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Truong Nguyen P, Kant R, Van den Broeck F, Suvanto MT, Alburkat H, Virtanen J, Ahvenainen E, Castren R, Hong SL, Baele G, Ahava MJ, Jarva H, Jokiranta ST, Kallio-Kokko H, Kekäläinen E, Kirjavainen V, Kortela E, Kurkela S, Lappalainen M, Liimatainen H, Suchard MA, Hannula S, Ellonen P, Sironen T, Lemey P, Vapalahti O, Smura T. The phylodynamics of SARS-CoV-2 during 2020 in Finland. COMMUNICATIONS MEDICINE 2022; 2:65. [PMID: 35698660 PMCID: PMC9187640 DOI: 10.1038/s43856-022-00130-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 05/23/2022] [Indexed: 02/01/2023] Open
Abstract
Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of infections and fatalities globally since its emergence in late 2019. The virus was first detected in Finland in January 2020, after which it rapidly spread among the populace in spring. However, compared to other European nations, Finland has had a low incidence of SARS-CoV-2. To gain insight into the origins and turnover of SARS-CoV-2 lineages circulating in Finland in 2020, we investigated the phylogeographic and -dynamic history of the virus. Methods The origins of SARS-CoV-2 introductions were inferred via Travel-aware Bayesian time-measured phylogeographic analyses. Sequences for the analyses included virus genomes belonging to the B.1 lineage and with the D614G mutation from countries of likely origin, which were determined utilizing Google mobility data. We collected all available sequences from spring and fall peaks to study lineage dynamics. Results We observed rapid turnover among Finnish lineages during this period. Clade 20C became the most prevalent among sequenced cases and was replaced by other strains in fall 2020. Bayesian phylogeographic reconstructions suggested 42 independent introductions into Finland during spring 2020, mainly from Italy, Austria, and Spain. Conclusions A single introduction from Spain might have seeded one-third of cases in Finland during spring in 2020. The investigations of the original introductions of SARS-CoV-2 to Finland during the early stages of the pandemic and of the subsequent lineage dynamics could be utilized to assess the role of transboundary movements and the effects of early intervention and public health measures.
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Affiliation(s)
- Phuoc Truong Nguyen
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Ravi Kant
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Frederik Van den Broeck
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Maija T. Suvanto
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Hussein Alburkat
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jenni Virtanen
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Ella Ahvenainen
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Robert Castren
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Samuel L. Hong
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Maarit J. Ahava
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Hanna Jarva
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Translational Immunology Research Program, University of Helsinki, Helsinki, Finland
- Department of Bacteriology and Immunology, University of Helsinki, Helsinki, Finland
| | - Suvi Tuulia Jokiranta
- Translational Immunology Research Program, University of Helsinki, Helsinki, Finland
- Department of Bacteriology and Immunology, University of Helsinki, Helsinki, Finland
| | - Hannimari Kallio-Kokko
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Eliisa Kekäläinen
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Translational Immunology Research Program, University of Helsinki, Helsinki, Finland
| | - Vesa Kirjavainen
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Elisa Kortela
- Infectious Diseases, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Satu Kurkela
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Maija Lappalainen
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Hanna Liimatainen
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Marc A. Suchard
- Departments of Biomathematics, Biostatistics and Human Genetics, University of California, Los Angeles (UCLA), Los Angeles, CA USA
| | - Sari Hannula
- Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Pekka Ellonen
- Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Tarja Sironen
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Olli Vapalahti
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Teemu Smura
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- HUS Diagnostic Center, HUSLAB, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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2
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Wells CR, Pandey A, Fitzpatrick MC, Crystal WS, Singer BH, Moghadas SM, Galvani AP, Townsend JP. Quarantine and testing strategies to ameliorate transmission due to travel during the COVID-19 pandemic: a modelling study. THE LANCET REGIONAL HEALTH. EUROPE 2022; 14:100304. [PMID: 35036981 PMCID: PMC8743228 DOI: 10.1016/j.lanepe.2021.100304] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND Numerous countries have imposed strict travel restrictions during the COVID-19 pandemic, contributing to a large socioeconomic burden. The long quarantines that have been applied to contacts of cases may be excessive for travel policy. METHODS We developed an approach to evaluate imminent countrywide COVID-19 infections after 0-14-day quarantine and testing. We identified the minimum travel quarantine duration such that the infection rate within the destination country did not increase compared to a travel ban, defining this minimum quarantine as "sufficient." FINDINGS We present a generalised analytical framework and a specific case study of the epidemic situation on November 21, 2021, for application to 26 European countries. For most origin-destination country pairs, a three-day or shorter quarantine with RT-PCR or antigen testing on exit suffices. Adaptation to the European Union traffic-light risk stratification provided a simplified policy tool. Our analytical approach provides guidance for travel policy during all phases of pandemic diseases. INTERPRETATION For nearly half of origin-destination country pairs analysed, travel can be permitted in the absence of quarantine and testing. For the majority of pairs requiring controls, a short quarantine with testing could be as effective as a complete travel ban. The estimated travel quarantine durations are substantially shorter than those specified for traced contacts. FUNDING EasyJet (JPT and APG), the Elihu endowment (JPT), the Burnett and Stender families' endowment (APG), the Notsew Orm Sands Foundation (JPT and APG), the National Institutes of Health (MCF), Canadian Institutes of Health Research (SMM) and Natural Sciences and Engineering Research Council of Canada EIDM-MfPH (SMM).
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Affiliation(s)
- Chad R. Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, 06520, USA
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, 06520, USA
| | - Meagan C. Fitzpatrick
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, 06520, USA
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland, 21201, USA
| | - William S. Crystal
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, 06520, USA
| | - Burton H. Singer
- Emerging Pathogens Institute, University of Florida, P.O. Box 100009, Gainesville, FL, 32610, USA
| | - Seyed M. Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada
| | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, 06520, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, 06525, USA
| | - Jeffrey P. Townsend
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, 06525, USA
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, 06510, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, 06511, USA
- Program in Microbiology, Yale University, New Haven, Connecticut, 06511, USA
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3
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Wells CR, Pandey A, Fitzpatrick MC, Crystal WS, Singer BH, Moghadas SM, Galvani AP, Townsend JP. Quarantine and testing strategies to ameliorate transmission due to travel during the COVID-19 pandemic: a modelling study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.04.25.21256082. [PMID: 34729563 PMCID: PMC8562544 DOI: 10.1101/2021.04.25.21256082] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND Numerous countries imposed strict travel restrictions, contributing to the large socioeconomic burden during the COVID-19 pandemic. The long quarantines that apply to contacts of cases may be excessive for travel policy. METHODS We developed an approach to evaluate imminent countrywide COVID-19 infections after 0-14-day quarantine and testing. We identified the minimum travel quarantine duration such that the infection rate within the destination country did not increase compared to a travel ban, defining this minimum quarantine as "sufficient." FINDINGS We present a generalised analytical framework and a specific case study of the epidemic situation on November 21, 2021, for application to 26 European countries. For most origin-destination country pairs, a three-day or shorter quarantine with RT-PCR or antigen testing on exit suffices. Adaptation to the European Union traffic-light risk stratification provided a simplified policy tool. Our analytical approach provides guidance for travel policy during all phases of pandemic diseases. INTERPRETATION For nearly half of origin-destination country pairs analysed, travel can be permitted in the absence of quarantine and testing. For the majority of pairs requiring controls, a short quarantine with testing could be as effective as a complete travel ban. The estimated travel quarantine durations are substantially shorter than those specified for traced contacts. FUNDING EasyJet (JPT and APG), the Elihu endowment (JPT), the Burnett and Stender families' endowment (APG), the Notsew Orm Sands Foundation (JPT and APG), the National Institutes of Health (MCF), Canadian Institutes of Health Research (SMM) and Natural Sciences and Engineering Research Council of Canada EIDM-MfPH (SMM).
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Affiliation(s)
- Chad R. Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
| | - Meagan C. Fitzpatrick
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland, 21201, USA
| | - William S. Crystal
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
| | - Burton H. Singer
- Emerging Pathogens Institute, University of Florida, P.O. Box 100009, Gainesville, FL 32610, USA
| | | | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 06525, USA
| | - Jeffrey P. Townsend
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 06525, USA
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut 06510, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06511, USA
- Program in Microbiology, Yale University, New Haven, Connecticut 06511, USA
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4
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Smith MR, Trofimova M, Weber A, Duport Y, Kühnert D, von Kleist M. Rapid incidence estimation from SARS-CoV-2 genomes reveals decreased case detection in Europe during summer 2020. Nat Commun 2021; 12:6009. [PMID: 34650062 PMCID: PMC8517019 DOI: 10.1038/s41467-021-26267-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 09/24/2021] [Indexed: 12/24/2022] Open
Abstract
By October 2021, 230 million SARS-CoV-2 diagnoses have been reported. Yet, a considerable proportion of cases remains undetected. Here, we propose GInPipe, a method that rapidly reconstructs SARS-CoV-2 incidence profiles solely from publicly available, time-stamped viral genomes. We validate GInPipe against simulated outbreaks and elaborate phylodynamic analyses. Using available sequence data, we reconstruct incidence histories for Denmark, Scotland, Switzerland, and Victoria (Australia) and demonstrate, how to use the method to investigate the effects of changing testing policies on case ascertainment. Specifically, we find that under-reporting was highest during summer 2020 in Europe, coinciding with more liberal testing policies at times of low testing capacities. Due to the increased use of real-time sequencing, it is envisaged that GInPipe can complement established surveillance tools to monitor the SARS-CoV-2 pandemic. In post-pandemic times, when diagnostic efforts are decreasing, GInPipe may facilitate the detection of hidden infection dynamics.
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Affiliation(s)
- Maureen Rebecca Smith
- Systems Medicine of Infectious Disease (P5), Robert Koch Institute, Berlin, Germany.
- Bioinformatics (MF1), Robert Koch Institute, Berlin, Germany.
| | - Maria Trofimova
- Systems Medicine of Infectious Disease (P5), Robert Koch Institute, Berlin, Germany
- Bioinformatics (MF1), Robert Koch Institute, Berlin, Germany
| | - Ariane Weber
- Transmission, Infection, Diversification and Evolution Group, Max-Planck Institute for the Science of Human History, Jena, Germany
| | - Yannick Duport
- Systems Medicine of Infectious Disease (P5), Robert Koch Institute, Berlin, Germany
- Bioinformatics (MF1), Robert Koch Institute, Berlin, Germany
| | - Denise Kühnert
- Transmission, Infection, Diversification and Evolution Group, Max-Planck Institute for the Science of Human History, Jena, Germany
- German COVID Omics Initiative (deCOI), Bonn, Germany
| | - Max von Kleist
- Systems Medicine of Infectious Disease (P5), Robert Koch Institute, Berlin, Germany.
- Bioinformatics (MF1), Robert Koch Institute, Berlin, Germany.
- German COVID Omics Initiative (deCOI), Bonn, Germany.
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5
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Arutkin M, Faranda D, Alberti T, Vallée A. Delayed epidemic peak caused by infection and recovery rate fluctuations. CHAOS (WOODBURY, N.Y.) 2021; 31:101107. [PMID: 34717319 DOI: 10.1063/5.0067625] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 09/13/2021] [Indexed: 06/13/2023]
Abstract
Forecasting epidemic scenarios has been critical to many decision-makers in imposing various public health interventions. Despite progresses in determining the magnitude and timing of epidemics, epidemic peak time predictions for H1N1 and COVID-19 were inaccurate, with the peaks delayed with respect to predictions. Here, we show that infection and recovery rate fluctuations play a critical role in peak timing. Using a susceptible-infected-recovered model with daily fluctuations on control parameters, we show that infection counts follow a lognormal distribution at the beginning of an epidemic wave, similar to price distributions for financial assets. The epidemic peak time of the stochastic solution exhibits an inverse Gaussian probability distribution, fitting the spread of the epidemic peak times observed across Italian regions. We also show that, for a given basic reproduction number R0, the deterministic model anticipates the peak with respect to the most probable and average peak time of the stochastic model. The epidemic peak time distribution allows one for a robust estimation of the epidemic evolution. Considering these results, we believe that the parameters' dynamical fluctuations are paramount to accurately predict the epidemic peak time and should be introduced in epidemiological models.
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Affiliation(s)
- Maxence Arutkin
- UMR CNRS 7083 Gulliver, ESPCI Paris, 10 rue Vauquelin, 75005 Paris, France
| | - Davide Faranda
- Laboratoire des Sciences du Climat et de l'Environnement, CEA Saclay l'Orme des Merisiers, UMR 8212 CEA-CNRS-UVSQ, Université Paris-Saclay & IPSL, 91191 Gif-sur-Yvette, France
| | - Tommaso Alberti
- INAF-Istituto di Astrofisica e Planetologia Spaziali, via del Fosso del Cavaliere 100, 00133 Rome, Italy
| | - Alexandre Vallée
- Department of Clinical Research and Innovation, Foch hospital, 92150 Suresnes, France
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6
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Kraemer MUG, Hill V, Ruis C, Dellicour S, Bajaj S, McCrone JT, Baele G, Parag KV, Battle AL, Gutierrez B, Jackson B, Colquhoun R, O'Toole Á, Klein B, Vespignani A, Volz E, Faria NR, Aanensen DM, Loman NJ, du Plessis L, Cauchemez S, Rambaut A, Scarpino SV, Pybus OG. Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence. Science 2021; 373:889-895. [PMID: 34301854 PMCID: PMC9269003 DOI: 10.1126/science.abj0113] [Citation(s) in RCA: 93] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 07/12/2021] [Indexed: 12/24/2022]
Abstract
Understanding the causes and consequences of the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern is crucial to pandemic control yet difficult to achieve because they arise in the context of variable human behavior and immunity. We investigated the spatial invasion dynamics of lineage B.1.1.7 by jointly analyzing UK human mobility, virus genomes, and community-based polymerase chain reaction data. We identified a multistage spatial invasion process in which early B.1.1.7 growth rates were associated with mobility and asymmetric lineage export from a dominant source location, enhancing the effects of B.1.1.7's increased intrinsic transmissibility. We further explored how B.1.1.7 spread was shaped by nonpharmaceutical interventions and spatial variation in previous attack rates. Our findings show that careful accounting of the behavioral and epidemiological context within which variants of concern emerge is necessary to interpret correctly their observed relative growth rates.
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Affiliation(s)
- Moritz U G Kraemer
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil.
- Department of Zoology, University of Oxford, Oxford, UK
| | - Verity Hill
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Christopher Ruis
- Department of Zoology, University of Oxford, Oxford, UK
- Molecular Immunity Unit, Department of Medicine, Cambridge University, Cambridge, UK
| | - Simon Dellicour
- Network Science Institute, Northeastern University, Boston, USA
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
| | - Sumali Bajaj
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
- Department of Zoology, University of Oxford, Oxford, UK
| | - John T McCrone
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Guy Baele
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, UK
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
| | - Kris V Parag
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Anya Lindström Battle
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Department of Plant Sciences, University of Oxford, Oxford, UK
| | - Bernardo Gutierrez
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
- Department of Plant Sciences, University of Oxford, Oxford, UK
- Department of Zoology, University of Oxford, Oxford, UK
| | - Ben Jackson
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Rachel Colquhoun
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Áine O'Toole
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Brennan Klein
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
- Network Science Institute, Northeastern University, Boston, USA
| | - Alessandro Vespignani
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
- Network Science Institute, Northeastern University, Boston, USA
| | - Erik Volz
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Nuno R Faria
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
- Department of Zoology, University of Oxford, Oxford, UK
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
| | - David M Aanensen
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Nicholas J Loman
- Molecular Immunity Unit, Department of Medicine, Cambridge University, Cambridge, UK
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
| | - Louis du Plessis
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil
- Department of Zoology, University of Oxford, Oxford, UK
| | - Simon Cauchemez
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
| | - Andrew Rambaut
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France.
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Samuel V Scarpino
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium.
- Network Science Institute, Northeastern University, Boston, USA
- Vermont Complex Systems Center, University of Vermont, Burlington, USA
- Santa Fe Institute, Santa Fe, USA
| | - Oliver G Pybus
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil.
- Department of Zoology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK
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7
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Wu J, Zhang L, Zhang Y, Wang H, Ding R, Nie J, Li Q, Liu S, Yu Y, Yang X, Duan K, Qu X, Wang Y, Huang W. The Antigenicity of Epidemic SARS-CoV-2 Variants in the United Kingdom. Front Immunol 2021; 12:687869. [PMID: 34220844 PMCID: PMC8247764 DOI: 10.3389/fimmu.2021.687869] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 05/24/2021] [Indexed: 11/13/2022] Open
Abstract
To determine whether the neutralization activity of monoclonal antibodies, convalescent sera and vaccine-elicited sera was affected by the top five epidemic SARS-CoV-2 variants in the UK, including D614G+L18F+A222V, D614G+A222V, D614G+S477N, VOC-202012/01(B.1.1.7) and D614G+69-70del+N439K, a pseudovirus-neutralization assay was performed to evaluate the relative neutralization titers against the five SARS-CoV-2 variants and 12 single deconvolution mutants based on the variants. In this study, 18 monoclonal antibodies, 10 sera from convalescent COVID-19 patients, 10 inactivated-virus vaccine-elicited sera, 14 mRNA vaccine-elicited sera, nine RBD-immunized mouse sera, four RBD-immunized horse sera, and four spike-encoding DNA-immunized guinea pig sera were tested and analyzed. The N501Y, N439K, and S477N mutations caused immune escape from nine of 18 mAbs. However, the convalescent sera, inactivated virus vaccine-elicited sera, mRNA vaccine-elicited sera, spike DNA-elicited sera, and recombinant RBD protein-elicited sera could still neutralize these variants (within three-fold changes compared to the reference D614G variant). The neutralizing antibody responses to different types of vaccines were different, whereby the response to inactivated-virus vaccine was similar to the convalescent sera.
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Affiliation(s)
- Jiajing Wu
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
- Wuhan Institute of Biological Products, Hubei, China
| | - Li Zhang
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
| | - Yue Zhang
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
- National Vaccine & Serum Institute, Beijing, China
| | - Haixin Wang
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
- Department of Pharmaceutical Engineering, College of Life Science and Technology, Dalian University, Dalian, China
| | - Ruxia Ding
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
| | - Jianhui Nie
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
| | - Qianqian Li
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
- Graduate School of Peking Union Medical College, Beijing, China
| | - Shuo Liu
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
| | - Yongxin Yu
- Wuhan Institute of Biological Products, Hubei, China
- Department of Arboviral Vaccine, National Institutes for Food and Drug Control, Beijing, China
| | - Xiaoming Yang
- China National Biotec Group Company Limited, Beijing, China
| | - Kai Duan
- Wuhan Institute of Biological Products, Hubei, China
- National Engineering Technology Research Center for Combined Vaccines, Wuhan Institute of Biological Products Co. Ltd., Wuhan, China
| | - Xiaowang Qu
- Translational Medicine Institute, First People’s Hospital of Chenzhou, University of South China, Chenzhou, China
| | - Youchun Wang
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
| | - Weijin Huang
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China
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