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Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave.
Davis, Jessica T; Chinazzi, Matteo; Perra, Nicola; Mu, Kunpeng; Pastore Y Piontti, Ana; Ajelli, Marco; Dean, Natalie E; Gioannini, Corrado; Litvinova, Maria; Merler, Stefano; Rossi, Luca; Sun, Kaiyuan; Xiong, Xinyue; Longini, Ira M; Halloran, M Elizabeth; Viboud, Cécile; Vespignani, Alessandro.
  • Davis JT; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
  • Chinazzi M; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
  • Perra N; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
  • Mu K; Networks and Urban Systems Centre, University of Greenwich, London, UK.
  • Pastore Y Piontti A; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
  • Ajelli M; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
  • Dean NE; Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
  • Gioannini C; Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA.
  • Litvinova M; ISI Foundation, Turin, Italy.
  • Merler S; Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
  • Rossi L; Bruno Kessler Foundation, Trento, Italy.
  • Sun K; ISI Foundation, Turin, Italy.
  • Xiong X; Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.
  • Longini IM; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
  • Halloran ME; Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
  • Viboud C; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
  • Vespignani A; Department of Biostatistics, University of Washington, Seattle, WA, USA.
Nature ; 600(7887): 127-132, 2021 12.
Article en En | MEDLINE | ID: mdl-34695837
Considerable uncertainty surrounds the timeline of introductions and onsets of local transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) globally1-7. Although a limited number of SARS-CoV-2 introductions were reported in January and February 2020 (refs.8,9), the narrowness of the initial testing criteria, combined with a slow growth in testing capacity and porous travel screening10, left many countries vulnerable to unmitigated, cryptic transmission. Here we use a global metapopulation epidemic model to provide a mechanistic understanding of the early dispersal of infections and the temporal windows of the introduction of SARS-CoV-2 and onset of local transmission in Europe and the USA. We find that community transmission of SARS-CoV-2 was likely to have been present in several areas of Europe and the USA by January 2020, and estimate that by early March, only 1 to 4 in 100 SARS-CoV-2 infections were detected by surveillance systems. The modelling results highlight international travel as the key driver of the introduction of SARS-CoV-2, with possible introductions and transmission events as early as December 2019 to January 2020. We find a heterogeneous geographic distribution of cumulative infection attack rates by 4 July 2020, ranging from 0.78% to 15.2% across US states and 0.19% to 13.2% in European countries. Our approach complements phylogenetic analyses and other surveillance approaches and provides insights that can be used to design innovative, model-driven surveillance systems that guide enhanced testing and response strategies.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: SARS-CoV-2 / COVID-19 / Modelos Epidemiológicos Tipo de estudio: Prognostic_studies Límite: Humans País como asunto: America do norte / Asia / Europa Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: SARS-CoV-2 / COVID-19 / Modelos Epidemiológicos Tipo de estudio: Prognostic_studies Límite: Humans País como asunto: America do norte / Asia / Europa Idioma: En Año: 2021 Tipo del documento: Article