Population mobility change for controlling the transmission of COVID-19: mobile phone data analysis in nine cities of China

IF 4.4 1区 地球科学 Q1 REMOTE SENSING Geo-spatial Information Science Pub Date : 2023-10-31 DOI:10.1080/10095020.2023.2246506
Jizhe Xia, Taicheng Li, Zhaoyang Yu, Erzhen Chen, Yang Yue, Zhen Li, Ying Zhou
{"title":"Population mobility change for controlling the transmission of COVID-19: mobile phone data analysis in nine cities of China","authors":"Jizhe Xia, Taicheng Li, Zhaoyang Yu, Erzhen Chen, Yang Yue, Zhen Li, Ying Zhou","doi":"10.1080/10095020.2023.2246506","DOIUrl":null,"url":null,"abstract":"Mobility restriction measures were the main tools to control the spread of COVID-19, but the extent to which the mobility has decreased remained unsure. We investigated the change in local population mobility and its correlation with COVID-19 infections, using 1185 billion aggregated mobile phone data records in nine main cities in China from 10 January to 24 February 2020. The mobility fell by as much as 79.57% compared to the normal days in 2020 and by 58.13% compared to the same lunar period in 2019. The daily incidence of COVID-19 was significantly correlated with local daily mobility (R2 = 0.77, P < 0.001). The instantaneous reproduction number R(t) declined by 3% when mobility was reduced by 10% in the GLM analysis (P < 0.05). Our study indicated that the decreased mobility level, driven by a mixture effect of holiday and public health interventions, could substantially reduce the transmission of COVID-19 to a low level. Our study could provide evidence of mobility restriction to control local transmission for other places facing COVID-19 outbreaks or potential next waves.","PeriodicalId":48531,"journal":{"name":"Geo-spatial Information Science","volume":"37 2","pages":"0"},"PeriodicalIF":4.4000,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geo-spatial Information Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/10095020.2023.2246506","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0

Abstract

Mobility restriction measures were the main tools to control the spread of COVID-19, but the extent to which the mobility has decreased remained unsure. We investigated the change in local population mobility and its correlation with COVID-19 infections, using 1185 billion aggregated mobile phone data records in nine main cities in China from 10 January to 24 February 2020. The mobility fell by as much as 79.57% compared to the normal days in 2020 and by 58.13% compared to the same lunar period in 2019. The daily incidence of COVID-19 was significantly correlated with local daily mobility (R2 = 0.77, P < 0.001). The instantaneous reproduction number R(t) declined by 3% when mobility was reduced by 10% in the GLM analysis (P < 0.05). Our study indicated that the decreased mobility level, driven by a mixture effect of holiday and public health interventions, could substantially reduce the transmission of COVID-19 to a low level. Our study could provide evidence of mobility restriction to control local transmission for other places facing COVID-19 outbreaks or potential next waves.
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
控制COVID-19传播的人口流动变化:中国9个城市的手机数据分析
限制流动措施是控制新冠肺炎传播的主要手段,但流动性下降的程度仍不确定。我们利用2020年1月10日至2月24日期间中国9个主要城市的11850亿条手机数据记录,调查了当地人口流动的变化及其与COVID-19感染的相关性。与2020年的正常天数相比,流动性下降了79.57%,与2019年同期相比下降了58.13%。日新冠肺炎发病率与当地日活动能力显著相关(R2 = 0.77, P < 0.001)。GLM分析结果显示,当迁移率降低10%时,瞬时繁殖数R(t)下降3% (P < 0.05)。我们的研究表明,在假期和公共卫生干预措施的混合作用下,流动性水平的降低可以将COVID-19的传播大大降低到较低水平。我们的研究可以为其他面临COVID-19疫情或潜在下一波疫情的地方提供限制人员流动的证据,以控制当地传播。
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
CiteScore
10.10
自引率
28.30%
发文量
710
审稿时长
31 weeks
期刊介绍: Geo-spatial Information Science was founded in 1998 by Wuhan University, and is now published in partnership with Taylor & Francis. The journal publishes high quality research on the application and development of surveying and mapping technology, including photogrammetry, remote sensing, geographical information systems, cartography, engineering surveying, GPS, geodesy, geomatics, geophysics, and other related fields. The journal particularly encourages papers on innovative applications and theories in the fields above, or of an interdisciplinary nature. In addition to serving as a source reference and archive of advancements in these disciplines, Geo-spatial Information Science aims to provide a platform for communication between researchers and professionals concerned with the topics above. The editorial committee of the journal consists of 21 professors and research scientists from different regions and countries, such as America, Germany, Switzerland, Austria, Hong Kong and China.
期刊最新文献
Remote sensing image super-resolution via cross-scale hierarchical transformer Improved estimation of the underestimated GEDI footprint LAI in dense forests Dual-environment feature fusion-based method for estimating building-scale population distributions PH-shape: an adaptive persistent homology-based approach for building outline extraction from ALS point cloud data Automated noise modelling using a triangulated terrain model
×
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