Title : Assessment of normalization factors in SARS-CoV-2 trends at four treatment plants: Basis for a wastewater surveillance in Mexico City
Abstract:
Background: The potential of wastewater-based epidemiology (WBE) as a surveillance and early warning tool for the COVID-19 outbreak and antimicrobial resistance has been demonstrated in numerous publications.
Since WBE is an emerging research area, connecting wastewater data to clinical surveillance remains challenging. To gain a better understanding of this phenomenon, we tested whether normalizing SARS-CoV-2 concentrations using biomarkers that measure the relative human fecal contribution could improve analysis to calculating trends of community infection. This study also aimed to assess the necessary conditions to establish a COVID-19 monitoring system in Mexico (one of the places with the highest number of cases in the world during the pandemic) and to develop a predictive model that generates quantitative estimates of the infected population through SARS-CoV-2 loads in wastewater.
Method: Long-term monitoring of SARS-CoV-2 in wastewaters of Mexico City was conducted at four wastewater plant treatment (WWTPs): the biggest WWTP in Latin-American (Atotonilco, 2020-2023), the first- and second-largest WWTPs in Mexico City, and the flag University campus treatment plant (2024) at UNAM. Concentrations of SARS-CoV-2 RNA were quantified by RT-qPCR, along with three fecal virus normalizers: Pepper mild mottle virus (PMMoV), F-specific RNA phages of human genogroup III (FRNAG-III) and Human adenoviruses serotype 41 (HAdVF-41). Linear regression analysis and cross-correlation analysis between viral genome copies and confirmed case data were performed.
Results: The three fecal normalizers included in this study (PMMoV, FRNAG-III, and HAdvF-41) were detected in all samples, regardless of the season. As expected, wastewater tracking showed HAdV-F41 genome copies peaked at different time points from COVID-19, while the other normalizers (PMMoV and FRNAG-III) remained without seasonal variation decreased titers during the rainy season (by fifty and thirty percent respectively) due to dilution. Incorporating flow rate improves the correlation between fecal normalizer concentration data and the estimated population served by each WWTP; however, flow-normalized SARSCoV-2 wastewater concentrations did not produce a strong correlation with COVID-19 cases (R2 =0.2-0.5). Our assessment shows that utilizing flow normalization, along with fecal indicators, to normalize SARS-CoV-2 wastewater concentrations yields stronger correlations between SARS-CoV-2 wastewater concentrations and COVID-19 cases (r=0.78-0.92).
Conclusions: The strongest correlation with reported COVID-19 cases was provided by SARS-CoV-2 wastewater concentrations normalized by flow plus fecal normalizer. FRNA-GIII showing the highest Pearson coefficient (0.92), a viable alternative to PMMoV, which is subject to regional dietary variability. The outcomes of this study provide a basis for improving public health decision-making regarding SARS-CoV-2 circulation in México.
