Deploying decentralized, privacy-preserving proximity tracing

doi:10.1145/3524107

Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/90764

Título:	Deploying decentralized, privacy-preserving proximity tracing
Autor(es):	Troncoso, Carmela Bogdanov, Dan Bugnion, Edouard Chatel, Sylvain Cremers, Cas Gurses, Seda Hubaux, Jean-Pierre Jackson, Dennis Larus, James R. Lueks, Wouter Oliveira, Rui Carlos Mendes de Payer, Mathias Preneel, Bart Pyrgelis, Apostolos Salathe, Marcel Stadler, Theresa Veale, Michael
Data:	2022
Editora:	Association for Computing Machinery
Revista:	Communications of the ACM
Citação:	Troncoso, C., Bogdanov, D., Bugnion, E., Chatel, S., Cremers, C., Gürses, S., … Veale, M. (2022, August 19). Deploying decentralized, privacy-preserving proximity tracing. Communications of the ACM. Association for Computing Machinery (ACM). http://doi.org/10.1145/3524107
Resumo(s):	[Excerpt] CONTACT TRACING IS a time-proven technique for breaking infection chains in epidemics. Public health officials interview those who come in contact with an infectious agent, such as a virus, to identify exposed, potentially infected people. These contacts are notified that they are at risk and should take efforts to avoid infecting others—for example, by going into quarantine, taking a test, wearing a mask continuously, or taking other precautionary measures. In March 2020, as the first wave of the COVID-19 pandemic was peaking, traditional manual contact tracing efforts in many countries were overwhelmed by the sheer volume of cases; by the rapid speed at which SARS-CoV-2 spread; and by the large fraction of asymptomatic, yet infectious, individuals. [...]
Tipo:	Artigo
URI:	https://hdl.handle.net/1822/90764
DOI:	10.1145/3524107
ISSN:	0001-0782
Versão da editora:	https://dl.acm.org/doi/10.1145/3524107
Arbitragem científica:	yes
Acesso:	Acesso aberto
Aparece nas coleções:	HASLab - Artigos em revistas internacionais