气候变化领域集成服务门户(CCPortal): Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing

CCPortal

DOI	10.1126/science.abb6936
	Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing
	Ferretti L.; Wymant C.; Kendall M.; Zhao L.; Nurtay A.; Abeler-Dörner L.; Parker M.; Bonsall D.; Fraser C.
发表日期	2020
ISSN	0036-8075
卷号	368 期号:6491
英文摘要	The newly emergent human virus SARS-CoV-2 (severe acute respiratory syndrome–coronavirus 2) is resulting in high fatality rates and incapacitated health systems. Preventing further transmission is a priority. We analyzed key parameters of epidemic spread to estimate the contribution of different transmission routes and determine requirements for case isolation and contact tracing needed to stop the epidemic. Although SARS-CoV-2 is spreading too fast to be contained by manual contact tracing, it could be controlled if this process were faster, more efficient, and happened at scale. A contact-tracing app that builds a memory of proximity contacts and immediately notifies contacts of positive cases can achieve epidemic control if used by enough people. By targeting recommendations to only those at risk, epidemics could be contained without resorting to mass quarantines (“lockdowns”) that are harmful to society. We discuss the ethical requirements for an intervention of this kind. © 2020 American Association for the Advancement of Science. All rights reserved.
关键词	disease control epidemic memory parasite transmission viral disease Article asymptomatic disease China contact examination coronavirus disease 2019 disease control disease transmission health care system human incubation time mathematical model mobile application mortality rate priority journal quarantine rating scale Severe acute respiratory syndrome coronavirus 2 virus transmission algorithm basic reproduction number Betacoronavirus contact examination Coronavirus infection epidemic ethics infection control mobile application mobile phone pandemic probability procedures theoretical model time factor virus pneumonia Coronavirus SARS coronavirus Algorithms Asymptomatic Diseases Basic Reproduction Number Betacoronavirus Cell Phone China Contact Tracing Coronavirus Infections Epidemics Humans Infection Control Mobile Applications Models, Theoretical Pandemics Pneumonia, Viral Probability Quarantine Time Factors
语种	英语
来源机构	Science
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/133518
推荐引用方式 GB/T 7714	Ferretti L.,Wymant C.,Kendall M.,et al. Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing[J]. Science,2020,368(6491).
APA	Ferretti L..,Wymant C..,Kendall M..,Zhao L..,Nurtay A..,...&Fraser C..(2020).Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing.,368(6491).
MLA	Ferretti L.,et al."Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing".368.6491(2020).