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An Inductive Approach to Using Google Search Trends To Identify Attitudes and Areas of COVID-19 Vaccine Hesitancy

In this study, we present and apply a novel inductive approach that uses Google Search Trends data for public health surveillance of COVID-19 vaccine hesitancy from January to April 2021. In contrast to previous studies that use researcher-curated keywords, our study combed through over 2 million social media posts on Twitter to identify over 3,000 keywords related to vaccination, enabling us to capture potential sources of vaccine hesitancy that would otherwise be missed. These keywords were used to retrieve Google Search Trends for 774 queries that yielded nonzero search volumes for at least 45 U.S. states. We then used the CovidCast survey of vaccine acceptance at the U.S. state level to calculate a Spearman’s rank correlation coefficient for each term. Negatively correlated queries, we argue, can help shed light on potential sources of vaccine hesitancy. As noted by Flahault et al. (2020), in order to achieve “precision global health” and “real-time action”, researchers must creatively combine multiple data sources in order to deliver targeted interventions. We are hopeful that our approach will be useful for practitioners in addressing the problem of vaccine hesitancy.