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Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing.
- Source :
-
Science (New York, N.Y.) [Science] 2020 May 08; Vol. 368 (6491). Date of Electronic Publication: 2020 Mar 31. - Publication Year :
- 2020
-
Abstract
- 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.<br /> (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)
- Subjects :
- Algorithms
Asymptomatic Diseases
Basic Reproduction Number
COVID-19
China epidemiology
Contact Tracing ethics
Coronavirus Infections epidemiology
Epidemics prevention & control
Humans
Infection Control
Models, Theoretical
Pneumonia, Viral epidemiology
Probability
Quarantine
SARS-CoV-2
Time Factors
Betacoronavirus
Cell Phone
Contact Tracing methods
Coronavirus Infections prevention & control
Coronavirus Infections transmission
Mobile Applications ethics
Pandemics prevention & control
Pneumonia, Viral prevention & control
Pneumonia, Viral transmission
Subjects
Details
- Language :
- English
- ISSN :
- 1095-9203
- Volume :
- 368
- Issue :
- 6491
- Database :
- MEDLINE
- Journal :
- Science (New York, N.Y.)
- Publication Type :
- Academic Journal
- Accession number :
- 32234805
- Full Text :
- https://doi.org/10.1126/science.abb6936