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意大利手足口病的数字流行病学和信息流行病学。通过谷歌和维基百科评估疾病趋势。

Digital epidemiology and infodemiology of hand-foot-mouth disease (HFMD) in Italy. Disease trend assessment via Google and Wikipedia.

机构信息

Regional Health Care and Social Agency of Lodi, ASST Lodi.

Department of Biomedical Sciences for Health, University of Milan.

出版信息

Acta Biomed. 2023 Aug 3;94(4):e2023107. doi: 10.23750/abm.v94i4.14184.

DOI:10.23750/abm.v94i4.14184
PMID:37539609
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10440772/
Abstract

BACKGROUND AND AIM

The study aimed to evaluate the epidemiological trend of hand, foot and mouth disease (HFMD) in Italy using data on Internet search volume.

METHODS

A cross-sectional study design was used. Data on Internet searches were obtained from Google Trends (GT) and Wikipedia. We used the following Italian search term: "Malattia mano-piede-bocca" (Hand-foot-mouth disease, in English). A monthly time-frame was extracted, partly overlapping, from July 2015 to December 2022. GT and Wikipedia were overlapped to perform a linear regression and correlation analyses. Statistical analyses were performed using the Spearman's rank correlation coefficient (rho). A linear regression analysis was performed considering Wikipedia and GT.

RESULTS

Search peaks for both Wikipedia and GT occurred in the months November-December during the autumn-winter season and in June during the spring-summer season, except for the period from June 2020 to June 2021, probably due to the restrictions of the COVID19 pandemic. A temporal correlation was observed between GT and Wikipedia search trends.

CONCLUSIONS

This is the first study in Italy that attempts to clarify the epidemiology of HFMD. Google search and Wikipedia can be valuable for public health surveillance; however, to date, digital epidemiology cannot replace the traditional surveillance system.

摘要

背景与目的

本研究旨在利用互联网搜索量数据评估意大利手足口病(HFMD)的流行病学趋势。

方法

采用横断面研究设计。从 Google Trends(GT)和 Wikipedia 中获取互联网搜索数据。我们使用了以下意大利语搜索词:“Malattia mano-piede-bocca”(手足口病,英文)。从 2015 年 7 月到 2022 年 12 月,提取了部分重叠的月度时间框架。GT 和 Wikipedia 重叠进行线性回归和相关分析。使用 Spearman 秩相关系数(rho)进行统计分析。考虑到 Wikipedia 和 GT,进行了线性回归分析。

结果

无论是 Wikipedia 还是 GT,搜索峰值都出现在秋冬季的 11 月至 12 月和春夏季的 6 月,除了 2020 年 6 月至 2021 年 6 月期间,这可能是由于 COVID19 大流行的限制。在 GT 和 Wikipedia 搜索趋势之间观察到了时间相关性。

结论

这是意大利首次尝试阐明 HFMD 的流行病学。谷歌搜索和 Wikipedia 可用于公共卫生监测;然而,到目前为止,数字流行病学还不能替代传统的监测系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/23fa14da4659/ACTA-94-107-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/a118cac8c555/ACTA-94-107-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/40d9438ad957/ACTA-94-107-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/3d6394528d71/ACTA-94-107-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/f14abe129345/ACTA-94-107-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/23fa14da4659/ACTA-94-107-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/a118cac8c555/ACTA-94-107-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/40d9438ad957/ACTA-94-107-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/3d6394528d71/ACTA-94-107-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/f14abe129345/ACTA-94-107-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56e7/10440772/23fa14da4659/ACTA-94-107-g005.jpg

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