Repositori institucional URV
| Autor/s de la URV: | Arenas Moreno, Alejandro / Gómez Jiménez, Sergio / Granell Martorell, Clara |
| Autor segons l'article: | Granell C; Gómez S; Gómez-Gardeñes J; Arenas A |
| Adreça de correu electrònic de l'autor: | clara.granell@urv.cat sergio.gomez@urv.cat alexandre.arenas@urv.cat |
| Identificador de l'autor: | 0000-0003-1820-0062 0000-0003-0937-0334 |
| Any de publicació de la revista: | 2024 |
| Tipus de publicació: | Journal Publications |
| Referència 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 |
| Referència a l'article segons font original: | Annalen Der Physik. 536 (10): |
| Resum: | 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 de l'article: | 10.1002/andp.202400078 |
| Enllaç font original: | https://onlinelibrary.wiley.com/doi/10.1002/andp.202400078 |
| Versió de l'article dipositat: | info:eu-repo/semantics/publishedVersion |
| Accès a la llicència d'ús: | https://creativecommons.org/licenses/by/3.0/es/ |
| Departament: | Enginyeria Informàtica i Matemàtiques |
| URL Document de llicència: | https://repositori.urv.cat/ca/proteccio-de-dades/ |
| Àrees temàtiques: | Physics, multidisciplinary Physics and astronomy (miscellaneous) Physics and astronomy (all) Physics Matemática / probabilidade e estatística General physics and astronomy Filosofía Engenharias iii Astronomia / física |
| Paraules clau: | Transmission Threshol Networks Network Modeling Metapopulation models Epidemiology Epidemics Dynamics Contagions Challenges Behavior |
| Entitat: | Universitat Rovira i Virgili |
| Data d'alta del registre: | 2024-10-26 |
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| DocumentPrincipal | DocumentPrincipal | application/pdf |
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