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Madhukar MK, Singh N, Iyer VR, Sowpati DT, Tallapaka KB, Mishra RK, Moharir SC. Antimicrobial resistance landscape in a metropolitan city context using open drain wastewater-based metagenomic analysis. ENVIRONMENTAL RESEARCH 2024; 252:118556. [PMID: 38503380 DOI: 10.1016/j.envres.2024.118556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 02/22/2024] [Accepted: 02/24/2024] [Indexed: 03/21/2024]
Abstract
One Health concept recognizes the inextricable interactions of diverse ecosystems and their subsequent effect on human, animal and plant health. Antimicrobial resistance (AMR) is a major One Health concern and is predicted to cause catastrophes if appropriate measures are not implemented. To understand the AMR landscape in a south Indian metropolitan city, metagenomic analysis of open drains was performed. The data suggests that in January 2022, macrolide class of antibiotics contributed the highest resistance of 40.1% in the city, followed by aminoglycoside- 24.4%, tetracycline- 11.3% and lincosamide- 6.7%. The 'mutations in the 23S rRNA gene conferring resistance to macrolide antibiotics' were the major contributor of resistance with a prevalence of 39.7%, followed by '16s rRNA with mutation conferring resistance to aminoglycoside antibiotics'- 22.2%, '16S rRNA with mutation conferring resistance to tetracycline derivatives'- 9.2%, and '23S rRNA with mutation conferring resistance to lincosamide antibiotics'- 6.7%. The most prevalent antimicrobial resistance gene (ARG) 'mutations in the 23S rRNA gene conferring resistance to macrolide antibiotics' was present in multiple pathogens including Escherichia coli, Campylobacter jejuni, Acinetobacter baumannii, Streptococcus pneumoniae, Pseudomonas aeruginosa, Neisseria gonorrhoeae, Klebsiella pneumoniae and Helicobacter pylori. Most of the geographical locations in the city showed a similar landscape for AMR. Considering human mobility and anthropogenic activities, such an AMR landscape could be common across other regions too. The data indicates that pathogens are evolving and acquiring antibiotic resistance genes to evade antibiotics of multiple major drug classes in diverse hosts. The outcomes of the study are relevant not only in understanding the resistance landscape at a broader level but are also important for identifying the resistant drug classes, the mechanisms of gaining resistance and for developing new drugs that target specific pathways. This kind of surveillance protocol can be extended to regions in other developing countries to assess and combat the problem of antimicrobial resistance.
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Affiliation(s)
| | - Nirupama Singh
- Tata Institute for Genetics and Society, Bengaluru, 560065, India
| | - V Rajesh Iyer
- Tata Institute for Genetics and Society, Bengaluru, 560065, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Divya Tej Sowpati
- Centre for Cellular and Molecular Biology, Hyderabad, 500007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Karthik Bharadwaj Tallapaka
- Centre for Cellular and Molecular Biology, Hyderabad, 500007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Rakesh Kumar Mishra
- Tata Institute for Genetics and Society, Bengaluru, 560065, India; Centre for Cellular and Molecular Biology, Hyderabad, 500007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
| | - Shivranjani Chandrashekhar Moharir
- Tata Institute for Genetics and Society, Bengaluru, 560065, India; Centre for Cellular and Molecular Biology, Hyderabad, 500007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
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Acheampong E, Husain AA, Dudani H, Nayak AR, Nag A, Meena E, Shrivastava SK, McClure P, Tarr AW, Crooks C, Lade R, Gomes RL, Singer A, Kumar S, Bhatnagar T, Arora S, Kashyap RS, Monaghan TM. Population infection estimation from wastewater surveillance for SARS-CoV-2 in Nagpur, India during the second pandemic wave. PLoS One 2024; 19:e0303529. [PMID: 38809825 PMCID: PMC11135679 DOI: 10.1371/journal.pone.0303529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 04/26/2024] [Indexed: 05/31/2024] Open
Abstract
Wastewater-based epidemiology (WBE) has emerged as an effective environmental surveillance tool for predicting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease outbreaks in high-income countries (HICs) with centralized sewage infrastructure. However, few studies have applied WBE alongside epidemic disease modelling to estimate the prevalence of SARS-CoV-2 in low-resource settings. This study aimed to explore the feasibility of collecting untreated wastewater samples from rural and urban catchment areas of Nagpur district, to detect and quantify SARS-CoV-2 using real-time qPCR, to compare geographic differences in viral loads, and to integrate the wastewater data into a modified Susceptible-Exposed-Infectious-Confirmed Positives-Recovered (SEIPR) model. Of the 983 wastewater samples analyzed for SARS-CoV-2 RNA, we detected significantly higher sample positivity rates, 43.7% (95% confidence interval (CI) 40.1, 47.4) and 30.4% (95% CI 24.66, 36.66), and higher viral loads for the urban compared with rural samples, respectively. The Basic reproductive number, R0, positively correlated with population density and negatively correlated with humidity, a proxy for rainfall and dilution of waste in the sewers. The SEIPR model estimated the rate of unreported coronavirus disease 2019 (COVID-19) cases at the start of the wave as 13.97 [95% CI (10.17, 17.0)] times that of confirmed cases, representing a material difference in cases and healthcare resource burden. Wastewater surveillance might prove to be a more reliable way to prepare for surges in COVID-19 cases during future waves for authorities.
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Affiliation(s)
- Edward Acheampong
- Department of Statistics and Actuarial Science, University of Ghana, Legon, Accra, Ghana
- School of Mathematical Sciences, University of Nottingham, University Park, Nottingham, United Kingdom
- Food Water Waste Research Group, Faculty of Engineering, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Aliabbas A. Husain
- Research Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS), Nagpur, Maharashtra, India
| | - Hemanshi Dudani
- Research Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS), Nagpur, Maharashtra, India
| | - Amit R. Nayak
- Research Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS), Nagpur, Maharashtra, India
| | - Aditi Nag
- Dr B.Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, India
| | - Ekta Meena
- Dr B.Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, India
| | - Sandeep K. Shrivastava
- Dr B.Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, India
| | - Patrick McClure
- National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
- Queen’s Medical Centre, School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
- Wolfson Centre for Global Virus Research, University of Nottingham, Nottingham, United Kingdom
| | - Alexander W. Tarr
- National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
- Queen’s Medical Centre, School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
- Wolfson Centre for Global Virus Research, University of Nottingham, Nottingham, United Kingdom
| | - Colin Crooks
- National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
- Nottingham Digestive Diseases Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | | | - Rachel L. Gomes
- Food Water Waste Research Group, Faculty of Engineering, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andrew Singer
- UK Centre for Ecology and Hydrology, Wallingford, United Kingdom
| | - Saravana Kumar
- ICMR-National Institute of Epidemiology, Chennai, Tamil Nadu, India
| | - Tarun Bhatnagar
- ICMR-National Institute of Epidemiology, Chennai, Tamil Nadu, India
| | - Sudipti Arora
- Dr B.Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, India
| | - Rajpal Singh Kashyap
- Dr B.Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, India
| | - Tanya M. Monaghan
- National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
- Nottingham Digestive Diseases Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
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3
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Torabi F, Li G, Mole C, Nicholson G, Rowlingson B, Smith CR, Jersakova R, Diggle PJ, Blangiardo M. Wastewater-based surveillance models for COVID-19: A focused review on spatio-temporal models. Heliyon 2023; 9:e21734. [PMID: 38053867 PMCID: PMC10694161 DOI: 10.1016/j.heliyon.2023.e21734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 12/07/2023] Open
Abstract
The evident shedding of the SARS-CoV-2 RNA particles from infected individuals into the wastewater opened up a tantalizing array of possibilities for prediction of COVID-19 prevalence prior to symptomatic case identification through community testing. Many countries have therefore explored the use of wastewater metrics as a surveillance tool, replacing traditional direct measurement of prevalence with cost-effective approaches based on SARS-CoV-2 RNA concentrations in wastewater samples. Two important aspects in building prediction models are: time over which the prediction occurs and space for which the predicted case numbers is shown. In this review, our main focus was on finding mathematical models which take into the account both the time-varying and spatial nature of wastewater-based metrics into account. We used six main characteristics as our assessment criteria: i) modelling approach; ii) temporal coverage; iii) spatial coverage; iv) sample size; v) wastewater sampling method; and vi) covariates included in the modelling. The majority of studies in the early phases of the pandemic recognized the temporal association of SARS-CoV-2 RNA concentration level in wastewater with the number of COVID-19 cases, ignoring their spatial context. We examined 15 studies up to April 2023, focusing on models considering both temporal and spatial aspects of wastewater metrics. Most early studies correlated temporal SARS-CoV-2 RNA levels with COVID-19 cases but overlooked spatial factors. Linear regression and SEIR models were commonly used (n = 10, 66.6 % of studies), along with machine learning (n = 1, 6.6 %) and Bayesian approaches (n = 1, 6.6 %) in some cases. Three studies employed spatio-temporal modelling approach (n = 3, 20.0 %). We conclude that the development, validation and calibration of further spatio-temporally explicit models should be done in parallel with the advancement of wastewater metrics before the potential of wastewater as a surveillance tool can be fully realised.
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Affiliation(s)
- Fatemeh Torabi
- Turing-RSS Health Data Lab, London, UK
- Population Data Science HDRUK-Wales, Medical School, Swansea University, Wales, UK
| | - Guangquan Li
- Turing-RSS Health Data Lab, London, UK
- Applied Statistics Research Group, Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
| | - Callum Mole
- Turing-RSS Health Data Lab, London, UK
- The Alan Turing Institute, London, UK
| | - George Nicholson
- Turing-RSS Health Data Lab, London, UK
- University of Oxford, Oxford, UK
| | - Barry Rowlingson
- Turing-RSS Health Data Lab, London, UK
- CHICAS, Lancaster Medical School, Lancaster University, England, UK
| | | | - Radka Jersakova
- Turing-RSS Health Data Lab, London, UK
- The Alan Turing Institute, London, UK
| | - Peter J. Diggle
- Turing-RSS Health Data Lab, London, UK
- CHICAS, Lancaster Medical School, Lancaster University, England, UK
| | - Marta Blangiardo
- Turing-RSS Health Data Lab, London, UK
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College, London, UK
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Arts PJ, Kelly JD, Midgley CM, Anglin K, Lu S, Abedi GR, Andino R, Bakker KM, Banman B, Boehm AB, Briggs-Hagen M, Brouwer AF, Davidson MC, Eisenberg MC, Garcia-Knight M, Knight S, Peluso MJ, Pineda-Ramirez J, Diaz Sanchez R, Saydah S, Tassetto M, Martin JN, Wigginton KR. Longitudinal and quantitative fecal shedding dynamics of SARS-CoV-2, pepper mild mottle virus, and crAssphage. mSphere 2023; 8:e0013223. [PMID: 37338211 PMCID: PMC10506459 DOI: 10.1128/msphere.00132-23] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 05/03/2023] [Indexed: 06/21/2023] Open
Abstract
Wastewater-based epidemiology (WBE) emerged during the coronavirus disease 2019 (COVID-19) pandemic as a scalable and broadly applicable method for community-level monitoring of infectious disease burden. The lack of high-resolution fecal shedding data for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) limits our ability to link WBE measurements to disease burden. In this study, we present longitudinal, quantitative fecal shedding data for SARS-CoV-2 RNA, as well as for the commonly used fecal indicators pepper mild mottle virus (PMMoV) RNA and crAss-like phage (crAssphage) DNA. The shedding trajectories from 48 SARS-CoV-2-infected individuals suggest a highly individualized, dynamic course of SARS-CoV-2 RNA fecal shedding. Of the individuals that provided at least three stool samples spanning more than 14 days, 77% had one or more samples that tested positive for SARS-CoV-2 RNA. We detected PMMoV RNA in at least one sample from all individuals and in 96% (352/367) of samples overall. CrAssphage DNA was detected in at least one sample from 80% (38/48) of individuals and was detected in 48% (179/371) of all samples. The geometric mean concentrations of PMMoV and crAssphage in stool across all individuals were 8.7 × 104 and 1.4 × 104 gene copies/milligram-dry weight, respectively, and crAssphage shedding was more consistent for individuals than PMMoV shedding. These results provide us with a missing link needed to connect laboratory WBE results with mechanistic models, and this will aid in more accurate estimates of COVID-19 burden in sewersheds. Additionally, the PMMoV and crAssphage data are critical for evaluating their utility as fecal strength normalizing measures and for source-tracking applications. IMPORTANCE This research represents a critical step in the advancement of wastewater monitoring for public health. To date, mechanistic materials balance modeling of wastewater-based epidemiology has relied on SARS-CoV-2 fecal shedding estimates from small-scale clinical reports or meta-analyses of research using a wide range of analytical methodologies. Additionally, previous SARS-CoV-2 fecal shedding data have not contained sufficient methodological information for building accurate materials balance models. Like SARS-CoV-2, fecal shedding of PMMoV and crAssphage has been understudied to date. The data presented here provide externally valid and longitudinal fecal shedding data for SARS-CoV-2, PMMoV, and crAssphage which can be directly applied to WBE models and ultimately increase the utility of WBE.
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Affiliation(s)
- Peter J. Arts
- Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - J. Daniel Kelly
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
- Institute for Global Health Sciences, University of California, San Francisco, California, USA
- Division of Hospital Medicine, UCSF, San Francisco, California, USA
- F.I. Proctor Foundation, University of California, San Francisco, California, USA
| | - Claire M. Midgley
- National Center for Immunizations and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Khamal Anglin
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
- Institute for Global Health Sciences, University of California, San Francisco, California, USA
| | - Scott Lu
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
- Institute for Global Health Sciences, University of California, San Francisco, California, USA
| | - Glen R. Abedi
- National Center for Immunizations and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Raul Andino
- Department of Microbiology and Immunology, UCSF, San Francisco, California, USA
| | - Kevin M. Bakker
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Bryon Banman
- Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Alexandria B. Boehm
- Department of Civil & Environmental Engineering, Stanford University, Stanford, California, USA
| | - Melissa Briggs-Hagen
- National Center for Immunizations and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Andrew F. Brouwer
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Marisa C. Eisenberg
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Sterling Knight
- Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Michael J. Peluso
- Division of HIV, Infectious Disease, and Global Medicine, UCSF, San Francisco, California, USA
| | - Jesus Pineda-Ramirez
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
- Institute for Global Health Sciences, University of California, San Francisco, California, USA
| | - Ruth Diaz Sanchez
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
- Institute for Global Health Sciences, University of California, San Francisco, California, USA
| | - Sharon Saydah
- National Center for Immunizations and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Michel Tassetto
- Department of Microbiology and Immunology, UCSF, San Francisco, California, USA
| | - Jeffrey N. Martin
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
| | - Krista R. Wigginton
- Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan, USA
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5
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Stockdale SR, Blanchard AM, Nayak A, Husain A, Nashine R, Dudani H, McClure CP, Tarr AW, Nag A, Meena E, Sinha V, Shrivastava SK, Hill C, Singer AC, Gomes RL, Acheampong E, Chidambaram SB, Bhatnagar T, Vetrivel U, Arora S, Kashyap RS, Monaghan TM. RNA-Seq of untreated wastewater to assess COVID-19 and emerging and endemic viruses for public health surveillance. THE LANCET REGIONAL HEALTH. SOUTHEAST ASIA 2023; 14:100205. [PMID: 37193348 PMCID: PMC10150210 DOI: 10.1016/j.lansea.2023.100205] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 04/10/2023] [Accepted: 04/24/2023] [Indexed: 05/18/2023]
Abstract
Background The COVID-19 pandemic showcased the power of genomic sequencing to tackle the emergence and spread of infectious diseases. However, metagenomic sequencing of total microbial RNAs in wastewater has the potential to assess multiple infectious diseases simultaneously and has yet to be explored. Methods A retrospective RNA-Seq epidemiological survey of 140 untreated composite wastewater samples was performed across urban (n = 112) and rural (n = 28) areas of Nagpur, Central India. Composite wastewater samples were prepared by pooling 422 individual grab samples collected prospectively from sewer lines of urban municipality zones and open drains of rural areas from 3rd February to 3rd April 2021, during the second COVID-19 wave in India. Samples were pre-processed and total RNA was extracted prior to genomic sequencing. Findings This is the first study that has utilised culture and/or probe-independent unbiased RNA-Seq to examine Indian wastewater samples. Our findings reveal the detection of zoonotic viruses including chikungunya, Jingmen tick and rabies viruses, which have not previously been reported in wastewater. SARS-CoV-2 was detectable in 83 locations (59%), with stark abundance variations observed between sampling sites. Hepatitis C virus was the most frequently detected infectious virus, identified in 113 locations and co-occurring 77 times with SARS-CoV-2; and both were more abundantly detected in rural areas than urban zones. Concurrent identification of segmented virus genomic fragments of influenza A virus, norovirus, and rotavirus was observed. Geographical differences were also observed for astrovirus, saffold virus, husavirus, and aichi virus that were more prevalent in urban samples, while the zoonotic viruses chikungunya and rabies, were more abundant in rural environments. Interpretation RNA-Seq can effectively detect multiple infectious diseases simultaneously, facilitating geographical and epidemiological surveys of endemic viruses that could help direct healthcare interventions against emergent and pre-existent infectious diseases as well as cost-effectively and qualitatively characterising the health status of the population over time. Funding UK Research and Innovation (UKRI) Global Challenges Research Fund (GCRF) grant number H54810, as supported by Research England.
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Affiliation(s)
| | - Adam M. Blanchard
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, United Kingdom
| | - Amit Nayak
- Research Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS), Nagpur, Maharashtra, India
| | - Aliabbas Husain
- Research Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS), Nagpur, Maharashtra, India
| | - Rupam Nashine
- Research Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS), Nagpur, Maharashtra, India
| | - Hemanshi Dudani
- Research Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS), Nagpur, Maharashtra, India
| | - C. Patrick McClure
- National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham University Hospitals National Health Service Trust, Nottingham, United Kingdom
- Wolfson Centre for Global Virus Research, University of Nottingham, Nottingham, United Kingdom
| | - Alexander W. Tarr
- National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham University Hospitals National Health Service Trust, Nottingham, United Kingdom
- Wolfson Centre for Global Virus Research, University of Nottingham, Nottingham, United Kingdom
- Queen's Medical Centre, School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Aditi Nag
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, India
| | - Ekta Meena
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, India
| | - Vikky Sinha
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, India
| | - Sandeep K. Shrivastava
- Centre for Innovation, Research & Development, Dr. B. Lal Clinical Laboratory Pvt. Ltd., Malviya Industrial Area, Malviya Nagar, Jaipur, India
| | - Colin Hill
- APC Microbiome Ireland, University College Cork, Co. Cork, Ireland
| | - Andrew C. Singer
- UK Centre for Ecology and Hydrology, Wallingford, United Kingdom
| | - Rachel L. Gomes
- Food Water Waste Research Group, Faculty of Engineering, University of Nottingham, United Kingdom
| | - Edward Acheampong
- Food Water Waste Research Group, Faculty of Engineering, University of Nottingham, United Kingdom
- Department of Statistics and Actuarial Science, University of Ghana, P.O. Box, LG 115, Legon, Ghana
| | - Saravana B. Chidambaram
- Department of Pharmacology, JSS College of Pharmacy, JSS Academy of Higher Education & Research, Mysuru, 570015, KA, India
| | - Tarun Bhatnagar
- ICMR-National Institute of Epidemiology, Chennai, Tamil Nadu, India
| | - Umashankar Vetrivel
- National Institute of Traditional Medicine, Indian Council of Medical Research, Belagavi, 590010, India
- Virology and Biotechnology Division, ICMR-National Institute for Research in Tuberculosis, Chennai, 600031, India
| | - Sudipti Arora
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, India
| | - Rajpal Singh Kashyap
- Research Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS), Nagpur, Maharashtra, India
| | - Tanya M. Monaghan
- National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham University Hospitals National Health Service Trust, Nottingham, United Kingdom
- Nottingham Digestive Diseases Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
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6
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Javvadi Y, Mohan SV. Understanding the distribution of antibiotic resistance genes in an urban community using wastewater-based epidemiological approach. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 868:161419. [PMID: 36623646 DOI: 10.1016/j.scitotenv.2023.161419] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 01/02/2023] [Accepted: 01/02/2023] [Indexed: 06/17/2023]
Abstract
The study aimed to evaluate the community-wide antimicrobial resistance (AMR) profile of an urban setting using the culture-independent wastewater-based epidemiological surveillance (WBE) approach. The domestic wastewater sample was collected at the converging point of the drain connecting the Sewage Treatment Plant (STP). The collected water sample was evaluated for the presence of 125 antibiotic resistance genes (ARGs) and 13 mobile genetic elements (MGEs, 5 integrons and 8 transposons). Antibiotic residues and the composition of bacterial communities were also examined. Community's sewage showed a diverse resistance pattern, with the positive detection of targeted ARGs, notably aph, aadA1, and strB being particularly abundant. Resistance to aminoglycoside and trimethoprim classes was prevalent, followed by chloramphenicol, sulfonamide, and β-lactams. According to the microbial diversity assessment, Proteobacteria, Bacteroidetes, Firmicutes, and Chloroflexi were abundant phyla observed, while Helicobacteraceae, Pseudomonadaceae, and Moraxellaceae were prevalent families. The study provided comprehensive baseline information of ARGs on a community scale and will be of use for ARG prevention and management.
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Affiliation(s)
- Yamini Javvadi
- Bioengineering and Environmental Science Lab, Department of Energy and Environmental Engineering, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad 500007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - S Venkata Mohan
- Bioengineering and Environmental Science Lab, Department of Energy and Environmental Engineering, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad 500007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
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7
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Szabo D, Marchiandi J, Samandra S, Johnston JM, Mulder RA, Green MP, Clarke BO. High-resolution temporal wastewater treatment plant investigation to understand influent mass flux of per- and polyfluoroalkyl substances (PFAS). JOURNAL OF HAZARDOUS MATERIALS 2023; 447:130854. [PMID: 36701979 DOI: 10.1016/j.jhazmat.2023.130854] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 01/11/2023] [Accepted: 01/21/2023] [Indexed: 06/17/2023]
Abstract
This study aims to identify sources of per- and polyfluoroalkyl substances (PFAS) to wastewater treatment plants (WWTPs) and reveals previously undescribed variability in daily PFAS concentrations by measuring their occurrence in WWTP influent each hour over the course of a week. ∑50PFAS concentrations ranged between 89 ± 38 on Monday and 173 ± 110 ng L-1 on Friday, where perfluoroalkyl carboxylic acids (PFCAs), disubstituted phosphate esters (diPAPs), and perfluoroalkyl sulfonic acids (PFSAs) contributed the largest proportion to overall weekly concentrations 37%, 30%, and 17% respectively. Simultaneous pulse events of perfluorooctanesulfonic acid (PFOS; 400 ng L-1) and perfluoroheptanesulfonic acid (PFHpS; 18 ng L-1) indicate significant industrial or commercial waste discharge that persists for up to 3 h. The minimum number of hourly grab samples required to detect variation of PFOS and PFHpS concentrations are 7 and 9 samples respectively, indicating a high degree of variability in PFAS concentrations between days. Overall, the risk of sampling bias from grab samples is high given the variability in PFAS concentrations and more frequent sampling campaigns must be balanced against the cost of analysis carefully to avoid the mischaracterisation of mass flux to receiving surface waters.
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Affiliation(s)
- Drew Szabo
- Australian Laboratory for Emerging Contaminants, School of Chemistry, University of Melbourne, Victoria 3010, Australia; Department of Materials and Environmental Chemistry, Stockholm University, Stockholm 11418, Sweden
| | - Jaye Marchiandi
- Australian Laboratory for Emerging Contaminants, School of Chemistry, University of Melbourne, Victoria 3010, Australia
| | - Subharthe Samandra
- Australian Laboratory for Emerging Contaminants, School of Chemistry, University of Melbourne, Victoria 3010, Australia
| | - Julia M Johnston
- Australian Laboratory for Emerging Contaminants, School of Chemistry, University of Melbourne, Victoria 3010, Australia
| | - Raoul A Mulder
- School of BioSciences, University of Melbourne, Victoria 3010, Australia
| | - Mark P Green
- School of BioSciences, University of Melbourne, Victoria 3010, Australia
| | - Bradley O Clarke
- Australian Laboratory for Emerging Contaminants, School of Chemistry, University of Melbourne, Victoria 3010, Australia.
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8
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Kisand V, Laas P, Palmik-Das K, Panksep K, Tammert H, Albreht L, Allemann H, Liepkalns L, Vooro K, Ritz C, Hauryliuk V, Tenson T. Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study. WATER RESEARCH 2023; 231:119617. [PMID: 36682239 PMCID: PMC9845016 DOI: 10.1016/j.watres.2023.119617] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 01/09/2023] [Accepted: 01/15/2023] [Indexed: 06/17/2023]
Abstract
Taking advantage of Estonia's small size and population, we have employed wastewater-based epidemiology approach to monitor the spread of SARS-CoV-2, releasing weekly nation-wide updates. In this study we report results obtained between August 2020 and December 2021. Weekly 24 h composite samples were collected from wastewater treatment plants of larger towns already covered 65% of the total population that was complemented up to 40 additional grab samples from smaller towns/villages and the specific sites of concern. The N3 gene abundance was quantified by RT-qPCR. The N3 gene copy number (concentration) in wastewater fluctuated in accordance with the SARS-CoV-2 spread within the total population, with N3 abundance starting to increase 1.25 weeks (9 days) (95% CI: [1.10, 1.41]) before a rise in COVID-19 positive cases. Statistical model between the load of virus in wastewater and number of infected people validated with the Alpha variant wave (B.1.1.17) could be used to predict the order of magnitude in incidence numbers in Delta wave (B.1.617.2) in fall 2021. Targeted testing of student dormitories, retirement and nursing homes and prisons resulted in successful early discovery of outbreaks. We put forward a SARS-CoV-2 Wastewater Index (SARS2-WI) indicator of normalized virus load as COVID-19 infection metric to complement the other metrics currently used in disease control and prevention: dynamics of effective reproduction number (Re), 7-day mean of new cases, and a sum of new cases within last 14 days. In conclusion, an efficient surveillance system that combines analysis of composite and grab samples was established in Estonia. There is considerable discussion how the viral load in wastewater correlates with the number of infected people. Here we show that this correlation can be found. Moreover, we confirm that an increased signal in wastewater is observed before the increase in the number of infections. The surveillance system helped to inform public health policy and place direct interventions during the COVID-19 pandemic in Estonia via early warning of epidemic spread in various regions of the country.
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Affiliation(s)
- Veljo Kisand
- Institute of Technology, University of Tartu, Estonia.
| | - Peeter Laas
- Institute of Technology, University of Tartu, Estonia
| | | | | | - Helen Tammert
- Institute of Technology, University of Tartu, Estonia
| | | | - Hille Allemann
- Estonian Environmental Research Centre, Tallinn, Estonia
| | | | - Katri Vooro
- Estonian Environmental Research Centre, Tallinn, Estonia
| | - Christian Ritz
- Department of Population Health and Morbidity, National Institute of Public Health, University of Southern Denmark, Denmark
| | - Vasili Hauryliuk
- Institute of Technology, University of Tartu, Estonia; Department of Experimental Medical Science, Lund University, Sweden
| | - Tanel Tenson
- Institute of Technology, University of Tartu, Estonia.
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9
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Martins RM, Carvalho T, Bittar C, Quevedo DM, Miceli RN, Nogueira ML, Ferreira HL, Costa PI, Araújo JP, Spilki FR, Rahal P, Calmon MF. Long-Term Wastewater Surveillance for SARS-CoV-2: One-Year Study in Brazil. Viruses 2022; 14:v14112333. [PMID: 36366431 PMCID: PMC9692902 DOI: 10.3390/v14112333] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/26/2022] [Accepted: 10/05/2022] [Indexed: 02/01/2023] Open
Abstract
Wastewater-based epidemiology (WBE) is a tool involving the analysis of wastewater for chemicals and pathogens at the community level. WBE has been shown to be an effective surveillance system for SARS-CoV-2, providing an early-warning-detection system for disease prevalence in the community via the detection of genetic materials in the wastewater. In numerous nation-states, studies have indicated the presence of SARS-CoV-2 in wastewater. Herein, we report the primary time-course monitoring of SARS-CoV-2 RNA in wastewater samples in São José do Rio Preto-SP/Brazil in order to explain the dynamics of the presence of SARS-CoV-2 RNA during one year of the SARS-CoV-2 pandemic and analyze possible relationships with other environmental parameters. We performed RNA quantification of SARS-CoV-2 by RT-qPCR using N1 and N2 targets. The proportion of positive samples for every target resulted in 100% and 96.6% for N1 and N2, respectively. A mean lag of -5 days is observed between the wastewater signal and the new SARS-CoV-2-positive cases reported. A correlation was found between the air and wastewater temperatures and therefore between the SARS-CoV-2 viral titers for N1 and N2 targets. We also observed a correlation between SARS-CoV-2 viral titers and media wastewater flow for the N1 target. In addition, we observed higher viral genome copies within the wastewater samples collected on non-rainy days for the N1 target. Thus, we propose that, based on our results, monitoring raw wastewater may be a broadly applicable strategy that might contribute to resolving the pressing problem of insufficient diagnostic testing; it may represent an inexpensive and early-warning method for future COVID-19 outbreaks, mainly in lower- and middle-income countries.
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Affiliation(s)
- Renan Moura Martins
- Laboratory of Genomic Studies, Institute of Biosciences, Letters and Exact Sciences (IBILCE), São Paulo State University (UNESP), São José do Rio Preto 15054-000, SP, Brazil
| | - Tamara Carvalho
- Laboratory of Genomic Studies, Institute of Biosciences, Letters and Exact Sciences (IBILCE), São Paulo State University (UNESP), São José do Rio Preto 15054-000, SP, Brazil
| | - Cintia Bittar
- Laboratory of Genomic Studies, Institute of Biosciences, Letters and Exact Sciences (IBILCE), São Paulo State University (UNESP), São José do Rio Preto 15054-000, SP, Brazil
| | - Daniela Muller Quevedo
- Institute of Exact and Technological Sciences (ICET), University Feevale, Novo Hamburgo 93525-075, RS, Brazil
| | - Rafael Nava Miceli
- SeMAE-Autonomous Municipal Water and Sewage Service, São José do Rio Preto 15048-000, SP, Brazil
| | - Mauricio Lacerda Nogueira
- Virology Research Laboratory (LPV), Faculty of Medicine of São José do Rio Preto (FAMERP), São José do Rio Preto 15090-000, SP, Brazil
| | - Helena Lage Ferreira
- Applied Preventive Veterinary Medicine Laboratory, Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering (FZEA), University of São Paulo (USP), Pirassununga 13635-900, SP, Brazil
| | - Paulo Inácio Costa
- Department of Clinical Analysis, School of Pharmaceutical Sciences, São Paulo State University (UNESP), Araraquara 14801-360, SP, Brazil
| | - João Pessoa Araújo
- Biotechnology Institute, São Paulo State University (UNESP), Botucatu 18607-440, SP, Brazil
| | - Fernando Rosado Spilki
- Molecular Microbiology Laboratory, University Feevale, Novo Hamburgo 93525-075, RS, Brazil
| | - Paula Rahal
- Laboratory of Genomic Studies, Institute of Biosciences, Letters and Exact Sciences (IBILCE), São Paulo State University (UNESP), São José do Rio Preto 15054-000, SP, Brazil
| | - Marilia Freitas Calmon
- Laboratory of Genomic Studies, Institute of Biosciences, Letters and Exact Sciences (IBILCE), São Paulo State University (UNESP), São José do Rio Preto 15054-000, SP, Brazil
- Correspondence:
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10
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Castro GB, Bernegossi AC, Sousa BJDO, De Lima E Silva MR, Silva FRD, Freitas BLS, Ogura AP, Corbi JJ. Global occurrence of SARS-CoV-2 in environmental aquatic matrices and its implications for sanitation and vulnerabilities in Brazil and developing countries. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2022; 32:2160-2199. [PMID: 34310248 DOI: 10.1080/09603123.2021.1949437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 06/23/2021] [Indexed: 06/13/2023]
Abstract
This paper includes a systematic review of the SARS-CoV-2 occurrence in environmental aquatic matrices and a critical sanitation analysis. We discussed the interconnection of sanitation services (wastewater, water supply, solid waste, and stormwater drainage) functioning as an important network for controlling the spread of SARS-CoV-2 in waters. We collected 98 studies containing data of the SARS-CoV-2 occurrence in aquatic matrices around the world, of which 40% were from developing countries. Alongside a significant number of people infected by the virus, developing countries face socioeconomic deficiencies and insufficient public investment in infrastructure. Therefore, our study focused on highlighting solutions to provide sanitation in developing countries, considering the virus control in waters by disinfection techniques and sanitary measures, including alternatives for the vulnerable communities. The need for multilateral efforts to improve the universal coverage of sanitation services demands urgent attention in a pandemic scenario.
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Affiliation(s)
- Gleyson B Castro
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Aline C Bernegossi
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Bruno José de O Sousa
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
| | | | - Fernando R Da Silva
- Department of Sanitary and Environmental Engineering, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Bárbara Luíza S Freitas
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Allan P Ogura
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
- PPG-SEA and CRHEA/SHS, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Juliano J Corbi
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
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11
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Alhama J, Maestre JP, Martín MÁ, Michán C. Monitoring COVID-19 through SARS-CoV-2 quantification in wastewater: progress, challenges and prospects. Microb Biotechnol 2022; 15:1719-1728. [PMID: 34905659 PMCID: PMC9151337 DOI: 10.1111/1751-7915.13989] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 11/25/2021] [Accepted: 11/26/2021] [Indexed: 12/13/2022] Open
Abstract
Wastewater-Based Epidemiology (WBE) is widely used to monitor the progression of the current SARS-CoV-2 pandemic at local levels. In this review, we address the different approaches to the steps needed for this surveillance: sampling wastewaters (WWs), concentrating the virus from the samples and quantifying them by qPCR, focusing on the main limitations of the methodologies used. Factors that can influence SARS-CoV-2 monitoring in WWs include: (i) physical parameters as temperature that can hamper the detection in warm seasons and tropical regions, (ii) sampling methodologies and timetables, being composite samples and Moore swabs the less variable and more sensitive approaches, (iii) virus concentration methodologies that need to be feasible and practicable in simpler laboratories and (iv) detection methodologies that should tend to use faster and cost-effective procedures. The efficiency of WW treatments and the use of WWs for SARS-CoV-2 variants detection are also addressed. Furthermore, we discuss the need for the development of common standardized protocols, although these must be versatile enough to comprise variations among target communities. WBE screening of risk populations will allow for the prediction of future outbreaks, thus alerting authorities to implement early action measurements.
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Affiliation(s)
- José Alhama
- Department of Biochemistry and Molecular BiologyUniversidad de CórdobaCampus de Excelencia Internacional Agroalimentario CeiA3, Edificio Severo OchoaCórdoba14071Spain
| | - Juan P. Maestre
- Department of Civil, Architectural, and Environmental EngineeringThe University of Texas at Austin301 E. Dean Keeton St., Stop C1786AustinTX78712USA
| | - M. Ángeles Martín
- Department of Inorganic Chemistry and Chemical EngineeringArea of Chemical EngineeringUniversidad de CórdobaInstitute of Fine Chemistry and Nanochemistry (IUNAN)Campus de Excelencia Internacional Agroalimentario CeiA3, Edificio Marie CurieCórdoba14071Spain
| | - Carmen Michán
- Department of Biochemistry and Molecular BiologyUniversidad de CórdobaCampus de Excelencia Internacional Agroalimentario CeiA3, Edificio Severo OchoaCórdoba14071Spain
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12
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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. 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). ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:342. [PMID: 35389102 PMCID: PMC8987519 DOI: 10.1007/s10661-022-09942-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 03/12/2022] [Indexed: 05/09/2023]
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.
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Affiliation(s)
- Sudipti Arora
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, 302017, India.
| | - Aditi Nag
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, 302017, India
| | - Aakanksha Kalra
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, 302017, India
| | - Vikky Sinha
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, 302017, India
| | - Ekta Meena
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, 302017, India
| | - Samvida Saxena
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, 302017, India
| | - Devanshi Sutaria
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, 302017, India
| | - Manpreet Kaur
- Centre for Innovation, Research & Development (CIRD), Dr. B, Lal Clinical Laboratory Pvt. Ltd, Jaipur, India
| | - Tamanna Pamnani
- Centre for Innovation, Research & Development (CIRD), Dr. B, Lal Clinical Laboratory Pvt. Ltd, Jaipur, India
| | - Komal Sharma
- Centre for Innovation, Research & Development (CIRD), Dr. B, Lal Clinical Laboratory Pvt. Ltd, Jaipur, India
| | - Sonika Saxena
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, 302017, India
| | - Sandeep K Shrivastava
- Centre for Innovation, Research & Development (CIRD), Dr. B, Lal Clinical Laboratory Pvt. Ltd, Jaipur, India
| | - A B Gupta
- Department of Civil Engineering, Malaviya National Institute of Technology, Jaipur, India
| | - Xuan Li
- School of Civil, Mining and Environmental Engineering, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
| | - Guangming Jiang
- School of Civil, Mining and Environmental Engineering, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
- Illawarra Health and Medical Research Institute (IHMRI), University of Wollongong, Wollongong, Australia
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13
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Twigg C, Wenk J. Review and Meta‐Analysis: SARS‐CoV‐2 and Enveloped Virus Detection in Feces and Wastewater. CHEMBIOENG REVIEWS 2022. [PMCID: PMC9083821 DOI: 10.1002/cben.202100039] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Detection and quantification of viruses supplies key information on their spread and allows risk assessment for public health. In wastewater, existing detection methods have been focusing on non‐enveloped enteric viruses due to enveloped virus transmission, such as coronaviruses, by the fecal‐oral route being less likely. Since the beginning of the SARS‐CoV‐2 pandemic, interest and importance of enveloped virus detection in wastewater has increased. Here, quantitative studies on SARS‐CoV‐2 occurrence in feces and raw wastewater and other enveloped viruses via quantitative real‐time reverse transcription polymerase chain reaction (RT‐qPCR) during the early stage of the pandemic until April 2021 are reviewed, including statistical evaluation of the positive detection rate and efficiency throughout the detection process involving concentration, extraction, and amplification stages. Optimized and aligned sampling protocols and concentration methods for enveloped viruses, along with SARS‐CoV‐2 surrogates, in wastewater environments may improve low and variable recovery rates providing increased detection efficiency and comparable data on viral load measured across different studies.
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Affiliation(s)
- Charlotte Twigg
- University of Bath Department of Chemical Engineering and Water Innovation and Research Centre (WIRC@Bath) Claverton Down BA2 7AY Bath Somerset United Kingdom
| | - Jannis Wenk
- University of Bath Department of Chemical Engineering and Water Innovation and Research Centre (WIRC@Bath) Claverton Down BA2 7AY Bath Somerset United Kingdom
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14
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Tharak A, Kopperi H, Hemalatha M, Kiran U, C. G. G, Moharir S, Mishra RK, Mohan SV. Longitudinal and Long-Term Wastewater Surveillance for COVID-19: Infection Dynamics and Zoning of Urban Community. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:2697. [PMID: 35270390 PMCID: PMC8910010 DOI: 10.3390/ijerph19052697] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 02/14/2022] [Accepted: 02/21/2022] [Indexed: 02/01/2023]
Abstract
Wastewater-based epidemiology (WBE) is emerging as a potential approach to study the infection dynamics of SARS-CoV-2 at a community level. Periodic sewage surveillance can act as an indicative tool to predict the early surge of pandemic within the community and understand the dynamics of infection and, thereby, facilitates for proper healthcare management. In this study, we performed a long-term epidemiological surveillance to assess the SARS-CoV-2 spread in domestic sewage over one year (July 2020 to August 2021) by adopting longitudinal sampling to represent a selected community (~2.5 lakhs population). Results indicated temporal dynamics in the viral load. A consistent amount of viral load was observed during the months from July 2020 to November 2020, suggesting a higher spread of the viral infection among the community, followed by a decrease in the subsequent two months (December 2020 and January 2021). A marginal increase was observed during February 2021, hinting at the onset of the second wave (from March 2021) that reached it speak in April 2021. Dynamics of the community infection rates were calculated based on the viral gene copies to assess the severity of COVID-19 spread. With the ability to predict the infection spread, longitudinal WBE studies also offer the prospect of zoning specific areas based on the infection rates. Zoning of the selected community based on the infection rates assists health management to plan and manage the infection in an effective way. WBE promotes clinical inspection with simultaneous disease detection and management, in addition to an advance warning signal to anticipate outbreaks, with respect to the slated community/zones, to tackle, prepare for and manage the pandemic.
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Affiliation(s)
- Athmakuri Tharak
- Bioengineering and Environmental Sciences Lab, Department of Energy and Environmental Engineering (DEEE), CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad 500007, India; (A.T.); (H.K.); (M.H.)
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India;
| | - Harishankar Kopperi
- Bioengineering and Environmental Sciences Lab, Department of Energy and Environmental Engineering (DEEE), CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad 500007, India; (A.T.); (H.K.); (M.H.)
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India;
| | - Manupati Hemalatha
- Bioengineering and Environmental Sciences Lab, Department of Energy and Environmental Engineering (DEEE), CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad 500007, India; (A.T.); (H.K.); (M.H.)
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India;
| | - Uday Kiran
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India;
- CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad 500007, India; (G.C.G.); (S.M.)
| | - Gokulan C. G.
- CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad 500007, India; (G.C.G.); (S.M.)
| | - Shivranjani Moharir
- CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad 500007, India; (G.C.G.); (S.M.)
| | - Rakesh K. Mishra
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India;
- CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad 500007, India; (G.C.G.); (S.M.)
| | - S. Venkata Mohan
- Bioengineering and Environmental Sciences Lab, Department of Energy and Environmental Engineering (DEEE), CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad 500007, India; (A.T.); (H.K.); (M.H.)
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India;
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