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Mashau F, Dada AC, Msolo L, Ebomah KE, Ekundayo TC, Iwu CD, Nontongana N, Okoh AI. Factors affecting detection and estimation of SARS-CoV-2 RNA concentration of COVID-19 positive cases in wastewater influent: A systematic review. Public Health 2024; 237:167-175. [PMID: 39418699 DOI: 10.1016/j.puhe.2024.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 09/09/2024] [Accepted: 10/08/2024] [Indexed: 10/19/2024]
Abstract
OBJECTIVE Wastewater Based Surveillance (WBS) has emerged as a novel monitoring tool for tracking and estimating the dissemination of the Novel Coronavirus Disease 2019 (COVID-19) within communities. STUDY DESIGN The goal of this review is to assess the factors that influence estimations of SARS-CoV-2 RNA concentration estimations in wastewater. SYSTEMATIC REVIEW The goal of this review is to assess the factors that influence estimations of SARS-CoV-2 RNA concentration estimations in wastewater. METHODS A literature search was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Scoping Reviews (PRISMA-ScR) criteria in the electronic databases Scopus, PubMed, Google Scholar, and Medline. The overall quality, sample methodologies, quantification methods, and estimating approaches of selected papers were assessed. RESULTS Our findings reveal that 16 out of 24 articles (67 %) focused on physiochemical analyses. This review showed that sampling strategies and laboratory methodologies play a crucial role in the detection of SARS-CoV-2 RNA in wastewater samples. Moreover, we found that WBS-based estimation of COVID-19 is influenced by several factors such as wastewater temperature, shedding rate, and population size. CONCLUSION This review reveals that the identified parameters require adjustments to achieve optimum conditions that accurately predict community infections. Including these factors that influence the estimation of SARS-CoV-2 RNA concentration in wastewater is essential for developing effective public health strategies to combat the spread of COVID-19.
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Affiliation(s)
- Funanani Mashau
- Department of Public Health, Faculty of Health Sciences, University of Fort Hare, East London, South Africa; SAMRC Microbial Water Quality Monitoring Centre, University of Fort Hare, Alice, 5700, South Africa; Applied and Environmental Microbiology Research Group (AEMREG), Department of Biochemistry and Microbiology, University of Fort Hare, Alice, 5700, South Africa.
| | - Ayokunle C Dada
- QMRA Data Experts, P. O. Box 37 Waikato Mail Centre, Hamilton, New Zealand
| | - Luyanda Msolo
- SAMRC Microbial Water Quality Monitoring Centre, University of Fort Hare, Alice, 5700, South Africa; Applied and Environmental Microbiology Research Group (AEMREG), Department of Biochemistry and Microbiology, University of Fort Hare, Alice, 5700, South Africa
| | - Kingsley E Ebomah
- SAMRC Microbial Water Quality Monitoring Centre, University of Fort Hare, Alice, 5700, South Africa; Applied and Environmental Microbiology Research Group (AEMREG), Department of Biochemistry and Microbiology, University of Fort Hare, Alice, 5700, South Africa
| | - Temitope C Ekundayo
- Department of Biotechnology and Food Science, Durban University of Technology, Steve Biko Campus, Health Services, 121 Steve Biko Rd, Musgrave, Berea, 4001, Durban, South Africa; Department of Biological Sciences, University of Medical Sciences, Ondo City, Ondo State, Nigeria
| | - Chidozie D Iwu
- SAMRC Microbial Water Quality Monitoring Centre, University of Fort Hare, Alice, 5700, South Africa
| | - Nolonwabo Nontongana
- SAMRC Microbial Water Quality Monitoring Centre, University of Fort Hare, Alice, 5700, South Africa; Applied and Environmental Microbiology Research Group (AEMREG), Department of Biochemistry and Microbiology, University of Fort Hare, Alice, 5700, South Africa
| | - Anthony I Okoh
- SAMRC Microbial Water Quality Monitoring Centre, University of Fort Hare, Alice, 5700, South Africa; Applied and Environmental Microbiology Research Group (AEMREG), Department of Biochemistry and Microbiology, University of Fort Hare, Alice, 5700, South Africa
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Zafeiriadou A, Nano K, Thomaidis NS, Markou A. Evaluation of PCR-enhancing approaches to reduce inhibition in wastewater samples and enhance viral load measurements. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 955:176768. [PMID: 39393702 DOI: 10.1016/j.scitotenv.2024.176768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 10/02/2024] [Accepted: 10/04/2024] [Indexed: 10/13/2024]
Abstract
Molecular-based assays are the most commonly used methods for the detection and quantification of viruses in wastewater. The variety of inhibitory substances present in the complex matrix of wastewater hinders downstream analysis and often leads to false negative results and underestimation of viral load. The development of robust and inhibitor-tolerant detection methods is necessary in the context of wastewater-based epidemiology, a valuable tool that has gained further importance since the emergence of the Covid-19 pandemic. Various strategies are used to mitigate inhibition in the polymerase chain reaction (PCR) with the most prevalent of all: the dilution of the sample and the inhibitor removal kits. In this study, we first indicated the presence of inhibitors in wastewater samples and the evaluation of eight different PCR enhancing strategies were further performed using reverse-transcription PCR (RT-qPCR) protocol. False negative results were eliminated through four approaches evaluated, a 10-fold dilution of the extracted sample, addition of T4 gene 32 protein (gp32), addition of Bovine Serum Albumin (BSA), and using an inhibitor removal kit. Among the methods that removed inhibition, the most significant for the removal of inhibition was the addition of gp32 (at a final concentration 0.2 μg/μl). This optimized protocol was further applied to wastewater samples tested for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and a direct comparison study was further performed with reverse-transcription droplet digital PCR (RT-ddPCR). The detection frequency of both methods was 100 % and the obtained viral concentrations were higher by RT-ddPCR; the optimized RT-qPCR assay showed a good correlation (Intraclass Correlation Coefficient: 0,713, p-value <0,007) with RT-ddPCR. This is the first study to directly compare common strategies for eliminating inhibition in wastewater and demonstrates the importance of developing robust assays to accurately assess the recovery rates and viral loads of the targets tested, in a simple, cost-effective and high-throughput manner.
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Affiliation(s)
- Anastasia Zafeiriadou
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Zografou, 15771 Athens, Greece
| | - Konstantina Nano
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Zografou, 15771 Athens, Greece
| | - Nikolaos S Thomaidis
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Zografou, 15771 Athens, Greece
| | - Athina Markou
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Zografou, 15771 Athens, Greece.
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Murakami M, Ando H, Yamaguchi R, Kitajima M. Evaluating survey techniques in wastewater-based epidemiology for accurate COVID-19 incidence estimation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 954:176702. [PMID: 39370003 DOI: 10.1016/j.scitotenv.2024.176702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Revised: 09/26/2024] [Accepted: 10/01/2024] [Indexed: 10/08/2024]
Abstract
Wastewater-based epidemiology (WBE) requires high-quality survey methods to determine the incidence of infections in wastewater catchment areas. In this study, the wastewater survey methods necessary for comprehending the incidence of infection by WBE are clarified. This clarification is based on the correlation with the number of confirmed coronavirus disease 2019 (COVID-19) cases, considering factors such as handling non-detect data, calculation method for representative values, analytical sensitivity, analytical reproducibility, sampling frequency, and survey duration. Data collected from 15 samples per week for two and a half years using a highly accurate analysis method were regarded as gold standard data, and the correlation between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater and confirmed COVID-19 cases was analyzed by Monte Carlo simulation under the hypothetical situation where the quality of the wastewater survey method was reduced. Regarding data handling, it was appropriate to replace non-detect data with estimates based on distribution, and to use geometric means to calculate representative values. For the analysis of SARS-CoV-2 RNA in samples, using a highly sensitive and reproducible method (non-detect rates of <40 %; ≤0.4 standard deviation) and surveying at least three samples, preferably five samples, per week were considered desirable. Furthermore, conducting the survey over a period of time that included at least 50 weeks was necessary. A WBE that meets these survey criteria is sufficient for the determination of the COVID-19 infection incidence in the catchment. Furthermore, WBE can offer additional insights into infection rates in the catchment, such as the estimated 48 % decrease in confirmed COVID-19 cases visiting a clinic following a COVID-19 legal reclassification in Japan.
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Affiliation(s)
- Michio Murakami
- Center for Infectious Disease Education and Research, Osaka University, 2-8 Yamadaoka, Suita-shi, Osaka 565-0871, Japan.
| | - Hiroki Ando
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan; Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ 85724, United States
| | - Ryo Yamaguchi
- Public Health Office, City of Sapporo, West 19, Odori, Chuo-ku, Sapporo, Hokkaido 060-0042, Japan
| | - Masaaki Kitajima
- Center for Infectious Disease Education and Research, Osaka University, 2-8 Yamadaoka, Suita-shi, Osaka 565-0871, Japan; Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan; Research Center for Water Environment Technology, School of Engineering, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan
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Jerpan J, Moriceau V, Salis A, Klein R, Olivier F, Salles J. Changes in suicide-related tweets before and during the COVID-19 pandemic in France: The importance of social media monitoring in public health prediction. L'ENCEPHALE 2024; 50:516-523. [PMID: 38040508 DOI: 10.1016/j.encep.2023.09.006] [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: 04/26/2023] [Revised: 09/03/2023] [Accepted: 09/19/2023] [Indexed: 12/03/2023]
Abstract
INTRODUCTION The COVID-19 pandemic impacted mental health, as demonstrated by numerous studies. In recent years, especially during the pandemic, the use of social networks, including Twitter, increased. This suggests that this media could help with mental health monitoring, as attested by previous studies. METHOD We conducted a multidisciplinary study on French tweets that were posted between January 1, 2019, and December 31, 2021. We selected the tweets via the Twitter API (Application Programming Interface) using five keywords relating to suicide: want to die, suicidal ideation, commit suicide, suicidal, and suicide attempt. A word frequency analysis was performed, and the data were compared with the number of emergency visits for suicidal ideation before and during the COVID-19 pandemic as recorded by the French national suicide observatory. RESULTS We observed that 189,005 tweets were related to suicide in 2019, 261,993 in 2020 (+38.62% of that observed in 2019), and 301,177 in 2021 (+59.35% of that observed in 2019). We also observed an increase in the number of tweets containing control words in 2020 (+30.07% of that observed in 2019), but in 2021, the number almost fell back to the level of that in 2019 (+5.96% of that observed in 2019). Furthermore, the difference between both ratios (of suicide-related tweets and of tweets containing control words) was most significant during the third lockdown. The change in the number of suicide-related tweets followed a curve that overlapped with the change in the number of emergency visits following suicidal ideations, as reported by the French national suicide observatory. In conclusion, Twitter can be an adequate and reliable tool for screening for suicidal ideation in the general population.
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Affiliation(s)
- Jeanne Jerpan
- Department of Psychiatry, CHU de Toulouse, University Hospital of Toulouse, Toulouse, France; Fédération Régionale de Recherche en Psychiatrie et santé mentale Occitanie, FERREPSY Occitanie, France
| | | | - Alexandrine Salis
- Department of Psychiatry, CHU de Toulouse, University Hospital of Toulouse, Toulouse, France; Fédération Régionale de Recherche en Psychiatrie et santé mentale Occitanie, FERREPSY Occitanie, France
| | - Remy Klein
- Union sanitaire et sociale Aude Pyrénées (USSAP), Limoux, France; Fédération Régionale de Recherche en Psychiatrie et santé mentale Occitanie, FERREPSY Occitanie, France
| | - François Olivier
- Centre Hospitalier de Montauban, Montauban, France; Fédération Régionale de Recherche en Psychiatrie et santé mentale Occitanie, FERREPSY Occitanie, France
| | - Juliette Salles
- Department of Psychiatry, Infinity (Toulouse Institute for Infectious and Inflammatory Diseases), Inserm UMR1291, CNRS UMR5051, CHU de Toulouse, University Hospital of Toulouse, Université Toulouse III, Toulouse, France; Fédération Régionale de Recherche en Psychiatrie et santé mentale Occitanie, FERREPSY Occitanie, France.
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Boza JM, Amirali A, Williams SL, Currall BB, Grills GS, Mason CE, Solo-Gabriele HM, Erickson DC. Evaluation of a field deployable, high-throughput RT-LAMP device as an early warning system for COVID-19 through SARS-CoV-2 measurements in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 944:173744. [PMID: 38844223 PMCID: PMC11249788 DOI: 10.1016/j.scitotenv.2024.173744] [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: 02/26/2024] [Revised: 05/02/2024] [Accepted: 06/01/2024] [Indexed: 06/16/2024]
Abstract
Quantification of SARS-CoV-2 RNA copies in wastewater can be used to estimate COVID-19 prevalence in communities. While such results are important for mitigating disease spread, SARS-CoV-2 measurements require sophisticated equipment and trained personnel, for which a centralized laboratory is necessary. This significantly impacts the time to result, defeating its purpose as an early warning detection tool. The objective of this study was to evaluate a field portable device (called MINI) for detecting SARS-CoV-2 viral loads in wastewater using real-time reverse transcriptase loop-mediated isothermal amplification (real-time RT-LAMP). The device was tested using wastewater samples collected from buildings (with 430 to 1430 inhabitants) that had known COVID-19-positive cases. Results show comparable performance of RT-LAMP against reverse transcriptase polymerase chain reaction (RT-qPCR) when detecting SARS-CoV-2 copies in wastewater. Both RT-LAMP and RT-qPCR detected SARS-CoV-2 in wastewater from buildings with at least three positive individuals within a 6-day time frame prior to diagnosis. The large 96-well throughput provided by MINI provided scalability to multi-building detection. The portability of the MINI device enabled decentralized on-site detection, significantly reducing the time to result. The overall findings support the use of RT-LAMP within the MINI configuration as an early detection system for COVID-19 infection using wastewater collected at the building scale.
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Affiliation(s)
- J M Boza
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14850, USA
| | - A Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - S L Williams
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - B B Currall
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - G S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - C 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
| | - H M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - D C Erickson
- Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14850, USA; Division of Nutritional Science, Cornell University, Ithaca, NY 14850, USA.
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Zhuang X, Moshi MA, Quinones O, Trenholm RA, Chang CL, Cordes D, Vanderford BJ, Vo V, Gerrity D, Oh EC. Drug Use Patterns in Wastewater and Socioeconomic and Demographic Indicators. JAMA Netw Open 2024; 7:e2432682. [PMID: 39312241 PMCID: PMC11420698 DOI: 10.1001/jamanetworkopen.2024.32682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/25/2024] Open
Abstract
Importance Measuring drug use behaviors in individuals and across large communities presents substantial challenges, often complicated by socioeconomic and demographic variables. Objectives To detect spatial and temporal changes in community drug use by analyzing concentrations of analytes in influent wastewater and exploring their associations with area-based socioeconomic and sociodemographic metrics like the area deprivation index (ADI) and rural-urban commuting area (RUCA) codes. Design, Setting, and Participants This longitudinal, cross-sectional wastewater study was performed from May 2022 to April 2023 and included biweekly influent wastewater samples of 39 analytes from 8 sampling locations across 6 wastewater treatment plants in southern Nevada. Statistical analyses were conducted in December 2023. Main Outcomes and Measures It was hypothesized that wastewater monitoring of pharmaceuticals and personal care products (PPCPs) and high-risk substances (HRSs) could reveal true spatial and temporal drug use patterns in near-real time. Data collection of samples for PPCPs and HRSs was performed using mass spectrometry. Both ADI and RUCA scores were utilized to characterize neighborhood contexts in the analysis. The false discovery rate (FDR) method was utilized to correct for multiple comparisons (PFDR). Results Over the 12-month wastewater monitoring period, 208 samples for PPCPs and HRSs were collected, and analysis revealed an increase in the consumption of HRSs and the seasonal variation in PPCP use in southern Nevada. There was a significant increase in levels of stimulant-associated analytes, such as cocaine (β = 9.17 × 10-4; SE = 1.29 × 10-4; PFDR = 1.40 × 10-10), and opioids or their metabolites, notably norfentanyl (β = 1.48 × 10-4; SE = 1.88 × 10-4; PFDR = 1.66 × 10-12). In contrast, DEET, an active ingredient in mosquito and tick repellents, demonstrated a seasonal use pattern (β = -4.85 × 10-4; SE = 2.09 × 10-4; PFDR = 4.87 × 10-2). Wastewater from more disadvantaged or rural neighborhoods, as assessed through ADI and RUCA scores, was more likely to show a significant positive correlation with HRSs, such as cocaine (β = 0.075; SE = 0.038; P = .05) and norfentanyl (β = 0.004; SE = 0.001; P = 1.64 × 10-5). Conclusions and Relevance These findings suggest that wastewater monitoring of PPCPs and HRSs offers a complementary method to existing public health tools, providing timely data for tracking substance use behaviors and use of PPCPs at a population level.
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Affiliation(s)
- Xiaowei Zhuang
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas
- Neuroscience Interdisciplinary PhD Program, University of Nevada, Las Vegas
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, Nevada
| | - Michael A Moshi
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas
- Neuroscience Interdisciplinary PhD Program, University of Nevada, Las Vegas
| | - Oscar Quinones
- Applied Research and Development Center, Southern Nevada Water Authority, Las Vegas
| | - Rebecca A Trenholm
- Applied Research and Development Center, Southern Nevada Water Authority, Las Vegas
| | - Ching-Lan Chang
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas
- Neuroscience Interdisciplinary PhD Program, University of Nevada, Las Vegas
| | - Dietmar Cordes
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, Nevada
| | - Brett J Vanderford
- Applied Research and Development Center, Southern Nevada Water Authority, Las Vegas
| | - Van Vo
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas
| | - Daniel Gerrity
- Applied Research and Development Center, Southern Nevada Water Authority, Las Vegas
| | - Edwin C Oh
- Laboratory of Neurogenetics and Precision Medicine, University of Nevada Las Vegas
- Neuroscience Interdisciplinary PhD Program, University of Nevada, Las Vegas
- Department of Brain Health, University of Nevada, Las Vegas
- Department of Internal Medicine, Kirk Kerkorian School of Medicine, University of Nevada, Las Vegas
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Sarekoski A, Lipponen A, Hokajärvi AM, Räisänen K, Tiwari A, Paspaliari D, Lehto KM, Oikarinen S, Heikinheimo A, Pitkänen T. Simultaneous biomass concentration and subsequent quantitation of multiple infectious disease agents and antimicrobial resistance genes from community wastewater. ENVIRONMENT INTERNATIONAL 2024; 191:108973. [PMID: 39182255 DOI: 10.1016/j.envint.2024.108973] [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: 11/20/2023] [Revised: 07/01/2024] [Accepted: 08/19/2024] [Indexed: 08/27/2024]
Abstract
Wastewater-based surveillance (WBS) of infectious disease agents is increasingly seen as a reliable source of population health data. To date, wastewater-based surveillance efforts have largely focused on individual pathogens. However, given that wastewater contains a broad range of pathogens circulating in the population, a more comprehensive approach could enhance its usability. We focused on the simultaneous detection of SARS-CoV-2, sapovirus, Campylobacter jejuni, Campylobacter coli, Salmonella spp., pathogenic Escherichia coli, Cryptosporidium spp., Giardia spp. and antimicrobial resistance genes (ARGs) of clinical relevance. To achieve this goal, biomass concentration and nucleic acid extraction methods were optimized, and samples were analyzed by using a set of (RT)-qPCR and (HT)-qPCR methods. We determined the prevalence and the spatial and temporal trends of the targeted pathogens and collected novel information on ARGs in Finnish wastewater. In addition, the use of different wastewater concentrates, namely the ultrafiltered concentrate of the supernatant and the centrifuged pellet, and the effect of freezing and thawing wastewater prior to sample processing were investigated with the indicator microbe crAssphage. Freeze-thawing of wastewater decreased the gene copy count of crAssphage in comparison to analyzing fresh samples (p < 0.001). Campylobacters were most abundant in two of the four studied summer months (30 % detection rate) and in wastewaters from regions with intensive animal farming. Salmonella, however, was detected in 40 % of the samples without any clear seasonal trends, and the highest gene copy numbers were recorded from the largest wastewater treatment plants. Beta-lactamase resistance genes that have commonly been detected in bacteria isolated from humans in Finland, namely blaCTX-M, blaOXA48, blaNDM, and blaKPC, were also frequently detected in wastewaters (100, 98, 98, and 70 % detection rates, respectively). These results confirm the reliability of using wastewater in public health surveillance and demonstrate the possibility to simultaneously perform WBS of multiple pathogens.
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Affiliation(s)
- Anniina Sarekoski
- Finnish Institute for Health and Welfare, Expert Microbiology Unit, Neulaniementie 4, Kuopio FI-70701, Finland; University of Helsinki, Faculty of Veterinary Medicine, Department of Food Hygiene and Environmental Health, Agnes Sjöbergin katu 2, Helsinki FI-00014, Finland.
| | - Anssi Lipponen
- Finnish Institute for Health and Welfare, Expert Microbiology Unit, Neulaniementie 4, Kuopio FI-70701, Finland.
| | - Anna-Maria Hokajärvi
- Finnish Institute for Health and Welfare, Expert Microbiology Unit, Neulaniementie 4, Kuopio FI-70701, Finland.
| | - Kati Räisänen
- Finnish Institute for Health and Welfare, Expert Microbiology Unit, Mannerheimintie 166, Helsinki FI-00271, Finland.
| | - Ananda Tiwari
- Finnish Institute for Health and Welfare, Expert Microbiology Unit, Neulaniementie 4, Kuopio FI-70701, Finland.
| | - Dafni Paspaliari
- Finnish Institute for Health and Welfare, Expert Microbiology Unit, Mannerheimintie 166, Helsinki FI-00271, Finland.
| | - Kirsi-Maarit Lehto
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, FI-33520 Tampere, Finland.
| | - Sami Oikarinen
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, FI-33520 Tampere, Finland.
| | - Annamari Heikinheimo
- University of Helsinki, Faculty of Veterinary Medicine, Department of Food Hygiene and Environmental Health, Agnes Sjöbergin katu 2, Helsinki FI-00014, Finland; Finnish Food Authority, Alvar Aallon katu 5, FI-60100 Seinäjoki, Finland.
| | - Tarja Pitkänen
- Finnish Institute for Health and Welfare, Expert Microbiology Unit, Neulaniementie 4, Kuopio FI-70701, Finland; University of Helsinki, Faculty of Veterinary Medicine, Department of Food Hygiene and Environmental Health, Agnes Sjöbergin katu 2, Helsinki FI-00014, Finland.
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Wascher M, Klaus CJ, Alvarado C, Panescu J, Quam M, Dannemiller KC, Tien JH. A mechanistic modeling and estimation framework for environmental pathogen surveillance. Math Biosci 2024; 377:109257. [PMID: 39173943 DOI: 10.1016/j.mbs.2024.109257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 05/30/2024] [Accepted: 07/08/2024] [Indexed: 08/24/2024]
Abstract
Environmental pathogen surveillance is a promising disease surveillance modality that has been widely adopted for SARS-CoV-2 monitoring. The highly variable nature of environmental pathogen data is a challenge for integrating these data into public health response. One source of this variability is heterogeneous infection both within an individual over the course of infection as well as between individuals in their pathogen shedding over time. We present a mechanistic modeling and estimation framework for connecting environmental pathogen data to the number of infected individuals. Infected individuals are modeled as shedding pathogen into the environment via a Poisson process whose rate parameter λt varies over the course of their infection. These shedding curves λt are themselves random, allowing for variation between individuals. We show that this results in a Poisson process for environmental pathogen levels with rate parameter a function of the number of infected individuals, total shedding over the course of infection, and pathogen removal from the environment. Theoretical results include determination of identifiable parameters for the model from environmental pathogen data and simple, explicit formulas for the likelihood for particular choices of individual shedding curves. We give a two step Bayesian inference framework, where the first step corresponds to calibration from data where the number of infected individuals is known, followed by an estimation step from environmental surveillance data when the number of infected individuals is unknown. We apply this modeling and estimation framework to synthetic data, as well as to an empirical case study of SARS-CoV-2 in environmental dust collected from isolation rooms housing university students. Both the synthetic data and empirical case study indicate high inter-individual variation in shedding, leading to wide credible intervals for the number of infected individuals. We examine how uncertainty in estimates of the number of infected individuals from environmental pathogen levels scales with the true number of infected individuals and model misspecification. While credible intervals for the number of infected individuals are wide, our results suggest that distinguishing between no infection and small-to-moderate levels of infection (≈10 infected individuals) may be possible, and that it is broadly possible to differentiate between moderate (≈40) and high (≈200) numbers of infected individuals.
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Affiliation(s)
- Matthew Wascher
- Division of Epidemiology, College of Public Health, The Ohio State University, United States of America; Department of Mathematics, Applied Mathematics, and Statistics, Case Western Reserve University, United States of America
| | - Colin J Klaus
- Mathematical Biosciences Institute and College of Public Health, The Ohio State University, United States of America
| | - Chance Alvarado
- Division of Epidemiology, College of Public Health, The Ohio State University, United States of America
| | - Jenny Panescu
- Department of Civil, Environmental and Geodetic Engineering, Division of Environmental Health Sciences, and Sustainability Institute, The Ohio State University, United States of America
| | - Mikkel Quam
- Division of Epidemiology, College of Public Health, The Ohio State University, United States of America
| | - Karen C Dannemiller
- Department of Civil, Environmental and Geodetic Engineering, Division of Environmental Health Sciences, and Sustainability Institute, The Ohio State University, United States of America
| | - Joseph H Tien
- Department of Mathematics and Division of Epidemiology, The Ohio State University, United States of America.
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Sartirano D, Morecchiato F, Antonelli A, Lotti T, Morelli D, Ramazzotti M, Rossolini GM, Lubello C. Verifying the feasibility of wastewater-based epidemiological monitoring for the small catchment and sewage networks with significant pretreatment. JOURNAL OF WATER AND HEALTH 2024; 22:1516-1526. [PMID: 39212284 DOI: 10.2166/wh.2024.121] [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: 03/20/2024] [Accepted: 07/14/2024] [Indexed: 09/04/2024]
Abstract
Wastewater-based epidemiology (WBE) has emerged as a valuable tool for COVID-19 monitoring, especially as the frequency of clinical testing diminishes. Beyond COronaVIrus Disease 19 (COVID-19), the tool's versatility extends to addressing various public health concerns, including antibiotic resistance and drug consumption. However, the complexity of sewage systems introduces noise when measuring chemical tracer concentrations, potentially compromising their applicability for modeling. In our study, we detail the approach adopted to determine the concentration of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) ribonucleiec acid (RNA) in wastewater from the Ponte a Niccheri wastewater treatment plant in Tuscany (Italy), with a sample size of N = 13,935 inhabitants. The unique characteristics of this wastewater system, including mandatory pretreatment in septic tanks with extended retention times, the presence of a hospital for COVID-19 patients, and mixed sewage networks, posed additional challenges. Nevertheless, our results highlight a robust and significant correlation between our measurements and the number of infections within the wastewater treatment plant's catchment area at the time of sampling. A simple linear model also shows promising results in estimating the number of infected people within the area.
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Affiliation(s)
- Daniele Sartirano
- Department of Civil and Environmental Engineering, University of Florence, Florence, Italy E-mail:
| | - Fabio Morecchiato
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Alberto Antonelli
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy; Microbiology and Virology Unit, Careggi University Hospital, University of Florence, Florence, Italy
| | - Tommaso Lotti
- Department of Civil and Environmental Engineering, University of Florence, Florence, Italy
| | | | - Matteo Ramazzotti
- Department of Experimental and Clinical Biomedical Sciences 'Mario Serio', University of Florence, Florence, Italy
| | - Gian Maria Rossolini
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy; Microbiology and Virology Unit, Careggi University Hospital, University of Florence, Florence, Italy
| | - Claudio Lubello
- Department of Civil and Environmental Engineering, University of Florence, Florence, Italy
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10
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D'Arpino MC, Sineli PE, Goroso G, Watanabe W, Saavedra ML, Hebert EM, Martínez MA, Migliavacca J, Gerstenfeld S, Chahla RE, Bellomio A, Albarracín VH. Wastewater monitoring of SARS-CoV-2 gene for COVID-19 epidemiological surveillance in Tucumán, Argentina. J Basic Microbiol 2024; 64:e2300773. [PMID: 38712352 DOI: 10.1002/jobm.202300773] [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: 12/29/2023] [Revised: 03/12/2024] [Accepted: 04/08/2024] [Indexed: 05/08/2024]
Abstract
Wastewater-based epidemiology provides temporal and spatial information about the health status of a population. The objective of this study was to analyze and report the epidemiological dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the province of Tucumán, Argentina during the second and third waves of coronavirus disease 2019 (COVID-19) between April 2021 and March 2022. The study aimed to quantify SARS-CoV-2 RNA in wastewater, correlating it with clinically reported COVID-19 cases. Wastewater samples (n = 72) were collected from 16 sampling points located in three cities of Tucumán (San Miguel de Tucumán, Yerba Buena y Banda del Río Salí). Detection of viral nucleocapsid markers (N1 gene) was carried out using one-step reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Viral loads were determined for each positive sample using a standard curve. A positive correlation (p < 0.05) was observed between viral load (copies/mL) and the clinically confirmed COVID-19 cases reported at specific sampling points in San Miguel de Tucumán (SP4, SP7, and SP8) in both months, May and June. Indeed, the high viral load concurred with the peaks of COVID-19 cases. This method allowed us to follow the behavior of SARS-CoV-2 infection during epidemic outbreaks. Thus, wastewater monitoring is a valuable epidemiological indicator that enables the anticipation of increases in COVID-19 cases and tracking the progress of the pandemic. SARS-CoV-2 genome-based surveillance should be implemented as a routine practice to prepare for any future surge in infections.
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Affiliation(s)
- María Cecilia D'Arpino
- Laboratory of Molecular and Ultraestructural Microbiology, Centro Integral de Microscopía Electrónica, (CIME-UNT-CONICET), Facultad de Agronomía, Zootecnia y Veterinaria, Universidad Nacional de Tucumán, Tucumán, Argentina
| | - Pedro Eugenio Sineli
- Planta Piloto de Procesos Industriales Microbiológicos (PROIMI-CONICET), Tucumán, Argentina
| | - Gustavo Goroso
- Laboratorio de Processamento de Sinais e Modelagem de Sistemas Biológicos. Núcleo de Pesquisas Tecnológicas, Universidade Mogi das Cruzes, Sao Paulo, Brasil
| | - William Watanabe
- Laboratorio de Processamento de Sinais e Modelagem de Sistemas Biológicos. Núcleo de Pesquisas Tecnológicas, Universidade Mogi das Cruzes, Sao Paulo, Brasil
| | | | | | | | | | | | | | - Augusto Bellomio
- Instituto Superior de Investigaciones Biológicas (INSIBIO, CONICET-Universidad Nacional de Tucumán), Tucumán, Argentina
| | - Virginia Helena Albarracín
- Laboratory of Molecular and Ultraestructural Microbiology, Centro Integral de Microscopía Electrónica, (CIME-UNT-CONICET), Facultad de Agronomía, Zootecnia y Veterinaria, Universidad Nacional de Tucumán, Tucumán, Argentina
- Facultad de Ciencias Naturales e Instituto Miguel Lillo, Universidad Nacional Tucumán, Tucumán, Argentina
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11
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Murni IK, Oktaria V, McCarthy DT, Supriyati E, Nuryastuti T, Handley A, Donato CM, Wiratama BS, Dinari R, Laksono IS, Thobari JA, Bines JE. Wastewater-based epidemiology surveillance as an early warning system for SARS-CoV-2 in Indonesia. PLoS One 2024; 19:e0307364. [PMID: 39024238 PMCID: PMC11257287 DOI: 10.1371/journal.pone.0307364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 07/03/2024] [Indexed: 07/20/2024] Open
Abstract
BACKGROUND Wastewater-based epidemiology (WBE) surveillance has been proposed as an early warning system (EWS) for community SARS-CoV-2 transmission. However, there is limited data from low-and middle-income countries (LMICs). This study aimed to assess the ability of WBE surveillance to detect SARS-CoV-2 in formal and informal environments in Indonesia using different methods of sample collection, to compare WBE data with patterns of clinical cases of COVID-19 within the relevant communities, and to assess the WBE potential to be used as an EWS for SARS-CoV-2 outbreaks within a community. MATERIALS AND METHODS We conducted WBE surveillance in three districts in Yogyakarta province, Indonesia, over eleven months (27 July 2021 to 7 January 2022 [Delta wave]; 18 January to 3 June 2022 [Omicron wave]). Water samples using grab, and/or passive sampling methods and soil samples were collected either weekly or fortnightly. RNA was extracted from membrane filters from processed water samples and directly from soil. Reverse-transcription quantitative real-time polymerase chain reaction (RT-qPCR) was performed to detect the SARS-CoV-2 N and ORF1ab genes. RESULTS A total of 1,582 samples were collected. Detection rates of SARS-CoV-2 in wastewater reflected the incidence of community cases, with rates of 85% at the peak to 2% at the end of the Delta wave and from 94% to 11% during the Omicron wave. A 2-week lag time was observed between the detection of SARS-CoV-2 in wastewater and increasing cases in the corresponding community. CONCLUSION WBE surveillance for SARS-CoV-2 in Indonesia was effective in monitoring patterns of cases of COVID-19 and served as an early warning system, predicting the increasing incidence of COVID-19 cases in the community.
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Affiliation(s)
- Indah Kartika Murni
- Center for Child Health – Pediatric Research Office, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
- Child Health Department, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Vicka Oktaria
- Center for Child Health – Pediatric Research Office, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
- Department of Biostatistics, Epidemiology, and Population Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - David T. McCarthy
- Department of Civil Engineering, Environmental and Public Health Microbiology Lab (EPHM Lab), Monash University, Clayton, Victoria Australia
- School of Civil and Environmental Engineering, Faculty of Engineering, Queensland University of Technology, Queensland, Australia
| | - Endah Supriyati
- Center for Tropical Medicine, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Titik Nuryastuti
- Department of Microbiology, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Amanda Handley
- Medicines Development for Global Health, Southbank, Victoria Australia
- Enteric Diseases Group, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Celeste M. Donato
- Enteric Diseases Group, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Australia
| | - Bayu Satria Wiratama
- Department of Biostatistics, Epidemiology, and Population Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Rizka Dinari
- Center for Child Health – Pediatric Research Office, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Ida Safitri Laksono
- Center for Child Health – Pediatric Research Office, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
- Child Health Department, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Jarir At Thobari
- Center for Child Health – Pediatric Research Office, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Julie E Bines
- Enteric Diseases Group, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Australia
- Department of Gastroenterology and Clinical Nutrition, Royal Children’s Hospital Melbourne, Victoria, Australia
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12
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Watson LM, Plank MJ, Armstrong BA, Chapman JR, Hewitt J, Morris H, Orsi A, Bunce M, Donnelly CA, Steyn N. Jointly estimating epidemiological dynamics of Covid-19 from case and wastewater data in Aotearoa New Zealand. COMMUNICATIONS MEDICINE 2024; 4:143. [PMID: 39009723 PMCID: PMC11250817 DOI: 10.1038/s43856-024-00570-3] [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: 08/22/2023] [Accepted: 07/04/2024] [Indexed: 07/17/2024] Open
Abstract
BACKGROUND Timely and informed public health responses to infectious diseases such as COVID-19 necessitate reliable information about infection dynamics. The case ascertainment rate (CAR), the proportion of infections that are reported as cases, is typically much less than one and varies with testing practices and behaviours, making reported cases unreliable as the sole source of data. The concentration of viral RNA in wastewater samples provides an alternate measure of infection prevalence that is not affected by clinical testing, healthcare-seeking behaviour or access to care. METHODS We construct a state-space model with observed data of levels of SARS-CoV-2 in wastewater and reported case incidence and estimate the hidden states of the effective reproduction number, R, and CAR using sequential Monte Carlo methods. RESULTS We analyse data from 1 January 2022 to 31 March 2023 from Aotearoa New Zealand. Our model estimates that R peaks at 2.76 (95% CrI 2.20, 3.83) around 18 February 2022 and the CAR peaks around 12 March 2022. We calculate that New Zealand's second Omicron wave in July 2022 is similar in size to the first, despite fewer reported cases. We estimate that the CAR in the BA.5 Omicron wave in July 2022 is approximately 50% lower than in the BA.1/BA.2 Omicron wave in March 2022. CONCLUSIONS Estimating R, CAR, and cumulative number of infections provides useful information for planning public health responses and understanding the state of immunity in the population. This model is a useful disease surveillance tool, improving situational awareness of infectious disease dynamics in real-time.
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Affiliation(s)
- Leighton M Watson
- School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand.
| | - Michael J Plank
- School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
| | | | - Joanne R Chapman
- Institute of Environmental Science and Research Ltd, Porirua, New Zealand
| | - Joanne Hewitt
- Institute of Environmental Science and Research Ltd, Porirua, New Zealand
| | - Helen Morris
- Institute of Environmental Science and Research Ltd, Porirua, New Zealand
| | - Alvaro Orsi
- Institute of Environmental Science and Research Ltd, Porirua, New Zealand
| | - Michael Bunce
- Institute of Environmental Science and Research Ltd, Porirua, New Zealand
| | - Christl A Donnelly
- Department of Statistics, University of Oxford, Oxford, United Kingdom
- Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom
| | - Nicholas Steyn
- Department of Statistics, University of Oxford, Oxford, United Kingdom
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13
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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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14
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Xu J, Liu C, Zhang Q, Zhu H, Cui F, Zhao Z, Song M, Zhou B, Zhang Y, Hu P, Li L, Wang Q, Wang P. The first detection of mpox virus DNA from wastewater in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 932:172742. [PMID: 38679098 DOI: 10.1016/j.scitotenv.2024.172742] [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: 01/24/2024] [Revised: 04/14/2024] [Accepted: 04/22/2024] [Indexed: 05/01/2024]
Abstract
Wastewater monitoring may be a valuable early surveillance tool for studying mpox virus (MPXV) circulation in China, a country with high population density and very few mpox patients. To evaluate the effectiveness of wastewater monitoring for MPXV in detecting local hidden transmission of the epidemic in the early period, the Chinese Center for Disease Control and Prevention initiated a wastewater monitoring program for MPXV in China in July 2023. To enhance the monitoring sensitivity of the program, an MPXV monitoring point was established in a gathering place of high-risk mpox population. Three different concentration methods, PEG precipitation, ultrafiltration, and magnetic beads method were evaluated and compared. Due to its high recovery efficiency, low limit of detection, and high degree of automation, the magnetic beads method was selected for the daily surveillance of MPXV in wastewater. On September 5, 2023, MPXV DNA was detected at the MPXV monitoring point in Zibo City, marking the first instance of MPXV detection of MPXV in wastewater in China. Next-generation sequencing was conducted on the MPXV genome obtained from the positive wastewater, positive environmental samples, and the single case of mpox in Zibo in September. The results showed that the genotypes of these three genomes were different but all belong to the IIb branch of the C.1 lineage, indicating a probably hidden transmission of mpox. Wastewater monitoring is potentially an effective early surveillance tool for tracking the spread of MPXV in areas with high population density and very few mpox patients.
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Affiliation(s)
- Jin Xu
- Center for Disease Control and Prevention of Zibo, Zibo 255000, PR China
| | - Chao Liu
- Center for Disease Control and Prevention of Zibo, Zibo 255000, PR China
| | - Qun Zhang
- Center for Disease Control and Prevention of Zibo, Zibo 255000, PR China
| | - Haining Zhu
- Center for Disease Control and Prevention of Zibo, Zibo 255000, PR China
| | - Feng Cui
- Center for Disease Control and Prevention of Zibo, Zibo 255000, PR China
| | - Zhiqiang Zhao
- Center for Disease Control and Prevention of Zibo, Zibo 255000, PR China
| | - Mingfang Song
- Sunan Institute for Molecular Engineering, Peking University, Suzhou 215000, PR China
| | - Bo Zhou
- Sunan Institute for Molecular Engineering, Peking University, Suzhou 215000, PR China
| | - Yunxiao Zhang
- Center for Disease Control and Prevention of Zibo, Zibo 255000, PR China
| | - Peilong Hu
- Center for Disease Control and Prevention of Zibo, Zibo 255000, PR China
| | - Lei Li
- Center for Disease Control and Prevention of Zibo, Zibo 255000, PR China
| | - Qin Wang
- Center for Disease Control and Prevention of Zibo, Zibo 255000, PR China.
| | - Peng Wang
- School of Material Science and Engineering, Shandong University of Technology, Zibo 255000, PR China
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15
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Morecchiato F, Coppi M, Niccolai C, Antonelli A, Di Gloria L, Calà P, Mancuso F, Ramazzotti M, Lotti T, Lubello C, Rossolini GM. Evaluation of different molecular systems for detection and quantification of SARS-CoV-2 RNA from wastewater samples. J Virol Methods 2024; 328:114956. [PMID: 38796134 DOI: 10.1016/j.jviromet.2024.114956] [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: 11/29/2023] [Revised: 05/16/2024] [Accepted: 05/17/2024] [Indexed: 05/28/2024]
Abstract
Wastewater-based epidemiology has proved to be a suitable approach for tracking the spread of epidemic agents including SARS-CoV-2 RNA. Different protocols have been developed for quantitative detection of SARS-CoV-2 RNA from wastewater samples, but little is known on their performance. In this study we compared three protocols based on Reverse Transcription Real Time-PCR (RT-PCR) and one based on Droplet Digital PCR (ddPCR) for SARS-CoV-2 RNA detection from 35 wastewater samples. Overall, SARS-CoV-2 RNA was detected by at least one method in 85.7 % of samples, while 51.4 %, 22.8 % and 8.6 % resulted positive with two, three or all four methods, respectively. Protocols based on commercial RT-PCR assays and on Droplet Digital PCR showed an overall higher sensitivity vs. an in-house assay. The use of more than one system, targeting different genes, could be helpful to increase detection sensitivity.
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Affiliation(s)
- Fabio Morecchiato
- Department of Experimental and Clinical Medicine (DMSC), University of Florence, Largo Brambilla, 3, Firenze (FI) 50134, Italy
| | - Marco Coppi
- Department of Experimental and Clinical Medicine (DMSC), University of Florence, Largo Brambilla, 3, Firenze (FI) 50134, Italy; Microbiology and Virology Unit, Careggi University Hospital, Largo Brambilla, 3, Firenze (FI) 50134, Italy
| | - Claudia Niccolai
- Department of Experimental and Clinical Medicine (DMSC), University of Florence, Largo Brambilla, 3, Firenze (FI) 50134, Italy; Microbiology and Virology Unit, Careggi University Hospital, Largo Brambilla, 3, Firenze (FI) 50134, Italy
| | - Alberto Antonelli
- Department of Experimental and Clinical Medicine (DMSC), University of Florence, Largo Brambilla, 3, Firenze (FI) 50134, Italy; Microbiology and Virology Unit, Careggi University Hospital, Largo Brambilla, 3, Firenze (FI) 50134, Italy
| | - Leandro Di Gloria
- Department of Experimental Biomedical and Clinical Sciences "Mario Serio" (SBSC), University of Florence, Viale Morgagni, 50, Firenze (FI) 50134, Italy
| | - Piergiuseppe Calà
- Tuscany Region, Department of Prevention Local Health Authority Tuscany Center, Via S. Salvi, 12, Firenze (FI) 50135, Italy
| | - Fabrizio Mancuso
- Ingegnerie Toscane - Area R&D, Via Bellatalla, 1, Pisa (PI) 56121, Italy
| | - Matteo Ramazzotti
- Department of Experimental Biomedical and Clinical Sciences "Mario Serio" (SBSC), University of Florence, Viale Morgagni, 50, Firenze (FI) 50134, Italy
| | - Tommaso Lotti
- Department of Civil and Environmental Engineering (DICEA), University of Florence, Via di S. Marta, 3, Firenze (FI) 50139, Italy
| | - Claudio Lubello
- Department of Civil and Environmental Engineering (DICEA), University of Florence, Via di S. Marta, 3, Firenze (FI) 50139, Italy
| | - Gian Maria Rossolini
- Department of Experimental and Clinical Medicine (DMSC), University of Florence, Largo Brambilla, 3, Firenze (FI) 50134, Italy; Microbiology and Virology Unit, Careggi University Hospital, Largo Brambilla, 3, Firenze (FI) 50134, Italy.
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16
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Corrêa-Moreira D, da Costa GL, de Lima Neto RG, Pinto T, Salomão B, Fumian TM, Mannarino CF, Prado T, Miagostovich MP, de Souza Ramos L, Souza Dos Santos AL, Oliveira MME. Screening of Candida spp. in wastewater in Brazil during COVID-19 pandemic: workflow for monitoring fungal pathogens. BMC Biotechnol 2024; 24:43. [PMID: 38909197 PMCID: PMC11193224 DOI: 10.1186/s12896-024-00868-z] [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: 01/29/2024] [Accepted: 06/07/2024] [Indexed: 06/24/2024] Open
Abstract
Fungal diseases are often linked to poverty, which is associated with poor hygiene and sanitation conditions that have been severely worsened by the COVID-19 pandemic. Moreover, COVID-19 patients are treated with Dexamethasone, a corticosteroid that promotes an immunosuppressive profile, making patients more susceptible to opportunistic fungal infections, such as those caused by Candida species. In this study, we analyzed the prevalence of Candida yeasts in wastewater samples collected to track viral genetic material during the COVID-19 pandemic and identified the yeasts using polyphasic taxonomy. Furthermore, we investigated the production of biofilm and hydrolytic enzymes, which are known virulence factors. Our findings revealed that all Candida species could form biofilms and exhibited moderate hydrolytic enzyme activity. We also proposed a workflow for monitoring wastewater using Colony PCR instead of conventional PCR, as this technique is fast, cost-effective, and reliable. This approach enhances the accurate taxonomic identification of yeasts in environmental samples, contributing to environmental monitoring as part of the One Health approach, which preconizes the monitoring of possible emergent pathogenic microorganisms, including fungi.
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Affiliation(s)
- Danielly Corrêa-Moreira
- Laboratory of Taxonomy, Biochemistry and Bioprospecting of Fungi, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, 21040-360, Brazil.
| | - Gisela Lara da Costa
- Laboratory of Taxonomy, Biochemistry and Bioprospecting of Fungi, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, 21040-360, Brazil
| | | | - Tatiana Pinto
- Medical Microbiology Department, Paulo de Goés Institute of Microbiology, Federal University of Rio de Janeiro, Rio de Janeiro, 21941-909, Brazil
| | - Bruna Salomão
- Laboratory of Microbiology, Federal Hospital of Andaraí, Rio de Janeiro, 20541-173, Brazil
| | - Tulio Machado Fumian
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, 21040-360, Brazil
| | - Camille Ferreira Mannarino
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, 21040-360, Brazil
| | - Tatiana Prado
- Laboratory of Respiratory, Exanthematic, Enteric viruses and Viral Emergencies, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, 21040-360, Brazil
| | - Marize Pereira Miagostovich
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, 21040-360, Brazil
| | - Lívia de Souza Ramos
- Laboratory for Advanced Studies of Emerging and Resistant Microorganisms, General Microbiology Department, Institute of Microbiology Paulo de Góes, Federal University of Rio de Janeiro, Rio de Janeiro, 21941-909, Brazil
| | - André Luis Souza Dos Santos
- Laboratory for Advanced Studies of Emerging and Resistant Microorganisms, General Microbiology Department, Institute of Microbiology Paulo de Góes, Federal University of Rio de Janeiro, Rio de Janeiro, 21941-909, Brazil
| | - Manoel Marques Evangelista Oliveira
- Laboratory of Taxonomy, Biochemistry and Bioprospecting of Fungi, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, 21040-360, Brazil.
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17
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Zhuang X, Vo V, Moshi MA, Dhede K, Ghani N, Akbar S, Chang CL, Young AK, Buttery E, Bendik W, Zhang H, Afzal S, Moser D, Cordes D, Lockett C, Gerrity D, Kan HY, Oh EC. Early Detection of Novel SARS-CoV-2 Variants from Urban and Rural Wastewater through Genome Sequencing and Machine Learning. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.18.24306052. [PMID: 38699326 PMCID: PMC11065002 DOI: 10.1101/2024.04.18.24306052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Genome sequencing from wastewater has emerged as an accurate and cost-effective tool for identifying SARS-CoV-2 variants. However, existing methods for analyzing wastewater sequencing data are not designed to detect novel variants that have not been characterized in humans. Here, we present an unsupervised learning approach that clusters co-varying and time-evolving mutation patterns leading to the identification of SARS-CoV-2 variants. To build our model, we sequenced 3,659 wastewater samples collected over a span of more than two years from urban and rural locations in Southern Nevada. We then developed a multivariate independent component analysis (ICA)-based pipeline to transform mutation frequencies into independent sources with co-varying and time-evolving patterns and compared variant predictions to >5,000 SARS-CoV-2 clinical genomes isolated from Nevadans. Using the source patterns as data-driven reference "barcodes", we demonstrated the model's accuracy by successfully detecting the Delta variant in late 2021, Omicron variants in 2022, and emerging recombinant XBB variants in 2023. Our approach revealed the spatial and temporal dynamics of variants in both urban and rural regions; achieved earlier detection of most variants compared to other computational tools; and uncovered unique co-varying mutation patterns not associated with any known variant. The multivariate nature of our pipeline boosts statistical power and can support accurate and early detection of SARS-CoV-2 variants. This feature offers a unique opportunity for novel variant and pathogen detection, even in the absence of clinical testing.
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18
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Yu Q, Olesen SW, Duvallet C, Grad YH. Assessment of sewer connectivity in the United States and its implications for equity in wastewater-based epidemiology. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0003039. [PMID: 38630670 PMCID: PMC11023481 DOI: 10.1371/journal.pgph.0003039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 02/28/2024] [Indexed: 04/19/2024]
Abstract
Wastewater-based epidemiology is a promising public health tool that can yield a more representative view of the population than case reporting. However, only about 80% of the U.S. population is connected to public sewers, and the characteristics of populations missed by wastewater-based epidemiology are unclear. To address this gap, we used publicly available datasets to assess sewer connectivity in the U.S. by location, demographic groups, and economic groups. Data from the U.S. Census' American Housing Survey revealed that sewer connectivity was lower than average when the head of household was American Indian and Alaskan Native, White, non-Hispanic, older, and for larger households and those with higher income, but smaller geographic scales revealed local variations from this national connectivity pattern. For example, data from the U.S. Environmental Protection Agency showed that sewer connectivity was positively correlated with income in Minnesota, Florida, and California. Data from the U.S. Census' American Community Survey and Environmental Protection Agency also revealed geographic areas with low sewer connectivity, such as Alaska, the Navajo Nation, Minnesota, Michigan, and Florida. However, with the exception of the U.S. Census data, there were inconsistencies across datasets. Using mathematical modeling to assess the impact of wastewater sampling inequities on inferences about epidemic trajectory at a local scale, we found that in some situations, even weak connections between communities may allow wastewater monitoring in one community to serve as a reliable proxy for an interacting community with no wastewater monitoring, when cases are widespread. A systematic, rigorous assessment of sewer connectivity will be important for ensuring an equitable and informed implementation of wastewater-based epidemiology as a public health monitoring system.
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Affiliation(s)
- QinQin Yu
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Scott W. Olesen
- Biobot Analytics, Inc., Cambridge, Massachusetts, United States of America
| | - Claire Duvallet
- Biobot Analytics, Inc., Cambridge, Massachusetts, United States of America
| | - Yonatan H. Grad
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
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19
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Perry WB, Chrispim MC, Barbosa MRF, de Souza Lauretto M, Razzolini MTP, Nardocci AC, Jones O, Jones DL, Weightman A, Sato MIZ, Montagner C, Durance I. Cross-continental comparative experiences of wastewater surveillance and a vision for the 21st century. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 919:170842. [PMID: 38340868 DOI: 10.1016/j.scitotenv.2024.170842] [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: 07/21/2023] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 02/12/2024]
Abstract
The COVID-19 pandemic has brought the epidemiological value of monitoring wastewater into sharp focus. The challenges of implementing and optimising wastewater monitoring vary significantly from one region to another, often due to the array of different wastewater systems around the globe, as well as the availability of resources to undertake the required analyses (e.g. laboratory infrastructure and expertise). Here we reflect on the local and shared challenges of implementing a SARS-CoV-2 monitoring programme in two geographically and socio-economically distinct regions, São Paulo state (Brazil) and Wales (UK), focusing on design, laboratory methods and data analysis, and identifying potential guiding principles for wastewater surveillance fit for the 21st century. Our results highlight the historical nature of region-specific challenges to the implementation of wastewater surveillance, including previous experience of using wastewater surveillance, stakeholders involved, and nature of wastewater infrastructure. Building on those challenges, we then highlight what an ideal programme would look like if restrictions such as resource were not a constraint. Finally, we demonstrate the value of bringing multidisciplinary skills and international networks together for effective wastewater surveillance.
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Affiliation(s)
| | - Mariana Cardoso Chrispim
- Environmental and Biosciences Department, School of Business, Innovation and Sustainability, Halmstad University, Kristian IV:s väg 3, 30118 Halmstad, Sweden
| | - Mikaela Renata Funada Barbosa
- Environmental Analysis Department, Environmental Company of the São Paulo State (CETESB), Av. Prof. Frederico Hermann Jr., 345, São Paulo CEP 05459-900, Brazil; NARA - Center for Research in Environmental Risk Assessment, School of Public Health, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil
| | - Marcelo de Souza Lauretto
- NARA - Center for Research in Environmental Risk Assessment, School of Public Health, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil; School of Arts, Sciences and Humanities, University of Sao Paulo, Rua Arlindo Bettio, 1000, São Paulo CEP 03828-000, Brazil
| | - Maria Tereza Pepe Razzolini
- NARA - Center for Research in Environmental Risk Assessment, School of Public Health, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil; School of Public Health, University of Sao Paulo, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil
| | - Adelaide Cassia Nardocci
- NARA - Center for Research in Environmental Risk Assessment, School of Public Health, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil; School of Public Health, University of Sao Paulo, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil
| | - Owen Jones
- School of Mathematics, Cardiff University, Cardiff CF24 4AG, UK
| | - Davey L Jones
- Environment Centre Wales, Bangor University, Bangor LL57 2UW, UK; Food Futures Institute, Murdoch University, Murdoch WA 6105, Australia
| | | | - Maria Inês Zanoli Sato
- Environmental Analysis Department, Environmental Company of the São Paulo State (CETESB), Av. Prof. Frederico Hermann Jr., 345, São Paulo CEP 05459-900, Brazil; NARA - Center for Research in Environmental Risk Assessment, School of Public Health, Environmental Health Department, Av. Dr Arnaldo, 715, 01246-904 São Paulo, Brazil
| | - Cassiana Montagner
- Environmental Chemistry Laboratory, Institute of Chemistry, University of Campinas, Campinas, São Paulo 13083970, Brazil
| | - Isabelle Durance
- School of Biosciences, Cardiff University, Cardiff CF10 3AX, UK.
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20
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Inson JGM, Malla B, Amalin DM, Carvajal TM, Enriquez MLD, Hirai S, Raya S, Rahmani AF, Angga MS, Sthapit N, Shrestha S, Ruti AA, Takeda T, Kitajima M, Alam ZF, Haramoto E. Detection of SARS-CoV-2 and Omicron variant RNA in wastewater samples from Manila, Philippines. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 919:170921. [PMID: 38350577 DOI: 10.1016/j.scitotenv.2024.170921] [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: 11/22/2023] [Revised: 01/26/2024] [Accepted: 02/10/2024] [Indexed: 02/15/2024]
Abstract
Manila, a highly urbanized city, is listed as one of the top cities with the highest recorded number of coronavirus disease 2019 (COVID-19) cases in the Philippines. This study aimed to detect and quantify the RNA of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the Omicron variant in 51 wastewater samples collected from three locations in Manila, namely Estero de Santa Clara, Estero de Pandacan, which are open drainages, and a sewage treatment plant (STP) at De La Salle University-Manila, between July 2022 and February 2023. Using one-step reverse transcription-quantitative polymerase chain reaction, SARS-CoV-2 and Omicron variant RNA were detected in 78 % (40/51; 4.9 ± 0.5 log10 copies/L) and 60 % (24/40; 4.4 ± 0.3 log10 copies/L) of wastewater samples collected from all sampling sites, respectively. SARS-CoV-2 RNA was detected frequently at Estero de Santa Clara (88 %, 15/17); its highest concentration was at the STP (6.3 log10 copies/L). The Omicron variant RNA was present in the samples collected (4.4 ± 0.3 log10 copies/L) from all sampling sites, with the highest concentration at the STP (4.9 log10 copies/L). Regardless of normalization, using concentrations of pepper mild mottle virus RNA, SARS-CoV-2 RNA concentrations exhibited the highest positive correlation with COVID-19 reported cases in Manila 5 days after the clinical report. These findings revealed that wastewater-based epidemiology may aid in identifying and monitoring of the presence of pathogens in open drainages and STPs in the Philippines. This paper provides the first documentation on SARS-CoV-2 and the Omicron variant in wastewater from Manila.
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Affiliation(s)
- Jessamine Gail M Inson
- Department of Biology, De La Salle University, Manila 1004, Philippines; Environmental Biomonitoring Research Unit, Center for Natural Sciences and Environmental Research, De La Salle University, Manila 1004, Philippines.
| | - Bikash Malla
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Divina M Amalin
- Department of Biology, De La Salle University, Manila 1004, Philippines; Biological Control Research Unit, Center for Natural Sciences and Environmental Research, De La Salle University, Manila 1004, Philippines.
| | - Thaddeus M Carvajal
- Department of Biology, De La Salle University, Manila 1004, Philippines; Biological Control Research Unit, Center for Natural Sciences and Environmental Research, De La Salle University, Manila 1004, Philippines.
| | | | - 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
| | - Niva Sthapit
- 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
| | - Annisa Andarini Ruti
- Department of Engineering, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Tomoko Takeda
- Department of Earth and Planetary Science, The University of Tokyo, Tokyo 113-0033, Japan.
| | - Masaaki Kitajima
- Division of Environmental Engineering, Hokkaido University, Sapporo, Hokkaido 060-8628, Japan.
| | - Zeba F Alam
- Department of Biology, De La Salle University, Manila 1004, Philippines; Environmental Biomonitoring Research Unit, Center for Natural Sciences and Environmental Research, De La Salle University, Manila 1004, Philippines.
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan.
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21
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Amirali A, Babler KM, Sharkey ME, Beaver CC, Boone MM, Comerford S, Cooper D, Currall BB, Goodman KW, Grills GS, Kobetz E, Kumar N, Laine J, Lamar WE, Mason CE, Reding BD, Roca MA, Ryon K, Schürer SC, Shukla BS, Solle NS, Stevenson M, Tallon JJ, Vidović D, Williams SL, Yin X, Solo-Gabriele HM. Wastewater based surveillance can be used to reduce clinical testing intensity on a university campus. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170452. [PMID: 38296085 PMCID: PMC10923133 DOI: 10.1016/j.scitotenv.2024.170452] [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: 11/09/2023] [Revised: 12/30/2023] [Accepted: 01/19/2024] [Indexed: 02/07/2024]
Abstract
Clinical testing has been a vital part of the response to and suppression of the COVID-19 pandemic; however, testing imposes significant burdens on a population. College students had to contend with clinical testing while simultaneously dealing with health risks and the academic pressures brought on by quarantines, changes to virtual platforms, and other disruptions to daily life. The objective of this study was to analyze whether wastewater surveillance can be used to decrease the intensity of clinical testing while maintaining reliable measurements of diseases incidence on campus. Twelve months of human health and wastewater surveillance data for eight residential buildings on a university campus were analyzed to establish how SARS-CoV-2 levels in the wastewater can be used to minimize clinical testing burden on students. Wastewater SARS-CoV-2 levels were used to create multiple scenarios, each with differing levels of testing intensity, which were compared to the actual testing volumes implemented by the university. We found that scenarios in which testing intensity fluctuations matched rise and falls in SARS-CoV-2 wastewater levels had stronger correlations between SARS-CoV-2 levels and recorded clinical positives. In addition to stronger correlations, most scenarios resulted in overall fewer weekly clinical tests performed. We suggest the use of wastewater surveillance to guide COVID-19 testing as it can significantly increase the efficacy of COVID-19 surveillance while reducing the burden placed on college students during a pandemic. Future efforts should be made to integrate wastewater surveillance into clinical testing strategies implemented on college campuses.
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Affiliation(s)
- Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - 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, 33136, FL, USA
| | - Cynthia C Beaver
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Melinda M Boone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Samuel Comerford
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | | | - Benjamin B Currall
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Kenneth W Goodman
- Frost Institute for Data Science & Computing, University of Miami, Coral Gables, FL 33146, USA; Institute for Bioethics and Health Policy, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Erin Kobetz
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - Naresh Kumar
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Walter E Lamar
- Division of Occupational Health, Safety & Compliance, University of Miami Health System, 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
| | - 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
| | - Krista Ryon
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10021, 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 Medicines, Miami, FL 33136, USA; Institute for Data Science & Computing, University of Miami, Coral Gables, FL 33146, USA
| | - Bhavarth S Shukla
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - Natasha Schaefer Solle
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA; Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Mario Stevenson
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL 33146, USA
| | - Dušica Vidović
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Sion L Williams
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Xue Yin
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA.
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22
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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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23
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Van Poelvoorde LAE, Gobbo A, Nauwelaerts SJD, Verhaegen B, Lesenfants M, Janssens R, Hutse V, Fraiture MA, De Keersmaecker S, Herman P, Van Hoorde K, Roosens N. Development of a reverse transcriptase digital droplet polymerase chain reaction-based approach for SARS-CoV-2 variant surveillance in wastewater. WATER ENVIRONMENT RESEARCH : A RESEARCH PUBLICATION OF THE WATER ENVIRONMENT FEDERATION 2024; 96:e10999. [PMID: 38414298 DOI: 10.1002/wer.10999] [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: 11/27/2023] [Revised: 01/16/2024] [Accepted: 01/27/2024] [Indexed: 02/29/2024]
Abstract
An urgent need for effective surveillance strategies arose due to the global emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although vaccines and antivirals are available, concerns persist about the evolution of new variants with potentially increased infectivity, transmissibility, and immune evasion. Therefore, variant monitoring is crucial for public health decision-making. Wastewater-based surveillance has proven to be an effective tool to monitor SARS-CoV-2 variants within populations. Specific SARS-CoV-2 variants are detected and quantified in wastewater in this study using a reverse transcriptase digital droplet polymerase chain reaction (RT-ddPCR) approach. The 11 designed assays were first validated in silico using a substantial dataset of high-quality SARS-CoV-2 genomes to ensure comprehensive variant coverage. The assessment of the sensitivity and specificity with reference material showed the capability of the developed assays to reliably identify target mutations while minimizing false positives and false negatives. The applicability of the assays was evaluated using wastewater samples from a wastewater treatment plant in Ghent, Belgium. The quantification of the specific mutations linked to the variants of concern present in these samples was calculated using these assays based on the detection of single mutations, which confirms their use for real-world variant surveillance. In conclusion, this study provides an adaptable protocol to monitor SARS-CoV-2 variants in wastewater with high sensitivity and specificity. Its potential for broader application in other viral surveillance contexts highlights its added value for rapid response to emerging infectious diseases. PRACTITIONER POINTS: Robust RT-ddPCR methodology for specific SARS-CoV-2 variants of concern detection in wastewater. Rigorous validation that demonstrates high sensitivity and specificity. Demonstration of real-world applicability using wastewater samples. Valuable tool for rapid response to emerging infectious diseases.
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Affiliation(s)
| | - Andrea Gobbo
- Transversal activities in Applied Genomics, Sciensano, Brussels, Belgium
| | | | | | - Marie Lesenfants
- Epidemiology of infectious diseases, Sciensano, Brussels, Belgium
| | - Raphael Janssens
- Epidemiology of infectious diseases, Sciensano, Brussels, Belgium
| | - Veronik Hutse
- Epidemiology of infectious diseases, Sciensano, Brussels, Belgium
| | | | | | | | | | - Nancy Roosens
- Transversal activities in Applied Genomics, Sciensano, Brussels, Belgium
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24
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Dostálková A, Zdeňková K, Bartáčková J, Čermáková E, Kapisheva M, Lopez Marin MA, Kouba V, Sýkora P, Chmel M, Bartoš O, Dresler J, Demnerová K, Rumlová M, Bartáček J. Prevalence of SARS-CoV-2 variants in Prague wastewater determined by nanopore-based sequencing. CHEMOSPHERE 2024; 351:141162. [PMID: 38218235 DOI: 10.1016/j.chemosphere.2024.141162] [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: 06/30/2023] [Revised: 01/07/2024] [Accepted: 01/08/2024] [Indexed: 01/15/2024]
Abstract
The early detection of upcoming disease outbreaks is essential to avoid both health and economic damage. The last four years of COVID-19 pandemic have proven wastewater-based epidemiology is a reliable system for monitoring the spread of SARS-CoV-2, a causative agent of COVID-19, in an urban population. As this monitoring enables the identification of the prevalence of spreading variants of SARS-CoV-2, it could provide a critical tool in the fight against this viral disease. In this study, we evaluated the presence of variants and subvariants of SARS-CoV-2 in Prague wastewater using nanopore-based sequencing. During August 2021, the data clearly showed that the number of identified SARS-CoV-2 RNA copies increased in the wastewater earlier than in clinical samples indicating the upcoming wave of the Delta variant. New SARS-CoV-2 variants consistently prevailed in wastewater samples around a month after they already prevailed in clinical samples. We also analyzed wastewater samples from smaller sub-sewersheds of Prague and detected significant differences in SARS-CoV-2 lineage progression dynamics among individual localities studied, e.g., suggesting faster prevalence of new variants among the sites with highest population density and mobility.
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Affiliation(s)
- Alžběta Dostálková
- Department of Biotechnology, University of Chemistry and Technology Prague, Czech Republic; National Institute of Virology and Bacteriology, University of Chemistry and Technology Prague, Czech Republic
| | - Kamila Zdeňková
- Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague, Czech Republic.
| | - Jana Bartáčková
- Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague, Czech Republic
| | - Eliška Čermáková
- Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague, Czech Republic
| | - Marina Kapisheva
- National Institute of Virology and Bacteriology, University of Chemistry and Technology Prague, Czech Republic
| | - Marco A Lopez Marin
- Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague, Czech Republic
| | - Vojtěch Kouba
- Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague, Czech Republic
| | - Petr Sýkora
- PVK a.s., Prague Water Supply and Sewerage Company, Czech Republic
| | - Martin Chmel
- Department of Infectious Diseases, First Faculty of Medicine, Charles University and Military University Hospital Prague, Prague, Czech Republic; Military Health Institute, Military Medical Agency, Czech Republic
| | - Oldřich Bartoš
- Military Health Institute, Military Medical Agency, Czech Republic
| | - Jiří Dresler
- Military Health Institute, Military Medical Agency, Czech Republic
| | - Kateřina Demnerová
- Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague, Czech Republic
| | - Michaela Rumlová
- Department of Biotechnology, University of Chemistry and Technology Prague, Czech Republic; National Institute of Virology and Bacteriology, University of Chemistry and Technology Prague, Czech Republic
| | - Jan Bartáček
- Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague, Czech Republic
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Zhuang X, Moshi MA, Quinones O, Trenholm RA, Chang CL, Cordes D, Vanderford BJ, Vo V, Gerrity D, Oh EC. Spatial and Temporal Drug Usage Patterns in Wastewater Correlate with Socioeconomic and Demographic Indicators in Southern Nevada. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.02.24302241. [PMID: 38352613 PMCID: PMC10863018 DOI: 10.1101/2024.02.02.24302241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
Evaluating drug use within populations in the United States poses significant challenges due to various social, ethical, and legal constraints, often impeding the collection of accurate and timely data. Here, we aimed to overcome these barriers by conducting a comprehensive analysis of drug consumption trends and measuring their association with socioeconomic and demographic factors. From May 2022 to April 2023, we analyzed 208 wastewater samples from eight sampling locations across six wastewater treatment plants in Southern Nevada, covering a population of 2.4 million residents with 50 million annual tourists. Using bi-weekly influent wastewater samples, we employed mass spectrometry to detect 39 analytes, including pharmaceuticals and personal care products (PPCPs) and high risk substances (HRS). Our results revealed a significant increase over time in the level of stimulants such as cocaine (pFDR=1.40×10-10) and opioids, particularly norfentanyl (pFDR =1.66×10-12), while PPCPs exhibited seasonal variation such as peak usage of DEET, an active ingredient in insect repellents, during the summer (pFDR =0.05). Wastewater from socioeconomically disadvantaged or rural areas, as determined by Area Deprivation Index (ADI) and Rural-Urban Commuting Area Codes (RUCA) scores, demonstrated distinct overall usage patterns, such as higher usage/concentration of HRS, including cocaine (p=0.05) and norfentanyl (p=1.64×10-5). Our approach offers a near real-time, comprehensive tool to assess drug consumption and personal care product usage at a community level, linking wastewater patterns to socioeconomic and demographic factors. This approach has the potential to significantly enhance public health monitoring strategies in the United States.
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Affiliation(s)
- Xiaowei Zhuang
- Laboratory of Neurogenetics and Precision Medicine, College of Sciences, Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
- Neuroscience Interdisciplinary Ph.D. program, Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV
| | - Michael A. Moshi
- Laboratory of Neurogenetics and Precision Medicine, College of Sciences, Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
- Neuroscience Interdisciplinary Ph.D. program, Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
| | - Oscar Quinones
- Applied Research and Development Center, Southern Nevada Water Authority, P.O. Box 99954, Las Vegas NV, 89193, USA
| | - Rebecca A. Trenholm
- Applied Research and Development Center, Southern Nevada Water Authority, P.O. Box 99954, Las Vegas NV, 89193, USA
| | - Ching-Lan Chang
- Laboratory of Neurogenetics and Precision Medicine, College of Sciences, Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
- Neuroscience Interdisciplinary Ph.D. program, Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
| | - Dietmar Cordes
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV
| | - Brett J. Vanderford
- Applied Research and Development Center, Southern Nevada Water Authority, P.O. Box 99954, Las Vegas NV, 89193, USA
| | - Van Vo
- Laboratory of Neurogenetics and Precision Medicine, College of Sciences, Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
| | - Daniel Gerrity
- Applied Research and Development Center, Southern Nevada Water Authority, P.O. Box 99954, Las Vegas NV, 89193, USA
| | - Edwin C. Oh
- Laboratory of Neurogenetics and Precision Medicine, College of Sciences, Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
- Neuroscience Interdisciplinary Ph.D. program, Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
- Department of Brain Health, Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
- Department of Internal Medicine, Kirk Kerkorian School of Medicine at UNLV, University of Nevada Las Vegas, Las Vegas, NV 89154
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26
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El Soufi G, Di Jorio L, Gerber Z, Cluzel N, Van Assche J, Delafoy D, Olaso R, Daviaud C, Loustau T, Schwartz C, Trebouet D, Hernalsteens O, Marechal V, Raffestin S, Rousset D, Van Lint C, Deleuze JF, Boni M, Rohr O, Villain-Gambier M, Wallet C. Highly efficient and sensitive membrane-based concentration process allows quantification, surveillance, and sequencing of viruses in large volumes of wastewater. WATER RESEARCH 2024; 249:120959. [PMID: 38070350 DOI: 10.1016/j.watres.2023.120959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 01/03/2024]
Abstract
Wastewater-based epidemiology is experiencing exponential development. Despite undeniable advantages compared to patient-centered approaches (cost, anonymity, survey of large populations without bias, detection of asymptomatic infected peoples…), major technical limitations persist. Among them is the low sensitivity of the current methods used for quantifying and sequencing viral genomes from wastewater. In situations of low viral circulation, during initial stages of viral emergences, or in areas experiencing heavy rains, the extremely low concentrations of viruses in wastewater may fall below the limit of detection of the current methods. The availability during crisis and the cost of the commercial kits, as well as the requirement of expensive materials such as high-speed centrifuge, can also present major blocks to the development of wastewater-based epidemiological survey, specifically in low-income countries. Thereby, highly sensitive, low cost and standardized methods are still needed, to increase the predictability of the viral emergences, to survey low-circulating viruses and to make the results from different labs comparable. Here, we outline and characterize new protocols for concentrating and quantifying SARS-CoV-2 from large volumes (500 mL-1 L) of untreated wastewater. In addition, we report that the methods are applicable for monitoring and sequencing. Our nucleic acid extraction technique (the routine C: 5 mL method) does not require sophisticated equipment such as automatons and is not reliant on commercial kits, making it readily available to a broader range of laboratories for routine epidemiological survey. Furthermore, we demonstrate the efficiency, the repeatability, and the high sensitivity of a new membrane-based concentration method (MBC: 500 mL method) for enveloped (SARS-CoV-2) and non-enveloped (F-specific RNA phages of genogroup II / FRNAPH GGII) viruses. We show that the MBC method allows the quantification and the monitoring of viruses in wastewater with a significantly improved sensitivity compared to the routine C method. In contexts of low viral circulation, we report quantifications of SARS-CoV-2 in wastewater at concentrations as low as 40 genome copies per liter. In highly diluted samples collected in wastewater treatment plants of French Guiana, we confirmed the accuracy of the MBC method compared to the estimations done with the routine C method. Finally, we demonstrate that both the routine C method processing 5 mL and the MBC method processing 500 mL of untreated wastewater are both compatible with SARS-CoV-2 sequencing. We show that the quality of the sequence is correlated with the concentration of the extracted viral genome. Of note, the quality of the sequences obtained with some MBC processed wastewater was improved by dilutions or enzyme substitutions suggesting the presence of specific enzyme inhibitors in some wastewater. To the best of our knowledge, our MBC method is one of the first efficient, sensitive, and repeatable method characterized for SARS-CoV-2 quantification and sequencing from large volumes of wastewater.
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Affiliation(s)
- G El Soufi
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France; CNRS, IPHC, UMR 7178, Université de Strasbourg, Strasbourg F-67000, France
| | - L Di Jorio
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - Z Gerber
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - N Cluzel
- Maison des Modélisations Ingénieries et Technologies (SUMMIT), Sorbonne Université, Paris 75005, France
| | - J Van Assche
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - D Delafoy
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - R Olaso
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - C Daviaud
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - T Loustau
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - C Schwartz
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - D Trebouet
- CNRS, IPHC, UMR 7178, Université de Strasbourg, Strasbourg F-67000, France
| | - O Hernalsteens
- Department of Molecular Biology (DBM), Service of Molecular Virology, Université Libre de Bruxelles (ULB), Gosselies 6041, Belgium
| | - V Marechal
- INSERM, Centre de Recherche Saint-Antoine, Sorbonne Université, Paris 75012, France; OBEPINE Consortium, Paris, France
| | - S Raffestin
- Institut Pasteur de la Guyane, French Guiana, Cayenne 97300, France; OBEPINE Consortium, Paris, France
| | - D Rousset
- Institut Pasteur de la Guyane, French Guiana, Cayenne 97300, France; OBEPINE Consortium, Paris, France
| | - C Van Lint
- Department of Molecular Biology (DBM), Service of Molecular Virology, Université Libre de Bruxelles (ULB), Gosselies 6041, Belgium
| | - J F Deleuze
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - M Boni
- French Armed Forces Biomedical Research Institute, 91220 Brétigny-sur-Orge, France; OBEPINE Consortium, Paris, France
| | - O Rohr
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France; OBEPINE Consortium, Paris, France.
| | - M Villain-Gambier
- CNRS, IPHC, UMR 7178, Université de Strasbourg, Strasbourg F-67000, France
| | - C Wallet
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France; OBEPINE Consortium, Paris, France
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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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28
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Nadeau S, Devaux AJ, Bagutti C, Alt M, Ilg Hampe E, Kraus M, Würfel E, Koch KN, Fuchs S, Tschudin-Sutter S, Holschneider A, Ort C, Chen C, Huisman JS, Julian TR, Stadler T. Influenza transmission dynamics quantified from RNA in wastewater in Switzerland. Swiss Med Wkly 2024; 154:3503. [PMID: 38579316 DOI: 10.57187/s.3503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2024] Open
Abstract
INTRODUCTION Influenza infections are challenging to monitor at the population level due to many mild and asymptomatic cases and similar symptoms to other common circulating respiratory diseases, including COVID-19. Methods for tracking cases outside of typical reporting infrastructure could improve monitoring of influenza transmission dynamics. Influenza shedding into wastewater represents a promising source of information where quantification is unbiased by testing or treatment-seeking behaviours. METHODS We quantified influenza A and B virus loads from influent at Switzerland's three largest wastewater treatment plants, serving about 14% of the Swiss population (1.2 million individuals). We estimated trends in infection incidence and the effective reproductive number (Re) in these catchments during a 2021/22 epidemic and compared our estimates to typical influenza surveillance data. RESULTS Wastewater data captured the same overall trends in infection incidence as laboratory-confirmed case data at the catchment level. However, the wastewater data were more sensitive in capturing a transient peak in incidence in December 2021 than the case data. The Re estimated from the wastewater data was roughly at or below the epidemic threshold of 1 during work-from-home measures in December 2021 but increased to at or above the epidemic threshold in two of the three catchments after the relaxation of these measures. The third catchment yielded qualitatively the same results but with wider confidence intervals. The confirmed case data at the catchment level yielded comparatively less precise R_e estimates before and during the work-from-home period, with confidence intervals that included one before and during the work-from-home period. DISCUSSION Overall, we show that influenza RNA in wastewater can help monitor nationwide influenza transmission dynamics. Based on this research, we developed an online dashboard for ongoing wastewater-based influenza surveillance in Switzerland.
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Affiliation(s)
- Sarah Nadeau
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | | | - Monica Alt
- State Laboratory of Basel-Stadt, Basel, Switzerland
| | | | - Melanie Kraus
- Department of Health, Canton of Basel-Stadt, Basel, Switzerland
| | - Eva Würfel
- Department of Health, Canton of Basel-Stadt, Basel, Switzerland
| | - Katrin N Koch
- Cantonal Office of Public Health, Department of Economics and Health, Canton of Basel-Landschaft, Liestal, Switzerland
| | - Simon Fuchs
- Department of Health, Canton of Basel-Stadt, Basel, Switzerland
| | - Sarah Tschudin-Sutter
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel and University of Basel, Basel, Switzerland
| | | | - Christoph Ort
- Department of Environmental Microbiology, EAWAG, Dübendorf, Switzerland
| | - Chaoran Chen
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Jana S Huisman
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Timothy R Julian
- Department of Environmental Microbiology, EAWAG, Dübendorf, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
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Ansari N, Kabir F, Khan W, Khalid F, Malik AA, Warren JL, Mehmood U, Kazi AM, Yildirim I, Tanner W, Kalimuddin H, Kanwar S, Aziz F, Memon A, Alam MM, Ikram A, Meschke JS, Jehan F, Omer SB, Nisar MI. Environmental surveillance for COVID-19 using SARS-CoV-2 RNA concentration in wastewater - a study in District East, Karachi, Pakistan. THE LANCET REGIONAL HEALTH. SOUTHEAST ASIA 2024; 20:100299. [PMID: 38234701 PMCID: PMC10794106 DOI: 10.1016/j.lansea.2023.100299] [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: 12/15/2022] [Revised: 04/18/2023] [Accepted: 09/28/2023] [Indexed: 01/19/2024]
Abstract
Background Wastewater-based surveillance is used to track the temporal patterns of the SARS-CoV-2 virus in communities. Viral RNA particle detection in wastewater samples can indicate an outbreak within a catchment area. We describe the feasibility of using a sewage network to monitor SARS-CoV-2 trend and use of genomic sequencing to describe the viral variant abundance in an urban district in Karachi, Pakistan. This was among the first studies from Pakistan to demonstrate the surveillance for SARS-CoV-2 from a semi-formal sewage system. Methods Four sites draining into the Lyari River in District East, Karachi, were identified and included in the current study. Raw sewage samples were collected early morning twice weekly from each site between June 10, 2021 and January 17, 2022, using Bag Mediated Filtration System (BMFS). Secondary concentration of filtered samples was achieved by ultracentrifugation and skim milk flocculation. SARS-CoV-2 RNA concentrations in the samples were estimated using PCR (Qiagen ProMega kits for N1 & N2 genes). A distributed-lag negative binomial regression model within a hierarchical Bayesian framework was used to describe the relationship between wastewater RNA concentration and COVID-19 cases from the catchment area. Genomic sequencing was performed using Illumina iSeq100. Findings Among the 151 raw sewage samples included in the study, 123 samples (81.5%) tested positive for N1 or N2 genes. The average SARS-CoV-2 RNA concentrations in the sewage samples at each lag (1-14 days prior) were associated with the cases reported for the respective days, with a peak association observed on lag day 10 (RR: 1.15; 95% Credible Interval: 1.10-1.21). Genomic sequencing showed that the delta variant dominated till September 2022, while the omicron variant was identified in November 2022. Interpretation Wastewater-based surveillance, together with genomic sequencing provides valuable information for monitoring the community temporal trend of SARS-CoV-2. Funding PATH, Bill & Melinda Gates Foundation, and Global Innovation Fund.
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Affiliation(s)
- Nadia Ansari
- Faculty of Health Sciences, Department of Paediatrics and Child Health, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
| | - Furqan Kabir
- Faculty of Health Sciences, Department of Paediatrics and Child Health, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
| | - Waqasuddin Khan
- CITRIC Centre for Bioinformatics and Computational Biology, Department of Paediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
| | - Farah Khalid
- Faculty of Health Sciences, Department of Paediatrics and Child Health, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
| | - Amyn Abdul Malik
- Yale Institute for Global Health, Yale University, New Haven, CT, USA
- Section of Infectious Diseases and Global Health, Department of Paediatrics, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Joshua L. Warren
- Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Usma Mehmood
- Faculty of Health Sciences, Department of Paediatrics and Child Health, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
| | - Abdul Momin Kazi
- Faculty of Health Sciences, Department of Paediatrics and Child Health, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
| | - Inci Yildirim
- Yale Institute for Global Health, Yale University, New Haven, CT, USA
- Section of Infectious Diseases and Global Health, Department of Paediatrics, Yale School of Medicine, Yale University, New Haven, CT, USA
- Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Windy Tanner
- Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Hussain Kalimuddin
- Faculty of Health Sciences, Department of Paediatrics and Child Health, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
| | - Samiah Kanwar
- Faculty of Health Sciences, Department of Paediatrics and Child Health, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
- CITRIC Centre for Bioinformatics and Computational Biology, Department of Paediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
| | - Fatima Aziz
- Faculty of Health Sciences, Department of Paediatrics and Child Health, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
| | - Arslan Memon
- District Health Office (East), Karachi, Pakistan
| | | | - Aamer Ikram
- National Institutes of Health, Chak Shahzad, Islamabad, Pakistan
| | | | - Fyezah Jehan
- Faculty of Health Sciences, Department of Paediatrics and Child Health, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
- CITRIC Centre for Bioinformatics and Computational Biology, Department of Paediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
| | - Saad B. Omer
- Yale Institute for Global Health, Yale University, New Haven, CT, USA
- Section of Infectious Diseases and Global Health, Department of Paediatrics, Yale School of Medicine, Yale University, New Haven, CT, USA
- Yale School of Public Health, Yale University, New Haven, CT, USA
- Yale School of Nursing, Orange, CT, USA
| | - Muhammad Imran Nisar
- Faculty of Health Sciences, Department of Paediatrics and Child Health, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
- CITRIC Centre for Bioinformatics and Computational Biology, Department of Paediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Stadium Road, Karachi 74800, Pakistan
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Gitter A, Bauer C, Wu F, Ramphul R, Chavarria C, Zhang K, Petrosino J, Mezzari M, Gallegos G, Terwilliger AL, Clark JR, Feliz K, Avadhanula V, Piedra T, Weesner K, Maresso A, Mena KD. Assessment of a SARS-CoV-2 wastewater monitoring program in El Paso, Texas, from November 2020 to June 2022. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024; 34:564-574. [PMID: 36595614 DOI: 10.1080/09603123.2022.2159017] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
The border city of El Paso, Texas, and its water utility, El Paso Water, initiated a SARS-CoV-2 wastewater monitoring program to assess virus trends and the appropriateness of a wastewater monitoring program for the community. Nearly weekly sample collection at four wastewater treatment facilities (WWTFs), serving distinct regions of the city, was analyzed for SARS-CoV-2 genes using the CDC 2019-Novel coronavirus Real-Time RT-PCR diagnostic panel. Virus concentrations ranged from 86.7 to 268,000 gc/L, varying across time and at each WWTF. The lag time between virus concentrations in wastewater and reported COVID-19 case rates (per 100,00 population) ranged from 4-24 days for the four WWTFs, with the strongest trend occurring from November 2021 - June 2022. This study is an assessment of the utility of a geographically refined SARS-CoV-2 wastewater monitoring program to supplement public health efforts that will manage the virus as it becomes endemic in El Paso.
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Affiliation(s)
- Anna Gitter
- Department of Epidemiology, Human Genetics & Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Cici Bauer
- Department of Biostatistics and Data Science, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Fuqing Wu
- Department of Epidemiology, Human Genetics & Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Ryan Ramphul
- Department of Epidemiology, Human Genetics & Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Carlos Chavarria
- Department of Epidemiology, Human Genetics & Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Kehe Zhang
- Department of Biostatistics and Data Science, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | | | | | - Gabriela Gallegos
- Department of Management, Policy & Community Health, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | | | | | - Karen Feliz
- Baylor College of Medicine, Houston, TX, USA
| | | | - Tony Piedra
- Baylor College of Medicine, Houston, TX, USA
| | | | | | - Kristina D Mena
- Department of Epidemiology, Human Genetics & Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
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31
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Xu X, Deng Y, Ding J, Shi X, Zheng X, Wang D, Yang Y, Liu L, Wang C, Li S, Gu H, Poon LLM, Zhang T. Refining detection methods for emerging SARS-CoV-2 mutants in wastewater: A case study on the Omicron variants. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166215. [PMID: 37591380 DOI: 10.1016/j.scitotenv.2023.166215] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 08/19/2023]
Abstract
COVID-19 is an ongoing public health threat worldwide driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Wastewater surveillance has emerged as a complementary tool to clinical surveillance to control the COVID-19 pandemic. With the emergence of new variants of SARS-CoV-2, accumulated mutations that occurred in the SARS-CoV-2 genome raise new challenges for RT-qPCR diagnosis used in wastewater surveillance. There is a pressing need to develop refined methods for modifying primer/probes to better detect these emerging variants in wastewater. Here, we exemplified this process by focusing on the Omicron variants, for which we have developed and validated a modified detection method. We first modified the primers/probe mismatches of three assays commonly used in wastewater surveillance according to in silico analysis results for the mutations of 882 sequences collected during the fifth-wave outbreak in Hong Kong, and then evaluated them alongside the seven original assays. The results showed that five of seven original assays had better sensitivity for detecting Omicron variants, with the limits of detection (LoDs) ranging from 1.53 to 2.76 copies/μL. UCDC-N1 and Charité-E sets had poor performances, having LoDs higher than 10 copies/μL and false-positive/false-negative results in wastewater testing, probably due to the mismatch and demonstrating the need for modification of primer/probe sequences. The modified assays exhibited higher sensitivity and specificity, along with better reproducibility in detecting 81 wastewater samples. In addition, the sequencing results of six wastewater samples by Illumina also validated the presence of mismatches in the primer/probe binding sites of the three assays. This study highlights the importance of re-configuration of the primer-probe sets and refinements for the sequences to ensure the diagnostic effectiveness of RT-qPCR detection.
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Affiliation(s)
- Xiaoqing Xu
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Yu Deng
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Jiahui Ding
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Xianghui Shi
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Xiawan Zheng
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Dou Wang
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Yu Yang
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Lei Liu
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Chunxiao Wang
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Shuxian Li
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Haogao Gu
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Sassoon Road, Hong Kong, China
| | - Leo L M Poon
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Sassoon Road, Hong Kong, China; HKU-Pasteur Research Pole, The University of Hong Kong, Sassoon Road, Hong Kong, China
| | - Tong Zhang
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China.
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Garcia-Pedemonte D, Carcereny A, Gregori J, Quer J, Garcia-Cehic D, Guerrero L, Ceretó-Massagué A, Abid I, Bosch A, Costafreda MI, Pintó RM, Guix S. Comparison of Nanopore and Synthesis-Based Next-Generation Sequencing Platforms for SARS-CoV-2 Variant Monitoring in Wastewater. Int J Mol Sci 2023; 24:17184. [PMID: 38139015 PMCID: PMC10743471 DOI: 10.3390/ijms242417184] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 11/30/2023] [Accepted: 12/04/2023] [Indexed: 12/24/2023] Open
Abstract
Shortly after the beginning of the SARS-CoV-2 pandemic, many countries implemented sewage sentinel systems to monitor the circulation of the virus in the population. A fundamental part of these surveillance programs is the variant tracking through sequencing approaches to monitor and identify new variants or mutations that may be of importance. Two of the main sequencing platforms are Illumina and Oxford Nanopore Technologies. Here, we compare the performance of MiSeq (Illumina) and MinION (Oxford Nanopore Technologies), as well as two different data processing pipelines, to determine the effect they may have on the results. MiSeq showed higher sequencing coverage, lower error rate, and better capacity to detect and accurately estimate variant abundances than MinION R9.4.1 flow cell data. The use of different variant callers (LoFreq and iVar) and approaches to calculate the variant proportions had a remarkable impact on the results generated from wastewater samples. Freyja, coupled with iVar, may be more sensitive and accurate than LoFreq, especially with MinION data, but it comes at the cost of having a higher error rate. The analysis of MinION R10.4.1 flow cell data using Freyja combined with iVar narrows the gap with MiSeq performance in terms of read quality, accuracy, sensitivity, and number of detected mutations. Although MiSeq should still be considered as the standard method for SARS-CoV-2 variant tracking, MinION's versatility and rapid turnaround time may represent a clear advantage during the ongoing pandemic.
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Affiliation(s)
- David Garcia-Pedemonte
- Enteric Virus Laboratory, Section of Microbiology, Virology and Biotechnology, Department of Genetics, Microbiology and Statistics, School of Biology, University of Barcelona, 08028 Barcelona, Spain; (D.G.-P.); (A.C.); (I.A.); (A.B.); (M.I.C.)
- Enteric Virus Laboratory, Institute of Nutrition and Food Safety (INSA), University of Barcelona, 08921 Santa Coloma de Gramenet, Spain
| | - Albert Carcereny
- Enteric Virus Laboratory, Section of Microbiology, Virology and Biotechnology, Department of Genetics, Microbiology and Statistics, School of Biology, University of Barcelona, 08028 Barcelona, Spain; (D.G.-P.); (A.C.); (I.A.); (A.B.); (M.I.C.)
- Enteric Virus Laboratory, Institute of Nutrition and Food Safety (INSA), University of Barcelona, 08921 Santa Coloma de Gramenet, Spain
| | - Josep Gregori
- Liver Unit, Liver Diseases—Viral Hepatitis, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Campus, 08035 Barcelona, Spain; (J.G.); (J.Q.); (D.G.-C.)
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Josep Quer
- Liver Unit, Liver Diseases—Viral Hepatitis, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Campus, 08035 Barcelona, Spain; (J.G.); (J.Q.); (D.G.-C.)
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Damir Garcia-Cehic
- Liver Unit, Liver Diseases—Viral Hepatitis, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Hospital Campus, 08035 Barcelona, Spain; (J.G.); (J.Q.); (D.G.-C.)
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Laura Guerrero
- Catalan Institute for Water Research (ICRA), 17003 Girona, Spain;
| | - Adrià Ceretó-Massagué
- Centre for Omic Sciences (COS), Joint Unit Universitat Rovira i Virgili-EURECAT, Unique Scientific and Technical Infrastructures (ICTS), 43204 Reus, Spain;
| | - Islem Abid
- Enteric Virus Laboratory, Section of Microbiology, Virology and Biotechnology, Department of Genetics, Microbiology and Statistics, School of Biology, University of Barcelona, 08028 Barcelona, Spain; (D.G.-P.); (A.C.); (I.A.); (A.B.); (M.I.C.)
- Center of Excellence in Biotechnology Research, College of Applied Science, King Saud University, Riyadh 11495, Saudi Arabia
| | - Albert Bosch
- Enteric Virus Laboratory, Section of Microbiology, Virology and Biotechnology, Department of Genetics, Microbiology and Statistics, School of Biology, University of Barcelona, 08028 Barcelona, Spain; (D.G.-P.); (A.C.); (I.A.); (A.B.); (M.I.C.)
- Enteric Virus Laboratory, Institute of Nutrition and Food Safety (INSA), University of Barcelona, 08921 Santa Coloma de Gramenet, Spain
| | - Maria Isabel Costafreda
- Enteric Virus Laboratory, Section of Microbiology, Virology and Biotechnology, Department of Genetics, Microbiology and Statistics, School of Biology, University of Barcelona, 08028 Barcelona, Spain; (D.G.-P.); (A.C.); (I.A.); (A.B.); (M.I.C.)
- Enteric Virus Laboratory, Institute of Nutrition and Food Safety (INSA), University of Barcelona, 08921 Santa Coloma de Gramenet, Spain
| | - Rosa M. Pintó
- Enteric Virus Laboratory, Section of Microbiology, Virology and Biotechnology, Department of Genetics, Microbiology and Statistics, School of Biology, University of Barcelona, 08028 Barcelona, Spain; (D.G.-P.); (A.C.); (I.A.); (A.B.); (M.I.C.)
- Enteric Virus Laboratory, Institute of Nutrition and Food Safety (INSA), University of Barcelona, 08921 Santa Coloma de Gramenet, Spain
| | - Susana Guix
- Enteric Virus Laboratory, Section of Microbiology, Virology and Biotechnology, Department of Genetics, Microbiology and Statistics, School of Biology, University of Barcelona, 08028 Barcelona, Spain; (D.G.-P.); (A.C.); (I.A.); (A.B.); (M.I.C.)
- Enteric Virus Laboratory, Institute of Nutrition and Food Safety (INSA), University of Barcelona, 08921 Santa Coloma de Gramenet, Spain
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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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34
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Farkas K, Pântea I, Woodhall N, Williams D, Lambert-Slosarska K, Williams RC, Grimsley JMS, Singer AC, Jones DL. Diurnal changes in pathogenic and indicator virus concentrations in wastewater. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:123785-123795. [PMID: 37989946 PMCID: PMC10746776 DOI: 10.1007/s11356-023-30381-3] [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: 03/28/2023] [Accepted: 10/06/2023] [Indexed: 11/23/2023]
Abstract
Wastewater-based epidemiology (WBE) has been commonly used for monitoring SARS-CoV-2 outbreaks. As sampling times and methods (i.e. grab vs composite) may vary, diurnal changes of viral concentrations in sewage should be better understood. In this study, we collected untreated wastewater samples hourly for 4 days at two wastewater treatment plants in Wales to establish diurnal patterns in virus concentrations and the physico-chemical properties of the water. Simultaneously, we also trialled three absorbent materials as passive samples as a simple and cost-efficient alternative for the collection of composite samples. Ninety-six percent of all liquid samples (n = 74) and 88% of the passive samplers (n = 59) were positive for SARS-CoV-2, whereas 87% and 97% of the liquid and passive samples were positive for the faecal indicator virus crAssphage, respectively. We found no significant daily variations in the concentration of the target viruses, ammonium and orthophosphate, and the pH and electrical conductivity levels were also stable. Weak positive correlations were found between some physico-chemical properties and viral concentrations. More variation was observed in samples taken from the influent stream as opposed to those taken from the influent tank. Of the absorbent materials trialled as passive samples, we found that tampons provided higher viral recoveries than electronegative filter paper and cotton gauze swabs. For all materials tested, viral recovery was dependent on the virus type. Our results indicate that grab samples may provide representative alternatives to 24-h composite samples if taken from the influent tank, hence reducing the costs of sampling for WBE programmes. Tampons are also viable alternatives for cost-efficient sampling; however, viral recovery should be optimised prior to use.
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Affiliation(s)
- Kata Farkas
- School of Environmental Natural Sciences, Bangor University, Bangor, LL57 2UW, Gwynedd, UK.
| | - Igor Pântea
- School of Environmental Natural Sciences, Bangor University, Bangor, LL57 2UW, Gwynedd, UK
| | - Nick Woodhall
- School of Environmental Natural Sciences, Bangor University, Bangor, LL57 2UW, Gwynedd, UK
| | - Denis Williams
- School of Environmental Natural Sciences, Bangor University, Bangor, LL57 2UW, Gwynedd, UK
| | | | - Rachel C Williams
- School of Environmental Natural Sciences, Bangor University, Bangor, LL57 2UW, Gwynedd, UK
| | - Jasmine M S Grimsley
- Data Analytics & Surveillance Division, UK Health Security Agency, 10 South Colonnade, Canary Wharf, London, E14 4PU, UK
- The London Data Company, London, EC2N 2AT, UK
| | - Andrew C Singer
- UK Centre for Ecology & Hydrology, Wallingford, OX10 8BB, UK
| | - Davey L Jones
- School of Environmental Natural Sciences, Bangor University, Bangor, LL57 2UW, Gwynedd, UK
- Food Futures Institute, Murdoch University, Murdoch, WA, 6150, Australia
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35
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Wong YHM, Lim JT, Griffiths J, Lee B, Maliki D, Thompson J, Wong M, Chae SR, Teoh YL, Ho ZJM, Lee V, Cook AR, Tay M, Wong JCC, Ng LC. Positive association of SARS-CoV-2 RNA concentrations in wastewater and reported COVID-19 cases in Singapore - A study across three populations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 902:166446. [PMID: 37604378 DOI: 10.1016/j.scitotenv.2023.166446] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/15/2023] [Accepted: 08/18/2023] [Indexed: 08/23/2023]
Abstract
Wastewater testing of SARS-CoV-2 has been adopted globally and has shown to be a useful, non-intrusive surveillance method for monitoring COVID-19 trends. In Singapore, wastewater surveillance has been widely implemented across various sites and has facilitated timely COVID-19 management and response. From April 2020 to February 2022, SARS-CoV-2 RNA concentrations in wastewater monitored across three populations, nationally, in the community, and in High Density Living Environments (HDLEs) were aggregated into indices and compared with reported COVID-19 cases and hospitalisations. Temporal trends and associations of these indices were compared descriptively and quantitatively, using Poisson Generalised Linear Models and Generalised Additive Models. National vaccination rates and vaccine breakthrough infection rates were additionally considered as confounders to shedding. Fitted models quantified the temporal associations between the indices and cases and COVID-related hospitalisations. At the national level, the wastewater index was a leading indicator of COVID-19 cases (p-value <0.001) of one week, and a contemporaneous association with hospitalisations (p-value <0.001) was observed. At finer levels of surveillance, the community index was observed to be contemporaneously associated with COVID-19 cases (p-value <0.001) and had a lagging association of 1-week in HDLEs (p-value <0.001). These temporal differences were attributed to differences in testing routines for different sites during the study period and the timeline of COVID-19 progression in infected persons. Overall, this study demonstrates the utility of wastewater surveillance in understanding underlying COVID-19 transmission and shedding levels, particularly for areas with falling or low case ascertainment. In such settings, wastewater surveillance showed to be a lead indicator of COVID-19 cases. The findings also underscore the potential of wastewater surveillance for monitoring other infectious diseases threats.
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Affiliation(s)
| | - Jue Tao Lim
- Environmental Health Institute, National Environment Agency, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Jane Griffiths
- Environmental Health Institute, National Environment Agency, Singapore
| | - Benjamin Lee
- Environmental Health Institute, National Environment Agency, Singapore
| | | | - Janelle Thompson
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Asian School of the Environment, Nanyang Technological University, Singapore
| | - Michelle Wong
- Saw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore
| | - Sae-Rom Chae
- Ministry of Health, Singapore; National Centre for Infectious Diseases, Singapore
| | - Yee Leong Teoh
- Ministry of Health, Singapore; National Centre for Infectious Diseases, Singapore
| | | | | | - Alex R Cook
- Saw Swee Hock School of Public Health, National University of Singapore, 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
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36
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Acosta N, Dai X, Bautista MA, Waddell BJ, Lee J, Du K, McCalder J, Pradhan P, Papparis C, Lu X, Chekouo T, Krusina A, Southern D, Williamson T, Clark RG, Patterson RA, Westlund P, Meddings J, Ruecker N, Lammiman C, Duerr C, Achari G, Hrudey SE, Lee BE, Pang X, Frankowski K, Hubert CRJ, Parkins MD. Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 900:165172. [PMID: 37379934 PMCID: PMC10292917 DOI: 10.1016/j.scitotenv.2023.165172] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 06/21/2023] [Accepted: 06/25/2023] [Indexed: 06/30/2023]
Abstract
Wastewater-based surveillance (WBS) of infectious diseases is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19's impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.4 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5 % (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4524 unrelated absences COVID-19 cases were recorded. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P < 0.0001). The Poisson regression with wastewater as a one-week leading signal has an Akaike information criterion (AIC) of 858, compared to a null model (excluding wastewater predictor) with an AIC of 1895. The likelihood-ratio test comparing the model with wastewater signal with the null model shows statistical significance (P < 0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.
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Affiliation(s)
- Nicole Acosta
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Xiaotian Dai
- Department of Mathematics and Statistics, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Maria A Bautista
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Barbara J Waddell
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Jangwoo Lee
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Kristine Du
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Janine McCalder
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Puja Pradhan
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Chloe Papparis
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Xuewen Lu
- Department of Mathematics and Statistics, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Thierry Chekouo
- Department of Mathematics and Statistics, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada; Division of Biostatistics, School of Public Health, University of Minnesota, 420 Delaware St. S.E., Minneapolis, MN 55455, USA
| | - Alexander Krusina
- Department of Community Health Sciences, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Medicine, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Danielle Southern
- Department of Community Health Sciences, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Medicine, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Tyler Williamson
- Department of Community Health Sciences, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Medicine, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; O'Brien Institute for Public Health, University of Calgary, 3280 Hospital Dr NW, Calgary, Alberta T2N 4Z6, Canada
| | - Rhonda G Clark
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Raymond A Patterson
- Haskayne School of Business, University of Calgary, SH 250, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | | | - Jon Meddings
- Department of Medicine, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada
| | - Norma Ruecker
- Water Services, City of Calgary, 625 25 Ave SE, Calgary, Alberta T2G 4k8, Canada
| | - Christopher Lammiman
- Calgary Emergency Management Agency (CEMA), City of Calgary, 673 1 St NE, Calgary, Alberta T2E 6R2, Canada
| | - Coby Duerr
- Calgary Emergency Management Agency (CEMA), City of Calgary, 673 1 St NE, Calgary, Alberta T2E 6R2, Canada
| | - Gopal Achari
- Department of Civil Engineering, University of Calgary, 622 Collegiate Pl NW, T2N 4V8, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada; Analytical and Environmental Toxicology, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada
| | - Bonita E Lee
- Department of Pediatrics, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada; Women & Children's Health Research Institute, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada; Li Ka Shing Institute of Virology, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada; Li Ka Shing Institute of Virology, University of Alberta, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada; Alberta Precision Laboratories, Public Health Laboratory, Alberta Health Services, 116 St. and 85 Ave, Edmonton, Alberta T6G 2R3, Canada
| | - Kevin Frankowski
- Advancing Canadian Water Assets, University of Calgary, 3131 210 Ave SE, Calgary, Alberta T0L 0X0, Canada
| | - Casey R J Hubert
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Michael D Parkins
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Department of Medicine, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada; Snyder Institute for Chronic Diseases, University of Calgary and Alberta Health Services, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada.
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Schmiege D, Kraiselburd I, Haselhoff T, Thomas A, Doerr A, Gosch J, Schoth J, Teichgräber B, Moebus S, Meyer F. Analyzing community wastewater in sub-sewersheds for the small-scale detection of SARS-CoV-2 variants in a German metropolitan area. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 898:165458. [PMID: 37454854 DOI: 10.1016/j.scitotenv.2023.165458] [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: 04/06/2023] [Revised: 06/09/2023] [Accepted: 07/08/2023] [Indexed: 07/18/2023]
Abstract
Wastewater surveillance of SARS-CoV-2 proved useful, including for identifying the local appearance of newly identified virus variants. Previous studies focused on wastewater treatment plants (WWTP) with sewersheds of several hundred thousand people or at single building level, representing only a small number of people. Both approaches may prove inadequate for small-scale intra-urban inferences for early detection of emerging or novel virus variants. Our study aims (i) to analyze SARS-CoV-2 single nucleotide variants (SNVs) in wastewater of sub-sewersheds and WWTP using whole genome sequencing in order to (ii) investigate the potential of small-scale detection of novel known SARS-CoV-2 variants of concern (VOC) within a metropolitan wastewater system. We selected three sub-sewershed sampling sites, based on estimated population- and built environment-related indicators, and the inlet of the receiving WWTP in the Ruhr region, Germany. Untreated wastewater was sampled weekly between October and December 2021, with a total of 22 samples collected. SARS-CoV-2 RNA was analyzed by RT-qPCR and whole genome sequencing. For all samples, genome sequences were obtained, while only 13 samples were positive for RT-qPCR. We identified multiple specific SARS-CoV-2 SNVs in the wastewater samples of the sub-sewersheds and the WWTP. Identified SNVs reflected the dominance of VOC Delta at the time of sampling. Interestingly, we could identify an Omicron-specific SNV in one sub-sewershed. A concurrent wastewater study sampling the same WWTP detected the VOC Omicron one week later. Our observations suggest that the small-scale approach may prove particularly useful for the detection and description of spatially confined emerging or existing virus variants circulating in populations. Future studies applying small-scale sampling strategies taking into account the specific features of the wastewater system will be useful to analyze temporal and spatial variance in more detail.
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Affiliation(s)
- Dennis Schmiege
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130 Essen, Germany.
| | - Ivana Kraiselburd
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131 Essen, Germany
| | - Timo Haselhoff
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130 Essen, Germany
| | - Alexander Thomas
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131 Essen, Germany
| | - Adrian Doerr
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131 Essen, Germany
| | - Jule Gosch
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131 Essen, Germany
| | - Jens Schoth
- Emschergenossenschaft/Lippeverband, Kronprinzenstraße 24, 45128 Essen, Germany
| | | | - Susanne Moebus
- Institute for Urban Public Health (InUPH), University Hospital Essen, University of Duisburg-Essen, 45130 Essen, Germany
| | - Folker Meyer
- Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, 45131 Essen, Germany
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Bohrerova Z, Brinkman NE, Chakravarti R, Chattopadhyay S, Faith SA, Garland J, Herrin J, Hull N, Jahne M, Kang DW, Keely SP, Lee J, Lemeshow S, Lenhart J, Lytmer E, Malgave D, Miao L, Minard-Smith A, Mou X, Nagarkar M, Quintero A, Savona FDR, Senko J, Slonczewski JL, Spurbeck RR, Sovic MG, Taylor RT, Weavers LK, Weir M. Ohio Coronavirus Wastewater Monitoring Network: Implementation of Statewide Monitoring for Protecting Public Health. JOURNAL OF PUBLIC HEALTH MANAGEMENT AND PRACTICE 2023; 29:845-853. [PMID: 37738597 PMCID: PMC10539008 DOI: 10.1097/phh.0000000000001783] [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: 09/24/2023]
Abstract
CONTEXT Prior to the COVID-19 pandemic, wastewater influent monitoring for tracking disease burden in sewered communities was not performed in Ohio, and this field was only on the periphery of the state academic research community. PROGRAM Because of the urgency of the pandemic and extensive state-level support for this new technology to detect levels of community infection to aid in public health response, the Ohio Water Resources Center established relationships and support of various stakeholders. This enabled Ohio to develop a statewide wastewater SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) monitoring network in 2 months starting in July 2020. IMPLEMENTATION The current Ohio Coronavirus Wastewater Monitoring Network (OCWMN) monitors more than 70 unique locations twice per week, and publicly available data are updated weekly on the public dashboard. EVALUATION This article describes the process and decisions that were made during network initiation, the network progression, and data applications, which can inform ongoing and future pandemic response and wastewater monitoring. DISCUSSION Overall, the OCWMN established wastewater monitoring infrastructure and provided a useful tool for public health professionals responding to the pandemic.
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Affiliation(s)
- Zuzana Bohrerova
- Ohio Water Resources Center (Drs Bohrerova, Lenhart, and Weavers), Civil, Environmental and Geodetic Engineering (Drs Bohrerova, Hull, Lenhart, and Weavers), Infectious Diseases Institute (Drs Faith and Lee and Ms Savona), Sustainability Institute (Dr Hull), Department of Food Science & Technology (Dr Lee), and Center for Applied Plant Sciences (Dr Sovic), The Ohio State University, Columbus, Ohio; Office of Research and Development, US Environmental Protection Agency, Washington, District of Columbia (Drs Brinkman, Garland, Jahne, Keely, and Nagarkar); Departments of Physiology and Pharmacology (Dr Chakravarti) and Medical Microbiology and Immunology (Drs Chattopadhyay and Taylor), University of Toledo College of Medicine and Life Sciences, Toledo, Ohio; LuminUltra Technologies Inc, Hialeah, Florida (Mr Herrin and Dr Quintero); Department of Civil and Environmental Engineering, University of Toledo, Toledo, Ohio (Dr Kang); Divisions of Environmental Health Sciences (Drs Lee and Weir) and Biostatistics (Drs Lemeshow and Malgave and Ms Miao), The Ohio State University College of Public Health, Columbus, Ohio; Department of Biological Sciences, Bowling Green State University, Bowling Green, Ohio (Ms Lytmer); Health Outcomes and Biotechnology Solutions, Battelle Memorial Institute, Columbus, Ohio (Ms Minard-Smith and Dr Spurbeck); Department of Biological Sciences, Kent State University, Kent, Ohio (Dr Mou); Department of Geosciences and Department of Biology, The University of Akron, Akron, Ohio (Dr Senko); and Department of Biology, Kenyon College, Gambier, Ohio (Dr Slonczewski)
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Hopkins L, Ensor KB, Stadler L, Johnson CD, Schneider R, Domakonda K, McCarthy JJ, Septimus EJ, Persse D, Williams SL. Public Health Interventions Guided by Houston's Wastewater Surveillance Program During the COVID-19 Pandemic. Public Health Rep 2023; 138:856-861. [PMID: 37503606 PMCID: PMC10576486 DOI: 10.1177/00333549231185625] [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: 07/29/2023] Open
Abstract
Since the start of the COVID-19 pandemic, wastewater surveillance has emerged as a powerful tool used by public health authorities to track SARS-CoV-2 infections in communities. In May 2020, the Houston Health Department began working with a coalition of municipal and academic partners to develop a wastewater monitoring and reporting system for the city of Houston, Texas. Data collected from the system are integrated with other COVID-19 surveillance data and communicated through different channels to local authorities and the general public. This information is used to shape policies and inform actions to mitigate and prevent the spread of COVID-19 at municipal, institutional, and individual levels. Based on the success of this monitoring and reporting system to drive public health protection efforts, the wastewater surveillance program is likely to become a standard part of the public health toolkit for responding to infectious diseases and, potentially, other disease-causing outbreaks.
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Affiliation(s)
- Loren Hopkins
- Community and Children’s Environmental Health, Houston Health Department, City of Houston, Houston, TX, USA
- Department of Statistics, Rice University, Houston, TX, USA
| | | | - Lauren Stadler
- Department of Civil and Environmental Engineering, Rice University, Houston, TX, USA
| | - Catherine D. Johnson
- Houston Health Foundation, Houston, TX, USA
- Texas Children’s Hospital, Houston, TX, USA
| | | | - Kaavya Domakonda
- Wastewater Surveillance, Houston Health Department, City of Houston, Houston, TX, USA
| | | | | | - David Persse
- City of Houston Emergency Medical Services, Houston, TX, USA
- Baylor College of Medicine, Houston, TX, USA
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Thapar I, Langan LM, Davis H, Norman RS, Bojes HK, Brooks BW. Influence of storage conditions and multiple freeze-thaw cycles on N1 SARS-CoV-2, PMMoV, and BCoV signal. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 896:165098. [PMID: 37392884 PMCID: PMC10307669 DOI: 10.1016/j.scitotenv.2023.165098] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 06/16/2023] [Accepted: 06/21/2023] [Indexed: 07/03/2023]
Abstract
Wastewater-based epidemiology/wastewater-based surveillance (WBE/WBS) continues to serve as an effective means of monitoring various diseases, including COVID-19 and the emergence of SARS-CoV-2 variants, at the population level. As the use of WBE expands, storage conditions of wastewater samples will play a critical role in ensuring the accuracy and reproducibility of results. In this study, the impacts of water concentration buffer (WCB), storage temperature, and freeze-thaw cycles on the detection of SARS-CoV-2 and other WBE-related gene targets were examined. Freeze-thawing of concentrated samples did not significantly affect (p > 0.05) crossing/cycle threshold (Ct) value for any of the gene targets studied (SARS-CoV-2 N1, PMMoV, and BCoV). However, use of WCB during concentration resulted in a significant (p < 0.05) decrease in Ct for all targets, and storage at -80 °C (in contrast to -20 °C) appeared preferable for wastewater storage signal stability based on decreased Ct values, although this was only significantly different (p < 0.05) for the BCoV target. Interestingly, when Ct values were converted to gene copies per influent sample, no significant differences (p > 0.05) were observed in any of the targets examined. Stability of RNA targets in concentrated wastewater against freeze-thaw degradation supports archiving of concentrated samples for use in retrospective examination of COVID-19 trends and tracing SARS-CoV-2 variants and potentially other viruses, and provides a starting point for establishing a consistent procedure for specimen collection and storage for the WBE/WBS community.
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Affiliation(s)
- Isha Thapar
- Department of Environmental Science, Baylor University, One Bear Place #97266, Waco, TX 76798, USA
| | - Laura M Langan
- Department of Environmental Science, Baylor University, One Bear Place #97266, Waco, TX 76798, USA; Center for Reservoir and Aquatic Systems Research, Baylor University, One Bear Place #97178, Waco, TX 76798, USA.
| | - Haley Davis
- Department of Environmental Science, Baylor University, One Bear Place #97266, Waco, TX 76798, USA; Harbor Branch Oceanographic Institute, Florida Atlantic University, 5600 US-1, Fort Pierce, FL 34946, USA
| | - R Sean Norman
- Department of Environmental Health Sciences, Arnold School of Public Health, South Carolina, 921 Assembly St., Columbia, SC 29208, USA
| | - Heidi K Bojes
- Environmental Epidemiology and Disease Registries Section, Texas Department of State Health Services, Austin, TX 78756, USA
| | - Bryan W Brooks
- Department of Environmental Science, Baylor University, One Bear Place #97266, Waco, TX 76798, USA; Center for Reservoir and Aquatic Systems Research, Baylor University, One Bear Place #97178, Waco, TX 76798, USA; Institute of Biomedical Studies, Baylor University, One Bear Place #97224, Waco, TX 76798, USA
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Zehnder C, Béen F, Vojinovic Z, Savic D, Torres AS, Mark O, Zlatanovic L, Abebe YA. Machine Learning for Detecting Virus Infection Hotspots Via Wastewater-Based Epidemiology: The Case of SARS-CoV-2 RNA. GEOHEALTH 2023; 7:e2023GH000866. [PMID: 37799774 PMCID: PMC10550031 DOI: 10.1029/2023gh000866] [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: 07/04/2023] [Accepted: 09/10/2023] [Indexed: 10/07/2023]
Abstract
Wastewater-based epidemiology (WBE) has been proven to be a useful tool in monitoring public health-related issues such as drug use, and disease. By sampling wastewater and applying WBE methods, wastewater-detectable pathogens such as viruses can be cheaply and effectively monitored, tracking people who might be missed or under-represented in traditional disease surveillance. There is a gap in current knowledge in combining hydraulic modeling with WBE. Recent literature has also identified a gap in combining machine learning with WBE for the detection of viral outbreaks. In this study, we loosely coupled a physically-based hydraulic model of pathogen introduction and transport with a machine learning model to track and trace the source of a pathogen within a sewer network and to evaluate its usefulness under various conditions. The methodology developed was applied to a hypothetical sewer network for the rapid detection of disease hotspots of the disease caused by the SARS-CoV-2 virus. Results showed that the machine learning model's ability to recognize hotspots is promising, but requires a high time-resolution of monitoring data and is highly sensitive to the sewer system's physical layout and properties such as flow velocity, the pathogen sampling procedure, and the model's boundary conditions. The methodology proposed and developed in this paper opens new possibilities for WBE, suggesting a rapid back-tracing of human-excreted biomarkers based on only sampling at the outlet or other key points, but would require high-frequency, contaminant-specific sensor systems that are not available currently.
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Affiliation(s)
- Calvin Zehnder
- Water Supply, Sanitation and Environmental Engineering DepartmentIHE Delft Institute for Water EducationDelftThe Netherlands
| | - Frederic Béen
- KWR Water Research InstituteNieuwegeinThe Netherlands
| | - Zoran Vojinovic
- Water Supply, Sanitation and Environmental Engineering DepartmentIHE Delft Institute for Water EducationDelftThe Netherlands
- Centre for Water SystemsCollege of EngineeringMathematics and Physical SciencesUniversity of ExeterExeterUK
- Faculty of Civil EngineeringUniversity of BelgradeBelgradeSerbia
- National Cheng Kung UniversityTainanTaiwan
| | - Dragan Savic
- KWR Water Research InstituteNieuwegeinThe Netherlands
- Centre for Water SystemsCollege of EngineeringMathematics and Physical SciencesUniversity of ExeterExeterUK
- Faculty of Civil EngineeringUniversity of BelgradeBelgradeSerbia
| | - Arlex Sanchez Torres
- Water Supply, Sanitation and Environmental Engineering DepartmentIHE Delft Institute for Water EducationDelftThe Netherlands
| | | | - Ljiljana Zlatanovic
- Sanitary EngineeringDelft University of TechnologyDelftThe Netherlands
- PWNVelserbroekThe Netherlands
| | - Yared Abayneh Abebe
- Water Supply, Sanitation and Environmental Engineering DepartmentIHE Delft Institute for Water EducationDelftThe Netherlands
- Department of Hydraulic EngineeringFaculty of Civil Engineering and GeosciencesDelft University of TechnologyDelftThe Netherlands
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Ruan Y, Huang T, Zhou W, Zhu J, Liang Q, Zhong L, Tang X, Liu L, Chen S, Xie Y. The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19. Sci Rep 2023; 13:14705. [PMID: 37679512 PMCID: PMC10484897 DOI: 10.1038/s41598-023-41939-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 09/04/2023] [Indexed: 09/09/2023] Open
Abstract
Internet search data was a useful tool in the pre-warning of COVID-19. However, the lead time and indicators may change over time and space with the new variants appear and massive nucleic acid testing. Since Omicron appeared in late 2021, we collected the daily number of cases and Baidu Search Index (BSI) of seven search terms from 1 January to 30 April, 2022 in 12 provinces/prefectures to explore the variation in China. Two search peaks of "COVID-19 epidemic", "Novel Coronavirus" and "COVID-19" can be observed. One in January, which showed 3 days lead time in Henan and Tianjin. Another on early March, which occurred 0-28 days ahead of the local epidemic but the lead time had spatial variation. It was 4 weeks in Shanghai, 2 weeks in Henan and 5-8 days in Jilin Province, Jilin and Changchun Prefecture. But it was only 1-3 days in Tianjin, Quanzhou Prefecture, Fujian Province and 0 day in Shenzhen, Shandong Province, Qingdao and Yanbian Prefecture. The BSI was high correlated (rs:0.70-0.93) to the number of cases with consistent epidemiological change trend. The lead time of BSI had spatial and temporal variation and was close related to the strength of nucleic acid testing. The case detection ability should be strengthened when perceiving BSI increase.
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Affiliation(s)
- Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Tengda Huang
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Wanwan Zhou
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Jinhui Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Qiuyu Liang
- Department of Health Management, The People's Hospital of Guangxi Zhuang Autonomous Region & Research Center of Health Management, Guangxi Academy of Medical Sciences, Nanning, China
| | - Lixian Zhong
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Xiaofen Tang
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Lu Liu
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Shiwen Chen
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Yihong Xie
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning, China.
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Amato E, Hyllestad S, Heradstveit P, Langlete P, Moen LV, Rohringer A, Pires J, Baz Lomba JA, Bragstad K, Feruglio SL, Aavitsland P, Madslien EH. Evaluation of the pilot wastewater surveillance for SARS-CoV-2 in Norway, June 2022 - March 2023. BMC Public Health 2023; 23:1714. [PMID: 37667223 PMCID: PMC10476384 DOI: 10.1186/s12889-023-16627-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 08/26/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND During the COVID-19 pandemic, wastewater-based surveillance gained great international interest as an additional tool to monitor SARS-CoV-2. In autumn 2021, the Norwegian Institute of Public Health decided to pilot a national wastewater surveillance (WWS) system for SARS-CoV-2 and its variants between June 2022 and March 2023. We evaluated the system to assess if it met its objectives and its attribute-based performance. METHODS We adapted the available guidelines for evaluation of surveillance systems. The evaluation was carried out as a descriptive analysis and consisted of the following three steps: (i) description of the WWS system, (ii) identification of users and stakeholders, and (iii) analysis of the system's attributes and performance including sensitivity, specificity, timeliness, usefulness, representativeness, simplicity, flexibility, stability, and communication. Cross-correlation analysis was performed to assess the system's ability to provide early warning signal of new wave of infections. RESULTS The pilot WWS system was a national surveillance system using existing wastewater infrastructures from the largest Norwegian municipalities. We found that the system was sensitive, timely, useful, representative, simple, flexible, acceptable, and stable to follow the general trend of infection. Preliminary results indicate that the system could provide an early signal of changes in variant distribution. However, challenges may arise with: (i) specificity due to temporary fluctuations of RNA levels in wastewater, (ii) representativeness when downscaling, and (iii) flexibility and acceptability when upscaling the system due to limited resources and/or capacity. CONCLUSIONS Our results showed that the pilot WWS system met most of its surveillance objectives. The system was able to provide an early warning signal of 1-2 weeks, and the system was useful to monitor infections at population level and complement routine surveillance when individual testing activity was low. However, temporary fluctuations of WWS values need to be carefully interpreted. To improve quality and efficiency, we recommend to standardise and validate methods for assessing trends of new waves of infection and variants, evaluate the WWS system using a longer operational period particularly for new variants, and conduct prevalence studies in the population to calibrate the system and improve data interpretation.
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Affiliation(s)
- Ettore Amato
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway.
| | - Susanne Hyllestad
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Petter Heradstveit
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Petter Langlete
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Line Victoria Moen
- Department of Virology, Norwegian Institute of Public Health, Oslo, Norway
| | - Andreas Rohringer
- Department of Virology, Norwegian Institute of Public Health, Oslo, Norway
| | - João Pires
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
- Public Health Microbiology path (EUPHEM), European Centre for Disease Prevention and Control (ECDC), ECDC Fellowship Programme, Stockholm, Sweden
| | - Jose Antonio Baz Lomba
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Karoline Bragstad
- Department of Virology, Norwegian Institute of Public Health, Oslo, Norway
| | - Siri Laura Feruglio
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Preben Aavitsland
- Norwegian Institute of Public Health, Oslo, Norway
- Pandemic Centre, University of Bergen, Bergen, Norway
| | - Elisabeth Henie Madslien
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
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Lombardi A, Voli A, Mancusi A, Girardi S, Proroga YTR, Pierri B, Olivares R, Cossentino L, Suffredini E, La Rosa G, Fusco G, Pizzolante A, Porta A, Campiglia P, Torre I, Pennino F, Tosco A. SARS-CoV-2 RNA in Wastewater and Bivalve Mollusk Samples of Campania, Southern Italy. Viruses 2023; 15:1777. [PMID: 37632119 PMCID: PMC10459311 DOI: 10.3390/v15081777] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 08/12/2023] [Accepted: 08/18/2023] [Indexed: 08/27/2023] Open
Abstract
SARS-CoV-2 can be detected in the feces of infected people, consequently in wastewater, and in bivalve mollusks, that are able to accumulate viruses due to their ability to filter large amounts of water. This study aimed to monitor SARS-CoV-2 RNA presence in 168 raw wastewater samples collected from six wastewater treatment plants (WWTPs) and 57 mollusk samples obtained from eight harvesting sites in Campania, Italy. The monitoring period spanned from October 2021 to April 2022, and the results were compared and correlated with the epidemiological situation. In sewage, the ORF1b region of SARS-CoV-2 was detected using RT-qPCR, while in mollusks, three targets-RdRp, ORF1b, and E-were identified via RT-dPCR. Results showed a 92.3% rate of positive wastewater samples with increased genomic copies (g.c.)/(day*inhabitant) in December-January and March-April 2022. In the entire observation period, 54.4% of mollusks tested positive for at least one SARS-CoV-2 target, and the rate of positive samples showed a trend similar to that of the wastewater samples. The lower SARS-CoV-2 positivity rate in bivalve mollusks compared to sewages is a direct consequence of the seawater dilution effect. Our data confirm that both sample types can be used as sentinels to detect SARS-CoV-2 in the environment and suggest their potential use in obtaining complementary information on SARS-CoV-2.
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Affiliation(s)
- Annalisa Lombardi
- Department of Public Health, University “Federico II”, Via Sergio Pansini 5, 80131 Naples, Italy; (A.L.)
| | - Antonia Voli
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, Italy; (A.V.); (A.P.); (P.C.)
| | - Andrea Mancusi
- Department of Food Security Coordination, Zooprophylactic Institute of Southern Italy, Via Salute 2, 80055 Portici, Italy; (A.M.); (S.G.); (Y.T.R.P.); (B.P.)
| | - Santa Girardi
- Department of Food Security Coordination, Zooprophylactic Institute of Southern Italy, Via Salute 2, 80055 Portici, Italy; (A.M.); (S.G.); (Y.T.R.P.); (B.P.)
| | - Yolande Thérèse Rose Proroga
- Department of Food Security Coordination, Zooprophylactic Institute of Southern Italy, Via Salute 2, 80055 Portici, Italy; (A.M.); (S.G.); (Y.T.R.P.); (B.P.)
| | - Biancamaria Pierri
- Department of Food Security Coordination, Zooprophylactic Institute of Southern Italy, Via Salute 2, 80055 Portici, Italy; (A.M.); (S.G.); (Y.T.R.P.); (B.P.)
| | - Renato Olivares
- Campania Regional Environmental Protection Agency (ARPAC), Via Vicinale Santa Maria del Pianto, 80143 Naples, Italy; (R.O.); (L.C.)
| | - Luigi Cossentino
- Campania Regional Environmental Protection Agency (ARPAC), Via Vicinale Santa Maria del Pianto, 80143 Naples, Italy; (R.O.); (L.C.)
| | - Elisabetta Suffredini
- Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy;
| | - Giuseppina La Rosa
- Department of Environment and Health, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy;
| | - Giovanna Fusco
- Zooprophylactic Institute of Southern Italy, Via Salute 2, 80055 Portici, Italy; (G.F.); (A.P.)
| | - Antonio Pizzolante
- Zooprophylactic Institute of Southern Italy, Via Salute 2, 80055 Portici, Italy; (G.F.); (A.P.)
| | - Amalia Porta
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, Italy; (A.V.); (A.P.); (P.C.)
| | - Pietro Campiglia
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, Italy; (A.V.); (A.P.); (P.C.)
| | - Ida Torre
- Department of Public Health, University “Federico II”, Via Sergio Pansini 5, 80131 Naples, Italy; (A.L.)
| | - Francesca Pennino
- Department of Public Health, University “Federico II”, Via Sergio Pansini 5, 80131 Naples, Italy; (A.L.)
| | - Alessandra Tosco
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, Italy; (A.V.); (A.P.); (P.C.)
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König AW, Ariano SS, Joksimovic D. Analysis of sampling strategies for pulse loads of SARS-CoV-2: implications for wastewater-based epidemiology. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2023; 88:1039-1057. [PMID: 37651336 PMCID: wst_2023_233 DOI: 10.2166/wst.2023.233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
A faecal transport model was applied to a 11.3 km2 wastewater servicing area in Toronto, Ontario, Canada to explore the role that different wastewater sampling campaigns have on estimating the prevalence of SARS-CoV-2 in a population of 60,000. A stochastic wastewater and water quality model was used to evaluate the effectiveness of 11 sampling campaigns during periods of high and low COVID-19 infection among the population, tested using virtual sampling during dry-weather flow. The virtual sampling campaigns were based on the most common automatic sampler programming capabilities and widely used wastewater-based epidemiology (WBE) sampling campaigns reported in the literature. Sampling campaigns differ in weighting method (time, volume, or flow-weighted sampling), sample count, collection period, or sample time. Results suggest that grab samples should be avoided and/or that sampling campaigns with the greatest sample counts and durations are the most robust at capturing COVID-19 infection among the population. Most surprisingly, changes to the weighting method were negligible indicating that a greater number of samples, and larger sample volumes are preferred. This work suggests that investment in flow monitoring equipment for flow- or volume-weighted sampling will not improve WBE results, and that standard time based sampling is sufficient.
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Affiliation(s)
- Albert Wilhelm König
- Institute of Urban Water Management and Landscape Water Engineering, Graz University of Technolog, Stremayrgasse 10/1, Graz 8010, Austria E-mail:
| | - Sarah Sydney Ariano
- Department of Earth and Planetary Sciences, McGill University, 3450 University Street, Montreal, QC, H3A 0E8, Canada
| | - Darko Joksimovic
- Department of Civil Engineering, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada
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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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Costa GLD, Negri M, Miranda RPRD, Corrêa-Moreira D, Pinto TCA, Ramos LDS, Ferreira DG, Salomão B, Fumian TM, Mannarino CF, Prado T, Miagostovich MP, Santos ALSD, Oliveira MME. Candida palmioleophila: A New Emerging Threat in Brazil? J Fungi (Basel) 2023; 9:770. [PMID: 37504758 PMCID: PMC10381623 DOI: 10.3390/jof9070770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 07/05/2023] [Accepted: 07/14/2023] [Indexed: 07/29/2023] Open
Abstract
Human activity directly or indirectly causes climate change, promoting changes in the composition of the atmosphere. This change is beyond the variation of the natural climate. In this manner, climate change could create an environmental pressure which is enough to trigger new fungal diseases. In addition to climate alterations, the onset of the COVID-19 pandemic has also been associated with the emergence of fungal pathogens. Fungi showed that an inability to grow at high temperatures limits the capacity of fungi to infect mammals. However, fungi can develop thermotolerance, gradually adapting to rising temperatures due to climate change, and generating a greater number of disease-causing organisms. In the present study, we reported the detection and identification of Candida palmioleophila isolates recovered from raw sewage samples in Niteroi city, Rio de Janeiro State, Brazil, during a monitoring program for measuring SARS-CoV-2 presence and concentration. Using polyphasic taxonomy to identify the species and evaluating some virulence aspects of this species, such as biofilm formation and extracellular enzyme production, our data highlight this species as a possible emerging pathogen in Brazil, especially in the pandemic context.
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Affiliation(s)
- Gisela Lara da Costa
- Laboratory of Taxonomy, Biochemistry and Bioprospecting of Fungi, Oswaldo Cruz Institution (IOC), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro 21040-900, Brazil
| | - Melyssa Negri
- Medical Mycology Laboratory, Clinical Analysis Department, State University of Maringá, Maringá 87020-900, Brazil
| | - Rodrigo Prado Rodrigues de Miranda
- Laboratory of Taxonomy, Biochemistry and Bioprospecting of Fungi, Oswaldo Cruz Institution (IOC), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro 21040-900, Brazil
- Insect Biochemistry and Physiology Laboratory, Oswaldo Cruz Institution (IOC), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro 21040-900, Brazil
| | - Danielly Corrêa-Moreira
- Laboratory of Taxonomy, Biochemistry and Bioprospecting of Fungi, Oswaldo Cruz Institution (IOC), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro 21040-900, Brazil
| | - Tatiana Castro Abreu Pinto
- Laboratory of Pathogenic Cocci and Microbiota, Paulo de Goés Institute of Microbiology, Federal University of Rio de Janeiro, Rio de Janeiro 21941-853, Brazil
| | - Livia de Souza Ramos
- Laboratory for Advanced Studies of Emerging and Resistant Microorganisms, Federal University of Rio de Janeiro, Rio de Janeiro 21941-853, Brazil
| | - Deisiany Gomes Ferreira
- Medical Mycology Laboratory, Clinical Analysis Department, State University of Maringá, Maringá 87020-900, Brazil
| | - Bruna Salomão
- Laboratory of Microbiology, Federal Hospital of Andaraí, Rio de Janeiro 20541-170, Brazil
| | - Tulio Machado Fumian
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-360, Brazil
| | - Camille Ferreira Mannarino
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-360, Brazil
| | - Tatiana Prado
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-360, Brazil
| | - Marise Pereira Miagostovich
- Laboratory of Comparative and Environmental Virology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-360, Brazil
| | - André Luis Souza Dos Santos
- Laboratory for Advanced Studies of Emerging and Resistant Microorganisms, Federal University of Rio de Janeiro, Rio de Janeiro 21941-853, Brazil
| | - Manoel Marques Evangelista Oliveira
- Laboratory of Taxonomy, Biochemistry and Bioprospecting of Fungi, Oswaldo Cruz Institution (IOC), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro 21040-900, Brazil
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de Graaf M, Langeveld J, Post J, Carrizosa C, Franz E, Izquierdo-Lara RW, Elsinga G, Heijnen L, Been F, van Beek J, Schilperoort R, Vriend R, Fanoy E, de Schepper EIT, Koopmans MPG, Medema G. Capturing the SARS-CoV-2 infection pyramid within the municipality of Rotterdam using longitudinal sewage surveillance. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 883:163599. [PMID: 37100150 PMCID: PMC10125208 DOI: 10.1016/j.scitotenv.2023.163599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 04/07/2023] [Accepted: 04/15/2023] [Indexed: 05/03/2023]
Abstract
Despite high vaccination rates in the Netherlands, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to circulate. Longitudinal sewage surveillance was implemented along with the notification of cases as two parts of the surveillance pyramid to validate the use of sewage for surveillance, as an early warning tool, and to measure the effect of interventions. Sewage samples were collected from nine neighborhoods between September 2020 and November 2021. Comparative analysis and modeling were performed to understand the correlation between wastewater and case trends. Using high resolution sampling, normalization of wastewater SARS-CoV-2 concentrations, and 'normalization' of reported positive tests for testing delay and intensity, the incidence of reported positive tests could be modeled based on sewage data, and trends in both surveillance systems coincided. The high collinearity implied that high levels of viral shedding around the onset of disease largely determined SARS-CoV-2 levels in wastewater, and that the observed relationship was independent of variants of concern and vaccination levels. Sewage surveillance alongside a large-scale testing effort where 58 % of a municipality was tested, indicated a five-fold difference in the number of SARS-CoV-2-positive individuals and reported cases through standard testing. Where trends in reported positive cases were biased due to testing delay and testing behavior, wastewater surveillance can objectively display SARS-CoV-2 dynamics for both small and large locations and is sensitive enough to measure small variations in the number of infected individuals within or between neighborhoods. With the transition to a post-acute phase of the pandemic, sewage surveillance can help to keep track of re-emergence, but continued validation studies are needed to assess the predictive value of sewage surveillance with new variants. Our findings and model aid in interpreting SARS-CoV-2 surveillance data for public health decision-making and show its potential as one of the pillars of future surveillance of (re)emerging viruses.
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Affiliation(s)
- Miranda de Graaf
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, the Netherlands; Pandemic and Disaster Preparedness Centre Rotterdam and Delft, the Netherlands.
| | - Jeroen Langeveld
- Partners4urbanwater, Nijmegen, the Netherlands; Delft University of Technology, Stevinweg 1, 2628 CN Delft, the Netherlands
| | - Johan Post
- Partners4urbanwater, Nijmegen, the Netherlands
| | - Christian Carrizosa
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Eelco Franz
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Ray W Izquierdo-Lara
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Goffe Elsinga
- KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, the Netherlands
| | - Leo Heijnen
- KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, the Netherlands
| | - Frederic Been
- KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, the Netherlands
| | - Janko van Beek
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Rianne Vriend
- Regional Public Health Service Rotterdam-Rijnmond, Rotterdam, the Netherlands
| | - Ewout Fanoy
- Regional Public Health Service Rotterdam-Rijnmond, Rotterdam, the Netherlands
| | - Evelien I T de Schepper
- Department of General Practice, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Marion P G Koopmans
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, the Netherlands; Pandemic and Disaster Preparedness Centre Rotterdam and Delft, the Netherlands
| | - Gertjan Medema
- Pandemic and Disaster Preparedness Centre Rotterdam and Delft, the Netherlands; KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, the Netherlands; Delft University of Technology, Stevinweg 1, 2628 CN Delft, the Netherlands
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49
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A'la R, Wijaya AY, Susilowati H, Kuncorojakti S, Diyantoro, Rahmahani J, Rantam FA. Inactivated SARS-CoV-2 vaccine candidate immunization on non-human primate animal model: B-cell and T-cell responses immune evaluation. Heliyon 2023; 9:e18039. [PMID: 37519714 PMCID: PMC10372371 DOI: 10.1016/j.heliyon.2023.e18039] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 06/21/2023] [Accepted: 07/05/2023] [Indexed: 08/01/2023] Open
Abstract
Background SARS-CoV-2 vaccine was proven to be an effective and efficient measure for mitigating pandemic. COVID-19 infection and mortality subsided along with the increaseing COVID-19 vaccination coverage. Vaccine and health resource equity are predominant factors in COVID-19 pandemic management. Vaccine development for Indonesia, aims to ensure a sustainable pandemic control and steady national stability restoration. A decent vaccine must induce immunity against COVID-19 with minimum adverse reaction. Immunogenicity and ability to induce neutralizing antibody evaluation needs to be performed as part of the SARS-CoV-2 inactivated vaccine development from East Java, Indonesia isolate (Vaksin Merah Putih-INAVAC). Objective This research demonstrated INAVAC performance in inducing the production neutralizing antibody along with its effects on CD4+ and CD8+ cells response in Macaca fascicularis (non-human primate). Methods Two dosages of 3 μg and 5 μg were tested, compared to sham (NaCl 0.9%) in 10 Macaca fascicularis (2 injection intramuscular with 14 days interval). All animals were monitored daily for clinical signs. Nasopharyngeal samples were analyzed using qRT-PCR while the serum were tested using ELISA and neutralization assay, whereas PBMCs were flowcytrometrically analyzed to measure CD4+ and CD8+ population. Results It is observed that both vaccine doses could stimulate relatively similar immune response and neutralizing antibody (end GMT post challenge = 905,1), whereas higher CD8+ cells response were reported in the 5 μg group after the 3rd day post-challenge. The dose of vaccine that produce adequate immune cell stimulation with neutralizing antibody induction can be adopted to clinical study, as favorable result of these parameters could predict minimum adverse reaction from inflammation response with balanced immune response. Conclusions Therefore, it is concluded that Vaksin Merah Putih-INAVAC with 3 μg dose showed a favorable potential to be developed and tested as human vaccine.
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Affiliation(s)
- Rofiqul A'la
- Faculty of Veterinary Medicine, Universitas Airlangga, Surabaya, Indonesia
| | | | - Helen Susilowati
- Research Center for Vaccine Technology and Development, Institute of Tropical Disease, Universitas Airlangga, Surabaya, Indonesia
| | - Suryo Kuncorojakti
- Department of Veterinary Anatomy, Faculty of Veterinary Medicine, Universitas Airlangga, Surabaya, Indonesia
| | - Diyantoro
- Doctoral Program of Medical Science, Faculty of Medicine, Universitas Airlangga, Indonesia
| | - Jola Rahmahani
- Virology and Immunology Laboratory, Department of Microbiology, Faculty of Veterinary Medicine, Universitas Airlangga, Surabaya, Indonesia
| | - Fedik Abdul Rantam
- Research Center for Vaccine Technology and Development, Institute of Tropical Disease, Universitas Airlangga, Surabaya, Indonesia
- Virology and Immunology Laboratory, Department of Microbiology, Faculty of Veterinary Medicine, Universitas Airlangga, Surabaya, Indonesia
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50
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Cimmino C, Rodrigues Capítulo L, Lerman A, Silva A, Von Haften G, Comino AP, Cigoy L, Scagliola M, Poncet V, Caló G, Uez O, Berón CM. Presence of SARS-CoV-2 in urban effluents in south-east Buenos Aires, Argentina, May 2020 to March 2022. Rev Panam Salud Publica 2023; 47:e94. [PMID: 37324201 PMCID: PMC10261580 DOI: 10.26633/rpsp.2023.94] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 03/14/2023] [Indexed: 06/17/2023] Open
Abstract
Objectives To implement and evaluate the use of wastewater sampling for detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in two coastal districts of Buenos Aires Province, Argentina. Methods In General Pueyrredon district, 400 mL of wastewater samples were taken with an automatic sampler for 24 hours, while in Pinamar district, 20 L in total (2.2 L at 20-minute intervals) were taken. Samples were collected once a week. The samples were concentrated based on flocculation using polyaluminum chloride. RNA purification and target gene amplification and detection were performed using reverse transcription polymerase chain reaction for clinical diagnosis of human nasopharyngeal swabs. Results In both districts, the presence of SARS-CoV-2 was detected in wastewater. In General Pueyrredon, SARS-CoV-2 was detected in epidemiological week 28, 2020, which was 20 days before the start of an increase in coronavirus virus disease 2019 (COVID-19) cases in the first wave (epidemiological week 31) and 9 weeks before the maximum number of laboratory-confirmed COVID-19 cases was recorded. In Pinamar district, the virus genome was detected in epidemiological week 51, 2020 but it was not possible to carry out the sampling again until epidemiological week 4, 2022, when viral circulation was again detected. Conclusions It was possible to detect SARS-CoV-2 virus genome in wastewater, demonstrating the usefulness of the application of wastewater epidemiology for long-term SARS-CoV-2 detection and monitoring.
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Affiliation(s)
- Carlos Cimmino
- Instituto Nacional de Epidemiología “Dr. Juan H. Jara”Mar del PlataArgentinaInstituto Nacional de Epidemiología “Dr. Juan H. Jara”, Mar del Plata, Argentina.
| | - Leandro Rodrigues Capítulo
- Centro de Estudios Integrales de la Dinámica ExógenaUniversidad Nacional de La PlataLa PlataArgentinaCentro de Estudios Integrales de la Dinámica Exógena, Universidad Nacional de La Plata, La Plata, Argentina.
| | - Andrea Lerman
- Instituto Nacional de Epidemiología “Dr. Juan H. Jara”Mar del PlataArgentinaInstituto Nacional de Epidemiología “Dr. Juan H. Jara”, Mar del Plata, Argentina.
| | - Andrea Silva
- Instituto Nacional de Epidemiología “Dr. Juan H. Jara”Mar del PlataArgentinaInstituto Nacional de Epidemiología “Dr. Juan H. Jara”, Mar del Plata, Argentina.
| | - Gabriela Von Haften
- Obras Sanitarias Sociedad de EstadoMar del PlataArgentinaObras Sanitarias Sociedad de Estado, Mar del Plata, Argentina.
| | - Ana P. Comino
- Obras Sanitarias Sociedad de EstadoMar del PlataArgentinaObras Sanitarias Sociedad de Estado, Mar del Plata, Argentina.
| | - Luciana Cigoy
- Obras Sanitarias Sociedad de EstadoMar del PlataArgentinaObras Sanitarias Sociedad de Estado, Mar del Plata, Argentina.
| | - Marcelo Scagliola
- Obras Sanitarias Sociedad de EstadoMar del PlataArgentinaObras Sanitarias Sociedad de Estado, Mar del Plata, Argentina.
| | - Verónica Poncet
- Instituto Nacional de Epidemiología “Dr. Juan H. Jara”Mar del PlataArgentinaInstituto Nacional de Epidemiología “Dr. Juan H. Jara”, Mar del Plata, Argentina.
| | - Gonzalo Caló
- Instituto de Investigaciones en Biodiversidad y Biotecnología and FIBAMar del PlataArgentinaInstituto de Investigaciones en Biodiversidad y Biotecnología and FIBA, Mar del Plata, Argentina.
| | - Osvaldo Uez
- Instituto Nacional de Epidemiología “Dr. Juan H. Jara”Mar del PlataArgentinaInstituto Nacional de Epidemiología “Dr. Juan H. Jara”, Mar del Plata, Argentina.
| | - Corina M. Berón
- Instituto de Investigaciones en Biodiversidad y Biotecnología and FIBAMar del PlataArgentinaInstituto de Investigaciones en Biodiversidad y Biotecnología and FIBA, Mar del Plata, Argentina.
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