Successful application of wastewater-based epidemiology in prediction and monitoring of the second wave of COVID-19 with fragmented sewerage systems-a case study of Jaipur (India)

利用污水流行病学成功预测和监测第二波 COVID-19 疫情(以印度斋浦尔为例),该研究以分散的污水处理系统为例。

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Abstract

The present study tracked the city-wide dynamics of severe acute respiratory syndrome-corona virus 2 ribonucleic acids (SARS-CoV-2 RNA) in the wastewater from nine different wastewater treatment plants (WWTPs) in Jaipur during the second wave of COVID-19 out-break in India. A total of 164 samples were collected weekly between February 19th and June 8th, 2021. SARS-CoV-2 was detected in 47.2% (52/110) influent samples and 37% (20/54) effluent samples. The increasing percentage of positive influent samples correlated with the city's increasing active clinical cases during the second wave of COVID-19 in Jaipur. Furthermore, wastewater-based epidemiology (WBE) evidence clearly showed early detection of about 20 days (9/9 samples reported positive on April 20th, 2021) before the maximum cases and maximum deaths reported in the city on May 8th, 2021. The present study further observed the presence of SARS-CoV-2 RNA in treated effluents at the time window of maximum active cases in the city even after tertiary disinfection treatments of ultraviolet (UV) and chlorine (Cl(2)) disinfection. The average genome concentration in the effluents and removal efficacy of six commonly used treatments, activated sludge process + chlorine disinfection (ASP + Cl(2)), moving bed biofilm reactor (MBBR) with ultraviolet radiations disinfection (MBBR + UV), MBBR + chlorine (Cl(2)), sequencing batch reactor (SBR), and SBR + Cl(2), were compared with removal efficacy of SBR + Cl(2) (81.2%) > MBBR + UV (68.8%) > SBR (57.1%) > ASP (50%) > MBBR + Cl(2) (36.4%). The study observed the trends and prevalence of four genes (E, RdRp, N, and ORF1ab gene) based on two different kits and found that prevalence of N > ORF1ab > RdRp > E gene suggested that the effective genome concentration should be calculated based on the presence/absence of multiple genes. Hence, it is imperative to say that using a combination of different detection genes (E, N, RdRp, & ORF1ab genes) increases the sensitivity in WBE.

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