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).
Arora, S
Nag, A
Kalra, A
Sinha, V
Meena, E
Saxena, S
Sutaria, D
Kaur, M
Pamnani, T
Sharma, K
Saxena, S
Shrivastava, SK
Gupta, AB
Li, X
Jiang, G
- Publisher:
- SPRINGER
- Publication Type:
- Journal Article
- Citation:
- Environ Monit Assess, 2022, 194, (5), pp. 342
- Issue Date:
- 2022-04-07
Closed Access
Filename | Description | Size | |||
---|---|---|---|---|---|
Successful application of wastewater-based epidemiology in prediction and monitoring of the second wave of COVID-19 with fra.pdf | Published version | 2.54 MB |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Arora, S | |
dc.contributor.author | Nag, A | |
dc.contributor.author | Kalra, A | |
dc.contributor.author | Sinha, V | |
dc.contributor.author | Meena, E | |
dc.contributor.author | Saxena, S | |
dc.contributor.author | Sutaria, D | |
dc.contributor.author | Kaur, M | |
dc.contributor.author | Pamnani, T | |
dc.contributor.author | Sharma, K | |
dc.contributor.author | Saxena, S | |
dc.contributor.author | Shrivastava, SK | |
dc.contributor.author | Gupta, AB | |
dc.contributor.author |
Li, X |
|
dc.contributor.author | Jiang, G | |
dc.date.accessioned | 2023-04-11T03:05:24Z | |
dc.date.available | 2022-03-12 | |
dc.date.available | 2023-04-11T03:05:24Z | |
dc.date.issued | 2022-04-07 | |
dc.identifier.citation | Environ Monit Assess, 2022, 194, (5), pp. 342 | |
dc.identifier.issn | 0167-6369 | |
dc.identifier.issn | 1573-2959 | |
dc.identifier.uri | http://hdl.handle.net/10453/169523 | |
dc.description.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 (Cl2) disinfection. The average genome concentration in the effluents and removal efficacy of six commonly used treatments, activated sludge process + chlorine disinfection (ASP + Cl2), moving bed biofilm reactor (MBBR) with ultraviolet radiations disinfection (MBBR + UV), MBBR + chlorine (Cl2), sequencing batch reactor (SBR), and SBR + Cl2, were compared with removal efficacy of SBR + Cl2 (81.2%) > MBBR + UV (68.8%) > SBR (57.1%) > ASP (50%) > MBBR + Cl2 (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. | |
dc.format | Electronic | |
dc.language | eng | |
dc.publisher | SPRINGER | |
dc.relation.ispartof | Environ Monit Assess | |
dc.relation.isbasedon | 10.1007/s10661-022-09942-5 | |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.subject.classification | Environmental Sciences | |
dc.subject.mesh | Biofilms | |
dc.subject.mesh | Bioreactors | |
dc.subject.mesh | COVID-19 | |
dc.subject.mesh | Chlorine | |
dc.subject.mesh | Environmental Monitoring | |
dc.subject.mesh | Humans | |
dc.subject.mesh | RNA, Viral | |
dc.subject.mesh | RNA-Dependent RNA Polymerase | |
dc.subject.mesh | SARS-CoV-2 | |
dc.subject.mesh | Wastewater | |
dc.subject.mesh | Wastewater-Based Epidemiological Monitoring | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Biofilms | |
dc.subject.mesh | Chlorine | |
dc.subject.mesh | RNA, Viral | |
dc.subject.mesh | Bioreactors | |
dc.subject.mesh | Environmental Monitoring | |
dc.subject.mesh | Wastewater-Based Epidemiological Monitoring | |
dc.subject.mesh | RNA-Dependent RNA Polymerase | |
dc.subject.mesh | COVID-19 | |
dc.subject.mesh | SARS-CoV-2 | |
dc.subject.mesh | Wastewater | |
dc.subject.mesh | Biofilms | |
dc.subject.mesh | Bioreactors | |
dc.subject.mesh | COVID-19 | |
dc.subject.mesh | Chlorine | |
dc.subject.mesh | Environmental Monitoring | |
dc.subject.mesh | Humans | |
dc.subject.mesh | RNA, Viral | |
dc.subject.mesh | RNA-Dependent RNA Polymerase | |
dc.subject.mesh | SARS-CoV-2 | |
dc.subject.mesh | Wastewater | |
dc.subject.mesh | Wastewater-Based Epidemiological Monitoring | |
dc.title | 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). | |
dc.type | Journal Article | |
utslib.citation.volume | 194 | |
utslib.location.activity | Netherlands | |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering | |
pubs.organisational-group | /University of Technology Sydney/Strength - CTWW - Centre for Technology in Water and Wastewater Treatment | |
utslib.copyright.status | closed_access | * |
dc.date.updated | 2023-04-11T03:05:19Z | |
pubs.issue | 5 | |
pubs.publication-status | Published online | |
pubs.volume | 194 | |
utslib.citation.issue | 5 |
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 (Cl2) disinfection. The average genome concentration in the effluents and removal efficacy of six commonly used treatments, activated sludge process + chlorine disinfection (ASP + Cl2), moving bed biofilm reactor (MBBR) with ultraviolet radiations disinfection (MBBR + UV), MBBR + chlorine (Cl2), sequencing batch reactor (SBR), and SBR + Cl2, were compared with removal efficacy of SBR + Cl2 (81.2%) > MBBR + UV (68.8%) > SBR (57.1%) > ASP (50%) > MBBR + Cl2 (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.
Please use this identifier to cite or link to this item:
Download statistics for the last 12 months
Not enough data to produce graph