The evolution of the COVID-19 pandemic through the lens of google searches

verfasst von: Robert Marty, Manuel Ramos-Maqueda, Nausheen Khan, Arndt Reichert
Abstract: Real-time data is essential for policymakers to adapt to a rapidly evolving situation like the COVID-19 pandemic. Using data from 221 countries and territories, we demonstrate the capacity of Google search data to anticipate reported COVID-19 cases and understand how containment policies are associated with changes in socioeconomic indicators. First, search interest in COVID-specific symptoms such as “loss of smell” strongly correlated with cases initially, but the association diminished as COVID-19 evolved; general terms such as “COVID symptoms” remained strongly associated with cases. Moreover, trends in search interest preceded trends in reported cases, particularly in the first year of the pandemic. Second, countries with more restrictive containment policies experienced greater search interest in unemployment and mental health terms after policies were implemented, indicating socio-economic externalities. Higher-income countries experienced a larger increase in searches related to unemployment and a larger reduction in relationship and family planning keywords relative to lower-income countries. The results demonstrate that real-time search interest can be a valuable tool to inform policies across multiple stages of the pandemic.
Organisationseinheit(en): Institut für Gesundheitsökonomie
Externe Organisation(en): Weltbank
Typ: Artikel
Journal: Scientific reports
Band: 13
Anzahl der Seiten: 14
ISSN: 2045-2322
Publikationsdatum: 13.11.2023
Publikationsstatus: Veröffentlicht
Peer-reviewed: Ja
ASJC Scopus Sachgebiete: Allgemein
Ziele für nachhaltige Entwicklung: SDG 3 – Gute Gesundheit und Wohlergehen
Elektronische Version(en): https://doi.org/10.1038/s41598-023-41675-4 (Zugang: Offen)

BibTeX

@article{62c1cbefb4124cc598e8041e25fa634e,
title = "The evolution of the COVID-19 pandemic through the lens of google searches",
abstract = "Real-time data is essential for policymakers to adapt to a rapidly evolving situation like the COVID-19 pandemic. Using data from 221 countries and territories, we demonstrate the capacity of Google search data to anticipate reported COVID-19 cases and understand how containment policies are associated with changes in socioeconomic indicators. First, search interest in COVID-specific symptoms such as “loss of smell” strongly correlated with cases initially, but the association diminished as COVID-19 evolved; general terms such as “COVID symptoms” remained strongly associated with cases. Moreover, trends in search interest preceded trends in reported cases, particularly in the first year of the pandemic. Second, countries with more restrictive containment policies experienced greater search interest in unemployment and mental health terms after policies were implemented, indicating socio-economic externalities. Higher-income countries experienced a larger increase in searches related to unemployment and a larger reduction in relationship and family planning keywords relative to lower-income countries. The results demonstrate that real-time search interest can be a valuable tool to inform policies across multiple stages of the pandemic.",
author = "Robert Marty and Manuel Ramos-Maqueda and Nausheen Khan and Arndt Reichert",
note = "Funding Information: This project received funding from the ieConnect for Impact program which is a collaboration between the World Bank's DIME group and the Transport Global Practice. The ieConnect program has been funded with UK aid from the UK government. ",
year = "2023",
month = nov,
day = "13",
doi = "10.1038/s41598-023-41675-4",
language = "English",
volume = "13",
journal = "Scientific reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
}