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Li J, Cheng R, Bian Z, Niu J, Xia J, Mao G, Liu H, Wu C, Hao C. Development of multiplex allele-specific RT-qPCR assays for differentiation of SARS-CoV-2 Omicron subvariants. Appl Microbiol Biotechnol 2024; 108:35. [PMID: 38183475 DOI: 10.1007/s00253-023-12941-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/18/2023] [Accepted: 10/25/2023] [Indexed: 01/08/2024]
Abstract
Quick differentiation of current circulating variants and the emerging recombinant variants of SARS-CoV-2 is essential to monitor their transmissions. However, the widely applied gene sequencing method is time-consuming and costly especially when facing recombinant variants, because a large part or whole genome sequencing is required. Allele-specific reverse transcriptase real time RT-PCR (RT-qPCR) represents a quick and cost-effective method for SNP (single nucleotide polymorphism) genotyping and has been successfully applied for SARS-CoV-2 variant screening. In the present study, we developed a panel of 5 multiplex allele-specific RT-qPCR assays targeting 20 key mutations for quick differentiation of the Omicron subvariants (BA.1 to BA.5 and their descendants) and the recombinant variants (XBB.1 and XBB.1.5). Two parallel multiplex RT-qPCR reactions were designed to separately target the prototype allele and the mutated allele of each mutation in the allele-specific RT-qPCR assay. Optimal annealing temperatures, primer and probe dosage, and time for annealing/extension for each reaction were determined by multi-factor and multi-level orthogonal test. The variation of Cp (crossing point) values (ΔCp) between the two multiplex RT-qPCR reactions was applied to determine if a mutation occurs or not. SARS-CoV-2 subvariants and related recombinant variants were differentiated by their unique mutation patterns. The developed multiplex allele-specific RT-qPCR assays exhibited excellent analytical sensitivities (with limits of detection (LoDs) of 1.47-18.52 copies per reaction), wide linear detection ranges (109-100 copies per reaction), good amplification efficiencies (88.25 to 110.68%), excellent reproducibility (coefficient of variations (CVs) < 5% in both intra-assay and inter-assay tests), and good clinical performances (99.5-100% consistencies with Sanger sequencing). The developed multiplex allele-specific RT-qPCR assays in the present study provide an alternative tool for quick differentiation of the SARS-CoV-2 Omicron subvariants and their recombinant variants. KEY POINTS: • A panel of five multiplex allele-specific RT-qPCR assays for quick differentiation of 11 SARS-CoV-2 Omicron subvariants (BA.1, BA.2, BA.4, BA.5, and their descendants) and 2 recombinant variants (XBB.1 and XBB.1.5). • The developed assays exhibited good analytical sensitivities and reproducibility, wide linear detection ranges, and good clinical performances, providing an alternative tool for quick differentiation of the SARS-CoV-2 Omicron subvariants and their recombinant variants.
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Affiliation(s)
- Jianguo Li
- Shanxi Provincial Key Laboratory of Medical Molecular Cell Biology, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, People's Republic of China.
| | - Ruiling Cheng
- Shanxi Provincial Key Laboratory of Medical Molecular Cell Biology, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, People's Republic of China
| | - Zixin Bian
- College of Life Sciences, Shanxi University, Taiyuan, 030006, People's Republic of China
| | - Jiahui Niu
- Shanxi Provincial Key Laboratory of Medical Molecular Cell Biology, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, People's Republic of China
| | - Juan Xia
- Shanxi Provincial Key Laboratory of Medical Molecular Cell Biology, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, People's Republic of China
| | - Guoli Mao
- Shanxi Guoxin Caregeno Biotechnology Co., Ltd., Taiyuan, 030032, People's Republic of China
| | - Hulong Liu
- Shanxi Guoxin Caregeno Biotechnology Co., Ltd., Taiyuan, 030032, People's Republic of China
| | - Changxin Wu
- Shanxi Provincial Key Laboratory of Medical Molecular Cell Biology, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, People's Republic of China
| | - Chunyan Hao
- School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan, 030024, People's Republic of China.
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2
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Li H, He F, Lv Z, Yi L, Zhang Z, Li H, Fu S. Tailored wastewater surveillance framework uncovered the epidemics of key pathogens in a Northwestern city of China. Sci Total Environ 2024; 926:171833. [PMID: 38522539 DOI: 10.1016/j.scitotenv.2024.171833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 03/03/2024] [Accepted: 03/18/2024] [Indexed: 03/26/2024]
Abstract
Wastewater surveillance enables rapid pathogen monitoring and community prevalence estimation. However, how to design an integrated and tailored wastewater surveillance framework to monitor major health threats in metropolises remains a major challenge. In this study, we first analyzed the historical clinical data of Xi'an city and designed a wastewater surveillance framework covering five key endemic viruses, namely, SARS-CoV-2, norovirus, influenza A virus (IAV), influenza B virus (IBV), respiratory syncytial virus (RSV), and hantavirus. Amplicon sequencing of SARS-CoV-2, norovirus and hantavirus was conducted biweekly to determine the prevalent community genotypes circulating in this region. The results showed that from April 2023 to August 2023, Xi'an experienced two waves of SARS-CoV-2 infection, which peaked in the middle of May-2023 and late August-2023. The sewage concentrations of IAV and RSV peaked in early March and early May 2023, respectively, while the sewage concentrations of norovirus fluctuated throughout the study period and peaked in late August. The dynamics of the sewage concentrations of SARS-CoV-2, norovirus, IAV, RSV, and hantavirus were in line with the trends in the sentinel hospital percent positivity data, indicating the role of wastewater surveillance in enhancing the understanding of epidemic trends. Amplicon sequencing of SARS-CoV-2 revealed a transition in the predominant genotype, which changed from DY.1 and FR.1.4 to the XBB and EG.5 subvariants. Amplicon sequencing also revealed that there was only one predominant hantavirus genotype in the local population, while highly diverse genotypes of norovirus GI and GII were found in the wastewater. In conclusion, this study provided valuable insights into the dynamics of infection trends and predominant genotypes of key pathogens in a city without sufficient clinical surveillance, highlighting the role of a tailored wastewater surveillance framework in addressing public health priorities. More importantly, our study provides the first evidence demonstrating the applicability of wastewater surveillance for hantavirus, which is a major health threat locally.
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Affiliation(s)
- Haifeng Li
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi'an 710069, China
| | - Fenglan He
- The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang 330038, China
| | - Ziquan Lv
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Liu Yi
- The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang 330038, China
| | - Ziqiang Zhang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi'an 710069, China
| | - Hui Li
- The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang 330038, China.
| | - Songzhe Fu
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi'an 710069, China; The Collaboration Unit for State Key Laboratory of Infectious Disease Prevention and Control, Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang 330038, China.
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3
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Girón-Guzmán I, Cuevas-Ferrando E, Barranquero R, Díaz-Reolid A, Puchades-Colera P, Falcó I, Pérez-Cataluña A, Sánchez G. Urban wastewater-based epidemiology for multi-viral pathogen surveillance in the Valencian region, Spain. Water Res 2024; 255:121463. [PMID: 38537489 DOI: 10.1016/j.watres.2024.121463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 02/28/2024] [Accepted: 03/12/2024] [Indexed: 04/24/2024]
Abstract
Wastewater-based epidemiology (WBE) has lately arised as a promising tool for monitoring and tracking viral pathogens in communities. In this study, we analysed WBE's role as a multi-pathogen surveillance strategy to detect the presence of several viral illness causative agents. Thus, an epidemiological study was conducted from October 2021 to February 2023 to estimate the weekly levels of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), Respiratory Syncytial virus (RSV), and Influenza A virus (IAV) in influent wastewater samples (n = 69). In parallel, a one-year study (October 2021 to October 2022) was performed to assess the presence of pathogenic human enteric viruses. Besides, monitoring of proposed viral fecal contamination indicators crAssphage and Pepper mild mottle virus (PMMoV) was also assessed, along with plaque counting of somatic coliphages. Genetic material of rotavirus (RV), human astrovirus (HAStV), and norovirus genogroup I (GI) and GII was found in almost all samples, while hepatitis A and E viruses (HAV and HEV) only tested positive in 3.77 % and 22.64 % of the samples, respectively. No seasonal patterns were overall found for enteric viruses, although RVs had a peak prevalence in the winter months. All samples tested positive for SARS-CoV-2 RNA, with a mean concentration of 5.43 log genome copies per liter (log GC/L). The tracking of the circulating SARS-CoV-2 variants of concern (VOCs) was performed by both duplex RT-qPCR and next generation sequencing (NGS). Both techniques reliably showed how the dominant VOC transitioned from Delta to Omicron during two weeks in Spain in December 2021. RSV and IAV viruses peaked in winter months with mean concentrations 6.40 and 4.10 log GC/L, respectively. Moreover, the three selected respiratory viruses strongly correlated with reported clinical data when normalised by wastewater physico-chemical parameters and presented weaker correlations when normalising sewage concentration levels with crAssphage or somatic coliphages titers. Finally, predictive models were generated for each respiratory virus, confirming high reliability on WBE data as an early-warning system and communities illness monitoring system. Overall, this study presents WBE as an optimal tool for multi-pathogen tracking reflecting viral circulation and diseases trends within a selected area, its value as a multi-pathogen early-warning tool stands out due to its public health interest.
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Affiliation(s)
- Inés Girón-Guzmán
- Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, Paterna, Valencia 46980, Spain
| | - Enric Cuevas-Ferrando
- Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, Paterna, Valencia 46980, Spain.
| | - Regino Barranquero
- Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, Paterna, Valencia 46980, Spain
| | - Azahara Díaz-Reolid
- Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, Paterna, Valencia 46980, Spain
| | - Pablo Puchades-Colera
- Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, Paterna, Valencia 46980, Spain
| | - Irene Falcó
- Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, Paterna, Valencia 46980, Spain; Department of Microbiology and Ecology, University of Valencia, Valencia, Spain
| | - Alba Pérez-Cataluña
- Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, Paterna, Valencia 46980, Spain
| | - Gloria Sánchez
- Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, Paterna, Valencia 46980, Spain.
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4
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Reis AC, Pinto D, Monteiro S, Santos R, Martins JV, Sousa A, Páscoa R, Lourinho R, Cunha MV. Systematic SARS-CoV-2 S-gene sequencing in wastewater samples enables early lineage detection and uncovers rare mutations in Portugal. Sci Total Environ 2024; 921:170961. [PMID: 38367735 DOI: 10.1016/j.scitotenv.2024.170961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 12/23/2023] [Accepted: 02/11/2024] [Indexed: 02/19/2024]
Abstract
As the COVID-19 pandemic reached its peak, many countries implemented genomic surveillance systems to track the evolution and transmission of SARS-CoV-2. Transition from the pandemic to the endemic phase prioritized alternative testing strategies to maintain effective epidemic surveillance at the population level, with less intensive sequencing efforts. One such promising approach was Wastewater-Based Surveillance (WBS), which offers non-invasive, cost-effective means for analysing virus trends at the sewershed level. From 2020 onwards, wastewater has been recognized as an instrumental source of information for public health, with national and international authorities exploring options to implement national wastewater surveillance systems and increasingly relying on WBS as early warning of potential pathogen outbreaks. In Portugal, several pioneer projects joined the academia, water utilities and Public Administration around WBS. To validate WBS as an effective genomic surveillance strategy, it is crucial to collect long term performance data. In this work, we present one year of systematic SARS-CoV-2 wastewater surveillance in Portugal, representing 35 % of the mainland population. We employed two complementary methods for lineage determination - allelic discrimination by RT-PCR and S-gene sequencing. This combination allowed us to monitor variant evolution in near-real-time and identify low-frequency mutations. Over the course of this year-long study, spanning from May 2022 to April 2023, we successfully tracked the dominant Omicron sub-lineages, their progression and evolution, which aligned with concurrent clinical surveillance data. Our results underscore the effectiveness of WBS as a tracking system for virus variants, with the ability to unveil mutations undetected via massive sequencing of clinical samples from Portugal, demonstrating the ability of WBS to uncover new mutations and detect rare genetic variants. Our findings emphasize that knowledge of the genetic diversity of SARS-CoV-2 at the population level can be extended far beyond via the combination of routine clinical genomic surveillance with wastewater sequencing and genotyping.
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Affiliation(s)
- Ana C Reis
- Centre for Ecology, Evolution and Environmental Changes (cE3c), CHANGE - Global Change and Sustainability Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal; Biosystems & Integrative Sciences Institute (BioISI), Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Daniela Pinto
- Centre for Ecology, Evolution and Environmental Changes (cE3c), CHANGE - Global Change and Sustainability Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal; Biosystems & Integrative Sciences Institute (BioISI), Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Sílvia Monteiro
- Laboratório de Análises, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal; CERIS - Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal; DECN - Department of Nuclear Sciences and Engineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
| | - Ricardo Santos
- Laboratório de Análises, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal; CERIS - Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal; DECN - Department of Nuclear Sciences and Engineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
| | | | | | | | | | - Mónica V Cunha
- Centre for Ecology, Evolution and Environmental Changes (cE3c), CHANGE - Global Change and Sustainability Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal; Biosystems & Integrative Sciences Institute (BioISI), Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.
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5
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Oh C, Xun G, Lane ST, Petrov VA, Zhao H, Nguyen TH. Portable, single nucleotide polymorphism-specific duplex assay for virus surveillance in wastewater. Sci Total Environ 2024; 912:168701. [PMID: 37992833 DOI: 10.1016/j.scitotenv.2023.168701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 11/14/2023] [Accepted: 11/17/2023] [Indexed: 11/24/2023]
Abstract
The Argonaute protein from the archaeon Pyrococcus furiosus (PfAgo) is a DNA-guided nuclease that targets DNA with any sequence. We designed a virus detection assay in which the PfAgo enzyme cleaves the reporter probe, thus generating fluorescent signals when amplicons from a reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) assay contain target sequences. We confirmed that the RT-LAMP-PfAgo assay for the SARS-CoV-2 Delta variant produced significantly higher fluorescent signals (p < 0.001) when a single nucleotide polymorphism (SNP), exclusive to the Delta variant, was present, compared to the samples without the SNP. Additionally, the duplex assay for Pepper mild mottle virus (PMMOV) and SARS-CoV-2 detection produced specific fluorescent signals (FAM or ROX) only when the corresponding sequences were present. Furthermore, the RT-LAMP-PfAgo assay does not require dilution to reduce the impact of environmental inhibitors. The limit of detection of the PMMOV assay, determined with 30 wastewater samples, was 28 gc/μL, with a 95 % confidence interval of [11,103]. Finally, using a point-of-use device, the RT-LAMP-PfAgo assay successfully detected PMMOV in wastewater samples. Based on our findings, we conclude that the RT-LAMP-PfAgo assay can be used as a portable, SNP-specific duplex assay, which will significantly improve virus surveillance in wastewater.
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Affiliation(s)
- Chamteut Oh
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA; Department of Environmental Engineering Sciences, University of Florida, Gainesville, FL, USA.
| | - Guanhua Xun
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Stephan Thomas Lane
- Carl R. Woese Institute of Genomic Biology, University of Illinois Urbana-Champaign, United States
| | - Vassily Andrew Petrov
- Carl R. Woese Institute of Genomic Biology, University of Illinois Urbana-Champaign, United States
| | - Huimin Zhao
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA; Carl R. Woese Institute of Genomic Biology, University of Illinois Urbana-Champaign, United States; Departments of Chemical and Biomolecular Engineering, Chemistry, and Biochemistry, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Thanh H Nguyen
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA; Carl R. Woese Institute of Genomic Biology, University of Illinois Urbana-Champaign, United States; Carle Illinois College of Medicine, University of Illinois Urbana-Champaign, Urbana, IL, USA
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6
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Baz Lomba JA, Pires J, Myrmel M, Arnø JK, Madslien EH, Langlete P, Amato E, Hyllestad S. Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic. J Water Health 2024; 22:197-234. [PMID: 38295081 PMCID: wh_2023_279 DOI: 10.2166/wh.2023.279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.
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Affiliation(s)
- Jose Antonio Baz Lomba
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway E-mail:
| | - João Pires
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway; ECDC fellowship Programme, Public Health Microbiology path (EUPHEM), European Centre for Disease Prevention and Control (ECDC), Solna, Sweden
| | - Mette Myrmel
- Faculty of Veterinary Medicine, Virology Unit, Norwegian University of Life Science (NMBU), Oslo, Norway
| | - Jorunn Karterud Arnø
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Elisabeth Henie Madslien
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Petter Langlete
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Ettore Amato
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Susanne Hyllestad
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
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7
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Ding J, Xu X, Deng Y, Zheng X, Zhang T. Circulation of SARS-CoV-2 Omicron sub-lineages revealed by multiplex genotyping RT-qPCR assays for sewage surveillance. Sci Total Environ 2023; 904:166300. [PMID: 37591390 DOI: 10.1016/j.scitotenv.2023.166300] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/09/2023] [Accepted: 08/12/2023] [Indexed: 08/19/2023]
Abstract
Sewage surveillance has proven to be an essential complementary tool to clinical diagnosis in combating the COVID-19 pandemic by tracking the spread of the SARS-CoV-2 virus and evaluating infection levels in populations. With the striking spreading and continuous evolution of SARS-CoV-2 Omicron VOC that characterized with higher transmissibility and potential immune evasion, there is an urgent need for the rapid surveillance of this prevalent strain and its sub-lineages in sewage. In this study, based on three multiplex allele-specific (AS) RT-qPCR assays, we established a rapid and high-throughput detection workflow for the simultaneous discrimination of Omicron sub-lineages BA.2.2, BA.2.12.1, BA.4 and BA.5 (hereafter referred to as BA.4/BA.5) to track their community circulation in Hong Kong. All primer-probe sets in the multiplex assays could correctly discriminate and quantitate their target genotypes with high sensitivity and specificity, even when multiple variants co-existed in the sewage samples. Using the established multiplex assays, the trends of SARS-CoV-2 total viral load and variant dynamics in influent samples collected from 11 wastewater treatment plants (WWTPs) during June 2022 and September 2022, aligned with the clinical data, successfully unveiling the swift emergence and predominance of Omicron BA.4/BA.5 in Hong Kong. The study highlights the feasibility and applicability of multiplex RT-qPCR assays for monitoring epidemic trends and tracking variant displacement dynamics in sewage samples, providing a more rapid, high-throughput and cost-effective alternative to enhance the current sewage surveillance system.
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Affiliation(s)
- Jiahui Ding
- Environmental Microbiome Engineering and Biotechnology Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Xiaoqing Xu
- Environmental Microbiome Engineering and Biotechnology Lab, 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 Lab, 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 Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Tong Zhang
- Environmental Microbiome Engineering and Biotechnology Lab, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China.
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8
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Hasing ME, Lee BE, Gao T, Li Q, Qiu Y, Ellehoj E, Graber TE, Fuzzen M, Servos M, Landgraff C, Delatolla R, Tipples G, Zelyas N, Hinshaw D, Maal-Bared R, Sikora C, Parkins M, Hubert CRJ, Frankowski K, Hrudey SE, Pang XL. Wastewater surveillance monitoring of SARS-CoV-2 variants of concern and dynamics of transmission and community burden of COVID-19. Emerg Microbes Infect 2023; 12:2233638. [PMID: 37409382 PMCID: PMC10408568 DOI: 10.1080/22221751.2023.2233638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 06/04/2023] [Accepted: 07/01/2023] [Indexed: 07/07/2023]
Abstract
Wastewater-based surveillance is a valuable approach for monitoring COVID-19 at community level. Monitoring SARS-CoV-2 variants of concern (VOC) in wastewater has become increasingly relevant when clinical testing capacity and case-based surveillance are limited. In this study, we ascertained the turnover of six VOC in Alberta wastewater from May 2020 to May 2022. Wastewater samples from nine wastewater treatment plants across Alberta were analysed using VOC-specific RT-qPCR assays. The performance of the RT-qPCR assays in identifying VOC in wastewater was evaluated against next generation sequencing. The relative abundance of each VOC in wastewater was compared to positivity rate in COVID-19 testing. VOC-specific RT-qPCR assays performed comparatively well against next generation sequencing; concordance rates ranged from 89% to 98% for detection of Alpha, Beta, Gamma, Omicron BA.1 and Omicron BA.2, with a slightly lower rate of 85% for Delta (p < 0.01). Elevated relative abundance of Alpha, Delta, Omicron BA.1 and BA.2 were each associated with increased COVID-19 positivity rate. Alpha, Delta and Omicron BA.2 reached 90% relative abundance in wastewater within 80, 111 and 62 days after their initial detection, respectively. Omicron BA.1 increased more rapidly, reaching a 90% relative abundance in wastewater after 35 days. Our results from VOC surveillance in wastewater correspond with clinical observations that Omicron is the VOC with highest disease burden over the shortest period in Alberta to date. The findings suggest that changes in relative abundance of a VOC in wastewater can be used as a supplementary indicator to track and perhaps predict COVID-19 burden in a population.
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Affiliation(s)
- Maria E. Hasing
- Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Bonita E. Lee
- Department of Paediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Tiejun Gao
- Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Qiaozhi Li
- School of Public Health, University of Alberta, Edmonton, Alberta, Canada
| | - Yuanyuan Qiu
- Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Erik Ellehoj
- Ellehoj Redmond Consulting, Edmonton, Alberta, Canada
| | - Tyson E. Graber
- Children’s Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
| | - Meghan Fuzzen
- Department of Biology, University of Waterloo, Waterloo, Ontario, Canada
| | - Mark Servos
- Department of Biology, University of Waterloo, Waterloo, Ontario, Canada
| | - Chrystal Landgraff
- Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, Ontario, Canada
| | - Graham Tipples
- Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
- Public Health Laboratory, Alberta Precision Laboratories, Edmonton, Alberta, Canada
| | - Nathan Zelyas
- Public Health Laboratory, Alberta Precision Laboratories, Edmonton, Alberta, Canada
| | - Deena Hinshaw
- Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | | | - Christopher Sikora
- Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Michael Parkins
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
| | - Casey R. J. Hubert
- Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada
| | - Kevin Frankowski
- Advancing Canadian Water Assets, University of Calgary, Calgary, Alberta, Canada
| | - Steve E. Hrudey
- Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Xiaoli L. Pang
- Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
- Public Health Laboratory, Alberta Precision Laboratories, Edmonton, Alberta, Canada
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9
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Barnes KG, Levy JI, Gauld J, Rigby J, Kanjerwa O, Uzzell CB, Chilupsya C, Anscombe C, Tomkins-Tinch C, Mbeti O, Cairns E, Thole H, McSweeney S, Chibwana MG, Ashton PM, Jere KC, Meschke JS, Diggle P, Cornick J, Chilima B, Jambo K, Andersen KG, Kawalazira G, Paterson S, Nyirenda TS, Feasey N. Utilizing river and wastewater as a SARS-CoV-2 surveillance tool in settings with limited formal sewage systems. Nat Commun 2023; 14:7883. [PMID: 38036496 PMCID: PMC10689440 DOI: 10.1038/s41467-023-43047-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 10/30/2023] [Indexed: 12/02/2023] Open
Abstract
The COVID-19 pandemic has profoundly impacted health systems globally and robust surveillance has been critical for pandemic control, however not all countries can currently sustain community pathogen surveillance programs. Wastewater surveillance has proven valuable in high-income settings, but less is known about the utility of water surveillance of pathogens in low-income countries. Here we show how wastewater surveillance of SAR-CoV-2 can be used to identify temporal changes and help determine circulating variants quickly. In Malawi, a country with limited community-based COVID-19 testing capacity, we explore the utility of rivers and wastewater for SARS-CoV-2 surveillance. From May 2020-May 2022, we collect water from up to 112 river or defunct wastewater treatment plant sites, detecting SARS-CoV-2 in 8.3% of samples. Peak SARS-CoV-2 detection in water samples predate peaks in clinical cases. Sequencing of water samples identified the Beta, Delta, and Omicron variants, with Delta and Omicron detected well in advance of detection in patients. Our work highlights how wastewater can be used to detect emerging waves, identify variants of concern, and provide an early warning system in settings with no formal sewage systems.
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Affiliation(s)
- Kayla G Barnes
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi.
- Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Vector Biology and Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, UK.
| | - Joshua I Levy
- Department of Vector Biology and Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, UK
| | - Jillian Gauld
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Jonathan Rigby
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Oscar Kanjerwa
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Christopher B Uzzell
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK
| | - Chisomo Chilupsya
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Catherine Anscombe
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Christopher Tomkins-Tinch
- Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, MA, USA
- Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Omar Mbeti
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | | | - Herbert Thole
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Shannon McSweeney
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Marah G Chibwana
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Philip M Ashton
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Blantyre District Health Office, Blantyre, Malawi
| | - Khuzwayo C Jere
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Blantyre District Health Office, Blantyre, Malawi
- Department of Clinical Infection, Microbiology and Immunology, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - John Scott Meschke
- NIHR Health Protection Research Unit in Gastrointestinal Infections, University of Liverpool, Liverpool, UK
| | - Peter Diggle
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, USA
| | - Jennifer Cornick
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Blantyre District Health Office, Blantyre, Malawi
| | - Benjamin Chilima
- CHICAS, Lancaster Medical School, Lancaster University, Lancaster, UK
| | - Kondwani Jambo
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
- Public Health Institute of Malawi, Lilongwe, Malawi
| | - Kristian G Andersen
- Department of Vector Biology and Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, UK
- Scripps Research Translational Institute, La Jolla, CA, USA
| | - Gift Kawalazira
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | | | - Tonney S Nyirenda
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Nicholas Feasey
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
- School of Medicine, University of St Andrews, St Andrews, UK
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10
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Sanchez Jimenez B, Sterling T, Brown A, Modica B, Gibson K, Collins H, Koch C, Schwarz T, Dye KN. Wastewater surveillance in the COVID-19 post-emergency pandemic period: A promising approach to monitor and predict SARS-CoV-2 surges and evolution. Heliyon 2023; 9:e22356. [PMID: 38045160 PMCID: PMC10689941 DOI: 10.1016/j.heliyon.2023.e22356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 09/17/2023] [Accepted: 11/10/2023] [Indexed: 12/05/2023] Open
Abstract
On May 24, 2023, approximately 3.5 years into the pandemic, the World Health Organization (WHO) declared the end of the COVID-19 global health emergency. However, as there are still ∼3000 COVID-19 deaths per day in May 2023, robust surveillance systems are still warranted to return to normalcy in times of low risk and respond appropriately in times of high risk. The different phases of the pandemic have been defined by infection numbers and variants, both of which have been determined through clinical tests that are subject to many biases. Unfortunately, the end of the COVID-19 emergency threatens to exasperate these biases, thereby warranting alternative tracking methods. We hypothesized that wastewater surveillance could be used as a more accurate and comprehensive method to track SARS-CoV-2 in the post-emergency pandemic period (PEPP). SARS-CoV-2 was quantified and sequenced from wastewater between June 2022 and March 2023 to research the anticipated 2022/23 winter surge. However, in the 2022/23 winter, there was lower-than-expected SARS-CoV-2 circulation, which was hypothesized to be due to diagnostic testing biases but was confirmed by our wastewater analysis, thereby emphasizing the unpredictable nature of SARS-CoV-2 surges while also questioning its winter seasonality. Even in times of low baseline circulation, we found wastewater surveillance to be sensitive enough to detect minor changes in circulation levels ∼30-46 days prior to diagnostic tests, suggesting that wastewater surveillance may be a more appropriate early warning system to prepare for unpredictable surges in the PEPP. Furthermore, sequencing of wastewater detected variants of concern that were positively correlated with clinical samples and also provided a method to identify mutations with a high likelihood of appearing in future variants, necessary for updating vaccines and therapeutics prior to novel variant circulation. Together, these data highlight the effectiveness of wastewater surveillance in the PEPP to limit the global health burden of SARS-CoV-2 due to increases in circulation and/or viral evolution.
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Affiliation(s)
| | - Trinity Sterling
- Department of Health Sciences, Stetson University, DeLand, FL, 32723, USA
| | - Austin Brown
- Department of Health Sciences, Stetson University, DeLand, FL, 32723, USA
| | - Brian Modica
- Department of Health Sciences, Stetson University, DeLand, FL, 32723, USA
| | - Kaylee Gibson
- Department of Health Sciences, Stetson University, DeLand, FL, 32723, USA
| | - Hannah Collins
- Department of Health Sciences, Stetson University, DeLand, FL, 32723, USA
| | - Carolyn Koch
- Department of Health Sciences, Stetson University, DeLand, FL, 32723, USA
| | - Tyler Schwarz
- Department of Health Sciences, Stetson University, DeLand, FL, 32723, USA
| | - Kristine N. Dye
- Department of Health Sciences, Stetson University, DeLand, FL, 32723, USA
- Department of Biology, Stetson University, DeLand, FL, 32723, USA
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11
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Nimsamer P, Sawaswong V, Klomkliew P, Kaewsapsak P, Puenpa J, Poovorawan Y, Payungporn S. "Nano COVID-19": Nanopore sequencing of spike gene to identify SARS-CoV-2 variants of concern. Exp Biol Med (Maywood) 2023; 248:1841-1849. [PMID: 37702217 DOI: 10.1177/15353702231190931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/14/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) is a worldwide pandemic infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). World Health Organization (WHO) has defined the viral variants of concern (VOC) which cause more severe disease, higher transmissibility, and reduced vaccine efficacy. In this study, the "Nano COVID-19" workflow based on Oxford nanopore sequencing of the full-length spike gene combined with flexible data analysis options was developed to identify SARS-CoV-2 VOCs. The primers were designed to cover the full-length spike gene and can amplify all VOC strains. The results of VOC identification based on phylogenetic analysis of the full-length spike gene were comparable to the whole genome sequencing (WGS). Compared to the standard VOC identification pipeline, the fast analysis based on Read Assignment, Mapping, and Phylogenetic Analysis in Real Time (RAMPART) and the user-friendly method based on EPI2ME yielded 89.3% and 97.3% accuracy, respectively. The EPI2ME pipeline is recommended for researchers without bioinformatic skills, whereas RAMPART is more suitable for bioinformaticians. This workflow provides a cost-effective, simplified pipeline with a rapid turnaround time. Furthermore, it is portable to point-of-care SARS-CoV-2 VOC identification and compatible with large-scale analysis. Therefore, "Nano COVID-19" is an alternative viral epidemic screening and transmission tracking workflow.
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Affiliation(s)
- Pattaraporn Nimsamer
- Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
- Division of Medical Bioinformatics, Research Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Long-Read Lab (Si-LoL), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Vorthon Sawaswong
- Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Pavit Klomkliew
- Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Pornchai Kaewsapsak
- Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
- Department of Biochemistry, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Jiratchaya Puenpa
- Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Yong Poovorawan
- Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Sunchai Payungporn
- Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
- Department of Biochemistry, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
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12
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Phan T, Brozak S, Pell B, Oghuan J, Gitter A, Hu T, Ribeiro RM, Ke R, Mena KD, Perelson AS, Kuang Y, Wu F. Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks. Water Res 2023; 243:120372. [PMID: 37494742 DOI: 10.1016/j.watres.2023.120372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 07/10/2023] [Accepted: 07/15/2023] [Indexed: 07/28/2023]
Abstract
Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health.
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Affiliation(s)
- Tin Phan
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Samantha Brozak
- School of Mathematical and Statistical Sciences, Arizona State University, AZ 85281, USA
| | - Bruce Pell
- Department of Mathematics and Computer Science, Lawrence Technological University, MI 48075, USA
| | - Jeremiah Oghuan
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Anna Gitter
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Tao Hu
- Department of Geography, Oklahoma State University, Stillwater, OK 74078, USA
| | - Ruy M Ribeiro
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Ruian Ke
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA
| | - Kristina D Mena
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Texas Epidemic Public Health Institute, Houston, TX 77030, USA
| | - Alan S Perelson
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, NM 87544, USA; Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Yang Kuang
- School of Mathematical and Statistical Sciences, Arizona State University, AZ 85281, USA
| | - Fuqing Wu
- School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Texas Epidemic Public Health Institute, Houston, TX 77030, USA.
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13
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Liddor Naim M, Fu Y, Shagan M, Bar-Or I, Marks R, Sun Q, Granek R, Kushmaro A. The Rise and Fall of Omicron BA.1 Variant as Seen in Wastewater Supports Epidemiological Model Predictions. Viruses 2023; 15:1862. [PMID: 37766269 PMCID: PMC10536904 DOI: 10.3390/v15091862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/20/2023] [Accepted: 08/30/2023] [Indexed: 09/29/2023] Open
Abstract
The COVID-19 pandemic caused by the SARS-CoV-2 virus has inflicted significant mortality and morbidity worldwide. Continuous virus mutations have led to the emergence of new variants. The Omicron BA.1 sub-lineage prevailed as the dominant variant globally at the beginning of 2022 but was subsequently replaced by BA.2 in numerous countries. Wastewater-based epidemiology (WBE) offers an efficient tool for capturing viral shedding from infected individuals, enabling early detection of potential pandemic outbreaks without relying solely on community cooperation and clinical testing resources. This study integrated RT-qPCR assays for detecting general SARS-CoV-2 and its variants levels in wastewater into a modified triple susceptible-infected-recovered-susceptible (SIRS) model. The emergence of the Omicron BA.1 variant was observed, replacing the presence of its predecessor, the Delta variant. Comparative analysis between the wastewater data and the modified SIRS model effectively described the BA.1 and subsequent BA.2 waves, with the decline of the Delta variant aligning with its diminished presence below the detection threshold in wastewater. This study demonstrates the potential of WBE as a valuable tool for future pandemics. Furthermore, by analyzing the sensitivity of different variants to model parameters, we are able to deduce real-life values of cross-variant immunity probabilities, emphasizing the asymmetry in their strength.
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Affiliation(s)
- Michal Liddor Naim
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Yu Fu
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
- Key Laboratory of Bio-Resources and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610064, China
| | - Marilou Shagan
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Itay Bar-Or
- Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan 5262000, Israel
| | - Robert Marks
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
- The Ilse Katz Center for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Qun Sun
- Key Laboratory of Bio-Resources and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610064, China
| | - Rony Granek
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
- The Ilse Katz Center for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Ariel Kushmaro
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
- The Ilse Katz Center for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
- School of Sustainability and Climate Change, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
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14
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Fuzzen M, Harper NBJ, Dhiyebi HA, Srikanthan N, Hayat S, Bragg LM, Peterson SW, Yang I, Sun JX, Edwards EA, Giesy JP, Mangat CS, Graber TE, Delatolla R, Servos MR. An improved method for determining frequency of multiple variants of SARS-CoV-2 in wastewater using qPCR assays. Sci Total Environ 2023; 881:163292. [PMID: 37030387 PMCID: PMC10079313 DOI: 10.1016/j.scitotenv.2023.163292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/17/2023] [Accepted: 03/31/2023] [Indexed: 06/01/2023]
Abstract
Wastewater-based surveillance has become an effective tool around the globe for indirect monitoring of COVID-19 in communities. Variants of Concern (VOCs) have been detected in wastewater by use of reverse transcription polymerase chain reaction (RT-PCR) or whole genome sequencing (WGS). Rapid, reliable RT-PCR assays continue to be needed to determine the relative frequencies of VOCs and sub-lineages in wastewater-based surveillance programs. The presence of multiple mutations in a single region of the N-gene allowed for the design of a single amplicon, multiple probe assay, that can distinguish among several VOCs in wastewater RNA extracts. This approach which multiplexes probes designed to target mutations associated with specific VOC's along with an intra-amplicon universal probe (non-mutated region) was validated in singleplex and multiplex. The prevalence of each mutation (i.e. VOC) is estimated by comparing the abundance of the targeted mutation with a non-mutated and highly conserved region within the same amplicon. This is advantageous for the accurate and rapid estimation of variant frequencies in wastewater. The N200 assay was applied to monitor frequencies of VOCs in wastewater extracts from several communities in Ontario, Canada in near real time from November 28, 2021 to January 4, 2022. This includes the period of the rapid replacement of the Delta variant with the introduction of the Omicron variant in these Ontario communities in early December 2021. The frequency estimates using this assay were highly reflective of clinical WGS estimates for the same communities. This style of qPCR assay, which simultaneously measures signal from a non-mutated comparator probe and multiple mutation-specific probes contained within a single qPCR amplicon, can be applied to future assay development for rapid and accurate estimations of variant frequencies.
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Affiliation(s)
- Meghan Fuzzen
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
| | | | - Hadi A Dhiyebi
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Nivetha Srikanthan
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Samina Hayat
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Leslie M Bragg
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Shelley W Peterson
- One-Health Division, Wastewater Surveillance Unit, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3M4, Canada
| | - Ivy Yang
- Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON M5S 3E5, Canada
| | - J X Sun
- Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON M5S 3E5, Canada
| | - Elizabeth A Edwards
- Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON M5S 3E5, Canada
| | - John P Giesy
- Department of Veterinary Biomedical Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, SK S7N 5B3, Canada; Department of Environmental Sciences, Baylor University, Waco, TX, USA; Department of Zoology and Center for Integrative Toxicology, Michigan State University, East Lansing, MI, USA
| | - Chand S Mangat
- One-Health Division, Wastewater Surveillance Unit, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3M4, Canada
| | - Tyson E Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario K1H 8L1, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
| | - Mark R Servos
- Department of Biology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
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15
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Férez JA, Cuevas-Ferrando E, Ayala-San Nicolás M, Simón Andreu PJ, López R, Truchado P, Sánchez G, Allende A. Wastewater-Based Epidemiology to Describe the Evolution of SARS-CoV-2 in the South-East of Spain, and Application of Phylogenetic Analysis and a Machine Learning Approach. Viruses 2023; 15:1499. [PMID: 37515186 PMCID: PMC10386001 DOI: 10.3390/v15071499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 06/28/2023] [Accepted: 06/28/2023] [Indexed: 07/30/2023] Open
Abstract
The COVID-19 pandemic has posed a significant global threat, leading to several initiatives for its control and management. One such initiative involves wastewater-based epidemiology, which has gained attention for its potential to provide early warning of virus outbreaks and real-time information on its spread. In this study, wastewater samples from two wastewater treatment plants (WWTPs) located in the southeast of Spain (region of Murcia), namely Murcia, and Cartagena, were analyzed using RT-qPCR and high-throughput sequencing techniques to describe the evolution of SARS-CoV-2 in the South-East of Spain. Additionally, phylogenetic analysis and machine learning approaches were applied to develop a pre-screening tool for the identification of differences among the variant composition of different wastewater samples. The results confirmed that the levels of SARS-CoV-2 in these wastewater samples changed concerning the number of SARS-CoV-2 cases detected in the population, and variant occurrences were in line with clinical reported data. The sequence analyses helped to describe how the different SARS-CoV-2 variants have been replaced over time. Additionally, the phylogenetic analysis showed that samples obtained at close sampling times exhibited a higher similarity than those obtained more distantly in time. A second analysis using a machine learning approach based on the mutations found in the SARS-CoV-2 spike protein was also conducted. Hierarchical clustering (HC) was used as an efficient unsupervised approach for data analysis. Results indicated that samples obtained in October 2022 in Murcia and Cartagena were significantly different, which corresponded well with the different virus variants circulating in the two locations. The proposed methods in this study are adequate for comparing consensus sequence types of the SARS-CoV-2 sequences as a preliminary evaluation of potential changes in the variants that are circulating in a given population at a specific time point.
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Affiliation(s)
- Jose A Férez
- Research Group on Microbiology and Quality of Fruit and Vegetables, CEBAS-CSIC, 30100 Murcia, Spain
| | - Enric Cuevas-Ferrando
- Environmental Virology and Food Safety Lab (VISAFELab), Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, 46980 Valencia, Spain
| | - María Ayala-San Nicolás
- Research Group on Microbiology and Quality of Fruit and Vegetables, CEBAS-CSIC, 30100 Murcia, Spain
| | - Pedro J Simón Andreu
- Entidad Regional de Saneamiento y Depuración de Murcia (ESAMUR), Avda. Juan Carlos I, s/n. Ed. Torre Jemeca, 30009 Murcia, Spain
| | - Román López
- Entidad Regional de Saneamiento y Depuración de Murcia (ESAMUR), Avda. Juan Carlos I, s/n. Ed. Torre Jemeca, 30009 Murcia, Spain
| | - Pilar Truchado
- Research Group on Microbiology and Quality of Fruit and Vegetables, CEBAS-CSIC, 30100 Murcia, Spain
| | - Gloria Sánchez
- Environmental Virology and Food Safety Lab (VISAFELab), Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, 46980 Valencia, Spain
| | - Ana Allende
- Research Group on Microbiology and Quality of Fruit and Vegetables, CEBAS-CSIC, 30100 Murcia, Spain
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16
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Chua FJD, Kim SY, Hill E, Cai JW, Lee WL, Gu X, Afri Affandi SA, Kwok WCG, Ng W, Leifels M, Armas F, Chandra F, Chen H, Alm EJ, Tay M, Wong CCJ, Ng LC, Wuertz S, Thompson JR. Co-incidence of BA.1 and BA.2 at the start of Singapore's Omicron wave revealed by Community and University Campus wastewater surveillance. Sci Total Environ 2023; 875:162611. [PMID: 36871716 DOI: 10.1016/j.scitotenv.2023.162611] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 02/28/2023] [Accepted: 02/28/2023] [Indexed: 06/18/2023]
Abstract
Wastewater surveillance (WWS) has been globally recognised to be a useful tool in quantifying SARS-CoV-2 RNA at the community and residential levels without biases associated with case-reporting. The emergence of variants of concern (VOCs) have given rise to an unprecedented number of infections even though populations are increasingly vaccinated. This is because VOCs have been reported to possess higher transmissibility and can evade host immune responses. The B.1.1.529 lineage (Omicron) has severely disrupted global plans to return to normalcy. In this study, we developed an allele-specific (AS) RT-qPCR assay which simultaneously targets the stretch of deletions and mutations in the spike protein from position 24-27 for quantitative detection of Omicron BA.2. Together with previous assays that detect mutations associated with Omicron BA.1 (deletion at position 69 and 70) and all Omicron (mutation at position 493 and 498), we report the validation and time series of these assays from September 2021 to May 2022 using influent samples from two wastewater treatment plants and across four University campus sites in Singapore. Viral RNA concentrations at the treatment plants corroborate with locally reported clinical cases, AS RT-qPCR assays revealed co-incidence of Omicron BA.1 and BA.2 on 12 January 2022, almost two months after initial BA.1 detection in South Africa and Botswana. BA.2 became the dominant variant by the end of January 2022 and completely displaced BA.1 by mid-March 2022. University campus sites were similarly positive for BA.1 and/or BA.2 in the same week as first detection at the treatment plants, where BA.2 became rapidly established as the dominant lineage within three weeks. These results corroborate clinical incidence of the Omicron lineages in Singapore and indicate minimal silent circulation prior to January 2022. The subsequent simultaneous spread of both variant lineages followed strategic relaxation of safe management measures upon meeting nationwide vaccination goals.
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Affiliation(s)
- Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Se Yeon Kim
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Eric Hill
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Jia Wei Cai
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Wei Lin Lee
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore
| | - Xiaoqiong Gu
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore
| | - Siti Aisyah Afri Affandi
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Wee Chiew Germaine Kwok
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Weijie Ng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore
| | - Federica Armas
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore
| | - Franciscus Chandra
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore
| | - Hongjie Chen
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore
| | - Eric J Alm
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore; Centre for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Martin Tay
- Environmental Health Institute, National Environmental Agency, 138667, Singapore
| | | | - Lee Ching Ng
- Environmental Health Institute, National Environmental Agency, 138667, Singapore; School of Biological Sciences, Nanyang Technological University, 637551, Singapore
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore; School of Civil and Environmental Engineering, Nanyang Technological University, 639798, Singapore
| | - Janelle R Thompson
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, 637551, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), 138602, Singapore; Asian School of the Environment, Nanyang Technological University, 637459, Singapore.
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17
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Shipulin GA, Savochkina Y, Shuryaeva AK, Glushchenko EE, Luparev AR, Polyakova VA, Danilov DI, Davydova EE, Vinogradov KS, Stetsenko IF, Aiginin AA, Matsvay AD, Kolbutova KB, Bogdan SA, Vashukova MA, Yudin SM. Development and application of an RT‒PCR assay for the identification of the delta and omicron variants of SARS-COV-2. Heliyon 2023; 9:e16917. [PMID: 37287602 PMCID: PMC10234363 DOI: 10.1016/j.heliyon.2023.e16917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 04/04/2023] [Accepted: 06/01/2023] [Indexed: 06/09/2023] Open
Abstract
The emergence of mutations in the coronavirus genome provides opportunities for occurrence new strains with higher transmissibility, severity and duration of the disease poses. In 2020, a new variant of the coronavirus SARS-COV-2 - Delta was identified in India. This genetic variant has spread rapidly and became dominant in many countries, including Russia. In November 2021, a new outbreak of COVID-19 occurred in Africa driven by a variant SARS-COV-2 named later Omicron. Both variants had increased transmissibility compared to previously encountered variants and quickly, replacing its around the world. To promptly monitor the epidemiological situation in the country, to assess the spread of dominant genetic variants of the virus and to take appropriate measures, we have developed an RT‒PCR reagent kit for the identification of Delta and Omicron by detecting a corresponding combination of major mutations. The minimum set of mutations was chosen which allows to differentiate Delta and Omicron variants, in order to increase the analysis productivity and reduce costs. Primers and LNA-modified probes were selected to detect mutations in the S gene, typical for the Delta and Omicron. Similar approach can be implemented for the rapid development of assays for differentiating important SARS-COV-2 variants or for other viruses genotyping for epidemiological surveillance or for diagnostic use in order to assist in making clinical decisions. It was demonstrated that the results of VOC Delta and Omicron detection and their typical mutations were concordant with genotyping based on WGS results for all 847 samples of SARS-CoV-2 RNA. The kit has high analytical sensitivity (1х103 copies/mL of SARS-CoV-2 RNA) for each of the detected genetic variants and possesses 100% analytic specificity for microorganism panel testing. The diagnostic sensitivity (95% confidence interval) obtained during pivotal trials was 91.1-100% for Omicron and 91.3-100% for Delta, while the diagnostic specificity with a 95% confidence interval was 92.2-100%. The use of a set of reagents in combination with sequencing of SARS-CoV-2 RNA as part of epidemiological monitoring made it possible to quickly track the dynamics of changes in Delta and Omicron prevalence in the Moscow region in the period from December 2021 to July 2022.
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Affiliation(s)
- G A Shipulin
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - YuA Savochkina
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - A K Shuryaeva
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - E E Glushchenko
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - A R Luparev
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - V A Polyakova
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - D I Danilov
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - E E Davydova
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - K S Vinogradov
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - I F Stetsenko
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - A A Aiginin
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - A D Matsvay
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
| | - K B Kolbutova
- Chief Federal State Budgetary Healthcare Institution "Centre of Hygiene and Epidemiology" of the Federal Medical Biological Agency, Moscow, Russia
| | - S A Bogdan
- Chief Federal State Budgetary Healthcare Institution "Centre of Hygiene and Epidemiology" of the Federal Medical Biological Agency, Moscow, Russia
| | - M A Vashukova
- Clinical Infectious Diseases Hospital Named After S.P. Botkin, St. Petersburg, Russia
| | - S M Yudin
- Federal State Budgetary Institution "Centre for Strategic Planning and Management of Biomedical Health Risks" of the Federal Medical Biological Agency, Moscow, Russia
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18
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Polcz P, Tornai K, Juhász J, Cserey G, Surján G, Pándics T, Róka E, Vargha M, Reguly IZ, Csikász-Nagy A, Pongor S, Szederkényi G. Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants. Water Res 2023; 241:120098. [PMID: 37295226 DOI: 10.1016/j.watres.2023.120098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/16/2023] [Accepted: 05/17/2023] [Indexed: 06/12/2023]
Abstract
(MOTIVATION) Wastewater-based epidemiology (WBE) has emerged as a promising approach for monitoring the COVID-19 pandemic, since the measurement process is cost-effective and is exposed to fewer potential errors compared to other indicators like hospitalization data or the number of detected cases. Consequently, WBE was gradually becoming a key tool for epidemic surveillance and often the most reliable data source, as the intensity of clinical testing for COVID-19 drastically decreased by the third year of the pandemic. Recent results suggests that the model-based fusion of wastewater measurements with clinical data and other indicators is essential in future epidemic surveillance. (METHOD) In this work, we developed a wastewater-based compartmental epidemic model with a two-phase vaccination dynamics and immune evasion. We proposed a multi-step optimization-based data assimilation method for epidemic state reconstruction, parameter estimation, and prediction. The computations make use of the measured viral load in wastewater, the available clinical data (hospital occupancy, delivered vaccine doses, and deaths), the stringency index of the official social distancing rules, and other measures. The current state assessment and the estimation of the current transmission rate and immunity loss allow a plausible prediction of the future progression of the pandemic. (RESULTS) Qualitative and quantitative evaluations revealed that the contribution of wastewater data in our computational epidemiological framework makes predictions more reliable. Predictions suggest that at least half of the Hungarian population has lost immunity during the epidemic outbreak caused by the BA.1 and BA.2 subvariants of Omicron in the first half of 2022. We obtained a similar result for the outbreaks caused by the subvariant BA.5 in the second half of 2022. (APPLICABILITY) The proposed approach has been used to support COVID management in Hungary and could be customized for other countries as well.
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Affiliation(s)
- Péter Polcz
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary.
| | - Kálmán Tornai
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
| | - János Juhász
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary; Institute of Medical Microbiology, Semmelweis University, Üllői út 26, Budapest, H-1085, Hungary
| | - György Cserey
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
| | - György Surján
- Department of Public Health Laboratory, National Public Health Centre, Albert Flórián út 2-6, Budapest, H-1097, Hungary; Department of Digital Health Sciences, Semmelweis University, Üllői út 26, Budapest, H-1085, Hungary
| | - Tamás Pándics
- Department of Public Health Laboratory, National Public Health Centre, Albert Flórián út 2-6, Budapest, H-1097, Hungary; Department of Public Health Sciences, Faculty of Health Sciences, Semmelweis University, Vas utca 17, Budapest, H-1088, Hungary
| | - Eszter Róka
- Department of Public Health Laboratory, National Public Health Centre, Albert Flórián út 2-6, Budapest, H-1097, Hungary
| | - Márta Vargha
- Department of Public Health Laboratory, National Public Health Centre, Albert Flórián út 2-6, Budapest, H-1097, Hungary
| | - István Z Reguly
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
| | - Attila Csikász-Nagy
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
| | - Sándor Pongor
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
| | - Gábor Szederkényi
- National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary
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19
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Yang K, Guo J, Møhlenberg M, Zhou H. SARS-CoV-2 surveillance in medical and industrial wastewater-a global perspective: a narrative review. Environ Sci Pollut Res Int 2023; 30:63323-63334. [PMID: 36988799 PMCID: PMC10049894 DOI: 10.1007/s11356-023-26571-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 03/16/2023] [Indexed: 05/11/2023]
Abstract
The novel coronavirus SARS-CoV-2 has spread at an unprecedented rate since late 2019, leading to the global COVID-19 pandemic. During the pandemic, being able to detect SARS-CoV-2 in human populations with high coverage quickly is a huge challenge. As SARS-CoV-2 is excreted in human excreta and thus exposed to the aqueous environment through sewers, the goal is to develop an ideal, non-invasive, cost-effective epidemiological method for detecting SARS-CoV-2. Wastewater surveillance has gained widespread interest and is increasingly being investigated as an effective early warning tool for monitoring the spread and evolution of the virus. This review emphasizes important findings on SARS-CoV-2 wastewater-based epidemiology (WBE) in different continents and techniques used to detect SARS-CoV-2 in wastewater during the period 2020-2022. The results show that WBE is a valuable population-level method for monitoring SARS-CoV-2 and is a valuable early warning alert. It can assist policymakers in formulating relevant policies to avoid the negative impacts of early or delayed action. Such strategy can also help avoid unnecessary wastage of medical resources, rationalize vaccine distribution, assist early detection, and contain large-scale outbreaks.
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Affiliation(s)
- Kaiwen Yang
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Liutai Road 1166, Wenjiang, Chengdu, 610000, China
| | - Jinlin Guo
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Liutai Road 1166, Wenjiang, Chengdu, 610000, China
| | - Michelle Møhlenberg
- Department of Biomedicine, Høegh-Guldbergs Gade 10, Building 1115, DK-8000, Aarhus C, Denmark
| | - Hao Zhou
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Liutai Road 1166, Wenjiang, Chengdu, 610000, China.
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20
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Barnes K, Levy J, Andersen K, Gauld J, Rigby J, Kanjerwa O, Uzzell C, Chilupsya C, Anscombe C, Tomkins-Tinch C, Mbeti O, Cairns E, Thole H, McSweeney S, Chibwana M, Ashton P, Jere K, Meschke J, Diggle P, Cornick J, Jambo K, Kawalazira G, Paterson S, Nyirenda T, Feasey N, Chilima B. Utilizing river and wastewater as a SARS-CoV-2 surveillance tool to predict trends and identify variants of concern in settings with limited formal sewage systems. Res Sq 2023:rs.3.rs-2801767. [PMID: 37090541 PMCID: PMC10120776 DOI: 10.21203/rs.3.rs-2801767/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
The COVID-19 pandemic continues to impact health systems globally and robust surveillance is critical for pandemic control, however not all countries can sustain community surveillance programs. Wastewater surveillance has proven valuable in high-income settings, but little is known about how river and informal sewage in low-income countries can be used for environmental surveillance of SARS-CoV-2. In Malawi, a country with limited community-based COVID-19 testing capacity, we explored the utility of rivers and wastewater for SARS-CoV-2 surveillance. From May 2020 - January 2022, we collected water from up to 112 river or informal sewage sites/month, detecting SARS-CoV-2 in 8.3% of samples. Peak SARS-CoV-2 detection in water samples predated peaks in clinical cases. Sequencing of water samples identified the Beta, Delta, and Omicron variants, with Delta and Omicron detected well in advance of detection in patients. Our work highlights wastewater can be used for detecting emerging waves, identifying variants of concern and function as an early warning system in settings with no formal sewage systems.
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Affiliation(s)
| | | | - Kristian Andersen
- Department of Immunology and Microbiology The Scripps Research Institute La Jolla CA USA
| | - Jillian Gauld
- Institute for Disease Modeling, Bill & Melinda Gates Foundation
| | - Jonathan Rigby
- Department of Clinical Sciences, Liverpool School of Tropical Medicine
| | - Oscar Kanjerwa
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | | | - Chisomo Chilupsya
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | | | | | | | - Edward Cairns
- Department of Evolution, Ecology and Behaviour, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool
| | - Herbert Thole
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences
| | - Shannon McSweeney
- Department of Clinical Sciences, Liverpool School of Tropical Medicine
| | - Marah Chibwana
- Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences
| | | | | | | | | | - Jennifer Cornick
- Department of Evolution, Ecology and Behaviour, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool
| | | | | | | | - Tonney Nyirenda
- Department of Pathology, Kamuzu University of Health Sciences
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21
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Pell B, Brozak S, Phan T, Wu F, Kuang Y. The emergence of a virus variant: dynamics of a competition model with cross-immunity time-delay validated by wastewater surveillance data for COVID-19. J Math Biol 2023; 86:63. [PMID: 36988621 PMCID: PMC10054223 DOI: 10.1007/s00285-023-01900-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 12/28/2022] [Accepted: 03/12/2023] [Indexed: 03/30/2023]
Abstract
We consider the dynamics of a virus spreading through a population that produces a mutant strain with the ability to infect individuals that were infected with the established strain. Temporary cross-immunity is included using a time delay, but is found to be a harmless delay. We provide some sufficient conditions that guarantee local and global asymptotic stability of the disease-free equilibrium and the two boundary equilibria when the two strains outcompete one another. It is shown that, due to the immune evasion of the emerging strain, the reproduction number of the emerging strain must be significantly lower than that of the established strain for the local stability of the established-strain-only boundary equilibrium. To analyze the unique coexistence equilibrium we apply a quasi steady-state argument to reduce the full model to a two-dimensional one that exhibits a global asymptotically stable established-strain-only equilibrium or global asymptotically stable coexistence equilibrium. Our results indicate that the basic reproduction numbers of both strains govern the overall dynamics, but in nontrivial ways due to the inclusion of cross-immunity. The model is applied to study the emergence of the SARS-CoV-2 Delta variant in the presence of the Alpha variant using wastewater surveillance data from the Deer Island Treatment Plant in Massachusetts, USA.
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Affiliation(s)
- Bruce Pell
- Mathematics and Computer Science Department, Lawrence Technological University, 21000 W. 10 Mile Rd, Southfield, MI, 48075, USA.
| | - Samantha Brozak
- School of Mathematical and Statistical Sciences, Arizona State University, 901 S. Palm Walk, Tempe, AZ, 85287-1804, USA
| | - Tin Phan
- Theoretical Biology and Biophysics Group, Houston, Los Alamos, NM, 87545, USA
| | - Fuqing Wu
- Texas Epidemic Public Health Institute, Houston, TX, 77030, USA
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, 77030, USA
| | - Yang Kuang
- School of Mathematical and Statistical Sciences, Arizona State University, 901 S. Palm Walk, Tempe, AZ, 85287-1804, USA
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22
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Sangsanont J, Rattanakul S, Makkaew P, Precha N, Rukthanapitak P, Sresung M, Siri Y, Kitajima M, Takeda T, Haramoto E, Puenpa J, Wanlapakorn N, Poovorawan Y, Mongkolsuk S, Sirikanchana K. Wastewater monitoring in tourist cities as potential sentinel sites for near real-time dynamics of imported SARS-CoV-2 variants. Sci Total Environ 2023; 860:160317. [PMID: 36436629 PMCID: PMC9691270 DOI: 10.1016/j.scitotenv.2022.160317] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 10/29/2022] [Accepted: 11/16/2022] [Indexed: 05/05/2023]
Abstract
Wastewater-based epidemiology (WBE) complements the clinical surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants' distribution in populations. Many developed nations have established national and regional WBE systems; however, governance and budget constraints could be obstacles for low- and middle-income countries. An urgent need thus exists to identify hotspots to serve as sentinel sites for WBE. We hypothesized that representative wastewater treatment plants (WWTPs) in two international gateway cities, Bangkok and Phuket, Thailand, could be sentineled for SARS-CoV-2 and its variants to reflect the clinical distribution patterns at city level and serve as early indicators of new variants entering the country. Municipal wastewater samples (n = 132) were collected from eight representative municipal WWTPs in Bangkok and Phuket during 19 sampling events from October 2021 to March 2022, which were tested by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) using the US CDC N1 and N2 multiplex and variant (Alpha, Delta, and Omicron BA.1 and BA.2) singleplex assays. The variant detection ratios from Bangkok and Phuket followed similar trends to the national clinical testing data, and each variant's viral loads agreed with the daily new cases (3-d moving average). Omicron BA.1 was detected in Phuket wastewater prior to Bangkok, possibly due to Phuket's WWTPs serving tourist communities. We found that the Omicron BA.1 and BA.2 viral loads predominantly drove the SARS-CoV-2 resurgence. We also noted a shifting pattern in the Bangkok WBE from a 22-d early warning in early 2021 to a near real-time pattern in late 2021. The potential application of tourist hotspots for WBE to indicate the arrival of new variants and re-emerging or unprecedented infectious agents could support tourism-dependent economies by complementing the reduced clinical regulations while maintaining public health protection via wastewater surveillance.
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Affiliation(s)
- Jatuwat Sangsanont
- Department of Environmental Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand; Water Science and Technology for Sustainable Environmental Research Group, Chulalongkorn University, Bangkok 10330, Thailand
| | - Surapong Rattanakul
- Department of Environmental Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand
| | - Prasert Makkaew
- Department of Environmental Health and Technology, School of Public Health, Walailak University, Nakhon Si Thammarat 80160, Thailand; One Health Research Center, Walailak University, Nakhon Si Thammarat 80160, Thailand
| | - Nopadol Precha
- Department of Environmental Health and Technology, School of Public Health, Walailak University, Nakhon Si Thammarat 80160, Thailand; One Health Research Center, Walailak University, Nakhon Si Thammarat 80160, Thailand
| | - Pratchaya Rukthanapitak
- Department of Environmental Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Montakarn Sresung
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok 10210, Thailand
| | - Yadpiroon Siri
- Environmental, Safety Technology and Health Program, School of Public Health, Walailak University, Thaiburi, Thasala, Nakhon Si Thammarat 80160, Thailand
| | - Masaaki Kitajima
- Division of Environmental Engineering, Hokkaido University, Hokkaido 060-8628, Japan
| | - Tomoko Takeda
- Department of Earth and Planetary Science, The University of Tokyo, 113-0033, Japan
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, Yamanashi 400-8511, Japan
| | - Jiratchaya Puenpa
- Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Nasamon Wanlapakorn
- Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Yong Poovorawan
- Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Skorn Mongkolsuk
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok 10210, Thailand; Center of Excellence on Environmental Health and Toxicology (EHT), OPS, MHESI, Bangkok 10400, Thailand
| | - Kwanrawee Sirikanchana
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok 10210, Thailand; Center of Excellence on Environmental Health and Toxicology (EHT), OPS, MHESI, Bangkok 10400, Thailand.
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23
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Gitter A, Oghuan J, Godbole AR, Chavarria CA, Monserrat C, Hu T, Wang Y, Maresso AW, Hanson BM, Mena KD, Wu F. Not a waste: Wastewater surveillance to enhance public health. Front Chem Eng 2023. [DOI: 10.3389/fceng.2022.1112876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Domestic wastewater, when collected and evaluated appropriately, can provide valuable health-related information for a community. As a relatively unbiased and non-invasive approach, wastewater surveillance may complement current practices towards mitigating risks and protecting population health. Spurred by the COVID-19 pandemic, wastewater programs are now widely implemented to monitor viral infection trends in sewersheds and inform public health decision-making. This review summarizes recent developments in wastewater-based epidemiology for detecting and monitoring communicable infectious diseases, dissemination of antimicrobial resistance, and illicit drug consumption. Wastewater surveillance, a quickly advancing Frontier in environmental science, is becoming a new tool to enhance public health, improve disease prevention, and respond to future epidemics and pandemics.
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Leifels M, Khalilur Rahman O, Sam IC, Cheng D, Chua FJD, Nainani D, Kim SY, Ng WJ, Kwok WC, Sirikanchana K, Wuertz S, Thompson J, Chan YF. The one health perspective to improve environmental surveillance of zoonotic viruses: lessons from COVID-19 and outlook beyond. ISME Commun 2022; 2:107. [PMID: 36338866 PMCID: PMC9618154 DOI: 10.1038/s43705-022-00191-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 09/26/2022] [Accepted: 10/11/2022] [Indexed: 11/11/2022]
Abstract
The human population has doubled in the last 50 years from about 3.7 billion to approximately 7.8 billion. With this rapid expansion, more people live in close contact with wildlife, livestock, and pets, which in turn creates increasing opportunities for zoonotic diseases to pass between animals and people. At present an estimated 75% of all emerging virus-associated infectious diseases possess a zoonotic origin, and outbreaks of Zika, Ebola and COVID-19 in the past decade showed their huge disruptive potential on the global economy. Here, we describe how One Health inspired environmental surveillance campaigns have emerged as the preferred tools to monitor human-adjacent environments for known and yet to be discovered infectious diseases, and how they can complement classical clinical diagnostics. We highlight the importance of environmental factors concerning interactions between animals, pathogens and/or humans that drive the emergence of zoonoses, and the methodologies currently proposed to monitor them-the surveillance of wastewater, for example, was identified as one of the main tools to assess the spread of SARS-CoV-2 by public health professionals and policy makers during the COVID-19 pandemic. One-Health driven approaches that facilitate surveillance, thus harbour the potential of preparing humanity for future pandemics caused by aetiological agents with environmental reservoirs. Via the example of COVID-19 and other viral diseases, we propose that wastewater surveillance is a useful complement to clinical diagnosis as it is centralized, robust, cost-effective, and relatively easy to implement.
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Affiliation(s)
- Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Omar Khalilur Rahman
- Department of Medical Microbiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
| | - I-Ching Sam
- Department of Medical Microbiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
- Department of Medical Microbiology, University Malaya Medical Centre, Kuala Lumpur, Malaysia
| | - Dan Cheng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Dhiraj Nainani
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Se Yeon Kim
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Wei Jie Ng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Wee Chiew Kwok
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
| | - Kwanrawee Sirikanchana
- Research Laboratory of Biotechnology, Chulabhorn Research Institute, Bangkok, Thailand
- Centre of Excellence on Environmental Health and Toxicology, CHE, Ministry of Education, Bangkok, Thailand
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore
| | - Janelle Thompson
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
| | - Yoke Fun Chan
- Department of Medical Microbiology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
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Westcott CE, Sokoloski KJ, Rouchka EC, Chariker JH, Holm RH, Yeager RA, Moore JB, Elliott EM, Talley D, Bhatnagar A, Smith T. The Detection of Periodic Reemergence Events of SARS-CoV-2 Delta Strain in Communities Dominated by Omicron. Pathogens 2022; 11:1249. [PMID: 36365000 PMCID: PMC9697103 DOI: 10.3390/pathogens11111249] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 10/14/2022] [Accepted: 10/24/2022] [Indexed: 12/01/2022] Open
Abstract
Despite entering an endemic phase, SARS-CoV-2 remains a significant burden to public health across the global community. Wastewater sampling has consistently proven utility to understanding SARS-CoV-2 prevalence trends and genetic variation as it represents a less biased assessment of the corresponding communities. Here, we report that ongoing monitoring of SARS-CoV-2 genetic variation in samples obtained from the wastewatersheds of the city of Louisville in Jefferson county Kentucky has revealed the periodic reemergence of the Delta strain in the presence of the presumed dominant Omicron strain. Unlike previous SARS-CoV-2 waves/emergence events, the Delta reemergence events were geographically restricted in the community and failed to spread into other areas as determined by wastewater analyses. Moreover, the reemergence of the Delta strain did not correlate with vaccination rates as communities with lower relative vaccination have been, to date, not affected. Importantly, Delta reemergence events correlate with increased public health burdens, as indicated by increased daily case rates and mortality relative to non-Delta wastewatershed communities. While the underlying reasons for the reemergence of the Delta variant remain unclear, these data reaffirm the ongoing importance of wastewater genomic analyses towards understanding SARS-CoV-2 as it enters the endemic phase.
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Jiang W, Ji W, Zhang Y, Xie Y, Chen S, Jin Y, Duan G. An Update on Detection Technologies for SARS-CoV-2 Variants of Concern. Viruses 2022; 14:v14112324. [PMID: 36366421 PMCID: PMC9693800 DOI: 10.3390/v14112324] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 10/15/2022] [Accepted: 10/20/2022] [Indexed: 01/18/2023] Open
Abstract
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is responsible for the global epidemic of Coronavirus Disease 2019 (COVID-19), with a significant impact on the global economy and human safety. Reverse transcription-quantitative polymerase chain reaction (RT-PCR) is the gold standard for detecting SARS-CoV-2, but because the virus's genome is prone to mutations, the effectiveness of vaccines and the sensitivity of detection methods are declining. Variants of concern (VOCs) include Alpha, Beta, Gamma, Delta, and Omicron, which are able to evade recognition by host immune mechanisms leading to increased transmissibility, morbidity, and mortality of COVID-19. A range of research has been reported on detection techniques for VOCs, which is beneficial to prevent the rapid spread of the epidemic, improve the effectiveness of public health and social measures, and reduce the harm to human health and safety. However, a meaningful translation of this that reduces the burden of disease, and delivers a clear and cohesive message to guide daily clinical practice, remains preliminary. Herein, we summarize the capabilities of various nucleic acid and protein-based detection methods developed for VOCs in identifying and differentiating current VOCs and compare the advantages and disadvantages of each method, providing a basis for the rapid detection of VOCs strains and their future variants and the adoption of corresponding preventive and control measures.
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Affiliation(s)
- Wenjie Jiang
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Wangquan Ji
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Yu Zhang
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Yaqi Xie
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Shuaiyin Chen
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
- Henan Key Laboratory of Molecular Medicine, Zhengzhou University, Zhengzhou 450001, China
- Correspondence: (S.C.); (Y.J.); (G.D.); Tel.: +86-13523408394 (S.C.); +86-0371-67781453 (Y.J.); +86-0371-67789797 (G.D.)
| | - Yuefei Jin
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
- Correspondence: (S.C.); (Y.J.); (G.D.); Tel.: +86-13523408394 (S.C.); +86-0371-67781453 (Y.J.); +86-0371-67789797 (G.D.)
| | - Guangcai Duan
- Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
- Henan Key Laboratory of Molecular Medicine, Zhengzhou University, Zhengzhou 450001, China
- Correspondence: (S.C.); (Y.J.); (G.D.); Tel.: +86-13523408394 (S.C.); +86-0371-67781453 (Y.J.); +86-0371-67789797 (G.D.)
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Lee WL, Gu X, Armas F, Leifels M, Wu F, Chandra F, Chua FJD, Syenina A, Chen H, Cheng D, Ooi EE, Wuertz S, Alm EJ, Thompson J. Monitoring human arboviral diseases through wastewater surveillance: Challenges, progress and future opportunities. Water Res 2022; 223:118904. [PMID: 36007397 DOI: 10.1016/j.watres.2022.118904] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 07/19/2022] [Accepted: 07/23/2022] [Indexed: 05/21/2023]
Abstract
Arboviral diseases are caused by a group of viruses spread by the bite of infected arthropods. Amongst these, dengue, Zika, west nile fever and yellow fever cause the greatest economic and social impact. Arboviral epidemics have increased in frequency, magnitude and geographical extent over the past decades and are expected to continue increasing with climate change and expanding urbanisation. Arboviral prevalence is largely underestimated, as most infections are asymptomatic, nevertheless existing surveillance systems are based on passive reporting of loosely defined clinical syndromes with infrequent laboratory confirmation. Wastewater-based surveillance (WBS), which has been demonstrated to be useful for monitoring diseases with significant asymptomatic populations including COVID19 and polio, could be a useful complement to arboviral surveillance. We review the current state of knowledge and identify key factors that affect the feasibility of monitoring arboviral diseases by WBS to include viral shedding loads by infected persons, the persistence of shed arboviruses and the efficiency of their recovery from sewage. We provide a simple model on the volume of wastewater that needs to be processed for detection of arboviruses, in face of lower arboviral shedding rates. In all, this review serves to reflect on the key challenges that need to be addressed and overcome for successful implementation of arboviral WBS.
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Affiliation(s)
- Wei Lin Lee
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Xiaoqiong Gu
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Federica Armas
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Fuqing Wu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, Center for Infectious Disease, University of Texas School of Public Health, Houston, TX, USA
| | - Franciscus Chandra
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Ayesa Syenina
- Program in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Viral Research and Experimental Medicine Centre (ViREMiCS), SingHealth Duke-NUS Academic Medical Centre, Singapore 169856, Singapore
| | - Hongjie Chen
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Dan Cheng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Eng Eong Ooi
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Program in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Viral Research and Experimental Medicine Centre (ViREMiCS), SingHealth Duke-NUS Academic Medical Centre, Singapore 169856, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549, Singapore
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Eric J Alm
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Janelle Thompson
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore 637459, Singapore.
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Wilhelm A, Agrawal S, Schoth J, Meinert-berning C, Bastian D, Orschler L, Ciesek S, Teichgräber B, Wintgens T, Lackner S, Weber F, Widera M. Early Detection of SARS-CoV-2 Omicron BA.4 and BA.5 in German Wastewater. Viruses 2022; 14:1876. [PMID: 36146683 PMCID: PMC9503272 DOI: 10.3390/v14091876] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/21/2022] [Accepted: 08/22/2022] [Indexed: 11/17/2022] Open
Abstract
Wastewater-based SARS-CoV-2 epidemiology (WBE) has been established as an important tool to support individual testing strategies. The Omicron sub-variants BA.4/BA.5 have spread globally, displacing the preceding variants. Due to the severe transmissibility and immune escape potential of BA.4/BA.5, early monitoring was required to assess and implement countermeasures in time. In this study, we monitored the prevalence of SARS-CoV-2 BA.4/BA.5 at six municipal wastewater treatment plants (WWTPs) in the Federal State of North Rhine-Westphalia (NRW, Germany) in May and June 2022. Initially, L452R-specific primers/probes originally designed for SARS-CoV-2 Delta detection were validated using inactivated authentic viruses and evaluated for their suitability for detecting BA.4/BA.5. Subsequently, the assay was used for RT-qPCR analysis of RNA purified from wastewater obtained twice a week at six WWTPs. The occurrence of L452R carrying RNA was detected in early May 2022, and the presence of BA.4/BA.5 was confirmed by variant-specific single nucleotide polymorphism PCR (SNP-PCR) targeting E484A/F486V and NGS sequencing. Finally, the mutant fractions were quantitatively monitored by digital PCR, confirming BA.4/BA.5 as the majority variant by 5 June 2022. In conclusion, the successive workflow using RT-qPCR, variant-specific SNP-PCR, and RT-dPCR demonstrates the strength of WBE as a versatile tool to rapidly monitor variants spreading independently of individual test capacities.
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