意大利四种最广泛传播的虫媒病毒病的病原学和监测情况

O. E. Santangelo, S. Provenzano, Carlotta Vella, Alberto Firenze, L. Stacchini, F. Cedrone, V. Gianfredi
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引用次数: 0

摘要

这项观察性研究旨在评估意大利国家专门监测系统(ISS 数据)报告最多的虫媒病毒疾病的潜在流行趋势与互联网搜索的对比情况,评估用户在谷歌和维基百科上的搜索与真实病例之间是否存在相关性/关联性。研究的时间跨度为 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,进行线性回归和相关分析。统计分析酌情使用皮尔逊相关系数(r)或斯皮尔曼等级相关系数(rho)。ISS 数据与维基百科或 GT 之间的所有相关性都具有统计学意义。登革热 GT 与 ISS 的相关性较强(rho = 0.71),而结核病 GT 与 ISS 的相关性较弱(rho = 0.71),其余相关性的 r 和 rho 值介于 0.32 和 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今后的研究奠定了基础,有助于更细致地探讨数字信息搜索行为与疾病流行之间的动态关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Infodemiology and Infoveillance of the Four Most Widespread Arbovirus Diseases in Italy
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.
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