G2TT
来源类型Working Paper
规范类型报告
DOI10.3386/w26990
来源IDWorking Paper 26990
The Geographic Spread of COVID-19 Correlates with the Structure of Social Networks as Measured by Facebook
Theresa Kuchler; Dominic Russel; Johannes Stroebel
发表日期2020-04-13
出版年2020
语种英语
摘要We use aggregated data from Facebook to show that COVID-19 was more likely to spread between regions with stronger social network connections. Areas with more social ties to two early COVID-19 “hotspots” (Westchester County, NY, in the U.S. and Lodi province in Italy) generally had more confirmed COVID-19 cases as of the end of March. These relationships hold after controlling for geographic distance to the hotspots as well as for the income and population densities of the regions. As the pandemic progressed in the U.S., a county's social proximity to recent COVID- 19 cases predicts future outbreaks over and above physical proximity. These results suggest data from online social networks can be useful to epidemiologists and others hoping to forecast the spread of communicable diseases such as COVID-19.
主题Health, Education, and Welfare ; Regional and Urban Economics ; COVID-19
URLhttps://www.nber.org/papers/w26990
来源智库National Bureau of Economic Research (United States)
引用统计
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/584662
推荐引用方式
GB/T 7714
Theresa Kuchler,Dominic Russel,Johannes Stroebel. The Geographic Spread of COVID-19 Correlates with the Structure of Social Networks as Measured by Facebook. 2020.
条目包含的文件
文件名称/大小 资源类型 版本类型 开放类型 使用许可
w26990.pdf(462KB)智库出版物 限制开放CC BY-NC-SA浏览
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Theresa Kuchler]的文章
[Dominic Russel]的文章
[Johannes Stroebel]的文章
百度学术
百度学术中相似的文章
[Theresa Kuchler]的文章
[Dominic Russel]的文章
[Johannes Stroebel]的文章
必应学术
必应学术中相似的文章
[Theresa Kuchler]的文章
[Dominic Russel]的文章
[Johannes Stroebel]的文章
相关权益政策
暂无数据
收藏/分享
文件名: w26990.pdf
格式: Adobe PDF
此文件暂不支持浏览

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。