Santangelo Omar Enzo, Provenzano Sandro, Vella Carlotta, Firenze Alberto, Stacchini Lorenzo, Cedrone Fabrizio, Gianfredi Vincenza
Regional Health Care and Social Agency of Lodi, ASST Lodi, 26900 Lodi, Italy.
Faculty of Medicine, University of Milan, 20133 Milan, Italy.
Epidemiologia (Basel). 2024 Jul 5;5(3):340-352. doi: 10.3390/epidemiologia5030024.
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.
这项观察性研究的目的是,评估意大利专门的国家监测系统(ISS数据)报告的最常见虫媒病毒病的潜在流行病学趋势,并与互联网搜索结果进行比较,以评估谷歌和维基百科上用户搜索与实际病例之间是否存在相关性/关联性。该研究考虑的时间间隔为2012年6月至2023年12月。我们使用了以下意大利语搜索词:“托斯卡纳病毒”、“西尼罗河病毒”、“蜱传脑炎”和“登革热”。我们将谷歌趋势和维基百科数据重叠,以进行线性回归和相关性分析。根据情况,使用皮尔逊相关系数(r)或斯皮尔曼等级相关系数(rho)进行统计分析。ISS数据与维基百科或谷歌趋势之间的所有相关性均具有统计学意义。登革热谷歌趋势与ISS之间的相关性很强(rho = 0.71),蜱传脑炎谷歌趋势与ISS之间的相关性也很强(rho = 0.71),而其余相关性的r和rho值在0.32至0.67之间,显示出中等程度的时间相关性。观察到的相关性和回归模型为未来的研究奠定了基础,鼓励对数字信息搜索行为与疾病流行率之间的动态关系进行更细致入微的探索。