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A mathematical model for the spatiotemporal epidemic spreading of COVID19

  • Datos identificativos

    Identificador: imarina:9006522
    Autores:
    Alex ArenasWesley CotaJesus Gomez-GardenesSergio GómezClara GranellJoan T MatamalasDavid Soriano-PanosBenjamin Steinegger
    Resumen:
    An outbreak of a novel coronavirus, named SARS-CoV-2, that provokes the COVID-19 disease, was first reported in Hubei, mainland China on 31 December 2019. As of 20 March 2020, cases have been reported in 166 countries/regions, including cases of human-to-human transmission around the world. The proportions of this epidemics is probably one of the largest challenges faced by our interconnected modern societies. According to the current epidemiological reports, the large basic reproduction number, R_0 ~ 2.3, number of secondary cases produced by an infected individual in a population of susceptible individuals, as well as an asymptomatic period (up to 14 days) in which infectious individuals are undetectable without further analysis, pave the way for a major crisis of the national health capacity systems. Recent scientific reports have pointed out that the detected cases of COVID19 at young ages is strikingly short and that lethality is concentrated at large ages. Here we adapt a Microscopic Markov Chain Approach (MMCA) metapopulation mobility model to capture the spread of COVID-19. We propose a model that stratifies the population by ages, and account for the different incidences of the disease at each strata. The model is used to predict the incidence of the epidemics in a spatial population through time, permitting investigation of control measures. The model is applied to the current epidemic in Spain, using the estimates of the epidemiological parameters and the mobility and demographic census data of the national institute of statistics (INE). The results indicate that the peak of incidence will happen in the first half of April …
  • Otros:

    Autor según el artículo: Alex Arenas; Wesley Cota; Jesus Gomez-Gardenes; Sergio Gómez; Clara Granell; Joan T Matamalas; David Soriano-Panos; Benjamin Steinegger
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: Arenas Moreno, Alejandro / Gómez Jiménez, Sergio / Matamalas Llodrà, Joan Tomàs / Steinegger, Benjamin Franz Josef
    Palabras clave: Good health and well-being
    Resumen: An outbreak of a novel coronavirus, named SARS-CoV-2, that provokes the COVID-19 disease, was first reported in Hubei, mainland China on 31 December 2019. As of 20 March 2020, cases have been reported in 166 countries/regions, including cases of human-to-human transmission around the world. The proportions of this epidemics is probably one of the largest challenges faced by our interconnected modern societies. According to the current epidemiological reports, the large basic reproduction number, R_0 ~ 2.3, number of secondary cases produced by an infected individual in a population of susceptible individuals, as well as an asymptomatic period (up to 14 days) in which infectious individuals are undetectable without further analysis, pave the way for a major crisis of the national health capacity systems. Recent scientific reports have pointed out that the detected cases of COVID19 at young ages is strikingly short and that lethality is concentrated at large ages. Here we adapt a Microscopic Markov Chain Approach (MMCA) metapopulation mobility model to capture the spread of COVID-19. We propose a model that stratifies the population by ages, and account for the different incidences of the disease at each strata. The model is used to predict the incidence of the epidemics in a spatial population through time, permitting investigation of control measures. The model is applied to the current epidemic in Spain, using the estimates of the epidemiological parameters and the mobility and demographic census data of the national institute of statistics (INE). The results indicate that the peak of incidence will happen in the first half of April …
    Áreas temáticas: Matemática / probabilidade e estatística Interdisciplinar General computer science Computer science, theory & methods Computer science, software, graphics, programming Computer science, software engineering Computer science, hardware & architecture Computer science (miscellaneous) Computer science (all) Ciência da computação
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: joantomas.matamalas@urv.cat benjamin.steinegger@estudiants.urv.cat sergio.gomez@urv.cat alexandre.arenas@urv.cat
    Identificador del autor: 0000-0002-7563-9269 0000-0002-0723-1536 0000-0003-1820-0062 0000-0003-0937-0334
    Fecha de alta del registro: 2024-11-23
    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: Communications Of The Acm.
    Referencia de l'ítem segons les normes APA: Alex Arenas; Wesley Cota; Jesus Gomez-Gardenes; Sergio Gómez; Clara Granell; Joan T Matamalas; David Soriano-Panos; Benjamin Steinegger (2020). A mathematical model for the spatiotemporal epidemic spreading of COVID19. Communications Of The Acm, (), -. DOI: 10.1101/2020.03.21.20040022
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2020
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Computer Science (Miscellaneous),Computer Science, Hardware & Architecture,Computer Science, Software Engineering,Computer Science, Software, Graphics, Programming,Computer Science, Theory & Methods
    Good health and well-being
    Matemática / probabilidade e estatística
    Interdisciplinar
    General computer science
    Computer science, theory & methods
    Computer science, software, graphics, programming
    Computer science, software engineering
    Computer science, hardware & architecture
    Computer science (miscellaneous)
    Computer science (all)
    Ciência da computação
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