Articles producció científica> Enginyeria Informàtica i Matemàtiques

Message-passing approach to epidemic tracing and mitigation with apps

  • Datos identificativos

    Identificador: imarina:9172955
    Handle: https://hdl.handle.net/20.500.11797/imarina9172955
    Autores:
    Bianconi, GinestraSun, HanlinRapisardi, GiacomoArenas, Alex
    Resumen:
    With the hit of new pandemic threats, scientific frameworks are needed to understand the unfolding of the epidemic. The use of mobile apps that are able to trace contacts is of utmost importance in order to control new infected cases and contain further propagation. Here we present a theoretical approach using both percolation and message-passing techniques, to the role of contact tracing, in mitigating an epidemic wave. We show how the increase of the app adoption level raises the value of the epidemic threshold, which is eventually maximized when high-degree nodes are preferentially targeted. Analytical results are compared with extensive Monte Carlo simulations showing good agreement for both homogeneous and heterogeneous networks. These results are important to quantify the level of adoption needed for contact-tracing apps to be effective in mitigating an epidemic.

  • Otros:

    Autor según el artículo: Bianconi, Ginestra; Sun, Hanlin; Rapisardi, Giacomo; Arenas, Alex
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: Arenas Moreno, Alejandro / Rapisardi, Giacomo
    Palabras clave: Theoretical approach Solvents Networks Monte carlo methods Mobile apps Message passing High-degree nodes Heterogeneous networks Epidemiology Epidemic threshold Contact tracing Complex Analytical results Adoption level
    Resumen: With the hit of new pandemic threats, scientific frameworks are needed to understand the unfolding of the epidemic. The use of mobile apps that are able to trace contacts is of utmost importance in order to control new infected cases and contain further propagation. Here we present a theoretical approach using both percolation and message-passing techniques, to the role of contact tracing, in mitigating an epidemic wave. We show how the increase of the app adoption level raises the value of the epidemic threshold, which is eventually maximized when high-degree nodes are preferentially targeted. Analytical results are compared with extensive Monte Carlo simulations showing good agreement for both homogeneous and heterogeneous networks. These results are important to quantify the level of adoption needed for contact-tracing apps to be effective in mitigating an epidemic.
    Áreas temáticas: Physics, multidisciplinary Physics and astronomy (miscellaneous) Physics and astronomy (all)
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: alexandre.arenas@urv.cat
    Identificador del autor: 0000-0003-0937-0334
    Fecha de alta del registro: 2024-09-28
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Physical Review Research. 3 (1): L012014-
    Referencia de l'ítem segons les normes APA: Bianconi, Ginestra; Sun, Hanlin; Rapisardi, Giacomo; Arenas, Alex (2021). Message-passing approach to epidemic tracing and mitigation with apps. Physical Review Research, 3(1), L012014-. DOI: 10.1103/PhysRevResearch.3.L012014
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2021
    Tipo de publicación: Journal Publications

  • Palabras clave:

    Physics and Astronomy (Miscellaneous),Physics, Multidisciplinary
    Theoretical approach
    Solvents
    Networks
    Monte carlo methods
    Mobile apps
    Message passing
    High-degree nodes
    Heterogeneous networks
    Epidemiology
    Epidemic threshold
    Contact tracing
    Complex
    Analytical results
    Adoption level
    Physics, multidisciplinary
    Physics and astronomy (miscellaneous)
    Physics and astronomy (all)

  • Documentos:

    DocumentPrincipal

  • Cerca a google

    Search to google scholar