Simplifying SARS-CoV-2 wastewater-based surveillance using an automated FDA EUA assay

Area of Science:

• Environmental microbiology
• Public health surveillance
• Molecular diagnostics

Background:

• Wastewater-based surveillance (WBS) is crucial for tracking infectious disease spread.
• Traditional WBS methods for SARS-CoV-2 are labor-intensive and time-consuming.
• Automated diagnostic assays offer potential for more efficient testing.

Purpose of the Study:

• To assess the feasibility of using an automated FDA EUA SARS-CoV-2 assay for WBS.
• To compare the performance of an automated assay with established laboratory-developed tests (LDTs).
• To evaluate the workflow efficiency and sample stability for automated WBS.

Main Methods:

• Collected 103 wastewater samples from seven municipalities over six months.
• Tested fresh supernatant with an automated Abbott RealTime SARS-CoV-2 assay (FDA EUA).
• Compared results with two polyethylene glycol (PEG) concentrated LDTs after freeze-thaw cycles.

Main Results:

• All three methods successfully detected SARS-CoV-2 viral RNA.
• The automated assay showed comparable results to LDTs, with minimal bias (-0.13 to -0.42 log copies/mL).
• Measurable viral RNA decreased by 33.9% after three freeze-thaw cycles.

Conclusions:

• An automated FDA EUA SARS-CoV-2 assay is feasible for WBS.
• This automated method offers a more efficient workflow, saving time and labor.
• Further validation is needed to confirm its quantitative accuracy for SARS-CoV-2 RNA in wastewater.