Estimation and demographic analysis of COVID-19 infections with respect to weather factors in Europe

IF 1.6 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of Business Analytics Pub Date : 2020-07-02 DOI:10.1080/2573234x.2020.1832866
Reza Gharoie Ahangar, R. Pavur, Mahdis Fathi, A. Shaik
{"title":"Estimation and demographic analysis of COVID-19 infections with respect to weather factors in Europe","authors":"Reza Gharoie Ahangar, R. Pavur, Mahdis Fathi, A. Shaik","doi":"10.1080/2573234x.2020.1832866","DOIUrl":null,"url":null,"abstract":"ABSTRACT The main objective of this study is to investigate the relationship between the COVID-19 and the weather factors of the most populated and industrialised countries in Europe and propose the best mathematical model to forecast the daily number of COVID-19 cases. To find the relationship between the COVID-19 and the weather factors of absolute humidity and temperature in Spain, France, Italy, Germany, and the United Kingdom, we conducted a Poisson analysis. We also used the General Linear Neural Network (GRNN) model to forecast the trend and number of daily COVID-19 cases in these European countries. The results reveal a statistically significant negative relationship between the number of COVID-19 infections and weather factors of temperature & absolute humidity. Furthermore, the results show a stronger negative relationship between COVID-19 and absolute humidity than temperature. In our proposed GRNN method, we find better compatibility for the COVID-19 cases in Italy relative to the other European countries in this study.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"56 1","pages":"93 - 106"},"PeriodicalIF":1.6000,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2573234x.2020.1832866","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 8

Abstract

ABSTRACT The main objective of this study is to investigate the relationship between the COVID-19 and the weather factors of the most populated and industrialised countries in Europe and propose the best mathematical model to forecast the daily number of COVID-19 cases. To find the relationship between the COVID-19 and the weather factors of absolute humidity and temperature in Spain, France, Italy, Germany, and the United Kingdom, we conducted a Poisson analysis. We also used the General Linear Neural Network (GRNN) model to forecast the trend and number of daily COVID-19 cases in these European countries. The results reveal a statistically significant negative relationship between the number of COVID-19 infections and weather factors of temperature & absolute humidity. Furthermore, the results show a stronger negative relationship between COVID-19 and absolute humidity than temperature. In our proposed GRNN method, we find better compatibility for the COVID-19 cases in Italy relative to the other European countries in this study.
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
欧洲COVID-19感染与天气因素的估计和人口分析
本研究的主要目的是调查欧洲人口最多和工业化国家的COVID-19与天气因素之间的关系,并提出预测COVID-19日病例数的最佳数学模型。为了找出COVID-19与西班牙、法国、意大利、德国和英国的绝对湿度和温度等天气因素之间的关系,我们进行了泊松分析。我们还使用通用线性神经网络(GRNN)模型预测了这些欧洲国家每日COVID-19病例的趋势和数量。结果显示,新冠肺炎感染人数与气温、绝对湿度等天气因素呈显著负相关。此外,研究结果表明,COVID-19与绝对湿度的负相关关系强于温度。在我们提出的GRNN方法中,我们发现相对于本研究中其他欧洲国家,意大利的COVID-19病例具有更好的兼容性。
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
Journal of Business Analytics
Journal of Business Analytics Business, Management and Accounting-Management Information Systems
CiteScore
2.50
自引率
0.00%
发文量
13
期刊最新文献
Exploring the relationship between YouTube video optimisation practices and video rankings for online marketing: a machine learning approach The era of business analytics: identifying and ranking the differences between business intelligence and data science from practitioners’ perspective using the Delphi method Intelligent decision support system using nested ensemble approach for customer churn in the hotel industry Introducing technological disruption: how breaking media attention on corporate events impacts online sentiment An adaptive and enhanced framework for daily stock market prediction using feature selection and ensemble learning algorithms
×
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:604180095
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