Data science approaches to confronting the COVID-19 pandemic: a narrative review

doi:10.1098/rsta.2021.0127

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	Data science approaches to confronting the COVID-19 pandemic: a narrative review
	Zhang, Qingpeng 1; Gao, Jianxi 2; Wu, Joseph T.3; Cao, Zhidong4,5 ; Zeng, Daniel Dajun4,5
发表期刊	PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
ISSN	1364-503X
	2022-01-10
卷号	380 期号:2214 页码:20
通讯作者	Zhang, Qingpeng(qingpeng.zhang@cityu.edu.hk)
摘要	During the COVID-19 pandemic, more than ever, data science has become a powerful weapon in combating an infectious disease epidemic and arguably any future infectious disease epidemic. Computer scientists, data scientists, physicists and mathematicians have joined public health professionals and virologists to confront the largest pandemic in the century by capitalizing on the large-scale 'big data' generated and harnessed for combating the COVID-19 pandemic. In this paper, we review the newly born data science approaches to confronting COVID-19, including the estimation of epidemiological parameters, digital contact tracing, diagnosis, policy-making, resource allocation, risk assessment, mental health surveillance, social media analytics, drug repurposing and drug development. We compare the new approaches with conventional epidemiological studies, discuss lessons we learned from the COVID-19 pandemic, and highlight opportunities and challenges of data science approaches to confronting future infectious disease epidemics. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.
关键词	infectious disease mathematical modelling data science big data COVID-19
DOI	10.1098/rsta.2021.0127
关键词[WOS]	BIG DATA ; PREPAREDNESS
收录类别	SCI
语种	英语
资助项目	Research Grants Council of the Hong Kong Special Administrative Region, China[11218221] ; Research Grants Council of the Hong Kong Special Administrative Region, China[C7154-20GF] ; Research Grants Council of the Hong Kong Special Administrative Region, China[C7151-20GF] ; Research Grants Council of the Hong Kong Special Administrative Region, China[C1143-20GF]
项目资助者	Research Grants Council of the Hong Kong Special Administrative Region, China
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000720844400014
出版者	ROYAL SOC
引用统计	被引频次：21[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/46525
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全
通讯作者	Zhang, Qingpeng
作者单位	1.City Univ Hong Kong, Sch Data Sci, Hong Kong, Peoples R China 2.Rensselaer Polytech Inst, Dept Comp Sci, Troy, NY 12180 USA 3.Univ Hong Kong, LKS Fac Med, WHO Collaborating Ctr Infect Dis Epidemiol & Cont, Sch Publ Hlth, Hong Kong, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Qingpeng,Gao, Jianxi,Wu, Joseph T.,et al. Data science approaches to confronting the COVID-19 pandemic: a narrative review[J]. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES,2022,380(2214):20.
APA	Zhang, Qingpeng,Gao, Jianxi,Wu, Joseph T.,Cao, Zhidong,&Zeng, Daniel Dajun.(2022).Data science approaches to confronting the COVID-19 pandemic: a narrative review.PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES,380(2214),20.
MLA	Zhang, Qingpeng,et al."Data science approaches to confronting the COVID-19 pandemic: a narrative review".PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES 380.2214(2022):20.