– Published in the journal “Science of the Total Environment”.
-The article, signed by CSIC, UVigo and GESECO, reports on the data collected at 11 wastewater treatment plants using an integrated methodology developed for detection, monitoring and prediction. It also reports on the presence of the virus in the marine environment at the plants’ discharge points, which revealed a lower impact of SARS-CoV-2 in seawater, marine sediments and wild and farmed mussels.
-The study, carried out within the DIMCoVAR project, has among its achievements the detection of virus variants and the development of the first dynamic mathematical model that incorporates health data and viral load in wastewater, producing 7-10 day forecasts.
Santiago de Compostela, 9 May 2022. In May 2020, in the midst of the COVID-19 pandemic, the Spanish National Research Council (CSIC), the University of Vigo (UVigo) and GESECO Aguas S.A. launched the “DIMCoVAR” project, funded by the CRUE-Santander Supera COVID Fund.
The overall objective was to determine whether wastewater analysis could detect the virus and predict the evolution of the pandemic in Galicia. The synergy between disciplines (virology, molecular biology, mathematical modelling and engineering) and between public (CSIC and UVigo) and private (GESECO) entities enabled the creation of a team that worked from the outset to provide pandemic managers with a tool to anticipate successive waves of infection.
“The rapid spread of the virus soon revealed the need to develop tools to massively detect its presence in local communities, since these tools, combined with individual detection methods, contributed to SARS-CoV-2 surveillance. The potential of a wastewater epidemiology approach for COVID-19 also soon became clear. Viral load in wastewater was therefore used to detect COVID-19 outbreaks and monitor the evolution of the infected population, and protocols for detecting and quantifying genetic material in wastewater have been increasingly optimised since the beginning of the pandemic,” explains Antonio Figueras, CSIC research professor at the IIM.
“Viral load in wastewater was used to detect COVID-19 outbreaks and monitor the evolution of the infected population and the protocols for detecting genetic material in wastewater.”
Two years after the project began, the CSIC, through the Institute of Marine Research — the Immunology and Genomics and Process Engineering groups — together with the Industrial Biotechnology and Environmental Engineering group of UVigo, GESECO Aguas S.A. and the Information and Communications Technology Research Centre, reports the results achieved.
They do so in the article “Wastewater and marine bioindicators surveillance to anticipate COVID-19 prevalence and to explore SARS-CoV-2 diversity by next generation sequencing: One-year study”, published in Science of the Total Environment.
The article presents the methodology developed for wastewater surveillance of SARS-CoV-2 in Galicia through 11 wastewater treatment plants located in medium-sized municipalities — 2,000-23,000 inhabitants — without hospital discharge: Baiona, Nigrán, Gondomar, Cambados, Moraña, Porto do Son, Muros, Melide, Ares, Cedeira and Noia. In addition, at the request of health authorities, four more plants were included to help control the pandemic: Pobra do Caramiñal, Betanzos, Burela and Viveiro.
Sampling was carried out both at the plants — 1/2 samples per week — and at the discharge point in the marine environment — every two weeks, samples of seawater, marine sediment and bioindicators from wild and farmed mussels. In the latter case, special attention was paid to detecting SARS-CoV-2 in mussels because of their extraordinary water-filtration capacity and their potential to concentrate viral RNA, increasing the probability of detecting viral genetic material.
“The methodology integrates wastewater sampling at the treatment plants under study (at the inlet, outlet effluent and final discharge points), sampling of marine sediments and bioindicators, pretreatment and quantification of biomarkers, RNA detection by RT-qPCR, sequencing of SARS-CoV-2 in wastewater samples, data management through a digital platform and epidemic forecasting using a predictive mechanistic model,” explains Beatriz Novoa, CSIC research professor at the IIM.
This model, developed by the IIM Process Engineering group through Antonio A. Alonso, Irene Otero-Muras and Manuel Pájaro, is the first to incorporate health data and viral load in water. “Through it, we have obtained predictions with 7-10 day horizons in the 11 towns under study. Because it is mechanistic, it also allows us to analyse the effects of different mitigation policies on the evolution of the number of infected people,” explains Irene Otero, who emphasises that “it is a robust and flexible tool that can be adapted for the detection, surveillance and monitoring of the spread of SARS-CoV-2 or other pathogens.”
“Through this mechanism, we have obtained predictions with 7-10 day horizons in the 11 towns under study.”
The viral load in the incoming stream of wastewater treatment plants was used to detect new COVID-19 outbreaks, and wastewater viral-load data combined with data provided by the health system were used to predict the evolution of the pandemic in the municipalities under study over a 7-day horizon.
“The work provides differentiating elements compared with previously published studies, notably the assessment of the fate of the virus in wastewater and marine environments, the evaluation of the efficiency of wastewater treatment plants in removing the virus’s genetic material and the development of a mechanistic model that, by combining health-system data, shows predictive capacity for forecasting the evolution of pandemics at municipal level. In addition, the comprehensive approach that includes variant detection from wastewater samples is an important source of information for monitoring the impact of the pandemic, since we have been able to detect virus variants circulating in the whole population, not only in patients. This is a very valuable tool for following the evolution of the virus,” Beatriz Novoa points out.
“The results confirmed the capacity of wastewater surveillance to track the evolution of the pandemic in Galicia through SARS-CoV-2 wastewater monitoring in a series of representative municipalities. In addition, unlike other studies on the presence of SARS-CoV-2 in wastewater, our study also aimed to explore virus detection in the marine environment and the virus-removal capacity of treatment plants, since Galicia is known for its fishing, shellfish and aquaculture activities. In this respect, the data confirmed the capacity of biological reactors and disinfection systems in wastewater treatment plants to remove the virus. The impact on the marine environment was of lesser importance, and detection of the virus in seawater and in wild and farmed mussels may be associated with uncontrolled wastewater discharges and contamination of the sewer network,” concludes Claudio Cameselle, from the University of Vigo.