Google Trends and Wikipedia Queries as Proxies for Measles Surveillance
Vol. 67 No. 3 (2026), Infectious Diseases
Vol. 67 No. 3 (2026)

Google Trends and Wikipedia Queries as Proxies for Measles Surveillance

Infectious Diseases
Published 2026-10-15
Omar Enzo Santangelo
Territorial Health and Social Care Authority of Lodi, ASST Lodi, Lodi, Italy
https://orcid.org/0000-0003-2017-3665
Anna Sole Pizzamiglio
Territorial Health and Social Care Authority of Lodi, ASST Lodi, Lodi, Italy
Carlotta Vella
Territorial Health and Social Care Authority of Lodi, ASST Lodi, Lodi, Italy
Danilo Greco
Local Health Unit of Trapani, ASP Trapani, Trapani, Italy
Alberto Firenze
Local Health Unit of Palermo, ASP Palermo, Palermo, Italy
Sandro Provenzano
Local Health Unit of Trapani, ASP Trapani, Trapani, Italy
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Keywords

infodemiology
Infoveillance
Measles
Infectious Diseases
Italy

Abstract

Introduction. The increasing digitalization of information behaviors has created new opportunities 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 (GT) search volumes, and Wikipedia page views related to measles in Italy. 

Methods. A retrospective ecological study with a time-series design was conducted using measles cases reported in Italy from January 2013 to November 2025. Monthly data from GT and Wikipedia were aggregated and compared with the monthly incidence reported in ISS bulletins. Linear regressions were performed to evaluate associations. 

Results. The results showed a statistically significant associations between reported measles cases and both GT searches and Wikipedia page views. Linear regression analyses confirmed significant associations between digital indicators and official surveillance data, suggesting that online user activity closely reflects measles epidemiological trends. 

Conclusion. These findings indicate that GT and Wikipedia may serve as useful and timely tools to complement 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.

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