Artículo
Toward Deep Digital Contact Tracing: Opportunities and Challenges
Cherini, Renato
; Detke, Ramiro Fernando
; Fraire, Juan Andres
; Madoery, Pablo Gustavo
; Finochietto, Jorge Manuel
Fecha de publicación:
11/2023
Editorial:
IEEE Computer Society
Revista:
Ieee Pervasive Computing
ISSN:
1536-1268
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
During the COVID-19 pandemic, digital contact tracing using mobile devices has been widely explored, with many proposals from academia and industry highlighting the benefits and challenges. Most approaches use Bluetooth low energy signals to learn and trace close contacts among users. However, tracing only these contacts can mask the risk of virus exposure in scenarios with low detection rates. To address this issue, we propose fostering users to exchange information beyond close contacts, particularly about prior âB B deepâB B contacts that may have transmitted the virus. This presents new opportunities for controlling the spread of the virus, but also poses challenges that require further investigation. We provide directions for addressing these challenges based on our recent work developing a technological solution using this approach.
Palabras clave:
COVID-19
,
DATA MODELS
,
DELAYS
,
HISTORY
,
MOBILE HANDSETS
,
PRIVACY
,
PROPOSALS
Archivos asociados
Licencia
Identificadores
Colecciones
Articulos(IDIT)
Articulos de INSTITUTO DE ESTUDIOS AVANZADOS EN INGENIERIA Y TECNOLOGIA
Articulos de INSTITUTO DE ESTUDIOS AVANZADOS EN INGENIERIA Y TECNOLOGIA
Citación
Cherini, Renato; Detke, Ramiro Fernando; Fraire, Juan Andres; Madoery, Pablo Gustavo; Finochietto, Jorge Manuel; Toward Deep Digital Contact Tracing: Opportunities and Challenges; IEEE Computer Society; Ieee Pervasive Computing; 22; 4; 11-2023; 15-25
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