0000000000314869
AUTHOR
Calamusa G.
Digital epidemiology: assessment of measles infection through Google Trends mechanism in Italy.
Introduction. The primary aim of this study is to evaluate the temporal correlation between Google Trends and the data on measles infection arising from the conventional surveillance system, reported by the Istituto Superiore di Sanità's (ISS) bulletin. Moreover, this study is also aimed at forecasting the trends of the reported infectious diseases cases over time. Materials and Methods. The reported cases of measles were selected from January 2013 until October 2018. The data on Internet searches have been obtained from Google Trends; the research data referred to the first 48 weeks of year 2017 have been aggregated on a weekly basis. The search volume provided by Google Trends has a relat…
Predicting disease outbreaks: evaluating measles infection with Wikipedia Trends.
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 Kopl…