Document detail
ID

oai:pubmedcentral.nih.gov:7975...

Topic
Original Article
Author
Gianfredi, Vincenza Santangelo, Omar Enzo Provenzano, Sandro
Langue
en
Editor

Mattioli 1885

Category

Acta Bio Medica : Atenei Parmensis

Year

2021

listing date

9/26/2023

Keywords
strongest influenza weekly 7501 lag data cough fever r=0 correlation
Metrics

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.

Gianfredi, Vincenza,Santangelo, Omar Enzo,Provenzano, Sandro, 2021, Correlation between flu and Wikipedia’s pages visualization, Mattioli 1885

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