2026-04-17T07:37:20Zhttps://recercat.cat/oai/request

oai:recercat.cat:2072/4678502026-03-28T08:37:00Zcom_2072_98col_2072_378192

urn:hdl:2072/467850 Bifurcation analysis of the Microscopic Markov Chain Approach to contact-based epidemic spreading in networks Arenas, Alex Garijo, Antoni Gómez, Sergio Villadelprat Yagüe, Jordi Altres ajuts: Universitat Rovira i Virgili, Spain (2019PFR-URV-B2-41); ICREA Academia The dynamics of many epidemic compartmental models for infectious diseases that spread in a single host population present a second-order phase transition. This transition occurs as a function of the infectivity parameter, from the absence of infected individuals to an endemic state. Here, we study this transition, from the perspective of dynamical systems, for a discrete-time compartmental epidemic model known as Microscopic Markov Chain Approach, whose applicability for forecasting future scenarios of epidemic spreading has been proved very useful during the COVID-19 pandemic. We show that there is an endemic state which is stable and a global attractor and that its existence is a consequence of a transcritical bifurcation. This mathematical analysis grounds the results of the model in practical applications. 2023 Article Agència de Gestió d'Ajuts Universitaris i de Recerca 2020PANDE00098 Agencia Estatal de Investigación PID2021-128005NB-C21 Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-896 Agència de Gestió d'Ajuts Universitaris i de Recerca PDAD14/20/00001 Agencia Estatal de Investigación MTM2017-86795-C3-2-P Chaos, solitons and fractals ; Vol. 166 (January 2023), art. 112921 open access Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. https://creativecommons.org/licenses/by-nc-nd/4.0/