Literature DB >> 31282485

Predicting disease outbreaks: evaluating measles infection with Wikipedia Trends.

Sandro Provenzano1, Omar Enzo Santangelo1, Domiziana Giordano1, Enrico Alagna1, Dario Piazza1, Dario Genovese1, Giuseppe Calamusa1, Alberto Firenze1.   

Abstract

The primary aim of this study was to evaluate the temporal correlation between Wikitrends and conventional surveillance data generated for measles infection reported by bulletin of Istituto Superiore di Sanità (ISS). The reported cases of measles were selected from July 2015 to October 2018. 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 and monthly basis. The following data were extracted: number of views by users from 1 July 2015 to 31 October 2018 of the Morbillo, Vaccinazione del Morbillo, Vaccinazione MPR and Macchie di Koplik pages (Measles, Measles Vaccination, MPR Vaccination and Koplik's spots in English). Cross-correlation results were obtained as product-moment correlations between the two time series. Regarding the database with monthly data, temporal correlation was observed between the bulletin of ISS and Wikipedia search trends: the strongest correlation was at a lag of 0 for Measles (r=0.9164), Measles Vaccination (r=0.8622), MPR Vaccination (r=0.7852) and Koplik's spots (r=0.8217). Regarding the database with weekly data, both moderate and strong correlation was observed. A possible future application for programming and management interventions of Public Health is proposed.

Entities:  

Year:  2019        PMID: 31282485     DOI: 10.1701/3182.31610

Source DB:  PubMed          Journal:  Recenti Prog Med        ISSN: 0034-1193


  6 in total

1.  Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis.

Authors:  U Venkatesh; Periyasamy Aravind Gandhi
Journal:  Healthc Inform Res       Date:  2020-07-31

2.  Can Google Trends and Wikipedia help traditional surveillance? A pilot study on measles.

Authors:  Omar Enzo Santangelo; Sandro Provenzano; Dimple Grigis; Domiziana Giordano; Francesco Armetta; Alberto Firenze
Journal:  Acta Biomed       Date:  2020-11-12

3.  Burden of measles using disability-adjusted life years, Umbria 2013-2018.

Authors:  Vincenza Gianfredi; Massimo Moretti; Igino Fusco Moffa
Journal:  Acta Biomed       Date:  2020-04-10

4.  Correlation between flu and Wikipedia's pages visualization.

Authors:  Vincenza Gianfredi; Omar Enzo Santangelo; Sandro Provenzano
Journal:  Acta Biomed       Date:  2021-02-08

5.  Infodemiology of flu: Google trends-based analysis of Italians' digital behavior and a focus on SARS-CoV-2, Italy.

Authors:  Omar Enzo Santangelo; Sandro Provenzano; Vincenza Gianfredi
Journal:  J Prev Med Hyg       Date:  2021-09-15

6.  What's hot and what's not in lay psychology: Wikipedia's most-viewed articles.

Authors:  Kaśmir Ciechanowski; Natalia Banasik-Jemielniak; Dariusz Jemielniak
Journal:  Curr Psychol       Date:  2022-10-12
  6 in total

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