Digital Infoveillance for Measles Surveillance in Italy: Analysis of Google Trends and Wikipedia Data (2013–2025)

The increasing digitalization of information behaviors has created new op-portunities in public health, promoting the development of infodemiology and infoveillance as complements to traditional epidemiological surveillance. This study aimed to assess the correlation and temporal association between official measles surveillance data published by the Italian National Institute of Health (ISS), Google Trends search volumes, and Wikipedia page views re-lated to measles in Italy. A cross-sectional analysis was conducted using mea-sles cases reported in Italy from January 2013 to November 2025. Monthly data from Google Trends and Wikipedia were aggregated and compared with the monthly incidence reported in ISS bulletins. Cross-correlation analyses and linear regressions were performed to evaluate associations. The results showed a statistically significant and strong correlation (r=0.81) between Google Trends search volume for “Morbillo” and reported measles cases. Linear re-gression analyses demonstrated significant associations between digital indi-cators and official surveillance data, suggesting that online user activity closely reflects measles epidemiological trends. These findings indicate that Google Trends and Wikipedia may serve as useful and timely tools to com-plement traditional measles surveillance. Although caution is needed due to methodological limitations and potential information bias, integrating digital data could enhance early outbreak detection and support more rapid public health responses.