Surveillance of SARS-CoV-2 in wastewater by quantitative PCR and digital PCR: a case study in Shijiazhuang city, Hebei province, China

ABSTRACT

In this study, we reported the first long-term monitoring of SARS-CoV-2 in wastewater in Mainland China from November 2021 to October 2023. The city of Shijiazhuang was employed for this case study. We developed a triple reverse transcription droplet digital PCR (RT-ddPCR) method using triple primer-probes for simultaneous detection of the N1 gene, E gene, and Pepper mild mottle virus (PMMoV) to achieve accurate quantification of SARS-CoV-2 RNA in wastewater. Both the RT-ddPCR method and the commercial multiplex reverse transcription quantitative polymerase chain reaction (RT-qPCR) method were implemented for the detection of SARS-CoV-2 in wastewater in Shijiazhuang City over a 24-month period. Results showed that SARS-CoV-2 was detected for the first time in the wastewater of Shijiazhuang City on 10 November 2022. The peak of COVID-19 cases occurred in the middle of December 2022, when the concentration of SARS-CoV-2 in the wastewater was highest. The trend of virus concentration increases and decreases forming a “long-tailed” shape in the COVID-19  outbreak and recession cycle. The results indicated that both multiplex RT-ddPCR and RT-qPCR are effective in detecting SARS-CoV-2 in wastewater, but RT-ddPCR is capable of detecting low concentrations of SARS-CoV-2 in wastewater which is more efficient. The SARS-CoV-2 abundance in wastewater is correlated to clinical data, outlining the public health utility of this work.

Highlights

• First long-term monitoring of SARS-CoV-2 in wastewater in Mainland China

• COVID-19 outbreak was tracked in Shijiazhuang City from outbreak to containment

• Wastewater was monitored simultaneously using RT-ddPCR and RT-qPCR methods

• Triple primer-probe RT-ddPCR detects N1 and E genes of SARS-CoV-2 and PMMoV

GRAPHICAL ABSTRACT

KEYWORDS:

• Wastewater
• monitoring
• SARS-CoV-2
• COVID-19
• RT-ddPCR

Acknowledgements

We thank LetPub (www.letpub.com) for linguistic assistance and pre-submission expert review.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Key Research and Development Program of Hebei Province [grant numbers 21377727D, 20277723D].