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Geiwitz M, Page OR, Marello T, Nichols ME, Kumar N, Hummel S, Belosevich V, Ma Q, van Opijnen T, Batten B, Meyer MM, Burch KS. Graphene Multiplexed Sensor for Point-of-Need Viral Wastewater-Based Epidemiology. ACS APPLIED BIO MATERIALS 2024. [PMID: 38954405 DOI: 10.1021/acsabm.4c00484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/04/2024]
Abstract
Wastewater-based epidemiology (WBE) can help mitigate the spread of respiratory infections through the early detection of viruses, pathogens, and other biomarkers in human waste. The need for sample collection, shipping, and testing facilities drives up the cost of WBE and hinders its use for rapid detection and isolation in environments with small populations and in low-resource settings. Given the ubiquitousness and regular outbreaks of respiratory syncytial virus, SARS-CoV-2, and various influenza strains, there is a rising need for a low-cost and easy-to-use biosensing platform to detect these viruses locally before outbreaks can occur and monitor their progression. To this end, we have developed an easy-to-use, cost-effective, multiplexed platform able to detect viral loads in wastewater with several orders of magnitude lower limit of detection than that of mass spectrometry. This is enabled by wafer-scale production and aptamers preattached with linker molecules, producing 44 chips at once. Each chip can simultaneously detect four target analytes using 20 transistors segregated into four sets of five for each analyte to allow for immediate statistical analysis. We show our platform's ability to rapidly detect three virus proteins (SARS-CoV-2, RSV, and Influenza A) and a population normalization molecule (caffeine) in wastewater. Going forward, turning these devices into hand-held systems would enable wastewater epidemiology in low-resource settings and be instrumental for rapid, local outbreak prevention.
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Affiliation(s)
- Michael Geiwitz
- Department of Physics, Boston College, Chestnut Hill, Massachusetts 02467, United States
| | - Owen Rivers Page
- Department of Biology, Boston College, Chestnut Hill, Massachusetts 02467, United States
| | - Tio Marello
- Department of Physics, Boston College, Chestnut Hill, Massachusetts 02467, United States
| | - Marina E Nichols
- Department of Physics, Boston College, Chestnut Hill, Massachusetts 02467, United States
| | - Narendra Kumar
- GRIP Molecular Technologies, Inc., 1000 Westgate Drive, Saint Paul, Minnesota 55114, United States
| | - Stephen Hummel
- Department of Chemistry and Life Science, United States Military Academy, West Point, New York 10996, United States
| | - Vsevolod Belosevich
- Department of Physics, Boston College, Chestnut Hill, Massachusetts 02467, United States
| | - Qiong Ma
- Department of Physics, Boston College, Chestnut Hill, Massachusetts 02467, United States
| | - Tim van Opijnen
- Department of Biology, Boston College, Chestnut Hill, Massachusetts 02467, United States
| | - Bruce Batten
- GRIP Molecular Technologies, Inc., 1000 Westgate Drive, Saint Paul, Minnesota 55114, United States
| | - Michelle M Meyer
- Department of Biology, Boston College, Chestnut Hill, Massachusetts 02467, United States
| | - Kenneth S Burch
- Department of Physics, Boston College, Chestnut Hill, Massachusetts 02467, United States
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Malla B, Shrestha S, Sthapit N, Hirai S, Raya S, Rahmani AF, Angga MS, Siri Y, Ruti AA, Haramoto E. Beyond COVID-19: Wastewater-based epidemiology for multipathogen surveillance and normalization strategies. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174419. [PMID: 38960169 DOI: 10.1016/j.scitotenv.2024.174419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 06/29/2024] [Accepted: 06/29/2024] [Indexed: 07/05/2024]
Abstract
Wastewater-based epidemiology (WBE) is a critical tool for monitoring community health. Although much attention has focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a causative agent of coronavirus disease 2019 (COVID-19), other pathogens also pose significant health risks. This study quantified the presence of SARS-CoV-2, influenza A virus (Inf-A), and noroviruses of genogroups I (NoV-GI) and II (NoV-GII) in wastewater samples collected weekly (n = 170) from July 2023 to February 2024 from five wastewater treatment plants (WWTPs) in Yamanashi Prefecture, Japan, by quantitative PCR. Inf-A RNA exhibited localized prevalence with positive ratios of 59 %-82 % in different WWTPs, suggesting regional outbreaks within specific areas. NoV-GI (94 %, 160/170) and NoV-GII (100 %, 170/170) RNA were highly prevalent, with NoV-GII (6.1 ± 0.8 log10 copies/L) consistently exceeding NoV-GI (5.4 ± 0.7 log10 copies/L) RNA concentrations. SARS-CoV-2 RNA was detected in 100 % of the samples, with mean concentrations of 5.3 ± 0.5 log10 copies/L in WWTP E and 5.8 ± 0.4 log10 copies/L each in other WWTPs. Seasonal variability was evident, with higher concentrations of all pathogenic viruses during winter. Non-normalized and normalized virus concentrations by fecal indicator bacteria (Escherichia coli and total coliforms), an indicator virus (pepper mild mottle virus (PMMoV)), and turbidity revealed significant positive associations with the reported disease cases. Inf-A and NoV-GI + GII RNA concentrations showed strong correlations with influenza and acute gastroenteritis cases, particularly when normalized to E. coli (Spearman's ρ = 0.70-0.81) and total coliforms (ρ = 0.70-0.81), respectively. For SARS-CoV-2, non-normalized concentrations showed a correlation of 0.61, decreasing to 0.31 when normalized to PMMoV, suggesting that PMMoV is unsuitable. Turbidity normalization also yielded suboptimal results. This study underscored the importance of selecting suitable normalization parameters tailored to specific pathogens for accurate disease trend monitoring using WBE, demonstrating its utility beyond COVID-19 surveillance.
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Affiliation(s)
- Bikash Malla
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Sadhana Shrestha
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Niva Sthapit
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Soichiro Hirai
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Sunayana Raya
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Aulia Fajar Rahmani
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Made Sandhyana Angga
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Yadpiroon Siri
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Annisa Andarini Ruti
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan.
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3
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Ofori B, Agoha RK, Bokoe EK, Armah ENA, Misita Morang'a C, Sarpong KAN. Leveraging wastewater-based epidemiology to monitor the spread of neglected tropical diseases in African communities. Infect Dis (Lond) 2024:1-15. [PMID: 38922811 DOI: 10.1080/23744235.2024.2369177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 06/13/2024] [Indexed: 06/28/2024] Open
Abstract
Neglected tropical diseases continue to cause a significant burden worldwide, with Africa accounting for more than one-third of the global burden. Over the past decade, progress has been made in eliminating, controlling, and eradicating these diseases in Africa. By December 2022, 47 out of 54 African countries had eliminated at least one neglected tropical disease, and more countries were close to achieving this milestone. Between 2020 and 2021, there was an 80 million reduction in people requiring intervention. However, continued efforts are needed to manage neglected tropical diseases and address their social and economic burden, as they deepen marginalisation and stigmatisation. Wastewater-based epidemiology involves analyzing wastewater to detect and quantify biomarkers of disease-causing pathogens. This approach can complement current disease surveillance systems in Africa and provide an additional layer of information for monitoring disease spread and detecting outbreaks. This is particularly important in Africa due to limited traditional surveillance methods. Wastewater-based epidemiology also provides a tsunami-like warning system for neglected tropical disease outbreaks and can facilitate timely intervention and optimised resource allocation, providing an unbiased reflection of the community's health compared to traditional surveillance systems. In this review, we highlight the potential of wastewater-based epidemiology as an innovative approach for monitoring neglected tropical disease transmission within African communities and improving existing surveillance systems. Our analysis shows that wastewater-based epidemiology can enhance surveillance of neglected tropical diseases in Africa, improving early detection and management of Buruli ulcers, hookworm infections, ascariasis, schistosomiasis, dengue, chikungunya, echinococcosis, rabies, and cysticercosis for better disease control.
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Affiliation(s)
- Benedict Ofori
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), University of Ghana, Accra, Ghana
- Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Ghana
| | - Righteous Kwaku Agoha
- Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Ghana
| | - Edem Kwame Bokoe
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), University of Ghana, Accra, Ghana
- Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Ghana
| | | | - Collins Misita Morang'a
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), University of Ghana, Accra, Ghana
- Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Ghana
| | - Kwabena Amofa Nketia Sarpong
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), University of Ghana, Accra, Ghana
- Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Ghana
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4
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Nash D, Ellmen I, Knapp JJ, Menon R, Overton AK, Cheng J, Lynch MDJ, Nissimov JI, Charles TC. A Novel Tiled Amplicon Sequencing Assay Targeting the Tomato Brown Rugose Fruit Virus (ToBRFV) Genome Reveals Widespread Distribution in Municipal Wastewater Treatment Systems in the Province of Ontario, Canada. Viruses 2024; 16:460. [PMID: 38543825 PMCID: PMC10974707 DOI: 10.3390/v16030460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 03/13/2024] [Accepted: 03/15/2024] [Indexed: 05/23/2024] Open
Abstract
Tomato Brown Rugose Fruit Virus (ToBRFV) is a plant pathogen that infects important Solanaceae crop species and can dramatically reduce tomato crop yields. The ToBRFV has rapidly spread around the globe due to its ability to escape detection by antiviral host genes which confer resistance to other tobamoviruses in tomato plants. The development of robust and reproducible methods for detecting viruses in the environment aids in the tracking and reduction of pathogen transmission. We detected ToBRFV in municipal wastewater influent (WWI) samples, likely due to its presence in human waste, demonstrating a widespread distribution of ToBRFV in WWI throughout Ontario, Canada. To aid in global ToBRFV surveillance efforts, we developed a tiled amplicon approach to sequence and track the evolution of ToBRFV genomes in municipal WWI. Our assay recovers 95.7% of the 6393 bp ToBRFV RefSeq genome, omitting the terminal 5' and 3' ends. We demonstrate that our sequencing assay is a robust, sensitive, and highly specific method for recovering ToBRFV genomes. Our ToBRFV assay was developed using existing ARTIC Network resources, including primer design, sequencing library prep, and read analysis. Additionally, we adapted our lineage abundance estimation tool, Alcov, to estimate the abundance of ToBRFV clades in samples.
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Affiliation(s)
- Delaney Nash
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada; (I.E.); (J.J.K.); (R.M.); (A.K.O.); (J.C.); (M.D.J.L.); (J.I.N.); (T.C.C.)
- Metagenom Bio Life Science Inc., Waterloo, ON N2L 5V4, Canada
| | - Isaac Ellmen
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada; (I.E.); (J.J.K.); (R.M.); (A.K.O.); (J.C.); (M.D.J.L.); (J.I.N.); (T.C.C.)
- Metagenom Bio Life Science Inc., Waterloo, ON N2L 5V4, Canada
| | - Jennifer J. Knapp
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada; (I.E.); (J.J.K.); (R.M.); (A.K.O.); (J.C.); (M.D.J.L.); (J.I.N.); (T.C.C.)
| | - Ria Menon
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada; (I.E.); (J.J.K.); (R.M.); (A.K.O.); (J.C.); (M.D.J.L.); (J.I.N.); (T.C.C.)
| | - Alyssa K. Overton
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada; (I.E.); (J.J.K.); (R.M.); (A.K.O.); (J.C.); (M.D.J.L.); (J.I.N.); (T.C.C.)
| | - Jiujun Cheng
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada; (I.E.); (J.J.K.); (R.M.); (A.K.O.); (J.C.); (M.D.J.L.); (J.I.N.); (T.C.C.)
- Metagenom Bio Life Science Inc., Waterloo, ON N2L 5V4, Canada
| | - Michael D. J. Lynch
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada; (I.E.); (J.J.K.); (R.M.); (A.K.O.); (J.C.); (M.D.J.L.); (J.I.N.); (T.C.C.)
- Metagenom Bio Life Science Inc., Waterloo, ON N2L 5V4, Canada
| | - Jozef I. Nissimov
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada; (I.E.); (J.J.K.); (R.M.); (A.K.O.); (J.C.); (M.D.J.L.); (J.I.N.); (T.C.C.)
| | - Trevor C. Charles
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada; (I.E.); (J.J.K.); (R.M.); (A.K.O.); (J.C.); (M.D.J.L.); (J.I.N.); (T.C.C.)
- Metagenom Bio Life Science Inc., Waterloo, ON N2L 5V4, Canada
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5
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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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Faherty EAG, Yuce D, Korban C, Bemis K, Kowalski R, Gretsch S, Ramirez E, Poretsky R, Packman A, Leisman KP, Pierce M, Kittner A, Teran R, Pacilli M. Correlation of wastewater surveillance data with traditional influenza surveillance measures in Cook County, Illinois, October 2022-April 2023. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169551. [PMID: 38135071 PMCID: PMC10913165 DOI: 10.1016/j.scitotenv.2023.169551] [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: 09/25/2023] [Revised: 12/18/2023] [Accepted: 12/18/2023] [Indexed: 12/24/2023]
Abstract
Influenza is a respiratory illness that can result in serious outcomes, particularly among persons who are immunocompromised, aged <5 years or aged >65 years. Traditional influenza surveillance approaches rely upon syndromic surveillance of emergency departments and public health reporting from clinicians and laboratories. Wastewater surveillance infrastructure developed to monitor SARS-CoV-2 is being used for influenza surveillance in the Chicago area. The goal was to evaluate timeliness and correlations between influenza virus detected through wastewater surveillance and traditional influenza surveillance measures to assess utility of wastewater surveillance for influenza at the county level. Specifically, we measured correlations between influenza virus gene copies in wastewater samples and 1) the number of intensive care unit admissions associated with a diagnosis of influenza, 2) the percentage emergency department (ED) visits for influenza-like-illness, and 3) the percentage of ED visits with influenza diagnosis at discharge2 in Cook County. Influenza concentrations in wastewater were strongly correlated with traditional influenza surveillance measures, particularly for catchment areas serving >100,000 residents. Wastewater indicators lagged traditional influenza surveillance measures by approximately one week when analyzed in cross-correlations. Although wastewater data lagged traditional influenza surveillance measures in this analysis, it can serve as a useful surveillance tool as a complement to syndromic surveillance; it is a form of influenza surveillance that does not rely on healthcare-seeking behavior or reporting by healthcare providers.
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Affiliation(s)
- Emily A G Faherty
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, United States of America; Chicago Department of Public Health, United States of America.
| | - Deniz Yuce
- Chicago Department of Public Health, United States of America
| | - Colin Korban
- Chicago Department of Public Health, United States of America
| | - Kelley Bemis
- Cook County Department of Public Health, United States of America
| | - Rishi Kowalski
- Cook County Department of Public Health, United States of America
| | | | - Enrique Ramirez
- Chicago Department of Public Health, United States of America
| | | | | | | | - Melissa Pierce
- University of Illinois System, Discovery Partners Institute, United States of America
| | - Alyse Kittner
- Chicago Department of Public Health, United States of America
| | - Richard Teran
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, United States of America; Chicago Department of Public Health, United States of America
| | - Massimo Pacilli
- Chicago Department of Public Health, United States of America
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7
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Philo SE, De León KB, Noble RT, Zhou NA, Alghafri R, Bar-Or I, Darling A, D'Souza N, Hachimi O, Kaya D, Kim S, Gaardbo Kuhn K, Layton BA, Mansfeldt C, Oceguera B, Radniecki TS, Ram JL, Saunders LP, Shrestha A, Stadler LB, Steele JA, Stevenson BS, Vogel JR, Bibby K, Boehm AB, Halden RU, Delgado Vela J. Wastewater surveillance for bacterial targets: current challenges and future goals. Appl Environ Microbiol 2024; 90:e0142823. [PMID: 38099657 PMCID: PMC10807411 DOI: 10.1128/aem.01428-23] [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] [Indexed: 01/25/2024] Open
Abstract
Wastewater-based epidemiology (WBE) expanded rapidly in response to the COVID-19 pandemic. As the public health emergency has ended, researchers and practitioners are looking to shift the focus of existing wastewater surveillance programs to other targets, including bacteria. Bacterial targets may pose some unique challenges for WBE applications. To explore the current state of the field, the National Science Foundation-funded Research Coordination Network (RCN) on Wastewater Based Epidemiology for SARS-CoV-2 and Emerging Public Health Threats held a workshop in April 2023 to discuss the challenges and needs for wastewater bacterial surveillance. The targets and methods used in existing programs were diverse, with twelve different targets and nine different methods listed. Discussions during the workshop highlighted the challenges in adapting existing programs and identified research gaps in four key areas: choosing new targets, relating bacterial wastewater data to human disease incidence and prevalence, developing methods, and normalizing results. To help with these challenges and research gaps, the authors identified steps the larger community can take to improve bacteria wastewater surveillance. This includes developing data reporting standards and method optimization and validation for bacterial programs. Additionally, more work is needed to understand shedding patterns for potential bacterial targets to better relate wastewater data to human infections. Wastewater surveillance for bacteria can help provide insight into the underlying prevalence in communities, but much work is needed to establish these methods.IMPORTANCEWastewater surveillance was a useful tool to elucidate the burden and spread of SARS-CoV-2 during the pandemic. Public health officials and researchers are interested in expanding these surveillance programs to include bacterial targets, but many questions remain. The NSF-funded Research Coordination Network for Wastewater Surveillance of SARS-CoV-2 and Emerging Public Health Threats held a workshop to identify barriers and research gaps to implementing bacterial wastewater surveillance programs.
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Affiliation(s)
- Sarah E. Philo
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana, USA
| | - Kara B. De León
- School of Biological Sciences, University of Oklahoma, Norman, Oklahoma, USA
| | - Rachel T. Noble
- Department of Earth, Marine, and Environmental Sciences, University of North Carolina at Chapel Hill, Institute of Marine Sciences, Morehead City, North Carolina, USA
| | - Nicolette A. Zhou
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Rashed Alghafri
- International Center for Forensic Sciences, Dubai Police, Dubai, UAE
| | - Itay Bar-Or
- Israel Ministry of Health, Jerusalem, Israel
| | - Amanda Darling
- Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, Virginia, USA
| | - Nishita D'Souza
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, USA
| | - Oumaima Hachimi
- School of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, Oregon, USA
| | - Devrim Kaya
- School of Public Health, San Diego State University, San Diego, California, USA
| | - Sooyeol Kim
- Department of Civil and Environmental Engineering, University of California Berkeley, Berkeley, California, USA
| | - Katrin Gaardbo Kuhn
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | | | - Cresten Mansfeldt
- Environmental Engineering Program, University of Colorado Boulder, Boulder, Colorado, USA
| | - Bethany Oceguera
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana, USA
| | - Tyler S. Radniecki
- School of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, Oregon, USA
| | - Jeffrey L. Ram
- Department of Physiology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | | | - Abhilasha Shrestha
- Environmental and Occupational Health Sciences Division, University of Illinois Chicago School of Public Health, Chicago, Illinois, USA
| | - Lauren B. Stadler
- Civil and Environmental Engineering, Rice University, Houston, Texas, USA
| | - Joshua A. Steele
- Department of Microbiology, Southern California Coastal Research Project, Costa Mesa, California, USA
| | | | - Jason R. Vogel
- School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, Oklahoma, USA
| | - Kyle Bibby
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana, USA
| | - Alexandria B. Boehm
- Department of Civil and Environmental Engineering, Stanford University, Stanford, California, USA
| | - Rolf U. Halden
- School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, Arizona, USA
| | - Jeseth Delgado Vela
- Department of Civil and Environmental Engineering, Duke University, Durham, North Carolina, USA
- Department of Civil and Environmental Engineering, Howard University, Washington, District of Columbia, USA
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8
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Kuroita T, Yoshimura A, Iwamoto R, Ando H, Okabe S, Kitajima M. Quantitative analysis of SARS-CoV-2 RNA in wastewater and evaluation of sampling frequency during the downward period of a COVID-19 wave in Japan. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:166526. [PMID: 37647962 DOI: 10.1016/j.scitotenv.2023.166526] [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: 06/05/2023] [Revised: 08/06/2023] [Accepted: 08/22/2023] [Indexed: 09/01/2023]
Abstract
Wastewater-based epidemiology (WBE) is a practical approach for detecting the presence of SARS-CoV-2 infections and assessing the epidemic trend of the coronavirus disease 2019 (COVID-19). The purpose of this study was to evaluate the minimum sampling frequency required to properly identify the COVID-19 trend during the downward epidemic period when using a highly sensitive RNA detection method. WBE was conducted using the Efficient and Practical virus Identification System with ENhanced Sensitivity for Solids (EPISENS-S), a highly sensitive SARS-CoV-2 RNA detection method, at nine neighboring wastewater treatment plants (WWTPs). These WWTPs were in the same prefecture in Japan, and they had different sewer types, sampling methods, and sampling frequencies. The overall detection rate of SARS-CoV-2 RNA was 97.8 % during the entire study period when the geometric means of new COVID-19 cases per 100,000 inhabitants were between 3.3 and 7.7 in each WWTP. The maximum SARS-CoV-2 RNA concentration in wastewater was 2.14 × 104 copies/L, which corresponded to pepper mild mottle virus (PMMoV)-normalized concentrations of 6.54 × 10-3. We evaluated the effect of sampling frequencies on the probability of a significant correlation with the number of newly reported COVID-19 cases by hypothetically reducing the sampling frequency in the same dataset. When the wastewater sampling frequency occurred 5, 3, 2, and 1 times per week, these results exhibited significant correlations of 100 % (5/5), 89 % (8/9), 85 % (23/27), and 48 % (13/27), respectively. To achieve significant correlation with a high probability of over 85 %, a minimum sampling frequency of twice per week is required, even if sampling methods and sewer types are different. WBE using the EPISENS-S method and a sampling frequency of more than twice a week can be used to properly monitor COVID-19 wave epidemic trends, even during downward periods.
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Affiliation(s)
- Tomohiro Kuroita
- AdvanSentinel Inc., 3-1-8, Doshomachi, Chuo-ku, Osaka 541-0045, Japan; Shionogi & Co., Ltd., 3-1-8, Doshomachi, Chuo-ku, Osaka 541-0045, Japan
| | - Akimasa Yoshimura
- Shionogi & Co., Ltd., 3-1-8, Doshomachi, Chuo-ku, Osaka 541-0045, Japan
| | - Ryo Iwamoto
- AdvanSentinel Inc., 3-1-8, Doshomachi, Chuo-ku, Osaka 541-0045, Japan; Shionogi & Co., Ltd., 3-1-8, Doshomachi, Chuo-ku, Osaka 541-0045, Japan
| | - Hiroki Ando
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Satoshi Okabe
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Masaaki Kitajima
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan.
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9
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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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10
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Hill DT, Alazawi MA, Moran EJ, Bennett LJ, Bradley I, Collins MB, Gobler CJ, Green H, Insaf TZ, Kmush B, Neigel D, Raymond S, Wang M, Ye Y, Larsen DA. Wastewater surveillance provides 10-days forecasting of COVID-19 hospitalizations superior to cases and test positivity: A prediction study. Infect Dis Model 2023; 8:1138-1150. [PMID: 38023490 PMCID: PMC10665827 DOI: 10.1016/j.idm.2023.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/13/2023] [Accepted: 10/13/2023] [Indexed: 12/01/2023] Open
Abstract
Background The public health response to COVID-19 has shifted to reducing deaths and hospitalizations to prevent overwhelming health systems. The amount of SARS-CoV-2 RNA fragments in wastewater are known to correlate with clinical data including cases and hospital admissions for COVID-19. We developed and tested a predictive model for incident COVID-19 hospital admissions in New York State using wastewater data. Methods Using county-level COVID-19 hospital admissions and wastewater surveillance covering 13.8 million people across 56 counties, we fit a generalized linear mixed model predicting new hospital admissions from wastewater concentrations of SARS-CoV-2 RNA from April 29, 2020 to June 30, 2022. We included covariates such as COVID-19 vaccine coverage in the county, comorbidities, demographic variables, and holiday gatherings. Findings Wastewater concentrations of SARS-CoV-2 RNA correlated with new hospital admissions per 100,000 up to ten days prior to admission. Models that included wastewater had higher predictive power than models that included clinical cases only, increasing the accuracy of the model by 15%. Predicted hospital admissions correlated highly with observed admissions (r = 0.77) with an average difference of 0.013 hospitalizations per 100,000 (95% CI = [0.002, 0.025]). Interpretation Using wastewater to predict future hospital admissions from COVID-19 is accurate and effective with superior results to using case data alone. The lead time of ten days could alert the public to take precautions and improve resource allocation for seasonal surges.
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Affiliation(s)
- Dustin T. Hill
- Department of Public Health, Syracuse University, Syracuse, NY, 13244, USA
| | - Mohammed A. Alazawi
- Center for Environmental Health, New York State Department of Health, Albany, NY, USA
| | - E. Joe Moran
- Center for Environmental Health, New York State Department of Health, Albany, NY, USA
- CDC Foundation, Atlanta, GA, USA
| | - Lydia J. Bennett
- Center for Environmental Health, New York State Department of Health, Albany, NY, USA
- CDC Foundation, Atlanta, GA, USA
| | - Ian Bradley
- Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY, USA
| | - Mary B. Collins
- School of Marine and Atmospheric Sciences, Sustainability Studies Division, Stony Brook University, Stony Brook, NY, USA
- Institute for Advanced Computational Science, Stony Brook University, Stony Brook, NY, USA
| | - Christopher J. Gobler
- New York State Center for Clean Water Technology, Stony Brook University, Stony Brook, NY, USA
- School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, USA
| | - Hyatt Green
- Department of Environmental Biology, State University of New York College of Environmental Science and Forestry, Syracuse, NY, USA
| | - Tabassum Z. Insaf
- Center for Environmental Health, New York State Department of Health, Albany, NY, USA
- Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, Rensselaer, NY, USA
| | - Brittany Kmush
- Department of Public Health, Syracuse University, Syracuse, NY, 13244, USA
| | - Dana Neigel
- Center for Environmental Health, New York State Department of Health, Albany, NY, USA
- CDC Foundation, Atlanta, GA, USA
| | - Shailla Raymond
- Center for Environmental Health, New York State Department of Health, Albany, NY, USA
- CDC Foundation, Atlanta, GA, USA
| | - Mian Wang
- New York State Center for Clean Water Technology, Stony Brook University, Stony Brook, NY, USA
- Department of Civil Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY, USA
| | - Yinyin Ye
- Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY, USA
| | - David A. Larsen
- Department of Public Health, Syracuse University, Syracuse, NY, 13244, USA
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