Evaluating Interlaboratory Variability in Wastewater-Based COVID-19 Surveillance

Evaluating Interlaboratory Variability in Wastewater-Based COVID-19 Surveillance

Wastewater-based environmental surveillance enables the monitoring of SARS-CoV-2 dynamics within populations, offering critical epidemiological insights. Numerous workflows for tracking SARS-CoV-2 have been developed globally, underscoring the need for interlaboratory comparisons to ensure data cons...

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Main Authors: Arianna Azzellino, Laura Pellegrinelli, Ramon Pedrini, Andrea Turolla, Barbara Bertasi, Sandro Binda, Sara Castiglioni, Clementina E. Cocuzza, Fabio Ferrari, Andrea Franzetti, Maria Giovanna Guiso, Marina Nadia Losio, Marianna Martinelli, Antonino Martines, Rosario Musumeci, Desdemona Oliva, Laura Sandri, Valeria Primache, Francesco Righi, Annalisa Scarazzato, Silvia Schiarea, Elena Pariani, Emanuela Ammoni, Danilo Cereda, Francesca Malpei
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Microorganisms
Subjects:
wastewater environmental surveillance
SARS-CoV2
interlaboratory ring test
detection methods
generalized linear models
Online Access:https://www.mdpi.com/2076-2607/13/3/526
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Summary:Wastewater-based environmental surveillance enables the monitoring of SARS-CoV-2 dynamics within populations, offering critical epidemiological insights. Numerous workflows for tracking SARS-CoV-2 have been developed globally, underscoring the need for interlaboratory comparisons to ensure data consistency and comparability. An inter-calibration test was conducted among laboratories within the network monitoring SARS-CoV-2 in wastewater samples across the Lombardy region (Italy). The test aimed to evaluate data reliability and identify potential sources of variability using robust statistical approaches. Three wastewater samples were analyzed in parallel by four laboratories using identical pre-analytical (PEG-8000-based centrifugation) and analytical processes (qPCR targeting N1/N3 and Orf-1ab). A two-way ANOVA framework within Generalized Linear Models was applied, and multiple pairwise comparisons among laboratories were performed using the Bonferroni post hoc test. The statistical analysis revealed that the primary source of variability in the results was associated with the analytical phase. This variability was likely influenced by differences in the standard curves used by the laboratories to quantify SARS-CoV-2 concentrations, as well as the size of the wastewater treatment plants. The findings of this study highlight the importance of interlaboratory testing in verifying the consistency of analytical determinations and in identifying the key sources of variation.
ISSN:2076-2607

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