship with Sciensano that includes: employment. Marie Lesenfants reports a relationship with Sciensano that includes: employment. Rosalie Pype reports a relationship with SPGE that includes: employment. Christian Didy reports a relationship with SPGE that includes: employment.

Auteurs

Xander Bertels (X)

Department of Bioanalysis, Ghent University, 9000 Ghent, Belgium.

Sven Hanoteaux (S)

Epidemiology and Public Health, Epidemiology of Infectious Diseases, Sciensano, 1050 Brussels, Belgium.

Raphael Janssens (R)

Epidemiology and Public Health, Epidemiology of Infectious Diseases, Sciensano, 1050 Brussels, Belgium.

Hadrien Maloux (H)

Epidemiology and Public Health, Epidemiology of Infectious Diseases, Sciensano, 1050 Brussels, Belgium.

Bavo Verhaegen (B)

Infectious Diseases in Humans, Foodborne Pathogens, Sciensano, 1050 Brussels, Belgium.

Peter Delputte (P)

Laboratory for Microbiology, Parasitology and Hygiene, University of Antwerp, 2610 Wilrijk, Belgium.

Tim Boogaerts (T)

Toxicological Centre, University of Antwerp, 2610 Antwerp, Belgium.

Alexander L N van Nuijs (ALN)

Toxicological Centre, University of Antwerp, 2610 Antwerp, Belgium.

Delphine Brogna (D)

Institute of Life, Earth and Environment, University of Namur, 5000 Namur, Belgium.

Catherine Linard (C)

Institute of Life, Earth and Environment, University of Namur, 5000 Namur, Belgium.

Jonathan Marescaux (J)

Institute of Life, Earth and Environment, University of Namur, 5000 Namur, Belgium; E-BIOM SA, 5000 Namur, Belgium.

Christian Didy (C)

Société Publique de Gestion de l'Eau, 4800 Verviers, Belgium.

Rosalie Pype (R)

Société Publique de Gestion de l'Eau, 4800 Verviers, Belgium.

Nancy H C Roosens (NHC)

Biological Health Risks, Transversal Activities in Applied Genomics, Sciensano, 1050 Brussels, Belgium.

Koenraad Van Hoorde (K)

Infectious Diseases in Humans, Foodborne Pathogens, Sciensano, 1050 Brussels, Belgium.

Marie Lesenfants (M)

Epidemiology and Public Health, Epidemiology of Infectious Diseases, Sciensano, 1050 Brussels, Belgium.

Lies Lahousse (L)

Department of Bioanalysis, Ghent University, 9000 Ghent, Belgium. Electronic address: lies.lahousse@ugent.be.

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Classifications MeSH