The Catalan Surveillance Network of SARS-CoV-2 in Sewage: design, implementation, and performance

Abstract

Wastewater-based epidemiology has shown to be an efficient tool to track the circulation of SARS-CoV-2 in communities assisted by wastewater treatment plants (WWTPs). The challenge comes when this approach is employed to help Health authorities in their decision-making. Here, we describe the roadmap for the design and deployment of SARSAIGUA, the Catalan Surveillance Network of SARS-CoV-2 in Sewage. The network monitors, weekly or biweekly, 56 WWTPs evenly distributed across the territory and serving 6 M inhabitants (80% of the Catalan population). Each week, samples from 45 WWTPs are collected, analyzed, results reported to Health authorities, and finally published within less than 72 h in an online dashboard ( https://sarsaigua.icra.cat ). After 20 months of monitoring (July 20-March 22), the standardized viral load (gene copies/day) in all the WWTPs monitored fairly matched the cumulative number of COVID-19 cases along the successive pandemic waves, showing a good fit with the diagnosed cases in the served municipalities (Spearman Rho = 0.69). Here we describe the roadmap of the design and deployment of SARSAIGUA while providing several open-access tools for the management and visualization of the surveillance data.

Figure 1

Map showing the location, the assisted population, and the sampling frequency of the 56 WWTPs finally selected within SARSAIGUA. Population density is shown using a grid with a resolution of 0.25 km. Population density information was obtained from the Global Human Settlement Population Grid 2015 (European Joint Research Center, https://ghsl.jrc.ec.europa.eu/ghs_pop.php). The main map has been built using QGIS 3.22 (https://www.qgis.org/en/site/) and county limits obtained from the Cartographic and Geological Institute of Catalonia (https://www.icgc.cat/ca/Descarregues/Cartografia-vectorial/Divisions-administratives). The upper map has been obtained from the ArcGIS Hub using ESRI data (https://hub.arcgis.com/datasets/esri::world-countries-generalized).

Figure 2

Images retrieved from the SARSAIGUA dashboard showing (A) the absolute abundance of SARS-COV-2 (in GC/L) at the monitored WWTP, and (B) weekly trends calculated at each monitored WWTP. For each WWTP, the temporal dynamics of its viral load and reported clinical cases in the assisted municipalities can also be displayed (C). Maps in the online dashboard were obtained from OpenStreetMap (https://www.openstreetmap.org/).

Figure 3

Communication pipeline of SARSAIGUA.

Figure 4

Timeline of SARS-CoV-2 standardized load in sewage (red) and diagnosed COVID-19 cases (blue) for each sampling data across all WWTP monitored. Shadowed ribbons represent the correspondent standard deviation values for each sampling date. The standard deviation values for each sampling date were smoothed using a rolling average with a window of 3 observations. The bottom plots show the same timeline when segregating viral loads and cases for large (> 150.000 inhabitants, left) and small (< 150.000 inhabitants, right) WWTPs. Values of Spearman Rho correlation coefficients are also shown. Case data have been obtained from the Information Systems of the Department of Health and the Catalan Health Service.