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Infodemiology and Infoveillance of the Four Most Widespread Arbovirus Diseases in Italy.
Santangelo, Omar Enzo; Provenzano, Sandro; Vella, Carlotta; Firenze, Alberto; Stacchini, Lorenzo; Cedrone, Fabrizio; Gianfredi, Vincenza.
Affiliation
  • Santangelo OE; Regional Health Care and Social Agency of Lodi, ASST Lodi, 26900 Lodi, Italy.
  • Provenzano S; Faculty of Medicine, University of Milan, 20133 Milan, Italy.
  • Vella C; Local Health Unit of Trapani, ASP Trapani, 91100 Trapani, Italy.
  • Firenze A; Regional Health Care and Social Agency of Lodi, ASST Lodi, 26900 Lodi, Italy.
  • Stacchini L; Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, 90133 Palermo, Italy.
  • Cedrone F; Department of Health Science, University of Florence, 50134 Florence, Italy.
  • Gianfredi V; Local Health Unit of Pescara, Hospital Management, 65122 Pescara, Italy.
Epidemiologia (Basel) ; 5(3): 340-352, 2024 Jul 05.
Article in En | MEDLINE | ID: mdl-39051204
ABSTRACT
The purpose of this observational study was to evaluate the potential epidemiological trend of arboviral diseases most reported in Italy by the dedicated national surveillance system (ISS data) compared to searches on the internet, assessing whether a correlation/association between users' searches in Google and Wikipedia and real cases exists. The study considers a time interval from June 2012 to December 2023. We used the following Italian search terms "Virus Toscana", "Virus del Nilo occidentale" (West Nile Virus in English), "Encefalite trasmessa da zecche" (Tick Borne encephalitis in English), and "Dengue". We overlapped Google Trends and Wikipedia data to perform a linear regression and correlation analysis. Statistical analyses were performed using Pearson's correlation coefficient (r) or Spearman's rank correlation coefficient (rho) as appropriate. All the correlations between the ISS data and Wikipedia or GT exhibited statistical significance. The correlations were strong for Dengue GT and ISS (rho = 0.71) and TBE GT and ISS (rho = 0.71), while the remaining correlations had values of r and rho between 0.32 and 0.67, showing a moderate temporal correlation. The observed correlations and regression models provide a foundation for future research, encouraging a more nuanced exploration of the dynamics between digital information-seeking behavior and disease prevalence.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Epidemiologia (Basel) Year: 2024 Document type: Article Affiliation country: Italia Country of publication: Suiza

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Epidemiologia (Basel) Year: 2024 Document type: Article Affiliation country: Italia Country of publication: Suiza