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.