Google Trends as a predictive tool for COVID-19 vaccinations in Italy: a retrospective infodemiological analysis

Background Google Trends is an infoveillance tool widely used by the scientific community to investigate different user behaviors related to COVID-19. However, several limitations regarding its adoption are reported in the literature. Objective This brief paper aims to provide an effective and efficient approach to investigating vaccine adherence against COVID-19 via Google Trends. Methods Through the cross-correlational analysis of well-targeted hypotheses, we investigate the predictive capacity of web searches related to COVID-19 towards vaccinations in Italy from November 2020 to November 2021. The keyword “vaccine reservation” (VRQ) was chosen as it reflects a real intention of being vaccinated (V). Furthermore, the impact of the second-largest Italian national newspaper on vaccines-related web searches was investigated to evaluate the role of the mass media as a confounding factor. Results Simple and generic keywords are more likely to identify the actual web interest in COVID-19 vaccines than specific and elaborated keywords. Cross-correlations between VRQ and V were very strong and significant (min r 2 = .460, P<.001, lag = 0 weeks; max r 2 = .903, P < .001, lag = 6 weeks). Cross-correlations between VRQ and news about COVID-19 vaccines have been markedly lower and characterized by greater lags (min r 2 = .190, P=.001, lag = 0 weeks; max r 2 = .493, P < .001, lag = -10 weeks). No correlation between news and vaccinations was sought since the lag would have been too high. Conclusions This research provides strong evidence in favor of using Google Trends as a surveillance and prediction tool for vaccine adherence against COVID-19 in Italy. These findings prove that the search for suitable keywords is a fundamental step to reduce confounding factors. Additionally, targeting hypotheses helps diminish the likelihood of spurious correlations. It is recommended that Google Trends be leveraged as a complementary infoveillance tool by government agencies to monitor and predict vaccine adherence in this and future crises by following the methods proposed in this manuscript.