51
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Girón-Guzmán I, Díaz-Reolid A, Truchado P, Carcereny A, García-Pedemonte D, Hernáez B, Bosch A, Pintó RM, Guix S, Allende A, Alcamí A, Pérez-Cataluña A, Sánchez G. Spanish wastewater reveals the current spread of Monkeypox virus. WATER RESEARCH 2023; 231:119621. [PMID: 36693290 PMCID: PMC9845017 DOI: 10.1016/j.watres.2023.119621] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 12/01/2022] [Accepted: 01/15/2023] [Indexed: 05/09/2023]
Abstract
Besides nasopharyngeal swabs, monkeypox virus (MPXV) DNA has been detected in a variety of samples such as saliva, semen, urine and fecal samples. Using the environmental surveillance network previously developed in Spain for the routine wastewater surveillance of SARS-CoV-2 (VATar COVID-19), we have analyzed the presence of MPXV DNA in wastewater from different areas of Spain. Samples (n = 312) from 24 different wastewater treatment plants were obtained between May 9 (week 19 of 2022) and August 4 (week 31 of 2022). Following concentration of viral particles by a validated aluminum adsorption-precipitation method, a qPCR procedure allowed us to detect MPXV DNA in 56 wastewater samples collected from May 16 to August 4, 2022, with values ranging between 2.2 × 103 to 8.7 × 104 genome copies (gc)/L. This study shows that MPXV DNA can be reproducibly detected by qPCR in longitudinal samples collected from different Spanish wastewater treatment plants. According to data from the National Epidemiological Surveillance Network (RENAVE) in Spain a total of 6,119 cases have been confirmed as of August 19, 2022. However, and based on the wastewater data, the reported clinical cases seem to be underestimated and asymptomatic infections may be more frequent than expected.
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Affiliation(s)
- Inés Girón-Guzmán
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, Avda. Catedrático Agustín Escardino 7, Valencia, Paterna 46980, Spain
| | - Azahara Díaz-Reolid
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, Avda. Catedrático Agustín Escardino 7, Valencia, Paterna 46980, Spain
| | - Pilar Truchado
- Department of Food Science and Technology, CEBAS-CSIC, Research Group on Quality and Safety of Fruits and Vegetables, Campus Universitario de Espinardo, 25, Murcia 30100, Spain
| | - Albert Carcereny
- Enteric Virus Laboratory, Department of Genetics, Microbiology, and Statistics, Section of Microbiology, Virology, and Biotechnology, School of Biology, University of Barcelona, Barcelona, Spain
| | - David García-Pedemonte
- Enteric Virus Laboratory, Department of Genetics, Microbiology, and Statistics, Section of Microbiology, Virology, and Biotechnology, School of Biology, University of Barcelona, Barcelona, Spain
| | - Bruno Hernáez
- Molecular Biology Center Severo Ochoa, CSIC-UAM, Campus de Cantoblanco, Nicolás Cabrera 1, 28049 Madrid, Spain
| | - Albert Bosch
- Enteric Virus Laboratory, Department of Genetics, Microbiology, and Statistics, Section of Microbiology, Virology, and Biotechnology, School of Biology, University of Barcelona, Barcelona, Spain
| | - Rosa María Pintó
- Enteric Virus Laboratory, Department of Genetics, Microbiology, and Statistics, Section of Microbiology, Virology, and Biotechnology, School of Biology, University of Barcelona, Barcelona, Spain
| | - Susana Guix
- Enteric Virus Laboratory, Department of Genetics, Microbiology, and Statistics, Section of Microbiology, Virology, and Biotechnology, School of Biology, University of Barcelona, Barcelona, Spain
| | - Ana Allende
- Department of Food Science and Technology, CEBAS-CSIC, Research Group on Quality and Safety of Fruits and Vegetables, Campus Universitario de Espinardo, 25, Murcia 30100, Spain
| | - Antonio Alcamí
- Molecular Biology Center Severo Ochoa, CSIC-UAM, Campus de Cantoblanco, Nicolás Cabrera 1, 28049 Madrid, Spain
| | - Alba Pérez-Cataluña
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, Avda. Catedrático Agustín Escardino 7, Valencia, Paterna 46980, Spain.
| | - Gloria Sánchez
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, Avda. Catedrático Agustín Escardino 7, Valencia, Paterna 46980, Spain.
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52
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Jamil K, Abdulrazack N, Fakhraldeen S, Kumar V, Al-Subiai S, Al-Aati T, Kamal H, Husain F, Ahmed I, Hussein I. Detection of pathogenic viruses in the urban wastewater in Kuwait-implications for monitoring viral disease outbreaks. ENVIRONMENTAL MONITORING AND ASSESSMENT 2023; 195:406. [PMID: 36792849 PMCID: PMC9931561 DOI: 10.1007/s10661-023-10986-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 01/28/2023] [Indexed: 06/18/2023]
Abstract
Effective surveillance for epidemic-prone viral diseases is essential for emergency preparedness to respond to threats and occurrences of pandemics. While it is difficult and expensive to conduct health facility-based surveillance, there is a growing interest in conducting sewage-based epidemiological studies to monitor the health of the urban population because of the relative ease of sample collection and the availability of advanced molecular techniques for the detection of pathogens in the sewage. Sewage samples offer unique means to study the aggregate health of the population as opposed to the monitoring of the health of any individual by traditional methods. We worked together with the Ministry of Public Works in Kuwait and developed a platform for the collection and testing of sewage samples from different regions of Kuwait for studying population health. In this report, we describe the results of a cross-sectional study conducted between 16 and 23 September 2019 in an attempt to detect influenza, Noro, Rota, hepatitis A, and hepatitis E viruses in urban sewage samples collected in Kuwait. All five targeted viruses were detected in the samples collected from urban wastewater in Kuwait using reverse-transcriptase quantitative PCR (RT-qPCR). We recently checked for the presence of SARS-CoV-2 in the stored cDNA samples and confirmed the absence of SARS-CoV-2 in them. This is the first report that demonstrates the preparedness in Kuwait for using sewage samples for the detection and monitoring of many pathogenic viruses which may greatly increase the capacity of the country to deal with a viral disease outbreak in the future.
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Affiliation(s)
- Kazi Jamil
- Kuwait Institute for Scientific Research, Kuwait City, Kuwait.
| | | | | | - Vinod Kumar
- Kuwait Institute for Scientific Research, Kuwait City, Kuwait
| | | | - Tareq Al-Aati
- Kuwait Institute for Scientific Research, Kuwait City, Kuwait
| | - Hebah Kamal
- Kuwait Institute for Scientific Research, Kuwait City, Kuwait
| | - Farhana Husain
- Kuwait Institute for Scientific Research, Kuwait City, Kuwait
| | - Imtiaz Ahmed
- Kuwait Institute for Scientific Research, Kuwait City, Kuwait
| | - Islam Hussein
- Microbiotix, Inc., One Innovation Drive, Worcester, MA, 01605, USA
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53
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Farkas K, Pellett C, Williams R, Alex-Sanders N, Bassano I, Brown MR, Denise H, Grimsley JMS, Kevill JL, Khalifa MS, Pântea I, Story R, Wade MJ, Woodhall N, Jones DL. Rapid Assessment of SARS-CoV-2 Variant-Associated Mutations in Wastewater Using Real-Time RT-PCR. Microbiol Spectr 2023; 11:e0317722. [PMID: 36629447 PMCID: PMC9927140 DOI: 10.1128/spectrum.03177-22] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 12/11/2022] [Indexed: 01/12/2023] Open
Abstract
Within months of the COVID-19 pandemic being declared on March 20, 2020, novel, more infectious variants of SARS-CoV-2 began to be detected in geospatially distinct regions of the world. With international travel being a lead cause of spread of the disease, the importance of rapidly identifying variants entering a country is critical. In this study, we utilized wastewater-based epidemiology (WBE) to monitor the presence of variants in wastewater generated in managed COVID-19 quarantine facilities for international air passengers entering the United Kingdom. Specifically, we developed multiplex reverse transcription quantitative PCR (RT-qPCR) assays for the identification of defining mutations associated with Beta (K417N), Gamma (K417T), Delta (156/157DEL), and Kappa (E154K) variants which were globally prevalent at the time of sampling (April to July 2021). The assays sporadically detected mutations associated with the Beta, Gamma, and Kappa variants in 0.7%, 2.3%, and 0.4% of all samples, respectively. The Delta variant was identified in 13.3% of samples, with peak detection rates and concentrations observed in May 2021 (24%), concurrent with its emergence in the United Kingdom. The RT-qPCR results correlated well with those from sequencing, suggesting that PCR-based detection is a good predictor for variant presence; although, inadequate probe binding may lead to false positive or negative results. Our findings suggest that WBE coupled with RT-qPCR may be used as a rapid, initial assessment to identify emerging variants at international borders and mass quarantining facilities. IMPORTANCE With the global spread of COVID-19, it is essential to identify emerging variants which may be more harmful or able to escape vaccines rapidly. To date, the gold standard to assess variants circulating in communities has been the sequencing of the S gene or the whole genome of SARS-CoV-2; however, that approach is time-consuming and expensive. In this study, we developed two duplex RT-qPCR assays to detect and quantify defining mutations associated with the Beta, Gamma, Delta, and Kappa variants. The assays were validated using RNA extracts derived from wastewater samples taken at quarantine facilities. The results showed good correlation with the results of sequencing and demonstrated the emergence of the Delta variant in the United Kingdom in May 2021. The assays developed here enable the assessment of variant-specific mutations within 2 h after the RNA extract was generated which is essential for outbreak rapid response.
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Affiliation(s)
- Kata Farkas
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
- School of Ocean Sciences, Bangor University, Menai Bridge, Anglesey, United Kingdom
| | - Cameron Pellett
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Rachel Williams
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Natasha Alex-Sanders
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Irene Bassano
- UK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom
- Department of Infectious Disease, Imperial College London, London, United Kingdom
| | - Mathew R. Brown
- UK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom
- School of Engineering, Newcastle University, Newcastle-upon-Tyne, United Kingdom
| | - Hubert Denise
- UK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom
| | - Jasmine M. S. Grimsley
- UK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom
- The London Data Company, London, United Kingdom
| | - Jessica L. Kevill
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Mohammad S. Khalifa
- UK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom
- Division of Biosciences, College of Health, Medicine and Life Sciences, Brunel University, London, United Kingdom
| | - Igor Pântea
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Rich Story
- UK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom
- Servita Professional Services (UK) Ltd., London, United Kingdom
| | - Matthew J. Wade
- UK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom
- School of Engineering, Newcastle University, Newcastle-upon-Tyne, United Kingdom
| | - Nick Woodhall
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Davey L. Jones
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
- Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
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54
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Vatanpour V, Naziri Mehrabani SA, Safarpour M, Ganjali MR, Habibzadeh S, Koyuncu I. Fabrication of the PES Membrane Embedded with Plasma-Modified Zeolite at Different O 2 Pressures. ACS APPLIED MATERIALS & INTERFACES 2023; 15:9892-9905. [PMID: 36776106 DOI: 10.1021/acsami.2c22237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
In this research, the non-thermal glow discharge plasma process was implemented to modify the surface of natural clinoptilolite zeolite before incorporation into the polyethersulfone (PES) membrane. The influence of plasma gas pressure variation on the fouling resistance and separation performance of the prepared membranes was studied. Fourier transform infrared, field emission scanning electron microscopy, and X-ray diffraction analyses of the unmodified and modified clinoptilolites revealed the Si-OH-Al bond's development during plasma treatment and the change in surface characteristics. In terms of performance, increasing the plasma gas pressure during clinoptilolite treatment resulted in the twofold enhancement of water flux from 91.2 L/m2 h of bare PES to 188 L/m2 h of the membrane containing plasma-treated clinoptilolite at 1.0 Torr pressure. Meanwhile, the antifouling behavior of membranes was improved by introducing more hydrophilic functional groups derived from the plasma treatment process. Additionally, the enhanced dye separation of membranes was indicated by the separation of 99 and 94% of reactive green 19 and reactive red 195, respectively.
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Affiliation(s)
- Vahid Vatanpour
- Department of Applied Chemistry, Faculty of Chemistry, Kharazmi University, Tehran 15719-14911, Iran
- National Research Center on Membrane Technologies, Istanbul Technical University, Maslak, Istanbul 34469, Turkey
- Environmental Engineering Department, Istanbul Technical University, Maslak, Istanbul 34469, Turkey
| | - Seyed Ali Naziri Mehrabani
- National Research Center on Membrane Technologies, Istanbul Technical University, Maslak, Istanbul 34469, Turkey
- Nano Science and Nano Engineering Department, Istanbul Technical University, Maslak, Istanbul 34469, Turkey
| | - Mahdie Safarpour
- Department of Chemistry, Faculty of Basic Science, Azarbaijan Shahid Madani University, Tabriz 53714-161, Iran
| | - Mohammad Reza Ganjali
- Center of Excellence in Electrochemistry, School of Chemistry, College of Science, University of Tehran, Tehran 14155-6619, Iran
| | - Sajjad Habibzadeh
- Surface Reaction and Advanced Energy Materials Laboratory, Chemical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), Tehran 15875-4413, Iran
| | - Ismail Koyuncu
- National Research Center on Membrane Technologies, Istanbul Technical University, Maslak, Istanbul 34469, Turkey
- Environmental Engineering Department, Istanbul Technical University, Maslak, Istanbul 34469, Turkey
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55
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Sellam AZ, Benlamoudi A, Cid CA, Dobelle L, Slama A, El Hillali Y, Taleb-Ahmed A. Deep Learning Solution for Quantification of Fluorescence Particles on a Membrane. SENSORS (BASEL, SWITZERLAND) 2023; 23:1794. [PMID: 36850392 PMCID: PMC9967937 DOI: 10.3390/s23041794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/28/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
The detection and quantification of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus particles in ambient waters using a membrane-based in-gel loop-mediated isothermal amplification (mgLAMP) method can play an important role in large-scale environmental surveillance for early warning of potential outbreaks. However, counting particles or cells in fluorescence microscopy is an expensive, time-consuming, and tedious task that only highly trained technicians and researchers can perform. Although such objects are generally easy to identify, manually annotating cells is occasionally prone to fatigue errors and arbitrariness due to the operator's interpretation of borderline cases. In this research, we proposed a method to detect and quantify multiscale and shape variant SARS-CoV-2 fluorescent cells generated using a portable (mgLAMP) system and captured using a smartphone camera. The proposed method is based on the YOLOv5 algorithm, which uses CSPnet as its backbone. CSPnet is a recently proposed convolutional neural network (CNN) that duplicates gradient information within the network using a combination of Dense nets and ResNet blocks, and bottleneck convolution layers to reduce computation while at the same time maintaining high accuracy. In addition, we apply the test time augmentation (TTA) algorithm in conjunction with YOLO's one-stage multihead detection heads to detect all cells of varying sizes and shapes. We evaluated the model using a private dataset provided by the Linde + Robinson Laboratory, California Institute of Technology, United States. The model achieved a mAP@0.5 score of 90.3 in the YOLOv5-s6.
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Affiliation(s)
- Abdellah Zakaria Sellam
- Institute of Applied Sciences and Intelligent Systems, National Research Council of Italy, 73100 Lecce, Italy
| | - Azeddine Benlamoudi
- Laboratoire de Génie Électrique, Faculté des Nouvelles Technologies de l’Information et de la Communication, Université Ouargla, Ouargla 30000, Algeria
| | - Clément Antoine Cid
- Linde Laboratories, California Institute of Technology, Pasadena, CA 91125, USA
| | - Leopold Dobelle
- Linde Laboratories, California Institute of Technology, Pasadena, CA 91125, USA
| | - Amina Slama
- Faculty of Humanities and Social Sciences, Mohamed Khider University of Biskra, Biskra 07000, Algeria
| | - Yassin El Hillali
- Institut d’Electronique de Microélectronique et de Nanotechnologie (IEMN), UMR 8520, Université Polytechnique Hauts de France, Université de Lille, CNRS, 59313 Valenciennes, France
| | - Abdelmalik Taleb-Ahmed
- Institut d’Electronique de Microélectronique et de Nanotechnologie (IEMN), UMR 8520, Université Polytechnique Hauts de France, Université de Lille, CNRS, 59313 Valenciennes, France
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56
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Bhattacharya S, Abhishek K, Samiksha S, Sharma P. Occurrence and transport of SARS-CoV-2 in wastewater streams and its detection and remediation by chemical-biological methods. JOURNAL OF HAZARDOUS MATERIALS ADVANCES 2023; 9:100221. [PMID: 36818681 PMCID: PMC9762044 DOI: 10.1016/j.hazadv.2022.100221] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 12/02/2022] [Accepted: 12/18/2022] [Indexed: 06/18/2023]
Abstract
This paper explains the transmission of SARS-CoV and influences of several environmental factors in the transmission process. The article highlighted several methods of collection, sampling and monitoring/estimation as well as surveillance tool for detecting SARS-CoV in wastewater streams. In this context, WBE (Wastewater based epidemiology) is found to be the most effective surveillance tool. Several methods of genomic sequencing are discussed in the paper, which are applied in WBE, like qPCR-based wastewater testing, metagenomics-based analysis, next generation sequencing etc. Additionally, several types of biosensors (colorimetric biosensor, mobile phone-based biosensors, and nanomaterials-based biosensors) showed promising results in sensing SARS-CoV in wastewater. Further, this review paper outlined the gaps in assessing the factors responsible for transmission and challenges in detection and monitoring along with the remediation and disinfection methods of this virus in wastewater. Various methods of disinfection of SARS-CoV-2 in wastewater are discussed (primary, secondary, and tertiary phases) and it is found that a suite of disinfection methods can be used for complete disinfection/removal of the virus. Application of ultraviolet light, ozone and chlorine-based disinfectants are also discussed in the context of treatment methods. This study calls for continuous efforts to gather more information about the virus through continuous monitoring and analyses and to address the existing gaps and identification of the most effective tool/ strategy to prevent SARS-CoV-2 transmission. Wastewater surveillance can be very useful in effective surveillance of future pandemics and epidemics caused by viruses, especially after development of new technologies in detecting and disinfecting viral pathogens more effectively.
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Affiliation(s)
- Sayan Bhattacharya
- School of Ecology and Environment Studies, Nalanda University, Rajgir, 803116, Bihar, India
| | - Kumar Abhishek
- School of Ecology and Environment Studies, Nalanda University, Rajgir, 803116, Bihar, India
- Department of Environment Forest and Climate Change, Government of Bihar, Patna, 800015, Bihar, India
| | - Shilpi Samiksha
- Bihar State Pollution Control Board, Patna, 800015, Bihar, India
| | - Prabhakar Sharma
- School of Ecology and Environment Studies, Nalanda University, Rajgir, 803116, Bihar, India
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57
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Grube AM, Coleman CK, LaMontagne CD, Miller ME, Kothegal NP, Holcomb DA, Blackwood AD, Clerkin TJ, Serre ML, Engel LS, Guidry VT, Noble RT, Stewart JR. Detection of SARS-CoV-2 RNA in wastewater and comparison to COVID-19 cases in two sewersheds, North Carolina, USA. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159996. [PMID: 36356771 PMCID: PMC9639408 DOI: 10.1016/j.scitotenv.2022.159996] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 10/28/2022] [Accepted: 11/02/2022] [Indexed: 06/16/2023]
Abstract
Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (⍴ ~0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.
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Affiliation(s)
- Alyssa M Grube
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Collin K Coleman
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Connor D LaMontagne
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Megan E Miller
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Nikhil P Kothegal
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - David A Holcomb
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - A Denene Blackwood
- Institute of Marine Sciences, Department of Earth, Marine, and Environmental Sciences, University of North Carolina at Chapel Hill, 3431 Arendell Street, Morehead City, NC 28557, United States
| | - Thomas J Clerkin
- Institute of Marine Sciences, Department of Earth, Marine, and Environmental Sciences, University of North Carolina at Chapel Hill, 3431 Arendell Street, Morehead City, NC 28557, United States
| | - Marc L Serre
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Lawrence S Engel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Virginia T Guidry
- Occupational and Environmental Epidemiology Branch, NC Department of Health and Human Services, 5505 Six Forks Road, Raleigh, NC 27609, United States
| | - Rachel T Noble
- Institute of Marine Sciences, Department of Earth, Marine, and Environmental Sciences, University of North Carolina at Chapel Hill, 3431 Arendell Street, Morehead City, NC 28557, United States
| | - Jill R Stewart
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States.
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58
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Rothman JA, Saghir A, Chung SA, Boyajian N, Dinh T, Kim J, Oval J, Sharavanan V, York C, Zimmer-Faust AG, Langlois K, Steele JA, Griffith JF, Whiteson KL. Longitudinal metatranscriptomic sequencing of Southern California wastewater representing 16 million people from August 2020-21 reveals widespread transcription of antibiotic resistance genes. WATER RESEARCH 2023; 229:119421. [PMID: 36455460 DOI: 10.1016/j.watres.2022.119421] [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: 08/10/2022] [Revised: 11/22/2022] [Accepted: 11/23/2022] [Indexed: 06/17/2023]
Abstract
Municipal wastewater provides a representative sample of human fecal waste across a catchment area and contains a wide diversity of microbes. Sequencing wastewater samples provides information about human-associated and medically important microbial populations, and may be useful to assay disease prevalence and antimicrobial resistance (AMR). Here, we present a study in which we used untargeted metatranscriptomic sequencing on RNA extracted from 275 sewage influent samples obtained from eight wastewater treatment plants (WTPs) representing approximately 16 million people in Southern California between August 2020 - August 2021. We characterized bacterial and viral transcripts, assessed metabolic pathway activity, and identified over 2,000 AMR genes/variants across all samples. Because we did not deplete ribosomal RNA, we have a unique window into AMR carried as ribosomal mutants. We show that AMR diversity varied between WTPs (as measured through PERMANOVA, P < 0.001) and that the relative abundance of many individual AMR genes/variants increased over time (as measured with MaAsLin2, Padj < 0.05). Similarly, we detected transcripts mapping to human pathogenic bacteria and viruses suggesting RNA sequencing is a powerful tool for wastewater-based epidemiology and that there are geographical signatures to microbial transcription. We captured the transcription of gene pathways common to bacterial cell processes, including central carbon metabolism, nucleotide synthesis/salvage, and amino acid biosynthesis. We also posit that due to the ubiquity of many viruses and bacteria in wastewater, new biological targets for microbial water quality assessment can be developed. To the best of our knowledge, our study provides the most complete longitudinal metatranscriptomic analysis of a large population's wastewater to date and demonstrates our ability to monitor the presence and activity of microbes in complex samples. By sequencing RNA, we can track the relative abundance of expressed AMR genes/variants and metabolic pathways, increasing our understanding of AMR activity across large human populations and sewer sheds.
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Affiliation(s)
- Jason A Rothman
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, United States of America.
| | - Andrew Saghir
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, United States of America
| | - Seung-Ah Chung
- Genomics High-Throughput Facility, Department of Biological Chemistry, University of California, Irvine, Irvine, CA, United States of America
| | - Nicholas Boyajian
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, United States of America
| | - Thao Dinh
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, United States of America
| | - Jinwoo Kim
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, United States of America
| | - Jordan Oval
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, United States of America
| | - Vivek Sharavanan
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, United States of America
| | - Courtney York
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, United States of America
| | - Amity G Zimmer-Faust
- Southern California Coastal Water Research Project, Costa Mesa, CA, United States of America
| | - Kylie Langlois
- Southern California Coastal Water Research Project, Costa Mesa, CA, United States of America
| | - Joshua A Steele
- Southern California Coastal Water Research Project, Costa Mesa, CA, United States of America
| | - John F Griffith
- Southern California Coastal Water Research Project, Costa Mesa, CA, United States of America
| | - Katrine L Whiteson
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, United States of America.
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59
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Kannan A, Sims N, Hold AJ, Jagadeesan K, Standerwick R, Barden R, Kasprzyk-Hordern B. The burden of city's pain treatment - A longitudinal one year study of two cities via wastewater-based epidemiology. WATER RESEARCH 2023; 229:119391. [PMID: 36462253 DOI: 10.1016/j.watres.2022.119391] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 11/04/2022] [Accepted: 11/18/2022] [Indexed: 06/17/2023]
Abstract
This paper explores Wastewater-Based Epidemiology (WBE) as a tool enabling understanding of city's pain treatment in an intercity longitudinal study. An intensive 13-month monitoring programme was undertaken in two adjacent urban areas in South-West England: a small commuter town Keynsham and the city of Bath (>180 samples collected). The study has shown a great potential of using triangulated WBE and National health Service (NHS) prescription data in understanding pain treatment in two contrasting communities with strong apparent seasonal patterns of short pain medications vs chronic pain treatment as well as the type of treatment used (e.g. oral vs topical). Community-wide usage of Non-Steroidal Anti-inflammatory Drugs (NSAIDs) and paracetamol in the intercity study is population size and season driven with the highest usage recorded in winter months. This contrasts with other pain pharmaceuticals, especially those used for chronic pain, where no/limited seasonal usage was recorded. Unmetabolized NSAIDs are, to a large extent, directly disposed of into the sewerage system bypassing metabolism due to their topical application. This is particularly apparent in winter months with naproxen showing the highest seasonal variability. Pharma/met (ratio of pharmaceutical and its metabolite concentration) analysis allows for tracking topical (non-metabolic) application/down-the-drain disposal of pharmaceuticals with frequent instances of direct disposal of NSAIDs into the sewerage system observed. Normalisation of pharma markers to population size shows comparable estimates of pharma usage in the two cities confirming population as the main driver of pharma loads in wastewater. Variable application patterns of pain pharmaceuticals make back-calculation of intake more convoluted. Intake calculated using percentage excretion of parent NSAIDs will likely lead to overestimation, as it is assumed that NSAIDs are subject to extensive metabolism (this is not the case for topical applications). Intake calculated using percentage excretion of metabolites (or parent compound) as consumption markers leads to underestimation of NSAIDs usage due to contributions from topical application not being accounted for. Prescription data indicates cumulative internal and topical usage, but the data ignores large proportion of over-the-counter usage. Therefore, we have proposed a combined approach allowing for estimation of total usage including, and differentiating between, topical application and oral administration.
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Affiliation(s)
- Andrew Kannan
- Department of Chemistry, University of Bath, Bath BA2 7AY, United Kingdom
| | - Natalie Sims
- Department of Chemistry, University of Bath, Bath BA2 7AY, United Kingdom
| | - Angus J Hold
- Department of Chemistry, University of Bath, Bath BA2 7AY, United Kingdom
| | - Kishore Jagadeesan
- Department of Chemistry, University of Bath, Bath BA2 7AY, United Kingdom
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60
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Liu L. The dynamics of early-stage transmission of COVID-19: A novel quantification of the role of global temperature. GONDWANA RESEARCH : INTERNATIONAL GEOSCIENCE JOURNAL 2023; 114:55-68. [PMID: 35035256 PMCID: PMC8747780 DOI: 10.1016/j.gr.2021.12.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 12/16/2021] [Accepted: 12/19/2021] [Indexed: 05/11/2023]
Abstract
The global outbreak of COVID-19 has emerged as one of the most devastating and challenging threats to humanity. As many frontline workers are fighting against this disease, researchers are struggling to obtain a better understanding of the pathways and challenges of this pandemic. This paper evaluates the concept that the transmission of COVID-19 is intrinsically linked to temperature. Some complex nonlinear functional forms, such as the cubic function, are introduced to the empirical models to understand the interaction between temperature and the "growth" in the number of infected cases. An accurate quantitative interaction between temperature and the confirmed COVID-19 cases is obtained as log(Y) = -0.000146(temp_H)3 + 0.007410(temp_H)2 -0.063332 temp_H + 7.793842, where Y is the periodic growth in confirmed COVID-19 cases, and temp_H is the maximum daily temperature. This equation alone may be the first confirmed way to measure the quantitative interaction between temperature and human transmission of COVID-19. In addition, four important regions are identified in terms of maximum daily temperature (in Celsius) to understand the dynamics in the transmission of COVID-19 related to temperature. First, the transmission decreases within the range of -50 °C to 5.02 °C. Second, the transmission accelerates in the range of 5.02 °C to 16.92 °C. Essentially, this is the temperature range for an outbreak. Third, the transmission increases more slowly in the range of 16.92 °C to 28.82 °C. Within this range, the number of infections continues to grow, but at a slower pace. Finally, the transmission decreases in the range of 28.82 °C to 50 °C. Thus, according to this hypothesis, the threshold of 16.92 °C is the most critical, as the point at which the infection rate is the greatest. This result sheds light on the mechanism in the cyclicity of the ongoing COVID-19 pandemic worldwide. The implications of these results on policy issues are also discussed concerning a possible cyclical fluctuation pattern between the Northern and Southern Hemispheres.
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Affiliation(s)
- Lu Liu
- School of Economics, Southwestern University of Finance and Economics, China
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61
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Gagliano E, Biondi D, Roccaro P. Wastewater-based epidemiology approach: The learning lessons from COVID-19 pandemic and the development of novel guidelines for future pandemics. CHEMOSPHERE 2023; 313:137361. [PMID: 36427570 PMCID: PMC9678975 DOI: 10.1016/j.chemosphere.2022.137361] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 11/20/2022] [Accepted: 11/21/2022] [Indexed: 05/05/2023]
Abstract
Wastewater-based epidemiology (WBE) provides a comprehensive real-time framework of population attitude and health status. This approach is attracting the interest of medical community and health authorities to monitor the prevalence of a virus (such as the severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) among a community. Indeed, WBE is currently fine-tuning as environmental surveillance tool for coronavirus disease 2019 (COVID-19) pandemic. After a bibliometric analysis conducted to discover the research trends in WBE field, this work aimed to side-by-side compare the conventional method based on clinical testing with WBE approach. Furthermore, novel guidelines were developed to apply the WBE approach to a pandemic. The growing interest on WBE approach for COVID-19 pandemic is demonstrated by looking at the sharp increase in scientific papers published in the last years and at the ongoing studies on viral quantification methods and analytical procedures. The side-by-side comparison highlighted the ability of WBE to identify the hot-spot areas faster than the conventional approach, reducing the costs (e.g., rational use of available resources) and the gatherings at medical centers. Contrary to clinical testing, WBE has the surveillance capacity for preventing the virus resurgence, including asymptomatic contribution, and ensuring the preservation of medical staff health by avoiding the exposure to the virus infection during clinical testing. As extensively reported, the time in collecting epidemiological data is crucial for establishing the prevention and mitigation measures that are essential for curbing a pandemic. The developed guidelines can help to build a WBE system useful to control any future pandemic.
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Affiliation(s)
- Erica Gagliano
- Department of Civil Engineering and Architecture, University of Catania, Catania, Italy; Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy
| | - Deborah Biondi
- Department of Civil Engineering and Architecture, University of Catania, Catania, Italy
| | - Paolo Roccaro
- Department of Civil Engineering and Architecture, University of Catania, Catania, Italy.
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Rainey AL, Buschang K, O’Connor A, Love D, Wormington AM, Messcher RL, Loeb JC, Robinson SE, Ponder H, Waldo S, Williams R, Shapiro J, McAlister EB, Lauzardo M, Lednicky JA, Maurelli AT, Sabo-Attwood T, Bisesi J. Retrospective Analysis of Wastewater-Based Epidemiology of SARS-CoV-2 in Residences on a Large College Campus: Relationships between Wastewater Outcomes and COVID-19 Cases across Two Semesters with Different COVID-19 Mitigation Policies. ACS ES&T WATER 2023; 3:16-29. [PMID: 37552720 PMCID: PMC9762499 DOI: 10.1021/acsestwater.2c00275] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 11/11/2022] [Accepted: 11/14/2022] [Indexed: 06/18/2023]
Abstract
Wastewater-based epidemiology (WBE) has been utilized for outbreak monitoring and response efforts in university settings during the coronavirus disease 2019 (COVID-19) pandemic. However, few studies examined the impact of university policies on the effectiveness of WBE to identify cases and mitigate transmission. The objective of this study was to retrospectively assess relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wastewater outcomes and COVID-19 cases in residential buildings of a large university campus across two academic semesters (August 2020-May 2021) under different COVID-19 mitigation policies. Clinical case surveillance data of student residents were obtained from the university COVID-19 response program. We collected and processed building-level wastewater for detection and quantification of SARS-CoV-2 RNA by RT-qPCR. The odds of obtaining a positive wastewater sample increased with COVID-19 clinical cases in the fall semester (OR = 1.50, P value = 0.02), with higher odds in the spring semester (OR = 2.63, P value < 0.0001). We observed linear associations between SARS-CoV-2 wastewater concentrations and COVID-19 clinical cases (parameter estimate = 1.2, P value = 0.006). Our study demonstrated the effectiveness of WBE in the university setting, though it may be limited under different COVID-19 mitigation policies. As a complementary surveillance tool, WBE should be accompanied by robust administrative and clinical testing efforts for the COVID-19 pandemic response.
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Affiliation(s)
- Andrew L. Rainey
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
| | - Katherine Buschang
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Amber O’Connor
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Deirdre Love
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Alexis M. Wormington
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Rebeccah L. Messcher
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
| | - Julia C. Loeb
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
| | - Sarah E. Robinson
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Hunter Ponder
- UF Health Screen, Test, and Protect,
University of Florida, Gainesville, Florida32611,
United States
- Florida Department of
Health, Alachua County, Gainesville, Florida32641, United
States
| | - Sarah Waldo
- UF Health Screen, Test, and Protect,
University of Florida, Gainesville, Florida32611,
United States
- Florida Department of
Health, Alachua County, Gainesville, Florida32641, United
States
| | - Roy Williams
- UF Health Screen, Test, and Protect,
University of Florida, Gainesville, Florida32611,
United States
- Florida Department of
Health, Alachua County, Gainesville, Florida32641, United
States
| | - Jerne Shapiro
- UF Health Screen, Test, and Protect,
University of Florida, Gainesville, Florida32611,
United States
- Florida Department of
Health, Alachua County, Gainesville, Florida32641, United
States
- Department of Epidemiology, College of Public
Health and Health Professions and College of Medicine, Gainesville,
Florida32611, United States
| | | | - Michael Lauzardo
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
- UF Health Screen, Test, and Protect,
University of Florida, Gainesville, Florida32611,
United States
- Department of Medicine, College of Medicine,
University of Florida, Gainesville, Florida32611,
United States
| | - John A. Lednicky
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
| | - Anthony T. Maurelli
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
| | - Tara Sabo-Attwood
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Joseph
H. Bisesi
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
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63
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Lott MEJ, Norfolk WA, Dailey CA, Foley AM, Melendez-Declet C, Robertson MJ, Rathbun SL, Lipp EK. Direct wastewater extraction as a simple and effective method for SARS-CoV-2 surveillance and COVID-19 community-level monitoring. FEMS MICROBES 2023; 4:xtad004. [PMID: 37333441 PMCID: PMC10117872 DOI: 10.1093/femsmc/xtad004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 11/23/2022] [Accepted: 01/11/2023] [Indexed: 10/22/2023] Open
Abstract
Wastewater surveillance has proven to be an effective tool to monitor the transmission and emergence of infectious agents at a community scale. Workflows for wastewater surveillance generally rely on concentration steps to increase the probability of detection of low-abundance targets, but preconcentration can substantially increase the time and cost of analyses while also introducing additional loss of target during processing. To address some of these issues, we conducted a longitudinal study implementing a simplified workflow for SARS-CoV-2 detection from wastewater, using a direct column-based extraction approach. Composite influent wastewater samples were collected weekly for 1 year between June 2020 and June 2021 in Athens-Clarke County, Georgia, USA. Bypassing any concentration step, low volumes (280 µl) of influent wastewater were extracted using a commercial kit, and immediately analyzed by RT-qPCR for the SARS-CoV-2 N1 and N2 gene targets. SARS-CoV-2 viral RNA was detected in 76% (193/254) of influent samples, and the recovery of the surrogate bovine coronavirus was 42% (IQR: 28%, 59%). N1 and N2 assay positivity, viral concentration, and flow-adjusted daily viral load correlated significantly with per-capita case reports of COVID-19 at the county-level (ρ = 0.69-0.82). To compensate for the method's high limit of detection (approximately 106-107 copies l-1 in wastewater), we extracted multiple small-volume replicates of each wastewater sample. With this approach, we detected as few as five cases of COVID-19 per 100 000 individuals. These results indicate that a direct-extraction-based workflow for SARS-CoV-2 wastewater surveillance can provide informative and actionable results.
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Affiliation(s)
- Megan E J Lott
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - William A Norfolk
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Cody A Dailey
- Department of Epidemiology and Biostatistics, University of Georgia, 101 Buck Road, Athens, GA 30606, United States
| | - Amelia M Foley
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Carolina Melendez-Declet
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Megan J Robertson
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Stephen L Rathbun
- Department of Epidemiology and Biostatistics, University of Georgia, 101 Buck Road, Athens, GA 30606, United States
| | - Erin K Lipp
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
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64
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Naughton CC, Roman FA, Alvarado AGF, Tariqi AQ, Deeming MA, Kadonsky KF, Bibby K, Bivins A, Medema G, Ahmed W, Katsivelis P, Allan V, Sinclair R, Rose JB. Show us the data: global COVID-19 wastewater monitoring efforts, equity, and gaps. FEMS MICROBES 2023; 4:xtad003. [PMID: 37333436 PMCID: PMC10117741 DOI: 10.1093/femsmc/xtad003] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 12/16/2022] [Accepted: 01/11/2023] [Indexed: 08/10/2023] Open
Abstract
A year since the declaration of the global coronavirus disease 2019 (COVID-19) pandemic, there were over 110 million cases and 2.5 million deaths. Learning from methods to track community spread of other viruses such as poliovirus, environmental virologists and those in the wastewater-based epidemiology (WBE) field quickly adapted their existing methods to detect SARS-CoV-2 RNA in wastewater. Unlike COVID-19 case and mortality data, there was not a global dashboard to track wastewater monitoring of SARS-CoV-2 RNA worldwide. This study provides a 1-year review of the "COVIDPoops19" global dashboard of universities, sites, and countries monitoring SARS-CoV-2 RNA in wastewater. Methods to assemble the dashboard combined standard literature review, Google Form submissions, and daily, social media keyword searches. Over 200 universities, 1400 sites, and 55 countries with 59 dashboards monitored wastewater for SARS-CoV-2 RNA. However, monitoring was primarily in high-income countries (65%) with less access to this valuable tool in low- and middle-income countries (35%). Data were not widely shared publicly or accessible to researchers to further inform public health actions, perform meta-analysis, better coordinate, and determine equitable distribution of monitoring sites. For WBE to be used to its full potential during COVID-19 and beyond, show us the data.
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Affiliation(s)
- Colleen C Naughton
- Department of Civil and Environmental Engineering, University of California, Merced, Merced, CA 95343, United States
| | - Fernando A Roman
- Department of Civil and Environmental Engineering, University of California, Merced, Merced, CA 95343, United States
| | - Ana Grace F Alvarado
- Department of Civil and Environmental Engineering, University of California, Merced, Merced, CA 95343, United States
| | - Arianna Q Tariqi
- Department of Civil and Environmental Engineering, University of California, Merced, Merced, CA 95343, United States
| | - Matthew A Deeming
- Department of Civil and Environmental Engineering, University of California, Merced, Merced, CA 95343, United States
| | - Krystin F Kadonsky
- Department of Civil and Environmental Engineering, University of California, Merced, Merced, CA 95343, United States
| | - Kyle Bibby
- Department of Civil and Environmental Engineering and Earth Science, University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, United States
| | - Aaron Bivins
- Department of Civil and Environmental Engineering and Earth Science, University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, United States
| | - Gertjan Medema
- KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, The Netherlands
- Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands
- Michigan State University, 1405 S Harrison Rd, East-Lansing, MI 48823, United States
| | - Warish Ahmed
- CSIRO Land and Water, Ecosciences Precinct, 41 Boggo Road, QLD 4102, Australia
| | | | - Vajra Allan
- PATH 2201 Westlake Avenue, Suite 200, Seattle, WA 98121, United States
| | - Ryan Sinclair
- Schools of Public Health and Earth and Biological Sciences, Loma Linda University, Loma Linda, CA 92350, United States
| | - Joan B Rose
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, United States
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65
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Mare R, Mare C, Hadarean A, Hotupan A, Rus T. COVID-19 and Water Variables: Review and Scientometric Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:957. [PMID: 36673718 PMCID: PMC9859563 DOI: 10.3390/ijerph20020957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 12/29/2022] [Accepted: 12/30/2022] [Indexed: 06/17/2023]
Abstract
COVID-19 has changed the world since 2020, and the field of water specifically, boosting scientific productivity (in terms of published articles). This paper focuses on the influence of COVID-19 on scientific productivity with respect to four water variables: (i) wastewater, (ii) renewable water resources, (iii) freshwater withdrawal, and (iv) access to improved and safe drinking water. The field's literature was firstly reviewed, and then the maps were built, emphasizing the strong connections between COVID-19 and water-related variables. A total of 94 countries with publications that assess COVID-19 vs. water were considered and evaluated for how they clustered. The final step of the research shows that, on average, scientific productivity on the water topic was mostly conducted in countries with lower COVID-19 infection rates but higher development levels as represented by gross domestic product (GDP) per capita and the human development index (HDI). According to the statistical analysis, the water-related variables are highly significant, with positive coefficients. This validates that countries with higher water-related values conducted more research on the relationship with COVID-19. Wastewater and freshwater withdrawal had the highest impact on the scientific productivity with respect to COVID-19. Access to safe drinking water becomes insignificant in the presence of the development parameters.
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Affiliation(s)
- Roxana Mare
- Department of Building Services Engineering, Faculty of Building Services Engineering, Technical University of Cluj-Napoca, 128-130 21 Decembrie 1989 Blv., 400604 Cluj-Napoca, Romania
| | - Codruța Mare
- Department of Statistics-Forecasts-Mathematics, Faculty of Economics and Business Administration, Babes-Bolyai University, 58-60 Teodor Mihali Str., 400591 Cluj-Napoca, Romania
- Interdisciplinary Centre for Data Science, Babes-Bolyai University, 68 Avram Iancu Str., 4th Floor, 400083 Cluj-Napoca, Romania
| | - Adriana Hadarean
- Department of Building Services Engineering, Faculty of Building Services Engineering, Technical University of Cluj-Napoca, 128-130 21 Decembrie 1989 Blv., 400604 Cluj-Napoca, Romania
| | - Anca Hotupan
- Department of Building Services Engineering, Faculty of Building Services Engineering, Technical University of Cluj-Napoca, 128-130 21 Decembrie 1989 Blv., 400604 Cluj-Napoca, Romania
| | - Tania Rus
- Department of Building Services Engineering, Faculty of Building Services Engineering, Technical University of Cluj-Napoca, 128-130 21 Decembrie 1989 Blv., 400604 Cluj-Napoca, Romania
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66
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Chaudhuri A, Pangaria A, Sodhi C, Kumar V N, Harshe S, Parikh N, Shridhar V. Building health system resilience and pandemic preparedness using wastewater-based epidemiology from SARS-CoV-2 monitoring in Bengaluru, India. Front Public Health 2023; 11:1064793. [PMID: 36908428 PMCID: PMC9999730 DOI: 10.3389/fpubh.2023.1064793] [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: 10/10/2022] [Accepted: 01/25/2023] [Indexed: 03/14/2023] Open
Abstract
The COVID-19 pandemic was a watershed event for wastewater-based epidemiology (WBE). It highlighted the inability of existing disease surveillance systems to provide sufficient forewarning to governments on the existing stage and scale of disease spread and underscored the need for an effective early warning signaling system. Recognizing the potentiality of environmental surveillance (ES), in May 2021, COVIDActionCollaborative launched the Precision Health platform. The idea was to leverage ES for equitable mapping of the disease spread in Bengaluru, India and provide early information regarding any inflection in the epidemiological curve of COVID-19. By sampling both networked and non-networked sewage systems in the city, the platform used ES for both equitable and comprehensive surveillance of the population to derive precise information on the existing stage of disease maturity across communities and estimate the scale of the approaching threat. This was in contrast to clinical surveillance, which during the peak of the COVID-19 pandemic in Bengaluru excluded a significant proportion of poor and vulnerable communities from its ambit of representation. The article presents the findings of a sense-making tool which the platform developed for interpreting emerging signals from wastewater data to map disease progression and identifying the inflection points in the epidemiological curve. Thus, the platform accurately generated early warning signals on disease escalation and disseminated it to the government and the general public. This information enabled concerned audiences to implement preventive measures in advance and effectively plan their next steps for improved disease management.
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67
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Farkas K, Williams R, Alex-Sanders N, Grimsley JMS, Pântea I, Wade MJ, Woodhall N, Jones DL. Wastewater-based monitoring of SARS-CoV-2 at UK airports and its potential role in international public health surveillance. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0001346. [PMID: 36963000 PMCID: PMC10021541 DOI: 10.1371/journal.pgph.0001346] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 12/24/2022] [Indexed: 01/20/2023]
Abstract
It is well established that air travel plays a key role in the global spread of many enteric and respiratory diseases, including COVID-19. Even with travel restrictions (e.g. mask wearing, negative COVID-19 test prior to departure), SARS-CoV-2 may be transmitted by asymptomatic or pre-symptomatic individuals carrying the virus. Due to the limitation of current clinical surveillance approaches, complementary methods need to be developed to allow estimation of the frequency of SARS-CoV-2 entry across international borders. Wastewater-based epidemiology (WBE) represents one such approach, allowing the unbiased sampling of SARS-CoV-2 carriage by passenger cohorts entering via airports. In this study, we monitored sewage in samples from terminals (n = 150) and aircraft (n = 32) at three major international airports in the UK for 1-3 weeks in March 2022. As the raw samples were more turbid than typical municipal wastewater, we used beef extract treatment followed by polyethylene glycol (PEG) precipitation to concentrate viruses, followed by reverse transcription quantitative PCR (RT-qPCR) for the detection of SARS-CoV-2 and a faecal indicator virus, crAssphage. All samples taken from sewers at the arrival terminals of Heathrow and Bristol airports, and 85% of samples taken from sites at Edinburgh airport, were positive for SARS-CoV-2. This suggests a high COVID-19 prevalence among passengers and/or airport staff members. Samples derived from aircraft also showed 93% SARS-CoV-2 positivity. No difference in viral prevalence was found before and after COVID-19 travel restrictions were lifted. Our results suggest that WBE is a useful tool for monitoring the global transfer rate of human pathogens and other disease-causing agents across international borders and should form part of wider international efforts to monitor and contain the spread of future disease outbreaks.
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Affiliation(s)
- Kata Farkas
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
- School of Ocean Sciences, Bangor University, Menai Bridge, Anglesey, United Kingdom
| | - Rachel Williams
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Natasha Alex-Sanders
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Jasmine M S Grimsley
- Data, Analytics, and Surveillance Group, UK Health Security Agency, London, United Kingdom
- The London Data Company, London, United Kingdom
| | - Igor Pântea
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Matthew J Wade
- Data, Analytics, and Surveillance Group, UK Health Security Agency, London, United Kingdom
- School of Engineering, Newcastle University, Newcastle-upon-Tyne, United Kingdom
| | - Nick Woodhall
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Davey L Jones
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
- Food Futures Institute, Murdoch University, Murdoch, Australia
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68
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D'Aoust PM, Tian X, Towhid ST, Xiao A, Mercier E, Hegazy N, Jia JJ, Wan S, Kabir MP, Fang W, Fuzzen M, Hasing M, Yang MI, Sun J, Plaza-Diaz J, Zhang Z, Cowan A, Eid W, Stephenson S, Servos MR, Wade MJ, MacKenzie AE, Peng H, Edwards EA, Pang XL, Alm EJ, Graber TE, Delatolla R. Wastewater to clinical case (WC) ratio of COVID-19 identifies insufficient clinical testing, onset of new variants of concern and population immunity in urban communities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 853:158547. [PMID: 36067855 PMCID: PMC9444156 DOI: 10.1016/j.scitotenv.2022.158547] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/10/2022] [Accepted: 09/01/2022] [Indexed: 05/14/2023]
Abstract
Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) will have greater value as an important diagnostic tool. An in-depth analysis and understanding of the metrics derived from WWS is required to interpret and utilize WWS-acquired data effectively (McClary-Gutierrez et al., 2021; O'Keeffe, 2021). In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven cities in Canada over periods ranging from 8 to 21 months. This work demonstrates that significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing (resulting in a reduction to testing access and a reduction in the number of daily tests) in these communities, despite increases in the wastewater signal. Furthermore, the WC ratio decreased significantly in 6 of the 7 studied locations, serving as a potential signal of the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community (40-60 % allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community (40-60 % allelic proportion). Finally, a significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant's greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when community immunity was high. The WC ratio, used as an additional monitoring metric, could complement clinical case counts and wastewater signals as individual metrics in its potential ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.
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Affiliation(s)
- Patrick M D'Aoust
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Xin Tian
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | | | - Amy Xiao
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - Elisabeth Mercier
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Nada Hegazy
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Jian-Jun Jia
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Shen Wan
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Md Pervez Kabir
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Wanting Fang
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Meghan Fuzzen
- Department of Biology, University of Waterloo, Waterloo, Canada
| | - Maria Hasing
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Canada
| | - Minqing Ivy Yang
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada
| | - Jianxian Sun
- Department of Chemistry, University of Toronto, Toronto, Canada
| | - Julio Plaza-Diaz
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Zhihao Zhang
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Aaron Cowan
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Walaa Eid
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Sean Stephenson
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Mark R Servos
- Department of Biology, University of Waterloo, Waterloo, Canada
| | - Matthew J Wade
- Data, Analytics and Surveillance Group, UK Health Security Agency, London, United Kingdom
| | - Alex E MacKenzie
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Hui Peng
- Department of Chemistry, University of Toronto, Toronto, Canada
| | - Elizabeth A Edwards
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada
| | - Xiao-Li Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Canada
| | - Eric J Alm
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - Tyson E Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada.
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69
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Malla B, Thakali O, Shrestha S, Segawa T, Kitajima M, Haramoto E. Application of a high-throughput quantitative PCR system for simultaneous monitoring of SARS-CoV-2 variants and other pathogenic viruses in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 853:158659. [PMID: 36096223 PMCID: PMC9461275 DOI: 10.1016/j.scitotenv.2022.158659] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 09/05/2022] [Accepted: 09/06/2022] [Indexed: 05/11/2023]
Abstract
Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are continuously emerging, highlighting the importance of regular surveillance of SARS-CoV-2 and other epidemiologically significant pathogenic viruses in the current context. Reverse transcription-quantitative PCR (RT-qPCR) is expensive, time-consuming, labor-intensive, requires a large reagent volume, and only tests a few targets in a single run. High-throughput qPCR (HT-qPCR) utilizing the Biomark HD system (Fluidigm) can be used as an alternative. This study applied an HT-qPCR to simultaneously detect SARS-CoV-2, SARS-CoV-2 nucleotide substituted RNA, and other pathogenic viruses in wastewater. Wastewater samples were collected from the coronavirus disease 2019 (COVID-19) quarantine facility between October 2020 and February 2021 (n = 4) and from the combined and separated sewer lines of a wastewater treatment plant (WWTP) in Yokkaichi, Mie Prefecture, Japan, between March and August 2021 (n = 23 each). The samples were analyzed by HT-qPCR using five SARS-CoV-2, nine SARS-CoV-2 spike gene nucleotide substitution-specific, five pathogenic viruses, and three process control assays. All samples from the quarantine facility tested positive for SARS-CoV-2 and the nucleotide substitutions N501Y and S69-70 del (Alpha variant) were detected in the December 2020 sample, coinciding with the first clinical case in Japan. Only three WWTP samples were positive when tested with a single SARS-CoV-2 assay, whereas more than eight samples were positive when tested with all assays, indicating that using multiple assays increases the likelihood of detection. The nucleotide substitution L452R (Delta variant) was detected in the WWTP samples of Mie Prefecture in April 2021, but the detection of Delta variant from patients had not been reported until May 2021. Aichi virus 1 and norovirus GII were prevalent in WWTP samples. This study demonstrated that HT-qPCR may be the most time- and cost-efficient method for tracking COVID-19 and broadly monitoring community health.
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Affiliation(s)
- Bikash Malla
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Ocean Thakali
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Sadhana Shrestha
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan; Institute for the Advanced Study of Sustainability, United Nations University, 5-53-70 Jingumae, Shibuya-ku, Tokyo 150-8925, Japan
| | - Takahiro Segawa
- Center for Life Science Research, University of Yamanashi, 1110 Shimokato, Chuo, Yamanashi 409-3898, Japan
| | - Masaaki Kitajima
- Division of Environmental Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan.
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70
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Sridhar J, Parit R, Boopalakrishnan G, Rexliene MJ, Praveen R, Viswananathan B. Importance of wastewater-based epidemiology for detecting and monitoring SARS-CoV-2. CASE STUDIES IN CHEMICAL AND ENVIRONMENTAL ENGINEERING 2022; 6:100241. [PMID: 37520919 PMCID: PMC9341170 DOI: 10.1016/j.cscee.2022.100241] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 07/26/2022] [Accepted: 07/27/2022] [Indexed: 08/01/2023]
Abstract
Coronavirus disease caused by the SARS-CoV-2 virus has emerged as a global challenge in terms of health and disease monitoring. COVID-19 infection is mainly spread through the SARS-CoV-2 infection leading to the development of mild to severe clinical manifestations. The virus binds to its cognate receptor ACE2 which is widely expressed among different tissues in the body. Notably, SARS-CoV-2 shedding in the fecal samples has been reported through the screening of sewage water across various countries. Wastewater screening for the presence of SARS-CoV-2 provides an alternative method to monitor infection threat, variant identification, and clinical evaluation to restrict the virus progression. Multiple cohort studies have reported the application of wastewater treatment approaches and epidemiological significance in terms of virus monitoring. Thus, the manuscript outlines consolidated and systematic information regarding the application of wastewater-based epidemiology in terms of monitoring and managing a viral disease outbreak like COVID-19.
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Affiliation(s)
- Jayavel Sridhar
- Department of Biotechnology (DDE), Madurai Kamaraj University, Madurai, 625021, Tamilnadu, India
| | - Rahul Parit
- Department of Biotechnology (DDE), Madurai Kamaraj University, Madurai, 625021, Tamilnadu, India
| | | | - M Johni Rexliene
- Department of Biotechnology (DDE), Madurai Kamaraj University, Madurai, 625021, Tamilnadu, India
| | - Rajkumar Praveen
- Department of Biotechnology (DDE), Madurai Kamaraj University, Madurai, 625021, Tamilnadu, India
| | - Balaji Viswananathan
- Department of Biotechnology (DDE), Madurai Kamaraj University, Madurai, 625021, Tamilnadu, India
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71
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VishnuRadhan R, Thresyamma DD, Eldho TI, Dhiman R, Bhavan SG. On the emergence of a health-pollutant-climate nexus in the wake of a global pandemic. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:85619-85631. [PMID: 34523098 PMCID: PMC8439646 DOI: 10.1007/s11356-021-16392-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 09/03/2021] [Indexed: 06/13/2023]
Abstract
COVID-19 has wreaked havoc throughout the planet within a short time frame, inducing substantial morbidity and mortality in the global population. The primary procedures commonly used to manage the pandemic can produce various environmental pollutants, primarily contaminants of emerging concern such as plastics, chemical disinfectants, and pharmaceutical waste. There is a huge influx of various environmental pollutants due to the pandemic effect. We, therefore, introduce the term "envirodemics" depicting the exacerbated surge in the amount of pandemic-induced pollutants. The general toxicity pattern of common chemical ingredients in widely used disinfectants shows negative impacts on the environment. We have identified some of the significant imprints of the pandemic on localizing the Sustainable Development Goals-environment interaction and their implications on achieving the goals in terms of environmental benefits. Climate change impacts are now widespread and have a profound effect on pollutant fluxes and distribution. The climate change signatures will impact the pandemic-induced enhanced fluxes of pollutants in the global waters, such as their transport and transformation. In this study, possible interactions and emerging pathways involving an emerging climate-health-pollutant nexus are discussed. The nexus is further elaborated by considering plastic as an example of an emerging pollutant that is produced in huge quantities as a by-product of COVID management and disaster risk reduction. Additionally, regulatory implications and future perspectives concerning the unleashed nexus are also discussed. We hope that this communication shall call for incisive investigations in the less explored realm concerning the health-pollutant-climate nexus.
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Affiliation(s)
- Renjith VishnuRadhan
- Department of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, Maharashtra, 400076, India.
| | - Divya David Thresyamma
- Arctic Ocean Atmospheric Studies, National Centre for Polar and Ocean Research, Ministry of Earth Sciences, Goa, 403804, Vasco da Gama, India
| | - T I Eldho
- Department of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, Maharashtra, 400076, India
| | - Ravinder Dhiman
- Centre for Geo Informatics, Jamsetji Tata School of Disaster Studies, Tata Institute of Social Sciences, Maharashtra, 400088, Mumbai, India
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72
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Hoar C, McClary-Gutierrez J, Wolfe MK, Bivins A, Bibby K, Silverman AI, McLellan SL. Looking Forward: The Role of Academic Researchers in Building Sustainable Wastewater Surveillance Programs. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:125002. [PMID: 36580023 PMCID: PMC9799055 DOI: 10.1289/ehp11519] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 12/08/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND In just over 2 years, tracking the COVID-19 pandemic through wastewater surveillance advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field. OBJECTIVES We examined the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition from early monitoring efforts to more formalized programs within the public health system. DISCUSSION Although wastewater surveillance has rapidly developed as a useful public health tool for tracking COVID-19, there remain technical challenges and open scientific questions that academic researchers are equipped to address. This includes validating methodology and backfilling important knowledge gaps, such as fate and transport of surveillance targets and epidemiological links to wastewater concentrations. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and draw useful lessons on how to promote synergy between different areas of expertise. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should promote knowledge co-development. We believe active involvement of academic researchers will contribute to building robust surveillance programs that will ultimately provide new insights into population health. https://doi.org/10.1289/EHP11519.
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Affiliation(s)
- Catherine Hoar
- Department of Civil and Urban Engineering, New York University Tandon School of Engineering, Brooklyn, New York, USA
| | - Jill McClary-Gutierrez
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
| | - Marlene K. Wolfe
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Aaron Bivins
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Kyle Bibby
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Indiana, USA
| | - Andrea I. Silverman
- Department of Civil and Urban Engineering, New York University Tandon School of Engineering, Brooklyn, New York, USA
| | - Sandra L. McLellan
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
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73
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Comparison of RT-dPCR and RT-qPCR and the effects of freeze-thaw cycle and glycine release buffer for wastewater SARS-CoV-2 analysis. Sci Rep 2022; 12:20641. [PMID: 36450877 PMCID: PMC9709738 DOI: 10.1038/s41598-022-25187-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022] Open
Abstract
Public health efforts to control the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic rely on accurate information on the spread of the disease in the community. Acute and surveillance testing has been primarily used to characterize the extent of the disease. However, obtaining a representative sample of the human population is challenging because of limited testing capacity and incomplete testing compliance. Wastewater-based epidemiology is an agnostic alternative to surveillance testing that provides an average sample from the population served by the treatment facility. We compare the performance of reverse transcription quantitative PCR (RT-qPCR) and reverse transcription digital droplet PCR (RT-dPCR) for analysis of SARS-CoV-2 RNA in a regional wastewater treatment facility in northern Indiana, USA from the earliest stages of the pandemic. 1-L grab samples of wastewater were clarified and concentrated. Nucleic acids were extracted from aliquots and analyzed in parallel using the two methods. Synthetic viral nucleic acids were used for method development and generation of add-in standard-curves. Both methods were highly sensitive in detecting SARS-CoV-2 in wastewater, with detection limits as low as 1 copy per 500 mL wastewater. RT-qPCR and RT-dPCR provided essentially identical coefficients of variation (s/[Formula: see text] = 0.15) for triplicate measurements made on wastewater samples taken on 16 days. We also observed a sevenfold decrease in viral load from a grab sample that was frozen at - 80 °C for 92 days compared to results obtained without freezing. Freezing samples before analysis should be discouraged. Finally, we found that treatment with a glycine release buffer resulted in a fourfold inhibition in RT-qPCR signal; treatment with a glycine release buffer also should be discouraged. Despite their prevalence and convenience in wastewater analysis, glycine release and freezing samples severely and additively (~ tenfold) degraded recovery and detection of SARS-CoV-2.
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74
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Gerrity D, Papp K, Pecson BM. Pathogen Peak "Averaging" in Potable Reuse Systems: Lessons Learned from Wastewater Surveillance of SARS-CoV-2. ACS ES&T WATER 2022; 2:1863-1870. [PMID: 37566355 PMCID: PMC8791031 DOI: 10.1021/acsestwater.1c00378] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 11/19/2021] [Accepted: 11/29/2021] [Indexed: 05/10/2023]
Abstract
This study describes wastewater concentrations of SARS-CoV-2 at seven different sampling locations in Southern Nevada (ranging from 4.2 to 8.7 log10 gc/L) and highlights several key variables affecting those concentrations, including COVID-19 incidence, sample type, and service area population. This information is important for implementing wastewater-based epidemiology, but it also provides insight relevant to the design and regulation of potable reuse systems. Specifically, smaller systems may be more prone to influent concentration spikes that can drive enteric pathogen risk during disease outbreaks. It may be possible to leverage reactor hydraulics to achieve peak "averaging" in these scenarios, although it then becomes important to consider how elevated risks at the lower percentiles potentially offset benefits at the upper percentiles. Informed by SARS-CoV-2 concentration dynamics, the current study simulated relative risk for a hypothetical enteric pathogen. Simulated reactor hydraulics (i.e., dispersion) increased pathogen concentrations by up to 2.6 logs at lower percentiles but also decreased concentrations by up to 1.1 logs at the upper percentiles that sometimes drive public health risk. Collectively, these data highlight the importance of considering outbreak conditions, pathogen spikes, and peak "averaging" in the design and operation of treatment systems and in the development of regulatory frameworks.
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Affiliation(s)
- Daniel Gerrity
- Applied Research and Development Center,
Southern Nevada Water Authority, Las Vegas, Nevada 89193,
United States
| | - Katerina Papp
- Applied Research and Development Center,
Southern Nevada Water Authority, Las Vegas, Nevada 89193,
United States
| | - Brian M. Pecson
- Trussell Technologies,
Inc., Oakland, California 94612, United States
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75
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Babler KM, Amirali A, Sharkey ME, Williams SL, Boone MM, Cosculluela GA, Currall BB, Grills GS, Laine J, Mason CE, Reding BD, Schürer SC, Stevenson M, Vidovic D, Solo-Gabriele HM. Comparison of Electronegative Filtration to Magnetic Bead-Based Concentration and V2G-qPCR to RT-qPCR for Quantifying Viral SARS-CoV-2 RNA from Wastewater. ACS ES&T WATER 2022; 2:2004-2013. [PMID: 37601294 PMCID: PMC10438908 DOI: 10.1021/acsestwater.2c00047] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/22/2023]
Abstract
Methods of wastewater concentration (electronegative filtration (ENF) versus magnetic bead-based concentration (MBC)) were compared for the analysis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), beta-2 microglobulin, and human-coronavirus OC43. Using ENF as the concentration method, two quantitative Polymerase Chain Reaction (qPCR) analytical methods were also compared: Volcano 2nd Generation (V2G)-qPCR and reverse transcriptase (RT)-qPCR measuring three different targets of the virus responsible for the COVID-19 illness (N1, modified N3, and ORF1ab). Correlations between concentration methods were strong and statistically significant for SARS-CoV-2 (r=0.77, p<0.001) and B2M (r=0.77, p<0.001). Comparison of qPCR analytical methods indicate that, on average, each method provided equivalent results with average ratios of 0.96, 0.96 and 1.02 for N3 to N1, N3 to ORF1ab, and N1 to ORF1ab and were supported by significant (p<0.001) correlation coefficients (r =0.67 for V2G (N3) to RT (N1), r =0.74 for V2G (N3) to RT (ORF1ab), r = 0.81 for RT (N1) to RT (ORF1ab)). Overall results suggest that the two concentration methods and qPCR methods provide equivalent results, although variability is observed for individual measurements. Given the equivalency of results, additional advantages and disadvantages, as described in the discussion, are to be considered when choosing an appropriate method.
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Affiliation(s)
- Kristina M. Babler
- Department of Chemical, Environmental and Materials Engineering, Coral Gables, FL USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental and Materials Engineering, Coral Gables, FL USA
| | - Mark E. Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL USA
| | - Sion L. Williams
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL USA
| | - Melinda M. Boone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL USA
| | | | - Benjamin B. Currall
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL USA
| | - George S. Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL USA
| | - Jennifer Laine
- Department of Physiology and Biophysics and the WorldQuant Initiative, Weill Cornell Medicine, New York City, NY USA
| | | | - Brian D. Reding
- Department of Physiology and Biophysics and the WorldQuant Initiative, Weill Cornell Medicine, New York City, NY USA
| | - Stephan C. Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL USA
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL USA
- Institute for Data Science & Computing, University of Miami, Coral Gables, FL USA
| | - Mario Stevenson
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL USA
| | - Dusica Vidovic
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL USA
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Duvallet C, Wu F, McElroy KA, Imakaev M, Endo N, Xiao A, Zhang J, Floyd-O’Sullivan R, Powell MM, Mendola S, Wilson ST, Cruz F, Melman T, Sathyanarayana CL, Olesen SW, Erickson TB, Ghaeli N, Chai P, Alm EJ, Matus M. Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States. ACS ES&T WATER 2022; 2:1899-1909. [PMID: 36380771 PMCID: PMC9092192 DOI: 10.1021/acsestwater.1c00434] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.
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Affiliation(s)
- Claire Duvallet
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Fuqing Wu
- Center
for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- MIT
Department of Biological Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
| | - Kyle A. McElroy
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Maxim Imakaev
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Noriko Endo
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Amy Xiao
- Center
for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- MIT
Department of Biological Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
| | - Jianbo Zhang
- Center
for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- MIT
Department of Biological Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
| | | | - Morgan M. Powell
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Samuel Mendola
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Shane T. Wilson
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Francis Cruz
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Tamar Melman
- Broad
Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States
| | | | - Scott W. Olesen
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Timothy B. Erickson
- Department
of Emergency Medicine, Harvard Medical School, Boston, Massachusetts 02115, United States
- Division
of Medical Toxicology, Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, Massachusetts 02115, United States
- Harvard
Humanitarian Initiative, Cambridge, Massachusetts 02138, United States
| | - Newsha Ghaeli
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Peter Chai
- Division
of Medical Toxicology, Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, Massachusetts 02115, United States
- The
Fenway Institute, Boston, Massachusetts 02215, United States
- The
Koch Institute for Integrated Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, United States
| | - Eric J. Alm
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
- Center
for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- MIT
Department of Biological Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02142, United States
- Broad
Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States
| | - Mariana Matus
- Biobot
Analytics, Inc., Cambridge, Massachusetts 02139, United States
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77
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Pang X, Gao T, Ellehoj E, Li Q, Qiu Y, Maal-Bared R, Sikora C, Tipples G, Diggle M, Hinshaw D, Ashbolt NJ, Talbot J, Hrudey SE, Lee BE. Wastewater-Based Surveillance Is an Effective Tool for Trending COVID-19 Prevalence in Communities: A Study of 10 Major Communities for 17 Months in Alberta. ACS ES&T WATER 2022; 2:2243-2254. [PMID: 36380772 PMCID: PMC9514327 DOI: 10.1021/acsestwater.2c00143] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 09/09/2022] [Accepted: 09/12/2022] [Indexed: 06/16/2023]
Abstract
The correlations between SARS-CoV-2 RNA levels in wastewater from 12 wastewater treatment plants and new COVID-19 cases in the corresponding sewersheds of 10 communities were studied over 17 months. The analysis from the longest continuous surveillance reported to date revealed that SARS-CoV-2 RNA levels correlated well with temporal changes of COVID-19 cases in each community. The strongest correlation was found during the third wave (r = 0.97) based on the population-weighted SARS-CoV-2 RNA levels in wastewater. Different correlations were observed (r from 0.51 to 0.86) in various sizes of communities. The population in the sewershed had no observed effects on the strength of the correlation. Fluctuation of SARS-CoV-2 RNA levels in wastewater mirrored increases and decreases of COVID-19 cases in the corresponding community. Since the viral shedding to sewers from all infected individuals is included, wastewater-based surveillance provides an unbiased and no-discriminate estimation of the prevalence of COVID-19 compared with clinical testing that was subject to testing-seeking behaviors and policy changes. Wastewater-based surveillance on SARS-CoV-2 represents a temporal trend of COVID-19 disease burden and is an effective and supplementary monitoring when the number of COVID-19 cases reaches detectable thresholds of SARS-CoV-2 RNA in wastewater of treatment facilities serving various sizes of populations.
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Affiliation(s)
- Xiaoli Pang
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
- Alberta
Precision Laboratories, Edmonton, Alberta T6G 2J2, Canada
| | - Tiejun Gao
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Erik Ellehoj
- Ellehoj
Redmond Consulting, Edmonton, Alberta T6G 0Y4, Canada
| | - Qiaozhi Li
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Yuanyuan Qiu
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | | | - Christopher Sikora
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Graham Tipples
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
- Alberta
Precision Laboratories, Edmonton, Alberta T6G 2J2, Canada
| | - Mathew Diggle
- Alberta
Precision Laboratories, Edmonton, Alberta T6G 2J2, Canada
| | - Deena Hinshaw
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | | | - James Talbot
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Steve E. Hrudey
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Bonita E. Lee
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
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78
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Holst MM, Person J, Jennings W, Welsh RM, Focazio MJ, Bradley PM, Schill WB, Kirby AE, Marsh ZA. Rapid Implementation of High-Frequency Wastewater Surveillance of SARS-CoV-2. ACS ES&T WATER 2022; 2:2201-2210. [PMID: 37552727 PMCID: PMC9291391 DOI: 10.1021/acsestwater.2c00094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 06/17/2022] [Accepted: 06/21/2022] [Indexed: 08/10/2023]
Abstract
There have been over 507 million cases of COVID-19, the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in 6 million deaths globally. Wastewater surveillance has emerged as a valuable tool in understanding SARS-CoV-2 burden in communities. The National Wastewater Surveillance System (NWSS) partnered with the United States Geological Survey (USGS) to implement a high-frequency sampling program. This report describes basic surveillance and sampling statistics as well as a comparison of SARS-CoV-2 trends between high-frequency sampling 3-5 times per week, referred to as USGS samples, and routine sampling 1-2 times per week, referred to as NWSS samples. USGS samples provided a more nuanced impression of the changes in wastewater trends, which could be important in emergency response situations. Despite the rapid implementation time frame, USGS samples had similar data quality and testing turnaround times as NWSS samples. Ensuring there is a reliable sample collection and testing plan before an emergency arises will aid in the rapid implementation of a high-frequency sampling approach. High-frequency sampling requires a constant flow of information and supplies throughout sample collection, testing, analysis, and data sharing. High-frequency sampling may be a useful approach for increased resolution of disease trends in emergency response.
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Affiliation(s)
- Meghan M. Holst
- Centers for Disease Control and Prevention,
National Center for Emerging and Zoonotic Infectious
Diseases, 1600 Clifton Road, Atlanta, Georgia 30333, United
States
| | - John Person
- Centers for Disease Control and Prevention,
National Center for Emerging and Zoonotic Infectious
Diseases, 1600 Clifton Road, Atlanta, Georgia 30333, United
States
| | - Wiley Jennings
- Centers for Disease Control and Prevention,
National Center for Emerging and Zoonotic Infectious
Diseases, 1600 Clifton Road, Atlanta, Georgia 30333, United
States
| | - Rory M. Welsh
- Centers for Disease Control and Prevention,
National Center for Emerging and Zoonotic Infectious
Diseases, 1600 Clifton Road, Atlanta, Georgia 30333, United
States
| | - Michael J. Focazio
- United States Geological
Survey, 12201 Sunrise Valley Drive, Reston, Virginia 20192,
United States
| | - Paul M. Bradley
- United States Geological
Survey, Columbia, South Carolina 29210, United
States
| | - William B. Schill
- United States Geological
Survey, Kearneysville, West Virginia 25430, United
States
| | - Amy E. Kirby
- Centers for Disease Control and Prevention,
National Center for Emerging and Zoonotic Infectious
Diseases, 1600 Clifton Road, Atlanta, Georgia 30333, United
States
| | - Zachary A. Marsh
- Centers for Disease Control and Prevention,
National Center for Emerging and Zoonotic Infectious
Diseases, 1600 Clifton Road, Atlanta, Georgia 30333, United
States
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79
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Langan LM, O’Brien M, Rundell ZC, Back JA, Ryan BJ, Chambliss CK, Norman RS, Brooks BW. Comparative Analysis of RNA-Extraction Approaches and Associated Influences on RT-qPCR of the SARS-CoV-2 RNA in a University Residence Hall and Quarantine Location. ACS ES&T WATER 2022; 2:1929-1943. [PMID: 37552714 PMCID: PMC9063990 DOI: 10.1021/acsestwater.1c00476] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 05/09/2023]
Abstract
Wastewater-based epidemiology (WBE) provides an early warning and trend analysis approach for determining the presence of COVID-19 in a community and complements clinical testing in assessing the population level, even as viral loads fluctuate. Here, we evaluate combinations of two wastewater concentration methods (i.e., ultrafiltration and composite supernatant-solid), four pre-RNA extraction modifications, and three nucleic acid extraction kits using two different wastewater sampling locations. These consisted of a quarantine facility containing clinically confirmed COVID-19-positive inhabitants and a university residence hall. Of the combinations examined, composite supernatant-solid with pre-RNA extraction consisting of water concentration and RNA/DNA shield performed the best in terms of speed and sensitivity. Further, of the three nucleic acid extraction kits examined, the most variability was associated with the Qiagen kit. Focusing on the quarantine facility, viral concentrations measured in wastewater were generally significantly related to positive clinical cases, with the relationship dependent on method, modification, kit, target, and normalization, although results were variable-dependent on individual time points (Kendall's Tau-b (τ) = 0.17 to 0.6) or cumulatively (Kendall's Tau-b (τ) = -0.048 to 1). These observations can support laboratories establishing protocols to perform wastewater surveillance and monitoring efforts for COVID-19.
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Affiliation(s)
- Laura M. Langan
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Megan O’Brien
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Zach C. Rundell
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Jeffrey A. Back
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Benjamin J. Ryan
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
| | - C. Kevin Chambliss
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
- Department of Chemistry and Biochemistry,
Baylor University, One Bear Place #97348, Waco, Texas 76798,
United States
| | - R. Sean Norman
- Environmental Health Sciences, Arnold
School of Public Health, South Carolina, 921 Assembly Street, Columbia,
South Carolina 29208, United States
| | - Bryan W. Brooks
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
- Institute of Biomedical Studies, Baylor
University, One Bear Place #97224, Waco, Texas 76798, United
States
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80
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Duvallet C, Wu F, McElroy KA, Imakaev M, Endo N, Xiao A, Zhang J, Floyd-O'Sullivan R, Powell MM, Mendola S, Wilson ST, Cruz F, Melman T, Sathyanarayana CL, Olesen SW, Erickson TB, Ghaeli N, Chai P, Alm EJ, Matus M. Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States. ACS ES&T WATER 2022; 2:1899-1909. [PMID: 36380771 DOI: 10.1101/2021.09.08.21263283] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.
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Affiliation(s)
- Claire Duvallet
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Fuqing Wu
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- MIT Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, United States
| | - Kyle A McElroy
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Maxim Imakaev
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Noriko Endo
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Amy Xiao
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- MIT Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, United States
| | - Jianbo Zhang
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- MIT Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, United States
| | | | - Morgan M Powell
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Samuel Mendola
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Shane T Wilson
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Francis Cruz
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Tamar Melman
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States
| | | | - Scott W Olesen
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Timothy B Erickson
- Department of Emergency Medicine, Harvard Medical School, Boston, Massachusetts 02115, United States
- Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02115, United States
- Harvard Humanitarian Initiative, Cambridge, Massachusetts 02138, United States
| | - Newsha Ghaeli
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
| | - Peter Chai
- Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02115, United States
- The Fenway Institute, Boston, Massachusetts 02215, United States
- The Koch Institute for Integrated Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, United States
| | - Eric J Alm
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- MIT Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, United States
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States
| | - Mariana Matus
- Biobot Analytics, Inc., Cambridge, Massachusetts 02139, United States
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81
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Langan LM, O’Brien M, Lovin LM, Scarlett KR, Davis H, Henke AN, Seidel SE, Archer N, Lawrence E, Norman RS, Bojes HK, Brooks BW. Quantitative Reverse Transcription PCR Surveillance of SARS-CoV-2 Variants of Concern in Wastewater of Two Counties in Texas, United States. ACS ES&T WATER 2022; 2:2211-2224. [PMID: 37552718 PMCID: PMC9291321 DOI: 10.1021/acsestwater.2c00103] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 06/10/2022] [Accepted: 06/13/2022] [Indexed: 06/02/2023]
Abstract
After its emergence in late November/December 2019, the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2) rapidly spread globally. Recognizing that this virus is shed in feces of individuals and that viral RNA is detectable in wastewater, testing for SARS-CoV-2 in sewage collections systems has allowed for the monitoring of a community's viral burden. Over a 9 month period, the influents of two regional wastewater treatment facilities were concurrently examined for wild-type SARS-CoV-2 along with variants B.1.1.7 and B.1.617.2 incorporated as they emerged. Epidemiological data including new confirmed COVID-19 cases and associated hospitalizations and fatalities were tabulated within each location. RNA from SARS-CoV-2 was detectable in 100% of the wastewater samples, while variant detection was more variable. Quantitative reverse transcription PCR (RT-qPCR) results align with clinical trends for COVID-19 cases, and increases in COVID-19 cases were positively related with increases in SARS-CoV-2 RNA load in wastewater, although the strength of this relationship was location specific. Our observations demonstrate that clinical and wastewater surveillance of SARS-CoV-2 wild type and constantly emerging variants of concern can be combined using RT-qPCR to characterize population infection dynamics. This may provide an early warning for at-risk communities and increases in COVID-19 related hospitalizations.
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Affiliation(s)
- Laura M. Langan
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Megan O’Brien
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
- Department of Public Health, Baylor
University, One Bear Place #97343, Waco, Texas 76798, United
States
| | - Lea M. Lovin
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Kendall R. Scarlett
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Haley Davis
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Abigail N. Henke
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
- Department of Biology, Baylor
University, One Bear Place #97388, Waco, Texas 76798, United
States
| | - Sarah E. Seidel
- Center for Health
Statistics, Texas Department of State Health Services, Austin, Texas
78756, United States
| | - Natalie Archer
- Environmental Epidemiology and Disease Registries
Section, Texas Department of State Health Services, Austin,
Texas 78756, United States
| | - Eric Lawrence
- Environmental Epidemiology and Disease Registries
Section, Texas Department of State Health Services, Austin,
Texas 78756, United States
| | - R. Sean Norman
- Department of Environmental Health Sciences, Arnold School of
Public Health, University of South Carolina, 921 Assembly
Street Columbia, South Carolina 29208, United States
| | - Heidi K. Bojes
- Environmental Epidemiology and Disease Registries
Section, Texas Department of State Health Services, Austin,
Texas 78756, United States
| | - Bryan W. Brooks
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
- Department of Public Health, Baylor
University, One Bear Place #97343, Waco, Texas 76798, United
States
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82
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Birnbaum DP, Vilardi KJ, Anderson CL, Pinto AJ, Joshi NS. Simple Affinity-Based Method for Concentrating Viruses from Wastewater Using Engineered Curli Fibers. ACS ES&T WATER 2022; 2:1836-1843. [PMID: 36778666 PMCID: PMC9916486 DOI: 10.1021/acsestwater.1c00208] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Wastewater surveillance is a proven method for tracking community spread and prevalence of some infectious viral diseases. A primary concentration step is often used to enrich viral particles from wastewater prior to subsequent viral quantification and/or sequencing. Here, we present a simple procedure for concentrating viruses from wastewater using bacterial biofilm protein nanofibers known as curli fibers. Through simple genetic engineering, we produced curli fibers functionalized with single-domain antibodies (also known as nanobodies) specific for the coat protein of the model virus bacteriophage MS2. Using these modified fibers in a simple spin-down protocol, we demonstrated efficient concentration of MS2 in both phosphate-buffered saline (PBS) and in the wastewater matrix. Additionally, we produced nanobody-functionalized curli fibers capable of binding the spike protein of SARS-CoV-2, showing the versatility of the system. Our concentration protocol is simple to implement, can be performed quickly under ambient conditions, and requires only components produced through bacterial culture. We believe this technology represents an attractive alternative to existing concentration methods and warrants further research and optimization for field-relevant applications.
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Affiliation(s)
- Daniel P Birnbaum
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States; Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
| | - Katherine J Vilardi
- Department of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States
| | - Christopher L Anderson
- Department of Civil and Environmental Engineering, Northeastern University, Boston, Massachusetts 02115, United States
| | - Ameet J Pinto
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Neel S Joshi
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
| |
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83
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Application of machine learning for multi-community COVID-19 outbreak predictions with wastewater surveillance. PLoS One 2022; 17:e0277154. [DOI: 10.1371/journal.pone.0277154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 10/20/2022] [Indexed: 11/12/2022] Open
Abstract
The potential of wastewater-based epidemiology (WBE) as a surveillance and early warning tool for the COVID-19 outbreak has been demonstrated. For areas with limited testing capacity, wastewater surveillance can provide information on the disease dynamic at a community level. A predictive model is a key to generating quantitative estimates of the infected population. Modeling longitudinal wastewater data can be challenging as biomarkers in wastewater are susceptible to variations caused by multiple factors associated with the wastewater matrix and the sewersheds characteristics. As WBE is an emerging trend, the model should be able to address the uncertainties of wastewater from different sewersheds. We proposed exploiting machine learning and deep learning techniques, which are supported by the growing WBE data. In this article, we reviewed the existing predictive models, among which the emerging machine learning/deep learning models showed great potential. However, most models are built for individual sewersheds with few features extracted from the wastewater. To fulfill the research gap, we compared different time-series and non-time-series models for their short-term predictive performance of COVID-19 cases in 9 diverse sewersheds. The time-series models, long short-term memory (LSTM) and Prophet, outcompeted the non-time-series models. Besides viral (SARS-CoV-2) loads and location identity, domain-specific features like biochemical parameters of wastewater, geographical parameters of the sewersheds, and some socioeconomic parameters of the communities can contribute to the models. With proper feature engineering and hyperparameter tuning, we believe machine learning models like LSTM can be a feasible solution for the COVID-19 trend prediction via WBE. Overall, this is a proof-of-concept study on the application of machine learning in COVID-19 WBE. Future studies are needed to deploy and maintain the model in more real-world applications.
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Cutrupi F, Cadonna M, Manara S, Postinghel M, La Rosa G, Suffredini E, Foladori P. The wave of the SARS-CoV-2 Omicron variant resulted in a rapid spike and decline as highlighted by municipal wastewater surveillance. ENVIRONMENTAL TECHNOLOGY & INNOVATION 2022; 28:102667. [PMID: 35615435 PMCID: PMC9122782 DOI: 10.1016/j.eti.2022.102667] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/12/2022] [Accepted: 05/12/2022] [Indexed: 05/10/2023]
Abstract
This paper highlights the extraordinarily rapid spread of SARS-CoV-2 loads in wastewater that during the Omicron wave in December 2021-February 2022, compared with the profiles acquired in 2020-21 with 410 samples from two wastewater treatment plants (Trento+suburbs, 132,500 inhabitants). Monitoring of SARS-CoV-2 in wastewater focused on: (i) 3 samplings/week and analysis, (ii) normalization to calculate genomic units (GU) inh-1 d-1; (iii) calculation of a 7-day moving average to smooth daily fluctuations; (iv) comparison with the 'current active cases'/100,000 inh progressively affected by the mass vaccination. The time profiles of SARS-CoV-2 in wastewater matched the waves of active cases. In February-April 2021, a viral load of 1.0E+07 GU inh-1 d - 1 corresponded to 700 active cases/100,000 inh. In July-September 2021, although the low current active cases, sewage revealed an appreciable SARS-CoV-2 circulation (in this period 2.2E+07 GU inh-1 d-1 corresponded to 90 active cases/100,000 inh). Omicron was not detected in wastewater until mid-December 2021. The Omicron spread caused a 5-6 fold increase of the viral load in two weeks, reaching the highest peak (2.0-2.2E+08 GU inh-1 d-1 and 4500 active cases/100,000 inh) during the pandemic. In this period, wastewater surveillance anticipated epidemiological data by about 6 days. In winter 2021-22, despite the 4-7 times higher viral loads in wastewater, hospitalizations were 4 times lower than in winter 2020-21 due to the vaccination coverage >80%. The Omicron wave demonstrated that SARS-CoV-2 monitoring of wastewater anticipated epidemiological data, confirming its importance in long-term surveillance.
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Affiliation(s)
- Francesca Cutrupi
- Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy
| | - Maria Cadonna
- ADEP, Agenzia per la Depurazione (Wastewater Treatment Agency), Autonomous Province of Trento, via Gilli 3, 38121 Trento, Italy
| | - Serena Manara
- Department of Cellular Computational and Integrative Biology-CIBIO, Via Sommarive 9, 38123 Trento, Italy
| | - Mattia Postinghel
- ADEP, Agenzia per la Depurazione (Wastewater Treatment Agency), Autonomous Province of Trento, via Gilli 3, 38121 Trento, Italy
| | - Giuseppina La Rosa
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - Elisabetta Suffredini
- Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
| | - Paola Foladori
- Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy
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A Metagenomic Investigation of Spatial and Temporal Changes in Sewage Microbiomes across a University Campus. mSystems 2022; 7:e0065122. [PMID: 36121163 PMCID: PMC9599454 DOI: 10.1128/msystems.00651-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Wastewater microbial communities are not static and can vary significantly across time and space, but this variation and the factors driving the observed spatiotemporal variation often remain undetermined. We used a shotgun metagenomic approach to investigate changes in wastewater microbial communities across 17 locations in a sewer network, with samples collected from each location over a 3-week period. Fecal material-derived bacteria constituted a relatively small fraction of the taxa found in the collected samples, highlighting the importance of environmental sources to the sewage microbiome. The prokaryotic communities were highly variable in composition depending on the location within the sampling network, and this spatial variation was most strongly associated with location-specific differences in sewage pH. However, we also observed substantial temporal variation in the composition of the prokaryotic communities at individual locations. This temporal variation was asynchronous across sampling locations, emphasizing the importance of independently considering both spatial and temporal variation when assessing the wastewater microbiome. The spatiotemporal patterns in viral community composition closely tracked those of the prokaryotic communities, allowing us to putatively identify the bacterial hosts of some of the dominant viruses in these systems. Finally, we found that antibiotic resistance gene profiles also exhibit a high degree of spatiotemporal variability, with most of these genes unlikely to be derived from fecal bacteria. Together, these results emphasize the dynamic nature of the wastewater microbiome, the challenges associated with studying these systems, and the utility of metagenomic approaches for building a multifaceted understanding of these microbial communities and their functional attributes. IMPORTANCE Sewage systems harbor extensive microbial diversity, including microbes derived from both human and environmental sources. Studies of the sewage microbiome are useful for monitoring public health and the health of our infrastructure, but the sewage microbiome can be highly variable in ways that are often unresolved. We sequenced DNA recovered from wastewater samples collected over a 3-week period at 17 locations in a single sewer system to determine how these communities vary across time and space. Most of the wastewater bacteria, and the antibiotic resistance genes they harbor, were not derived from human feces, but human usage patterns did impact how the amounts and types of bacteria and bacterial genes we found in these systems varied over time. Likewise, the wastewater communities, including both bacteria and their viruses, varied depending on location within the sewage network, highlighting the challenges and opportunities in efforts to monitor and understand the sewage microbiome.
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Jakariya M, Ahmed F, Islam MA, Al Marzan A, Hasan MN, Hossain M, Ahmed T, Hossain A, Reza HM, Hossen F, Nahla T, Rahman MM, Bahadur NM, Islam MT, Didar-Ul-Alam M, Mow N, Jahan H, Barceló D, Bibby K, Bhattacharya P. Wastewater-based epidemiological surveillance to monitor the prevalence of SARS-CoV-2 in developing countries with onsite sanitation facilities. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 311:119679. [PMID: 35753547 PMCID: PMC9225114 DOI: 10.1016/j.envpol.2022.119679] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 06/20/2022] [Accepted: 06/21/2022] [Indexed: 05/23/2023]
Abstract
Wastewater-based epidemiology (WBE) has emerged as a valuable approach for forecasting disease outbreaks in developed countries with a centralized sewage infrastructure. On the other hand, due to the absence of well-defined and systematic sewage networks, WBE is challenging to implement in developing countries like Bangladesh where most people live in rural areas. Identification of appropriate locations for rural Hotspot Based Sampling (HBS) and urban Drain Based Sampling (DBS) are critical to enable WBE based monitoring system. We investigated the best sampling locations from both urban and rural areas in Bangladesh after evaluating the sanitation infrastructure for forecasting COVID-19 prevalence. A total of 168 wastewater samples were collected from 14 districts of Bangladesh during each of the two peak pandemic seasons. RT-qPCR commercial kits were used to target ORF1ab and N genes. The presence of SARS-CoV-2 genetic materials was found in 98% (165/168) and 95% (160/168) wastewater samples in the first and second round sampling, respectively. Although wastewater effluents from both the marketplace and isolation center drains were found with the highest amount of genetic materials according to the mixed model, quantifiable SARS-CoV-2 RNAs were also identified in the other four sampling sites. Hence, wastewater samples of the marketplace in rural areas and isolation centers in urban areas can be considered the appropriate sampling sites to detect contagion hotspots. This is the first complete study to detect SARS-CoV-2 genetic components in wastewater samples collected from rural and urban areas for monitoring the COVID-19 pandemic. The results based on the study revealed a correlation between viral copy numbers in wastewater samples and SARS-CoV-2 positive cases reported by the Directorate General of Health Services (DGHS) as part of the national surveillance program for COVID-19 prevention. The findings of this study will help in setting strategies and guidelines for the selection of appropriate sampling sites, which will facilitate in development of comprehensive wastewater-based epidemiological systems for surveillance of rural and urban areas of low-income countries with inadequate sewage infrastructure.
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Affiliation(s)
- Md Jakariya
- Department of Environmental Science and Management, North South University, Bashundhara, Dhaka, 1229, Bangladesh
| | - Firoz Ahmed
- COVID-19 Diagnostic Laboratory, Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh
| | - Md Aminul Islam
- COVID-19 Diagnostic Laboratory, Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh; Advanced Molecular Laboratory, Department of Microbiology, President Abdul Hamid Medical College, Karimganj, Kishoreganj, Bangladesh
| | - Abdullah Al Marzan
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh
| | - Mohammad Nayeem Hasan
- Department of Statistics, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh
| | - Maqsud Hossain
- Department of Biochemistry and Microbiology, North South University, Bashundhara, Dhaka, 1229, Bangladesh
| | - Tanvir Ahmed
- Department of Civil Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh
| | - Ahmed Hossain
- Department of Public Health, North South University, Bashundhara, Dhaka, 1229, Bangladesh
| | - Hasan Mahmud Reza
- Department of Pharmaceutical Sciences, North South University, Bashundhara, Dhaka, 1229, Bangladesh
| | - Foysal Hossen
- COVID-19 Diagnostic Laboratory, Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh
| | - Turasa Nahla
- Department of Environmental Science and Management, North South University, Bashundhara, Dhaka, 1229, Bangladesh
| | - Mohammad Moshiur Rahman
- Department of Environmental Science and Management, North South University, Bashundhara, Dhaka, 1229, Bangladesh
| | - Newaz Mohammed Bahadur
- Department of Applied Chemistry and Chemical Engineering, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh
| | - Md Tahmidul Islam
- WaterAid Bangladesh, Dhaka, 1213, Bangladesh; COVID-19 Research@KTH, Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, Teknikringen 10B, SE-10044, Stockholm, Sweden
| | - Md Didar-Ul-Alam
- Noakhali Science and Technology University, Noakhali, 3814, Bangladesh
| | - Nowrin Mow
- WaterAid Bangladesh, Dhaka, 1213, Bangladesh
| | - Hasin Jahan
- WaterAid Bangladesh, Dhaka, 1213, Bangladesh
| | - Damiá Barceló
- Water, Environmental and Food Chemistry Unit (ENFOCHEM), Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA), Spanish National Research Council (CSIC), C. Jordi Giron 18-26, 08034, Barcelona, Spain
| | - Kyle Bibby
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Prosun Bhattacharya
- COVID-19 Research@KTH, Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, Teknikringen 10B, SE-10044, Stockholm, Sweden.
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Mahlknecht J. Presence and persistence of SARS-CoV-2 in aquatic environments: A mini-review. CURRENT OPINION IN ENVIRONMENTAL SCIENCE & HEALTH 2022; 29:100385. [PMID: 35992049 PMCID: PMC9382236 DOI: 10.1016/j.coesh.2022.100385] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The introduction of SARS-CoV-2 into water bodies via sewage raises public health concerns. For the assessment of public health risks, it is necessary to know the presence and persistence of infectious SARS-CoV-2 in water and wastewater. The present mini-review documents the occurrence and decay rates of viable infectious SARS-CoV-2 and SARS-CoV-2 RNA in different water matrices including wastewater, river water, groundwater, tap water, and seawater. Persistence of viable SARS-CoV-2 is mainly temperature dependent. A rapid inactivation of infectious SARS-CoV-2 is found in river water, sea water, and wastewater compared to tap water. SARS-CoV-2 RNA was found to be considerably more stable than infectious SARS-CoV-2, indicating that the environmental detection of RNA alone does not prove risk of infection. Persistence assays need to consider physicochemical and biological water composition as well as the effect of detergents, enzymes, and filtering particulate matter.
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Affiliation(s)
- Jürgen Mahlknecht
- Escuela de Ingenieria y Ciencias, Tecnologico de Monterrey, Campus Monterrey, Eugenio Garza Sada 2501, Monterrey, 64849, Nuevo Leon, Mexico
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88
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de Freitas Bueno R, Claro ICM, Augusto MR, Duran AFA, Camillo LDMB, Cabral AD, Sodré FF, Brandão CCS, Vizzotto CS, Silveira R, de Melo Mendes G, Arruda AF, de Brito NN, Machado BAS, Duarte GRM, de Lourdes Aguiar-Oliveira M. Wastewater-based epidemiology: A Brazilian SARS-COV-2 surveillance experience. JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING 2022; 10:108298. [PMID: 35873721 PMCID: PMC9295330 DOI: 10.1016/j.jece.2022.108298] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 07/05/2022] [Accepted: 07/17/2022] [Indexed: 05/11/2023]
Abstract
Since 2020, developed countries have rapidly shared both publicly and academically relevant wastewater surveillance information. Data on SARS-CoV-2 circulation is pivotal for guiding public health policies and improving the COVID-19 pandemic response. Conversely, low- and middle-income countries, such as Latin America and the Caribbean, showed timid activities in the Wastewater-Based Epidemiology (WBE) context. In these countries, isolated groups perform viral wastewater monitoring, and the data are unevenly shared or accessible to health agencies and the scientific community. This manuscript aims to highlight the relevance of a multiparty effort involving research, public health, and governmental agencies to support usage of WBE methodology to its full potential during the COVID-19 pandemic as part of a joint One Health surveillance approach. Thus, in this study, we explored the results obtained from wastewater surveillance in different regions of Brazil as a part of the COVID-19 Wastewater Monitoring Network ANA (National Water Agency), MCTI (Ministry of Science, Technology, and Innovations) and MS (Ministry of Health). Over the epidemiological weeks of 2021 and early 2022, viral RNA concentrations in wastewater followed epidemiological trends and variations. The highest viral loads in wastewater samples were detected during the second Brazilian wave of COVID-19. Corroborating international reports, our experience demonstrated usefulness of the WBE approach in viral surveillance. Wastewater surveillance allows hotspot identification, and therefore, early public health interventions. In addition, this methodology allows tracking of asymptomatic and oligosymptomatic individuals, who are generally underreported, especially in emerging countries with limited clinical testing capacity. Therefore, WBE undoubtedly contributes to improving public health responses in the context of this pandemic, as well as other sanitary emergencies.
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Affiliation(s)
- Rodrigo de Freitas Bueno
- Federal University of ABC. Center of Engineering, Modelling and Applied Social Sciences (CECS), Santo Andre, São Paulo, Brazil
| | - Ieda Carolina Mantovani Claro
- Federal University of ABC. Center of Engineering, Modelling and Applied Social Sciences (CECS), Santo Andre, São Paulo, Brazil
| | - Matheus Ribeiro Augusto
- Federal University of ABC. Center of Engineering, Modelling and Applied Social Sciences (CECS), Santo Andre, São Paulo, Brazil
| | - Adriana Feliciano Alves Duran
- Federal University of ABC. Center of Engineering, Modelling and Applied Social Sciences (CECS), Santo Andre, São Paulo, Brazil
| | | | - Aline Diniz Cabral
- Federal University of ABC. Center of Engineering, Modelling and Applied Social Sciences (CECS), Santo Andre, São Paulo, Brazil
| | | | | | - Carla Simone Vizzotto
- University of Brasilia, Department of Civil and Environmental Engineering, Brasília, Federal District, Brazil
| | - Rafaella Silveira
- University of Brasilia. Institute of Chemistry, Brasília, Federal District, Brazil
- University of Brasilia, Department of Civil and Environmental Engineering, Brasília, Federal District, Brazil
| | | | | | | | - Bruna Aparecida Souza Machado
- University Center SENAI/CIMATEC. SENAI Institute of Innovation (ISI) in Health Advanced Systems (CIMATEC ISI SAS), Salvador, Bahia, Brazil
| | | | - Maria de Lourdes Aguiar-Oliveira
- Laboratory of Respiratory Viruses and Measles, National/MoH and International/WHO Reference Laboratory in COVID-19, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro, Brazil
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89
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MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes. PLoS Comput Biol 2022; 18:e1010472. [PMID: 36149894 PMCID: PMC9534451 DOI: 10.1371/journal.pcbi.1010472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 10/05/2022] [Accepted: 08/05/2022] [Indexed: 11/19/2022] Open
Abstract
The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa’s relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome. Wastewater-based epidemiology (WBE) is an emerging field that employs sewage as aggregated samples of human populations. This approach is particularly promising for tracking diseases that can spread asymptomatically in large populations, such as the COVID-19. As a new type of biological data, sewage has its own unique challenges to utilize. While wastewater samples are usually assumed to represent large populations, the assumption is not guaranteed at locations closer to residences due to stochasticity in toilet flushes; thus, unlike epidemiological experiments collecting data from individuals, sample size, herein the human population size represented by a wastewater sample, is a fundamental yet difficult-to-characterize parameter for sewage samples. Researchers would need to aggregate data from large areas and week-long collection to stabilize data, during which, important spikes in small areas or short time scales may be lost. It also remains challenging to turn viral titers into case prevalences, evaluating representativeness, or comparing measurements across sites/studies. This study provides a framework to estimate human population size from sewage utilizing human gut-associated microorganisms. Through analysis, we demonstrate that variance of taxon abundances and single-nucleotide polymorphism as two variables that change with population size. We provide a new tool MicrobiomeCensus that performs population size estimation from microbial taxon abundances. MicrobiomeCensus outperforms generic algorithms in terms of computational efficiency while at comparable or better accuracy. Using MicrobiomeCensus, we detected population size differences in sewage samples taken in Cambridge, MA, under two sampling approaches, i.e., “grab” or “composite” sampling. This study provides a framework to utilize individual-level microbiomes to learn from sewage, paving the way to prevalence estimation and improved spatio-temporal resolutions in WBE.
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90
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Cao H, Mao K, Ran F, Xu P, Zhao Y, Zhang X, Zhou H, Yang Z, Zhang H, Jiang G. Paper Device Combining CRISPR/Cas12a and Reverse-Transcription Loop-Mediated Isothermal Amplification for SARS-CoV-2 Detection in Wastewater. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:13245-13253. [PMID: 36040863 PMCID: PMC9454323 DOI: 10.1021/acs.est.2c04727] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 08/16/2022] [Accepted: 08/17/2022] [Indexed: 05/04/2023]
Abstract
Wastewater-based surveillance of the COVID-19 pandemic holds great promise; however, a point-of-use detection method for SARS-CoV-2 in wastewater is lacking. Here, a portable paper device based on CRISPR/Cas12a and reverse-transcription loop-mediated isothermal amplification (RT-LAMP) with excellent sensitivity and specificity was developed for SARS-CoV-2 detection in wastewater. Three primer sets of RT-LAMP and guide RNAs (gRNAs) that could lead Cas12a to recognize target genes via base pairing were used to perform the high-fidelity RT-LAMP to detect the N, E, and S genes of SARS-CoV-2. Due to the trans-cleavage activity of CRISPR/Cas12a after high-fidelity amplicon recognition, carboxyfluorescein-ssDNA-Black Hole Quencher-1 and carboxyfluorescein-ssDNA-biotin probes were adopted to realize different visualization pathways via a fluorescence or lateral flow analysis, respectively. The reactions were integrated into a paper device for simultaneously detecting the N, E, and S genes with limits of detection (LODs) of 25, 310, and 10 copies/mL, respectively. The device achieved a semiquantitative analysis from 0 to 310 copies/mL due to the different LODs of the three genes. Blind experiments demonstrated that the device was suitable for wastewater analysis with 97.7% sensitivity and 82% semiquantitative accuracy. This is the first semiquantitative endpoint detection of SARS-CoV-2 in wastewater via different LODs, demonstrating a promising point-of-use method for wastewater-based surveillance.
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Affiliation(s)
- Haorui Cao
- State Key Laboratory of Environmental Geochemistry,
Institute of Geochemistry, Chinese Academy of Sciences,
Guiyang550081, China
- University of Chinese Academy of
Sciences, Beijing100049, China
| | - Kang Mao
- State Key Laboratory of Environmental Geochemistry,
Institute of Geochemistry, Chinese Academy of Sciences,
Guiyang550081, China
| | - Fang Ran
- State Key Laboratory of Environmental Geochemistry,
Institute of Geochemistry, Chinese Academy of Sciences,
Guiyang550081, China
| | - Pengqi Xu
- Precision Medicine Center, The Seventh
Affiliated Hospital, Sun Yat-sen University, Shenzhen518107,
China
| | - Yirong Zhao
- State Key Laboratory of Environmental Geochemistry,
Institute of Geochemistry, Chinese Academy of Sciences,
Guiyang550081, China
- University of Chinese Academy of
Sciences, Beijing100049, China
| | - Xiangyan Zhang
- Guizhou Provincial People’s
Hospital, Guiyang550002, China
| | - Hourong Zhou
- Guizhou Provincial People’s
Hospital, Guiyang550002, China
- Jiangjunshan Hospital of Guizhou
Province, Guiyang550001, China
| | - Zhugen Yang
- School of Water, Energy, and Environment,
Cranfield University, CranfieldMK43 0AL,
UK
| | - Hua Zhang
- State Key Laboratory of Environmental Geochemistry,
Institute of Geochemistry, Chinese Academy of Sciences,
Guiyang550081, China
| | - Guibin Jiang
- State Key Laboratory of Environmental Chemistry and
Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing100085, China
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91
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McGowan J, Borucki M, Omairi H, Varghese M, Vellani S, Chakravarty S, Fan S, Chattopadhyay S, Siddiquee M, Thissen JB, Mulakken N, Moon J, Kimbrel J, Tiwari AK, Taylor RT, Kang DW, Jaing C, Chakravarti R, Chattopadhyay S. SARS-CoV-2 Monitoring in Wastewater Reveals Novel Variants and Biomarkers of Infection. Viruses 2022; 14:2032. [PMID: 36146835 PMCID: PMC9503862 DOI: 10.3390/v14092032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 09/06/2022] [Accepted: 09/09/2022] [Indexed: 12/02/2022] Open
Abstract
Wastewater-based epidemiology (WBE) is a popular tool for the early indication of community spread of infectious diseases. WBE emerged as an effective tool during the COVID-19 pandemic and has provided meaningful information to minimize the spread of infection. Here, we present a combination of analyses using the correlation of viral gene copies with clinical cases, sequencing of wastewater-derived RNA for the viral mutants, and correlative analyses of the viral gene copies with the bacterial biomarkers. Our study provides a unique platform for potentially using the WBE-derived results to predict the spread of COVID-19 and the emergence of new variants of concern. Further, we observed a strong correlation between the presence of SARS-CoV-2 and changes in the microbial community of wastewater, particularly the significant changes in bacterial genera belonging to the families of Lachnospiraceae and Actinomycetaceae. Our study shows that microbial biomarkers could be utilized as prediction tools for future infectious disease surveillance and outbreak responses. Overall, our comprehensive analyses of viral spread, variants, and novel bacterial biomarkers will add significantly to the growing body of literature on WBE and COVID-19.
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Affiliation(s)
- Jenna McGowan
- Physiology and Pharmacology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Monica Borucki
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Hicham Omairi
- Department of Civil and Environmental Engineering, University of Toledo College of Engineering, Toledo, OH 43607, USA
| | - Merina Varghese
- Medical Microbiology and Immunology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Shahnaz Vellani
- Physiology and Pharmacology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Sukanya Chakravarty
- Medical Microbiology and Immunology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Shumin Fan
- Medical Microbiology and Immunology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Srestha Chattopadhyay
- College of Pharmacy and Pharmaceutical Sciences, University of Toledo, Toledo, OH 43606, USA
| | - Mashuk Siddiquee
- Department of Civil and Environmental Engineering, University of Toledo College of Engineering, Toledo, OH 43607, USA
| | - James B. Thissen
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Nisha Mulakken
- Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Joseph Moon
- Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Jeffrey Kimbrel
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Amit K. Tiwari
- College of Pharmacy and Pharmaceutical Sciences, University of Toledo, Toledo, OH 43606, USA
- Center for Medical Bio-Allied Health Sciences Research, Ajman University, Ajman P.O. Box 346, United Arab Emirates
| | - Roger Travis Taylor
- Medical Microbiology and Immunology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Dae-Wook Kang
- Department of Civil and Environmental Engineering, University of Toledo College of Engineering, Toledo, OH 43607, USA
| | - Crystal Jaing
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Ritu Chakravarti
- Physiology and Pharmacology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
| | - Saurabh Chattopadhyay
- Medical Microbiology and Immunology, University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA
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92
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de Sousa ARV, do Carmo Silva L, de Curcio JS, da Silva HD, Eduardo Anunciação C, Maria Salem Izacc S, Neto FOS, de Paula Silveira Lacerda E. "pySewage": a hybrid approach to predict the number of SARS-CoV-2-infected people from wastewater in Brazil. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:67260-67269. [PMID: 35524091 PMCID: PMC9075719 DOI: 10.1007/s11356-022-20609-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 04/30/2022] [Indexed: 05/21/2023]
Abstract
It is well known that the new coronavirus pandemic has global environmental, public health, and economic implications. In this sense, this study aims to monitor SARS-CoV-2 in the largest wastewater treatment plant of Goiânia, which processes wastewater from more than 700,000 inhabitants, and to correlate the molecular and clinical data collected. Influent and effluent samples were collected at Dr. Helio de Seixo Britto's wastewater treatment plant from January to August 2021. Viral concentration was performed with polyethylene glycol before viral RNA extraction. Real-time qPCR (N1 and N2 gene assays) was performed to detect and quantify the viral RNA present in the samples. The results showed that 43.63% of the samples were positive. There is no significant difference between the detection of primers N1 (mean 3.23 log10 genome copies/L, std 0.23) and N2 (mean 2.95 log10 genome copies/L, std 0.29); also, there is no significant difference between the detection of influent and effluent samples. Our molecular data revealed a positive correlation with clinical data, and infection prevalence was higher than clinical data. In addition, we developed a user-friendly web application to predict the number of infected people based on the detection of viral load present in wastewater samples and may be applied as a public policy strategy for monitoring ongoing outbreaks.
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Affiliation(s)
| | - Lívia do Carmo Silva
- Department of Genetics, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
| | - Juliana Santana de Curcio
- Department of Genetics, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
| | - Hugo Delleon da Silva
- Department of Genetics, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
- Universitary Center of Goiás (UNIGOIÁS), Goiânia, Goiás, Brazil
| | - Carlos Eduardo Anunciação
- Department of Biochemistry and Molecular Biology, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
| | - Silvia Maria Salem Izacc
- Department of Genetics, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
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93
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Estévez-Danta A, Bijlsma L, Capela R, Cela R, Celma A, Hernández F, Lertxundi U, Matias J, Montes R, Orive G, Prieto A, Santos MM, Rodil R, Quintana JB. Use of illicit drugs, alcohol and tobacco in Spain and Portugal during the COVID-19 crisis in 2020 as measured by wastewater-based epidemiology. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 836:155697. [PMID: 35523346 PMCID: PMC9065690 DOI: 10.1016/j.scitotenv.2022.155697] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 04/27/2022] [Accepted: 04/30/2022] [Indexed: 05/11/2023]
Abstract
The COVID-19 pandemic spread rapidly worldwide in the year 2020, which was initially restrained by drastic mobility restrictions. In this work, we investigated the use of illicit drugs (amphetamine, methamphetamine, ecstasy, cocaine and cannabis), and licit substances of abuse (alcohol and tobacco) during the earlier months (March-July 2020) of the pandemic restrictions in four Spanish (Bilbao and its metropolitan area, Vitoria-Gasteiz, Castellón and Santiago de Compostela) and two Portuguese (Porto and Vila do Conde) locations by wastewater-based epidemiology (WBE). The results show that no methamphetamine was detected in any of the locations monitored, while amphetamine use was only detectable in the two locations from the Basque Country (Bilbao and its metropolitan area and Vitoria-Gasteiz), with high estimated average usage rates (700-930 mg day-1 1000 inhabitant-1). The remaining substances were detected in all the investigated catchment areas. In general, no remarkable changes were found in population normalized loads compared to former years, except for cocaine (i.e. its main metabolite, benzoylecgonine). For this drug, a notable decrease in use was discernible in Castellón, while its usage in Porto and Santiago de Compostela seemed to continue in a rising trend, already initiated in former years. Furthermore, two events of ecstasy (3,4-methylenedioxymethamphetamine, MDMA) dumping in the sewage network were confirmed by enantiomeric analysis, one in Santiago de Compostela just prior the lockdown and the second one in the Bilbao and its metropolitan area in July after relieving the more stringent measures. The latter could also be associated with a police intervention. The comparison of WBE with (web) survey data, which do not provide information at a local level, points towards contradictory conclusions for some of the substances, thereby highlighting the need for stable WBE networks capable of near real-time monitoring drug use.
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Affiliation(s)
- Andrea Estévez-Danta
- Department of Analytical Chemistry, Nutrition and Food Sciences, Institute of Research on Chemical and Biological Analysis (IAQBUS), Universidade de Santiago de Compostela, Constantino Candeira S/N, 15782 Santiago de Compostela, Spain
| | - Lubertus Bijlsma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda Sos Baynat s/n, 12071 Castellón, Spain
| | - Ricardo Capela
- CIMAR/CIIMAR, Interdisciplinary Centre of Marine and Environmental Research, Group of Endocrine Disrupter and Emerging Contaminants, University of Porto, Avenida General Norton de Matos s/n, 4450-208 Matosinhos, Portugal; FCUP-Department of Biology, Faculty of Sciences, University of Porto, Rua Do Campo Alegre, 4169-007 Porto, Portugal
| | - Rafael Cela
- Department of Analytical Chemistry, Nutrition and Food Sciences, Institute of Research on Chemical and Biological Analysis (IAQBUS), Universidade de Santiago de Compostela, Constantino Candeira S/N, 15782 Santiago de Compostela, Spain
| | - Alberto Celma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda Sos Baynat s/n, 12071 Castellón, Spain
| | - Félix Hernández
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda Sos Baynat s/n, 12071 Castellón, Spain
| | - Unax Lertxundi
- Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba Mental Health Network, Araba Psychiatric Hospital, Pharmacy Service, c/Alava 43, 01006 Vitoria-Gasteiz, Alava, Spain
| | - João Matias
- European Monitoring Centre for Drugs and Drug Addiction, 1249-289 Lisbon, Portugal
| | - Rosa Montes
- Department of Analytical Chemistry, Nutrition and Food Sciences, Institute of Research on Chemical and Biological Analysis (IAQBUS), Universidade de Santiago de Compostela, Constantino Candeira S/N, 15782 Santiago de Compostela, Spain
| | - Gorka Orive
- NanoBioCel Group, Laboratory of Pharmaceutics, School of Pharmacy, University of the Basque Country UPV/EHU, Paseo de la Universidad 7, Vitoria-Gasteiz 01006, Spain; Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Vitoria-Gasteiz, Spain; University Institute for Regenerative Medicine and Oral Implantology - UIRMI (UPV/EHU-Fundación Eduardo Anitua), Vitoria-Gasteiz, Spain; Singapore Eye Research Institute, The Academia, 20 College Road, Discovery Tower, Singapore; Bioaraba, NanoBioCel Research Group, Vitoria-Gasteiz, Spain
| | - Ailette Prieto
- Department of Analytical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Basque Country, Spain; Research Centre for Experimental Marine Biology and Biotechnology (PIE), University of the Basque Country (UPV/EHU), Plentzia, Basque Country, Spain
| | - Miguel M Santos
- CIMAR/CIIMAR, Interdisciplinary Centre of Marine and Environmental Research, Group of Endocrine Disrupter and Emerging Contaminants, University of Porto, Avenida General Norton de Matos s/n, 4450-208 Matosinhos, Portugal; FCUP-Department of Biology, Faculty of Sciences, University of Porto, Rua Do Campo Alegre, 4169-007 Porto, Portugal
| | - Rosario Rodil
- Department of Analytical Chemistry, Nutrition and Food Sciences, Institute of Research on Chemical and Biological Analysis (IAQBUS), Universidade de Santiago de Compostela, Constantino Candeira S/N, 15782 Santiago de Compostela, Spain.
| | - José Benito Quintana
- Department of Analytical Chemistry, Nutrition and Food Sciences, Institute of Research on Chemical and Biological Analysis (IAQBUS), Universidade de Santiago de Compostela, Constantino Candeira S/N, 15782 Santiago de Compostela, Spain.
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94
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Vo V, Tillett RL, Papp K, Shen S, Gu R, Gorzalski A, Siao D, Markland R, Chang CL, Baker H, Chen J, Schiller M, Betancourt WQ, Buttery E, Pandori M, Picker MA, Gerrity D, Oh EC. Use of wastewater surveillance for early detection of Alpha and Epsilon SARS-CoV-2 variants of concern and estimation of overall COVID-19 infection burden. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 835:155410. [PMID: 35469875 PMCID: PMC9026949 DOI: 10.1016/j.scitotenv.2022.155410] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 04/15/2022] [Accepted: 04/16/2022] [Indexed: 05/14/2023]
Abstract
A decline in diagnostic testing for SARS-CoV-2 is expected to delay the tracking of COVID-19 variants of concern and interest in the United States. We hypothesize that wastewater surveillance programs provide an effective alternative for detecting emerging variants and assessing COVID-19 incidence, particularly when clinical surveillance is limited. Here, we analyzed SARS-CoV-2 RNA in wastewater from eight locations across Southern Nevada between March 2020 and April 2021. Trends in SARS-CoV-2 RNA concentrations (ranging from 4.3 log10 gc/L to 8.7 log10 gc/L) matched trends in confirmed COVID-19 incidence, but wastewater surveillance also highlighted several limitations with the clinical data. Amplicon-based whole genome sequencing (WGS) of 86 wastewater samples identified the B.1.1.7 (Alpha) and B.1.429 (Epsilon) lineages in December 2020, but clinical sequencing failed to identify the variants until January 2021, thereby demonstrating that 'pooled' wastewater samples can sometimes expedite variant detection. Also, by calibrating fecal shedding (11.4 log10 gc/infection) and wastewater surveillance data to reported seroprevalence, we estimate that ~38% of individuals in Southern Nevada had been infected by SARS-CoV-2 as of April 2021, which is significantly higher than the 10% of individuals confirmed through clinical testing. Sewershed-specific ascertainment ratios (i.e., X-fold infection undercounts) ranged from 1.0 to 7.7, potentially due to demographic differences. Our data underscore the growing application of wastewater surveillance in not only the identification and quantification of infectious agents, but also the detection of variants of concern that may be missed when diagnostic testing is limited or unavailable.
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Affiliation(s)
- Van Vo
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Richard L Tillett
- Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Katerina Papp
- Southern Nevada Water Authority, P.O. Box 99954, Las Vegas, NV, 89193, USA
| | - Shirley Shen
- Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Richard Gu
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | | | - Danielle Siao
- Nevada State Public Health Laboratory, Reno, NV 89597, USA
| | - Rayma Markland
- Southern Nevada Public Health Laboratory of the Southern Nevada Health District, Las Vegas, NV 89106, USA
| | - Ching-Lan Chang
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Hayley Baker
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Jingchun Chen
- Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Martin Schiller
- Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Walter Q Betancourt
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Erin Buttery
- Southern Nevada Public Health Laboratory of the Southern Nevada Health District, Las Vegas, NV 89106, USA
| | - Mark Pandori
- Nevada State Public Health Laboratory, Reno, NV 89597, USA
| | - Michael A Picker
- Southern Nevada Public Health Laboratory of the Southern Nevada Health District, Las Vegas, NV 89106, USA
| | - Daniel Gerrity
- Southern Nevada Water Authority, P.O. Box 99954, Las Vegas, NV, 89193, USA.
| | - Edwin C Oh
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Department of Internal Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA.
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95
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Holton E, Sims N, Jagadeesan K, Standerwick R, Kasprzyk-Hordern B. Quantifying community-wide antimicrobials usage via wastewater-based epidemiology. JOURNAL OF HAZARDOUS MATERIALS 2022; 436:129001. [PMID: 35594673 DOI: 10.1016/j.jhazmat.2022.129001] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 04/19/2022] [Accepted: 04/21/2022] [Indexed: 06/15/2023]
Abstract
Increasing usage of antimicrobials is a significant contributor to the emergence and dissemination of antimicrobial resistance. Wastewater-based epidemiology is a useful tool for evaluating public health, via the monitoring of chemical and biological markers in wastewater influent, such as antibiotics. Sixteen antimicrobials and their metabolites were studied: sulfonamides, trimethoprim, metronidazole, quinolones, nitrofurantoin, cyclines, and antiretrovirals. Correction factors (CFs) for human drug excretion, for various drug forms, were determined via a systematic literature review of pharmacokinetic research. Analyte stability was examined over a 24 h study. The estimation of community-wide drug intake was evaluated using the corresponding catchment prescription data. Overall, antimicrobials excreted in an unchanged form were often observed to over-estimate daily intake. This could be attributed to biotransformation, e.g., via glucuronide cleavage, or direct disposal of unused drugs. Acetyl-sulfonamides, trimethoprim, hydroxy-metronidazole, clarithromycin, ciprofloxacin, ofloxacin, tetracycline, and oxytetracycline generally performed well in the estimation of drug intake, relative to prescription records. The low prevalence of quinolone and trimethoprim metabolites, and the low stability of nitrofurantoin, limited the ability to evaluate these metabolites and their respective CFs.
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Affiliation(s)
| | - Natalie Sims
- University of Bath, Department of Chemistry, Bath BA2 7AY, UK
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96
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Novoa B, Ríos-Castro R, Otero-Muras I, Gouveia S, Cabo A, Saco A, Rey-Campos M, Pájaro M, Fajar N, Aranguren R, Romero A, Panebianco A, Valdés L, Payo P, Alonso AA, Figueras A, Cameselle C. Wastewater and marine bioindicators surveillance to anticipate COVID-19 prevalence and to explore SARS-CoV-2 diversity by next generation sequencing: One-year study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 833:155140. [PMID: 35421481 PMCID: PMC8996449 DOI: 10.1016/j.scitotenv.2022.155140] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 04/05/2022] [Accepted: 04/05/2022] [Indexed: 05/13/2023]
Abstract
This study presents the results of SARS-CoV-2 surveillance in sewage water of 11 municipalities and marine bioindicators in Galicia (NW of Spain) from May 2020 to May 2021. An integrated pipeline was developed including sampling, pre-treatment and biomarker quantification, RNA detection, SARS-CoV-2 sequencing, mechanistic mathematical modeling and forecasting. The viral load in the inlet stream to the wastewater treatment plants (WWTP) was used to detect new outbreaks of COVID-19, and the data of viral load in the wastewater in combination with data provided by the health system was used to predict the evolution of the pandemic in the municipalities under study within a time horizon of 7 days. Moreover, the study shows that the viral load was eliminated from the treated sewage water in the WWTP, mainly in the biological reactors and the disinfection system. As a result, we detected a minor impact of the virus in the marine environment through the analysis of seawater, marine sediments and, wild and aquacultured mussels in the final discharge point of the WWTP.
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Affiliation(s)
- Beatriz Novoa
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | - Raquel Ríos-Castro
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | - Irene Otero-Muras
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain; Institute for Integrative Systems Biology I2SYSBIO (UV, CSIC), Spanish National Research Council, 46980 València, Spain
| | - Susana Gouveia
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain; University of Vigo, BiotecnIA Group, Department of Chemical Engineering, 36310 Vigo, Spain
| | - Adrián Cabo
- University of Vigo, BiotecnIA Group, Department of Chemical Engineering, 36310 Vigo, Spain; GESECO Aguas S.A. Vigo, Spain
| | - Amaro Saco
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | - Magalí Rey-Campos
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | - Manuel Pájaro
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain; CITIC Research Center, Department of Applied Mathematics, University of A Coruña, 15071 A Coruña, Spain
| | - Noelia Fajar
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | - Raquel Aranguren
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | - Alejandro Romero
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | - Antonella Panebianco
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | - Lorena Valdés
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | | | - Antonio A Alonso
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | - Antonio Figueras
- Marine Research Institute IIM-CSIC, Spanish National Research Council, 36208 Vigo, Spain
| | - Claudio Cameselle
- University of Vigo, BiotecnIA Group, Department of Chemical Engineering, 36310 Vigo, Spain.
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97
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Rothman JA, Saghir A, Chung SA, Boyajian N, Dinh T, Kim J, Oval J, Sharavanan V, York C, Zimmer-Faust AG, Langlois K, Steele JA, Griffith JF, Whiteson KL. Longitudinal metatranscriptomic sequencing of Southern California wastewater representing 16 million people from August 2020-21 reveals widespread transcription of antibiotic resistance genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2022.08.02.502560. [PMID: 35982656 PMCID: PMC9387120 DOI: 10.1101/2022.08.02.502560] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Municipal wastewater provides a representative sample of human fecal waste across a catchment area and contains a wide diversity of microbes. Sequencing wastewater samples provides information about human-associated and medically-important microbial populations, and may be useful to assay disease prevalence and antimicrobial resistance (AMR). Here, we present a study in which we used untargeted metatranscriptomic sequencing on RNA extracted from 275 sewage influent samples obtained from eight wastewater treatment plants (WTPs) representing approximately 16 million people in Southern California between August 2020 - August 2021. We characterized bacterial and viral transcripts, assessed metabolic pathway activity, and identified over 2,000 AMR genes/variants across all samples. Because we did not deplete ribosomal RNA, we have a unique window into AMR carried as ribosomal mutants. We show that AMR diversity varied between WTPs and that the relative abundance of many individual AMR genes/variants increased over time and may be connected to antibiotic use during the COVID-19 pandemic. Similarly, we detected transcripts mapping to human pathogenic bacteria and viruses suggesting RNA sequencing is a powerful tool for wastewater-based epidemiology and that there are geographical signatures to microbial transcription. We captured the transcription of gene pathways common to bacterial cell processes, including central carbon metabolism, nucleotide synthesis/salvage, and amino acid biosynthesis. We also posit that due to the ubiquity of many viruses and bacteria in wastewater, new biological targets for microbial water quality assessment can be developed. To the best of our knowledge, our study provides the most complete longitudinal metatranscriptomic analysis of a large population's wastewater to date and demonstrates our ability to monitor the presence and activity of microbes in complex samples. By sequencing RNA, we can track the relative abundance of expressed AMR genes/variants and metabolic pathways, increasing our understanding of AMR activity across large human populations and sewer sheds.
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Affiliation(s)
- Jason A. Rothman
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA
| | - Andrew Saghir
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA
| | - Seung-Ah Chung
- Genomics High-Throughput Facility, Department of Biological Chemistry, University of California, Irvine, Irvine, CA, USA
| | - Nicholas Boyajian
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA
| | - Thao Dinh
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA
| | - Jinwoo Kim
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA
| | - Jordan Oval
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA
| | - Vivek Sharavanan
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA
| | - Courtney York
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA
| | | | - Kylie Langlois
- Southern California Coastal Water Research Project, Costa Mesa, CA, USA
| | - Joshua A. Steele
- Southern California Coastal Water Research Project, Costa Mesa, CA, USA
| | - John F. Griffith
- Southern California Coastal Water Research Project, Costa Mesa, CA, USA
| | - Katrine L. Whiteson
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA
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98
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Soller J, Jennings W, Schoen M, Boehm A, Wigginton K, Gonzalez R, Graham KE, McBride G, Kirby A, Mattioli M. Modeling infection from SARS-CoV-2 wastewater concentrations: promise, limitations, and future directions. JOURNAL OF WATER AND HEALTH 2022; 20:1197-1211. [PMID: 36044189 PMCID: PMC10911093 DOI: 10.2166/wh.2022.094] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Estimating total infection levels, including unreported and asymptomatic infections, is important for understanding community disease transmission. Wastewater can provide a pooled community sample to estimate total infections that is independent of case reporting biases toward individuals with moderate to severe symptoms and by test-seeking behavior and access. We derive three mechanistic models for estimating community infection levels from wastewater measurements based on a description of the processes that generate SARS-CoV-2 RNA signals in wastewater and accounting for the fecal strength of wastewater through endogenous microbial markers, daily flow, and per-capita wastewater generation estimates. The models are illustrated through two case studies of wastewater data collected during 2020-2021 in Virginia Beach, VA, and Santa Clara County, CA. Median simulated infection levels generally were higher than reported cases, but at times, were lower, suggesting a discrepancy between the reported cases and wastewater data, or inaccurate modeling results. Daily simulated infection estimates showed large ranges, in part due to dependence on highly variable clinical viral fecal shedding data. Overall, the wastewater-based mechanistic models are useful for normalization of wastewater measurements and for understanding wastewater-based surveillance data for public health decision-making but are currently limited by lack of robust SARS-CoV-2 fecal shedding data.
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Affiliation(s)
- Jeffrey Soller
- Soller Environmental, LLC, 3022 King St, Berkeley, CA 94703, USA
| | - Wiley Jennings
- Waterborne Disease Prevention Branch, Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA E-mail:
| | - Mary Schoen
- Soller Environmental, LLC, 3022 King St, Berkeley, CA 94703, USA
| | - Alexandria Boehm
- Stanford University Department of Civil and Environmental Engineering, Stanford, California, USA
| | - Krista Wigginton
- Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor 48109, Michigan, USA
| | - Raul Gonzalez
- Hampton Roads Sanitation District, 1434 Air Rail Avenue, Virginia Beach, VA 23455, USA
| | - Katherine E Graham
- Stanford University Department of Civil and Environmental Engineering, Stanford, California, USA
| | - Graham McBride
- National Institute of Water & Atmospheric Research Ltd (NIWA), Hillcrest, Hamilton, New Zealand
| | - Amy Kirby
- Waterborne Disease Prevention Branch, Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA E-mail:
| | - Mia Mattioli
- Waterborne Disease Prevention Branch, Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA E-mail:
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99
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Kumar M, Jiang G, Kumar Thakur A, Chatterjee S, Bhattacharya T, Mohapatra S, Chaminda T, Kumar Tyagi V, Vithanage M, Bhattacharya P, Nghiem LD, Sarkar D, Sonne C, Mahlknecht J. Lead time of early warning by wastewater surveillance for COVID-19: Geographical variations and impacting factors. CHEMICAL ENGINEERING JOURNAL (LAUSANNE, SWITZERLAND : 1996) 2022; 441:135936. [PMID: 35345777 PMCID: PMC8942437 DOI: 10.1016/j.cej.2022.135936] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/07/2022] [Accepted: 03/19/2022] [Indexed: 05/05/2023]
Abstract
The global data on the temporal tracking of the COVID-19 through wastewater surveillance needs to be comparatively evaluated to generate a proper and precise understanding of the robustness, advantages, and sensitivity of the wastewater-based epidemiological (WBE) approach. We reviewed the current state of knowledge based on several scientific articles pertaining to temporal variations in COVID-19 cases captured via viral RNA predictions in wastewater. This paper primarily focuses on analyzing the WBE-based temporal variation reported globally to check if the reported early warning lead-time generated through environmental surveillance is pragmatic or latent. We have compiled the geographical variations reported as lead time in various WBE reports to strike a precise correlation between COVID-19 cases and genome copies detected through wastewater surveillance, with respect to the sampling dates, separately for WASH and non-WASH countries. We highlighted sampling methods, climatic and weather conditions that significantly affected the concentration of viral SARS-CoV-2 RNA detected in wastewater, and thus the lead time reported from the various climatic zones with diverse WASH situations were different. Our major findings are: i) WBE reports around the world are not comparable, especially in terms of gene copies detected, lag-time gained between monitored RNA peak and outbreak/peak of reported case, as well as per capita RNA concentrations; ii) Varying sanitation facility and climatic conditions that impact virus degradation rate are two major interfering features limiting the comparability of WBE results, and iii) WBE is better applicable to WASH countries having well-connected sewerage system.
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Affiliation(s)
- Manish Kumar
- Sustainability Cluster, School of Engineering, University of Petroleum & Energy Studies, Dehradun, Uttarakhand 248007, India
| | - Guangming Jiang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Australia
- Illawarra Health and Medical Research Institute (IHMRI), University of Wollongong, Wollongong, Australia
| | - Alok Kumar Thakur
- Discipline of Earth Science, Indian Institute of Technology Gandhinagar, Gujarat 382 355, India
| | - Shreya Chatterjee
- Encore Insoltech Pvt Ltd, Randesan, Gandhinagar, Gujarat 382 307, India
| | - Tanushree Bhattacharya
- Department of Civil and Environmental Engineering, Birla Institute of Technology, Mesra 835215, India
| | - Sanjeeb Mohapatra
- NUS Environmental Research Institute, National University of Singapore, Singapore
| | - Tushara Chaminda
- Department of Civil and Environmental Engineering, University of Ruhuna, Sri Lanka
| | - Vinay Kumar Tyagi
- Environmental BioTechnology Group (EBiTG), Department of Civil Engineering, Indian Institute of Technology Roorkee, Uttarakhand, India
| | - Meththika Vithanage
- Sustainability Cluster, School of Engineering, University of Petroleum & Energy Studies, Dehradun, Uttarakhand 248007, India
- Ecosphere Resilience Research Center, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka
| | - Prosun Bhattacharya
- COVID-19 Research@KTH, Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology,SE-100 44, Stockholm, Sweden
| | - Long D Nghiem
- Centre for Technology in Water & Wastewater, University of Technology Sydney, Ultimo 2007, Australia
| | - Dibyendu Sarkar
- Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, NJ 07030, USA
| | - Christian Sonne
- Sustainability Cluster, School of Engineering, University of Petroleum & Energy Studies, Dehradun, Uttarakhand 248007, India
- Department of Ecoscience, Aarhus University, Roskilde DK-4000, Denmark
| | - Jürgen Mahlknecht
- Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Campus Monterey, Monterrey 64849, Nuevo Leon, Mexico
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Full-Length 16S rRNA Gene Sequences from Raw Sewage Samples Spanning Geographic and Seasonal Gradients in Conveyance Systems across the United States. Microbiol Resour Announc 2022; 11:e0031922. [PMID: 35727055 PMCID: PMC9302073 DOI: 10.1128/mra.00319-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Wastewater microbiome research often relies on sequencing of hypervariable regions of 16S rRNA genes, which are difficult to classify at refined taxonomic levels. Here, we introduce a data set of near-full-length 16S rRNA genes from samples designed to capture known geographic and seasonal variations in municipal wastewater microbial communities.
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