Web browser as a tool for predicting the incidence of influenza

Sylwia W. Wójcik, M. Duplaga, M. Grysztar, P. Pałka
{"title":"Web browser as a tool for predicting the incidence of influenza","authors":"Sylwia W. Wójcik, M. Duplaga, M. Grysztar, P. Pałka","doi":"10.17219/PZP/84984","DOIUrl":null,"url":null,"abstract":"Background. Infodemiology is focused on the analysis of web content to predict health phenomena. Google Trends (GT) is a free and publicly available service that permits analyses of searches performed with the Google web search engine. With GT it is possible to specify how often certain keywords are searched for. Objectives. The purpose of the study was to determine the feasibility of using data on the frequency of searches with the Google search engine to predict influenza incidence. Material and methods. Using the GT service, data on the frequency of searches for the Polish equivalents of “flu”, “cold” and “fever” in the period of 2014–2016 in Poland were retrieved. Simultaneously, the epidemiological reports prepared by the National Institute of Public Health – National Institute of Hygiene (NIPH-NIH) were obtained for influenza incidence in the same period. Correlations between the variables were assessed using Spearman's rank-order correlation. Results. A statistically significant correlation was confirmed between the average daily search coefficients (ADSC) for all 3 keywords and weekly influenza incidence according to the NIPH-NIH data. The strongest correlation was found for the ADSC of the word “cold” (r = 0.77; p < 0.05). Conclusions. The frequency of searches implemented with the Google search engine may be used for predicting the incidence of influenza in the Polish population.","PeriodicalId":52931,"journal":{"name":"Pielegniarstwo i Zdrowie Publiczne","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pielegniarstwo i Zdrowie Publiczne","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17219/PZP/84984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Background. Infodemiology is focused on the analysis of web content to predict health phenomena. Google Trends (GT) is a free and publicly available service that permits analyses of searches performed with the Google web search engine. With GT it is possible to specify how often certain keywords are searched for. Objectives. The purpose of the study was to determine the feasibility of using data on the frequency of searches with the Google search engine to predict influenza incidence. Material and methods. Using the GT service, data on the frequency of searches for the Polish equivalents of “flu”, “cold” and “fever” in the period of 2014–2016 in Poland were retrieved. Simultaneously, the epidemiological reports prepared by the National Institute of Public Health – National Institute of Hygiene (NIPH-NIH) were obtained for influenza incidence in the same period. Correlations between the variables were assessed using Spearman's rank-order correlation. Results. A statistically significant correlation was confirmed between the average daily search coefficients (ADSC) for all 3 keywords and weekly influenza incidence according to the NIPH-NIH data. The strongest correlation was found for the ADSC of the word “cold” (r = 0.77; p < 0.05). Conclusions. The frequency of searches implemented with the Google search engine may be used for predicting the incidence of influenza in the Polish population.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
网络浏览器作为预测流感发病率的工具
背景。信息流行病学侧重于分析网络内容以预测健康现象。谷歌Trends (GT)是一个免费的公共服务,允许分析使用谷歌web搜索引擎执行的搜索。使用GT,可以指定搜索某些关键字的频率。目标。这项研究的目的是确定利用谷歌搜索引擎的搜索频率数据来预测流感发病率的可行性。材料和方法。使用GT服务,检索了2014-2016年波兰语中“流感”、“感冒”和“发烧”对应词的搜索频率数据。同时,还获得了国家公共卫生研究所-国家卫生研究所(NIPH-NIH)编制的同期流感发病率流行病学报告。变量之间的相关性采用Spearman秩序相关性进行评估。结果。根据NIPH-NIH数据,所有3个关键词的平均每日搜索系数(ADSC)与每周流感发病率之间存在统计学显著相关性。“冷”一词的ADSC相关性最强(r = 0.77;P < 0.05)。结论。使用谷歌搜索引擎实现的搜索频率可用于预测波兰人口中的流感发病率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
53 weeks
期刊最新文献
Attitudes of young people towards antibiotic therapy Food consumption patterns among children and adolescents and their correlation with overweight/obesity in Egypt: A cross-sectional study Selected predictors of suicidal behavior of youth in Poland Food intake changes across the menstrual cycle: A preliminary study Can nurses strike for more money? Challenges for taking nurses’ self-interests into account in the light of the deliberative systems theory: A partial analysis of 2016 strike in the Children’s Memorial Health Institute
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1