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Global disparities in SARS-CoV-2 genomic surveillance.
Brito, Anderson F; Semenova, Elizaveta; Dudas, Gytis; Hassler, Gabriel W; Kalinich, Chaney C; Kraemer, Moritz U G; Ho, Joses; Tegally, Houriiyah; Githinji, George; Agoti, Charles N; Matkin, Lucy E; Whittaker, Charles; Howden, Benjamin P; Sintchenko, Vitali; Zuckerman, Neta S; Mor, Orna; Blankenship, Heather M; de Oliveira, Tulio; Lin, Raymond T P; Siqueira, Marilda Mendonça; Resende, Paola Cristina; Vasconcelos, Ana Tereza R; Spilki, Fernando R; Aguiar, Renato Santana; Alexiev, Ivailo; Ivanov, Ivan N; Philipova, Ivva; Carrington, Christine V F; Sahadeo, Nikita S D; Gurry, Céline; Maurer-Stroh, Sebastian; Naidoo, Dhamari; von Eije, Karin J; Perkins, Mark D; van Kerkhove, Maria; Hill, Sarah C; Sabino, Ester C; Pybus, Oliver G; Dye, Christopher; Bhatt, Samir; Flaxman, Seth; Suchard, Marc A; Grubaugh, Nathan D; Baele, Guy; Faria, Nuno R.
Afiliação
  • Brito AF; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA.
  • Semenova E; Instituto Todos pela Saúde, São Paulo, São Paulo, Brazil.
  • Dudas G; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA.
  • Hassler GW; Department of Mathematics, Imperial College London, London, UK.
  • Kalinich CC; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA.
  • Kraemer MUG; Gothenburg Global Biodiversity Centre, Gothenburg, Sweden.
  • Ho J; Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
  • Tegally H; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA.
  • Githinji G; Yale School of Medicine, Yale University, New Haven, Connecticut, USA.
  • Agoti CN; Department of Zoology, University of Oxford, Oxford, United Kingdom.
  • Matkin LE; GISAID Global Data Science Initiative, Munich, Germany.
  • Whittaker C; Bioinformatics Institute & ID Labs, Agency for Science Technology and Research, Singapore, Singapore.
  • Howden BP; Department of Zoology, University of Oxford, Oxford, United Kingdom.
  • Sintchenko V; MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
  • Zuckerman NS; The Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, United Kingdom.
  • Siqueira MM; Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia.
  • Resende PC; Sydney Institute for Infectious Diseases, The University of Sydney, Sydney, New South Wales, Australia.
  • Vasconcelos ATR; Institute of Clinical Pathology and Medical Research, NSW Health Pathology, Westmead, New South Wales 2145, Australia.
  • Spilki FR; Central Virology Laboratory, Israel Ministry of Health, Sheba Medical Center, Israel.
  • Aguiar RS; Central Virology Laboratory, Israel Ministry of Health, Sheba Medical Center, Israel.
  • Alexiev I; Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, Michigan, USA.
  • Ivanov IN; KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa.
  • Philipova I; Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.
  • Carrington CVF; Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa.
  • Sahadeo NSD; Department of Global Health, University of Washington, Seattle, Washington, USA.
  • Gurry C; National Centre for Infectious Diseases, Singapore.
  • Maurer-Stroh S; Laboratory of Respiratory Viruses and Measles, FIOCRUZ, Rio de Janeiro, Brazil.
  • Naidoo D; Laboratory of Respiratory Viruses and Measles, FIOCRUZ, Rio de Janeiro, Brazil.
  • von Eije KJ; Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil.
  • Perkins MD; Feevale University, Institute of Health Sciences, Novo Hamburgo, Rio Grande do Sul, Brazil.
  • van Kerkhove M; Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
  • Hill SC; Instituto D'Or de Pesquisa e Ensino (IDOR), Rio de Janeiro, Brazil.
  • Sabino EC; National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria.
  • Pybus OG; National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria.
  • Dye C; National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria.
  • Bhatt S; Department of Preclinical Sciences, Faculty of Medical Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago.
  • Flaxman S; Department of Preclinical Sciences, Faculty of Medical Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago.
  • Suchard MA; GISAID Global Data Science Initiative, Munich, Germany.
  • Grubaugh ND; GISAID Global Data Science Initiative, Munich, Germany.
  • Baele G; Bioinformatics Institute & ID Labs, Agency for Science Technology and Research, Singapore, Singapore.
  • Faria NR; National Centre for Infectious Diseases, Singapore.
medRxiv ; 2021 Dec 09.
Article em En | MEDLINE | ID: mdl-34462754
ABSTRACT
Genomic sequencing provides critical information to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments and vaccines, and guide public health responses. To investigate the spatiotemporal heterogeneity in the global SARS-CoV-2 genomic surveillance, we estimated the impact of sequencing intensity and turnaround times (TAT) on variant detection in 167 countries. Most countries submit genomes >21 days after sample collection, and 77% of low and middle income countries sequenced <0.5% of their cases. We found that sequencing at least 0.5% of the cases, with a TAT <21 days, could be a benchmark for SARS-CoV-2 genomic surveillance efforts. Socioeconomic inequalities substantially impact our ability to quickly detect SARS-CoV-2 variants, and undermine the global pandemic preparedness.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Screening_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Screening_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article