Comparison of Different Reverse Transcriptase-Polymerase Chain Reaction-Based Methods for Wastewater Surveillance of SARS-CoV-2: Exploratory Study.

BACKGROUND: Many countries have applied the wastewater surveillance of the COVID-19 pandemic to their national public health monitoring measures. The most used methods for detecting SARS-CoV-2 in wastewater are quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR) and reverse transcriptase-droplet digital polymerase chain reaction (RT-ddPCR). Previous comparison studies have produced conflicting results, thus more research on the subject is required. OBJECTIVE: This study aims to compare RT-qPCR and RT-ddPCR for detecting SARS-CoV-2 in wastewater. It also aimed to investigate the effect of changes in the analytical pipeline, including the RNA extraction kit, RT-PCR kit, and target gene assay, on the results. Another aim was to find a detection method for low-resource settings. METHODS: We compared 2 RT-qPCR kits, TaqMan RT-qPCR and QuantiTect RT-qPCR, and RT-ddPCR based on sensitivity, positivity rates, variability, and correlation of SARS-CoV-2 gene copy numbers in wastewater to the incidence of COVID-19. Furthermore, we compared 2 RNA extraction methods, column- and magnetic-bead-based. In addition, we assessed 2 target gene assays for RT-qPCR, N1 and N2, and 2 target gene assays for ddPCR N1 and E. Reverse transcription strand invasion-based amplification (RT-SIBA) was used to detect SARS-CoV-2 from wastewater qualitatively. RESULTS: Our results indicated that the most sensitive method to detect SARS-CoV-2 in wastewater was RT-ddPCR. It had the highest positivity rate (26/30), and its limit of detection was the lowest (0.06 gene copies/µL). However, we obtained the best correlation between COVID-19 incidence and SARS-CoV-2 gene copy number in wastewater using TaqMan RT-qPCR (correlation coefficient [CC]=0.697, P<.001). We found a significant difference in sensitivity between the TaqMan RT-qPCR kit and the QuantiTect RT-qPCR kit, the first having a significantly lower limit of detection and a higher positivity rate than the latter. Furthermore, the N1 target gene assay was the most sensitive for both RT-qPCR kits, while no significant difference was found between the gene targets using RT-ddPCR. In addition, the use of different RNA extraction kits affected the result when the TaqMan RT-qPCR kit was used. RT-SIBA was able to detect SARS-CoV-2 RNA in wastewater. CONCLUSIONS: As our study, as well as most of the previous studies, has shown RT-ddPCR to be more sensitive than RT-qPCR, its use in the wastewater surveillance of SARS-CoV-2 should be considered, especially if the amount of SARS-CoV-2 circulating in the population was low. All the analysis steps must be optimized for wastewater surveillance as our study showed that all the analysis steps including the compatibility of the RNA extraction, the RT-PCR kit, and the target gene assay influence the results. In addition, our study showed that RT-SIBA could be used to detect SARS-CoV-2 in wastewater if a qualitative result is sufficient.

Wastewater-based surveillance is an efficient monitoring tool for tracking influenza A in the community.

Around the world, influenza A virus has caused severe pandemics, and the risk of future pandemics remains high. Currently, influenza A virus surveillance is based on the clinical diagnosis and reporting of disease cases. In this study, we apply wastewater-based surveillance to monitor the amount of the influenza A virus RNA at the population level. We report the influenza A virus RNA levels in 10 wastewater treatment plant catchment areas covering 40 % of the Finnish population. Altogether, 251 monthly composite influent wastewater samples (collected between February 2021 and February 2023) were analysed from supernatant fraction using influenza A virus specific RT-qPCR method. During the study period, an influenza A virus epidemic occurred in three waves in Finland. This study shows that the influenza A virus RNA can be detected from the supernatant fraction of 24 h composite influent wastewater samples. The influenza A virus RNA gene copy number in wastewater correlated with the number of confirmed disease cases in the Finnish National Infectious Diseases Register. The median Kendall's τ correlation strength was 0.636 (min= 0.486 and max=0.804) and it was statistically significant in all 10 WTTPs. Wastewater-based surveillance of the influenza A virus RNA is an independent from individual testing method and cost-efficiently reflects the circulation of the virus in the entire population. Thus, wastewater monitoring complements the available, but often too sparse, information from individual testing and improves health care and public health preparedness for influenza A virus pandemics.

Developing wastewater-based surveillance schemes for multiple pathogens: The WastPan project in Finland.

Wastewater comprises multiple pathogens and offers a potential for wastewater-based surveillance (WBS) to track the prevalence of communicable diseases. The Finnish WastPan project aimed to establish wastewater-based pandemic preparedness for multiple pathogens (viruses, bacteria, parasites, fungi), including antimicrobial resistance (AMR). This article outlines WastPan's experiences in this project, including the criteria for target selection, sampling locations, frequency, analysis methods, and results communication. Target selection relied on epidemiological and microbiological evidence and practical feasibility. Within the WastPan framework, wastewater samples were collected between 2021 and 2023 from 10 wastewater treatment plants (WWTPs) covering 40 % of Finland's population. WWTP selection was validated for reported cases of Extended Spectrum Beta-lactamase-producing bacterial pathogens (Escherichia coli and Klebsiella pneumoniae) from the National Infectious Disease Register. The workflow included 24-h composite influent samples, with one fraction for culture-based analysis (bacteria and fungi) and the rest of the sample was reserved for molecular analysis (viruses, bacteria, antibiotic resistance genes, and parasites). The reproducibility of the monitoring workflow was assessed for SARS-CoV-2 through inter-laboratory comparisons using the N2 and N1 assays. Identical protocols were applied to same-day samples, yielding similar positivity trends in the two laboratories, but the N2 assay achieved a significantly higher detection rate (Laboratory 1: 91.5 %; Laboratory 2: 87.4 %) than the N1 assay (76.6 %) monitored only in Laboratory 2 (McNemar, p < 0.001 Lab 1, = 0.006 Lab 2). This result indicates that the selection of monitoring primers and assays may impact monitoring sensitivity in WBS. Overall, the current study recommends that the selection of sampling frequencies and population coverage of the monitoring should be based on pathogen-specific epidemiological characteristics. For example, pathogens that are stable over time may need less frequent annual sampling, while those that are occurring across regions may require reduced sample coverage. Here, WastPan successfully piloted WBS for monitoring multiple pathogens, highlighting the significance of one-litre community composite wastewater samples for assessing community health. The infrastructure established for COVID-19 WBS is valuable for monitoring various pathogens. The prioritization of the monitoring targets optimizes resource utilization. In the future legislative support in target selection, coverage determination, and sustained funding for WBS is recomended.