Repositori institucional URV
| Autor/es de la URV: | Arenas Moreno, Alejandro / Gómez Jiménez, Sergio / Granell Martorell, Clara |
| Autor según el artículo: | Granell C; Gómez S; Gómez-Gardeñes J; Arenas A |
| Direcció de correo del autor: | clara.granell@urv.cat sergio.gomez@urv.cat alexandre.arenas@urv.cat |
| Identificador del autor: | 0000-0003-1820-0062 0000-0003-0937-0334 |
| Año de publicación de la revista: | 2024 |
| Tipo de publicación: | Journal Publications |
| Referencia de l'ítem segons les normes APA: | Granell C; Gómez S; Gómez-Gardeñes J; Arenas A (2024). Probabilistic Discrete-Time Models for Spreading Processes in Complex Networks: A Review. Annalen Der Physik, 536(10), -. DOI: 10.1002/andp.202400078 |
| Referencia al articulo segun fuente origial: | Annalen Der Physik. 536 (10): |
| Resumen: | Research into network dynamics of spreading processes typically employs both discrete and continuous time methodologies. Although each approach offers distinct insights, integrating them can be challenging, particularly when maintaining coherence across different time scales. This review focuses on the Microscopic Markov Chain Approach (MMCA), a probabilistic f ramework originally designed for epidemic modeling. MMCA uses discrete dynamics to compute the probabilities of individuals transitioning between epidemiological states. By treating each time step-usually a day-as a discrete event, the approach captures multiple concurrent changes within this time frame. The approach allows to estimate the likelihood of individuals or populations being in specific states, which correspond to distinct epidemiological compartments. This review synthesizes key findings from the application of this approach, providing a comprehensive overview of its utility in understanding epidemic spread. |
| DOI del artículo: | 10.1002/andp.202400078 |
| Enlace a la fuente original: | https://onlinelibrary.wiley.com/doi/10.1002/andp.202400078 |
| Versión del articulo depositado: | info:eu-repo/semantics/publishedVersion |
| Acceso a la licencia de uso: | https://creativecommons.org/licenses/by/3.0/es/ |
| Departamento: | Enginyeria Informàtica i Matemàtiques |
| URL Documento de licencia: | https://repositori.urv.cat/ca/proteccio-de-dades/ |
| Áreas temáticas: | Physics, multidisciplinary Physics and astronomy (miscellaneous) Physics and astronomy (all) Physics Matemática / probabilidade e estatística General physics and astronomy Filosofía Engenharias iii Astronomia / física |
| Palabras clave: | Transmission Threshol Networks Network Modeling Metapopulation models Epidemiology Epidemics Dynamics Contagions Challenges Behavior |
| Entidad: | Universitat Rovira i Virgili |
| Fecha de alta del registro: | 2024-10-26 |
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| Archivo | Descripción | Formato | |
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| DocumentPrincipal | DocumentPrincipal | application/pdf |
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