Comparison of Different PCR Methods for the Detection of SARS-CoV-2 RNA in Wastewater Based on the Reported Incidence of COVID-19 in Finland

The spatial and temporal changes of the COVID-19 pandemic have been monitored with wastewater-based surveillance, which many countries have applied to their national public health monitoring measures. The most commonly used methods for the detection of SARS-CoV-2 in wastewater are RT-qPCR and RT-ddPCR. Previous comparisons of the two methods have produced conflicting results; some found RT-ddPCR to be more sensitive, one found RT-qPCR to be more sensitive, and others found them to be equal in sensitivity. This research was conducted to further study these two methods as well as two different RNA extraction methodologies and gene assays for the detection of SARS-CoV-2 in wastewater. We compared two RT-qPCR kits and RT-ddPCR based on sensitivity, variability, and the correlation of SARS-CoV-2 gene copy numbers in wastewater with the incidence of COVID-19. Our results indicate that the most sensitive and low-variance method to detect SARS-CoV-2 in wastewater was RT-ddPCR. However, we obtained the best correlation between COVID-19 incidence and SARS-CoV-2 gene copy number in wastewater using RT-qPCR (CC = 0.697, p < 0.001). We found a significant difference in sensitivity between the two RT-qPCR kits, one having a significantly lower limit of detection and a higher percentage of positive samples than the other. Furthermore, the CDC N1 primers and probe were the most sensitive for both RT-qPCR kits, while there was no significant difference between the tested gene targets using RT-ddPCR. For the most sensitive RT-qPCR, the use of different RNA extraction kits affected the result. All methods showed a trend between COVID-19 incidence and SARS-CoV-2 gene copy numbers in wastewater. In addition, we tested an isothermal amplification method for the detection of SARS-CoV-2 RNA in wastewater. It proved to be a viable option if results are expected quickly, resources are limited, and presence–absence information is sufficient. Highlights ![Figure][1] Created with [BioRender.com][2] ### Competing Interest Statement Sami Oikarinen reports a relationship with Greenseq Ltd that includes: board membership. Kirsi-Maarit Lehto reports a relationship with Greenseq Ltd that includes: board membership and travel reimbursement. ### Funding Statement This work was funded by Academy of Finland, grant number 339416 ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The data was retrieved from the Finnish National Infectious Diseases register: https://sampo.thl.fi/pivot/prod/fi/ttr/shp/fact_shp The National Institute of Health and Welfare gave us their permission to use the data. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors * GC : gene copy WBS : wastewater-based surveillance WWTP : wastewater treatment plant RT-SIBA : reverse transcription strand invasion based amplification [1]: pending:yes [2]: http://BioRender.com