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Jimenez-Silva C, Rivero R, Douglas J, Bouckaert R, Villabona-Arenas CJ, Atkins KE, Gastelbondo B, Calderon A, Guzman C, Echeverri-De la Hoz D, Muñoz M, Ballesteros N, Castañeda S, Patiño LH, Ramirez A, Luna N, Paniz-Mondolfi A, Serrano-Coll H, Ramirez JD, Mattar S, Drummond AJ. Genomic epidemiology of SARS-CoV-2 variants during the first two years of the pandemic in Colombia. COMMUNICATIONS MEDICINE 2023; 3:97. [PMID: 37443390 DOI: 10.1038/s43856-023-00328-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 06/22/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND The emergence of highly transmissible SARS-CoV-2 variants has led to surges in cases and the need for global genomic surveillance. While some variants rapidly spread worldwide, other variants only persist nationally. There is a need for more fine-scale analysis to understand transmission dynamics at a country scale. For instance, the Mu variant of interest, also known as lineage B.1.621, was first detected in Colombia and was responsible for a large local wave but only a few sporadic cases elsewhere. METHODS To better understand the epidemiology of SARS-Cov-2 variants in Colombia, we used 14,049 complete SARS-CoV-2 genomes from the 32 states of Colombia. We performed Bayesian phylodynamic analyses to estimate the time of variants' introduction, their respective effective reproductive number, and effective population size, and the impact of disease control measures. RESULTS Here, we detect a total of 188 SARS-CoV-2 Pango lineages circulating in Colombia since the pandemic's start. We show that the effective reproduction number oscillated drastically throughout the first two years of the pandemic, with Mu showing the highest transmissibility (Re and growth rate estimation). CONCLUSIONS Our results reinforce that genomic surveillance programs are essential for countries to make evidence-driven interventions toward the emergence and circulation of novel SARS-CoV-2 variants.
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Affiliation(s)
- Cinthy Jimenez-Silva
- Centre for Computational Evolution, University of Auckland, Auckland, New Zealand.
- School of Biological Sciences, University of Auckland, Auckland, New Zealand.
| | - Ricardo Rivero
- Instituto de Investigaciones Biológicas del Trópico (IIBT), Facultad de Medicina Veterinaria y Zootecnia, Universidad de Córdoba, Montería, Colombia.
- Paul G. Allen School for Global Health, Washington State University, Pullman, Washington, USA.
| | - Jordan Douglas
- Centre for Computational Evolution, University of Auckland, Auckland, New Zealand
- Department of Physics, University of Auckland, Auckland, New Zealand
| | - Remco Bouckaert
- Centre for Computational Evolution, University of Auckland, Auckland, New Zealand
- School of Computer Science, University of Auckland, Auckland, New Zealand
| | - Ch Julian Villabona-Arenas
- Centre for Mathematical Modelling of Infectious Diseases and Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Katherine E Atkins
- Centre for Mathematical Modelling of Infectious Diseases and Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- Centre for Global Health, Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Bertha Gastelbondo
- Instituto de Investigaciones Biológicas del Trópico (IIBT), Facultad de Medicina Veterinaria y Zootecnia, Universidad de Córdoba, Montería, Colombia
- Grupo de Investigaciones Microbiológicas y Biomédicas de Córdoba-GIMBIC, Universidad de Córdoba, Monteria, Colombia
- Grupo de Salud Pública y Auditoría en Salud, Corporación Universitaria del Caribe- CECAR, Sincelejo, Colombia
| | - Alfonso Calderon
- Instituto de Investigaciones Biológicas del Trópico (IIBT), Facultad de Medicina Veterinaria y Zootecnia, Universidad de Córdoba, Montería, Colombia
| | - Camilo Guzman
- Instituto de Investigaciones Biológicas del Trópico (IIBT), Facultad de Medicina Veterinaria y Zootecnia, Universidad de Córdoba, Montería, Colombia
- Grupo de Investigación, Evaluación y Desarrollo de Farmacos y Afines - IDEFARMA, Universidad de Córdoba, Montería, Colombia
| | - Daniel Echeverri-De la Hoz
- Instituto de Investigaciones Biológicas del Trópico (IIBT), Facultad de Medicina Veterinaria y Zootecnia, Universidad de Córdoba, Montería, Colombia
| | - Marina Muñoz
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia
| | - Nathalia Ballesteros
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia
| | - Sergio Castañeda
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia
| | - Luz H Patiño
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia
| | - Angie Ramirez
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia
| | - Nicolas Luna
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia
| | - Alberto Paniz-Mondolfi
- Molecular Microbiology Laboratory, Department of Pathology, Molecular and Cell-based Medicine, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Hector Serrano-Coll
- Instituto Colombiano de Medicina Tropical-Universidad CES, Medellín, Colombia
| | - Juan David Ramirez
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia.
- Molecular Microbiology Laboratory, Department of Pathology, Molecular and Cell-based Medicine, Icahn School of Medicine at Mount Sinai, New York, USA.
| | - Salim Mattar
- Instituto de Investigaciones Biológicas del Trópico (IIBT), Facultad de Medicina Veterinaria y Zootecnia, Universidad de Córdoba, Montería, Colombia.
| | - Alexei J Drummond
- Centre for Computational Evolution, University of Auckland, Auckland, New Zealand
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
- School of Computer Science, University of Auckland, Auckland, New Zealand
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2
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Musa SS, Tariq A, Yuan L, Haozhen W, He D. Infection fatality rate and infection attack rate of COVID-19 in South American countries. Infect Dis Poverty 2022. [PMID: 35382879 DOI: 10.21203/rs.3.rs-1126392/v1] [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] [Indexed: 05/03/2023] Open
Abstract
BACKGROUND The ongoing COVID-19 pandemic hit South America badly with multiple waves. Different COVID-19 variants have been storming across the region, leading to more severe infections and deaths even in places with high vaccination coverage. This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate (IFR), infection attack rate (IAR) and reproduction number ([Formula: see text]) for twelve most affected South American countries. METHODS We fit a susceptible-exposed-infectious-recovered (SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities. Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization, Johns Hopkins Coronavirus Resource Center and Our World in Data. We investigate the COVID-19 mortalities in these countries, which could represent the situation for the overall South American region. We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR, IAR and [Formula: see text] of COVID-19 for the South American countries. RESULTS We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR (varies between 0.303% and 0.723%), IAR (varies between 0.03 and 0.784) and [Formula: see text] (varies between 0.7 and 2.5) for the 12 South American countries. We observe that the severity, dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous. Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America. CONCLUSIONS This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America. We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths. Thus, strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.
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Affiliation(s)
- Salihu Sabiu Musa
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
- Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria
| | - Amna Tariq
- Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, USA
| | - Liu Yuan
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
| | - Wei Haozhen
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
| | - Daihai He
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.
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3
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Musa SS, Tariq A, Yuan L, Haozhen W, He D. Infection fatality rate and infection attack rate of COVID-19 in South American countries. Infect Dis Poverty 2022; 11:40. [PMID: 35382879 PMCID: PMC8983329 DOI: 10.1186/s40249-022-00961-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 03/14/2022] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND The ongoing COVID-19 pandemic hit South America badly with multiple waves. Different COVID-19 variants have been storming across the region, leading to more severe infections and deaths even in places with high vaccination coverage. This study aims to assess the spatiotemporal variability of the COVID-19 pandemic and estimate the infection fatality rate (IFR), infection attack rate (IAR) and reproduction number ([Formula: see text]) for twelve most affected South American countries. METHODS We fit a susceptible-exposed-infectious-recovered (SEIR)-based model with a time-varying transmission rate to the reported COVID-19 deaths for the twelve South American countries with the highest mortalities. Most of the epidemiological datasets analysed in this work are retrieved from the disease surveillance systems by the World Health Organization, Johns Hopkins Coronavirus Resource Center and Our World in Data. We investigate the COVID-19 mortalities in these countries, which could represent the situation for the overall South American region. We employ COVID-19 dynamic model with-and-without vaccination considering time-varying flexible transmission rate to estimate IFR, IAR and [Formula: see text] of COVID-19 for the South American countries. RESULTS We simulate the model in each scenario under suitable parameter settings and yield biologically reasonable estimates for IFR (varies between 0.303% and 0.723%), IAR (varies between 0.03 and 0.784) and [Formula: see text] (varies between 0.7 and 2.5) for the 12 South American countries. We observe that the severity, dynamical patterns of deaths and time-varying transmission rates among the countries are highly heterogeneous. Further analysis of the model with the effect of vaccination highlights that increasing the vaccination rate could help suppress the pandemic in South America. CONCLUSIONS This study reveals possible reasons for the two waves of COVID-19 outbreaks in South America. We observed reductions in the transmission rate corresponding to each wave plausibly due to improvement in nonpharmaceutical interventions measures and human protective behavioral reaction to recent deaths. Thus, strategies coupling social distancing and vaccination could substantially suppress the mortality rate of COVID-19 in South America.
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Affiliation(s)
- Salihu Sabiu Musa
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
- Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria
| | - Amna Tariq
- Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA USA
| | - Liu Yuan
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
| | - Wei Haozhen
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
| | - Daihai He
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
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4
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Knyazev S, Chhugani K, Sarwal V, Ayyala R, Singh H, Karthikeyan S, Deshpande D, Baykal PI, Comarova Z, Lu A, Porozov Y, Vasylyeva TI, Wertheim JO, Tierney BT, Chiu CY, Sun R, Wu A, Abedalthagafi MS, Pak VM, Nagaraj SH, Smith AL, Skums P, Pasaniuc B, Komissarov A, Mason CE, Bortz E, Lemey P, Kondrashov F, Beerenwinkel N, Lam TTY, Wu NC, Zelikovsky A, Knight R, Crandall KA, Mangul S. Unlocking capacities of genomics for the COVID-19 response and future pandemics. Nat Methods 2022; 19:374-380. [PMID: 35396471 PMCID: PMC9467803 DOI: 10.1038/s41592-022-01444-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
During the COVID-19 pandemic, genomics and bioinformatics have emerged as essential public health tools. The genomic data acquired using these methods have supported the global health response, facilitated development of testing methods, and allowed timely tracking of novel SARS-CoV-2 variants. Yet the virtually unlimited potential for rapid generation and analysis of genomic data is also coupled with unique technical, scientific, and organizational challenges. Here, we discuss the application of genomic and computational methods for the efficient data driven COVID-19 response, advantages of democratization of viral sequencing around the world, and challenges associated with viral genome data collection and processing.
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Affiliation(s)
- Sergey Knyazev
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Karishma Chhugani
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Varuni Sarwal
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA
| | - Ram Ayyala
- Department of Translational Biomedical Informatics, University of Southern California, Los Angeles, CA, USA
| | - Harman Singh
- Department of Electrical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, India
| | - Smruthi Karthikeyan
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Dhrithi Deshpande
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Pelin Icer Baykal
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Zoia Comarova
- Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, CA, USA
| | - Angela Lu
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Yuri Porozov
- World-Class Research Center "Digital biodesign and personalized healthcare", I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Department of Computational Biology, Sirius University of Science and Technology, Sochi, Russia
| | - Tetyana I Vasylyeva
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Joel O Wertheim
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Braden T Tierney
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Charles Y Chiu
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Medicine, Division of Infectious Diseases, University of California, San Francisco, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, University of California, San Francisco, San Francisco, CA, USA
| | - Ren Sun
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, Los Angeles, CA, USA
- School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, P.R. China
| | - Aiping Wu
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Suzhou Institute of Systems Medicine, Suzhou, China
| | - Malak S Abedalthagafi
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
- King Salman Center for Disability Research, Riyadh, Saudi Arabia
| | - Victoria M Pak
- Emory University, School of Nursing, Atlanta, GA, CA, USA
- Emory University, Rollins School of Public Health, Department of Epidemiology, Atlanta, GA, CA, USA
| | - Shivashankar H Nagaraj
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia
- Translational Research Institute, Brisbane, Queensland, Australia
| | - Adam L Smith
- Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, CA, USA
| | - Pavel Skums
- Department of Computer Science, College of Art and Science, Georgia State University, Atlanta, GA, USA
| | - Bogdan Pasaniuc
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrey Komissarov
- Smorodintsev Research Institute of Influenza, Saint Petersburg, Russia
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA
- The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Eric Bortz
- Department of Biological Sciences, University of Alaska Anchorage, Anchorage, AK, CA, USA
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven-University of Leuven, Leuven, Belgium
| | - Fyodor Kondrashov
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Tommy Tsan-Yuk Lam
- State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, P.R. China
- Laboratory of Data Discovery for Health Limited, Hong Kong SAR, P.R. China
- Centre for Immunology & Infection Limited, Hong Kong SAR, P.R. China
| | - Nicholas C Wu
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Alex Zelikovsky
- Department of Computer Science, College of Art and Science, Georgia State University, Atlanta, GA, USA
| | - Rob Knight
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Keith A Crandall
- Computational Biology Institute and Department of Biostatistics & Bioinformatics, Milken Institute School of Public Health, George Washington University, Washington, DC, USA
| | - Serghei Mangul
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, USA.
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Resende PC, Delatorre E, Gräf T, Mir D, Motta FC, Appolinario LR, da Paixão ACD, Mendonça ACDF, Ogrzewalska M, Caetano B, Wallau GL, Docena C, dos Santos MC, de Almeida Ferreira J, Sousa Junior EC, da Silva SP, Fernandes SB, Vianna LA, Souza LDC, Ferro JFG, Nardy VB, Santos CA, Riediger I, do Carmo Debur M, Croda J, Oliveira WK, Abreu A, Bello G, Siqueira MM. Evolutionary Dynamics and Dissemination Pattern of the SARS-CoV-2 Lineage B.1.1.33 During the Early Pandemic Phase in Brazil. Front Microbiol 2021; 11:615280. [PMID: 33679622 PMCID: PMC7925893 DOI: 10.3389/fmicb.2020.615280] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 12/21/2020] [Indexed: 12/13/2022] Open
Abstract
A previous study demonstrates that most of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Brazilian strains fell in three local clades that were introduced from Europe around late February 2020. Here we investigated in more detail the origin of the major and most widely disseminated SARS-CoV-2 Brazilian lineage B.1.1.33. We recovered 190 whole viral genomes collected from 13 Brazilian states from February 29 to April 31, 2020 and combined them with other B.1.1 genomes collected globally. Our genomic survey confirms that lineage B.1.1.33 is responsible for a variable fraction of the community viral transmissions in Brazilian states, ranging from 2% of all SARS-CoV-2 genomes from Pernambuco to 80% of those from Rio de Janeiro. We detected a moderate prevalence (5-18%) of lineage B.1.1.33 in some South American countries and a very low prevalence (<1%) in North America, Europe, and Oceania. Our study reveals that lineage B.1.1.33 evolved from an ancestral clade, here designated B.1.1.33-like, that carries one of the two B.1.1.33 synapomorphic mutations. The B.1.1.33-like lineage may have been introduced from Europe or arose in Brazil in early February 2020 and a few weeks later gave origin to the lineage B.1.1.33. These SARS-CoV-2 lineages probably circulated during February 2020 and reached all Brazilian regions and multiple countries around the world by mid-March, before the implementation of air travel restrictions in Brazil. Our phylodynamic analysis also indicates that public health interventions were partially effective to control the expansion of lineage B.1.1.33 in Rio de Janeiro because its median effective reproductive number (R e ) was drastically reduced by about 66% during March 2020, but failed to bring it to below one. Continuous genomic surveillance of lineage B.1.1.33 might provide valuable information about epidemic dynamics and the effectiveness of public health interventions in some Brazilian states.
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Affiliation(s)
- Paola Cristina Resende
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), SARS-CoV-2 National Reference Laboratory for the Brazilian Ministry of Health (MoH) and Regional Reference Laboratory in Americas for the Pan-American Health Organization (PAHO/WHO), Rio de Janeiro, Brazil
| | - Edson Delatorre
- Departamento de Biologia, Centro de Ciencias Exatas, Naturais e da Saude, Universidade Federal do Espirito Santo, Alegre, Brazil
| | - Tiago Gräf
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Daiana Mir
- Unidad de Genomica y Bioinformatica, Centro Universitario Regional del Litoral Norte, Universidad de la Republica, Salto, Uruguay
| | - Fernando Couto Motta
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), SARS-CoV-2 National Reference Laboratory for the Brazilian Ministry of Health (MoH) and Regional Reference Laboratory in Americas for the Pan-American Health Organization (PAHO/WHO), Rio de Janeiro, Brazil
| | - Luciana Reis Appolinario
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), SARS-CoV-2 National Reference Laboratory for the Brazilian Ministry of Health (MoH) and Regional Reference Laboratory in Americas for the Pan-American Health Organization (PAHO/WHO), Rio de Janeiro, Brazil
| | - Anna Carolina Dias da Paixão
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), SARS-CoV-2 National Reference Laboratory for the Brazilian Ministry of Health (MoH) and Regional Reference Laboratory in Americas for the Pan-American Health Organization (PAHO/WHO), Rio de Janeiro, Brazil
| | - Ana Carolina da Fonseca Mendonça
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), SARS-CoV-2 National Reference Laboratory for the Brazilian Ministry of Health (MoH) and Regional Reference Laboratory in Americas for the Pan-American Health Organization (PAHO/WHO), Rio de Janeiro, Brazil
| | - Maria Ogrzewalska
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), SARS-CoV-2 National Reference Laboratory for the Brazilian Ministry of Health (MoH) and Regional Reference Laboratory in Americas for the Pan-American Health Organization (PAHO/WHO), Rio de Janeiro, Brazil
| | - Braulia Caetano
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), SARS-CoV-2 National Reference Laboratory for the Brazilian Ministry of Health (MoH) and Regional Reference Laboratory in Americas for the Pan-American Health Organization (PAHO/WHO), Rio de Janeiro, Brazil
| | | | - Cássia Docena
- Instituto Aggeu Magalhaes, Fundação Oswaldo Cruz, Recife, Brazil
| | | | | | | | | | | | - Lucas Alves Vianna
- Laboratorio Central de Saude Publica do Estado Espirito Santo (LACEN-ES), Vitoria, Brazil
| | | | - Jean F. G. Ferro
- Laboratorio Central de Saude Publica de Alagoas (LACEN-AL), Maceio, Brazil
| | - Vanessa B. Nardy
- Laboratorio Central de Saude Publica da Bahia (LACEN-BA), Salvador, Brazil
| | - Cliomar A. Santos
- Laboratorio Central de Saude Publica de Sergipe (LACEN-SE), Aracaju, Brazil
| | - Irina Riediger
- Laboratorio Central de Saude Publica de Parana (LACEN-PR), Curitiba, Brazil
| | | | - Júlio Croda
- Fiocruz Mato Grosso do Sul, Campo Grande, Brazil
- Universidade Federal de Mato Grosso do Sul – UFMS, Campo Grande, Brazil
| | | | - André Abreu
- Coordenadoria Geral de Laboratorios – Ministério da Saude, Brazilia, Brazil
| | - Gonzalo Bello
- Laboratorio de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Marilda M. Siqueira
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), SARS-CoV-2 National Reference Laboratory for the Brazilian Ministry of Health (MoH) and Regional Reference Laboratory in Americas for the Pan-American Health Organization (PAHO/WHO), Rio de Janeiro, Brazil
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Flores-Alanis A, Cruz-Rangel A, Rodríguez-Gómez F, González J, Torres-Guerrero CA, Delgado G, Cravioto A, Morales-Espinosa R. Molecular Epidemiology Surveillance of SARS-CoV-2: Mutations and Genetic Diversity One Year after Emerging. Pathogens 2021; 10:184. [PMID: 33572190 PMCID: PMC7915391 DOI: 10.3390/pathogens10020184] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 02/02/2021] [Accepted: 02/06/2021] [Indexed: 12/16/2022] Open
Abstract
In December 2019, the first cases of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were identified in the city of Wuhan, China. Since then, it has spread worldwide with new mutations being reported. The aim of the present study was to monitor the changes in genetic diversity and track non-synonymous substitutions (dN) that could be implicated in the fitness of SARS-CoV-2 and its spread in different regions between December 2019 and November 2020. We analyzed 2213 complete genomes from six geographical regions worldwide, which were downloaded from GenBank and GISAID databases. Although SARS-CoV-2 presented low genetic diversity, there has been an increase over time, with the presence of several hotspot mutations throughout its genome. We identified seven frequent mutations that resulted in dN substitutions. Two of them, C14408T>P323L and A23403G>D614G, located in the nsp12 and Spike protein, respectively, emerged early in the pandemic and showed a considerable increase in frequency over time. Two other mutations, A1163T>I120F in nsp2 and G22992A>S477N in the Spike protein, emerged recently and have spread in Oceania and Europe. There were associations of P323L, D614G, R203K and G204R substitutions with disease severity. Continuous molecular surveillance of SARS-CoV-2 will be necessary to detect and describe the transmission dynamics of new variants of the virus with clinical relevance. This information is important to improve programs to control the virus.
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Affiliation(s)
- Alejandro Flores-Alanis
- Departamento de Microbiología y Parasitología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City 04360, Mexico; (A.F.-A.); (G.D.); (A.C.)
| | - Armando Cruz-Rangel
- Laboratorio de Bioquímica de Enfermedades Crónicas, Instituto Nacional de Medicina Genómica, Mexico City 14610, Mexico;
| | - Flor Rodríguez-Gómez
- Departamento de Ciencias Computacionales, Centro Universitario de Ciencias Exactas e Ingenierías, Universidad de Guadalajara, Guadalajara 44430, Jalisco, Mexico;
| | - James González
- Departamento de Biología Celular, Facultad de Ciencias, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico;
| | | | - Gabriela Delgado
- Departamento de Microbiología y Parasitología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City 04360, Mexico; (A.F.-A.); (G.D.); (A.C.)
| | - Alejandro Cravioto
- Departamento de Microbiología y Parasitología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City 04360, Mexico; (A.F.-A.); (G.D.); (A.C.)
| | - Rosario Morales-Espinosa
- Departamento de Microbiología y Parasitología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City 04360, Mexico; (A.F.-A.); (G.D.); (A.C.)
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7
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Mercado M, Malagón-Rojas J, Delgado G, Rubio VV, Muñoz Galindo L, Parra Barrera EL, Gaviria P, Zabaleta G, Alarcon Z, Arévalo A, Cifuentes HC, Estrada K, Puerto G, Herrera Sepúlveda MT, Rodríguez H, Galindo M, Ospina Ramírez ML. Evaluation of nine serological rapid tests for the detection of SARS-CoV-2. Rev Panam Salud Publica 2020. [PMCID: PMC7734239 DOI: 10.26633/rpsp.2020.149] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Objective. To evaluate the operative capacity of nine serological rapid tests to detect the IgM/IgG antibodies response in serum from patients with SARS-CoV-2 in different clinical stages. Methods. A cross-sectional study of serological rapid tests was designed to compare the performance of the evaluated immunochromatographic tests for the diagnosis of SARS-CoV-2. A total of 293 samples was used, including negatives, asymptomatic, and symptomatic serum samples. Results. The sensitivity of the evaluated tests was low and moderate in the groups of asymptomatic serum samples and the group of serums coming from patients with less than 11 days since the onset of the symptoms. The specificity for the anti-SARS-CoV-2 antibodies tests ranged between 86.5%-99% for IgM and 86.5%-99.5% for IgG. The sensitivity and the likelihood ratio were different according to the study groups. The usefulness of these tests is restricted to symptomatic patients and their sensitivity is greater than 85% after 11 days from the appearance of symptoms. Conclusions. Serological tests are not an adequate strategy for the identification of asymptomatic and pre-symptomatic patients. Serological rapid tests for the detection of specific anti-SARS-CoV-2 antibodies can be used as a diagnostic aid, but diagnosis must be confirmed by RT-PCR. Rapid tests should be reserved for patients with symptoms lasting more than 11 days.
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Affiliation(s)
| | | | | | | | | | | | - Paula Gaviria
- Instituto Distrital de Ciencia, Biotecnología e Innovación en Salud, Bogotá, Colombia
| | | | | | | | | | - Kelly Estrada
- Instituto de Evaluación Tecnológica en Salud, Bogotá, Colombia
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8
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Álvarez-Díaz DA, Laiton-Donato K, Franco-Muñoz C, Mercado-Reyes M. SARS-CoV-2 sequencing: The technological initiative to strengthen early warning systems for public health emergencies in Latin America and the Caribbean. BIOMEDICA : REVISTA DEL INSTITUTO NACIONAL DE SALUD 2020; 40:188-197. [PMID: 33152203 PMCID: PMC7676827 DOI: 10.7705/biomedica.5841] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 10/19/2020] [Indexed: 12/14/2022]
Abstract
The COVID-19 pandemic caused by SARS-CoV-2 is a public health problem on a scale unprecedented in the last 100 years, as has been the response focused on the rapid genomic characterization of SARS-CoV-2 in virtually all regions of the planet. This pandemic emerged during the era of genomic epidemiology, a science fueled by continued advances in next-generation sequencing. Since its recent appearance, genomic epidemiology included the precise identification of new lineages or species of pathogens and the reconstruction of their genetic variability in real time, evidenced in past outbreaks of influenza H1N1, MERS, and SARS. However, the global and uncontrolled scale of this pandemic created a scenario where genomic epidemiology was put into practice en masse, from the rapid identification of SARS-CoV-2 to the registration of new lineages and their active surveillance throughout the world. Prior to the COVID-19 pandemic, the availability of genomic data on circulating pathogens in several Latin America and the Caribbean countries was scarce or nil. With the arrival of SARS-CoV-2, this scenario changed significantly, although the amount of available information remains scarce and, in countries such as Colombia, Brazil, Argentina, and Chile, the genomic information of SARS-CoV-2 was obtained mainly by research groups in genomic epidemiology rather than the product of a public health surveillance policy or program. This indicates the need to establish public health policies aimed at implementing genomic epidemiology as a tool to strengthen surveillance and early warning systems against threats to public health in the region.
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Affiliation(s)
- Diego A Álvarez-Díaz
- Unidad de Secuenciación y Genómica, Dirección de Investigación en Salud Pública, Instituto Nacional de Salud, Bogotá, D.C., Colombia; Grupo de Salud Materna y Perinatal, Dirección de Investigación en Salud Pública, Instituto Nacional de Salud, Bogotá, D.C., Colombia.
| | - Katherine Laiton-Donato
- Unidad de Secuenciación y Genómica, Dirección de Investigación en Salud Pública, Instituto Nacional de Salud, Bogotá, D. C., Colombia.
| | - Carlos Franco-Muñoz
- Grupo de Parasitología, Dirección de Investigación en Salud Pública, Instituto Nacional de Salud, Bogotá, D. C., Colombia.
| | - Marcela Mercado-Reyes
- Grupo de Salud Materna y Perinatal, Dirección de Investigación en Salud Pública, Instituto Nacional de Salud, Bogotá, Colombia; Dirección de Investigación en Salud Pública, Instituto Nacional de Salud, Bogotá, D.C., Colombia.
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9
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Díaz FJ, Aguilar-Jiménez W, Flórez-Álvarez L, Valencia G, Laiton-Donato K, Franco-Muñoz C, Álvarez-Díaz D, Mercado-Reyes M, Rugeles MT. Isolation and characterization of an early SARS-CoV-2 isolate from the 2020 epidemic in Medellín, Colombia. BIOMEDICA : REVISTA DEL INSTITUTO NACIONAL DE SALUD 2020; 40:148-158. [PMID: 33152198 PMCID: PMC7676823 DOI: 10.7705/biomedica.5834] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 10/15/2020] [Indexed: 11/24/2022]
Abstract
Introduction: SARS-CoV-2 has been identified as the new coronavirus causing an outbreak of acute respiratory disease in China in December, 2019. This disease, currently named COVID-19, has been declared as a pandemic by the World Health Organization (WHO). The first case of COVID-19 in Colombia was reported on March 6, 2020. Here we characterize an early SARS-CoV-2 isolate from the pandemic recovered in April, 2020. Objective: To describe the isolation and characterization of an early SARS-CoV-2 isolate from the epidemic in Colombia. Materials and methods: A nasopharyngeal specimen from a COVID-19 positive patient was inoculated on different cell lines. To confirm the presence of SARS-CoV-2 on cultures we used qRT-PCR, indirect immunofluorescence assay, transmission and scanning electron microscopy, and next-generation sequencing. Results: We determined the isolation of SARS-CoV-2 in Vero-E6 cells by the appearance of the cytopathic effect three days post-infection and confirmed it by the positive results in the qRT-PCR and the immunofluorescence with convalescent serum. Transmission and scanning electron microscopy images obtained from infected cells showed the presence of structures compatible with SARS-CoV-2. Finally, a complete genome sequence obtained by next-generation sequencing allowed classifying the isolate as B.1.5 lineage. Conclusion: The evidence presented in this article confirms the first isolation of SARSCoV-2 in Colombia. In addition, it shows that this strain behaves in cell culture in a similar way to that reported in the literature for other isolates and that its genetic composition is consistent with the predominant variant in the world. Finally, points out the importance of viral isolation for the detection of neutralizing antibodies, for the genotypic and phenotypic characterization of the strain and for testing compounds with antiviral potential.
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Affiliation(s)
- Francisco J Díaz
- Grupo de Inmunovirología, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia.
| | - Wbeimar Aguilar-Jiménez
- Grupo de Inmunovirología, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia.
| | - Lizdany Flórez-Álvarez
- Grupo de Inmunovirología, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia.
| | - Gladys Valencia
- Ayudas Diagnósticas de Laboratorio Clínico, ADILAB, Medellín, Colombia.
| | | | - Carlos Franco-Muñoz
- Unidad de Secuenciación Genómica, Instituto Nacional de Salud, Bogotá, D.C., Colombia.
| | - Diego Álvarez-Díaz
- Unidad de Secuenciación Genómica, Instituto Nacional de Salud, Bogotá, D.C., Colombia.
| | - Marcela Mercado-Reyes
- Unidad de Secuenciación Genómica, Instituto Nacional de Salud, Bogotá, D.C., Colombia.
| | - María Teresa Rugeles
- Grupo de Inmunovirología, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia.
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