Journal Article Epublish
PubMed: 40142419 DOI: 10.3390/microorganisms13030526
Evaluating Interlaboratory Variability in Wastewater-Based COVID-19 Surveillance.
Microorganisms 13(3)
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
Affiliations
- Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, Italy.
- Department of Biomedical Sciences of Health, University of Milan, 20133 Milan, Italy.
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia-Romagna "B. Ubertini", 25124 Brescia, Italy.
- Department of Environmental Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milan, Italy.
- Department of Medicine and Surgery, University of Milano-Bicocca, 20900 Monza, Italy.
- CAP Holding Spa, 20142 Milan, Italy.
- Department of Earth and Environmental, Sciences-DISAT, University of Milano-Bicocca, 20126 Milan, Italy.
- DG Welfare, Regione Lombardia, 20124 Milan, Italy.
Abstract
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.
MeSH
Laboratories, Covid-19