000144921 001__ 144921
000144921 005__ 20250923084435.0
000144921 0247_ $$2doi$$a10.1002/andp.202400078
000144921 0248_ $$2sideral$$a139730
000144921 037__ $$aART-2024-139730
000144921 041__ $$aeng
000144921 100__ $$aGranell, Clara
000144921 245__ $$aProbabilistic discrete-time models for spreading processes in complex networks: a review
000144921 260__ $$c2024
000144921 5060_ $$aAccess copy available to the general public$$fUnrestricted
000144921 5203_ $$aResearch 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.
000144921 536__ $$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-113582GB-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-128005NB-C21$$9info:eu-repo/grantAgreement/ES/UZ-IBERCAJA/224220
000144921 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000144921 590__ $$a2.5$$b2024
000144921 592__ $$a0.563$$b2024
000144921 591__ $$aPHYSICS, MULTIDISCIPLINARY$$b43 / 114 = 0.377$$c2024$$dQ2$$eT2
000144921 593__ $$aPhysics and Astronomy (miscellaneous)$$c2024$$dQ2
000144921 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000144921 700__ $$aGómez, Sergio
000144921 700__ $$0(orcid)0000-0001-5204-1937$$aGómez-Gardeñes, Jesús$$uUniversidad de Zaragoza
000144921 700__ $$aArenas, Alex
000144921 7102_ $$12003$$2395$$aUniversidad de Zaragoza$$bDpto. Física Materia Condensa.$$cÁrea Física Materia Condensada
000144921 773__ $$g536, 10 (2024), 2400078 [20 pp.]$$pAnn. Phys.$$tANNALEN DER PHYSIK$$x0003-3804
000144921 8564_ $$s1176874$$uhttps://zaguan.unizar.es/record/144921/files/texto_completo.pdf$$yVersión publicada
000144921 8564_ $$s2896516$$uhttps://zaguan.unizar.es/record/144921/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000144921 909CO $$ooai:zaguan.unizar.es:144921$$particulos$$pdriver
000144921 951__ $$a2025-09-22-14:46:26
000144921 980__ $$aARTICLE