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Devianto LA, Amarasiri M, Wang L, Iizuka T, Sano D. Identification of protein biomarkers in wastewater linked to the incidence of COVID-19. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175649. [PMID: 39168326 DOI: 10.1016/j.scitotenv.2024.175649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 07/19/2024] [Accepted: 08/17/2024] [Indexed: 08/23/2024]
Abstract
Wastewater-based epidemiological (WBE) surveillance is a viable disease surveillance technique capable of monitoring the spread of infectious disease agents in sewershed communities. In addition to detecting viral genomes in wastewater, WBE surveillance can identify other endogenous biomarkers that are significantly elevated and excreted in the saliva, urine, and/or stool of infected individuals. Human protein biomarkers allow the realization of real-time WBE surveillance using highly sensitive biosensors. In this study, we analyzed endogenous protein biomarkers present in wastewater influent through liquid chromatography-tandem mass spectrophotometry and scaffold data-independent acquisition to identify candidate target protein biomarkers for WBE surveillance of SARS-CoV-2. We found that out of the 1382 proteins observed in the wastewater samples, 44 were human proteins associated with infectious diseases. These included immune response substances such as immunoglobulins, cytokine-chemokines, and complements, as well as proteins belonging to antimicrobial and antiviral groups. A significant correlation was observed between the intensity of human infectious disease-related protein biomarkers in wastewater and COVID-19 case numbers. Real-time WBE surveillance using biosensors targeting immune response proteins, such as antibodies or immunoglobulins, in wastewater holds promise for expediting the implementation of relevant policies for the effective prevention of infectious diseases in the near future.
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Affiliation(s)
- Luhur Akbar Devianto
- Department of Frontier Science for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Sendai, Miyagi 980-8579, Japan; Department of Environmental Engineering, Faculty of Agriculture Technology, Brawijaya University, Malang 65145, Indonesia
| | - Mohan Amarasiri
- Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Miyagi 980-8579, Japan
| | - Luyao Wang
- Department of Frontier Science for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Sendai, Miyagi 980-8579, Japan
| | - Takehito Iizuka
- Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Miyagi 980-8579, Japan
| | - Daisuke Sano
- Department of Frontier Science for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Sendai, Miyagi 980-8579, Japan; Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Miyagi 980-8579, Japan; Wastewater Information Research Center, Graduate School of Engineering, Tohoku University, Sendai, Miyagi 980-8579, Japan; New Industry Creation Hatchery Center, Tohoku University, Sendai, Miyagi 980-8579, Japan.
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2
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Brosky H, Prasek SM, Innes GK, Pepper IL, Miranda J, Brierley PE, Slinski SL, Polashenski L, Betancourt WQ, Gronbach K, Gomez D, Neupane R, Johnson J, Weiss J, Yaglom HD, Engelthaler DM, Hepp CM, Crank K, Gerrity D, Stewart JR, Schmitz BW. A framework for integrating wastewater-based epidemiology and public health. Front Public Health 2024; 12:1418681. [PMID: 39131575 PMCID: PMC11312382 DOI: 10.3389/fpubh.2024.1418681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Accepted: 06/24/2024] [Indexed: 08/13/2024] Open
Abstract
Wastewater-based epidemiology (WBE) is an environmental approach to monitor community health through the analysis of sewage. The COVID-19 pandemic catalyzed scientists and public health professionals to revisit WBE as a tool to optimize resource allocation to mitigate disease spread and prevent outbreaks. Some studies have highlighted the value of WBE programs that coordinate with public health professionals; however, the details necessary for implementation are not well-characterized. To respond to this knowledge gap, this article documents the framework of a successful WBE program in Arizona, titled Wastewater Analysis for Tactical Epidemiological Response Systems (WATERS), detailing the developed structure and methods of communication that enabled public health preparedness and response actions. This communication illustrates how program operations were employed to reduce outbreak severity. The structure outlined here is customizable and may guide other programs in the implementation of WBE as a public health tool.
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Affiliation(s)
- Hanna Brosky
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, Tucson, AZ, United States
- Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, NC, United States
| | - Sarah M. Prasek
- Water and Energy Sustainable Technology (WEST) Center, University of Arizona, Tucson, AZ, United States
| | - Gabriel K. Innes
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, Tucson, AZ, United States
| | - Ian L. Pepper
- Water and Energy Sustainable Technology (WEST) Center, University of Arizona, Tucson, AZ, United States
| | - Jasmine Miranda
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, Tucson, AZ, United States
| | - Paul E. Brierley
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, Tucson, AZ, United States
| | - Stephanie L. Slinski
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, Tucson, AZ, United States
| | - Lois Polashenski
- Water and Energy Sustainable Technology (WEST) Center, University of Arizona, Tucson, AZ, United States
| | - Walter Q. Betancourt
- Water and Energy Sustainable Technology (WEST) Center, University of Arizona, Tucson, AZ, United States
| | - Katie Gronbach
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, Tucson, AZ, United States
| | - Diana Gomez
- Yuma County Public Health Services District, Yuma, AZ, United States
| | - Reshma Neupane
- Arizona Department of Health Services, Office of Infectious Disease Services, Phoenix, AZ, United States
| | - Jasmine Johnson
- Arizona Department of Health Services, Office of Infectious Disease Services, Phoenix, AZ, United States
| | - Joli Weiss
- Arizona Department of Health Services, Office of Infectious Disease Services, Phoenix, AZ, United States
| | - Hayley D. Yaglom
- Translational Genomics Research Institute, Pathogen and Microbiome Institute, Flagstaff, AZ, United States
| | - David M. Engelthaler
- Translational Genomics Research Institute, Pathogen and Microbiome Institute, Flagstaff, AZ, United States
| | - Crystal M. Hepp
- Translational Genomics Research Institute, Pathogen and Microbiome Institute, Flagstaff, AZ, United States
| | - Katherine Crank
- Applied Research and Development Center, Southern Nevada Water Authority, Las Vegas, NV, United States
| | - Daniel Gerrity
- Applied Research and Development Center, Southern Nevada Water Authority, Las Vegas, NV, United States
| | - Jill R. Stewart
- Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, NC, United States
| | - Bradley W. Schmitz
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, Tucson, AZ, United States
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Paracchini V, Petrillo M, Arcot Rajashekar A, Robuch P, Vincent U, Corbisier P, Tavazzi S, Raffael B, Suffredini E, La Rosa G, Gawlik BM, Marchini A. EU surveys insights: analytical tools, future directions, and the essential requirement for reference materials in wastewater monitoring of SARS-CoV-2, antimicrobial resistance and beyond. Hum Genomics 2024; 18:72. [PMID: 38937848 PMCID: PMC11210120 DOI: 10.1186/s40246-024-00641-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 06/17/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND Wastewater surveillance (WWS) acts as a vigilant sentinel system for communities, analysing sewage to protect public health by detecting outbreaks and monitoring trends in pathogens and contaminants. To achieve a thorough comprehension of present and upcoming practices and to identify challenges and opportunities for standardisation and improvement in WWS methodologies, two EU surveys were conducted targeting over 750 WWS laboratories across Europe and other regions. The first survey explored a diverse range of activities currently undertaken or planned by laboratories. The second survey specifically targeted methods and quality controls utilised for SARS-CoV-2 surveillance. RESULTS The findings of the two surveys provide a comprehensive insight into the procedures and methodologies applied in WWS. In Europe, WWS primarily focuses on SARS-CoV-2 with 99% of the survey participants dedicated to this virus. However, the responses highlighted a lack of standardisation in the methodologies employed for monitoring SARS-CoV-2. The surveillance of other pathogens, including antimicrobial resistance, is currently fragmented and conducted by only a limited number of laboratories. Notably, these activities are anticipated to expand in the future. Survey replies emphasise the collective recognition of the need to enhance the accuracy of results in WWS practices, reflecting a shared commitment to advancing precision and effectiveness in WWS methodologies. CONCLUSIONS These surveys identified a lack of standardised common procedures in WWS practices and the need for quality standards and reference materials to enhance the accuracy and reliability of WWS methods in the future. In addition, it is important to broaden surveillance efforts beyond SARS-CoV-2 to include other emerging pathogens and antimicrobial resistance to ensure a comprehensive approach to protecting public health.
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Affiliation(s)
| | | | | | - Piotr Robuch
- European Commission, Joint Research Centre (JRC), Geel, Belgium
| | - Ursula Vincent
- European Commission, Joint Research Centre (JRC), Geel, Belgium
| | | | - Simona Tavazzi
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Barbara Raffael
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Elisabetta Suffredini
- Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità (ISS), Rome, Italy
| | - Giuseppina La Rosa
- National Center for Water Safety (CeNSia), Istituto Superiore di Sanità (ISS), Rome, Italy
| | | | - Antonio Marchini
- European Commission, Joint Research Centre (JRC), Geel, Belgium.
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Li L, Haak L, Carine M, Pagilla KR. Temporal assessment of SARS-CoV-2 detection in wastewater and its epidemiological implications in COVID-19 case dynamics. Heliyon 2024; 10:e29462. [PMID: 38638959 PMCID: PMC11024598 DOI: 10.1016/j.heliyon.2024.e29462] [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] [Received: 01/04/2024] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 04/20/2024] Open
Abstract
This research evaluated the relationship between daily new Coronavirus Disease 2019 (COVID-19) cases and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) concentrations in wastewater, followed by effects of differential SARS-CoV-2 shedding loads across various COVID-19 outbreaks. Linear regression analyses were utilized to examine the lead time of the SARS-CoV-2 signal in wastewater relative to new COVID-19 clinical cases. During the Delta wave, no lead time was evident, highlighting limited predictive capability of wastewater monitoring during this phase. However, significant lead times were observed during the Omicron wave, potentially attributed to testing capacity overload and subsequent case reporting delays or changes in shedding patterns. During the Post-Omicron wave (Febuary 23 to May 19, 2022), no lead time was discernible, whereas following the lifting of the COVID-19 state of emergency (May 30, 2022 to May 30, 2023), the correlation coefficient increased and demonstrated the potential of wastewater surveillance as an early warning system. Subsequently, we explored the virus shedding in wastewater through feces, operationalized as the ratio of SARS-CoV-2 concentrations to daily new COVID-19 cases. This ratio varied significantly across the Delta, Omicron, other variants and post-state-emergency phases, with the Kruskal-Wallis H test confirming a significant difference in medians across these stages (P < 0.0001). Despite its promise, wastewater surveillance of COVID-19 disease prevalence presents several challenges, including virus shedding variability, data interpretation complexity, the impact of environmental factors on viral degradation, and the lack of standardized testing procedures. Overall, our findings offer insights into the correlation between COVID-19 cases and wastewater viral concentrations, potential variation in SARS-CoV-2 shedding in wastewater across different pandemic phases, and underscore the promise and limitations of wastewater surveillance as an early warning system for disease prevalence trends.
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Affiliation(s)
- Lin Li
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
| | - Laura Haak
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
| | - Madeline Carine
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
| | - Krishna R. Pagilla
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
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Manirambona E, Khan SH, Siddiq A, Albakri K, Salamah HM, Hassan NAIF, Musa SS, Dhama K. Intriguing insight into unanswered questions about Mpox: exploring health policy implications and considerations. Health Res Policy Syst 2024; 22:37. [PMID: 38520018 PMCID: PMC10960492 DOI: 10.1186/s12961-024-01123-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 02/17/2024] [Indexed: 03/25/2024] Open
Abstract
The 2022 multi-country Monkeypox (Mpox) outbreak has added concerns to scientific research. However, unanswered questions about the disease remain. These unanswered questions lie in different aspects, such as transmission, the affected community, clinical presentations, infection and prevention control and treatment and vaccination. It is imperative to address these issues to stop the spread and transmission of disease. We documented unanswered questions with Mpox and offered suggestions that could help put health policy into practice. One of those questions is why gay, bisexual or other men who have sex with men (gbMSM) are the most affected community, underscoring the importance of prioritizing this community regarding treatment, vaccination and post-exposure prophylaxis. In addition, destigmatizing gbMSM and implementing community-based gbMSM consultation and action alongside ethical surveillance can facilitate other preventive measures such as ring vaccination to curb disease transmission and track vaccine efficacy. Relevant to that, vaccine and drug side effects have implied the questionability of their use and stimulated the importance of health policy development regarding expanded access and off-label use, expressing the need for safe drug and vaccine development manufacturing. The possibility of reverse zoonotic has also been raised, thus indicating the requirement to screen not only humans, but also their related animals to understand the real magnitude of reverse zoonosis and its potential risks. Implementing infection prevention and control measures to stop the virus circulation at the human-animal interface that includes One Health approach is essential.
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Affiliation(s)
- Emery Manirambona
- College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda.
| | | | | | - Khaled Albakri
- Faculty of Medicine, The Hashemite University, Zarqa, Jordan
| | | | | | | | - Kuldeep Dhama
- Division of Pathology, ICAR-Indian Veterinary Research Institute (IVRI), Izatnagar, Bareilly, Uttar Pradesh, 243122, India
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Anupong S, Chadsuthi S, Hongsing P, Hurst C, Phattharapornjaroen P, Rad S.M. AH, Fernandez S, Huang AT, Vatanaprasan P, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Ngamwongsatit N, Badavath VN, Thuptimdang W, Leelahavanichkul A, Kanjanabuch T, Miyanaga K, Cui L, Nanbo A, Shibuya K, Kupwiwat R, Sano D, Furukawa T, Sei K, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, Ishikawa H, Amarasiri M, Modchang C, Wannigama DL. Exploring indoor and outdoor dust as a potential tool for detection and monitoring of COVID-19 transmission. iScience 2024; 27:109043. [PMID: 38375225 PMCID: PMC10875567 DOI: 10.1016/j.isci.2024.109043] [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] [Received: 08/02/2023] [Revised: 11/09/2023] [Accepted: 01/23/2024] [Indexed: 02/21/2024] Open
Abstract
This study investigated the potential of using SARS-CoV-2 viral concentrations in dust as an additional surveillance tool for early detection and monitoring of COVID-19 transmission. Dust samples were collected from 8 public locations in 16 districts of Bangkok, Thailand, from June to August 2021. SARS-CoV-2 RNA concentrations in dust were quantified, and their correlation with community case incidence was assessed. Our findings revealed a positive correlation between viral concentrations detected in dust and the relative risk of COVID-19. The highest risk was observed with no delay (0-day lag), and this risk gradually decreased as the lag time increased. We observed an overall decline in viral concentrations in public places during lockdown, closely associated with reduced human mobility. The effective reproduction number for COVID-19 transmission remained above one throughout the study period, suggesting that transmission may persist in locations beyond public areas even after the lockdown measures were in place.
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Affiliation(s)
- Suparinthon Anupong
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Sudarat Chadsuthi
- Department of Physics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
| | - Parichart Hongsing
- Mae Fah Luang University Hospital, Chiang Rai, Thailand
- School of Integrative Medicine, Mae Fah Luang University, Chiang Rai, Thailand
| | - Cameron Hurst
- Molly Wardaguga Research Centre, Charles Darwin University, Brisbane, QLD, Australia
- Statistics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Phatthranit Phattharapornjaroen
- Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
- Institute of Clinical Sciences, Department of Surgery, Sahlgrenska Academy, Gothenburg University, 40530 Gothenburg, Sweden
| | - Ali Hosseini Rad S.M.
- Department of Microbiology and Immunology, University of Otago, Dunedin, Otago 9010, New Zealand
- Center of Excellence in Immunology and Immune-Mediated Diseases, Chulalongkorn University, Bangkok 10330, Thailand
| | - Stefan Fernandez
- Department of Virology, U.S. Army Medical Directorate, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Angkana T. Huang
- Department of Virology, U.S. Army Medical Directorate, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
- Department of Genetics, University of Cambridge, Cambridge, UK
| | | | - Thammakorn Saethang
- Department of Computer Science, Faculty of Science, Kasetsart University, Bangkok, Thailand
| | - Sirirat Luk-in
- Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand
| | - Robin James Storer
- Office of Research Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Puey Ounjai
- Department of Biology, Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Naveen Kumar Devanga Ragupathi
- Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield, UK
- Biofilms and Antimicrobial Resistance Consortium of ODA Receiving Countries, The University of Sheffield, Sheffield, UK
- Division of Microbial Interactions, Department of Research and Development, Bioberrys Healthcare and Research Centre, Vellore 632009, India
| | - Phitsanuruk Kanthawee
- Public Health Major, School of Health Science, Mae Fah Luang University, Chiang Rai 57100, Thailand
| | - Natharin Ngamwongsatit
- Department of Clinical Sciences and Public Health, Faculty of Veterinary Science, Mahidol University, Nakhon Pathom, Thailand
| | - Vishnu Nayak Badavath
- School of Pharmacy & Technology Management, SVKM’s Narsee Monjee Institute of Management Studies (NMIMS), Hyderabad 509301, India
| | - Wanwara Thuptimdang
- Institute of Biomedical Engineering, Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand
| | - Asada Leelahavanichkul
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Translational Research in Inflammation and Immunology Research Unit (TRIRU), Department of Microbiology, Chulalongkorn University, Bangkok, Thailand
| | - Talerngsak Kanjanabuch
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Kidney Metabolic Disorders, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Dialysis Policy and Practice Program (DiP3), School of Global Health, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Peritoneal Dialysis Excellence Center, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Kazuhiko Miyanaga
- Division of Bacteriology, School of Medicine, Jichi Medical University, Tochigi, Japan
| | - Longzhu Cui
- Division of Bacteriology, School of Medicine, Jichi Medical University, Tochigi, Japan
| | - Asuka Nanbo
- The National Research Center for the Control and Prevention of Infectious Diseases, Nagasaki University, Nagasaki, Japan
| | - Kenji Shibuya
- Tokyo Foundation for Policy Research, Minato-ku, Tokyo, Japan
| | - Rosalyn Kupwiwat
- Department of Dermatology. Faculty of Medicine Siriraj Hospital. Mahidol University, Bangkok, Thailand
| | - Daisuke Sano
- Department of Frontier Sciences for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Sendai, Miyagi, Japan
- Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Miyagi, Japan
| | - Takashi Furukawa
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Minato City, Tokyo 108-8641, Japan
| | - Kazunari Sei
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Minato City, Tokyo 108-8641, Japan
| | - Paul G. Higgins
- Institute for Medical Microbiology, Immunology and Hygiene, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Centre for Infection Research, Partner Site Bonn-Cologne, Cologne, Germany
| | - Anthony Kicic
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, University of Western Australia, Nedlands WA 6009, Australia
- Centre for Cell Therapy and Regenerative Medicine, Medical School, The University of Western Australia, Nedlands, WA 6009, Australia
- Department of Respiratory and Sleep Medicine, Perth Children’s Hospital, Nedlands WA 6009, Australia
- School of Population Health, Curtin University, Bentley WA 6102, Australia
| | | | - Tanittha Chatsuwan
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Antimicrobial Resistance and Stewardship, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Sam Trowsdale
- Department of Environmental Science, University of Auckland, Auckland 1010, New Zealand
| | - Shuichi Abe
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Hitoshi Ishikawa
- Yamagata Prefectural University of Health Sciences, Kamiyanagi, Yamagata 990-2212, Japan
| | - Mohan Amarasiri
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Minato City, Tokyo 108-8641, Japan
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
- Centre of Excellence in Mathematics, MHESI, Bangkok 10400, Thailand
- Thailand Center of Excellence in Physics, Ministry of Higher Education, Science, Research and Innovation, 328 Si Ayutthaya Road, Bangkok 10400, Thailand
| | - Dhammika Leshan Wannigama
- Biofilms and Antimicrobial Resistance Consortium of ODA Receiving Countries, The University of Sheffield, Sheffield, UK
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Antimicrobial Resistance and Stewardship, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
- Yamagata Prefectural University of Health Sciences, Kamiyanagi, Yamagata 990-2212, Japan
- School of Medicine, Faculty of Health and Medical Sciences, The University of Western Australia, Nedlands, WA, Australia
- Pathogen Hunter’s Research Collaborative Team, Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
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7
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Parkins MD, Lee BE, Acosta N, Bautista M, Hubert CRJ, Hrudey SE, Frankowski K, Pang XL. Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond. Clin Microbiol Rev 2024; 37:e0010322. [PMID: 38095438 PMCID: PMC10938902 DOI: 10.1128/cmr.00103-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2024] Open
Abstract
Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.
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Affiliation(s)
- Michael D. Parkins
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- O’Brien Institute of Public Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Bonita E. Lee
- Department of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Nicole Acosta
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Maria Bautista
- Department of Biological Sciences, Faculty of Science, University of Calgary, Calgary, Alberta, Canada
| | - Casey R. J. Hubert
- Department of Biological Sciences, Faculty of Science, University of Calgary, Calgary, Alberta, Canada
| | - Steve E. Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Kevin Frankowski
- Advancing Canadian Water Assets, University of Calgary, Calgary, Alberta, Canada
| | - Xiao-Li Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
- Provincial Health Laboratory, Alberta Health Services, Calgary, Alberta, Canada
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8
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Saleem MH, Mfarrej MFB, Khan KA, Alharthy SA. Emerging trends in wastewater treatment: Addressing microorganic pollutants and environmental impacts. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 913:169755. [PMID: 38176566 DOI: 10.1016/j.scitotenv.2023.169755] [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: 11/11/2023] [Revised: 12/26/2023] [Accepted: 12/27/2023] [Indexed: 01/06/2024]
Abstract
This review focuses on the challenges and advances associated with the treatment and management of microorganic pollutants, encompassing pesticides, industrial chemicals, and persistent organic pollutants (POPs) in the environment. The translocation of these contaminants across multiple media, particularly through atmospheric transport, emphasizes their pervasive nature and the subsequent ecological risks. The urgency to develop cost-effective remediation strategies for emerging organic contaminants is paramount. As such, wastewater-based epidemiology and the increasing concern over estrogenicity are explored. By incorporating conventional and innovative wastewater treatment techniques, this article highlights the integration of environmental management strategies, analytical methodologies, and the importance of renewable energy in waste treatment. The primary objective is to provide a comprehensive perspective on the current scenario, imminent threats, and future directions in mitigating the effects of these pollutants on the environment. Furthermore, the review underscores the need for international collaboration in developing standardized guidelines and policies for monitoring and controlling these microorganic pollutants. It advocates for increased investment in research and development of advanced materials and technologies that can efficiently remove or neutralize these contaminants, thereby safeguarding environmental health and promoting sustainable practice.
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Affiliation(s)
- Muhammad Hamzah Saleem
- Office of Academic Research, Office of VP for Research & Graduate Studies, Qatar University, Doha 2713, Qatar.
| | - Manar Fawzi Bani Mfarrej
- Department of Life and Environmental Sciences, College of Natural and Health Sciences, Zayed University, Abu Dhabi 144534, United Arab Emirates.
| | - Khalid Ali Khan
- Applied College, Center of Bee Research and its Products, Unit of Bee Research and Honey Production, and Research Center for Advanced Materials Science (RCAMS), King Khalid University, P.O. Box 9004, Abha 61413, Saudi Arabia.
| | - Saif A Alharthy
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, P.O. Box 80216, Jeddah 21589, Saudi Arabia; Toxicology and Forensic Sciences Unit, King Fahd Medical Research Center, King Abdulaziz University, P.O. Box 80216, Jeddah 21589, Saudi Arabia.
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9
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Haskell BR, Dhiyebi HA, Srikanthan N, Bragg LM, Parker WJ, Giesy JP, Servos MR. Implementing an adaptive, two-tiered SARS-CoV-2 wastewater surveillance program on a university campus using passive sampling. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168998. [PMID: 38040360 DOI: 10.1016/j.scitotenv.2023.168998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 12/03/2023]
Abstract
Building-level wastewater-based surveillance (WBS) has been increasingly applied upstream from wastewater treatment plants to conduct targeted monitoring for SARS-CoV-2. In this study, a two-tiered, trigger-based wastewater surveillance program was developed on a university campus to monitor dormitory wastewater. The objective was to determine if passive sampling with cotton gauze as a sampling medium could be used to support institution-level public health action. Two nucleocapsid gene targets (N1 and N2) of SARS-CoV-2 as well as the endogenous fecal indicator pepper mild mottle virus (PMMoV) were quantified using RT-qPCR. >500 samples were analyzed during two contrasting surveillance periods. In the Fall of 2021 community viral burden was low and a tiered sampling network was able to isolate individual clinical cases at the building-scale. In the Winter of 2022 wastewater signals were quickly elevated by the emergence of the highly transmissible SARS-CoV-2 Omicron (B.1.1.529) variant. Prevalence of SARS-CoV-2 shifted surveillance objectives from isolating cases to monitoring trends, revealing both the benefits and limitations of a tiered surveillance design under different public health situations. Normalization of SARS-CoV-2 by PMMoV was not reflective of upstream population differences, suggesting saturation of the material occurred during the exposure period. The passive sampling method detected nearly all known clinical cases and in one instance was able to identify one pre-symptomatic individual days prior to confirmation by clinical test. Comparisons between campus samplers and municipal wastewater influent suggests that the spread of COVID-19 on the campus was similar to that of the broader community. The results demonstrate that passive sampling is an effective tool that can produce semi-quantitative data capable of tracking temporal trends to guide targeted public health decision-making at an institutional level. Practitioners of WBS can utilize these results to inform surveillance program designs that prioritize efficient resource use and rapid reporting.
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Affiliation(s)
- Blake R Haskell
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
| | - Hadi A Dhiyebi
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
| | - Nivetha Srikanthan
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada
| | - Leslie M Bragg
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
| | - Wayne J Parker
- Department of Civil and Environmental Engineering, University of Waterloo, 200 University Ave. W, Waterloo, ON N2L 3G1, Canada.
| | - John P Giesy
- Toxicology Centre, University of Saskatchewan, 44 Campus Dr., Saskatoon, Saskatchewan S7N 5B3, Canada; Department of Environmental Science, Baylor University, 1 Bear Trail, Waco, TX 76798, USA
| | - Mark R Servos
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
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10
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Liu S, Zhou X, Zhang M, Shi C, Ren R, Hou C, Di B. Estimating the prevalence of dyslipidemia by measuring fenofibrate in 33 cities in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169426. [PMID: 38128665 DOI: 10.1016/j.scitotenv.2023.169426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/05/2023] [Accepted: 12/14/2023] [Indexed: 12/23/2023]
Abstract
Dyslipidemia, recognized as a predominant risk factor for atherosclerotic cardiovascular disease (CVD), remains a pressing health concern worldwide, particularly in China with nearly 40 % of the population adversely suffering. Fenofibrate, as one of the most commonly used drugs for dyslipidemia therapy, excreted as the format of fenofibrate-acid, which showed considerable stability in sewage samples and could be detected as WBE-biomarkers to monitor the prevalence of dyslipidemia. In this work, we reported the first research on estimating the prevalence of dyslipidemia by WBE approach. 527 sewage samples from 33 cities in China were extracted by solid phase and analyzed by LC-MS/MS. The detected concentration of fenofibrate acid in sewage was on an average of 120.5 ± 59.9 ng/L, and the reverse-calculated consumption of fenofibrate based on fenofibrate acid was 77.8 ± 25.0 mg/day/1000inh. Detailed analysis unveiled an average prevalence of fenofibrate at 0.056 % ± 0.018 %, and the dyslipidemia prevalence among the population aged over 15 was ultimately estimated to be 37.9 % ± 9.3 % and was in accordance with the China Cardiovascular research result of 40.4 %, which proves that WBE is a substitutable approach of traditional epidemiological investigation methods due to its timeliness and cost-effectiveness. This study demonstrated that estimating dyslipidemia prevalence by WBE with metabolite fenofibrate acid as a biomarker is feasible in most Chinese cities.
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Affiliation(s)
- ShuCheng Liu
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing 210009, China
| | - XinXin Zhou
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing 210009, China
| | - Manlei Zhang
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing 210009, China
| | - Chen Shi
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing 210009, China
| | - Ren Ren
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing 210009, China
| | - ChenZhi Hou
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing 210009, China; Key Laboratory of Drug Quality Control and Pharmacovigilance, China Pharmaceutical University, Ministry of Education, No. 639 Longmian Avenue, Nanjing 211100, China.
| | - Bin Di
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing 210009, China; Key Laboratory of Drug Quality Control and Pharmacovigilance, China Pharmaceutical University, Ministry of Education, No. 639 Longmian Avenue, Nanjing 211100, China.
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11
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Dorevitch S, Shrestha A. Priority setting for global WASH challenges in the age of wastewater-based epidemiological surveillance. JOURNAL OF WATER AND HEALTH 2024; 22:367-371. [PMID: 38421630 PMCID: wh_2024_298 DOI: 10.2166/wh.2024.298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
HIGHLIGHTS
Mortality due to inadequate WASH facilities exceeded that of COVID-19 in the regions of South-East Asia and Africa. The costs and benefits of wastewater-based surveillance are not known; however, the benefits of WASH interventions greatly exceed the costs. The dedication of effort and resources to wastewater-based surveillance and WASH in low- and middle-income countries should reflect disease burdens and cost/benefit assessments.
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Affiliation(s)
- Samuel Dorevitch
- University of Illinois Chicago School of Public Health, 1603 W. Taylor St., Chicago, IL 60612, USA E-mail:
| | - Abhilasha Shrestha
- University of Illinois Chicago School of Public Health, 1603 W. Taylor St., Chicago, IL 60612, USA
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12
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Clark EC, Neumann S, Hopkins S, Kostopoulos A, Hagerman L, Dobbins M. Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review. JMIR Public Health Surveill 2024; 10:e49185. [PMID: 38241067 PMCID: PMC10837764 DOI: 10.2196/49185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/06/2023] [Accepted: 12/07/2023] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND Public health surveillance plays a vital role in informing public health decision-making. The onset of the COVID-19 pandemic in early 2020 caused a widespread shift in public health priorities. Global efforts focused on COVID-19 monitoring and contact tracing. Existing public health programs were interrupted due to physical distancing measures and reallocation of resources. The onset of the COVID-19 pandemic intersected with advancements in technologies that have the potential to support public health surveillance efforts. OBJECTIVE This scoping review aims to explore emergent public health surveillance methods during the early COVID-19 pandemic to characterize the impact of the pandemic on surveillance methods. METHODS A scoping search was conducted in multiple databases and by scanning key government and public health organization websites from March 2020 to January 2022. Published papers and gray literature that described the application of new or revised approaches to public health surveillance were included. Papers that discussed the implications of novel public health surveillance approaches from ethical, legal, security, and equity perspectives were also included. The surveillance subject, method, location, and setting were extracted from each paper to identify trends in surveillance practices. Two public health epidemiologists were invited to provide their perspectives as peer reviewers. RESULTS Of the 14,238 unique papers, a total of 241 papers describing novel surveillance methods and changes to surveillance methods are included. Eighty papers were review papers and 161 were single studies. Overall, the literature heavily featured papers detailing surveillance of COVID-19 transmission (n=187). Surveillance of other infectious diseases was also described, including other pathogens (n=12). Other public health topics included vaccines (n=9), mental health (n=11), substance use (n=4), healthy nutrition (n=1), maternal and child health (n=3), antimicrobial resistance (n=2), and misinformation (n=6). The literature was dominated by applications of digital surveillance, for example, by using big data through mobility tracking and infodemiology (n=163). Wastewater surveillance was also heavily represented (n=48). Other papers described adaptations to programs or methods that existed prior to the COVID-19 pandemic (n=9). The scoping search also found 109 papers that discuss the ethical, legal, security, and equity implications of emerging surveillance methods. The peer reviewer public health epidemiologists noted that additional changes likely exist, beyond what has been reported and available for evidence syntheses. CONCLUSIONS The COVID-19 pandemic accelerated advancements in surveillance and the adoption of new technologies, especially for digital and wastewater surveillance methods. Given the investments in these systems, further applications for public health surveillance are likely. The literature for surveillance methods was dominated by surveillance of infectious diseases, particularly COVID-19. A substantial amount of literature on the ethical, legal, security, and equity implications of these emerging surveillance methods also points to a need for cautious consideration of potential harm.
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Affiliation(s)
- Emily C Clark
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
| | - Sophie Neumann
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
| | - Stephanie Hopkins
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
| | - Alyssa Kostopoulos
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
| | - Leah Hagerman
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
| | - Maureen Dobbins
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
- School of Nursing, McMaster University, Hamilton, ON, Canada
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13
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Baz Lomba JA, Pires J, Myrmel M, Arnø JK, Madslien EH, Langlete P, Amato E, Hyllestad S. Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic. JOURNAL OF WATER AND HEALTH 2024; 22:197-234. [PMID: 38295081 PMCID: wh_2023_279 DOI: 10.2166/wh.2023.279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.
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Affiliation(s)
- Jose Antonio Baz Lomba
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway E-mail:
| | - João Pires
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway; ECDC fellowship Programme, Public Health Microbiology path (EUPHEM), European Centre for Disease Prevention and Control (ECDC), Solna, Sweden
| | - Mette Myrmel
- Faculty of Veterinary Medicine, Virology Unit, Norwegian University of Life Science (NMBU), Oslo, Norway
| | - Jorunn Karterud Arnø
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Elisabeth Henie Madslien
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Petter Langlete
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Ettore Amato
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Susanne Hyllestad
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
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14
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Kumar M, Joshi M, Prajapati B, Sirikanchana K, Mongkolsuk S, Kumar R, Gallage TP, Joshi C. Early warning of statewide COVID-19 Omicron wave by sentineled urbanized sewer network monitoring using digital PCR in a province capital city, of Gujarat, India. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167060. [PMID: 37709091 DOI: 10.1016/j.scitotenv.2023.167060] [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: 06/17/2023] [Revised: 08/15/2023] [Accepted: 09/11/2023] [Indexed: 09/16/2023]
Abstract
Wastewater-based epidemiology (WBE) has been implemented globally. However, there remains confusion about the number and frequency of samples to be collected, as well as which types of treatment systems can provide reliable specific details about the virus prevalence in specific areas or communities, enabling prompt management and intervention measures. More research is necessary to fully comprehend the possibility of deploying sentinel locations in sewer networks in larger geographic areas. The present study introduces the first report on wastewater-based surveillance in Gandhinagar City using digital PCR (d-PCR) as a SARS-Cov-2 quantification tool, which describes the viral load from five pumping stations in Gandhinagar from October 2021 to March 2022. Raw wastewater samples (n = 119) were received and analyzed weekly to detect SARS-CoV-2 RNA, 109 of which were positive for N1 or N2 genes. The monthly variation analysis in viral genome copies depicted the highest concentrations in January 2022 and February 2022 (p < 0.05; Wilcoxon signed rank test) coincided with the Omicron wave, which contributed mainly from Vavol and Jaspur pumping stations. Cross-correlation analysis indicated that WBE from five stations in Gandhinagar, i.e., capital city sewer networks, provided two-week lead times to the citywide and statewide active cases (time-series cross-correlation function [CCF]; 0.666 and 0.648, respectively), mainly from individual contributions of the urbanized Kudasan and Vavol stations (CCF; 0.729 and 0.647, respectively). These findings suggest that sewer pumping stations in urbanized neighborhoods can be used as sentinel sites for statewide clinical surveillance and that WBE surveillance using digital PCR can be an efficient monitoring and management tool.
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Affiliation(s)
- Manish Kumar
- Sustainability Cluster, School of Engineering, University of Petroleum & Energy Studies, Dehradun, Uttarakhand 248007, India; Escuela de Ingeniería y Ciencias, Technologico de Monterrey, Campus Monterey, Monterrey 64849, Nuevo Leon, Mexico.
| | - Madhvi Joshi
- Gujarat Biotechnology Research Centre, Gandhinagar, Gujarat 382011, India
| | - Bhumika Prajapati
- Gujarat Biotechnology Research Centre, Gandhinagar, Gujarat 382011, India
| | - Kwanrawee Sirikanchana
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok 10210, Thailand; Center of Excellence on Environmental Health and Toxicology (EHT), OPS, MHESI, Bangkok, Thailand
| | - Skorn Mongkolsuk
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok 10210, Thailand; Center of Excellence on Environmental Health and Toxicology (EHT), OPS, MHESI, Bangkok, Thailand
| | - Rakesh Kumar
- School of Ecology and Environment Studies, Nalanda University, Rajgir 803116, India; Department of Biosystems Engineering, Auburn University, Auburn, AL 36849, USA
| | - Tharindu Pollwatta Gallage
- Program in Environmental Toxicology, Chulabhorn Graduate Institute, Chulabhorn Royal Academy, Bangkok 10210, Thailand
| | - Chaitanya Joshi
- Gujarat Biotechnology Research Centre, Gandhinagar, Gujarat 382011, India
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15
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Bowes DA, Henke KB, Driver EM, Newell ME, Block I, Shaffer G, Varsani A, Scotch M, Halden RU. Enhanced detection of mpox virus in wastewater using a pre-amplification approach: A pilot study informing population-level monitoring of low-titer pathogens. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 903:166230. [PMID: 37574063 PMCID: PMC10592092 DOI: 10.1016/j.scitotenv.2023.166230] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 08/09/2023] [Accepted: 08/09/2023] [Indexed: 08/15/2023]
Abstract
A recent outbreak of the mpox virus (MPXV) occurred in non-endemic regions of the world beginning in May 2022. Pathogen surveillance systems faced pressure to quickly establish response protocols, offering an opportunity to employ wastewater-based epidemiology (WBE) for population-level monitoring. The pilot study reported herein aimed to: (i) develop a reliable protocol for MPXV DNA detection in wastewater which would reduce false negative reporting, (ii) test this protocol on wastewater from various regions across the United States, and (iii) conduct a state of the science review of the current literature reporting on experimental methods for MPXV detection using WBE. Twenty-four-hour composite samples of untreated municipal wastewater were collected from the states of New Jersey, Georgia, Illinois, Texas, Arizona, and Washington beginning July 3rd, 2022 through October 16th, 2022 (n = 60). Samples underwent vacuum filtration, DNA extraction from captured solids, MPXV DNA pre-amplification, and qPCR analysis. Of the 60 samples analyzed, a total of eight (13%) tested positive for MPXV in the states of Washington, Texas, New Jersey, and Illinois. The presence of clade IIb MPXV DNA in these samples was confirmed via Sanger sequencing and integration of pre-amplification prior to qPCR decreased the rate of false negative detections by 87% as compared to qPCR analysis alone. Wastewater-derived detections of MPXV were compared to clinical datasets, with 50% of detections occurring as clinical cases were increasing/peaking and 50% occurring as clinical cases waned. Results from the literature review (n = 9 studies) revealed successful strategies for the detection of MPXV DNA in wastewater, however also emphasized a need for further method optimization and standardization. Overall, this work highlights the use of pre-amplification prior to qPCR detection as a means to capture the presence of MPXV DNA in community wastewater and offers guidance for monitoring low-titer pathogens via WBE.
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Affiliation(s)
- Devin A Bowes
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Katherine B Henke
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Erin M Driver
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Melanie Engstrom Newell
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Izabella Block
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Gray Shaffer
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Arvind Varsani
- The Biodesign Institute Center for Fundamental and Applied Microbiomics, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA; School of Life Sciences, Arizona State University, 427 E. Tyler Mall, Tempe, AZ 85281, USA; Center of Evolution and Medicine, Arizona State University, 427 E. Tyler Mall, Tempe, AZ 85281, USA
| | - Matthew Scotch
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA; College of Health Solutions, Arizona State University, 550 N. 3rd St., Phoenix, AZ 85004, USA
| | - Rolf U Halden
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA; School for Sustainable Engineering and the Built Environment, Arizona State University, 660 S. College Ave., Tempe, AZ 85281, USA; OneWaterOneHealth, The Arizona State University Foundation, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA; Global Futures Laboratory, Arizona State University, 800 S. Cady Mall, Tempe, AZ 85281, USA.
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16
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Schmiege D, Kraiselburd I, Haselhoff T, Thomas A, Doerr A, Gosch J, Schoth J, Teichgräber B, Moebus S, Meyer F. Analyzing community wastewater in sub-sewersheds for the small-scale detection of SARS-CoV-2 variants in a German metropolitan area. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 898:165458. [PMID: 37454854 DOI: 10.1016/j.scitotenv.2023.165458] [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: 04/06/2023] [Revised: 06/09/2023] [Accepted: 07/08/2023] [Indexed: 07/18/2023]
Abstract
Wastewater surveillance of SARS-CoV-2 proved useful, including for identifying the local appearance of newly identified virus variants. Previous studies focused on wastewater treatment plants (WWTP) with sewersheds of several hundred thousand people or at single building level, representing only a small number of people. Both approaches may prove inadequate for small-scale intra-urban inferences for early detection of emerging or novel virus variants. Our study aims (i) to analyze SARS-CoV-2 single nucleotide variants (SNVs) in wastewater of sub-sewersheds and WWTP using whole genome sequencing in order to (ii) investigate the potential of small-scale detection of novel known SARS-CoV-2 variants of concern (VOC) within a metropolitan wastewater system. We selected three sub-sewershed sampling sites, based on estimated population- and built environment-related indicators, and the inlet of the receiving WWTP in the Ruhr region, Germany. Untreated wastewater was sampled weekly between October and December 2021, with a total of 22 samples collected. SARS-CoV-2 RNA was analyzed by RT-qPCR and whole genome sequencing. For all samples, genome sequences were obtained, while only 13 samples were positive for RT-qPCR. We identified multiple specific SARS-CoV-2 SNVs in the wastewater samples of the sub-sewersheds and the WWTP. Identified SNVs reflected the dominance of VOC Delta at the time of sampling. Interestingly, we could identify an Omicron-specific SNV in one sub-sewershed. A concurrent wastewater study sampling the same WWTP detected the VOC Omicron one week later. Our observations suggest that the small-scale approach may prove particularly useful for the detection and description of spatially confined emerging or existing virus variants circulating in populations. Future studies applying small-scale sampling strategies taking into account the specific features of the wastewater system will be useful to analyze temporal and spatial variance in more detail.
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Affiliation(s)
- Dennis Schmiege
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130 Essen, Germany.
| | - Ivana Kraiselburd
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131 Essen, Germany
| | - Timo Haselhoff
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130 Essen, Germany
| | - Alexander Thomas
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131 Essen, Germany
| | - Adrian Doerr
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131 Essen, Germany
| | - Jule Gosch
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131 Essen, Germany
| | - Jens Schoth
- Emschergenossenschaft/Lippeverband, Kronprinzenstraße 24, 45128 Essen, Germany
| | | | - Susanne Moebus
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130 Essen, Germany
| | - Folker Meyer
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131 Essen, Germany
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17
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Chen W, Bibby K. Making waves: Establishing a modeling framework to evaluate novel targets for wastewater-based surveillance. WATER RESEARCH 2023; 245:120573. [PMID: 37688859 DOI: 10.1016/j.watres.2023.120573] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 08/27/2023] [Accepted: 09/02/2023] [Indexed: 09/11/2023]
Abstract
Wastewater-based surveillance (WBS) monitoring of pathogens circulating within a community provides an improved understanding of the occurrence and spread of infectious diseases. However, the potential suitability of WBS for novel disease targets is unclear, including many emerging and neglected diseases. The current ad hoc approach of conducting wastewater detection experiments on novel disease targets to determine their suitability for WBS monitoring is resource intensive and may stall investment in this promising technology. In addition, detections, or non-detections, without the context of disease prevalence and shedding by infected individuals are difficult to interpret upon initial WBS target development. In this paper, we present a WBS feasibility analysis framework to identify which diseases are theoretically appropriate for WBS applications and to improve the initial interpretation of target detections. We then discuss five primary factors that influence the probability of detection in WBS monitoring - genome shedding rate, infection rate, per capita wastewater usage, process limit of detection (PLOD), and the number of PCR replicates. Clarifying the relationships between these factors and the likelihood of detection enhances quantitative insights into applying WBS, guiding researchers and stakeholders into mitigating inherent uncertainties of wastewater monitoring and subsequent improvements in WBS outcomes, thereby supporting future investment and expansion of WBS research, especially in novel disease targets.
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Affiliation(s)
- William Chen
- Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, United States
| | - Kyle Bibby
- Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, United States.
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18
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Phan T, Brozak S, Pell B, Oghuan J, Gitter A, Hu T, Ribeiro RM, Ke R, Mena KD, Perelson AS, Kuang Y, Wu F. Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks. WATER RESEARCH 2023; 243:120372. [PMID: 37494742 DOI: 10.1016/j.watres.2023.120372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 07/10/2023] [Accepted: 07/15/2023] [Indexed: 07/28/2023]
Abstract
Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health.
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Affiliation(s)
- Tin Phan
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Samantha Brozak
- School of Mathematical and Statistical Sciences, Arizona State University, AZ 85281, USA
| | - Bruce Pell
- Department of Mathematics and Computer Science, Lawrence Technological University, MI 48075, USA
| | - Jeremiah Oghuan
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Anna Gitter
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Tao Hu
- Department of Geography, Oklahoma State University, Stillwater, OK 74078, USA
| | - Ruy M Ribeiro
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Ruian Ke
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Kristina D Mena
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Texas Epidemic Public Health Institute, Houston, TX 77030, USA
| | - Alan S Perelson
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA; Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Yang Kuang
- School of Mathematical and Statistical Sciences, Arizona State University, AZ 85281, USA
| | - Fuqing Wu
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Texas Epidemic Public Health Institute, Houston, TX 77030, USA.
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19
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Wannigama DL, Amarasiri M, Hongsing P, Hurst C, Modchang C, Chadsuthi S, Anupong S, Phattharapornjaroen P, Rad S. M. AH, Fernandez S, Huang AT, Vatanaprasan P, Jay DJ, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Sano D, Furukawa T, Sei K, Leelahavanichkul A, Kanjanabuch T, Hirankarn N, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, McLellan AD, Ishikawa H. COVID-19 monitoring with sparse sampling of sewered and non-sewered wastewater in urban and rural communities. iScience 2023; 26:107019. [PMID: 37351501 PMCID: PMC10250052 DOI: 10.1016/j.isci.2023.107019] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 03/31/2023] [Accepted: 05/30/2023] [Indexed: 06/24/2023] Open
Abstract
Equitable SARS-CoV-2 surveillance in low-resource communities lacking centralized sewers is critical as wastewater-based epidemiology (WBE) progresses. However, large-scale studies on SARS-CoV-2 detection in wastewater from low-and middle-income countries is limited because of economic and technical reasons. In this study, wastewater samples were collected twice a month from 186 urban and rural subdistricts in nine provinces of Thailand mostly having decentralized and non-sewered sanitation infrastructure and analyzed for SARS-CoV-2 RNA variants using allele-specific RT-qPCR. Wastewater SARS-CoV-2 RNA concentration was used to estimate the real-time incidence and time-varying effective reproduction number (Re). Results showed an increase in SARS-CoV-2 RNA concentrations in wastewater from urban and rural areas 14-20 days earlier than infected individuals were officially reported. It also showed that community/food markets were "hot spots" for infected people. This approach offers an opportunity for early detection of transmission surges, allowing preparedness and potentially mitigating significant outbreaks at both spatial and temporal scales.
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Affiliation(s)
- Dhammika Leshan Wannigama
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Antimicrobial Resistance and Stewardship, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- School of Medicine, Faculty of Health and Medical Sciences, The University of Western Australia, Nedlands, WA, Australia
- Biofilms and Antimicrobial Resistance Consortium of ODA receiving countries, The University of Sheffield, Sheffield, UK
- Pathogen Hunter’s Research Collaborative Team, Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Mohan Amarasiri
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Kitasato, Sagamihara-Minami, Kanagawa 252-0373, Japan
| | - Parichart Hongsing
- Mae Fah Luang University Hospital, Chiang Rai, Thailand
- School of Integrative Medicine, Mae Fah Luang University, Chiang Rai, Thailand
| | - Cameron Hurst
- Molly Wardaguga Research Centre, Charles Darwin University, Brisbane, QLD, Australia
- Statistics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
- Centre of Excellence in Mathematics, MHESI, Bangkok 10400, Thailand
- Thailand Center of Excellence in Physics, Ministry of Higher Education, Science, Research and Innovation, 328 Si Ayutthaya Road, Bangkok 10400, Thailand
| | - Sudarat Chadsuthi
- Department of Physics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
| | - Suparinthon Anupong
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Phatthranit Phattharapornjaroen
- Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
- Institute of Clinical Sciences, Department of Surgery, Sahlgrenska Academy, Gothenburg University, 40530 Gothenburg, Sweden
| | - Ali Hosseini Rad S. M.
- Department of Microbiology and Immunology, University of Otago, Dunedin, Otago 9010, New Zealand
- Center of Excellence in Immunology and Immune-Mediated Diseases, Chulalongkorn University, Bangkok 10330, Thailand
| | - Stefan Fernandez
- Department of Virology, U.S. Army Medical Directorate, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Angkana T. Huang
- Department of Virology, U.S. Army Medical Directorate, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | | | - Dylan John Jay
- Pathogen Hunter’s Research Collaborative Team, Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Thammakorn Saethang
- Department of Computer Science, Faculty of Science, Kasetsart University, Bangkok, Thailand
| | - Sirirat Luk-in
- Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand
| | - Robin James Storer
- Office of Research Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Puey Ounjai
- Department of Biology, Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Naveen Kumar Devanga Ragupathi
- School of Medicine, Faculty of Health and Medical Sciences, The University of Western Australia, Nedlands, WA, Australia
- Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield, UK
- Department of Clinical Microbiology, Christian Medical College, Vellore, India
| | - Phitsanuruk Kanthawee
- Public Health major, School of Health Science, Mae Fah Luang University, Chiang Rai, Thailand
| | - Daisuke Sano
- Department of Frontier Sciences for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Sendai, Miyagi, Japan
- Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Miyagi, Japan
| | - Takashi Furukawa
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Kitasato, Sagamihara-Minami, Kanagawa 252-0373, Japan
| | - Kazunari Sei
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Kitasato, Sagamihara-Minami, Kanagawa 252-0373, Japan
| | - Asada Leelahavanichkul
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
- Translational Research in Inflammation and Immunology Research Unit (TRIRU), Department of Microbiology, Chulalongkorn University, Bangkok, Thailand
| | - Talerngsak Kanjanabuch
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Kidney Metabolic Disorders, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Dialysis Policy and Practice Program (DiP3), School of Global Health, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Peritoneal Dialysis Excellence Center, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Nattiya Hirankarn
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Immunology and Immune-Mediated Diseases, Chulalongkorn University, Bangkok 10330, Thailand
| | - Paul G. Higgins
- Institute for Medical Microbiology, Immunology and Hygiene, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Centre for Infection Research, Partner site Bonn-Cologne, Cologne, Germany
| | - Anthony Kicic
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, University of Western Australia, Nedlands, WA 6009, Australia
- Centre for Cell Therapy and Regenerative Medicine, Medical School, The University of Western Australia, Nedlands, WA 6009, Australia
- Department of Respiratory and Sleep Medicine, Perth Children’s Hospital, Nedlands, WA 6009, Australia
- School of Population Health, Curtin University, Bentley, WA 6102, Australia
| | | | - Tanittha Chatsuwan
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Antimicrobial Resistance and Stewardship, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Sam Trowsdale
- Department of Environmental Science, University of Auckland, Auckland 1010, New Zealand
| | - Shuichi Abe
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Alexander D. McLellan
- Department of Microbiology and Immunology, University of Otago, Dunedin, Otago 9010, New Zealand
| | - Hitoshi Ishikawa
- Yamagata Prefectural University of Health Sciences, Kamiyanagi, Yamagata 990-2212, Japan
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20
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Zhao L, Geng Q, Corchis-Scott R, McKay RM, Norton J, Xagoraraki I. Targeting a free viral fraction enhances the early alert potential of wastewater surveillance for SARS-CoV-2: a methods comparison spanning the transition between delta and omicron variants in a large urban center. Front Public Health 2023; 11:1140441. [PMID: 37546328 PMCID: PMC10400354 DOI: 10.3389/fpubh.2023.1140441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 06/30/2023] [Indexed: 08/08/2023] Open
Abstract
Introduction Wastewater surveillance has proven to be a valuable approach to monitoring the spread of SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19). Recognizing the benefits of wastewater surveillance as a tool to support public health in tracking SARS-CoV-2 and other respiratory pathogens, numerous wastewater virus sampling and concentration methods have been tested for appropriate applications as well as their significance for actionability by public health practices. Methods Here, we present a 34-week long wastewater surveillance study that covers nearly 4 million residents of the Detroit (MI, United States) metropolitan area. Three primary concentration methods were compared with respect to recovery of SARS-CoV-2 from wastewater: Virus Adsorption-Elution (VIRADEL), polyethylene glycol precipitation (PEG), and polysulfone (PES) filtration. Wastewater viral concentrations were normalized using various parameters (flow rate, population, total suspended solids) to account for variations in flow. Three analytical approaches were implemented to compare wastewater viral concentrations across the three primary concentration methods to COVID-19 clinical data for both normalized and non-normalized data: Pearson and Spearman correlations, Dynamic Time Warping (DTW), and Time Lagged Cross Correlation (TLCC) and peak synchrony. Results It was found that VIRADEL, which captures free and suspended virus from supernatant wastewater, was a leading indicator of COVID-19 cases within the region, whereas PEG and PES filtration, which target particle-associated virus, each lagged behind the early alert potential of VIRADEL. PEG and PES methods may potentially capture previously shed and accumulated SARS-CoV-2 resuspended from sediments in the interceptors. Discussion These results indicate that the VIRADEL method can be used to enhance the early-warning potential of wastewater surveillance applications although drawbacks include the need to process large volumes of wastewater to concentrate sufficiently free and suspended virus for detection. While lagging the VIRADEL method for early-alert potential, both PEG and PES filtration can be used for routine COVID-19 wastewater monitoring since they allow a large number of samples to be processed concurrently while being more cost-effective and with rapid turn-around yielding results same day as collection.
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Affiliation(s)
- Liang Zhao
- Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, United States
| | - Qiudi Geng
- Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, Canada
| | - Ryland Corchis-Scott
- Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, Canada
| | - Robert Michael McKay
- Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, Canada
- Great Lakes Center for Fresh Waters and Human Health, Bowling Green State University, Bowling Green, OH, United States
| | - John Norton
- Great Lakes Water Authority, Detroit, MI, United States
| | - Irene Xagoraraki
- Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, United States
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21
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Haque R, Hossain ME, Miah M, Rahman M, Amin N, Rahman Z, Islam MS, Rahman MZ. Monitoring SARS-CoV-2 variants in wastewater of Dhaka City, Bangladesh: approach to complement public health surveillance systems. Hum Genomics 2023; 17:58. [PMID: 37420264 PMCID: PMC10326934 DOI: 10.1186/s40246-023-00505-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 06/28/2023] [Indexed: 07/09/2023] Open
Abstract
BACKGROUND Wastewater-based epidemiological surveillance has been considered a powerful tool for early detection and monitoring of the dynamics of SARS-CoV-2 and its lineages circulating in a community. This study is aimed to investigate the complexity of SARS-CoV-2 infection dynamics in Dhaka city by examining its genetic variants in wastewater. Also, the study seeks to determine a connection between the SARS-CoV-2 variations detected in clinical testing and those found in wastewater samples. RESULTS Out of 504 samples tested in RT-qPCR, 185 (36.7%) tested positive for SARS-CoV-2 viral RNA. The median log10 concentration of SARS-CoV-2 N gene copies/Liter of wastewater (gc/L) was 5.2, and the median log10 concentration of ORF1ab was 4.9. To further reveal the genetic diversity of SARS-CoV-2, ten samples with ORF1ab real-time RT-PCR cycle threshold (Ct) values ranging from 28.78 to 32.13 were subjected to whole genome sequencing using nanopore technology. According to clade classification, sequences from wastewater samples were grouped into 4 clades: 20A, 20B, 21A, 21J, and the Pango lineage, B.1, B.1.1, B.1.1.25, and B.1.617.2, with coverage ranging from 94.2 to 99.8%. Of them, 70% belonged to clade 20B, followed by 10% to clade 20A, 21A, and 21J. Lineage B.1.1.25 was predominant in Bangladesh and phylogenetically related to the sequences from India, the USA, Canada, the UK, and Italy. The Delta variant (B.1.617.2) was first identified in clinical samples at the beginning of May 2021. In contrast, we found that it was circulating in the community and was detected in wastewater in September 2020. CONCLUSION Environmental surveillance is useful for monitoring temporal and spatial trends of existing and emerging infectious diseases and supports evidence-based public health measures. The findings of this study supported the use of wastewater-based epidemiology and provided the baseline data for the dynamics of SARS-CoV-2 variants in the wastewater environment in Dhaka, Bangladesh.
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Affiliation(s)
- Rehnuma Haque
- Environmental Interventions Unit, Infectious Diseases Division, icddr,b, 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka, 1212, Bangladesh.
- Department of Women's and Children's Health, Uppsala University, Akademiska Sjukhuset, 75185, Uppsala, Sweden.
| | - Mohammad Enayet Hossain
- One Health Laboratory, Infectious Diseases Division, icddr,b, 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka, 1212, Bangladesh
| | - Mojnu Miah
- One Health Laboratory, Infectious Diseases Division, icddr,b, 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka, 1212, Bangladesh
| | - Mahbubur Rahman
- Environmental Interventions Unit, Infectious Diseases Division, icddr,b, 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka, 1212, Bangladesh
| | - Nuhu Amin
- Environmental Interventions Unit, Infectious Diseases Division, icddr,b, 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka, 1212, Bangladesh
- Institute for Sustainable Futures, The University of Technology Sydney, 235 Jones St, Ultimo, NSW, 2007, Australia
| | - Ziaur Rahman
- Environmental Interventions Unit, Infectious Diseases Division, icddr,b, 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka, 1212, Bangladesh
| | - Md Shariful Islam
- Environmental Interventions Unit, Infectious Diseases Division, icddr,b, 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka, 1212, Bangladesh
- The School of Public Health, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Mohammed Ziaur Rahman
- One Health Laboratory, Infectious Diseases Division, icddr,b, 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka, 1212, Bangladesh
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22
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Gentry Z, Zhao L, Faust RA, David RE, Norton J, Xagoraraki I. Wastewater surveillance beyond COVID-19: a ranking system for communicable disease testing in the tri-county Detroit area, Michigan, USA. Front Public Health 2023; 11:1178515. [PMID: 37333521 PMCID: PMC10272568 DOI: 10.3389/fpubh.2023.1178515] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 05/12/2023] [Indexed: 06/20/2023] Open
Abstract
Introduction Throughout the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has been utilized to monitor the disease in the United States through routine national, statewide, and regional monitoring projects. A significant canon of evidence was produced showing that wastewater surveillance is a credible and effective tool for disease monitoring. Hence, the application of wastewater surveillance can extend beyond monitoring SARS-CoV-2 to encompass a diverse range of emerging diseases. This article proposed a ranking system for prioritizing reportable communicable diseases (CDs) in the Tri-County Detroit Area (TCDA), Michigan, for future wastewater surveillance applications at the Great Lakes Water Authority's Water Reclamation Plant (GLWA's WRP). Methods The comprehensive CD wastewater surveillance ranking system (CDWSRank) was developed based on 6 binary and 6 quantitative parameters. The final ranking scores of CDs were computed by summing the multiplication products of weighting factors for each parameter, and then were sorted based on decreasing priority. Disease incidence data from 2014 to 2021 were collected for the TCDA. Disease incidence trends in the TCDA were endowed with higher weights, prioritizing the TCDA over the state of Michigan. Results Disparities in incidences of CDs were identified between the TCDA and state of Michigan, indicating epidemiological differences. Among 96 ranked CDs, some top ranked CDs did not present relatively high incidences but were prioritized, suggesting that such CDs require significant attention by wastewater surveillance practitioners, despite their relatively low incidences in the geographic area of interest. Appropriate wastewater sample concentration methods are summarized for the application of wastewater surveillance as per viral, bacterial, parasitic, and fungal pathogens. Discussion The CDWSRank system is one of the first of its kind to provide an empirical approach to prioritize CDs for wastewater surveillance, specifically in geographies served by centralized wastewater collection in the area of interest. The CDWSRank system provides a methodological tool and critical information that can help public health officials and policymakers allocate resources. It can be used to prioritize disease surveillance efforts and ensure that public health interventions are targeted at the most potentially urgent threats. The CDWSRank system can be easily adopted to geographical locations beyond the TCDA.
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Affiliation(s)
- Zachary Gentry
- Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, United States
| | - Liang Zhao
- Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, United States
| | | | - Randy E. David
- Wayne State University School of Medicine, Detroit, MI, United States
| | - John Norton
- Great Lakes Water Authority, Detroit, MI, United States
| | - Irene Xagoraraki
- Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, United States
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23
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Polcz P, Tornai K, Juhász J, Cserey G, Surján G, Pándics T, Róka E, Vargha M, Reguly IZ, Csikász-Nagy A, Pongor S, Szederkényi G. Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants. WATER RESEARCH 2023; 241:120098. [PMID: 37295226 DOI: 10.1016/j.watres.2023.120098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/16/2023] [Accepted: 05/17/2023] [Indexed: 06/12/2023]
Abstract
(MOTIVATION) Wastewater-based epidemiology (WBE) has emerged as a promising approach for monitoring the COVID-19 pandemic, since the measurement process is cost-effective and is exposed to fewer potential errors compared to other indicators like hospitalization data or the number of detected cases. Consequently, WBE was gradually becoming a key tool for epidemic surveillance and often the most reliable data source, as the intensity of clinical testing for COVID-19 drastically decreased by the third year of the pandemic. Recent results suggests that the model-based fusion of wastewater measurements with clinical data and other indicators is essential in future epidemic surveillance. (METHOD) In this work, we developed a wastewater-based compartmental epidemic model with a two-phase vaccination dynamics and immune evasion. We proposed a multi-step optimization-based data assimilation method for epidemic state reconstruction, parameter estimation, and prediction. The computations make use of the measured viral load in wastewater, the available clinical data (hospital occupancy, delivered vaccine doses, and deaths), the stringency index of the official social distancing rules, and other measures. The current state assessment and the estimation of the current transmission rate and immunity loss allow a plausible prediction of the future progression of the pandemic. (RESULTS) Qualitative and quantitative evaluations revealed that the contribution of wastewater data in our computational epidemiological framework makes predictions more reliable. Predictions suggest that at least half of the Hungarian population has lost immunity during the epidemic outbreak caused by the BA.1 and BA.2 subvariants of Omicron in the first half of 2022. We obtained a similar result for the outbreaks caused by the subvariant BA.5 in the second half of 2022. (APPLICABILITY) The proposed approach has been used to support COVID management in Hungary and could be customized for other countries as well.
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Affiliation(s)
- Péter Polcz
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary.
| | - Kálmán Tornai
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
| | - János Juhász
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary; Institute of Medical Microbiology, Semmelweis University, Üllői út 26, Budapest, H-1085, Hungary
| | - György Cserey
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
| | - György Surján
- Department of Public Health Laboratory, National Public Health Centre, Albert Flórián út 2-6, Budapest, H-1097, Hungary; Department of Digital Health Sciences, Semmelweis University, Üllői út 26, Budapest, H-1085, Hungary
| | - Tamás Pándics
- Department of Public Health Laboratory, National Public Health Centre, Albert Flórián út 2-6, Budapest, H-1097, Hungary; Department of Public Health Sciences, Faculty of Health Sciences, Semmelweis University, Vas utca 17, Budapest, H-1088, Hungary
| | - Eszter Róka
- Department of Public Health Laboratory, National Public Health Centre, Albert Flórián út 2-6, Budapest, H-1097, Hungary
| | - Márta Vargha
- Department of Public Health Laboratory, National Public Health Centre, Albert Flórián út 2-6, Budapest, H-1097, Hungary
| | - István Z Reguly
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
| | - Attila Csikász-Nagy
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
| | - Sándor Pongor
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
| | - Gábor Szederkényi
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
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24
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Schenk H, Heidinger P, Insam H, Kreuzinger N, Markt R, Nägele F, Oberacher H, Scheffknecht C, Steinlechner M, Vogl G, Wagner AO, Rauch W. Prediction of hospitalisations based on wastewater-based SARS-CoV-2 epidemiology. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 873:162149. [PMID: 36773921 PMCID: PMC9911153 DOI: 10.1016/j.scitotenv.2023.162149] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/06/2023] [Accepted: 02/06/2023] [Indexed: 05/03/2023]
Abstract
Wastewater-based epidemiology is widely applied in Austria since April 2020 to monitor the SARS-CoV-2 pandemic. With a steadily increasing number of monitored wastewater facilities, 123 plants covering roughly 70 % of the 9 million population were monitored as of August 2022. In this study, the SARS-CoV-2 viral concentrations in raw sewage were analysed to infer short-term hospitalisation occupancy. The temporal lead of wastewater-based epidemiological time series over hospitalisation occupancy levels facilitates the construction of forecast models. Data pre-processing techniques are presented, including the approach of comparing multiple decentralised wastewater signals with aggregated and centralised clinical data. Time‑lead quantification was performed using cross-correlation analysis and coefficient of determination optimisation approaches. Multivariate regression models were successfully applied to infer hospitalisation bed occupancy. The results show a predictive potential of viral loads in sewage towards Covid-19 hospitalisation occupancy, with an average lead time towards ICU and non-ICU bed occupancy between 14.8-17.7 days and 8.6-11.6 days, respectively. The presented procedure provides access to the trend and tipping point behaviour of pandemic dynamics and allows the prediction of short-term demand for public health services. The results showed an increase in forecast accuracy with an increase in the number of monitored wastewater treatment plants. Trained models are sensitive to changing variant types and require recalibration of model parameters, likely caused by immunity by vaccination and/or infection. The utilised approach displays a practical and rapidly implementable application of wastewater-based epidemiology to infer hospitalisation occupancy.
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Affiliation(s)
- Hannes Schenk
- Unit of Environmental Engineering, University of Innsbruck, Technikerstraße 13, Innsbruck 6020, Austria.
| | - Petra Heidinger
- Austrian Centre of Industrial Biotechnology, Krenngasse 37, Graz 8010, Austria.
| | - Heribert Insam
- Department of Microbiology, University of Innsbruck, Technikerstraße 25d, Innsbruck 6020, Austria.
| | - Norbert Kreuzinger
- Institute of Water Quality and Resource Management at TU Wien, Karlsplatz 13, Vienna 1040, Austria.
| | - Rudolf Markt
- Department of Microbiology, University of Innsbruck, Technikerstraße 25d, Innsbruck 6020, Austria; Department of Health Sciences and Social Work, Carinthia University of Applied Sciences, St. Veiter Straße, 47, Klagenfurt 9020, Austria.
| | - Fabiana Nägele
- Department of Microbiology, University of Innsbruck, Technikerstraße 25d, Innsbruck 6020, Austria.
| | - Herbert Oberacher
- Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Müllerstraße, 44, Innsbruck 6020, Austria.
| | - Christoph Scheffknecht
- Institut für Umwelt und Lebensmittelsicherheit des Landes Vorarlberg, Montfortstraße 4, Bregenz 6900, Austria.
| | - Martin Steinlechner
- Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Müllerstraße, 44, Innsbruck 6020, Austria.
| | - Gunther Vogl
- Institut f¨ur Lebensmittelsicherheit, Veterinärmedizin und Umwelt, Kirchengasse 43, Klagenfurt 9020, Austria.
| | - Andreas Otto Wagner
- Department of Microbiology, University of Innsbruck, Technikerstraße 25d, Innsbruck 6020, Austria.
| | - Wolfgang Rauch
- Unit of Environmental Engineering, University of Innsbruck, Technikerstraße 13, Innsbruck 6020, Austria.
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25
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Schill R, Nelson KL, Harris-Lovett S, Kantor RS. The dynamic relationship between COVID-19 cases and SARS-CoV-2 wastewater concentrations across time and space: Considerations for model training data sets. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 871:162069. [PMID: 36754324 PMCID: PMC9902279 DOI: 10.1016/j.scitotenv.2023.162069] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
During the COVID-19 pandemic, wastewater-based surveillance has been used alongside diagnostic testing to monitor infection rates. With the decline in cases reported to public health departments due to at-home testing, wastewater data may serve as the primary input for epidemiological models, but training these models is not straightforward. We explored factors affecting noise and bias in the ratio between wastewater and case data collected in 26 sewersheds in California from October 2020 to March 2022. The strength of the relationship between wastewater and case data appeared dependent on sampling frequency and population size, but was not increased by wastewater normalization to flow rate or case count normalization to testing rates. Additionally, the lead and lag times between wastewater and case data varied over time and space, and the ratio of log-transformed individual cases to wastewater concentrations changed over time. This ratio decreased between the Epsilon/Alpha and Delta variant surges of COVID-19 and increased during the Omicron BA.1 variant surge, and was also related to the diagnostic testing rate. Based on this analysis, we present a framework of scenarios describing the dynamics of the case to wastewater ratio to aid in data handling decisions for ongoing modeling efforts.
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Affiliation(s)
- Rebecca Schill
- TUM School of Engineering and Design, Technical University of Munich, Germany
| | - Kara L Nelson
- Civil and Environmental Engineering, University of California, Berkeley, CA, USA
| | | | - Rose S Kantor
- Civil and Environmental Engineering, University of California, Berkeley, CA, USA.
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26
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Hart JJ, Jamison MN, McNair JN, Szlag DC. Frequency and degradation of SARS-CoV-2 markers N1, N2, and E in sewage. JOURNAL OF WATER AND HEALTH 2023; 21:514-524. [PMID: 37119151 DOI: 10.2166/wh.2023.314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Coronavirus disease 2019 (COVID-19) is an infectious disease that is mainly spread through aerosolized droplets containing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is excreted in feces by infected individuals. Sewage surveillance has been applied widely to obtain data on the prevalence of COVID-19 in whole communities. We used SARS-CoV-2 gene targets N1, N2, and E to determine the prevalence of COVID-19 at both municipal and building levels. Frequency analysis of wastewater testing indicated that single markers detected only 85% or less of samples that were detected as positive for SARS-CoV-2 with the three markers combined, indicating the necessity of pairing markers to lower the false-negative rate. The best pair of markers in both municipal and building level monitoring was N1 and N2, which correctly identified 98% of positive samples detected with the three markers combined. The degradation rates of all three targets were assessed at two different temperatures (25 and 35 °C) as a possible explanation for observed differences between markers in frequency. Results indicated that all three RNA targets degrade at nearly the same rate, indicating that differences in degradation rate are not responsible for the observed differences in marker frequency.
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Affiliation(s)
- John J Hart
- Oakland University, Department of Chemistry, 146 Library Dr, Rochester, MI 48309, USA E-mail: ; Robert B. Annis Water Resources Institute, 740 West Shoreline Dr, Muskegon, MI 49441, USA
| | - Megan N Jamison
- Oakland University, Department of Chemistry, 146 Library Dr, Rochester, MI 48309, USA E-mail: ; The Ohio State University, 281 W Lane Ave, Columbus, OH 43210, USA
| | - James N McNair
- Robert B. Annis Water Resources Institute, 740 West Shoreline Dr, Muskegon, MI 49441, USA
| | - David C Szlag
- Oakland University, Department of Chemistry, 146 Library Dr, Rochester, MI 48309, USA E-mail:
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27
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Zhao L, Zou Y, David RE, Withington S, McFarlane S, Faust RA, Norton J, Xagoraraki I. Simple methods for early warnings of COVID-19 surges: Lessons learned from 21 months of wastewater and clinical data collection in Detroit, Michigan, United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 864:161152. [PMID: 36572285 PMCID: PMC9783093 DOI: 10.1016/j.scitotenv.2022.161152] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/19/2022] [Accepted: 12/19/2022] [Indexed: 05/12/2023]
Abstract
Wastewater-based epidemiology (WBE) has drawn great attention since the Coronavirus disease 2019 (COVID-19) pandemic, not only due to its capability to circumvent the limitations of traditional clinical surveillance, but also due to its potential to forewarn fluctuations of disease incidences in communities. One critical application of WBE is to provide "early warnings" for upcoming fluctuations of disease incidences in communities which traditional clinical testing is incapable to achieve. While intricate models have been developed to determine early warnings based on wastewater surveillance data, there is an exigent need for straightforward, rapid, broadly applicable methods for health departments and partner agencies to implement. Our purpose in this study is to develop and evaluate such early-warning methods and clinical-case peak-detection methods based on WBE data to mount an informed public health response. Throughout an extended wastewater surveillance period across Detroit, MI metropolitan area (the entire study period is from September 2020 to May 2022) we designed eight early-warning methods (three real-time and five post-factum). Additionally, we designed three peak-detection methods based on clinical epidemiological data. We demonstrated the utility of these methods for providing early warnings for COVID-19 incidences, with their counterpart accuracies evaluated by hit rates. "Hit rates" were defined as the number of early warning dates (using wastewater surveillance data) that captured defined peaks (using clinical epidemiological data) divided by the total number of early warning dates. Hit rates demonstrated that the accuracy of both real-time and post-factum methods could reach 100 %. Furthermore, the results indicate that the accuracy was influenced by approaches to defining peaks of disease incidence. The proposed methods herein can assist health departments capitalizing on WBE data to assess trends and implement quick public health responses to future epidemics. Besides, this study elucidated critical factors affecting early warnings based on WBE amid the COVID-19 pandemic.
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Affiliation(s)
- Liang Zhao
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, USA
| | - Yangyang Zou
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, USA
| | - Randy E David
- Detroit Health Department, 100 Mack Ave, Detroit, MI 48201, USA
| | | | - Stacey McFarlane
- Macomb County Health Division, 43525 Elizabeth Rd, Mount Clemens, MI 48043, USA
| | - Russell A Faust
- Oakland County Health Division, 1200 Telegraph Rd, Pontiac, MI 48341, USA
| | - John Norton
- Great Lakes Water Authority, 735 Randolph, Detroit, MI 48226, USA
| | - Irene Xagoraraki
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, USA.
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28
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Davis A, Keely SP, Brinkman NE, Bohrer Z, Ai Y, Mou X, Chattopadhyay S, Hershey O, Senko J, Hull N, Lytmer E, Quintero A, Lee J. Evaluation of intra- and inter-lab variability in quantifying SARS-CoV-2 in a state-wide wastewater monitoring network. ENVIRONMENTAL SCIENCE : WATER RESEARCH & TECHNOLOGY 2023; 9:1053-1068. [PMID: 37701755 PMCID: PMC10494892 DOI: 10.1039/d2ew00737a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
In December 2019, SARS-CoV-2, the virus that causes coronavirus disease 2019, was first reported and subsequently triggered a global pandemic. Wastewater monitoring, a strategy for quantifying viral gene concentrations from wastewater influents within a community, has served as an early warning and management tool for the spread of SARS-CoV-2 in a community. Ohio built a collaborative statewide wastewater monitoring network that is supported by eight labs (university, government, and commercial laboratories) with unique sample processing workflows. Consequently, we sought to characterize the variability in wastewater monitoring results for network labs. Across seven trials between October 2020 and November 2021, eight participating labs successfully quantified two SARS-CoV-2 RNA targets and human fecal indicator virus targets in wastewater sample aliquots with reproducible results, although recovery efficiencies of spiked surrogates ranged from 3 to 75%. When SARS-CoV-2 gene fragment concentrations were adjusted for recovery efficiency and flow, the proportion of variance between laboratories was minimized, serving as the best model to account for between-lab variance. Another adjustment factor (alone and in different combinations with the above factors) considered to account for sample and measurement variability includes fecal marker normalization. Genetic quantification variability can be attributed to many factors, including the methods, individual samples, and water quality parameters. In addition, statistically significant correlations were observed between SARS-CoV-2 RNA and COVID-19 case numbers, supporting the notion that wastewater surveillance continues to serve as an effective monitoring tool. This study serves as a real-time example of multi-laboratory collaboration for public health preparedness for infectious diseases.
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Affiliation(s)
- Angela Davis
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, 1841 Neil Avenue, Columbus, OH 43210, USA
| | - Scott P Keely
- United States Environmental Protection Agency, Office of Research and Development, USA
| | - Nichole E Brinkman
- United States Environmental Protection Agency, Office of Research and Development, USA
| | | | - Yuehan Ai
- Department of Food Science & Technology, The Ohio State University, USA
| | - Xiaozhen Mou
- Department of Biological Sciences, Kent State University, USA
| | - Saurabh Chattopadhyay
- Department of Medical Microbiology and Immunology, College of Medicine and Life Sciences, Department of Biology and Department of Geosciences, University of Toledo, USA
| | - Olivia Hershey
- Department of Geosciences and Biology, University of Akron, USA
| | - John Senko
- Department of Geosciences and Biology, University of Akron, USA
| | - Natalie Hull
- Department of Civil, Environmental and Geodetic Engineering and Sustainability Institute, The Ohio State University, USA
| | - Eva Lytmer
- Department of Biological Sciences, Bowling Green State University, USA
| | | | - Jiyoung Lee
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, 1841 Neil Avenue, Columbus, OH 43210, USA
- Department of Food Science & Technology, The Ohio State University, USA
- Infectious Diseases Institute, The Ohio State University, USA
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29
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Wolken M, Sun T, McCall C, Schneider R, Caton K, Hundley C, Hopkins L, Ensor K, Domakonda K, Kalvapalle P, Persse D, Williams S, Stadler LB. Wastewater surveillance of SARS-CoV-2 and influenza in preK-12 schools shows school, community, and citywide infections. WATER RESEARCH 2023; 231:119648. [PMID: 36702023 PMCID: PMC9858235 DOI: 10.1016/j.watres.2023.119648] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 12/16/2022] [Accepted: 01/18/2023] [Indexed: 06/17/2023]
Abstract
Wastewater surveillance is a passive and efficient way to monitor the spread of infectious diseases in large populations and high transmission areas such as preK-12 schools. Infections caused by respiratory viruses in school-aged children are likely underreported, particularly because many children may be asymptomatic or mildly symptomatic. Wastewater monitoring of SARS-CoV-2 has been studied extensively and primarily by sampling at centralized wastewater treatment plants, and there are limited studies on SARS-CoV-2 in preK-12 school wastewater. Similarly, wastewater detections of influenza have only been reported in wastewater treatment plant and university manhole samples. Here, we present the results of a 17-month wastewater monitoring program for SARS-CoV-2 (n = 2176 samples) and influenza A and B (n = 1217 samples) in 51 preK-12 schools. We show that school wastewater concentrations of SARS-CoV-2 RNA were strongly associated with COVID-19 cases in schools and community positivity rates, and that influenza detections in school wastewater were significantly associated with citywide influenza diagnosis rates. Results were communicated back to schools and local communities to enable mitigation strategies to stop the spread, and direct resources such as testing and vaccination clinics. This study demonstrates that school wastewater surveillance is reflective of local infections at several population levels and plays a crucial role in the detection and mitigation of outbreaks.
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Affiliation(s)
- Madeline Wolken
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, USA; Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center, 1200 Pressler Street, Houston, TX, USA
| | - Thomas Sun
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, USA
| | - Camille McCall
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, USA
| | | | - Kelsey Caton
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA
| | - Courtney Hundley
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA
| | - Loren Hopkins
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, USA; Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA
| | - Katherine Ensor
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, USA
| | - Kaavya Domakonda
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA
| | | | - David Persse
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA; Department of Medicine and Surgery, Baylor College of Medicine, Houston, TX, USA; City of Houston Emergency Medical Services, Houston, TX, USA
| | - Stephen Williams
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA
| | - Lauren B Stadler
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, USA.
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30
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Ash KT, Li Y, Alamilla I, Joyner DC, Williams DE, McKay PJ, Green BM, Iler C, DeBlander SE, North CM, Kara-Murdoch F, Swift CM, Hazen TC. SARS-CoV-2 raw wastewater surveillance from student residences on an urban university campus. Front Microbiol 2023; 14:1101205. [PMID: 36846780 PMCID: PMC9948028 DOI: 10.3389/fmicb.2023.1101205] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 01/26/2023] [Indexed: 02/11/2023] Open
Abstract
The COVID-19 pandemic brought about an urgent need to monitor the community prevalence of infection and detect the presence of SARS-CoV-2. Testing individual people is the most reliable method to measure the spread of the virus in any given community, but it is also the most expensive and time-consuming. Wastewater-based epidemiology (WBE) has been used since the 1960s when scientists implemented monitoring to measure the effectiveness of the Polio vaccine. Since then, WBE has been used to monitor populations for various pathogens, drugs, and pollutants. In August 2020, the University of Tennessee-Knoxville implemented a SARS-CoV-2 surveillance program that began with raw wastewater surveillance of the student residence buildings on campus, the results of which were shared with another lab group on campus that oversaw the pooled saliva testing of students. Sample collection began at 8 am, and the final RT-qPCR results were obtained by midnight. The previous day's results were presented to the campus administrators and the Student Health Center at 8 am the following morning. The buildings surveyed included all campus dormitories, fraternities, and sororities, 46 buildings in all representing an on-campus community of over 8,000 students. The WBE surveillance relied upon early morning "grab" samples and 24-h composite sampling. Because we only had three Hach AS950 Portable Peristaltic Sampler units, we reserved 24-h composite sampling for the dormitories with the highest population of students. Samples were pasteurized, and heavy sediment was centrifuged and filtered out, followed by a virus concentration step before RNA extraction. Each sample was tested by RT-qPCR for the presence of SARS-CoV-2, using the CDC primers for N Capsid targets N1 and N3. The subsequent pooled saliva tests from sections of each building allowed lower costs and minimized the total number of individual verification tests that needed to be analyzed by the Student Health Center. Our WBE results matched the trend of the on-campus cases reported by the student health center. The highest concentration of genomic copies detected in one sample was 5.06 × 107 copies/L. Raw wastewater-based epidemiology is an efficient, economical, fast, and non-invasive method to monitor a large community for a single pathogen or multiple pathogen targets.
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Affiliation(s)
- K. T. Ash
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States,Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
| | - Y. Li
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
| | - I. Alamilla
- Student Health Center, University of Tennessee, Knoxville, TN, United States
| | - D. C. Joyner
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - D. E. Williams
- Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States
| | - P. J. McKay
- Student Health Center, University of Tennessee, Knoxville, TN, United States
| | - B. M. Green
- Department of Microbiology, University of Tennessee, Knoxville, TN, United States
| | - C. Iler
- Facilities Services Department, University of Tennessee, Knoxville, TN, United States
| | - S. E. DeBlander
- College of Natural Science, Michigan State University, East Lansing, MI, United States
| | - C. M. North
- Student Health Center, University of Tennessee, Knoxville, TN, United States
| | - F. Kara-Murdoch
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States,Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States,Battelle Memorial Institute, Columbus, OH, United States
| | - C. M. Swift
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States,Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States
| | - T. C. Hazen
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States,Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States,Department of Microbiology, University of Tennessee, Knoxville, TN, United States,Department of Earth and Planetary Sciences, University of Tennessee, Knoxville, TN, United States,Institute for a Secure and Sustainable Environment, University of Tennessee, Knoxville, TN, United States,*Correspondence: T. C. Hazen, ✉
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31
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Early detection of local SARS-CoV-2 outbreaks by wastewater surveillance: a feasibility study. Epidemiol Infect 2023; 151:e28. [PMID: 36722251 PMCID: PMC9990400 DOI: 10.1017/s0950268823000146] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Wastewater surveillance and quantitative analysis of SARS-CoV-2 RNA are increasingly used to monitor the spread of COVID-19 in the community. We studied the feasibility of applying the surveillance data for early detection of local outbreaks. A Monte Carlo simulation model was constructed, applying data on reported variation in RNA gene copy concentration in faeces and faecal masses shed. It showed that, even with a constant number of SARS-CoV-2 RNA shedders, the variation in concentrations found in wastewater samples will be large, and that it will be challenging to translate viral concentrations into incidence estimates, especially when the number of shedders is low. Potential signals for early detection of hypothetical outbreaks were analysed for their performance in terms of sensitivity and specificity of the signals. The results suggest that a sudden increase in incidence is not easily identified on the basis of wastewater surveillance data, especially in small sampling areas and in low-incidence situations. However, with a high number of shedders and when combining data from multiple consecutive tests, the performance of wastewater sampling is expected to improve considerably. The developed modelling approach can increase our understanding of the results from wastewater surveillance of SARS-CoV-2.
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32
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Prasek SM, Pepper IL, Innes GK, Slinski S, Betancourt WQ, Foster AR, Yaglom HD, Porter WT, Engelthaler DM, Schmitz BW. Variant-specific SARS-CoV-2 shedding rates in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159165. [PMID: 36195153 PMCID: PMC9527179 DOI: 10.1016/j.scitotenv.2022.159165] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 09/23/2022] [Accepted: 09/28/2022] [Indexed: 05/21/2023]
Abstract
Previous studies show that SARS-CoV-2 waste shedding rates vary by community and are influenced by multiple factors; however, differences in shedding rates across multiple variants have yet to be evaluated. The purpose of this work is to build on previous research that evaluated waste shedding rates for early SARS-CoV-2 and the Delta variant, and update population level waste shedding rates for the more-recent Omicron variant in six communities. Mean SARS-CoV-2 waste shedding rates were found to increase with the predominance of the Delta variant and subsequently decrease with Omicron infections. Interestingly, the Delta stage had the highest mean shedding rates and was associated with the most severe disease symptoms reported in other clinical studies, while Omicron, exhibiting reduced symptoms, had the lowest mean shedding rates. Additionally, shedding rates were most consistent across communities during the Omicron stage. This is the first paper to identify waste shedding rates specific to the Omicron variant and fills a knowledge gap critical to disease prevalence modeling.
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Affiliation(s)
- Sarah M Prasek
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Ian L Pepper
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Gabriel K Innes
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8th St., Yuma, AZ 85364, USA
| | - Stephanie Slinski
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8th St., Yuma, AZ 85364, USA
| | - Walter Q Betancourt
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Aidan R Foster
- Water & Energy Sustainable Technology (WEST) Center, University of Arizona, 2959 W. Calle Agua Nueva, Tucson, AZ 85745, USA
| | - Hayley D Yaglom
- The Translational Genomics Research Institute (TGen), 445 N. Fifth Street, Phoenix, AZ 85004, USA
| | - W Tanner Porter
- The Translational Genomics Research Institute (TGen), 445 N. Fifth Street, Phoenix, AZ 85004, USA
| | - David M Engelthaler
- The Translational Genomics Research Institute (TGen), 445 N. Fifth Street, Phoenix, AZ 85004, USA
| | - Bradley W Schmitz
- Yuma Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8th St., Yuma, AZ 85364, USA.
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33
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Tiwari A, Adhikari S, Kaya D, Islam MA, Malla B, Sherchan SP, Al-Mustapha AI, Kumar M, Aggarwal S, Bhattacharya P, Bibby K, Halden RU, Bivins A, Haramoto E, Oikarinen S, Heikinheimo A, Pitkänen T. Monkeypox outbreak: Wastewater and environmental surveillance perspective. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 856:159166. [PMID: 36202364 PMCID: PMC9534267 DOI: 10.1016/j.scitotenv.2022.159166] [Citation(s) in RCA: 44] [Impact Index Per Article: 44.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 09/22/2022] [Accepted: 09/28/2022] [Indexed: 04/13/2023]
Abstract
Monkeypox disease (MPXD), a viral disease caused by the monkeypox virus (MPXV), is an emerging zoonotic disease endemic in some countries of Central and Western Africa but seldom reported outside the affected region. Since May 2022, MPXD has been reported at least in 74 countries globally, prompting the World Health Organization to declare the MPXD outbreak a Public Health Emergency of International Concern. As of July 24, 2022; 92 % (68/74) of the countries with reported MPXD cases had no historical MPXD case reports. From the One Health perspective, the spread of MPXV in the environment poses a risk not only to humans but also to small mammals and may, ultimately, spread to potent novel host populations. Wastewater-based surveillance (WBS) has been extensively utilized to monitor communicable diseases, particularly during the ongoing COVID-19 pandemic. It helped in monitoring infectious disease caseloads as well as specific viral variants circulating in communities. The detection of MPXV DNA in lesion materials (e.g. skin, vesicle fluid, crusts), skin rashes, and various body fluids, including respiratory and nasal secretions, saliva, urine, feces, and semen of infected individuals, supports the possibility of using WBS as an early proxy for the detection of MPXV infections. WBS of MPXV DNA can be used to monitor MPXV activity/trends in sewerage network areas even before detecting laboratory-confirmed clinical cases within a community. However, several factors affect the detection of MPXV in wastewater including, but not limited to, routes and duration time of virus shedding by infected individuals, infection rates in the relevant affected population, environmental persistence, the processes and analytical sensitivity of the used methods. Further research is needed to identify the key factors that impact the detection of MPXV biomarkers in wastewater and improve the utility of WBS of MPXV as an early warning and monitoring tool for safeguarding human health. In this review, we shortly summarize aspects of the MPXV outbreak relevant to wastewater monitoring and discuss the challenges associated with WBS.
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Affiliation(s)
- Ananda Tiwari
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Finland; Department of Health Security, Expert Microbiology Research Unit, Finnish Institute for Health and Welfare, Finland.
| | - Sangeet Adhikari
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Devrim Kaya
- School of Chemical, Biological, and Environmental Engineering, Oregon State University (OSU), Corvallis, OR, USA
| | - 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
| | - Bikash Malla
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Samendra P Sherchan
- Department of Biology, Morgan State University, Baltimore, MD, USA; Department of Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Ahmad I Al-Mustapha
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Finland; Department of Veterinary Public Health and Preventive Medicine, Faculty of Veterinary Medicine, University of Ibadan, Oyo State, Nigeria; Department of Veterinary Services, Kwara State Ministry of Agriculture and Rural Development, Ilorin, Kwara State, Nigeria
| | - Manish Kumar
- Sustainability Cluster, School of Engineering, University of Petroleum & Energy Studies, Dehradun, Uttarakhand 248007, India
| | - Srijan Aggarwal
- Department of Civil, Geological and Environmental Engineering, College of Engineering and Mines, University of Alaska Fairbanks, PO Box 755900, Fairbanks, AK 99775, USA
| | - Prosun Bhattacharya
- Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, SE-10044 Stockholm, Sweden
| | - Kyle Bibby
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, IN 46556, USA
| | - Rolf U Halden
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Aaron Bivins
- Department of Civil & Environmental Engineering, Louisiana State University, LA, USA
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Sami Oikarinen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Annamari Heikinheimo
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Finland; Finnish Food Authority, Seinäjoki, Finland
| | - Tarja Pitkänen
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Finland; Department of Health Security, Expert Microbiology Research Unit, Finnish Institute for Health and Welfare, Finland
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Maal-Bared R, Qiu Y, Li Q, Gao T, Hrudey SE, Bhavanam S, Ruecker NJ, Ellehoj E, Lee BE, Pang X. Does normalization of SARS-CoV-2 concentrations by Pepper Mild Mottle Virus improve correlations and lead time between wastewater surveillance and clinical data in Alberta (Canada): comparing twelve SARS-CoV-2 normalization approaches. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 856:158964. [PMID: 36167131 PMCID: PMC9508694 DOI: 10.1016/j.scitotenv.2022.158964] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/13/2022] [Accepted: 09/19/2022] [Indexed: 05/02/2023]
Abstract
Wastewater-based surveillance (WBS) data normalization is an analyte measurement correction that addresses variations resulting from dilution of fecal discharge by non-sanitary sewage, stormwater or groundwater infiltration. No consensus exists on what WBS normalization parameters result in the strongest correlations and lead time between SARS-CoV-2 WBS data and COVID-19 cases. This study compared flow, population size and biomarker normalization impacts on the correlations and lead times for ten communities in twelve sewersheds in Alberta (Canada) between September 2020 and October 2021 (n = 1024) to determine if normalization by Pepper Mild Mottle Virus (PMMoV) provides any advantages compared to other normalization parameters (e.g., flow, reported and dynamic population sizes, BOD, TSS, NH3, TP). PMMoV concentrations (GC/mL) corresponded with plant influent flows and were highest in the urban centres. SARS-CoV-2 target genes E, N1 and N2 were all negatively associated with wastewater influent pH, while PMMoV was positively associated with temperature. Pooled data analysis showed that normalization increased ρ-values by almost 0.1 and was highest for ammonia, TKN and TP followed by PMMoV. Normalization by other parameters weakened associations. None of the differences were statistically significant. Site-specific correlations showed that normalization of SARS-CoV-2 data by PMMoV only improved correlations significantly in two of the twelve systems; neither were large sewersheds or combined sewer systems. In five systems, normalization by traditional wastewater strength parameters and dynamic population estimates improved correlations. Lead time ranged between 1 and 4 days in both pooled and site-specific comparisons. We recommend that WBS researchers and health departments: a) Investigate WWTP influent properties (e.g., pH) in the WBS planning phase and use at least two parallel approaches for normalization only if shown to provide value; b) Explore normalization by wastewater strength parameters and dynamic population size estimates further; and c) Evaluate purchasing an influent flow meter in small communities to support long-term WBS efforts and WWTP management.
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Affiliation(s)
- Rasha Maal-Bared
- Quality Assurance and Environment, EPCOR Water, Edmonton, Alberta, Canada.
| | - Yuanyuan Qiu
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Qiaozhi Li
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Tiejun Gao
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Sudha Bhavanam
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Norma J Ruecker
- Water Quality Services, City of Calgary, Calgary, Alberta, Canada
| | - Erik Ellehoj
- Ellehoj Redmond Consulting, Edmonton, Alberta, Canada
| | - Bonita E Lee
- Department of Paediatrics, University of Alberta, Edmonton, Alberta, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada; Public Health Laboratories (ProvLab), Alberta Precision Laboratories (APL), Edmonton, Alberta, Canada
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Gitter A, Oghuan J, Godbole AR, Chavarria CA, Monserrat C, Hu T, Wang Y, Maresso AW, Hanson BM, Mena KD, Wu F. Not a waste: Wastewater surveillance to enhance public health. FRONTIERS IN CHEMICAL ENGINEERING 2023. [DOI: 10.3389/fceng.2022.1112876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Domestic wastewater, when collected and evaluated appropriately, can provide valuable health-related information for a community. As a relatively unbiased and non-invasive approach, wastewater surveillance may complement current practices towards mitigating risks and protecting population health. Spurred by the COVID-19 pandemic, wastewater programs are now widely implemented to monitor viral infection trends in sewersheds and inform public health decision-making. This review summarizes recent developments in wastewater-based epidemiology for detecting and monitoring communicable infectious diseases, dissemination of antimicrobial resistance, and illicit drug consumption. Wastewater surveillance, a quickly advancing Frontier in environmental science, is becoming a new tool to enhance public health, improve disease prevention, and respond to future epidemics and pandemics.
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Tang J, Zheng H, Cai J, Liu J, Wang Y, Deng J. Research progress of electrochemical oxidation and self-action of electric field for medical wastewater treatment. Front Microbiol 2023; 13:1083974. [PMID: 36687586 PMCID: PMC9853389 DOI: 10.3389/fmicb.2022.1083974] [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: 10/29/2022] [Accepted: 12/14/2022] [Indexed: 01/11/2023] Open
Abstract
A large number of pathogenic microorganisms exist in medical wastewater, which could invade the human body through the water and cause harm to human health. With the global pandemic coronavirus (COVID-19), public health safety become particularly important, and medical wastewater treatment is an important part of it. In particular, electrochemical disinfection technology has been widely studied in medical wastewater treatment due to its greenness, high efficiency, convenient operation, and other advantages. In this paper, the development status of electrochemical disinfection technology in the treatment of medical wastewater is reviewed, and an electrochemical three-stage disinfection system is proposed for the treatment of medical wastewater. Moreover, prospects for the electrochemical treatment of medical wastewater will be presented. It is hoped that this review could provide insight and guidance for the research and application of electrochemical disinfection technology to treat medical wastewater.GRAPHICAL ABSTRACT.
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Affiliation(s)
- Jun Tang
- Department of Neurothoracic Surgery, The Third People's Hospital of Hubei Province Yangluo Campus, Jianghan University, Wuhan, China
| | - Heng Zheng
- Department of Neurothoracic Surgery, The Third People's Hospital of Hubei Province Yangluo Campus, Jianghan University, Wuhan, China
- College of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan, China
| | - Jinzhong Cai
- Department of Interventional Radiology, Shenzhen People's Hospital (The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, China
| | - Jiang Liu
- College of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan, China
| | - Yangyang Wang
- Department of Neurothoracic Surgery, The Third People's Hospital of Hubei Province Yangluo Campus, Jianghan University, Wuhan, China
- College of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan, China
| | - Jun Deng
- College of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan, China
- Department of Emergency, The Third People's Hospital of Hubei Province, Jianghan University, Wuhan, China
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Kotlarz N, Holcomb DA, Tanvir Pasha ABM, Reckling S, Kays J, Lai YC, Daly S, Palani S, Bailey E, Guidry VT, Christensen A, Berkowitz S, Hoppin JA, Mitasova H, Engel LS, Reyes FLDL, Harris A. Timing and Trends for Municipal Wastewater, Lab-Confirmed Case, and Syndromic Case Surveillance of COVID-19 in Raleigh, North Carolina. Am J Public Health 2023; 113:79-88. [PMID: 36356280 PMCID: PMC9755929 DOI: 10.2105/ajph.2022.307108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/26/2022] [Indexed: 11/12/2022]
Abstract
Objectives. To compare 4 COVID-19 surveillance metrics in a major metropolitan area. Methods. We analyzed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater influent and primary solids in Raleigh, North Carolina, from April 10 through December 13, 2020. We compared wastewater results with lab-confirmed COVID-19 cases and syndromic COVID-like illness (CLI) cases to answer 3 questions: (1) Did they correlate? (2) What was the temporal alignment of the different surveillance systems? (3) Did periods of significant change (i.e., trends) align? Results. In the Raleigh sewershed, wastewater influent, wastewater primary solids, lab-confirmed cases, and CLI were strongly or moderately correlated. Trends in lab-confirmed cases and wastewater influent were observed earlier, followed by CLI and, lastly, wastewater primary solids. All 4 metrics showed sustained increases in COVID-19 in June, July, and November 2020 and sustained decreases in August and September 2020. Conclusions. In a major metropolitan area in 2020, the timing of and trends in municipal wastewater, lab-confirmed case, and syndromic case surveillance of COVID-19 were in general agreement. Public Health Implications. Our results provide evidence for investment in SARS-CoV-2 wastewater and CLI surveillance to complement information provided through lab-confirmed cases. (Am J Public Health. 2023;113(1):79-88. https://doi.org/10.2105/AJPH.2022.307108).
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Affiliation(s)
- Nadine Kotlarz
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - David A Holcomb
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - A B M Tanvir Pasha
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Stacie Reckling
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Judith Kays
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Yi-Chun Lai
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Sean Daly
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Sivaranjani Palani
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Erika Bailey
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Virginia T Guidry
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Ariel Christensen
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Steven Berkowitz
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Jane A Hoppin
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Helena Mitasova
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Lawrence S Engel
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Francis L de Los Reyes
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Angela Harris
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
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Clark JR, Terwilliger A, Avadhanula V, Tisza M, Cormier J, Javornik-Cregeen S, Ross MC, Hoffman KL, Troisi C, Hanson B, Petrosino J, Balliew J, Piedra PA, Rios J, Deegan J, Bauer C, Wu F, Mena KD, Boerwinkle E, Maresso AW. Wastewater pandemic preparedness: Toward an end-to-end pathogen monitoring program. Front Public Health 2023; 11:1137881. [PMID: 37026145 PMCID: PMC10070845 DOI: 10.3389/fpubh.2023.1137881] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 02/09/2023] [Indexed: 04/08/2023] Open
Abstract
Molecular analysis of public wastewater has great potential as a harbinger for community health and health threats. Long-used to monitor the presence of enteric viruses, in particular polio, recent successes of wastewater as a reliable lead indicator for trends in SARS-CoV-2 levels and hospital admissions has generated optimism and emerging evidence that similar science can be applied to other pathogens of pandemic potential (PPPs), especially respiratory viruses and their variants of concern (VOC). However, there are substantial challenges associated with implementation of this ideal, namely that multiple and distinct fields of inquiry must be bridged and coordinated. These include engineering, molecular sciences, temporal-geospatial analytics, epidemiology and medical, and governmental and public health messaging, all of which present their own caveats. Here, we outline a framework for an integrated, state-wide, end-to-end human pathogen monitoring program using wastewater to track viral PPPs.
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Affiliation(s)
- Justin R. Clark
- TAILOR Labs, Baylor College of Medicine, Houston, TX, United States
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
| | - Austen Terwilliger
- TAILOR Labs, Baylor College of Medicine, Houston, TX, United States
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
| | - Vasanthi Avadhanula
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
| | - Michael Tisza
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
- Alkek Center for Metagenomics and Microbiome Research, CMMR, Baylor College of Medicine, Houston, TX, United States
| | - Juwan Cormier
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
- Alkek Center for Metagenomics and Microbiome Research, CMMR, Baylor College of Medicine, Houston, TX, United States
| | - Sara Javornik-Cregeen
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
- Alkek Center for Metagenomics and Microbiome Research, CMMR, Baylor College of Medicine, Houston, TX, United States
| | - Matthew Clayton Ross
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
- Alkek Center for Metagenomics and Microbiome Research, CMMR, Baylor College of Medicine, Houston, TX, United States
| | - Kristi Louise Hoffman
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
- Alkek Center for Metagenomics and Microbiome Research, CMMR, Baylor College of Medicine, Houston, TX, United States
| | - Catherine Troisi
- UTHealth Houston School of Public Health, Houston, TX, United States
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, United States
| | - Blake Hanson
- UTHealth Houston School of Public Health, Houston, TX, United States
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, United States
- Center for Infectious Diseases, Department of Epidemiology, Human Genetics and Environmental Sciences, Houston, TX, United States
| | - Joseph Petrosino
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
- Alkek Center for Metagenomics and Microbiome Research, CMMR, Baylor College of Medicine, Houston, TX, United States
| | - John Balliew
- El Paso Water Utility, El Paso, TX, United States
| | - Pedro A. Piedra
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
- Pediatrics Department, Baylor College of Medicine, Houston, TX, United States
| | - Janelle Rios
- UTHealth Houston School of Public Health, Houston, TX, United States
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, United States
| | - Jennifer Deegan
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, United States
- The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Cici Bauer
- UTHealth Houston School of Public Health, Houston, TX, United States
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, United States
- Department of Biostatistics and Data Science, UTHealth School of Public Health, Houston, TX, United States
| | - Fuqing Wu
- UTHealth Houston School of Public Health, Houston, TX, United States
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, United States
| | - Kristina D. Mena
- UTHealth Houston School of Public Health, Houston, TX, United States
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, United States
| | - Eric Boerwinkle
- UTHealth Houston School of Public Health, Houston, TX, United States
- Texas Epidemic Public Health Institute (TEPHI), UTHealth Houston, Houston, TX, United States
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, Houston, TX, United States
| | - Anthony W. Maresso
- TAILOR Labs, Baylor College of Medicine, Houston, TX, United States
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, United States
- Anthony W. Maresso
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SARS-CoV-2 RNA Is Readily Detectable at Least 8 Months after Shedding in an Isolation Facility. mSphere 2022; 7:e0017722. [PMID: 36218344 PMCID: PMC9769851 DOI: 10.1128/msphere.00177-22] [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] [Indexed: 01/13/2023] Open
Abstract
Environmental monitoring of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for research and public health purposes has grown exponentially throughout the coronavirus disease 2019 (COVID-19) pandemic. Monitoring wastewater for SARS-CoV-2 provides early warning signals of virus spread and information on trends in infections at a community scale. Indoor environmental monitoring (e.g., swabbing of surfaces and air filters) to identify potential outbreaks is less common, and the evidence for its utility is mixed. A significant challenge with surface and air filter monitoring in this context is the concern of "relic RNA," noninfectious RNA found in the environment that is not from recently deposited virus. Here, we report detection of SARS-CoV-2 RNA on surfaces in an isolation unit (a university dorm room) for up to 8 months after a COVID-19-positive individual vacated the space. Comparison of sequencing results from the same location over two time points indicated the presence of the entire viral genome, and sequence similarity confirmed a single source of the virus. Our findings highlight the need to develop approaches that account for relic RNA in environmental monitoring. IMPORTANCE Environmental monitoring of SARS-CoV-2 is rapidly becoming a key tool in infectious disease research and public health surveillance. Such monitoring offers a complementary and sometimes novel perspective on population-level incidence dynamics relative to that of clinical studies by potentially allowing earlier, broader, more affordable, less biased, and less invasive identification. Environmental monitoring can assist public health officials and others when deploying resources to areas of need and provides information on changes in the pandemic over time. Environmental surveillance of the genetic material of infectious agents (RNA and DNA) in wastewater became widely applied during the COVID-19 pandemic. There has been less research on other types of environmental samples, such as surfaces, which could be used to indicate that someone in a particular space was shedding virus. One challenge with surface surveillance is that the noninfectious genetic material from a pathogen (e.g., RNA from SARS-CoV-2) may be detected in the environment long after an infected individual has left the space. This study aimed to determine how long SARS-CoV-2 RNA could be detected in a room after a COVID-positive person had been housed there.
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40
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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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Gafurov A, Baláž A, Amman F, Boršová K, Čabanová V, Klempa B, Bergthaler A, Vinař T, Brejová B. VirPool: model-based estimation of SARS-CoV-2 variant proportions in wastewater samples. BMC Bioinformatics 2022; 23:551. [PMID: 36536300 PMCID: PMC9761630 DOI: 10.1186/s12859-022-05100-3] [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: 06/21/2022] [Accepted: 12/06/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The genomes of SARS-CoV-2 are classified into variants, some of which are monitored as variants of concern (e.g. the Delta variant B.1.617.2 or Omicron variant B.1.1.529). Proportions of these variants circulating in a human population are typically estimated by large-scale sequencing of individual patient samples. Sequencing a mixture of SARS-CoV-2 RNA molecules from wastewater provides a cost-effective alternative, but requires methods for estimating variant proportions in a mixed sample. RESULTS We propose a new method based on a probabilistic model of sequencing reads, capturing sequence diversity present within individual variants, as well as sequencing errors. The algorithm is implemented in an open source Python program called VirPool. We evaluate the accuracy of VirPool on several simulated and real sequencing data sets from both Illumina and nanopore sequencing platforms, including wastewater samples from Austria and France monitoring the onset of the Alpha variant. CONCLUSIONS VirPool is a versatile tool for wastewater and other mixed-sample analysis that can handle both short- and long-read sequencing data. Our approach does not require pre-selection of characteristic mutations for variant profiles, it is able to use the entire length of reads instead of just the most informative positions, and can also capture haplotype dependencies within a single read.
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Affiliation(s)
- Askar Gafurov
- grid.7634.60000000109409708Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava, Bratislava, Slovakia
| | - Andrej Baláž
- grid.7634.60000000109409708Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava, Bratislava, Slovakia
| | - Fabian Amman
- grid.4299.60000 0001 2169 3852CeMM Research Center for Molecular Medicine, Austrian Academy of Sciences, Lazarettgasse 14 AKH BT 25.3, 1090 Vienna, Austria ,grid.22937.3d0000 0000 9259 8492Institute of Hygiene and Applied Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Kinderspitalsgasse 15, Vienna, 1090 Austria
| | - Kristína Boršová
- grid.419303.c0000 0001 2180 9405Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Viktória Čabanová
- grid.419303.c0000 0001 2180 9405Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Boris Klempa
- grid.419303.c0000 0001 2180 9405Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Andreas Bergthaler
- grid.4299.60000 0001 2169 3852CeMM Research Center for Molecular Medicine, Austrian Academy of Sciences, Lazarettgasse 14 AKH BT 25.3, 1090 Vienna, Austria ,grid.22937.3d0000 0000 9259 8492Institute of Hygiene and Applied Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Kinderspitalsgasse 15, Vienna, 1090 Austria
| | - Tomáš Vinař
- grid.7634.60000000109409708Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava, Bratislava, Slovakia
| | - Broňa Brejová
- grid.7634.60000000109409708Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava, Bratislava, Slovakia
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42
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Li Y, Miyani B, Zhao L, Spooner M, Gentry Z, Zou Y, Rhodes G, Li H, Kaye A, Norton J, Xagoraraki I. Surveillance of SARS-CoV-2 in nine neighborhood sewersheds in Detroit Tri-County area, United States: Assessing per capita SARS-CoV-2 estimations and COVID-19 incidence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158350. [PMID: 36041621 PMCID: PMC9419442 DOI: 10.1016/j.scitotenv.2022.158350] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/02/2022] [Accepted: 08/24/2022] [Indexed: 05/14/2023]
Abstract
Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area. Using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR), concentrations of N1 and N2 genes in the studied sites were quantified, with N1 values ranging from 1.92 × 102 genomic copies/L to 6.87 × 103 gc/L and N2 values ranging from 1.91 × 102 gc/L to 6.45 × 103 gc/L. The strongest correlations were observed with between cumulative COVID-19 cases per capita (referred as COVID-19 incidences thereafter), and SARS-CoV-2 concentrations normalized by total Kjeldahl nitrogen (TKN), creatinine, 5-hydroxyindoleacetic acid (5-HIAA) and xanthine when correlating the per capita SARS-CoV-2 and COVID-19 incidences. When SARS-CoV-2 concentrations in wastewater were normalized and compared with COVID-19 incidences, the differences between neighborhoods of varying demographics were reduced as compared to differences observed when comparing non-normalized SARS-CoV-2 with COVID-19 cases. This indicates when studying the disease burden in communities of different demographics, accurate per capita estimation is of great importance. The study suggests that monitoring selected water quality parameters or biomarkers, along with RNA concentrations in wastewater, will allow adequate data normalization for spatial comparisons, especially in areas where detailed sanitary sewage flows and contributing populations in the catchment areas are not available. This opens the possibility of using WBE to assess community infections in rural areas or the developing world where the contributing population of a sample could be unknown.
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Affiliation(s)
- Yabing Li
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America.
| | - Brijen Miyani
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Liang Zhao
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Maddie Spooner
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Zach Gentry
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Yangyang Zou
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Geoff Rhodes
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, East Lansing, MI 48824, United States of America
| | - Hui Li
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, East Lansing, MI 48824, United States of America
| | - Andrew Kaye
- CDM Smith, 535 Griswold St, Detroit, MI 48226, United States of America
| | - John Norton
- Great Lakes Water Authority, 735 Randolph, Detroit, MI 48226, United States of America
| | - Irene Xagoraraki
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
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43
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Ahmed W, Smith WJM, Metcalfe S, Jackson G, Choi PM, Morrison M, Field D, Gyawali P, Bivins A, Bibby K, Simpson SL. Comparison of RT-qPCR and RT-dPCR Platforms for the Trace Detection of SARS-CoV-2 RNA in Wastewater. ACS ES&T WATER 2022; 2:1871-1880. [PMID: 36380768 PMCID: PMC8848507 DOI: 10.1021/acsestwater.1c00387] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
We compared reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and RT digital PCR (RT-dPCR) platforms for the trace detection of SARS-CoV-2 RNA in low-prevalence COVID-19 locations in Queensland, Australia, using CDC N1 and CDC N2 assays. The assay limit of detection (ALOD), PCR inhibition rates, and performance characteristics of each assay, along with the positivity rates with the RT-qPCR and RT-dPCR platforms, were evaluated by seeding known concentrations of exogenous SARS-CoV-2 in wastewater. The ALODs using RT-dPCR were approximately 2-5 times lower than those using RT-qPCR. During sample processing, the endogenous (n = 96) and exogenous (n = 24) SARS-CoV-2 wastewater samples were separated, and RNA was extracted from both wastewater eluates and pellets (solids). The RT-dPCR platform demonstrated a detection rate significantly greater than that of RT-qPCR for the CDC N1 and CDC N2 assays in the eluate (N1, p = 0.0029; N2, p = 0.0003) and pellet (N1, p = 0.0015; N2, p = 0.0067) samples. The positivity results also indicated that for the analysis of SARS-CoV-2 RNA in wastewater, including the eluate and pellet samples may further increase the detection sensitivity using RT-dPCR.
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Affiliation(s)
- Warish Ahmed
- CSIRO
Land and Water, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Wendy J. M. Smith
- CSIRO
Land and Water, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Suzanne Metcalfe
- CSIRO
Land and Water, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Greg Jackson
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Phil M. Choi
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Mary Morrison
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Daniel Field
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Pradip Gyawali
- Institute
of Environmental Science and Research Ltd. (ESR), Porirua 5240, New Zealand
| | - Aaron Bivins
- Department
of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Kyle Bibby
- Department
of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, United States
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44
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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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45
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Cohen A, Maile-Moskowitz A, Grubb C, Gonzalez RA, Ceci A, Darling A, Hungerford L, Fricker R, Finkielstein CV, Pruden A, Vikesland PJ. Subsewershed SARS-CoV-2 Wastewater Surveillance and COVID-19 Epidemiology Using Building-Specific Occupancy and Case Data. ACS ES&T WATER 2022; 2:2047-2059. [PMID: 37552724 PMCID: PMC9128018 DOI: 10.1021/acsestwater.2c00059] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/25/2022] [Accepted: 04/27/2022] [Indexed: 08/10/2023]
Abstract
To evaluate the use of wastewater-based surveillance and epidemiology to monitor and predict SARS-CoV-2 virus trends, over the 2020-2021 academic year we collected wastewater samples twice weekly from 17 manholes across Virginia Tech's main campus. We used data from external door swipe card readers and student isolation/quarantine status to estimate building-specific occupancy and COVID-19 case counts at a daily resolution. After analyzing 673 wastewater samples using reverse transcription quantitative polymerase chain reaction (RT-qPCR), we reanalyzed 329 samples from isolation and nonisolation dormitories and the campus sewage outflow using reverse transcription digital droplet polymerase chain reaction (RT-ddPCR). Population-adjusted viral copy means from isolation dormitory wastewater were 48% and 66% higher than unadjusted viral copy means for N and E genes (1846/100 mL to 2733/100 mL/100 people and 2312/100 mL to 3828/100 mL/100 people, respectively; n = 46). Prespecified analyses with random-effects Poisson regression and dormitory/cluster-robust standard errors showed that the detection of N and E genes were associated with increases of 85% and 99% in the likelihood of COVID-19 cases 8 days later (incident-rate ratio (IRR) = 1.845, p = 0.013 and IRR = 1.994, p = 0.007, respectively; n = 215), and one-log increases in swipe card normalized viral copies (copies/100 mL/100 people) for N and E were associated with increases of 21% and 27% in the likelihood of observing COVID-19 cases 8 days following sample collection (IRR = 1.206, p < 0.001, n = 211 for N; IRR = 1.265, p < 0.001, n = 211 for E). One-log increases in swipe normalized copies were also associated with 40% and 43% increases in the likelihood of observing COVID-19 cases 5 days after sample collection (IRR = 1.403, p = 0.002, n = 212 for N; IRR = 1.426, p < 0.001, n = 212 for E). Our findings highlight the use of building-specific occupancy data and add to the evidence for the potential of wastewater-based epidemiology to predict COVID-19 trends at subsewershed scales.
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Affiliation(s)
- Alasdair Cohen
- Department of Population Health Sciences,
Virginia Tech, Blacksburg, Virginia 24061, United
States
- Department of Civil and Environmental Engineering,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Ayella Maile-Moskowitz
- Department of Civil and Environmental Engineering,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Christopher Grubb
- Department of Statistics, Virginia
Tech, Blacksburg, Virginia 24061, United States
| | - Raul A. Gonzalez
- Hampton Roads Sanitation
District, Virginia Beach, Virginia 23455, United
States
| | - Alessandro Ceci
- Molecular Diagnostics Laboratory, Fralin Biomedical
Research Institute, Virginia Tech, Roanoke, Virginia 24016,
United States
| | - Amanda Darling
- Department of Population Health Sciences,
Virginia Tech, Blacksburg, Virginia 24061, United
States
- Department of Civil and Environmental Engineering,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Laura Hungerford
- Department of Population Health Sciences,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Ronald
D. Fricker
- Department of Statistics, Virginia
Tech, Blacksburg, Virginia 24061, United States
| | - Carla V. Finkielstein
- Molecular Diagnostics Laboratory, Fralin Biomedical
Research Institute, Virginia Tech, Roanoke, Virginia 24016,
United States
- Integrated Cellular Responses Laboratory, Fralin
Biomedical Research Institute at VTC, Roanoke, Virginia 24016,
United States
- Department of Biological Sciences,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Amy Pruden
- Department of Civil and Environmental Engineering,
Virginia Tech, Blacksburg, Virginia 24061, United
States
| | - Peter J. Vikesland
- Department of Civil and Environmental Engineering,
Virginia Tech, Blacksburg, Virginia 24061, United
States
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46
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Xie Y, Challis JK, Oloye FF, Asadi M, Cantin J, Brinkmann M, McPhedran KN, Hogan N, Sadowski M, Jones PD, Landgraff C, Mangat C, Servos MR, Giesy JP. RNA in Municipal Wastewater Reveals Magnitudes of COVID-19 Outbreaks across Four Waves Driven by SARS-CoV-2 Variants of Concern. ACS ES&T WATER 2022; 2:1852-1862. [PMID: 37552734 PMCID: PMC8887651 DOI: 10.1021/acsestwater.1c00349] [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: 09/19/2021] [Revised: 02/10/2022] [Accepted: 02/11/2022] [Indexed: 05/07/2023]
Abstract
There are no standardized protocols for quantifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater to date, especially for population normalization. Here, a pipeline was developed, applied, and assessed to quantify SARS-CoV-2 and key variants of concern (VOCs) RNA in wastewater at Saskatoon, Canada. Normalization approaches using recovery ratio and extraction efficiency, wastewater parameters, or population indicators were assessed by comparing to daily numbers of new cases. Viral load was positively correlated with daily new cases reported in the sewershed. Wastewater surveillance (WS) had a lead time of approximately 7 days, which indicated surges in the number of new cases. WS revealed the variant α and δ driving the third and fourth wave, respectively. The adjustment with the recovery ratio and extraction efficiency improved the correlation between viral load and daily new cases. Normalization of viral concentration to concentrations of the artificial sweetener acesulfame K improved the trend of viral load during the Christmas and New Year holidays when populations were dynamic and variable. Acesulfame K performed better than pepper mild mottle virus, creatinine, and ammonia for population normalization. Hence, quality controls to characterize recovery ratios and extraction efficiencies and population normalization with acesulfame are promising for precise WS programs supporting decision-making in public health.
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Affiliation(s)
- Yuwei Xie
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
| | - Jonathan K. Challis
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
| | - Femi F. Oloye
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
| | - Mohsen Asadi
- Department of Civil, Geological and Environmental
Engineering, College of Engineering, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5A9,
Canada
| | - Jenna Cantin
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
| | - Markus Brinkmann
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
- School of Environment and Sustainability,
University of Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
- Global Institute for Water Security,
University of Saskatchewan, Saskatoon, Saskatchewan S7N 3H5,
Canada
| | - Kerry N. McPhedran
- Department of Civil, Geological and Environmental
Engineering, College of Engineering, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5A9,
Canada
- Global Institute for Water Security,
University of Saskatchewan, Saskatoon, Saskatchewan S7N 3H5,
Canada
| | - Natacha Hogan
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
- College of Agriculture and Bioresources, Department of
Animal and Poultry Sciences, University of Saskatchewan,
Saskatoon, Saskatchewan S7N 5A8, Canada
| | - Mike Sadowski
- Wastewater Treatment Plant, Saskatoon Water Department,
City of Saskatoon, Saskatoon, Saskatchewan S7M 1X5,
Canada
| | - Paul D. Jones
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
- School of Environment and Sustainability,
University of Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
| | - Chrystal Landgraff
- Division of Enteric Diseases, National Microbiology
Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba
R3E 3R2, Canada
- Food Science Department, University of
Guelph, Guelph, Ontario N1G 2W1, Canada
| | - Chand Mangat
- Antimicrobial Resistance and Nosocomial Infections,
National Microbiology Laboratory, Public Health Agency of
Canada, Winnipeg, Manitoba R3E 3R2, Canada
| | - Mark R. Servos
- Department of Biology, University of
Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - John P. Giesy
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
- Department of Veterinary Biomedical Sciences,
University of Saskatchewan, Saskatoon, Saskatchewan S7N 5B4,
Canada
- Department of Environmental Sciences,
Baylor University, Waco, Texas 76706, United
States
- Department of Zoology and Center for Integrative
Toxicology, Michigan State University, East Lansing, Michigan
48824, United States
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47
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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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48
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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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49
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Wartell BA, Proano C, Bakalian L, Kaya D, Croft K, McCreary M, Lichtenstein N, Miske V, Arcellana P, Boyer J, Benschoten IV, Anderson M, Crabb A, Gilson S, Gourley A, Wheeler T, Trest B, Bowman G, Kjellerup BV. Implementing wastewater surveillance for SARS-CoV-2 on a university campus: Lessons learned. WATER ENVIRONMENT RESEARCH : A RESEARCH PUBLICATION OF THE WATER ENVIRONMENT FEDERATION 2022; 94:e10807. [PMID: 36372781 PMCID: PMC9827968 DOI: 10.1002/wer.10807] [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: 05/10/2022] [Revised: 10/16/2022] [Accepted: 10/17/2022] [Indexed: 06/16/2023]
Abstract
Wastewater surveillance, also known as wastewater-based epidemiology (WBE), has been successfully used to detect SARS-CoV-2 and other viruses in sewage in many locations in the United States and globally. This includes implementation of the surveillance on college and university campuses. A two-phase study was conducted during the 2020-2021 academic year to test the feasibility of a WBE system on campus and to supplement the clinical COVID-19 testing performed for the student, staff, and faculty body. The primary objective during the Fall 2020 semester was to monitor a large portion of the on-campus population and to obtain an understanding of the spreading of the SARS-CoV-2 virus. The Spring 2021 objective was focused on selected residence halls and groups of residents on campus, as this was more efficient and relevant for an effective follow-up response. Logistical problems and planning oversights initially occurred but were corrected with improved communication and experience. Many lessons were learned, including effective mapping, site planning, communication, personnel organization, and equipment management, and obtained along the way, thereby paving an opportune guide for future planning efforts. PRACTITIONER POINTS: WBE was successful in the detection of many SARS-CoV-2 variants incl. Alpha, Beta, Gamma, Delta, Lambda, Mu, and Omicron. Careful planning and contingencies were essential for a successful implementation of a SARS-CoV-2 monitoring program. A surveillance program may be important for detection and monitoring of other public health relevant targets in wastewater incl. bacteria, viruses, fungi and viruses. Diverse lessons were learned incl. effective mapping, site planning, communication, personnel organization, and equipment management, thereby providing a guide for future planning efforts.
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Affiliation(s)
- Brian A. Wartell
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Camila Proano
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Lena Bakalian
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Devrim Kaya
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Kristen Croft
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Michael McCreary
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Naomi Lichtenstein
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Victoria Miske
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Patricia Arcellana
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Jessica Boyer
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Isabelle Van Benschoten
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Marya Anderson
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Andrea Crabb
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Susan Gilson
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Anthony Gourley
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Tim Wheeler
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Brian Trest
- Facilities ManagementUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Glynnis Bowman
- Facilities ManagementUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Birthe V. Kjellerup
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
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50
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Zhao L, Zou Y, Li Y, Miyani B, Spooner M, Gentry Z, Jacobi S, David RE, Withington S, McFarlane S, Faust R, Sheets J, Kaye A, Broz J, Gosine A, Mobley P, Busch AWU, Norton J, Xagoraraki I. Five-week warning of COVID-19 peaks prior to the Omicron surge in Detroit, Michigan using wastewater surveillance. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 844:157040. [PMID: 35779714 PMCID: PMC9239917 DOI: 10.1016/j.scitotenv.2022.157040] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 06/24/2022] [Accepted: 06/24/2022] [Indexed: 04/14/2023]
Abstract
Wastewater-based epidemiology (WBE) is useful in predicting temporal fluctuations of COVID-19 incidence in communities and providing early warnings of pending outbreaks. To investigate the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in communities, a 12-month study between September 1, 2020, and August 31, 2021, prior to the Omicron surge, was conducted. 407 untreated wastewater samples were collected from the Great Lakes Water Authority (GLWA) in southeastern Michigan. N1 and N2 genes of SARS-CoV-2 were quantified using RT-ddPCR. Daily confirmed COVID-19 cases for the City of Detroit, and Wayne, Macomb, Oakland counties between September 1, 2020, and October 4, 2021, were collected from a public data source. The total concentrations of N1 and N2 genes ranged from 714.85 to 7145.98 gc/L and 820.47 to 6219.05 gc/L, respectively, which were strongly correlated with the 7-day moving average of total daily COVID-19 cases in the associated areas, after 5 weeks of the viral measurement. The results indicate a potential 5-week lag time of wastewater surveillance preceding COVID-19 incidence for the Detroit metropolitan area. Four statistical models were established to analyze the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in the study areas. Under a 5-week lag time scenario with both N1 and N2 genes, the autoregression model with seasonal patterns and vector autoregression model were more effective in predicting COVID-19 cases during the study period. To investigate the impact of flow parameters on the correlation, the original N1 and N2 gene concentrations were normalized by wastewater flow parameters. The statistical results indicated the optimum models were consistent for both normalized and non-normalized data. In addition, we discussed parameters that explain the observed lag time. Furthermore, we evaluated the impact of the omicron surge that followed, and the impact of different sampling methods on the estimation of lag time.
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Affiliation(s)
- Liang Zhao
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Yangyang Zou
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Yabing Li
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Brijen Miyani
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Maddie Spooner
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Zachary Gentry
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Sydney Jacobi
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Randy E David
- Detroit Health Department, 100 Mack Ave, Detroit, MI 48201, United States of America
| | - Scott Withington
- Detroit Health Department, 100 Mack Ave, Detroit, MI 48201, United States of America
| | - Stacey McFarlane
- Macomb County Health Division, 43525 Elizabeth Rd, Mount Clemens, MI 48043, United States of America
| | - Russell Faust
- Oakland County Health Division, 1200 Telegraph Rd, Pontiac, MI 48341, United States of America
| | - Johnathon Sheets
- CDM-Smith, 535 Griswold St, Detroit, MI 48226, United States of America
| | - Andrew Kaye
- CDM-Smith, 535 Griswold St, Detroit, MI 48226, United States of America
| | - James Broz
- CDM-Smith, 535 Griswold St, Detroit, MI 48226, United States of America
| | - Anil Gosine
- Detroit Water and Sewerage Department, 735 Randolph Street building, Detroit, MI 48226, United States of America
| | - Palencia Mobley
- Detroit Water and Sewerage Department, 735 Randolph Street building, Detroit, MI 48226, United States of America
| | - Andrea W U Busch
- Great Lakes Water Authority, 735 Randolph, Detroit, MI 48226, United States of America
| | - John Norton
- Great Lakes Water Authority, 735 Randolph, Detroit, MI 48226, United States of America
| | - Irene Xagoraraki
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America.
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