Wastewater-based epidemiology (WBE) can be used to track the spread of SARS-CoV-2 in a population. This study presents the learning outcomes from over two-year long monitoring of SARS-CoV-2 in Stockholm, Sweden. The three main wastewater treatment plants in Stockholm, with a total of six inlets, were monitored from April 2020 until June 2022 (in total 600 samples). This spans five major SARS-CoV-2 waves, where WBE data provided early warning signals for each wave. Further, the measured SARS-CoV-2 content in the wastewater correlated significantly with the level of positive COVID-19 tests (r = 0.86; p << 0.0001) measured by widespread testing of the population. Moreover, as a proof-of-concept, six SARS-CoV-2 variants of concern were monitored using hpPCR assay, demonstrating that variants can be traced through wastewater monitoring.

Although SARS-CoV-2 levels correlated significantly to the number of positive clinical COVID-19 cases during each respective wave, we detected considerably higher viral loads of SARS-CoV-2 in the wastewater in relation to positive clinical cases during wave 3 and onwards (Fig. 1). It is known that at the beginning of 2021, the variants B.1.1.7 (Alpha), B.1.351 (Beta), and P.1 (Gamma) appeared and became dominant. These variants increased the shedding and transmission (Sandoval Torrientes et al., 2021). Therefore, in addition to the viral load measurements, the identification of the prevalent viral variants at each wave of the pandemic provides additional information of major epidemiological relevance. Here, the identification of SARS-CoV-2 variants in the wastewater samples was performed using a novel hpPCR assay. Thirty-six representative samples, covering the five COVID-19 waves in Stockholm were analyzed by hpPCR. The presence of Alpha, Beta, Delta, Gamma, Kappa, and different Omicron (BA.1, BA.2, BA.4, BA.5, and BA.2.12.1) variants was investigated. Besides targeting the variant-specific regions, the SARS-CoV-2 N-gene and PMMoV were also measured simultaneously in each sample.

First, we compared the calculated N-gene and PMMoV copy number generated by the hpPCR data with our previously generated data based on qPCR. The N and PMMoV genes were detected in all samples using hpPCR and showed a similar semi-quantitative output as the previous qPCR (Fig. S8). Next, we investigated the SARS-CoV-2 variants (Fig. 3). Although the Alpha variant would be expected in the wave 3, we did not detect any variant before week 35,2021. This coincides with the implementation of the higher-yield RNA extraction protocol (Promega), suggesting that the detection of variants may require relatively higher RNA concentrations. The variants that then emerged from the analysis were first Delta appearing in week 37 and becoming dominant (nearly 100 % of detected variants) by week 52,2021. The Delta variant thus preceded wave 4 but did not appear to cause a wave on its own. However, after Omicron BA.1 appeared in week 49, quickly followed by BA.2 (week 51), wave 4 grew into the largest peak to date. Both Omicron variants became dominant by week 3,2022 at the peak of wave 4. While BA.1 disappeared by week 9, BA.2 remained during wave 5 and was still dominant by week 20,2022. Week 20 was the last sampling point for the hpPCR analysis which did not include wave 6, and at this time Omicron BA.4, BA.5, and BA.2.12.1 were not detected in the wastewater of Stockholm by hpPCR (Fig. 3). Thus, hpPCR could semi-quantitatively detect SARS-CoV-2 variants in wastewater samples.

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Perez-Zabaleta et al., Long-term SARS-CoV-2 surveillance in the wastewater of Stockholm: What lessons can be learned from the Swedish perspective?, Science of The Total Environment