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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; Branda, Ben; 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.
  • Brito AF; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA. andersonfbrito@gmail.com.
  • Semenova E; Instituto Todos pela Saúde, São Paulo, SP, Brazil. andersonfbrito@gmail.com.
  • Dudas G; Department of Computer Science, University of Oxford, Oxford, UK.
  • Hassler GW; Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania.
  • Kalinich CC; Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
  • Kraemer MUG; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
  • Ho J; Yale School of Medicine, Yale University, New Haven, CT, USA.
  • Tegally H; Department of Biology, University of Oxford, Oxford, UK.
  • Githinji G; GISAID Global Data Science Initiative, Munich, Germany.
  • Agoti CN; Bioinformatics Institute & ID Labs, Agency for Science Technology and Research, Singapore, Singapore.
  • Matkin LE; KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa.
  • Whittaker C; Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.
  • 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, NSW, Australia.
  • Vasconcelos ATR; Institute of Clinical Pathology and Medical Research, NSW Health Pathology, Westmead, NSW, Australia.
  • Spilki FR; Central Virology Laboratory, Israel Ministry of Health, Sheba Medical Center, Ramat Gan, Israel.
  • Aguiar RS; Central Virology Laboratory, Israel Ministry of Health, Sheba Medical Center, Ramat Gan, Israel.
  • Alexiev I; Michigan Department of Health and Human Services, Bureau of Laboratories, Lansing, MI, 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, WA, USA.
  • Branda B; National Centre for Infectious Diseases, Singapore, Singapore.
  • Gurry C; Laboratory of Respiratory Viruses and Measles, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil.
  • Maurer-Stroh S; Laboratory of Respiratory Viruses and Measles, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil.
  • Naidoo D; Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil.
  • von Eije KJ; Feevale University, Institute of Health Sciences, Novo Hamburgo, RS, Brazil.
  • Perkins MD; Laboratório de Biologia Integrativa, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
  • van Kerkhove M; Instituto D'Or de Pesquisa e Ensino (IDOR), Rio de Janeiro, Brazil.
  • Hill SC; National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria.
  • Sabino EC; National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria.
  • Pybus OG; National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria.
  • Dye C; Department of Preclinical Sciences, Faculty of Medical Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago.
  • Bhatt S; Department of Preclinical Sciences, Faculty of Medical Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago.
  • Flaxman S; GISAID Global Data Science Initiative, Munich, Germany.
  • 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, Singapore.
Nat Commun ; 13(1): 7003, 2022 Nov 16.
Article in English | MEDLINE | ID: covidwho-2116500
ABSTRACT
Genomic sequencing is essential to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments, vaccines, and guide public health responses. To investigate the global SARS-CoV-2 genomic surveillance, we used sequences shared via GISAID to estimate the impact of sequencing intensity and turnaround times on variant detection in 189 countries. In the first two years of the pandemic, 78% of high-income countries sequenced >0.5% of their COVID-19 cases, while 42% of low- and middle-income countries reached that mark. Around 25% of the genomes from high income countries were submitted within 21 days, a pattern observed in 5% of the genomes from low- and middle-income countries. We found that sequencing around 0.5% of the cases, with a turnaround time <21 days, could provide a benchmark for SARS-CoV-2 genomic surveillance. Socioeconomic inequalities undermine the global pandemic preparedness, and efforts must be made to support low- and middle-income countries improve their local sequencing capacity.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study Topics: Vaccines / Variants Limits: Humans Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2022 Document Type: Article Affiliation country: S41467-022-33713-y

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study Topics: Vaccines / Variants Limits: Humans Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2022 Document Type: Article Affiliation country: S41467-022-33713-y