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Improvement of Contact Tracing with Citizen's Distributed Risk Maps.
Rebollo, Miguel; Benito, Rosa María; Losada, Juan Carlos; Galeano, Javier.
  • Rebollo M; VRAIn-Valencian Research Institute for Artificial Intelligence, Universitat Politècnica de València, 46022 Valencia, Spain.
  • Benito RM; Complex Systems Group, Universidad Politécnica de Madrid, 28040 Madrid, Spain.
  • Losada JC; Complex Systems Group, Universidad Politécnica de Madrid, 28040 Madrid, Spain.
  • Galeano J; Complex Systems Group, Universidad Politécnica de Madrid, 28040 Madrid, Spain.
Entropy (Basel) ; 23(5)2021 May 20.
Article en En | MEDLINE | ID: mdl-34065581
The rapid spread of COVID-19 has demonstrated the need for accurate information to contain its diffusion. Technological solutions are a complement that can help citizens to be informed about the risk in their environment. Although measures such as contact traceability have been successful in some countries, their use raises society's resistance. This paper proposes a variation of the consensus processes in directed networks to create a risk map of a determined area. The process shares information with trusted contacts: people we would notify in the case of being infected. When the process converges, each participant would have obtained the risk map for the selected zone. The results are compared with the pilot project's impact testing of the Spanish contact tracing app (RadarCOVID). The paper also depicts the results combining both strategies: contact tracing to detect potential infections and risk maps to avoid movements into conflictive areas. Although some works affirm that contact tracing apps need 60% of users to control the propagation, our results indicate that a 40% could be enough. On the other hand, the elaboration of risk maps could work with only 20% of active installations, but the effect is to delay the propagation instead of reducing the contagion. With both active strategies, this methodology is able to significantly reduce infected people with fewer participants.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Etiology_studies / Risk_factors_studies Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Etiology_studies / Risk_factors_studies Idioma: En Año: 2021 Tipo del documento: Article