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Gupta P, Liao S, Ezekiel M, Novak N, Rossi A, LaCross N, Oakeson K, Rohrwasser A. Wastewater Genomic Surveillance Captures Early Detection of Omicron in Utah. Microbiol Spectr 2023; 11:e0039123. [PMID: 37154725 PMCID: PMC10269515 DOI: 10.1128/spectrum.00391-23] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 04/12/2023] [Indexed: 05/10/2023] Open
Abstract
Wastewater-based epidemiology has emerged as a powerful public health tool to trace new outbreaks, detect trends in infection, and provide an early warning of COVID-19 community spread. Here, we investigated the spread of SARS-CoV-2 infections across Utah by characterizing lineages and mutations detected in wastewater samples. We sequenced over 1,200 samples from 32 sewersheds collected between November 2021 and March 2022. Wastewater sequencing confirmed the presence of Omicron (B.1.1.529) in Utah in samples collected on November 19, 2021, up to 10 days before its corresponding detection via clinical sequencing. Analysis of diversity of SARS-CoV-2 lineages revealed Delta as the most frequently detected lineage during November 2021 (67.71%), but it started declining in December 2021 with the onset of Omicron (B.1.1529) and its sublineage BA.1 (6.79%). The proportion of Omicron increased to ~58% by January 4, 2022, and completely displaced Delta by February 7, 2022. Wastewater genomic surveillance revealed the presence of Omicron sublineage BA.3, a lineage that was not identified from Utah's clinical surveillance. Interestingly, several Omicron-defining mutations began to appear in early November 2021 and increased in prevalence across sewersheds from December to January, aligning with the surge in clinical cases. Our study highlights the importance of tracking epidemiologically relevant mutations in detecting emerging lineages in the early stages of an outbreak. Wastewater genomic epidemiology provides an unbiased representation of community-wide infection dynamics and is an excellent complementary tool to SARS-CoV-2 clinical surveillance, with the potential of guiding public health action and policy decisions. IMPORTANCE SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has had a significant impact on public health. Global emergence of novel SARS-CoV-2 variants, shift to at-home tests, and reduction in clinical tests demonstrate the need for a reliable and effective surveillance strategy to contain COVID-19 spread. Monitoring of SARS-CoV-2 viruses in wastewater is an effective way to trace new outbreaks, establish baseline levels of infection, and complement clinical surveillance efforts. Wastewater genomic surveillance, in particular, can provide valuable insights into the evolution and spread of SARS-CoV-2 variants. We characterized the diversity of SARS-CoV-2 mutations and lineages using whole-genome sequencing to trace the introduction of lineage B.1.1.519 (Omicron) in Utah. Our data showed that Omicron appeared in Utah on November 19, 2021, up to 10 days prior to its detection in patient samples, indicating that wastewater surveillance provides an early warning signal. Our findings are important from a public health perspective as timely identification of communities with high COVID-19 transmission could help guide public health interventions.
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Affiliation(s)
- Pooja Gupta
- Utah Public Health Laboratory, Utah Department of Health and Human Services, Salt Lake City, Utah, USA
| | - Stefan Liao
- Utah Public Health Laboratory, Utah Department of Health and Human Services, Salt Lake City, Utah, USA
| | - Maleea Ezekiel
- Utah Public Health Laboratory, Utah Department of Health and Human Services, Salt Lake City, Utah, USA
| | - Nicolle Novak
- Utah Public Health Laboratory, Utah Department of Health and Human Services, Salt Lake City, Utah, USA
| | - Alessandro Rossi
- Utah Public Health Laboratory, Utah Department of Health and Human Services, Salt Lake City, Utah, USA
| | - Nathan LaCross
- Utah Department of Health and Human Services, Salt Lake City, Utah, USA
| | - Kelly Oakeson
- Utah Public Health Laboratory, Utah Department of Health and Human Services, Salt Lake City, Utah, USA
| | - Andreas Rohrwasser
- Utah Public Health Laboratory, Utah Department of Health and Human Services, Salt Lake City, Utah, USA
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Phan T, Brozak S, Pell B, Ciupe SM, Ke R, Ribeiro RM, Gitter A, Mena KD, Perelson AS, Kuang Y, Wu F. Prolonged viral shedding from noninfectious individuals confounds wastewater-based epidemiology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.08.23291144. [PMID: 37333173 PMCID: PMC10274979 DOI: 10.1101/2023.06.08.23291144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Wastewater surveillance has been widely used to track and estimate SARS-CoV-2 incidence. While both infectious and recovered individuals shed virus into wastewater, epidemiological inferences using wastewater often only consider the viral contribution from the former group. Yet, the persistent shedding in the latter group could confound wastewater-based epidemiological inference, especially during the late stage of an outbreak when the recovered population outnumbers the infectious population. To determine the impact of recovered individuals' viral shedding on the utility of wastewater surveillance, we develop a quantitative framework that incorporates population-level viral shedding dynamics, measured viral RNA in wastewater, and an epidemic dynamic model. We find that the viral shedding from the recovered population can become higher than the infectious population after the transmission peak, which leads to a decrease in the correlation between wastewater viral RNA and case report data. Furthermore, the inclusion of recovered individuals' viral shedding into the model predicts earlier transmission dynamics and slower decreasing trends in wastewater viral RNA. The prolonged viral shedding also induces a potential delay in the detection of new variants due to the time needed to generate enough new cases for a significant viral signal in an environment dominated by virus shed by the recovered population. This effect is most prominent toward the end of an outbreak and is greatly affected by both the recovered individuals' shedding rate and shedding duration. Our results suggest that the inclusion of viral shedding from non-infectious recovered individuals into wastewater surveillance research is important for precision epidemiology.
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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
| | - Stanca M. Ciupe
- Department of Mathematics, Virginia Tech, Blacksburg, VA 24060, USA
| | - Ruian Ke
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Ruy M. Ribeiro
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Anna Gitter
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Texas Epidemic Public Health Institute, TX, 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, TX, 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, TX, USA
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53
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Trigo-Tasende N, Vallejo JA, Rumbo-Feal S, Conde-Pérez K, Vaamonde M, López-Oriona Á, Barbeito I, Nasser-Ali M, Reif R, Rodiño-Janeiro BK, Fernández-Álvarez E, Iglesias-Corrás I, Freire B, Tarrío-Saavedra J, Tomás L, Gallego-García P, Posada D, Bou G, López-de-Ullibarri I, Cao R, Ladra S, Poza M. Wastewater early warning system for SARS-CoV-2 outbreaks and variants in a Coruña, Spain. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023:10.1007/s11356-023-27877-3. [PMID: 37286834 DOI: 10.1007/s11356-023-27877-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 05/19/2023] [Indexed: 06/09/2023]
Abstract
Wastewater-based epidemiology has been widely used as a cost-effective method for tracking the COVID-19 pandemic at the community level. Here we describe COVIDBENS, a wastewater surveillance program running from June 2020 to March 2022 in the wastewater treatment plant of Bens in A Coruña (Spain). The main goal of this work was to provide an effective early warning tool based in wastewater epidemiology to help in decision-making at both the social and public health levels. RT-qPCR procedures and Illumina sequencing were used to weekly monitor the viral load and to detect SARS-CoV-2 mutations in wastewater, respectively. In addition, own statistical models were applied to estimate the real number of infected people and the frequency of each emerging variant circulating in the community, which considerable improved the surveillance strategy. Our analysis detected 6 viral load waves in A Coruña with concentrations between 103 and 106 SARS-CoV-2 RNA copies/L. Our system was able to anticipate community outbreaks during the pandemic with 8-36 days in advance with respect to clinical reports and, to detect the emergence of new SARS-CoV-2 variants in A Coruña such as Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529 and BA.2) in wastewater with 42, 30, and 27 days, respectively, before the health system did. Data generated here helped local authorities and health managers to give a faster and more efficient response to the pandemic situation, and also allowed important industrial companies to adapt their production to each situation. The wastewater-based epidemiology program developed in our metropolitan area of A Coruña (Spain) during the SARS-CoV-2 pandemic served as a powerful early warning system combining statistical models with mutations and viral load monitoring in wastewater over time.
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Affiliation(s)
- Noelia Trigo-Tasende
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Juan A Vallejo
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Soraya Rumbo-Feal
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Kelly Conde-Pérez
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Manuel Vaamonde
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Ángel López-Oriona
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Inés Barbeito
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Mohammed Nasser-Ali
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Rubén Reif
- Center for Research in Biological Chemistry and Molecular Materials (CiQUS), University of Santiago de Compostela (USC), 15782, Santiago de Compostela, Spain
| | - Bruno K Rodiño-Janeiro
- BFlow, University of Santiago de Compostela (USC) and Health Research Institute of Santiago de Compostela (IDIS), Campus Vida, 15706, Santiago de Compostela, A Coruña, Spain
| | - Elisa Fernández-Álvarez
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Iago Iglesias-Corrás
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Borja Freire
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Javier Tarrío-Saavedra
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Laura Tomás
- CINBIO, Universidade de Vigo, 36310, Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312, Vigo, Spain
| | - Pilar Gallego-García
- CINBIO, Universidade de Vigo, 36310, Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312, Vigo, Spain
| | - David Posada
- CINBIO, Universidade de Vigo, 36310, Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312, Vigo, Spain
- Department of Biochemistry, Genetics, and Immunology, Universidade de Vigo, 36310, Vigo, Spain
| | - Germán Bou
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Ignacio López-de-Ullibarri
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Ricardo Cao
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Susana Ladra
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Margarita Poza
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain.
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54
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Khan M, Li L, Haak L, Payen SH, Carine M, Adhikari K, Uppal T, Hartley PD, Vasquez-Gross H, Petereit J, Verma SC, Pagilla K. Significance of wastewater surveillance in detecting the prevalence of SARS-CoV-2 variants and other respiratory viruses in the community - A multi-site evaluation. One Health 2023; 16:100536. [PMID: 37041760 PMCID: PMC10074727 DOI: 10.1016/j.onehlt.2023.100536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/30/2023] [Accepted: 03/31/2023] [Indexed: 04/13/2023] Open
Abstract
Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome in wastewater has proven to be useful for tracking the trends of virus prevalence within the community. The surveillance also provides precise and early detection of any new and circulating variants, which aids in response to viral outbreaks. Site-specific monitoring of SARS-CoV-2 variants provides valuable information on the prevalence of new or emerging variants in the community. We sequenced the genomic RNA of viruses present in the wastewater samples and analyzed for the prevalence of SARS-CoV-2 variants as well as other respiratory viruses for a period of one year to account for seasonal variations. The samples were collected from the Reno-Sparks metropolitan area on a weekly basis between November 2021 to November 2022. Samples were analyzed to detect the levels of SARS-CoV-2 genomic copies and variants identification. This study confirmed that wastewater monitoring of SARS-CoV-2 variants can be used for community surveillance and early detection of circulating variants and supports wastewater-based epidemiology (WBE) as a complement to clinical respiratory virus testing as a healthcare response effort. Our study showed the persistence of the SARS-CoV-2 virus throughout the year compared to a seasonal presence of other respiratory viruses, implicating SARS-CoV-2's broad genetic diversity and strength to persist and infect susceptible hosts. Through secondary analysis, we further identified antimicrobial resistance (AMR) genes in the same wastewater samples and found WBE to be a feasible tool for community AMR detection and monitoring.
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Affiliation(s)
- Majid Khan
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Lin Li
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
| | - Laura Haak
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
| | - Shannon Harger Payen
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Madeline Carine
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
| | - Kabita Adhikari
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Timsy Uppal
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Paul D. Hartley
- Nevada Genomics Center, University of Nevada, Reno, NV 89557, USA
| | - Hans Vasquez-Gross
- Nevada Bioinformatics Center (RRID:SCR_017802), University of Nevada, Reno, NV 89557, USA
| | - Juli Petereit
- Nevada Bioinformatics Center (RRID:SCR_017802), University of Nevada, Reno, NV 89557, USA
| | - Subhash C. Verma
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Krishna Pagilla
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
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55
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Joung MJ, Mangat CS, Mejia EM, Nagasawa A, Nichani A, Perez-Iratxeta C, Peterson SW, Champredon D. Coupling wastewater-based epidemiological surveillance and modelling of SARS-COV-2/COVID-19: Practical applications at the Public Health Agency of Canada. CANADA COMMUNICABLE DISEASE REPORT = RELEVE DES MALADIES TRANSMISSIBLES AU CANADA 2023; 49:166-174. [PMID: 38404704 PMCID: PMC10890812 DOI: 10.14745/ccdr.v49i05a01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Wastewater-based surveillance (WBS) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) offers a complementary tool for clinical surveillance to detect and monitor coronavirus disease 2019 (COVID-19). Since both symptomatic and asymptomatic individuals infected with SARS-CoV-2 can shed the virus through the fecal route, WBS has the potential to measure community prevalence of COVID-19 without restrictions from healthcare-seeking behaviours and clinical testing capacity. During the Omicron wave, the limited capacity of clinical testing to identify COVID-19 cases in many jurisdictions highlighted the utility of WBS to estimate disease prevalence and inform public health strategies; however, there is a plethora of in-sewage, environmental and laboratory factors that can influence WBS outcomes. The implementation of WBS, therefore, requires a comprehensive framework to outline a pipeline that accounts for these complex and nuanced factors. This article reviews the framework of the national WBS conducted at the Public Health Agency of Canada to present WBS methods used in Canada to track and monitor SARS-CoV-2. In particular, we focus on five Canadian cities-Vancouver, Edmonton, Toronto, Montréal and Halifax-whose wastewater signals are analyzed by a mathematical model to provide case forecasts and reproduction number estimates. The goal of this work is to share our insights on approaches to implement WBS. Importantly, the national WBS system has implications beyond COVID-19, as a similar framework can be applied to monitor other infectious disease pathogens or antimicrobial resistance in the community.
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Affiliation(s)
- Meong Jin Joung
- National Microbiology Laboratory, Public Health Risk Sciences Division, Public Health Agency of Canada, Guelph, ON
- Dalla Lana School of Public Health, University of Toronto. Toronto, ON
| | - Chand S Mangat
- National Microbiology Laboratory, Wastewater Surveillance Unit, Public Health Agency of Canada, Winnipeg, MB
| | - Edgard M Mejia
- National Microbiology Laboratory, Wastewater Surveillance Unit, Public Health Agency of Canada, Winnipeg, MB
| | - Audra Nagasawa
- Statistics Canada, Centre for Direct Health Measures, Ottawa, ON
| | - Anil Nichani
- National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON
| | | | - Shelley W Peterson
- National Microbiology Laboratory, Wastewater Surveillance Unit, Public Health Agency of Canada, Winnipeg, MB
| | - David Champredon
- National Microbiology Laboratory, Public Health Risk Sciences Division, Public Health Agency of Canada, Guelph, ON
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56
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de Graaf M, Langeveld J, Post J, Carrizosa C, Franz E, Izquierdo-Lara RW, Elsinga G, Heijnen L, Been F, van Beek J, Schilperoort R, Vriend R, Fanoy E, de Schepper EIT, Koopmans MPG, Medema G. Capturing the SARS-CoV-2 infection pyramid within the municipality of Rotterdam using longitudinal sewage surveillance. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 883:163599. [PMID: 37100150 PMCID: PMC10125208 DOI: 10.1016/j.scitotenv.2023.163599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 04/07/2023] [Accepted: 04/15/2023] [Indexed: 05/03/2023]
Abstract
Despite high vaccination rates in the Netherlands, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to circulate. Longitudinal sewage surveillance was implemented along with the notification of cases as two parts of the surveillance pyramid to validate the use of sewage for surveillance, as an early warning tool, and to measure the effect of interventions. Sewage samples were collected from nine neighborhoods between September 2020 and November 2021. Comparative analysis and modeling were performed to understand the correlation between wastewater and case trends. Using high resolution sampling, normalization of wastewater SARS-CoV-2 concentrations, and 'normalization' of reported positive tests for testing delay and intensity, the incidence of reported positive tests could be modeled based on sewage data, and trends in both surveillance systems coincided. The high collinearity implied that high levels of viral shedding around the onset of disease largely determined SARS-CoV-2 levels in wastewater, and that the observed relationship was independent of variants of concern and vaccination levels. Sewage surveillance alongside a large-scale testing effort where 58 % of a municipality was tested, indicated a five-fold difference in the number of SARS-CoV-2-positive individuals and reported cases through standard testing. Where trends in reported positive cases were biased due to testing delay and testing behavior, wastewater surveillance can objectively display SARS-CoV-2 dynamics for both small and large locations and is sensitive enough to measure small variations in the number of infected individuals within or between neighborhoods. With the transition to a post-acute phase of the pandemic, sewage surveillance can help to keep track of re-emergence, but continued validation studies are needed to assess the predictive value of sewage surveillance with new variants. Our findings and model aid in interpreting SARS-CoV-2 surveillance data for public health decision-making and show its potential as one of the pillars of future surveillance of (re)emerging viruses.
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Affiliation(s)
- Miranda de Graaf
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, the Netherlands; Pandemic and Disaster Preparedness Centre Rotterdam and Delft, the Netherlands.
| | - Jeroen Langeveld
- Partners4urbanwater, Nijmegen, the Netherlands; Delft University of Technology, Stevinweg 1, 2628 CN Delft, the Netherlands
| | - Johan Post
- Partners4urbanwater, Nijmegen, the Netherlands
| | - Christian Carrizosa
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Eelco Franz
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Ray W Izquierdo-Lara
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Goffe Elsinga
- KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, the Netherlands
| | - Leo Heijnen
- KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, the Netherlands
| | - Frederic Been
- KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, the Netherlands
| | - Janko van Beek
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Rianne Vriend
- Regional Public Health Service Rotterdam-Rijnmond, Rotterdam, the Netherlands
| | - Ewout Fanoy
- Regional Public Health Service Rotterdam-Rijnmond, Rotterdam, the Netherlands
| | - Evelien I T de Schepper
- Department of General Practice, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Marion P G Koopmans
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, the Netherlands; Pandemic and Disaster Preparedness Centre Rotterdam and Delft, the Netherlands
| | - Gertjan Medema
- Pandemic and Disaster Preparedness Centre Rotterdam and Delft, the Netherlands; KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, the Netherlands; Delft University of Technology, Stevinweg 1, 2628 CN Delft, the Netherlands
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57
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Ferreira RDO, Guimarães ATB, Luz TMD, Rodrigues ASDL, Islam ARMT, Rahman MM, Ragavendran C, Kamaraj C, Charlie-Silva I, Durigon EL, Braz HLB, Arias AH, Santiago OC, Barceló D, Malafaia G. First report on the toxicity of SARS-CoV-2, alone and in combination with polyethylene microplastics in neotropical fish. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 882:163617. [PMID: 37088384 PMCID: PMC10122543 DOI: 10.1016/j.scitotenv.2023.163617] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/10/2023] [Accepted: 04/17/2023] [Indexed: 05/03/2023]
Abstract
The COVID-19 pandemic has caused unprecedented negative impacts in the modern era, including economic, social, and public health losses. On the other hand, the potential effects that the input of SARS-CoV-2 in the aquatic environment from sewage may represent on non-target organisms are not well known. In addition, it is not yet known whether the association of SARS-CoV-2 with other pollutants, such as microplastics (MPs), may further impact the aquatic biota. Thus, we aimed to evaluate the possible ecotoxicological effects of exposure of male adults Poecilia reticulata, for 15 days, to inactivated SARS-CoV-2 (0.742 pg/L; isolated SARS.CoV2/SP02.2020.HIAE.Br) and polyethylene MP (PE MPs) (7.1 × 104 particles/L), alone and in combination, from multiple biomarkers. Our data suggest that exposure to SARS-CoV-2 induced behavioral changes (in the open field test), nephrotoxic effect (inferred by the increase in creatinine), hepatotoxic effect (inferred by the increase in bilirubin production), imbalance in the homeostasis of Fe, Ca, and Mg, as well as an anticholinesterase effect in the animals [marked by the reduction of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) activity]. On the other hand, exposure to PE MPs induced a genotoxic effect (assessed by the comet assay), as well as an increase in enzyme activity alpha-amylase, alkaline phosphatase, and carboxylesterases. However, we did not show synergistic, antagonistic, or additive effects caused by the combined exposure of P. reticulata to SARS-CoV-2 and PE MPs. Principal component analysis (PCA) and values from the "Integrated Biomarker Response" index indicate that exposure to SARS-CoV-2 was determinant for a more prominent effect in the evaluated animals. Therefore, our study sheds light on the ecotoxicity of the new coronavirus in non-target organisms and ratifies the need for more attention to the impacts of COVID-19 on aquatic biota.
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Affiliation(s)
- Raíssa de Oliveira Ferreira
- Laboratory of Toxicology Applied to the Environment, Goiano Federal Institute, Urutaí, GO, Brazil; Post-Graduation Program in Conservation of Cerrado Natural Resources, Goiano Federal Institute, Urutaí, GO, Brazil; Water and Soil Quality Research Group, Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), JordiGirona 1826, 08034 Barcelona, Spain
| | | | - Thiarlen Marinho da Luz
- Laboratory of Toxicology Applied to the Environment, Goiano Federal Institute, Urutaí, GO, Brazil; Post-Graduation Program in Conservation of Cerrado Natural Resources, Goiano Federal Institute, Urutaí, GO, Brazil
| | - Aline Sueli de Lima Rodrigues
- Laboratory of Toxicology Applied to the Environment, Goiano Federal Institute, Urutaí, GO, Brazil; Post-Graduation Program in Conservation of Cerrado Natural Resources, Goiano Federal Institute, Urutaí, GO, Brazil
| | | | - Md Mostafizur Rahman
- Laboratory of Environmental Health and Ecotoxicology, Department of Environmental Sciences, Jahangirnagar University, Dhaka 1342, Bangladesh
| | - Chinnasamy Ragavendran
- Department of Conservative Dentistry and Endodontics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, India
| | - Chinnaperumal Kamaraj
- Interdisciplinary Institute of Indian System of Medicine (IIISM), Directorate of Research and Virtual Education, SRM Institute of Science and Technology (SRMIST), Kattankulathur 603203, Tamil Nadu, India
| | - Ives Charlie-Silva
- Chemistry Institute, São Paulo State University (UNESP) Campus Araraquara, Brazil
| | - Edison Luiz Durigon
- Laboratory of Clinical and Molecular Virology, Institute of Biomedical Sciences, University of São Paulo, Brazil
| | | | - Andrés Hugo Arias
- National University of the South Bahía Blanca, CONICET Instituto Argentino de Oceanografía (IADO), Argentina
| | - Omar Cruz Santiago
- Multidisciplinary Postgraduate Program for Environmental Sciences, Universidad Autónoma de San Luis Potosí, Mexico
| | - Damià Barceló
- Catalan Institute for Water Research (ICRA-CERCA), H2O Building, Scientific and Technological Park of the University of Girona, Emili Grahit 101, 17003 Girona, Spain
| | - Guilherme Malafaia
- Laboratory of Toxicology Applied to the Environment, Goiano Federal Institute, Urutaí, GO, Brazil; Post-Graduation Program in Conservation of Cerrado Natural Resources, Goiano Federal Institute, Urutaí, GO, Brazil; Post-Graduation Program in Ecology, Conservation, and Biodiversity, Federal University of Uberlândia, Uberlândia, MG, Brazil; Post-Graduation Program in Biotechnology and Biodiversity, Federal University of Goiás, Goiânia, GO, Brazil; Brazilian Academy of Young Scientists (ABJC), Brazil.
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58
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Dehghan Banadaki M, Torabi S, Strike WD, Noble A, Keck JW, Berry SM. Improving wastewater-based epidemiology performance through streamlined automation. JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING 2023; 11:109595. [PMID: 36875746 PMCID: PMC9970922 DOI: 10.1016/j.jece.2023.109595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 02/02/2023] [Accepted: 02/26/2023] [Indexed: 06/18/2023]
Abstract
Wastewater-based epidemiology (WBE) has enabled us to describe Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections in populations. However, implementation of wastewater monitoring of SARS-CoV-2 is limited due to the need for expert staff, expensive equipment, and prolonged processing times. As WBE increases in scope (beyond SARS-CoV-2) and scale (beyond developed regions), there is a need to make WBE processes simpler, cheaper, and faster. We developed an automated workflow based on a simplified method termed exclusion-based sample preparation (ESP). Our automated workflow takes 40 min from raw wastewater to purified RNA, which is several times faster than conventional WBE methods. The total assay cost per sample/replicate is $6.50 which includes consumables and reagents for concentration, extraction, and RT-qPCR quantification. The assay complexity is reduced significantly, as extraction and concentration steps are integrated and automated. The high recovery efficiency of the automated assay (84.5 ± 25.4%) yielded an improved Limit of Detection (LoDAutomated=40 copies/mL) compared to the manual process (LoDManual=206 copies/mL), increasing analytical sensitivity. We validated the performance of the automated workflow by comparing it with the manual method using wastewater samples from several locations. The results from the two methods correlated strongly (r = 0.953), while the automated method was shown to be more precise. In 83% of the samples, the automated method showed lower variation between replicates, which is likely due to higher technical errors in the manual process e.g., pipetting. Our automated wastewater workflow can support the expansion of WBE in the fight against Coronavirus Disease of 2019 (COVID-19) and other epidemics.
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Affiliation(s)
| | - Soroosh Torabi
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States
| | - William D Strike
- Department of Biomedical Engineering, College of Engineering, University of Kentucky, United States
| | - Ann Noble
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States
| | - James W Keck
- Department of Family and Community Medicine, College of Medicine, University of Kentucky, United States
| | - Scott M Berry
- Department of Mechanical Engineering, College of Engineering, University of Kentucky, United States
- Department of Biomedical Engineering, College of Engineering, University of Kentucky, United States
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59
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Swift CL, Isanovic M, Correa Velez KE, Norman RS. SARS-CoV-2 concentration in wastewater consistently predicts trends in COVID-19 case counts by at least two days across multiple WWTP scales. ENVIRONMENTAL ADVANCES 2023; 11:100347. [PMID: 36718477 PMCID: PMC9876004 DOI: 10.1016/j.envadv.2023.100347] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/17/2023] [Accepted: 01/21/2023] [Indexed: 06/18/2023]
Abstract
Wastewater surveillance of SARS-CoV-2 has proven instrumental in mitigating the spread of COVID-19 by providing an economical and equitable approach to disease surveillance. Here, we analyze the correlation of SARS-CoV-2 RNA in influents of seven wastewater plants (WWTPs) across the state of South Carolina with corresponding daily case counts to determine whether underlying characteristics of WWTPs and sewershed populations predict stronger correlations. The populations served by these WWTPs have varying social vulnerability and represent 24% of the South Carolina population. The study spanned 15 months from April 19, 2020, to July 1, 2021, which includes the administration of the first COVID-19 vaccines. SARS-CoV-2 RNA concentrations were measured by either reverse transcription quantitative PCR (RT-qPCR) or droplet digital PCR (RT-ddPCR). Although populations served and average flow rate varied across WWTPs, the strongest correlation was identified for six of the seven WWTPs when daily case counts were lagged two days after the measured SARS-CoV-2 RNA concentration in wastewater. The weakest correlation was found for WWTP 6, which had the lowest ratio of population served to average flow rate, indicating that the SARS-CoV-2 signal was too dilute for a robust correlation. Smoothing daily case counts by a 7-day moving average improved correlation strength between case counts and SARS-CoV-2 RNA concentration in wastewater while dampening the effect of lag-time optimization. Correlation strength between cases and SARS-CoV-2 RNA was compared for cases determined at the ZIP-code and sewershed levels. The strength of correlations using ZIP-code-level versus sewershed-level cases were not statistically different across WWTPs. Results indicate that wastewater surveillance, even without normalization to fecal indicators, is a strong predictor of clinical cases by at least two days, especially when SARS-CoV-2 RNA is measured using RT-ddPCR. Furthermore, the ratio of population served to flow rate may be a useful metric to assess whether a WWTP is suitable for a surveillance program.
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Affiliation(s)
- Candice L Swift
- Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA
| | - Mirza Isanovic
- Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA
| | - Karlen E Correa Velez
- Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA
| | - R Sean Norman
- Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA
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Babler KM, Sharkey ME, Abelson S, Amirali A, Benitez A, Cosculluela GA, Grills GS, Kumar N, Laine J, Lamar W, Lamm ED, Lyu J, Mason CE, McCabe PM, Raghavender J, Reding BD, Roca MA, Schürer SC, Stevenson M, Szeto A, Tallon JJ, Vidović D, Zarnegarnia Y, Solo-Gabriele HM. Degradation rates influence the ability of composite samples to represent 24-hourly means of SARS-CoV-2 and other microbiological target measures in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 867:161423. [PMID: 36623667 PMCID: PMC9817413 DOI: 10.1016/j.scitotenv.2023.161423] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 12/25/2022] [Accepted: 01/02/2023] [Indexed: 06/17/2023]
Abstract
The utility of using severe-acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA for assessing the prevalence of COVID-19 within communities begins with the design of the sample collection program. The objective of this study was to assess the utility of 24-hour composites as representative samples for measuring multiple microbiological targets in wastewater, and whether normalization of SARS-CoV-2 by endogenous targets can be used to decrease hour to hour variability at different watershed scales. Two sets of experiments were conducted, in tandem with the same wastewater, with samples collected at the building, cluster, and community sewershed scales. The first set of experiments focused on evaluating degradation of microbiological targets: SARS-CoV-2, Simian Immunodeficiency Virus (SIV) - a surrogate spiked into the wastewater, plus human waste indicators of Pepper Mild Mottle Virus (PMMoV), Beta-2 microglobulin (B2M), and fecal coliform bacteria (FC). The second focused on the variability of these targets from samples, collected each hour on the hour. Results show that SARS-CoV-2, PMMoV, and B2M were relatively stable, with minimal degradation over 24-h. SIV, which was spiked-in prior to analysis, degraded significantly and FC increased significantly over the course of 24 h, emphasizing the possibility for decay and growth within wastewater. Hour-to-hour variability of the source wastewater was large between each hour of sampling relative to the variability of the SARS-CoV-2 levels calculated between sewershed scales; thus, differences in SARS-CoV-2 hourly variability were not statistically significant between sewershed scales. Results further provided that the quantified representativeness of 24-h composite samples (i.e., statistical equivalency compared against hourly collected grabs) was dependent upon the molecular target measured. Overall, improvements made by normalization were minimal within this study. Degradation and multiplication for other targets should be evaluated when deciding upon whether to collect composite or grab samples in future studies.
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Affiliation(s)
- Kristina M Babler
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Mark E Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Samantha Abelson
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Aymara Benitez
- Miami-Dade Water and Sewer Department, Miami, FL 33149, USA
| | - Gabriella A Cosculluela
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Naresh Kumar
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Walter Lamar
- Division of Occupational Health, Safety & Compliance, University of Miami Health System, Miami, FL 33136, USA
| | - Erik D Lamm
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Jiangnan Lyu
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10021, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY 10021, USA
| | - Philip M McCabe
- Department of Psychology, University of Miami, Coral Gables, FL 33146, USA; Department of Biomedical Engineering, University of Miami, Coral Gables, FL 33146, USA
| | | | - Brian D Reding
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Matthew A Roca
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Institute for Data Science & Computing, University of Miami, Coral Gables, FL, USA
| | - Mario Stevenson
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Angela Szeto
- Department of Psychology, University of Miami, Coral Gables, FL 33146, USA
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL 33146, USA
| | - Dusica Vidović
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Yalda Zarnegarnia
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA.
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Cha G, Graham KE, Zhu KJ, Rao G, Lindner BG, Kocaman K, Woo S, D'amico I, Bingham LR, Fischer JM, Flores CI, Spencer JW, Yathiraj P, Chung H, Biliya S, Djeddar N, Burton LJ, Mascuch SJ, Brown J, Bryksin A, Pinto A, Hatt JK, Konstantinidis KT. Parallel deployment of passive and composite samplers for surveillance and variant profiling of SARS-CoV-2 in sewage. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 866:161101. [PMID: 36581284 PMCID: PMC9792180 DOI: 10.1016/j.scitotenv.2022.161101] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 12/14/2022] [Accepted: 12/17/2022] [Indexed: 05/12/2023]
Abstract
Wastewater-based epidemiology during the COVID-19 pandemic has proven useful for public health decision-making but is often hampered by sampling methodology constraints, particularly at the building- or neighborhood-level. Time-weighted composite samples are commonly used; however, autosamplers are expensive and can be affected by intermittent flows in sub-sewershed contexts. In this study, we compared time-weighted composite, grab, and passive sampling via Moore swabs, at four locations across a college campus to understand the utility of passive sampling. After optimizing the methods for sample handling and processing for viral RNA extraction, we quantified SARS-CoV-2 N1 and N2, as well as a fecal strength indicator, PMMoV, by ddRT-PCR and applied tiled amplicon sequencing of the SARS-CoV-2 genome. Passive samples compared favorably with composite samples in our study area: for samples collected concurrently, 42 % of the samples agreed between Moore swab and composite samples and 58 % of the samples were positive for SARS-CoV-2 using Moore swabs while composite samples were below the limit of detection. Variant profiles from Moore swabs showed a shift from variant BA.1 to BA.2, consistent with in-person saliva samples. These data have implications for the broader implementation of sewage surveillance without advanced sampling technologies and for the utilization of passive sampling approaches for other emerging pathogens.
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Affiliation(s)
- Gyuhyon Cha
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Katherine E Graham
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Kevin J Zhu
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7431, USA
| | - Gouthami Rao
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7431, USA
| | - Blake G Lindner
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Kumru Kocaman
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Seongwook Woo
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Isabelle D'amico
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Lilia R Bingham
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Jamie M Fischer
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Camryn I Flores
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - John W Spencer
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Pranav Yathiraj
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Hayong Chung
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Shweta Biliya
- Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30306, USA
| | - Naima Djeddar
- Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30306, USA
| | - Liza J Burton
- Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30306, USA
| | - Samantha J Mascuch
- Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30306, USA
| | - Joe Brown
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7431, USA
| | - Anton Bryksin
- Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30306, USA
| | - Ameet Pinto
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Janet K Hatt
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
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Ando H, Ahmed W, Iwamoto R, Ando Y, Okabe S, Kitajima M. Impact of the COVID-19 pandemic on the prevalence of influenza A and respiratory syncytial viruses elucidated by wastewater-based epidemiology. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 880:162694. [PMID: 36894088 PMCID: PMC9991320 DOI: 10.1016/j.scitotenv.2023.162694] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 03/03/2023] [Accepted: 03/03/2023] [Indexed: 05/23/2023]
Abstract
Since the COVID-19 pandemic, a decrease in the prevalence of Influenza A virus (IAV) and respiratory syncytial virus (RSV) has been suggested by clinical surveillance. However, there may be potential biases in obtaining an accurate overview of infectious diseases in a community. To elucidate the impact of the COVID-19 on the prevalence of IAV and RSV, we quantified IAV and RSV RNA in wastewater collected from three wastewater treatment plants (WWTPs) in Sapporo, Japan, between October 2018 and January 2023, using highly sensitive EPISENS™ method. From October 2018 to April 2020, the IAV M gene concentrations were positively correlated with the confirmed cases in the corresponding area (Spearman's r = 0.61). Subtype-specific HA genes of IAV were also detected, and their concentrations showed trends that were consistent with clinically reported cases. RSV A and B serotypes were also detected in wastewater, and their concentrations were positively correlated with the confirmed clinical cases (Spearman's r = 0.36-0.52). The detection ratios of IAV and RSV in wastewater decreased from 66.7 % (22/33) and 42.4 % (14/33) to 4.56 % (12/263) and 32.7 % (86/263), respectively in the city after the COVID-19 prevalence. The present study demonstrates the potential usefulness of wastewater-based epidemiology combined with the preservation of wastewater (wastewater banking) as a tool for better management of respiratory viral diseases.
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Affiliation(s)
- Hiroki Ando
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Warish Ahmed
- CSIRO Environment, Ecosciences Precinct, 41 Boggo Road, QLD 4102, Australia
| | - Ryo Iwamoto
- Shionogi & Co. Ltd., 1-8, Doshomachi 3-Chome, Chuo-ku, Osaka, Osaka 541-0045, Japan; AdvanSentinel Inc., 1-8 Doshomachi 3-Chome, Chuo-ku, Osaka, Osaka 541-0045, Japan
| | - Yoshinori Ando
- Shionogi & Co. Ltd., 1-8, Doshomachi 3-Chome, Chuo-ku, Osaka, Osaka 541-0045, Japan
| | - Satoshi Okabe
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Masaaki Kitajima
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan.
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63
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Ando H, Murakami M, Ahmed W, Iwamoto R, Okabe S, Kitajima M. Wastewater-based prediction of COVID-19 cases using a highly sensitive SARS-CoV-2 RNA detection method combined with mathematical modeling. ENVIRONMENT INTERNATIONAL 2023; 173:107743. [PMID: 36867995 PMCID: PMC9824953 DOI: 10.1016/j.envint.2023.107743] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 01/06/2023] [Accepted: 01/06/2023] [Indexed: 05/05/2023]
Abstract
Wastewater-based epidemiology (WBE) has the potential to predict COVID-19 cases; however, reliable methods for tracking SARS-CoV-2 RNA concentrations (CRNA) in wastewater are lacking. In the present study, we developed a highly sensitive method (EPISENS-M) employing adsorption-extraction, followed by one-step RT-Preamp and qPCR. The EPISENS-M allowed SARS-CoV-2 RNA detection from wastewater at 50 % detection rate when newly reported COVID-19 cases exceed 0.69/100,000 inhabitants in a sewer catchment. Using the EPISENS-M, a longitudinal WBE study was conducted between 28 May 2020 and 16 June 2022 in Sapporo City, Japan, revealing a strong correlation (Pearson's r = 0.94) between CRNA and the newly COVID-19 cases reported by intensive clinical surveillance. Based on this dataset, a mathematical model was developed based on viral shedding dynamics to estimate the newly reported cases using CRNA data and recent clinical data prior to sampling day. This developed model succeeded in predicting the cumulative number of newly reported cases after 5 days of sampling day within a factor of √2 and 2 with a precision of 36 % (16/44) and 64 % (28/44), respectively. By applying this model framework, another estimation mode was developed without the recent clinical data, which successfully predicted the number of COVID-19 cases for the succeeding 5 days within a factor of √2 and 2 with a precision of 39 % (17/44) and 66 % (29/44), respectively. These results demonstrated that the EPISENS-M method combined with the mathematical model can be a powerful tool for predicting COVID-19 cases, especially in the absence of intensive clinical surveillance.
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Affiliation(s)
- Hiroki Ando
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Michio Murakami
- Center for Infectious Disease Education and Research, Osaka University, 2-8 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Warish Ahmed
- CSIRO Environment, Ecosciences Precinct, 41 Boggo Road, QLD 4102, Australia
| | - Ryo Iwamoto
- Shionogi & Co. Ltd, 1-8, Doshomachi 3-Chome, Chuo-ku, Osaka, Osaka 541-0045, Japan; AdvanSentinel Inc, 1-8 Doshomachi 3-Chome, Chuo-ku, Osaka, Osaka 541-0045, Japan
| | - Satoshi Okabe
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Masaaki Kitajima
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan.
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Kisand V, Laas P, Palmik-Das K, Panksep K, Tammert H, Albreht L, Allemann H, Liepkalns L, Vooro K, Ritz C, Hauryliuk V, Tenson T. Prediction of COVID-19 positive cases, a nation-wide SARS-CoV-2 wastewater-based epidemiology study. WATER RESEARCH 2023; 231:119617. [PMID: 36682239 PMCID: PMC9845016 DOI: 10.1016/j.watres.2023.119617] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 01/09/2023] [Accepted: 01/15/2023] [Indexed: 06/17/2023]
Abstract
Taking advantage of Estonia's small size and population, we have employed wastewater-based epidemiology approach to monitor the spread of SARS-CoV-2, releasing weekly nation-wide updates. In this study we report results obtained between August 2020 and December 2021. Weekly 24 h composite samples were collected from wastewater treatment plants of larger towns already covered 65% of the total population that was complemented up to 40 additional grab samples from smaller towns/villages and the specific sites of concern. The N3 gene abundance was quantified by RT-qPCR. The N3 gene copy number (concentration) in wastewater fluctuated in accordance with the SARS-CoV-2 spread within the total population, with N3 abundance starting to increase 1.25 weeks (9 days) (95% CI: [1.10, 1.41]) before a rise in COVID-19 positive cases. Statistical model between the load of virus in wastewater and number of infected people validated with the Alpha variant wave (B.1.1.17) could be used to predict the order of magnitude in incidence numbers in Delta wave (B.1.617.2) in fall 2021. Targeted testing of student dormitories, retirement and nursing homes and prisons resulted in successful early discovery of outbreaks. We put forward a SARS-CoV-2 Wastewater Index (SARS2-WI) indicator of normalized virus load as COVID-19 infection metric to complement the other metrics currently used in disease control and prevention: dynamics of effective reproduction number (Re), 7-day mean of new cases, and a sum of new cases within last 14 days. In conclusion, an efficient surveillance system that combines analysis of composite and grab samples was established in Estonia. There is considerable discussion how the viral load in wastewater correlates with the number of infected people. Here we show that this correlation can be found. Moreover, we confirm that an increased signal in wastewater is observed before the increase in the number of infections. The surveillance system helped to inform public health policy and place direct interventions during the COVID-19 pandemic in Estonia via early warning of epidemic spread in various regions of the country.
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Affiliation(s)
- Veljo Kisand
- Institute of Technology, University of Tartu, Estonia.
| | - Peeter Laas
- Institute of Technology, University of Tartu, Estonia
| | | | | | - Helen Tammert
- Institute of Technology, University of Tartu, Estonia
| | | | - Hille Allemann
- Estonian Environmental Research Centre, Tallinn, Estonia
| | | | - Katri Vooro
- Estonian Environmental Research Centre, Tallinn, Estonia
| | - Christian Ritz
- Department of Population Health and Morbidity, National Institute of Public Health, University of Southern Denmark, Denmark
| | - Vasili Hauryliuk
- Institute of Technology, University of Tartu, Estonia; Department of Experimental Medical Science, Lund University, Sweden
| | - Tanel Tenson
- Institute of Technology, University of Tartu, Estonia.
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Brooks YM, Gryskwicz B, Sidaway E, Shelley B, Coroi L, Downing M, Downing T, McDonnell S, Ostrye D, Hoop K, Parrish G. A case study of a community-organized wastewater surveillance in a small community: correlating weekly reported COVID-19 cases with SARS-CoV-2 RNA concentrations during fall 2020 to summer 2021 in Yarmouth, ME. JOURNAL OF WATER AND HEALTH 2023; 21:329-342. [PMID: 37338313 PMCID: wh_2023_238 DOI: 10.2166/wh.2023.238] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Wastewater surveillance offers a rapid evaluation of SARS-CoV-2 transmission in a community. We describe how a community group, the Yarmouth Wastewater Testing Team (YWTT), in Yarmouth, Maine, (population 8,990) utilized an asset-based community design framework to organize and manage a program to monitor SARS-CoV-2 RNA concentrations. From September 22, 2020 through June 8, 2021, the YWTT disseminated weekly reports of the wastewater results and reported COVID-19 cases within the Yarmouth postal code. After high and increasing SARS-CoV-2 RNA concentrations, the YWTT issued two community advisories to encourage extra care to reduce exposure. Correlations between SARS-CoV-2 RNA concentrations and COVID-19 cases were stronger the week after sampling, and the average of the COVID-19 cases during the week of sampling and the following week, indicating that surveillance provided advance notice of cases. A 10% increase in SARS-CoV-2 RNA concentrations was associated with a 13.29% increase in the average number of weekly reported cases of COVID-19 during the week of sampling and the following week (R2 = 0.42; p < 0.001). Adjusting for viral recovery (December 21, 2020 through June 8, 2021), improved R2 from 0.60 to 0.68. Wastewater surveillance was an effective tool for the YWTT to quickly respond to viral transmission.
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Affiliation(s)
- Yolanda M Brooks
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Bailey Gryskwicz
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Eilidh Sidaway
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Brianna Shelley
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Laura Coroi
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Margaret Downing
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Tom Downing
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Sharon McDonnell
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Dan Ostrye
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Katrina Hoop
- Department of Social Sciences, University of Maine at Augusta, 46 University Drive, Augusta, ME 04330, USA
| | - Gib Parrish
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
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Li Q, Lee BE, Gao T, Qiu Y, Ellehoj E, Yu J, Diggle M, Tipples G, Maal-Bared R, Hinshaw D, Sikora C, Ashbolt NJ, Talbot J, Hrudey SE, Pang X. Number of COVID-19 cases required in a population to detect SARS-CoV-2 RNA in wastewater in the province of Alberta, Canada: Sensitivity assessment. J Environ Sci (China) 2023; 125:843-850. [PMID: 36375966 PMCID: PMC9068596 DOI: 10.1016/j.jes.2022.04.047] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/24/2022] [Accepted: 04/27/2022] [Indexed: 05/03/2023]
Abstract
With a unique and large size of testing results of 1,842 samples collected from 12 wastewater treatment plants (WWTP) for 14 months through from low to high prevalence of COVID-19, the sensitivity of RT-qPCR detection of SARS-CoV-2 RNA in wastewater that correspond to the communities was computed by using Probit analysis. This study determined the number of new COVID-19 cases per 100,000 population required to detect SARS-CoV-2 RNA in wastewater at defined probabilities and provided an evidence-based framework of wastewater-based epidemiology surveillance (WBE). Input data were positive and negative test results of SARS-CoV-2 RNA in wastewater samples and the corresponding new COVID-19 case rates per 100,000 population served by each WWTP. The analyses determined that RT-qPCR-based SARS-CoV-2 RNA detection threshold at 50%, 80% and 99% probability required a median of 8 (range: 4-19), 18 (9-43), and 38 (17-97) of new COVID-19 cases /100,000, respectively. Namely, the positive detection rate at 50%, 80% and 99% probability were 0.01%, 0.02%, and 0.04% averagely for new cases in the population. This study improves understanding of the performance of WBE SARS-CoV-2 RNA detection using the large datasets and prolonged study period. Estimated COVID-19 burden at a community level that would result in a positive detection of SARS-CoV-2 in wastewater is critical to support WBE application as a supplementary warning/monitoring system for COVID-19 prevention and control.
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Affiliation(s)
- Qiaozhi Li
- School of Public Health, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Bonita E Lee
- Department of Pediatrics, University of Alberta, Edmonton, AB T6G 1C9, Canada
| | - Tiejun Gao
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Yuanyuan Qiu
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Erik Ellehoj
- University of Alberta Central Receiving, Edmonton, Alberta, T6G 2R3, Canada
| | - Jiaao Yu
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Mathew Diggle
- Provincial Laboratory for Public Health, Edmonton, Alberta, Canada
| | - Graham Tipples
- Provincial Laboratory for Public Health, Edmonton, Alberta, Canada
| | | | - Deena Hinshaw
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada
| | - Christopher Sikora
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada
| | - Nicholas J Ashbolt
- Faculty of Science and Engineering, Southern Cross University, East Lismore NSW 2480, Australia
| | - James Talbot
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada; Provincial Laboratory for Public Health, Edmonton, Alberta, Canada.
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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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Henriques TB, Cassini ST, de Pinho Keller R. Contribution of wastewater-based epidemiology to SARS-CoV-2 screening in Brazil and the United States. JOURNAL OF WATER AND HEALTH 2023; 21:343-353. [PMID: 37338314 PMCID: wh_2023_260 DOI: 10.2166/wh.2023.260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Wastewater-based epidemiology (WBE) is a valuable tool for investigating the existence, prevalence, and spread of pathogens, such as SARS-CoV-2, in a given population. WBE, proposed as part of the SARS-CoV-2 surveillance strategy for monitoring virus circulation, may complement clinical data and contribute to reducing the spread of the disease through early detection. In developing countries such as Brazil, where clinical data are scarce, information obtained from wastewater monitoring can be crucial for designing public health interventions. In the United States, the country with the largest number of confirmed SARS-CoV-2 cases worldwide, WBE programs have begun to be carried out to investigate correlations with coronavirus disease 2019 (COVID-19) clinical data and support health agencies in decision-making to prevent the spread of the disease. This systematic review aimed to assess the contribution of WBE to SARS-CoV-2 screening in Brazil and the United States and compare studies conducted in a developed and developing country. Studies in Brazil and the United States showed WBE to be an important epidemiological surveillance strategy in the context of the COVID-19 pandemic. WBE approaches are useful for early detection of COVID-19 outbreaks, estimation of clinical cases, and assessment of the effectiveness of vaccination program.
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Affiliation(s)
- Taciane Barbosa Henriques
- Sanitation Laboratory, Department of Environmental Engineering, Federal University of Espírito Santo, Vitória, Espirito Santo, Brazil E-mail:
| | - Servio Túlio Cassini
- Sanitation Laboratory, Department of Environmental Engineering, Federal University of Espírito Santo, Vitória, Espirito Santo, Brazil E-mail:
| | - Regina de Pinho Keller
- Sanitation Laboratory, Department of Environmental Engineering, Federal University of Espírito Santo, Vitória, Espirito Santo, Brazil E-mail:
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69
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Temporal Series Analysis of Population Cycle Threshold Counts as a Predictor of Surge in Cases and Hospitalizations during the SARS-CoV-2 Pandemic. Viruses 2023; 15:v15020421. [PMID: 36851635 PMCID: PMC9959442 DOI: 10.3390/v15020421] [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: 12/31/2022] [Revised: 01/23/2023] [Accepted: 01/26/2023] [Indexed: 02/05/2023] Open
Abstract
Tools to predict surges in cases and hospitalizations during the COVID-19 pandemic may help guide public health decisions. Low cycle threshold (CT) counts may indicate greater SARS-CoV-2 concentrations in the respiratory tract, and thereby may be used as a surrogate marker of enhanced viral transmission. Several population studies have found an association between the oscillations in the mean CT over time and the evolution of the pandemic. For the first time, we applied temporal series analysis (Granger-type causality) to validate the CT counts as an epidemiological marker of forthcoming pandemic waves using samples and analyzing cases and hospital admissions during the third pandemic wave (October 2020 to May 2021) in Madrid. A total of 22,906 SARS-CoV-2 RT-PCR-positive nasopharyngeal swabs were evaluated; the mean CT value was 27.4 (SD: 2.1) (22.2% below 20 cycles). During this period, 422,110 cases and 36,727 hospital admissions were also recorded. A temporal association was found between the CT counts and the cases of COVID-19 with a lag of 9-10 days (p ≤ 0.01) and hospital admissions by COVID-19 (p < 0.04) with a lag of 2-6 days. According to a validated method to prove associations between variables that change over time, the short-term evolution of average CT counts in the population may forecast the evolution of the COVID-19 pandemic.
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70
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Wang Y, Liu P, VanTassell J, Hilton SP, Guo L, Sablon O, Wolfe M, Freeman L, Rose W, Holt C, Browning M, Bryan M, Waller L, Teunis PFM, Moe CL. When case reporting becomes untenable: Can sewer networks tell us where COVID-19 transmission occurs? WATER RESEARCH 2023; 229:119516. [PMID: 37379453 PMCID: PMC9763902 DOI: 10.1016/j.watres.2022.119516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 12/11/2022] [Accepted: 12/18/2022] [Indexed: 06/30/2023]
Abstract
Monitoring SARS-CoV-2 in wastewater is a valuable approach to track COVID-19 transmission. Designing wastewater surveillance (WWS) with representative sampling sites and quantifiable results requires knowledge of the sewerage system and virus fate and transport. We developed a multi-level WWS system to track COVID-19 in Atlanta using an adaptive nested sampling strategy. From March 2021 to April 2022, 868 wastewater samples were collected from influent lines to wastewater treatment facilities and upstream community manholes. Variations in SARS-CoV-2 concentrations in influent line samples preceded similar variations in numbers of reported COVID-19 cases in the corresponding catchment areas. Community sites under nested sampling represented mutually-exclusive catchment areas. Community sites with high SARS-CoV-2 detection rates in wastewater covered high COVID-19 incidence areas, and adaptive sampling enabled identification and tracing of COVID-19 hotspots. This study demonstrates how a well-designed WWS provides actionable information including early warning of surges in cases and identification of disease hotspots.
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Affiliation(s)
- Yuke Wang
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Pengbo Liu
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Jamie VanTassell
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Stephen P Hilton
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Lizheng Guo
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Orlando Sablon
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Marlene Wolfe
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Lorenzo Freeman
- City of Atlanta Department of Watershed Management, Atlanta, GA 30303, USA
| | - Wayne Rose
- City of Atlanta Department of Watershed Management, Atlanta, GA 30303, USA
| | - Carl Holt
- City of Atlanta Department of Watershed Management, Atlanta, GA 30303, USA
| | - Mikita Browning
- City of Atlanta Department of Watershed Management, Atlanta, GA 30303, USA
| | - Michael Bryan
- Georgia Department of Public Health, Atlanta, GA 30303, USA
| | - Lance Waller
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Peter F M Teunis
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Christine L Moe
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
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Phan T, Brozak S, Pell B, Gitter A, Xiao A, Mena KD, Kuang Y, Wu F. A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159326. [PMID: 36220466 PMCID: PMC9547654 DOI: 10.1016/j.scitotenv.2022.159326] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 09/15/2022] [Accepted: 10/05/2022] [Indexed: 06/12/2023]
Abstract
Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in a population-level SEIR model. We demonstrated that the effect of temperature on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020-Jan 25, 2021) in the Greater Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 6-16 days and 8.3-10.2 folds (R = 0.93). This work showcases a simple yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.
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Affiliation(s)
- Tin Phan
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, NM, USA
| | - Samantha Brozak
- School of Mathematical and Statistical Sciences, Arizona State University, AZ, USA
| | - Bruce Pell
- Department of Mathematics and Computer Science, Lawrence Technological University, MI, USA
| | - Anna Gitter
- The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA 77030
| | - Amy Xiao
- Center for Microbiome Informatics and Therapeutics; Department of Biological Engineering, Massachusetts Institute of Technology
| | - Kristina D Mena
- The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA 77030
| | - Yang Kuang
- School of Mathematical and Statistical Sciences, Arizona State University, AZ, USA.
| | - Fuqing Wu
- The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA 77030.
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Helm B, Geissler M, Mayer R, Schubert S, Oertel R, Dumke R, Dalpke A, El-Armouche A, Renner B, Krebs P. Regional and temporal differences in the relation between SARS-CoV-2 biomarkers in wastewater and estimated infection prevalence - Insights from long-term surveillance. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159358. [PMID: 36240928 PMCID: PMC9554318 DOI: 10.1016/j.scitotenv.2022.159358] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 10/06/2022] [Accepted: 10/07/2022] [Indexed: 06/16/2023]
Abstract
Wastewater-based epidemiology provides a conceptual framework for the evaluation of the prevalence of public health related biomarkers. In the context of the Coronavirus disease-2019, wastewater monitoring emerged as a complementary tool for epidemic management. In this study, we evaluated data from six wastewater treatment plants in the region of Saxony, Germany. The study period lasted from February to December 2021 and covered the third and fourth regional epidemic waves. We collected 1065 daily composite samples and analyzed SARS-CoV-2 RNA concentrations using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Regression models quantify the relation between RNA concentrations and disease prevalence. We demonstrated that the relation is site and time specific. Median loads per diagnosed case differed by a factor of 3-4 among sites during both waves and were on average 45 % higher during the third wave. In most cases, log-log-transformed data achieved better regression performance than non-transformed data and local calibration outperformed global models for all sites. The inclusion of lag/lead time, discharge and detection probability improved model performance in all cases significantly, but the importance of these components was also site and time specific. In all cases, models with lag/lead time and log-log-transformed data obtained satisfactory goodness-of-fit with adjusted coefficients of determination higher than 0.5. Back-estimation of testing efficiency from wastewater data confirmed state-wide prevalence estimation from individual testing statistics, but revealed pronounced differences throughout the epidemic waves and among the different sites.
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Affiliation(s)
- Björn Helm
- Institute of Urban and Industrial Water Management, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany.
| | - Michael Geissler
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Robin Mayer
- Institute of Urban and Industrial Water Management, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany
| | - Sara Schubert
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; Institute of Hydrobiology, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany
| | - Reinhard Oertel
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Roger Dumke
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Alexander Dalpke
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; University Heidelberg, Institute of Medical Microbiology and Hygiene, Heidelberg, Germany
| | - Ali El-Armouche
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; Institute of Pharmacology and Toxicology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Bertold Renner
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Peter Krebs
- Institute of Urban and Industrial Water Management, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany
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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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75
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Singh CK, Sodhi KK. The emerging significance of nanomedicine-based approaches to fighting COVID-19 variants of concern: A perspective on the nanotechnology’s role in COVID-19 diagnosis and treatment. FRONTIERS IN NANOTECHNOLOGY 2023. [DOI: 10.3389/fnano.2022.1084033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
COVID-19, one of the worst-hit pandemics, has quickly spread like fire across nations with very high mortality rates. Researchers all around the globe are making consistent efforts to address the main challenges faced due to COVID-19 infection including prompt diagnosis and therapeutics to reduce mortality. Conventional medical technology does not effectively contain the havoc caused by deadly COVID-19. This signals a crucial mandate for innovative and novel interventions in diagnostics and therapeutics to combat this ongoing pandemic and counter its successor or disease if it were ever to arise. The expeditious solutions can spring from promising areas such as nanomedicine and nanotechnology. Nanomedicine is a dominant tool that has a huge potential to alleviate the disease burden by providing nanoparticle-based vaccines and carriers. Nanotechnology encompasses multidisciplinary aspects including artificial intelligence, chemistry, biology, material science, physical science, and medicine. Nanoparticles offer many advantages compared to larger particles, including better magnetic properties and a multiplied surface-to-volume ratio. Given this, the present review focuses on promising nanomedicine-based solutions to combat COVID-19 and their utility to control a broad range of pathogens and viruses, along with understanding their role in the therapy, diagnosis, and prevention of COVID-19. Various studies, reports, and recent research and development from the nanotechnology perspective are discussed in this article.
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76
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Mahlangeni N, Street R, Horn S, Mathee A, Mangwana N, Dias S, Sharma JR, Ramharack P, Louw J, Reddy T, Surujlal-Naicker S, Nkambule S, Webster C, Mdhluli M, Gray G, Muller C, Johnson R. Using Wastewater Surveillance to Compare COVID-19 Outbreaks during the Easter Holidays over a 2-Year Period in Cape Town, South Africa. Viruses 2023; 15:162. [PMID: 36680203 PMCID: PMC9863979 DOI: 10.3390/v15010162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 12/22/2022] [Accepted: 12/28/2022] [Indexed: 01/06/2023] Open
Abstract
Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown to be an important approach to determine early outbreaks of infections. Wastewater-based epidemiology (WBE) is regarded as a complementary tool for monitoring SARS-CoV-2 trends in communities. In this study, the changes in the SARS-CoV-2 RNA levels in wastewater during Easter holidays in 2021 and 2022 in the City of Cape Town were monitored over nine weeks. Our findings showed a statistically significant difference in the SARS-CoV-2 RNA viral load between the study weeks over the Easter period in 2021 and 2022, except for study week 1 and 4. During the Easter week, 52% of the wastewater treatment plants moved from the lower (low viral RNA) category in 2021 to the higher (medium to very high viral RNA) categories in 2022. As a result, the median SARS-CoV-2 viral loads where higher during the Easter week in 2022 than Easter week in 2021 (p = 0.0052). Mixed-effects model showed an association between the SARS-CoV-2 RNA viral loads and Easter week over the Easter period in 2021 only (p < 0.01). The study highlights the potential of WBE to track outbreaks during the holiday period.
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Affiliation(s)
- Nomfundo Mahlangeni
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg 2028, South Africa
| | - Renée Street
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg 2028, South Africa
- Environmental Health Department, Faculty of Health Sciences, University of Johannesburg, Johannesburg 2028, South Africa
| | - Suranie Horn
- Occupational Hygiene and Health Research Initiative, North-West University, Potchefstroom 2531, South Africa
| | - Angela Mathee
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg 2028, South Africa
- Environmental Health Department, Faculty of Health Sciences, University of Johannesburg, Johannesburg 2028, South Africa
| | - Noluxabiso Mangwana
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Stephanie Dias
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
| | - Jyoti Rajan Sharma
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
| | - Pritika Ramharack
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
- Discipline of Pharmaceutical Sciences, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
| | - Johan Louw
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
- Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa
| | - Tarylee Reddy
- Biostatistics Research Unit, South African Medical Research Council (SAMRC), Durban 4091, South Africa
| | - Swastika Surujlal-Naicker
- Scientific Services, Water and Sanitation Department, City of Cape Town Metropolitan Municipality, Cape Town 8000, South Africa
| | - Sizwe Nkambule
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg 2028, South Africa
| | - Candice Webster
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg 2028, South Africa
| | - Mongezi Mdhluli
- Chief Research Operations Office, South African Medical Research Council (SAMRC), Tygerberg 7050, South Africa
| | - Glenda Gray
- Office of the President, South African Medical Research Council (SAMRC), Tygerberg 7050, South Africa
| | - Christo Muller
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa
- Division of Medical Physiology, Faculty of Medicine and Health Sciences, Centre for Cardio-Metabolic Research in Africa, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Rabia Johnson
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
- Division of Medical Physiology, Faculty of Medicine and Health Sciences, Centre for Cardio-Metabolic Research in Africa, Stellenbosch University, Stellenbosch 7600, South Africa
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77
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Armas F, Chandra F, Lee WL, Gu X, Chen H, Xiao A, Leifels M, Wuertz S, Alm EJ, Thompson J. Contextualizing Wastewater-Based surveillance in the COVID-19 vaccination era. ENVIRONMENT INTERNATIONAL 2023; 171:107718. [PMID: 36584425 PMCID: PMC9783150 DOI: 10.1016/j.envint.2022.107718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 12/16/2022] [Accepted: 12/22/2022] [Indexed: 06/17/2023]
Abstract
SARS-CoV-2 wastewater-based surveillance (WBS) offers a tool for cost-effective oversight of a population's infections. In the past two years, WBS has proven to be crucial for managing the pandemic across different geographical regions. However, the changing context of the pandemic due to high levels of COVID-19 vaccination warrants a closer examination of its implication towards SARS-CoV-2 WBS. Two main questions were raised: 1) Does vaccination cause shedding of viral signatures without infection? 2) Does vaccination affect the relationship between wastewater and clinical data? To answer, we review historical reports of shedding from viral vaccines in use prior to the COVID-19 pandemic including for polio, rotavirus, influenza and measles infection and provide a perspective on the implications of different COVID-19 vaccination strategies with regard to the potential shedding of viral signatures into the sewershed. Additionally, we reviewed studies that looked into the relationship between wastewater and clinical data and how vaccination campaigns could have affected the relationship. Finally, analyzing wastewater and clinical data from the Netherlands, we observed changes in the relationship concomitant with increasing vaccination coverage and switches in dominant variants of concern. First, that no vaccine-derived shedding is expected from the current commercial pipeline of COVID-19 vaccines that may confound interpretation of WBS data. Secondly, that breakthrough infections from vaccinated individuals contribute significantly to wastewater signals and must be interpreted in light of the changing dynamics of shedding from new variants of concern.
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Affiliation(s)
- Federica Armas
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Franciscus Chandra
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Wei Lin Lee
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Xiaoqiong Gu
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Hongjie Chen
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Amy Xiao
- Department of Biological Engineering, Massachusetts Institute of Technology, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology
| | - Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore
| | - Eric J Alm
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Department of Biological Engineering, Massachusetts Institute of Technology, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Janelle Thompson
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore.
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78
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Oh C, Zhou A, O'Brien K, Jamal Y, Wennerdahl H, Schmidt AR, Shisler JL, Jutla A, Schmidt AR, Keefer L, Brown WM, Nguyen TH. Application of neighborhood-scale wastewater-based epidemiology in low COVID-19 incidence situations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 852:158448. [PMID: 36063927 PMCID: PMC9436825 DOI: 10.1016/j.scitotenv.2022.158448] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/08/2022] [Accepted: 08/28/2022] [Indexed: 05/17/2023]
Abstract
Wastewater-based epidemiology (WBE), an emerging approach for community-wide COVID-19 surveillance, was primarily characterized at large sewersheds such as wastewater treatment plants serving a large population. Although informed public health measures can be better implemented for a small population, WBE for neighborhood-scale sewersheds is less studied and not fully understood. This study applied WBE to seven neighborhood-scale sewersheds (average population of 1471) from January to November 2021. Community testing data showed an average of 0.004 % incidence rate in these sewersheds (97 % of monitoring periods reported two or fewer daily infections). In 92 % of sewage samples, SARS-CoV-2 N gene fragments were below the limit of quantification. We statistically determined 10-2.6 as the threshold of the SARS-CoV-2 N gene concentration normalized to pepper mild mottle virus (N/PMMOV) to alert high COVID-19 incidence rate in the studied sewershed. This threshold of N/PMMOV identified neighborhood-scale outbreaks (COVID-19 incidence rate higher than 0.2 %) with 82 % sensitivity and 51 % specificity. Importantly, neighborhood-scale WBE can discern local outbreaks that would not otherwise be identified by city-scale WBE. Our findings suggest that neighborhood-scale WBE is an effective community-wide disease surveillance tool when COVID-19 incidence is maintained at a low level.
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Affiliation(s)
- Chamteut Oh
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, United States.
| | - Aijia Zhou
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, United States
| | - Kate O'Brien
- School of Integrative Biology, University of Illinois Urbana-Champaign, United States
| | - Yusuf Jamal
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, United States
| | - Hayden Wennerdahl
- Illinois State Water Survey, Prairie Research Institute, University of Illinois Urbana-Champaign, United States
| | - Arthur R Schmidt
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, United States
| | - Joanna L Shisler
- Department of Microbiology, University of Illinois Urbana-Champaign, United States
| | - Antarpreet Jutla
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, United States
| | - Arthur R Schmidt
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, United States
| | - Laura Keefer
- Illinois State Water Survey, Prairie Research Institute, University of Illinois Urbana-Champaign, United States
| | - William M Brown
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois Urbana-Champaign, United States
| | - Thanh H Nguyen
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, United States; Institute of Genomic Biology, University of Illinois Urbana-Champaign, United States
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79
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Mitranescu A, Uchaikina A, Kau AS, Stange C, Ho J, Tiehm A, Wurzbacher C, Drewes JE. Wastewater-Based Epidemiology for SARS-CoV-2 Biomarkers: Evaluation of Normalization Methods in Small and Large Communities in Southern Germany. ACS ES&T WATER 2022; 2:2460-2470. [PMID: 37552738 PMCID: PMC9578648 DOI: 10.1021/acsestwater.2c00306] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/21/2022] [Accepted: 09/27/2022] [Indexed: 06/18/2023]
Abstract
In the context of the COVID-19 pandemic, wastewater-based epidemiology (WBE) emerged as a useful tool to account for the prevalence of SARS-CoV-2 infections on a population scale. In this study, we analyzed wastewater samples from three large (>300,000 people served) and four small (<25,000 people served) communities throughout southern Germany from August to December 2021, capturing the fourth infection wave in Germany dominated by the Delta variant (B.1.617.2). As dilution can skew the SARS-CoV-2 biomarker concentrations in wastewater, normalization to wastewater parameters can improve the relationship between SARS-CoV-2 biomarker data and clinical prevalence data. In this study, we investigated the suitability and performance of various normalization parameters. Influent flow data showed strong relationships to precipitation data; accordingly, flow-normalization reacted distinctly to precipitation events. Normalization by surrogate viruses CrAssphage and pepper mild mottle virus showed varying performance for different sampling sites. The best normalization performance was achieved with a mixed fecal indicator calculated from both surrogate viruses. Analyzing the temporal and spatial variation of normalization parameters proved to be useful to explain normalization performance. Overall, our findings indicate that the performance of surrogate viruses, flow, and hydro-chemical data is site-specific. We recommend testing the suitability of normalization parameters individually for specific sewage systems.
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Affiliation(s)
- Alexander Mitranescu
- Chair of Urban Water Systems Engineering,
Technical University of Munich, Am Coulombwall 3,
85748Garching, Germany
| | - Anna Uchaikina
- Chair of Urban Water Systems Engineering,
Technical University of Munich, Am Coulombwall 3,
85748Garching, Germany
| | - Anna-Sonia Kau
- Chair of Urban Water Systems Engineering,
Technical University of Munich, Am Coulombwall 3,
85748Garching, Germany
| | - Claudia Stange
- Department of Water Microbiology, TZW:
DVGW-Technologiezentrum Wasser, Karlsruher Straße 84, 76139Karlsruhe,
Germany
| | - Johannes Ho
- Department of Water Microbiology, TZW:
DVGW-Technologiezentrum Wasser, Karlsruher Straße 84, 76139Karlsruhe,
Germany
| | - Andreas Tiehm
- Department of Water Microbiology, TZW:
DVGW-Technologiezentrum Wasser, Karlsruher Straße 84, 76139Karlsruhe,
Germany
| | - Christian Wurzbacher
- Chair of Urban Water Systems Engineering,
Technical University of Munich, Am Coulombwall 3,
85748Garching, Germany
| | - Jörg E. Drewes
- Chair of Urban Water Systems Engineering,
Technical University of Munich, Am Coulombwall 3,
85748Garching, Germany
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80
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Lancaster E, Byrd K, Ai Y, Lee J. Socioeconomic status correlations with confirmed COVID-19 cases and SARS-CoV-2 wastewater concentrations in small-medium sized communities. ENVIRONMENTAL RESEARCH 2022; 215:114290. [PMID: 36096171 PMCID: PMC9458761 DOI: 10.1016/j.envres.2022.114290] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 08/16/2022] [Accepted: 09/04/2022] [Indexed: 06/15/2023]
Abstract
Over two years into the COVID-19 pandemic, it is apparent that some populations across the world are more susceptible than others to SARS-CoV-2 infection and spread. Understanding how populations with varying demographic patterns are impacted by COVID-19 may highlight which factors are most important in targeting to combat global suffering. The first objective of this study was to investigate the association of various socioeconomic status (SES) parameters and confirmed COVID-19 cases in the state of Ohio, USA. This study examines the largest and capital city of Ohio (Columbus) and various small-medium-sized communities. The second objective was to determine the relationship between SES parameters and community-level SARS-CoV-2 concentrations using municipal wastewater samples from each city's respective wastewater treatment plants from August 2020 to January 2021. SES parameters include population size, median income, poverty, race/ethnicity, education, health care access, types of COVID-19 testing sites, and social vulnerability index. Statistical analysis results show that confirmed (normalized and/or non-normalized) COVID-19 cases were negatively associated with White percentage and registered hospitals, and positively associated with registered physicians and various COVID-19 testing sites. Wastewater viral concentrations were negatively associated with poverty, and positively associated with median income, community health centers, and onsite rapid testing locations. Additional analyses conclude that population is a significant factor in determining COVID-19 cases and SARS-CoV-2 wastewater concentrations. Results indicate that community healthcare parameters relate to a negative health outcome (COVID-19) and that demographic parameters can be associated with community-level SARS-CoV-2 wastewater concentrations. As the first study that examines the association between socioeconomic parameters and SARS-CoV-2 wastewater concentrations as well as confirmed COVID-19 cases, it is apparent that social determinants have an impact in determining the health burden of small-medium sized Ohioan cities. This study design and innovative approach are scalable and applicable for endemic and pandemic surveillance across the world.
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Affiliation(s)
- Emma Lancaster
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA; Environmental Sciences Graduate Program, The Ohio State University, Columbus, OH, USA
| | - Kendall Byrd
- Environmental Sciences Graduate Program, The Ohio State University, Columbus, OH, USA
| | - Yuehan Ai
- Department of Food Science & Technology, The Ohio State University, Columbus, OH, USA
| | - Jiyoung Lee
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA; Environmental Sciences Graduate Program, The Ohio State University, Columbus, OH, USA; Department of Food Science & Technology, The Ohio State University, Columbus, OH, USA; Infectious Diseases Institute, The Ohio State University, Columbus, OH, USA.
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81
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Sellers SC, Gosnell E, Bryant D, Belmonte S, Self S, McCarter MSJ, Kennedy K, Norman RS. Building-level wastewater surveillance of SARS-CoV-2 is associated with transmission and variant trends in a university setting. ENVIRONMENTAL RESEARCH 2022; 215:114277. [PMID: 36084672 PMCID: PMC9448636 DOI: 10.1016/j.envres.2022.114277] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/30/2022] [Accepted: 09/02/2022] [Indexed: 05/31/2023]
Abstract
The University of South Carolina (UofSC) was among the first universities to include building-level wastewater surveillance of SARS-CoV-2 to complement clinical testing during its reopening in the Fall 2020 semester. In the Spring 2021 semester, 24h composite wastewater samples were collected twice per week from 10 residence halls and the on-campus student isolation and quarantine building. The isolation and quarantine building served as a positive control site. The wastewater was analyzed using RT-ddPCR for the quantification of nucleocapsid genes (N1 and N2) to identify viral transmission trends within residence halls. Log10 SARS-CoV-2 RNA concentrations were compared to both new clinical cases identified in the days following wastewater collection and recovered cases returning to sites during the days preceding sample collection to test temporal and spatial associations. There was a statistically significant positive relationship between the number of cases reported from the sites during the seven-day period following wastewater sampling and the log10 viral RNA copies/L (overall IRR 1.08 (1.02, 1.16) p-value 0.0126). Additionally, a statistically significant positive relationship was identified between the number of cases returning to the residence halls after completing isolation during the seven-day period preceding wastewater sampling and the log10 viral RNA copies/L (overall 1.09 (1.01, 1.17) p-value 0.0222). The statistical significance of both identified cases and recovered return cases on log10 viral RNA copies/L in wastewater indicates the importance of including both types of clinical data in wastewater-based epidemiology (WBE) research. Genetic mutations associated with variants of concern (VOCs) were also monitored. The emergence of the Alpha variant on campus was identified, which contributed to the second wave of COVID-19 cases at UofSC. The study was able to identify sub-community transmission hotspots for targeted intervention in real-time, making WBE cost-effective and creating less of a burden on the general public compared to repeated individual testing methods.
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Affiliation(s)
- Sarah C Sellers
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC, USA
| | - Emily Gosnell
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC, USA
| | - Dillon Bryant
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC, USA
| | - Stefano Belmonte
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC, USA
| | - Stella Self
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 915 Green Street, Columbia, SC, USA
| | - Maggie S J McCarter
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 915 Green Street, Columbia, SC, USA
| | - Kirsten Kennedy
- Student Housing and Sustainability, Division of Student Affairs and Academic Support, University of South Carolina, 1520 Devine Street, Columbia, SC, USA
| | - R Sean Norman
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC, USA.
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82
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Pang X, Gao T, Ellehoj E, Li Q, Qiu Y, Maal-Bared R, Sikora C, Tipples G, Diggle M, Hinshaw D, Ashbolt NJ, Talbot J, Hrudey SE, Lee BE. Wastewater-Based Surveillance Is an Effective Tool for Trending COVID-19 Prevalence in Communities: A Study of 10 Major Communities for 17 Months in Alberta. ACS ES&T WATER 2022; 2:2243-2254. [PMID: 36380772 PMCID: PMC9514327 DOI: 10.1021/acsestwater.2c00143] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 09/09/2022] [Accepted: 09/12/2022] [Indexed: 06/16/2023]
Abstract
The correlations between SARS-CoV-2 RNA levels in wastewater from 12 wastewater treatment plants and new COVID-19 cases in the corresponding sewersheds of 10 communities were studied over 17 months. The analysis from the longest continuous surveillance reported to date revealed that SARS-CoV-2 RNA levels correlated well with temporal changes of COVID-19 cases in each community. The strongest correlation was found during the third wave (r = 0.97) based on the population-weighted SARS-CoV-2 RNA levels in wastewater. Different correlations were observed (r from 0.51 to 0.86) in various sizes of communities. The population in the sewershed had no observed effects on the strength of the correlation. Fluctuation of SARS-CoV-2 RNA levels in wastewater mirrored increases and decreases of COVID-19 cases in the corresponding community. Since the viral shedding to sewers from all infected individuals is included, wastewater-based surveillance provides an unbiased and no-discriminate estimation of the prevalence of COVID-19 compared with clinical testing that was subject to testing-seeking behaviors and policy changes. Wastewater-based surveillance on SARS-CoV-2 represents a temporal trend of COVID-19 disease burden and is an effective and supplementary monitoring when the number of COVID-19 cases reaches detectable thresholds of SARS-CoV-2 RNA in wastewater of treatment facilities serving various sizes of populations.
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Affiliation(s)
- Xiaoli Pang
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
- Alberta
Precision Laboratories, Edmonton, Alberta T6G 2J2, Canada
| | - Tiejun Gao
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Erik Ellehoj
- Ellehoj
Redmond Consulting, Edmonton, Alberta T6G 0Y4, Canada
| | - Qiaozhi Li
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Yuanyuan Qiu
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | | | - Christopher Sikora
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Graham Tipples
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
- Alberta
Precision Laboratories, Edmonton, Alberta T6G 2J2, Canada
| | - Mathew Diggle
- Alberta
Precision Laboratories, Edmonton, Alberta T6G 2J2, Canada
| | - Deena Hinshaw
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | | | - James Talbot
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Steve E. Hrudey
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Bonita E. Lee
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
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83
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McMahan CS, Lewis D, Deaver JA, Dean D, Rennert L, Kalbaugh CA, Shi L, Kriebel D, Graves D, Popat SC, Karanfil T, Freedman DL. Predicting COVID-19 Infected Individuals in a Defined Population from Wastewater RNA Data. ACS ES&T WATER 2022; 2:2225-2232. [PMID: 37406033 PMCID: PMC9331160 DOI: 10.1021/acsestwater.2c00105] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 06/27/2022] [Accepted: 06/29/2022] [Indexed: 06/04/2023]
Abstract
Wastewater surveillance of SARS-CoV-2 RNA has become an important tool for tracking the presence of the virus and serving as an early indicator for the onset of rapid transmission. Nevertheless, wastewater data are still not commonly used to predict the number of infected individuals in a sewershed. The main objective of this study was to calibrate a susceptible-exposed-infectious-recovered (SEIR) model using RNA copy rates in sewage (i.e., gene copies per liter times flow rate) and the number of SARS-CoV-2 saliva-test-positive infected individuals in a university student population that was subject to repeated weekly testing during the Spring 2021 semester. A strong correlation was observed between the RNA copy rates and the number of infected individuals. The parameter in the SEIR model that had the largest impact on calibration was the maximum shedding rate, resulting in a mean value of 7.72 log10 genome copies per gram of feces. Regressing the saliva-test-positive infected individuals on predictions from the SEIR model based on the RNA copy rates yielded a slope of 0.87 (SE=0.11), which is statistically consistent with a 1:1 relationship between the two. These findings demonstrate that wastewater surveillance of SARS-CoV-2 can be used to estimate the number of infected individuals in a sewershed.
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Affiliation(s)
- Christopher S. McMahan
- School of Mathematics & Statistical Sciences, Clemson University, Clemson, SC 29634, USA
| | - Dan Lewis
- Clemson Computing and Information Technology (CCIT), Clemson University, Clemson, SC 29634, USA
| | - Jessica A. Deaver
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, SC 29634, USA
| | - Delphine Dean
- Department of Bioengineering, Clemson University, Clemson, South Carolina 29634, USA
| | - Lior Rennert
- Department of Public Health Sciences, Clemson University, Clemson, SC 9634, USA
| | - Corey A. Kalbaugh
- Department of Public Health Sciences, Clemson University, Clemson, SC 9634, USA
| | - Lu Shi
- Department of Public Health Sciences, Clemson University, Clemson, SC 9634, USA
| | - David Kriebel
- Lowell Center for Sustainable Production and Department of Public Health, University of Massachusetts, Lowell, MA 01854, USA
| | | | - Sudeep C. Popat
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, SC 29634, USA
| | - Tanju Karanfil
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, SC 29634, USA
| | - David L. Freedman
- Department of Environmental Engineering and Earth Sciences, Clemson University, Clemson, SC 29634, USA
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84
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Leifels M, Khalilur Rahman O, Sam IC, Cheng D, Chua FJD, Nainani D, Kim SY, Ng WJ, Kwok WC, Sirikanchana K, Wuertz S, Thompson J, Chan YF. The one health perspective to improve environmental surveillance of zoonotic viruses: lessons from COVID-19 and outlook beyond. ISME COMMUNICATIONS 2022; 2:107. [PMID: 36338866 PMCID: PMC9618154 DOI: 10.1038/s43705-022-00191-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 09/26/2022] [Accepted: 10/11/2022] [Indexed: 11/11/2022]
Abstract
The human population has doubled in the last 50 years from about 3.7 billion to approximately 7.8 billion. With this rapid expansion, more people live in close contact with wildlife, livestock, and pets, which in turn creates increasing opportunities for zoonotic diseases to pass between animals and people. At present an estimated 75% of all emerging virus-associated infectious diseases possess a zoonotic origin, and outbreaks of Zika, Ebola and COVID-19 in the past decade showed their huge disruptive potential on the global economy. Here, we describe how One Health inspired environmental surveillance campaigns have emerged as the preferred tools to monitor human-adjacent environments for known and yet to be discovered infectious diseases, and how they can complement classical clinical diagnostics. We highlight the importance of environmental factors concerning interactions between animals, pathogens and/or humans that drive the emergence of zoonoses, and the methodologies currently proposed to monitor them-the surveillance of wastewater, for example, was identified as one of the main tools to assess the spread of SARS-CoV-2 by public health professionals and policy makers during the COVID-19 pandemic. One-Health driven approaches that facilitate surveillance, thus harbour the potential of preparing humanity for future pandemics caused by aetiological agents with environmental reservoirs. Via the example of COVID-19 and other viral diseases, we propose that wastewater surveillance is a useful complement to clinical diagnosis as it is centralized, robust, cost-effective, and relatively easy to implement.
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Affiliation(s)
- Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Omar Khalilur Rahman
- Department of Medical Microbiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
| | - I-Ching Sam
- Department of Medical Microbiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
- Department of Medical Microbiology, University Malaya Medical Centre, Kuala Lumpur, Malaysia
| | - Dan Cheng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Dhiraj Nainani
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Se Yeon Kim
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Wei Jie Ng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Wee Chiew Kwok
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Kwanrawee Sirikanchana
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok, Thailand
- Centre of Excellence on Environmental Health and Toxicology, CHE, Ministry of Education, Bangkok, Thailand
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore
| | - Janelle Thompson
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
| | - Yoke Fun Chan
- Department of Medical Microbiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
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85
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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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86
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Eryildiz B, Yavuzturk Gul B, Koyuncu I. A sustainable approach for the removal methods and analytical determination methods of antiviral drugs from water/wastewater: A review. JOURNAL OF WATER PROCESS ENGINEERING 2022; 49:103036. [PMID: 35966450 PMCID: PMC9359512 DOI: 10.1016/j.jwpe.2022.103036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 06/26/2022] [Accepted: 07/28/2022] [Indexed: 05/05/2023]
Abstract
In the last years, antiviral drugs especially used for the treatment of COVID-19 have been considered emerging contaminants because of their continuous occurrence and persistence in water/wastewater even at low concentrations. Furthermore, as compared to antiviral drugs, their metabolites and transformation products of these pharmaceuticals are more persistent in the environment. They have been found in environmental matrices all over the world, demonstrating that conventional treatment technologies are unsuccessful for removing them from water/wastewater. Several approaches for degrading/removing antiviral drugs have been studied to avoid this contamination. In this study, the present level of knowledge on the input sources, occurrence, determination methods and, especially, the degradation and removal methods of antiviral drugs are discussed in water/wastewater. Different removal methods, such as conventional treatment methods (i.e. activated sludge), advanced oxidation processes (AOPs), adsorption, membrane processes, and combined processes, were evaluated. In addition, the antiviral drugs and these metabolites, as well as the transformation products created as a result of treatment, were examined. Future perspectives for removing antiviral drugs, their metabolites, and transformation products were also considered.
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Affiliation(s)
- Bahriye Eryildiz
- Istanbul Technical University, Environmental Engineering Department, Maslak 34469, Istanbul, Turkey
- National Research Center on Membrane Technologies, Istanbul Technical University, Maslak 34469, Istanbul, Turkey
| | - Bahar Yavuzturk Gul
- National Research Center on Membrane Technologies, Istanbul Technical University, Maslak 34469, Istanbul, Turkey
- Department of Molecular Biology and Genetics, Istanbul Technical University, Maslak 34469, Istanbul, Turkey
| | - Ismail Koyuncu
- Istanbul Technical University, Environmental Engineering Department, Maslak 34469, Istanbul, Turkey
- National Research Center on Membrane Technologies, Istanbul Technical University, Maslak 34469, Istanbul, Turkey
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87
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Joshi M, Kumar M, Srivastava V, Kumar D, Rathore DS, Pandit R, Graham DW, Joshi CG. Genetic sequencing detected the SARS-CoV-2 delta variant in wastewater a month prior to the first COVID-19 case in Ahmedabad (India). ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 310:119757. [PMID: 35853573 PMCID: PMC9287018 DOI: 10.1016/j.envpol.2022.119757] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 06/22/2022] [Accepted: 07/08/2022] [Indexed: 05/23/2023]
Abstract
Wastewater-based genomic surveillance can identify a huge majority of variants shed by the infected individuals within a population, which goes beyond genomic surveillance based on clinical samples (i.e., symptomatic patients only). We analyzed four samples to detect key mutations in the SARS-CoV-2 genome and track circulating variants in Ahmedabad during the first wave (Sep/Nov 2020) and before the second wave (in Feb 2021) of COVID-19 in India. The analysis identified a total of 34 mutations in the spike protein across samples categorized into 23 types. The spike protein mutations were linked to the VOC-21APR-02; B.1.617.2 lineage (Delta variant) with 57% frequency in wastewater samples of Feb 2021. The key spike protein mutations were T19R, L452R, T478K, D614G, & P681R and deletions at 22029 (6 bp), 28248 (6 bp), & 28271 (1 bp). Interestingly, these mutations were not seen in the samples from Sep/Nov 2020 but did appear before the massive second wave of COVID-19 cases, which in India started in early April 2021. In fact, genetic traces of the Delta variant were found in samples of early Feb 2021, more than a month before the first clinically confirmed case of this in March 2021 in Ahmedabad, Gujarat. The present work describes the circulating of SARS-CoV-2 variants in Ahmedabad and confirms the consequential value of wastewater surveillance for the early detection of variants of concerns (VOCs). Such monitoring must be included as a major component of future health protection systems.
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Affiliation(s)
- Madhvi Joshi
- Gujarat Biotechnology Research Centre (GBRC), Sector- 11, Gandhinagar, Gujarat, 382 011, India
| | - Manish Kumar
- Discipline of Earth Science, Indian Institute of Technology Gandhinagar, Gujarat, 382 355, India; Sustainability Cluster, School of Engineering, University of Petroleum & Energy Studies, Dehradun, Uttarakhand, 248007, India.
| | - Vaibhav Srivastava
- Sustainability Cluster, School of Engineering, University of Petroleum & Energy Studies, Dehradun, Uttarakhand, 248007, India
| | - Dinesh Kumar
- Gujarat Biotechnology Research Centre (GBRC), Sector- 11, Gandhinagar, Gujarat, 382 011, India
| | - Dalip Singh Rathore
- Gujarat Biotechnology Research Centre (GBRC), Sector- 11, Gandhinagar, Gujarat, 382 011, India
| | - Ramesh Pandit
- Gujarat Biotechnology Research Centre (GBRC), Sector- 11, Gandhinagar, Gujarat, 382 011, India
| | - David W Graham
- Newcastle University, School of Engineering, Cassie Building, Newcastle-upon-Tyne, NE1 7RU, UK
| | - Chaitanya G Joshi
- Gujarat Biotechnology Research Centre (GBRC), Sector- 11, Gandhinagar, Gujarat, 382 011, India.
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88
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Wastewater surveillance in smaller college communities may aid future public health initiatives. PLoS One 2022; 17:e0270385. [PMID: 36112629 PMCID: PMC9481015 DOI: 10.1371/journal.pone.0270385] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 09/01/2022] [Indexed: 11/26/2022] Open
Abstract
To date, the COVID-19 pandemic has resulted in over 570 million cases and over 6 million deaths worldwide. Predominant clinical testing methods, though invaluable, may create an inaccurate depiction of COVID-19 prevalence due to inadequate access, testing, or most recently under-reporting because of at-home testing. These concerns have created a need for unbiased, community-level surveillance. Wastewater-based epidemiology has been used for previous public health threats, and more recently has been established as a complementary method of SARS-CoV-2 surveillance. Here we describe the application of wastewater surveillance for SARS-CoV-2 in two university campus communities located in rural Lincoln Parish, Louisiana. This cost-effective approach is especially well suited to rural areas where limited access to testing may worsen the spread of COVID-19 and quickly exhaust the capacity of local healthcare systems. Our work demonstrates that local universities can leverage scientific resources to advance public health equity in rural areas and enhance their community involvement.
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89
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de Araújo JC, Mota VT, Teodoro A, Leal C, Leroy D, Madeira C, Machado EC, Dias MF, Souza CC, Coelho G, Bressani T, Morandi T, Freitas GTO, Duarte A, Perdigão C, Tröger F, Ayrimoraes S, de Melo MC, Laguardia F, Reis MTP, Mota C, Chernicharo CAL. Long-term monitoring of SARS-CoV-2 RNA in sewage samples from specific public places and STPs to track COVID-19 spread and identify potential hotspots. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:155959. [PMID: 35588823 DOI: 10.2139/ssrn.4055085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/10/2022] [Accepted: 05/11/2022] [Indexed: 05/21/2023]
Abstract
Coronavirus pandemic started in March 2020 and since then has caused millions of deaths worldwide. Wastewater-based epidemiology (WBE) can be used as an epidemiological surveillance tool to track SARS-CoV-2 dissemination and provide warning of COVID-19 outbreaks. Considering that there are public places that could be potential hotspots of infected people that may reflect the local epidemiological situation, the presence of SARS-CoV-2 RNA was analyzed by RT-qPCR for approximately 16 months in sewage samples from five public places located in the metropolitan area of Belo Horizonte, MG, Brazil: the sewage treatment plant of Confins International Airport (AIR), the main interstate bus terminal (BUS), an upscale shopping centre (SHC1), a popular shopping centre (SHC2) and a university institute (UNI). The results were compared to those of the influent sewage of the two main sewage treatment plants of Belo Horizonte (STP1 and STP2). Viral monitoring in the STPs proved to be an useful regional surveillance tool, reflecting the trends of COVID-19 cases. However, the viral concentrations in the samples from the selected public places were generally much lower than those of the municipal STPs, which may be due to the behaviour of the non-infected or asymptomatic people, who are likely to visit these places relatively more than the symptomatic infected ones. Among these places, the AIR samples presented the highest viral concentrations and concentration peaks were observed previously to local outbreaks. Therefore, airport sewage monitoring can provide an indication of the regional epidemiological situation. For the other places, particularly the UNI, the results suggested a greater potential to detect the infection and trace cases especially among employees and regular attendees. Taken together, the results indicate that for a regular and permanent sentinel sewage surveillance the sewage from STPs, AIR and UNI could be monitored.
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Affiliation(s)
- Juliana Calábria de Araújo
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil.
| | - Vera Tainá Mota
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Amanda Teodoro
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Cíntia Leal
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Deborah Leroy
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Camila Madeira
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Elayne C Machado
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Marcela F Dias
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Cassia C Souza
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Gabriela Coelho
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Thiago Bressani
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Thiago Morandi
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Gabriel Tadeu O Freitas
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Alyne Duarte
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | | | - Flávio Tröger
- National Agency for Water and Sanitation (ANA), Brazil
| | | | | | | | | | - César Mota
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Carlos A L Chernicharo
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
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90
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de Araújo JC, Mota VT, Teodoro A, Leal C, Leroy D, Madeira C, Machado EC, Dias MF, Souza CC, Coelho G, Bressani T, Morandi T, Freitas GTO, Duarte A, Perdigão C, Tröger F, Ayrimoraes S, de Melo MC, Laguardia F, Reis MTP, Mota C, Chernicharo CAL. Long-term monitoring of SARS-CoV-2 RNA in sewage samples from specific public places and STPs to track COVID-19 spread and identify potential hotspots. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:155959. [PMID: 35588823 PMCID: PMC9110006 DOI: 10.1016/j.scitotenv.2022.155959] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/10/2022] [Accepted: 05/11/2022] [Indexed: 05/21/2023]
Abstract
Coronavirus pandemic started in March 2020 and since then has caused millions of deaths worldwide. Wastewater-based epidemiology (WBE) can be used as an epidemiological surveillance tool to track SARS-CoV-2 dissemination and provide warning of COVID-19 outbreaks. Considering that there are public places that could be potential hotspots of infected people that may reflect the local epidemiological situation, the presence of SARS-CoV-2 RNA was analyzed by RT-qPCR for approximately 16 months in sewage samples from five public places located in the metropolitan area of Belo Horizonte, MG, Brazil: the sewage treatment plant of Confins International Airport (AIR), the main interstate bus terminal (BUS), an upscale shopping centre (SHC1), a popular shopping centre (SHC2) and a university institute (UNI). The results were compared to those of the influent sewage of the two main sewage treatment plants of Belo Horizonte (STP1 and STP2). Viral monitoring in the STPs proved to be an useful regional surveillance tool, reflecting the trends of COVID-19 cases. However, the viral concentrations in the samples from the selected public places were generally much lower than those of the municipal STPs, which may be due to the behaviour of the non-infected or asymptomatic people, who are likely to visit these places relatively more than the symptomatic infected ones. Among these places, the AIR samples presented the highest viral concentrations and concentration peaks were observed previously to local outbreaks. Therefore, airport sewage monitoring can provide an indication of the regional epidemiological situation. For the other places, particularly the UNI, the results suggested a greater potential to detect the infection and trace cases especially among employees and regular attendees. Taken together, the results indicate that for a regular and permanent sentinel sewage surveillance the sewage from STPs, AIR and UNI could be monitored.
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Affiliation(s)
- Juliana Calábria de Araújo
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil.
| | - Vera Tainá Mota
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Amanda Teodoro
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Cíntia Leal
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Deborah Leroy
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Camila Madeira
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Elayne C Machado
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Marcela F Dias
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Cassia C Souza
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Gabriela Coelho
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Thiago Bressani
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Thiago Morandi
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Gabriel Tadeu O Freitas
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Alyne Duarte
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | | | - Flávio Tröger
- National Agency for Water and Sanitation (ANA), Brazil
| | | | | | | | | | - César Mota
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
| | - Carlos A L Chernicharo
- Department of Sanitary and Environmental Engineering (DESA), Federal University of Minas Gerais (UFMG), Brazil
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91
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SARS-CoV-2 Surveillance in Belgian Wastewaters. Viruses 2022; 14:v14091950. [PMID: 36146757 PMCID: PMC9506219 DOI: 10.3390/v14091950] [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: 07/07/2022] [Revised: 08/30/2022] [Accepted: 08/30/2022] [Indexed: 11/16/2022] Open
Abstract
Wastewater-based surveillance was conducted by the national public health authority to monitor SARS-CoV-2 circulation in the Belgian population. Over 5 million inhabitants representing 45% of the Belgian population were monitored throughout 42 wastewater treatment plants for 15 months comprising three major virus waves. During the entire period, a high correlation was observed between the daily new COVID-19 cases and the SARS-CoV-2 concentration in wastewater corrected for rain impact and covered population size. Three alerting indicators were included in the weekly epidemiological assessment: High Circulation, Fast Increase, and Increasing Trend. These indicators were computed on normalized concentrations per individual treatment plant to allow for a comparison with a reference period as well as between analyses performed by distinct laboratories. When the indicators were not corrected for rain impact, rainy events caused an underestimation of the indicators. Despite this negative impact, the indicators permitted us to effectively monitor the evolution of the fourth virus wave and were considered complementary and valuable information to conventional epidemiological indicators in the weekly wastewater reports communicated to the National Risk Assessment Group.
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92
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Sensor-based surveillance for digitising real-time COVID-19 tracking in the USA (DETECT): a multivariable, population-based, modelling study. Lancet Digit Health 2022; 4:e777-e786. [PMID: 36154810 PMCID: PMC9499390 DOI: 10.1016/s2589-7500(22)00156-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 07/19/2022] [Accepted: 08/02/2022] [Indexed: 11/22/2022]
Abstract
Background Traditional viral illness surveillance relies on in-person clinical or laboratory data, paper-based data collection, and outdated technology for data transfer and aggregation. We aimed to assess whether continuous sensor data can provide an early warning signal for COVID-19 activity as individual physiological and behavioural changes might precede symptom onset, care seeking, and diagnostic testing. Methods This multivariable, population-based, modelling study recruited adult (aged ≥18 years) participants living in the USA who had a smartwatch or fitness tracker on any device that connected to Apple HealthKit or Google Fit and had joined the DETECT study by downloading the MyDataHelps app. In the model development cohort, we included people who had participated in DETECT between April 1, 2020, and Jan 14, 2022. In the validation cohort, we included individuals who had participated between Jan 15 and Feb 15, 2022. When a participant joins DETECT, they fill out an intake survey of demographic information, including their ZIP code (postal code), and surveys on symptoms, symptom onset, and viral illness test dates and results, if they become unwell. When a participant connects their device, historical sensor data are collected, if available. Sensor data continue to be collected unless a participant withdraws from the study. Using sensor data, we collected each participant's daily resting heart rate and step count during the entire study period and identified anomalous sensor days, in which resting heart rate was higher than, and step count was lower than, a specified threshold calculated for each individual by use of their baseline data. The proportion of users with anomalous data each day was used to create a 7-day moving average. For the main cohort, a negative binomial model predicting 7-day moving averages for COVID-19 case counts, as reported by the Centers for Disease Control and Prevention (CDC), in real time, 6 days in the future, and 12 days in the future in the USA and California was fitted with CDC-reported data from 3 days before alone (H0) or in combination with anomalous sensor data (H1). We compared the predictions with Pearson correlation. We then validated the model in the validation cohort. Findings Between April 1, 2020, and Jan 14, 2022, 35 842 participants enrolled in DETECT, of whom 4006 in California and 28 527 in the USA were included in our main cohort. The H1 model significantly outperformed the H0 model in predicting the 7-day moving average COVID-19 case counts in California and the USA. For example, Pearson correlation coefficients for predictions 12 days in the future increased by 32·9% in California (from 0·70 [95% CI 0·65–0·73] to 0·93 [0·92–0·94]) and by 12·2% (from 0·82 [0·79–0·84] to 0·92 [0·91–0·93]) in the USA from the H0 model to the H1 model. Our validation model also showed significant correlations for predictions in real time, 6 days in the future, and 12 days in the future. Interpretation Our study showed that passively collected sensor data from consenting participants can provide real-time disease tracking and forecasting. With a growing population of wearable technology users, these sensor data could be integrated into viral surveillance programmes. Funding The National Center for Advancing Translational Sciences of the US National Institutes of Health, The Rockefeller Foundation, and Amazon Web Services.
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93
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Lee WL, Gu X, Armas F, Leifels M, Wu F, Chandra F, Chua FJD, Syenina A, Chen H, Cheng D, Ooi EE, Wuertz S, Alm EJ, Thompson J. Monitoring human arboviral diseases through wastewater surveillance: Challenges, progress and future opportunities. WATER RESEARCH 2022; 223:118904. [PMID: 36007397 DOI: 10.1016/j.watres.2022.118904] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 07/19/2022] [Accepted: 07/23/2022] [Indexed: 05/21/2023]
Abstract
Arboviral diseases are caused by a group of viruses spread by the bite of infected arthropods. Amongst these, dengue, Zika, west nile fever and yellow fever cause the greatest economic and social impact. Arboviral epidemics have increased in frequency, magnitude and geographical extent over the past decades and are expected to continue increasing with climate change and expanding urbanisation. Arboviral prevalence is largely underestimated, as most infections are asymptomatic, nevertheless existing surveillance systems are based on passive reporting of loosely defined clinical syndromes with infrequent laboratory confirmation. Wastewater-based surveillance (WBS), which has been demonstrated to be useful for monitoring diseases with significant asymptomatic populations including COVID19 and polio, could be a useful complement to arboviral surveillance. We review the current state of knowledge and identify key factors that affect the feasibility of monitoring arboviral diseases by WBS to include viral shedding loads by infected persons, the persistence of shed arboviruses and the efficiency of their recovery from sewage. We provide a simple model on the volume of wastewater that needs to be processed for detection of arboviruses, in face of lower arboviral shedding rates. In all, this review serves to reflect on the key challenges that need to be addressed and overcome for successful implementation of arboviral WBS.
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Affiliation(s)
- Wei Lin Lee
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Xiaoqiong Gu
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Federica Armas
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Fuqing Wu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, Center for Infectious Disease, University of Texas School of Public Health, Houston, TX, USA
| | - Franciscus Chandra
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Ayesa Syenina
- Program in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Viral Research and Experimental Medicine Centre (ViREMiCS), SingHealth Duke-NUS Academic Medical Centre, Singapore 169856, Singapore
| | - Hongjie Chen
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Dan Cheng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Eng Eong Ooi
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Program in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Viral Research and Experimental Medicine Centre (ViREMiCS), SingHealth Duke-NUS Academic Medical Centre, Singapore 169856, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549, Singapore
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Eric J Alm
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Janelle Thompson
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore 637459, Singapore.
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94
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Robins PE, Dickson N, Kevill JL, Malham SK, Singer AC, Quilliam RS, Jones DL. Predicting the dispersal of SARS-CoV-2 RNA from the wastewater treatment plant to the coast. Heliyon 2022; 8:e10547. [PMID: 36091966 PMCID: PMC9448708 DOI: 10.1016/j.heliyon.2022.e10547] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/22/2022] [Accepted: 09/01/2022] [Indexed: 11/28/2022] Open
Abstract
Viral pathogens including SARS-CoV-2 RNA have been detected in wastewater treatment effluent, and untreated sewage overflows, that pose an exposure hazard to humans. We assessed whether SARS-CoV-2 RNA was likely to have been present in detectable quantities in UK rivers and estuaries during the first wave of the Covid-19 pandemic. We simulated realistic viral concentrations parameterised on the Camel and Conwy catchments (UK) and their populations, showing detectable SARS-CoV-2 RNA concentrations for untreated but not for treated loading, but also being contingent on viral decay, hydrology, catchment type/shape, and location. Under mean or low river flow conditions, viral RNA concentrated within the estuaries allowing for viral build-up and caused a lag by up to several weeks between the peak in community infections and the viral peak in the environment. There was an increased hazard posed by SARS-CoV-2 RNA with a T90 decay rate >24 h, as the estuarine build-up effect increased. High discharge events transported the viral RNA downstream and offshore, increasing the exposure risk to coastal bathing waters and shellfisheries – although dilution in this case reduced viral concentrations well below detectable levels. Our results highlight the sensitivity of exposure to viral pathogens downstream of wastewater treatment, across a range of viral loadings and catchment characteristics – with implications to environmental surveillance. SARS-CoV-2 RNA from treated sewage unlikely to be detectable in estuaries. SARS-CoV-2 RNA from untreated sewage can be detectable in estuaries. Peak RNA concentration in estuaries can be delayed from peak community infection. RNA concentration is sensitive to viral loading, decay, hydrology, and estuary shape.
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Affiliation(s)
- Peter E. Robins
- School of Ocean Sciences, Bangor University, Menai Bridge, Anglesey LL59 5AB, UK
- Corresponding author.
| | - Neil Dickson
- School of Ocean Sciences, Bangor University, Menai Bridge, Anglesey LL59 5AB, UK
| | - Jessica L. Kevill
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd LL57 2UW, UK
| | - Shelagh K. Malham
- School of Ocean Sciences, Bangor University, Menai Bridge, Anglesey LL59 5AB, UK
| | | | - Richard S. Quilliam
- Biological and Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UK
| | - Davey L. Jones
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd LL57 2UW, UK
- Food Futures Institute, Murdoch University, 90 South Street, Murdoch, WA 6105, Australia
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95
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Johnson R, Mangwana N, Sharma JR, Muller CJF, Malemela K, Mashau F, Dias S, Ramharack P, Kinnear C, Glanzmann B, Viraragavin A, Louw J, Surujlal-Naicker S, Nkambule S, Webster C, Mdhluli M, Gray G, Mathee A, Preiser W, Vorster A, Dalvie S, Street R. Delineating the spread and prevalence of SARS-CoV-2 Omicron sub-lineages (BA.1- BA.5) and Deltacron using wastewater in the Western Cape, South Africa. J Infect Dis 2022; 226:1418-1427. [PMID: 36017801 PMCID: PMC9574669 DOI: 10.1093/infdis/jiac356] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 08/24/2022] [Indexed: 11/26/2022] Open
Abstract
This study was one of the first to detect Omicron sublineages BA.4 and BA.5 in wastewater from South Africa. Spearman rank correlation analysis confirmed a strong positive correlation between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA in wastewater samples and clinical cases (r = 0.7749, P < .0001). SARS-CoV-2 viral load detected in wastewater, resulting from the Delta-driven third wave, was significantly higher than during the Omicron-driven fourth wave. Whole-genome sequencing confirmed presence of Omicron lineage defining mutations in wastewater with the first occurrence reported 23 November 2021 (BA.1 predominant). The variant spread rapidly, with prevalence of Omicron-positive wastewater samples rising to >80% by 10 January 2022 with BA.2 as the predominant sublineage by 10 March 2022, whilst on 18 April 2022 BA.4 and BA.5 were detected in selected wastewater sites. These findings demonstrate the value of wastewater-based epidemiology to monitor the spatiotemporal spread and potential origin of new Omicron sublineages.
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Affiliation(s)
- Rabia Johnson
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa.,Centre for Cardio-metabolic Research in Africa, Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg 7505, South Africa
| | - Noluxabiso Mangwana
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
| | - Jyoti R Sharma
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa.,Centre for Cardio-metabolic Research in Africa, Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg 7505, South Africa
| | - Christo J F Muller
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa.,Centre for Cardio-metabolic Research in Africa, Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg 7505, South Africa.,Department of Biochemistry and Microbiology, University of Zululand, Kwa-Dlangezwa, South Africa
| | - Kholofelo Malemela
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
| | - Funanani Mashau
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
| | - Stephanie Dias
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
| | - Pritika Ramharack
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa.,Pharmaceutical Sciences, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
| | - Craig Kinnear
- Genomics Centre, South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Brigitte Glanzmann
- Pharmaceutical Sciences, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
| | - Amsha Viraragavin
- Genomics Centre, South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
| | - Johan Louw
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa.,Department of Biochemistry and Microbiology, University of Zululand, Kwa-Dlangezwa, South Africa
| | - Swastika Surujlal-Naicker
- Scientific Services, Water and Sanitation Department, City of Cape Town Metropolitan Municipality, Cape Town, South Africa
| | - Sizwe Nkambule
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Durban, South Africa
| | - Candice Webster
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), JohannesburgSouth Africa
| | - Mongezi Mdhluli
- Chief Research Operations Office, South African Medical Research Council, Tygerberg 7050, South Africa
| | - Glenda Gray
- Office of the President, South African Medical Research Council, Tygerberg 7050, South Africa
| | - Angela Mathee
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), JohannesburgSouth Africa
| | - Wolfgang Preiser
- Division of Medical Virology at NHLS Tygerberg Hospital and Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Alvera Vorster
- Central Analytical Facilities, Stellenbosch University, South Africa
| | - Shareefa Dalvie
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa.,SAMRC, Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Renee Street
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Durban, South Africa
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96
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Yaniv K, Ozer E, Shagan M, Paitan Y, Granek R, Kushmaro A. Managing an evolving pandemic: Cryptic circulation of the Delta variant during the Omicron rise. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 836:155599. [PMID: 35504376 PMCID: PMC9055682 DOI: 10.1016/j.scitotenv.2022.155599] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 04/11/2022] [Accepted: 04/25/2022] [Indexed: 05/18/2023]
Abstract
SARS-CoV-2 continued circulation results in mutations and the emergence of various variants. Until now, whenever a new, dominant, variant appeared, it overpowered its predecessor after a short parallel period. The latest variant of concern, Omicron, is spreading swiftly around the world with record morbidity reports. Unlike the Delta variant, previously considered to be the main variant of concern in most countries, including Israel, the dynamics of the Omicron variant showed different characteristics. To enable quick assessment of the spread of this variant we developed an RT-qPCR primers-probe set for the direct detection of Omicron variant. Characterized as highly specific and sensitive, the new Omicron detection set was deployed on clinical and wastewater samples. In contrast to the expected dynamics whereupon the Delta variant diminishes as Omicron variant increases, representative results received from wastewater detection indicated a cryptic circulation of the Delta variant even with the increased levels of Omicron variant. Resulting wastewater data illustrated the very initial Delta-Omicron dynamics occurring in real time. Despite this, the future development and dynamics of the two variants side-by-side is still mainly unknown. Based on the initial results, a double susceptible-infected-recovered model was developed for the Delta and Omicron variants. According to the developed model, it can be expected that the Omicron levels will decrease until eliminated, while Delta variant will maintain its cryptic circulation. If this comes to pass, the mentioned cryptic circulation may result in the reemergence of a Delta morbidity wave or in the possible generation of a new threatening variant. In conclusion, the deployment of wastewater-based epidemiology is recommended as a convenient and representative tool for pandemic containment.
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Affiliation(s)
- Karin Yaniv
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Eden Ozer
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Marilou Shagan
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Yossi Paitan
- Ilex Labs, Ilex Medical Ltd, 7 Hatnufa St., Petach-Tikva 4951025, Israel
| | - Rony Granek
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; The Ilse Katz Center for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel
| | - Ariel Kushmaro
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; The Ilse Katz Center for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel; School of Sustainability and Climate Change, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel.
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97
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Wang H, Churqui MP, Tunovic T, Enache L, Johansson A, Kärmander A, Nilsson S, Lagging M, Andersson M, Dotevall L, Brezicka T, Nyström K, Norder H. The amount of SARS-CoV-2 RNA in wastewater relates to the development of the pandemic and its burden on the health system. iScience 2022; 25:105000. [PMID: 36035197 PMCID: PMC9398557 DOI: 10.1016/j.isci.2022.105000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 06/13/2022] [Accepted: 08/18/2022] [Indexed: 11/01/2022] Open
Abstract
Virus surveillance in wastewater can be a useful indicator of the development of the COVID-19 pandemic in communities. However, knowledge about how the amount of SARS-CoV-2 RNA in wastewater relates to different data on the burden on the health system is still limited. Herein, we monitored the amount of SARS-CoV-2 RNA and the spectrum of virus variants in weekly pooled wastewater samples for two years from mid-February 2020 and compared with several clinical data. The two-year monitoring showed the weekly changes in the amount of viral RNA in wastewater preceded the hospital care needs for COVID-19 and the number of acute calls on adult acute respiratory distress by 1-2 weeks during the first three waves of COVID-19. Our study demonstrates that virus surveillance in wastewater can predict the development of a pandemic and its burden on the health system, regardless of society's test capacity and possibility of tracking infected cases.
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Affiliation(s)
- Hao Wang
- Institute of Biomedicine, Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden.,Sahlgrenska University Hospital, Department of Clinical Microbiology, Region Västra Götaland, Gothenburg, Sweden
| | - Marianela Patzi Churqui
- Institute of Biomedicine, Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden
| | - Timur Tunovic
- Institute of Biomedicine, Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden
| | | | | | - Ambjörn Kärmander
- Institute of Biomedicine, Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden
| | - Staffan Nilsson
- Institute of Biomedicine, Department of Pathology and Genetics, University of Gothenburg, Gothenburg, Sweden
| | - Martin Lagging
- Institute of Biomedicine, Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden.,Sahlgrenska University Hospital, Department of Clinical Microbiology, Region Västra Götaland, Gothenburg, Sweden
| | - Maria Andersson
- Institute of Biomedicine, Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden.,Sahlgrenska University Hospital, Department of Clinical Microbiology, Region Västra Götaland, Gothenburg, Sweden
| | - Leif Dotevall
- Department of Communicable Disease Control, Region Västra Götaland, Gothenburg, Sweden
| | - Thomas Brezicka
- Sahlgrenska University Hospital, Department of Quality and Patient Safety, Region Västra Götaland, Gothenburg, Sweden
| | - Kristina Nyström
- Institute of Biomedicine, Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden.,Sahlgrenska University Hospital, Department of Clinical Microbiology, Region Västra Götaland, Gothenburg, Sweden
| | - Heléne Norder
- Institute of Biomedicine, Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden.,Sahlgrenska University Hospital, Department of Clinical Microbiology, Region Västra Götaland, Gothenburg, Sweden
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98
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Alghamdi YS, Mashraqi MM, Alzamami A, Alturki NA, Ahmad S, Alharthi AA, Alshamrani S, Asiri SA. Unveiling the multitargeted potential of N-(4-Aminobutanoyl)-S-(4-methoxybenzyl)-L-cysteinylglycine (NSL-CG) against SARS CoV-2: a virtual screening and molecular dynamics simulation study. J Biomol Struct Dyn 2022:1-10. [PMID: 35971958 DOI: 10.1080/07391102.2022.2110158] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Abstract
The coronaviridae family has caused the most destruction among all the viral families in modern sciences. It is one of the recently discovered and added members of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which has caused the global pandemic and significant destruction worldwide. However, scientists worldwide have developed vaccines, which are being given to humans. The mutated strain of the virus has caused various uncertainties about whether the discovered drug and vaccines affect it. Even after the World Health Organization's approval for the vaccines, their effectiveness and protection ratio are still a major concern. At the community level, to this date, there is no medicine available to cure the patients. In this study, we have screened the vast library from Drug Bank and identified N-(4-Aminobutanoyl)-S-(4-methoxybenzyl)-L-cysteinylglycine (NSL-CG) that can work against two major targets of SARS CoV-2, replication-transcription and RNA dependent polymerase. Further, we have performed the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and molecular dynamics simulation of the compound with both proteins individually, giving us enough evidence that the said drugs can work against the two targets together. Inhibiting the action of any of both proteins may lead to retaining the virus, and having a dual-targeted drug can be an extra precise measure for this process. The NSL-CG is an experimental drug belonging to the peptidomimetics class included in the small group of drugs with a docking score of -9.079 kcal/mol with replication-transcription -7.885 kcal/mol with RNA-dependent polymerase. Hence, through the complete flowed study, the NSL-CG can be further experimentally validated in in-vitro and in-vivo conditions before human utilisation.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
| | - Mutaib M Mashraqi
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Najran University, Najran, Saudi Arabia
| | - Ahmad Alzamami
- Clinical Laboratory Science Department, College of Applied Medical Science, Shaqra University, AlQuwayiyah, Saudi Arabia
| | - Norah A Alturki
- Clinical Laboratory Science Department, College of Applied Medical Science, King Saud University, Riyadh, Saudi Arabia
| | - Shaban Ahmad
- Agriculture Knowledge Management Unit, ICAR-Indian Agricultural Research Institute, New Dehli, India
| | - Afaf Awwadh Alharthi
- College of applied medical sciences, Department of Clinical laboratory sciences, Taif University, Taif, Saudi Arabia
| | - Saleh Alshamrani
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Najran University, Najran, Saudi Arabia
| | - Saeed A Asiri
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Najran University, Najran, Saudi Arabia
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99
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Sapoval N, Liu Y, Lou EG, Hopkins L, Ensor KB, Schneider R, Stadler LB, Treangen TJ. QuaID: Enabling Earlier Detection of Recently Emerged SARS-CoV-2 Variants of Concern in Wastewater. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2021.09.08.21263279. [PMID: 35898338 PMCID: PMC9327636 DOI: 10.1101/2021.09.08.21263279] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variants of concern (VoC) in communities. Multiple recent studies support that wastewater-based SARS-CoV-2 detection of circulating VoC can precede clinical cases by up to two weeks. Furthermore, wastewater based epidemiology enables wide population-based screening and study of viral evolutionary dynamics. However, highly sensitive detection of emerging variants remains a complex task due to the pooled nature of environmental samples and genetic material degradation. In this paper we propose quasi-unique mutations for VoC identification, implemented in a novel bioinformatics tool (QuaID) for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3 week earlier VoC detection compared to existing approaches, (ii) enables more sensitive VoC detection, which is shown to be tolerant of >50% mutation drop-out, and (iii) leverages all mutational signatures, including insertions & deletions.
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Affiliation(s)
- Nicolae Sapoval
- Department of Computer Science, Rice University, 6100 Main Street, Houston, TX 77005, USA
| | - Yunxi Liu
- Department of Computer Science, Rice University, 6100 Main Street, Houston, TX 77005, USA
| | - Esther G Lou
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA
| | - Loren Hopkins
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX 77054
- Department of Statistics, Rice University, 6100 Main Street, Houston, TX 77005, USA
| | - Katherine B Ensor
- Department of Statistics, Rice University, 6100 Main Street, Houston, TX 77005, USA
| | | | - Lauren B Stadler
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA
| | - Todd J Treangen
- Department of Computer Science, Rice University, 6100 Main Street, Houston, TX 77005, USA
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Lee WL, Armas F, Guarneri F, Gu X, Formenti N, Wu F, Chandra F, Parisio G, Chen H, Xiao A, Romeo C, Scali F, Tonni M, Leifels M, Chua FJD, Kwok GW, Tay JY, Pasquali P, Thompson J, Alborali GL, Alm EJ. Rapid displacement of SARS-CoV-2 variant Delta by Omicron revealed by allele-specific PCR in wastewater. WATER RESEARCH 2022; 221:118809. [PMID: 35841797 PMCID: PMC9250349 DOI: 10.1016/j.watres.2022.118809] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 06/18/2022] [Accepted: 07/01/2022] [Indexed: 05/06/2023]
Abstract
On November 26, 2021, the B.1.1.529 COVID-19 variant was classified as the Omicron variant of concern (VOC). Reports of higher transmissibility and potential immune evasion triggered flight bans and heightened health control measures across the world to stem its distribution. Wastewater-based surveillance has demonstrated to be a useful complement for clinical community-based tracking of SARS-CoV-2 variants. Using design principles of our previous assays that detect SARS-CoV-2 variants (Alpha and Delta), we developed an allele-specific RT-qPCR assay which simultaneously targets the stretch of mutations from Q493R to Q498R for quantitative detection of the Omicron variant in wastewater. We report their validation against 10-month longitudinal samples from the influent of a wastewater treatment plant in Italy. SARS-CoV-2 RNA concentrations and variant frequencies in wastewater determined using these variant assays agree with clinical cases, revealing rapid displacement of the Delta variant by the Omicron variant within three weeks. These variant trends, when mapped against vaccination rates, support clinical studies that found the rapid emergence of SARS-CoV-2 Omicron variant being associated with an infection advantage over Delta in vaccinated persons. These data reinforce the versatility, utility and accuracy of these open-sourced methods using allele-specific RT-qPCR for tracking the dynamics of variant displacement in communities through wastewater for informed public health responses.
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Affiliation(s)
- Wei Lin Lee
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Federica Armas
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Flavia Guarneri
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Xiaoqiong Gu
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Nicoletta Formenti
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Fuqing Wu
- Center for Infectious Disease, Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas School of Public Health, Houston, TX, USA
| | - Franciscus Chandra
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Giovanni Parisio
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Hongjie Chen
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Amy Xiao
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, USA; Department of Biological Engineering, Massachusetts Institute of Technology, USA
| | - Claudia Romeo
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Federico Scali
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Matteo Tonni
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore
| | - Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore
| | - Germaine Wc Kwok
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore
| | - Joey Yr Tay
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Paolo Pasquali
- Dipartimento di Sicurezza Alimentare, Nutrizione e Sanità Pubblica Veterinaria, Istituto Superiore di Sanità, Italy
| | - Janelle Thompson
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore.
| | - Giovanni Loris Alborali
- Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna "Bruno Ubertini" (IZSLER), Italy
| | - Eric J Alm
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, USA; Department of Biological Engineering, Massachusetts Institute of Technology, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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