Evaluating Interlaboratory Variability in Wastewater-Based COVID-19 Surveillance.

Area of Science:

• Environmental science
• Epidemiology
• Molecular biology

Background:

• Wastewater-based surveillance is crucial for monitoring SARS-CoV-2 population dynamics.
• Global development of SARS-CoV-2 tracking workflows necessitates interlaboratory comparisons for data reliability.

Purpose of the Study:

• To assess data consistency and identify variability sources in SARS-CoV-2 wastewater surveillance.
• To evaluate interlaboratory performance using standardized methods.

Main Methods:

• An inter-calibration test involving four laboratories analyzing SARS-CoV-2 in wastewater samples.
• Utilized identical pre-analytical (PEG-8000 centrifugation) and analytical (qPCR) processes.
• Applied two-way ANOVA and Bonferroni post hoc tests for statistical analysis.

Main Results:

• The primary source of data variability was identified in the analytical phase.
• Differences in laboratory standard curves for SARS-CoV-2 quantification and wastewater treatment plant size contributed to variability.
• Interlaboratory comparisons are essential for verifying analytical consistency.

Conclusions:

• Analytical phase variations, particularly standard curves, are key drivers of inconsistency in SARS-CoV-2 wastewater surveillance.
• Standardizing analytical procedures and reference materials is critical for improving data comparability.
• Interlaboratory testing is vital for ensuring the accuracy and reliability of environmental surveillance data.