| Autor: |
Belmonte-Lopes, Ricardo, Barquilha, Carlos E. R., Kozak, Caroline, Barcellos, Demian S., Leite, Bárbara Z., da Costa, Fernanda J. O. Gomes, Martins, William L., Oliveira, Pâmela E., Pereira, Edy H. R. A., Filho, Cesar R. Mota, de Souza, Emanuel M., Possetti, Gustavo R. C., Vicente, Vania A., Etchepare, Ramiro G. |
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| Zdroj: |
Environmental Science & Pollution Research; Jul2023, Vol. 30 Issue 31, p76687-76701, 15p |
| Abstrakt: |
The COVID-19 pandemic resulted in the collapse of healthcare systems and led to the development and application of several approaches of wastewater-based epidemiology to monitor infected populations. The main objective of this study was to carry out a SARS-CoV-2 wastewater based surveillance in Curitiba, Southern Brazil Sewage samples were collected weekly for 20 months at the entrance of five treatment plants representing the entire city and quantified by qPCR using the N1 marker. The viral loads were correlated with epidemiological data. The correlation by sampling points showed that the relationship between the viral loads and the number of reported cases was best described by a cross-correlation function, indicating a lag between 7 and 14 days amidst the variables, whereas the data for the entire city presented a higher correlation (0.84) with the number of positive tests at lag 0 (sampling day). The results also suggest that the Omicron VOC resulted in higher titers than the Delta VOC. Overall, our results showed that the approach used was robust as an early warning system, even with the use of different epidemiological indicators or changes in the virus variants in circulation. Therefore, it can contribute to public decision-makers and health interventions, especially in vulnerable and low-income regions with limited clinical testing capacity. Looking toward the future, this approach will contribute to a new look at environmental sanitation and should even induce an increase in sewage coverage rates in emerging countries. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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