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Tiwari A, Radu E, Kreuzinger N, Ahmed W, Pitkänen T. Key considerations for pathogen surveillance in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 945:173862. [PMID: 38876348 DOI: 10.1016/j.scitotenv.2024.173862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 06/03/2024] [Accepted: 06/06/2024] [Indexed: 06/16/2024]
Abstract
Wastewater surveillance (WWS) has received significant attention as a rapid, sensitive, and cost-effective tool for monitoring various pathogens in a community. WWS is employed to assess the spatial and temporal trends of diseases and identify their early appearances and reappearances, as well as to detect novel and mutated variants. However, the shedding rates of pathogens vary significantly depending on factors such as disease severity, the physiology of affected individuals, and the characteristics of pathogen. Furthermore, pathogens may exhibit differential fate and decay kinetics in the sewerage system. Variable shedding rates and decay kinetics may affect the detection of pathogens in wastewater. This may influence the interpretation of results and the conclusions of WWS studies. When selecting a pathogen for WWS, it is essential to consider it's specific characteristics. If data are not readily available, factors such as fate, decay, and shedding rates should be assessed before conducting surveillance. Alternatively, these factors can be compared to those of similar pathogens for which such data are available.
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Affiliation(s)
- Ananda Tiwari
- Finnish Institute for Health and Welfare, Department of Health Security, Kuopio, Finland; University of Helsinki, Faculty of Veterinary Medicine, Helsinki, Finland.
| | - Elena Radu
- Institute for Water Quality and Resource Management, Vienna University of Technology, Karlsplatz 13/226, 1040 Vienna, Austria; Stefan S. Nicolau Institute of Virology, Department of Cellular and Molecular Pathology, 285 Mihai Bravu Avenue, 030304 Bucharest, Romania; University of Medicine and Pharmacy Carol Davila, Department of Virology, 37 Dionisie Lupu Street, 020021 Bucharest, Romania.
| | - Norbert Kreuzinger
- Institute for Water Quality and Resource Management, Vienna University of Technology, Karlsplatz 13/226, 1040 Vienna, Austria.
| | - Warish Ahmed
- CSIRO Environment, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia.
| | - Tarja Pitkänen
- Finnish Institute for Health and Welfare, Department of Health Security, Kuopio, Finland; University of Helsinki, Faculty of Veterinary Medicine, Helsinki, Finland.
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Cha G, Huang Y, Graham KE, Luo A, Chen W, Hatt JK, Konstantinidis KT, Xie X. Cold-chain free nucleic acid preservation using porous super-absorbent polymer (PSAP) beads to facilitate wastewater surveillance. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 939:173468. [PMID: 38788933 DOI: 10.1016/j.scitotenv.2024.173468] [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: 01/10/2024] [Revised: 05/19/2024] [Accepted: 05/21/2024] [Indexed: 05/26/2024]
Abstract
The instability of viral targets including SARS-CoV-2 in sewage is an important challenge in wastewater monitoring projects. The unrecognized interruptions in the 'cold-chain' transport from the sample collection to RNA quantification in the laboratory may undermine the accurate quantification of the virus. In this study, bovine serum albumin (BSA)-modified porous superabsorbent polymer (PSAP) beads were applied to absorb raw sewage samples as a simple method for viral RNA preservation. The preservation efficiency for SARS-CoV-2 and pepper mild mottle virus (PMMoV) RNA were examined during storage for 14 days at 4 °C or room temperature against the control (no beads applied). While a non-significant difference was observed at 4 °C (∼80 % retention for both control and PSAP-treated sewage), the reduction of SARS-CoV-2 RNA concentrations was significantly lower in sewage retrieved from PSAP beads (25-40 % reduction) compared to control (>60 % reduction) at room temperature. On the other hand, the recovery of PMMoV, known for its high persistence in raw sewage, from PSAP beads or controls were consistently above 85 %, regardless of the storage temperature. Our results demonstrate the applicability of PSAP beads to wastewater-based epidemiology (WBE) projects for preservation of SARS-CoV-2 RNA in sewage, especially in remote settings with no refrigeration capabilities.
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Affiliation(s)
- Gyuhyon Cha
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Yixuan Huang
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Katherine E Graham
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Anjin Luo
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Wensi Chen
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Janet K Hatt
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | | | - Xing Xie
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
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Ribeiro AVC, Mannarino CF, Novo SPC, Prado T, Lermontov A, de Paula BB, Fumian TM, Miagostovich MP. Assessment of crAssphage as a biological variable for SARS-CoV-2 data normalization in wastewater surveillance. J Appl Microbiol 2024; 135:lxae177. [PMID: 39013607 DOI: 10.1093/jambio/lxae177] [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: 03/20/2024] [Revised: 07/09/2024] [Accepted: 07/15/2024] [Indexed: 07/18/2024]
Abstract
AIMS This study aimed to assess the use of cross-assembled phage (crAssphage) as an endogenous control employing a multivariate normalization analysis and its application as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) data normalizer. METHODS AND RESULTS A total of 188 twelve-hour composite raw sewage samples were obtained from eight wastewater treatment plants (WWTP) during a 1-year monitoring period. Employing the N1 and N2 target regions, SARS-CoV-2 RNA was detected in 94% (177) and 90% (170) of the samples, respectively, with a global median of 5 log10 genomic copies per liter (GC l-1). CrAssphage was detected in 100% of the samples, ranging from 8.29 to 10.43 log10 GC l-1, with a median of 9.46 ± 0.40 log10 GC l-1, presenting both spatial and temporal variabilities. CONCLUSIONS Although SARS-CoV-2 data normalization employing crAssphage revealed a correlation with clinical cases occurring during the study period, crAssphage normalization by the flow per capita per day of each WWTP increased this correlation, corroborating the importance of normalizing wastewater surveillance data in disease trend monitoring.
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Affiliation(s)
- André Vinicius Costa Ribeiro
- Department of Sanitation and Environmental Health, Sergio Arouca National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, Brazil
| | - Camille Ferreira Mannarino
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, Brazil
| | - Shênia Patrícia Corrêa Novo
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, Brazil
| | - Tatiana Prado
- Laboratory of Respiratory, Exanthematic, Enteroviruses and Viral Emergencies, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, Brazil
| | - André Lermontov
- Chemical and Biochemical Process Technology, School of Chemistry/Federal University of Rio de Janeiro - EQ/UFRJ, Rio de Janeiro 21941-909, Brazil
| | - Bruna Barbosa de Paula
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, Brazil
| | - Tulio Machado Fumian
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, Brazil
| | - Marize Pereira Miagostovich
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, Brazil
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Subroyen S, Pillay L, Bux F, Kumari S. Evaluating storage conditions and enhancement strategies on viral biomarker recovery for WBE applications. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2024; 90:213-224. [PMID: 39007315 DOI: 10.2166/wst.2024.203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 05/31/2024] [Indexed: 07/16/2024]
Abstract
Wastewater-based epidemiology (WBE) is a valuable disease surveillance tool. However, little is known on how factors such as transportation, storage, and wastewater characteristics influence the accuracy of the quantification methods. Hence, this study investigated the impact of storage temperatures and physicochemical characteristics of wastewater on SARS-CoV-2 and influenza A stability using droplet digital PCR. Additionally, strategies to enhance viral recovery were explored. Municipal influent wastewater stored between ±25 and -80 °C was assessed for a period of 84 days to determine viral degradation. Degradation up to 94.1% of influenza A and SARS-CoV-2 was observed in all samples with the highest at ±25 °C. Viral degradation was correlated to the changes in wastewater physicochemical characteristics. The low degradation observed of SARS-CoV-2 in the spiked pellets were indicative of viral adhesion to wastewater solids, which correlated with changes in pH. Ultrasonication frequencies ranging from 4 to 16 kHz, increased SARS-CoV-2 concentrations in the supernatant between 3.30 and 35.65%, indicating viral RNA attachment to wastewater solids. These results highlight the importance of additional pretreatment methods for maximizing RNA recovery from wastewater samples. Based on these findings, it was deduced that wastewater preservation studies are essential, and pretreatment should be included in the WBE methodology.
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Affiliation(s)
- Sueyanka Subroyen
- Institute for Water and Wastewater Technology, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa
| | - Leanne Pillay
- Institute for Water and Wastewater Technology, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa
| | - Faizal Bux
- Institute for Water and Wastewater Technology, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa
| | - Sheena Kumari
- Institute for Water and Wastewater Technology, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa E-mail:
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Mohring J, Leithäuser N, Wlazło J, Schulte M, Pilz M, Münch J, Küfer KH. Estimating the COVID-19 prevalence from wastewater. Sci Rep 2024; 14:14384. [PMID: 38909097 PMCID: PMC11193770 DOI: 10.1038/s41598-024-64864-1] [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: 11/03/2023] [Accepted: 06/13/2024] [Indexed: 06/24/2024] Open
Abstract
Wastewater based epidemiology has become a widely used tool for monitoring trends of concentrations of different pathogens, most notably and widespread of SARS-CoV-2. Therefore, in 2022, also in Rhineland-Palatinate, the Ministry of Science and Health has included 16 wastewater treatment sites in a surveillance program providing biweekly samples. However, the mere viral load data is subject to strong fluctuations and has limited value for political deciders on its own. Therefore, the state of Rhineland-Palatinate has commissioned the University Medical Center at Johannes Gutenberg University Mainz to conduct a representative cohort study called SentiSurv, in which an increasing number of up to 12,000 participants have been using sensitive antigen self-tests once or twice a week to test themselves for SARS-CoV-2 and report their status. This puts the state of Rhineland-Palatinate in the fortunate position of having time series of both, the viral load in wastewater and the prevalence of SARS-CoV-2 in the population. Our main contribution is a calibration study based on the data from 2023-01-08 until 2023-10-01 where we identified a scaling factor ( 0.208 ± 0.031 ) and a delay ( 5.07 ± 2.30 days) between the virus load in wastewater, normalized by the pepper mild mottle virus (PMMoV), and the prevalence recorded in the SentiSurv study. The relation is established by fitting an epidemiological model to both time series. We show how that can be used to estimate the prevalence when the cohort data is no longer available and how to use it as a forecasting instrument several weeks ahead of time. We show that the calibration and forecasting quality and the resulting factors depend strongly on how wastewater samples are normalized.
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Affiliation(s)
- Jan Mohring
- Fraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany.
| | - Neele Leithäuser
- Fraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany
| | - Jarosław Wlazło
- Fraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany
| | - Marvin Schulte
- Fraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany
| | - Maximilian Pilz
- Fraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany
| | - Johanna Münch
- Fraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany
| | - Karl-Heinz Küfer
- Fraunhofer Institute for Industrial Mathematics, 67663, Kaiserslautern, Germany
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6
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Champredon D, Papst I, Yusuf W. ern: An [Formula: see text] package to estimate the effective reproduction number using clinical and wastewater surveillance data. PLoS One 2024; 19:e0305550. [PMID: 38905266 PMCID: PMC11192340 DOI: 10.1371/journal.pone.0305550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 05/31/2024] [Indexed: 06/23/2024] Open
Abstract
The effective reproduction number, [Formula: see text], is an important epidemiological metric used to assess the state of an epidemic, as well as the effectiveness of public health interventions undertaken in response. When [Formula: see text] is above one, it indicates that new infections are increasing, and thus the epidemic is growing, while an [Formula: see text] is below one indicates that new infections are decreasing, and so the epidemic is under control. There are several established software packages that are readily available to statistically estimate [Formula: see text] using clinical surveillance data. However, there are comparatively few accessible tools for estimating [Formula: see text] from pathogen wastewater concentration, a surveillance data stream that cemented its utility during the COVID-19 pandemic. We present the [Formula: see text] package ern that aims to perform the estimation of the effective reproduction number from real-world wastewater or aggregated clinical surveillance data in a user-friendly way.
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Affiliation(s)
- David Champredon
- Public Health Risk Sciences Division, Public Health Agency of Canada, National Microbiology Laboratory, Guelph, Ontario, Canada
| | - Irena Papst
- Public Health Risk Sciences Division, Public Health Agency of Canada, National Microbiology Laboratory, Guelph, Ontario, Canada
| | - Warsame Yusuf
- Public Health Risk Sciences Division, Public Health Agency of Canada, National Microbiology Laboratory, Guelph, Ontario, Canada
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Jin S, Tay M, Ng LC, Wong JCC, Cook AR. Combining wastewater surveillance and case data in estimating the time-varying effective reproduction number. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 928:172469. [PMID: 38621542 DOI: 10.1016/j.scitotenv.2024.172469] [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: 12/24/2023] [Revised: 03/25/2024] [Accepted: 04/11/2024] [Indexed: 04/17/2024]
Abstract
Wastewater surveillance has been increasingly acknowledged as a useful tool for monitoring transmission dynamics of infections of public health concern, including the coronavirus disease (COVID-19). While a range of models have been proposed to estimate the time-varying effective reproduction number (Rt) utilizing clinical data, few have harnessed the viral concentration in wastewater samples to do so, leaving uncertainties about the potential precision gains with its use. In this study, we developed a Bayesian hierarchical model which simultaneously reconstructed the latent infection trajectory and estimated Rt. Focusing on the 2022 and early 2023 COVID-19 transmission trends in Singapore, where mass community wastewater surveillance has become routine, we performed estimations using a spectrum of data sources, including reported case counts, hospital admissions, deaths, and wastewater viral loads. We further explored the performance of our wastewater model across various scenarios with different sampling strategies. The results showed consistent estimates derived from models employing diverse data streams, while models incorporating more wastewater samples exhibited greater uncertainty and variation in the inferred Rts. Additionally, our analysis revealed prominent day-of-the-week effect in reported case counts and substantial temporal variations in ascertainment rates. In response to these findings, we advocate for a hybrid approach leveraging both clinical and wastewater surveillance data to account for changes in case-ascertainment rates. Furthermore, our study demonstrates the possibility of reducing sampling frequency or sample size without compromising estimation accuracy for Rt, highlighting the potential for optimizing resource allocation in surveillance efforts while maintaining robust insights into the transmission dynamics of infectious diseases.
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Affiliation(s)
- Shihui Jin
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Martin Tay
- Environmental Health Institute, National Environment Agency, Singapore
| | - Lee Ching Ng
- Environmental Health Institute, National Environment Agency, Singapore; School of Biological Sciences, Nanyang Technological University, Singapore
| | | | - Alex R Cook
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore; Department of Statistics and Data Science, National University of Singapore, Singapore.
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Fondriest M, Vaccari L, Aldrovandi F, De Lellis L, Ferretti F, Fiorentino C, Mari E, Mascolo MG, Minelli L, Perlangeli V, Bortone G, Pandolfi P, Colacci A, Ranzi A. Wastewater-Based Epidemiology for SARS-CoV-2 in Northern Italy: A Spatiotemporal Model. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:741. [PMID: 38928987 PMCID: PMC11203876 DOI: 10.3390/ijerph21060741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/23/2024] [Accepted: 05/31/2024] [Indexed: 06/28/2024]
Abstract
The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring the SARS-CoV-2 prevalence in a city in northern Italy from October 2021 to May 2023. Based on a previously used deterministic model, this study proposed a variation to account for the population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated using healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred during the period considered, demonstrating the ability of the model to predict the relevant fluctuations in the number of cases. The population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied to compare the virus load values across cities with different population demographics and sewer network structures, improving the comparability of the WBE data for effective surveillance and intervention strategies.
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Affiliation(s)
- Matilde Fondriest
- Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, 40139 Bologna, Italy; (L.V.); (E.M.); (M.G.M.); (G.B.); (A.C.); (A.R.)
| | - Lorenzo Vaccari
- Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, 40139 Bologna, Italy; (L.V.); (E.M.); (M.G.M.); (G.B.); (A.C.); (A.R.)
| | - Federico Aldrovandi
- Alma Mater Institute on Healthy Planet, Department of Biological, Geological and Environmental Sciences, University of Bologna, 40138 Bologna, Italy;
| | | | - Filippo Ferretti
- Local Health Authority of Bologna, Department of Public Health, 40124 Bologna, Italy; (F.F.); (C.F.); (V.P.); (P.P.)
| | - Carmine Fiorentino
- Local Health Authority of Bologna, Department of Public Health, 40124 Bologna, Italy; (F.F.); (C.F.); (V.P.); (P.P.)
| | - Erica Mari
- Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, 40139 Bologna, Italy; (L.V.); (E.M.); (M.G.M.); (G.B.); (A.C.); (A.R.)
- Local Health Authority of Bologna, Department of Public Health, 40124 Bologna, Italy; (F.F.); (C.F.); (V.P.); (P.P.)
| | - Maria Grazia Mascolo
- Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, 40139 Bologna, Italy; (L.V.); (E.M.); (M.G.M.); (G.B.); (A.C.); (A.R.)
| | | | - Vincenza Perlangeli
- Local Health Authority of Bologna, Department of Public Health, 40124 Bologna, Italy; (F.F.); (C.F.); (V.P.); (P.P.)
| | - Giuseppe Bortone
- Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, 40139 Bologna, Italy; (L.V.); (E.M.); (M.G.M.); (G.B.); (A.C.); (A.R.)
| | - Paolo Pandolfi
- Local Health Authority of Bologna, Department of Public Health, 40124 Bologna, Italy; (F.F.); (C.F.); (V.P.); (P.P.)
| | - Annamaria Colacci
- Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, 40139 Bologna, Italy; (L.V.); (E.M.); (M.G.M.); (G.B.); (A.C.); (A.R.)
| | - Andrea Ranzi
- Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, 40139 Bologna, Italy; (L.V.); (E.M.); (M.G.M.); (G.B.); (A.C.); (A.R.)
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Rashid A, Ayub M, Gao X, Khattak SA, Ali L, Li C, Ahmad A, Khan S, Rinklebe J, Ahmad P. Hydrogeochemical characteristics, stable isotopes, positive matrix factorization, source apportionment, and health risk of high fluoride groundwater in semiarid region. JOURNAL OF HAZARDOUS MATERIALS 2024; 469:134023. [PMID: 38492393 DOI: 10.1016/j.jhazmat.2024.134023] [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: 01/30/2024] [Revised: 03/02/2024] [Accepted: 03/11/2024] [Indexed: 03/18/2024]
Abstract
Chronic exposure to high fluoride (F-) levels in groundwater causes community fluorosis and non-carcinogenic health concerns in local people. This study described occurrence, dental fluorosis, and origin of high F-groundwater using δ2H and δ18O isotopes at semiarid Gilgit, Pakistan. Therefore, groundwater (n = 85) was collected and analyzed for F- concentrations using ion-chromatography. The lowest F- concentration was 0.4 mg/L and the highest 6.8 mg/L. F- enrichment is linked with higher pH, NaHCO3, NaCl, δ18O, Na+, HCO3-, and depleted Ca+2 aquifers. The depleted δ2H and δ18O values indicated precipitation and higher values represented the evaporation effect. Thermodynamic considerations of fluorite minerals showed undersaturation, revealing that other F-bearing minerals viz. biotite and muscovite were essential in F- enrichment in groundwater. Positive matrix factorization (PMF) and principal component analysis multilinear regression (PCAMLR) models were used to determine four-factor solutions for groundwater contamination. The PMF model results were accurate and reliable compared with those of the PCAMLR model, which compiled the overlapping results. Therefore, 28.3% exceeded the WHO permissible limit of 1.5 mg/L F-. Photomicrographs of granite rocks showed enriched F-bearing minerals that trigger F- in groundwater. The community fluorosis index values were recorded at > 0.6, revealing community fluorosis and unsuitability of groundwater for drinking.
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Affiliation(s)
- Abdur Rashid
- State Key Laboratory of Biogeology and Environmental Geology, School of Environmental Studies, China University of Geosciences, Wuhan 430074, PR China; National Centre of Excellence in Geology, University of Peshawar, 25130, Pakistan.
| | - Muhammad Ayub
- Department of Botany Hazara University, Mansehra PO 21300 Pakistan
| | - Xubo Gao
- State Key Laboratory of Biogeology and Environmental Geology, School of Environmental Studies, China University of Geosciences, Wuhan 430074, PR China.
| | - Seema Anjum Khattak
- National Centre of Excellence in Geology, University of Peshawar, 25130, Pakistan
| | - Liaqat Ali
- National Centre of Excellence in Geology, University of Peshawar, 25130, Pakistan
| | - Chengcheng Li
- State Key Laboratory of Biogeology and Environmental Geology, School of Environmental Studies, China University of Geosciences, Wuhan 430074, PR China
| | - Ajaz Ahmad
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia
| | - Sardar Khan
- Department of Environmental Sciences, University of Peshawar, PO 25120, Pakistan
| | - Jörg Rinklebe
- University of Wuppertal, School of Architecture and Civil Engineering, Laboratory of Soil, and Groundwater-Management, Pauluskirchstraße 7, 42285 Wuppertal, Germany
| | - Parvaiz Ahmad
- Department of Botany, GDC, Pulwama 192301, Jammu and Kashmir, India
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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.
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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
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11
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Li Y, Ash K, Alamilla I, Joyner D, Williams DE, McKay PJ, Green B, DeBlander S, North C, Kara-Murdoch F, Swift C, Hazen TC. COVID-19 trends at the University of Tennessee: predictive insights from raw sewage SARS-CoV-2 detection and evaluation and PMMoV as an indicator for human waste. Front Microbiol 2024; 15:1379194. [PMID: 38605711 PMCID: PMC11007199 DOI: 10.3389/fmicb.2024.1379194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 03/19/2024] [Indexed: 04/13/2024] Open
Abstract
Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring the prevalence of SARS-CoV-2 on university campuses. However, concerns about effectiveness of raw sewage as a COVID-19 early warning system still exist, and it's not clear how useful normalization by simultaneous comparison of Pepper Mild Mottle Virus (PMMoV) is in addressing variations resulting from fecal discharge dilution. This study aims to contribute insights into these aspects by conducting an academic-year field trial at the student residences on the University of Tennessee, Knoxville campus, raw sewage. This was done to investigate the correlations between SARS-CoV-2 RNA load, both with and without PMMoV normalization, and various parameters, including active COVID-19 cases, self-isolations, and their combination among all student residents. Significant positive correlations between SARS-CoV-2 RNA load a week prior, during the monitoring week, and the subsequent week with active cases. Despite these correlations, normalization by PMMoV does not enhance these associations. These findings suggest the potential utility of SARS-CoV-2 RNA load as an early warning indicator and provide valuable insights into the application and limitations of WBE for COVID-19 surveillance specifically within the context of raw sewage on university campuses.
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Affiliation(s)
- Ye Li
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
| | - Kurt Ash
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | | | - Dominique Joyner
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
| | - Daniel Edward Williams
- Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States
| | - Peter J. McKay
- Battelle Memorial Institute, Columbus, OH, United States
| | - Brianna Green
- Department of Microbiology, University of Tennessee, Knoxville, TN, United States
| | - Sydney DeBlander
- College of Natural Science, Michigan State University, East Lansing, MI, United States
| | - Carman North
- Student Health Center, University of Tennessee, Knoxville, TN, United States
| | - Fadime Kara-Murdoch
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
- Battelle Memorial Institute, Columbus, OH, United States
- Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States
| | - Cynthia Swift
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
- Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States
| | - Terry C. Hazen
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
- Department of Microbiology, University of Tennessee, Knoxville, TN, United States
- Department of Earth and Planetary Sciences, University of Tennessee, Knoxville, TN, United States
- Institute for a Secure and Sustainable Environment, University of Tennessee, Knoxville, TN, United States
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12
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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.
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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
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13
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Anupong S, Chadsuthi S, Hongsing P, Hurst C, Phattharapornjaroen P, Rad S.M. AH, Fernandez S, Huang AT, Vatanaprasan P, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Ngamwongsatit N, Badavath VN, Thuptimdang W, Leelahavanichkul A, Kanjanabuch T, Miyanaga K, Cui L, Nanbo A, Shibuya K, Kupwiwat R, Sano D, Furukawa T, Sei K, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, Ishikawa H, Amarasiri M, Modchang C, Wannigama DL. Exploring indoor and outdoor dust as a potential tool for detection and monitoring of COVID-19 transmission. iScience 2024; 27:109043. [PMID: 38375225 PMCID: PMC10875567 DOI: 10.1016/j.isci.2024.109043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 11/09/2023] [Accepted: 01/23/2024] [Indexed: 02/21/2024] Open
Abstract
This study investigated the potential of using SARS-CoV-2 viral concentrations in dust as an additional surveillance tool for early detection and monitoring of COVID-19 transmission. Dust samples were collected from 8 public locations in 16 districts of Bangkok, Thailand, from June to August 2021. SARS-CoV-2 RNA concentrations in dust were quantified, and their correlation with community case incidence was assessed. Our findings revealed a positive correlation between viral concentrations detected in dust and the relative risk of COVID-19. The highest risk was observed with no delay (0-day lag), and this risk gradually decreased as the lag time increased. We observed an overall decline in viral concentrations in public places during lockdown, closely associated with reduced human mobility. The effective reproduction number for COVID-19 transmission remained above one throughout the study period, suggesting that transmission may persist in locations beyond public areas even after the lockdown measures were in place.
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Affiliation(s)
- Suparinthon Anupong
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Sudarat Chadsuthi
- Department of Physics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
| | - Parichart Hongsing
- Mae Fah Luang University Hospital, Chiang Rai, Thailand
- School of Integrative Medicine, Mae Fah Luang University, Chiang Rai, Thailand
| | - Cameron Hurst
- Molly Wardaguga Research Centre, Charles Darwin University, Brisbane, QLD, Australia
- Statistics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Phatthranit Phattharapornjaroen
- Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
- Institute of Clinical Sciences, Department of Surgery, Sahlgrenska Academy, Gothenburg University, 40530 Gothenburg, Sweden
| | - Ali Hosseini Rad S.M.
- Department of Microbiology and Immunology, University of Otago, Dunedin, Otago 9010, New Zealand
- Center of Excellence in Immunology and Immune-Mediated Diseases, Chulalongkorn University, Bangkok 10330, Thailand
| | - Stefan Fernandez
- Department of Virology, U.S. Army Medical Directorate, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Angkana T. Huang
- Department of Virology, U.S. Army Medical Directorate, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
- Department of Genetics, University of Cambridge, Cambridge, UK
| | | | - Thammakorn Saethang
- Department of Computer Science, Faculty of Science, Kasetsart University, Bangkok, Thailand
| | - Sirirat Luk-in
- Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand
| | - Robin James Storer
- Office of Research Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Puey Ounjai
- Department of Biology, Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Naveen Kumar Devanga Ragupathi
- Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield, UK
- Biofilms and Antimicrobial Resistance Consortium of ODA Receiving Countries, The University of Sheffield, Sheffield, UK
- Division of Microbial Interactions, Department of Research and Development, Bioberrys Healthcare and Research Centre, Vellore 632009, India
| | - Phitsanuruk Kanthawee
- Public Health Major, School of Health Science, Mae Fah Luang University, Chiang Rai 57100, Thailand
| | - Natharin Ngamwongsatit
- Department of Clinical Sciences and Public Health, Faculty of Veterinary Science, Mahidol University, Nakhon Pathom, Thailand
| | - Vishnu Nayak Badavath
- School of Pharmacy & Technology Management, SVKM’s Narsee Monjee Institute of Management Studies (NMIMS), Hyderabad 509301, India
| | - Wanwara Thuptimdang
- Institute of Biomedical Engineering, Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand
| | - Asada Leelahavanichkul
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Translational Research in Inflammation and Immunology Research Unit (TRIRU), Department of Microbiology, Chulalongkorn University, Bangkok, Thailand
| | - Talerngsak Kanjanabuch
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Kidney Metabolic Disorders, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Dialysis Policy and Practice Program (DiP3), School of Global Health, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Peritoneal Dialysis Excellence Center, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Kazuhiko Miyanaga
- Division of Bacteriology, School of Medicine, Jichi Medical University, Tochigi, Japan
| | - Longzhu Cui
- Division of Bacteriology, School of Medicine, Jichi Medical University, Tochigi, Japan
| | - Asuka Nanbo
- The National Research Center for the Control and Prevention of Infectious Diseases, Nagasaki University, Nagasaki, Japan
| | - Kenji Shibuya
- Tokyo Foundation for Policy Research, Minato-ku, Tokyo, Japan
| | - Rosalyn Kupwiwat
- Department of Dermatology. Faculty of Medicine Siriraj Hospital. Mahidol University, Bangkok, Thailand
| | - Daisuke Sano
- Department of Frontier Sciences for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Sendai, Miyagi, Japan
- Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Miyagi, Japan
| | - Takashi Furukawa
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Minato City, Tokyo 108-8641, Japan
| | - Kazunari Sei
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Minato City, Tokyo 108-8641, Japan
| | - Paul G. Higgins
- Institute for Medical Microbiology, Immunology and Hygiene, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Centre for Infection Research, Partner Site Bonn-Cologne, Cologne, Germany
| | - Anthony Kicic
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, University of Western Australia, Nedlands WA 6009, Australia
- Centre for Cell Therapy and Regenerative Medicine, Medical School, The University of Western Australia, Nedlands, WA 6009, Australia
- Department of Respiratory and Sleep Medicine, Perth Children’s Hospital, Nedlands WA 6009, Australia
- School of Population Health, Curtin University, Bentley WA 6102, Australia
| | | | - Tanittha Chatsuwan
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Antimicrobial Resistance and Stewardship, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Sam Trowsdale
- Department of Environmental Science, University of Auckland, Auckland 1010, New Zealand
| | - Shuichi Abe
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Hitoshi Ishikawa
- Yamagata Prefectural University of Health Sciences, Kamiyanagi, Yamagata 990-2212, Japan
| | - Mohan Amarasiri
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Minato City, Tokyo 108-8641, Japan
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
- Centre of Excellence in Mathematics, MHESI, Bangkok 10400, Thailand
- Thailand Center of Excellence in Physics, Ministry of Higher Education, Science, Research and Innovation, 328 Si Ayutthaya Road, Bangkok 10400, Thailand
| | - Dhammika Leshan Wannigama
- Biofilms and Antimicrobial Resistance Consortium of ODA Receiving Countries, The University of Sheffield, Sheffield, UK
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Antimicrobial Resistance and Stewardship, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
- Yamagata Prefectural University of Health Sciences, Kamiyanagi, Yamagata 990-2212, Japan
- School of Medicine, Faculty of Health and Medical Sciences, The University of Western Australia, Nedlands, WA, Australia
- Pathogen Hunter’s Research Collaborative Team, Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
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14
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Krogsgaard LW, Benedetti G, Gudde A, Richter SR, Rasmussen LD, Midgley SE, Qvesel AG, Nauta M, Bahrenscheer NS, von Kappelgaard L, McManus O, Hansen NC, Pedersen JB, Haimes D, Gamst J, Nørgaard LS, Jørgensen ACU, Ejegod DM, Møller SS, Clauson-Kaas J, Knudsen IM, Franck KT, Ethelberg S. Results from the SARS-CoV-2 wastewater-based surveillance system in Denmark, July 2021 to June 2022. WATER RESEARCH 2024; 252:121223. [PMID: 38310802 DOI: 10.1016/j.watres.2024.121223] [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: 07/19/2023] [Revised: 11/01/2023] [Accepted: 01/28/2024] [Indexed: 02/06/2024]
Abstract
The microbiological analysis of wastewater samples is increasingly used for the surveillance of SARS-CoV-2 globally. We described the setup process of the national SARS-CoV-2 wastewater-based surveillance system in Denmark, presented its main results during the first year of activities, from July 2021 to June 2022, and discussed their operational significance. The Danish SARS-CoV-2 wastewater-based surveillance system was designed to cover 85 % of the population in Denmark and it entailed taking three weekly samples from 230 sites. Samples were RT-qPCR tested for SARS-CoV-2 RNA, targeting the genetic markers N1, N2 and RdRp, and for two faecal indicators, Pepper Mild Mottle Virus and crAssphage. We calculated the weekly SARS-CoV-2 RNA concentration in the wastewater from each sampling site and monitored it in view of the results from individual testing, at the national and regional levels. We attempted to use wastewater results to identify potential local outbreaks, and we sequenced positive wastewater samples using Nanopore sequencing to monitor the circulation of viral variants in Denmark. The system reached its full implementation by October 2021 and covered up to 86.4 % of the Danish population. The system allowed for monitoring of the national and regional trends of SARS-CoV-2 infections in Denmark. However, the system contribution to the identification of potential local outbreaks was limited by the extensive information available from clinical testing. The sequencing of wastewater samples identified relevant variants of concern, in line with results from sequencing of human samples. Amidst the COVID-19 pandemic, Denmark implemented a nationwide SARS-CoV-2 wastewater-based surveillance system that integrated routine surveillance from individual testing. Today, while testing for COVID-19 at the community level has been discontinued, the system is on the frontline to monitor the occurrence and spread of SARS-CoV-2 in Denmark.
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Affiliation(s)
- Lene Wulff Krogsgaard
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Guido Benedetti
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark.
| | - Aina Gudde
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Stine Raith Richter
- Department of Virus and Microbiological Special Diagnostics, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Lasse Dam Rasmussen
- Department of Virus and Microbiological Special Diagnostics, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Sofie Elisabeth Midgley
- Department of Virus and Microbiological Special Diagnostics, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Amanda Gammelby Qvesel
- Department of Virus and Microbiological Special Diagnostics, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Maarten Nauta
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Naja Stolberg Bahrenscheer
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Lene von Kappelgaard
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Oliver McManus
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark; European Programme for Intervention Epidemiology Training (EPIET), European Centre for Disease Prevention and Control, Gustav III: s Boulevard 40, 16973 Solna, Sweden
| | - Nicco Claudio Hansen
- Test Centre Denmark, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Jan Bryla Pedersen
- Department of Finance, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Danny Haimes
- Danish Patient Safety Authority, Islands Brygge 67, 2300 Copenhagen, Denmark
| | - Jesper Gamst
- Eurofins Environment, Ladelundvej 85, 6600 Vejen, Denmark
| | | | | | | | | | - Jes Clauson-Kaas
- HOFOR - Greater Copenhagen Utility, Ørestads Boulevard 35, 2300 Copenhagen, Denmark
| | - Ida Marie Knudsen
- HOFOR - Greater Copenhagen Utility, Ørestads Boulevard 35, 2300 Copenhagen, Denmark
| | - Kristina Træholt Franck
- Department of Virus and Microbiological Special Diagnostics, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Steen Ethelberg
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark; Department of Public Health, Global Health Section, University of Copenhagen, Øster Farimagsgade 5, 1014 Copenhagen, Denmark
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15
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Carducci A, Federigi I, Lauretani G, Muzio S, Pagani A, Atomsa NT, Verani M. Critical Needs for Integrated Surveillance: Wastewater-Based and Clinical Epidemiology in Evolving Scenarios with Lessons Learned from SARS-CoV-2. FOOD AND ENVIRONMENTAL VIROLOGY 2024; 16:38-49. [PMID: 38168848 DOI: 10.1007/s12560-023-09573-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024]
Abstract
During the COVID-19 pandemic, wastewater-based epidemiology (WBE) and clinical surveillance have been used as tools for analyzing the circulation of SARS-CoV-2 in the community, but both approaches can be strongly influenced by some sources of variability. From the challenging perspective of integrating environmental and clinical data, we performed a correlation analysis between SARS-CoV-2 concentrations in raw sewage and incident COVID-19 cases in areas served by medium-size wastewater treatment plants (WWTPs) from 2021 to 2023. To this aim, both datasets were adjusted for several sources of variability: WBE data were adjusted for factors including the analytical protocol, sewage flow, and population size, while clinical data adjustments considered the demographic composition of the served population. Then, we addressed the impact on the correlation of differences among sewerage networks and variations in the frequency and type of swab tests due to changes in political and regulatory scenarios. Wastewater and clinical data were significantly correlated when restrictive containment measures and limited movements were in effect (ρ = 0.50) and when COVID-19 cases were confirmed exclusively through molecular testing (ρ = 0.49). Moreover, a positive (although weak) correlation arose for WWTPs located in densely populated areas (ρ = 0.37) and with shorter sewerage lengths (ρ = 0.28). This study provides methodological approaches for interpreting WBE and clinical surveillance data, which could also be useful for other infections. Data adjustments and evaluation of possible sources of bias need to be carefully considered from the perspective of integrated environmental and clinical surveillance of infections.
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Affiliation(s)
- Annalaura Carducci
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
| | - Ileana Federigi
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy.
| | - Giulia Lauretani
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
| | - Sara Muzio
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
| | - Alessandra Pagani
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
| | - Nebiyu Tariku Atomsa
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
| | - Marco Verani
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127, Pisa, Italy
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16
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Saleem MH, Mfarrej MFB, Khan KA, Alharthy SA. Emerging trends in wastewater treatment: Addressing microorganic pollutants and environmental impacts. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 913:169755. [PMID: 38176566 DOI: 10.1016/j.scitotenv.2023.169755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 12/26/2023] [Accepted: 12/27/2023] [Indexed: 01/06/2024]
Abstract
This review focuses on the challenges and advances associated with the treatment and management of microorganic pollutants, encompassing pesticides, industrial chemicals, and persistent organic pollutants (POPs) in the environment. The translocation of these contaminants across multiple media, particularly through atmospheric transport, emphasizes their pervasive nature and the subsequent ecological risks. The urgency to develop cost-effective remediation strategies for emerging organic contaminants is paramount. As such, wastewater-based epidemiology and the increasing concern over estrogenicity are explored. By incorporating conventional and innovative wastewater treatment techniques, this article highlights the integration of environmental management strategies, analytical methodologies, and the importance of renewable energy in waste treatment. The primary objective is to provide a comprehensive perspective on the current scenario, imminent threats, and future directions in mitigating the effects of these pollutants on the environment. Furthermore, the review underscores the need for international collaboration in developing standardized guidelines and policies for monitoring and controlling these microorganic pollutants. It advocates for increased investment in research and development of advanced materials and technologies that can efficiently remove or neutralize these contaminants, thereby safeguarding environmental health and promoting sustainable practice.
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Affiliation(s)
- Muhammad Hamzah Saleem
- Office of Academic Research, Office of VP for Research & Graduate Studies, Qatar University, Doha 2713, Qatar.
| | - Manar Fawzi Bani Mfarrej
- Department of Life and Environmental Sciences, College of Natural and Health Sciences, Zayed University, Abu Dhabi 144534, United Arab Emirates.
| | - Khalid Ali Khan
- Applied College, Center of Bee Research and its Products, Unit of Bee Research and Honey Production, and Research Center for Advanced Materials Science (RCAMS), King Khalid University, P.O. Box 9004, Abha 61413, Saudi Arabia.
| | - Saif A Alharthy
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, P.O. Box 80216, Jeddah 21589, Saudi Arabia; Toxicology and Forensic Sciences Unit, King Fahd Medical Research Center, King Abdulaziz University, P.O. Box 80216, Jeddah 21589, Saudi Arabia.
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17
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Clark EC, Neumann S, Hopkins S, Kostopoulos A, Hagerman L, Dobbins M. Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review. JMIR Public Health Surveill 2024; 10:e49185. [PMID: 38241067 PMCID: PMC10837764 DOI: 10.2196/49185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/06/2023] [Accepted: 12/07/2023] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND Public health surveillance plays a vital role in informing public health decision-making. The onset of the COVID-19 pandemic in early 2020 caused a widespread shift in public health priorities. Global efforts focused on COVID-19 monitoring and contact tracing. Existing public health programs were interrupted due to physical distancing measures and reallocation of resources. The onset of the COVID-19 pandemic intersected with advancements in technologies that have the potential to support public health surveillance efforts. OBJECTIVE This scoping review aims to explore emergent public health surveillance methods during the early COVID-19 pandemic to characterize the impact of the pandemic on surveillance methods. METHODS A scoping search was conducted in multiple databases and by scanning key government and public health organization websites from March 2020 to January 2022. Published papers and gray literature that described the application of new or revised approaches to public health surveillance were included. Papers that discussed the implications of novel public health surveillance approaches from ethical, legal, security, and equity perspectives were also included. The surveillance subject, method, location, and setting were extracted from each paper to identify trends in surveillance practices. Two public health epidemiologists were invited to provide their perspectives as peer reviewers. RESULTS Of the 14,238 unique papers, a total of 241 papers describing novel surveillance methods and changes to surveillance methods are included. Eighty papers were review papers and 161 were single studies. Overall, the literature heavily featured papers detailing surveillance of COVID-19 transmission (n=187). Surveillance of other infectious diseases was also described, including other pathogens (n=12). Other public health topics included vaccines (n=9), mental health (n=11), substance use (n=4), healthy nutrition (n=1), maternal and child health (n=3), antimicrobial resistance (n=2), and misinformation (n=6). The literature was dominated by applications of digital surveillance, for example, by using big data through mobility tracking and infodemiology (n=163). Wastewater surveillance was also heavily represented (n=48). Other papers described adaptations to programs or methods that existed prior to the COVID-19 pandemic (n=9). The scoping search also found 109 papers that discuss the ethical, legal, security, and equity implications of emerging surveillance methods. The peer reviewer public health epidemiologists noted that additional changes likely exist, beyond what has been reported and available for evidence syntheses. CONCLUSIONS The COVID-19 pandemic accelerated advancements in surveillance and the adoption of new technologies, especially for digital and wastewater surveillance methods. Given the investments in these systems, further applications for public health surveillance are likely. The literature for surveillance methods was dominated by surveillance of infectious diseases, particularly COVID-19. A substantial amount of literature on the ethical, legal, security, and equity implications of these emerging surveillance methods also points to a need for cautious consideration of potential harm.
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Affiliation(s)
- Emily C Clark
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
| | - Sophie Neumann
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
| | - Stephanie Hopkins
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
| | - Alyssa Kostopoulos
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
| | - Leah Hagerman
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
| | - Maureen Dobbins
- National Collaborating Centre for Methods and Tools, Hamilton, ON, Canada
- School of Nursing, McMaster University, Hamilton, ON, Canada
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18
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Yao Y, Zhu Y, Nogueira R, Klawonn F, Wallner M. Optimal Selection of Sampling Points within Sewer Networks for Wastewater-Based Epidemiology Applications. Methods Protoc 2024; 7:6. [PMID: 38251199 PMCID: PMC10801534 DOI: 10.3390/mps7010006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 12/19/2023] [Accepted: 01/01/2024] [Indexed: 01/23/2024] Open
Abstract
Wastewater-based epidemiology (WBE) has great potential to monitor community public health, especially during pandemics. However, it faces substantial hurdles in pathogen surveillance through WBE, encompassing data representativeness, spatiotemporal variability, population estimates, pathogen decay, and environmental factors. This paper aims to enhance the reliability of WBE data, especially for early outbreak detection and improved sampling strategies within sewer networks. The tool implemented in this paper combines a monitoring model and an optimization model to facilitate the optimal selection of sampling points within sewer networks. The monitoring model utilizes parameters such as feces density and average water consumption to define the detectability of the virus that needs to be monitored. This allows for standardization and simplicity in the process of moving from the analysis of wastewater samples to the identification of infection in the source area. The entropy-based model can select optimal sampling points in a sewer network to obtain the most specific information at a minimum cost. The practicality of our tool is validated using data from Hildesheim, Germany, employing SARS-CoV-2 as a pilot pathogen. It is important to note that the tool's versatility empowers its extension to monitor other pathogens in the future.
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Affiliation(s)
- Yao Yao
- Institute for Information Engineering, Ostfalia University of Applied Sciences, Salzdahlumer Str. 46/48, 38302 Wolfenbüttel, Germany;
| | - Yibo Zhu
- Faculty of Civil and Environmental Engineering, Ostfalia University of Applied Sciences, Herbert-Meyer-Str. 7, 29556 Suderburg, Germany; (Y.Z.); (M.W.)
| | - Regina Nogueira
- Institute of Sanitary Engineering and Waste Management, Leibniz University Hannover, Welfengarten 1, 30167 Hannover, Germany;
| | - Frank Klawonn
- Biostatistics Research Group, Helmholtz Centre for Infection Research, 38124 Braunschweig, Germany
| | - Markus Wallner
- Faculty of Civil and Environmental Engineering, Ostfalia University of Applied Sciences, Herbert-Meyer-Str. 7, 29556 Suderburg, Germany; (Y.Z.); (M.W.)
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19
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Therrien JD, Thomson M, Sion ES, Lee I, Maere T, Nicolaï N, Manuel DG, Vanrolleghem PA. A comprehensive, open-source data model for wastewater-based epidemiology. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2024; 89:1-19. [PMID: 38214983 PMCID: wst_2023_409 DOI: 10.2166/wst.2023.409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/14/2024]
Abstract
The recent SARS-COV-2 pandemic has sparked the adoption of wastewater-based epidemiology (WBE) as a low-cost way to monitor the health of populations. In parallel, the pandemic has encouraged researchers to openly share their data to serve the public better and accelerate science. However, environmental surveillance data are highly dependent on context and are difficult to interpret meaningfully across sites. This paper presents the second iteration of the Public Health Environmental Surveillance Open Data Model (PHES-ODM), an open-source dictionary and set of data tools to enhance the interoperability of environmental surveillance data and enable the storage of contextual (meta)data. The data model describes how to store environmental surveillance program data, metadata about measurements taken on various specimens (water, air, surfaces, sites, populations) and data about measurement protocols. The model provides software tools that support the collection and use of PHES-ODM formatted data, including performing PCR calculations and data validation, recording data into input templates, generating wide tables for analysis, and producing SQL database definitions. Fully open-source and already adopted by institutions in Canada, the European Union, and other countries, the PHES-ODM provides a path forward for creating robust, interoperable, open datasets for environmental public health surveillance for SARS-CoV-2 and beyond.
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Affiliation(s)
| | - Mathew Thomson
- Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Eugen-Sorin Sion
- European Commission, European Research Council, Joint Research Centre, Ispra, Italy
| | - Ivan Lee
- Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Thomas Maere
- modelEAU, Université Laval, Québec City, QC G1V 0A6, Canada
| | - Niels Nicolaï
- modelEAU, Université Laval, Québec City, QC G1V 0A6, Canada
| | - Douglas G Manuel
- Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
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20
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Rao G, Capone D, Zhu K, Knoble A, Linden Y, Clark R, Lai A, Kim J, Huang CH, Bivins A, Brown J. Simultaneous detection and quantification of multiple pathogen targets in wastewater. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.23.23291792. [PMID: 37425908 PMCID: PMC10327253 DOI: 10.1101/2023.06.23.23291792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Wastewater-based epidemiology has emerged as a critical tool for public health surveillance, building on decades of environmental surveillance work for pathogens such as poliovirus. Work to date has been limited to monitoring a single pathogen or small numbers of pathogens in targeted studies; however, few studies consider simultaneous quantitative analysis of a wide variety of pathogens, which could greatly increase the utility of wastewater surveillance. We developed a novel quantitative multi-pathogen surveillance approach (35 pathogen targets including bacteria, viruses, protozoa, and helminths) using TaqMan Array Cards (TAC) and applied the method on concentrated wastewater samples collected at four wastewater treatment plants in Atlanta, GA from February to October of 2020. From sewersheds serving approximately 2 million people, we detected a wide range of targets including many we expected to find in wastewater (e.g., enterotoxigenic E. coli and Giardia in 97% of 29 samples at stable concentrations) as well as unexpected targets including Strongyloides stercoralis (a human threadworm rarely observed in the USA). Other notable detections included SARS-CoV-2, but also several pathogen targets that are not commonly included in wastewater surveillance like Acanthamoeba spp., Balantidium coli, Entamoeba histolytica, astrovirus, norovirus, and sapovirus. Our data suggest broad utility in expanding the scope of enteric pathogen surveillance in wastewaters, with potential for application in a variety of settings where pathogen quantification in fecal waste streams can inform public health surveillance and selection of control measures to limit infections.
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Affiliation(s)
- Gouthami Rao
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Drew Capone
- Department of Environmental and Occupational Health, School of Public Health, Indiana University, Bloomington, IN, USA
| | - Kevin Zhu
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Abigail Knoble
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yarrow Linden
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ryan Clark
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda Lai
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Juhee Kim
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Ching-Hua Huang
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Aaron Bivins
- Department of Civil & Environmental Engineering, Louisiana State University, Baton Rouge, LA, USA
| | - Joe Brown
- Department of Environmental Sciences and Engineering, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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21
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Tang S, Cao Y. A phenomenological neural network powered by the National Wastewater Surveillance System for estimation of silent COVID-19 infections. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 902:166024. [PMID: 37541490 DOI: 10.1016/j.scitotenv.2023.166024] [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: 06/12/2023] [Revised: 07/31/2023] [Accepted: 08/01/2023] [Indexed: 08/06/2023]
Abstract
Although wastewater-based epidemiology (WBE) has emerged as an inexpensive and non-intrusive method in contrast to clinical testing to track public health at community levels, there is a lack of structured interpretative criteria to translate the SARS-CoV-2 concentrations in wastewater to COVID-19 infection cases. The difficulties lie in the uncertainties of the amount of virus shed by an infected individual to wastewater as documented in clinical studies. This situation is even worse considering the existence of a population of silent infections and many other confounding factors. In this research, a quantitative framework of a phenomenological neural network (PNN) was developed to compute silent infections. The PNN was trained using the WBE data from the National Wastewater Surveillance System (NWSS) - a program launched by the CDC of the United States in 2020. It is found that the PNN excelled with superior interpretability and reduced overfitting. A big-data perspective on virus shedding by an infected population revealed more deterministic virus-shedding dynamics compared to the clinical studies perspective on virus shedding by an infected individual. With such characteristics employed as the theoretical basis for the estimation of the silent infections, a ratio of silent to reported infections was found to be 5.7 as the national median during the studied period. The study also noted the influence of temperature, sewershed population, and per-capita flow rates on the computation of silent infections. It is expected that the proposed framework in this work would facilitate public health actions guided by the SARS-CoV-2 concentrations in wastewater. In case of a new wave emergence or a new virus disease outbreak like COVID-19, the PNN powered by the NWSS would outline consolidated and systematic information that would enable rapid deployment of public health actions.
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Affiliation(s)
- Shunyu Tang
- Department of Mathematical and Computer Sciences, Indiana University of Pennsylvania, Indiana, PA 15705, United States of America
| | - Yongtao Cao
- Department of Mathematical and Computer Sciences, Indiana University of Pennsylvania, Indiana, PA 15705, United States of America.
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22
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Choi BJ, Hoselton S, Njau GN, Idamawatta I, Carson P, McEvoy J. Estimating the prevalence of COVID-19 cases through the analysis of SARS-CoV-2 RNA copies derived from wastewater samples from North Dakota. GLOBAL EPIDEMIOLOGY 2023; 6:100124. [PMID: 37881481 PMCID: PMC10594563 DOI: 10.1016/j.gloepi.2023.100124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/10/2023] [Accepted: 10/10/2023] [Indexed: 10/27/2023] Open
Abstract
The SARS-CoV-2 virus was first detected in December 2019, which prompted many researchers to investigate how the virus spreads. SARS-CoV-2 is mainly transmitted through respiratory droplets. Symptoms of the SARS-CoV-2 virus appear after an incubation period. Moreover, the asymptomatic infected individuals unknowingly spread the virus. Detecting infected people requires daily tests and contact tracing, which are expensive. The early detection of infectious diseases, including COVID-19, can be achieved with wastewater-based epidemiology, which is timely and cost-effective. In this study, we collected wastewater samples from wastewater treatment plants in several cities in North Dakota and then extracted viral RNA copies. We used log-RNA copies in the model to predict the number of infected cases using Quantile Regression (QR) and K-Nearest Neighbor (KNN) Regression. The model's performance was evaluated by comparing the Mean Absolute Percentage Error (MAPE). The QR model performs well in cities where the population is >10000 . In addition, the model predictions were compared with the basic Susceptible-Infected-Recovered (SIR) model which is the golden standard model for infectious diseases.
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Affiliation(s)
- Bong-Jin Choi
- Department of Statistics and Department of Public Health, North Dakota State University, United States of America
| | - Scott Hoselton
- Department of Microbiological Sciences, North Dakota State University, United States of America
| | - Grace N. Njau
- North Dakota Department of Health, United States of America
| | - I.G.C.G. Idamawatta
- Department of Statistics, North Dakota State University, United States of America
| | - Paul Carson
- Center for Immunization Research and Education (CIRE), Department of Public Health, North Dakota State University, United States of America
| | - John McEvoy
- Department of Microbiological Sciences, North Dakota State University, United States of America
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23
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Bertels X, Hanoteaux S, Janssens R, Maloux H, Verhaegen B, Delputte P, Boogaerts T, van Nuijs ALN, Brogna D, Linard C, Marescaux J, Didy C, Pype R, Roosens NHC, Van Hoorde K, Lesenfants M, Lahousse L. Time series modelling for wastewater-based epidemiology of COVID-19: A nationwide study in 40 wastewater treatment plants of Belgium, February 2021 to June 2022. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 899:165603. [PMID: 37474075 DOI: 10.1016/j.scitotenv.2023.165603] [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: 02/18/2023] [Revised: 07/11/2023] [Accepted: 07/15/2023] [Indexed: 07/22/2023]
Abstract
BACKGROUND Wastewater-based epidemiology (WBE) has been implemented to monitor surges of COVID-19. Yet, multiple factors impede the usefulness of WBE and quantitative adjustment may be required. AIM We aimed to model the relationship between WBE data and incident COVID-19 cases, while adjusting for confounders and autocorrelation. METHODS This nationwide WBE study includes data from 40 wastewater treatment plants (WWTPs) in Belgium (02/2021-06/2022). We applied ARIMA-based modelling to assess the effect of daily flow rate, pepper mild mottle virus (PMMoV) concentration, a measure of human faeces in wastewater, and variants (alpha, delta, and omicron strains) on SARS-CoV-2 RNA levels in wastewater. Secondly, adjusted WBE metrics at different lag times were used to predict incident COVID-19 cases. Model selection was based on AICc minimization. RESULTS In 33/40 WWTPs, RNA levels were best explained by incident cases, flow rate, and PMMoV. Flow rate and PMMoV were associated with -13.0 % (95 % prediction interval: -26.1 to +0.2 %) and +13.0 % (95 % prediction interval: +5.1 to +21.0 %) change in RNA levels per SD increase, respectively. In 38/40 WWTPs, variants did not explain variability in RNA levels independent of cases. Furthermore, our study shows that RNA levels can lead incident cases by at least one week in 15/40 WWTPs. The median population size of leading WWTPs was 85.1 % larger than that of non‑leading WWTPs. In 17/40 WWTPs, however, RNA levels did not lead or explain incident cases in addition to autocorrelation. CONCLUSION This study provides quantitative insights into key determinants of WBE, including the effects of wastewater flow rate, PMMoV, and variants. Substantial inter-WWTP variability was observed in terms of explaining incident cases. These findings are of practical importance to WBE practitioners and show that the early-warning potential of WBE is WWTP-specific and needs validation.
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Affiliation(s)
- Xander Bertels
- Department of Bioanalysis, Ghent University, 9000 Ghent, Belgium
| | - Sven Hanoteaux
- Epidemiology and Public Health, Epidemiology of Infectious Diseases, Sciensano, 1050 Brussels, Belgium
| | - Raphael Janssens
- Epidemiology and Public Health, Epidemiology of Infectious Diseases, Sciensano, 1050 Brussels, Belgium
| | - Hadrien Maloux
- Epidemiology and Public Health, Epidemiology of Infectious Diseases, Sciensano, 1050 Brussels, Belgium
| | - Bavo Verhaegen
- Infectious Diseases in Humans, Foodborne Pathogens, Sciensano, 1050 Brussels, Belgium
| | - Peter Delputte
- Laboratory for Microbiology, Parasitology and Hygiene, University of Antwerp, 2610 Wilrijk, Belgium
| | - Tim Boogaerts
- Toxicological Centre, University of Antwerp, 2610 Antwerp, Belgium
| | | | - Delphine Brogna
- Institute of Life, Earth and Environment, University of Namur, 5000 Namur, Belgium
| | - Catherine Linard
- Institute of Life, Earth and Environment, University of Namur, 5000 Namur, Belgium
| | - Jonathan Marescaux
- Institute of Life, Earth and Environment, University of Namur, 5000 Namur, Belgium; E-BIOM SA, 5000 Namur, Belgium
| | - Christian Didy
- Société Publique de Gestion de l'Eau, 4800 Verviers, Belgium
| | - Rosalie Pype
- Société Publique de Gestion de l'Eau, 4800 Verviers, Belgium
| | - Nancy H C Roosens
- Biological Health Risks, Transversal Activities in Applied Genomics, Sciensano, 1050 Brussels, Belgium
| | - Koenraad Van Hoorde
- Infectious Diseases in Humans, Foodborne Pathogens, Sciensano, 1050 Brussels, Belgium
| | - Marie Lesenfants
- Epidemiology and Public Health, Epidemiology of Infectious Diseases, Sciensano, 1050 Brussels, Belgium
| | - Lies Lahousse
- Department of Bioanalysis, Ghent University, 9000 Ghent, Belgium.
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24
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Marques Dos Santos M, Caixia L, Snyder SA. Evaluation of wastewater-based epidemiology of COVID-19 approaches in Singapore's 'closed-system' scenario: A long-term country-wide assessment. WATER RESEARCH 2023; 244:120406. [PMID: 37542765 DOI: 10.1016/j.watres.2023.120406] [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: 07/23/2022] [Revised: 07/21/2023] [Accepted: 07/23/2023] [Indexed: 08/07/2023]
Abstract
With the COVID-19 pandemic the use of WBE to track diseases spread has rapidly evolved into a widely applied strategy worldwide. However, many of the current studies lack the necessary systematic approach and supporting quality of epidemiological data to fully evaluate the effectiveness and usefulness of such methods. Use of WBE in a very low disease prevalence setting and for long-term monitoring has yet to be validated and it is critical for its intended use as an early warning system. In this study we seek to evaluate the sensitivity of WBE approaches under low prevalence of disease and ability to provide early warning. Two monitoring scenarios were used: (i) city wide monitoring (population 5,700,000) and (ii) community/localized monitoring (population 24,000 to 240,000). Prediction of active cases by WBE using multiple linear regression shows that a multiplexed qPCR approach with three gene targets has a significant advantage over single-gene monitoring approaches, with R2 = 0.832 (RMSE 0.053) for an analysis using N, ORF1ab and S genes (R2 = 0.677 to 0.793 for single gene strategies). A predicted disease prevalence of 0.001% (1 in 100,000) for a city-wide monitoring was estimated by the multiplexed RT-qPCR approach and was corroborated by epidemiological data evidence in three 'waves'. Localized monitoring setting shows an estimated detectable disease prevalence of ∼0.002% (1 in 56,000) and is supported by the geospatial distribution of active cases and local population dynamics data. Data analysis also shows that this approach has a limitation in sensitivity, or hit rate, of 62.5 % and an associated high miss rate (false negative rate) of 37.5 % when compared to available epidemiological data. Nevertheless, our study shows that, with enough sampling resolution, WBE at a community level can achieve high precision and accuracies for case detection (96 % and 95 %, respectively) with low false omission rate (4.5 %) even at low disease prevalence levels.
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Affiliation(s)
- Mauricius Marques Dos Santos
- Nanyang Technological University, Nanyang Environment & Water Research Institute (NEWRI), 1 Cleantech Loop, CleanTech One, #06-08, Singapore 637141
| | - Li Caixia
- Nanyang Technological University, Nanyang Environment & Water Research Institute (NEWRI), 1 Cleantech Loop, CleanTech One, #06-08, Singapore 637141
| | - Shane Allen Snyder
- Nanyang Technological University, Nanyang Environment & Water Research Institute (NEWRI), 1 Cleantech Loop, CleanTech One, #06-08, Singapore 637141; School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
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25
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López-Peñalver RS, Cañas-Cañas R, Casaña-Mohedo J, Benavent-Cervera JV, Fernández-Garrido J, Juárez-Vela R, Pellín-Carcelén A, Gea-Caballero V, Andreu-Fernández V. Predictive potential of SARS-CoV-2 RNA concentration in wastewater to assess the dynamics of COVID-19 clinical outcomes and infections. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 886:163935. [PMID: 37164095 PMCID: PMC10164651 DOI: 10.1016/j.scitotenv.2023.163935] [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: 01/16/2023] [Revised: 04/27/2023] [Accepted: 04/30/2023] [Indexed: 05/12/2023]
Abstract
Coronavirus disease 2019 - caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) -, has triggered a worldwide pandemic resulting in 665 million infections and over 6.5 million deaths as of December 15, 2022. The development of different epidemiological tools have helped predict new outbreaks and assess the behavior of clinical variables in different health contexts. In this study, we aimed to monitor concentrations of SARS-CoV-2 in wastewater as a tool to predict the progression of clinical variables during Waves 3, 5, and 6 of the pandemic in the Spanish city of Xátiva from September 2020 to March 2022. We estimated SARS-CoV-2 RNA concentrations in 195 wastewater samples using the RT-PCR Diagnostic Panel validated by the Center for Disease Control and Prevention. We also compared the trends of several clinical variables (14-day cumulative incidence, positive cases, hospital cases and stays, critical cases and stays, primary care visits, and deaths) for each study wave against wastewater SARS-CoV-2 RNA concentrations using Pearson's product-moment correlations, a two-sided Mann-Whitney U test, and a cross-correlation analysis. We found strong correlations between SARS-CoV-2 concentrations with 14-day cumulative incidence and positive cases over time. Wastewater RNA concentrations showed strong correlations with these variables one and two weeks in advance. There were significant correlations with hospitalizations and critical care during Wave 3 and Wave 6; cross-correlations were stronger for hospitalization stays one week before during Wave 6. No association between vaccination percentages and wastewater viral concentrations was observed. Our findings support wastewater SARS-CoV-2 concentrations as a potential surveillance tool to anticipate infection and epidemiological data such as 14-day cumulative incidence, hospitalizations, and critical care stays. Public health authorities could use this epidemiological tool on a similar population as an aid for health care decision-making during an epidemic outbreak.
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Affiliation(s)
- Raimundo Seguí López-Peñalver
- Faculty of Health Sciences, Valencian International University (VIU), 46002, Valencia, Spain; Global Omnium, Valencia, Spain
| | | | - Jorge Casaña-Mohedo
- Faculty of Health Sciences, Valencian International University (VIU), 46002, Valencia, Spain; Faculty of Health Sciences, Universidad Católica de Valencia San Vicente Mártir, 46001, Valencia, Spain
| | | | - Julio Fernández-Garrido
- Consellería de Sanidad Universal y Salud Pública, Generalitat Valenciana, Department of Nursing, University of Valencia, 46001 Jaume Roig St, Valencia, Spain
| | - Raúl Juárez-Vela
- Faculty of Health Sciences, La Rioja University, 26006 Logroño, Spain
| | - Ana Pellín-Carcelén
- Faculty of Health Sciences, Valencian International University (VIU), 46002, Valencia, Spain
| | - Vicente Gea-Caballero
- Faculty of Health Sciences, Valencian International University (VIU), 46002, Valencia, Spain
| | - Vicente Andreu-Fernández
- Faculty of Health Sciences, Valencian International University (VIU), 46002, Valencia, Spain; Biosanitary Research Institute, Valencian International University (VIU), 46002, Valencia, Spain.
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26
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McManus O, Christiansen LE, Nauta M, Krogsgaard LW, Bahrenscheer NS, von Kappelgaard L, Christiansen T, Hansen M, Hansen NC, Kähler J, Rasmussen A, Richter SR, Rasmussen LD, Franck KT, Ethelberg S. Predicting COVID-19 Incidence Using Wastewater Surveillance Data, Denmark, October 2021-June 2022. Emerg Infect Dis 2023; 29:1589-1597. [PMID: 37486168 PMCID: PMC10370843 DOI: 10.3201/eid2908.221634] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2023] Open
Abstract
Analysis of wastewater is used in many settings for surveillance of SARS-CoV-2, but it remains unclear how well wastewater testing results reflect incidence. Denmark has had an extensive wastewater analysis system that conducts 3 weekly tests in ≈200 sites and has 85% population coverage; the country also offers free SARS-CoV-2 PCR tests to all residents. Using time series analysis for modeling, we found that wastewater data, combined with information on circulating variants and the number of human tests performed, closely fitted the incidence curve of persons testing positive. The results were consistent at a regional level and among a subpopulation of frequently tested healthcare personnel. We used wastewater analysis data to estimate incidence after testing was reduced to a minimum after March 2022. These results imply that data from a large-scale wastewater surveillance system can serve as a good proxy for COVID-19 incidence and for epidemic control.
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Li X, Liu H, Gao L, Sherchan SP, Zhou T, Khan SJ, van Loosdrecht MCM, Wang Q. Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties. Nat Commun 2023; 14:4548. [PMID: 37507407 PMCID: PMC10382499 DOI: 10.1038/s41467-023-40305-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 07/19/2023] [Indexed: 07/30/2023] Open
Abstract
Although the coronavirus disease (COVID-19) emergency status is easing, the COVID-19 pandemic continues to affect healthcare systems globally. It is crucial to have a reliable and population-wide prediction tool for estimating COVID-19-induced hospital admissions. We evaluated the feasibility of using wastewater-based epidemiology (WBE) to predict COVID-19-induced weekly new hospitalizations in 159 counties across 45 states in the United States of America (USA), covering a population of nearly 100 million. Using county-level weekly wastewater surveillance data (over 20 months), WBE-based models were established through the random forest algorithm. WBE-based models accurately predicted the county-level weekly new admissions, allowing a preparation window of 1-4 weeks. In real applications, periodically updated WBE-based models showed good accuracy and transferability, with mean absolute error within 4-6 patients/100k population for upcoming weekly new hospitalization numbers. Our study demonstrated the potential of using WBE as an effective method to provide early warnings for healthcare systems.
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Affiliation(s)
- Xuan Li
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia
| | - Huan Liu
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia
| | - Li Gao
- South East Water, 101 Wells Street, Frankston, VIC, 3199, Australia
| | - Samendra P Sherchan
- Department of Biology, Morgan State University, Baltimore, MD, USA
- Department of Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Ting Zhou
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia
| | - Stuart J Khan
- Water Research Centre, School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Mark C M van Loosdrecht
- Department of Biotechnology, Delft University of Technology, Julianalaan 67, 2628 BC, Delft, the Netherlands
| | - Qilin Wang
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW, 2007, Australia.
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Wannigama DL, Amarasiri M, Hongsing P, Hurst C, Modchang C, Chadsuthi S, Anupong S, Phattharapornjaroen P, Rad S. M. AH, Fernandez S, Huang AT, Vatanaprasan P, Jay DJ, Saethang T, Luk-in S, Storer RJ, Ounjai P, Devanga Ragupathi NK, Kanthawee P, Sano D, Furukawa T, Sei K, Leelahavanichkul A, Kanjanabuch T, Hirankarn N, Higgins PG, Kicic A, Singer AC, Chatsuwan T, Trowsdale S, Abe S, McLellan AD, Ishikawa H. COVID-19 monitoring with sparse sampling of sewered and non-sewered wastewater in urban and rural communities. iScience 2023; 26:107019. [PMID: 37351501 PMCID: PMC10250052 DOI: 10.1016/j.isci.2023.107019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 03/31/2023] [Accepted: 05/30/2023] [Indexed: 06/24/2023] Open
Abstract
Equitable SARS-CoV-2 surveillance in low-resource communities lacking centralized sewers is critical as wastewater-based epidemiology (WBE) progresses. However, large-scale studies on SARS-CoV-2 detection in wastewater from low-and middle-income countries is limited because of economic and technical reasons. In this study, wastewater samples were collected twice a month from 186 urban and rural subdistricts in nine provinces of Thailand mostly having decentralized and non-sewered sanitation infrastructure and analyzed for SARS-CoV-2 RNA variants using allele-specific RT-qPCR. Wastewater SARS-CoV-2 RNA concentration was used to estimate the real-time incidence and time-varying effective reproduction number (Re). Results showed an increase in SARS-CoV-2 RNA concentrations in wastewater from urban and rural areas 14-20 days earlier than infected individuals were officially reported. It also showed that community/food markets were "hot spots" for infected people. This approach offers an opportunity for early detection of transmission surges, allowing preparedness and potentially mitigating significant outbreaks at both spatial and temporal scales.
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Affiliation(s)
- Dhammika Leshan Wannigama
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Antimicrobial Resistance and Stewardship, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- School of Medicine, Faculty of Health and Medical Sciences, The University of Western Australia, Nedlands, WA, Australia
- Biofilms and Antimicrobial Resistance Consortium of ODA receiving countries, The University of Sheffield, Sheffield, UK
- Pathogen Hunter’s Research Collaborative Team, Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Mohan Amarasiri
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Kitasato, Sagamihara-Minami, Kanagawa 252-0373, Japan
| | - Parichart Hongsing
- Mae Fah Luang University Hospital, Chiang Rai, Thailand
- School of Integrative Medicine, Mae Fah Luang University, Chiang Rai, Thailand
| | - Cameron Hurst
- Molly Wardaguga Research Centre, Charles Darwin University, Brisbane, QLD, Australia
- Statistics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
- Centre of Excellence in Mathematics, MHESI, Bangkok 10400, Thailand
- Thailand Center of Excellence in Physics, Ministry of Higher Education, Science, Research and Innovation, 328 Si Ayutthaya Road, Bangkok 10400, Thailand
| | - Sudarat Chadsuthi
- Department of Physics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
| | - Suparinthon Anupong
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Phatthranit Phattharapornjaroen
- Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
- Institute of Clinical Sciences, Department of Surgery, Sahlgrenska Academy, Gothenburg University, 40530 Gothenburg, Sweden
| | - Ali Hosseini Rad S. M.
- Department of Microbiology and Immunology, University of Otago, Dunedin, Otago 9010, New Zealand
- Center of Excellence in Immunology and Immune-Mediated Diseases, Chulalongkorn University, Bangkok 10330, Thailand
| | - Stefan Fernandez
- Department of Virology, U.S. Army Medical Directorate, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Angkana T. Huang
- Department of Virology, U.S. Army Medical Directorate, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | | | - Dylan John Jay
- Pathogen Hunter’s Research Collaborative Team, Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Thammakorn Saethang
- Department of Computer Science, Faculty of Science, Kasetsart University, Bangkok, Thailand
| | - Sirirat Luk-in
- Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok, Thailand
| | - Robin James Storer
- Office of Research Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Puey Ounjai
- Department of Biology, Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Naveen Kumar Devanga Ragupathi
- School of Medicine, Faculty of Health and Medical Sciences, The University of Western Australia, Nedlands, WA, Australia
- Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield, UK
- Department of Clinical Microbiology, Christian Medical College, Vellore, India
| | - Phitsanuruk Kanthawee
- Public Health major, School of Health Science, Mae Fah Luang University, Chiang Rai, Thailand
| | - Daisuke Sano
- Department of Frontier Sciences for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Sendai, Miyagi, Japan
- Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Miyagi, Japan
| | - Takashi Furukawa
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Kitasato, Sagamihara-Minami, Kanagawa 252-0373, Japan
| | - Kazunari Sei
- Laboratory of Environmental Hygiene, Department of Health Science, School of Allied Health Sciences, Graduate School of Medical Sciences, Kitasato University, Kitasato, Sagamihara-Minami, Kanagawa 252-0373, Japan
| | - Asada Leelahavanichkul
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
- Translational Research in Inflammation and Immunology Research Unit (TRIRU), Department of Microbiology, Chulalongkorn University, Bangkok, Thailand
| | - Talerngsak Kanjanabuch
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Kidney Metabolic Disorders, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Dialysis Policy and Practice Program (DiP3), School of Global Health, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Peritoneal Dialysis Excellence Center, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Nattiya Hirankarn
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Immunology and Immune-Mediated Diseases, Chulalongkorn University, Bangkok 10330, Thailand
| | - Paul G. Higgins
- Institute for Medical Microbiology, Immunology and Hygiene, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Centre for Infection Research, Partner site Bonn-Cologne, Cologne, Germany
| | - Anthony Kicic
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, University of Western Australia, Nedlands, WA 6009, Australia
- Centre for Cell Therapy and Regenerative Medicine, Medical School, The University of Western Australia, Nedlands, WA 6009, Australia
- Department of Respiratory and Sleep Medicine, Perth Children’s Hospital, Nedlands, WA 6009, Australia
- School of Population Health, Curtin University, Bentley, WA 6102, Australia
| | | | - Tanittha Chatsuwan
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Center of Excellence in Antimicrobial Resistance and Stewardship, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Sam Trowsdale
- Department of Environmental Science, University of Auckland, Auckland 1010, New Zealand
| | - Shuichi Abe
- Department of Infectious Diseases and Infection Control, Yamagata Prefectural Central Hospital, Yamagata, Japan
| | - Alexander D. McLellan
- Department of Microbiology and Immunology, University of Otago, Dunedin, Otago 9010, New Zealand
| | - Hitoshi Ishikawa
- Yamagata Prefectural University of Health Sciences, Kamiyanagi, Yamagata 990-2212, Japan
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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.
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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.
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Kallem P, Hegab H, Alsafar H, Hasan SW, Banat F. SARS-CoV-2 detection and inactivation in water and wastewater: Review on analytical methods, limitations and future research recommendations. Emerg Microbes Infect 2023:2222850. [PMID: 37279167 DOI: 10.1080/22221751.2023.2222850] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been detected in wastewater. Wastewater-based epidemiology (WBE) is a practical and cost-effective tool for the assessment and controlling of pandemics and probably for examining SARS-CoV-2 presence. Implementation of WBE during the outbreaks is not without limitations. Temperature, suspended solids, pH, and disinfectants affect the stability of viruses in wastewater. Due to these limitations, instruments and techniques have been utilized to detect SARS-CoV-2. SARS-CoV-2 has been detected in sewage using various concentration methods and computer-aided analyzes. RT-qPCR, ddRT-PCR, multiplex PCR, RT-LAMP, and electrochemical immunosensors have been employed to detect low levels of viral contamination. Inactivation of SARS-CoV-2 is a crucial preventive measure against coronavirus disease 2019 (COVID-19). To better assess the role of wastewater as a transmission route, detection, and quantification methods need to be refined. In this paper, the latest improvements in quantification, detection, and inactivation of SARS-CoV-2 in wastewater are explained. Finally, limitations and future research recommendations are thoroughly described.
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Affiliation(s)
- Parashuram Kallem
- Center for Membranes and Advanced Water Technology (CMAT), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates
- Department of Chemical Engineering, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates
- Environmental Health and Safety Program, College of Health Sciences, Abu Dhabi University, Abu Dhabi P.O. Box 59911, United Arab Emirates
| | - Hanaa Hegab
- Center for Membranes and Advanced Water Technology (CMAT), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates
- Department of Chemical Engineering, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates
| | - Habiba Alsafar
- Center for Biotechnology (BTC), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates
- Department of Biomedical Engineering, College of Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Emirates Bio-research center, Ministry of interior, Abu Dhabi, United Arab Emirates
| | - Shadi W Hasan
- Center for Membranes and Advanced Water Technology (CMAT), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates
- Department of Chemical Engineering, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates
| | - Fawzi Banat
- Center for Membranes and Advanced Water Technology (CMAT), Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates
- Department of Chemical Engineering, Khalifa University of Science and Technology, PO Box 127788, Abu Dhabi, United Arab Emirates
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31
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Jiang G, Liu Y, Tang S, Kitajima M, Haramoto E, Arora S, Choi PM, Jackson G, D'Aoust PM, Delatolla R, Zhang S, Guo Y, Wu J, Chen Y, Sharma E, Prosun TA, Zhao J, Kumar M, Honda R, Ahmed W, Meiman J. Moving forward with COVID-19: Future research prospects of wastewater-based epidemiology methodologies and applications. CURRENT OPINION IN ENVIRONMENTAL SCIENCE & HEALTH 2023; 33:100458. [PMID: 37034453 PMCID: PMC10065412 DOI: 10.1016/j.coesh.2023.100458] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Wastewater-based epidemiology (WBE) has been demonstrated for its great potential in tracking of coronavirus disease 2019 (COVID-19) transmission among populations despite some inherent methodological limitations. These include non-optimized sampling approaches and analytical methods; stability of viruses in sewer systems; partitioning/retention in biofilms; and the singular and inaccurate back-calculation step to predict the number of infected individuals in the community. Future research is expected to (1) standardize best practices in wastewater sampling, analysis and data reporting protocols for the sensitive and reproducible detection of viruses in wastewater; (2) understand the in-sewer viral stability and partitioning under the impacts of dynamic wastewater flow, properties, chemicals, biofilms and sediments; and (3) achieve smart wastewater surveillance with artificial intelligence and big data models. Further specific research is essential in the monitoring of other viral pathogens with pandemic potential and subcatchment applications to maximize the benefits of WBE beyond COVID-19.
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Affiliation(s)
- Guangming Jiang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Yanchen Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health (NIEH), Chinese Center for Disease Control and Prevention (China CDC), Chaoyang District, Beijing 100021, China
| | - Masaaki Kitajima
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Sudipti Arora
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, 302017, India
| | - Phil M Choi
- Water Unit, Health Protection Branch, Queensland Public Health and Scientific Services, Queensland Health, Australia
| | - Greg Jackson
- Water Unit, Health Protection Branch, Queensland Public Health and Scientific Services, Queensland Health, Australia
| | - Patrick M D'Aoust
- Department of Civil Engineering, University of Ottawa, Ottawa, Ontario, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, Ontario, Canada
| | - Shuxin Zhang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Ying Guo
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Jiangping Wu
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Yan Chen
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Elipsha Sharma
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Tanjila Alam Prosun
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Jiawei Zhao
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Manish Kumar
- Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India
- Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Campus Monterey, Monterrey, 64849, Nuevo Leon, Mexico
| | - Ryo Honda
- Faculty of Geosciences and Civil Engineering, Kanazawa University, Kanazawa, Japan
| | - Warish Ahmed
- CSIRO Environment, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Jon Meiman
- Wisconsin Department of Health Services, Madison, WI 53701, USA
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Schenk H, Heidinger P, Insam H, Kreuzinger N, Markt R, Nägele F, Oberacher H, Scheffknecht C, Steinlechner M, Vogl G, Wagner AO, Rauch W. Prediction of hospitalisations based on wastewater-based SARS-CoV-2 epidemiology. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 873:162149. [PMID: 36773921 PMCID: PMC9911153 DOI: 10.1016/j.scitotenv.2023.162149] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/06/2023] [Accepted: 02/06/2023] [Indexed: 05/03/2023]
Abstract
Wastewater-based epidemiology is widely applied in Austria since April 2020 to monitor the SARS-CoV-2 pandemic. With a steadily increasing number of monitored wastewater facilities, 123 plants covering roughly 70 % of the 9 million population were monitored as of August 2022. In this study, the SARS-CoV-2 viral concentrations in raw sewage were analysed to infer short-term hospitalisation occupancy. The temporal lead of wastewater-based epidemiological time series over hospitalisation occupancy levels facilitates the construction of forecast models. Data pre-processing techniques are presented, including the approach of comparing multiple decentralised wastewater signals with aggregated and centralised clinical data. Time‑lead quantification was performed using cross-correlation analysis and coefficient of determination optimisation approaches. Multivariate regression models were successfully applied to infer hospitalisation bed occupancy. The results show a predictive potential of viral loads in sewage towards Covid-19 hospitalisation occupancy, with an average lead time towards ICU and non-ICU bed occupancy between 14.8-17.7 days and 8.6-11.6 days, respectively. The presented procedure provides access to the trend and tipping point behaviour of pandemic dynamics and allows the prediction of short-term demand for public health services. The results showed an increase in forecast accuracy with an increase in the number of monitored wastewater treatment plants. Trained models are sensitive to changing variant types and require recalibration of model parameters, likely caused by immunity by vaccination and/or infection. The utilised approach displays a practical and rapidly implementable application of wastewater-based epidemiology to infer hospitalisation occupancy.
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Affiliation(s)
- Hannes Schenk
- Unit of Environmental Engineering, University of Innsbruck, Technikerstraße 13, Innsbruck 6020, Austria.
| | - Petra Heidinger
- Austrian Centre of Industrial Biotechnology, Krenngasse 37, Graz 8010, Austria.
| | - Heribert Insam
- Department of Microbiology, University of Innsbruck, Technikerstraße 25d, Innsbruck 6020, Austria.
| | - Norbert Kreuzinger
- Institute of Water Quality and Resource Management at TU Wien, Karlsplatz 13, Vienna 1040, Austria.
| | - Rudolf Markt
- Department of Microbiology, University of Innsbruck, Technikerstraße 25d, Innsbruck 6020, Austria; Department of Health Sciences and Social Work, Carinthia University of Applied Sciences, St. Veiter Straße, 47, Klagenfurt 9020, Austria.
| | - Fabiana Nägele
- Department of Microbiology, University of Innsbruck, Technikerstraße 25d, Innsbruck 6020, Austria.
| | - Herbert Oberacher
- Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Müllerstraße, 44, Innsbruck 6020, Austria.
| | - Christoph Scheffknecht
- Institut für Umwelt und Lebensmittelsicherheit des Landes Vorarlberg, Montfortstraße 4, Bregenz 6900, Austria.
| | - Martin Steinlechner
- Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Müllerstraße, 44, Innsbruck 6020, Austria.
| | - Gunther Vogl
- Institut f¨ur Lebensmittelsicherheit, Veterinärmedizin und Umwelt, Kirchengasse 43, Klagenfurt 9020, Austria.
| | - Andreas Otto Wagner
- Department of Microbiology, University of Innsbruck, Technikerstraße 25d, Innsbruck 6020, Austria.
| | - Wolfgang Rauch
- Unit of Environmental Engineering, University of Innsbruck, Technikerstraße 13, Innsbruck 6020, Austria.
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Sweetapple C, Wade MJ, Melville-Shreeve P, Chen AS, Lilley C, Irving J, Grimsley JMS, Bunce JT. Dynamic population normalisation in wastewater-based epidemiology for improved understanding of the SARS-CoV-2 prevalence: a multi-site study. JOURNAL OF WATER AND HEALTH 2023; 21:625-642. [PMID: 37254910 PMCID: wh_2023_318 DOI: 10.2166/wh.2023.318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Wastewater-based epidemiology (WBE) is a valuable tool for monitoring the circulation of COVID-19. However, while variations in population size are recognised as major sources of uncertainty, wastewater SARS-CoV-2 measurements are not routinely population-normalised. This paper aims to determine whether dynamic population normalisation significantly alters SARS-CoV-2 dynamics observed through wastewater monitoring, and whether it is beneficial or necessary to provide an understanding of COVID-19 epidemiology. Data from 394 sites in England are used, and normalisation is implemented based on ammoniacal nitrogen and orthophosphate concentrations. Raw and normalised wastewater SARS-CoV-2 metrics are evaluated at the site and spatially aggregated levels are compared against indicators of prevalence based on the Coronavirus Infection Survey and Test and Trace polymerase chain reaction test results. Normalisation is shown, on average, to have a limited impact on overall temporal trends. However, significant variability in the degree to which it affects local-level trends is observed. This is not evident from previous WBE studies focused on single sites and, critically, demonstrates that while the impact of normalisation on SARS-CoV-2 trends is small on average, this may not always be the case. When averaged across many sites, normalisation strengthens the correlation between wastewater SARS-CoV-2 data and prevalence indicators; however, confidence in the improvement is low.
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Affiliation(s)
- Chris Sweetapple
- UK Health Security Agency, Environmental Monitoring for Health Protection, Nobel House, London SW1P 3JR, United Kingdom E-mail: ; Centre for Water Systems, Faculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QF, United Kingdom
| | - Matthew J Wade
- UK Health Security Agency, Environmental Monitoring for Health Protection, Nobel House, London SW1P 3JR, United Kingdom E-mail: ; School of Engineering, Newcastle University, Newcastle-upon-Tyne NE1 7RU, United Kingdom
| | - Peter Melville-Shreeve
- Centre for Water Systems, Faculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QF, United Kingdom
| | - Albert S Chen
- Centre for Water Systems, Faculty of Environment, Science and Economy, University of Exeter, Exeter EX4 4QF, United Kingdom
| | - Chris Lilley
- UK Health Security Agency, Environmental Monitoring for Health Protection, Nobel House, London SW1P 3JR, United Kingdom E-mail:
| | - Jessica Irving
- UK Health Security Agency, Environmental Monitoring for Health Protection, Nobel House, London SW1P 3JR, United Kingdom E-mail:
| | - Jasmine M S Grimsley
- UK Health Security Agency, Environmental Monitoring for Health Protection, Nobel House, London SW1P 3JR, United Kingdom E-mail: ; The London Data Company, London EC2N 2AT, UK
| | - Joshua T Bunce
- UK Health Security Agency, Environmental Monitoring for Health Protection, Nobel House, London SW1P 3JR, United Kingdom E-mail: ; School of Engineering, Newcastle University, Newcastle-upon-Tyne NE1 7RU, United Kingdom; Department for Environment, Food and Rural Affairs, Seacole Building, London SW1P 4DF, United Kingdom
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Jahne MA, Schoen ME, Kaufmann A, Pecson BM, Olivieri A, Sharvelle S, Anderson A, Ashbolt NJ, Garland JL. Enteric pathogen reduction targets for onsite non-potable water systems: A critical evaluation. WATER RESEARCH 2023; 233:119742. [PMID: 36848851 PMCID: PMC10084472 DOI: 10.1016/j.watres.2023.119742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 02/10/2023] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
Abstract
Onsite non-potable water systems (ONWS) collect and treat local source waters for non-potable end uses such as toilet flushing and irrigation. Quantitative microbial risk assessment (QMRA) has been used to set pathogen log10-reduction targets (LRTs) for ONWS to achieve the risk benchmark of 10-4 infections per person per year (ppy) in a series of two efforts completed in 2017 and 2021. In this work, we compare and synthesize the ONWS LRT efforts to inform the selection of pathogen LRTs. For onsite wastewater, greywater, and stormwater, LRTs for human enteric viruses and parasitic protozoa were within 1.5-log10 units between 2017 and 2021 efforts, despite differences in approaches used to characterize pathogens in these waters. For onsite wastewater and greywater, the 2017 effort used an epidemiology-based model to simulate pathogen concentrations contributed exclusively from onsite waste and selected Norovirus as the viral reference pathogen; the 2021 effort used municipal wastewater pathogen data and cultivable adenoviruses as the reference viral pathogen. Across source waters, the greatest differences occurred for viruses in stormwater, given the newly available municipal wastewater characterizations used for modeling sewage contributions in 2021 and the different selection of reference pathogens (Norovirus vs. adenoviruses). The roof runoff LRTs support the need for protozoa treatment, but these remain difficult to characterize due to the pathogen variability in roof runoff across space and time. The comparison highlights adaptability of the risk-based approach, allowing for updated LRTs as site specific or improved information becomes available. Future research efforts should focus on data collection of onsite water sources.
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Affiliation(s)
- Michael A Jahne
- Office of Research and Development, U.S. Environmental Protection Agency, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, USA.
| | - Mary E Schoen
- Soller Environmental, LLC, 3022 King St., Berkeley, CA 94703, USA
| | - Anya Kaufmann
- Trussell Technologies, Inc., 1939 Harrison St., Oakland, CA 94612, USA
| | - Brian M Pecson
- Trussell Technologies, Inc., 1939 Harrison St., Oakland, CA 94612, USA
| | | | - Sybil Sharvelle
- Colorado State University, Department of Civil and Environmental Engineering, 1372 Campus Delivery, Fort Collins, CO 80523, USA
| | - Anita Anderson
- Minnesota Department of Health, 625 Robert St. N, St. Paul, MN 55164, USA
| | | | - Jay L Garland
- Office of Research and Development, U.S. Environmental Protection Agency, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, USA
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Zhang S, Shi J, Sharma E, Li X, Gao S, Zhou X, O'Brien J, Coin L, Liu Y, Sivakumar M, Hai F, Jiang G. In-sewer decay and partitioning of Campylobacter jejuni and Campylobacter coli and implications for their wastewater surveillance. WATER RESEARCH 2023; 233:119737. [PMID: 36801582 DOI: 10.1016/j.watres.2023.119737] [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: 12/21/2022] [Revised: 02/08/2023] [Accepted: 02/10/2023] [Indexed: 06/18/2023]
Abstract
Campylobacter jejuni and coli are two main pathogenic species inducing diarrhoeal diseases in humans, which are responsible for the loss of 33 million lives each year. Current Campylobacter infections are mainly monitored by clinical surveillance which is often limited to individuals seeking treatment, resulting in under-reporting of disease prevalence and untimely indicators of community outbreaks. Wastewater-based epidemiology (WBE) has been developed and employed for the wastewater surveillance of pathogenic viruses and bacteria. Monitoring the temporal changes of pathogen concentration in wastewater allows the early detection of disease outbreaks in a community. However, studies investigating the WBE back-estimation of Campylobacter spp. are rare. Essential factors including the analytical recovery efficiency, the decay rate, the effect of in-sewer transport, and the correlation between the wastewater concentration and the infections in communities are lacking to support wastewater surveillance. This study carried out experiments to investigate the recovery of Campylobacter jejuni and coli from wastewater and the decay under different simulated sewer reactor conditions. It was found that the recovery of Campylobacter spp. from wastewater varied with their concentrations in wastewater and depended on the detection limit of quantification methods. The concentration reduction of Campylobacter. jejuni and coli in sewers followed a two-phase reduction model, and the faster concentration reduction during the first phase is mainly due to their partitioning onto sewer biofilms. The total decay of Campylobacter. jejuni and coli varied in different types of sewer reactors, i.e. rising main vs. gravity sewer. In addition, the sensitivity analysis for WBE back-estimation of Campylobacter suggested that the first-phase decay rate constant (k1) and the turning time point (t1) are determining factors and their impacts increased with the hydraulic retention time of wastewater.
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Affiliation(s)
- Shuxin Zhang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Australia
| | - Jiahua Shi
- Illawarra Health and Medical Research Institute (IHMRI), University of Wollongong, Wollongong, Australia; School of Medical, Indigenous and Health Sciences, University of Wollongong, Australia
| | - Elipsha Sharma
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Australia
| | - Xuan Li
- Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Shuhong Gao
- State Key Laboratory of Urban Water Resource and Environment, School of Civil & Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
| | - Xu Zhou
- State Key Laboratory of Urban Water Resource and Environment, School of Civil & Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
| | - Jake O'Brien
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Brisbane, Australia
| | - Lachlan Coin
- Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia
| | - Yanchen Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Muttucumaru Sivakumar
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Australia
| | - Faisal Hai
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Australia
| | - Guangming Jiang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Australia; Illawarra Health and Medical Research Institute (IHMRI), University of Wollongong, Wollongong, Australia.
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Babler KM, Sharkey ME, Abelson S, Amirali A, Benitez A, Cosculluela GA, Grills GS, Kumar N, Laine J, Lamar W, Lamm ED, Lyu J, Mason CE, McCabe PM, Raghavender J, Reding BD, Roca MA, Schürer SC, Stevenson M, Szeto A, Tallon JJ, Vidović D, Zarnegarnia Y, Solo-Gabriele HM. Degradation rates influence the ability of composite samples to represent 24-hourly means of SARS-CoV-2 and other microbiological target measures in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 867:161423. [PMID: 36623667 PMCID: PMC9817413 DOI: 10.1016/j.scitotenv.2023.161423] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 12/25/2022] [Accepted: 01/02/2023] [Indexed: 06/17/2023]
Abstract
The utility of using severe-acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA for assessing the prevalence of COVID-19 within communities begins with the design of the sample collection program. The objective of this study was to assess the utility of 24-hour composites as representative samples for measuring multiple microbiological targets in wastewater, and whether normalization of SARS-CoV-2 by endogenous targets can be used to decrease hour to hour variability at different watershed scales. Two sets of experiments were conducted, in tandem with the same wastewater, with samples collected at the building, cluster, and community sewershed scales. The first set of experiments focused on evaluating degradation of microbiological targets: SARS-CoV-2, Simian Immunodeficiency Virus (SIV) - a surrogate spiked into the wastewater, plus human waste indicators of Pepper Mild Mottle Virus (PMMoV), Beta-2 microglobulin (B2M), and fecal coliform bacteria (FC). The second focused on the variability of these targets from samples, collected each hour on the hour. Results show that SARS-CoV-2, PMMoV, and B2M were relatively stable, with minimal degradation over 24-h. SIV, which was spiked-in prior to analysis, degraded significantly and FC increased significantly over the course of 24 h, emphasizing the possibility for decay and growth within wastewater. Hour-to-hour variability of the source wastewater was large between each hour of sampling relative to the variability of the SARS-CoV-2 levels calculated between sewershed scales; thus, differences in SARS-CoV-2 hourly variability were not statistically significant between sewershed scales. Results further provided that the quantified representativeness of 24-h composite samples (i.e., statistical equivalency compared against hourly collected grabs) was dependent upon the molecular target measured. Overall, improvements made by normalization were minimal within this study. Degradation and multiplication for other targets should be evaluated when deciding upon whether to collect composite or grab samples in future studies.
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Affiliation(s)
- Kristina M Babler
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Mark E Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Samantha Abelson
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Aymara Benitez
- Miami-Dade Water and Sewer Department, Miami, FL 33149, USA
| | - Gabriella A Cosculluela
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Naresh Kumar
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Walter Lamar
- Division of Occupational Health, Safety & Compliance, University of Miami Health System, Miami, FL 33136, USA
| | - Erik D Lamm
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Jiangnan Lyu
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10021, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY 10021, USA
| | - Philip M McCabe
- Department of Psychology, University of Miami, Coral Gables, FL 33146, USA; Department of Biomedical Engineering, University of Miami, Coral Gables, FL 33146, USA
| | | | - Brian D Reding
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Matthew A Roca
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Institute for Data Science & Computing, University of Miami, Coral Gables, FL, USA
| | - Mario Stevenson
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Angela Szeto
- Department of Psychology, University of Miami, Coral Gables, FL 33146, USA
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL 33146, USA
| | - Dusica Vidović
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Yalda Zarnegarnia
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA.
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Prado T, Rey-Benito G, Miagostovich MP, Sato MIZ, Rajal VB, Filho CRM, Pereira AD, Barbosa MRF, Mannarino CF, da Silva AS. Wastewater-based epidemiology for preventing outbreaks and epidemics in Latin America - Lessons from the past and a look to the future. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 865:161210. [PMID: 36581294 DOI: 10.1016/j.scitotenv.2022.161210] [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: 10/19/2022] [Revised: 12/05/2022] [Accepted: 12/22/2022] [Indexed: 06/17/2023]
Abstract
Wastewater-based epidemiology (WBE) is an approach with the potential to complement clinical surveillance systems. Using WBE, it is possible to carry out an early warning of a possible outbreak, monitor spatial and temporal trends of infectious diseases, produce real-time results and generate representative epidemiological information in a territory, especially in areas of social vulnerability. Despite the historical uses of this approach, particularly in the Global Polio Eradication Initiative, and for other pathogens, it was during the COVID-19 pandemic that occurred an exponential increase in environmental surveillance programs for SARS-CoV-2 in wastewater, with many experiences and developments in the field of public health using data for decision making and prioritizing actions to control the pandemic. In Latin America, WBE was applied in heterogeneous contexts and with emphasis on populations that present many socio-environmental inequalities, a condition shared by all Latin American countries. This manuscript addresses the concepts and applications of WBE in public health actions, as well as different experiences in Latin American countries, and discusses a model to implement this surveillance system at the local or national level. We emphasize the need to implement this sentinel surveillance system in countries that want to detect the early entry and spread of new pathogens and monitor outbreaks or epidemics of infectious agents in their territories as a complement of public health surveillance systems.
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Affiliation(s)
- Tatiana Prado
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Av. Brasil, 4365, Manguinhos, Rio de Janeiro, CEP 21040-360, Brazil.
| | - Gloria Rey-Benito
- Pan American Health Organization (PAHO/WHO), 525 23rd St NW, Washington, DC 20037, United States of America.
| | - Marize Pereira Miagostovich
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Av. Brasil, 4365, Manguinhos, Rio de Janeiro, CEP 21040-360, Brazil
| | - Maria Inês Zanoli Sato
- Department of Environmental Analysis, Environmental Company of the São Paulo State (CETESB), Av. Prof. Frederico Hermann Jr., 345, São Paulo CEP 05459-900, Brazil
| | - Veronica Beatriz Rajal
- Instituto de Investigaciones para la Industria Química (INIQUI), Universidad Nacional de Salta (UNSa) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and Facultad de Ingeniería, UNSa, Av. Bolivia 5150, Salta 4400, Argentina; Singapore Centre for Environmental Life Science Engineering (SCELSE), Nanyang Technological University, Singapore
| | - Cesar Rossas Mota Filho
- Department of Sanitary and Environmental Engineering, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil
| | - Alyne Duarte Pereira
- Department of Sanitary and Environmental Engineering, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil
| | - Mikaela Renata Funada Barbosa
- Department of Environmental Analysis, Environmental Company of the São Paulo State (CETESB), Av. Prof. Frederico Hermann Jr., 345, São Paulo CEP 05459-900, Brazil
| | - Camille Ferreira Mannarino
- Sergio Arouca National School of Public Health, Oswaldo Cruz Foundation, Av. Brasil, 4365, Manguinhos, Rio de Janeiro, CEP 21040-360, Brazil
| | - Agnes Soares da Silva
- Pan American Health Organization (PAHO/WHO), 525 23rd St NW, Washington, DC 20037, United States of America.
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Gao Z, Gao M, Chen CH, Zhou Y, Zhan ZH, Ren Y. Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:28373-28382. [PMID: 36662433 PMCID: PMC9867605 DOI: 10.1007/s11356-023-25237-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 01/05/2023] [Indexed: 04/16/2023]
Abstract
Wastewater-based epidemiology (WBE) has contributed significantly to the monitoring of drug use and transmission of viruses that has been published in numerous research papers. In this paper, we used LitStraw, a self-developed text extraction tool, to extract, analyze, and construct knowledge graphs from nearly 900 related papers in PDF format collected in Web of Science from 2000 to 2021 to analyze the research hotspots and development trends of WBE. The results showed a growing number of WBE publications in multidisciplinary cross-collaboration, with more publications and close collaboration between the USA, Australia, China, and European countries. The keywords of illicit drugs and pharmaceuticals still maintain research hotness, but the specific research hotspots change significantly, among which the research hotspots of new psychoactive substances, biomarkers, and stability show an increasing trend. In addition, judging the spread of COVID-19 by the presence of SARS-CoV-2 RNA in sewage has become the focus since 2020. This work can show the development of WBE more clearly by constructing a knowledge graph and also provide new ideas for the paper mining analysis methods in different fields.
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Affiliation(s)
- Zhihan Gao
- School of Environment and Energy, South China University of Technology, Higher Education Mega Center, 510006, Guangzhou, China
| | - Min Gao
- School of Computer Science and Engineering, South China University of Technology, 510006, Guangzhou, China
| | - Chun-Hua Chen
- School of Software Engineering, South China University of Technology, 510006, Guangzhou, China
| | - Yifan Zhou
- School of Electronic and Information Engineering, South China University of Technology, 510006, Guangzhou, China
| | - Zhi-Hui Zhan
- School of Computer Science and Engineering, South China University of Technology, 510006, Guangzhou, China
| | - Yuan Ren
- School of Environment and Energy, South China University of Technology, Higher Education Mega Center, 510006, Guangzhou, China.
- The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, 510006, Guangzhou, China.
- The Key Laboratory of Environmental Protection and Eco-Remediation of Guangdong Regular Higher Education Institution, 510006, Guangzhou, China.
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Daza-Torres ML, Montesinos-López JC, Kim M, Olson R, Bess CW, Rueda L, Susa M, Tucker L, García YE, Schmidt AJ, Naughton CC, Pollock BH, Shapiro K, Nuño M, Bischel HN. Model training periods impact estimation of COVID-19 incidence from wastewater viral loads. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159680. [PMID: 36306854 PMCID: PMC9597566 DOI: 10.1016/j.scitotenv.2022.159680] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 05/13/2023]
Abstract
Wastewater-based epidemiology (WBE) has been deployed broadly as an early warning tool for emerging COVID-19 outbreaks. WBE can inform targeted interventions and identify communities with high transmission, enabling quick and effective responses. As the wastewater (WW) becomes an increasingly important indicator for COVID-19 transmission, more robust methods and metrics are needed to guide public health decision-making. This research aimed to develop and implement a mathematical framework to infer incident cases of COVID-19 from SARS-CoV-2 levels measured in WW. We propose a classification scheme to assess the adequacy of model training periods based on clinical testing rates and assess the sensitivity of model predictions to training periods. A testing period is classified as adequate when the rate of change in testing is greater than the rate of change in cases. We present a Bayesian deconvolution and linear regression model to estimate COVID-19 cases from WW data. The effective reproductive number is estimated from reconstructed cases using WW. The proposed modeling framework was applied to three Northern California communities served by distinct WW treatment plants. The results showed that training periods with adequate testing are essential to provide accurate projections of COVID-19 incidence.
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Affiliation(s)
- Maria L Daza-Torres
- Department of Public Health Sciences, University of California Davis, Davis, CA 95616, United States.
| | | | - Minji Kim
- Department of Pathology, Microbiology and Immunology, School of Veterinary Medicine, University of California Davis, Davis, CA 95616, United States
| | - Rachel Olson
- Department of Civil and Environmental Engineering, University of California Davis, Davis, CA 95616, United States
| | - C Winston Bess
- Department of Civil and Environmental Engineering, University of California Davis, Davis, CA 95616, United States
| | - Lezlie Rueda
- Department of Pathology, Microbiology and Immunology, School of Veterinary Medicine, University of California Davis, Davis, CA 95616, United States
| | - Mirjana Susa
- Department of Public Health Sciences, University of California Davis, Davis, CA 95616, United States
| | - Linnea Tucker
- Department of Civil and Environmental Engineering, University of California Davis, Davis, CA 95616, United States
| | - Yury E García
- Department of Public Health Sciences, University of California Davis, Davis, CA 95616, United States
| | - Alec J Schmidt
- Department of Public Health Sciences, University of California Davis, Davis, CA 95616, United States
| | - Colleen C Naughton
- Department of Civil and Environmental Engineering, University of California Merced, Merced, CA 95343, United States
| | - Brad H Pollock
- Department of Public Health Sciences, University of California Davis, Davis, CA 95616, United States
| | - Karen Shapiro
- Department of Pathology, Microbiology and Immunology, School of Veterinary Medicine, University of California Davis, Davis, CA 95616, United States
| | - Miriam Nuño
- Department of Public Health Sciences, University of California Davis, Davis, CA 95616, United States
| | - Heather N Bischel
- Department of Civil and Environmental Engineering, University of California Davis, Davis, CA 95616, United States.
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Gagliano E, Biondi D, Roccaro P. Wastewater-based epidemiology approach: The learning lessons from COVID-19 pandemic and the development of novel guidelines for future pandemics. CHEMOSPHERE 2023; 313:137361. [PMID: 36427570 PMCID: PMC9678975 DOI: 10.1016/j.chemosphere.2022.137361] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 11/20/2022] [Accepted: 11/21/2022] [Indexed: 05/05/2023]
Abstract
Wastewater-based epidemiology (WBE) provides a comprehensive real-time framework of population attitude and health status. This approach is attracting the interest of medical community and health authorities to monitor the prevalence of a virus (such as the severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) among a community. Indeed, WBE is currently fine-tuning as environmental surveillance tool for coronavirus disease 2019 (COVID-19) pandemic. After a bibliometric analysis conducted to discover the research trends in WBE field, this work aimed to side-by-side compare the conventional method based on clinical testing with WBE approach. Furthermore, novel guidelines were developed to apply the WBE approach to a pandemic. The growing interest on WBE approach for COVID-19 pandemic is demonstrated by looking at the sharp increase in scientific papers published in the last years and at the ongoing studies on viral quantification methods and analytical procedures. The side-by-side comparison highlighted the ability of WBE to identify the hot-spot areas faster than the conventional approach, reducing the costs (e.g., rational use of available resources) and the gatherings at medical centers. Contrary to clinical testing, WBE has the surveillance capacity for preventing the virus resurgence, including asymptomatic contribution, and ensuring the preservation of medical staff health by avoiding the exposure to the virus infection during clinical testing. As extensively reported, the time in collecting epidemiological data is crucial for establishing the prevention and mitigation measures that are essential for curbing a pandemic. The developed guidelines can help to build a WBE system useful to control any future pandemic.
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Affiliation(s)
- Erica Gagliano
- Department of Civil Engineering and Architecture, University of Catania, Catania, Italy; Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy
| | - Deborah Biondi
- Department of Civil Engineering and Architecture, University of Catania, Catania, Italy
| | - Paolo Roccaro
- Department of Civil Engineering and Architecture, University of Catania, Catania, Italy.
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Helm B, Geissler M, Mayer R, Schubert S, Oertel R, Dumke R, Dalpke A, El-Armouche A, Renner B, Krebs P. Regional and temporal differences in the relation between SARS-CoV-2 biomarkers in wastewater and estimated infection prevalence - Insights from long-term surveillance. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159358. [PMID: 36240928 PMCID: PMC9554318 DOI: 10.1016/j.scitotenv.2022.159358] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 10/06/2022] [Accepted: 10/07/2022] [Indexed: 06/16/2023]
Abstract
Wastewater-based epidemiology provides a conceptual framework for the evaluation of the prevalence of public health related biomarkers. In the context of the Coronavirus disease-2019, wastewater monitoring emerged as a complementary tool for epidemic management. In this study, we evaluated data from six wastewater treatment plants in the region of Saxony, Germany. The study period lasted from February to December 2021 and covered the third and fourth regional epidemic waves. We collected 1065 daily composite samples and analyzed SARS-CoV-2 RNA concentrations using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Regression models quantify the relation between RNA concentrations and disease prevalence. We demonstrated that the relation is site and time specific. Median loads per diagnosed case differed by a factor of 3-4 among sites during both waves and were on average 45 % higher during the third wave. In most cases, log-log-transformed data achieved better regression performance than non-transformed data and local calibration outperformed global models for all sites. The inclusion of lag/lead time, discharge and detection probability improved model performance in all cases significantly, but the importance of these components was also site and time specific. In all cases, models with lag/lead time and log-log-transformed data obtained satisfactory goodness-of-fit with adjusted coefficients of determination higher than 0.5. Back-estimation of testing efficiency from wastewater data confirmed state-wide prevalence estimation from individual testing statistics, but revealed pronounced differences throughout the epidemic waves and among the different sites.
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Affiliation(s)
- Björn Helm
- Institute of Urban and Industrial Water Management, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany.
| | - Michael Geissler
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Robin Mayer
- Institute of Urban and Industrial Water Management, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany
| | - Sara Schubert
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; Institute of Hydrobiology, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany
| | - Reinhard Oertel
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Roger Dumke
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Alexander Dalpke
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; University Heidelberg, Institute of Medical Microbiology and Hygiene, Heidelberg, Germany
| | - Ali El-Armouche
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; Institute of Pharmacology and Toxicology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Bertold Renner
- Institute of Clinical Pharmacology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Peter Krebs
- Institute of Urban and Industrial Water Management, Technische Universität Dresden, Helmholtzstrasse 10, 01069 Dresden, Germany
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Li X, Zhang S, Sherchan S, Orive G, Lertxundi U, Haramoto E, Honda R, Kumar M, Arora S, Kitajima M, Jiang G. Correlation between SARS-CoV-2 RNA concentration in wastewater and COVID-19 cases in community: A systematic review and meta-analysis. JOURNAL OF HAZARDOUS MATERIALS 2023; 441:129848. [PMID: 36067562 PMCID: PMC9420035 DOI: 10.1016/j.jhazmat.2022.129848] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 05/26/2023]
Abstract
Wastewater-based epidemiology (WBE) has been considered as a promising approach for population-wide surveillance of coronavirus disease 2019 (COVID-19). Many studies have successfully quantified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater (CRNA). However, the correlation between the CRNA and the COVID-19 clinically confirmed cases in the corresponding wastewater catchments varies and the impacts of environmental and other factors remain unclear. A systematic review and meta-analysis were conducted to identify the correlation between CRNA and various types of clinically confirmed case numbers, including prevalence and incidence rates. The impacts of environmental factors, WBE sampling design, and epidemiological conditions on the correlation were assessed for the same datasets. The systematic review identified 133 correlation coefficients, ranging from -0.38 to 0.99. The correlation between CRNA and new cases (either daily new, weekly new, or future cases) was stronger than that of active cases and cumulative cases. These correlation coefficients were potentially affected by environmental and epidemiological conditions and WBE sampling design. Larger variations of air temperature and clinical testing coverage, and the increase of catchment size showed strong negative impacts on the correlation between CRNA and COVID-19 case numbers. Interestingly, the sampling technique had negligible impact although increasing the sampling frequency improved the correlation. These findings highlight the importance of viral shedding dynamics, in-sewer decay, WBE sampling design and clinical testing on the accurate back-estimation of COVID-19 case numbers through the WBE approach.
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Affiliation(s)
- Xuan Li
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, Australia; Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Shuxin Zhang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, Australia
| | - Samendrdra Sherchan
- Department of Environmental Health Sciences, Tulane University, New Orleans, LA 70112, USA
| | - Gorka Orive
- NanoBioCel Group, Laboratory of Pharmaceutics, School of Pharmacy, University of the Basque Country UPV/EHU, Paseo de la Universidad 7, Vitoria-Gasteiz 01006, Spain; Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Vitoria-Gasteiz, Spain
| | - Unax Lertxundi
- Bioaraba Health Research Institute; Osakidetza Basque Health Service, Araba Mental Health Network, Araba Psychiatric Hospital, Pharmacy Service, Vitoria-Gasteiz, Spain
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, Kofu, Japan
| | - Ryo Honda
- Faculty of Geosciences and Civil Engineering, Kanazawa University, Kanazawa, Japan
| | - Manish Kumar
- Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India
| | - Sudipti Arora
- Dr. B. Lal Institute of Biotechnology, Jaipur, India
| | - Masaaki Kitajima
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, Hokkaido, Japan
| | - Guangming Jiang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, Australia; Illawarra Health and Medical Research Institute (IHMRI), University of Wollongong, Wollongong, Australia.
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43
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McMinn BR, Korajkic A, Pemberton AC, Kelleher J, Ahmed W, Villegas EN, Oshima K. Assessment of two volumetrically different concentration approaches to improve sensitivities for SARS-CoV-2 detection during wastewater monitoring. J Virol Methods 2023; 311:114645. [PMID: 36332716 PMCID: PMC9624105 DOI: 10.1016/j.jviromet.2022.114645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 10/31/2022] [Indexed: 11/06/2022]
Abstract
Wastewater monitoring for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), the virus responsible for the global coronavirus disease 2019 (COVID-19) pandemic, has highlighted the need for methodologies capable of assessing viral prevalence during periods of low population infection. To address this need, two volumetrically different, methodologically similar concentration approaches were compared for their abilities to detect viral nucleic acid and infectious SARS-CoV-2 signal from primary influent samples. For Method 1, 2 L of SARS-CoV-2 seeded wastewater was evaluated using a dead-end hollow fiber ultrafilter (D-HFUF) for primary concentration, followed by the CP Select™ for secondary concentration. For Method 2, 100 mL of SARS-CoV-2 seeded wastewater was evaluated using the CP Select™ procedure. Following D-HFUF concentration (Method 1), significantly lower levels of infectious SARS-CoV-2 were lost (P value range: 0.0398-0.0027) compared to viral gene copy (GC) levels detected by the US Centers for Disease Control (CDC) N1 and N2 reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR) assays. Subsamples at different steps in the concentration process were also taken to better characterize the losses of SARS-CoV-2 during the concentration process. During the centrifugation step (prior to CP Select™ concentration), significantly higher losses (P value range: 0.0003 to <0.0001) occurred for SARS-CoV-2 GC levels compared to infectious virus for Method 1, while between the methods, significantly higher infectious viral losses were observed for Method 2 (P = 0.0002). When analyzing overall recovery of endogenous SARS-CoV-2 in wastewater samples, application of Method 1 improved assay sensitivities (P = <0.0001) compared with Method 2; this was especially evident during periods of lower COVID-19 case rates within the sewershed. This study describes a method which can successfully concentrate infectious SARS-CoV-2 and viral RNA from wastewater. Moreover, we demonstrated that large volume wastewater concentration provides additional sensitivity needed to improve SARS-CoV-2 detection, especially during low levels of community disease prevalence.
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Affiliation(s)
- Brian R. McMinn
- Office of Research and Development, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, OH 45268 United States,Corresponding author
| | - Asja Korajkic
- Office of Research and Development, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, OH 45268 United States
| | - Adin C. Pemberton
- Office of Research and Development, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, OH 45268 United States
| | - Julie Kelleher
- Office of Research and Development, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, OH 45268 United States
| | - Warish Ahmed
- CSIRO Land and Water, Ecosciences Precinct, 41 Boggo Road, QLD 4102, Australia
| | - Eric N. Villegas
- Office of Research and Development, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, OH 45268 United States
| | - Kevin Oshima
- Office of Research and Development, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, OH 45268 United States
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44
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D'Aoust PM, Tian X, Towhid ST, Xiao A, Mercier E, Hegazy N, Jia JJ, Wan S, Kabir MP, Fang W, Fuzzen M, Hasing M, Yang MI, Sun J, Plaza-Diaz J, Zhang Z, Cowan A, Eid W, Stephenson S, Servos MR, Wade MJ, MacKenzie AE, Peng H, Edwards EA, Pang XL, Alm EJ, Graber TE, Delatolla R. Wastewater to clinical case (WC) ratio of COVID-19 identifies insufficient clinical testing, onset of new variants of concern and population immunity in urban communities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 853:158547. [PMID: 36067855 PMCID: PMC9444156 DOI: 10.1016/j.scitotenv.2022.158547] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/10/2022] [Accepted: 09/01/2022] [Indexed: 05/14/2023]
Abstract
Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) will have greater value as an important diagnostic tool. An in-depth analysis and understanding of the metrics derived from WWS is required to interpret and utilize WWS-acquired data effectively (McClary-Gutierrez et al., 2021; O'Keeffe, 2021). In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven cities in Canada over periods ranging from 8 to 21 months. This work demonstrates that significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing (resulting in a reduction to testing access and a reduction in the number of daily tests) in these communities, despite increases in the wastewater signal. Furthermore, the WC ratio decreased significantly in 6 of the 7 studied locations, serving as a potential signal of the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community (40-60 % allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community (40-60 % allelic proportion). Finally, a significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant's greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when community immunity was high. The WC ratio, used as an additional monitoring metric, could complement clinical case counts and wastewater signals as individual metrics in its potential ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.
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Affiliation(s)
- Patrick M D'Aoust
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Xin Tian
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | | | - Amy Xiao
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - Elisabeth Mercier
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Nada Hegazy
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Jian-Jun Jia
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Shen Wan
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Md Pervez Kabir
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Wanting Fang
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Meghan Fuzzen
- Department of Biology, University of Waterloo, Waterloo, Canada
| | - Maria Hasing
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Canada
| | - Minqing Ivy Yang
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada
| | - Jianxian Sun
- Department of Chemistry, University of Toronto, Toronto, Canada
| | - Julio Plaza-Diaz
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Zhihao Zhang
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Aaron Cowan
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada
| | - Walaa Eid
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Sean Stephenson
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Mark R Servos
- Department of Biology, University of Waterloo, Waterloo, Canada
| | - Matthew J Wade
- Data, Analytics and Surveillance Group, UK Health Security Agency, London, United Kingdom
| | - Alex E MacKenzie
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Hui Peng
- Department of Chemistry, University of Toronto, Toronto, Canada
| | - Elizabeth A Edwards
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada
| | - Xiao-Li Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Canada
| | - Eric J Alm
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - Tyson E Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, Canada.
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45
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Zhang X, Zhang L, Wang Y, Zhang M, Zhou J, Liu X, Wang Y, Qu C, Han W, Hou M, Deng F, Luo Y, Mao Y, Gu W, Dong Z, Pan Y, Zhang D, Tang S, Zhang L. Detection of the SARS-CoV-2 Delta Variant in the Transboundary Rivers of Yunnan, China. ACS ES&T WATER 2022; 2:2367-2377. [PMID: 37552741 PMCID: PMC9631342 DOI: 10.1021/acsestwater.2c00224] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 10/08/2022] [Accepted: 10/10/2022] [Indexed: 05/30/2023]
Abstract
Ruili and Longchuan, two border counties in southwestern China, are facing epidemic control challenges due to the high rate of COVID-19 infections originating from neighboring Myanmar. Here, we aimed to establish the applicability of wastewater and environmental water surveillance of SARS-CoV-2 and conduct whole-genome sequencing (WGS) to trace the possible infection origin. In August 2021, total 72 wastewater and river water samples were collected from 32 sampling sites. SARS-CoV-2 ORF1ab and N genes were measured by RT-qPCR. We found that 19 samples (26.39%) were positive, and the viral loads of ORF1ab and N genes were 6.62 × 102-2.55×105 and 1.86 × 103-2.32 × 105 copies/L, respectively. WGS further indicated the sequences in two transboundary river samples, and one hospital wastewater sample belonged to the delta variant, suggesting that the infection source might be areas with high COVID-19 delta variant incidence in Southeast Asia (e.g., Myanmar). We reported for the first time the detection and quantification of SARS-CoV-2 RNA in the transboundary rivers of Myanmar-China. Our findings demonstrate that wastewater and environmental water may provide independent and nonintrusive surveillance points to monitor the global spread of emerging COVID-19 variants of concern, particularly in high-risk regions or border areas with considerable epidemic challenges and poor wastewater treatment facilities.
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Affiliation(s)
- Xiao Zhang
- China CDC Key Laboratory of Environment and Population
Health, National Institute of Environmental Health, Chinese Center for
Disease Control and Prevention, Beijing100021,
China
| | - Liang Zhang
- China CDC Key Laboratory of Environment and Population
Health, National Institute of Environmental Health, Chinese Center for
Disease Control and Prevention, Beijing100021,
China
| | - Yuanyuan Wang
- China CDC Key Laboratory of Environment and Population
Health, National Institute of Environmental Health, Chinese Center for
Disease Control and Prevention, Beijing100021,
China
| | - Meiling Zhang
- Acute Infectious Disease Prevention and Control
Institute, Yunnan Center for Disease Control and Prevention,
Kunming, Yunnan650022, China
| | - Jienan Zhou
- Acute Infectious Disease Prevention and Control
Institute, Yunnan Center for Disease Control and Prevention,
Kunming, Yunnan650022, China
| | - Xin Liu
- Ruili Center for Disease Control and
Prevention, Ruili, Yunnan678599, China
| | - Yan Wang
- Ruili Center for Disease Control and
Prevention, Ruili, Yunnan678599, China
| | - Changsheng Qu
- Longchuan Center for Disease Control and
Prevention, Longchuan, Yunnan678799, China
| | - Wenxiang Han
- Longchuan Center for Disease Control and
Prevention, Longchuan, Yunnan678799, China
| | - Min Hou
- China CDC Key Laboratory of Environment and Population
Health, National Institute of Environmental Health, Chinese Center for
Disease Control and Prevention, Beijing100021,
China
| | - Fuchang Deng
- China CDC Key Laboratory of Environment and Population
Health, National Institute of Environmental Health, Chinese Center for
Disease Control and Prevention, Beijing100021,
China
| | - Yueyun Luo
- China CDC Key Laboratory of Environment and Population
Health, National Institute of Environmental Health, Chinese Center for
Disease Control and Prevention, Beijing100021,
China
| | - Yixin Mao
- China CDC Key Laboratory of Environment and Population
Health, National Institute of Environmental Health, Chinese Center for
Disease Control and Prevention, Beijing100021,
China
| | - Wen Gu
- China CDC Key Laboratory of Environment and Population
Health, National Institute of Environmental Health, Chinese Center for
Disease Control and Prevention, Beijing100021,
China
| | - Zhaomin Dong
- School of Space and Environment, Beihang
University, Beijing100191, China
| | - Yang Pan
- Institute for Infectious Disease and Endemic Disease Control,
Beijing Center for Disease Prevention and Control,
Beijing100013, China
| | - Daitao Zhang
- Institute for Infectious Disease and Endemic Disease Control,
Beijing Center for Disease Prevention and Control,
Beijing100013, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population
Health, National Institute of Environmental Health, Chinese Center for
Disease Control and Prevention, Beijing100021,
China
| | - Lan Zhang
- China CDC Key Laboratory of Environment and Population
Health, National Institute of Environmental Health, Chinese Center for
Disease Control and Prevention, Beijing100021,
China
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46
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Verani M, Federigi I, Muzio S, Lauretani G, Calà P, Mancuso F, Salvadori R, Valentini C, La Rosa G, Suffredini E, Carducci A. Calibration of Methods for SARS-CoV-2 Environmental Surveillance: A Case Study from Northwest Tuscany. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:16588. [PMID: 36554466 PMCID: PMC9778686 DOI: 10.3390/ijerph192416588] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/02/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
The current pandemic has provided an opportunity to test wastewater-based epidemiology (WBE) as a complementary method to SARS-CoV-2 monitoring in the community. However, WBE infection estimates can be affected by uncertainty factors, such as heterogeneity in analytical procedure, wastewater volume, and population size. In this paper, raw sewage SARS-CoV-2 samples were collected from four wastewater treatment plants (WWTPs) in Tuscany (Northwest Italy) between February and December 2021. During the surveillance period, viral concentration was based on polyethylene glycol (PEG), but its precipitation method was modified from biphasic separation to centrifugation. Therefore, in parallel, the recovery efficiency of each method was evaluated at lab-scale, using two spiking viruses (human coronavirus 229E and mengovirus vMC0). SARS-CoV-2 genome was found in 80 (46.5%) of the 172 examined samples. Lab-scale experiments revealed that PEG precipitation using centrifugation had the best recovery efficiency (up to 30%). Viral SARS-CoV-2 load obtained from sewage data, adjusted by analytical method and normalized by population of each WWTP, showed a good association with the clinical data in the study area. This study highlights that environmental surveillance data need to be carefully analyzed before their use in the WBE, also considering the sensibility of the analytical methods.
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Affiliation(s)
- Marco Verani
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127 Pisa, Italy
| | - Ileana Federigi
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127 Pisa, Italy
| | - Sara Muzio
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127 Pisa, Italy
| | - Giulia Lauretani
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127 Pisa, Italy
| | - Piergiuseppe Calà
- Tuscany Region-Health, Department of Prevention Local Health Authority Tuscany Center, Via S. Salvi 12, 50135 Firenze, Italy
| | - Fabrizio Mancuso
- Ingegnerie Toscane-Area R&D, Via Bellatalla 1, 56121 Pisa, Italy
| | | | | | - Giuseppina La Rosa
- Department of Environment and Health, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Elisabetta Suffredini
- Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Annalaura Carducci
- Laboratory of Hygiene and Environmental Virology, Department of Biology, University of Pisa, Via S. Zeno 35/39, 56127 Pisa, Italy
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47
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Bonanno Ferraro G, Veneri C, Mancini P, Iaconelli M, Suffredini E, Bonadonna L, Lucentini L, Bowo-Ngandji A, Kengne-Nde C, Mbaga DS, Mahamat G, Tazokong HR, Ebogo-Belobo JT, Njouom R, Kenmoe S, La Rosa G. A State-of-the-Art Scoping Review on SARS-CoV-2 in Sewage Focusing on the Potential of Wastewater Surveillance for the Monitoring of the COVID-19 Pandemic. FOOD AND ENVIRONMENTAL VIROLOGY 2022; 14:315-354. [PMID: 34727334 PMCID: PMC8561373 DOI: 10.1007/s12560-021-09498-6] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 09/21/2021] [Indexed: 05/07/2023]
Abstract
The outbreak of coronavirus infectious disease-2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has rapidly spread throughout the world. Several studies have shown that detecting SARS-CoV-2 in untreated wastewater can be a useful tool to identify new outbreaks, establish outbreak trends, and assess the prevalence of infections. On 06 May 2021, over a year into the pandemic, we conducted a scoping review aiming to summarize research data on SARS-CoV-2 in sewage. Papers dealing with raw sewage collected at wastewater treatment plants, sewer networks, septic tanks, and sludge treatment facilities were included in this review. We also reviewed studies on sewage collected in community settings such as private or municipal hospitals, healthcare facilities, nursing homes, dormitories, campuses, airports, aircraft, and cruise ships. The literature search was conducted using the electronic databases PubMed, EMBASE, and Web Science Core Collection. This comprehensive research yielded 1090 results, 66 of which met the inclusion criteria and are discussed in this review. Studies from 26 countries worldwide have investigated the occurrence of SARS-CoV-2 in sewage of different origin. The percentage of positive samples in sewage ranged from 11.6 to 100%, with viral concentrations ranging from ˂LOD to 4.6 × 108 genome copies/L. This review outlines the evidence currently available on wastewater surveillance: (i) as an early warning system capable of predicting COVID-19 outbreaks days or weeks before clinical cases; (ii) as a tool capable of establishing trends in current outbreaks; (iii) estimating the prevalence of infections; and (iv) studying SARS-CoV-2 genetic diversity. In conclusion, as a cost-effective, rapid, and reliable source of information on the spread of SARS-CoV-2 and its variants in the population, wastewater surveillance can enhance genomic and epidemiological surveillance with independent and complementary data to inform public health decision-making during the ongoing pandemic.
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Affiliation(s)
- G Bonanno Ferraro
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | | | - P Mancini
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - M Iaconelli
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - E Suffredini
- Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
| | - L Bonadonna
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - L Lucentini
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - A Bowo-Ngandji
- Department of Microbiology, The University of Yaounde I, Yaounde, Cameroon
| | - C Kengne-Nde
- Research Monitoring and Planning Unit, National Aids Control Committee, Douala, Cameroon
| | - D S Mbaga
- Department of Microbiology, The University of Yaounde I, Yaounde, Cameroon
| | - G Mahamat
- Department of Microbiology, The University of Yaounde I, Yaounde, Cameroon
| | - H R Tazokong
- Department of Microbiology, The University of Yaounde I, Yaounde, Cameroon
| | - J T Ebogo-Belobo
- Medical Research Centre, Institute of Medical Research and Medicinal Plants Studies, Yaounde, Cameroon
| | - R Njouom
- Virology Department, Centre Pasteur of Cameroon, Yaounde, Cameroon
| | - S Kenmoe
- Virology Department, Centre Pasteur of Cameroon, Yaounde, Cameroon
| | - G La Rosa
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy.
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48
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Parra-Arroyo L, Martinez-Ruiz M, Lucero S, Oyervides-Muñoz MA, Wilkinson M, Melchor-Martínez EM, Araújo RG, Coronado-Apodaca KG, Velasco Bedran H, Buitrón G, Noyola A, Barceló D, Iqbal HM, Sosa-Hernández JE, Parra-Saldívar R. Degradation of viral RNA in wastewater complex matrix models and other standards for wastewater-based epidemiology: A review. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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49
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Silva CS, Tryndyak VP, Camacho L, Orloff MS, Porter A, Garner K, Mullis L, Azevedo M. Temporal dynamics of SARS-CoV-2 genome and detection of variants of concern in wastewater influent from two metropolitan areas in Arkansas. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 849:157546. [PMID: 35914602 PMCID: PMC9338166 DOI: 10.1016/j.scitotenv.2022.157546] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 07/14/2022] [Accepted: 07/17/2022] [Indexed: 06/15/2023]
Abstract
Although SARS-CoV-2 can cause severe illness and death, a percentage of the infected population is asymptomatic. This, along with other factors, such as insufficient diagnostic testing and underreporting due to self-testing, contributes to the silent transmission of SARS-CoV-2 and highlights the importance of implementing additional surveillance tools. The fecal shedding of the virus from infected individuals enables its detection in community wastewater, and this has become a valuable public health tool worldwide as it allows the monitoring of the disease on a populational scale. Here, we monitored the presence of SARS-CoV-2 and its dynamic genomic changes in wastewater sampled from two metropolitan areas in Arkansas during major surges of COVID-19 cases and assessed how the viral titers in these samples related to the clinical case counts between late April 2020 and January 2022. The levels of SARS-CoV-2 RNA were quantified by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) using a set of TaqMan assays targeting three different viral genes (encoding ORF1ab polyprotein, surface glycoprotein, and nucleocapsid phosphoprotein). An allele-specific RT-qPCR approach was used to screen the samples for SARS-CoV-2 mutations. The identity and genetic diversity of the virus were further investigated through amplicon-based RNA sequencing, and SARS-CoV-2 variants of concern were detected in wastewater samples throughout the duration of this study. Our data show how changes in the virus genome can affect the sensitivity of specific RT-qPCR assays used in COVID-19 testing with the surge of new variants. A significant association was observed between viral titers in wastewater and recorded number of COVID-19 cases in the areas studied, except when assays failed to detect targets due to the presence of particular variants. These findings support the use of wastewater surveillance as a reliable complementary tool for monitoring SARS-CoV-2 and its genetic variants at the community level.
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Affiliation(s)
- Camila S Silva
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA.
| | - Volodymyr P Tryndyak
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Luísa Camacho
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Mohammed S Orloff
- Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Center for the Studies of Tobacco, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Austin Porter
- Department of Health Policy and Management, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Arkansas Department of Health, Little Rock, AR, USA
| | - Kelley Garner
- Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Arkansas Department of Health, Little Rock, AR, USA
| | - Lisa Mullis
- Division of Microbiology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Marli Azevedo
- Division of Microbiology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
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Nguyen Quoc B, Saingam P, RedCorn R, Carter JA, Jain T, Candry P, Gattuso M, Huang MLW, Greninger AL, Meschke JS, Bryan A, Winkler MKH. Case Study: Impact of Diurnal Variations and Stormwater Dilution on SARS-CoV-2 RNA Signal Intensity at Neighborhood Scale Wastewater Pumping Stations. ACS ES&T WATER 2022; 2:1964-1975. [PMID: 37552740 PMCID: PMC9261832 DOI: 10.1021/acsestwater.2c00016] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 06/09/2022] [Accepted: 06/10/2022] [Indexed: 05/14/2023]
Abstract
Wastewater based epidemiology (WBE) has emerged as a tool to track the spread of SARS-CoV-2. However, sampling at wastewater treatment plants (WWTPs) cannot identify transmission hotspots within a city. Here, we sought to understand the diurnal variations (24 h) in SARS-CoV-2 RNA titers at the neighborhood level, using pump stations that serve vulnerable communities (e.g., essential workers, more diverse communities). Hourly composite samples were collected from wastewater pump stations located in (i) a residential area and (ii) a shopping district. In the residential area, SARS-CoV-2 RNA concentration (N1, N2, and E assays) varied by up to 42-fold within a 24 h period. The highest viral load was observed between 5 and 7 am, when viral RNA was not diluted by stormwater. Normalizing peak concentrations during this time window with nutrient concentrations (N and P) enabled correcting for rainfall to connect sewage to clinical cases reported in the sewershed. Data from the shopping district pump station were inconsistent, probably due to the fluctuation of customers shopping at the mall. This work indicates pump stations serving the residential area offer a narrow time period of high signal intensity that could improve the sensitivity of WBE, and tracer compounds (N, P concentration) can be used to normalize SARS-CoV-2 signals during rainfall.
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Affiliation(s)
- Bao Nguyen Quoc
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - Prakit Saingam
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - Raymond RedCorn
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - John A. Carter
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - Tanisha Jain
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - Pieter Candry
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - Meghan Gattuso
- Seattle Public Utilities,
Seattle, Washington 98124, United States
| | - Meei-Li W. Huang
- Dept of Laboratory Medicine and Pathology,
University of Washington, Seattle, Washington 98105,
United States
| | - Alexander L. Greninger
- Dept of Laboratory Medicine and Pathology,
University of Washington, Seattle, Washington 98105,
United States
| | - John Scott Meschke
- Department of Environmental & Occupational Health
Sciences, University of Washington, Seattle, Washington 98105,
United States
| | - Andrew Bryan
- Dept of Laboratory Medicine and Pathology,
University of Washington, Seattle, Washington 98105,
United States
| | - Mari K. H. Winkler
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
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