1
|
Schmiege D, Haselhoff T, Thomas A, Kraiselburd I, Meyer F, Moebus S. Small-scale wastewater-based epidemiology (WBE) for infectious diseases and antibiotic resistance: A scoping review. Int J Hyg Environ Health 2024; 259:114379. [PMID: 38626689 DOI: 10.1016/j.ijheh.2024.114379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 03/25/2024] [Accepted: 04/08/2024] [Indexed: 04/18/2024]
Abstract
Wastewater analysis can serve as a source of public health information. In recent years, wastewater-based epidemiology (WBE) has emerged and proven useful for the detection of infectious diseases. However, insights from the wastewater treatment plant do not allow for the small-scale differentiation within the sewer system that is needed to analyze the target population under study in more detail. Small-scale WBE offers several advantages, but there has been no systematic overview of its application. The aim of this scoping review is to provide a comprehensive overview of the current state of knowledge on small-scale WBE for infectious diseases, including methodological considerations for its application. A systematic database search was conducted, considering only peer-reviewed articles. Data analyses included quantitative summary and qualitative narrative synthesis. Of 2130 articles, we included 278, most of which were published since 2020. The studies analyzed wastewater at the building level (n = 203), especially healthcare (n = 110) and educational facilities (n = 80), and at the neighborhood scale (n = 86). The main analytical parameters were viruses (n = 178), notably SARS-CoV-2 (n = 161), and antibiotic resistance (ABR) biomarkers (n = 99), often analyzed by polymerase chain reaction (PCR), with DNA sequencing techniques being less common. In terms of sampling techniques, active sampling dominated. The frequent lack of detailed information on the specification of selection criteria and the characterization of the small-scale sampling sites was identified as a concern. In conclusion, based on the large number of studies, we identified several methodological considerations and overarching strategic aspects for small-scale WBE. An enabling environment for small-scale WBE requires inter- and transdisciplinary knowledge sharing across countries. Promoting the adoption of small-scale WBE will benefit from a common international conceptualization of the approach, including standardized and internationally accepted terminology. In particular, the development of good WBE practices for different aspects of small-scale WBE is warranted. This includes the establishment of guidelines for a comprehensive characterization of the local sewer system and its sub-sewersheds, and transparent reporting to ensure comparability of small-scale WBE results.
Collapse
Affiliation(s)
- Dennis Schmiege
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130, Essen, Germany.
| | - Timo Haselhoff
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130, Essen, Germany
| | - Alexander Thomas
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131, Essen, Germany
| | - Ivana Kraiselburd
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131, Essen, Germany
| | - Folker Meyer
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131, Essen, Germany
| | - Susanne Moebus
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130, Essen, Germany
| |
Collapse
|
2
|
Sovová K, Vašíčková P, Valášek V, Výravský D, Očenášková V, Juranová E, Bušová M, Tuček M, Bencko V, Mlejnková HZ. SARS-CoV-2 wastewater surveillance in the Czech Republic: Spatial and temporal differences in SARS-CoV-2 RNA concentrations and relationship to clinical data and wastewater parameters. WATER RESEARCH X 2024; 23:100220. [PMID: 38628304 PMCID: PMC11017050 DOI: 10.1016/j.wroa.2024.100220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/20/2024] [Accepted: 03/27/2024] [Indexed: 04/19/2024]
Abstract
This study presents the results of systematic wastewater monitoring of SARS-CoV-2 RNA and basic wastewater parameters from four different wastewater treatment plants (WWTPs) in the Czech Republic over the 2020-2022 epidemic. Two-step reverse-transcription quantitative PCR targeting genes encoding the N and Nsp12 proteins was employed to detect SARS-CoV-2 RNA loading in 420 wastewater samples. The results obtained were used to evaluate the potential of wastewater analysis for describing the epidemiological situation in cities of different sizes and determining temporal differences based on the prevailing SARS-CoV-2 variant. Strong correlations between the number of active and hospitalised COVID-19 cases in each WWTP catchment area and the concentration of SARS-CoV-2 RNA detected in the wastewater clearly demonstrated the suitability of this wastewater-based epidemiological approach for WWTPs of different sizes and characteristics, despite differences in SARS-CoV-2 variant waves, with some WWTPs showing high predictive potential. This study demonstrated on the data from the Czech Republic that targeted systematic monitoring of wastewater provides sufficiently robust data for surveillance of viral loads in sample populations, and thus contributes to preventing the spread of infection and subsequent introduction of appropriate measures.
Collapse
Affiliation(s)
- Kateřina Sovová
- T. G. Masaryk Water Research Institute p.r.i., Brno Branch, Mojmírovo náměstí 16, 612 00 Brno, Czech Republic
| | - Petra Vašíčková
- Masaryk University, Faculty of Science, Kotlářská 267/2, 611 37 Brno, Czech Republic
| | - Vojtěch Valášek
- T. G. Masaryk Water Research Institute, Podbabská 30, 160 00 Prague, Czech Republic
| | - David Výravský
- T. G. Masaryk Water Research Institute p.r.i., Brno Branch, Mojmírovo náměstí 16, 612 00 Brno, Czech Republic
| | - Věra Očenášková
- T. G. Masaryk Water Research Institute, Podbabská 30, 160 00 Prague, Czech Republic
| | - Eva Juranová
- T. G. Masaryk Water Research Institute, Podbabská 30, 160 00 Prague, Czech Republic
| | - Milena Bušová
- Charles University, First Faculty of Medicine, Institute of Hygiene and Epidemiology, Studničkova 7, 128 00 Prague, Czech Republic
| | - Milan Tuček
- Charles University, First Faculty of Medicine, Institute of Hygiene and Epidemiology, Studničkova 7, 128 00 Prague, Czech Republic
| | - Vladimír Bencko
- Charles University, First Faculty of Medicine, Institute of Hygiene and Epidemiology, Studničkova 7, 128 00 Prague, Czech Republic
| | | |
Collapse
|
3
|
Qiao S, Huang W, Kuzma D, Kormendi A. Acesulfame and other artificial sweeteners in a wastewater treatment plant in Alberta, Canada: Occurrence, degradation, and emission. CHEMOSPHERE 2024; 356:141893. [PMID: 38582168 DOI: 10.1016/j.chemosphere.2024.141893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 03/04/2024] [Accepted: 04/01/2024] [Indexed: 04/08/2024]
Abstract
Acesulfame (ACE), sucralose (SUC), cyclamate (CYC), and saccharin (SAC) are widely used artificial sweeteners that undergo negligible metabolism in the human body, and thus ubiquitously exist in wastewater treatment plants (WWTPs). Due to their persistence in WWTPs, ACE and SUC are found in natural waters globally. Wastewater samples were collected from the primary influent, primary effluent, secondary effluent, and final effluent of a WWTP in Alberta, Canada between August 2022 and February 2023, and the artificial sweeteners concentrations were measured by LC-MS/MS. Using wastewater-based epidemiology, the daily per capita consumption of ACE in the studied wastewater treatment plant catchment was estimated to be the highest in the world. Similar to other studies, the removal efficiency in WWTP was high for SAC and CYC, but low or even negative for SUC. However, ACE removal remained surprisingly high (>96%), even in the cold Canadian winter months. This result may indicate a further adaptation of microorganisms capable of biodegrading ACE in WWTP. The estimated per capita discharge into the environment of ACE, CYC, and SAC is low in Alberta due to the prevalent utilization of secondary treatment throughout the province, but is 17.4-18.8 times higher in Canada, since only 70.3% of total discharged wastewater in Canada undergoes secondary treatment.
Collapse
Affiliation(s)
- Shuang Qiao
- Department of Civil Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta, T2N 1N4, Canada
| | - Wendy Huang
- Department of Civil Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta, T2N 1N4, Canada.
| | - Darina Kuzma
- Advancing Canadian Water Assets, University of Calgary, 3131 210 Ave SE, Calgary, Alberta, T0L 0X0, Canada
| | - Aleshia Kormendi
- Advancing Canadian Water Assets, University of Calgary, 3131 210 Ave SE, Calgary, Alberta, T0L 0X0, Canada
| |
Collapse
|
4
|
Saingam P, Jain T, Woicik A, Li B, Candry P, Redcorn R, Wang S, Himmelfarb J, Bryan A, Winkler MKH, Gattuso M. Integrating socio-economic vulnerability factors improves neighborhood-scale wastewater-based epidemiology for public health applications. WATER RESEARCH 2024; 254:121415. [PMID: 38479175 DOI: 10.1016/j.watres.2024.121415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 02/28/2024] [Accepted: 03/03/2024] [Indexed: 04/06/2024]
Abstract
Wastewater Based Epidemiology (WBE) of COVID-19 is a low-cost, non-invasive, and inclusive early warning tool for disease spread. Previously studied WBE focused on sampling at wastewater treatment plant scale, limiting the level at which demographic and geographic variations in disease dynamics can be incorporated into the analysis of certain neighborhoods. This study demonstrates the integration of demographic mapping to improve the WBE of COVID-19 and associated post-COVID disease prediction (here kidney disease) at the neighborhood level using machine learning. WBE was conducted at six neighborhoods in Seattle during October 2020 - February 2022. Wastewater processing and RT-qPCR were performed to obtain SARS-CoV-2 RNA concentration. Census data, clinical data of COVID-19, as well as patient data of acute kidney injury (AKI) cases reported during the study period were collected and the distribution across the city was studied using Geographic Information System (GIS) mapping. Further, we analyzed the data set to better understand socioeconomic impacts on disease prevalence of COVID-19 and AKI per neighborhood. The heterogeneity of eleven demographic factors (such as education and age among others) was observed within neighborhoods across the city of Seattle. Dynamics of COVID-19 clinical cases and wastewater SARS-CoV-2 varied across neighborhood with different levels of demographics. Machine learning models trained with data from the earlier stages of the pandemic were able to predict both COVID-19 and AKI incidence in the later stages of the pandemic (Spearman correlation coefficient of 0·546 - 0·904), with the most predictive model trained on the combination of wastewater data and demographics. The integration of demographics strengthened machine learning models' capabilities to predict prevalence of COVID-19, and of AKI as a marker for post-COVID sequelae. Demographic-based WBE presents an effective tool to monitor and manage public health beyond COVID-19 at the neighborhood level.
Collapse
Affiliation(s)
- Prakit Saingam
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States.
| | - Tanisha Jain
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States
| | - Addie Woicik
- Department of Computer Science & Engineering, University of Washington, Seattle, WA, United States
| | - Bo Li
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States
| | - Pieter Candry
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States
| | - Raymond Redcorn
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States
| | - Sheng Wang
- Department of Computer Science & Engineering, University of Washington, Seattle, WA, United States
| | - Jonathan Himmelfarb
- Kidney Research Institute, University of Washington, Seattle, WA, United States; Center for Dialysis Innovation, University of Washington, Seattle, WA, United States
| | - Andrew Bryan
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Mari K H Winkler
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States
| | - Meghan Gattuso
- Seattle Public Utilities, Project Delivery and Engineering, 700 5th Ave, Seattle, WA 98104, United States
| |
Collapse
|
5
|
Chen C, Kaur G, Adiga A, Espinoza B, Venkatramanan S, Warren A, Lewis B, Crow J, Singh R, Lorentz A, Toney D, Marathe M. Wastewater-based Epidemiology for COVID-19 Surveillance: A Survey. ARXIV 2024:arXiv:2403.15291v1. [PMID: 38562450 PMCID: PMC10984000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology (WBE) for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding WBE for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.
Collapse
Affiliation(s)
- Chen Chen
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Gursharn Kaur
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Aniruddha Adiga
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Baltazar Espinoza
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Srinivasan Venkatramanan
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Andrew Warren
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Bryan Lewis
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Justin Crow
- Virginia Department of Health, Richmond, 23219, United States
| | - Rekha Singh
- Virginia Department of Health, Richmond, 23219, United States
| | - Alexandra Lorentz
- Division of Consolidated Laboratory Services, Department of General Services, Richmond, 23219, United States
| | - Denise Toney
- Division of Consolidated Laboratory Services, Department of General Services, Richmond, 23219, United States
| | - Madhav Marathe
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
- Department of Computer Science, University of Virginia, Charlottesville, 22904, United States
| |
Collapse
|
6
|
Leisman KP, Owen C, Warns MM, Tiwari A, Bian GZ, Owens SM, Catlett C, Shrestha A, Poretsky R, Packman AI, Mangan NM. A modeling pipeline to relate municipal wastewater surveillance and regional public health data. WATER RESEARCH 2024; 252:121178. [PMID: 38309063 DOI: 10.1016/j.watres.2024.121178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 12/18/2023] [Accepted: 01/22/2024] [Indexed: 02/05/2024]
Abstract
As COVID-19 becomes endemic, public health departments benefit from improved passive indicators, which are independent of voluntary testing data, to estimate the prevalence of COVID-19 in local communities. Quantification of SARS-CoV-2 RNA from wastewater has the potential to be a powerful passive indicator. However, connecting measured SARS-CoV-2 RNA to community prevalence is challenging due to the high noise typical of environmental samples. We have developed a generalized pipeline using in- and out-of-sample model selection to test the ability of different correction models to reduce the variance in wastewater measurements and applied it to data collected from treatment plants in the Chicago area. We built and compared a set of multi-linear regression models, which incorporate pepper mild mottle virus (PMMoV) as a population biomarker, Bovine coronavirus (BCoV) as a recovery control, and wastewater system flow rate into a corrected estimate for SARS-CoV-2 RNA concentration. For our data, models with BCoV performed better than those with PMMoV, but the pipeline should be used to reevaluate any new data set as the sources of variance may change across locations, lab methods, and disease states. Using our best-fit model, we investigated the utility of RNA measurements in wastewater as a leading indicator of COVID-19 trends. We did this in a rolling manner for corrected wastewater data and for other prevalence indicators and statistically compared the temporal relationship between new increases in the wastewater data and those in other prevalence indicators. We found that wastewater trends often lead other COVID-19 indicators in predicting new surges.
Collapse
Affiliation(s)
- Katelyn Plaisier Leisman
- Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA
| | - Christopher Owen
- Department of Biological Sciences, University of Illinois Chicago, Chicago, IL, USA
| | - Maria M Warns
- Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA
| | - Anuj Tiwari
- Discovery Partners Institute, University of Illinois Chicago, Chicago, IL, USA
| | - George Zhixin Bian
- Department of Computer Science, Northwestern University, Evanston, IL, USA
| | - Sarah M Owens
- Biosciences, Argonne National Laboratory, Lemont, IL, USA
| | - Charlie Catlett
- Discovery Partners Institute, University of Illinois Chicago, Chicago, IL, USA; Computing, Environment, and Life Sciences, Argonne National Laboratory, Lemont, IL, USA
| | - Abhilasha Shrestha
- Division of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois Chicago, Chicago, IL, USA
| | - Rachel Poretsky
- Department of Biological Sciences, University of Illinois Chicago, Chicago, IL, USA
| | - Aaron I Packman
- Center for Water Research, Northwestern University, Evanston, IL, USA; Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA
| | - Niall M Mangan
- Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA; Center for Water Research, Northwestern University, Evanston, IL, USA.
| |
Collapse
|
7
|
Dai X, Acosta N, Lu X, Hubert CRJ, Lee J, Frankowski K, Bautista MA, Waddell BJ, Du K, McCalder J, Meddings J, Ruecker N, Williamson T, Southern DA, Hollman J, Achari G, Ryan MC, Hrudey SE, Lee BE, Pang X, Clark RG, Parkins MD, Chekouo T. A Bayesian framework for modeling COVID-19 case numbers through longitudinal monitoring of SARS-CoV-2 RNA in wastewater. Stat Med 2024; 43:1153-1169. [PMID: 38221776 PMCID: PMC11239317 DOI: 10.1002/sim.10009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 11/11/2023] [Accepted: 12/21/2023] [Indexed: 01/16/2024]
Abstract
Wastewater-based surveillance has become an important tool for research groups and public health agencies investigating and monitoring the COVID-19 pandemic and other public health emergencies including other pathogens and drug abuse. While there is an emerging body of evidence exploring the possibility of predicting COVID-19 infections from wastewater signals, there remain significant challenges for statistical modeling. Longitudinal observations of viral copies in municipal wastewater can be influenced by noisy datasets and missing values with irregular and sparse samplings. We propose an integrative Bayesian framework to predict daily positive cases from weekly wastewater observations with missing values via functional data analysis techniques. In a unified procedure, the proposed analysis models severe acute respiratory syndrome coronavirus-2 RNA wastewater signals as a realization of a smooth process with error and combines the smooth process with COVID-19 cases to evaluate the prediction of positive cases. We demonstrate that the proposed framework can achieve these objectives with high predictive accuracies through simulated and observed real data.
Collapse
Affiliation(s)
- Xiaotian Dai
- Department of Mathematics, Illinois State University, Normal, Illinois, USA
- Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada
| | - Nicole Acosta
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
| | - Xuewen Lu
- Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada
| | - Casey R J Hubert
- Department of Biological Science, University of Calgary, Calgary, Alberta, Canada
| | - Jangwoo Lee
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
- Department of Biological Science, University of Calgary, Calgary, Alberta, Canada
| | - Kevin Frankowski
- Advancing Canadian Water Assets, University of Calgary, Calgary, Alberta, Canada
| | - Maria A Bautista
- Department of Biological Science, University of Calgary, Calgary, Alberta, Canada
| | - Barbara J Waddell
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
| | - Kristine Du
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
| | - Janine McCalder
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
- Department of Biological Science, University of Calgary, Calgary, Alberta, Canada
| | - Jon Meddings
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Alberta Health Services, Edmonton, Alberta, Canada
| | - Norma Ruecker
- Water Services, City of Calgary, Calgary, Alberta, Canada
| | - Tyler Williamson
- Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Danielle A Southern
- Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Jordan Hollman
- Department of Geosciences, University of Calgary, Calgary, Alberta, Canada
| | - Gopal Achari
- Department of Civil Engineering, University of Calgary, Calgary, Alberta, Canada
| | - M Cathryn Ryan
- Department of Geosciences, University of Calgary, Calgary, Alberta, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Bonita E Lee
- Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Rhonda G Clark
- Department of Biological Science, University of Calgary, Calgary, Alberta, Canada
| | - Michael D Parkins
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Alberta Health Services, Edmonton, Alberta, Canada
| | - Thierry Chekouo
- Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada
- Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| |
Collapse
|
8
|
Parkins MD, Lee BE, Acosta N, Bautista M, Hubert CRJ, Hrudey SE, Frankowski K, Pang XL. Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond. Clin Microbiol Rev 2024; 37:e0010322. [PMID: 38095438 PMCID: PMC10938902 DOI: 10.1128/cmr.00103-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2024] Open
Abstract
Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.
Collapse
Affiliation(s)
- Michael D. Parkins
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- O’Brien Institute of Public Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Bonita E. Lee
- Department of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Nicole Acosta
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Maria Bautista
- Department of Biological Sciences, Faculty of Science, University of Calgary, Calgary, Alberta, Canada
| | - Casey R. J. Hubert
- Department of Biological Sciences, Faculty of Science, University of Calgary, Calgary, Alberta, Canada
| | - Steve E. Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Kevin Frankowski
- Advancing Canadian Water Assets, University of Calgary, Calgary, Alberta, Canada
| | - Xiao-Li Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
- Provincial Health Laboratory, Alberta Health Services, Calgary, Alberta, Canada
| |
Collapse
|
9
|
Ensor KB, Schedler JC, Sun T, Schneider R, Mulenga A, Wu J, Stadler LB, Hopkins L. Online trend estimation and detection of trend deviations in sub-sewershed time series of SARS-CoV-2 RNA measured in wastewater. Sci Rep 2024; 14:5575. [PMID: 38448481 PMCID: PMC10918082 DOI: 10.1038/s41598-024-56175-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 03/03/2024] [Indexed: 03/08/2024] Open
Abstract
Wastewater surveillance has proven a cost-effective key public health tool to understand a wide range of community health diseases and has been a strong source of information on community levels and spread for health departments throughout the SARS- CoV-2 pandemic. Studies spanning the globe demonstrate the strong association between virus levels observed in wastewater and quality clinical case information of the population served by the sewershed. Few of these studies incorporate the temporal dependence present in sampling over time, which can lead to estimation issues which in turn impact conclusions. We contribute to the literature for this important public health science by putting forward time series methods coupled with statistical process control that (1) capture the evolving trend of a disease in the population; (2) separate the uncertainty in the population disease trend from the uncertainty due to sampling and measurement; and (3) support comparison of sub-sewershed population disease dynamics with those of the population represented by the larger downstream treatment plant. Our statistical methods incorporate the fact that measurements are over time, ensuring correct statistical conclusions. We provide a retrospective example of how sub-sewersheds virus levels compare to the upstream wastewater treatment plant virus levels. An on-line algorithm supports real-time statistical assessment of deviations of virus level in a population represented by a sub-sewershed to the virus level in the corresponding larger downstream wastewater treatment plant. This information supports public health decisions by spotlighting segments of the population where outbreaks may be occurring.
Collapse
Affiliation(s)
- Katherine B Ensor
- Department of Statistics, Rice University, 6100 Main St., Houston, TX, 77005, USA.
| | - Julia C Schedler
- Department of Statistics, Rice University, 6100 Main St., Houston, TX, 77005, USA
| | - Thomas Sun
- Department of Statistics, Rice University, 6100 Main St., Houston, TX, 77005, USA
| | - Rebecca Schneider
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, 77054, USA
| | - Anthony Mulenga
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, 77054, USA
| | - Jingjing Wu
- Department of Civil and Environment Engineering, Rice University, 6100 Main St, Houston, TX, 77005, USA
| | - Lauren B Stadler
- Department of Civil and Environment Engineering, Rice University, 6100 Main St, Houston, TX, 77005, USA
| | - Loren Hopkins
- Houston Health Department and Department of Statistics, Rice University, 6100 Main St., Houston, TX, 77005, USA
| |
Collapse
|
10
|
Van Dusen J, LeBlanc H, Nastasi N, Panescu J, Shamblin A, Smith JW, Sovic MG, Williams A, Quam MBM, Faith S, Dannemiller KC. Identification of SARS-CoV-2 variants in indoor dust. PLoS One 2024; 19:e0297172. [PMID: 38335205 PMCID: PMC10857703 DOI: 10.1371/journal.pone.0297172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 12/30/2023] [Indexed: 02/12/2024] Open
Abstract
Environmental surveillance of pathogens underlying infectious disease is critical to ensure public health. Recent efforts to track SARS-CoV-2 have utilized wastewater sampling to infer community trends in viral abundance and variant composition. Indoor dust has also been used for building-level inferences, though to date no sequencing data providing variant-scale resolution have been reported from dust samples, and strategies to monitor circulating variants in dust are needed to help inform public health decisions. In this study, we demonstrate that SARS-CoV-2 lineages can be detected and sequenced from indoor bulk dust samples. We collected 93 vacuum bags from April 2021 to March 2022 from buildings on The Ohio State University's (OSU) Columbus campus, and the dust was used to develop and apply an amplicon-based whole-genome sequencing protocol to identify the variants present and estimate their relative abundances. Three variants of concern were detected in the dust: Alpha, Delta, and Omicron. Alpha was found in our earliest sample in April 2021 with an estimated frequency of 100%. Delta was the primary variant present from October of 2021 to January 2022, with an average estimated frequency of 91% (±1.3%). Omicron became the primary variant in January 2022 and was the dominant strain in circulation through March with an estimated frequency of 87% (±3.2%). The detection of these variants on OSU's campus correlates with the circulation of these variants in the surrounding population (Delta p<0.0001 and Omicron p = 0.02). Overall, these results support the hypothesis that dust can be used to track COVID-19 variants in buildings.
Collapse
Affiliation(s)
- John Van Dusen
- Department of Microbiology, College of Arts and Sciences, The Ohio State University, Columbus, Ohio, United States of America
| | - Haley LeBlanc
- Genetic Counseling Program, College of Biological Sciences, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Nicholas Nastasi
- Environmental Sciences Graduate Program, The Ohio State University, Columbus, Ohio, United States of America
- Department of Civil, Environmental & Geodetic Engineering, College of Engineering, The Ohio State University, Columbus, Ohio, United States of America
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America
| | - Jenny Panescu
- Department of Civil, Environmental & Geodetic Engineering, College of Engineering, The Ohio State University, Columbus, Ohio, United States of America
| | - Austin Shamblin
- Applied Microbiology Services Lab, The Ohio State University, Columbus, Ohio, United States of America
| | - Jacob W. Smith
- Department of Chemistry and Biochemistry, College of Arts and Sciences, The Ohio State University, Columbus, Ohio, United States of America
| | - Michael G. Sovic
- Applied Microbiology Services Lab, The Ohio State University, Columbus, Ohio, United States of America
- Infectious Diseases Institute, The Ohio State University, Columbus, Ohio, United States of America
| | - Amanda Williams
- Institute for Genomic Medicine, Nationwide Children’s Hospital, Columbus, Ohio, United States of America
| | - Mikkel B. M. Quam
- Infectious Diseases Institute, The Ohio State University, Columbus, Ohio, United States of America
- Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America
- Section of Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Seth Faith
- Applied Microbiology Services Lab, The Ohio State University, Columbus, Ohio, United States of America
- Infectious Diseases Institute, The Ohio State University, Columbus, Ohio, United States of America
| | - Karen C. Dannemiller
- Department of Civil, Environmental & Geodetic Engineering, College of Engineering, The Ohio State University, Columbus, Ohio, United States of America
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America
- Sustainability Institute, The Ohio State University, Columbus, Ohio, United States of America
| |
Collapse
|
11
|
Zammit I, Badia S, Mejías-Molina C, Rusiñol M, Bofill-Mas S, Borrego CM, Corominas L. Zooming in to the neighborhood level: A year-long wastewater-based epidemiology monitoring campaign for COVID-19 in small intraurban catchments. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:167811. [PMID: 37852481 DOI: 10.1016/j.scitotenv.2023.167811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 09/14/2023] [Accepted: 10/11/2023] [Indexed: 10/20/2023]
Abstract
In recent years, wastewater-based epidemiology (WBE) has emerged as a valuable and cost-effective tool for monitoring the prevalence of COVID-19. Large-scale monitoring efforts have been implemented in numerous countries, primarily focusing on sampling at the entrance of wastewater treatment plants (WWTPs) to cover a large population. However, sampling at a finer spatial scale, such as at the neighborhood level (NGBs), pose new challenges, including the absence of composite sampling infrastructure and increased uncertainty due to the dynamics of small catchments. This study aims to investigate the feasibility and accuracy of WBE when deployed at the neighborhood level (sampling in sewers) compared to the city level (sampling at the entrance of a WWTP). To achieve this, we deployed specific WBE sampling stations at the intraurban scale within three NGBs in Barcelona, Spain. The study period covers the 5th and the 6th waves of COVID-19 in Spain, spanning from March 2021 to March 2022, along with the WWTP downstream from the NGBs. The results showed a strong correlation between the dynamics of COVID-19 clinical cases and wastewater SARS-CoV-2 loads at both the NGB and city levels. Notably, during the 5th wave, which was dominated by the Delta SARS-CoV-2 variant, wastewater loads were higher than during the 6th wave (Omicron variant), despite a lower number of clinical cases recorded during the 5th wave. The correlations between wastewater loads and clinical cases at the NGB level were stronger than at the WWTP level. However, the early warning potential varied across neighborhoods and waves, with some cases showing a one-week early warning and others lacking any significant early warning signal. Interestingly, the prevalence of COVID-19 did not exhibit major differences among NGBs with different socioeconomic statuses.
Collapse
Affiliation(s)
- Ian Zammit
- Catalan Institute for Water Research (ICRA-CERCA), Emili Grahit 101, 17003 Girona, Spain; University of Girona, Plaça de Sant Domènec 3, 17004 Girona, Spain
| | - Sergi Badia
- Catalan Institute for Water Research (ICRA-CERCA), Emili Grahit 101, 17003 Girona, Spain; University of Girona, Plaça de Sant Domènec 3, 17004 Girona, Spain
| | - Cristina Mejías-Molina
- Laboratory of Viruses Contaminants of Water and Food, Genetics, Microbiology & Statistics Dept., Universitat de Barcelona, Barcelona, Catalonia, Spain; The Water Research Institute (IdRA), Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Marta Rusiñol
- Laboratory of Viruses Contaminants of Water and Food, Genetics, Microbiology & Statistics Dept., Universitat de Barcelona, Barcelona, Catalonia, Spain; The Water Research Institute (IdRA), Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Sílvia Bofill-Mas
- Laboratory of Viruses Contaminants of Water and Food, Genetics, Microbiology & Statistics Dept., Universitat de Barcelona, Barcelona, Catalonia, Spain; The Water Research Institute (IdRA), Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Carles M Borrego
- Catalan Institute for Water Research (ICRA-CERCA), Emili Grahit 101, 17003 Girona, Spain; Group of Molecular Microbial Ecology, Institute of Aquatic Ecology, University of Girona, Girona, Catalonia, Spain
| | - Lluís Corominas
- Catalan Institute for Water Research (ICRA-CERCA), Emili Grahit 101, 17003 Girona, Spain; University of Girona, Plaça de Sant Domènec 3, 17004 Girona, Spain.
| |
Collapse
|
12
|
Baz Lomba JA, Pires J, Myrmel M, Arnø JK, Madslien EH, Langlete P, Amato E, Hyllestad S. Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic. JOURNAL OF WATER AND HEALTH 2024; 22:197-234. [PMID: 38295081 PMCID: wh_2023_279 DOI: 10.2166/wh.2023.279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.
Collapse
Affiliation(s)
- Jose Antonio Baz Lomba
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway E-mail:
| | - João Pires
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway; ECDC fellowship Programme, Public Health Microbiology path (EUPHEM), European Centre for Disease Prevention and Control (ECDC), Solna, Sweden
| | - Mette Myrmel
- Faculty of Veterinary Medicine, Virology Unit, Norwegian University of Life Science (NMBU), Oslo, Norway
| | - Jorunn Karterud Arnø
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Elisabeth Henie Madslien
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Petter Langlete
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Ettore Amato
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Susanne Hyllestad
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| |
Collapse
|
13
|
Bowes DA, Henke KB, Driver EM, Newell ME, Block I, Shaffer G, Varsani A, Scotch M, Halden RU. Enhanced detection of mpox virus in wastewater using a pre-amplification approach: A pilot study informing population-level monitoring of low-titer pathogens. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 903:166230. [PMID: 37574063 PMCID: PMC10592092 DOI: 10.1016/j.scitotenv.2023.166230] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 08/09/2023] [Accepted: 08/09/2023] [Indexed: 08/15/2023]
Abstract
A recent outbreak of the mpox virus (MPXV) occurred in non-endemic regions of the world beginning in May 2022. Pathogen surveillance systems faced pressure to quickly establish response protocols, offering an opportunity to employ wastewater-based epidemiology (WBE) for population-level monitoring. The pilot study reported herein aimed to: (i) develop a reliable protocol for MPXV DNA detection in wastewater which would reduce false negative reporting, (ii) test this protocol on wastewater from various regions across the United States, and (iii) conduct a state of the science review of the current literature reporting on experimental methods for MPXV detection using WBE. Twenty-four-hour composite samples of untreated municipal wastewater were collected from the states of New Jersey, Georgia, Illinois, Texas, Arizona, and Washington beginning July 3rd, 2022 through October 16th, 2022 (n = 60). Samples underwent vacuum filtration, DNA extraction from captured solids, MPXV DNA pre-amplification, and qPCR analysis. Of the 60 samples analyzed, a total of eight (13%) tested positive for MPXV in the states of Washington, Texas, New Jersey, and Illinois. The presence of clade IIb MPXV DNA in these samples was confirmed via Sanger sequencing and integration of pre-amplification prior to qPCR decreased the rate of false negative detections by 87% as compared to qPCR analysis alone. Wastewater-derived detections of MPXV were compared to clinical datasets, with 50% of detections occurring as clinical cases were increasing/peaking and 50% occurring as clinical cases waned. Results from the literature review (n = 9 studies) revealed successful strategies for the detection of MPXV DNA in wastewater, however also emphasized a need for further method optimization and standardization. Overall, this work highlights the use of pre-amplification prior to qPCR detection as a means to capture the presence of MPXV DNA in community wastewater and offers guidance for monitoring low-titer pathogens via WBE.
Collapse
Affiliation(s)
- Devin A Bowes
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Katherine B Henke
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Erin M Driver
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Melanie Engstrom Newell
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Izabella Block
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Gray Shaffer
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA
| | - Arvind Varsani
- The Biodesign Institute Center for Fundamental and Applied Microbiomics, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA; School of Life Sciences, Arizona State University, 427 E. Tyler Mall, Tempe, AZ 85281, USA; Center of Evolution and Medicine, Arizona State University, 427 E. Tyler Mall, Tempe, AZ 85281, USA
| | - Matthew Scotch
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA; College of Health Solutions, Arizona State University, 550 N. 3rd St., Phoenix, AZ 85004, USA
| | - Rolf U Halden
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA; School for Sustainable Engineering and the Built Environment, Arizona State University, 660 S. College Ave., Tempe, AZ 85281, USA; OneWaterOneHealth, The Arizona State University Foundation, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ 85281, USA; Global Futures Laboratory, Arizona State University, 800 S. Cady Mall, Tempe, AZ 85281, USA.
| |
Collapse
|
14
|
Acosta N, Dai X, Bautista MA, Waddell BJ, Lee J, Du K, McCalder J, Pradhan P, Papparis C, Lu X, Chekouo T, Krusina A, Southern D, Williamson T, Clark RG, Patterson RA, Westlund P, Meddings J, Ruecker N, Lammiman C, Duerr C, Achari G, Hrudey SE, Lee BE, Pang X, Frankowski K, Hubert CRJ, Parkins MD. Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 900:165172. [PMID: 37379934 PMCID: PMC10292917 DOI: 10.1016/j.scitotenv.2023.165172] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 06/21/2023] [Accepted: 06/25/2023] [Indexed: 06/30/2023]
Abstract
Wastewater-based surveillance (WBS) of infectious diseases is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19's impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.4 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5 % (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4524 unrelated absences COVID-19 cases were recorded. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P < 0.0001). The Poisson regression with wastewater as a one-week leading signal has an Akaike information criterion (AIC) of 858, compared to a null model (excluding wastewater predictor) with an AIC of 1895. The likelihood-ratio test comparing the model with wastewater signal with the null model shows statistical significance (P < 0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.
Collapse
Affiliation(s)
- Nicole Acosta
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Xiaotian Dai
- Department of Mathematics and Statistics, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Maria A Bautista
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Barbara J Waddell
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Jangwoo Lee
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Kristine Du
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Janine McCalder
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Puja Pradhan
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Chloe Papparis
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Xuewen Lu
- Department of Mathematics and Statistics, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Thierry Chekouo
- Department of Mathematics and Statistics, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada; Division of Biostatistics, School of Public Health, University of Minnesota, 420 Delaware St. S.E., Minneapolis, MN 55455, USA
| | - Alexander Krusina
- Department of Community Health Sciences, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Medicine, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Danielle Southern
- Department of Community Health Sciences, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Medicine, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Tyler Williamson
- Department of Community Health Sciences, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Medicine, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; O'Brien Institute for Public Health, University of Calgary, 3280 Hospital Dr NW, Calgary, Alberta T2N 4Z6, Canada
| | - Rhonda G Clark
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Raymond A Patterson
- Haskayne School of Business, University of Calgary, SH 250, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | | | - Jon Meddings
- Department of Medicine, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Norma Ruecker
- Water Services, City of Calgary, 625 25 Ave SE, Calgary, Alberta T2G 4k8, Canada
| | - Christopher Lammiman
- Calgary Emergency Management Agency (CEMA), City of Calgary, 673 1 St NE, Calgary, Alberta T2E 6R2, Canada
| | - Coby Duerr
- Calgary Emergency Management Agency (CEMA), City of Calgary, 673 1 St NE, Calgary, Alberta T2E 6R2, Canada
| | - Gopal Achari
- Department of Civil Engineering, University of Calgary, 622 Collegiate Pl NW, T2N 4V8, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada; Analytical and Environmental Toxicology, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada
| | - Bonita E Lee
- Department of Pediatrics, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada; Women & Children's Health Research Institute, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada; Li Ka Shing Institute of Virology, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada; Li Ka Shing Institute of Virology, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada; Alberta Precision Laboratories, Public Health Laboratory, Alberta Health Services, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada
| | - Kevin Frankowski
- Advancing Canadian Water Assets, University of Calgary, 3131 210 Ave SE, Calgary, Alberta T0L 0X0, Canada
| | - Casey R J Hubert
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Michael D Parkins
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Medicine, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Snyder Institute for Chronic Diseases, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada.
| |
Collapse
|
15
|
Zhao J, Lu J, Zhao H, Yan Y, Dong H. In five wastewater treatment plants in Xinjiang, China: Removal processes for illicit drugs, their occurrence in receiving river waters, and ecological risk assessment. CHEMOSPHERE 2023; 339:139668. [PMID: 37517667 DOI: 10.1016/j.chemosphere.2023.139668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/24/2023] [Accepted: 07/27/2023] [Indexed: 08/01/2023]
Abstract
Residues of illicit drugs are frequently detected in wastewater, but data on their removal efficiency by wastewater treatment plants (WWTPs) and the ecological risks to the aquatic environment are lacking in this study. The research evaluates the residues, mass load, drug removal efficiency, and risk assessment of illicit drugs in WWTPs and aquatic environments (lakes) in Xinjiang, China. Initially, the concentration (incidence) and mass load of 10 selected illicit drugs were analyzed through wastewater analysis. The detected substances included methamphetamine (METH), morphine (MOR), 3,4-methylenedioxy methamphetamine (MDMA), methadone (MTD), cocaine (COC), benzoylecgonine (BE), ketamine (KET), and codeine (COD), with concentrations ranging from 0.11 ± 0.01 ng/L (methadone) to 48.26 ± 25.05 ng/L (morphine). Notably, morphine (59.74 ± 5.82 g/day) and methamphetamine (41.81 ± 4.91 g/day) contributed significantly to the WWTPs. Next, the drug removal efficiency by different sewage treatment processes was ranked as follows: Anaerobic-Oxic (A/O) combined Membrane Bio-Reactor (MBR) treatment process > Oxidation ditch treatment process > Anaerobic-Anoxic-Oxic (A2/O) treatment process > Anaerobic-Anoxic-Oxic combined Membrane Bio-Reactor treatment process. Finally, the research reviewed the concentration and toxicity assessments of these substances in the aquatic environment (lakes). The results indicated that Lake1 presented a medium risk level concerning the impact of illicit drugs on the aquatic environment, whereas the other lakes exhibited a low risk level. As a result, it is recommended to conduct long-term monitoring and source analysis of illicit drugs, specifically in Lake1, for further investigation. In conclusion, to enhance the understanding of the effects of illicit drugs on the environment, future research should expand the list of target analytes.
Collapse
Affiliation(s)
- Jie Zhao
- School of Chemistry and Chemical Engineering, Key Laboratory of Environmental Monitoring and Pollutant Control of Xinjiang Bingtuan, Shihezi University, Shihezi, 832003, China
| | - Jianjiang Lu
- School of Chemistry and Chemical Engineering, Key Laboratory of Environmental Monitoring and Pollutant Control of Xinjiang Bingtuan, Shihezi University, Shihezi, 832003, China.
| | - Haijun Zhao
- The First Affiliated Hospital, School of Medicine, Shihezi University, Shihezi, 832003, China
| | - Yujun Yan
- School of Chemistry and Chemical Engineering, Key Laboratory of Environmental Monitoring and Pollutant Control of Xinjiang Bingtuan, Shihezi University, Shihezi, 832003, China
| | - Hongyu Dong
- School of Chemistry and Chemical Engineering, Key Laboratory of Environmental Monitoring and Pollutant Control of Xinjiang Bingtuan, Shihezi University, Shihezi, 832003, China
| |
Collapse
|
16
|
Lee J, Acosta N, Waddell BJ, Du K, Xiang K, Van Doorn J, Low K, Bautista MA, McCalder J, Dai X, Lu X, Chekouo T, Pradhan P, Sedaghat N, Papparis C, Buchner Beaudet A, Chen J, Chan L, Vivas L, Westlund P, Bhatnagar S, Stefani S, Visser G, Cabaj J, Bertazzon S, Sarabi S, Achari G, Clark RG, Hrudey SE, Lee BE, Pang X, Webster B, Ghali WA, Buret AG, Williamson T, Southern DA, Meddings J, Frankowski K, Hubert CRJ, Parkins MD. Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community. WATER RESEARCH 2023; 244:120469. [PMID: 37634459 DOI: 10.1016/j.watres.2023.120469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 08/06/2023] [Accepted: 08/07/2023] [Indexed: 08/29/2023]
Abstract
Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.
Collapse
Affiliation(s)
- Jangwoo Lee
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Nicole Acosta
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Barbara J Waddell
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Kristine Du
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Kevin Xiang
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Jennifer Van Doorn
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Kashtin Low
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Maria A Bautista
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Janine McCalder
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Xiaotian Dai
- Department of Mathematics and Statistics, University of Calgary, Calgary, Canada
| | - Xuewen Lu
- Department of Mathematics and Statistics, University of Calgary, Calgary, Canada
| | - Thierry Chekouo
- Department of Mathematics and Statistics, University of Calgary, Calgary, Canada; Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, USA
| | - Puja Pradhan
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Navid Sedaghat
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Chloe Papparis
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Alexander Buchner Beaudet
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Jianwei Chen
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Leslie Chan
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Laura Vivas
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | | | - Srijak Bhatnagar
- Department of Biological Sciences, University of Calgary, Calgary, Canada; Faculty of Science and Technology, Athabasca University, Athabasca, Alberta, Canada
| | - September Stefani
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Gail Visser
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Jason Cabaj
- Department of Community Health Sciences, University of Calgary, Calgary, Canada; Department of Medicine, University of Calgary and Alberta Health Services, Calgary, Canada; Provincial Population & Public Health, Alberta Health Services, Calgary, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Canada
| | | | - Shahrzad Sarabi
- Department of Geography, University of Calgary, Calgary, Canada
| | - Gopal Achari
- Department of Civil Engineering, University of Calgary, Calgary, Canada
| | - Rhonda G Clark
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada; Analytical and Environmental Toxicology, University of Alberta, Edmonton, Alberta, Canada
| | - Bonita E Lee
- Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada; Women & Children's Health Research Institute, Li Ka Shing Institute of Virology, Edmonton, Alberta, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada; Alberta Precision Laboratories, Public Health Laboratory, Alberta Health Services, Edmonton, Alberta, Canada; Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alberta, Canada
| | - Brendan Webster
- Occupational Health Staff Wellness, University of Calgary, Calgary, Canada
| | - William Amin Ghali
- Department of Community Health Sciences, University of Calgary, Calgary, Canada; Department of Medicine, University of Calgary and Alberta Health Services, Calgary, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Canada; Centre for Health Informatics, University of Calgary, Calgary, Canada
| | - Andre Gerald Buret
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Tyler Williamson
- Department of Community Health Sciences, University of Calgary, Calgary, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Canada; Centre for Health Informatics, University of Calgary, Calgary, Canada
| | - Danielle A Southern
- Department of Community Health Sciences, University of Calgary, Calgary, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Canada; Centre for Health Informatics, University of Calgary, Calgary, Canada
| | - Jon Meddings
- Department of Medicine, University of Calgary and Alberta Health Services, Calgary, Canada
| | - Kevin Frankowski
- Advancing Canadian Water Assets, University of Calgary, Calgary, Canada
| | - Casey R J Hubert
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Michael D Parkins
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Medicine, University of Calgary and Alberta Health Services, Calgary, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Canada.
| |
Collapse
|
17
|
Ashraf MA, Nawaz M, Asif A, Ali MA, Mehmood A, Aziz MW, Shabbir MZ, Mukhtar N, Shabbir MAB, Raza S, Yaqub T. Temporal study of wastewater surveillance from September 2020 to March 2021: an estimation of COVID-19 patients in Lahore, Pakistan. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:80855-80862. [PMID: 37308626 DOI: 10.1007/s11356-023-28041-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 05/29/2023] [Indexed: 06/14/2023]
Abstract
The first aim of study was to quantify the viral load in the wastewater samples by RT-qPCR testing in Lahore population to estimate the number of patients affected and predict the next resurgence of COVID-19 wave in the city. The second aim of the study was to determine the hotspot areas of Lahore which remained positive more often for virus with high viral load. In this study, n = 420 sewage samples were collected on an average of two weeks intervals from 30 different sewage water disposal stations (14 sampling events) from Sept 2020 to March 2021. RNA was extracted and quantified by RT-qPCR without concentrating the virus in samples. Number of positive disposal sites (7-93%), viral load from sewage samples (100.296 to 103.034), and estimated patients (660-17,030) ranged from low to high according to the surge and restrain of 2nd and 3rd COVID-19 waves in the country. The viral load and estimated patients were reported high in January 2021 and March 2021 which were similar to the peak of 2nd and 3rd waves in Pakistan. Site 18 (Niaz Baig village DS) showed the highest viral load among all sites. Findings of the present study helped to estimate the number of patients and track the resurgence in COVID-19 waves in Lahore particularly, and in Punjab generally. Furthermore, it emphasizes the role of wastewater-based epidemiology to help policymakers strengthen the quarantine measures along with immunization to overcome enteric viral diseases. Local and national stake holders should work in collaboration to improve the environmental hygiene to control the disease.
Collapse
Affiliation(s)
- Muhammad Adnan Ashraf
- Institute of Microbiology, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
| | - Muhammad Nawaz
- Institute of Microbiology, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan.
| | - Ali Asif
- Institute of Microbiology, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
| | - Muhammad Asad Ali
- Institute of Microbiology, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
| | - Adnan Mehmood
- Institute of Microbiology, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
| | - Muhammad Waqar Aziz
- Institute of Microbiology, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
| | - Muhammad Zubair Shabbir
- Institute of Microbiology, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
| | - Nadia Mukhtar
- Institute of Microbiology, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
| | | | - Sohail Raza
- Institute of Microbiology, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
| | - Tahir Yaqub
- Institute of Microbiology, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
| |
Collapse
|
18
|
Ciannella S, González-Fernández C, Gomez-Pastora J. Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 878:162953. [PMID: 36948304 PMCID: PMC10028212 DOI: 10.1016/j.scitotenv.2023.162953] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/13/2023] [Accepted: 03/15/2023] [Indexed: 05/13/2023]
Abstract
On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19), whose causative agent is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pandemic. This virus is predominantly transmitted via respiratory droplets and shed via sputum, saliva, urine, and stool. Wastewater-based epidemiology (WBE) has been able to monitor the circulation of viral pathogens in the population. This tool demands both in-lab and computational work to be meaningful for, among other purposes, the prediction of outbreaks. In this context, we present a systematic review that organizes and discusses laboratory procedures for SARS-CoV-2 RNA quantification from a wastewater matrix, along with modeling techniques applied to the development of WBE for COVID-19 surveillance. The goal of this review is to present the current panorama of WBE operational aspects as well as to identify current challenges related to it. Our review was conducted in a reproducible manner by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. We identified a lack of standardization in wastewater analytical procedures. Regardless, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach was the most reported technique employed to detect and quantify viral RNA in wastewater samples. As a more convenient sample matrix, we suggest the solid portion of wastewater to be considered in future investigations due to its higher viral load compared to the liquid fraction. Regarding the epidemiological modeling, the data-driven approach was consistently used for the prediction of variables associated with outbreaks. Future efforts should also be directed toward the development of rapid, more economical, portable, and accurate detection devices.
Collapse
Affiliation(s)
- Stefano Ciannella
- Department of Chemical Engineering, Texas Tech University, Lubbock 79409, TX, USA.
| | - Cristina González-Fernández
- Department of Chemical Engineering, Texas Tech University, Lubbock 79409, TX, USA; Departamento de Ingenierías Química y Biomolecular, Universidad de Cantabria, Avda. Los Castros, s/n, 39005 Santander, Spain.
| | | |
Collapse
|
19
|
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.
Collapse
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
| |
Collapse
|
20
|
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: 4] [Impact Index Per Article: 4.0] [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.
Collapse
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.
| |
Collapse
|
21
|
Wen J, Duan L, Wang B, Dong Q, Liu Y, Huang J, Yu G. Stability and WBE biomarkers possibility of 17 antiviral drugs in sewage and gravity sewers. WATER RESEARCH 2023; 238:120023. [PMID: 37150064 PMCID: PMC10149109 DOI: 10.1016/j.watres.2023.120023] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 03/31/2023] [Accepted: 04/28/2023] [Indexed: 05/09/2023]
Abstract
Wastewater-based epidemiology (WBE) is a promising technique for monitoring the rapidly increasing use of antiviral drugs during the COVID-19 pandemic. It is essential to evaluate the in-sewer stability of antiviral drugs in order to determine appropriate biomarkers. This study developed an analytical method for quantification of 17 typical antiviral drugs, and investigated the stability of target compounds in sewer through 4 laboratory-scale gravity sewer reactors. Nine antiviral drugs (lamivudine, acyclovir, amantadine, favipiravir, nevirapine, oseltamivir, ganciclovir, emtricitabine and telbivudine) were observed to be stable and recommended as appropriate biomarkers for WBE. As for the other 8 unstable drugs (abacavir, arbidol, ribavirin, zidovudine, ritonavir, lopinavir, remdesivir and efavirenz), their attenuation was driven by adsorption, biodegradation and diffusion. Moreover, reaction kinetics revealed that the effects of sediments and biofilms were regarded to be independent in gravity sewers, and the rate constants of removal by biofilms was directly proportional to the ratio of surface area against wastewater volume. The study highlighted the potential importance of flow velocity for compound stability, since an increased flow velocity significantly accelerated the removal of unstable biomarkers. In addition, a framework for graded evaluation of biomarker stability was proposed to provide reference for researchers to select suitable WBE biomarkers. Compared with current classification method, this framework considered the influences of residence time and different removal mechanisms, which additionally screened four antiviral drugs as viable WBE biomarkers. This is the first study to report the stability of antiviral drugs in gravity sewers.
Collapse
Affiliation(s)
- Jiaqi Wen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory for Emerging Organic Contaminants Control, Beijing Laboratory for Environmental Frontier Technologies, China
| | - Lei Duan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory for Emerging Organic Contaminants Control, Beijing Laboratory for Environmental Frontier Technologies, China
| | - Bin Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory for Emerging Organic Contaminants Control, Beijing Laboratory for Environmental Frontier Technologies, China
| | - Qian Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yanchen Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jun Huang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory for Emerging Organic Contaminants Control, Beijing Laboratory for Environmental Frontier Technologies, China
| | - Gang Yu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory for Emerging Organic Contaminants Control, Beijing Laboratory for Environmental Frontier Technologies, China; Advanced Interdisciplinary Institute of Environment and Ecology, Beijing Normal University at Zhuhai, 519087, China.
| |
Collapse
|
22
|
Rainey AL, Liang S, Bisesi JH, Sabo-Attwood T, Maurelli AT. A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19. PLoS One 2023; 18:e0284370. [PMID: 37043469 PMCID: PMC10096268 DOI: 10.1371/journal.pone.0284370] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 03/29/2023] [Indexed: 04/13/2023] Open
Abstract
Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring SARS-CoV-2 infection trends throughout the COVID-19 pandemic. Population biomarkers that measure the relative human fecal contribution to normalize SARS-CoV-2 wastewater concentrations are needed for improved analysis and interpretation of community infection trends. The Centers for Disease Control and Prevention National Wastewater Surveillance System (CDC NWSS) recommends using the wastewater flow rate or human fecal indicators as population normalization factors. However, there is no consensus on which normalization factor performs best. In this study, we provided the first multistate assessment of the effects of flow rate and human fecal indicators (crAssphage, F+ Coliphage, and PMMoV) on the correlation of SARS-CoV-2 wastewater concentrations and COVID-19 cases using the CDC NWSS dataset of 182 communities across six U.S. states. Flow normalized SARS-CoV-2 wastewater concentrations produced the strongest correlation with COVID-19 cases. The correlation from the three human fecal indicators were significantly lower than flow rate. Additionally, using reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) significantly improved correlation values over samples that were analyzed with real-time reverse transcription quantitative polymerase chain reaction (rRT-qPCR). Our assessment shows that utilizing flow normalization with RT-ddPCR generate the strongest correlation between SARS-CoV-2 wastewater concentrations and COVID-19 cases.
Collapse
Affiliation(s)
- Andrew L. Rainey
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Song Liang
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Joseph H. Bisesi
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- Center for Environmental and Human Toxicology, University of Florida, Gainesville, Florida, United States of America
| | - Tara Sabo-Attwood
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- Center for Environmental and Human Toxicology, University of Florida, Gainesville, Florida, United States of America
| | - Anthony T. Maurelli
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| |
Collapse
|
23
|
Cruz MC, Sanguino-Jorquera D, Aparicio González M, Irazusta VP, Poma HR, Cristóbal HA, Rajal VB. Sewershed surveillance as a tool for smart management of a pandemic in threshold countries. Case study: Tracking SARS-CoV-2 during COVID-19 pandemic in a major urban metropolis in northwestern Argentina. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 862:160573. [PMID: 36460114 PMCID: PMC9705263 DOI: 10.1016/j.scitotenv.2022.160573] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/24/2022] [Accepted: 11/25/2022] [Indexed: 06/17/2023]
Abstract
Wastewater-based epidemiology is an economical and effective tool for monitoring the COVID-19 pandemic. In this study we proposed sampling campaigns that addressed spatial-temporal trends within a metropolitan area. This is a local study of detection and quantification of SARS-CoV-2 in wastewater during the onset, rise, and decline of COVID-19 cases in Salta city (Argentina) over the course of a twenty-one-week period (13 Aug to 30 Dec) in 2020. Wastewater samples were gathered from 13 sewer manholes specific to each sewershed catchment, prior to convergence or mixing with other sewer lines, resulting in samples specific to individual catchments with defined areas. The 13 sewershed catchments selected comprise 118,832 connections to the network throughout the city, representing 84.7 % (534,747 individuals) of the total population. The number of COVID19-related exposure and symptoms cases in each area were registered using an application developed for smartphones by the provincial government. Geographical coordinates provided by the devices were recorded, and consequently, it was possible to geolocalise all app-cases and track them down to which of the 13 sampling catchments belonged. RNA fragments of SARS-CoV-2 were detected in every site since the beginning of the monitoring, anticipating viral circulation in the population. Over the course of the 21-week study, the concentrations of SARS-CoV-2 ranged between 1.77 × 104 and 4.35 × 107 genome copies/L. There was a correspondence with the highest viral load in wastewater and the peak number of cases reported by the app for each catchment. The associations were evaluated with correlation analysis. The viral loads of SARS-CoV-2 in wastewater were a feasible means to describe the trends of COVID-19 infections. Surveillance at sewershed scale, provided reliable and strategic information that could be used by local health stakeholders to manage the COVID-19 pandemic.
Collapse
Affiliation(s)
- Mercedes Cecilia Cruz
- Instituto de Investigaciones para la Industria Química (INIQUI), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), Av. Bolivia 5150, 4400 Salta, Argentina.
| | - Diego Sanguino-Jorquera
- Instituto de Investigaciones para la Industria Química (INIQUI), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), Av. Bolivia 5150, 4400 Salta, Argentina
| | - Mónica Aparicio González
- Instituto de Investigaciones para la Industria Química (INIQUI), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), Av. Bolivia 5150, 4400 Salta, Argentina
| | - Verónica Patricia Irazusta
- Instituto de Investigaciones para la Industria Química (INIQUI), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), Av. Bolivia 5150, 4400 Salta, Argentina; Facultad de Ciencias Naturales, UNSa, Salta, Argentina
| | - Hugo Ramiro Poma
- Instituto de Investigaciones para la Industria Química (INIQUI), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), Av. Bolivia 5150, 4400 Salta, Argentina
| | - Héctor Antonio Cristóbal
- Instituto de Investigaciones para la Industria Química (INIQUI), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), Av. Bolivia 5150, 4400 Salta, Argentina; Facultad de Ciencias Naturales, UNSa, Salta, Argentina
| | - Verónica Beatriz Rajal
- Instituto de Investigaciones para la Industria Química (INIQUI), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), Av. Bolivia 5150, 4400 Salta, Argentina; Facultad de Ingeniería, UNSa, Salta, Argentina; Singapore Centre for Environmental Life Sciences Engineering (SCELSE), Nanyang Technological University, Singapore, Singapore.
| |
Collapse
|
24
|
Acosta N, Bautista MA, Waddell BJ, Du K, McCalder J, Pradhan P, Sedaghat N, Papparis C, Beaudet AB, Chen J, Van Doorn J, Xiang K, Chan L, Vivas L, Low K, Lu X, Lee J, Westlund P, Chekouo T, Dai X, Cabaj J, Bhatnagar S, Ruecker N, Achari G, Clark RG, Pearce C, Harrison JJ, Meddings J, Leal J, Ellison J, Missaghi B, Kanji JN, Larios O, Rennert‐May E, Kim J, Hrudey SE, Lee BE, Pang X, Frankowski K, Conly J, Hubert CRJ, Parkins MD. Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks. J Med Virol 2023; 95:e28442. [PMID: 36579780 PMCID: PMC9880705 DOI: 10.1002/jmv.28442] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/20/2022] [Accepted: 12/26/2022] [Indexed: 12/30/2022]
Abstract
Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with >2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to nonoutbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals.
Collapse
Affiliation(s)
- Nicole Acosta
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada
| | | | - Barbara J. Waddell
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada
| | - Kristine Du
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada
| | - Janine McCalder
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada,Department of Biological SciencesUniversity of CalgaryCalgaryCanada
| | - Puja Pradhan
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada,Department of Biological SciencesUniversity of CalgaryCalgaryCanada
| | - Navid Sedaghat
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada,Department of Biological SciencesUniversity of CalgaryCalgaryCanada
| | - Chloe Papparis
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada,Department of Biological SciencesUniversity of CalgaryCalgaryCanada
| | | | - Jianwei Chen
- Department of Biological SciencesUniversity of CalgaryCalgaryCanada
| | | | - Kevin Xiang
- Department of Biological SciencesUniversity of CalgaryCalgaryCanada
| | - Leslie Chan
- Department of Biological SciencesUniversity of CalgaryCalgaryCanada
| | - Laura Vivas
- Department of Biological SciencesUniversity of CalgaryCalgaryCanada
| | - Kashtin Low
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada
| | - Xuewen Lu
- Department of Mathematics and StatisticsUniversity of CalgaryCalgaryCanada
| | - Jangwoo Lee
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada
| | | | - Thierry Chekouo
- Department of Mathematics and StatisticsUniversity of CalgaryCalgaryCanada,Division of Biostatistics, School of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Xiaotian Dai
- Department of Mathematics and StatisticsUniversity of CalgaryCalgaryCanada
| | - Jason Cabaj
- Department of Community Health SciencesUniversity of CalgaryCalgaryCanada,Department of MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada,Provincial Population & Public HealthAlberta Health ServicesCalgaryCanada,O'Brien Institute for Public HealthUniversity of CalgaryCalgaryCanada
| | - Srijak Bhatnagar
- Faculty of Science and TechnologyAthabasca UniversityAthabascaAlbertaCanada
| | | | - Gopal Achari
- Department of Civil EngineeringUniversity of CalgaryCalgaryCanada
| | - Rhonda G. Clark
- Department of Biological SciencesUniversity of CalgaryCalgaryCanada
| | - Craig Pearce
- Infection Prevention and ControlAlberta Health ServicesCalgaryCanada
| | - Joe J. Harrison
- Department of Biological SciencesUniversity of CalgaryCalgaryCanada,Snyder Institute for Chronic DiseasesUniversity of Calgary and Alberta Health ServicesCalgaryCanada
| | - Jon Meddings
- Department of MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada
| | - Jenine Leal
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada,Department of Community Health SciencesUniversity of CalgaryCalgaryCanada,O'Brien Institute for Public HealthUniversity of CalgaryCalgaryCanada,Infection Prevention and ControlAlberta Health ServicesCalgaryCanada
| | - Jennifer Ellison
- Infection Prevention and ControlAlberta Health ServicesCalgaryCanada
| | - Bayan Missaghi
- Department of MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada,Infection Prevention and ControlAlberta Health ServicesCalgaryCanada
| | - Jamil N. Kanji
- Department of MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada,Department of Laboratory Medicine and PathologyUniversity of AlbertaEdmontonAlbertaCanada,Alberta Precision Laboratories, Public Health LaboratoryAlberta Health ServicesEdmontonAlbertaCanada,Department of Pathology and Laboratory MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada
| | - Oscar Larios
- Department of MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada,Infection Prevention and ControlAlberta Health ServicesCalgaryCanada,Alberta Precision Laboratories, Public Health LaboratoryAlberta Health ServicesEdmontonAlbertaCanada
| | - Elissa Rennert‐May
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada,Department of Community Health SciencesUniversity of CalgaryCalgaryCanada,Department of MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada,O'Brien Institute for Public HealthUniversity of CalgaryCalgaryCanada,Snyder Institute for Chronic DiseasesUniversity of Calgary and Alberta Health ServicesCalgaryCanada
| | - Joseph Kim
- Department of MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada,Infection Prevention and ControlAlberta Health ServicesCalgaryCanada
| | - Steve E. Hrudey
- Department of Laboratory Medicine and PathologyUniversity of AlbertaEdmontonAlbertaCanada,Department of Analytical and Environmental ToxicologyUniversity of AlbertaEdmontonAlbertaCanada
| | - Bonita E. Lee
- Department of PediatricsUniversity of AlbertaEdmontonAlbertaCanada,Women & Children's Health Research InstituteEdmontonAlbertaCanada,Li Ka Shing Institute of VirologyUniversity of AlbertaEdmontonAlbertaCanada
| | - Xiaoli Pang
- Department of Laboratory Medicine and PathologyUniversity of AlbertaEdmontonAlbertaCanada,Alberta Precision Laboratories, Public Health LaboratoryAlberta Health ServicesEdmontonAlbertaCanada,Li Ka Shing Institute of VirologyUniversity of AlbertaEdmontonAlbertaCanada
| | - Kevin Frankowski
- Advancing Canadian Water AssetsUniversity of CalgaryCalgaryCanada
| | - John Conly
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada,Department of MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada,O'Brien Institute for Public HealthUniversity of CalgaryCalgaryCanada,Infection Prevention and ControlAlberta Health ServicesCalgaryCanada,Snyder Institute for Chronic DiseasesUniversity of Calgary and Alberta Health ServicesCalgaryCanada,Department of Pathology and Laboratory MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada
| | | | - Michael D. Parkins
- Department of Microbiology, Immunology and Infectious DiseasesUniversity of CalgaryCalgaryCanada,Department of MedicineUniversity of Calgary and Alberta Health ServicesCalgaryCanada,Snyder Institute for Chronic DiseasesUniversity of Calgary and Alberta Health ServicesCalgaryCanada
| |
Collapse
|
25
|
Barber C, Crank K, Papp K, Innes GK, Schmitz BW, Chavez J, Rossi A, Gerrity D. Community-Scale Wastewater Surveillance of Candida auris during an Ongoing Outbreak in Southern Nevada. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:1755-1763. [PMID: 36656763 PMCID: PMC9893721 DOI: 10.1021/acs.est.2c07763] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 12/21/2022] [Accepted: 12/22/2022] [Indexed: 05/29/2023]
Abstract
Candida auris is an opportunistic fungal pathogen and an emerging global public health threat, given its high mortality among infected individuals, antifungal resistance, and persistence in healthcare environments. This study explored the applicability of wastewater surveillance for C. auris in a metropolitan area with reported outbreaks across multiple healthcare facilities. Influent or primary effluent samples were collected over 10 weeks from seven sewersheds in Southern Nevada. Pelleted solids were analyzed using an adapted quantitative polymerase chain reaction (qPCR) assay targeting the ITS2 region of the C. auris genome. Positive detection was observed in 72 of 91 samples (79%), with higher detection frequencies in sewersheds serving healthcare facilities involved in the outbreak (94 vs 20% sample positivity). Influent wastewater concentrations ranged from 2.8 to 5.7 log10 gene copies per liter (gc/L), and primary clarification achieved an average log reduction value (LRV) of 1.24 ± 0.34. Presumptive negative surface water and wastewater controls were non-detect. These results demonstrate that wastewater surveillance may assist in tracking the spread of C. auris and serve as an early warning tool for public health action. These findings provide the foundation for future application of wastewater-based epidemiology (WBE) to community- or facility-level surveillance of C. auris and other high consequence, healthcare-associated infectious agents.
Collapse
Affiliation(s)
- Casey Barber
- School
of Public Health, University of Nevada Las
Vegas, 4700 S. Maryland Parkway, Las Vegas, Nevada 89119, United States
- Southern
Nevada Water Authority, P.O. Box 99954, Las Vegas, Nevada 89193, United States
| | - Katherine Crank
- Southern
Nevada Water Authority, P.O. Box 99954, Las Vegas, Nevada 89193, United States
| | - Katerina Papp
- Southern
Nevada Water Authority, P.O. Box 99954, Las Vegas, Nevada 89193, United States
| | - Gabriel K. Innes
- Yuma
Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8th Street, Yuma, Arizona 85364, United States
| | - Bradley W. Schmitz
- Yuma
Center of Excellence for Desert Agriculture (YCEDA), University of Arizona, 6425 W. 8th Street, Yuma, Arizona 85364, United States
| | - Jorge Chavez
- Utah
Department of Health and Human Services, Utah Public Health Laboratory, 4431 South 2700 West, Taylorsville, Utah 84129, United States
| | - Alessandro Rossi
- Utah
Department of Health and Human Services, Utah Public Health Laboratory, 4431 South 2700 West, Taylorsville, Utah 84129, United States
| | - Daniel Gerrity
- Southern
Nevada Water Authority, P.O. Box 99954, Las Vegas, Nevada 89193, United States
| |
Collapse
|
26
|
Lott MEJ, Norfolk WA, Dailey CA, Foley AM, Melendez-Declet C, Robertson MJ, Rathbun SL, Lipp EK. Direct wastewater extraction as a simple and effective method for SARS-CoV-2 surveillance and COVID-19 community-level monitoring. FEMS MICROBES 2023; 4:xtad004. [PMID: 37333441 PMCID: PMC10117872 DOI: 10.1093/femsmc/xtad004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 11/23/2022] [Accepted: 01/11/2023] [Indexed: 10/22/2023] Open
Abstract
Wastewater surveillance has proven to be an effective tool to monitor the transmission and emergence of infectious agents at a community scale. Workflows for wastewater surveillance generally rely on concentration steps to increase the probability of detection of low-abundance targets, but preconcentration can substantially increase the time and cost of analyses while also introducing additional loss of target during processing. To address some of these issues, we conducted a longitudinal study implementing a simplified workflow for SARS-CoV-2 detection from wastewater, using a direct column-based extraction approach. Composite influent wastewater samples were collected weekly for 1 year between June 2020 and June 2021 in Athens-Clarke County, Georgia, USA. Bypassing any concentration step, low volumes (280 µl) of influent wastewater were extracted using a commercial kit, and immediately analyzed by RT-qPCR for the SARS-CoV-2 N1 and N2 gene targets. SARS-CoV-2 viral RNA was detected in 76% (193/254) of influent samples, and the recovery of the surrogate bovine coronavirus was 42% (IQR: 28%, 59%). N1 and N2 assay positivity, viral concentration, and flow-adjusted daily viral load correlated significantly with per-capita case reports of COVID-19 at the county-level (ρ = 0.69-0.82). To compensate for the method's high limit of detection (approximately 106-107 copies l-1 in wastewater), we extracted multiple small-volume replicates of each wastewater sample. With this approach, we detected as few as five cases of COVID-19 per 100 000 individuals. These results indicate that a direct-extraction-based workflow for SARS-CoV-2 wastewater surveillance can provide informative and actionable results.
Collapse
Affiliation(s)
- Megan E J Lott
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - William A Norfolk
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Cody A Dailey
- Department of Epidemiology and Biostatistics, University of Georgia, 101 Buck Road, Athens, GA 30606, United States
| | - Amelia M Foley
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Carolina Melendez-Declet
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Megan J Robertson
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| | - Stephen L Rathbun
- Department of Epidemiology and Biostatistics, University of Georgia, 101 Buck Road, Athens, GA 30606, United States
| | - Erin K Lipp
- Department of Environmental Health Science, University of Georgia, 150 East Green Street, Athens, GA 30602, United States
| |
Collapse
|
27
|
Hopkins L, Persse D, Caton K, Ensor K, Schneider R, McCall C, Stadler LB. Citywide wastewater SARS-CoV-2 levels strongly correlated with multiple disease surveillance indicators and outcomes over three COVID-19 waves. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 855:158967. [PMID: 36162580 PMCID: PMC9507781 DOI: 10.1016/j.scitotenv.2022.158967] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
Public health surveillance systems for COVID-19 are multifaceted and include multiple indicators reflective of different aspects of the burden and spread of the disease in a community. With the emergence of wastewater disease surveillance as a powerful tool to track infection dynamics of SARS-CoV-2, there is a need to integrate and validate wastewater information with existing disease surveillance systems and demonstrate how it can be used as a routine surveillance tool. A first step toward integration is showing how it relates to other disease surveillance indicators and outcomes, such as case positivity rates, syndromic surveillance data, and hospital bed use rates. Here, we present an 86-week long surveillance study that covers three major COVID-19 surges. City-wide SARS-CoV-2 RNA viral loads in wastewater were measured across 39 wastewater treatment plants and compared to other disease metrics for the city of Houston, TX. We show that wastewater levels are strongly correlated with positivity rate, syndromic surveillance rates of COVID-19 visits, and COVID-19-related general bed use rates at hospitals. We show that the relative timing of wastewater relative to each indicator shifted across the pandemic, likely due to a multitude of factors including testing availability, health-seeking behavior, and changes in viral variants. Next, we show that individual WWTPs led city-wide changes in SARS-CoV-2 viral loads, indicating a distributed monitoring system could be used to enhance the early-warning capability of a wastewater monitoring system. Finally, we describe how the results were used in real-time to inform public health response and resource allocation.
Collapse
Affiliation(s)
- Loren Hopkins
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America; Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, United States of America
| | - David Persse
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America; Department of Medicine and Surgery, Baylor College of Medicine, Houston, TX, United States of America; City of Houston Emergency Medical Services, Houston, TX, United States of America
| | - Kelsey Caton
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America
| | - Katherine Ensor
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, United States of America
| | - Rebecca Schneider
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America
| | - Camille McCall
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, United States of America
| | - Lauren B Stadler
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, United States of America.
| |
Collapse
|
28
|
Boeraș I, Curtean-Bănăduc A, Bănăduc D, Cioca G. Anthropogenic Sewage Water Circuit as Vector for SARS-CoV-2 Viral ARN Transport and Public Health Assessment, Monitoring and Forecasting-Sibiu Metropolitan Area (Transylvania/Romania) Study Case. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:11725. [PMID: 36141997 PMCID: PMC9517256 DOI: 10.3390/ijerph191811725] [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: 06/15/2022] [Revised: 09/08/2022] [Accepted: 09/13/2022] [Indexed: 06/16/2023]
Abstract
Water is a risk factor for epidemics of waterborne diseases with effects on human health. In 2019, new viral pneumonia cases occurred in China and spread worldwide. The aim of this study was to assess the feasibility and accuracy of a wastewater-based epidemiological (WBE) monitoring tool in a SARS-CoV-2 hot spot (Sibiu City metropolitan area), namely to highlight the correlation between the number of infections on the days of sampling and the amount of viral RNA detected in wastewater. Wastewater samples were collected once a week, and viral RNA was extracted and quantified. In parallel, the daily number of SARS-CoV-2 infections was obtained from the local council. The correlation between the number of infections and viruses detected in sewage was measured by Pearson correlation coefficients. The results show the amount of viral RNA in the wastewater is directly correlated with the number of infections reported in the week up to the sampling day and also the number of infections reported for the sampling day. Moreover, correlation coefficients show the amount of viral RNA in wastewater increases in advance of the increase in reported infection cases. Therefore, WBE can be used as a tool for monitoring virus spread trends in human communities and can help anticipate the trend of this type of viral infection.
Collapse
Affiliation(s)
- Ioana Boeraș
- Applied Ecology Research Center, Faculty of Sciences, Lucian Blaga University of Sibiu, 550012 Sibiu, Romania
| | - Angela Curtean-Bănăduc
- Applied Ecology Research Center, Faculty of Sciences, Lucian Blaga University of Sibiu, 550012 Sibiu, Romania
| | - Doru Bănăduc
- Applied Ecology Research Center, Faculty of Sciences, Lucian Blaga University of Sibiu, 550012 Sibiu, Romania
| | - Gabriela Cioca
- Preclinical Department, Faculty of Medicine, Lucian Blaga University of Sibiu, 550169 Sibiu, Romania
| |
Collapse
|
29
|
Hubert CRJ, Acosta N, Waddell BJM, Hasing ME, Qiu Y, Fuzzen M, Harper NBJ, Bautista MA, Gao T, Papparis C, Van Doorn J, Du K, Xiang K, Chan L, Vivas L, Pradhan P, McCalder J, Low K, England WE, Kuzma D, Conly J, Ryan MC, Achari G, Hu J, Cabaj JL, Sikora C, Svenson L, Zelyas N, Servos M, Meddings J, Hrudey SE, Frankowski K, Parkins MD, Pang XL, Lee BE. Tracking Emergence and Spread of SARS-CoV-2 Omicron Variant in Large and Small Communities by Wastewater Monitoring in Alberta, Canada. Emerg Infect Dis 2022. [PMID: 35867051 DOI: 10.1101/2022.03.07.22272055] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2023] Open
Abstract
Wastewater monitoring of SARS-CoV-2 enables early detection and monitoring of the COVID-19 disease burden in communities and can track specific variants of concern. We determined proportions of the Omicron and Delta variants across 30 municipalities covering >75% of the province of Alberta (population 4.5 million), Canada, during November 2021-January 2022. Larger cities Calgary and Edmonton exhibited more rapid emergence of Omicron than did smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a medium-sized northern community that has many workers who fly in and out regularly. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden by late December, before the peak in newly diagnosed clinical cases throughout Alberta in mid-January. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of SARS-CoV-2 variants.
Collapse
|
30
|
Dai X, Champredon D, Fazil A, Mangat CS, Peterson SW, Mejia EM, Lu X, Chekouo T. Statistical framework to support the epidemiological interpretation of SARS-CoV-2 concentration in municipal wastewater. Sci Rep 2022; 12:13490. [PMID: 35931713 PMCID: PMC9355971 DOI: 10.1038/s41598-022-17543-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 07/27/2022] [Indexed: 11/23/2022] Open
Abstract
The ribonucleic acid (RNA) of the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is detectable in municipal wastewater as infected individuals can shed the virus in their feces. Viral concentration in wastewater can inform the severity of the COVID-19 pandemic but observations can be noisy and sparse and hence hamper the epidemiological interpretation. Motivated by a Canadian nationwide wastewater surveillance data set, unlike previous studies, we propose a novel Bayesian statistical framework based on the theories of functional data analysis to tackle the challenges embedded in the longitudinal wastewater monitoring data. By employing this framework to analyze the large-scale data set from the nationwide wastewater surveillance program covering 15 sampling sites across Canada, we successfully detect the true trends of viral concentration out of noisy and sparsely observed viral concentrations, and accurately forecast the future trajectory of viral concentrations in wastewater. Along with the excellent performance assessment using simulated data, this study shows that the proposed novel framework is a useful statistical tool and has a significant potential in supporting the epidemiological interpretation of noisy viral concentration measurements from wastewater samples in a real-life setting.
Collapse
Affiliation(s)
- Xiaotian Dai
- Department of Mathematics and Statistics, University of Calgary, Calgary, AB, Canada
| | - David Champredon
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada
| | - Aamir Fazil
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada
| | - Chand S Mangat
- One Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Shelley W Peterson
- One Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Edgard M Mejia
- One Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Xuewen Lu
- Department of Mathematics and Statistics, University of Calgary, Calgary, AB, Canada
| | - Thierry Chekouo
- Department of Mathematics and Statistics, University of Calgary, Calgary, AB, Canada.
| |
Collapse
|
31
|
Hubert CRJ, Acosta N, Waddell BJM, Hasing ME, Qiu Y, Fuzzen M, Harper NBJ, Bautista MA, Gao T, Papparis C, Van Doorn J, Du K, Xiang K, Chan L, Vivas L, Pradhan P, McCalder J, Low K, England WE, Kuzma D, Conly J, Ryan MC, Achari G, Hu J, Cabaj JL, Sikora C, Svenson L, Zelyas N, Servos M, Meddings J, Hrudey SE, Frankowski K, Parkins MD, Pang XL, Lee BE. Tracking Emergence and Spread of SARS-CoV-2 Omicron Variant in Large and Small Communities by Wastewater Monitoring in Alberta, Canada. Emerg Infect Dis 2022; 28:1770-1776. [PMID: 35867051 PMCID: PMC9423933 DOI: 10.3201/eid2809.220476] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Wastewater monitoring of SARS-CoV-2 enables early detection and monitoring of the COVID-19 disease burden in communities and can track specific variants of concern. We determined proportions of the Omicron and Delta variants across 30 municipalities covering >75% of the province of Alberta (population 4.5 million), Canada, during November 2021-January 2022. Larger cities Calgary and Edmonton exhibited more rapid emergence of Omicron than did smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a medium-sized northern community that has many workers who fly in and out regularly. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden by late December, before the peak in newly diagnosed clinical cases throughout Alberta in mid-January. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of SARS-CoV-2 variants.
Collapse
|