Google Trends Data to Determine Vaping Prevalence and Predictability in Europe: Usability Study (Preprint)

BACKGROUND The increasing use, and negative health effects, of e-cigarettes across Europe warrants continuous surveillance. Google Trends (GT) is a promising surveillance tool, providing real-time data that contrasts positively with cross-sectional surveys. However, its applicability to monitor e-cigarette use across Europe is unknown. OBJECTIVE To monitor changes in online interest in e-cigarettes from 2012 to 2020, to investigate the relationship between GT searches on e-cigarettes and prevalence data and to assess the predictive capabilities of GT in Europe. METHODS GT data for "electronic cigarette" and "vaporizer" were extracted for 27 European countries, whilst e-cigarette prevalence data were sourced from Eurobarometer. Regression and change-point analysis identified temporal changes in online interest and cross-correlation investigated the relationship between the two datasets. Countries displaying the strongest correlation underwent time series forecasting analysis using simple exponential smoothing (SES), and autoregressive integrated moving average (ARIMA) models. RESULTS Significant correlations between GT and e-cigarette prevalence emerged for ten and seven countries for the "electronic cigarette" and "vaporizer" topics, respectively, while ARIMA outperformed SES in all but one country. Boosted ARIMA improved forecasts further in the evaluated countries. CONCLUSIONS This study affirms GT’s potential to supplant cross-sectional e-cigarette data in certain European countries and highlights its predictive ability. However, future research should determine factors driving forecasting performance differences between countries and models. This work has potential to inform preventative policies using a flexible and continuous monitoring tool.