题名

Google Trends搜尋關鍵字熱度與COVID-19疫情趨勢的相關性－以臺灣為例的網路行為觀察性研究

并列篇名

Correlations between Google Trends Query Data and Covid-19 Epidemic Trends-an Observational Study of the Popular Search Behavior in Taiwan

作者

張昱維(Yu-Wei Chang)；蔡易昌(Yi-Chang Tsai)；楊惠春(Hui-Chun Yang)；樊聖(Frank Sheng Fan)

关键词

嚴重特殊傳染性肺炎 ； Google Trends ； 疫情監測工具 ； 巨量數據分析 ； COVID-19 ； Google Trends ； Epidemic surveillance tool ； Big data analysis

期刊名称

醫學與健康期刊

卷期/出版年月

10卷3期（2021 / 11 / 01）

页次

17 - 31

内容语文

繁體中文
中文摘要

目的：嚴重特殊傳染性肺炎（COVID-19）的疫情已蔓延全球。核酸檢測是診斷COVID-19的參考方法，然而受限於實驗室資源，部分地區無法即時反應疫情。本次研究分析關鍵字搜尋熱度與COVID-19疫情相關性，希望建立即時疫情監測工具。方法：以Pearson係數分析COVID-19確診數與Google Trends搜尋熱度之相關性。結果：結果顯示COVID-19、corona等搜尋熱度與當周確診數有高度相關性；肺炎、冠狀病毒、口罩等則顯示中度相關。COVID-19、corona、防護衣、社區感染、隔離及葉克膜等關鍵字與延後一周的確診數具高度相關。結論：Google Trends搜尋熱度可即時反應COVID-19疫情趨勢。以巨量數據分析來監測疫情的效果將比傳統實驗室結果更具防疫優勢。
英文摘要

Objectives. Coronavirus disease 2019 (COVID-19) is an atypical pneumonia caused by SARS-CoV-2 infection, which is continuing to spread worldwide. Nowadays, nucleic acid testing is the golden standard to diagnosis COVID-19. However, technique limitation remains in some less-developed countries and remote areas. Therefore, we aim to develop a surveillance system suitable for monitoring epidemic outbreaks and assessing public opinion. Methods. We used Pearson coefficients to analyze the correlation between COVID-19 epidemic data (confirmed case) and online search query data. Results. Based on our approach, we noted that keywords ＂COVID-19＂, ＂corona＂, ＂PPE (Personal protective equipment)＂, ＂community infection＂, ＂smell＂ exhibited good correlation between Google Trends query data and COVID-19 incidence; keywords ＂pneumonia＂, ＂corona virus＂, ＂mask＂, ＂quarantine＂, ＂fever＂, ＂taste＂, ＂dyspnea＂, exhibited moderate correlation. Furthermore, some keywords displayed high correlation with 1-week lag COVID-19 incidence, including ＂corona＂, ＂PPE＂, ＂community infection＂, ＂quarantine＂ and ＂ECMO＂. Conclusion. These results suggested that Google Trends can be a potential surveillance tool for COVID-19 outbreaks in Taiwan. Online search activity indicates what people concerned during epidemic outbreaks, even if they do not visit hospitals. This finding prompted us to analyze the big data and serve as useful tools to monitor social media during an epidemic. These media usage reflects infectious disease trends more quickly than does traditional reporting.
主题分类 醫藥衛生 > 預防保健與衛生學
醫藥衛生 > 社會醫學
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