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Price M, Simpson BS, Tscharke BJ, Ahmed F, Keller EL, Sussex H, Kah M, Sila-Nowicka K, Chappell A, Gerber C, Trowsdale S. Reporting population size in wastewater-based epidemiology: A scoping review. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 953:176076. [PMID: 39244059 DOI: 10.1016/j.scitotenv.2024.176076] [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: 06/19/2024] [Revised: 08/20/2024] [Accepted: 09/04/2024] [Indexed: 09/09/2024]
Abstract
Knowledge of the number of people present in a catchment is fundamental for the assessment of spatio-temporal trends in wastewater-based epidemiology (WBE). Accurately estimating the number of people connected to wastewater catchments is challenging however, because populations are dynamic. Methods used to estimate population size can significantly influence the calculation and interpretation of population-normalised wastewater data (PNWD). This paper systematically reviews the reporting of population data in 339 WBE studies. Studies were evaluated based on their reporting of population size, the source of population data, the population calculation methods, and the uncertainties in population estimates. Most papers reported population size (96 %) and the source of population data (60 %). Fewer studies reported the uncertainties in their population data (50 %) and the methods used to calculate these estimates (28 %). This is relevant because different methods have unique strengths and limitations which can affect the accuracy of PNWD. Only 64 studies (19 %) reported all four components of population data. The reporting of population data has remained consistent in the past decade. Based on the findings, we recommend generalised reporting criteria for population data in WBE. As WBE is further mainstreamed and applied, the clear and comprehensive reporting of population data will only become increasingly important.
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Affiliation(s)
- Mackay Price
- School of Environment, University of Auckland, 23 Symonds Street, Auckland 1010, New Zealand.
| | - Bradley S Simpson
- Clinical and Health Sciences, University of South Australia, Adelaide, South Australia 5000, Australia
| | - Benjamin J Tscharke
- Queensland Alliance for Environmental Health Sciences, University of Queensland, 20 Cornwall Street, Queensland 4102, Australia
| | - Fahad Ahmed
- Independent researcher, Brisbane, Queensland, Australia
| | - Emma L Keller
- Clinical and Health Sciences, University of South Australia, Adelaide, South Australia 5000, Australia
| | | | - Melanie Kah
- School of Environment, University of Auckland, 23 Symonds Street, Auckland 1010, New Zealand
| | - Katarzyna Sila-Nowicka
- School of Environment, University of Auckland, 23 Symonds Street, Auckland 1010, New Zealand; Institute of Geodesy and Geoinformatics, Wroclaw University of Environmental and Life Sciences, Wroclaw 50-357, Poland
| | - Andrew Chappell
- Institute of Environmental Science and Research (ESR) Ltd., 27 Creyke Road, Ilam, Christchurch 8041, New Zealand
| | - Cobus Gerber
- Clinical and Health Sciences, University of South Australia, Adelaide, South Australia 5000, Australia
| | - Sam Trowsdale
- School of Environment, University of Auckland, 23 Symonds Street, Auckland 1010, New Zealand
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Foladori P, Cutrupi F, Cadonna M, Postinghel M. Normalization of viral loads in Wastewater-Based Epidemiology using routine parameters: One year monitoring of SARS-CoV-2 in urban and tourist sewersheds. JOURNAL OF HAZARDOUS MATERIALS 2024; 478:135352. [PMID: 39128155 DOI: 10.1016/j.jhazmat.2024.135352] [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: 01/27/2024] [Revised: 07/13/2024] [Accepted: 07/26/2024] [Indexed: 08/13/2024]
Abstract
In wastewater-based epidemiology, normalization of experimental data is a crucial aspect, as emerged in the recent surveillance of COVID-19. Normalization facilitates the comparison between different areas or periods, and it helps in evaluating the differences due to the fluctuation of the population due to seasonal employment or tourism. Analysis of biomarkers in wastewater (i.e. drugs, beverage and food compounds, microorganisms such as PMMoV or crAssphage, etc.) is complex to perform, and it is not routinely monitored. This study compares the results of alternative normalization approaches applied to SARS-CoV-2 loads in wastewater using population size calculated with conventional hydraulic and/or chemical parameters (i.e. total suspended solids, chemical oxygen demand, nitrogen forms, etc.) commonly used in the routine monitoring of water quality. A total of 12 wastewater treatment plants were monitored, and 1068 samples of influent wastewater were collected in urban areas and in highly touristic areas (summer and/or winter). The results indicated that both census and population estimated with ammonium are effective and reliable parameters with which to normalize SARS-CoV-2 loads in wastewater from urban sewersheds with negligible fluctuating populations. However, this study reveals that, in the case of tourist locations, the population calculated using NH4-N loads can provide a better normalization of the specific viral load per inhabitant.
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Affiliation(s)
- Paola Foladori
- Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, Trento 38123, Italy.
| | - Francesca Cutrupi
- Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, Trento 38123, Italy
| | - Maria Cadonna
- ADEP, Agenzia per la Depurazione (Wastewater Treatment Agency), Autonomous Province of Trento, via Gilli 3, Trento 38121, Italy
| | - Mattia Postinghel
- ADEP, Agenzia per la Depurazione (Wastewater Treatment Agency), Autonomous Province of Trento, via Gilli 3, Trento 38121, Italy
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3
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Boogaerts T, Van Wichelen N, Quireyns M, Burgard D, Bijlsma L, Delputte P, Gys C, Covaci A, van Nuijs ALN. Current state and future perspectives on de facto population markers for normalization in wastewater-based epidemiology: A systematic literature review. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 935:173223. [PMID: 38761943 PMCID: PMC11270913 DOI: 10.1016/j.scitotenv.2024.173223] [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: 03/28/2024] [Revised: 05/10/2024] [Accepted: 05/11/2024] [Indexed: 05/20/2024]
Abstract
Wastewater-based epidemiology (WBE) and wastewater surveillance have become a valuable complementary data source to collect information on community-wide exposure through the measurement of human biomarkers in influent wastewater (IWW). In WBE, normalization of data with the de facto population that corresponds to a wastewater sample is crucial for a correct interpretation of spatio-temporal trends in exposure and consumption patterns. However, knowledge gaps remain in identifying and validating suitable de facto population biomarkers (PBs) for refinement of WBE back-estimations. WBE studies that apply de facto PBs (including hydrochemical parameters, utility consumption data sources, endo- and exogenous chemicals, biological biomarkers and signalling records) for relative trend analysis and absolute population size estimation were systematically reviewed from three databases (PubMed, Web of Science, SCOPUS) according to the PRISMA guidelines. We included in this review 81 publications that accounted for daily variations in population sizes by applying de facto population normalization. To date, a wide range of PBs have been proposed for de facto population normalization, complicating the comparability of normalized measurements across WBE studies. Additionally, the validation of potential PBs is complicated by the absence of an ideal external validator, magnifying the overall uncertainty for population normalization in WBE. Therefore, this review proposes a conceptual tier-based cross-validation approach for identifying and validating de facto PBs to guide their integration for i) relative trend analysis, and ii) absolute population size estimation. Furthermore, this review also provides a detailed evaluation of the uncertainty observed when comparing different de jure and de facto population estimation approaches. This study shows that their percentual differences can range up to ±200 %, with some exceptions showing even larger variations. This review underscores the need for collaboration among WBE researchers to further streamline the application of de facto population normalization and to evaluate the robustness of different PBs in different socio-demographic communities.
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Affiliation(s)
- Tim Boogaerts
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium; Exposome Center of Excellence, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Natan Van Wichelen
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium; Exposome Center of Excellence, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Maarten Quireyns
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium; Exposome Center of Excellence, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Dan Burgard
- Department of Chemistry and Biochemistry, University of Puget Sound, Tacoma, WA, USA
| | - Lubertus Bijlsma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Castellón, Spain
| | - Peter Delputte
- Laboratory for Microbiology, Parasitology and Hygiene, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium; Infla-Med Center of Excellence, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Celine Gys
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium; Exposome Center of Excellence, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Adrian Covaci
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium; Exposome Center of Excellence, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Alexander L N van Nuijs
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium; Exposome Center of Excellence, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
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Che X, Liu P, Ding Y, Tao W, Zheng X, Di B, Qiao H. In-sample stability and postsampling analysis of 21 illicit drugs, their metabolites and cotinine in wastewater. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 270:115900. [PMID: 38176186 DOI: 10.1016/j.ecoenv.2023.115900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 12/22/2023] [Accepted: 12/26/2023] [Indexed: 01/06/2024]
Abstract
A thorough understanding of the degradation of chemical biomarkers in wastewater after the sampling is critical in the surveillance of illicit drug use based on the back-calculation technique. Herein, three temperatures, eight groups of matrices, and acidification were applied to simulate the preservation condition of 21 illicit drugs, their metabolites, and cotinine for a 240-day stability study. It was proved that the temperature, matrices, and acidification play vital roles in their stability in wastewater. Most of them demonstrated high stability (transformation rates < 20%) during room temperature for 45 days, and the transformation rates decreased while the storage temperature reduced. The stability of the target compounds such as cocaine (COC), 6-monoacetylmorphine (6-MAM), and amphetamine (AM) is influenced by matrices. Acidification prevented the majority of analytes from transforming, making it a feasible solution for preservation after sampling. A model that combined the effects of temperature and matrix was developed to back-calculate the concentration of target compounds during the postsampling process. The feasibility of this model was validated by correcting the loss of COC and 6-MAM from 24.2% and 16.2% to 2.98% and 2.77%. This study simulated a typical large-scale sampling and storage scenario. The effect of the temperature, pH, and matrix on in-sample stability and the postsampling analysis of selected target compounds was investigated for the first time in this study.
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Affiliation(s)
- Xinfeng Che
- School of Pharmacy, China Pharmaceutical University, Nanjing 210009, PR China; Office of China National Narcotics Control Commission-China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, Beijing 100193, PR China
| | - Peipei Liu
- Office of China National Narcotics Control Commission-China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, Beijing 100193, PR China; Key Laboratory of Drug Monitoring and Control, Drug Intelligence and Forensic Center, Ministry of Public Security, Beijing 100193, PR China
| | - Yan Ding
- School of Pharmacy, China Pharmaceutical University, Nanjing 210009, PR China; Office of China National Narcotics Control Commission-China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, Beijing 100193, PR China
| | - Wenjia Tao
- School of Pharmacy, China Pharmaceutical University, Nanjing 210009, PR China; Office of China National Narcotics Control Commission-China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, Beijing 100193, PR China
| | - Xiaoyu Zheng
- Office of China National Narcotics Control Commission-China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, Beijing 100193, PR China; Key Laboratory of Drug Monitoring and Control, Drug Intelligence and Forensic Center, Ministry of Public Security, Beijing 100193, PR China
| | - Bin Di
- School of Pharmacy, China Pharmaceutical University, Nanjing 210009, PR China; Office of China National Narcotics Control Commission-China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, Beijing 100193, PR China.
| | - Hongwei Qiao
- Office of China National Narcotics Control Commission-China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, Beijing 100193, PR China; Key Laboratory of Drug Monitoring and Control, Drug Intelligence and Forensic Center, Ministry of Public Security, Beijing 100193, PR China.
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5
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Marin-Ramirez A, Mahoney T, Smith T, Holm RH. Predicting wastewater treatment plant influent in mixed, separate, and combined sewers using nearby surface water discharge for better wastewater-based epidemiology sampling design. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167375. [PMID: 37774884 DOI: 10.1016/j.scitotenv.2023.167375] [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: 07/07/2023] [Revised: 08/28/2023] [Accepted: 09/24/2023] [Indexed: 10/01/2023]
Abstract
For wastewater sample collection approaches supporting public health applications, few high hydrologic activity normalizing guidelines currently consider readily available environmental flow data that may earlier capture information regarding periods of influent mixing and dilution of wastewater with groundwater and runoff. This study aimed to identify wastewater sampling rules for high hydrological activity events, allowing for an earlier decision point in the control of dilution before sample collection. We defined the sampling rules via data-driven models (Random Forest and linear regression) using environmental data (i.e., wastewater treatment facility influent rates, nearby stream discharge flow, and precipitation). These models were applied to five treatment plants in Jefferson County, Kentucky (USA) in mixed, separate, and combined sewers with different population sizes. We proposed cutoffs of 10 %, 25 %, and 50 % flow conditions for orientation towards public health samples. The results showed a strong nonlinear relationship between nearby stream discharge and treatment facility flow rates, which was used to infer the hydrological conditions that produce high volumes of diluted wastewater in the sewer system. Accumulated Local Effects and SHapley Additive exPlanations aided in deciphering the relationship between the predictors and response variables of the Random Forest models. The influent rate to the treatment plant from the previous day and two USGS stream gages were needed to adequately predict the degree of infiltration and inflow mixing on a given day. Surface water discharge data can be used to provide an earlier workflow decision point during wet weather periods to improve understanding of flow conditions for wastewater-based epidemiological studies to inform laboratory analysis and data interpretation. Not only total flow, but also the specific proportions of infiltration and inflow to wastewater volume in influent should be considered when analyzing data for normalization purposes, and our method provides a starting point for doing so rapidly and at low cost.
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Affiliation(s)
- Arlex Marin-Ramirez
- Department of Civil and Environmental Engineering, J. B. Speed School of Engineering, University of Louisville, 132 E. Pkwy., Louisville, KY 40202, United States
| | - Tyler Mahoney
- Department of Civil and Environmental Engineering, J. B. Speed School of Engineering, University of Louisville, 132 E. Pkwy., Louisville, KY 40202, United States
| | - Ted Smith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY 40202, United States
| | - Rochelle H Holm
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, 302 E. Muhammad Ali Blvd., Louisville, KY 40202, United States.
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6
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Zhong Y, Hou C, Gao X, Wang M, Yao Y, Chen M, Di B, Su M. Application of wastewater-based epidemiology to estimate the usage of beta-agonists in 31 cities in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 894:164956. [PMID: 37343858 DOI: 10.1016/j.scitotenv.2023.164956] [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: 02/03/2023] [Revised: 06/13/2023] [Accepted: 06/15/2023] [Indexed: 06/23/2023]
Abstract
The illegal use of beta-agonists could cause severe problems to human health. In this study, the usage of beta-agonists in 31 cities across China was estimated using wastewater-based epidemiology (WBE). The proposed method is based on solid-phase extraction (SPE) and LC-MS/MS and was developed and validated to determine the concentration of seven beta-agonists in wastewater. A population model based on cotinine (COT), NH4-N and the flow volume was constructed to estimate the population equivalents for different wastewater treatment plants (WWTPs). Clenbuterol and ractopamine are banned in China for both animal husbandry and medical use, but were nevertheless detected in some wastewater samples at rates of 6.2 % and 4.7 %, respectively (n = 339). The WBE-based consumption of clenbuterol and ractopamine were compared with the acceptable daily intake (ADI) and the health risks were assessed by their hazard quotients (0.26-6.62 for clenbuterol and 9.27 × 10-4-0.05 for ractopamine). Salbutamol, clorprenaline and terbutaline were observed in practically all wastewater samples at concentrations of up to several ng/L, whereas the formoterol and bambuterol concentrations were below the detection limit in all samples. Salbutamol consumption (7.35 ± 4.14 mg/1000 inh/day) was highest among the examined beta-agonists and varied regionally. Beta-agonist consumption based on WBE was higher in some cities than that based on medical survey data, indicating potential illegal use. These results show that WBE can be a straightforward and supplementary method for monitoring beta-agonist usage at the population level and spatially.
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Affiliation(s)
- Yuling Zhong
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
| | - Chenzhi Hou
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
| | - Xinyi Gao
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
| | - Mingyu Wang
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
| | - Yan Yao
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
| | - Mengyi Chen
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
| | - Bin Di
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China; Key Laboratory of Drug Quality Control and Pharmacovigilance, China Pharmaceutical University, Ministry of Education, No. 639 Longmian Avenue, Nanjing, 211100, China.
| | - Mengxiang Su
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China; China National Narcotics Control Commission, China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China; Key Laboratory of Drug Quality Control and Pharmacovigilance, China Pharmaceutical University, Ministry of Education, No. 639 Longmian Avenue, Nanjing, 211100, China.
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7
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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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Xu L, Lu YT, Wu DF, Li X, Song M, Hang TJ, Su MX. Application of the metal ions as potential population biomarkers for wastewater-based epidemiology: estimating tobacco consumption in Southern China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023:1-13. [PMID: 37060434 PMCID: PMC10105154 DOI: 10.1007/s10653-023-01558-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 03/29/2023] [Indexed: 06/19/2023]
Abstract
Wastewater-based epidemiology (WBE) is an objective approach for the estimation of population-level exposure to a wide range of substances, in which the use of a population biomarker (PB) could significantly reduce back-calculation errors. Although some endogenous or exogenous compounds such as cotinine and other hormones have been developed as PBs, more PBs still need to be identified and evaluated. This study aimed to propose a novel method to estimate population parameters from the mass load of metal ion biomarkers in wastewater, and estimate the consumption of tobacco in 24 cities in Southern China using the developed method. Daily wastewater samples were collected from 234 wastewater treatment plants (WWTPs) in 24 cities in Southern China. Atomic absorption spectroscopy (AAS) was applied to determine the concentrations of common health-related metal ions in wastewater, including sodium (Na), potassium (K), magnesium (Mg), calcium (Ca), iron (Fe), and zinc (Zn), and compared them with the daily mass load of cotinine corresponding to catchment populations. The concentrations of cotinine in wastewater samples were measured using liquid chromatography-tandem mass spectrometry. There were clear and strong correlations between the target metal ion equivalent population and census data. The correlation coefficients (R) were RK = 0.78, RNa = 0.66, RCa = 0.81, RMg = 0.77, and RFe = 0.69, at p < 0.01 and R2 > 0.6. Subsequently, the combination of WBE and metal ion PBs was used to estimate tobacco consumption. Daily consumption of nicotine was estimated to be approximately 1.76 ± 1.19 mg/d/capita, equivalent to an average of 13.0 ± 8.75 cigarettes/d being consumed by smokers. The data on tobacco consumption in this study were consistent with those in traditional surveys in Southern China. The metal ion potassium is an appropriate PB for reflecting the real-time population and could be used to evaluate the tobacco consumption in WBE study.
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Affiliation(s)
- Lei Xu
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
- China National Narcotics Control Commission - China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
- Department of Pharmacy, Ordos Central Hospital, No. 23 Yijinhuoluo Road, Ordos, 017000, China
| | - Yu-Ting Lu
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
- China National Narcotics Control Commission - China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
| | - Dong-Feng Wu
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
- China National Narcotics Control Commission - China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
| | - Xuan Li
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
- China National Narcotics Control Commission - China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
| | - Min Song
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
- China National Narcotics Control Commission - China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China
| | - Tai-Jun Hang
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China.
- China National Narcotics Control Commission - China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China.
| | - Meng-Xiang Su
- School of Pharmacy, China Pharmaceutical University, No. 24 Tongjiaxiang Road, Nanjing, 210009, China.
- China National Narcotics Control Commission - China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, No. 24 Tongjiaxiang Road, Nanjing, 210009, China.
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9
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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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10
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Guo Z, Hatakeyama T, Yoshimura C, Wang T, Hatano Y. Basic influent sewage quality reflects sewershed characteristics in Tokyo city. JOURNAL OF WATER AND HEALTH 2022; 20:972-984. [PMID: 35768971 DOI: 10.2166/wh.2022.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Sewage comprises multifarious information on sewershed characteristics. For instance, influent sewage quality parameters (ISQPs) (e.g., total nitrogen (TN)) are being monitored regularly at all treatment plants. However, the relationship between ISQPs and sewershed characteristics is rarely investigated. Therefore, this study statistically investigated relationships between ISQPs and sewershed characteristics, covering demographic, social, and economic properties in Tokyo city as an example of a megacity. To this end, we collected ISQPs and sewershed characteristic data from 2015 to 2020 in 10 sewersheds in Tokyo city. By principal component analysis, spatial variability of ISQPs was aggregated into two principal components (89.8% contribution in total), indicating organics/nutrients and inorganic salts, respectively. Concentrations of organics/nutrients were significantly correlated with the population in sewersheds (daytime population density, family size, age distribution, etc.). Inorganic salts are significantly correlated with land cover ratios. Finally, a multiple regression model was developed for estimating the concentration of TN based on sewershed characteristics (R2=0.97). Scenario analysis using the regression model revealed that possible population movements in response to the coronavirus pandemic would substantially reduce the concentration of TN. These results indicate close relationships between ISQPs and sewershed characteristics and the potential applicability of big data of ISQPs to estimate sewershed characteristics and vice versa.
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Affiliation(s)
- Zhongyu Guo
- Department of Civil and Environmental Engineering, Tokyo Institute of Technology, Meguro-Ku, Tokyo 152-8552, Japan E-mail:
| | - Takayuki Hatakeyama
- Department of Civil and Environmental Engineering, Tokyo Institute of Technology, Meguro-Ku, Tokyo 152-8552, Japan E-mail:
| | - Chihiro Yoshimura
- Department of Civil and Environmental Engineering, Tokyo Institute of Technology, Meguro-Ku, Tokyo 152-8552, Japan E-mail:
| | - Tingting Wang
- Graduate School of Science, Nagoya University, Furo-Cho, Chikusa-Ku, Nagoya 464-8602, Japan
| | - Yuta Hatano
- Department of Civil and Environmental Engineering, Tokyo Institute of Technology, Meguro-Ku, Tokyo 152-8552, Japan E-mail:
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Berzina Z, Pavlenko R, Jansons M, Bartkiene E, Neilands R, Pugajeva I, Bartkevics V. Application of Wastewater-Based Epidemiology for Tracking Human Exposure to Deoxynivalenol and Enniatins. Toxins (Basel) 2022; 14:91. [PMID: 35202119 PMCID: PMC8878170 DOI: 10.3390/toxins14020091] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 01/17/2022] [Accepted: 01/21/2022] [Indexed: 11/24/2022] Open
Abstract
Wastewater-based epidemiology (WBE) is a promising biomonitoring approach with the potential to provide direct information on human intake and exposure to food contaminants and environmental chemicals. The aim of this study was to apply WBE while employing the normalization method for exploring human exposure to selected mycotoxins according to population biomarker 5-hydroxyindoleacetic acid (5-HIAA). This type of normalization technique has been previously used to detect various other compounds. However, to the best of our knowledge, this is the first study tracking human exposure to mycotoxins. A sensitive analytical methodology was developed to achieve reliable quantification of deoxynivalenol, enniatins, and beauvericin in wastewater (WW) samples. The applicability of the method was evaluated by testing 29 WW samples collected at WW treatment plants in Latvia. With frequency of detection greater than 86%, enniatins B, B1, A, and A1 were revealed in WW samples. The estimated total daily intake for enniatins was in the range of 1.8-27.6 µg/day per person. Free deoxynivalenol (DON) was determined in all analysed WW samples. Based on the average 5-HIAA excretion level and the determined 5-HIAA content in the samples, the intake of DON by the human population of Riga was estimated at 325 ng/kg b.w. day.
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Affiliation(s)
- Zane Berzina
- Animal Health and Environment “BIOR”, Institute of Food Safety, Lejupes 3, LV-1076 Riga, Latvia; (R.P.); (M.J.); (I.P.); (V.B.)
- Faculty of Chemistry, University of Latvia, Jelgavas 1, LV-1004 Riga, Latvia
| | - Romans Pavlenko
- Animal Health and Environment “BIOR”, Institute of Food Safety, Lejupes 3, LV-1076 Riga, Latvia; (R.P.); (M.J.); (I.P.); (V.B.)
- Faculty of Chemistry, University of Latvia, Jelgavas 1, LV-1004 Riga, Latvia
| | - Martins Jansons
- Animal Health and Environment “BIOR”, Institute of Food Safety, Lejupes 3, LV-1076 Riga, Latvia; (R.P.); (M.J.); (I.P.); (V.B.)
| | - Elena Bartkiene
- Department of Food Safety and Quality, Lithuanian University of Health Sciences, Mickeviciaus 9, LT-44307 Kaunas, Lithuania;
| | - Romans Neilands
- Department of Water Engineering and Technology, Riga Technical University, Kalku 1, LV-1658 Riga, Latvia;
| | - Iveta Pugajeva
- Animal Health and Environment “BIOR”, Institute of Food Safety, Lejupes 3, LV-1076 Riga, Latvia; (R.P.); (M.J.); (I.P.); (V.B.)
| | - Vadims Bartkevics
- Animal Health and Environment “BIOR”, Institute of Food Safety, Lejupes 3, LV-1076 Riga, Latvia; (R.P.); (M.J.); (I.P.); (V.B.)
- Faculty of Chemistry, University of Latvia, Jelgavas 1, LV-1004 Riga, Latvia
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Picó Y, Barceló D. Identification of biomarkers in wastewater-based epidemiology: Main approaches and analytical methods. Trends Analyt Chem 2021; 145:116465. [PMID: 34803197 PMCID: PMC8591405 DOI: 10.1016/j.trac.2021.116465] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Wastewater-based epidemiology (WBE) has become popular to estimate the use of drugs of abuse and recently to establish the incidence of CoVID 19 in large cities. However, its possibilities have been expanded recently as a technique that allows to establish a fingerprint of the characteristics of a city, such as state of health/disease, healthy/unhealthy living habits, exposure to different types of contaminants, etc. with respect to other cities. This has been thanks to the identification of human biomarkers as well as to the fingerprinting and profiling of the characteristics of the wastewater catchment that determine these circumstances. The purpose of this review is to analyze the different methodological schemes that have been developed to perform this biomarker identification as well as the most characteristic analytical techniques in each scheme, their advantages and disadvantages and the knowledge gaps identified. We also discussed the future scope for development.
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Affiliation(s)
- Yolanda Picó
- Environmental and Food Safety Research Group of the University of Valencia (SAMA-UV), Desertification Research Centre (CIDE), CSIC-GV-UV, Moncada Naquera Road Km 4.3, 46113 Moncada, Valencia, Spain
| | - Damià Barceló
- Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, 08034 Barcelona, Spain
- Catalan Institute for Water Research, ICRA - CERCA, Technological Park of the University of Girona, Emili Grahit 101, 17003 Girona, Spain
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13
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Street R, Mathee A, Mangwana N, Dias S, Sharma JR, Ramharack P, Louw J, Reddy T, Brocker L, Surujlal-Naicker S, Berkowitz N, Malema MS, Nkambule S, Webster C, Mahlangeni N, Gelderblom H, Mdhluli M, Gray G, Muller C, Johnson R. Spatial and Temporal Trends of SARS-CoV-2 RNA from Wastewater Treatment Plants over 6 Weeks in Cape Town, South Africa. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:12085. [PMID: 34831841 PMCID: PMC8618134 DOI: 10.3390/ijerph182212085] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 10/13/2021] [Accepted: 10/20/2021] [Indexed: 11/22/2022]
Abstract
Recent scientific trends have revealed that the collection and analysis of data on the occurrence and fate of SARS-CoV-2 in wastewater may serve as an early warning system for COVID-19. In South Africa, the first COVID-19 epicenter emerged in the Western Cape Province. The City of Cape Town, located in the Western Cape Province, has approximately 4 million inhabitants. This study reports on the monitoring of SARS-CoV-2 RNA in the wastewater of the City of Cape Town's wastewater treatment plants (WWTPs) during the peak of the epidemic. During this period, the highest overall median viral RNA signal was observed in week 1 (9200 RNA copies/mL) and declined to 127 copies/mL in week 6. The overall decrease in the amount of detected viral SARS-CoV-2 RNA over the 6-week study period was associated with a declining number of newly identified COVID-19 cases in the city. The SARS-CoV-2 early warning system has now been established to detect future waves of COVID-19.
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Affiliation(s)
- Renée Street
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (A.M.); (M.S.M.); (S.N.); (C.W.); (N.M.)
| | - Angela Mathee
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (A.M.); (M.S.M.); (S.N.); (C.W.); (N.M.)
- Environmental Health Department, Faculty of Health Sciences, University of Johannesburg, Johannesburg 2092, South Africa
| | - Noluxabiso Mangwana
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (N.M.); (S.D.); (J.R.S.); (P.R.); (J.L.); (C.M.); (R.J.)
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa;
| | - Stephanie Dias
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (N.M.); (S.D.); (J.R.S.); (P.R.); (J.L.); (C.M.); (R.J.)
| | - Jyoti Rajan Sharma
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (N.M.); (S.D.); (J.R.S.); (P.R.); (J.L.); (C.M.); (R.J.)
| | - Pritika Ramharack
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (N.M.); (S.D.); (J.R.S.); (P.R.); (J.L.); (C.M.); (R.J.)
| | - Johan Louw
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (N.M.); (S.D.); (J.R.S.); (P.R.); (J.L.); (C.M.); (R.J.)
- Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa
| | - Tarylee Reddy
- Biostatistics Unit, South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa;
| | - Ludwig Brocker
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa;
| | - Swastika Surujlal-Naicker
- Scientific Services, Water and Sanitation Department, City of Cape Town Metropolitan Municipality, Cape Town 8000, South Africa;
| | - Natacha Berkowitz
- Community Services and Health, City Health, City of Cape Town, Hertzog Boulevard, Cape Town 8001, South Africa;
| | - Mokaba Shirley Malema
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (A.M.); (M.S.M.); (S.N.); (C.W.); (N.M.)
| | - Sizwe Nkambule
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (A.M.); (M.S.M.); (S.N.); (C.W.); (N.M.)
| | - Candice Webster
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (A.M.); (M.S.M.); (S.N.); (C.W.); (N.M.)
| | - Nomfundo Mahlangeni
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (A.M.); (M.S.M.); (S.N.); (C.W.); (N.M.)
| | - Huub Gelderblom
- COVID-19 Prevention Network (COVPN), Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA;
| | - Mongezi Mdhluli
- Office of the President, South African Medical Research Council, Tygerberg 7050, South Africa;
| | - Glenda Gray
- Chief Research Operations Office, South African Medical Research Council, Tygerberg 7050, South Africa;
| | - Christo Muller
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (N.M.); (S.D.); (J.R.S.); (P.R.); (J.L.); (C.M.); (R.J.)
- Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa
- Centre for Cardio-Metabolic Research in Africa, Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Rabia Johnson
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa; (N.M.); (S.D.); (J.R.S.); (P.R.); (J.L.); (C.M.); (R.J.)
- Centre for Cardio-Metabolic Research in Africa, Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch 7600, South Africa
- Discipline of Pharmaceutical Sciences, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
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