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

Contents

1. Abstract
2. Citation
3. Links

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 socioeconomic 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.

This is an output of the ieConnect for Impact Programme.

Citation

Marty, R. Ramos-Maqueda, M. Khan, N. Reichert, A. 'The evolution of the COVID-19 pandemic through the lens of Google searches' Scientific Reports, 2023: volume 13 issue 1, article number 19843

Links

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

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