Correlation between flu and Wikipedia’s pages visualization

Vincenza Gianfredi; Omar Enzo Santangelo; Sandro Provenzano

doi:10.23750/abm.v92i1.9790

Correlation between flu and Wikipedia’s pages visualization

Authors

Vincenza Gianfredi
Omar Enzo Santangelo https://orcid.org/0000-0003-2017-3665
Sandro Provenzano

DOI: https://doi.org/10.23750/abm.v92i1.9790

Keywords:

Flu, Italy, Medical Informatics Computing, Vaccine-preventable diseases, Medical Informatics

Abstract

Introduction: This study aimed to assess if the frequency of the Italian general public searches for influenza, using the Wikipedia web-page, are aligned with Istituto Superiore di Sanità (ISS) influenza cases.
Materials and Methods: The reported cases of flu were selected from October 2015 to May 2019. Wikipedia Trends was used to assess how many times a specific page was read by users; data were extracted as daily data and aggregated on a weekly basis. The following data were extracted: number of weekly views by users from the October 2015 to May 2019 of the pages: Influenza, Febbre and Tosse (Flu, Fever and Cough, in English). Cross-correlation results are obtained as product-moment correlations between the two times series.
Results: Regarding the database with weekly data, temporal correlation was observed between the bulletin of ISS and Wikipedia search trends. The strongest correlation was at a lag of 0 for number of cases and Flu (r=0.7571), Fever and Cough (r=0.7501). The strongest correlation was at a lag of -1 for Fever and Cough (r=0.7501). The strongest correlation was at a lag of 1 for number of cases and Flu (r=0.7559), Fever and Cough (r=0.7501).
Conclusions: A possible future application for programming and management interventions of Public Health is proposed.

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