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Mencius J, Chen W, Zheng Y, An T, Yu Y, Sun K, Feng H, Feng Z. Restoring flowcell type and basecaller configuration from FASTQ files of nanopore sequencing data. Nat Commun 2025; 16:4102. [PMID: 40316544 PMCID: PMC12048652 DOI: 10.1038/s41467-025-59378-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2024] [Accepted: 04/22/2025] [Indexed: 05/04/2025] Open
Abstract
As nanopore sequencing has been widely adopted, data accumulation has surged, resulting in over 700,000 public datasets. While these data hold immense potential for advancing genomic research, their utility is compromised by the absence of flowcell type and basecaller configuration in about 85% of the data and associated publications. These parameters are essential for many analysis algorithms, and their misapplication can lead to significant drops in performance. To address this issue, we present LongBow, designed to infer flowcell type and basecaller configuration directly from the base quality value patterns of FASTQ files. LongBow has been tested on 66 in-house basecalled FAST5/POD5 datasets and 1989 public FASTQ datasets, achieving accuracies of 95.33% and 91.45%, respectively. We demonstrate its utility by reanalyzing nanopore sequencing data from the COVID-19 Genomics UK (COG-UK) project. The results show that LongBow is essential for reproducing reported genomic variants and, through a LongBow-based analysis pipeline, we discovered substantially more functionally important variants while improving accuracy in lineage assignment. Overall, LongBow is poised to play a critical role in maximizing the utility of public nanopore sequencing data, while significantly enhancing the reproducibility of related research.
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Affiliation(s)
- Jun Mencius
- Department of Computational Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Wenjun Chen
- Department of Clinical Genetics, Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Youqi Zheng
- Department of Computational Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Tingyi An
- Department of Computational Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Yongguo Yu
- Department of Clinical Genetics, Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Kun Sun
- Department of Clinical Genetics, Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Department of Pediatric Cardiology, Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Huijuan Feng
- Department of Computational Biology, School of Life Sciences, Fudan University, Shanghai, China.
| | - Zhixing Feng
- Department of Clinical Genetics, Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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2
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Pham K, Chaguza C, Lopes R, Cohen T, Taylor-Salmon E, Wilkinson M, Katebi V, Grubaugh ND, Hill V. Large-Scale Genomic Analysis of SARS-CoV-2 Omicron BA.5 Emergence, United States. Emerg Infect Dis 2025; 31:45-56. [PMID: 40359081 PMCID: PMC12078544 DOI: 10.3201/eid3113.240981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/15/2025] Open
Abstract
The COVID-19 pandemic has been marked by continuous emergence of novel SARS-CoV-2 variants. Questions remain about the mechanisms with which those variants establish themselves in new geographic areas. We performed a discrete phylogeographic analysis on 18,529 sequences of the SARS-CoV-2 Omicron BA.5 sublineage sampled during February-June 2022 to elucidate emergence of that sublineage in different regions of the United States. The earliest BA.5 sublineage introductions came from Africa, the putative variant origin, but most were from Europe, matching a high volume of air travelers. In addition, we discovered extensive domestic transmission between different US regions, driven by population size and cross-country transmission between key hotspots. We found most BA.5 virus transmission within the United States occurred between 3 regions in the southwestern, southeastern, and northeastern parts of the country. Our results form a framework for analyzing emergence of novel SARS-CoV-2 variants and other pathogens in the United States.
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3
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Piazzese C, Williams S, Brentall A, Kele B, Bible J, Harris K, Cutino‐Moguel T. Analysis of Variants' Dynamic Using the CLIMB Database in COVID-19 Patients Admitted to Hospitals of Barts Health NHS Trust. J Med Virol 2025; 97:e70402. [PMID: 40411238 PMCID: PMC12102684 DOI: 10.1002/jmv.70402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2024] [Revised: 02/04/2025] [Accepted: 05/05/2025] [Indexed: 05/26/2025]
Abstract
The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant global health challenges. This study analyzes the dynamics of SARS-CoV-2 variants among patients admitted to Barts Health National Health Service (NHS) Trust hospitals using data from the CLIMB-COVID decentralized digital infrastructure allowing precise identification of SARS-CoV-2 variants. A total of 423 patients admitted between October 2020 and March 2021 were included in the study and divided into two groups: the alpha lineage group, which comprised the B.1.1.7 variant, and the other lineages group, which included all other variants. Whole-genome sequencing of SARS-CoV-2 genomes was conducted using the COVID-CLIMB pipelines. Clinical outcomes, such as mortality rates and deterioration within 28 days, were analyzed. To ensure robust findings, analyzes were adjusted for confounding factors, including age and comorbidities. Our findings revealed a significant increase in mortality with age for the alpha lineage and other lineages. The study underscores the importance of age adjustment in clinical studies to accurately assess the impact of different variants. Consistent genomic sequencing and data completeness are crucial for obtaining reliable results and guiding public health responses. These insights are vital for improving patient outcomes and providing a truthful picture of the pandemic, informing both current and future healthcare strategies.
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Affiliation(s)
- Concetta Piazzese
- PHURIQueen Mary University of LondonLondonEnglandUK
- DERIQueen Mary University of LondonLondonEnglandUK
- Barts Life SciencesBarts Health NHS TrustLondonEnglandUK
| | - Sophie Williams
- PHURIQueen Mary University of LondonLondonEnglandUK
- DERIQueen Mary University of LondonLondonEnglandUK
- Barts Life SciencesBarts Health NHS TrustLondonEnglandUK
| | - Adam Brentall
- Wolfson Institute of Population HealthQueen Mary University of LondonLondonEnglandUK
| | - Beatrix Kele
- Respiratory Virus UnitUK Health Security AgencyLondonEnglandUK
| | - Jon Bible
- Department of Virology, Division of InfectionBarts Health NHS TrustLondonEnglandUK
| | - Kathryn Harris
- Department of Virology, Division of InfectionBarts Health NHS TrustLondonEnglandUK
| | - Teresa Cutino‐Moguel
- Department of Virology, Division of InfectionBarts Health NHS TrustLondonEnglandUK
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4
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Översti S, Weber A, Baran V, Kieninger B, Dilthey A, Houwaart T, Walker A, Schneider-Brachert W, Kühnert D. Evolutionary and epidemic dynamics of COVID-19 in Germany exemplified by three Bayesian phylodynamic case studies. Bioinform Biol Insights 2025; 19:11779322251321065. [PMID: 40078196 PMCID: PMC11898094 DOI: 10.1177/11779322251321065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Accepted: 01/29/2025] [Indexed: 03/14/2025] Open
Abstract
The importance of genomic surveillance strategies for pathogens has been particularly evident during the coronavirus disease 2019 (COVID-19) pandemic, as genomic data from the causative agent, severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), have guided public health decisions worldwide. Bayesian phylodynamic inference, integrating epidemiology and evolutionary biology, has become an essential tool in genomic epidemiological surveillance. It enables the estimation of epidemiological parameters, such as the reproductive number, from pathogen sequence data alone. Despite the phylodynamic approach being widely adopted, the abundance of phylodynamic models often makes it challenging to select the appropriate model for specific research questions. This article illustrates the application of phylodynamic birth-death-sampling models in public health using genomic data, with a focus on SARS-CoV-2. Targeting researchers less familiar with phylodynamics, it introduces a comprehensive workflow, including the conceptualisation of a research study and detailed steps for data preprocessing and postprocessing. In addition, we demonstrate the versatility of birth-death-sampling models through three case studies from Germany, utilising the BEAST2 software and its model implementations. Each case study addresses a distinct research question relevant not only to SARS-CoV-2 but also to other pathogens: Case study 1 finds traces of a superspreading event at the start of an early outbreak, exemplifying how simple models for genomic data can provide information that would otherwise only be accessible through extensive contact tracing. Case study 2 compares transmission dynamics in a nosocomial outbreak to community transmission, highlighting distinct dynamics through integrative analysis. Case study 3 investigates whether local transmission patterns align with national trends, demonstrating how phylodynamic models can disentangle complex population substructure with little additional information. For each case study, we emphasise critical points where model assumptions and data properties may misalign and outline appropriate validation assessments. Overall, we aim to provide researchers with examples on using birth-death-sampling models in genomic epidemiology, balancing theoretical and practical aspects.
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Affiliation(s)
- Sanni Översti
- Transmission, Infection, Diversification & Evolution Group (tide), Max Planck Institute of Geoanthropology, Jena, Germany
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Ariane Weber
- Transmission, Infection, Diversification & Evolution Group (tide), Max Planck Institute of Geoanthropology, Jena, Germany
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Viktor Baran
- Department of Infection Prevention and Infectious Diseases, University Hospital Regensburg, Regensburg, Germany
| | - Bärbel Kieninger
- Department of Infection Prevention and Infectious Diseases, University Hospital Regensburg, Regensburg, Germany
| | - Alexander Dilthey
- Institute of Medical Microbiology and Hospital Hygiene, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Torsten Houwaart
- Institute of Medical Microbiology and Hospital Hygiene, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Andreas Walker
- Institute of Virology, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Wulf Schneider-Brachert
- Department of Infection Prevention and Infectious Diseases, University Hospital Regensburg, Regensburg, Germany
| | - Denise Kühnert
- Transmission, Infection, Diversification & Evolution Group (tide), Max Planck Institute of Geoanthropology, Jena, Germany
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Phylogenomics Unit, Centre for Artificial Intelligence in Public Health Research, Robert Koch Institute, Wildau, Germany
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Zhao N, He M, Wang H, Zhu L, Wang N, Yong W, Fan H, Ding S, Ma T, Zhang Z, Dong X, Wang Z, Dong X, Min X, Zhang H, Ding J. Genomic epidemiology reveals the variation and transmission properties of SARS-CoV-2 in a single-source community outbreak. Virus Evol 2024; 10:veae085. [PMID: 39493536 PMCID: PMC11529616 DOI: 10.1093/ve/veae085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Revised: 09/04/2024] [Accepted: 10/10/2024] [Indexed: 11/05/2024] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the coronavirus disease 2019 (COVID-19) pandemic, which is still a global public health concern. During March 2022, a rapid and confined single-source outbreak of SARS-CoV-2 was identified in a community in Nanjing municipal city. Overall, 95 individuals had laboratory-confirmed SARS-CoV-2 infection. The whole genomes of 61 viral samples were obtained, which were all members of the BA.2.2 lineage and clearly demonstrated the presence of one large clade, and all the infections could be traced back to the original index case. The most distant sequence from the index case presented a difference of 4 SNPs, and 118 intrahost single-nucleotide variants (iSNVs) at 74 genomic sites were identified. Some minor iSNVs can be transmitted and subsequently rapidly fixed in the viral population. The minor iSNVs transmission resulted in at least two nucleotide substitutions among all seven SNPs identified in the outbreak, generating genetically diverse populations. We estimated the overall transmission bottleneck size to be 3 using 11 convincing donor-recipient transmission pairs. Our study provides new insights into genomic epidemiology and viral transmission, revealing how iSNVs become fixed in local clusters, followed by viral transmission across the community, which contributes to population diversity.
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Affiliation(s)
- Ning Zhao
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - Min He
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
- School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, Jiangsu 211166, China
| | - HengXue Wang
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - LiGuo Zhu
- Department of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, Jiangsu 210009, China
| | - Nan Wang
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - Wei Yong
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - HuaFeng Fan
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - SongNing Ding
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - Tao Ma
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - Zhong Zhang
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - XiaoXiao Dong
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - ZiYu Wang
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - XiaoQing Dong
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - XiaoYu Min
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - HongBo Zhang
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - Jie Ding
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
- School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, Jiangsu 211166, China
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6
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Bevan I, Bauld L, Street A. Who We Test For: Aligning Relational and Public Health Responsibilities in COVID-19 Testing in Scotland. Med Anthropol 2024; 43:277-294. [PMID: 38713821 PMCID: PMC11104742 DOI: 10.1080/01459740.2024.2349514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2024]
Abstract
COVID-19 testing programs in the UK often called on people to test to "protect others." In this article we explore motivations to test and the relationships to "others" involved in an asymptomatic testing program at a Scottish university. We show that participants engaged with testing as a relational technology, through which they navigated multiple overlapping responsibilities to kin, colleagues, flatmates, strangers, and to more diffuse publics. We argue that the success of testing as a technique of governance depends not only on the production of disciplined selves, but also on the program's capacity to align interpersonal and public scales of responsibility.
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Affiliation(s)
- Imogen Bevan
- School of Social and Political Science, University of Edinburgh, Edinburgh, UK
| | - Linda Bauld
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Alice Street
- School of Social and Political Science, University of Edinburgh, Edinburgh, UK
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Kogoj R, Grašek M, Suljič A, Zakotnik S, Vlaj D, Kotnik Koman K, Fafangel M, Petrovec M, Avšič-Županc T, Korva M. Sequencing analysis of SARS-CoV-2 cases in Slovenian long-term care facilities to support outbreak control. Front Public Health 2024; 12:1406777. [PMID: 38813418 PMCID: PMC11133669 DOI: 10.3389/fpubh.2024.1406777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 05/02/2024] [Indexed: 05/31/2024] Open
Abstract
Introduction Residents of long-term care facilities (LTCFs) are at high risk of morbidity and mortality due to COVID-19, especially when new variants of concern (VOC) emerge. To provide intradisciplinary data in order to tailor public health interventions during future epidemics, available epidemiologic and genomic data from Slovenian LTCFs during the initial phases of the COVID-19 pandemic was analyzed. Methods The first part of the study included SARS-CoV-2 reverse-transcription Real-Time PCR (rtRT-PCR) positive LTCF residents, from 21 facilities with COVID-19 outbreaks occurring in October 2020. The second part of the study included SARS-CoV-2 rtRT-PCR positive LTCF residents and staff between January and April 2021, when VOC Alpha emerged in Slovenia. Next-generation sequencing (NGS) was used to acquire SARS-CoV-2 genomes, and lineage determination. In-depth phylogenetic and mutational profile analysis were performed and coupled with available field epidemiological data to assess the dynamics of SARS-CoV-2 introduction and transmission. Results 370/498 SARS-CoV-2 positive residents as well as 558/699 SARS-CoV-2 positive residents and 301/358 staff were successfully sequenced in the first and second part of the study, respectively. In October 2020, COVID-19 outbreaks in the 21 LTCFs were caused by intra-facility transmission as well as multiple independent SARS-CoV-2 introductions. The Alpha variant was confirmed in the first LTCF resident approximately 1.5 months after the first Alpha case was identified in Slovenia. The data also showed a slower replacement of existing variants by Alpha in residents compared to staff and the general population. Discussion Multiple SARS CoV-2 introductions as well as intra-facility spreading impacted disease transmission in Slovenian LTCFs. Timely implementation of control measures aimed at limiting new introductions while controlling in-facility transmission are of paramount importance, especially as new VOCs emerge. Sequencing, in conjunction with epidemiological data, can facilitate the determination of the need for future improvements in control measures to protect LTCF residents from COVID-19 or other respiratory infections.
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Affiliation(s)
- Rok Kogoj
- Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Manja Grašek
- Communicable Diseases Center, National Institute of Public Health, Ljubljana, Slovenia
| | - Alen Suljič
- Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Samo Zakotnik
- Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Doroteja Vlaj
- Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Kaja Kotnik Koman
- Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Mario Fafangel
- Communicable Diseases Center, National Institute of Public Health, Ljubljana, Slovenia
| | - Miroslav Petrovec
- Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tatjana Avšič-Županc
- Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Misa Korva
- Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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Monge D, Gallego-Gil A, Neria F, Canellas S, Caballero F, Díaz de Bustamante A, Samper M. General infection prevention, mitigation, and control procedures implemented in the university education during the COVID-19 pandemic to achieve classroom attendance: a successful community case study. Front Public Health 2024; 11:1309902. [PMID: 38449900 PMCID: PMC10915036 DOI: 10.3389/fpubh.2023.1309902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 12/21/2023] [Indexed: 03/08/2024] Open
Abstract
Introduction The COVID-19 pandemic entailed confinement and elimination of face-to-face university classes in Spain. The Francisco de Vitoria University in Madrid (UFV by its Spanish acronym) implemented risk management systems to enable on-campus university activity to avoid a negative impact on students, teachers, and faculties. Methods A tracking/registry system was implemented to collect data, identify COVID-19-related cases, implement containment measures, and do follow-up in the UFV community (administration/services personnel [ASP], teaching/research personnel [TRP], and students), from September 2020 to April 2022. In addition, a prevention plan was implemented on campus to avoid COVID-19 spreading. Satisfaction with these measures was assessed through an online questionnaire. Results A total of 7,165 suspected COVID-19 cases (84.7% students, 7.7% ASP, 6.5% TRP) were tracked (62.5% female cases, mean age (±SD) 24.8 years (±9.2 years)), and 45% of them confirmed (82% symptomatic/16% asymptomatic), being the student group that with the highest percentage (38.3% total tracked cases). The source of infection was identified in 50.6% of the confirmed cases (90.2% located off-campus). Nineteen COVID-19 outbreaks were registered (inside-10/outside-9). COVID-19 incidence rates were similar or lower than those reported in the Community of Madrid, except in the last wave, corresponding to Omicron variant. The degree of satisfaction (scale 1-6) with the implemented measures was high (scores 4.48-5.44). Conclusion During the COVID-19 pandemic, UFV control measures, periodic monitoring, and the effectiveness of the tracking system have contributed to maintaining classroom teaching, guaranteeing health and safety. UFV has adapted to a new reality as an example of good practice for future pandemics or emergency situations.
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Affiliation(s)
- Diana Monge
- Facultad de Medicina, Universidad Francisco de Vitoria, Madrid, Spain
| | - Ana Gallego-Gil
- Servicio de Seguridad, Salud y Bienestar, Universidad Francisco de Vitoria, Madrid, Spain
| | - Fernando Neria
- Facultad de Medicina, Universidad Francisco de Vitoria, Madrid, Spain
| | - Soledad Canellas
- Unidad Técnica de Estrategias Poblacionales en Vacuna, Subdirección General de Prevención y Promoción de la Salud, Dirección General de Salud Pública, Madrid, Spain
| | | | - Ana Díaz de Bustamante
- Servicio de Seguridad, Salud y Bienestar, Universidad Francisco de Vitoria, Madrid, Spain
| | - Mónica Samper
- Servicio de Seguridad, Salud y Bienestar, Universidad Francisco de Vitoria, Madrid, Spain
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Ciubotariu II, Wilkes RP, Kattoor JJ, Christian EN, Carpi G, Kitchen A. Investigating the rise of Omicron variant through genomic surveillance of SARS-CoV-2 infections in a highly vaccinated university population. Microb Genom 2024; 10:001194. [PMID: 38334271 PMCID: PMC10926704 DOI: 10.1099/mgen.0.001194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 01/23/2024] [Indexed: 02/10/2024] Open
Abstract
Novel variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to emerge as the coronavirus disease 2019 (COVID-19) pandemic extends into its fourth year. Understanding SARS-CoV-2 circulation in university populations is vital for effective interventions in higher education settings and will inform public health policy during pandemics. In this study, we generated 793 whole-genome sequences collected over an entire academic year in a university population in Indiana, USA. We clearly captured the rapidity with which Delta variant was wholly replaced by Omicron variant across the West Lafayette campus over the length of two academic semesters in a community with high vaccination rates. This mirrored the emergence of Omicron throughout the state of Indiana and the USA. Further, phylogenetic analyses demonstrated that there was a more diverse set of potential geographic origins for Omicron viruses introduction into campus when compared to Delta. Lastly, statistics indicated that there was a more significant role for international and out-of-state migration in the establishment of Omicron variants at Purdue. This surveillance workflow, coupled with viral genomic sequencing and phylogeographic analyses, provided critical insights into SARS-CoV-2 transmission dynamics and variant arrival.
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Affiliation(s)
- Ilinca I. Ciubotariu
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana 47907, USA
| | - Rebecca P. Wilkes
- Department of Comparative Pathobiology, Animal Disease Diagnostic Laboratory, Purdue University College of Veterinary Medicine, West Lafayette, Indiana 47907, USA
| | - Jobin J. Kattoor
- Department of Comparative Pathobiology, Animal Disease Diagnostic Laboratory, Purdue University College of Veterinary Medicine, West Lafayette, Indiana 47907, USA
| | - Erin N. Christian
- Department of Comparative Pathobiology, Animal Disease Diagnostic Laboratory, Purdue University College of Veterinary Medicine, West Lafayette, Indiana 47907, USA
| | - Giovanna Carpi
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana 47907, USA
- Purdue Institute of Inflammation, Immunology and Infectious Disease, West Lafayette, Indiana 47907, USA
| | - Andrew Kitchen
- Department of Anthropology, University of Iowa, Iowa City, Iowa, USA
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10
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Dack K, Wilson A, Turner C, Anderson C, Hughes GJ. COVID-19 associated with universities in England, October 2020-February 2022. Public Health 2023; 224:106-112. [PMID: 37742583 DOI: 10.1016/j.puhe.2023.08.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 08/20/2023] [Accepted: 08/22/2023] [Indexed: 09/26/2023]
Abstract
OBJECTIVES The aim of this study was to describe the epidemiology of COVID-19 cases at universities in England (October 2020-February 2022) and investigate factors associated with rates of COVID-19 among students during autumn/winter of 2021/22. STUDY DESIGN The study was an observational retrospective study using routine contact tracing data. METHODS Estimates of COVID-19 cases among students and staff at universities were described. Student cases aged 18-24 years were calculated as a percentage of all cases within that age group. Count regression was used to explore university characteristics associated with case numbers. RESULTS We identified 102,382 cases among students and 28,639 among staff. Student cases reflected trends in the wider population of the same age group, but the observed fraction aged 18-24 years who were students was consistently below the expected level (32%). Phased reopening of universities in March-May 2021 was associated with small peaks but low absolute numbers. Russell group membership, campus universities, and higher student proportions in halls of residence were all associated with increased case numbers. CONCLUSIONS COVID-19 case numbers among students in England varied considerably. At no time were the observed case numbers as high as expected from community prevalence. Characteristics of universities associated with higher case rates can inform future guidance for higher education settings.
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Affiliation(s)
- K Dack
- Field Service, United Kingdom Health Security Agency, London, UK
| | - A Wilson
- Field Service, United Kingdom Health Security Agency, London, UK
| | - C Turner
- Field Service, United Kingdom Health Security Agency, London, UK
| | - C Anderson
- Field Service, United Kingdom Health Security Agency, London, UK
| | - G J Hughes
- Field Service, United Kingdom Health Security Agency, Leeds, UK.
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Lee J, Acosta N, Waddell BJ, Du K, Xiang K, Van Doorn J, Low K, Bautista MA, McCalder J, Dai X, Lu X, Chekouo T, Pradhan P, Sedaghat N, Papparis C, Buchner Beaudet A, Chen J, Chan L, Vivas L, Westlund P, Bhatnagar S, Stefani S, Visser G, Cabaj J, Bertazzon S, Sarabi S, Achari G, Clark RG, Hrudey SE, Lee BE, Pang X, Webster B, Ghali WA, Buret AG, Williamson T, Southern DA, Meddings J, Frankowski K, Hubert CRJ, Parkins MD. Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community. WATER RESEARCH 2023; 244:120469. [PMID: 37634459 DOI: 10.1016/j.watres.2023.120469] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 08/06/2023] [Accepted: 08/07/2023] [Indexed: 08/29/2023]
Abstract
Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.
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Affiliation(s)
- Jangwoo Lee
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Nicole Acosta
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Barbara J Waddell
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Kristine Du
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Kevin Xiang
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Jennifer Van Doorn
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Kashtin Low
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Maria A Bautista
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Janine McCalder
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Xiaotian Dai
- Department of Mathematics and Statistics, University of Calgary, Calgary, Canada
| | - Xuewen Lu
- Department of Mathematics and Statistics, University of Calgary, Calgary, Canada
| | - Thierry Chekouo
- Department of Mathematics and Statistics, University of Calgary, Calgary, Canada; Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, USA
| | - Puja Pradhan
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Navid Sedaghat
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Chloe Papparis
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Alexander Buchner Beaudet
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Jianwei Chen
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Leslie Chan
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Laura Vivas
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | | | - Srijak Bhatnagar
- Department of Biological Sciences, University of Calgary, Calgary, Canada; Faculty of Science and Technology, Athabasca University, Athabasca, Alberta, Canada
| | - September Stefani
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Gail Visser
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada
| | - Jason Cabaj
- Department of Community Health Sciences, University of Calgary, Calgary, Canada; Department of Medicine, University of Calgary and Alberta Health Services, Calgary, Canada; Provincial Population & Public Health, Alberta Health Services, Calgary, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Canada
| | | | - Shahrzad Sarabi
- Department of Geography, University of Calgary, Calgary, Canada
| | - Gopal Achari
- Department of Civil Engineering, University of Calgary, Calgary, Canada
| | - Rhonda G Clark
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada; Analytical and Environmental Toxicology, University of Alberta, Edmonton, Alberta, Canada
| | - Bonita E Lee
- Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada; Women & Children's Health Research Institute, Li Ka Shing Institute of Virology, Edmonton, Alberta, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada; Alberta Precision Laboratories, Public Health Laboratory, Alberta Health Services, Edmonton, Alberta, Canada; Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alberta, Canada
| | - Brendan Webster
- Occupational Health Staff Wellness, University of Calgary, Calgary, Canada
| | - William Amin Ghali
- Department of Community Health Sciences, University of Calgary, Calgary, Canada; Department of Medicine, University of Calgary and Alberta Health Services, Calgary, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Canada; Centre for Health Informatics, University of Calgary, Calgary, Canada
| | - Andre Gerald Buret
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Tyler Williamson
- Department of Community Health Sciences, University of Calgary, Calgary, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Canada; Centre for Health Informatics, University of Calgary, Calgary, Canada
| | - Danielle A Southern
- Department of Community Health Sciences, University of Calgary, Calgary, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Canada; Centre for Health Informatics, University of Calgary, Calgary, Canada
| | - Jon Meddings
- Department of Medicine, University of Calgary and Alberta Health Services, Calgary, Canada
| | - Kevin Frankowski
- Advancing Canadian Water Assets, University of Calgary, Calgary, Canada
| | - Casey R J Hubert
- Department of Biological Sciences, University of Calgary, Calgary, Canada
| | - Michael D Parkins
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive, NW, Calgary, Alberta T2N 2V5, Canada; Department of Medicine, University of Calgary and Alberta Health Services, Calgary, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Canada.
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12
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Deroche L, Bellecave P, David R, Ouattara E, Garcia M, Roblot F, Boinot L, Faucher JF, Rejasse A, Gschwind G, Malvy D, Filleul L, Rogez S, Lévêque N, Lafon ME. One year of SARS-CoV-2 circulation in the Nouvelle-Aquitaine region, February 2021-2022, France. Front Microbiol 2023; 14:1176575. [PMID: 37577437 PMCID: PMC10420073 DOI: 10.3389/fmicb.2023.1176575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 07/17/2023] [Indexed: 08/15/2023] Open
Abstract
Background Since 2021, 3 variants of concern (VOC) have spread to France, causing successive epidemic waves. Objectives To describe the features of Alpha, Delta and Omicron VOC circulation in the Nouvelle-Aquitaine region, France, between February 2021 and February 2022. Study design Data from the three university hospitals (UH) of Nouvelle-Aquitaine were used to describe regional SARS-CoV-2 circulation (RT-PCR positive rates and identified VOC) as well as its consequences (total number of hospitalizations and admissions in intensive care unit). They were analyzed according to the predominant variant and compared with national data. Results A total of 611,106 SARS-CoV-2 RT-PCR tests were performed in the 3 Nouvelle-Aquitaine UH during the study period. The 37,750 positive samples were analyzed by variant-specific RT-PCR or whole-genome sequencing. In 2021, Alpha VOC was detected from week 5 until week 35. Delta became the most prevalent variant (77.3%) in week 26, reaching 100% in week 35. It was replaced by Omicron, which was initially detected week 48, represented 77% of positive samples in week 52 and was still predominant in February 2022. The RT-PCR positive rates were 4.3, 4.2, and 21.9% during the Alpha, Delta and Omicron waves, respectively. The ratio between intensive care unit admissions and total hospitalizations was lower during the Omicron wave than during the two previous waves due to the Alpha and Delta variants. Conclusion This study highlighted the need for strong regional cooperation to achieve effective SARS-CoV-2 epidemiological surveillance, in close association with the public health authorities.
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Affiliation(s)
- Luc Deroche
- Virology Laboratory, CHU Poitiers, Poitiers, France
| | | | - Romain David
- Virology Laboratory, CHU Bordeaux, Bordeaux, France
| | - Eric Ouattara
- Medical Information Analysis and Coordination Unit (UCAIM-DIM), Medical Information Department, Bordeaux University Hospital, Bordeaux, France
| | - Magali Garcia
- Virology Laboratory, CHU Poitiers, Poitiers, France
- LITEC UR15560, Université de Poitiers, Poitiers, France
| | - France Roblot
- Tropical Infectious Diseases Department, Poitiers University Hospital, Poitiers, France
- INSERM U1070, Université de Poitiers, Poitiers, France
| | - Laurence Boinot
- Service d’Information Médicale, CHU Poitiers, Poitiers, France
| | - Jean-François Faucher
- Tropical Infectious Diseases Department, Limoges University Hospital, Limoges, France
| | - Aurélie Rejasse
- Medical Information Department, Limoges University Hospital, Limoges, France
| | - Guillaume Gschwind
- Medical Information Department, Limoges University Hospital, Limoges, France
| | - Denis Malvy
- Department of Infectious and Tropical Diseases, CHU Bordeaux, Bordeaux, France
- UMR Inserm 1219/IRD, University of Bordeaux, Bordeaux, France
| | - Laurent Filleul
- Regional Office-Nouvelle Aquitaine, Santé publique France, Bordeaux, France
| | - Sylvie Rogez
- Virology Laboratory, CHU Limoges, Limoges, France
| | - Nicolas Lévêque
- Virology Laboratory, CHU Poitiers, Poitiers, France
- LITEC UR15560, Université de Poitiers, Poitiers, France
| | - Marie-Edith Lafon
- Virology Laboratory, CHU Bordeaux, Bordeaux, France
- CNRS UMR 5234, University of Bordeaux, Bordeaux, France
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13
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DeJonge PM, Lambrou AS, Segaloff HE, Bateman A, Sterkel A, Griggs C, Baggott J, Kelly P, Thornburg N, Epperson M, Desamu-Thorpe R, Abedi G, Hsu CH, Nakayama JY, Ruffin J, Turner-Harper D, Matanock A, Almendares O, Whaley M, Chakrabarti A, DeGruy K, Daly M, Westergaard R, Tate JE, Kirking HL. Assessment of Anti-SARS-CoV-2 antibody levels among university students vaccinated with different COVID-19 primary and booster doses - fall 2021, Wisconsin. BMC Infect Dis 2023; 23:374. [PMID: 37277736 DOI: 10.1186/s12879-023-08332-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 05/16/2023] [Indexed: 06/07/2023] Open
Abstract
BACKGROUND University students commonly received COVID-19 vaccinations before returning to U.S. campuses in the Fall of 2021. Given likely immunologic variation among students based on differences in type of primary series and/or booster dose vaccine received, we conducted serologic investigations in September and December 2021 on a large university campus in Wisconsin to assess anti-SARS-CoV-2 antibody levels. METHODS We collected blood samples, demographic information, and COVID-19 illness and vaccination history from a convenience sample of students. Sera were analyzed for both anti-spike (anti-S) and anti-nucleocapsid (anti-N) antibody levels using World Health Organization standardized binding antibody units per milliliter (BAU/mL). Levels were compared across categorical primary COVID-19 vaccine series received and binary COVID-19 mRNA booster status. The association between anti-S levels and time since most recent vaccination dose was estimated by mixed-effects linear regression. RESULTS In total, 356 students participated, of whom 219 (61.5%) had received a primary vaccine series of Pfizer-BioNTech or Moderna mRNA vaccines and 85 (23.9%) had received vaccines from Sinovac or Sinopharm. Median anti-S levels were significantly higher for mRNA primary vaccine series recipients (2.90 and 2.86 log [BAU/mL], respectively), compared with those who received Sinopharm or Sinovac vaccines (1.63 and 1.95 log [BAU/mL], respectively). Sinopharm and Sinovac vaccine recipients were associated with a significantly faster anti-S decline over time, compared with mRNA vaccine recipients (P <.001). By December, 48/172 (27.9%) participants reported receiving an mRNA COVID-19 vaccine booster, which reduced the anti-S antibody discrepancies between primary series vaccine types. CONCLUSIONS Our work supports the benefit of heterologous boosting against COVID-19. COVID-19 mRNA vaccine booster doses were associated with increases in anti-SARS-CoV-2 antibody levels; following an mRNA booster dose, students with both mRNA and non-mRNA primary series receipt were associated with comparable levels of anti-S IgG.
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Affiliation(s)
- Peter M DeJonge
- Epidemic Intelligence Service, CDC, Atlanta, Georgia, 30329, USA.
- Wisconsin Department of Health Services, Division of Public Health, Madison, Wisconsin, 53703, USA.
| | | | - Hannah E Segaloff
- Epidemic Intelligence Service, CDC, Atlanta, Georgia, 30329, USA
- Wisconsin Department of Health Services, Division of Public Health, Madison, Wisconsin, 53703, USA
| | - Allen Bateman
- Wisconsin State Laboratory of Hygiene, Madison, Wisconsin, 53703, USA
| | - Alana Sterkel
- Wisconsin State Laboratory of Hygiene, Madison, Wisconsin, 53703, USA
| | - Carol Griggs
- University Health Services, University of Wisconsin - Madison, Madison, Wisconsin, 53703, USA
| | - Jake Baggott
- University Health Services, University of Wisconsin - Madison, Madison, Wisconsin, 53703, USA
| | - Patrick Kelly
- University Health Services, University of Wisconsin - Madison, Madison, Wisconsin, 53703, USA
| | | | | | | | - Glen Abedi
- CDC COVID-19 Response Team, Atlanta, Georgia, 30329, USA
| | | | - Jasmine Y Nakayama
- Epidemic Intelligence Service, CDC, Atlanta, Georgia, 30329, USA
- CDC COVID-19 Response Team, Atlanta, Georgia, 30329, USA
| | - Jasmine Ruffin
- CDC COVID-19 Response Team, Atlanta, Georgia, 30329, USA
| | | | - Almea Matanock
- CDC COVID-19 Response Team, Atlanta, Georgia, 30329, USA
| | | | - Melissa Whaley
- CDC COVID-19 Response Team, Atlanta, Georgia, 30329, USA
| | | | - Kyle DeGruy
- CDC COVID-19 Response Team, Atlanta, Georgia, 30329, USA
| | - Michele Daly
- CDC COVID-19 Response Team, Atlanta, Georgia, 30329, USA
| | - Ryan Westergaard
- Wisconsin Department of Health Services, Division of Public Health, Madison, Wisconsin, 53703, USA
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14
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Andrews KR, New DD, Gour DS, Francetich K, Minnich SA, Robison BD, Hovde CJ. Genomic surveillance identifies potential risk factors for SARS-CoV-2 transmission at a mid-sized university in a small rural town. Sci Rep 2023; 13:7902. [PMID: 37193760 PMCID: PMC10185956 DOI: 10.1038/s41598-023-34625-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 05/04/2023] [Indexed: 05/18/2023] Open
Abstract
Understanding transmission dynamics of SARS-CoV-2 in institutions of higher education (IHEs) is important because these settings have potential for rapid viral spread. Here, we used genomic surveillance to retrospectively investigate transmission dynamics throughout the 2020-2021 academic year for the University of Idaho ("University"), a mid-sized IHE in a small rural town. We generated genome assemblies for 1168 SARS-CoV-2 samples collected during the academic year, representing 46.8% of positive samples collected from the University population and 49.8% of positive samples collected from the surrounding community ("Community") at the local hospital during this time. Transmission dynamics differed for the University when compared to the Community, with more infection waves that lasted shorter lengths of time, potentially resulting from high-transmission congregate settings along with mitigation efforts implemented by the University to combat outbreaks. We found evidence for low transmission rates between the University and Community, with approximately 8% of transmissions into the Community originating from the University, and approximately 6% of transmissions into the University originating from the Community. Potential transmission risk factors identified for the University included congregate settings such as sorority and fraternity events and residences, holiday travel, and high caseloads in the surrounding community. Knowledge of these risk factors can help the University and other IHEs develop effective mitigation measures for SARS-CoV-2 and similar pathogens.
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Affiliation(s)
- Kimberly R Andrews
- Institute for Interdisciplinary Data Sciences, University of Idaho, Moscow, ID, 83844, USA.
| | - Daniel D New
- Institute for Interdisciplinary Data Sciences, University of Idaho, Moscow, ID, 83844, USA
| | - Digpal S Gour
- Institute for Interdisciplinary Data Sciences, University of Idaho, Moscow, ID, 83844, USA
| | | | - Scott A Minnich
- Department of Animal, Veterinary and Food Science, University of Idaho, Moscow, ID, 83844, USA
| | - Barrie D Robison
- Institute for Interdisciplinary Data Sciences, University of Idaho, Moscow, ID, 83844, USA
| | - Carolyn J Hovde
- Department of Animal, Veterinary and Food Science, University of Idaho, Moscow, ID, 83844, USA
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15
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van Tonder AJ, McCullagh F, McKeand H, Thaw S, Bellis K, Raisen C, Lay L, Aggarwal D, Holmes M, Parkhill J, Harrison EM, Kucharski A, Conlan A. Colonization and transmission of Staphylococcus aureus in schools: a citizen science project. Microb Genom 2023; 9:mgen000993. [PMID: 37074324 PMCID: PMC10210949 DOI: 10.1099/mgen.0.000993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 02/22/2023] [Indexed: 04/20/2023] Open
Abstract
Aggregation of children in schools has been established to be a key driver of transmission of infectious diseases. Mathematical models of transmission used to predict the impact of control measures, such as vaccination and testing, commonly depend on self-reported contact data. However, the link between self-reported social contacts and pathogen transmission has not been well described. To address this, we used Staphylococcus aureus as a model organism to track transmission within two secondary schools in England and test for associations between self-reported social contacts, test positivity and the bacterial strain collected from the same students. Students filled out a social contact survey and their S. aureus colonization status was ascertained through self-administered swabs from which isolates were sequenced. Isolates from the local community were also sequenced to assess the representativeness of school isolates. A low frequency of genome-linked transmission precluded a formal analysis of links between genomic and social networks, suggesting that S. aureus transmission within schools is too rare to make it a viable tool for this purpose. Whilst we found no evidence that schools are an important route of transmission, increased colonization rates found within schools imply that school-age children may be an important source of community transmission.
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Affiliation(s)
| | | | | | - Sue Thaw
- St Bede's Inter-Church School, Cambridge, UK
| | - Katie Bellis
- Wellcome Sanger Institute, Hinxton, UK
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - Claire Raisen
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Liz Lay
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Dinesh Aggarwal
- Wellcome Sanger Institute, Hinxton, UK
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - Mark Holmes
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Julian Parkhill
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Ewan M. Harrison
- Wellcome Sanger Institute, Hinxton, UK
- Department of Medicine, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Adam Kucharski
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Andrew Conlan
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
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16
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Farjo M, Brooke CB. Low Viral Diversity Limits the Effectiveness of Sequence-Based Transmission Inference for SARS-CoV-2. mSphere 2023; 8:e0054422. [PMID: 36695609 PMCID: PMC9942562 DOI: 10.1128/msphere.00544-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Tracking the spread of infection amongst individuals within and between communities has been a major challenge during viral outbreaks. With the unprecedented scale of viral sequence data collection during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the possibility of using phylogenetics to reconstruct past transmission events has been explored as a more rigorous alternative to traditional contact tracing; however, the reliability of sequence-based inference of transmission networks has yet to be directly evaluated. E. E. Bendall, G. Paz-Bailey, G. A. Santiago, C. A. Porucznik, et al. (mSphere 7:e00400-22, 2022, https://doi.org/10.1128/mSphere.00400-22) evaluate the potential of this technique by applying best practices sequence comparison methods to three geographically distinct cohorts that include known transmission pairs and demonstrate that linked pairs are often indistinguishable from unrelated samples. This study clearly establishes how low viral diversity limits the utility of genomic methods of epidemiological inference for SARS-CoV-2.
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Affiliation(s)
- Mireille Farjo
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Christopher B. Brooke
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
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17
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Bendall EE, Paz-Bailey G, Santiago GA, Porucznik CA, Stanford JB, Stockwell MS, Duque J, Jeddy Z, Veguilla V, Major C, Rivera-Amill V, Rolfes MA, Dawood FS, Lauring AS. SARS-CoV-2 Genomic Diversity in Households Highlights the Challenges of Sequence-Based Transmission Inference. mSphere 2022; 7:e0040022. [PMID: 36377913 PMCID: PMC9769559 DOI: 10.1128/msphere.00400-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 10/24/2022] [Indexed: 11/16/2022] Open
Abstract
The reliability of sequence-based inference of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is not clear. Sequence data from infections among household members can define the expected genomic diversity of a virus along a defined transmission chain. SARS-CoV-2 cases were identified prospectively among 2,369 participants in 706 households. Specimens with a reverse transcription-PCR cycle threshold of ≤30 underwent whole-genome sequencing. Intrahost single-nucleotide variants (iSNV) were identified at a ≥5% frequency. Phylogenetic trees were used to evaluate the relationship of household and community sequences. There were 178 SARS-CoV-2 cases in 706 households. Among 147 specimens sequenced, 106 yielded a whole-genome consensus with coverage suitable for identifying iSNV. Twenty-six households had sequences from multiple cases within 14 days. Consensus sequences were indistinguishable among cases in 15 households, while 11 had ≥1 consensus sequence that differed by 1 to 2 mutations. Sequences from households and the community were often interspersed on phylogenetic trees. Identification of iSNV improved inference in 2 of 15 households with indistinguishable consensus sequences and in 6 of 11 with distinct ones. In multiple-infection households, whole-genome consensus sequences differed by 0 to 1 mutations. Identification of shared iSNV occasionally resolved linkage, but the low genomic diversity of SARS-CoV-2 limits the utility of "sequence-only" transmission inference. IMPORTANCE We performed whole-genome sequencing of SARS-CoV-2 from prospectively identified cases in three longitudinal household cohorts. In a majority of multi-infection households, SARS-CoV-2 consensus sequences were indistinguishable, and they differed by 1 to 2 mutations in the rest. Importantly, even with modest genomic surveillance of the community (3 to 5% of cases sequenced), it was not uncommon to find community sequences interspersed with household sequences on phylogenetic trees. Identification of shared minority variants only occasionally resolved these ambiguities in transmission linkage. Overall, the low genomic diversity of SARS-CoV-2 limits the utility of "sequence-only" transmission inference. Our work highlights the need to carefully consider both epidemiologic linkage and sequence data to define transmission chains in households, hospitals, and other transmission settings.
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Affiliation(s)
- Emily E. Bendall
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
| | | | | | - Christina A. Porucznik
- Division of Public Health, Department of Family and Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Joseph B. Stanford
- Division of Public Health, Department of Family and Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Melissa S. Stockwell
- Division of Child and Adolescent Health, Department of Pediatrics, Columbia University Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York, New York, USA
| | | | - Zuha Jeddy
- Abt Associates, Rockville, Maryland, USA
| | - Vic Veguilla
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Chelsea Major
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Vanessa Rivera-Amill
- Ponce Research Institute, Ponce Health Sciences University, Ponce, Puerto Rico, USA
| | | | | | - Adam S. Lauring
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
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18
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Akintola AA, Aborode TA, Hwang UW. Africa needs genomic epidemiologists - Correspondence. Int J Surg 2022; 108:106999. [PMID: 36356825 DOI: 10.1016/j.ijsu.2022.106999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 11/06/2022] [Indexed: 11/09/2022]
Affiliation(s)
- A A Akintola
- School of Industrial Technology Advances, Kyungpook National University, Daegu, 41566, Republic of Korea Department of Chemistry, Mississippi State University, USA Department of Biology, Teachers College and Institute for Phylogenomics and Evolution, Kyungpook National University, Daegu, 41566, Republic of Korea Institute for Korean Herb-Bio Convergence Promotion, Kyungpook National University, Daegu, 41566, Republic of Korea Phylomics Inc., Daegu, 41910, Republic of Korea
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19
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Vanbesien M, Molenberghs G, Geenen C, Thibaut J, Gorissen S, André E, Raymenants J. Risk factors for SARS-CoV-2 transmission in student residences: a case-ascertained study. Arch Public Health 2022; 80:212. [PMID: 36131328 PMCID: PMC9491668 DOI: 10.1186/s13690-022-00966-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 09/07/2022] [Indexed: 11/15/2022] Open
Abstract
Background We aimed to investigate the overall secondary attack rates (SAR) of COVID-19 in student residences and to identify risk factors for higher transmission. Methods We retrospectively analysed the SAR in living units of student residences which were screened in Leuven (Belgium) following the detection of a COVID-19 case. Students were followed up in the framework of a routine testing and tracing follow-up system. We considered residence outbreaks followed up between October 30th 2020 and May 25th 2021. We used generalized estimating equations (GEE) to evaluate the impact of delay to follow-up, shared kitchen or sanitary facilities, the presence of a known external infection source and the recent occurrence of a social gathering. We used a generalized linear mixed model (GLMM) for validation. Results We included 165 student residences, representing 200 residence units (N screened residents = 2324). Secondary transmission occurred in 68 units which corresponded to 176 secondary cases. The overall observed SAR was 8.2%. In the GEE model, shared sanitary facilities (p = 0.04) and the recent occurrence of a social gathering (p = 0.003) were associated with a significant increase in SAR in a living unit, which was estimated at 3% (95%CI 1.5-5.2) in the absence of any risk factor and 13% (95%CI 11.4-15.8) in the presence of both. The GLMM confirmed these findings. Conclusions Shared sanitary facilities and the occurrence of social gatherings increase the risk of COVID-19 transmission and should be considered when screening and implementing preventive measures. Supplementary Information The online version contains supplementary material available at 10.1186/s13690-022-00966-4.
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20
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Nickbakhsh S, Hughes J, Christofidis N, Griffiths E, Shaaban S, Enright J, Smollett K, Nomikou K, Palmalux N, Tong L, Carmichael S, Sreenu VB, Orton R, Goldstein EJ, Tomb RM, Templeton K, Gunson RN, da Silva Filipe A, Milosevic C, Thomson E, Robertson DL, Holden MTG, Illingworth CJR, Smith-Palmer A. Genomic epidemiology of SARS-CoV-2 in a university outbreak setting and implications for public health planning. Sci Rep 2022; 12:11735. [PMID: 35853960 PMCID: PMC9296497 DOI: 10.1038/s41598-022-15661-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 06/27/2022] [Indexed: 11/09/2022] Open
Abstract
Whole genome sequencing of SARS-CoV-2 has occurred at an unprecedented scale, and can be exploited for characterising outbreak risks at the fine-scale needed to inform control strategies. One setting at continued risk of COVID-19 outbreaks are higher education institutions, associated with student movements at the start of term, close living conditions within residential halls, and high social contact rates. Here we analysed SARS-CoV-2 whole genome sequences in combination with epidemiological data to investigate a large cluster of student cases associated with University of Glasgow accommodation in autumn 2020, Scotland. We identified 519 student cases of SARS-CoV-2 infection associated with this large cluster through contact tracing data, with 30% sequencing coverage for further analysis. We estimated at least 11 independent introductions of SARS-CoV-2 into the student population, with four comprising the majority of detected cases and consistent with separate outbreaks. These four outbreaks were curtailed within a week following implementation of control measures. The impact of student infections on the local community was short-term despite an underlying increase in community infections. Our study highlights the need for context-specific information in the formation of public health policy for higher educational settings.
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Affiliation(s)
- Sema Nickbakhsh
- Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow, G2 6QE, UK.
- Institute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Graham Kerr Building, Glasgow, G12 8QQ, UK.
| | - Joseph Hughes
- Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow, G2 6QE, UK
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | | | - Emily Griffiths
- Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow, G2 6QE, UK
| | - Sharif Shaaban
- Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow, G2 6QE, UK
| | - Jessica Enright
- School of Computing Science, University of Glasgow, 18 Lilybank Gardens, Glasgow, G12 8RZ, UK
| | - Katherine Smollett
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | - Kyriaki Nomikou
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | - Natasha Palmalux
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | - Lily Tong
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | - Stephen Carmichael
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | - Vattipally B Sreenu
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | - Richard Orton
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | - Emily J Goldstein
- West of Scotland Specialist Virology Centre, NHS Greater Glasgow and Clyde, Glasgow Royal Infirmary, New Lister Building, Glasgow, G31 2ER, UK
| | - Rachael M Tomb
- West of Scotland Specialist Virology Centre, NHS Greater Glasgow and Clyde, Glasgow Royal Infirmary, New Lister Building, Glasgow, G31 2ER, UK
| | - Kate Templeton
- Royal Infirmary of Edinburgh, NHS Lothian, 51 Little France Crescent, Edinburgh, EH16 4SA, UK
| | - Rory N Gunson
- West of Scotland Specialist Virology Centre, NHS Greater Glasgow and Clyde, Glasgow Royal Infirmary, New Lister Building, Glasgow, G31 2ER, UK
| | - Ana da Silva Filipe
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | - Catriona Milosevic
- NHS Greater Glasgow and Clyde, Gartnavel General Hospital, 1055 Great Western Road, Glasgow, G12 0XH, UK
| | - Emma Thomson
- Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow, G2 6QE, UK
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | - David L Robertson
- Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow, G2 6QE, UK
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK
| | - Matthew T G Holden
- Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow, G2 6QE, UK
- School of Medicine, University of St Andrews, North Haugh, St Andrews, KY16 9TF, UK
| | - Christopher J R Illingworth
- MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, G61 1QH, UK.
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK.
- MRC Biostatistics Unit, University of Cambridge, East Forvie Building, Forvie Site, Robinson Way, Cambridge, CB2 0SR, UK.
| | - Alison Smith-Palmer
- Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow, G2 6QE, UK
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21
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Chaguza C, Hahn AM, Petrone ME, Zhou S, Ferguson D, Breban MI, Pham K, Peña-Hernández MA, Castaldi C, Hill V, Yale SARS-CoV-2 Genomic Surveillance Initiative, Schulz W, Swanstrom RI, Roberts SC, Grubaugh ND. Accelerated SARS-CoV-2 intrahost evolution leading to distinct genotypes during chronic infection. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.06.29.22276868. [PMID: 35794895 PMCID: PMC9258298 DOI: 10.1101/2022.06.29.22276868] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
The chronic infection hypothesis for novel SARS-CoV-2 variant emergence is increasingly gaining credence following the appearance of Omicron. Here we investigate intrahost evolution and genetic diversity of lineage B.1.517 during a SARS-CoV-2 chronic infection lasting for 471 days (and still ongoing) with consistently recovered infectious virus and high viral loads. During the infection, we found an accelerated virus evolutionary rate translating to 35 nucleotide substitutions per year, approximately two-fold higher than the global SARS-CoV-2 evolutionary rate. This intrahost evolution led to the emergence and persistence of at least three genetically distinct genotypes suggesting the establishment of spatially structured viral populations continually reseeding different genotypes into the nasopharynx. Finally, using unique molecular indexes for accurate intrahost viral sequencing, we tracked the temporal dynamics of genetic diversity to identify advantageous mutations and highlight hallmark changes for chronic infection. Our findings demonstrate that untreated chronic infections accelerate SARS-CoV-2 evolution, ultimately providing opportunity for the emergence of genetically divergent and potentially highly transmissible variants as seen with Delta and Omicron.
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Affiliation(s)
- Chrispin Chaguza
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Anne M. Hahn
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Mary E. Petrone
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
- School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia
| | - Shuntai Zhou
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - David Ferguson
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Mallery I. Breban
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Kien Pham
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Mario A. Peña-Hernández
- Department of Biological and Biomedical Sciences, Yale School of Medicine, New Haven, Connecticut, USA
| | | | - Verity Hill
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | | | - Wade Schulz
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, USA
- Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, USA
| | - Ronald I. Swanstrom
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Nathan D. Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
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22
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Leeman D, Flannagan J, Chudasama D, Dack K, Anderson C, Dabrera G, Lamagni T. Effect of Returning University Students on COVID-19 Infections in England, 2020. Emerg Infect Dis 2022; 28:1366-1374. [PMID: 35642474 PMCID: PMC9239898 DOI: 10.3201/eid2807.212332] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Each September in England, ≈1 million students relocate to study at universities. To determine COVID-19 cases and outbreaks among university students after their return to university during the COVID pandemic in September 2020, we identified students with COVID-19 (student case-patients) by reviewing contact tracing records identifying attendance at university and residence in student accommodations identified by matching case-patients’ residential addresses with national property databases. We determined COVID-19 rates in towns/cities with and without a university campus. We identified 53,430 student case-patients during September 1–December 31, 2020, which accounted for 2.7% of all cases during this period. Student case-patients increased rapidly after the start of the term, driven initially by cases and outbreaks in student accommodations. Case rates among students 18–23 years of age doubled at the start of term in towns with universities. Our findings highlight the need for face-to-face and control measures to reduce virus transmission.
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23
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Illingworth CJR, Hamilton WL, Jackson C, Warne B, Popay A, Meredith L, Hosmillo M, Jahun A, Fieldman T, Routledge M, Houldcroft CJ, Caller L, Caddy S, Yakovleva A, Hall G, Khokhar FA, Feltwell T, Pinckert ML, Georgana I, Chaudhry Y, Curran M, Parmar S, Sparkes D, Rivett L, Jones NK, Sridhar S, Forrest S, Dymond T, Grainger K, Workman C, Gkrania-Klotsas E, Brown NM, Weekes MP, Baker S, Peacock SJ, Gouliouris T, Goodfellow I, Angelis DD, Török ME. A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events. Mol Biol Evol 2022; 39:msac025. [PMID: 35106603 PMCID: PMC8892943 DOI: 10.1093/molbev/msac025] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Identifying linked cases of infection is a critical component of the public health response to viral infectious diseases. In a clinical context, there is a need to make rapid assessments of whether cases of infection have arrived independently onto a ward, or are potentially linked via direct transmission. Viral genome sequence data are of great value in making these assessments, but are often not the only form of data available. Here, we describe A2B-COVID, a method for the rapid identification of potentially linked cases of COVID-19 infection designed for clinical settings. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and evolutionary analysis of genome sequences to assess whether data collected from cases of infection are consistent or inconsistent with linkage via direct transmission. A retrospective analysis of data from two wards at Cambridge University Hospitals NHS Foundation Trust during the first wave of the pandemic showed qualitatively different patterns of linkage between cases on designated COVID-19 and non-COVID-19 wards. The subsequent real-time application of our method to data from the second epidemic wave highlights its value for monitoring cases of infection in a clinical context.
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Affiliation(s)
- Christopher J R Illingworth
- MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom
- Institut für Biologische Physik, Universität zu Köln, Köln, Germany
| | - William L Hamilton
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | | | - Ben Warne
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Ashley Popay
- Public Health England Field Epidemiology Unit, Cambridge Institute of Public Health, Cambridge, United Kingdom
| | - Luke Meredith
- Department of Pathology, Division of Virology, University of Cambridge, Cambridge, United Kingdom
| | - Myra Hosmillo
- Department of Pathology, Division of Virology, University of Cambridge, Cambridge, United Kingdom
| | - Aminu Jahun
- Department of Pathology, Division of Virology, University of Cambridge, Cambridge, United Kingdom
| | - Tom Fieldman
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Matthew Routledge
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Clinical Microbiology and Public Health Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | | | | | - Sarah Caddy
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge, United Kingdom
| | - Anna Yakovleva
- Department of Pathology, Division of Virology, University of Cambridge, Cambridge, United Kingdom
| | - Grant Hall
- Department of Pathology, Division of Virology, University of Cambridge, Cambridge, United Kingdom
| | - Fahad A Khokhar
- Department of Pathology, Division of Virology, University of Cambridge, Cambridge, United Kingdom
| | - Theresa Feltwell
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Malte L Pinckert
- Department of Pathology, Division of Virology, University of Cambridge, Cambridge, United Kingdom
| | - Iliana Georgana
- Department of Pathology, Division of Virology, University of Cambridge, Cambridge, United Kingdom
| | - Yasmin Chaudhry
- Department of Pathology, Division of Virology, University of Cambridge, Cambridge, United Kingdom
| | - Martin Curran
- Clinical Microbiology and Public Health Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Surendra Parmar
- Clinical Microbiology and Public Health Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Dominic Sparkes
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Clinical Microbiology and Public Health Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Lucy Rivett
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Clinical Microbiology and Public Health Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Nick K Jones
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Clinical Microbiology and Public Health Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Sushmita Sridhar
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge, United Kingdom
- Wellcome Sanger Institute, Hinxton, United Kingdom
| | | | - Tom Dymond
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Kayleigh Grainger
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Chris Workman
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Effrossyni Gkrania-Klotsas
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- MRC Epidemiology Unit, University of Cambridge, Level 3 Institute of Metabolic Science, Cambridge, United Kingdom
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Nicholas M Brown
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Clinical Microbiology and Public Health Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Michael P Weekes
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge, United Kingdom
| | - Stephen Baker
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge, United Kingdom
| | - Sharon J Peacock
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
- Wellcome Sanger Institute, Hinxton, United Kingdom
| | - Theodore Gouliouris
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
- Clinical Microbiology and Public Health Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Ian Goodfellow
- Department of Pathology, Division of Virology, University of Cambridge, Cambridge, United Kingdom
| | - Daniela De Angelis
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
- Public Health England, National Infection Service, London, United Kingdom
| | - M Estée Török
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
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24
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Aggarwal D, Warne B, Jahun AS, Hamilton WL, Fieldman T, du Plessis L, Hill V, Blane B, Watkins E, Wright E, Hall G, Ludden C, Myers R, Hosmillo M, Chaudhry Y, Pinckert ML, Georgana I, Izuagbe R, Leek D, Nsonwu O, Hughes GJ, Packer S, Page AJ, Metaxaki M, Fuller S, Weale G, Holgate J, Brown CA, Howes R, McFarlane D, Dougan G, Pybus OG, Angelis DD, Maxwell PH, Peacock SJ, Weekes MP, Illingworth C, Harrison EM, Matheson NJ, Goodfellow IG. Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission. Nat Commun 2022; 13:751. [PMID: 35136068 PMCID: PMC8826310 DOI: 10.1038/s41467-021-27942-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 12/17/2021] [Indexed: 12/20/2022] Open
Abstract
Understanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.
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Affiliation(s)
- Dinesh Aggarwal
- University of Cambridge, Department of Medicine, Cambridge, UK.
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK.
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK.
- Wellcome Sanger Institute, Hinxton, Cambridge, UK.
| | - Ben Warne
- University of Cambridge, Department of Medicine, Cambridge, UK
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge, UK
| | - Aminu S Jahun
- University of Cambridge, Department of Pathology, Division of Virology, Cambridge, UK
| | - William L Hamilton
- University of Cambridge, Department of Medicine, Cambridge, UK
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - Thomas Fieldman
- University of Cambridge, Department of Medicine, Cambridge, UK
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
| | | | - Verity Hill
- Institute of Evolutionary Virology, University of Edinburgh, Edinburgh, UK
| | - Beth Blane
- University of Cambridge, Department of Medicine, Cambridge, UK
| | - Emmeline Watkins
- Public Health Directorate, Cambridgeshire County Council and Peterborough City Council, Peterborough, UK
| | - Elizabeth Wright
- Public Health Directorate, Cambridgeshire County Council and Peterborough City Council, Peterborough, UK
| | - Grant Hall
- University of Cambridge, Department of Pathology, Division of Virology, Cambridge, UK
| | - Catherine Ludden
- University of Cambridge, Department of Medicine, Cambridge, UK
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Richard Myers
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Myra Hosmillo
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
- University of Cambridge, Department of Pathology, Division of Virology, Cambridge, UK
| | - Yasmin Chaudhry
- University of Cambridge, Department of Pathology, Division of Virology, Cambridge, UK
| | - Malte L Pinckert
- University of Cambridge, Department of Pathology, Division of Virology, Cambridge, UK
| | - Iliana Georgana
- University of Cambridge, Department of Pathology, Division of Virology, Cambridge, UK
| | - Rhys Izuagbe
- University of Cambridge, Department of Pathology, Division of Virology, Cambridge, UK
| | - Danielle Leek
- University of Cambridge, Department of Medicine, Cambridge, UK
| | | | - Gareth J Hughes
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Simon Packer
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Andrew J Page
- Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK
| | - Marina Metaxaki
- University of Cambridge, Department of Medicine, Cambridge, UK
| | - Stewart Fuller
- University of Cambridge, Department of Medicine, Cambridge, UK
| | - Gillian Weale
- Health, Safety & Regulated Facilities Division, University of Cambridge, Cambridge, UK
| | - Jon Holgate
- University Information Services, University of Cambridge, Cambridge, UK
| | - Christopher A Brown
- Cambridge Covid-19 Testing Centre, Discovery Sciences, R&D, AstraZenenca, Cambridge, UK
- Charles River Laboratories, Chesterford Research Park, Saffron Walden, CB10 1XL, UK
| | - Rob Howes
- Cambridge Covid-19 Testing Centre, Discovery Sciences, R&D, AstraZenenca, Cambridge, UK
| | - Duncan McFarlane
- Institute for Manufacturing, University of Cambridge, Cambridge, UK
| | - Gordon Dougan
- University of Cambridge, Department of Medicine, Cambridge, UK
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge, UK
| | | | - Daniela De Angelis
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
- MRC Biostatistics Unit, University of Cambridge, East Forvie Building, Forvie Site, Robinson Way, Cambridge, CB2 0SR, UK
| | - Patrick H Maxwell
- University of Cambridge, Department of Medicine, Cambridge, UK
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
| | - Sharon J Peacock
- University of Cambridge, Department of Medicine, Cambridge, UK
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
| | - Michael P Weekes
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
- Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
| | - Chris Illingworth
- MRC Biostatistics Unit, University of Cambridge, East Forvie Building, Forvie Site, Robinson Way, Cambridge, CB2 0SR, UK
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Ewan M Harrison
- University of Cambridge, Department of Medicine, Cambridge, UK.
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK.
- Wellcome Sanger Institute, Hinxton, Cambridge, UK.
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Nicholas J Matheson
- University of Cambridge, Department of Medicine, Cambridge, UK.
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK.
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge, UK.
- NHS Blood and Transplant, Cambridge, UK.
| | - Ian G Goodfellow
- University of Cambridge, Department of Pathology, Division of Virology, Cambridge, UK.
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