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

INTRODUCTION: Cases of measles in some European countries are increasing. The aim of this study is to find the correlation between Google Trends and Wikipedia searches and the real number of cases notified. MATERIALS AND METHODS: The data on Internet searches have been obtained from Google Trends and Wikipedia. The reported cases of measles were selected from January 2013 until December 2018 for Google Trends and July 2015 until December 2018  from for Wikipedia. We have selected data from four European Countries: Italy, France, Germany and Romania. The data extracted from Wikipedia and Google Trends have been moved over time (Lag), one month in the future and one month in the past. Cross-correlation results are obtained as product-moment correlations between the two time series. The statistical analyses have been performed by using the Spearman's rank correlation coefficient or Pearson correlation coefficient. RESULTS: A temporal correlation was observed between the bulletin of ECDC and Wikipedia search trends. For Wikipedia the strongest correlation is at a lag of +1 for rougeole (r=0.9006) and masern (r=0.7023) and at lag 0 for morbillo (r=0.8892) and rujeola (r=0.5462); for Google Trends the strongest correlation at a lag 0 for rougeole (rho=0.7398), symptômes rougeole (rho=0.3399), masern (rho=0.6484), sintomi morbillo (rho=0.6029), rujeola (rho=0.7209), simptome rujeola (rho=0.5297) and at lag -1 for masern symptom (rho=0.4536) and morbillo (rho=0.5804). CONCLUSIONS: Google and Wikipedia could play an important role in surveillance, although these tools need to be combined with traditional surveillance systems.

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 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.

Nursing students and depressive symptomatology: an observational study in University of Palermo.

PURPOSE: Depression is a common and serious medical illness, considered as a public health issue because it interferes with the interpersonal, social and professional functioning of the individual, and its frequency is constantly increasing. According to a recent review, approximately 34 per cent of nursing students had experienced depression worldwide. The university period may represent a moment in which the mental well-being of students is subjected to stress with a relative predisposition to the development of diseases related to mood disorders. The purpose of this study is to estimate the prevalence and examine the socio-demographic correlates of depressive symptomatology. DESIGN/METHODOLOGY/APPROACH: In April 2019, a questionnaire was administered to all the nursing students of University of Palermo of the three years of course, accompanied by informed consent. Multivariable logistic regression was performed. The statistical significance level chosen for all analyses was 0.05. The results were analyzed using the STATA statistical software version 14. Results are expressed as adjusted odds ratio (aOR) with 95 per cent confidence intervals. FINDINGS: The sample consists of 493 students who completed the questionnaire, and the average age of the sample participants is 21.88 years. The multivariable logistic regression model shows that the risk to have depressive symptomatology is significantly associated with the following independent variables: female gender (aOR 1.91), being single (aOR 1.87), second year of study (aOR 1.94), third year of study (aOR 1.92), not performing regular physical activity (aOR 1.78) and perceived low health status (aOR 3.08). ORIGINALITY/VALUE: This study shows that belonging to the female gender, being further along in the years of study, having a chronic illness and perceiving a low state of health are all factors that can increase the risk of developing the symptoms of depression; rather, regular physical activity, friendship and romantic relationships can be considered factors protecting them from the risk of falling into depression that can undermine both the study and work performance. Certainly, it is important to analyze all the involved variables to improve the global health not only of the nursing students but of all the students.