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Improvement of Contact Tracing with Citizen’s Distributed Risk Maps

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 co...

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Autores principales: Rebollo, Miguel, Benito, Rosa María, Losada, Juan Carlos, Galeano, Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8160685/
https://www.ncbi.nlm.nih.gov/pubmed/34065581
http://dx.doi.org/10.3390/e23050638
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author Rebollo, Miguel
Benito, Rosa María
Losada, Juan Carlos
Galeano, Javier
author_facet Rebollo, Miguel
Benito, Rosa María
Losada, Juan Carlos
Galeano, Javier
author_sort Rebollo, Miguel
collection PubMed
description 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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spelling pubmed-81606852021-05-29 Improvement of Contact Tracing with Citizen’s Distributed Risk Maps Rebollo, Miguel Benito, Rosa María Losada, Juan Carlos Galeano, Javier Entropy (Basel) Article 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. MDPI 2021-05-20 /pmc/articles/PMC8160685/ /pubmed/34065581 http://dx.doi.org/10.3390/e23050638 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rebollo, Miguel
Benito, Rosa María
Losada, Juan Carlos
Galeano, Javier
Improvement of Contact Tracing with Citizen’s Distributed Risk Maps
title Improvement of Contact Tracing with Citizen’s Distributed Risk Maps
title_full Improvement of Contact Tracing with Citizen’s Distributed Risk Maps
title_fullStr Improvement of Contact Tracing with Citizen’s Distributed Risk Maps
title_full_unstemmed Improvement of Contact Tracing with Citizen’s Distributed Risk Maps
title_short Improvement of Contact Tracing with Citizen’s Distributed Risk Maps
title_sort improvement of contact tracing with citizen’s distributed risk maps
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8160685/
https://www.ncbi.nlm.nih.gov/pubmed/34065581
http://dx.doi.org/10.3390/e23050638
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