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洞察数据:维基百科对意大利虫媒病毒的研究及真实案例

Insight the data: Wikipedia's researches and real cases of arboviruses in Italy.

作者信息

Provenzano Sandro, Gianfredi Vincenza, Santangelo Omar Enzo

机构信息

Azienda Ospedaliera Universitaria Policlinico "P. Giaccone", Palermo, Italy.

School of Medicine, Vita-Salute San Raffaele University, Milan, Italy.

出版信息

Public Health. 2021 Mar;192:21-29. doi: 10.1016/j.puhe.2020.12.010. Epub 2021 Feb 16.

Abstract

OBJECTIVES

The primary aim of this study was to evaluate the temporal correlation between Wikitrends and conventional surveillance data generated for Chikungunya, Dengue, Zika, and West Nile Virus infection reported by bulletin of Italian National Institute of Health (Istituto Superiore di Sanità in italian, ISS).

STUDY DESIGN

A cross-sectional study design was used.

METHODS

The reported cases of Dengue and Chikungunya were selected from July 2015 to December 2019. For West Nile Virus, the bulletins are issued in the period June-November (6 months) of the years 2015-2019, and for Zika virus, the data reported in the ISS bulletin start from January 2016. From Wikipedia Trends, we extracted the number of monthly views by users from the July 2015 to December 2019 of the pages Chikungunya, Dengue, Zika virus, and West Nile Virus.

RESULTS

A correlation was observed between the bulletin of ISS and Wikipedia Wikitrends, the correlation was strong for Chikungunya and West Nile Virus (r = 0.9605; r = 0.9556, respectively), and highly statistically significant with P-values <0.001. The correlation was moderate for Dengue and Zika virus (r = 0.6053; r = 0.5888, respectively), but highly statistically significant with P-values <0.001.

CONCLUSIONS

Classical surveillance system should be integrated with the tools of digital epidemiology that have potential role in public health for the dynamic information and provide near real-time indicators of the spread of infectious disease.

摘要

目的

本研究的主要目的是评估维基趋势(Wikitrends)与意大利国家卫生研究所(意大利语为Istituto Superiore di Sanità,简称ISS)公告所报告的基孔肯雅热、登革热、寨卡病毒和西尼罗河病毒感染的传统监测数据之间的时间相关性。

研究设计

采用横断面研究设计。

方法

选取2015年7月至2019年12月报告的登革热和基孔肯雅热病例。对于西尼罗河病毒,公告发布时间为2015 - 2019年6月至11月(6个月);对于寨卡病毒,ISS公告报告的数据从2016年1月开始。从维基百科趋势中,我们提取了2015年7月至2019年12月期间用户对基孔肯雅热、登革热、寨卡病毒和西尼罗河病毒页面的每月浏览量。

结果

观察到ISS公告与维基百科趋势之间存在相关性,基孔肯雅热和西尼罗河病毒的相关性较强(分别为r = 0.9605;r = 0.9556),P值<0.001,具有高度统计学意义。登革热和寨卡病毒的相关性中等(分别为r = 0.6053;r = 0.5888),但P值<0.001,具有高度统计学意义。

结论

经典监测系统应与数字流行病学工具相结合,这些工具在公共卫生中对于动态信息具有潜在作用,并能提供传染病传播的近实时指标。

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