Using Google Trends to Predict COVID-19 Vaccinations and Monitor Search Behaviours about Vaccines: A Retrospective Analysis of Italian Data

Vaccines

Andrea Maugeri¹  Martina Barchitta¹  Antonella Agodi¹ 

[1] Department of Medical and Surgical Sciences and Advanced Technologies “GF Ingrassia”, University of Catania, 95123 Catania, Italy;

关键词: COVID-19;    SARS-CoV-2;    vaccine;    vaccinations;    hesitancy;   

DOI  :  10.3390/vaccines10010119

来源: DOAJ

【 摘 要 】

Google Trends data are an efficient source for analysing internet search behaviour and providing valuable insights into community dynamics and health-related problems. In this article, we aimed to evaluate if Google Trends data could help monitor the COVID-19 vaccination trend over time and if the introduction of COVID-19 vaccines modified the interest of pregnant women in vaccination. Data related to Google internet searches and the number of vaccine doses administered in Italy were used. We found moderate to strong correlations between search volumes of vaccine-related terms and the number of vaccines administered. In particular, a model based on Google Trends with a 3-week lag showed the best performance in fitting the number of COVID-19 vaccinations over time. We also observed that the introduction of COVID-19 vaccines affected the search interest for the argument “vaccination in pregnancy” both quantitatively and qualitatively. There was a significant increase in the search interest after the launch of the COVID-19 vaccination campaign in Italy. Qualitative analysis suggested that this increase was probably due to concerns about COVID-19 vaccines. Thus, our study suggests the benefits of using Google Trends data to predict the number of COVID-19 vaccine doses administered, and to monitor feelings about vaccination.

【 授权许可】

Unknown