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
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: Ciência da computação Computer science (all) Computer science (miscellaneous) Computer science, hardware & architecture Computer science, software engineering Computer science, software, graphics, programming Computer science, theory & methods General computer science Interdisciplinar Matemática / probabilidade e estatística
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
Direcció de correo del autor: benjamin.steinegger@estudiants.urv.cat sergio.gomez@urv.cat alexandre.arenas@urv.cat joantomas.matamalas@urv.cat
Identificador del autor: 0000-0002-0723-1536 0000-0003-1820-0062 0000-0003-0937-0334 0000-0002-7563-9269
Fecha de alta del registro: 2024-02-03
Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
Enlace a la fuente original: https://journals.aps.org/prx/abstract/10.1103/PhysRevX.10.041055
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
URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/
DOI del artículo: 10.1101/2020.03.21.20040022
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2020
Tipo de publicación: Journal Publications
Repositori URV