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

authored by

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.

Organisation(s)

Institute of Health Economics

External Organisation(s)

World Bank

Type

Article

Journal

Scientific reports

Volume

13

No. of pages

14

ISSN

2045-2322

Publication date

13.11.2023

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

General

Sustainable Development Goals

SDG 3 - Good Health and Well-being

Electronic version(s)

https://doi.org/10.1038/s41598-023-41675-4 (Access: Open)