Estudio de la búsqueda de información sobre la pandemia SARS-CoV-2 en Galicia

  1. Miguel Mayo-Yáñez
  2. Lucía González-Torres 1
  3. MiguelChristian Calvo-Henríquez 2
  4. Carlos Chiesa-Estomba 3
  1. 1 Pediatrics Department, Complexo Hospitalario Universitario A Coruña (CHUAC)
  2. 2 Otorhinolaryngology – Head and Neck Surgery Department, Complexo Hospitalario Clinical Research in Medicine, International Center for Doctorate and Advanced Studies (CIEDUS), Universidade de Santiago de Compostela (USC); Young-Otolaryngologists of the International Federations of Oto-RhinoLaryngological Societies (YO-IFOS) Study Group, Paris, France; Otorhinolaryngology – Head and Neck Surgery Department, Complexo Hospitalario Universitario Santiago de Compostela (CHUS).
  3. 3 Young-Otolaryngologists of the International Federations of Oto-RhinoLaryngological Societies (YO-IFOS) Study Group, Paris, France
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Revista:
Galicia Clínica

ISSN: 0304-4866,  1989-3922

Año de publicación: 2021

Volumen: 82

Número: 1

Páginas: 13-16

Tipo: Artículo

DOI: 10.22546/60/2305 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Galicia Clínica

Objetivos de desarrollo sostenible

Resumen

Introduction: This manuscript analyses the use and evolution, through Google Trends as a source of information, of internet-based information-seeking behaviour related to the SARS-CoV-2 pandemic using the terms: Coronavirus, COVID-19, SARS-CoV-2 from January 1, 2020 to April 15, 2020. Methods: A generalized linear model was used to analyse the relation between SARS-CoV-2 data epidemiology and the Search Volume Index of the terms obtained from the Google Trends query. Significant trend changes were assessed by Joinpoint methodology. Results: A total of 7,873 SARS-CoV-2 confirmed cases were collected with an increase of 4.7% in the selected period. A relation was found between the confirmed cases (dependent variable) and the Search Volume Index of the Coronavirus term, with a correlation rho = 0.79 (p <0.000). Conclusion: The analysis of search engine query data in order to create mathematical models that forecast disease spread could be useful and helpful to activate and improve strategic plan to control an outbreak

Fuente de los datos: Dialnet