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. 2023 Jun;15(2):131-143.
doi: 10.1007/s12560-023-09555-2. Epub 2023 May 3.

Wastewater-Based Epidemiology of SARS-CoV-2: Assessing Prevalence and Correlation with Clinical Cases

Hima Wani  1 , Smita Menon  1   2 , Dipen Desai  1 , Nishita D'Souza  3 , Zarine Bhathena  2 , Nishith Desai  1 , Joan B Rose  3 , Sandhya Shrivastava  4
Affiliations

Wastewater-Based Epidemiology of SARS-CoV-2: Assessing Prevalence and Correlation with Clinical Cases

Hima Wani et al. Food Environ Virol. 2023 Jun.

Abstract

Wastewater-based epidemiology has been recognized as a tool to monitor the progress of COVID-19 pandemic worldwide. The study presented herein aimed at quantitating the SARS-CoV-2 RNA in the wastewaters, predicting the number of infected individuals in the catchment areas, and correlating it with the clinically reported COVID-19 cases. Wastewater samples (n = 162) from different treatment stages were collected from three wastewater treatment plants (WWTPs) from Mumbai city during the 2nd surge of COVID-19 (April 2021 to June 2021). SARS-CoV-2 causing COVID-19, was detected in 76.2% and 4.8% of raw and secondary treated (n = 63 each) wastewater samples respectively while all tertiary treated samples (n = 36) were negative. The quantity of SARS-CoV-2 RNA determined as gene copies/100 mL varied among all the three WWTPs under study. The gene copy numbers thus obtained were further used to estimate the number of infected individuals within the population served by these WWTPs using two published methods. A positive correlation (p < 0.05) was observed between the estimated number of infected individuals and clinically confirmed COVID-19 cases reported during the sampling period in two WWTPs. Predicted infected individuals calculated in this study were 100 times higher than the reported COVID-19 cases in all the WWTPs assessed. The study findings demonstrated that the present wastewater treatment technologies at the three WWTPs studied were adequate to remove the virus. However, SARS-CoV-2 genome surveillance with emphasis on monitoring its variants should be implemented as a routine practice to prepare for any future surge in infections.

Keywords: COVID-19; RT-qPCR; SARS-CoV-2; Surveillance; Wastewater treatment plants; Wastewater-Based Epidemiology.

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Conflict of interest statement

The authors declare no competing interests.

The authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
Location of the three WWTPs of Mumbai city under study
Fig. 2
Fig. 2
Gene copies of SARS-CoV-2 gene targets in 3 WWTP using Box and Whiskers plot. The data represents the average number of SARS-CoV-2 gene copies for N1 gene, ORF-1ab and RdRp gene per 100 mL of sewage sample obtained in the untreated wastewater samples from the Three WWTPs
Fig. 3
Fig. 3
Week-wise trend of mean SARS-CoV-2 gene copies estimated in raw wastewater versus reported COVID-19 cases in the WWTPs served area. A WWTP-Z1 (Colaba), B WWTP-Z3 (Bhandup) and C WWTP-Z5 (Charkop). Bars represent weekly mean SARS-CoV-2 gene copies/100 mL of sewage and Line represents the weekly mean COVID-19 cases for the ward area served by the WWTP
Fig. 4
Fig. 4
Reported and Predicted COVID 19 infected cases across 3 WWTPs. The figure represents mean of week-wise COVID-19 reported cases and predicted infected individuals using Ahmed et al. (2020) and Hemalatha et al. (2021) methods using Wastewater-based Epidemiology approach. The correlation between reported and predicted COVID-19 cases was significant (p < 0.05) among WWTP-Z3 and Z5 and vice-versa
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