Wastewater surveillance could prove to be an effective system for monitoring COVID-19 prevalence and act as an early warning system for predicting upcoming outbreaks. See below for general introduction to wastewater epidemiology.
This dashboard presents wastewater epidemiology data from various Swedish cities which have a total population of over 3 million people. The data presented here originates from analyses conducted by the two wastewater laboratories of SEEC (The Swedish Environmental Epidemiology Center), a pandemic laboratory preparedness resource project within SciLifeLab’s Pandemic Preparedness Programme. Samples are analysed in two nodes of SEEC:
SEEC-SLU: Samples from multiple sites, including Uppsala, Örebro, and Umeå, among others, are analysed at the Swedish University of Agricultural Sciences node led by associate professor Anna J. Székely (firstname.lastname@example.org) and associate professor Maja Malmberg (email@example.com).
SEEC-KTH: Samples from Stockholm and Malmö are analysed at the KTH Royal Institute of Technology node led by associate professor Zeynep Cetecioglu Gurol (firstname.lastname@example.org).
Note that there are slight differences between the methods of the two laboratories, which have to be considered when comparing the data generated by them. To correct for variations in population size and wastewater flow, both groups quantify the pepper mild mottle virus (PMMoV) using a modified version of the assay of Zhang et al. (2006). PMMoV is an abundant RNA virus in human feces and serves as an estimator of human fecal content (Symonds et al., 2019). However, for the quantification of SARS-CoV-2, the SEEC-SLU laboratory uses the SARS-CoV-2 specific N1 assay from the Centers for Disease Control and Prevention (CDC), while the SEEC-KTH laboratory uses the SARS-like virus specific N3-primers (Lu et al., 2020) with SYBR Green chemistry (Perez-Zabaleta et al., 2023). Furthermore, differences in the wastewater collection systems and populations of different cities might bias the direct comparison between cities measured even with the same method.
Map of sample collection sites
Monitoring by SEEC-SLU
This project is led by associate professor Anna J. Székely (SLU, Swedish University of Agricultural Sciences) and associate professor Maja Malmberg (SLU, Swedish University of Agricultural Sciences).
The regular wastewater monitoring by this group started in Uppsala in August 2020, while other places joined the program later. For all places, raw, untreated wastewater samples representative of a single day (24 hours) are collected by flow compensated samplers. All measurements represent only 1 day except for Uppsala. For Uppsala, all measurements since week 16 of 2021 instead represent 1 week, as samples are collected each day and then combined flow-proportionally into 1 composite weekly sample.
The samples are processed according to standard methods. Briefly, the viral genomic material is concentrated and extracted by the direct capture method using the Maxwell RSC Enviro TNA kit (Promega) and the copy number of SARS-CoV-2 genomes is quantified by RT-qPCR using the CDC RUO nCOV N1 assay (IDT DNA). To correct for variations in population size and wastewater flow, we also quantify the pepper mild mottle virus (PMMoV) which is the most abundant RNA virus in human feces and serves as an estimator of human fecal content (Symonds et al., 2019). For more about the evaluation of this normalisation method, please consult the corresponding publication: Isaksson et al. (2022). The data is presented on the graph as the ratio of the copy numbers measured by the N1 and PMMoV-assays multiplied by 10^4. As N1 copy number is a proxy for SARS-CoV-2 virus content in the wastewater and PMMoV is a proxy of the fecal content, which is related to the contributing population, this ratio can be considered as proxy of the prevalence of infections in the population of the wastewater catchment area.
Note that the scores provided in the dataset and depicted in plots below are preliminary. The team is still conducting method efficiency checks that might slightly affect the final results.
Download the data: N1-gene copy number per PMMoV gene copy number, CSV file. Data available starting from week 38 of 2020; updated weekly.
Contact: email@example.com and firstname.lastname@example.org
How to cite method:
Isaksson, F., Lundy, L., Hedström, A., Székely, A. J., Mohamed, N. (2022). Evaluating the Use of Alternative Normalization Approaches on SARS-CoV-2 Concentrations in Wastewater: Experiences from Two Catchments in Northern Sweden. Environments, 9, 39. https://doi.org/10.3390/environments9030039.
How to cite dataset:
Székely, A. J., Mohamed, N., Dafalla, I., Vargas, J., Malmberg, M. (2021). Dataset of SARS-CoV-2 wastewater data from Uppsala, Umeå, Örebro, Kalmar, and various towns in Uppsala and Stockholm region, Sweden. https://doi.org/10.17044/scilifelab.14256317.
Important note: Historical data for Knivsta, Vaxholm, and Österåker is available in the dataset linked above. However, they are no longer included in the visualisations below.
Please note that the plot below displays the same data, but the y axis is shown as a log scale.
SEEC-KTH: Samples from Stockholm and Malmö
This project, led by associate professor Zeynep Cetecioglu Gurol and colleagues (KTH Royal Institute of Technology; email@example.com), is a collaboration between the SciLifeLab COVID-19 National Research Program and the SEED and Chemical Engineering departments at KTH.
Analysis of wastewater samples from Stockholm takes place in close collaboration with Stockholm Vatten och Avfall and the Käppala Association. The sampling of wastewater started in mid-April 2020 from Bromma, Henriksdal, and Käppala wastewater treatment plants. These plants receive wastewater from a population of approximately 360,000; 860,000 and 500,000, respectively. Please consult this map for the exact catchment area of the wastewater collection channels in Käppala and this map for the exact catchment area of the wastewater collection channels in Bromma and Henriksdal.
Wastewater sample collection from the Sjölunda wastewater treatment plant in Malmö started from week 39 of 2021. This plant processes water from the larger part of Malmö as well as from Burlöv municipanity and parts of Lomma, Staffanstorp, and Svedala municipalities. In total, there are around 300 000 people living in the catchment area of this wastewater treatment plant. See a map of the catchment area and information in this PDF.
After concentration, filtering, and preparation, the samples are analysed using qPCR technique for SARS CoV-2 RNA. Primers of the nucleocapsid (N) gene were used to detect the SARS-COV-2 gene (previously used and verified by Medema et al. (2020)). In some cases, the raw wastewater has been frozen at –20 degrees, and concentrated wastewater or purified RNA have been stored at -80 C before the next analysis step was carried out. The concentration method used by prof. Zeynep Cetecioglu Gurol and her colleagues from the beginning of the project until week 35 of 2021 was based on their published study (Jafferali et al., 2021) comparing four different concentration methods. From week 35 of 2021, the group is using the Promega kit for the concentration step.
Download the data: N3-gene copy number per PMMoV gene copy number; Excel file. Results are available (partially) starting from week 16 of 2020 for Stockholm and starting from week 39 of 2021 for Malmö; updated weekly.
How to cite dataset: Cetecioglu, Z. G., Williams, C., Khatami, K., Atasoy, M., Nandy, P., Jafferali, M. H., Birgersson, M. (2021). SARS-CoV-2 Wastewater Data from Stockholm, Sweden. https://doi.org/10.17044/scilifelab.14315483.
Please note that the plot below displays the same data, but the y axis is shown as a log scale and only data starting from January 2021 is displayed.
- Historic data for Örebro and Umeå; amount of SARS-CoV-2 in Umeå and Örebro wastewater between October 2020 and June 2021.
- Historic data for Stockholm; Gene copy number/week (raw wastewater) with bovine + PMMoV factor between April 2020 and August 2021
Background: Wastewater-based epidemiology
SARS-CoV-2 virus genome can be detected in feces samples from COVID-19 patients using polymerase chain reaction (PCR) (see, for example, Wu et al. (2020)). Monitoring of SARS CoV-2 virus levels in wastewater from communities could therefore provide early surveillance of disease prevalence at a population-wide level, referred to as wastewater-based epidemiology (Corpuz et al., 2020).
Wastewater-based epidemiology studies the amount of virus genome present in the wastewater, measured using PCR technology. Waste water, also referred too as “sewage,” includes water from households or building, kitchen sinks, toilets, showers. However, it could also include water from non-household sources (for example, rainwater and water from industrial use). Samples are periodically taken at wastewater treatment facilities, allowing to make comparisons of the viral load over time. It has previously been shown that the SARS CoV-2 virus content in wastewater can predict increases in infection in the population and follows the epidemic trend measured by the number of COVID-19 cases and hospitalisation rate (see Peccia et al. (2020)). During the COVID-19 pandemic, surveillance of viral RNA levels in waste water has become increasingly used to monitor and predict the spread of the disease.
Please note that the graphs presented on this page are based on preliminary and not yet completely evaluated data. The shared data should therefore be used with caution. Note also that because different sample collection and data analysis methods are used in different research projects below (i.e. for different cities), it is not possible to make comparisons of viral load across these projects (i.e. across cities). Comparisons should be made within each project (i.e. city) since the methodology remains the same for different weeks of measurement. Wastewater monitoring should primarily be seen as a monitoring system. Taken together with data for infection testing, intensive care admissions etc., it may help understanding of the regional dynamics of the COVID-19 pandemic.